ALBERT

Description: Machine learning is emerging nowadays as an important tool for decision support in many areas of research. In the field of education, both educational organizations and students are the target beneficiaries. It facilitates the educational sector in predicting the student’s outcome at the end of their course and for the students in deciding to choose a suitable course for them based on their performances in previous exams and other behavioral features. In this study, a systematic literature review is performed to extract the algorithms and the features that have been used in the prediction studies. Based on the search criteria, 2700 articles were initially considered. Using specified inclusion and exclusion criteria, quality scores were provided, and up to 56 articles were filtered for further analysis. The utmost care was taken in studying the features utilized, database used, algorithms implemented, and the future directions as recommended by researchers. The features were classified as demographic, academic, and behavioral features, and finally, only 34 articles with these features were finalized, whose details of study are provided. Based on the results obtained from the systematic review, we conclude that the machine learning techniques have the ability to predict the students’ performance based on specified features as categorized and can be used by students as well as academic institutions. A specific machine learning model identification for the purpose of student academic performance prediction would not be feasible, since each paper taken for review involves different datasets and does not include benchmark datasets. However, the application of the machine learning techniques in educational mining is still limited, and a greater number of studies should be carried out in order to obtain well-formed and generalizable results. We provide future guidelines to practitioners and researchers based on the results obtained in this work.

Description: Debris laser ranging (DLR) is receiving considerable attention as an accurate and effective method of determining and predicting the orbits of space debris. This paper reports some technologies of DLR, such as the high pulse repetition frequency (PRF) laser pulse, large-aperture telescope, telescope array, multi-static stations receiving signals. DLR with a picosecond laser at the Shanghai Astronomical Observatory is also presented. A few hundred laps of space debris laser-ranging measurements have been made. A double-pulse picosecond laser with an average power of 4.2 W, a PRF of 1 kHz, and a wavelength of 532 nm has been implemented successfully in DLR, it’s the first time that DLR technology has reached a ranging precision at the sub-decimeter level. In addition, the characteristics of the picosecond-pulse-width laser transmission with the advantages of transmission in laser ranging were analyzed. With a mode of the pulse-burst picosecond laser having high average power, the DLR system has tracked small debris with a radar cross-section (RCS) of 0.91 m2 at a ranging distance up to 1726.8 km, corresponding to an RCS of 0.1 m2 at a distance of 1000 km. These works are expected to provide new technologies to further improve the performance of DLR.

Description: Speaker recognition deals with recognizing speakers by their speech. Most speaker recognition systems are built upon two stages, the first stage extracts low dimensional correlation embeddings from speech, and the second performs the classification task. The robustness of a speaker recognition system mainly depends on the extraction process of speech embeddings, which are primarily pre-trained on a large-scale dataset. As the embedding systems are pre-trained, the performance of speaker recognition models greatly depends on domain adaptation policy, which may reduce if trained using inadequate data. This paper introduces a speaker recognition strategy dealing with unlabeled data, which generates clusterable embedding vectors from small fixed-size speech frames. The unsupervised training strategy involves an assumption that a small speech segment should include a single speaker. Depending on such a belief, a pairwise constraint is constructed with noise augmentation policies, used to train AutoEmbedder architecture that generates speaker embeddings. Without relying on domain adaption policy, the process unsupervisely produces clusterable speaker embeddings, termed unsupervised vectors (u-vectors). The evaluation is concluded in two popular speaker recognition datasets for English language, TIMIT, and LibriSpeech. Also, a Bengali dataset is included to illustrate the diversity of the domain shifts for speaker recognition systems. Finally, we conclude that the proposed approach achieves satisfactory performance using pairwise architectures.

Description: The North Railroad Avenue Plume, discovered in 1989, contained chlorinated solvent groundwater plumes extending over 23.5 hectares (58 acres) and three hydrostratigraphic units. The source contaminant, tetrachloroethene, stemmed from release at a dry cleaner/laundromat business. The anaerobic biodegradation byproducts trichloroethene, isomers of dichloroethene (DCE), and vinyl chloride were detected in groundwater samples collected prior to remedial action. The impacted aquifers are the sole source drinking water aquifers for the communities near the site. Following the remedial investigation and feasibility study, the selected alternative for full-scale remedial action at the site was enhanced reductive dichlorination (ERD) focused on four treatment areas: the shallow source zone, the shallow hotspot area, the shallow downgradient area, and the deep zone. Pilot testing, which was conducted in the source zone and hotspot areas, is the subject of this paper. The primary objectives of the pilot test were to obtain the necessary information to select an ERD treatment formulation, dose, and frequency of dosing for use during full-scale remedial action, as well as to refine the site’s hydrogeologic conceptual site model and design parameters. Four (4) test cells, each of which contained well pairs of injection and downgradient extraction wells, were used to test ERD bio-amendment formulations: ethyl lactate, dairy whey, emulsified vegetable oil (EVO), and a combination of EVO and a hydrogen gas infusion. A conservative tracer, bromide, was added to the recirculation flow to record tracer breakthrough, peak, and dissipation at extraction wells. The results of these dipole tracer tests were used to reassess the hydraulic conductivity and hydrodynamic dispersity used in the remedial design. In addition to water quality analyses of contaminants and substrates, groundwater samples were also analyzed for biological analyses before, during, and after the addition of bioamendment. Analyses of phospholipid fatty acids and deoxyribonucleic acid (DNA) extracts from fresh groundwater samples informed decisions on the capacity for complete ERD without DCE stalling and tracked the shifts in the bacterial and archaeal taxonomy and phylogeny stemming from the addition of bioamendments. The pilot test concluded that EVO was the most suitable, considering (1) support of the native microbial consortia for ERD, (2) mechanics and hydraulics of the remediation system, and (3) sustainability/retention of the substrate in the subsurface. Along with EVO, the addition of a nutrient broth derived from brewery waste accelerated and sustained the desired conditions and microbial diversity and population levels. The pilot test results were also used to assess the utilization kinetics of the injected substrates based on total organic carbon (TOC) concentrations measured in the groundwater. After determining that substrate utilization followed Monod kinetics, a TOC threshold at 300 milligrams per liter, equivalent to approximately twice its half-saturation constant was established. Full scale treatment dosing and dose frequency were designed around this threshold, assuming the maximum substrate utilization would yield optimum ERD.

Description: Faced with the biggest virus outbreak in a century, world governments at the start of 2020 took unprecedented measures to protect their healthcare systems from being overwhelmed in the light of the COVID-19 pandemic. International travel was halted and lockdowns were imposed. Many nations adopted measures to stop the transmission of the virus, such as imposing the wearing of face masks, social distancing, and limits on social gatherings. Technology was quickly developed for mobile phones, allowing governments to track people’s movements concerning locations of the virus (both people and places). These are called contact tracing applications. Contact tracing applications raise serious privacy and security concerns. Within Europe, two systems evolved: a centralised system, which calculates risk on a central server, and a decentralised system, which calculates risk on the users’ handset. This study examined both systems from a threat perspective to design a framework that enables privacy and security for contact tracing applications. Such a framework is helpful for App developers. The study found that even though both systems comply with the General Data Protection Regulation (GDPR), Europe’s privacy legislation, the centralised system suffers from severe risks against the threats identified. Experiments, research, and reviews tested the decentralised system in various settings but found that it performs better but still suffers from inherent shortcomings. User tracking and re-identification are possible, especially when users report themselves as infected. Based on these data, the study identified and validated a framework that enables privacy and security. The study also found that the current implementations using the decentralised Google/Apple API do not comply with the framework.

Description: Recent years have witnessed the advancement of the Internet of Things (IoT) and its emergence as a technology that could revolutionize many businesses. It helps considerably in creating data-driven business models with the insights it provides. IoT systems are deployed in data collection, monitor processes, provide insights and allow businesses to make data-driven productivity improvements. However, IoT systems are often experiencing data loss due to inevitable failures ranging from devices, networks, to the application layer, especially in scarce infrastructure resources environments. Data loss might be unrecoverable in many circumstances. As such, this research presents a blockchain based IoT model (framework) with the aim of circumventing data loss. We envisioned IoT blockchain technology in enhancing data veracity with data loss tolerance. That is, to have blockchain enhancing the IoT data veracity by leveraging on the features existed in its peer-to-peer network (P2P) and distributed ledger storage technology (DLT). Additionally, the edge computing of IoT blockchain technology is also conceptually workable; with intelligent small computing resources, it opens up a new era of bringing the intelligence of data collection, connectivity, computation and storage into the edge/device layer. A novel IoT blockchain strength monitoring system is also been studied to further enhance data veracity; this is achieved through a capacitance monitoring on the IoT blockchain system. The empirical results show that the proposed IoT blockchain with a strength monitoring model can alleviate data loss and thus enhance data veracity with data loss tolerance.

Description: This paper analyses the construction time and advance rate of a 3 km long drill and blast tunnel under various geological conditions using an upgraded NTNU drill and blast prediction model. The analysis was carried out for the five types of Korean tunnel supports according to the rock mass quality (from Type 1, meaning a very good rock mass quality; to Type 5, meaning a very poor rock mass quality). Four kinds of rock properties, as well as the rock mass quality, for each tunnel support type were applied to simulate different geological conditions based on previous studies and the NTNU model. The construction time was classified into five categories: basic, standard, gross, tunnel and total, according to the operation characteristics to more effectively analyse the time. In addition, to consider the actual geological conditions in tunnelling, the construction times for the three mixed geological cases were analysed. It was found that total construction time of a tunnel covering all the operations and site preparations with a very poor rock mass quality was more than twice that of a tunnel with a very good rock mass quality for the same tunnel length. It is thought that this study can be a useful approach to estimating the construction time and advance rate in the planning or design stage of a drill and blast tunnel.

Description: As more and more fields utilize deep learning, there is an increasing demand to make suitable training data for each field. The existing interactive object segmentation models can easily make the mask label data because these can accurately segment the area of the target object through user interaction. However, it is difficult to accurately segment the target part in the object using the existing models. We propose a method to increase the accuracy of part segmentation by using the proposed interactive object segmentation model trained only with edge images instead of color images. The results evaluated with the PASCAL VOC Part dataset show that the proposed method can accurately segment the target part compared to the existing interactive object segmentation model and the semantic part-segmentation model.

Description: Dynamic behavior modeling and parameter optimization of the spray boom based on multi-body vibration were developed to study the influence of the boom sprayer’s motion in a complex working environment on the dynamic behavior of the spray boom. First, a geometric continuous model of spray boom vibration was established considering the influence of the boom sprayer body and boom suspension. Then, the dynamic behavior of the spray boom under step excitation was studied on a SWAN3WP-500 self-propelled boom spray experimental platform. The time-domain response of spray boom movement was characterized using a multi-channel dynamic test system, and the simulation results of the geometric continuous model were verified. The correlation coefficient between the simulated and experimental results is 0.917, and the maximum relative error is 12.16%. Finally, the effects of boom sprayer speed, spray boom length, and spray boom cross-section shape on spray boom vibration were analyzed through the geometric continuous model. (1) The amplitude and period of vibration at the extremity of the spray boom gradually decline with a rise in boom sprayer speed. (2) The amplitude and period of vibration at the extremity of the spray boom gradually increase when the unilateral spray boom is shorter than 5 m but slowly decrease when it is longer than 5 m. To avoid excessive static elastic deformation of the spray boom, the length of the unilateral spray boom should be controlled within 6 m. (3) A reasonable cross-sectional shape can improve the spray boom vibration, and the spray boom with a type B cross-section can better inhibit the vertical vibration of the spray boom under the same cross-sectional area.

Description: The applicability of high voltage electrical discharges for the decomposition of CO2 has been extensively demonstrated. In this study, a new AC parallel-plate plasma reactor is presented which was designed for this purpose. Detailed experimental characterization and simulation of this reactor were performed. Gas chromatography of the exhaust gases enabled calculation of the CO2 conversion and energy efficiency. A conversion factor approximating 25% was obtained which is higher in comparison to existing plasma sources. Optical emission spectroscopy enabled the determination of the emission intensities of atoms and molecules inside the plasma and characterization of the discharge. The Stark broadening of the Balmer hydrogen line Hβ was used for the estimation of the electron density. The obtained densities were of the order of 5 × 1014 cm−3 which indicates that the electron kinetic energy dominated the discharge. The rotational, vibrational, and excitation temperatures were determined from the vibro-rotational band of the OH radical. A 2-temperature plasma was found where the estimated electron temperatures (~18,000 K) were higher than the gas temperatures (~2000 K). Finally, a 2-D model using the fluid equations was developed for determining the main processes in the CO2 splitting. The solution to this model, using the finite element method, gave the temporal and spatial behaviors of the formed species densities, the electric potential, and the temperatures of electrons.

Description: Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE 〈 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R2 = 0.77) than that between population density and total imperviousness (R2 = 0.52); (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.

Description: In Europe, the qualification of injection anchors in masonry under static and quasi-static actions is based on an assessment of tests performed in undamaged masonry. Nevertheless, in seismic prone countries like Italy the influences deriving from earthquake actions cannot be disregarded. Masonry elements are very sensitive to cyclic/seismic action and research on the behavior of anchors in damaged masonry is rather limited. The paper presents the results of an experimental campaign aimed at evaluating the residual tensile strength of adhesive anchors installed into undamaged walls that were subsequently subjected to cyclic in-plane loading to simulate seismic actions before. Consequently, the anchors experienced different stresses depending on their location within the walls. Overall, 29 tests were performed with anchors placed both, in undamaged and damaged areas. The results showed that there is a correlation between residual tensile strength and masonry initial conditions, and therefore the installation of anchors in masonry elements should be carefully planned avoiding areas that could be heavily damaged during seismic events or considering redundant connections in critical areas. In particular, it seems that the width of the crack (created by cyclic actions) that passes nearby/into the anchor borehole is the main parameter that affects the ultimate resistance of the anchors.

Description: Picking operations is the most time-consuming and laborious warehousing activity. Managers have been seeking smart manufacturing methods to increase picking efficiency. Because storage location planning profoundly affects the efficiency of picking operations, this study uses clustering methods to propose an optimal storage location planning-based consolidated picking methodology for driving the smart manufacturing of wireless modules. Firstly, based on the requirements of components derived by the customer orders, this research analyzes the storage space demands for these components. Next, this research uses the data of the received dates and the pick-up dates for these components to calculate the average duration of stay (DoS) values. Using the DoS values and the storage space demands, this paper executes the analysis of optimal storage location planning to decide the optimal storage location of each component. In accordance with the optimal storage location, this research can evaluate the similarity among the picking lists and then separately applies hierarchical clustering and K-means clustering to formulate the optimal consolidated picking strategy. Finally, the proposed method was verified by using the real case of company H. The result shows that the travel time and the distance for the picking operation can be diminished drastically.

Description: SentryGlas® Plus (SGP) laminated glass is a novel type of safety glass with high strength and stiffness. On the other hand, cold bending is a novel technique to build curved glass curtain walls, and is advantageous in terms of its greater energy efficiency and cost-effectiveness as well as its simple construction processes. The cold bending of SGP laminated glass could result in broad applications for the material and provide huge economic benefits in the field of glass curtain wall construction. To study cold-bending stress and its reverse-coupling effect with the uniform load in SGP laminated glass panels, single-corner cold-bending tests, uniform load tests, and ultimate capacity tests were conducted on eight pieces of such panels with different cold-bending curvatures and interlayer thicknesses. The results revealed that cold-bending stress in the glass panels under single-corner cold bending demonstrated a saddle-shaped distribution, with the maximum and second-largest cold-bending stresses located near the corner of the short side and the long side adjacent to the cold-bending corner, respectively. The cold-bending stress and coupling stress increased nonlinearly as the cold-bending curvature rose and the interlayer thickness became greater. Moreover, cold-bending curvature was a factor that affected the cold-bending stress and coupling stress more significantly than the interlayer thickness. The ultimate capacity and ultimate deflection of the glass panels decreased as the cold-bending curvature and interlayer thickness grew.

Description: This paper presents the usage of artificial neural networks (NNs) in bicycle route planning. This research aimed to check the possibility of NNs to transfer human expertise in bicycle route design by training the NN on an already established set of bicycle routes and then using the trained NN to design the routes on the novel area. We created two NNs capable of choosing the best route among the given road network by training them on two different areas. The bicycle routes produced by NNs were the same at best and had 75% overlap at the worst compared to those produced by human experts. Furthermore, the mean square error for all of our NN models varied from 0.015 and 0.081. We compared this new approach to the traditional multicriteria GIS (geographic information system) analysis (MA) that requires the human expert to define the bicycle route selection criteria. The benefit of using NN over the MA was that the NN directly transfers the human expertise to a model. In contrast, the MA needs the expert to select multiple criteria and adjust their weights carefully.

Description: Due to the appearance of COVID-19 in 2019, person-to-person interactions were drastically reduced. The impact of these restrictions on the economic environment was significant. For example, technical assistance for commissioning or adjusting the parameters of some complex machines/installations had to be postponed. Economic operators became interested in the possibility of remote collaboration, depending on the manufactured products and the performance of the production lines that they owned. This bibliographic research was undertaken to address these needs. The purpose of this review was to analyze the current solutions, approaches, and technologies that workers and specialists can implement to obtain a reliable remote collaboration system. This survey focuses on techniques, devices, and tools that are being used in different contexts to provide remote guidance. We present communication cues and methods being employed, the implemented technological support, and the areas that benefit from remote collaboration. We hope that our effort will be useful to those who develop such systems and people who want to learn about the existence of collaborative solutions, and that it will increase awareness about the applications and the importance of the domain. We are convinced that, with the development of communication systems, the advancement of remote support systems will be a goal for many economic operators.

Description: Synthesis of Ni/C nanostructured composites based on a natural raw material, i.e., wheat straw, is carried out in this work. The synthesis is performed by one- and two-stage methods using NiCl2 as the activating agent. The X-ray diffraction and EDS analyses reveal the presence of metallic nickel in the structure of the composites, whereas magnetic measurements showed that nickel was contained in the porous carbon matrix in the nanoparticle state. For nanocomposites synthesized by the one-stage method, the largest contribution to the formation of the porous structure might be attributed to pores with radii from 5 to 30 nm; for a nanocomposite synthesized in two stages, the pore distribution function exhibits a narrow isolated peak with a maximum of around 2.6 nm. Based on the obtained magnetic data, the coercive force, specific saturation magnetization and nickel content in nanocomposites are calculated. For the measured values of the coercive force, the average size of magnetic moment carriers is determined to be ~100 nm for the two-stage synthesis nanocomposite and ~100 ÷ 110 nm for the one-stage synthesis nanocomposites. The developed Ni/C nanocomposites might be used as a cheap material for energy storage applications or as magnetically controlled adsorbents.

Description: A dual-band dual-polarized antenna with high isolation characteristics is proposed for polarimetric synthetic aperture radar (PolSAR) applications. The antenna consists of four dipole antennas and 2 × 2 patch antenna arrays operating at the P-band (450–730 MHz) and Ka-band (34–36 GHz), respectively. The dipole antennas and the patch antenna arrays need dual-linear polarization characteristics to acquire PolSAR data. Improvements in the isolation characteristics at the P-band are achieved by inserting a metamaterial absorber with a fractal geometry between the transmitting (Tx) and receiving (Rx) dipole antennas. Without the absorber, the simulated isolation characteristics between the Tx and Rx antennas are lower than 19.2 dB over the target band. On the other hand, with the absorbers, the simulated isolation characteristics are higher than 23.44 dB over the target band, and remarkable improvement is achieved around the resonance frequency of the absorber. The measured results are in good agreement with the simulated ones, showing that the proposed antenna can be a good candidate for PolSAR applications.

Description: In the natural science curriculum, chemistry is a very important domain. However, when conducting chemistry experiments, safety issues need to be taken seriously, and excessive material waste may be caused during the experiment. Based on the 11-year-old student science curriculum, this paper proposed a virtual chemistry laboratory, which was designed by combining a virtual experiment application with physical teaching materials. The virtual experiment application was a virtual experiment laboratory environment created by using selected experimental equipment cards in combination with augmented reality (AR) technology. The physical teaching materials included all virtual equipment required for experiment units. Each piece of equipment had corresponding cards for learners to choose from and utilize in specific experimental operations. It was hoped that students were able to achieve the desired learning effectiveness of experimental teaching while reducing the waste of experimental materials through the virtual experimental environment. This study employed the quasi-experimental and questionnaire survey methods to evaluate both learning effectiveness and learning motivation. Eighty-one students and eight elementary school teachers were surveyed as research subjects. The experimental results revealed that significant differences in learning effectiveness existed between the experimental group and control group, indicating that the application of AR technology to teaching substantively helped enhance students’ learning effectiveness and motivation. In addition, the results of the teacher questionnaire demonstrated that the virtual chemistry laboratory proposed in this study could effectively assist with classroom teaching.

Description: The cross-flow rotating packed bed (RPB) has attracted wide attention in recent years because of its advantages of large gas capacity, low pressure drop and lack of flooding limitation. However, the complex structure of the packing makes it difficult to obtain the gas flow characteristics in the cross-flow RPB by experiments. In this study, the dry pressure drop in the cross-flow RPB was investigated by computational fluid dynamics (CFD). The packing was modeled by the porous media model and the rotation of the packing was simulated by the sliding mesh model. The simulation results obtained by three turbulence models were compared with experimental results, and the RNG k-ε model was found to best describe the turbulence behaviors in the cross-flow RPB. Then, the effects of gas flow rate and rotating speed on dry pressure drop in different parts of the cross-flow RPB were analyzed. The results of this study can provide important insights into the design and scale-up of cross-flow RPB.

Description: During mechanical stimulation-induced bone remodeling, interstitial fluid around microcracks may produce a flow field with gradient fluid shear stress (FSS). Osteoclast precursors can sense this gradient FSS and migrate toward the low FSS region. However, the local distribution of wall FSS on bone cells under a flow field with globally gradient FSS remains unknown. In this study, finite element models of a modified plate flow chamber with cells were constructed. The effect of oscillatory flow with different FSS levels and cell spacings or frequencies on the distribution of local wall FSS around cells was simulated by using a fluid–solid coupling method. Results showed that the polarization of wall FSS distribution in a cell decreased with the increase in cell spacing. At a low FSS level, the frequency of oscillatory flow had a minimal effect on the wall FSS distribution. At a high FSS level, the increase in flow frequency enhanced the fluctuation of local wall FSS distribution on cells. These results provide a basis for future research on the flow-induced migration of osteoclast precursors and clarify the mechanism of mechanical stimulation-induced bone resorption.

Description: In this paper, a hybrid bat optimization algorithm based on variable neighbourhood structure and two learning strategies is proposed to solve a three-stage distributed assembly permutation flowshop scheduling problem to minimize the makespan. The algorithm is firstly designed to increase the population diversity by classifying the populations, which solves the difficult trade-off between convergence and diversity of the bat algorithm. Secondly, a selection mechanism is used to update the bat’s velocity and location, solving the difficulty of the algorithm to trade-off exploration and mining capacity. Finally, the Gaussian learning strategy and elite learning strategy assist the whole population to jump out of the local optimal frontier. The simulation results demonstrate that the algorithm proposed in this paper can well solve the DAPFSP. In addition, compared with other metaheuristic algorithms, IHBA has better performance and gives full play to its advantage of finding optimal solutions.

Description: MicroRNAs (miRNAs) are endogenous single-stranded non-coding small RNAs of 20–24 nucleotides and play important roles in many plant biological and metabolic processes. Wax gourd is an important vegetable of Cucurbitacea family, with great economic and medicinal value. Although miRNAs have been extensively studied in model plant species, less is known in wax gourd (Benincasa hispida). In this study, in order to identify miRNAs in wax groud, five independent small RNA libraries were constructed using leaf, root, stem, flower, and fruit of B227. Based on high-throughput Illumina deep sequencing. In total, 422 known and 409 novel miRNAs were identified from five libraries. Comparative analysis revealed that many miRNAs were differentially expressed among different tissues, indicating tissue-specific expression of some miRNAs. qRT-PCR verified the reliability of small RNA sequencing results. Furthermore, miRNAs with similar expression patterns among five tissues were clustered into the same profile, among which many miRNAs were found with relatively high expression in the fruit of wax gourd. MiR164-x had the highest expression in fruit than in other tissues and many NAC transcription factors were predicted as its target genes. We propose that miR164 might regulate fruit development by forming miR164-NAC module in wax gourd. Taken together, this study provides the first global miRNAs profiling of wax gourd, and lays the foundation for understanding the regulatory roles of miRNAs in the growth and development processes of wax gourd.

Description: This paper summarizes the main factors affecting the large deformation of soft rock tunnels, including the lithology combination, weathering effect, and underground water status, by reviewing the typical cases of largely-deformed soft rock tunnels. The engineering geological properties of the rock mass were quantified using the rock mass block index (RBI) and the absolute weathering index (AWI) to calculate the geological strength index (GSI). Then, the long-term strength σr and the elastic modulus E0 of the rock mass were calculated according to the Hoek–Brown failure criterion and substituted into the creep constitutive model based on the Nashihara model. Finally, the creep parameters of the surrounding rock mass of the Ganbao tunnel were inverted and validated by integrating the on-site monitoring and BP neural network. The inversion results were consistent with the measured convergence during monitoring and satisfied the engineering requirements of accuracy. The method proposed in this paper can be used to invert the geological parameters of the surrounding rock mass for a certain point, which can provide important mechanical parameters for the design and construction of tunnels, and ensure the stability of the surrounding rock mass during the period of construction and the safety of the lining structure during operation.

Description: In this work, the design of a convex conformal reflectarray (CRA), suitable to be used for high gain on board antenna in mobile communication systems, is presented. The reflector is not planar, as in usual reflectarray configurations, but the re-radiating elements are printed on a surface conformed to a cylinder to mimic a curved surface, such as the fuselage of an airplane, on which the reflectarray could be mounted. To compensate for the loss in efficiency due to the curvature, an ad hoc feed is designed; the results obtained with the simulation of the entire structure and the measurements of its prototype prove the effectiveness of the design procedure and its capability in enhancing the CRA features, in comparison with similar but more conventional solutions.

Description: The need for line detection in images is growing rapidly due to its importance in many image processing applications. The selection of an appropriate line detection method is essential for accurate detection of line pixels, but few studies provide an analytical basis for selecting a specific line detection method. In this study, to solve the problem, a method to analytically determine the signal-to-noise ratio (SNR) of line detection methods is proposed. Three line detection methods were selected for comparison: edge-detection (ED)-based, second derivative (SD)-based, and the sum of gradient angle differences (SGAD)-based line detection methods. Then, this study quantifies the SNR of the three line detectors through error propagation and signal noise coupling. In addition, the derived SNRs are graphically visualized to explicitly compare the performance of line detectors. Then, the quantified SNRs were validated by showing that they are highly correlated with the completeness and correctness observed in the experiment with a set of natural images. The experimental results show that the proposed SNR analysis can be used to select or design a suitable line detector.

Description: The aim of this study is to compare the seismic response of reinforced concrete (RC) symmetric buildings, with a varied number of stories, strengthening with three types of passive energy dissipation systems, as tuned mass dampers, viscous dampers, and friction dampers. The paper presents an overview of design optimization with the object of minimizing certain functions: (i) the maximum displacement at the top of the structures, (ii) the base shear loads, and (iii) the maximum interstory drift. The objective functions were evaluated in three residents’ buildings (a four-story building, a nine-story building, and a sixteen-story building) subjected to seven (real and artificial) seismic recorded accelerograms. For this purpose, 94 nonlinear dynamic analyses were carried out. The effects of each strengthening solution are presented, and from this innovative comparison (optimal design, three different passive energy systems, three different story numbers), further useful results were observed. The outcomes of the study show the effectiveness of a tuned mass damper (TMD) system, and how it might be better for tall and flexible structures than for stiffer structures. However, the response of the pendulum tuned mass damper (TMD) configuration is better than the conventional one because it acts in all directions. The viscous dampers (VDs) provide a significant reduction for mid-rise buildings, while friction dampers (FDs) boost the performance of all structures under seismic action, especially in terms of displacement, and they are more suitable for low-rise buildings.

Description: Nowadays, the demand for personalized goods is increasing, with small batches of customized products. Companies are asked to cope with this need to be more competitive; thus, it is crucial to optimally set up the production process to cope with the demand. Among the products composed of several parts, sales kits occupy a significant role. Sales kits are sets of different components, supplied as a single unit. Automation is usually used to reduce the unit direct production costs for assembled products, and this is especially true for kitting since it has minimum added value, compared to other technologies. The wide range of components leads to frequent reconfiguration of the feeding devices between different products, increasing the setup time. The aim of this work is to provide a model that minimizes the setup times of automatic kitting systems when working with a high variety of products. To reach this goal, we propose to apply the traveling salesman problem (TSP) to the production process by integrating a multi-clustering model, thus increasing its appeal to several applications. This method is applied both to simulations and to a real case study, and proves to be able to provide a good solution in a reasonable time.

Description: Sleep apnea syndrome (SAS) is a condition characterized by recurrent episodes of total or partial collapse of the upper respiratory tract associated with daytime drowsiness that cannot be explained by other factors. SAS is a pathology that can cause ophthalmological damage both directly through the pathophysiological mechanism characteristic of the disease on the ocular system, and indirectly by promoting the development of other pathologies (cardiovascular, metabolic), which are a risk factor for ocular morbidity in the absence of sleep apnea syndrome. The aim of this paper is to highlight the ocular symptoms determined by sleep apnea syndrome (SAS), by analyzing literature over the past 20 years. Method: A mini-review that collected data from Pub Med Central, ResearchGate, GoogleScholar, DovePress, ScienceDirect, Elsevier, related to the ocular implications given by sleep apnea syndrome, with or without continuous positive airway pressure (CPAP) treatment. The study included articles that identified a number of eye conditions associated with sleep apnea, such as: dry eye syndrome and impaired ocular surface, glaucoma, non-arteritic anterior ischemic optic neuropathy, floppy eyelid syndrome, keratoconus, central serous chorioretinopathy, central vein occlusion, corneal neovascularization, and age-related macular degeneration. Sleep apnea syndrome is a pathology that can cause the onset or worsening of varying degrees of severity eye diseases by its pathophysiological mechanism, with a different impact on the quality of the individual’s life. On one hand, the purpose of this review is to identify studies in literature that associate sleep apnea syndrome with eye alterations; on the other hand, to inform the Romanian medical staff in different fields of the patients’ guidance diagnosed with SAS to an ophthalmology clinic since early and mild symptoms, so that these patients benefit from an ophthalmological approach and monitoring, in an attempt to diagnose and treat eye diseases in time and prevent their worsening.

Description: Inflammation is the primary biological reaction to induce severe infection or injury in the immune system. Control of different inflammatory cytokines, such as nitric oxide (NO), interleukins (IL), tumor necrosis factor alpha-(TNF-α), noncytokine mediator, prostaglandin E2 (PGE2), mitogen activated protein kinases (MAPKs) and nuclear factor kappa B (NF-κB), facilitates anti-inflammatory effect of different substances. Coordination metal complexes have been applied as metallo-drugs. Several metal complexes have found to possess potent biological activities, especially anticancer, cardioprotective, chondroprotective and anti-parasitosis activities. Among the metallo drugs, ruthenium-based (Ru) complexes have paid much attention in clinical applications. Despite the kinetic nature of Ru complexes is similar to platinum in terms of cell division events, their toxic effect is lower than that of cisplatin. This paper reviews the anti-inflammatory effect of novel synthetic Ru complexes with potential molecular mechanisms that are actively involved.

Description: ZnO thin films with oxygen vacancies and doped with Al, Ga, and In (Zn1-xMxO1−y (x = 0.03)) have been successfully deposited on soda-lime glass substrates using a simple soft chemical method. The crystalline structure shows a single hexagonal phase of wurtzite with preferred crystal growth along the 002 plane. The surface morphology, characterized by SEM, revealed that the grain shape varies depending on the dopant agent used. Optical measurements displayed an increase in the bandgap values for doped films from 3.29 for ZnO to 3.35, 3.32, and 3.36 for Al, Ga, and In doped films, respectively, and an average transmittance superior to 90% in some cases (in the range between 400 and 800 nm). The electrical response of the films was evaluated with a four-point probe being 229.69, 385.71, and 146.94 Ω/sq for aluminium, gallium, and indium doped films, respectively.

Description: In this study, the design of a metal stent which expands under the influence of a difference in hydraulic pressure is presented. Using the action of existing stents as a reference, the joint of the metal stent model is joined, to lock its own elastic force. The maximum energy storage formula was applied to determine if the joint could withstand the elastic force that is integral to the stent model. Simulations of the stent, under the influence of differences in hydraulic pressure, were performed. During simulation, the fluid pressure, the width of the joint of the stent, the angle of the pipe model, and some other parameters, were changed to determine their impact on the stent joint and to explore the differences.

Description: Human mesenchymal stem cells can differentiate into various cell types and are useful for applications in regenerative medicine. Previous studies indicated that dental pulp exfoliated from deciduous teeth is a valuable alternative for dental tissue engineering because it contains stem cells with a relatively high proliferation rate. For clinical application, it is necessary to rapidly obtain a sufficient number of cells in vitro and maintain their undifferentiated state; however, the abundance of stem cells in the dental pulp tissue is limited. Non-thermal atmospheric pressure plasma (NTAPP) has been applied in regenerative medicine because it activates cell proliferation. Here, we examined the effects of NTAPP to activate the proliferation of human deciduous dental pulp fibroblast-like cells (hDDPFs) in vitro. Compared with untreated cells, NTAPP increased cell proliferation by 1.3-fold, significantly upregulated well-known pluripotent genes for stemness (e.g., Oct4, Sox2, and Nanog), and activated the expression of stem cell-specific surface markers (e.g., CD105). Overall, NTAPP activated the proliferation of various mesodermal-derived human adult stem cells while maintaining their pluripotency and stemness. In conclusion, NTAPP is a potential tool to expand the population of various adult stem cells in vitro for medical applications.

Description: Lung cancer is a deadly cancer that causes millions of deaths every year around the world. Accurate lung nodule detection and segmentation in computed tomography (CT) images is a vital step for diagnosing lung cancer early. Most existing systems face several challenges, such as the heterogeneity in CT images and variation in nodule size, shape, and location, which limit their accuracy. In an attempt to handle these challenges, this article proposes a fully automated deep learning framework that consists of lung nodule detection and segmentation models. Our proposed system comprises two cascaded stages: (1) nodule detection based on fine-tuned Faster R-CNN to localize the nodules in CT images, and (2) nodule segmentation based on the U-Net architecture with two effective blocks, namely position attention-aware weight excitation (PAWE) and channel attention-aware weight excitation (CAWE), to enhance the ability to discriminate between nodule and non-nodule feature representations. The experimental results demonstrate that the proposed system yields a Dice score of 89.79% and 90.35%, and an intersection over union (IoU) of 82.34% and 83.21% on the publicly available LUNA16 and LIDC-IDRI datasets, respectively.

Description: Concrete block pavement is used as a modern pavement type owing to its economic benefits. The physical properties, mechanical properties, and functional characteristics of bedding sand and joint sand, the main components of concrete block pavements, should be accurately understood. Owing to the discontinuous structure of these pavements, load transfer efficiency (LTE) is the most important index from the perspective of performance. The factors that affect LTE are bedding sand (type, grading, and thickness), joint sand (type and grading), and concrete block (shape and pattern). Therefore, the optimal design for concrete block pavements can be achieved by analyzing each factor. In this study, three types of sand (river, quartz, and manufactured) were selected to examine the mechanical properties via direct transfer experiments. It was observed that the shear strength of river sand was the highest. It was also found that the difference between the shear strength and the internal friction angle (according to the content of 0.6 mm in the grading of bedding sand) was not large, and the shear strength and the friction angle increased as the content increased to 0.075 mm. In addition, the load transfer characteristics of the joint and rotational interlocking of the block were evaluated through a non-destructive test using the degree of joint filling, block shape, and construction pattern as variables. As a result, the degree of joint filling had the greatest effect on the load transfer characteristics of the joint and rotational interlocking of the block. The effect of the block shape was larger than that of the construction pattern. When a heavy load is applied, the LTE between blocks must be maintained at 50% or more, and the rotation of blocks at 0.6° or less, if 75% or more of the joint must be filled for preventing excessive vertical deformation.

Description: The aim of the study was to assess the color matching ability and color stability of a single-shade resin-based composite (Omnichroma—OM) in comparison to a conventional dental composite. One hundred and sixty lower molar acrylic teeth in four different shades (B1, B2, A3, and C3) were prepared with class I cavities. Eighty teeth were divided into two groups based on the two resin composite materials (OM and Filtek Z-350 (FT)) for cavity restoration. Three groups were included in the color matching assessment, namely Gp 1-FT, Gp 2-OM-light cured (C), and Gp 3-OM-uncured (UC) groups. The color assessment was performed prior to cavity restoration and after cavity filling and before and after light curing to detect color matching. The 80 remaining teeth were restored with OM (n = 40) and FT (n = 40); half (n = 40) were submerged in coffee and the other half (n = 40) were submerged in cola for 2 weeks. The color stability was assessed by calculating material color (spectrophotometry) changes (∆E) before and after staining in immersion medium. The means and standard deviations of the ∆E values relating to color matching and color stability (stain resistance) among the study groups were analyzed using ANOVA and Tukey’s post hoc test. FT showed significantly better color matching (lower ΔE) in comparison to OM-UC specimens for shades B1, B2, and A3 (p 〈 0.01). Regarding the color stability in cola, the FT samples showed significantly lower ΔE values (indicating better color stability) compared to OM samples for all four shades (p 〈 0.01). The ΔE values of OM and FT samples in coffee were comparable (p 〉 0.01), showing comparable color stability. The color matching ability of the single-shade resin composite (OM) was influenced by the tooth color. The conventional resin composite showed better color matching than the single-shade composite (OM). The color stability of the single-shade resin composite (OM) was dependent on the staining medium. The OM composite showed more compromised color stability than the conventional resin composite in cola and comparable color stability to conventional resin composite in coffee.

Description: In the current trend of consumption, electricity consumption will become a very high cost for the end-users. Consumers acquire energy from suppliers who use short, medium, and long-term forecasts to place bids in the power market. This study offers a detailed analysis of relevant literature and proposes a deep learning methodology for forecasting industrial electric usage for the next 24 h. The hourly load curves forecasted are from a large furniture factory. The hourly data for one year is split into training (80%) and testing (20%). The algorithms use the previous two weeks of hourly consumption and exogenous variables as input in the deep neural networks. The best results prove that deep recurrent neural networks can retain long-term dependencies in high volatility time series. Gated recurrent units (GRU) obtained the lowest mean absolute percentage error of 4.82% for the testing period. The GRU improves the forecast by 6.23% compared to the second-best algorithm implemented, a combination of GRU and Long short-term memory (LSTM). From a practical perspective, deep learning methods can automate the forecasting processes and optimize the operation of power systems.

Description: The effect of mixing in a flotation column has long been recognized as an important factor in determining the performance of flotation. The paper presents the effects of mixing on the rate constant in a flotation column, and the establishment of relationships based on vessel dispersion numbers (Nd) that can describe axial dispersion. The rate constants were evaluated using models of plug flow, fully mixed tanks, and axial mixing for a coal cleaning operation. Results showed that fine particles are similar between each model; however, for coarse particles, the deviation is large in the case of perfect mixing, while axial mixing is suitable. It reveals the suitability of using an axial dispersion model for estimating the rate constants, particularly for coarser particles. A regression equation to determine the flotation rate constant was also developed with Nd values between 0.2 to 0.5. The ratio of particles to liquid the residence times time (τp/τL) decreases with particle size from small sizes to coarser sizes. Axial dispersion is increased by the superficial gas velocity while is suppressed by the wash water. The relationship between calculated and observed Nd can be used with a 94% accuracy for the coal cleaning application within the range of operating conditions of superficial gas velocity (0.7–1.6 cm/s), superficial wash water velocity (0.1–0.4 cm/s), and Hc/dc (26.8–32.7). The empirical relationship of Nd with significant variables along with the aspect ratio of the column was found to be applicable for coal beneficiation. It may be useful in terms of design and scale up of the columns.

Description: With the advantages of high resolution, structural simplicity, reliability, compact size, and high sensitivity, inductive sensors have been widely used in nanopositioning systems. However, the measuring range of traditional inductive sensors are usually limited to 0.2 mm. A novel analysis and design methodology of the miniaturized inductive sensor with large measuring range and nanoscale resolution is proposed. Firstly, an accurate leakage inductance model is established. Secondly, a design rule of armature size is proposed by considering the fringing effect. Then, the error terms introduced by the measurement circuit of differential inductive sensors are analyzed and the corresponding error suppression methods are illustrated. Moreover, A design rule of selecting the optimal excitation frequency is proposed to meet the requirements of high Q value and high bandwidth, and to minimize the impact of core loss resistance on the performance of the sensor. Validated by the experiments, the proposed analysis and design method can effectively guide the design of the miniaturized inductive sensor with nanoscale resolution in the measuring range of ±0.5‍ mm. The overall size of the fabricated sensor prototypes is less than 6 mm × 6 mm × 3 mm. Combined with large range, high resolution and ideal miniaturization, this inductive sensor can be well suitable for compact and large stroke nanopositioning systems.

Description: This work presents different formulations to obtain the solution for the Giesekus constitutive model for a flow between two parallel plates. The first one is the formulation based on work by Schleiniger, G; Weinacht, R.J., [Journal of Non-Newtonian Fluid Mechanics, 40, 79–102 (1991)]. The second formulation is based on the concept of changing the independent variable to obtain the solution of the fluid flow components in terms of this variable. This change allows the flow components to be obtained analytically, with the exception of the velocity profile, which is obtained using a high-order numerical integration method. The last formulation is based on the numerical simulation of the governing equations using high-order approximations. The results show that each formulation presented has advantages and disadvantages, and it was investigated different viscoelastic fluid flows by varying the dimensionless parameters, considering purely polymeric fluid flow, closer to purely polymeric fluid flow, solvent contribution on the mixture of fluid, and high Weissenberg numbers.

Description: High dynamic performance of a deep-sea electric oil-filled joint actuator is an important premise to guarantee the working performance of an electric underwater manipulator. However, the unfavorable factors (i.e., extremely high water pressure, near freezing temperature) brought by the deep-sea working environment seriously affect the characteristic and dynamic performance of the electric oil-filled joint actuator, which mainly includes oil stirring viscos loss, output shaft dynamic seal loss, and core loss. In this paper, a novel observer-based robust control method named prescribed performance non-singular fast-terminal sliding-mode control (PP-NFTSMC-ESO) was synthesized for improving the dynamic performance of a deep-sea electric oil-filled joint actuator. The extended state observer (ESO) was employed to observe the unmeasured joint velocity signal and estimate the lumped uncertainties, while the prescribed performance function (PPF) was applied to constrain the instantaneous and steady-state performance of the trajectory-tracking error. The robust NFTSMC control method was then established by integrating the function of ESO and PPF through backstepping methodology. The stability of the proposed PP-NFTSMC-ESO strategy was analyzed and proved by the Lyapunov’s stability theory. It was proven that under the proposed controller, all the closed-loop signals are bounded and the trajectory tracking errors will converge to a small neighborhood of the origin with appropriate design parameters. The effectiveness of the proposed control scheme was illustrated by comparative simulation studies.

Description: Historically, researchers and practitioners have often failed to consider all the areas, factors, and implications of a process within an integrated manufacturing model. Thus, the aim of this research was to propose a holistic approach to manufacturing processes in order to assess their status and performance to improve target indicators such as product quality. For this purpose, a conceptual model is designed by identifying areas, flows, and indicators that are relevant to the assessment of a manufacturing system. Moreover, using the conceptual model, manufacturing systems can be modeled considering all related flows and decision-making options in the respective areas of production, maintenance, and quality. As a result, this model serves as the basis for the integral management and control of manufacturing systems in digital twin models for the regulation of process stability and quality with maintenance strategies. Thus, an assessment based on the conceptual model improves the knowledge level of all elements involved in the manufacturing of a product according to the desired quality specifications. The continuous monitoring of all areas and flows together with the optimal strategies in the quality and maintenance areas can enable companies to increase their profitability and customer service level. In this context, the discussion section lists key decision aspects for the assessment and improvement of manufacturing systems, while also providing a methodological sequence to evaluate and improve manufacturing systems. In conclusion, the conceptual approach allows better decision making, ensuring continuous optimization along the manufacturing asset lifecycle and providing a unique selling proposition for equipment producers and service engineering suppliers, as well as for production and assembly companies.

Description: Focused Ion Beam-Induced Deposition (FIBID) is a single-step nanopatterning technique that applies a focused beam of ions to induce the decomposition of a gaseous precursor. The processing rate of FIBID increases by two orders of magnitude when the process is performed at cryogenic temperatures (Cryo-FIBID): the precursor forms a condensed layer on the surface of the cooled substrate, greatly enhancing the amount of material available for decomposition. Cryo-FIBID has been achieved so far by making use of liquid nitrogen-based cooling circuits, which require the passage of a flowing gas as a cooling agent. Here, the Cryo-FIBID of the W(CO)6 precursor is performed using a coolant-free thermoelectric plate utilizing the Peltier effect. Performed at -60 ºC, the procedure yields a W–C-based material with structural and electrical properties comparable to those of its counterpart grown in coolant-based Cryo-FIBID. The use of the thermoelectric plate significantly reduces the vibrations and sample drift induced by the flow of passing coolant gas and allows for the fabrication of similar nanostructures. In summary, the reported process represents a further step towards the practical implementation of the Cryo-FIBID technique, and it will facilitate its use by a broader research community.

Description: Usually, the residual layer remains after patterning TiO2 sol. The existence of the TiO2 residual layer in the non-pattern region affects its application in microelectronic devices. Here, a simple method, based on room-temperature imprinting, to fabricate a residual-free TiO2 pattern is proposed. The thermoplastic polymer with Ti4+ salt was fast patterned at room temperature by imprinting, based on the different interfacial force. Then, the patterned thermoplastic polymer with Ti4+ salt was induced into the TiO2 lines without residual layer under the hydrothermal condition. This method provides a new idea to pattern metal oxide without residual layer, which is potentially applied to the gas sensor, the optical detector and the light emitting diode.

Description: Due to the development and industrialization of science and technology, aluminum alloys have been developed in various fields. Recently, the government has been pursuing ways to decrease the weight and increase the recyclability of various components in order to conserve resources, energy, and the environmental. In keeping with this trend, cast iron products are being replaced by aluminum products in the foundry industry by using high-pressure die casting (HPDC). Casting layout design, relies on the experience and knowledge of mold designers in the casting industry, which proves insufficient to respond to the rapidly changing needs of the era and to increasing production costs. Designing and producing casting layouts using CAD/CAM/CAE technology has become a critical issue. Computer-Aided Engineering (CAE) technology is rapidly increasing with the development of computer software and hardware. CAE technology not only predicts defects in mass production but also performs filling or solidification analysis during the mold design stage before production, enabling optimal mold design methods. New technologies that combine the emerging casting processes of filling and solidification analysis using computer simulation with existing technology and practical experience in the field are rapidly increasing in the foundry industry. Based on empirical knowledge, the layout and design of casting products has traditionally progressed through trial and error. The solutions achieved through scientific calculation and analysis using CAE technology can save a great deal of money and time in the building of die-casting molds and in their design and fabrication. In this study, numerical analysis of household appliances (cooking grills) quickly and accurately predicts problems arising from the filling and solidification of the melted metal in the casting process, thereby ensuring the quality of the final cast product. These results can be used to quickly establish a sound casting layout with reduced production costs.

Description: The assessment of indoor environmental quality in historic buildings converted to museums is a significant tool in deep energy renovation processes, as it provides insights for the microclimatic conditions in the interiors of the building where vast numbers of visitors walk every year and where artifacts that are vulnerable to pollution are exhibited. In this work, aiming to contribute to the development of an energy retrofitting protocol applied in the Mediterranean region (HAPPEN MedZeb protocol) for museums hosted in historic buildings by providing useful data, an experimental campaign to evaluate the indoor environmental quality of a museum housed in a historic building located in Athens took place from February 2019 to April 2021 and was divided into two periods. The findings revealed high concentrations of volatile organic compounds as well as poor thermal comfort levels since the sensors recorded low acceptable percentages of T values within the limits from 7 to 33% for the entire experimental period. Based on the findings, recommendations for retrofitting interventions are made.

Description: Six degree-of-freedom (6-DOF) robotic manipulators have been increasingly adopted in various applications in industries due to various advantages, such as large operation space, more degrees of freedom, low cost, easy placement, and convenient programming. However, the robotic manipulator has the problem of insufficient stiffness due to the series structures, which will cause motion errors of the manipulator end. In this paper, taking a 6-DOF robotic manipulator as an example, forward and inverse kinematics models are established, and a new modeling method for the joint angle and space stiffness of the end of the manipulator is proposed, which can establish the composite stiffness model of joint link stiffness and joint stiffness. An error compensation model is subsequently established. The experimental results indicate that the proposed error compensation method can effectively reduce the end motion error of the robotic manipulator, and hence, the working performance and accuracy of the manipulator can be improved. The proposed research is helpful for extending the application of robotic manipulators in precision machining and measurement.

Description: We report on research in the field of low-noise receiving systems in the sub-terahertz (THz) range, carried out in recent years, aimed at developing receivers with quantum sensitivity for implementation in space and ground-based radio telescopes. Superconductor-Insulator-Superconductor (SIS) mixers based on high-quality tunnel junctions are the key elements of the most sensitive sub-THz heterodyne receivers. Motivations and physical background for technology improvement and optimization, as well as fabrication details, are described. This article presents the results of the SIS receiver developments for the 211–275 GHz and 790–950 GHz frequency ranges with a noise temperature in the double sideband (DSB) mode of approximTELY 20 K and 200 K, respectively. These designs and achievements are implemented in the development of the receiving systems for the Russian Space Agency mission “Millimetron”, and for the ground-based APEX (Atacama Pathfinder EXperiment) telescope.

Description: Smart factories have made great progress with the development of various ICT technologies, such as IoT, big data, and artificial intelligence. The recent development of smart factory technology has shown results in automation and data acquisition and processing. However, it still has incomplete points to be converted to advanced technology, including intelligence. For intelligentization, there is a need to propose a new research method in addition to the previous methodologies. Considering the specificity of the factory, the data structure and methodology of the Semantic Web can be effective. Therefore, in this study, a smart factory was designed by the convergence of monitoring technology, autonomous control technology, and semantic web technologies. Based on the proposed methodology, a methodology for the autonomous control of a smart factory on a digital twin was designed.

Description: The SARS-CoV-2 virus that causes COVID-19 has wreaked havoc on the global community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine has been conducted in earnest. Much of the advanced research has been distributed in leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, pediatrics, geriatrics, and biostatistics.

Description: In preparation for whole-genome sequencing, the axenic culture for two strains of a freshwater diatom Fragilaria radians were produced. Although their axenicity was controlled for the cultures’ entire lifetime, the published genomic assembly was later found to contain a large amount of bacterial sequences. Using various in silico analyses of whole genome read libraries and 16S rRNA sequencing of culture samples, we reconstruct the history of the contamination and document the failures of various axenicity control methods. This knowledge is used to discuss how these failures could have been avoided, and to provide guidelines for future works on axenic diatom cultures.

Description: This study is a continuation of our research on understanding the possible chemical routes to the evolution of life on earth based on the “Selective Energy Transfer” (SET) theory. This theory identifies the specific vibrational mode of the catalyst that is in energy-resonance with a suitable vibrational mode of the reactant. In this way, energy is transferred from catalyst to reactant up to the energy of activation, making possible a particular chemical outcome. Then, we extend this model to the mostly unknown and highly complex environment of the hydrothermal vents, to speculate how prebiotic chemicals, necessary for the evolution of life, could have formed. It is to the credit of the SET theory that it can reflect the slight difference in the catalytic system that gives dramatically very different chemical outcome. It is shown, here, how in model laboratory experiments, methanol gives dimethyl ether (DME) in a 100% yield with Cu exchanged montmorillonite as the catalyst, or a very different product methyl formate (MF) in lower yields, with another Cu2+ ion-exchanged clay mineral (laponite) as the catalyst system. We also show, based on standard laboratory experiments, how COS (carbonyl sulfide) with a strong absorption band at 2079 cm−1 by itself and/or catalyzed by montmorillonite with strong Si-O-Si asymmetric vibration of 1040 cm−1 can react with alpha-amino acids to form alpha-amino acid thiocarbamate (AATC), which we feel could represent the most primitive analogue to coenzyme A (CoASH), a highly versatile bio-enzyme that is vital both for the metabolism and the synthesis of biochemicals in the living system. AATC itself may have undergone evolutionary developments through billions of years to transform itself into coenzyme A (CoASH) and its acetyl ester analogue acetyl coenzyme A (ACoA).

Description: A truncated basis is employed to analyze the influence of the point interaction on the eigenvalues and eigenfunctions in quantum billiards. The point interaction is numerically confirmed to cause the shift in the eigenvalue that leads the original eigenfunctions to be superposed to form the new eigenfunction. The amplitude and nodal-line patterns of the eigenfunctions are found to vary significantly with the coupling strength. It is further verified that the point-driven Chladni plates can be employed to analogously manifest the noticeable dependence of the nodal-line pattern on the coupling strength. More importantly, the dispersion relation between the frequency and the wave number for the flexural wave can be precisely determined in the process of utilizing the point interaction to model the modern Chladni plates.

Description: Optical sol-gel environmental pH sensors have been applied for air evaluation in exhibition halls of the Museo Nacional de Ciencias Naturales (Madrid, Spain). Sensor synthesis and calibration was undertaken following a previous patent by some of the present authors. Monitoring was carried out for one full year to check the influence of meteorological seasons as well as quality of surrounding outdoor air to a big avenue located in downtown Madrid and close to the museum. Particular sites selected for sensor positions were inside showcases, under the free environment of exhibition halls, and outdoor façades of the building, for comparison purposes. pH recordings showed that exhibition halls near the outdoor air entrance had slightly low pH values, which can be attributed to outdoor pollution. However, halls located far from air entrance had neutral conditions. Concerning showcases tested, some of them showed slightly acidic pH while others were moderately acidic due to natural goods exhibited and/or to materials with which showcases were made. pH values recorded allowed the museum to make some decisions on its preventive conservation strategy.

Description: PHM technology plays an increasingly significant role in modern aviation condition-based maintenance. As an important part of prognostics and health management (PHM), a health assessment can effectively estimate the health status of a system and provide support for maintenance decision making. However, in actual conditions, various uncertain factors will amplify assessment errors and cause large fluctuations in assessment results. In this paper, uncertain factors are incorporated into flight control system health assessment modeling. First, four uncertain factors of health assessment characteristic parameters are quantified and described by the extended λ-PDF method to acquire their probability distribution function. Secondly, a Monte Carlo simulation (MCS) is used to simulate a flight control system health assessment process with uncertain factors. Thirdly, the probability distribution of the output health index is solved by the maximum entropy principle. Finally, the proposed model was verified with actual flight data. The comparison between assessment results with and without uncertain factors shows that a health assessment conducted under uncertain conditions can reduce the impact of the uncertainty of outliers on the assessment results and make the assessment results more stable; therefore, the false alarm rate can be reduced.

Description: The objective of the study was to investigate the effect of the partial replacement of carbon black (CB) by nanodiamonds (NDs) on the vulcanization, mechanical and dynamic properties of a natural rubber—butadiene rubber compound, a typical elastomer compound found in several applications (the tire and mining industry, for example). A studied hybrid filler system resulted in a 28% increase in tensile strength and 29% increase in 300% modulus at low ND loadings even though the total weight fraction of the filler system was kept constant at 25 parts per hundred rubber. The hybrid filler system improved dispersion of both fillers as was proven by scanning electron microscopy and the Payne effect study. In addition, the replacement of 2.5 and 5 phr CB by NDs resulted in 62% improvement in wear resistance. The DMA study showed that a certain ND-CB filler combination has a positive effect on tire properties such as wet grip and rolling resistance.

Description: This study investigates the effect of support structures on the properties of Inconel 718 (i.e., IN718) parts produced by the laser powder bed fusion (LPBF) additive manufacturing process. Specifically, the effects of support structure shape (i.e., pin-type, angled-type, cone-type) and geometry (i.e., support wall thickness, and gap) on their composition, hardness, microstructure, and material/time consumption are investigated and compared to the conventionally fabricated Inconel 718. From the microstructural analysis, the deepest melt pools appeared to be formed in the sample fabricated on top of the pin-type support structure having a relatively low wall thickness. The XRD results conveyed that a proper selection of geometrical variables for designing support structure results in elevated levels of the strengthening phases of IN718. The sample fabricated on top of the pin-type support structure showed the highest Vickers hardness value of 460.5 HV, which was even higher than what was reported for the heat-treated wrought Inconel 718 (355–385 HV). Moreover, for the thinner support wall thickness, an improvement in the hardness value of the fabricated samples was observed. This study urges a reconsideration of the common approach of selecting supports for additive manufacturing of samples when a higher quality of the as-fabricated parts is desired.

Description: Crop identification is key to global food security. Due to the large scale of crop estimation, the science of remote sensing was able to do well in this field. The purpose of this study is to study the shortcomings and strengths of combined radar data and optical images to identify the type of crops in Tarom region (Iran). For this purpose, Sentinel 1 and Sentinel 2 images were used to create a map in the study area. The Sentinel 1 data came from Google Earth Engine’s (GEE) Level-1 Ground Range Detected (GRD) Interferometric Wide Swath (IW) product. Sentinel 1 radar observations were projected onto a standard 10-m grid in GRD output. The Sen2Cor method was used to mask for clouds and cloud shadows, and the Sentinel 2 Level-1C data was sourced from the Copernicus Open Access Hub. To estimate the purpose of classification, stochastic forest classification method was used to predict classification accuracy. Using seven types of crops, the classification map of the 2020 growth season in Tarom was prepared using 10-day Sentinel 2 smooth mosaic NDVI and 12-day Sentinel 1 back mosaic. Kappa coefficient of 0.75 and a maximum accuracy of 85% were reported in this study. To achieve maximum classification accuracy, it is recommended to use a combination of radar and optical data, as this combination increases the chances of examining the details compared to the single-sensor classification method and achieves more reliable information.

Description: In recent years, the photovoltaic (PV) system was designed to supply solar power through photovoltaic arrays. The PV generator exhibits nonlinear voltage–current characteristics and its maximum power point tracking (MPPT), which varies with temperature and radiation. In the event of non-uniform solar insolation, several multiple maximum power points (MPPs) appear in the power–voltage characteristic of the PV module. Thus, a hybrid combination of binary particle swarm optimization (BPSO) and grey wolf optimization (GWO) is proposed herein to handle multiple MPPs. This combination is nowhere found in the literature, so the author chose this hybrid technique; and the main advantage of the proposed method is its ability to predict the global MPP (GMPP) in a very short time and to maintain accurate performance, even under different environmental conditions. Moreover, a 31-level multilevel inverter (MLI) was designed with a lower blocking voltage process to reduce the complexity of the circuit design. The entire system was executed in the MATLAB platform to examine the performance of the PV system, which was shown to extract a maximum power of 92.930 kW. The simulation design clearly showed that the proposed method with a 31-level MLI achieved better results in terms of total harmonic distortion (THD) at 1.60%, which is less when compared to the existing genetic algorithm (GA) and artificial neural networks (ANNs).

Description: When the finite element-strength reduction method is used for two-dimensional slope stability analysis for elastic-perfectly plastic material, the failure criterion usually adopts the criterion of plastic zone penetration. That is, when the slope is in the limit equilibrium state, the plastic zone goes through the slope from the toe to the top. Meanwhile, the critical slip surface is composed of a series of points of maximum equivalent plastic strain along the depth direction. By deploying a set of parallel lines approximately perpendicular to the slope surface and picking out the points of these lines with the maximum equivalent strain points, we obtain a series of points taking on a wave shape, which constitutes a signal function. Subsequently, the wavelet packet analysis is used to smooth these points, i.e., locating the critical slip surface. The analysis of classic examples and comparison with Spencer’s method show that the proposed method in this paper is reasonable and effective.

Description: In this work, the performance of discrete and continuum computational models for addressing granular flow dynamics in a rotating drum at different regimes is studied. The results are compared to the experimental observations obtained by image processing of a high-speed camera on a pilot plant rotating drum. For the discrete modeling, Discrete Elements Method (DEM) through the open-source software LIGGGHTS(R) is used, while for the continuum model, the μ(I)-rheology is implemented in the general structure of a Volume-Of-Fluid (VOF) solver of the OpenFOAM(R) platform. Four test cases consisting of different sets of particles filling and rotational speed are considered and the results are analyzed in terms of solids distribution, the velocity of the particles, and mixing patterns. The solids distribution and velocities for each one of the tests considered are fairly similar between both computational techniques and the experimental observations. In general, DEM results show a higher level of agreement with the experiments, with minor differences that might be irrelevant in some cases (e.g., more splashing of particles for the fastest regimes). Among the drawbacks of the continuum model, it was unable to predict the slumping regime observed experimentally which can be attributed to the lack of a yield criterion and a slower dragging of the granular material when the drum is being accelerated, which can be attributed to the need of adding non-local effects to the rheology. On the other hand, the dynamic of the bed in the rolling and cascading regimes are accurately predicted by the continuum model in less time than DEM, even in a pilot plant scale system. These results suggest that the use of a continuum model with granular fluid rheology is more suited for simulating industrial-scale rotating drums at different regimes than DEM, but only if all the phenomenological features (i.e., yield criteria and non-local effects) are taken into account in the model.

Description: Driven by the supply chain, suppliers, manufacturers and warehouses are working more closely together for improving service quality. However, tremendous cost may incur in the supply chain if transportation is not planned properly and efficiently, which frustrates enterprises in the intense market. In this paper, we present a model of vehicle routing problem in complex supply chain (VRPCSC) and propose an intelligent algorithm called hybrid chaotic discrete bat algorithm with variable neighborhood search for minimizing the purchase cost of materials, processing cost, and delivery cost along the path from suppliers, to manufacturers and warehouses in the vehicle routing problem. Based on the principles of bat algorithm, a discrete chaotic initialization strategy (DCIS) and a variable neighborhood search (VNS) are adopted to enhance the convergence capacity. Finally, two sets of experiments are conducted, which show that the proposed algorithm can solve the VRPCSC effectively.

Description: It is essential to measure and monitor the intravenous (IV) infusion rate of inpatients. Medical staff monitor the IV infusion rate continually to ensure that a constant value is maintained. Developing an IV infusion monitoring system can help alleviate the workload of medical staff. Therefore, this paper proposes a method based on optical sensors, in conjunction with the Internet of Things, to overcome the challenges of IV therapy. To increase the sensitivity of the system, both optical sensors and load cells are used to compensate for their disadvantages. Our system yielded accuracies of 87.9% and 89.9% under horizontal and vertical motion conditions, respectively. The proposed system can send notifications to nursing stations regarding the residual IV fluid, current infusion rate, and expected end time, which can be monitored remotely by medical staff. Furthermore, this system can help prevent possible medical accidents during fluid treatment.

Description: Microplastics (MPs), and specifically microfibres (MPFs), are ubiquitous in water bodies, including wastewater and drinking water. In this work, a thorough literature review on the occurrence and removal of MPs, and specifically MPFs in WWTPs and DWTPs, has been carried out. When the water is treated, an average microfiber removal efficiency over 70% is achieved in WWTPs and DWTPs. These high percentages are still inefficient for avoiding the presence of a large number of microfibres in treated wastewater and also in tap water. RSF, DAF, oxidation ditch and CAS processes have been described as the most efficient treatments for eliminating MPFs from wastewater treatment. It is remarkable the wide range of the data reported on this topic; for example, treated wastewater contains between not detected and 347 MPFs/L, whereas tap water contains between not detected and 168 MPFs/L. Microfibres constitute more than half of the MPs found in treated wastewater and sewage sludge, whereas in DWTP effluents the percentage of MPFs is around 32%. Nevertheless, the relative amount of MPFs reported in tap water is notably higher (71%). Microfibres from WWTPs are discharged to the environment, being a source of MP pollution. Additionally, MPs released by DWTPs directly enter the drinking water lines, which constitute a direct route for MP human consumption, so that it has been estimated that an adult may ingest an average value of 7500 MPFs per year only via tap water. Thus, this review provides an update on the performance of WWTPs and DWTPs in removing MPs from water, which is an issue of great interest.

Description: Commercial grid-connected rooftop solar PV systems are widely applied worldwide as part of affordable and clean energy initiatives and viable long-term solutions for energy security. This is particularly true in a crowded city where space is a constraint and at the same time, there are unutilized rooftops. With the recently announced Net Energy Metering (NEM) 3.0, commercial buildings in Malaysia can apply up to 75% capacity of the maximum demand (MD), which can be connected to the grid. Apart from reducing electricity bills, the owner can offset energy for 10 years. This paper presents a design analysis with the details of the sizing of a rooftop PV system. The PVsyst software tool is used to estimate the energy produced by a 380 kWp system, and this study provides a financial analysis to evaluate the profitability of the system with a particular interest in commercial buildings under the NEM 3.0 policy, which has resulted in 8.4 years return of investment (ROI). PVsyst is a software used to size the PV system and provides technical, financial, and environmental analysis. This in-depth analysis could provide a useful case study for asset owners in deciding the way forward for sustainable energy production, cost saving, and combating the energy security issue, since Malaysia is blessed with an abundance of sunshine throughout the year.

Description: As the number of stroke survivors is continuously growing, with an important number suffering from consequent functional deficits, the rehabilitation field is facing more complex demands. Technological progress gives us the opportunity to remotely assist patients while they exercise at home through telerehabilitation (TR), addressing the problems of limited medical resources and staff, difficult transportation, or living a long distance from rehabilitation centers. In addition, TR is a way to provide continuity in long-term post-stroke recovery during the COVID-19 pandemic, which limits traveling and human interaction. While the implementation of TR is increasing, the biggest challenges are to raise patients’ acceptability of the new method and their motivation and engagement during the program. In this review, we aimed to find methods to address these challenges by identifying the patients who benefit the most from this therapy and efficiently organizing the space and technology used for telerehabilitation. User-friendly technologies and devices along with therapists’ constant support and feedback are some of the most important aspects that make TR an efficient intervention and an alternative to conventional therapy.

Description: Purpose: Both anatomic total shoulder arthroplasty (TSA) and shoulder hemiarthroplasty (SHA) are used for the management of end-stage glenohumeral osteoarthritis (GHOA). The present study compared TSA and SHA in terms of clinical outcome and complication rate. Methods: This meta-analysis followed the PRISMA guidelines. In October 2021, the following databases were accessed: Web of Science, Google Scholar, Pubmed, Scopus. All clinical trials comparing anatomical TSA versus SHA for GHOA were considered. Results: Data from 11,027 procedures were retrieved. The mean length of the follow-up was 81.8 (16 to 223.20) months. The mean age of the patients was 61.4 ± 8.6 years, and 56.0% (5731 of 10,228 patients) were women. At last follow-up, the age-adjusted constant score was greater following TSA (p 〈 0.0001), as were active elevation (p 〈 0.0001), flexion (p 〈 0.0001), abduction (p 〈 0.0001), and American Shoulder and Elbow Surgeons Shoulder Score (p 〈 0.0001). Postoperative pain (p 〈 0.0001) and revision rate (p = 0.02) were lower in the TSA group. Conclusions: Anatomic TSA performed better than SHA in patients with GHOA.

Description: The need to compete for users’ attention and provide them with the best user experience has increased the use of persuasion strategies in modern systems. Currently, Persuasive Systems (PSs) promote healthy behavior for well-being, energy consumption, and learning. Although the educational domain has limited investigation compared to other areas, PSs in education have been shown to be effective in motivating students. This paper summarizes the existing evidence on Persuasive Educational Systems (PESs), emphasizing research on the current design methods, evaluation methods, and characteristics. We follow Kitchenham’s method to perform a systematic literature review about PESs published between 2014 and 2020, with 19 relevant studies selected. We highlight some results from the analysis of selected papers such as persuasion strategies, use of a personalized persuasion technique, study of students’ susceptibility to strategies, integration of gamification mechanisms, and proposed tools to design PES. Moreover, we discuss interesting facts such as the common practice of using more than one tool to design PES, aspects of interaction, persuasion, learning, and the challenges in evaluating persuasive impact. Finally, as the main contribution of the paper we identify the seven necessary characteristics to build a persuasive educational system.

Description: In this work, we propose a convenient method for evaluating levels of angular jerk in augmented reality (AR) and virtual reality (VR). Jerk is a rarely analyzed metric in usability studies, although it can be measured and calculated easily with most head-worn displays and can yield highly relevant information to designers. Here, we developed and implemented a system capable of calculating and analyzing jerk in real-time based on orientation data from an off-the-shelf head-worn display. An experiment was then carried out to determine whether the presence of AR user interface annotations results in changes to users’ angular head jerk when conducting a time-pressured visual search task. Analysis of the data indicates that a decrease in jerk is significantly associated with the use of AR augmentations. As noted in the limitations section, however, the conclusions drawn from this work should be limited, as this analysis method is novel in the VR/AR space and because of methodological limitations that limited the reliability of the jerk data. The work presented herein considerably facilitates the use of jerk as a quick component measure of usability and serves as an initial point off which future research involving jerk in VR and AR can be performed.

Description: Recombination of charge carriers can affect the response of ionization detectors used for the dosimetry of radiotherapy fields. In this work, we present a method for correcting online the recombination effects in arrays of ionization chambers irradiated with time-varying dose rates. The method is based on the characterization of the dose rate/recombination response of the detector, and the measurement of the instant ionization current in the detector, rather than the integrated charge. The proposed method was investigated with simulations of the response of different air and liquid ionization chambers in situations where recombination can be large. In addition, we experimentally investigated the application of the method with an in-house-developed liquid-filled ionization chamber. The proposed online correction method can compensate for recombination losses and seems feasible to implement in the software of ionization arrays/detectors used for the dosimetry of radiotherapy fields.

Description: The variance κ1 of the natural time analysis of earthquake catalogs was proposed in 2005 as an order parameter for seismicity, whose fluctuations proved, in 2011, to be minimized a few months before the strongest mainshock when studying the earthquakes in a given area. After the introduction of earthquake networks based on similar activity patterns, in 2012, the study of their higher order cores revealed, in 2019, the selection of appropriate areas in which the precursory minima βmin of the fluctuations β of the seismicity order parameter κ1 could be observed up to six months before all strong earthquakes above a certain threshold. The eastern Mediterranean region was studied in 2019, where all earthquakes of magnitude M≥7.1 were found to be preceded by βmin without any false alarm. Combining these results with the method of nowcasting earthquakes, introduced in 2016, for seismic risk estimation, here, we show that the epicenter of an impending strong earthquake can be estimated. This is achieved by employing—at the time of observing the βmin—nowcasting earthquakes in a square lattice grid in the study area and by averaging, self-consistently, the results obtained for the earthquake potential score. This is understood in the following context: the minimum βmin is ascertained to almost coincide with the onset of Seismic Electric Signals activity, which is accompanied by the development of long range correlations between earthquake magnitudes in the area that is a candidate for a mainshock.

Description: This paper investigates the dynamic forecasting of lead-time, which can be performed by a logistics company for optimizing temporal shipment consolidation. Shipment consolidation is usually utilized to reduce outbound shipments costs, but it can increase the lead time. Forecasting in this paper is performed in a make-to-order supply chain using real data, where the logistics company does not know the internal production data of manufacturers. Forecasting was performed in several steps using machine-learning methods such as linear regression and logistic regression. The last step checks if the order will come in the next delivery week or not. Forecasting is evaluated after each shipment delivery to check the possibility of delaying the current arriving orders for a certain customer until the next week or making the delivery to the customer immediately. The results showed reasonable accuracy expressed in different ways, and one of them depends on a type I error with an average value of 0.07. This is the first paper that performs dynamic forecasting for the purpose of shipment temporal consolidation optimization in the consolidation center.

Description: The extraction of a road network is critical for city planning and has been widely studied in previous research using high resolution images, whereas the high cost of high-resolution remote sensing data and the complexity of its analysis also cause huge challenges for the extraction. The successful launch of a high resolution (130 m) nighttime remote sensing satellite, Luojia 1-01, provides great potential in the study of urban issues. This study attempted to extract city roads using a Luojia 1-01 nighttime lighting image. The urban regions were firstly distinguished through a threshold method. Then, an unsupervised PCNN (pulse coupled neural network) was established to extract the road networks in urban regions. A series of optimizing methods was proposed to enhance the image contrast and eliminate the residential regions along the roads. The final extraction results after optimizing were compared with OSM (OpenStreetMap) data, showing the high precision of the proposed approach with the accuracy rate reaching 83.2%. We also found the precision of city centers to be lower than suburban regions due to the influence of intensive human activities. Our study confirms the potential of Luojia 1-01 data in the extraction of city roads and provides new thought for more complex and microscopic study of city issues.

Description: The growing interest of consumers in regional and traditional products drew our attention to innovative products manufactured at home and using craft methods, which include, among others, alcohol tinctures of edible flowers. The aim of this paper is to present selected tinctures of edible flowers from home and craft production, their phenol content, antioxidant properties and colour. Novel alcoholic beverages obtained from edible flowers are characterized. The tinctures from wild rose flowers, elderberry, marigold and cornflower were studied. The content of phenolic compounds, the antioxidant properties and the colour of tinctures in the CIE L*a*b* system were analysed. The study showed that edible flower tinctures are characterized by an intense colour, which is not adversely affected by the maceration process. The determined parameters were influenced by the form of flowers (fresh or dried). The total content of polyphenolic compounds and antioxidant activity in the studied tinctures were lower than in the fresh flowers. Edible flower tinctures can be an interesting alternative for both consumers looking for product innovations and alcohol connoisseurs.