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The domain of human locomotion identification through smartphone sensors is witnessing rapid expansion within the realm of research. This domain boasts significant potential across various sectors, including healthcare, sports, security systems, home automation, and real-time location tracking. Despite the considerable volume of existing
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The domain of human locomotion identification through smartphone sensors is witnessing rapid expansion within the realm of research. This domain boasts significant potential across various sectors, including healthcare, sports, security systems, home automation, and real-time location tracking. Despite the considerable volume of existing research, the greater portion of it has primarily concentrated on locomotion activities. Comparatively less emphasis has been placed on the recognition of human localization patterns. In the current study, we introduce a system by facilitating the recognition of both human physical and location-based patterns. This system utilizes the capabilities of smartphone sensors to achieve its objectives. Our goal is to develop a system that can accurately identify different human physical and localization activities, such as walking, running, jumping, indoor, and outdoor activities. To achieve this, we perform preprocessing on the raw sensor data using a Butterworth filter for inertial sensors and a Median Filter for Global Positioning System (GPS) and then applying Hamming windowing techniques to segment the filtered data. We then extract features from the raw inertial and GPS sensors and select relevant features using the variance threshold feature selection method. The extrasensory dataset exhibits an imbalanced number of samples for certain activities. To address this issue, the permutation-based data augmentation technique is employed. The augmented features are optimized using the Yeo–Johnson power transformation algorithm before being sent to a multi-layer perceptron for classification. We evaluate our system using the K-fold cross-validation technique. The datasets used in this study are the Extrasensory and Sussex Huawei Locomotion (SHL), which contain both physical and localization activities. Our experiments demonstrate that our system achieves high accuracy with 96% and 94% over Extrasensory and SHL in physical activities and 94% and 91% over Extrasensory and SHL in the location-based activities, outperforming previous state-of-the-art methods in recognizing both types of activities.
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Tubular joints are important connecting parts of a welded steel tube structure. The S-N curves based on the hot spot stress (HSS) method are often used to evaluate the fatigue life of tubular joints in practical engineering. The stress concentration factor (SCF) is
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Tubular joints are important connecting parts of a welded steel tube structure. The S-N curves based on the hot spot stress (HSS) method are often used to evaluate the fatigue life of tubular joints in practical engineering. The stress concentration factor (SCF) is a key parameter to calculate HSS. In this paper, stress concentration tests of hollow-section and concrete-filled double-skin tubular (CFDST) K-joints were carried out, respectively, and then finite element models of K-joints considering the weld were established. The developed models were validated with the experimental results. The influence of key geometrical parameters, such as the diameter ratio of brace to chord β, the diameter to thickness ratio of chord γ, the wall thickness ratio of brace to chord τ, brace angle θ, and hollow section ratio ζ on the distribution and key position of SCFs along the weld toe, was discussed. Parametric studies were conducted to obtain the calculating equations for the SCF values of CFDST K-joints. The results demonstrate that infill concrete can effectively reduce SCFs along the weld on the chord. When the hollow section ratio was reduced to 0.317, the SCF was reduced by 77.2%. Notably, the SCF reduction rate was sensitive to γ and θ, with a decrease observed as γ increased. The hollow section ratio ζ had a less pronounced effect on SCF distribution patterns, but as ζ decreased, the chord’s stiffness improved, suggesting a potential approach to enhance joint performance. The distribution of SCFs is similar for joints of the same type but different geometric configurations. The innovatively integrated hollow section ratio in the CFDST design equation significantly simplifies and enhances the precision of SCF calculations for CFDST K-joints.
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This study introduces an advanced algorithm for intelligent vehicle target detection in hazy conditions, aiming to bolster the environmental perception capabilities of autonomous vehicles. The proposed approach integrates a hybrid convolutional module (HDC) into an all-in-one dehazing network, AOD-Net, to expand the perceptual
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This study introduces an advanced algorithm for intelligent vehicle target detection in hazy conditions, aiming to bolster the environmental perception capabilities of autonomous vehicles. The proposed approach integrates a hybrid convolutional module (HDC) into an all-in-one dehazing network, AOD-Net, to expand the perceptual domain for image feature extraction and refine the clarity of dehazed images. To accelerate model convergence and enhance generalization, the loss function has been optimized. For practical deployment in intelligent vehicle systems, the ShuffleNetv2 lightweight network module is incorporated into the YOLOv5s network backbone, and the feature pyramid network (FPN) within the neck network has been refined. Additionally, the network employs a global shuffle convolution (GSconv) to balance accuracy with parameter count. To further focus on the target, a convolutional block attention module (CBAM) is introduced, which helps in reducing the network’s parameter count without compromising accuracy. A comparative experiment was conducted, and the results indicated that our algorithm achieved an impressive mean average precision (mAP) of 76.8% at an intersection-over-union (IoU) threshold of 0.5 in hazy conditions, outperforming YOLOv5 by 7.4 percentage points.
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In laser beam processing, the angle or offset between the auxiliary gas and the laser beam axis have been proved to be two new process optimization parameters for improving cutting speed and quality. However, a traditional electromechanical actuator cannot achieve high-speed and high-precision
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In laser beam processing, the angle or offset between the auxiliary gas and the laser beam axis have been proved to be two new process optimization parameters for improving cutting speed and quality. However, a traditional electromechanical actuator cannot achieve high-speed and high-precision motion control with a compact structure. This paper proposes a magnetic levitation actuator which could realize the 5-DOF motion control of a lens using six groups of differential electromagnets. At first, the nonlinear characteristic of a magnetic driving force was analyzed by establishing an analytical model and finite element calculation. Then, the dynamic model of the magnetic levitation actuator was established using the Taylor series. And the mathematical relationship between the detected distance and five-degree-of-freedom was determined. Next, the centralized control system based on PID control was designed. Finally, a driving test was carried out to verify the five-degrees-of-freedom motion of the proposed electromagnetic levitation actuator. The results show it can achieve a stable levitation and precision positioning with a desired command motion. It also proves that the proposed magnetic levitation actuator has the potential application in an off-axis laser cutting machine tool.
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The reuse and reincorporation of waste are the principles of circular economies. Compost, biofuels, animal feed, dyes, and bioactive compounds can be obtained from the revaluation of organic waste. Research on this subject is scarce and limited to specific sectors, such as agriculture
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The reuse and reincorporation of waste are the principles of circular economies. Compost, biofuels, animal feed, dyes, and bioactive compounds can be obtained from the revaluation of organic waste. Research on this subject is scarce and limited to specific sectors, such as agriculture and agroindustry, leaving aside others that generate large quantities of organic waste, such as floriculture. The remains of these sectors have a low decomposition rate compared to other organic wastes. They are a source of bioactive compounds (e.g., essential oils, pigments, phenols) that can be reincorporated into the production chain of various industries. This review describes the composition of waste from agroindustry, agriculture, and floriculture, analyzing their potential revalorization as a source of bioactive compounds and an alternative supply source.
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Community structure is a very interesting attribute and feature in complex networks, which has attracted scholars’ attention and research on community detection. Many single-objective optimization algorithms have been migrated and modified to serve community detection problems. Due to the limitation of resolution, the
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Community structure is a very interesting attribute and feature in complex networks, which has attracted scholars’ attention and research on community detection. Many single-objective optimization algorithms have been migrated and modified to serve community detection problems. Due to the limitation of resolution, the final algorithm implementation effect is not ideal. In this paper, a multi-objective community detection method based on a pigeon-inspired optimization algorithm, MOPIO-Net, is proposed. Firstly, the PIO algorithm is discretized in terms of the solution space representation, position, and velocity-updating strategies to adapt to discrete community detection scenarios. Secondly, by minimizing the two objective functions of community score and community fitness at the same time, the community structure with a tight interior and sparse exterior is obtained. Finally, for the misclassification caused by boundary nodes, a mutation strategy is added to improve the accuracy of the final community recognition. Experiments on synthetic and real networks verify that the proposed algorithm is more accurate in community recognition compared to 11 benchmark algorithms, confirming the effectiveness of the proposed method.
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This paper proposes the assessment of the impacts of using electric vehicles for urban service trips. In particular, the focus is on trips performed for delivering and installing products, as well as for reverse logistics. Such components of commercial traffic in urban areas
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This paper proposes the assessment of the impacts of using electric vehicles for urban service trips. In particular, the focus is on trips performed for delivering and installing products, as well as for reverse logistics. Such components of commercial traffic in urban areas have not received the level of attention it deserves. In fact, recent research on commercial traffic mainly deals with shop restocking, service visits to establishments and e-commerce deliveries, and limited attention has been paid to the service sector (e.g., installation, maintenance, repairs) which can have a high impact on city sustainability in terms of pollution emissions, congestion as well as land use for parking. Furthermore, pushed by the current trend towards the promotion of electric vehicles, an assessment is developed comparing potential service patterns using real data from the inner area of Rome (Italy) when the electric fleet replaces the traditional one. Results show the opportunity to decouple the delivery operation from the installation one, and to integrate service with reverse logistics. These significant results could address the adoption of suitable integrated urban policies to make the most of the opportunities arising from the use of electric vehicles.
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Spinal cord injury (SCI) can result in the permanent loss of mobility, sensation, and autonomic function. Secondary degeneration after SCI both initiates and propagates a hostile microenvironment that is resistant to natural repair mechanisms. Consequently, exogenous stem cells have been investigated as a
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Spinal cord injury (SCI) can result in the permanent loss of mobility, sensation, and autonomic function. Secondary degeneration after SCI both initiates and propagates a hostile microenvironment that is resistant to natural repair mechanisms. Consequently, exogenous stem cells have been investigated as a potential therapy for repairing and recovering damaged cells after SCI and other CNS disorders. This focused review highlights the contributions of mesenchymal (MSCs) and dental stem cells (DSCs) in attenuating various secondary injury sequelae through paracrine and cell-to-cell communication mechanisms following SCI and other types of neurotrauma. These mechanistic events include vascular dysfunction, oxidative stress, excitotoxicity, apoptosis and cell loss, neuroinflammation, and structural deficits. The review of studies that directly compare MSC and DSC capabilities also reveals the superior capabilities of DSC in reducing the effects of secondary injury and promoting a favorable microenvironment conducive to repair and regeneration. This review concludes with a discussion of the current limitations and proposes improvements in the future assessment of stem cell therapy through the reporting of the effects of DSC viability and DSC efficacy in attenuating secondary damage after SCI.
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The effective capture and recovery of radioiodine species associated with nuclear fuel reprocessing is of significant importance in nuclear power plants. Porous materials have been proven to be one of the most effective adsorbents for the capture of radioiodine. In this work, we
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The effective capture and recovery of radioiodine species associated with nuclear fuel reprocessing is of significant importance in nuclear power plants. Porous materials have been proven to be one of the most effective adsorbents for the capture of radioiodine. In this work, we design and synthesize a series of conjugated microporous polymers (CMPs), namely, TPDA–TFPB CMP, TPDA–TATBA CMP, and TPDA–TECHO CMP, which are constructed based on a planar rectangular 4-connected organic monomer and three triangular 3-connected organic monomers, respectively. The resultant CMPs are characterized using various characterization techniques and used as effective adsorbents for iodine capture. Our experiments indicated that the CMPs exhibit excellent iodine adsorption capacities as high as 6.48, 6.25, and 6.37 g g−1 at 348 K and ambient pressure. The adsorption mechanism was further investigated and the strong chemical adsorption between the iodine and the imine/tertiary ammonia of the CMPs, 3D network structure with accessible hierarchical pores, uniform micromorphology, wide π-conjugated structure, and high-density Lewis-base sites synergistically contribute to their excellent iodine adsorption performance. Moreover, the CMPs demonstrated good recyclability. This work provides guidance for the construction of novel iodine adsorbent materials with high efficiency in the nuclear power field.
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Solar energy is one type of clean energy resource, and currently the IMO, EU and UK are targeting net zero carbon emissions by 2050. This paper delves into the integration of photovoltaic (PV) systems into hybrid vessels in order to meet their strategies
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Solar energy is one type of clean energy resource, and currently the IMO, EU and UK are targeting net zero carbon emissions by 2050. This paper delves into the integration of photovoltaic (PV) systems into hybrid vessels in order to meet their strategies and targets. The technical challenges that come with designing such systems as well as their economic and environmental impacts are examined. By optimizing the usage of harnessed solar energy, we discover the operational strategy that provides maximal benefits through day-to-day savings as well as over the 25 year lifespan of solar panels. It demonstrates impressive economic viability, with cost savings of up to GBP 4.55 per day and a payoff period as short as 9 years. It also displays a modest emission reduction of up to 8.002 kg of CO2, which serves as proof for a pathway to greener practices in the maritime industry. This report highlights the operational flexibility that a hybrid vessel possesses once paired with a PV system through the ability to withstand regulatory and market changes. Also, when looking ahead, further adoption of PV technology creates opportunities for innovation in adopting renewable energy solutions in maritime transportation.
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The unidirectional hybrid three-phase rectifier (UHTR) with Boost converter consists of two different rectifiers (Rectifier 1 and 2), where Rectifier 2 consists of modules corresponding to the phases. Each rectifier processes different part of the current waveform at the input, so that the
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The unidirectional hybrid three-phase rectifier (UHTR) with Boost converter consists of two different rectifiers (Rectifier 1 and 2), where Rectifier 2 consists of modules corresponding to the phases. Each rectifier processes different part of the current waveform at the input, so that the sum of the current waveform parts is sinusoidal, or multilevel. Analyzing existing literature, the UHTR with Boost converter and isolation transformer, is proven as a classic solution with high weight, volume and cost. Therefore, in 2019 the UHTR with Boost converter was proposed, without any isolation transformer. To do this, it was necessary to replace the Boost inductor of each Rectifier 2 module with a coupled inductor. However, the proposed UHTR has not described the coupled inductor in details, neither the control circuit and the decoupling of the power circuit with the control circuit were described. Therefore, this main objective this paper is to provide answers to those aspects, and consequently present the UHTR proposal in a more realistic and practical application way, thus favoring the implementation of the prototype. A simulation of the proposed UHTR with coupled inductor was performed in the PSIM version 12.0 software with a power of 20 kW. The results of the proposed UHTR show that there is no current interaction and it works correctly, having a high PF of 99.92% and low total harmonic distortion of 3.96% at full load. In this way, it is proven that it is possible to implement an UHTR with a Boost converter and using coupled inductor.
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This manuscript explores the use of lipid nanoparticles (LNPs) in addressing the pivotal challenges of lung cancer treatment, including drug delivery inefficacy and multi-drug resistance. LNPs have significantly advanced targeted therapy by improving the precision and reducing the systemic toxicity of chemotherapeutics such
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This manuscript explores the use of lipid nanoparticles (LNPs) in addressing the pivotal challenges of lung cancer treatment, including drug delivery inefficacy and multi-drug resistance. LNPs have significantly advanced targeted therapy by improving the precision and reducing the systemic toxicity of chemotherapeutics such as doxorubicin and paclitaxel. This manuscript details the design and benefits of various LNP systems, including solid lipid–polymer hybrids, which offer controlled release and enhanced drug encapsulation. Despite achievements in reducing tumor size and enhancing survival, challenges such as manufacturing complexity, biocompatibility, and variable clinical outcomes persist. Future directions are aimed at refining targeting capabilities, expanding combinatorial therapies, and integrating advanced manufacturing techniques to tailor treatments to individual patient profiles, thus promising to transform lung cancer therapy through interdisciplinary collaboration and regulatory innovation.
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The IEEE 802.11ah standard is introduced to address the growing scale of internet of things (IoT) applications. To reduce contention and enhance energy efficiency in the system, the restricted access window (RAW) mechanism is introduced in the medium access control (MAC) layer to
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The IEEE 802.11ah standard is introduced to address the growing scale of internet of things (IoT) applications. To reduce contention and enhance energy efficiency in the system, the restricted access window (RAW) mechanism is introduced in the medium access control (MAC) layer to manage the significant number of stations accessing the network. However, to achieve optimized network performance, it is necessary to appropriately determine the RAW parameters, including the number of RAW groups, the number of slots in each RAW, and the duration of each slot. In this paper, we optimize the configuration of RAW parameters in the uplink IEEE 802.11ah-based IoT network. To improve network throughput, we analyze and establish a RAW parameters optimization problem. To effectively cope with the complex and dynamic network conditions, we propose a deep reinforcement learning (DRL) approach to determine the preferable RAW parameters to optimize network throughput. To enhance learning efficiency and stability, we employ the proximal policy optimization (PPO) algorithm. We construct network environments with periodic and random traffic in an NS-3 simulator to validate the performance of the proposed PPO-based RAW parameters optimization algorithm. The simulation results reveal that using the PPO-based DRL algorithm, optimized RAW parameters can be obtained under different network conditions, and network throughput can be improved significantly.
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Untreated or inadequately treated silver−containing wastewater may pose adverse effects on hu−man health and the ecological environment. Currently, significant progress has been made in the treatment of Ag(I) in wastewater using adsorption methods, with adsorbents playing a pivotal role in this process. This
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Untreated or inadequately treated silver−containing wastewater may pose adverse effects on hu−man health and the ecological environment. Currently, significant progress has been made in the treatment of Ag(I) in wastewater using adsorption methods, with adsorbents playing a pivotal role in this process. This paper provides a systematic review of various adsorbents for the recovery and treatment of Ag(I) in wastewater, including MOFs, COFs, transition metal sulfides, metal oxides, biomass materials, and other polymeric materials. The adsorption mechanisms of these materials for Ag(I) are elaborated upon, along with the challenges currently faced. Furthermore, insights into optimizing adsorbents and developing novel adsorbents are proposed in this study.
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In order to produce detergents with improved performance and good market acceptability, it is crucial to develop formulations with improved foamability and cleaning performance. The use of a delicate balance of surfactants and additives is an appealing strategy to obtain good results and
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In order to produce detergents with improved performance and good market acceptability, it is crucial to develop formulations with improved foamability and cleaning performance. The use of a delicate balance of surfactants and additives is an appealing strategy to obtain good results and enables a reduction in the amount of chemicals used in formulations. Mixtures of hydrophobically modified linear polymers and surfactants, as well as balanced mixtures with co-surfactants and/or hydrotropes, are the most effective parameters to control foamability and foam stability. In the present study, the effect of the addition of hydrophobically modified linear polymers, nonionic co-surfactants and hydrotropes, and their mixtures to anionic and zwitterionic surfactant aqueous solutions was evaluated. It was found that the presence of the hydrophobically modified polymer (HM-P) prevented the bubbles from bursting, resulting in better stability of the foam formed using zwitterionic surfactant solutions. Also, the surfactant packing was inferred to be relevant to obtaining foamability. Mixtures of surfactants, in the presence of a co-surfactant or hydrotrope led, tendentially, to an increase in the critical packing parameter (CPP), resulting in higher foam volumes and lower surface tension for most of the studied systems. Additionally, it was observed that the good cleaning efficiency of the developed surfactant formulations obtained a higher level of fat solubilization compared to a widely used brand of commercial dishwashing detergent.
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Introduction: Chyloperitoneum arises from lymph leakage into the abdominal cavity, leading to an accumulation of milky fluid rich in triglycerides. Diagnosis can be challenging, and mortality rates vary depending on the underlying cause, with intestinal volvulus being just one potential acute cause. Despite
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Introduction: Chyloperitoneum arises from lymph leakage into the abdominal cavity, leading to an accumulation of milky fluid rich in triglycerides. Diagnosis can be challenging, and mortality rates vary depending on the underlying cause, with intestinal volvulus being just one potential acute cause. Despite its rarity, our case series highlights chyloperitoneum associated with non-ischemic small bowel volvulus. The aims of our study include assessing the incidence of this association and evaluating diagnostic and therapeutic approaches. Material and Methods: We present two cases of acute abdominal peritonitis with suspected small bowel volvulus identified via contrast-enhanced computed tomography (CT). Emergency laparotomy revealed milky-free fluid and bowel volvulus. Additionally, we conducted a systematic review up to 31 October 2023, identifying 15 previously reported cases of small bowel volvulus and chyloperitoneum in adults (via the PRISMA scheme). Conclusions: Clarifying the etiopathogenetic mechanism of chyloperitoneum requires specific diagnostic tools. Magnetic resonance imaging (MRI) may be useful in non-emergency situations, while contrast-enhanced CT is employed in emergencies. Although small bowel volvulus infrequently causes chyloperitoneum, prompt treatment is necessary. The volvulus determines lymphatic flow obstruction at the base of the mesentery, with exudation and chyle accumulation in the abdominal cavity. Derotation of the volvulus alone may resolve chyloperitoneum without intestinal ischemia.
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Silicon is the most commonly used material in the microelectronics industry, due to its inherent advantages of high natural abundance, low cost, and high purity, coupled with the chemical and electrical stability at the interface with its oxide. For molecular electronics applications, oxide-free
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Silicon is the most commonly used material in the microelectronics industry, due to its inherent advantages of high natural abundance, low cost, and high purity, coupled with the chemical and electrical stability at the interface with its oxide. For molecular electronics applications, oxide-free Si surfaces are widely used because of the relative ease of removing the oxide (SiOx) by chemical means, yielding a surface which forms strong covalent bonds with a wide range of chemical functional groups; another advantage is that these surfaces remain oxide-free in the absence of oxidising agents. Standard procedures require the use of either HF, NH4F, or a mixture of both as the etching solution; however, these two chemicals are highly corrosive and toxic, posing a significant risk to the experimentalist. Here, we report that for silicon wafers etched by using potassium fluoride, a less toxic chemical, the resulting surface is free of oxides and can be functionalized by self-assembled monolayers of 1,8-nonadiyne. To demonstrate this, Si/SiOx wafers were etched by using either KF or NH4F, followed by hydrosilylation with 1,8-nonadiyne and a click reaction of the terminal alkyne with azidomethylferrocene. The surface coverages and electron transfer kinetics of the ferrocene-terminated KF-etched surfaces are comparable to those formed by acidic fluoride etching procedures. This is the first study comparing the differences between surfaces functionalized by self-assembled monolayers of 1,8-nonadiyne which were etched by KF and NH4F. KF could be used as a replacement chemical for etching silicon wafers when a less corrosive and toxic chemical is required.
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A variable pressure differential fuzzy control method is proposed based on the online identification method for key parameters and the fuzzy subset inference fuzzy control method of the chilled water system network model. Firstly, a phase plane fuzzy identification method is proposed for
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A variable pressure differential fuzzy control method is proposed based on the online identification method for key parameters and the fuzzy subset inference fuzzy control method of the chilled water system network model. Firstly, a phase plane fuzzy identification method is proposed for the most unfavorable thermal loop. The study focuses on analyzing the trend of room temperature deviation and deviation change in different quadrants in the phase plane. Furthermore, we establish a chilled water pipe network model that recalculates flow variation in both the main pipe and each branch pipe section to eliminate the most unfavorable thermal loop. Finally, the test platform for the fan coil variable flow air conditioning water system was designed and constructed to meet the requirements of energy-saving regulation. Additionally, the network monitoring system for the test platform was completed. The calibration and debugging results demonstrate that the monitoring error is within ±5.0%, ensuring precise control of room temperature at the end of the branch within ±0.5 °C. Results demonstrate that our novel method exhibits superior stability in room temperature control compared to traditional linear variable pressure differential set point controls while achieving energy saving ranging from 4.7% to 6.5%.
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by
Guillermo De Grau-Bassal, Mireia Mallandrich, Lilian Sosa, Lupe Espinoza, Ana Cristina Calpena, Núria Bozal-de Febrer, María J. Rodríguez-Lagunas, María L. Garduño-Ramírez and María Rincón
Pharmaceutics2024, 16(5), 643; https://doi.org/10.3390/pharmaceutics16050643 (registering DOI) - 10 May 2024
Recently, the number of people acquiring tattoos has increased, with tattoos gaining significant popularity in people between 20 and 40 years old. Inflammation is a common reaction associated with tattooing. The purpose of this study was to evaluate a nanostructured lipid carrier loading
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Recently, the number of people acquiring tattoos has increased, with tattoos gaining significant popularity in people between 20 and 40 years old. Inflammation is a common reaction associated with tattooing. The purpose of this study was to evaluate a nanostructured lipid carrier loading pranoprofen (PRA-NLC) as a tattoo aftercare formulation to reduce the inflammation associated with tattooing. In this context, the in vitro drug release and the ex vivo permeation-through-human-skin tests using Franz cells were appraised. The tolerance of our formulation on the skin was evaluated by studying the skin’s biomechanical properties. In addition, an in vivo anti-inflammatory study was conducted on mice skin to evaluate the efficacy of the formulation applied topically after tattooing the animals. PRA-NLC showed a sustained release up to 72 h, and the amount of pranoprofen retained in the skin was found to be 33.48 µg/g/cm2. The formulation proved to be well tolerated; it increased stratum corneum hydration, and no signs of skin irritation were observed. Furthermore, it was demonstrated to be non-cytotoxic since the cell viability was greater than 80%. Based on these results, we concluded that PRA-NLC represents a suitable drug delivery carrier for the transdermal delivery of pranoprofen to alleviate the local skin inflammation associated with tattooing.
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This paper proposes a solution to address the challenges of high storage and transport costs associated with using hydrogen () as an energy source. It suggests utilizing ammonia () as a hydrogen carrier to produce onsite for hydrogen gas turbines. offers higher volumetric
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This paper proposes a solution to address the challenges of high storage and transport costs associated with using hydrogen () as an energy source. It suggests utilizing ammonia () as a hydrogen carrier to produce onsite for hydrogen gas turbines. offers higher volumetric hydrogen density compared to liquid , potentially reducing shipping costs by 40%. The process involves pyrolysis, which utilizes the heat waste from exhaust gas generated by gas turbines to produce and nitrogen (). Numerical simulations were conducted to design and understand the behaviour of the heat recapture decomposition system. The design considerations included the concept of the number of transfer units and heat exchanger efficiency, achieving a heat recapture system efficiency of up to 91%. The simulation of decomposition was performed using ANSYS, a commercial simulation software, considering wall surface reactions, turbulent flow, and chemical reaction. Parameters such as activation energy and pre-exponential factor were provided by a study utilizing a nickel wire for decomposition experiments. The conversion of reached up to 94% via a nickel-based catalyst within a temperature range of 823 K to 923 K which is the exhaust gas temperature range. Various factors were considered to compare the efficiency of the system, including the mass flow of , operating gauge pressure, mass flow of exhaust gas, among others. Result showed that pressure would not affect the conversion of at temperatures above 800 K, thus a lower amount of energy is required for a compression purpose in this approach. The conversion is maintained at 94% to 97% when lower activation energy is applied via a ruthenium-based catalyst. Overall, this study showed the feasibility of utilizing convective heat transfer from exhaust gas in hydrogen production by pyrolysis, and this will further enhance the development of as the potential carrier for onsite production in hydrogen power generation.
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In this paper, we study the dynamic meal delivery routing problem (MDRP) with time-sensitive customers. The multi-objective MDRP optimization model is developed to maximize customer satisfaction and minimize delay penalty cost and riding cost. To solve the dynamic MDRP, a novel waiting strategy
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In this paper, we study the dynamic meal delivery routing problem (MDRP) with time-sensitive customers. The multi-objective MDRP optimization model is developed to maximize customer satisfaction and minimize delay penalty cost and riding cost. To solve the dynamic MDRP, a novel waiting strategy is proposed to divide the dynamic problem into a series of static subproblems. This waiting strategy utilizes the decision threshold to determine rerouting points based on the number of dynamic meal orders. Meanwhile, time-sensitive priority is introduced to accelerate assignment and routing decisions for orders from customers with high time sensitivity. For each static subproblem, a hybrid AGA–ALNS algorithm that incorporates the adaptive genetic algorithm and adaptive large neighborhood search is developed to improve both the global and local search capabilities of the genetic algorithm. We validate the performance of the proposed waiting strategy and the AGA–ALNS algorithm through numerical instances. In addition, managerial insights are obtained from sensitivity analysis experiments.
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Yellow pitahaya (Selenicereus megalanthus Haw.) is an exotic fruit with great potential for exportation in Ecuador. The research was carried out with the objective of evaluating the fruit growth and ripening as affected by four elicitors: salicylic acid (SA), methyl salicylate (MeSa),
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Yellow pitahaya (Selenicereus megalanthus Haw.) is an exotic fruit with great potential for exportation in Ecuador. The research was carried out with the objective of evaluating the fruit growth and ripening as affected by four elicitors: salicylic acid (SA), methyl salicylate (MeSa), methyl jasmonate (MeJa), and oxalic acid (OA), all of them at 1, 5, and 10 mM concentration, compared with untreated plants (control). For each elicitor, nine plants were selected, and on each plant, three fruits were marked to follow up the growth by measuring polar and equatorial diameters. At harvest, yield (kg plant−1 and number of fruits plant−1), fruit weight, percentage of pulp and skin, total soluble solids (TSS), titratable acidity (TA), and firmness were determined. Treated plants enhanced fruit size, crop yield, and fruit weight compared with control fruits, although results depended on the elicitor tested and applied doses. The highest and lowest TSS were found in 10 mM MeSa and 5 mM MeJa-treated fruit, respectively, while the highest TA content was shown in 5 mM SA. Firmness was only enhanced in MeJa-treated fruits. Overall, results suggest that preharvest use of elicitors could modulate the pitahaya ripening and could improve quality attributes at harvest.
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Fine chemicals are produced in small annual volume batch processes (often <10,000 tonnes per year), with a high associated price (usually >USD 10/kg). As a result of their usage in the production of speciality chemicals, in areas including agrochemicals, fragrances, and pharmaceuticals, the
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Fine chemicals are produced in small annual volume batch processes (often <10,000 tonnes per year), with a high associated price (usually >USD 10/kg). As a result of their usage in the production of speciality chemicals, in areas including agrochemicals, fragrances, and pharmaceuticals, the need for them will remain high for the foreseeable future. This review article assesses current methods used to produce fine chemicals with heterogeneous catalysts, including both well-established and newer experimental methods. A wide range of methods, utilising microporous and mesoporous catalysts, has been explored, including their preparation and modification before use in industry. Their potential drawbacks and benefits have been analysed, with their feasibility compared to newer, recently emerging catalysts. The field of heterogeneous catalysis for fine chemical production is a dynamic and ever-changing area of research. This deeper insight into catalytic behaviour and material properties will produce more efficient, selective, and sustainable processes in the fine chemical industry. The findings from this article will provide an excellent foundation for further exploration and a critical review in the field of fine chemical production using micro- and mesoporous heterogeneous catalysts.
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Metals
Biomolecules
Vaccines
Education Sciences
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Horticulturae
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JPM
Bioengineering
