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  • machine learning  (590)
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  • 2020-2024  (593)
  • 1945-1949
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  • 101
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The reprint focuses on artificial intelligence-based learning approaches and their applications in remote sensing fields. The explosive development of machine learning, deep learning approaches and its wide applications in signal processing have been witnessed in remote sensing. The new developments in remote sensing have led to a high resolution monitoring of ground on a global scale, giving a huge amount of ground observation data. Thus, artificial intelligence-based deep learning approaches and its applied signal processing are required for remote sensing. These approaches can be universal or specific tools of artificial intelligence, including well known neural networks, regression methods, decision trees, etc. It is worth compiling the various cutting-edge techniques and reporting on their promising applications.
    Keywords: pine wilt disease dataset ; GIS application visualization ; test-time augmentation ; object detection ; hard negative mining ; video synthetic aperture radar (SAR) ; moving target ; shadow detection ; deep learning ; false alarms ; missed detections ; synthetic aperture radar (SAR) ; on-board ; ship detection ; YOLOv5 ; lightweight detector ; remote sensing image ; spectral domain translation ; generative adversarial network ; paired translation ; synthetic aperture radar ; ship instance segmentation ; global context modeling ; boundary-aware box prediction ; land-use and land-cover ; built-up expansion ; probability modelling ; landscape fragmentation ; machine learning ; support vector machine ; frequency ratio ; fuzzy logic ; artificial intelligence ; remote sensing ; interferometric phase filtering ; sparse regularization (SR) ; deep learning (DL) ; neural convolutional network (CNN) ; semantic segmentation ; open data ; building extraction ; unet ; deeplab ; classifying-inversion method ; AIS ; atmospheric duct ; ship detection and classification ; rotated bounding box ; attention ; feature alignment ; weather nowcasting ; ResNeXt ; radar data ; spectral-spatial interaction network ; spectral-spatial attention ; pansharpening ; UAV visual navigation ; Siamese network ; multi-order feature ; MIoU ; imbalanced data classification ; data over-sampling ; graph convolutional network ; semi-supervised learning ; troposcatter ; tropospheric turbulence ; intercity co-channel interference ; concrete bridge ; visual inspection ; defect ; deep convolutional neural network ; transfer learning ; interpretation techniques ; weakly supervised semantic segmentation ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 102
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: Air pollution is a worldwide environmental hazard that poses serious consequences not only for human health and the climate but also for agriculture, ecosystems, and cultural heritage, among other factors. According to the WHO, there are 8 million premature deaths every year as a result of exposure to ambient air pollution. In addition, more than 90% of the world’s population live in areas where the air quality is poor, exceeding the recommended limits. On the other hand, air pollution and the climate co-influence one another through complex physicochemical interactions in the atmosphere that alter the Earth’s energy balance and have implications for climate change and the air quality. It is important to measure specific atmospheric parameters and pollutant compound concentrations, monitor their variations, and analyze different scenarios with the aim of assessing the air pollution levels and developing early warning and forecast systems as a means of improving the air quality and safeguarding public health. Such measures can also form part of efforts to achieve a reduction in the number of air pollution casualties and mitigate climate change phenomena. This book contains contributions focusing on remote sensing techniques for evaluating air quality, including the use of in situ data, modeling approaches, and the synthesis of different instrumentations and techniques. The papers published in this book highlight the importance and relevance of air quality studies and the potential of remote sensing, particularly that conducted from Earth observation platforms, to shed light on this topic.
    Keywords: tropospheric NO2 concentrations ; nitrogen dioxide ; OMI ; spatio-temporal trends ; DBEST ; PolyTrend ; time-series analysis ; breakpoint detection ; air pollution ; TROPOMI ; COVID ; nitrogen oxides ; satellite-based ; NO2 ; land use regression ; exposure assessment ; carbon monoxide ; COVID-19 ; China ; surface concentration ; IASI ; drone ; UAV ; gas sensors ; odour ; industrial emissions ; mapping ; environmental monitoring ; aerosol optical depth ; CAMS ; machine learning ; MODIS ; urban form ; PM2.5 ; landscape metrics ; geographically weighted regression ; Yunnan Plateau ; biomass burning ; cross-border transport ; WRF-Chem ; formaldehyde ; trend ; satellite ; monitor ; annual ; seasonal ; temperature ; meteorology ; AOD ; Europe ; open data ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RB Earth sciences::RBP Meteorology & climatology
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  • 103
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint contains a collection of research articles covering the recent advances of process systems engineering tools in the areas of integrated biorefineries and ionic liquid design. The reprint comprises original research contributions and review articles on these topics.
    Keywords: energy crop ; solid biofuel ; renewable energy ; Napier grass ; gasification ; hydrothermal liquefaction ; black liquor ; process integration ; techno-economic analysis ; utility system ; total site heat integration ; absorption ; carbon dioxide capture ; deep eutectic solvents ; density functional theory ; hydrogen bond ; ionic liquids ; integrated biorefineries ; process systems engineering ; process optimization ; molecular design ; biorefining ; sustainable design ; distributed manufacturing ; centralized facilities ; integration ; CAPEX correlation ; ionic liquid ; toxicity ; machine learning ; neural network ; support vector machine ; green manufacturing ; multi-objective optimisation ; chemical product design ; inverse design techniques ; pyrolysis bio-oil ; CAMD ; solvent design ; fuzzy multi-objective optimisation ; cost optimisation ; pinch analysis ; power generation ; bioenergy ; composite curves ; flower waste ; integrated biorefinery ; waste valorisation ; value-added product ; mathematical optimisation ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering
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  • 104
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Fast, non-destructive detection technology and equipment for food quality and safety is a powerful technical support tool to ensure the development of food industry informatization and intelligence, with the advantages of fast speed, convenient operation, and easy online inspection. During the past two decades, such technologies have found numerous successful applications for food and agricultural product detection and processing. Owing to improvements in the manufacturing of photoelectric sensor pieces and progress in artificial intelligence and software algorithms, fast non-destructive detection technologies are able to provide more accurate, reliable, and stable solutions for food quality and safety detection and processing. They are closely integrated with the Internet of Things and intelligent manufacturing, promoting a new wave of innovation in intelligent manufacturing in the food industry. The application of new sensing technology and equipment in the fast, non-destructive detection of food has always been at the forefront of scientific and technological research. This Special Issue aims to focus on the latest research progress of this application and jointly discuss the focus of development of this research direction.
    Keywords: maize ; moldy level ; catalase activity ; hyperspectral image ; data fusion ; feature selection ; fruit quality monitoring ; room-temperature ethylene sensor ; density functional theory ; adsorption energy ; band energy alignment ; apple ; NIR ; size correction ; extinction coefficient ; fruit diameter difference ; acceptability ; benchtop NMR ; mandarins ; NMR ; successive projective algorithm ; uninformative variable elimination ; support vector regression ; Korla fragrant pear ; stone cell content ; intelligent evaluation ; cultivation ; visible/near infrared spectrum ; fresh jujube ; model update ; variable fusion ; defective apples ; apple grading ; deep learning ; object detection ; semantic segmentation ; shrimp ; hot air drying ; quality change ; hyperspectral images ; low field magnetic resonance ; micro Raman ; microfluidic chip ; fungal spores ; crop disease ; numerical simulation ; degree of milling ; multi-scale information fusion ; residual network model ; Bayesian optimization algorithm ; hyperspectral imaging ; maize seeds ; defect detection ; convolutional neural network ; tomato ; leaf mildew ; terahertz time-domain spectroscopy ; near infrared hyperspectral technology ; multi-source information fusion ; YOLOv5 ; walnut kernels ; impurities detection ; small object detection ; liposomes ; high stability ; freshness ; bi-layer indicator ; light penetration depth ; spatial-frequency domain imaging ; depth-resolved ; bruise ; scattering ; near infrared spectroscopy ; vegetables ; anthocyanidins ; fast determination ; Curcumae Longae Rhizoma ; volatile oil ; 60Co ; GC–IMS ; SERS detection ; chromium contamination ; tea sample ; carbimazole hydrolysate ; Au@Ag nanoparticles ; PAEs ; Raman ; DFT ; HF ; theoretical study ; gas sensor ; spoilage monitoring ; early warning ; logistics control ; simulated annealing ; surface-enhanced Raman spectroscopy ; flexible substrate ; polycyclic aromatic hydrocarbons ; in situ detection ; common carp ; texture ; machine learning ; visualization ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
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  • 105
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
    Keywords: lung ; conventional radiography ; diagnostic procedure ; chronic obstructive pulmonary disease ; COVID-19 ; computed tomography ; lungs ; variability ; segmentation ; hybrid deep learning ; artificial intelligence ; deep learning ; computer-based devices ; radiology ; thoracic diagnostic imaging ; chest X-ray ; CT ; observer tests ; performance ; lung CT images ; nodule detection ; VGG-SegNet ; pre-trained VGG19 ; cardiac amyloidosis ; AL/TTR amyloidosis ; hypertrophic cardiomyopathy ; left ventricular hypertrophy ; convolutional neural network ; Tuberculosis (TB) ; drug resistance ; chest X-rays ; generalization ; localization ; Electrical Impedance Tomography ; lung imaging ; cardiopulmonary monitoring ; aorta ; lung cancer ; pulmonary artery ; pulmonary hypertension ; modality-specific knowledge ; object detection ; RetinaNet ; ensemble learning ; pneumonia ; mean average precision ; source data set ; supervised classification ; coronary artery disease ; machine learning ; cardiopulmonary disease ; faster CNN ; medical imaging ; X-rays ; transfer learning ; explainability ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 106
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
    Keywords: lung ; conventional radiography ; diagnostic procedure ; chronic obstructive pulmonary disease ; COVID-19 ; computed tomography ; lungs ; variability ; segmentation ; hybrid deep learning ; artificial intelligence ; deep learning ; computer-based devices ; radiology ; thoracic diagnostic imaging ; chest X-ray ; CT ; observer tests ; performance ; lung CT images ; nodule detection ; VGG-SegNet ; pre-trained VGG19 ; cardiac amyloidosis ; AL/TTR amyloidosis ; hypertrophic cardiomyopathy ; left ventricular hypertrophy ; convolutional neural network ; Tuberculosis (TB) ; drug resistance ; chest X-rays ; generalization ; localization ; Electrical Impedance Tomography ; lung imaging ; cardiopulmonary monitoring ; aorta ; lung cancer ; pulmonary artery ; pulmonary hypertension ; modality-specific knowledge ; object detection ; RetinaNet ; ensemble learning ; pneumonia ; mean average precision ; source data set ; supervised classification ; coronary artery disease ; machine learning ; cardiopulmonary disease ; faster CNN ; medical imaging ; X-rays ; transfer learning ; explainability ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 107
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint addresses the unique opportunities and challenges associated with human–computer interaction with intelligent systems. First, state-of-the-art reviews are presented about speech emotions, automatic spelling correction, and art usage in virtual reality. We encouraged authors to submit reports describing systems built for different languages and multilingual systems. The linguistic, emotional, prosodic, and dialogue aspects of speech communication are investigated. Special attention is given to sentiment and emotional analysis from text and speech. Speech audiometry, offline speech recognition, and text-independent speaker verification systems are elaborated. The rapidly growing domain of virtual reality applications is of interest both as an application domain in which new interfaces and interaction methods are needed and as a potential testbed for evaluating speech and other interface modalities.
    Keywords: pediatric speech audiometry ; hearing tests ; conditioned play audiometry ; human–computer interaction ; mechatronic devices ; Internet of Things ; cyber-physical systems ; system control ; augmented reality ; mixed reality ; Azure cloud ; sentiment analysis ; opinion classification ; lexicon-based approach ; hybrid approach ; lexicon generation ; lexicon labelling ; particle swarm optimization ; spelling correction ; natural language processing ; diacritization ; error model ; context model ; Natural Language Processing ; deep learning ; grammar error detection ; word embedding ; text-independent speaker verification system ; self-attentive pooling ; multi-layer aggregation ; feature recalibration ; deep length normalization ; speaker embedding ; shortcut connections ; convolutional neural networks ; ResNet ; human–robot interaction ; dictionary approach ; machine learning approach ; social robotics ; human-robot interaction ; mental workload ; heart rate variability ; machine learning ; sentiment level evaluation ; handicraft product ; 3D handicraft products ; smartphone applications ; user interaction ; user’s attracting attention ; question-answering forum ; healthcare informatics ; recommendation system ; user study ; speech emotion recognition ; attention mechanism ; recurrent neural network ; long short-term memory ; user experience ; usability evaluation methods ; domain usability ; domain-specific languages ; graphical user interfaces ; virtual reality ; art therapy ; rehabilitation ; neurorehabilitation ; neuroplasticity ; brain injury ; ASR ; speech-to-text ; edge AI ; Wav2Vec ; transformers ; PyTorch ; emotion recognition ; dimensional to categorical emotion representation mapping ; activation ; arousal and valence regression ; X-vectors ; SVM ; n/a ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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  • 108
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: Buildings play an indispensable role in urban development. As typical structures of transportation buildings, bridges serve as crucial nodes in connecting different regions, promoting economic growth, and ensuring social security. However, with the extension of their service life, the performance of bridges will inevitably decline. Performance monitoring and evaluation are crucial during the life cycle of bridges. The accelerating convergence of civil engineering, materials science, and artificial intelligence has sparked the interest of researchers from different disciplines in the emerging field of bridge state perception. This reprint covers topics on condition monitoring and assessment of engineering structures, featuring 13 papers. These studies provide some novel methods, models, and technological applications for bridge condition perception, which are of great significance for the design, construction, and assessment of bridges.
    Keywords: shield tunnelling ; active underpinning ; bridge substructure ; 3D FEM modelling ; field verification ; cantilever anti-slide pile ; trapezoidal thrust load ; bearing characteristics ; optimized calculation method of internal force ; evolution law of internal force and deformation ; bridge engineering ; moving loads identification ; MobileNetV2 ; transfer learning ; plate end debonding ; intermediate crack debonding ; fiber-reinforced polymer ; machine learning ; dung beetle optimizer (DBO) ; large-span track bridge ; steel-concrete composite beam ; cable-stayed bridge ; alignment prediction ; response surface method ; Monte Carlo ; bridge temperature ; non-uniform temperature field ; longitudinal temperature distribution ; steel box girder ; long-span bridge ; steel tube concrete truss arch ; highway basket-handle arch bridge ; arch rib inclination angle ; finite element method ; lateral stability ; working stress ; rebar ; monitoring ; magnetoelastic effect ; magnetic resonance ; moving force identification ; vehicle–bridge interaction ; Newmark-β method ; Tikhonov regularisation ; stay cable ; corrosion factors ; neural networks ; spatial diffusion model ; rigid-frame arch bridge ; scale model test ; test design ; loading system ; weight calculation method ; CFST arch bridge ; super-long span ; friction-pendulum bearing ; stayed-buckle cable ; seismic-performance improvement ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 109
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Renewable energy resources are used as distributed generation (DG) units and installed near to where the energy is converted and consumed. Further, the integration of renewable energy sources at home is very important. IoT helps smart grids to support various network functions throughout the generation, distribution, and consumption of energy by incorporating IoT devices (such as sensors, actuators, and smart meters), as well as by providing connectivity, automation, and tracking for such devices. For these applications, the use of low-power long-range wireless networks (LPWAN) is fundamental to facilitate all the necessary tasks in the smart grids in City 4.0 and Industry 4.0. The integration of renewable energies (photovoltaic solar, wind energy, biomass energy, hydroelectric energy, and other sources) in smart grids implies the monitoring of households, cities, industries, and electric vehicles at all times. In this sense, the development of monitoring and control applications using mobile devices is a fundamental tool in this type of system, which complements all the possibilities offered by the IoT. Smart energy meters are used to allow for communication between consumers and utility command centers to exchange messages about electrical consumption. Thus, it is essential to have access from any location and instant access to information using mobile devices or computers.
    Keywords: knowledge-based sensor ; Internet of Things ; high-concentration photovoltaic systems ; sun tracker ; buildings energy management ; deep learning ; energy consumption prediction ; LSTM ; autoencoder ; load forecasting ; smart sensors ; smart meter ; temporal data granularity ; electric load profile ; time slices ; time series ; advanced metering infrastructure ; monitoring ; data acquisition systems ; renewable energy ; multi-objective optimization ; reactive power (RP) planning ; hybrid algorithm ; virus colony search ; particle swarm optimization ; LoRaWAN ; smart irrigation systems ; smart energy ; IoT ; renewable energy sources ; photovoltaic energy ; I-V curve ; monitoring and data acquisition ; microgrid ; open-source ; communication protocols ; DC interrupting ; digitization ; remote control ; electric energy measurement ; miniature circuit breaker ; power meter ; internet of things ; load control ; energy meter ; smart socket ; intelligent campus ; smart building ; internet of things platform ; remote monitoring and control ; classification ; data anomalies ; data imputation ; energy consumption data ; ensemble classifiers ; machine learning ; smart home data ; smart meter data ; tracebase dataset ; home energy management system ; smart home ; cloud infrastructure ; distributed PV ; energy management system ; energy storage units ; charging piles ; smart grid ; redundancy ; Home Assistant ; low-carbon island ; Kinmen ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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  • 110
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Polymer-processing techniques are of the utmost importance for producing polymeric parts. They must produce parts with the desired qualities, which are usually related to mechanical performance, dimensional conformity, and appearance. Aiming to maximize the overall efficiency of the polymer-processing techniques, advanced modeling codes along with experimental measurements are needed to simulate and optimize the processes. Thus, this reprint exploits the digital transformation of the plastics industry, both through the creation of more robust and accurate modeling tools and the development of cutting-edge experimental techniques. Furthermore, it addresses advanced topics, such as crystallization during the solidification processes, prediction of fiber orientation in the cases of short and long fiber composites, prediction of the foaming process (such as microcellular foaming), and flow instabilities by including viscoelastic constitutive equations.
    Keywords: polymer electrolyte membrane for fuel cell ; molecular dynamics simulations ; side chain ; penetration ; injection molding ; thermoplastic composites ; mold heating ; mold temperature control ; melt filling ; thin wall injection molding ; suspensions ; micro-polar fluids ; yield stress ; extrusion ; extrudate swell ; interface tracking ; least-squares volume-to-point interpolation ; consistent PISO ; finite volume method ; OpenFOAM ; poly(ether ether ketone) ; thermo–mechanical response ; constitutive modeling ; polymer processing ; elongational flow ; vane extruder ; eccentric rotor extruder ; numerical simulation ; warpage ; prediction ; crystallinity ; multi-layer structure ; simulation ; annocatacin B ; ND1 subunit ; mitochondrial respiratory complex I ; MRC-I ; MD ; Hirshfeld charges ; MM/PBSA ; poly(lactic acid) ; urea ; melt blending ; slow-release fertilizer ; leakage flow ; modeling and simulation ; sheet die design ; manufacturing process design ; coat-hanger die ; modeling ; rheology ; constant shear-rate die ; non-Newtonian fluids ; poly (3-hydroxybutyric-co-3-hydroxyvaleric acid) (PHBV) ; flax ; hemp ; short fibers ; properties ; lithium-ion ; high energy pouch cell ; state of charge ; electrolyte ; load position ; motor core ; iron sheet ; computer-aided engineering tools ; gluing ; machine learning ; multilayer perceptron ; neural network ; regression ; plasticizing ; polymers ; basic settings ; data-based ; model ; quality ; conformal cooling ; sustainability ; industrial design ; manufacturing ; degree of assembly ; a family mold system ; CAE-DOE optimization ; green channels ; temperature maps ; finite difference methods ; meshless interpolation ; numerical solution ; polymer flows ; viscoelastic flows ; plastic optical barrel ; roundness ; concentricity ; Taguchi method ; RGD peptide (1FUV) ; ab initio molecular dynamics ; total bond order ; partial charge ; dielectric function ; suspension ; rodlike particles ; micropolar fluids ; anisotropy ; hysteresis ; fiber reinforced polymer composites ; lead nanoparticles ; shielding ; attenuation coefficient ; empirical derivation ; PEG-PCL ; non-isothermal crystallization ; flash differential scanning calorimeter ; polymer blends ; microstructure ; multiscale simulation ; hybrid injection molding ; continuous fiber-reinforced thermoplastics ; finite element analysis (fem) ; FDM ; Taguchi ; multilateral ; CAE ; transfer learning ; LDPE ; triangular-loop shear ; trapezoidal-loop shear ; time-dependent viscoelastic property ; Rivlin–Sawyers equation ; fillers ; rubber compounds ; viscoelasticity ; thixotropy ; structure ; tailings flocculation ; seawater ; calcium and magnesium removal ; lime ; sodium carbonate ; FEM ; pipe die ; polymer melt ; Herschel–Bulkley fluids ; free-surfaces ; conformal cooling channel ; rapid tooling technology ; mold material ; cooling medium ; polymer solution ; Giesekus ; eXtended Pom-Pom ; visualization ; analytical solution ; deep learning ; stacked learning ; Oldroyd-B fluid ; Giesekus fluid ; sphere drag coefficient ; plastic pallet ; flatness ; sequential valve gate system ; molding flow analysis ; particle settling ; dilute polymeric solutions ; Oldroyd-B model ; microfluidic rheometry ; drag coefficient ; hydraulic fracturing ; polyethylene recycling ; artificial engineering ; polymer extrusion ; mold additive manufacturing ; polymer molds ; subtractive manufacturing ; mold characterization ; rapid tooling ; thermal homogenisation ; pre-distribution ; heat pipe ; blown film extrusion ; CFD ; n/a ; pyrolysis ; mixed polymers ; thermogravimetric analyzer (TGA) ; artificial neural networks (ANN) ; polypropylene ; glass fiber ; fiber reinforced ; fiber shortening ; compound ; SIGMA ; dynamic image analysis ; Monte Carlo ; nanoporous matter ; proton ; transport behavior ; GEANT4 code ; boundary layer ; Herschel–Bulkley fluid ; Carbopol ; cement ; bacterial cellulose ; plasma treatment ; magnetron sputtering ; silver nanoparticles ; antimicrobial activity ; X-ray photoelectron spectroscopy ; fully implicit coupled solver ; viscoelastic flow ; log-conformation tensor approach ; non-isothermal effects ; Phan-Thien-Tanner constitutive equation ; semi-analytical method ; solvent viscosity contribution ; pipe flow ; channel flow ; Au nanoparticles ; plasmonics ; polymer matrix ; nanocomposite ; thermal annealing ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 111
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: This reprint brings together fifteen articles published in the Special Issue of the journal Atmosphere, entitled “High-Performance Computing Serving Atmospheric Transport & Dispersion Modelling”. These articles cover a wide variety of topics related to air quality in urban areas and nature-based solutions to improve it in the context of climate change; impact studies on human health and the environment of facilities and infrastructure projects as well as risk studies; the assessment of emerging threats; and preparations for and responses to emergencies involving toxic, flammable, or explosive atmospheric releases. As the fifteen articles presented here remarkably illustrate, what these contemporary topics have in common is the implementation of multi-scale simulations of atmospheric transport and dispersion by means of physical models of computational fluid dynamics (CFDs), whose potential is enhanced by high-performance computing (HPC). This reprint thus addresses the answers provided by modelling and the most advanced simulations to some societal matters of major interest.
    Keywords: operational emergency modeling ; atmospheric release ; high-resolution metric grid ; 3D ; PMSS modeling system ; Code_Saturne ; EMERGENCIES project ; lattice Boltzmann method ; large eddy simulation ; pollutant dispersion ; urban physics ; urban air pollution ; nature-based solutions ; green infrastructure ; PMSS Lagrangian model ; NOx ; PM10 ; large-eddy simulation ; plume dispersion ; urban area ; coupling simulation ; mesoscale meteorological simulation model ; meteorological observation ; graphics processing unit computing ; atmospheric dispersion modelling ; microscale dispersion ; model validation ; database ; on-site meteorological observation ; water mist dispersion ; lagrangian dispersion model ; web visualization ; web mapping ; emergencies project ; atmospheric boundary layer ; OpenFOAM ; gas dispersion ; CFD ; turbulence model ; hazard assessment ; horizontal homogeneity ; wind field ; deposition ; machine learning ; hazardous release ; WRF ; FLEXPART ; prediction ; air pollution ; air quality modelling ; ADMS-Urban ; high performance computing ; HPC ; West Midlands ; air quality ; urban scale ; traffic emissions ; micro-scale dispersion models ; aerosols ; South Asia ; WRF-Chem ; precipitation ; CAPE ; CIN ; urban dispersion ; complex terrain ; fast-response dispersion modeling ; computational fluid dynamics ; RANS ; urban dispersion modelling ; Reynolds-averaged Navier–Stokes ; situational awareness ; CityGML ; air quality impact study ; PMSS model ; high resolution grid ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 112
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In recent years, we have been witnessing the exponential proliferation of the Internet of Things (IoT), networks of physical devices, vehicles, appliances and other items embedded with electronics, software, sensors, actuators and connectivity that enables these objects to connect and exchange data. Enabling the introduction of highly efficient IoT, wireless sensing and network technologies will reduce the need for traditional processes that are currently be carried out manually, thus freeing up the precious resources of dwindling working staff, to do more meaningful and human-centered work. This reprint aims to bring together innovative developments in areas related to IoT, wireless sensing and networking. The aspects covered include software-defined network (SDN)-based IoT networks, artificial intelligence (AI) for IoT, industrial IoT, smart sensors, optimization of energy efficiency for IoT, and wireless sensor networks, IoT applications for agriculture, smart cities, healthcare, localization and environment monitoring.
    Keywords: lawful interception ; hybrid SDN ; intercept access point ; minimum vertex cover ; text detection ; natural scene ; feature fusion ; soil water content ; sensor networks ; distributed sensing ; IoT measurements ; Precision Agriculture ; moisture sensor ; wireless communication ; LoRa ; LoRaWAN™ ; indoor localisation ; fingerprinting ; landmark ; wearable device ; inertial measurement device ; motion mode detection ; body shadowing compensation ; nearest neighbour ; label-free biosensor ; machine learning ; support vector machine ; artificial neural network ; principal component analysis ; Green IoT ; IIoT ; edge computing ; AI ; edge AI ; sustainability ; digital transition ; digital circular economy ; Industry 5.0 ; direction-of-arrival estimation ; geometric algebra ; ESPRIT algorithm ; electromagnetic vector-sensor array ; hardware security ; electromagnetic sensing ; real time ; cybersecurity ; anomaly detection ; the Internet of Things ; deep learning ; blockchain ; 5G/6G ; URLLC ; tactile Internet ; industrial IoT ; network emulator ; robotic simulator ; virtual testbed ; wireless power transfer ; energy harvesting ; power conversion efficiency ; single diode rectifier ; voltage doubler ; harmonic balance method ; autonomous sensor node ; wireless sensor network ; multi-tone signal ; full-wave simulations of PCB ; millimeter wave ; new radio ; unmanned aerial vehicles ; LoS blockage ; closed-from approximation ; rooftop deployments ; coverage path planning ; unmanned aerial vehicle ; cell decomposition ; decomposition methods ; energy-aware approaches ; energy optimal path ; multi-robot systems ; multi-UAV ; smart cities ; Internet of Things (IoT) ; sensors ; 6G ; wireless communications ; resilience ; climate change ; connectivity ; data ; wireless systems ; mobile sensors ; D2D ; technological development ; Internet of things ; LoRaWAN ; reliability ; downlink ; safety ; IoT ; LPWAN ; proximal soil sensor device ; conventional communication methods ; ultralow power consumption ; long-distance transmission ; economic value ; inventoried sensor devices ; digital twin ; LSTM model ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Polymer-processing techniques are of the utmost importance for producing polymeric parts. They must produce parts with the desired qualities, which are usually related to mechanical performance, dimensional conformity, and appearance. Aiming to maximize the overall efficiency of the polymer-processing techniques, advanced modeling codes along with experimental measurements are needed to simulate and optimize the processes. Thus, this reprint exploits the digital transformation of the plastics industry, both through the creation of more robust and accurate modeling tools and the development of cutting-edge experimental techniques. Furthermore, it addresses advanced topics, such as crystallization during the solidification processes, prediction of fiber orientation in the cases of short and long fiber composites, prediction of the foaming process (such as microcellular foaming), and flow instabilities by including viscoelastic constitutive equations.
    Keywords: polymer electrolyte membrane for fuel cell ; molecular dynamics simulations ; side chain ; penetration ; injection molding ; thermoplastic composites ; mold heating ; mold temperature control ; melt filling ; thin wall injection molding ; suspensions ; micro-polar fluids ; yield stress ; extrusion ; extrudate swell ; interface tracking ; least-squares volume-to-point interpolation ; consistent PISO ; finite volume method ; OpenFOAM ; poly(ether ether ketone) ; thermo–mechanical response ; constitutive modeling ; polymer processing ; elongational flow ; vane extruder ; eccentric rotor extruder ; numerical simulation ; warpage ; prediction ; crystallinity ; multi-layer structure ; simulation ; annocatacin B ; ND1 subunit ; mitochondrial respiratory complex I ; MRC-I ; MD ; Hirshfeld charges ; MM/PBSA ; poly(lactic acid) ; urea ; melt blending ; slow-release fertilizer ; leakage flow ; modeling and simulation ; sheet die design ; manufacturing process design ; coat-hanger die ; modeling ; rheology ; constant shear-rate die ; non-Newtonian fluids ; poly (3-hydroxybutyric-co-3-hydroxyvaleric acid) (PHBV) ; flax ; hemp ; short fibers ; properties ; lithium-ion ; high energy pouch cell ; state of charge ; electrolyte ; load position ; motor core ; iron sheet ; computer-aided engineering tools ; gluing ; machine learning ; multilayer perceptron ; neural network ; regression ; plasticizing ; polymers ; basic settings ; data-based ; model ; quality ; conformal cooling ; sustainability ; industrial design ; manufacturing ; degree of assembly ; a family mold system ; CAE-DOE optimization ; green channels ; temperature maps ; finite difference methods ; meshless interpolation ; numerical solution ; polymer flows ; viscoelastic flows ; plastic optical barrel ; roundness ; concentricity ; Taguchi method ; RGD peptide (1FUV) ; ab initio molecular dynamics ; total bond order ; partial charge ; dielectric function ; suspension ; rodlike particles ; micropolar fluids ; anisotropy ; hysteresis ; fiber reinforced polymer composites ; lead nanoparticles ; shielding ; attenuation coefficient ; empirical derivation ; PEG-PCL ; non-isothermal crystallization ; flash differential scanning calorimeter ; polymer blends ; microstructure ; multiscale simulation ; hybrid injection molding ; continuous fiber-reinforced thermoplastics ; finite element analysis (fem) ; FDM ; Taguchi ; multilateral ; CAE ; transfer learning ; LDPE ; triangular-loop shear ; trapezoidal-loop shear ; time-dependent viscoelastic property ; Rivlin–Sawyers equation ; fillers ; rubber compounds ; viscoelasticity ; thixotropy ; structure ; tailings flocculation ; seawater ; calcium and magnesium removal ; lime ; sodium carbonate ; FEM ; pipe die ; polymer melt ; Herschel–Bulkley fluids ; free-surfaces ; conformal cooling channel ; rapid tooling technology ; mold material ; cooling medium ; polymer solution ; Giesekus ; eXtended Pom-Pom ; visualization ; analytical solution ; deep learning ; stacked learning ; Oldroyd-B fluid ; Giesekus fluid ; sphere drag coefficient ; plastic pallet ; flatness ; sequential valve gate system ; molding flow analysis ; particle settling ; dilute polymeric solutions ; Oldroyd-B model ; microfluidic rheometry ; drag coefficient ; hydraulic fracturing ; polyethylene recycling ; artificial engineering ; polymer extrusion ; mold additive manufacturing ; polymer molds ; subtractive manufacturing ; mold characterization ; rapid tooling ; thermal homogenisation ; pre-distribution ; heat pipe ; blown film extrusion ; CFD ; n/a ; pyrolysis ; mixed polymers ; thermogravimetric analyzer (TGA) ; artificial neural networks (ANN) ; polypropylene ; glass fiber ; fiber reinforced ; fiber shortening ; compound ; SIGMA ; dynamic image analysis ; Monte Carlo ; nanoporous matter ; proton ; transport behavior ; GEANT4 code ; boundary layer ; Herschel–Bulkley fluid ; Carbopol ; cement ; bacterial cellulose ; plasma treatment ; magnetron sputtering ; silver nanoparticles ; antimicrobial activity ; X-ray photoelectron spectroscopy ; fully implicit coupled solver ; viscoelastic flow ; log-conformation tensor approach ; non-isothermal effects ; Phan-Thien-Tanner constitutive equation ; semi-analytical method ; solvent viscosity contribution ; pipe flow ; channel flow ; Au nanoparticles ; plasmonics ; polymer matrix ; nanocomposite ; thermal annealing ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
    Keywords: EEG ; transfer learning ; review ; decoding ; classification ; e-textile ; head phantom ; electroencephalography ; conductive material ; mental stress ; data analysis ; connectivity network ; machine Learning ; deep learning ; vigilance decrement ; sustained attention ; mental fatigue ; cross-participant ; cross-task ; task-generic ; electroencephalogram ; wavelet spectrum ; ridge ; segmentation ; phase connectivity ; epilepsy ; traumatic brain injury ; feature extraction ; functional connectivity network ; time-frequency features ; machine learning ; ALS ; classifier ; neural ; connectivity ; frequency-specific ; BCI ; acupuncture ; dimensionality ; neural subspace ; latent variables ; attractor ; adaptive threshold ; coherence ; functional connectivity ; multilayer network ; otsu ; phase locking value ; weighted phase lag index ; complex Pearson correlation coefficients ; transcranial magnetic stimulation ; cerebral cortex stimulation ; electromagnetic influence ; neurostimulation ; brain activity ; virtual reality ; neuropathic pain ; spinal cord injury ; fractal dimension ; ERP ; speech discrimination ; seizure detection ; features ; feature selection ; motion artifact ; electroencephalogram (EEG) ; functional near-infrared spectroscopy (fNIRS) ; wavelet packet decomposition (WPD) ; canonical correlation analysis (CCA) ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Due to the COVID-19 pandemic, the character of academic conferences has changed. Formerly, conferences required the physical presence of their members and audiences. However, travel restrictions due to the pandemic caused a shift in the traditional conference format, thus resulting in the rise of online conferences after 2020. In 2021 and 2022, the journal “Diversity” similarly organized online conferences. The well-attended online conference in March of 2021 attracted a wide range of speakers on biodiversity, ecology and evolution, as well as on 17 publications from this Special Issue. The publications cover several timely aspects of biodiversity, such as the importance of invasive species, the ecology of urbanization, the effects of drought on wildlife in Southern Africa, the results of human activities on insect, mammal, bird, reptile and amphibia populations, and the genetic diversity of animal breeds, microbiomes and planktonic organisms. Additionally, taxonomic and biosystematic topics are also covered in several SI publications.
    Keywords: chelonians ; pelomedusidae ; foraging ecology ; invasive species ; alien ; translocated ; critically endangered ; freshwater fishes ; freshwater ecosystems ; conservation ; biodiversity ; red list ; diversity ; algae ; alpine lake ; bioindication ; ecological characteristic ; ecosystem ; Nesamovyte Lake ; Eastern Carpathians ; CITES ; endangered species ; SDM ; degraded amazon ; machine learning ; taxonomic diversity ; functional richness ; Rao’s quadratic entropy ; climatic variables ; generalized additive mixed models ; macroecological patterns ; diversity drivers ; urban birds ; bird assemblages ; urbanisation ; landscape ecology ; land use change ; geographic object-based image analysis (GEOBIA) ; Australian monsoonal tropics ; wild goats ; single nucleotide polymorphisms ; genetic diversity ; population structure ; cattle ; Kalmyk cattle ; Kyrgyz cattle ; Kazakh cattle ; Kazakh white-headed breed ; historical specimens ; microsatellites ; consensus genotypes ; sheep ; runs of homozygosity ; genomic inbreeding ; bees ; pollinators ; urban management ; ecological niche model ; distribution ; aquaculture ; mosquitofish ; climate change ; expansion ; catena ecosystem ; ephemeral mud wallows ; habitat use ; mammal variety ; Skukuza area ; species presence ; Stevenson-Hamilton supersite ; Bryodelphax mareki sp. nov. ; DNA barcoding ; Eutardigrada ; Heterotardigrada ; Macrobiotus birendrai sp. nov. ; water bears ; eutrophication ; exotic species ; tropical lakes ; zooplankton ; agroecosystems ; arthropods ; environment ; indicators ; RDP measures ; Porifera ; microbiome ; sponge disease ; 16S rRNA sequencing ; Baikal ; Poland ; Europe ; Cydalima perspectalis ; box tree moth ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint, entitled “Process Control and Smart Manufacturing for Industry 4.0”, contains the extended papers from the Series of annual IFSA conferences on Automation, Robotics and Communications for Industry 4.0/5.0 (ARCI) on the following topics: Process Automation, Process Control and Monitoring, Design Principles in Industry 4.0, Smart Manufacturing and Technologies, Smart Factories, Machine Learning and Artificial Intelligence in Manufacturing. The reprint contains 13 chapters written by 54 ARCI conference participants from seven countries: China, Croatia, Denmark, Germany, Italy, Poland and Romania. This reprint will inform readers of cutting-edge developments in the field and provide effective starting points and a road map for further research and development. All chapters follow the same structure: firstly, an introduction to the specific topic under study; secondly, a description of the field, including sensing or/and measuring applications. Each chapter ends with a curated list of references, including books, journals, conference proceedings and websites. “Process Control and Smart Manufacturing for Industry 4.0” is intended for researchers and scientists from academia and industry, as well as for postgraduate students.
    Keywords: steel alloys ; resistance spot welding ; RSW ; electrode wear ; electrode tip-dressing ; process monitoring ; mushrooming ; plateau forming ; quality control ; COVID-19 ; FDM ; 3D printing ; injection molding ; personal protection ; rapid prototyping ; protective face shields ; mechatronics line ; visual servoing system ; wheeled mobile robot ; industrial robotic manipulator ; Industry 4.0 ; NDT ; magnetic particle inspection ; optimization ; condition monitoring ; vibration ; acoustic emission ; drive train ; data fusion ; machine learning ; product morphology ; core data model ; phase rule filter ; phase private data model ; storage system ; forklift AGV ; deep learning ; semantic segmentation ; H-Swish ; community transformation ; community innovation governance ; ternary space ; coupling and coordination analysis ; lean manufacturing ; lean principles ; pull principle ; production control mechanisms ; production processes ; lean implementation ; batch process ; partial least squares ; multi-phase ; multi-mode ; master production scheduling ; make-to-order ; mathematical programming ; agent-based ; overtime ; earliness ; tardiness ; equipment selection decision ; business compass ; energy consumption ; processing time ; beetle antennae search algorithm ; sustainable blank dimension design ; energy-saving ; low-carbon ; grey wolf algorithm ; gas–solid ; cyclone ; separator ; gas dynamics ; erosion ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The second volume of the Special Issue entitled “Antimicrobial Prescribing and Stewardship” consists of manuscripts, including original research articles, review articles, and opinion papers regarding antimicrobial stewardship-related topics, including disease-based/organism-based antimicrobial stewardship; the influence of antimicrobial utilization changes on antimicrobial resistance; the impact of antimicrobial stewardship on quality performance measures and patient outcomes; novel antimicrobial stewardship education and training approaches or interventions aimed toward the public and/or healthcare workers; behavioral change approaches to antimicrobial stewardship; collaborative practice agreements in antimicrobial stewardship; antimicrobial stewardship in special populations (e.g., pediatrics, geriatrics, emergency medicine, hematology/oncology); tackling AMR through antimicrobial stewardship in low- and middle-income countries; antimicrobial stewardship for animal health; antimicrobial stewardship in alternative settings (e.g., community practice, long-term care, resource-limited settings, small and rural hospitals); antimicrobial use and stewardship in the context of the COVID-19 pandemic; and global collaborations to tackle AMR through antimicrobial stewardship.
    Keywords: antimicrobial stewardship programs ; hospitals ; multi-drug resistance ; antibiotics ; antimicrobial stewardship ; quality of prescription ; prescriptive appropriateness ; surgical prophylaxis ; antibiotic stewardship ; febrile neutropenia ; appropriateness ; pharmacist-driven ; hematology oncologic patient ; hospital care ; primary care ; physicians ; antibiotic ; prescription ; Portugal ; upper respiratory tract infections ; antimicrobial resistance ; parental knowledge ; attitudes ; practices ; child ; Greece ; COVID-19 ; emergency department ; prescribing ; antimicrobial prescribing ; behavior change ; primary healthcare ; general practice ; community pharmacy ; qualitative study ; patient attitudes ; self-care ; questionnaire ; behavioural science ; global-pps ; antimicrobial surveillance ; antimicrobials ; ceftriaxone prescription ; prevalence ; Uganda ; life-long ; suppression ; multi-resistant organisms ; antibiotic prophylaxis ; joint replacement ; prosthetic joint infection ; oral implantology ; dental implants ; hospital physicians ; low-resistance country ; antibiotic prescription ; semi-structured interviews ; antibiotic prescribing quality ; low-risk intra-abdominal infections ; post-operative antibiotic treatment ; antimicrobial drug use ; dairy cattle ; knowledge ; logistic regression models ; machine learning ; survey ; cystitis ; fluoroquinolones ; point prevalence survey ; antibiotic use surveillance ; hospital ; private sector ; global health security ; multisectoral ; stewardship ; surveillance ; collaboration ; antimicrobial use ; food animals ; AMU ; DDD ; biosecurity ; animal welfare ; anthelmintics ; prudent use ; imprudent use ; livestock production systems ; Fiji ; healthcare providers ; infectious diseases ; caregivers ; antibiotic resistance ; rural population ; India ; antimicrobial resistance (AMR) ; antimicrobial stewardship (AMS) ; AMS Game ; board game ; online game ; Commonwealth Partnerships for Antimicrobial Stewardship ; CwPAMS ; gaming ; game-based learning ; gamification ; prescribing app ; anti-infective ; antimicrobial ; behaviour change ; healthcare workers ; national action plans ; pharmacy ; One Health ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSG Microbiology (non-medical)
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue aimed to collect and present all breakthrough research on all intentional or unintentional explosions and impact problems. During the last decade, the investigation of these phenomena has been an active area of research in different fields (i.e., civil, defense, mining, aeronautical, naval, etc.), including experimental studies, analytical models, or numerical simulations; and this Special Issue is a faithful reflection of this trend.A total of twenty-six papers (twenty-five research papers and one review paper) in various fields of blast and impact engineering including blast loading issues over structures, beams, walls; penetration and impact; explosives safety and security; blasting effects on rocks and tunnels; are presented in this Special Issue.
    Keywords: shaped charge ; jet ; cumulative charge ; numerical simulation ; LS-Dyna ; blast-induced damage ; explosion crater ; lateral blasting ; in situ stress ; lateral free surface ; blast ; tunnel ; pressure reduction module ; LS-DYNA ; mitigation ; grid ; water curtain ; peak particle velocity ; blasting-induced vibration ; prediction ; artificial neural networks ; site factors K and m ; open-pit blasting ; blast loads ; slab ; column ; connections ; numerical analysis ; numerical modeling ; blasting stress wave ; underground rock masses ; initial stress ; transmission coefficient ; blast load ; concrete columns ; experimental testing ; steel plate reinforced concrete walls ; FE simulation ; perforation analytical model ; cavity expansion analysis ; thin plates petaling ; penetration ; machine learning ; concrete ; rigid projectile ; symbolic regression ; engineering structures ; validation ; Semtex ; hypervelocity impact ; whipple shield ; honeycomb passive shielding ; micro-meteoroid and orbital debris (MMOD) ; Smoothed Particle Hydrodynamics (SPH) ; finite-element analysis ; LSDyna ; IEDs ; field test ; reinforced concrete ; blasting experiment ; stemming material ; shear thickening fluid ; sand ; blockage performance ; AAC block ; masonry wall ; finite element ; strengthening ; ABAQUS ; RCP ; recycled aggregate concrete ; impact loading ; impact force ; cracking ; peak displacement ; blast effects ; hydrocode analysis ; effects of explosions ; blast loading ; SDOF systems ; thermochemistry of explosives ; fragments ; crater formation ; damage to people ; detonation ; TNT ; dynamite ; air blast wave ; overpressure ; battle damage ; X-ray tomography ; two-stage light gas gun ; high-velocity fragment ; rock tunnel ; sandstone ; missile impact ; blasting ; airblast ; input selection ; hybrid SVR model ; rod projectile ; angle of attack ; liquid cabin ; overturn and yaw ; trajectory ; internal explosion ; shock wave ; corner ; structural dimensions ; Mach waves ; improvised explosive device ; sympathetic detonation ; blasting cap ; UHPC ; mesoscale equivalent model ; penetration experiments ; parametric analysis ; DOP prediction equation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This Special Issue, "Mathematical and Molecular Topology" welcomed papers from a broad interdisciplinary area, since topology is concerned with the properties of objects that are preserved under continuous deformations, such as stretching, twisting, crumpling and bending. One of the oldest problems in topology is The Seven Bridges of Königsberg. Topology naturally finds application in all fields of engineering, physical sciences, life sciences, social sciences, medicine, business and even arts. The motivating insight behind topology is that some geometric problems depend not on the exact shape of the objects involved, but rather on the way they are put together. Circa 1750, Euler stated the polyhedron formula, V − E + F = 2 (where V, E, and F respectively indicate the number of vertices, edges, and faces of the polyhedron), which may be regarded as the first theorem, signaling the birth of topology. Subjects included in topology are graph theory and algebraic topology.
    Keywords: closure space ; canonically closed ; weakly normal ; almost normal ; π-normal ; weakly π-normal ; κ-normal ; local convergence ; nonlinear equations ; Banach space ; Fréchet-derivative ; Gaussian ; optimization ; geometry ; molecular modeling ; amino acids ; maximum clique ; protein graphs ; machine learning ; ProBiS ; entropies via various molecular descriptors ; H3BO3 layer structure ; subdivision of H3BO3 ; line graph of H3BO3 ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: In today's global food market, ensuring both consumer satisfaction and the highest standards of safety is paramount. Food quality analysis covers chemical composition, physical properties, taste evaluation, and even traceability. Traditional methods are often slow, expensive, and eco-unfriendly due to their destructive nature. Here's the exciting part! Advanced spectroscopy techniques offer solutions. Imagine using non-destructive methods like X-rays, hyperspectral imaging, NMR, and Raman—quick, cost-effective, and eco-friendly, using less solvent. Now, let's demystify chemometrics—it extracts hidden info from spectra or image data, creating models for both qualitative and quantitative food analysis. This reprint presents recent advances in spectroscopy and chemometrics, focusing on their role in food analysis, quality evaluation, safety, and practical industry use. It's all about ensuring safe, delicious, and trustworthy food. Whether you're a curious consumer, food enthusiast, or industry insider, this reprint unveils cutting-edge methods for maintaining top food standards. With advanced spectroscopy and chemometrics, we're on track to boost consumer confidence in the food we love.
    Keywords: hyperspectral imaging ; pesticide residue ; table grape ; deep learning ; non-destructive detection ; Salvia spp. ; GC/Q-ToF analysis ; chemometrics ; quality evaluation ; chemical fingerprints ; 1H-NMR ; carbohydrates ; fruits ; PCA ; LDA ; laser-induced breakdown spectroscopy ; brown rice flour adulteration ; time-resolved spectra ; machine learning ; red pepper powder ; multivariate analysis ; moisture adjustment ; Theobroma cacao L. ; dry matter ; fermentation index ; protein content ; meliponine honey ; physicochemical properties ; biomes ; antioxidant potential ; mineral profile ; mass spectrometry analysis ; spatial frequency domain imaging (SFDI) ; optical properties ; absorption ; reduced scattering ; long short-term memory (LSTM) ; FTIR ; mid-infrared ; caprine milk ; milk absorbance spectra ; variance components ; sources of variation ; Fritillaria thunbergii ; heavy metals ; variable selection ; food analysis ; food authenticity ; food chemicals ; spectroscopy techniques ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This is a collection of research articles reporting the most recent progress in organic optoelectronic materials and devices. The involved research work covers materials of organic and hybrid semiconductors, designs in micro and nano scales, structures for microcavity and random lasing, and devices for light emission or detection. Although these research results deal with only a narrow band of the broad topic of organic optoelectronics, they are believed to make excellent contributions to the new development of related fields. Appreciations should be delivered to all of the authors, whose support enabled the successful completion of this Special Issue.
    Keywords: quasicrystal resonator ; analytic model ; cavity coupling ; micro-nano photonics devices ; optical microcavity ; micro-nano vortex laser ; orbital angular momentum ; plasmonic devices ; flexible transparent electrodes ; silver nanowires ; laser nano-welding ; organic electronics ; small molecules ; crystallization ; moving in solid film ; glass transition temperature ; annealing temperature ; annealing time ; two-dimensional patterning ; periodical grids ; hybrid halide perovskites ; random lasing ; large-scale thin-film networks ; all-inorganic lead halide perovskite ; CsPbBr3 ; Cs4PbBr6 ; perovskite nanocrystals ; photodetector ; Y6 ; non-fullerene acceptor ; organic solar cell ; machine learning ; multi-function ; substrate effects ; random lasers ; surface morphology ; multicrystalline film of MAPbBr3 ; contact angles ; narrowband ; near-infrared ; perovskite ; organic ; TCAD ; responsivity ; FWHM ; random laser ; spatial coherence ; random scattering feedback ; tunable scattering coefficient ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PN Chemistry ; thema EDItEUR::P Mathematics and Science::PN Chemistry::PNN Organic chemistry
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint was established after the 9th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.
    Keywords: distributor’s pallet loading problem ; heuristics ; bin packing ; real-life instances ; emergency medical services ; emergency medicine ; decision-support system ; pre-hospital emergency care ; ambulance response time ; machine learning ; geo-indistinguishability ; differential privacy ; privacy-preserving machine learning ; input perturbation ; estimation of distribution algorithm ; Mallows model ; moth-flame algorithm ; job shop scheduling problem ; quay crane scheduling problem ; first-passage time ; Markov chain ; queueing theory ; simulation ; OR in health services ; KPI ; wind energy ; wind turbine blades ; erosion ; modal analysis ; aerodynamic analysis ; AutoML ; feature selection ; fault severity assessment ; gearboxes ; XGBoost classifiers ; autism ; attention ; ASD ; learning activities ; EEG ; BCI ; features ; artificial intelligence ; Grouping Genetic Algorithm ; variable decomposition ; Large-Scale Constrained Optimization ; DVT ; early diagnosis ; machine-learning ; smart system ; embedded system ; edge computing ; edge device ; OpenFOAM ; CFD ; ANFIS ; ANFIS (GA) ; ANFIS (PSO) ; ANFIS (FFA) ; nonlinear programming ; largest small polygons (LSP) ; {LSP(n)} model-class ; optimal area sequence {A(n)} ; revised LSP model ; mathematica model development environment ; IPOPT solver engine ; numerical optimization results and regression model for estimating {A(n)} ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Dive into the fascinating world of photosynthesis through the latest publications. This comprehensive work delves deep into the intricate regulatory mechanisms that underpin the vital process of photosynthesis. From the molecular reactions at the core to the overarching responses of entire plants, explore the diverse facets of this fundamental phenomenon. Discover how plants adeptly adapt to an ever-changing and often challenging environment. Gain valuable insights with real-world applications, spanning agriculture, forestry, and biotechnology. Whether you're a scientist, educator, or enthusiast, this reprint promises to unravel the mysteries of life's essential processes. Join us in this exploration of photosynthesis as we bridge the gap between scientific inquiry and practical knowledge, ensuring a sustainable future for both natural ecosystems and cultivated environments.
    Keywords: abiotic stressors ; environmental stress ; growth ; light intensity ; photosynthetic pigments ; picocyanobacteria ; plant physiology ; Alternaria brassicicola ; chlorophyll a fluorescence ; chloroplast ultrastructure ; defense response ; microarray ; photosynthesis ; susceptibility ; chlorophyll fluorescence ; extremely low frequency magnetic field ; Schumann resonance frequencies ; photosynthetic light reactions ; non-photochemical quenching ; quantum yield of photosystem II ; wheat ; pea ; endophytes ; culture filtrate ; exogenously hormone ; Phaseolus vulgaris ; antioxidant enzymes ; antioxidants ; carotenoids ; photochemical efficiency ; protein ; tocopherol ; xanthophyll cycle ; zeaxanthin ; root ; rhizosphere ; rhizobacteria ; root morphology ; abiotic stresses ; phase-sensitive imaging ; magnetopriming ; UV exclusion ; leaf venation ; leaf hydraulics ; high light ; thylakoid membrane ; microdomains ; photoprotection ; Synechocystis ; photoinhibition ; photosystems ; seed priming ; nanotechnology ; germination ; seed resistance ; sustainability ; cold plasma technology ; machine learning ; proton gradient regulation 5 (PGR5) ; PGR5-like photosynthetic phenotype 1 (PGRL1) ; photosynthetic electron transport ; PSI photoinhibition ; oxidation of P700 ; oxidative stress ; combined effect ; Pisum sativum L. ; nanoparticles ; cerium oxide ; zinc oxide ; metal uptake ; hydroponic culture ; photomorphogenesis ; Pinus sylvestris ; light of various spectral composition ; gene expression ; pigment content ; lipid droplets ; microalgae ; Raman spectroscopy ; Surface-enhanced Raman Spectroscopy ; cyanobacteria ; heavy metals ; nitrogenase ; heterocyst ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Advanced intelligent control is a rapidly developing, complex and challenging field with significant practical importance and potential applications. The authors aim to stimulate advancements in science and technology by addressing this field and presenting new trends in the design, control and applications of real-time intelligent sensor system control using advanced intelligent control methods and techniques. The purpose of the Special Issue is to promote in-depth research and communication regarding these topics. The authors focus on innovative multi-sensor fusion techniques integrated into robots, which are combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication including remote control, adaptive sensor networks and human–robot (H2R) interaction systems. Special attention is given to advancements in sensors, actuators, computation technology and communication networks that provide the necessary tools for implementing intelligent control hardware. These advancements are targeted toward various scientific research fields, including machine learning (such as deep learning), bio-inspired algorithms, recurrent neural networks, neuro-fuzzy control and artificial intelligence in general. The Special Issue includes original research papers that report on the recent advancements in intelligent control using intelligent sensors. It serves as a further extension of the previously successful Special Issue, “Advanced Intelligent Control through Versatile Intelligent Portable Platforms”.
    Keywords: nonlinear intelligent control ; support vector regression ; feedforward control ; human arm viscoelastic ; resource-aware control ; co-regulation ; feedback scheduling ; time-varying system ; neural adaptive control ; fault-tolerant control ; integrated attitude and position control ; spacecraft proximity operations ; indirect neural approximation ; Lyapunov analysis ; real-time trajectory prediction ; mechanically thrown objects ; internal logistics ; smart manufacturing systems ; multi-camera simulation ; many-to-many time series forecasting ; encoder-decoder bidirectional LSTM deep neural networks ; arbitrary order sliding mode ; networked system ; finite-time systems ; nonlinear system ; hybrid position/force control ; sliding mode control ; decision method ; neutrosophic logic ; extension set ; mobile robot ; advanced intelligent control ; wheeled–legged ; trajectory tracking ; model predictive control ; smart vehicle ; probabilistic roadmap algorithm ; pseudo-random sampling ; collision detection ; path smoothing ; monocular vision ; human joint angle measurement ; visual detection method ; hand disability ; mobile manipulator ; motion planning ; simultaneous control ; path analysis ; ROS ; rehabilitation robot ; human–robot interaction ; admittance control ; robust control ; active strength training ; sEMG ; lower limb rehabilitation robot ; compliance control ; training mode ; MOTOmed ; continuous passive motion ; straight leg raise ; feature analysis ; wire + arc additive manufacturing ; surface roughness ; deep neural network ; arc welding ; quadruped robot ; change of running direction ; dynamic model ; stability index system ; simulation analysis ; self-collision detection ; dual-manipulator system ; artificial intelligence ; GJK algorithm ; robotics control ; local path planner ; task redundancy ; collision avoidance strategy ; drone ; UAV ; multi-agent ; ArUco ; markers ; group of drones ; machine vision ; computer vision ; sensors ; machine learning ; industry ; manufacturing ; robotics ; sensor systems ; remote control and communication ; simulation ; mobile health ; stroke monitoring ; iomt-stacked convolutional neural networks ; GMDH neural networks ; Deep LSTM ; biomedical EMG signal processing ; rapidly-exploring random tree (RRT) ; path planning ; robot manipulator ; object pick-and-place ; collision-free ; robot operating system (ROS) ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    Springer Nature | Springer International Publishing
    Publication Date: 2024-04-14
    Description: This book constitutes the refereed proceedings of the 4th Symposium of the Norwegian AI Society, NAIS 2022, held in Oslo, Norway, during May 31–June 1, 2022. The 11 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: robotics and intelligent systems; ai in cyber and digital sphere; ai in biological applications and medicine; and towards new ai methods. This is an open access book.
    Keywords: artificial intelligence ; clustering algorithms ; computer security ; computer vision ; correlation analysis ; data handling ; data integration ; engineering ; expert systems ; Human-Computer Interaction (HCI) ; image analysis ; image processing ; integrated data ; machine learning ; network protocols ; software engineering ; unsupervised learning ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMZ Software Engineering ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMZ Software Engineering
    Language: English
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: This reprint contains a summary of what has been presented at the 19th “Calorimetry for High Energy Physics Experiment” (CALOR) conference, which was held at the University of Sussex (Brighton, UK) in May 2022. The state of the art of particle detection, as well as of simulation tools for particle interactions with material, is presented and discussed by world leaders in the Research & Development of particle detectors, as well as early career researchers, sparking very exciting conversations within the detector development community during the five days of the conference.
    Keywords: ATLAS ; Tile Calorimeter ; calorimeter calibration ; calorimeter performance ; liquid scintillator ; PMTs ; calibration ; energy nonlinearity ; energy resolution ; dual calorimetry ; fast-timing ; electromagnetic calorimetry ; radiation-hard detectors ; LAr ; upgrade ; calorimeter ; readout ; electronics ; electromagnetic calorimeter ; compact muon solenoid ; high luminosity large hadron collider ; liquid argon detectors ; liquid argon calibration ; signal processing ; particle identification ; resolution ; pre-shower ; scintillating glass ; hadronic calorimeter ; high granularity calorimetry ; silicon photomultiplier ; cosmic rays ; calorimeters ; space instrumentation ; large detector systems for particle and astroparticle physics ; energy reconstruction ; cluster splitting algorithm ; resistive plate chambers ; gaseous imaging and tracking detectors ; hadron calorimetry ; dual-readout calorimetry ; future colliders ; Phase-1 ; commissioning ; calorimetry ; particle detectors ; photomultipliers ; Higgs factory ; crystal ; SiPM ; high granularity ; Geant4 ; geant-val ; simulation ; hadronic interaction ; test-beam ; Cherenkov calorimeter ; high-granularity ; neural network ; GNN ; CNN ; electromagnetic showers ; Cherenkov light ; optical fibres ; liquid argon ; plasma light source ; scintillation light ; dark photon ; signal reconstruction ; machine learning ; graph neural network ; high energy physics ; calorimeter reconstruction ; secondary electron emission ; radiation hardness ; forward calorimetry ; dual-readout ; ADRIANO2 ; JUNO ; JUNO-TAO ; neutrino detectors ; reactor neutrinos ; MAPS ; silicon detectors ; linear collider ; astroparticles ; γ-ray astronomy ; scintillation ; light yield ; tile calorimeter ; large hadron collider ; FCC ; liquified noble gas ; irradiation ; crystals ; scintillators ; protons ; neutrons ; proton CT ; image reconstruction ; proton tracking ; deep learning ; SiPMs ; calorimetry for high energy physics ; dual readout detector R&D ; PbF2 ; mechanics ; LHC ; trigger ; FPGA ; SLR ; LYSO ; intensity frontier ; ceramics ; time of flight ; ultrafast calorimetry ; charge transfer luminescence ; fast timing ; front-end ; MPPC ; flavour violation ; hadron calorimeter ; silicon photomultipliers ; CMS ; phase-2 ; HGCAL ; particle flow ; TileCal ; Phase-II upgrade ; quality assurance testing ; burn-in ; transformer-coupled buck converters ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: Neurodegenerative disorders (NDs) are becoming more prevalent in our aging population, and traditional methods of monitoring ND symptoms can be challenging. Wearable technology offers several advantages, such as continuous monitoring, objective measurements, and remote monitoring. The present reprint includes a collection of eleven research and review articles that propose wearable solutions and explore signal processing, machine learning, and deep learning approaches for the computerized diagnosis and monitoring of NDs. Topics covered include using wearable technology to measure blood pressure, movement, sleep patterns, and brain activity, and developing predictive models to support clinicians in making informed decisions about treatment and care. This reprint is a valuable resource for anyone interested in the potential of wearable technology to improve the diagnosis and management of NDs.
    Keywords: gait analysis ; Parkinson’s disease ; convolutional neural networks ; gate recurrent units ; deep learning ; cardiovascular diseases ; blood pressure ; hypertension ; photoplethysmography ; artificial neural networks ; neurodegenerative disease ; remote monitoring ; telemonitoring ; wearable sensor ; Parkinson’s Disease ; image processing ; hypomimia ; FE ; classic techniques ; machine learning ; ANN ; KNN ; machine learning (ML) ; naïve Bayes classification ; SVM ; bradykinesia ; wearables ; inertial sensors ; artificial intelligence ; Internet of Things ; trust management ; healthcare ; digital revolution ; edge clouds ; security ; privacy preservation ; neurological disorders ; wearable sensors ; frequency harmonics ; gait impairments ; gait ; harmonic ratio (HR) ; smoothness ; symmetry ; older adults ; inertial sensor ; biofeedback ; neurodegenerative diseases ; movement anticipation ; rs-fMRI ; classifications ; high-order neuro-dynamic functional network ; Alzheimer’s disease ; sleep monitoring ; sleep disorders ; Parkinson disease ; dementia ; Alzheimer Disease ; video analysis ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint covers some significant impacts in the recent research in both the private and public sectors of cancer diagnosis and therapy, in which Artificial Intelligence (AI) and Machine Learning are significant. This reprint is also a collection of forty different complex and challenging problems arranged in five groups: AI in prognosis, grading, and prediction, AI in clinical image analysis, AI models for pathological diagnosis, ML and statistical models for molecular cancer diagnostics and genetics, and AI in triage, risk stratification, and screening cancer, which are all focused on using AI in cancer diagnosis and therapy. All the necessary concepts, solutions, methodologies, and references are supplied except for some fundamental knowledge that is well-known in the general fields of AI and cancer diagnosis and therapy. The readers may, therefore, gain the main concepts of each chapter, with as little of a need as possible to refer to the concepts of the other chapters and references. The readers may hence start to read one or more chapters of the book for their own interests.
    Keywords: artificial intelligence ; machine learning ; bioinformatics ; modeling complex biological systems ; &nbsp ; computational cancer biology ; computational drug discovery ; radiology ; radiation therapy (oncology) ; cancer diagnosis and cancer therapy. ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MJ Clinical & internal medicine::MJC Diseases & disorders::MJCL Oncology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: In collaboration with the MDPI publishing house, we are pleased to introduce the reader to our new project, a Special Issue entitled “Advanced Eco-friendly Wood-Based Composites”. This Special Issue provides an opportunity to investigate advanced eco-friendly wood-based composites from a broader perspective. The coronavirus pandemic and shutdown measures employed to contain it, as well as the ongoing war in Ukraine, have influenced and decelerated the world economy and adversely impacted research activities on most levels in all countries. Surprisingly, researchers in the field of wood-based composites have continued to make progress, which is also described in this Special Issue.
    Keywords: polyurethane foams ; filler ; wood particles ; structure ; properties ; magnesium lignosulfonate ; sodium lignosulfonate ; bio-based adhesives ; urea formaldehyde resin ; wood-based composites ; particleboards ; formaldehyde content ; physical and mechanical properties ; acid-base buffer ; lightweight panels ; waste cardboard ; corner joints ; bending strength ; stiffness ; eco-friendly wood ; lattice beams ; mechanical properties ; wood characterization ; photodegradation ; artificial weathering ; color change ; ultraviolet radiation ; machine learning ; fractionated lignin ; bio-polyurethane resin ; ramie fiber ; impregnation ; thermal stability ; biopolymer ; wood ; upcycling ; composite ; recycling ; physical properties ; carbon storage ; raspberry ; black chokeberry ; bio waste ; moisture content ; angle of repose ; slippery angle of repose ; poured bulk density ; tapped bulk density ; alternative raw material ; walnut ; applied pressure ; wood residues ; resin content ; particleboard ; hemp ; polymer ; composites ; chemical and physical properties ; fiber ; extract ; separation efficiency ; wood dust ; long-term filtration ; dust filtration ; maturation of filter bags ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint compiles the articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles. This reprint encompasses the key topics related to drone design, communications as well as autonomous Flight and Navigation. Special attention is paid to the drones’ applications to environmental and earth sciences, including in agriculture, forestry, water, and marine environments; other innovative applications are also explored including in relation to the field of application, such as the inclusion of new deep learning techniques.
    Keywords: convolutional neural network ; deep learning ; transfer learning ; point clouds ; structural damage assessment ; vegetation indices ; RGB cameras ; unmanned aerial vehicle (UAV) ; empirical line method ; Green leaf index ; open aerial map ; autonomous ; hexacopter ; water quality ; water stratification ; water temperature ; drones ; Martian atmosphere ; thermal analysis ; aerodynamics ; thermoelectric generators ; hyperspectral images ; multispectral data ; machine learning ; ice detection ; UAS ; GCP ; 3D point cloud ; DSM ; image processing accuracy ; actual evapotranspiration ; high spatiotemporal resolution ; multispectral imagery ; thermal infrared imagery ; METRIC energy balance model ; irrigated field crops ; precision agriculture ; travelling salesman problem ; UAV-based precision farming ; Euclidean distance ; Voronoi ; site-specific fertilizer spray ; UAV ; RPAAS ; aerial application ; backpack sprayer ; spray deposition ; droplet spectra ; palmer amaranth ; morningglory ; Reforming-Controlled Compression Ignition ; UAV applications ; exergy analysis ; hydrogen ; dimethyl ether ; fuel reactivity control ; FANETs ; ad hoc networking ; drone swarms ; efficient routing ; traffic monitoring ; 4G/LTE ; VPN ; real-time video ; computer vision ; unmanned aerial systems ; autonomous systems ; wildland fire ; forest fires ; fire detection ; UAVs ; safety ; signal processing ; condition-based maintenance ; structural health monitoring ; fault diagnostics ; fault mitigation ; contingency planning ; streamflow ; sediment loading ; digital terrain model ; rocky coast ; Galicia ; ecosystems ; geomorphic change detection ; GIS ; drone ; dragonfly ; insect ; biomimetic ; biological inspiration ; design ; remote sensing ; coral reefs ; linear unmixing ; R ; Google Earth Engine ; persistent surveillance ; hierarchical architecture of UAV teaming ; communication aware UAV formation ; dynamical object tracking ; intercommunication quality ; UAV-based monitoring ; agricultural robotics ; plant disease detection ; RGB images ; Cercospora leaf spot ; CNNs ; semantic segmentation ; phenotyping ; bog ; Oculus Quest 2 ; Mer Bleue ; SfM ; augmented reality ; AR ; unmanned aerial systems (UAS) ; aerial photogrammetry ; habitat monitoring ; braided river habitats ; efficiency ; data envelopment analysis (DEA) ; civilian use ; factors ; design and selection ; law-making ; mind-mining ; expert groups ; literature study ; triple helix model (THM) ; analytic hierarchy process (AHP) ; collision avoidance ; depth cameras ; point cloud ; CPU ; GPU ; spiral ; Mars ; autogyro ; gyroplane ; autonomous flight ; indoor positioning ; cyber pilot ; sensor fusion ; distributed electric propulsion ; boundary layer ingestion ; propeller ; fixed wing ; aerial drones ; autonomous navigation ; path planning ; reactive control ; obstacle avoidance ; sense-and-avoid ; hybrid navigation method ; dynamic environments ; small unmanned aircraft systems ; photogrammetry ; structure-from-motion ; wind impact ; turbulence ; crash scene reconstruction ; traffic incident management ; detection ; CBRNe ; MOX ; chemical sensor ; simulation ; fluid dynamics simulations ; green water ; integrated water management strategies ; smallholder farms ; water productivity ; localization ; communication ; drone swarm ; lidar ; streams ; canopy height ; roughness ; vegetation density ; change detection ; NB-IoT ; network analysis ; simulations ; landslides ; multispectral ; RGB ; vegetation monitoring ; legislation ; ethics ; spatial social sciences ; advanced leak detection ; advanced leak quantification ; source estimation ; environmental monitoring ; landfill ; natural gas ; human–swarm interaction ; situation awareness ; user-centered interface design ; thermal imaging ; blackbody ; emissivity ; thermography ; base stations ; cellular networks ; photovoltaic system ; battery ; search and rescue ; autonomous drones ; acceleration ; deceleration ; drone classification ; CNN ; HERM lines ; micro-Doppler ; radars ; aeromagnetics ; drone survey ; mineral exploration ; geophysical prospecting ; speed ; RFID ; inventory ; labor ; forecast ; drone technology ; aquaculture ; precision aquaculture ; aquaculture monitoring ; aquaculture drones ; internet of things ; swarm robotics ; unmanned aerial vehicle ; evolutionary game theory ; evolutionary algorithm ; surveillance system ; multi-objective optimisation ; digital elevation model (DEM) ; digital surface model (DSM) ; orthomosaic ; Earth observation ; unmanned aerial vehicles (UAV) ; social acceptance ; urban air mobility (UAM) ; CORUS-XUAM ; proper orthogonal decomposition ; cellular-enabled drones ; aerial base stations ; 5G/B5G/6G cellular networks ; gesture recognition ; small drone ; long-distance surveillance ; ground target tracking ; track-to-track association ; image-to-position conversion ; anti-collision radar ; autonomous flight unmanned aerial system ; obstacle detection ; radar mapping ; unmanned aerial system (UAS) ; n/a ; grazing density ; nutrient ; pasture management ; forage grass ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint aims to provide a common forum to share knowledge about the growing threat of geohazards such as landslides, earthquakes, floods, tsunamis, coastal changes, and drought, among many others, due to the expanding size of cities and urban areas, the critical use of agricultural lands, the increased use of infrastructure, and the effects of climate change.A total of thirty-one papers (twenty-eight research papers, one review paper, and one technical note) on different topics like coastal changes, landslides, earthquakes, and others are presented in this reprint. The published works have been carried out in different parts of the world, such as Spain, Portugal, France, Italy, Hungary, China, South Korea, India, Malaysia, Algeria, Canada, or Mexico.
    Keywords: debris flow ; berm ; mitigation measure ; volumetric concentration ; gas hydrates ; European margins ; geohazard assessment ; electric tomography ; three-dimensional ; electrodes ; seat control ; foundations ; stabilization methodology ; landslide displacement prediction ; decomposition-ensemble model ; recurrent neural network (RNN) ; ensemble empirical mode decomposition (EEMD) ; maximal information coefficient (MIC) ; flood vulnerability ; spatial analysis ; logistic regression ; ROC analysis ; flood detection ; site effects ; spectral ratio ; trans-mexican volcanic belt ; landslide ; safety factor ; Central Spanish Pyrenees ; soft rocks ; stabilization measures ; b value ; stable state ; depth ; Longmenshan fault ; flood risk ; cultural heritage sites ; bathymetric data ; manning’s roughness coefficient ; hydrodynamic modelling ; beach erosion ; storm waves ; recovery process ; video monitoring ; pocket beach ; Middle-Chelif sedimentary basin ; HVSR ; array measurement ; frequency–wavenumber (F–K) method ; landslide-induced wave ; lake-tsunami assessment ; mountain lakes ; landslides ; artificial rainfall ; grain size ; rainfall pattern ; pore water pressure ; generator of earthquakes ; low-to-moderate seismicity ; stochastic ; France ; loess ; dry-wet cycles ; triaxial creep test ; creep behavior ; strain-time ; long-term strength ; forest fires ; Cat model ; climate change ; disaster risk ; machine learning ; R programming language ; extreme droughts ; modeling ; crop yield losses ; crop insurance ; landslide dynamics ; landslide classification ; dynamic models ; depth-averaged model ; GIS ; coastal morpho-sedimentary dynamics ; erosion/accretion patterns ; remote sensing ; beach types ; meteo-ocean effects ; landslide susceptibility ; volume ratio ; reserve increase-rate-analysis method ; Loess Plateau ; landslide risk ; natural phenomena ; Reggio Calabria ; AHP method ; multi-hazard ; earthquake ; wind ; flood ; hazards ; hurricane ; mitigation ; resilience ; risk assessment ; bridge ; building ; wind turbine ; control system ; Middle-Chelif Basin ; ambient vibrations ; array techniques ; Vs30 ; site classification ; liquefaction ; electron bursts ; NOAA satellite ; East Pacific earthquakes ; conditional probability ; risk reduction ; validation ; predictive capability ; tropical climate ; Malaysia ; insurance hazard model ; earthquake clustering ; space–time ETAS model ; Hungarian earthquake catalogue ; 2020 Petrinja earthquake ; multi-criteria decision analysis (MCDA) ; analytical hierarchy process (AHP) ; receiver operating characteristics ; area under the curve (AUC) ; completely weathered granite ; runoff ; sediment production ; slope erosion ; flow velocity hydrodynamic characteristics ; combination weighting method ; cluster analysis ; optimization ; classification of debris flows ; Longmenshan Town ; dune cliff ; land management ; data analysis ; earth fissure ; microtremor testing ; spectrum analysis ; amplification effect ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This volume gathers papers from the fields of philosophy, theology, and empirical psychology on the topic of gratitude to God. Central themes include the difference between gratitude to God and gratitude to human benefactors and correlations between gratitude to God and important life outcomes.
    Keywords: gratitude ; religiosity ; spirituality ; well-being ; Aquinas ; virtue ; religion ; gratitude to God ; health ; federal funding ; systematic review ; conceptual metaphor ; analogy ; anthropomorphism ; God concepts ; gratitude expressions ; public gratitude ; social media ; data science ; machine learning ; challenges ; review ; God ; supernatural attribution ; gift ; divine attributions ; religious attributions ; religious appraisals ; measurement ; religious belief ; liturgy ; group action ; joint action ; social ontology ; extraversion ; optimism ; vitality ; self-esteem ; agreeableness ; honesty–humility ; entitlement ; secure attachment ; construal ; religiousness ; Christianity ; theism ; Dietrich Bonhoeffer ; Jonathan Edwards ; Soren Kierkegaard ; Karl Barth ; creation ; Mozart ; Beethoven ; Bible ; doctrine of Scripture ; tradition ; inspiration ; church ; canon ; theology ; acceptance ; pantheism ; axiarchism ; ultimism ; Stoicism ; Kierkegaard ; local evils ; suffering ; transcendent gratitude ; cosmic gratitude ; transcendence ; beliefs ; case study ; qualitative ; doubt ; atheism ; agnosticism ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBN Public health & preventive medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The topic of the reprint is very important nowadays, because ever-evolving machine learning techniques make it possible to obtain better real-world data. Therefore, this reprint contains information related to real data in fields such as automatic sign language translation, bike-sharing travel characteristics, stock index, sports data, fake news data, and more. However, it should be noted that the reprint also contains a lot of information on new developments in machine learning, new algorithms, algorithm modifications, and a new measure of classification quality assessment that also takes into account the preferences of the decision maker.
    Keywords: machine learning ; optical networks ; imbalanced data ; one-class classification ; entropy measure ; real-world data ; preprocessing ; decision table ; classification ; query set ; decision tree ; differential cryptanalysis ; metaheuristics ; symmetric block ciphers ; memetic algorithms ; DES ; simulated annealing ; COVID-19 ; vaccination ; agent-based modelling ; dynamic stochastic general equilibrium models ; scenario analyses ; validation of results ; stock index forecasting ; CEEMDAN ; ADF ; ARMA ; LSTM ; hybrid model ; classification measure ; quality of classification ; quality measure ; preference-driven classification ; fast iterative filtering ; parameter adaptive refined composite multiscale fluctuation-based dispersion entropy ; rotating machinery ; fault diagnosis ; short-term demand prediction ; bike-sharing ; travel characteristics analysis ; hybrid TCN-GRU model ; distributed data ; decision tables ; information systems ; decision trees ; decision rules ; tests ; reducts ; association rules ; Pawlak conflict analysis model ; independent data sources ; coalitions ; dispersed data ; length ; support ; greedy heuristics ; feature selection ; rough sets ; action units ; automatic translation ; sign language ; entropy of real data ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-02
    Description: This reprint, as a continuation of a previous Special Issue entitled “Efficiency and Optimization of Buildings Energy Consumption”, gives an up-to-date overview of new technologies based on Machine Learning (ML) and Internet of Things (IoT) procedures to improve the mathematical approach of algorithms that allow control systems to be improved with the aim of reducing housing sector energy consumption.
    Keywords: ventilation ; energy ; COVID-19 ; procedure ; building ; ISO ; energy consumption ; building construction ; Passivhaus ; affordable housing ; neural network ; LSTM ; MLP ; thermal inertia ; building performance ; artificial intelligence ; artificial neural network ; demand-side management ; evolutionary computing ; non-intrusive appliance load monitoring ; parallel computing ; smart grid ; smart house ; cellular concrete ; lightweight materials ; thermal conductivity ; electricity ; dynamic simulation ; housing ; climate change ; weather controlled central system ; energy saving ; thermal improved of buildings ; new energy technologies ; sustainable buildings ; energy efficiency ; heat loss coefficient ; machine learning ; XGBoost ; SVR ; load disaggregation ; multi-scale ; attention mechanism ; residual network ; energy savings ; daylighting ; photovoltaic system ; EnergyPlus ; Homer PRO ; Net Zero Energy Buildings ; solar radiation ; support vector machine ; heuristic algorithm ; renewable energy ; solar energy systems ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Encyclopedia of Engineering aims at providing a collection of entries concerning several fields of Engineering Sciences. The reprint provides a historical overview, starting from the investigation of Mechanics and Science in Ancient Greece and showing their evolution over time. The topical collection focuses on Civil, Mechanical and Aerospace Engineering providing basic concepts as well as novel trends in modeling, design and construction of engineering systems, structures, and materials. Special attention is also given to the recent developments and achievements in the framework of Nanoscience and Nanotechnology.
    Keywords: ball burnishing ; acoustoplasticity ; vibration-assistance ; surface integrity ; surface topology ; classical mechanics ; fundaments ; history ; epistemology ; analytical mechanics ; nanoparticles ; colloidal solutions ; electrical charging ; self-polarization ; mixed-electrode ; particle growth ; particle interaction ; machine learning ; supervised learning ; unsupervised learning ; reinforcement learning ; additive manufacturing ; design for additive manufacturing ; additive manufacturing process ; additive manufacturing monitoring ; limits of nanotechnology ; nanofacility shrinking ; modularity ; sustainability ; hierarchical organization ; entropy export ; time scales ; life cycles ; non-thermal extraction ; bioactive compounds ; nanoencapsulation ; ultrasound ; cold plasma ; high-pressure processing ; supercritical extraction ; pulse electric field ; speed ; infrastructure ; rolling stock ; in-cab signaling system ; absence of level crossing ; approach alignment ; outer radius ; circulatory roadway ; apron ; splitter island ; roundabout entry ; roundabout exit ; longitudinal slope ; smart factory ; cloud computing ; fog computing ; edge computing ; knowledge integration ; knowledge management ; data analytics ; text analytics ; knowledge graph ; high carbon steel wire ; reinforcing material ; automobile tire ; steel cord ; bead wire ; drawing ; patenting ; brass-plated wire ; laying ; cooling systems ; turbine casings ; Active Clearance Control ; silicon micro-strips ; tracker detectors ; positioning algorithms ; least-squares method ; track reconstructions ; natural hazards ; disasters ; global impacts ; disaster management ; built environment ; GNSS ; ionosphere ; remote sensing ; catalysis ; buildings ; heat pumps ; dehumidification ; carbon capture ; emissions ; indoor air quality ; cogeneration ; non-precious metals ; photo-catalysis ; electrocatalysis ; aircraft icing ; aircraft safety ; computational fluid dynamics ; OpenFOAM ; data-driven modeling ; offsite manufacturing ; inter-modular connections ; Design for Manufacturing and Assembly (DfMA) ; structural design ; modularisation ; modular construction ; panelised construction ; connection design—worked example ; design for transportation ; lifting and handling ; mechanics ; mathematics ; natural philosophy ; Aristotle ; Euclid ; flywheel energy storage ; high-speed rotors ; mechanical design ; manufacturing ; analytical modeling ; failure prediction ; decision matrix ; tsunami alert ; tsunami awareness ; tsunami efficiency ; tsunami hazard ; tsunami messages ; tsunami preparedness ; tsunami ready ; tsunami risk ; tsunami warning ; polyelectrolyte microcapsules ; decapsulation ; controlled release ; infilled RC frames ; nonstructural elements ; earthquake damages ; macro-models ; seismic behavior ; two-lane highways ; rural ; passing ; platooning ; access ; mobility ; low-volume roads ; desiccation cracking ; hydromechanical coupling ; unsaturated soil mechanics ; release node technique ; urban transportation ; transportation demand management ; electrification of urban transportation ; intelligent transportation system ; transit-oriented development (TOD) ; GNSS-RTN ; real-time network ; highly accurate geospatial data ; transportation ; tall buildings ; gravity-load systems ; lateral-load systems ; shear walls ; bracings ; rigid frames ; structural systems charts ; tube structures ; core-outrigger systems ; interior and exterior systems ; solar architecture ; energy engineering ; solar solution ; application category ; application group ; solar surface ; energy conversion ; energy harvesting ; energy losses ; solar irradiation ; life cycle assessment ; balance ; carbon ; cost ; return on investment ; road markings ; road signs ; road safety ; traffic control devices ; road infrastructure ; maintenance ; rehabilitation ; sewer history ; sewer system ; architecture ; biology ; bioinspiration ; biomimetics ; biomimicry ; interdisciplinarity ; analogical design process ; nonlocal continuum mechanics ; nanostructures ; integral elasticity ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, machine learning models; undertakes critical comparisons with existing techniques; and presents an interpretation of the results. The topics within the chapters of the publication fall into six categories: computer vision, teaching and learning, social media, forecasting, basic problems of machine learning, and other topics.
    Keywords: robust matrix factorization ; student grade prediction ; educational data mining ; side information graph ; personal teaching and learning ; deep multi-target prediction ; Felder–Silverman learning style ; adaptive e-learning systems ; artificial neural network ; deep learning ; transfer learning ; student performance prediction ; Machine learning analysis ; sentence modeling ; topic analysis ; cross referencing topic ; machine learning ; classification ; preprocessing ; instance selection ; data mining ; predictive analytics ; sales ; performance measurement ; human resources ; rumor refuter ; nature language processing ; XGBoost ; feature analysis ; Bitcoin ; higher order neural network ; volatility forecasting ; hybrid models ; warehouse optimization ; genetic algorithms ; crossover ; construction productivity ; construction safety ; synthetic data ; tracking ; academic performance ; course grades ; grade point average ; prediction ; undergraduate ; cloud detection ; superpixel segmentation ; convolutional neural networks ; support vector machines ; machine learning algorithms ; multiple linear regression ; SVM ; management ; social network services ; image representation ; local features ; autoencoder ; convolutional neural network ; user generated content ; sentiment analysis ; keyword extraction ; text representation ; sampling ; TripAdvisor ; adaptive camouflage ; convolutional neural network (CNN) ; k-means ; object detection ; image completion ; saliency detection ; social media ; micro-blogs (Twitter) ; towards recommending influencers based on topic classification ; investigation framework ; comparison of various techniques for topic classification ; cost-benefit function ; partial differential equations ; physics-informed neural network ; wave equation ; KdV-Burgers equation ; KdV equation ; neural network ; cyclical learning rate ; remote sensing ; scene classification ; backscatter data ; lidar ceilometer ; weather detection ; online taxi-hailing demand ; backpropagation neural network ; extreme gradient boosting ; real-time prediction ; climate zone ; climate change impact ; Jhelum River Basin ; Chenab River Basin ; support vector machine ; decision tree ; large-scale dataset ; relative support distance ; support vector candidates ; answer set programming ; non-deterministic automata induction ; grammatical inference ; geopolymer concrete ; deep neural network ; ResNet ; compressive strength ; fly ash ; sleep apnea ; airflow signal ; Gaussian Mixture Models (GMM) ; cyber security ; vulnerability detection ; word embedding ; drifter trajectory ; evolutionary computation ; NCLS ; stock performance ; earning rate ; volatility ; heatwaves ; big data ; random forest regression model ; semi-regression ; early prognosis ; interpretation ; COREG algorithm ; cascaded classifier ; computer vision ; construction site management ; consumer classification ; over-the-top ; time-aware classification ; code auto-completion ; GPT-2 model ; advanced design methods ; mass operator ; structural stress ; live prediction ; vibration test ; genetic programming ; parsing expression grammar ; BiLSTM ; BERT ; NLP ; context-aware ; LDA ; LSTM ; crowdfunding ; project recommendation system ; optimization ; weather nowcasting ; deep neural networks ; autoencoders ; Principal Component Analysis ; learning classifier systems ; anticipatory classifier systems ; reinforcement learning ; OpenAI gym ; healthcare ; COVID ; time-series predictions ; ARIMA ; Prophet ; GRNN ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
    Keywords: EEG ; transfer learning ; review ; decoding ; classification ; e-textile ; head phantom ; electroencephalography ; conductive material ; mental stress ; data analysis ; connectivity network ; machine Learning ; deep learning ; vigilance decrement ; sustained attention ; mental fatigue ; cross-participant ; cross-task ; task-generic ; electroencephalogram ; wavelet spectrum ; ridge ; segmentation ; phase connectivity ; epilepsy ; traumatic brain injury ; feature extraction ; functional connectivity network ; time-frequency features ; machine learning ; ALS ; classifier ; neural ; connectivity ; frequency-specific ; BCI ; acupuncture ; dimensionality ; neural subspace ; latent variables ; attractor ; adaptive threshold ; coherence ; functional connectivity ; multilayer network ; otsu ; phase locking value ; weighted phase lag index ; complex Pearson correlation coefficients ; transcranial magnetic stimulation ; cerebral cortex stimulation ; electromagnetic influence ; neurostimulation ; brain activity ; virtual reality ; neuropathic pain ; spinal cord injury ; fractal dimension ; ERP ; speech discrimination ; seizure detection ; features ; feature selection ; motion artifact ; electroencephalogram (EEG) ; functional near-infrared spectroscopy (fNIRS) ; wavelet packet decomposition (WPD) ; canonical correlation analysis (CCA) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint highlights the importance of Deep Learning (DL), which has garnered significant attention in science, industry, and academia. It draws inspiration from the functioning of the human brain and the concept of learning. Unlike traditional and machine learning methods, deep learning techniques emulate the human brain's neural networks at a lower scale, allowing them to process and analyze substantial quantities of unstructured data. The remarkable proficiency of deep learning in unveiling intricate structures within extensive datasets genuinely resembles the extraordinary aptitude of the brain to recognize patterns and form complex connections. This unique characteristic allows DL to excel in modeling and solving complex problems across various scientific and technological fields. Just as the brain learns from experience, DL architectures learn through algorithms from data by adjusting numerous parameters during training to optimize their performance and accuracy. This concept of learning and adaptation is fundamental to DL's success. This reprint serves as an excellent opportunity to disseminate current knowledge beyond academic boundaries, reaching a diverse audience encompassing academics, professionals, and the general public. This wide readership fosters the potential for meaningful connections to established projects and the cultivation of collaboration for future research endeavors.
    Keywords: PSO ; sign language recognition ; optimization of convolutional neural networks ; breast segmentation ; mammogram ; deep learning ; semantic segmentation ; radar image prediction ; rain radar ; precipitation nowcasting ; UNet ; PredRNN_v2 ; cubical complex ; cubical homology ; image classification ; persistent homology ; labor exports ; Northeast Asian Countries ; backpropagation neural network (BPNN) ; k-Nearest Neighbor (kNN) ; random forest regression (RFR) ; decision making ; emotion distribution learning ; text-based emotion analysis ; affective words ; multi-task CNN ; ghettos ; GIS ; networks ; Washington D.C. ; machine learning ; segregation ; hybrid deep learning ; time series ; LSTM ; Stacked LSTM ; CNN-LSTMs ; BDLSTM ; CNN ; GRU ; modeling ; SARS-CoV-2 ; generative adversarial network ; image generation ; image synthesis ; GAN ; generative model ; Inception score ; scoreGAN ; waste classification ; angle detection box ; dynamic smoothing ; YOLOv5 ; computer vision ; object detection ; traffic sign detection ; you only look once (YOLO) ; attention mechanism ; feature fusion ; barrier options ; Black–Scholes model ; polynomial regression ; random forest regression ; artificial neural network ; option Greeks ; data analysis ; ski goggles lenses ; surface defect ; automatic optical inspection ; Faster-RCNN ; fine-tune ; MobileNetV3 ; FPN ; RPN ; DNS ; firewall ; malicious ; domain ; name ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 139
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-08-08
    Description: With the development of society and the economy, sustainable structures and construction are becoming increasingly necessary in civil engineering. Sustainability in construction refers to eco-friendly and economical practices that occur throughout the whole life cycle of structures, including their design, construction, service and demolition. Sustainable structures include fabricated and modular structures, structures constructed using bio-based materials, as well as others. Specifically, timber, bamboo and light steel have become increasingly popular building materials. Additionally, wall panels made from eco-friendly materials can be used to reduce buildings’ energy consumption and carbon emissions. Sustainable construction necessitates prefabricated construction and the recycling and reuse of materials, structures, etc. Key problems have been proposed and solved in regard to sustainable structures and construction in practice. This Special Issue provides an international forum for the presentation and discussion of the latest developments in sustainable structures and construction in civil engineering. The topics of interest include the modeling, testing and construction of sustainable structures. Original papers focused on all aspects of sustainable structures and construction have been accepted for publication.
    Keywords: sustainable construction ; construction site of prefabricated buildings ; multi-objective layout and optimization ; MPC-NSGA-II algorithm ; clay ; pile foundation ; base resistance ; influence depth ; cone penetration test ; super-large span ; mega-latticed structure ; dynamic characteristics ; seismic performance ; plastic development ; model selection ; composite beam ; material performance test ; bending performance ; theoretical analysis ; numerical simulation ; soft soil ; compressive bearing capacity ; carbon emission ; diagonally stiffened plates ; combined action ; elastic buckling coefficient ; machine learning ; Shapley Additive exPlanations ; bio-based materials and structures ; sustainable structures ; plant fiber concrete ; light steel keel wall panel ; thermal performance ; optimum design ; rural light steel frame structure ; building information modeling ; simulated annealing algorithm ; long-term monitoring data ; temperature-induced stress ; multi-scale model ; substructure ; state evaluation ; sustainable structure ; digital twin ; mechanical response ; reliability analysis ; experimental validation ; straw bio-based material ; wheat straw strand board ; paper straw board ; temperature control box—heat flux meter method ; thermal conductivity ; sustainable architecture ; rural prefabricated housing ; climate analysis ; structural thermal bridges ; energy optimization ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 140
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Sensors used to diagnose, monitor or treat diseases in the medical domain are known as medical sensors. There are several types of medical sensors that can be utilized for various applications, such as temperature probes, force sensors, pressure sensors, oximeters, electrocardiogram sensors that measure the electrical activity of the heart, heart rate sensors, electroencephalogram sensors that measure the electrical activity of the brain, electromyogram sensors that record electrical activity produced by skeletal muscles, and respiration rate sensors that count how many times the chest rises in a minute. The output of these sensors used to be interpreted by humans, which was time consuming and tedious; however, such interpretations became easy with advances in artificial intelligence (AI) techniques and the integration of the sensor outputs into computer-aided diagnostic (CAD) systems. This reprint presents some of the state-of-the-art AI approaches that are used to diagnose different diseases and disorders based on the data collected from different medical sensors. The ultimate goal is to develop comprehensive and automated computer-aided diagnosis by focusing on the different machine learning algorithms that can be used for this purpose as well as novel applications in the medical field.
    Keywords: prostate cancer ; image processing ; histopathology images ; digital image analysis ; computational pathology ; artificial intelligence ; Nosema disease ; machine learning ; deep learning ; image ; disease detection ; blood flow velocity quantification ; conjunctival microvessel ; motion correction ; optical imaging system ; vessel segmentation ; transfer learning ; ALexNet ; VGGNet ; ADC maps ; computer-aided diagnosis ; convolutional neural networks ; diabetic retinopathy ; diabetic retinopathy classification ; diabetic retinopathy lesions localization ; YOLO ; thyroid ; cancer ; CNN ; MRI ; DWI ; radiomics ; BITalino ; BrainAmp ; ICC ; intraclass correlation coefficient ; Bland–Altman method ; big healthcare data ; classification ; decision-making ; feature selection ; whale optimization ; naive bayes ; renal cell carcinoma ; CE-CT ; morphology ; texture ; functionality ; RC-CAD ; electrocardiogram (ECG) ; affective computing ; emotion recognition system ; healthcare ; Alzheimer’s disease ; personalized diagnosis ; mild cognitive impairment ; sMRI ; U-NET ; uveitis grading ; OCT segmentation ; computed tomography (CT) ; lung ; chest ; segmentation ; COVID-19 ; autism ; ASD ; CWT ; dendritic cells ; electrical characterization ; immune system ; macrophages ; chest X-ray ; diagnosis ; POCUS ; multichannel system ; channel data ; bladder monitoring ; POUR ; machine-learning ; NC protein ; optical detection ; protein–protein interactions ; RBD ; SARS-CoV-2 ; grade groups ; CAD system ; chewing ; smart devices ; discrete wavelet decomposition ; low pass filter ; number of chews ; carotid intima-media thickness ; IMT ; CCA ; encoder-decoder model ; left ventricular assist devices ; sensor-based control ; pump independent ; suction index ; physiological perfusion ; suction prevention ; biomedical informatics ; cardiovascular disease ; ECG ; heart rate variability ; PPG ; smartphones ; smart wearables ; thermal camera ; non-contact spirometry ; artificial intelligence regression ; respiration signal ; respiration rate mobile application ; multiple object tracking ; data association ; dataset ; semantic attribute ; autism spectrum disorder (ASD) ; DTI ; neuroimaging ; ABIDE-II ; lung sound detection ; heart sound detection ; convolutional neural network ; model fusion ; multi-features ; texture analysis ; shape features ; functional features ; PSA ; osteoporosis ; strength training ; osteopenia ; bone mass ; DEXA ; diabetic retinopathy (DR) ; optical coherence tomography angiography (OCTA) ; convolutional neural networks (CNN) ; image encryption ; security analysis ; convolutional neural network (CNN) ; brain imaging ; machine learning (ML) ; cervical cancer ; human papillomavirus (HPV) ; gradient boosting ; support vector machine (SVM) ; skin lesions ; skin cancer ; melanoma ; image classification ; Diabetic Retinopathy ; fundus images ; lesions detection ; n/a
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
    Keywords: fintech ; financial technology ; blockchain ; deep learning ; regtech ; environment ; social sciences ; machine learning ; learning analytics ; student field forecasting ; imbalanced datasets ; explainable machine learning ; intelligent tutoring system ; adversarial machine learning ; transfer learning ; cognitive bias ; stock market ; behavioural finance ; investor’s profile ; Teheran Stock Exchange ; unsupervised learning ; clustering ; big data frameworks ; fault tolerance ; stream processing systems ; distributed frameworks ; Spark ; Hadoop ; Storm ; Samza ; Flink ; comparative analysis ; a survey ; data science ; educational data mining ; supervised learning ; secondary education ; academic performance ; text-to-SQL ; natural language processing ; database ; machine translation ; medical image segmentation ; convolutional neural networks ; SE block ; U-net ; DeepLabV3plus ; cyber-security ; medical services ; cyber-attacks ; data communication ; distributed ledger ; identity management ; RAFT ; HL7 ; electronic health record ; Hyperledger Composer ; cybersecurity ; password security ; browser security ; social media ; ANOVA ; SPSS ; internet of things ; cloud computing ; computational models ; metaheuristics ; phishing detection ; website phishing ; thema EDItEUR::U Computing and Information Technology
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  • 142
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: This topic has been successfully completed. A total of 180 scientific articles were sent, of which 66 have been accepted for publication. These 66 articles are published in reprint.
    Keywords: artificial intelligence ; expert systems ; machine learning ; deep learning ; modeling ; prediction ; probabilistic models ; prediction models ; sustainable mobility ; smart cities ; smart grids ; sustainable energy systems ; renewable energy sources ; nonrenewable energy sources ; electrical storage ; green hydrogen ; sustainable greenhouses ; wind ; microgrids ; tidal ; solar ; biomass ; power network ; solar thermal ; solar photovoltaic ; hydraulics ; ANN ; neural networks, fuzzy logic, genetic algorithms ; hybrid models based on artificial intelligence ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: This reprint, titled "Sustainable Crop Plants Protection: Implications for Pest and Disease Control", has become of scientific interest again for a reason: to continue its mission of advancing the science and practice of sustainable agriculture. This Special Issue delves into the multifaceted world of crop protection, exploring innovative approaches, technologies, and solutions that are pivotal for the future of agriculture. Our objectives remain as relevant today as they were when the first call went out for the Special Issue of sustainability, to shed light on sustainable pest and disease control strategies, foster scientific collaboration, and provide a platform for sharing knowledge that can transform agriculture for the better.
    Keywords: antioxidant enzymes ; extracellular enzymes ; pathogen ; reactive oxygen species ; systemic acquired resistance ; soil microbes ; microbial respiration ; organic carbon ; Phytonematodes ; soil ; machine learning ; Black Sigatoka ; Musa ; production ; banana disease ; random forest ; plant health system ; stakeholder analysis ; plant health problems ; rootstock ; grapevines ; Colomerus vitis ; oxidase ; resveratrol ; mite ; Oecophylla genus ; population abundance ; territorial foragers ; quarantine defoliators ; IPM ; biological control ; beneficial microorganisms ; microbial metabolite ; Fragaria annanasa ; time series ; data augmentation ; deep learning ; pest forecasting ; generative adversarial network (GAN) ; cypress oil ; nanoemulsion ; terpenes ; Sitophilus oryzae ; bioactivity ; biosafety ; diagnostic ; disease ; pepper ; ribonucleic acid ; survey ; viruses ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
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  • 144
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint focuses on quantitatively assessing the impact of climate change on agricultural production based on multi-source model simulation and reveals the role and mechanism of improved management measures in adapting to climate change. Modeling is a key tool for exploring the impacts of climate change on agriculture and proposing adaptation strategies. The insights derived from this reprint will be helpful for relevant decision makers in the areas of agricultural adaptation and food security.
    Keywords: temperature ; evaluation ; CLDAS ; GLDAS ; ERA5-Land ; adaptation ; climate change ; summer maize ; phenology shift ; GCM ; CNRM-CM6 ; PET ; IPCC-AR6 ; SSP scenarios ; solar induced chlorophyll fluorescence (SIF) ; winter wheat ; yield forecast ; random forest ; enhanced vegetation index (EVI) ; geographic distribution ; suitable habitat ; Rheum nanum ; MaxEnt ; ArcGIS ; range shifts ; climate scenario ; agriculture ; food security ; planting boundary ; crop modelling ; yield ; future climate scenarios ; soybean ; CROPWAT ; reference crop evapotranspiration (ET0) ; crop water requirement (ETc) ; irrigation water requirement (Ir) ; crop yield ; cultivated area ; water use ; wheat–corn ; DNDC ; net greenhouse effect ; anaerobic digestion ; biogas production ; k-nearest neighbours ; support vector machine ; middle and lower reaches of Yangtze River ; rice ; heat stress ; nitrous oxide ; soil gas flux ; silicone diffusion cell ; soil gas diffusivity ; passive gas sampling ; soil gas diffusion coefficient ; soil gas flux simulation ; carbon sequestration ; different scenarios ; land use ; sustainable development ; Xinjiang ; ETo ; yield response factor ; irrigation water requirement ; cotton ; GCMs ; CERES-rice model ; rice yield ; light and heat resource utilization ; potential evapotranspiration (ET0) ; Penman–Monteith ; sensitivity analysis ; contribution rate ; optimal irrigation ; sustainable irrigation ; water use efficiency ; North China Plain ; sugarcane ; SPEI ; waterlogging ; growth stage ; climatic yield ; yield prediction ; machine learning ; APSIM model ; climate indices ; range shift ; apple trees ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: Global population growth, population aging, declining labor force levels, and rising production costs pose more challenges to agricultural production. In recent years, due to the improved performance of artificial intelligence, precision agriculture, and advanced control, they have been widely used in various agricultural applications, including management, disease detection, crop monitoring, yield estimation, and crop harvesting. Robotics and autonomous machines represent a high-level application of automation in agriculture, based on precise and resource-efficient approaches to sustainably achieve greater efficiency and quality in the production of agricultural products while reducing environmental impact. Reactive technologies based on agricultural robots and autonomous machines are separate but closely related fields covering the application of automated control and robotic platforms at all levels of agricultural production. In robotic or autonomous systems, agricultural sensing and control is particularly difficult due to the complexity of the environment in which agricultural production operates. The open robot system has good expansibility, versatility and flexible operation ability. The establishment of agricultural robot control system can guarantee the reliability and real-time control. A total of 26 papers are included that explores the various ways in which robotics and autonomous machines for agricultural production address general problems.
    Keywords: mobile manipulation ; optimization and optimal control ; agricultural robotics ; viticulture ; jujube pruning ; manipulator ; kinematic analysis ; high-speed photography technology ; performance test ; picking manipulator ; motion planning ; TO-RRT ; step-size dichotomy ; regression superposition ; robotic pest control ; Mask R-CNN ; skeleton extraction ; binocular vision ; stereo matching ; machine vision ; picking robot ; apple detection ; YOLOX ; ShufflenetV2 ; point cloud registration of fruit trees ; lightning attachment procedure optimization ; density-based spatial clustering of applications with noise ; information perception of fruit trees ; precision planter ; motor-driven ; CANopen protocol ; photoelectric sensor ; no-tillage ; straw-rotting fungus ; multiarm harvesting trajectory optimization ; multiobjective optimization ; cluster fruit ; genetic ant colony stepwise algorithm ; dairy farm ; pusher robot ; path extraction ; obstacle avoidance ; high-performance film for full recycling ; film recycling ; field experiment ; film recycling rate ; precision agriculture ; Industry 4.0 ; technology ; adoption ; unmanned vehicles ; smart production ; drones ; robots ; cotton precision planter ; cotton seeds ; broadcast monitoring ; missed broadcast monitoring ; sowing quality ; electrical characteristics ; poultry eggs ; nondestructive detection ; cracked eggs ; machine learning ; garlic seeding ; orientation recognition ; garlic clove righting ; deep learning ; fully connected neural network ; autonomous navigation ; navigation line extraction ; orchard machinery ; least-square ; apple harvesting ; soft gripper ; Fin Ray effect ; finite element analysis ; constant-pressure feedback ; slip detection ; fresh weight prediction ; growth model ; naive Bayesian network ; solar greenhouse ; substrate-cultivated lettuce ; phenotyping ; agricultural robot ; tiller counting ; residual network ; agriculture ; path planning ; neighborhood collection ; autonomous vehicle ; genetic algorithm ; global optimization ; bale collection problem ; forage handling ; pineapple eye ; three-dimensional ; YOLOv5 ; stereo-matching ; cotton seeder ; duckbill ; Simufact Welding ; welding robot ; automated welding ; apple grader ; attention mechanism SE ; DIoU_Loss ; mish ; autonomous robots ; data acquisition ; computer vision ; shrimp ; automatic peeling machines ; tactile perception ; recognition ; wavelet scattering convolutional network ; microcurrent signal analysis ; egg’s electrical characteristic model ; artificial intelligence ; IoT ; cloud computing ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Liquid biopsy shows promise for cancer screening and diagnostics. This reprint collects recent scientific literature on the identification and application of tumor biomarkers in biological fluids to improve the diagnosis of cancer and the identification of optimal therapeutic strategies.
    Keywords: primary breast cancer ; circulating nucleosomes ; circulating tumor cells ; plasminogen activator inhibitor-1 ; cytokines ; prostate cancer ; breast cancer ; treatment decisions ; exosomes ; molecular composition ; cancer pathogenesis ; diagnostics ; therapeutics ; leptomeningeal metastasis ; cerebrospinal fluid ; extracellular vesicle ; biomarker ; RNA sequencing ; small non-coding RNA ; microRNA ; exo-oncomiRNAS ; TWEAK ; semen ; rheumatoid factor ; autoimmunity ; autoantibodies ; cancer ; predictive biomarker ; prognostic biomarker ; cancer progression ; cancer development ; immunotherapy ; cancer susceptibility ; tumor recurrence ; tumor load ; fecal immunochemical test (FIT) ; colonoscopy ; flexible sigmoidoscopy ; liquid biopsy ; mRNA ; ctDNA ; proteins ; extracellular vesicles ; biomarkers ; exosome ; lung cancer ; miRNA ; plasma ; serum ; volatile organic compounds (VOCs) ; gas chromatography (GC) ; mass spectrometry (MS) ; headspace solid phase microextraction (HS-SPME) ; breast cancer biomarkers ; principal component analysis (PCA) ; linear discriminant analysis (LDA) ; principal component regression (PCR) ; cfDNA ; hereditary and familial pancreatic cancer ; somatic mutation profiling ; potentially druggable genes ; uveal melanoma ; circulating tumor DNA ; next generation sequencing ; PKC inhibitor ; treatment ; response ; melanoma ; ovarian cancer ; lipidomics ; lipid ; prognosis ; ceramide ; phospholipid ; plasmalogen ; patient stratification ; outcome ; personalized medicine ; neuroblastoma ; immune monitoring ; anti-GD2 ; IL-2 ; GM-CSF ; ASCT ; dinutuximab ; anti-PD-1 ; urothelial cancer ; blood biomarkers ; NETs ; disease modelling ; machine learning ; metabolic signaling ; molecular pathways ; plasma metabolites ; diagnostic biomarkers ; urine ; urine liquid biopsy ; DNA ; sncRNA ; bladder cancer ; metabolic pathways ; metabolism ; metabolomics ; epigenetics ; miRNAs ; epigenetic biomarkers ; DNA methylation ; micro-RNAs ; human papillomavirus ; oropharyngeal squamous cell carcinoma ; treatment de-escalation ; E7 oncoprotein ; HPV DNA ; HPV antibodies ; ELISA ; cancer biomarkers ; diagnosis ; early detection ; n/a ; early diagnosis ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: This reprint includes 15 articles in the field of non-communicable Diseases, big data, and artificial intelligence, overviewing the most recent advances in the field of AI and their application potential in 3P medicine.
    Keywords: artificial intelligence ; computer-aided diagnosis ; facial phenotypes ; machine learning ; complexity theory ; dementia ; cognitive dysfunction ; neuropsychological tests ; mental status and dementia tests ; spontaneous intracerebral hemorrhage (SICH) ; 90-day function outcome ; mortality ; osteoarthritis ; venous thrombosis ; VTE risk prediction ; machine learning algorithm ; population-based cohort study ; pituitary adenoma ; craniopharyngioma ; optic chiasm ; multicenter ; treatment outcome ; liver neoplasms ; deep learning ; diabetic complication ; gene-gene interaction ; AGER ; IL6R ; multiple sclerosis ; DNA methylation ; entropy ; atherosclerosis ; plaque characterization ; physical activity ; osteoporosis ; osteoporotic fracture ; vertebral fracture ; hip fracture ; distal radius fracture ; small for gestational age ; exposure to radiation ; prediction ; coronary plaque ; major adverse cardiovascular events ; coronary artery disease ; coronary computed tomographic angiography ; acute pancreatitis ; predictor ; interventions ; type 2 diabetes mellitus (T2DM) ; prediction model ; Chinese elderly ; prediabetes ; incident diabetes ; predictive models ; bic Book Industry Communication::M Medicine
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  • 148
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The present reprint contains all of the articles accepted and published in the Special Issue " Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education" from the MDPI journal Mathematics. This Special Issue aims to develop more efficient and effective approaches to healthcare and education, leveraging the increasing availability of big data and advancements in artificial intelligence. By sharing new methods, applications, and case studies, this reprint is dedicated to the development of innovative solutions that improve healthcare and education for all. The topics addressed in this Special Issue cover a wide range of areas, including data mining, machine learning, learning analytics, prediction methods, pattern recognition, decision analysis, probabilistic reasoning, fuzzy systems, student or patient modelling, adaptive systems, collaborative systems, recommendation systems, experimental design, and empirical study cases. We hope that this reprint will enable the scientific community in both medicine and education to leverage the techniques from statistics and artificial intelligence to drive significant advances in their respective fields. These approaches hold promise for improving patient outcomes and enhancing the quality of education for students around the world.
    Keywords: Alzheimer’s disease ; dementia ; functional data analysis ; functional depth ; statistical data depth ; symmetry ; elemental information matrix ; gamma distribution ; poisson distribution ; D-optimization ; misspecification ; machine learning ; modeling ; programming ; text analysis ; remote rehabilitation ; recommender system ; stroke ; fuzzy logic ; telemedicine ; collaborative learning ; collaborative work ; genetic algorithms ; group formation ; personality traits ; computer-supported cooperative learning ; non-parametric statistics ; predictive methods ; supervised classification ; random methods ; after-school exercise ; academic performance ; structural relationship ; quantile regression ; instrumental variable quantile regression ; vitamin D ; decision making ; anthropometric parameters ; optimal experimental design ; bioimpedance ; impedance spectroscopy ; algorithm ; competency-based model ; didactic planning ; ontology ; natural language processing ; Bloom’s taxonomy ; retina ; fundus image ; retinal vasculature ; retinal disorders ; semantic segmentation ; learning behavior ; student performance prediction ; deep neural network (DNN) ; recurrent neural network (RNN) ; educational data mining (EDM) ; probabilistic graphical models ; bayesian networks ; value-based potentials ; approximate inference ; medical applications ; electrocardiogram signal ; discriminative convolutional sparse coding ; dictionary filter learning ; linear SVM ; student dropout ; Feature Selection ; Artificial Neural Networks ; Support Vector Machines ; decision trees ; logistic regression ; ECG ; mental fatigue ; signal analysis ; classification ; OpenMarkov ; Bayesian Networks ; d-separation ; inference ; Learning Bayesian Networks ; continuous assessment ; Bayesian networks ; artificial neural networks ; influenza-like illness ; COVID-19 ; Arabic sentiment analysis ; disease classification ; Facebook ; Algerian dialect ; mobile computing ; dual tasking ; cognitive decline ; human motion tracking ; gait analysis ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science
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  • 149
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Transportation, logistics, and supply chain systems and networks constitute one of the pillars of modern economies and societies. From sustainable traffic management in smart cities or air transportation to green and socially responsible logistics practices, many enterprises and governments around the world have to make decisions that affect the efficiency of these complex systems. Typically, optimization algorithms are employed to deal with these challenges, and simulation approaches are utilized when considering scenarios under uncertainty. However, better results might be achieved by hybridizing both optimization algorithms with simulation techniques to deal with real-life transportation, logistics, and SCM challenges, which often are large-scale and NP-hard problems under uncertainty conditions. Hence, simheuristic algorithms (combining metaheuristics with simulation) as well as other simulation optimization approaches constitute an effective way to support decision makers in such complex scenarios. This reprint presents a collection of selected articles on simulation optimization in transportation, logistics, and supply chain management. The reprint is strongly connected to the topics covered in the Winter Simulation Conference (WSC) track on logistics, transportation, and SCM, which includes a stream in simheuristic algorithms as well.
    Keywords: omnichannel retail stores ; vehicle routing problem ; pick-up and delivery ; biased-randomized heuristics ; simheuristics ; scheduling ; uncertainty ; discrete event simulation ; hybrid flow shop ; scrap ; local search ; tabu search ; machine qualifications ; clustering ; shortest processing time ; maritime transportation ; liner network design ; synchronization ; weather uncertainty ; optimization simulation ; discrete-event simulation ; simulation-based optimization ; assignment problem ; neighborhood search ; warehouse ; nonlinear-flight-mechanics ; neural networks ; guidance, navigation, and control ; machine learning ; model ; matlab-simulink ; stochastic project scheduling ; genetic algorithm ; composite priority rules ; agent-based simulation ; horizontal cooperation ; e-groceries ; optimization ; simulation ; logistics ; distribution networks ; container terminal ; meta-heuristic ; horizontal transportation ; hyper-parameter optimization ; hybrid modeling ; system dynamics ; facility location Problems ; Monte Carlo simulation ; automated parcel lockers ; last-mile delivery ; location routing problem ; heuristics ; fuzzy logic ; dockless bike-sharing system ; Markovian queueing network ; relocation ; unequal demand ; bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies::KNT Media, information & communication industries::KNTX Information technology industries ; bic Book Industry Communication::U Computing & information technology::UY Computer science
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  • 150
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-23
    Description: There has been an increased interest in renewable energy sources in the last few decades. Modern power systems rely mainly on power electronic-based generation and loads, leading to the adoption of smart grids that leverage digital communication infrastructure. Smart grids have several advantages, including the potential to provide consumers with a continuous power supply, reduced line losses, enhanced renewable output and storage, consumer participation in electricity markets, and demand-side responsiveness. Future power systems, also known as smart grids, will rely more on renewable energy sources, such as solar and wind, as well as storage. Power electronic converters are used in renewable energy generation and storage. Each converter/inverter manufacturer has an algorithm for programming and optimizing hardware. Furthermore, these converters rely on communication protocols to respond to any signal from the system operator. As a result, cyber-attacks on these smart converters/inverters are a concern. Although numerous cyber–physical systems (CPS) have been presented, no universal CPS standard can be employed with various types of converters. This reprint is a collection of specialized work addressing cybersecurity challenges.
    Keywords: augmented reality ; cybersecurity ; smart city ; systematic literature review ; cyber security for smart cities ; communication wireless network ; man-in-the-middle (MITM) attack ; network intrusion detection system (NIDS) ; malicious URLs ; cyber threat intelligence ; ensemble learning ; internet security ; convolution neural network ; deep learning ; Internet of Things ; intrusion detection ; path planning ; Max-Min Ant Colony Optimization ; differential evolution ; Cauchy mutation ; malware detection ; malware visualization ; transfer learning ; network traffic ; explainable AI ; cyber security ; time series ; fractal analysis ; fractal dimension ; Hurst exponent ; scaling exponent ; cyberattacks ; electricity theft detection ; smart grids ; robustness ; smart meters ; Tomek links ; Levenberg–Marquardt backpropagation ; protection sensor ; Bayesian optimization ; modular multilevel converter ; computer networks ; cyber attack ; signal detection ; machine learning ; smart grid ; transformer neural network ; convolutional neural network ; thema EDItEUR::A The Arts::AT Performing arts::ATF Films, cinema ; thema EDItEUR::A The Arts::AT Performing arts::ATJ Television
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  • 151
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: This topic has been successfully completed. A total of 180 scientific articles were sent, of which 66 have been accepted for publication. These 66 articles are published in reprint.
    Keywords: artificial intelligence ; expert systems ; machine learning ; deep learning ; modeling ; prediction ; probabilistic models ; prediction models ; sustainable mobility ; smart cities ; smart grids ; sustainable energy systems ; renewable energy sources ; nonrenewable energy sources ; electrical storage ; green hydrogen ; sustainable greenhouses ; wind ; microgrids ; tidal ; solar ; biomass ; power network ; solar thermal ; solar photovoltaic ; hydraulics ; ANN ; neural networks, fuzzy logic, genetic algorithms ; hybrid models based on artificial intelligence ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 152
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: With increasing speed, new diagnostic and therapeutic approaches for facial nerve disorders are being published. Many of them have improved decision-making, treatment, and the rehabilitation of patients. Unfortunately, there is often a lack of high-quality studies that prove long-term effects or identify subgroups that are of particular benefit. Even a reliable characterization of patients with facial nerve disabilities is often complicated. Therefore, evidence-based management remains challenging. With this Special Issue on the topic of “Evidence-Based Diagnosis and Management of Facial Nerve Disorders”, we have brought together experts from various fields, including speech pathology, plastic surgery, otolaryngology, neurology, and physical therapy, to present the latest developments in relation to facial nerve disorders and to present a great variety of topics to our readership. We can see that the topic of facial nerve palsy offers a vast and dynamic spectrum of developments, and hope that the research presented in this Special Issue shows the importance of a multidisciplinary approach. We hope it will not only enhance our knowledge of this condition, but also ultimately improve patient outcomes and their quality of life to some extent.
    Keywords: auricular muscles ; facial muscles ; human ; facial palsy ; electrophysiology ; ear wiggling ; vestibular schwannoma ; electrodiagnostic study ; blink reflex ; needle electromyography ; Kabat ; facial nerve palsy ; FNP ; facial nerve paralysis ; salivary gland surgery ; facial nerve disorders ; osteoradionecrosis ; temporal bone ; radiotherapy ; head and neck cancer ; mastoidectomy ; surgery ; post-paralytic facial synkinesis ; emotion recognition ; facial feedback ; longstanding facial palsy ; gracilis transfer ; masseteric nerve ; outcome ; clinical decision support systems ; computerized assessment ; facial palsy detection ; facial paralysis diagnose ; machine learning ; medical diagnosis ; medical screening ; severity grading ; Depressor Anguli Oris ; zygomaticus major ; high-resolution ultrasound ; facial reanimation ; synkinesis ; natural smile ; facial surgery ; facial symmetry ; smile restoration ; central facial paresis ; stroke ; facial nerve schwannomas ; n/a
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  • 153
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations. Employing technological tools for collection, processing, and analysis incorporates understanding the patient’s status and developing the treatment plan. Achieving highly accurate models requires a huge dataset. This issue can be solved by having enough knowledge around medical data processing and their analysis. This reprint shows state-of-the-art research in the field of medical data processing and analysis. The medical data are represented in signals, images, raw data, protein sequences, etc. Processing and analysis of any kind can indicate specific issues in the medical sector such as diagnosis, detection, prediction, and segmentation to enhance the visualization of the processed data
    Keywords: atrial fibrillation ; perfect matrix of Lagrange differences ; statistical indicator ; decision support system ; deep learning ; heart failure ; mortality ; risk prediction ; time-varying covariates ; motor imagery ; Isolation Forest ; anomaly detection ; EEG signals classification ; PIMA dataset ; Type-2 diabetes ; Recurrent Neural Networks ; weight optimization ; Hamlet Pattern ; protein sequence classification ; SARS-CoV-2 ; bioinformatics ; machine learning ; ensemble learning ; heart disease ; ECG ; iris-spectrogram ; scalogram ; CNN ; ResNet101 ; ShuffleNet ; heart rhythm ; H. pylori ; atrophic gastritis ; convolution neural network ; feature fusion ; Canonical Correlation Analysis ; ReliefF ; generalized additive model ; diabetes mellitus ; blood glucose prediction ; forecasting ; long short-term memory ; nature-inspired feature selection ; leukemia ; white blood cell ; classification ; medical imaging ; breast cancer ; histopathological image ; review ; COVID-19 pandemic ; hybrid models ; public health ; accuracy and efficiency ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
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  • 154
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint presents a comprehensive exploration of cutting-edge research in various domains, ranging from blockchain integration in agriculture to innovative tools for employees’ performance measurement. The topics cover machine learning applications, healthcare information systems and the adoption of digital business solutions. An emphasis is placed on emerging technologies, like IoT, VR and AR, offering insights into the future of information systems and technologies. The interdisciplinary nature of the papers reflects a wide spectrum of applications, including smart home systems, energy microgrids and novel approaches to classification using online reviews.
    Keywords: blockchain ; IoT ; machine learning ; healthcare systems ; bioinformatics ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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  • 155
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: Given the current growth in global challenges, the need for smart agriculture practices and effective strategies is emerging as an imminent issue at a planetary scale. Agriculture 4.0 involves a large variety of mobile apps, web applications, Internet of Things (IoT) devices and platforms, drones, robots, and smart machinery for precision agriculture. The expansion of cloud technologies, artificial intelligence (AI), machine learning (ML), deep learning (DL), and big data collection are setting the stage for Agriculture 5.0. Agriculture science and natural sciences are further promoting this trend with the development of leading-edge scientific models and platforms, including stochastic, process-based, and data-driven machine learning modeling. This Special Issue covers the most recent and up-to-date progress in all aspects of internet and computer software applications in agriculture, focusing on the development of web applications and mobile apps, smart IoT devices and platforms, AI, ML and DL solutions in precision agriculture for detection, recognition, classification, monitoring, cultivation, harvesting, and marketing; development of cloud technologies for smart agriculture; computer and machine vision methods and applications for drones and smart machinery, and sensors for field operations; diagnostics and data collection; big data science; scientific process-based and stochastic modeling; and machine learning modeling for agriculture, agroecosystems and natural ecosystems. The research in this Special Issue will contribute to the promotion of modern agriculture practices in the current climate and in the future.
    Keywords: grape varieties identification ; Support Vector Machine (SVM) ; Convolutional Neural Network (CNN) ; deep feature fusion ; Canonical Correlation Analysis (CCA) ; smart machinery ; digital agriculture ; Chinese agricultural diseases and pests ; named entity recognition ; adversarial training ; semantic enhancement ; technology innovation ; food processing ; transition pathways ; sustainable food systems ; transformation ; smart farming ; IoT ; WSN ; containerization ; multi-agent ; neural network ; LSTM ; leisure agricultural park ; traveler group ; COVID-19 pandemic ; fuzzy collaborative intelligence ; machine vision ; maize seeds ; classification ; deep learning ; convolutional neural network ; decision support systems ; agricultural water management ; water security ; data-driven modeling ; conceptual resilience model ; input uncertainty ; climate extreme ; process-based modeling ; vehicle routing problem ; fresh agricultural products ; split delivery ; NSGA-II algorithm ; farm management information system ; farmers’ information needs assessment ; soft system methodology ; smallholder farmers ; conceptual model ; Indonesian chili farmers ; residual block ; attention mechanism ; grape leaf disease ; aquatic products price forecast ; VMD ; IBES ; hybrid model ; precision agriculture ; sensor network ; semi-literate farmers ; interactive interface ; User Interface (UI) ; Android apps ; machine learning ; regression algorithms ; web application ; early prediction of crop yield ; grape detection ; self-attention ; buffalo breeds ; Neural Networks ; Self Activated CNN ; DeepLabv3+ ; semantic segmentation ; picking point identification ; e-commerce interest linkage ; participation willingness and behaviors ; government policies ; farmers’ cognition ; evolutionary game model ; structural equation model ; object detection ; YOLOv7 ; hemp duck count ; smart agriculture ; LoRaWAN ; water status ; supply chain ; horticulture ; logistics ; operations ; planning framework ; decision support ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PH Physics
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  • 156
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Computer Vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive remote sensing data, are still challenging. This reprint collected novel developments in the field of deep learning and computer vision methods for remote sensing. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems, have been published. With practical examples and real-world case studies, this reprint provides a valuable resource for researchers, professionals, and students seeking to harness the power of deep learning in the field of remote sensing. Here are some major topics that are addressed in this reprint: Satellite image processing and analysis based on deep learning; Deep learning for object detection, image classification, and semantic and instance segmentation; Deep learning for remote sensing scene understanding and classification; Transfer learning, deep reinforcement learning for remote sensing; Supervised and unsupervised representation learning for remote sensing environments.
    Keywords: pose estimation ; landmark regression ; space target ; 1D landmark representation ; deep learning ; convolutional neural network (CNN) ; deep supervision ; lightweight model ; remote sensing ; semantic segmentation ; convolutional neural networks (CNNs) ; remote sensing images ; object detection ; knowledge inference module ; convolutional neural networks ; tree ensemble methods ; multi-label classification ; complex-valued U-Net ; complex-valued capsule network ; polarimetric synthetic aperture radar ; unmanned aerial vehicle (UAV) ; grassland grazing livestock ; remote sensing image ; artificial intelligence ; building extraction ; multi-scale object detection ; multi-feature fusion and attention network ; multi-branch convolution ; attention mechanism ; loss function ; remote-sensing image ; neural architecture search ; sparse regularization ; HRNet ; Earth observation ; land use and land cover classification ; transfer learning ; dynamic resolution adaptation ; small-object detection ; machine learning ; data augmentation ; automatic target recognition ; synthetic aperture radar ; spacecraft recognition ; few-shot feature adaptation ; generative family ; neural processes ; remote sensing imagery ; transformer ; Landsat ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 157
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-01-05
    Description: This Special Issue welcomes research papers on new approaches that have been applied or are under development to improve preparedness and emergency response. We especially encourage the submission of inter-disciplinary and crosscutting research. We also encourage the submission of manuscripts that focus on various types of disasters, disaster and emergency research, and on policy or management solutions at multiple scales.
    Keywords: alcohol ; ethanol ; pedestrians ; traffic accidents ; flood ; disasters ; emergency preparedness ; hospital preparedness ; Saudi Arabia ; first aid ; education ; basic life support ; cardiopulmonary resuscitation ; feedback device ; simulation ; quality ; skill retention ; motivation ; chest recoil ; mannequin ; contact tracing ; ethics ; pandemic ; psychology ; public education ; public health ; alternative care facilities ; flexible surge capacity ; major incidents and disasters ; surge capacity ; information and communication technology ; smart disaster management system ; Internet of Things ; disaster ; flood early warning ; flood response ; community volunteerism ; disaster volunteer group ; resilience ; governance and planning ; disaster management ; sustainability ; security ; safety ; crisis management ; risk management ; emergencies ; health emergency ; management ; disaster legislation ; preparedness ; COVID-19 ; stress ; stressors ; cortisol ; medical simulation ; low-fidelity simulation ; high-fidelity simulation ; stress appraisal questionnaire ; KOS-B ; nursing ; machine learning ; health geomatics ; geographic information system ; emergency medical services ; spatial filtering ; geo-AI ; resources management ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBN Public health & preventive medicine
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  • 158
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-08-08
    Description: This Special Issue (SI), entitled “Application of (Big) Data Analysis in A/E/C (architecture, engineering, and construction)”, in Buildings has published quality papers outlining novel contributions of the application of big data theory, modeling techniques, and methodologies as a tool for leveraging data analytics in the building industry. Contributions have covered related topics from various application domains of the global A/E/C industry, including structures/structural engineering, materials/geotechnical engineering, construction design/measure, IS/BIM, transport/energy planning and building management, etc. As can be seen in the editorial essay, some domains have been addressed with more emphasis, but some are not. In addition to the editorial essay, the published research works have also touched almost all phases of (big) data analytics, including data collection and curation, data pre-processing, data analysis, prediction, (data-driven) decision making and decision supports, etc., except that related topics about forecasting are still missing. This allows for identifying ‘hot zones’ of research, in which follow-up research and extended studies should be performed, and ‘cold zones’, awaiting the utilization and novel application of data and theories/models.
    Keywords: high performance concrete (HPC) ; experimental parameters ; data-driven analysis ; pre-project material testing ; pairwise comparison analysis ; correlation analysis ; cosine similarity ; predictive regression modelling ; heat map ; variable transform ; energy generation ; green energy ; wind turbines ; fan-blade damage ; mechanical condition monitoring system ; fault diagnosis ; maintenance by prediction ; accelerometer ; vibration data ; big-data analytics ; reliability analysis ; RC slab-column structure ; machine learning ; Monte Carlo simulation ; shapley additive explanation ; wireless sensor network ; historic building ; real-time monitoring ; recycling of waste materials ; water-to-binder ratio (W/B ratio) ; waste PE ; cement mortar ; durability ; steel assembly bracing ; foundation pit ; environmental temperature ; vibration analysis ; building information model ; 3D point cloud ; semantic segmentation ; deep learning ; highway data quality assessment ; data quality dimensions ; semiotic framework ; decision-making ; construction image ; artificial intelligence ; object detection ; single shot multibox detector (SSD) ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 159
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: The field of Artificial Intelligence (AI) has undergone enormous expansion since its inception in the mid-20th century, as demonstrated by its application across an array of engineering and scientific challenges. Particularly in the last decade, AI has witnessed a significant breakthrough with the advent of deep learning, which has facilitated the employment of various AI models across a multitude of domains. This reprint features ten papers accepted for publication in the Special Issue titled "Advanced Artificial Intelligence Models and Their Applications," published in the MDPI Mathematics journal. These papers explore numerous facets of advanced artificial intelligence models and their applications, covering areas such as cybersecurity, image classification, logistics optimization, automatic music generation, human capital investment, writer recognition, remote sensing image indexing, target tracking, and more. These diverse subjects highlight the extensive scope and capability of AI models in tackling intricate challenges across distinct fields, underlining the vast potential inherent in this cutting-edge technology.
    Keywords: target features ; siamese trackers ; lightweight network ; target tracking ; chaotic system ; fruit fly optimization algorithm ; quantum-inspired computation ; parameter estimation ; neural network ; binary hash code ; image retrieval ; remote sensing ; writer recognition ; self-supervised learning ; embeddings ; dimension reduction ; clustering ; twin network ; Big Five personality test ; artificial intelligence ; human resources ; employee selection ; teamwork ; machine learning ; automatic music generation ; generative pre-training ; embedding ; representation learning ; logistics management ; artificial immune systems ; vehicle routing problem ; cross-docking ; automotive ; condition monitoring ; predictive maintenance ; deep learning ; class-imbalance learning ; feature clustering ; long-tailed classification ; classwise splitting ; SQL injection attacks ; recurrent neural network (RNN) autoencoder ; ANN ; CNN ; decision tree ; naive Bayes ; SVM ; random forest ; logistic regression ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science
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  • 160
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
    Keywords: distribution patterns ; fibroblast cells ; HCT-8 colon-cancer cells ; nature-inspired techniques ; quantification ; segmentation ; myocardial infarction ; vectorcardiogram ; multivariate VMD ; deep CNN ; accuracy ; deep learning ; image segmentation ; brain tumors ; radiosurgery ; magnetic resonance imaging ; age-related macular degeneration ; choroidal neovascularization ; convolutional neural networks ; image classification ; optical coherence tomography angiography ; brain metastasis ; glioblastoma ; machine learning ; oxygenation ; tumor infiltration ; breast cancer detection ; microwave breast imaging ; computer-aided diagnosis (CAD) ; first-in-human (FiH) study ; semantic segmentation ; triceps surae muscle ; medical image segmentation ; breast cancer ; pattern recognition ; clinical feasibility ; computer-assisted segmentation ; artificial intelligence ; orthopedics ; neural network ; mandible ; craniomaxillofacial bone ; multi-center ; histopathology ; lung cancer ; supervised segmentation ; unsupervised segmentation ; stroke ; fine tactile sensation ; electroencephalography ; evaluation ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
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  • 161
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: This reprint addresses the unique opportunities and challenges associated with human–computer interaction with intelligent systems. First, state-of-the-art reviews are presented about speech emotions, automatic spelling correction, and art usage in virtual reality. We encouraged authors to submit reports describing systems built for different languages and multilingual systems. The linguistic, emotional, prosodic, and dialogue aspects of speech communication are investigated. Special attention is given to sentiment and emotional analysis from text and speech. Speech audiometry, offline speech recognition, and text-independent speaker verification systems are elaborated. The rapidly growing domain of virtual reality applications is of interest both as an application domain in which new interfaces and interaction methods are needed and as a potential testbed for evaluating speech and other interface modalities.
    Keywords: pediatric speech audiometry ; hearing tests ; conditioned play audiometry ; human–computer interaction ; mechatronic devices ; Internet of Things ; cyber-physical systems ; system control ; augmented reality ; mixed reality ; Azure cloud ; sentiment analysis ; opinion classification ; lexicon-based approach ; hybrid approach ; lexicon generation ; lexicon labelling ; particle swarm optimization ; spelling correction ; natural language processing ; diacritization ; error model ; context model ; Natural Language Processing ; deep learning ; grammar error detection ; word embedding ; text-independent speaker verification system ; self-attentive pooling ; multi-layer aggregation ; feature recalibration ; deep length normalization ; speaker embedding ; shortcut connections ; convolutional neural networks ; ResNet ; human–robot interaction ; dictionary approach ; machine learning approach ; social robotics ; human-robot interaction ; mental workload ; heart rate variability ; machine learning ; sentiment level evaluation ; handicraft product ; 3D handicraft products ; smartphone applications ; user interaction ; user’s attracting attention ; question-answering forum ; healthcare informatics ; recommendation system ; user study ; speech emotion recognition ; attention mechanism ; recurrent neural network ; long short-term memory ; user experience ; usability evaluation methods ; domain usability ; domain-specific languages ; graphical user interfaces ; virtual reality ; art therapy ; rehabilitation ; neurorehabilitation ; neuroplasticity ; brain injury ; ASR ; speech-to-text ; edge AI ; Wav2Vec ; transformers ; PyTorch ; emotion recognition ; dimensional to categorical emotion representation mapping ; activation ; arousal and valence regression ; X-vectors ; SVM ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 162
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The reprint focuses on environmental monitoring as a key issue in the sustainable management of land resources, where the increasing availability of temporal and spatial soil data plays a fundamental role. Remote sensing and GIS (Geographic Information System) applications allow the efficient handling of these data with the aim of developing predictive and robust models to reduce land degradation and soil erosion.
    Keywords: sediment monitoring ; remote sensing ; lakes ; water capacity ; sonar ; aquatic drone ; USLE ; MMF ; soil quality ; soil properties ; indices ; Andean region ; landslide ; logistic regression ; environmental hazard ; risk assessment ; soil mapping ; interpolation methods ; different depths ; regional scale ; analytical hierarchical process ; land degradation vulnerability ; NDVI ; land surface temperature ; debris flow ; fine sediments ; cohesion ; Beichuan ; RUSLE ; GIS ; climate change ; soil erosion ; erosion risk assessment ; drought ; ecosystem services ; land use ; soil moisture dynamics ; water stress ; soil salinization ; saline soil treatment ; remote sensing monitoring ; model construction ; DVI ; machine learning ; random forest ; spatial mapping ; soil salinity ; salinity indices ; vegetation indices ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 163
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of generating adversarial samples through byte sequence feature extraction using deep learning; a state-of-the-art comparative evaluation of deep learning approaches for mobile botnet detection; a novel visualization-based approach that utilizes images for Android botnet detection; a study on the detection of drive-by exploits in images using deep learning; etc. Furthermore, this reprint presents state-of-the-art reviews about machine learning-based detection techniques that will increase researchers' knowledge in the field and enable them to identify future research and development directions.
    Keywords: malware analysis and detection ; applied machine learning ; mobile security ; neural network ; ensemble classification ; botnet detection ; deep learning ; Android botnets ; convolutional neural networks ; dense neural networks ; recurrent neural networks ; long short-term memory ; gated recurrent unit ; CNN-LSTM ; CNN-GRU ; Android security ; malware detection ; code vulnerability ; machine learning ; malware ; static analysis ; dynamic analysis ; hybrid analysis ; security ; Monte-Carlo simulation ; reinforcement learning ; adversarial sample ; convolutional neural network ; Histogram of Oriented Gradients ; image processing ; android botnets ; digital forensic ; optimization ; multilayer perceptron ; salp swarm algorithm ; connection weights ; business email compromise (BEC) ; email phishing ; phishing detection ; machine learning (ML) ; systematic literature review ; steganography ; steganalysis ; polyglots ; neural networks ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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  • 164
    Publication Date: 2024-03-28
    Description: This Special Issue of Biomolecules, “Physics of Protein Folding, Misfolding, and Intrinsic Disorder: A Themed Issue in Honour of Professor Vladimir Uversky on the Occasion of His 60th Birthday”, is a dedication to one of the discoverers of IDPs. This collection is a small token of the respect, admiration, and affection the contributors have for Prof. Vladimir (Volodya) Uversky. It is also a celebration of his illustrious career, and his accomplishments, and contributions to the IDP field that have inspired so many minds worldwide. This Special Issue presents the state of the art as it emerges from the contribution of the community of IDP researchers (IDPers), who have responded to the invitation to give credit to the pioneering work of Prof. Vladimir Uversky aimed at defining the class of disordered proteins and at promoting the attention of scientists toward the existence of “non-globular proteins”. The papers in this collection show the advancement of our knowledge through the application of an integrative structural approach and witnesses at the same time the interest of the IDPer community toward new concepts (i.e., liquid-liquid phase separation) and new methodological frontiers (i.e., the application of machine learning and artificial intelligence to disorder prediction and modelling).
    Keywords: charge clustering ; polyelectrolytes ; average shape of conformational ensembles ; charged-residue patterning ; hydrodynamic radius ; solvent-accessible surface area ; proline content ; conformational compactness ; ellipsoid model ; intrinsically disordered proteins (IDPs) ; intrinsically disordered protein regions (IDRs) ; LC–MS/MS ; IUPred analysis ; Ostrinia nubilalis ; cold hardiness ; intrinsic disorder ; intrinsically disordered proteins ; intrinsic disordered regions ; disorder scale ; disorder propensity ; amino acids ; amino acid bias ; predictive performance ; disorder prediction ; SARS-CoV-2 ; COVID-19 ; IDP ; RNA ; NMR ; pH ; liquid-liquid phase separation ; protein solubility ; protein disorder ; mutations ; bioinformatics ; kinetics ; fluorescence ; site-directed mutagenesis ; protein–protein interactions ; SH2 domains ; Crkl ; Paxillin ; Calvin-Benson-Bassham cycle ; conditionally disordered protein ; history of modern science ; metabolism regulation ; moonlighting protein ; protein-protein interaction ; biomolecular condensates ; machine learning ; predictor ; physical interactions ; phase separation ; liquid–liquid phase separation ; biomineralization ; calcium carbonate ; otoliths ; nucleation pathways ; nickel ; intrinsically disordered regions ; lung cancer ; nmr ; isothermal titration calorimetry ; circular dichroism ; light scattering ; Dss1 ; intrinsically disordered protein ; IDPs ; molecular dynamics ; sequence composition ; SAXS ; membrane-less organelles ; stress ; long foldable segments ; pyHCA ; soluble domains ; protein sequence ; conditional order ; hidden order ; dark proteomes ; intrinsically disordered domains ; coexistence line ; tumor suppressor p53 ; intramolecular interaction ; salt-dependent binding affinity ; counterion condensation theory ; DNA binding ; fluorescence anisotropy ; van’t Hoff ; protein purification ; affinity chromatography ; Tau ; androgen receptor (AF1) ; isoform ; large-scale analysis ; protein structure ; AlphaFold ; canonical protein ; alpha-synuclein ; membrane ; synaptic vesicle ; synapsin ; Parkinson’s ; Myc ; drug targets ; SLiM ; small-molecule inhibitors ; glutamate receptor ; discrete molecular dynamics ; single molecule fluorescence ; integrative structural biology ; unfolded ; unstructured ; flexible ; protein function ; polymer physics ; percolation ; entanglement ; topology ; polymer rheology ; D/E repeats ; K/R repeats ; molecular dynamics simulations ; hub proteins ; multivalency ; transcription factor ; linker length ; heterogeneity ; dimers ; duplexes ; coarse-grained simulation ; molecular mass ; LLPS stability ; FUS ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-02-20
    Description: This book presents the latest advances in applications of continuous, objective, and automated sensing technologies and computer tools for sustainable and efficient poultry production, and it offers solutions to the poultry industry to address challenges in terms of poultry management, the environment, nutrition, automation and robotics, health, welfare assessment, behavior monitoring, waste management, etc. The reader will find original research papers that address, on a global scale, the sustainability and efficiency of the poultry industry and explore the above-mentioned areas through applications of PPF solutions in poultry meat and egg production
    Keywords: broiler ; activity index ; time interval ; age ; image processing ; poultry ; cage-free ; preening behavior ; mask R-CNN ; residual network ; broiler chicken ; machine vision ; image restoring ; precision poultry farming ; feeding system ; pecking force ; precision livestock farming ; poultry farming ; information management ; cloud database ; disease detection ; acoustic ; audio ; frequency ; behavior ; image analysis ; animal welfare ; movement analysis ; LED ; comfort index ; manure area ; manure coverage proportion ; environment control ; ammonia emission ; layer house ; laying hen ; daily behavior ; machine learning ; inertia sensor ; walking ability ; animal behavior ; precision livestock ; PLF ; precise feeding ; ideal protein ; animal health ; immune system ; productive parameters ; management ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFF Social issues & processes::JFFZ Animals & society
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Young readers will find the Reprint useful for learning about the systematic study and review of the many themes in the area of microfluidic-based biosensing. Empirical research and comprehensive reviews regarding the use of microfluidic technology in biosensing and point-of-care system development are included in this Reprint.
    Keywords: biosensors ; electrochemical detection ; water quality monitoring ; bio-recognition element ; in-situ monitoring ; surface modification ; La(OH)3@MWCNT ; electrochemical sensor ; uric acid ; DAMP molecule ; cell damage ; stress ; electrochemical device ; hyaluronic acid methacrylate hydrogel ; metal ion–amide complexation ; electrochemical accumulation ; lead removal ; modified electrode ; impedimetric biosensor ; folate ; food pathogen ; microfluidic ; biosensing ; fluorescence microscopy ; PoC device ; nucleic acid concentration ; biosensor ; machine learning ; regression model ; impedance cytometry ; microfluidic chip ; cancer marker ; PSA ; CEA ; sandwich assay ; human serum ; metasurface ; fluorescence detection ; robustness ; Raman spectroscopy ; renal amyloidosis ; human kidney tissue ; amyloid subtyping ; stem cell differentiation ; nano- and micromaterials ; lab-on-a-chip ; cancer detection ; microfluidic chips ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint comprises a collection of 20 articles that were accepted and published in the Special Issue titled " Recent Advances in Swarm Intelligence Algorithms and Their Applications" of the MDPI journal Mathematics. These articles cover a wide range of topics related to swarm intelligence algorithms and their theories. The topics include improvements in algorithm mechanisms, fusion algorithms, multiobjective optimization, and the optimization of large-scale problems, as well as the application of swarm intelligence in various fields such as engineering optimization problems, vehicle swarm motion, viscoelastic Maxwell-type DVA, and deep learning. It is hoped that this reprint will be helpful for scholars engaged in the field of swarm intelligence and also suitable for researchers interested in staying updated with the latest advancements in swarm intelligence algorithms and their applications. Nowadays, swarm intelligence is closely intertwined with various aspects of life. This reprint aims to provide readers with an understanding of these developments and further expand the application boundaries of such algorithms.
    Keywords: preference incorporation ; ant colony optimisation ; grey wolf optimisation ; interval outranking ; multi-criteria decision analysis ; swarm intelligence algorithms ; piecewise linearization ; optimization ; parameter tuning ; approximation ; experimental comparison ; graph convolutional network ; relation extraction ; machine learning ; natural language processing ; metaheuristic algorithms ; Whale Optimization Algorithm ; HBA ; radial distribution systems ; power loss ; sensitivity analysis ; DG optimal allocation ; voltage deviation ; capacitor banks ; electricity market ; optimal bidding ; Harris Hawk Optimization ; multi layered neural network ; bi-level optimization ; strategic bidding ; ground-penetrating radar (GPR) ; cavity morphology recognition ; few-shot learning (FSL) ; deep learning (DL) ; relation network (RelationNet) ; unmanned aerial vehicle swarm ; antenna array ; near-field beamforming ; array element position error compensation ; spatial area division ; economic load dispatch ; pigeon-inspired optimizer ; oppositional-based learning ; swarm intelligence algorithm ; oppositional-based pigeon-inspired optimizer ; tunicate swarm algorithm ; chaotic mapping ; Lévy flight strategy ; benchmark test functions ; engineering design problems ; meta-heuristic ; large-scale agents ; attack and defense ; multi-population mean-field game ; high-dimensional solution space ; neural networks ; bat algorithm ; hybrid strategy ; energy harvesting ; NOMA ; cognitive relay network ; multimodal optimization ; multiple optima ; partition-based random search ; niching ; global optimization problems ; moth-flame optimization ; premature convergence ; population diversity ; grey wolf optimization ; swarm intelligence ; real world application ; spiking neural P system ; AEC system ; LMS ; neuromorphic architecture ; FPGA ; Harris hawks optimization ; elite opposition-based learning ; Sobol sequence ; nonlinear weight ; Gaussian walk learning ; particle swarm optimization algorithm ; dynamic vibration absorber ; Maxwell-type ; inerter ; negative stiffness ; chaotic-based PPE algorithm ; meta-heuristic algorithm ; chaotic maps ; Mahjong ; differential evolution ; deficiency number ; combinatorial optimization ; reinforcement learning ; multi-agent reinforcement learning ; self play ; population play ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: The eradication of vector-borne diseases is threatened by the limited range of available insecticides, leading, inevitably, to the development of resistance. This is particularly concerning for malaria control, which relies heavily on insecticide-treated nets (ITNs) and indoor residual sprays (IRS). New chemistries are being developed, and innovative deployment of insecticides may play a role in overcoming resistance, either through new types of tools or new means of distribution. A variety of novel product types and vector control strategies are under development and evaluation, which is to be celebrated, but a strong evidence base is needed to guide effective operational deployment decisions. Novel approaches should be supported by robust data collected using appropriate and validated methods to monitor efficacy, durability, and any emerging resistance. This reprint presents original research into developing and characterizing new vector control products, as well as understanding and monitoring insecticide resistance. Review articles explore the impact of insecticide resistance and offer guidance on insecticide choice in the face of pyrethroid resistance. Consensus methodologies are presented, in the form of standard operating procedures (SOPs) designed to be adopted and used to generate reproducible data that can be compared and interpreted across and between studies. It is hoped that this collection of articles offers inspiration and guidance on how consistent data can be generated to inform more effective development, evaluation, and use of new and existing vector control tools.
    Keywords: prallethrin ; insecticide ; spatial treatment ; mosquito fitness ; protection ; pyrethroids ; Aedes albopictus ; Culex pipiens ; life tables ; mosquito ; bite-proof garment ; model ; textile ; non-insecticidal ; physical barrier ; insecticide selection ; out-crossing ; strain authentication ; laboratory screening ; pyrethroid ; pyrethroid resistance ; insecticide resistance ; insecticide resistance management ; vector control ; malaria ; malaria control ; Anopheles ; host-seeking behavior ; insecticide exposure ; pathogen transmission ; Aedes aegypti ; Anopheles gambiae ; ATSB ; Culex quinquefasciatus ; Iroquois ; RNAi ; Saccharomyces cerevisiae ; yeast ; Anopheles mosquito ; fertility ; ovary development ; pyriproxyfen (PPF) ; side-effects ; machine learning ; image classification ; automated identification ; convolutional neural network ; insecticide-treated net (ITN) ; PBO ITN ; synergist ITN ; dual-AI ITN ; insecticide resistance management (IRM) ; method validation ; durability monitoring ; bioinsecticide ; disease transmission ; insecticide-resistance ; mosquito-borne disease ; mosquito control ; natural compounds ; phytochemical ; malaria vector ; insecticide treated nets ; cytochrome P450s ; kdr ; cuticular resistance ; deltamethrin ; imidacloprid ; bifenthrin ; β-cyfluthrin ; etofenprox ; α-cypermethrin ; λ-cyhalothrin ; thiacloprid ; mosquitoes ; Attractive Toxic Sugar Bait (ATSB) ; Attractive Targeted Sugar Bait (ATSB) ; diagnostic bioassay ; resistance monitoring ; insecticide-treated nets (ITN) ; strain characterisation ; method development ; product evaluation ; quality control (QC) ; dual active ingredients (dual-AI) ; bioefficacy ; IRS ; application technology ; broflanilide ; clothianidin ; pirimiphos-methyl ; WHO tube ; WHO tunnel test ; ITNs ; interceptor ; interceptor G2 ; membrane ; human arm ; rabbit ; bioassay ; bio-efficacy ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: Drought stress is one of the main factors limiting horticultural crops, especially in environments like the Mediterranean basin, which is often characterized by sub-optimal water availability. The global change will determine the increase in semi-arid conditions, so all horticultural crops will have to cope with the water scarcity. Appropriate plant selection and new cultivation methods, especially methods of deficit irrigation, are crucial in improving the crop cultivation performances.Horticultural plants can have specific adaptive mechanisms to overcome the negative effects of drought stress. Drought-tolerant plants show different adjustment mechanisms to overcome this stress, including morphological, physiological, and biochemical modifications. The plant responses include increasing the root/shoot ratio, growth reduction, leaf anatomy change, reduction of leaf size, and reduction of total leaf area to limit the water loss and guarantee the photosynthesis process. Furthermore, drought stress influences gas exchange and other physiological parameters. Recent acquisitions on the mechanism of signal transduction and the development of drought tolerance in plants are useful to understand the action mechanisms. Dr. Stefania Toscano Dr. Giulia Franzoni Dr. Sara Álvarez Guest Editors
    Keywords: drought stress ; osmotic regulation ; LEA protein ; ROS ; signaling ; drought-responsive gene ; ornamental species ; water deficit ; water stress ; defense mechanisms ; climate change ; stress responsive genes ; stress adaptation ; Vigna unguiculata (L.) Walp ; water deficiency ; physiological parameters ; productivity ; potato ; hyperspectral image ; machine learning ; band importance ; Zinnia elegans L. ; bedding plants ; deficit irrigation ; stomata characteristics ; gas exchange ; proline ; enzyme activity ; Callistemon citrinus (Curtis) Skeels ; Viburnum tinus L. ‘Lucidum’ ; plant biomass ; root/shoot ratio ; relative water content ; AChE activity ; antioxidant ; LOX activity ; phenolics ; damask rose ; abiotic stresses ; biochemical response ; drought ; legumes ; mungbean ; tomato ; SSRs ; breeding ; gene-associated SSRs ; genetic diversity ; canopy temperature ; chlorophyll fluorescence ; rhizobacteria ; Lilium ; drought tolerance ; leaf morphology and structure ; photosynthetic capacity ; membership function ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: The recognition of global climate change as an environmental issue has drawn attention to the climatic impact of human activities. Scientists and environmentalists have pointed out that human-induced climate change results from disturbances in all aspects of the environment. Among them, aquatic environments (including water, sediments, aquatic organisms, etc.,) are closely related to all kinds of human interference. However, they are under increasing stress due to climate change and human disturbances, such as an increased input of pollutants, a loss of biodiversity and a decrease in ecological functions. Fortunately, realizing the urgency and importance of the matter, researchers have started to work on coping strategies, including effective water treatment and energy recovery. This Special Issue focuses on revealing the effects of climate change and anthropogenic disturbances on water ecological environments, analyzing physical, chemical and biological aspects.
    Keywords: biofilm resilience ; water-soluble organic matter ; microbial community ; co-occurrence network ; phytoplankton ; environmental factors ; connections ; eutrophic lakes ; alpine lakes ; water resources security ; DPSIR ; confidence threshold method ; spatial autocorrelation ; Moran’s I ; air pollution transmission channels ; ambient air quality standards ; WHO Global Air Quality Guidelines ; Microcystis aeruginosa ; Chlorella pyrenoidosa ; ultraviolet B radiation ; photosynthetic efficiency ; adaptation capability ; nutrient enrichment ; adsorption ; degradation ; B2O3 ; TiO2/C3N4 ; molten ; heavy metal ; sediment ; ecological risk ; fish species ; photocatalysis ; N-doped films ; visible light ; titanium dioxide ; water quality index (WQI) ; machine learning ; parameter selection ; positive matrix factorization (PMF) ; source apportionment ; enrofloxacin ; Eriocheir sinensis ; transcriptome ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Keywords: tree species ; forest ; biodiversity ; time series ; spatial autocorrelation ; cross-validation ; accuracy ; tree species classification ; Sentinel-2 ; multi-temporal ; Wienerwald biosphere reserve ; semideciduous forest ; hyperspectral multitemporal information ; UAV ; classification ; segmentation ; single trees ; forest structure analysis ; dead wood ; illumination correction ; GEE ; forest species ; Mount Taishan ; species diversity ; spectral diversity ; convex hull volume ; AVIRIS-NG ; tropical forests ; ISRO–NASA campaign ; climatic gradient ; woody vegetation ; probability random forest ; forest inventory ; Serbia ; object-based ; mapping ; WorldView-3 ; LiDAR ; machine learning ; CNN ; RGB ; boreal forest ; forest cover and species ; Siberia ; Landsat ; spatial divergence ; forest stands classification ; curve matching ; data fusion ; multisource remote sensing data ; tree species mapping ; ALS ; forestry ; high-resolution remote sensing imagery ; individual tree species recognition ; individual tree crown delineation ; convolutional neural network ; deep learning ; convolutional networks ; biosecurity ; forest pathology ; myrtle rust ; urban forestry ; aerial imagery ; trees species identification ; phenological metrics ; scale effect ; up-scaling ; endangered tree species ; selective logging ; imbalanced data ; pixel-based classification ; machine learning algorithm ; multi-layer perception ; savanna ; species distribution model ; Sentinel-1 ; multitemporal ; random forest ; BPWW ; feature extraction ; optical data ; SAR ; radiative transfer model ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: Though the number of infants born with heart disease each year is relatively small (approximately 1% of the population), it is still a substantial issue worthy of investigation, which is why this Special Issue focuses on congenital heart disease in both children and adults. Advances in the treatment of such malformations have led to increased life spans for this population. Consequently, today, most patients treated for congenital heart disease are adults. The purpose of this Special Issue is to deal with the latest developments in the care of the fetus, infants and children, and how these patients should be treated, as well as to describe the results of follow-ups and the potential special needs of adults with congenital heart disease.
    Keywords: congenital heart disease ; STE echocardiography ; atria ; pediatric cardiac surgery ; CT angiography ; Fallot tetralogy ; coronary arteries ; aortic arch anomalies ; brain abnormalities ; Doppler velocimetry ; artificial intelligence ; pediatric cardiology ; machine learning ; congenital heart diseases ; ventricular septal defect ; child development ; psychological adjustment ; quality of life ; stress ; adolescence ; longitudinal study ; mental health ; cortisol ; coronary vessels anomalies ; anomalous origin of the left circumflex coronary artery from the pulmonary artery ; ALXCAPA ; coronary CT angiography ; patent ductus arteriosus ; pulmonary hypertension ; transcatheter closure ; risk factor ; prognosis ; Fontan procedure ; single ventricle ; miscarriage ; pregnancy ; prematurity ; Fontan circulation ; Fontan-associated liver disease ; cholestasis ; bile acids ; hemostasis ; thromboprophylaxis ; acquired von Willebrand syndrome ; echocardiography ; borderline right ventricles ; scores ; pediatrics ; adult congenital heart disease (ACHD) ; transcatheter valve repair ; atrioventricular (AV) regurgitation ; hybrid ; transcatheter edge-to-edge repair (TEER) ; Cardioband ; valve-in-valve (ViV) ; bic Book Industry Communication::M Medicine ; bic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue will highlight the latest advances in numerical modeling of combustion-related applications. With the recent advancements in computational capacities and the widespread use of simulations in engineering problems, numerical methods are becoming increasingly important to improve existing models and develop new models that can help researchers to better understand the underlying mechanisms of combustion, their interaction with other physical phenomena, such as turbulence, and their impacts on the performance of related applications at both fundamental and practical levels.
    Keywords: gas fire suppression ; inert gas agents ; agent quantity ; discharge rate ; ventilation rate ; premixed combustion ; obstructed channels ; flame acceleration ; thermal expansion ; computational simulations ; machine learning ; soot concentration ; soot emissions ; artificial neural network ; estimator ; computational fluid dynamics ; combustion ; biogas ; hydrogen ; laminar flame speed ; correlation ; jet-and-recirculation stabilized combustion ; OH* measurements ; numerical CFD analysis ; RANS modeling ; detailed chemistry schemes ; heat-loss modeling ; low-calorific combustion ; syngas fuel ; micro-combustion ; syngas ; repetitive extinction and ignition (FREI) ; numerical simulations ; flame instabilities ; flame propagation ; closed spherical bomb ; incipient stage ; methane ; N2O ; flash boiling ; gasoline direct injection ; Spray G ; discrete droplet method ; fuel surrogates ; combustion process ; reactivity model ; synthetic jet fuels ; turbine engines ; two-stroke engine ; multiple injection ; emission ; numerical simulation ; computational fluid dynamic (CFD) ; natural gas ; laminar burning velocity (LBV) ; closed vessel combustion ; numerical study ; microcombustion ; complex geometry ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint focuses on quantitatively assessing the impact of climate change on agricultural production based on multi-source model simulation and reveals the role and mechanism of improved management measures in adapting to climate change. Modeling is a key tool for exploring the impacts of climate change on agriculture and proposing adaptation strategies. The insights derived from this reprint will be helpful for relevant decision makers in the areas of agricultural adaptation and food security.
    Keywords: temperature ; evaluation ; CLDAS ; GLDAS ; ERA5-Land ; adaptation ; climate change ; summer maize ; phenology shift ; GCM ; CNRM-CM6 ; PET ; IPCC-AR6 ; SSP scenarios ; solar induced chlorophyll fluorescence (SIF) ; winter wheat ; yield forecast ; random forest ; enhanced vegetation index (EVI) ; geographic distribution ; suitable habitat ; Rheum nanum ; MaxEnt ; ArcGIS ; range shifts ; climate scenario ; agriculture ; food security ; planting boundary ; crop modelling ; yield ; future climate scenarios ; soybean ; CROPWAT ; reference crop evapotranspiration (ET0) ; crop water requirement (ETc) ; irrigation water requirement (Ir) ; crop yield ; cultivated area ; water use ; wheat–corn ; DNDC ; net greenhouse effect ; anaerobic digestion ; biogas production ; k-nearest neighbours ; support vector machine ; middle and lower reaches of Yangtze River ; rice ; heat stress ; nitrous oxide ; soil gas flux ; silicone diffusion cell ; soil gas diffusivity ; passive gas sampling ; soil gas diffusion coefficient ; soil gas flux simulation ; carbon sequestration ; different scenarios ; land use ; sustainable development ; Xinjiang ; ETo ; yield response factor ; irrigation water requirement ; cotton ; GCMs ; CERES-rice model ; rice yield ; light and heat resource utilization ; potential evapotranspiration (ET0) ; Penman–Monteith ; sensitivity analysis ; contribution rate ; optimal irrigation ; sustainable irrigation ; water use efficiency ; North China Plain ; sugarcane ; SPEI ; waterlogging ; growth stage ; climatic yield ; yield prediction ; machine learning ; APSIM model ; climate indices ; range shift ; apple trees ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-27
    Description: Since the launch of Seasat, TIROS-N, and Nimbus-7 satellites equipped with ocean observation sensors in 1978, a new era of ocean remote sensing has opened. Today, remotely sensed data have been widely used in oceanographic studies. This reprint collects various advanced ocean remote sensing technologies and their applications, including the use of artificial intelligence techniques to explore ocean information and bibliometric analysis to assess researchers and trends in this scientific field. The observations of various sensors enrich the application of ocean environment monitoring and ocean dynamical analysis. If you are interested in understanding the application of ocean remote sensing, this monograph should be very helpful.
    Keywords: bibliometric analysis ; remote sensing ; oil slicks ; oil detection ; coastal waters of Myanmar ; upwelling ; monsoon ; remote equatorial forcing ; coastal upwelling ; Himawari-8 ; sea surface temperature ; Taiwan ; topographic position index ; upwelling index ; mapping ; satellite remote sensing ; quantitative mapping ; spatial analysis ; the East Australian Current ; New South Wales ; shelf circulation ; seagrass ; Zostera marina L. ; reclamation ; spatial and temporal changes ; mesoscale eddies ; the Indonesian Seas ; sea level anomaly ; nonlinearity ; barotropic instability ; baroclinic instability ; SAR ; CNN ; Sentinel-1 ; ship detection ; geostationary ocean color imager (GOCI) ; GDPS ; SeaDAS ; normalized water-leaving radiance ; atmospheric correction ; fish assemblage ; temperature ; environmental change ; Yellow Sea coastal current ; East China Sea ; lidar ; remote sensing sensors ; backward scattering intensity ; ocean Scheimpflug lidar ; volume scattering function ; Arabian Gulf ; Gulf of Oman ; MODIS ; algal blooms ; chlorophyll-a ; SST ; bathymetry ; semidiurnal internal tides ; the Sulu-Sulawesi Seas ; sea surface height ; plane wave fit method ; energy flux ; Kuroshio intrusion ; Kuroshio Current Loop ; cold-core anticyclonic eddy ; cloud masking ; turbid water ; spectral variability ; total suspended sediment ; chlorophyll-a bloom ; typhoon ; South China Sea ; alongshore current ; marine heatwaves ; sea surface temperatures ; summer 2021 ; northwestern Pacific Ocean ; westerly jet ; North Pacific Subtropical High ; ocean color ; water type taxonomies ; trophic state ; inherent optical properties ; Forel-Ule Scale ; Sargassum ; aerosols ; OLCI ; Daya Bay Nuclear Power Plants ; thermal discharge ; long-term changes ; Landsat ; radiative transfer equation ; split-window algorithm ; power plant installed capacity ; flood tide ; ebb tide ; wind field ; bias correction ; deep learning ; ConvLSTM ; 3D-C BAM ; Kuroshio branch ; salinity ; North Pacific subtropical gyre ; satellite observation ; in situ observation ; Taiwan Strait ; flow pattern ; high-frequency radar ; drifter ; tide ; turbulent mixing ; upper ocean response ; Super Typhoon Goni ; satellite observations ; HYCOM reanalysis results ; internal tides ; spatiotemporal variation ; modal structure ; energy cascade ; machine learning ; ocean subsurface salinity structure ; satellite remote sensing data ; data fusion ; offshore detection ; SAR images ; meteorological data ; AI explanation ; sea ice ; Bayesian algorithm ; CFOSAT ; scatterometer ; internal solitary waves ; turbulence ; Yellow Sea ; wake detection ; radiation sensitivity ; noise equivalent reflectance difference ; three-dimensional eddy reconstruction ; loop current rings ; gulf of Mexico ; gravest empirical modes ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The reprint “Energy-efficient communication networks and systems” gives insights into the range of problems in the field of obtaining more energy-efficient communication networks and systems. The reprint contains the outcomes of the “Special Issue on energy-efficient communication networks and systems” organized for the Sensors journal published by the Multidisciplinary Digital Publishing Institute (MDPI). The 12 high-quality papers published in the frame of the Sensors journal Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field to which this reprint is dedicated.Published papers consolidated in this reprint are self-contained peer-reviewed scientific works. Among published papers, one paper is editorial, one paper is a review type of paper, and the remaining ten articles are research articles. The papers are authored by 40 authors coming from academia and industry. The published articles target the improvement of energy efficiency in the fields of fiber-wireless, vehicle-to-vehicle/infrastructure, sensors, satellites, 5G, virtual elements, and cognitive radio networks. The contributions of published papers provide valuable insights into the latest research and technologies for improving the energy efficiency of communication networks and systems.This reprint can serve the readers as a source of information when needed in their industrial, teaching and/or research and development activities since it presents the recent advances in different fields related to improving the energy efficiency of communication networks and systems.
    Keywords: green communications ; green networking ; 5G ; radio access network ; base station ; energy-efficiency ; metric ; data ; coverage ; power ; mobile network operator ; wireless ; spectrum sensing ; energy detection ; SLC ; OFDM ; noise uncertainty ; dynamic threshold ; MIMO ; SISO ; cognitive networks ; SNR ; probability ; false alarm ; transmit ; receive ; energy consumption management ; content forwarding ; information-centric networks ; internet of things ; smart city ; LEO satellite communications ; massive MIMO ; multigroup multicast ; user scheduling ; hybrid beamforming ; robust ; joint design ; energy efficiency ; 5G HetNets ; BPSO ; classification trees (CTs) ; soft frequency reuse (SFR) ; small cells (SCs) ; virtualization ; power consumption ; power models ; power meters ; energy-aware algorithms ; vehicular communications ; deep reinforcement learning ; deep Q-network ; resource allocation ; radio ; access ; networks ; fiber ; D-RAN ; C-RAN ; Mobile fronthaul ; RoF ; digitized RoF ; analog RoF ; NGFI ; FiWi ; NG–PON ; SDN ; NFV ; MEC ; machine learning ; telecom services operator ; traffic prediction ; Internet of Remote Things ; sparse LEO satellite transmission ; water-level monitoring ; wireless networks ; data dissemination ; broadcast tree ; MAXFLAT ; PDM ; sigma–delta ; microphone ; sensor array ; decimation ; beamforming ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-04-05
    Description: This reprint is focuses on how recent urbanization processes modifies the organization and management of the land uses at integrated rural areas in peri-urban and intra-metropolitan areas at local, national, and global levels. The Guest Editors expect that this reprint could serve to provide some answers regarding the impacts of urbanization on rural areas.
    Keywords: extractivism ; capitalist periphery ; rurality ; urbanization ; rural-urban pluriactivity ; deagrarianization ; depeasantization ; rural proletarianization ; south-central Andes ; urban sprawl ; discontinuous urban fabric ; suburbanisation ; functional urban area ; de-agrarianisation ; post-agricultural brownfield ; regeneration ; urban renewal ; Central Europe ; post-socialist city ; hazards ; early warning system ; LST ; urban–rural fringes ; machine learning ; ANFIS ; random forest ; decision tree ; sustainable development goals ; urbanization quality ; agricultural development ; main grain-producing areas ; China ; rural–urban integration ; countryside urbanisation ; deagrarianisation ; land use ; land access ; agricultural entrepreneurship ; land law ; sustainable production ; Benin ; urban expansion ; suburbs ; systemic risk ; risk resistance ; differentiation ; management policy ; rural residential areas ; suitability of human settlements ; suitability evaluation ; Hengshui ; rural–urban interaction ; economic tertiarization ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
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  • 178
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: This reprint captures recent advancements in the introduction, usage, and adoption of smart and digital disruptive technologies in the built environment. It consists of 17 chapters covering a range of topics and article types. The key topics include the adoption of smart technologies, automation, and disruption in the built environment, such as wearable devices and augmented reality in construction safety, electronic process monitoring for construction tasks, digital capture of buildings through point clouds, UAVs, and LIDAR, BIM for a learning environment, underground works and wood construction, collaborative information management technologies in construction, techniques for structural health monitoring and evaluation, construction risk management, inclusive walking communities, smart spin models for cities, landfill and waste management in cities, and circular economy in construction for sustainable development.
    Keywords: artificial intelligence ; building corrosion detection ; building damage detection ; civil infrastructure crack detection ; civil infrastructure inspection ; image processing ; machine learning ; unmanned aerial vehicles ; BIM ; BIM-enabled learning ; BIM education ; virtual learning environment ; AEC-FM ; underground works ; innovation ; common data environment ; wearable device ; bibliometric analysis ; construction safety ; CiteSpace ; LIDAR ; TLS ; UAV ; point cloud ; 3D modelling ; occupational risk prevention (ORP) ; collective protection elements (CPE) ; construction safety inspection ; augmented reality ; building information modeling (BIM) ; construction industry ; geographic information systems ; landfill site selection ; landfill site ranking ; remote sensing ; solid waste ; solid waste management ; causal loop diagram ; profitability-influencing risk factors ; profitability-influencing risk categories ; system dynamics ; systems thinking ; China Pakistan Economic Corridor ; host country attitude towards foreigners ; legal risk ; political risk ; project performance ; social safety risk ; construction supply chain ; collaborative technologies ; information complexity ; information management ; smart city industry ; industrial ecosystem ; spectrum ; penetration ; impact ; network ; input–output table ; new mega-subcontrolled structural system (MSCSS) ; steel plate shear wall (SPSW) ; infill panel ; plastic deformation ; nonlinear dynamic analysis ; energy dissipation ; circular economy ; sustainable development ; building information modelling (BIM) ; wood construction ; grounded theory ; electronic performance monitoring ; wearable devices ; process modelling ; multivariate statistical analysis ; inclusive city ; digital tool ; age-friendly ; walkability ; accessibility ; multi-criteria evaluation ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
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  • 179
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: This reprint contains 15 articles from the Special Issue of the MDPI journal Processes on "Machine Learning-Assisted Intelligent Processing and Optimization of Complex Systems". These articles focus on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling.Focusing on the abovementioned subjects, this reprint can be useful for researchers interested in intelligent optimization techniques and their applications in the fields of artificial intelligence and machine learning. We believe that this reprint will encourage the convergence between many communities.
    Keywords: Chilo suppressalis ; meteorological data ; time series analysis ; DeepAR ; deep learning ; integrated pest management ; text vectorization ; topic model ; pretrained model ; transfer learning ; drop impact ; maximum spreading diameter ; scaling laws ; analytical models ; machine learning ; agribusiness ; optimization of the production flow ; cold storage management ; endogenous fruits ; peaches ; lean tools ; 5S ; Kaizen ; Value Stream Mapping ; inappropriately wearing facemask ; mask detection ; UAV edge network ; popularity prediction ; cache strategy ; artificial bee colony ; turbulence ; passive scalar ; convolutional neural network ; estimating diffusion source distance ; leaking gas detection ; waste marble powder ; flexural strength ; support vector machines ; Gaussian processes ; ANFIS ; cross-domain ; MEC ; resource allocation ; IIOT ; knowledge graph ; knowledge structuring ; entity extraction methods ; asset administration shell ; process industry entity relationship networks ; Industry 5.0 ; human-centricity ; human-centred ; I5.0 technologies ; artificial intelligence ; robotics ; cyber-physical systems ; digitalization ; acoustic signal ; fault diagnosis ; adaptive multi-threshold segmentation ; subdomain adaptation ; variable speed condition ; local maximum mean discrepancy ; weed detection ; weed classification ; support decision-making algorithm ; fruit detection ; disease detection ; CNN ; performance metrics ; agriculture ; deep learning neural network ; process control ; hydraulic fracture ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 180
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: The aim of this reprint is to report on new scenarios, technologies, and applications related to the concept of the Internet of Everything and discuss challenges and risks. We introduced a wide range of topics related to emerging technologies. This reprint includes research on vendor-managed inventory mechanisms based on the SCADA of the Internet of Things, in-memory computing architecture for a convolutional neural network, face prediction system for missing children in a smart city safety network, anomaly electricity usage behavior in residence using an autoencoder, cloud-edge-smart IoT architecture for speeding up the deployment of neural network models, generative adversarial network and diverse feature extraction methods to enhance the classification accuracy of the tool-wear status, classifying conditions of speckles and wrinkles on the human face using a deep learning approach, repetition with learning approaches in massive machine-type communications, GDPR personal privacy security mechanism for smart home systems, and the development of an autonomous vehicle training and verification system. These articles demonstrate the rapid advances being made in the field of electronics and highlight the potential for these technologies to impact our daily lives.
    Keywords: Internet of Things ; SCADA ; Customer-to-Business ; vendor-managed inventory ; Artificial Neural Network ; digital transformation ; convolution neural network ; computing in memory ; processing in memory ; distributed arithmetic ; MRAM ; SOT-MRAM ; face aging ; generative adversarial network ; StyleGAN2 ; FaceNet ; missing child ; energy saving ; carbon reduction ; advanced metering infrastructure ; low-voltage users ; anomaly detection ; autoencoder ; deep learning ; transfer learning ; lightweight neural network ; edge computing ; tool wear ; data imbalance ; GAN ; ensemble learning ; image processing ; skin condition detection ; ResNet ; massive machine type communications (mMTC) ; enhanced machine type communication (eMTC) ; repetition ; machine learning ; k-nearest neighbor (KNN) ; support vector machine (SVM) ; Internet of Things (IoT) ; EU general data protection regulation (GDPR) ; consensus mechanism ; self-driving car ; donkey car ; autonomous car ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 181
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: Machine learning and computational intelligence have been applied to various areas and witnessed many successes. The research in this publication explorse many intelligent algorithms which are characterized by computational adaptability, robustness, and high performance. These algorithms facilitate intelligent behavior in complex and dynamic environments and the development of technology that enables machines to think, behave, or act in a more humanesque fashion. This reprint aims to present and discuss the most recent innovations, trends, concerns, challenges, solutions, and application fields in the areas of machine learning and computational intelligence.
    Keywords: left ventricle segmentation ; UNet 3+ ; encoder–decoder ; transformer ; magnetic resonance imaging ; beta function ; crow search algorithm ; dynamic multi-objective optimization problems ; evolutionary algorithm ; many-objective optimization problems ; naive Bayesian classifier ; attribute independence assumption ; mixed-attribute classification ; conditional probability ; Bayesian network ; attribute transformation ; subsection proximal policy optimization ; weighted importance sampling ; TORCS ; vehicle-following ; autonomous driving ; credit scoring ; machine learning ; deep learning ; model predictive control ; reinforcement learning ; parameter adaptive ; quadruped robot ; facial skin problem ; mask R-CNN ; super resolution ; Generative Adversarial Network (GAN) ; tactics for high performance ; R5DOS intersection matrix ; RJA-star algorithm ; jump point search algorithm ; path planning ; sentiment analysis ; cross-validation ; vectorization ; feature importance ; differential evolution strategy ; global search optimization ; optimization algorithm ; search accuracy ; weighted mean of vectors ; n/a ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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  • 182
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint compiles the articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles. This reprint encompasses the key topics related to drone design, communications as well as autonomous Flight and Navigation. Special attention is paid to the drones’ applications to environmental and earth sciences, including in agriculture, forestry, water, and marine environments; other innovative applications are also explored including in relation to the field of application, such as the inclusion of new deep learning techniques.
    Keywords: convolutional neural network ; deep learning ; transfer learning ; point clouds ; structural damage assessment ; vegetation indices ; RGB cameras ; unmanned aerial vehicle (UAV) ; empirical line method ; Green leaf index ; open aerial map ; autonomous ; hexacopter ; water quality ; water stratification ; water temperature ; drones ; Martian atmosphere ; thermal analysis ; aerodynamics ; thermoelectric generators ; hyperspectral images ; multispectral data ; machine learning ; ice detection ; UAS ; GCP ; 3D point cloud ; DSM ; image processing accuracy ; actual evapotranspiration ; high spatiotemporal resolution ; multispectral imagery ; thermal infrared imagery ; METRIC energy balance model ; irrigated field crops ; precision agriculture ; travelling salesman problem ; UAV-based precision farming ; Euclidean distance ; Voronoi ; site-specific fertilizer spray ; UAV ; RPAAS ; aerial application ; backpack sprayer ; spray deposition ; droplet spectra ; palmer amaranth ; morningglory ; Reforming-Controlled Compression Ignition ; UAV applications ; exergy analysis ; hydrogen ; dimethyl ether ; fuel reactivity control ; FANETs ; ad hoc networking ; drone swarms ; efficient routing ; traffic monitoring ; 4G/LTE ; VPN ; real-time video ; computer vision ; unmanned aerial systems ; autonomous systems ; wildland fire ; forest fires ; fire detection ; UAVs ; safety ; signal processing ; condition-based maintenance ; structural health monitoring ; fault diagnostics ; fault mitigation ; contingency planning ; streamflow ; sediment loading ; digital terrain model ; rocky coast ; Galicia ; ecosystems ; geomorphic change detection ; GIS ; drone ; dragonfly ; insect ; biomimetic ; biological inspiration ; design ; remote sensing ; coral reefs ; linear unmixing ; R ; Google Earth Engine ; persistent surveillance ; hierarchical architecture of UAV teaming ; communication aware UAV formation ; dynamical object tracking ; intercommunication quality ; UAV-based monitoring ; agricultural robotics ; plant disease detection ; RGB images ; Cercospora leaf spot ; CNNs ; semantic segmentation ; phenotyping ; bog ; Oculus Quest 2 ; Mer Bleue ; SfM ; augmented reality ; AR ; unmanned aerial systems (UAS) ; aerial photogrammetry ; habitat monitoring ; braided river habitats ; efficiency ; data envelopment analysis (DEA) ; civilian use ; factors ; design and selection ; law-making ; mind-mining ; expert groups ; literature study ; triple helix model (THM) ; analytic hierarchy process (AHP) ; collision avoidance ; depth cameras ; point cloud ; CPU ; GPU ; spiral ; Mars ; autogyro ; gyroplane ; autonomous flight ; indoor positioning ; cyber pilot ; sensor fusion ; distributed electric propulsion ; boundary layer ingestion ; propeller ; fixed wing ; aerial drones ; autonomous navigation ; path planning ; reactive control ; obstacle avoidance ; sense-and-avoid ; hybrid navigation method ; dynamic environments ; small unmanned aircraft systems ; photogrammetry ; structure-from-motion ; wind impact ; turbulence ; crash scene reconstruction ; traffic incident management ; detection ; CBRNe ; MOX ; chemical sensor ; simulation ; fluid dynamics simulations ; green water ; integrated water management strategies ; smallholder farms ; water productivity ; localization ; communication ; drone swarm ; lidar ; streams ; canopy height ; roughness ; vegetation density ; change detection ; NB-IoT ; network analysis ; simulations ; landslides ; multispectral ; RGB ; vegetation monitoring ; legislation ; ethics ; spatial social sciences ; advanced leak detection ; advanced leak quantification ; source estimation ; environmental monitoring ; landfill ; natural gas ; human–swarm interaction ; situation awareness ; user-centered interface design ; thermal imaging ; blackbody ; emissivity ; thermography ; base stations ; cellular networks ; photovoltaic system ; battery ; search and rescue ; autonomous drones ; acceleration ; deceleration ; drone classification ; CNN ; HERM lines ; micro-Doppler ; radars ; aeromagnetics ; drone survey ; mineral exploration ; geophysical prospecting ; speed ; RFID ; inventory ; labor ; forecast ; drone technology ; aquaculture ; precision aquaculture ; aquaculture monitoring ; aquaculture drones ; internet of things ; swarm robotics ; unmanned aerial vehicle ; evolutionary game theory ; evolutionary algorithm ; surveillance system ; multi-objective optimisation ; digital elevation model (DEM) ; digital surface model (DSM) ; orthomosaic ; Earth observation ; unmanned aerial vehicles (UAV) ; social acceptance ; urban air mobility (UAM) ; CORUS-XUAM ; proper orthogonal decomposition ; cellular-enabled drones ; aerial base stations ; 5G/B5G/6G cellular networks ; gesture recognition ; small drone ; long-distance surveillance ; ground target tracking ; track-to-track association ; image-to-position conversion ; anti-collision radar ; autonomous flight unmanned aerial system ; obstacle detection ; radar mapping ; unmanned aerial system (UAS) ; n/a ; grazing density ; nutrient ; pasture management ; forage grass ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 183
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: With increasing awareness about environmental sustainability issues, the geotechnical engineering community is in search of sustainable materials, innovative applications and ground improvement technologies which are resilient to climate change, involve low carbon emissions, are ecologically friendly and affordable, yet effective. As such, this reprint brings together 18 novel contributions providing the state-of-the-art in “Sustainable Geotechnics” with special focus on the reuse and recycling of waste materials in geotechnical applications as well as sustainable design, construction, and monitoring of the performance of geostructures. This reprint may be of particular interest to geotechnical professional engineers and researchers who are facing the challenging task of increasing the sustainability and resiliency of geotechnical assets and infrastructures.
    Keywords: cement bound base course ; unbound base course ; compaction technology ; Proctor test ; vibrating hammer test ; recycled rubber ; geotechnical properties ; diesel ; contaminated soil ; clay ; environmental geotechnics ; impact monitoring ; geotechnical influence ; ground improvement ; soil nailing system ; soil characteristics ; soil slope ; foundation pressure ; nailed soil ; end-of-life tires ; recycling ; gravel–rubber mixtures ; sustainable geotechnical applications ; foundation systems ; soil freezing ; probability ; return period ; reliability ; correction coefficient ; depth of ground freezing ; pullout test ; retaining structures ; gabions ; bearing resistance ; welded steel grid ; woven steel grid ; reinforcement of embankments ; safety factor ; Neogene clay elevation ; Warsaw Slope ; finite element method ; electrical resistivity tomography ; biomineralization ; Bacillus pasteurii ; marine clay ; MICP ; soil improvement ; acidic soil ; soil treatment ; ammonia-soda residue ; compressibility ; constant rate of strain ; drained ; shear strength ; triaxial test ; calcium carbonate precipitation induced by microorganisms ; silt ; void ratio ; fine particle content ; unconfined compressive strength ; permeability coefficient ; XRD ; SEM ; stepped spillways ; flow 3D ; energy dissipations ; pressure profiles ; cavitation ; incremental equations ; non-cohesive soil ; partial saturation ; liquefaction ; Taiwan mudstone ; engineering compaction ; cement paste ; engineering material improvement ; machine learning ; decision trees ; random forests ; penetrometer ; MWD ; rigid inclusions ; soil stabilization ; chitosan ; non-traditional additives ; soil shear modulus ; temporary geotechnical structures ; calcium carbonate ; HPMC ; surface strength ; ammonia retention rate ; wind erosion resistance ; reinforced soil walls ; experimental tests ; facing displacements ; analytical methods ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 184
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Antimicrobial resistance remains a major concern in medicine, especially during the COVID-19 pandemic, where microbial infections were frequent complications. To combat drug-resistant pathogens, there has been a renewed interest in the use of antimicrobial peptides (AMPs). This reprint focuses on the in-silico approaches used for the rational discovery and design of AMPs. Such computational methodologies range from classical homology-based and machine-learning prediction algorithms to complex similarity networks and evolutionary algorithms that use models of sequence evolution. Furthermore, the reprint explores the improvement of high-throughput screening techniques in the discovery of AMPs from biological samples, which has also led to the evolution of computational approaches that aid in this biodiscovery process. The reprint contains original research and review papers, which serve as valuable references for researchers dedicated to peptide drug development.
    Keywords: cancer ; tumor-homing peptide ; in silico drug discovery ; complex network ; chemical space network ; centrality measure ; similarity searching ; group fusion ; motif discovery ; starPep toolbox software ; FOF1-ATP synthase ; allosteric inhibition ; structure-based drug design ; evolutionary and PPI algorithms ; peptide design ; artificial intelligence ; machine learning ; AMPs ; evolutionary algorithms ; molecular descriptors ; complex networks ; proteogenomics ; antimicrobial peptide ; AMP discovery ; genome mining ; antimicrobial resistance ; Streptomyces ; secondary metabolites ; genome ; biosynthetic gene clusters ; high-performance liquid chromatography (HPLC) ; mass spectrometry ; amphipathic peptides ; multifunctional ; design ; penetratins ; antimicrobial ; antiviral ; anticancer ; anti-inflammatory ; cell-penetrating ; non-toxic ; cathelicidins ; antimicrobial peptides ; LL-37 ; biofilms ; abscess model ; skin model ; reptiles ; Apicomplexan ; bioactive peptides ; toxoplasmosis ; cryptosporidiosis ; malaria ; antibacterial peptide ; AMPs database ; StarPep ; Gram staining-based target ; peptide library screening ; human peptidome ; redox system ; Cryptococcus neoformans ; ROS metabolism ; ergosterol ; synthetic antimicrobial peptides ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PN Chemistry
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  • 185
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-03-07
    Description: When adopting remote sensing techniques in precision agriculture, there are two main areas to consider: data acquisition and data analysis methodologies. Imagery and remote sensor data collected using different platforms provide a variety of information volumes and formats. For example, recent research in precision agriculture has used multispectral images from different platforms, such as satellites, airborne, and, most recently, drones. These images have been used for various analyses, from the detection of pests and diseases, growth, and water status of crops to yield estimations. However, accurately detecting specific biotic or abiotic stresses requires a narrow range of spectral information to be analyzed for each application. In data analysis, the volume and complexity of data formats obtained using the latest technologies in remote sensing (e.g., a cube of data for hyperspectral imagery) demands complex data processing systems and data analysis using multiple inputs to estimate specific categorical or numerical targets. New and emerging methodologies within artificial intelligence, such as machine learning and deep learning, have enabled us to deal with these increasing data volumes and the analysis complexity.
    Keywords: vineyard ; pesticide application ; variable rate application ; unmanned aerial vehicle ; satellite ; nanosatellite ; monsoon crops ; leaf area index ; leaf chlorophyll concentration ; crop water content ; multispectral ; hyperspectral ; deep learning ; forage dry matter yield ; high-throughput phenotyping ; Brazilian pasture ; nitrogen indicator ; nitrogen nutrition diagnosis ; optical sensor ; spectral index ; UAV ; wheat lodging ; lightweight ; digital surface model (DSM) ; winter wheat ; fractional order differential ; continuous wavelet transform ; optimal subset regression ; support vector machine ; wheat powdery mildew ; machine learning ; information fusion ; remote sensing monitoring ; hyperspectral imaging ; dimensionality reduction ; LDA ; PLS ; PCA ; RandomForest ; ReliefF ; XGB ; Meloidogyne ; Solanum tuberosum ; soil salinity sensitive parameter ; random forest ; optimal retrieval model ; remote sensing ; high throughput phenotyping ; UAV/drone ; biomass estimation ; oats ; wheat ; yield prediction ; random forests ; satellite imagery ; Normalized Difference Vegetation Index (NDVI) ; n/a ; bic Book Industry Communication::M Medicine
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: "Functional Nanomaterials for Healthcare" is a collection showcasing cutting-edge research in advanced nanomaterials for healthcare applications. As healthcare evolves through science and innovation, these articles provide the latest insights into nanomaterial applications. Researchers have tailored nanomaterials for improved diagnostics, medical imaging, precise drug delivery, tissue engineering, and groundbreaking theranostics. This compilation, written by experts, explores advanced nanomaterial synthesis, functionalization, characterization, and diverse medical uses. Dive into this significant contribution to the field, offering a comprehensive overview of the latest innovations in healthcare nanomaterials for researchers, students, and healthcare professionals.
    Keywords: mitochondrial targeting ; gold nanoparticles ; cancer chemotherapy ; drug delivery ; betulinic acid ; laminin receptor ; zinc oxide nanoparticles ; organic surface deposit ; cytotoxicity assay ; photocatalytic activity ; ROS generation ; toxicity mechanism ; MDA-MB-231 ; HT-29 ; ebselen ; cerium ; ERK1/2 ; STAT-6 ; IL-4 ; STAT-1 ; antimicrobial activity ; carbon nanotubes ; human SP-D ; cancer cells ; apoptosis ; immunotherapy ; Alhydrogel® ; silica nanoparticles ; Bet v 1 ; BM4 ; SiO2 ; allergen ; structural integrity ; alum ; nanoparticles ; antimicrobial resistance ; bacteria ; resistance mechanism ; hyaluronic acid ; adipic acid dihydrazide ; silver nanoparticles ; polymer molecular weight ; antimicrobial ; SARS-CoV-2 ; protein nanoparticles ; vaccines ; nanovaccine ; nanomedicine ; protein-based nanotechnology ; graphene oxide ; biopolymer blends ; biomineralization ; ectopic bone formation ; osteoinduction ; ex vivo analysis ; nanotechnology ; cosmetic ; chitosan ; essential oils ; preservative agents ; metal-organic framework ; cardiovascular diseases ; graphene ; G+ ; PLA ; Grafylon ; scaffold ; neuronal differentiation ; stem cells ; 3D printing ; regenerative medicine ; Curcumin ; Paclitaxel ; triple-negative breast cancer cell lines (4T1 and MDA MB 231) ; metastasis ; capsaicin ; human ; pruritogens ; desensitization ; itch ; polymers ; compartments ; biomedical ; mesoporous silica nanoparticles ; MSN ; porous materials ; functionalisation ; NMR ; HR-MAS NMR ; surface ; COVID-19 ; cationic surfactants ; virucidal activity ; quaternary ammonium compounds ; disinfectants ; nanoprophylaxis ; viral inhibition ; human papillomavirus ; HPV ; pseudovirus ; viral infection inhibition ; nanocomplex formation ; photodynamic therapy ; photosensitizer ; upconversion nanoparticles ; graphene quantum dots ; reactive oxygen species ; green synthesis ; carbon nanomaterials ; biomass ; sustainability ; nanomaterials ; machine learning ; antioxidant ; biopolymers ; therapeutic substances ; incorporation ; biocompatibility ; healthcare ; biomedical applications ; surface characterization ; quantum yield ; label-free detection ; zinc oxide nanostructure ; surface functionalization ; mesoporous polydopamine ; ferric ions ; doxorubicin (DOX) ; hyaluronic acid target modification ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: The huge prevalence of type 2 diabetes is a leading human and economic concern worldwide. The diagnosis code of type 2 diabetes includes multiple clinical phenotypes showing different degrees of obesity, fat distribution patterns, types of dyslipidemia, and characteristics of insulin resistance syndrome. In addition, subjects with type 2 diabetes could develop different clinical trajectories, with age being a critical factor in progression. The chronic complications of type 2 diabetes are a major cause of mortality and disability, and are ranked in the top places in western countries’ scores. The pathophysiological heterogeneity of type 2 diabetes is not captured by the current classifications and guidelines. The potential for diabetes progression and complications developing is different depending on the type 2 diabetes cluster, which is mostly regardless of the degree of glycemic control. However, the impact on quality and life expectancy with the current therapeutic approach is not always the same for every individual. Clinical research is the key to reducing the burden of diabetes. New basic, digital, and clinical approaches are obtaining useful knowledge and designing more individualized interventions to prevent, track, and treat diabetic complications. This Special Issue is a clear reflection of this methodological evolution.
    Keywords: dipeptidyl peptidase-4 inhibitor ; diabetes mellitus ; diabetic retinopathy ; progression ; machine learning ; diabetic sensorimotor polyneuropathy ; random forest ; prediction ; electrophysiology ; COVID-19 ; hyperglycemia ; glycemic control ; blood glucose monitoring ; telemedicine ; fibrosis ; NAFLD ; diabetes ; screening ; primary care ; secondary care ; glucose variability ; end-stage kidney disease ; Korean National Health Insurance Corporation ; microvascular complications ; cardiac autonomic neuropathy ; diabetic peripheral neuropathy ; diabetic nephropathy ; patient profiles ; non-alcoholic fatty liver disease ; non-alcoholic steatohepatitis ; NASH ; type 2 diabetes ; cardiovascular disease ; cardiovascular complications ; CVD ; complex intervention ; behaviour change intervention ; co-design ; continuity of care ; developing country ; Ethiopia ; patient participation ; patient transfer ; stroke outcome ; skin autofluorescence ; advanced glycation end products ; poststroke complications ; obesity and diabetes mellitus type 2 ; research ; hospitalization ; risk factors ; cardiovascular diseases ; type 2 ; gender ; type 2 diabetes mellitus ; bone fragility ; fracture risk ; bone structure ; bone quality ; cardiac fibrosis ; pulse wave velocity ; liraglutide ; body weight ; obesity ; hypoglycemia ; meta-analysis ; nephropathy ; urine albumin-creatinine ratio ; diabetes complications ; coronavirus infections ; hypoglycemic agents ; ambulatory care ; comorbidity ; glucagon-like peptide-1 receptor agonist ; HbA1c ; real-world evidence ; semaglutide ; SURE study ; pneumatosis intestinalis ; alpha-glucosidase inhibitors ; acarbose ; voglibose ; miglitol ; comorbidities ; concomitant drugs ; prednisone ; immunosuppressants ; n/a ; depression ; sex ; in-hospital mortality ; readmission ; empagliflozin ; SGLT-2 ; monocytes ; endothelial cells ; vascular dysfunction ; chemotaxis ; reactive oxygen species (ROS) ; glucose transport ; VEGFR-2 ; VEGFR-1 ; bic Book Industry Communication::M Medicine
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  • 188
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue, entitled “Non-Destructive Testing in Civil Engineering”, aims to present to interested researchers and engineers the latest achievements in the field of new research methods, as well as the original results of scientific research carried out with their use—not only in laboratory conditions but also in selected case studies. The articles published in this Special Issue are theoretical–experimental and experimental, and also show the practical nature of the research. They are grouped by topic, and the main content of each article is briefly discussed for your convenience. These articles extend the knowledge in the field of non-destructive testing in civil engineering with regard to new and improved non-destructive testing (NDT) methods, their complementary application, and also the analysis of their results—including the use of sophisticated mathematical algorithms and artificial intelligence, as well as the diagnostics of materials, components, structures, entire buildings, and interesting case studies.
    Keywords: conveyor belt ; climatic factors ; thermal shocks ; mechanical properties ; applied geophysics ; urban geophysics ; Eleftheria Square ; ERT ; probability-based ERT inversion (PERTI) method ; GPR ; EMI ; impact-echo ; tooth gear impactor ; contact duration ; delamination ; rapid scanning ; non-destructive testing ; concrete slab ; building defects ; building diagnosis ; building envelope ; building inspection system ; urgency of repair ; historic buildings ; brick walls ; nondestructive testing ; artificial neural networks ; Nearly Zero Energy Buildings (NZEB) ; passive house (PH) ; heat flux meter (HFM) ; quantitative infrared thermography (QIRT) ; building thermal performance ; U-value ; Mediterranean climate ; electrical resistivity ; electrical impedance ; concrete ; mortar ; measurement accuracy ; ultrasonic elastography ; underground detection ; soil inspection ; underwater acoustics ; non-destructive test ; monitoring ; housing ; buildings ; façade ; thermal transmittance ; HFM method ; infrared thermography ; solar loading thermography ; lock-in thermography ; passive thermography ; thermal thickness ; thermal effusivity ; infrastructure ; NDT ; onsite X-ray bridge inspection ; 950 keV/3.95 MeV X-ray sources ; PC bridge ; unfilled grout ; quantitative evaluation of stage of unfilled grout ; step-heating thermography ; active thermography ; linear effusivity fit ; ground-penetrating radar ; signal features ; material moisture ; classification ; machine learning ; moisture measurements ; building floors ; civil engineering ; crack measurement ; image processing ; high resolution ; working distance ; crack width ; visual inspection ; structure state assessment ; ground sample distance (GSD) ; sonic resonant method ; impulse excitation technique ; resonant frequency ; steel fiber reinforced concrete ; fiber orientation ; micro-computed tomography ; ultrasound ; spectral induced polarization ; small force ; load ; instrumental signal ; two-point bending test ; strain gauge ; calibration equation ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 189
    Publication Date: 2024-04-11
    Description: This reprint exists to solve high complexity issues in remote sensing data processing, geochemical data analysis, geophysical data analysis and appropriate applications of GIS techniques for data fusion designed for mineral and hydrocarbon exploration. This reprint contains updated and informative knowledge of remote sensing imagery, geochemistry, geophysics and geospatial techniques that can assist in delineating the signatures and patterns linked to deep-seated, covered, blind, or buried mineral deposits and onshore oil slick detection, offshore oil spill monitoring and hydrocarbon exploration. It includes several color figures for remotely-sensed recognition of mineralization-related footprints. Additionally, this reprint comprehends several interactive flowcharts for describing the procedures explained therein.
    Keywords: multispectral satellite data ; PALSAR ; gold exploration ; Wadi Hodein shear belt ; transpressional deformation ; gold-bearing quartz veins ; resources characterization ; bauxite residues ; band ratio ; kriging of component ; mineral grade ; ASTER ; chromite ; Khoy ophiolite ; spectral angle mapper (SAM) ; principal component analysis (PCA) ; porphyry copper deposits ; machine learning ; DP ; SVM ; SAM ; zonality method ; remote sensing ; vertical zonality index ; geological layer ; alteration ; K-nearest neighbor ; porphyry-Cu deposit ; magnetic method ; gravity method ; magmatic intrusion ; hydrothermal fluid ; Lower Benue Trough ; southeast Nigeria ; aeromagnetic ; Bornu Basin ; Precambrian ; basement depth ; fault system analysis ; massive sulfide copper exploration ; airborne geophysical analysis ; Fry analysis ; multifractal technique ; high latitudes ; weak information ; thermal anomalies ; radioactive element deposits ; Kroh shale ; aromatic hydrocarbons ; spectroscopy ; humic acid ; organic carbon ; mineral exploration ; OLI ; Sentinel-2 ; GIS ; Khnaiguiyah ; Saudi Arabia ; mineral prospectivity mapping ; random forest ; gold mineralization ; Sudan ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-30
    Description: The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power-constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks.
    Keywords: propagation trends ; social networks ; group features ; dilated CNN ; machine learning ; physical layer security ; Rice channels ; wireless communications ; 6G security ; sycon ; cube attack ; state recovery ; wireless body area networks ; authentication ; biometric ; physical unclonable function ; BAN logic ; RoR model ; AVISPA ; 6G wireless communications ; chi-square ; cybersecurity ; intrusion detection system ; machine learning techniques ; meta-model ; stacking ensemble learning ; voting techniques ; fault attack ; error detection ; code abiding ; overcost ; bitslice cipher ; multiple eavesdroppers ; full-duplex ; underground mine ; amplify-and-forward relay ; communication system security ; physical layer ; wireless communication ; precoding ; wire-tap channel ; blockchain ; wireless communication network ; malicious node ; security protocol ; intrusion detection ; in-vehicle communication ; inter-vehicle communication ; optical communication ; security wireless ; visible light communication ; wireless optical communication ; convolutional neural network ; CNN ; counterfeit detection ; device fingerprinting ; distinct native attribute (DNA) ; information and communications technology ; multiple discriminant analysis ; MDA ; WirelessHART ; wireless communications security ; digital twin ; Internet of Things ; healthcare ; encryption ; privacy ; rural ; LPWAN ; secure localization ; positioning ; distance vector hop ; DV-Hop ; security attacks ; wireless sensor network ; security ; steganalysis ; covert channel ; steganography ; undetectability ; aggregator-based grouping ; wireless sensor networks ; encryption and decryption operations ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries ; thema EDItEUR::U Computing and Information Technology::UY Computer science
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    Springer Nature | Springer International Publishing
    Publication Date: 2024-04-14
    Description: The four-volume set LNCS 13350, 13351, 13352, and 13353 constitutes the proceedings of the 22ndt International Conference on Computational Science, ICCS 2022, held in London, UK, in June 2022.* The total of 175 full papers and 78 short papers presented in this book set were carefully reviewed and selected from 474 submissions. 169 full and 36 short papers were accepted to the main track; 120 full and 42 short papers were accepted to the workshops/ thematic tracks. *The conference was held in a hybrid format This is an open access book.
    Keywords: artificial intelligence ; communication systems ; computer networks ; computer systems ; computer vision ; correlation analysis ; data mining ; image analysis ; image processing ; machine learning ; network protocols ; neural networks ; numerical methods ; signal processing ; telecommunication systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Duckweed (Lemnaceae) represents a small aquatic monocot plant family presently composed of 36 species. These plants gained importance in recent decades for their applications in wastewater purification, as animal food or human nutrition, as well as for energy production. This Reprint presents 39 manuscripts published in the Special Issue “Duckweed: Research meets applications” of the journal Plants. We provide an overview of the present state of the art of duckweed research in taxonomy of the family, phytoremediation, accumulation of protein or starch, interaction with microorganisms, and phytomonitoring of toxic compounds. This Special Issue also invited the participants of the 6th International Conference on Duckweed Research and Applications (ICDRAs) held in Gatersleben, Germany, organised on behalf of the International Steering Committee on Duckweed Research and Applications (ISCDRAs). This Reprint is organised as follows:1. Introduction; 2. Molecular Characterization and Taxonomy; 3. Phytoremediation: Wastewater; 4. Applications: Accumulation of Protein or Starch; 5. Interaction with Microorganisms; 6. Physiology and Phytomonitoring.The manuscripts were organised by the Guest Editors Viktor Oláh (University of Debrecen, Debrecen, Hungary), Klaus-J. Appenroth (Friedrich Schiller University, Jena, Germany), and K. Sowjanya Sree (Central University Kerala, Periye, India).
    Keywords: Lemnaceae ; remediation ; feed safety ; mineral supplements ; accumulation ; agricultural wastewater ; nutrient recovery ; biosynthesis inhibitor ; duckweed ; occurrence ; overcome ; phytohormones ; wastewater ; density ; surface cover ; circular economy ; lemna ; amino acids ; biomass production ; cultivation ; nutrient medium ; uptake ; water lentils ; yield ; Wolffia sp. ; space plant biology ; astrobiology ; bioregenerative life support system (BLSS) ; biomass ; aquatic plants ; Araceae ; duckweeds ; Lemnoideae ; molecular phylogenetics ; taxonomy ; chlorophyll fluorescence imaging ; PAM fluorometry ; duckweed test ; Spirodela polyrhiza ; phytotoxicity ; hormesis ; interspecific hybrids ; tubulin-based polymorphism ; β-tubulin ; nitrogen assimilation ; nitrate reductase ; nitrite reductase ; glutamine synthetase ; GOGAT ; gene expression ; chlorophyll fluorescence ; electron transport chain ; inflammation ; lutein ; photosystem ; photosynthetic capacity ; relative growth rate ; duckweed-associated bacteria ; Microbacterium ; Azospirillum ; auxin ; AXR1 ; Arabidopsis ; amplified fragment length polymorphism (AFLP) ; biodiversity ; intraspecific diversity ; Lemna minor ; population analysis ; Wolffiella hyalina ; red/blue ratio ; standardized production ; light quality ; light quantity ; controlled environment ; sustainable fish feed ; alternative proteins ; on-growing phase ; barcoding ; chloroplast DNA ; molecular evolution ; aquaponics ; steroid 17β-estradiol ; Scenedesmus quadricauda ; Lemna minor ; fish wastewater ; population growth ; biomolecule synthesis ; machine learning ; image analysis ; machine training ; Lemna ; phytoremediation ; chromosome number ; evolution ; genome size ; karyotype ; microbiome ; 16S rRNA ; metagenome ; stress ; adhesion ; aquatic ; biomonitoring ; microplastics ; microbeads ; anaerobic digestate ; biomass generation ; genotyping ; intraspecific variation ; aquaculture effluents ; IMTA ; RAS ; phytoplankton ; bacteria ; Lemnacea ; alternative protein ; water recovery ; continuous systems ; giant duckweed ; Lymnaea stagnalis ; great pond snail ; microbiota ; adaptation ; herbivory ; tolerance ; resistance ; fatty acids ; DNA barcoding ; diversity ; biogeography ; nitrogen content ; protein concentration ; migration ; heavy metal ; metallothionein ; metal accumulation ; ionomics ; ICP-OES ; micro-XRF ; poly(styrene-co-methylmethacrylate) ; free-floating plant ; freshwater ; microplastic adsorption ; phytotoxic effect ; chronic impact ; manganese toxicity ; ammonium transporter ; transcription factors ; Spirodela ; water pollutants ; nitrogen ; phosphorus ; heavy metals ; agrochemicals wastewater remediation ; plant-microbe interactions ; plant-bacteria associations ; bacterial colonization ; RISA ; Azospirillum brasilense Sp7 ; Azospirillum brasilense Sp245 ; strain-specific primers ; bead-beating ; starch accumulation ; AtPSP1 overexpression ; sulfur deficiency ; Lemna turionifera 5511 ; whole genome sequencing ; abiotic stress management ; biotic stress management ; abiotic stress ; biotic stress ; turion ; Lemna gibba ; polyploidisation ; spontaneous mutation ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Following on from the Special Issue “Recent Advances and Contribution of Synthetic Aperture Radar (SAR) Applications for Agricultural Monitoring”, we concluded that SAR has now become a pivotal sensor for agricultural monitoring. In this Special Issue, you will find a variety of background material discussing SAR and its applications. Several papers focused on using machine learning approaches with SAR to monitor crop stages and classify crops, while others focused on the polarimetric mode to estimate crop height. Going forward, we hope that you will find this Special Issue to be a useful reference.
    Keywords: monsoon cropland ; Sentinel ; smallholders ; Google Earth Engine ; SAR ; India ; tropical agricultural monitoring ; canopy development analysis ; phenology retrieval ; Sentinel-1 ; multitemporal SAR ; multi-task machine learning ; crop development ; remote sensing ; productivity indicators ; wheat ; growth dynamics ; synthetic aperture radar ; Sentinel-1A ; rice detection ; time-series data ; rice growth-related features ; crop height ; RADARSAT-2 ; corn ; Synthetic Aperture Radar (SAR) ; PolSAR ; machine learning ; RFR ; SVR ; agriculture ; temporal composite ; object-oriented ; crop classification ; crop monitoring ; polarimetry ; decomposition ; field variability ; crop parameters ; multitemporal analysis ; crop identification ; parcel-based classification ; Common Agricultural Policy ; dual-pol ; crop characterization ; phenology ; unsupervised classification ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-07-14
    Description: Human activity recognition (HAR) and human behavior recognition (HBR) play increasingly important roles in the digital age. High-quality sensory observations applicable to recognizing users’ activities and behaviors, including electrical, magnetic, mechanical (kinetic), optical, acoustic, thermal, and chemical biosignals, are inseparable from sensors’ sophisticated design and appropriate application. Traditional sensors suitable for HAR and HBR, including external sensors for smart homes, optical sensors such as cameras for capturing video signals, and bioelectrical, biomagnetic, and biomechanical sensors for wearable applications, have been studied and verified adequately. They continue to be researched in depth for more effective and efficient usage, and brand-new areas facilitated by sensor-based HAR/HBR are emerging, such as interactive edutainment, single-motion duration analysis, time series information retrieval, handcrafted and high-level feature design, and fall detection. Meanwhile, innovative sensor research for HAR or HBR is also very active in the academic community, including new sensors appropriate for HAR/HBR, new designs and applications of the above-mentioned traditional sensors, and the usage of non-traditional HAR-/HBR-related sensor types, among others.
    Keywords: human activity recognition ; validation methodology ; leave-one-subject-out cross-validation ; explainable methods ; Shapley additive explanations ; machine learning ; camera calibration ; point-to-point camera distortion calibration ; vision-based human activity recognition ; speckle pattern ; digital image correlation ; sensing technique ; HAR ; semi-supervised learning ; adversarial learning ; syn-LSTM ; smart home ; Wi-Fi sensing ; multi-location ; deep complex network ; ankle–foot orthoses ; energy consumption ; functional electrical stimulation ; human in the loop ; smart retail ; in-store camera ; customer behavior recognition ; behavior reconstruction ; indoor localization ; pedestrian dead reckoning ; deep learning ; GPS ; domain generalization ; accelerometer ; psychological stress ; electrocardiogram ; heart rate variability ; gated recurrent unit ; VR high-altitude experiment ; wearable devices ; n/a ; bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBG Medical equipment & techniques
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This reprint explores the latest developments and advancements in the application of artificial intelligence (AI) and machine learning (ML) for forecasting and optimization in the field of power engineering. In recent years, AI and ML methods have been gaining significant traction and are becoming two of the most important fields in computing. These methods have proven to be effective in solving forecasting and optimization problems in power engineering. The topics covered in the chapters fall into four categories: electricity demand forecasting, wind power forecasting, photovoltaic power forecasting, and optimization.
    Keywords: hybrid AC/DC microgrid ; optimization of configuration and operating states ; CLONALG ; modified hypermutation operator ; wind energy ; wind farm ; ensemble methods ; short-term forecasting ; electric energy production ; machine learning ; deep neural network ; swarm intelligence ; voltage control ; voltage quality ; renewable energy ; metaheuristic optimisation ; medium voltage ; Q(U) characteristics ; microgrids ; operation control ; power generation ; PV system ; very-short-term forecasting ; interval type-2 fuzzy logic system ; distribution of electric power ; distributed storage and generation ; smart grids ; power distribution reliability ; information and communication technology ; energy efficiency ; cooling towers ; chillers ; evolutionary multi-objective optimization ; mid-term forecast ; e-mobility ; electric vehicles (EVs) ; power system demand ; load profile forecast ; machine learning (ML) ; electricity load forecasting ; bootstrap aggregating ; singular spectrum analysis ; time series forecasting ; calendar variation ; electrical power demand ; power systems ; autoregressive forecasting methods ; classical forecasting methods ; artificial intelligence methods ; Big Data ; Data Mining ; auto-regressive integrated moving average (ARIMA) ; long short-term memory (LSTM) ; Optuna ; isolation forest (IF) ; elliptic envelope (EE) ; one-class support vector machine (OCSVM) ; neuromorphic computing ; spiking neural network ; short-term wind power forecasting ; random forest ; regression tree ; pattern representation of time series ; short-term load forecasting ; transfer learning ; wind power ; photovolatic power ; autoencoders ; deep learning ; time series ; wind power prediction ; hybrid methods ; time series analysis ; forecasting error ; evaluation criteria metrics ; wind power forecasting ; wind turbine ; statistical analysis of errors ; medium-term load forecasting ; pattern-based forecasting ; time-series preprocessing ; photovoltaic (PV) ; forecast ; behind-the-meter (BTM) ; spatio-temporal ; strategic training ; deep neural networks ; LSTM ; time series prediction ; optimisation ; GA ; PSO ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: Modernization in the agriculture sector is important to ensure food security and poverty alleviation, which are the primary themes of UN-SDGs. There are many challenges in developing advanced agricultural techniques, tools, and systems, by which sustainable agriculture and food security can be satisfied. Worldwide, agricultural mechanization and modernization can be attained with advancements in agricultural engineering technologies and their associated applications. The concept is directly linked to the technological advancements in agricultural automation and robotics; precision agriculture; high-efficiency irrigation systems; farm energy systems; handling, storage, and processing of agricultural products; livestock and poultry sheds; farm water/wastewater management; biomass, biogas, and biochar; remote sensing and geographical studies; societal aspects in agriculture; and the associated bioenvironment. Such advances in agricultural engineering technologies and applications are the need of the 21st century, particularly from the viewpoint of the agricultural water–energy–food security nexus. Therefore, this Special Issue comprises original research and review studies in the abovementioned research areas.
    Keywords: wet rice ; adhesion ; hot airflow ; dispersion characteristic ; minimum suspension speed ; surface water content ; pipe diameter ; operation frequency ; genetic algorithm ; rotation irrigation sectoring ; irrigation cost ; energy cost ; network cost ; pick-up device ; stretchable style ; kinematical analysis ; seedling picking test ; cropping pattern ; water stress ; LCC area ; surface water availability ; CROPWAT ; Ananas comosus ; somatic embryogenesis ; micropropagation ; organogenesis ; SSR markers ; ISSR markers ; pineapple ; cantaloupe bowl seedlings transplanting ; mechanical equipment ; institutional design ; field test ; data analysis and discussion ; up-cut rotary blade ; edge curve ; Cyperus esculentus plant ; flexible model ; arch shed ; automatic cuttage ; force feedback ; simulation design ; trajectory planning ; Chrysanthemum indicum L. ; maximum shear force ; finite element ; calibration ; single-bud ; billet planter ; planting uniformity ; numerical simulation ; seed-filling ; single-bud billet ; seed-metering ; EDEM ; wheel-track high clearance chassis ; walking performance ; climbing angle ; simulation ; rape windrower ; longitudinal axial flow ; flexible ; millet threshing device ; staggered threshing element ; micro rotary tubular concave screen ; machine learning ; deep learning ; plant leaf diseases ; photovoltaic module ; LED lighting system ; power grid ; step-up converter ; efficient power take-off ; monitoring system ; Codonopsis planting ; ditching device ; working parameters ; EDEM simulation ; orthogonal test ; air-blast sprayer ; precision spraying ; spray control parameter ; three-factor regression analysis ; highly efficient soil return ; liquid fertilizer deep application technique ; DEM ; soil bin test ; combine harvester ; differential inverse gearbox ; order analysis ; fault diagnosis method ; fatigue test ; tractor ; diesel engine ; emission ; artificial neural network ; improved particle swarm algorithm ; computational fluid dynamics (CFD) ; eave height ; natural ventilation ; venlo greenhouse ; fertilization uniformity ; closed-loop control ; single-chip microcomputer ; fuzzy PID ; solid-fertilizer-dissolving device ; precision fertilizer application ; BP neural network ; PSO optimization algorithm ; PID control ; watermelon ; sonication ; microwave ; synergistic effects ; quality characteristics ; electro-hydraulic hitch system ; tillage depth adjustment ; tillage depth control algorithm ; key components ; maize ; soil ; cavity planter ; interaction mechanism ; verification ; ultrasonic sensor ; canopy leaf area density ; ultrasonic echo signal ; verification experiment ; potato planter ; soil cultivation ; mechanization ; seed metering device ; intelligent seeding ; broiler house ; building energy simulation ; forecasting system ; heat stress index ; temperature humidity index (THI) ; smart agriculture ; greenhouse technologies ; artificial intelligence ; agricultural waste ; nano-activated carbon ; adsorption ; wastewater treatment ; modification ; agricultural engineering ; irrigation and drainage system ; pumping station ; sump ; hydraulic characteristics ; entropy production ; onion ; transplanting ; air-feeding seed discharge system ; seed tube ; gas-solid two-phase flow ; computer simulation ; discrete element method ; cotton stalk particles ; contact parameters ; response surface methodology ; image classification ; lightweight neural networks ; zea mays ; ECA attention ; CycleGAN ; tangential threshing ; vibration analysis ; FFT demodulation ; random vibration analysis ; bearing fault ; machine condition ; sustainable development goals ; agri-food security ; equality ; information and communication technologies ; technology 4.0 ; uplift resistance ; continuous pipe foundation ; single-span plastic greenhouse ; pipe connector ; vegetable greenhouses ; multi-arch greenhouses ; arch cross type ; resistance to the typhoon ; online non-destructive detection ; structure of plant stems ; ultrasonic feature ; feature extraction ; feature contribution ; backyard farming ; self-assembly ; vertical expansion ; factory in a box ; automated farming ; vertical farming ; sustainable farm ; aerogels ; porous materials ; agricultural activated carbon ; fine-grained ; attention mechanism ; maturity classification ; open-world ; solar air heater (SAH) ; computational fluid dynamics ; performance optimization ; milk powder ; agricultural drying ; post-harvest losses ; spices ; paneer ; storage ; proximate ; composition ; sensory evaluation ; antioxidant potential ; environmental monitoring ; imputation ; pig house ; recurrent neural network ; agriculture advancement ; large scale solar ; natural cooling ; agrivoltaic ; sustainability ; tractor-trailer ; trajectory tracking ; prescribed performance ; model predictive control ; robust sliding mode control ; stubble-crushing ; plain straight blade ; DEM-CFD ; dynamic motion ; seedbed preparation ; strip tillage ; energy saving ; F-ASHP model ; nursery pig ; storage pen ; Simulink ; industrial hemp ; bionic blade ; cutting energy consumption ; parameter optimization ; conservation tillage technology ; adoption of time persistence ; nonparametric K-M survival analysis method ; discrete duration model ; cavitation ; pretreatment ; jet-driven Helmholtz oscillator ; anaerobic digestion ; tea bud detection ; YOLOv5 ; depth camera ; pose estimation ; CAM ; OPVSM ; prediction models ; hyperspectral image ; PLSR model ; AdaBoost ; XGBoost ; LightGBM ; agricultural sensor network ; EMP-ZBR ; network topology ; routing transmission algorithm ; UV-A LED ; laser fly control ; light trap ; fungus gnats ; mushroom pests ; corn seeds ; collision recovery coefficient ; static friction coefficient ; multi-point collision ; sound waveform ; characteristic dimensions ; bulb tubular pump ; bulb form ; optimization design ; hydraulic performance ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-28
    Description: Energy and its economic implications have been in the spotlight of policymakers, academics, traders, speculators and the industry for decades now. It has been an active research topic for more than 150 years. From the 19th century, the problem of creating, processing, storing and transporting energy was well defined. The issues of efficiently producing, pricing, distributing, and forecasting the demand, supply and prices of energy-related products and services are central to most modern economies irrespective of their level of development. These issues are apparent in times of relative tranquility in the respective markets but become central for all stakeholders in times of turbulence. This volume focuses on emerging methodologies of analysis, description, modelling, and forecasting in the topical area of Energy Economics. Includes emerging and innovative methodological approaches from the areas of machine learning, artificial intelligence, econometrics, and statistics aimed to model, describe or forecast the energy markets at all levels. Additionally, the volume also presents a bibliographical review, summarizes and compares results of different studies in the energy-sustainable economic growth and development nexus. The practical importance of the results to all energy market stakeholders in terms of regulating, pricing, and distributing energy is evident. Theoretical robustness, methodological innovation, and possible direct applicability of the conclusions were the basic requirements for research work to be included in this publication.
    Keywords: economic growth ; innovation activity ; globalization ; international trade ; uncertainty ; spillovers ; realized variance ; crude oil ; forecasting ; bibliometric analysis ; development economics ; energy ; renewable energy ; energy-growth nexus ; sustainable economy ; new economics ; critical review ; natural gas ; spot price ; machine learning ; energy commodities ; financial crises ; Brent ; WTI ; gasoline ; clustering ; t-SNE ; COVID-19 pandemic ; target model ; Greek wholesale electricity market ; day-ahead market ; intraday market ; balancing market ; trading volumes ; COVID-19 ; pandemic ; energy market volatility ; announcements ; deaths ; infections ; load forecasting ; load series ; mode decomposition ; extreme learning machine ; kernel density estimation ; geopolitical risk ; renewable energy sources ; energy production ; ARDL ; GDP ; CO2 emissions ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general ; thema EDItEUR::P Mathematics and Science::PH Physics
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-11-30
    Description: The reprint presents a collection of systems biology-related topics and new studies that utilize computational, mathematical, and systems-oriented approaches to reveal important aspects of various biological problems.
    Keywords: differential entropy ; discrete entropy ; geometrical information ; heterogeneity ; information theory ; cell death ; apoptosis ; necroptosis ; ferroptosis ; pyroptosis ; immunogenic cell death ; regulatory networks ; death execution pathways ; mathematical models ; computational analysis ; mathematical modeling ; artificial neural networks ; numerical solutions ; delay differential equations ; optimization techniques ; machine learning ; Levenberg—Marquardt algorithm ; HPA axis ; Major Depressive Disorder ; stress test ; Python ; Verification & Validation ; differential equations model ; reversible code ; gray map ; DNA codes ; mathematical model ; fractional order ; Caputo ; cholera ; well-posedness ; saturated incidence rate ; asymptotic stability ; batch fermentation ; in silico experimentation ; Kluyveromyces marxianus ; nonlinear data fitting ; nonlinear mechanistic model ; reaction–diffusion models in morphogenesis ; pattern formation ; developmental gene regulatory networks ; Alan Turing ; Eric Davidson ; evolutionary origins ; critical learning period ; liquid state machine ; reservoir computing ; echo state network ; stochastic simulation algorithm ; stochastic biochemical systems ; sensitivity analysis ; finite-difference methods ; parameter subset selection ; estimability analysis ; biophysical modeling ; radiation-induced DNA damage ; system size expansion ; DNA damage repair ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: Machine learning and deep learning have made tremendous progress over the last decade and have become the de facto standard across a wide range of image, video, text, and sound processing domains, from object recognition to image generation. Recently, deep learning and deep reinforcement learning have begun to develop end-to-end training to solve more complex operation research and combinatorial optimization problems, such as covering problems, vehicle routing problems, traveling salesman problems, scheduling problems, and other complex problems requiring general simulations. These methods also sometimes include classic search and optimization algorithms for machine learning, such as Monte Carlo Tree Search in AlphaGO. The present reprint contains all of the articles accepted and published in the Special Issue of Mathematics entitled "Advances in Machine Learning and Mathematical Modeling for Optimization Problems”. The articles presented in this Special Issue provide insights into related fields, including models, performance evaluation and improvements, and application developments. We hope that readers will benefit from the insights of these papers and contribute to these rapidly growing areas. We also hope that this Special Issue will shed light on major developments in the area of machine learning and mathematical modeling for optimization problems and that it will attract the attention of the scientific community to pursue further investigations, leading to the rapid implementation of these techniques.
    Keywords: machine learning ; deep reinforcement learning ; evolutionary computation ; artificial neural networks (ANNs) ; end-to-end learning ; feature selection ; statistical learning ; convex minimization problems ; optimization problems ; decision theory ; traveling salesman problem ; resource allocation ; vehicle routing problem ; pickup and delivery ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-09-11
    Description: As base metals, zinc and lead are widely developed in various types of deposits. Zinc and lead also form various types of independent deposits and are associated with a variety of critical metals. Zn-Pb deposits occupy an important position in the world, including volcanic-hosted massive sulphide (VHMS/VMS), magmatic–hydrothermal-associated skarn and/or epithermal types, sediment-hosted types (e.g., clastic-hosted sedimentary exhalative, SEDEX; carbonate-hosted Mississippi Valley type, MVT; sandstone-hosted type, SST; and shale-hosted type), and hydrothermal vein types. This Special Issue reprint aims to provide a comprehensive understanding of Zn-Pb deposits and associated critical metals, and promote global prospecting.
    Keywords: machine learning ; sphalerite ; LA–ICP–MS ; Pb–Zn deposits ; web app ; fault structure ; dispersed metals ; fractal structure characteristic ; Fry analysis ; prospecting direction ; eastern Guizhou metallogenic belt ; SW China ; 3D deposit model ; weight of evidence method ; neural network method ; metallogenic prediction ; the Dulong Sn-Zn polymetallic deposit ; Sichuan–Yunnan–Guizhou Pb-Zn metallogenic province ; Lekai Pb-Zn deposit ; calcite/dolomite REE ; C–O–Mg isotope ; metallogenic fluid source ; in situ S and Pb isotopes ; the source of ore-forming elements ; ore genesis ; Caiyuanzi Pb–Zn deposit ; porosity ; permeability ; lead–zinc ore ; Huize ; altered wall rocks ; in situ S isotope ; elemental geochemistry ; pyrite ; Fule Pb-Zn deposit ; northeast Yunnan ; China ; Banbianjie Ge-Zn deposit ; gangue minerals ; nature ; source and evolution of ore-forming fluids ; trace elements ; Western Hunan–Eastern Guizhou Pb-Zn metallogenic belt ; garnet ; granite porphyry ; ore-forming age ; tectonic setting ; in-site trace elements ; substitution mechanisms ; Nanmushu Zn–Pb deposit ; Mayuan district ; Mississippi Valley-type (MVT) deposit ; smithsonite ; ore deposit genesis ; supergene oxidation ; Huoshaoyun deposit ; resistivity ; chargeability ; mineral exploration ; 2D and 3D inversion ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::R Earth sciences, geography, environment, planning
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