bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Polymers on Magnesium-Based Hydrogen Storage Systems
Authors: Thangarasu Sadhasivam , Oh Tae
Published: June 2022

In the present scenario, much importance has been provided to hydrogen energy systems (HES) in the energy sector because of their clean and green behavior during utilization. The developments of novel techniques and materials have focused on overcoming the practical difficulties in the HES (production, storage and utilization). Comparatively, considerable attention needs to be provided in the hydrogen storage systems (HSS) because of physical-based storage (compressed gas, cold/cryo compressed and liquid) issues such as low gravimetric/volumetric density, storage conditions/parameters and safety. In material-based HSS, a high amount of hydrogen can be effectively stored in materials via physical or chemical bonds. In different hydride materials, Mg-based hydrides (Mg–H) showed considerable benefits such as low density, hydrogen uptake and reversibility. However, the inferior sorption kinetics and severe oxidation/contamination at exposure to air limit its benefits. There are numerous kinds of efforts, like the inclusion of catalysts that have been made for Mg–H to alter the thermodynamic-related issues. Still, those efforts do not overcome the oxidation/contamination-related issues. The developments of Mg–H encapsulated by gas-selective polymers can effectively and positively influence hydrogen sorption kinetics and prevent the Mg–H from contaminating (air and moisture). In this review, the impact of different polymers (carboxymethyl cellulose, polystyrene, polyimide, polypyrrole, polyvinylpyrrolidone, polyvinylidene fluoride, polymethylpentene, and poly(methyl methacrylate)) with Mg–H systems has been systematically reviewed. In polymer-encapsulated Mg–H, the polymers act as a barrier for the reaction between Mg–H and O2/H2O, selectively allowing the H2 gas and preventing the aggregation of hydride nanoparticles. Thus, the H2 uptake amount and sorption kinetics improved considerably in Mg–H.
Microstructure Analysis of Drawing Effect and Mechanical Properties of Polyacrylonitrile Precursor Fiber According to Molecular Weight
Authors: Ahn Hyunchul , Gwak Hyeon Jung , Kim Yong Min , Yu Woong-Ryeol , Lee Won Jun , Yeo Sang Young
Published: June 2022

Polyacrylonitrile (PAN) fiber is the most widely used carbon fiber precursor, and methyl acrylate (MA) copolymer is widely used for research and commercial purposes. The properties of P (AN-MA) fibers improve increasingly as the molecular weight increases, but high-molecular-weight materials have some limitations with respect to the manufacturing process. In this study, P (AN-MA) precursor fibers of different molecular weights were prepared and analyzed to identify an efficient carbon fiber precursor manufacturing process. The effects of the molecular weight of P (AN-MA) on its crystallinity and void structure were examined, and precursor fiber content and process optimizations with respect to molecular weight were conducted. The mechanical properties of high-molecular-weight P (AN-MA) were good, but the internal structure of the high-molecular-weight material was not the best because of differences in molecular entanglement and mobility. The structural advantages of a relatively low molecular weight were confirmed. The findings of this study can help in the manufacturing of precursor fibers and carbon fibers with improved properties.
Comparative Study of Polyethylene Films Embedded with Oxide Nanoparticles of Granulated and Free-Standing Nature
Authors: Christopoulos Stavros , Angastiniotis Nicos C. , Laux - Le Guyon Valerie , Bsaibess Eliane , Koutsokeras Loukas , Duponchel Benoît , El-Rifai Joumana , Li Liang , Slimani Ahmed
Published: June 2022

Nanocomposite polymer films are a very diverse research field due to their many applications. The search for low-cost, versatile methods, producing regulated properties of the final products, has thus become extremely relevant. We have previously reported a bulk-scale process, dispersing granulated metal oxide nanoparticles, of both unary and multi-component nature, in a low-density polyethylene (LDPE) polymer matrix, establishing a reference in the produced films’ optical properties, due to the high degree of homogeneity and preservation of the primary particle size allowed by this method. In this work, unmodified, free-standing particles, namely zinc oxide (ZnO), titanium dioxide (TiO2), aluminum oxide (Al2O3), and silicon dioxide (SiO2) are blended directly with LDPE, and the optical properties of the fabricated films are compared to those of films made using the granulation process. The direct blending process evidently allows for control of the secondary particle size and ensures a homogeneous dispersion of the particles, albeit to a lesser extent than the granulation process. Despite the secondary particle size being comparatively larger than its granulated counterpart, the process still provides a regulated degree of deagglomeration of the free-standing oxide particles, so it can be used as a low-cost alternative. The regulation of the secondary particle size tunes the transmission and reflection spectra, in both unary and mixed oxide compositions. Finally, the direct blending process exhibits a clear ability to tune the energy band gap in mixed oxides.
Design and Mechanical Characterization Using Digital Image Correlation of Soft Tissue-Mimicking Polymers
Authors: Grimaldo Ruiz Oliver , Rodriguez Reinoso Mariana , Ingrassia Elena , Vecchio Federico , Maniero Filippo , Burgio Vito , Civera Marco , Bitan Ido , Lacidogna Giuseppe , Surace Cecilia
Published: June 2022

Present and future anatomical models for biomedical applications will need bio-mimicking three-dimensional (3D)-printed tissues. These would enable, for example, the evaluation of the quality-performance of novel devices at an intermediate step between ex-vivo and in-vivo trials. Nowadays, PolyJet technology produces anatomical models with varying levels of realism and fidelity to replicate organic tissues. These include anatomical presets set with combinations of multiple materials, transitions, and colors that vary in hardness, flexibility, and density. This study aims to mechanically characterize multi-material specimens designed and fabricated to mimic various bio-inspired hierarchical structures targeted to mimic tendons and ligaments. A Stratasys® J750™ 3D Printer was used, combining the Agilus30™ material at different hardness levels in the bio-mimicking configurations. Then, the mechanical properties of these different options were tested to evaluate their behavior under uni-axial tensile tests. Digital Image Correlation (DIC) was used to accurately quantify the specimens’ large strains in a non-contact fashion. A difference in the mechanical properties according to pattern type, proposed hardness combinations, and matrix-to-fiber ratio were evidenced. The specimens V, J1, A1, and C were selected as the best for every type of pattern. Specimens V were chosen as the leading combination since they exhibited the best balance of mechanical properties with the higher values of Modulus of elasticity (2.21 ± 0.17 MPa), maximum strain (1.86 ± 0.05 mm/mm), and tensile strength at break (2.11 ± 0.13 MPa). The approach demonstrates the versatility of PolyJet technology that enables core materials to be tailored based on specific needs. These findings will allow the development of more accurate and realistic computational and 3D printed soft tissue anatomical solutions mimicking something much closer to real tissues.
Natural Biopolymers as Additional Tools for Cell Microencapsulation Applied to Cellular Therapy
Authors: Cardoso Liana Monteiro da Fonseca , Barreto Tatiane , Gama Jaciara Fernanda Gomes , Alves Luiz Anastacio
Published: June 2022

One of the limitations in organ, tissue or cellular transplantations is graft rejection. To minimize or prevent this, recipients must make use of immunosuppressive drugs (IS) throughout their entire lives. However, its continuous use generally causes several side effects. Although some IS dose reductions and withdrawal strategies have been employed, many patients do not adapt to these protocols and must return to conventional IS use. Therefore, many studies have been carried out to offer treatments that may avoid IS administration in the long term. A promising strategy is cellular microencapsulation. The possibility of microencapsulating cells originates from the opportunity to use biomaterials that mimic the extracellular matrix. This matrix acts as a support for cell adhesion and the syntheses of new extracellular matrix self-components followed by cell growth and survival. Furthermore, by involving the cells in a polymeric matrix, the matrix acts as an immunoprotective barrier, protecting cells against the recipient’s immune system while still allowing essential cell survival molecules to diffuse bilaterally through the polymer matrix pores. In addition, this matrix can be associated with IS, thus diminishing systemic side effects. In this context, this review will address the natural biomaterials currently in use and their importance in cell therapy.
To Build the New Jerusalem: The Ministry and Citizenship of Protestant Women in Twentieth Century Scotland
Authors: Orr Lesley
Published: June 2022

The question of women’s ordination to offices within churches, and in particular to the ministry of word and sacrament, gave rise to one of the major ecclesiological debates of the modern era. In common with other contested issues during this period, different approaches to biblical interpretation and the doing of theology were at stake, but while the precise chronology, arguments and outcomes differed in particular denominations and locations, comparison across a range of churches—certainly within Britain—indicates that these were related predominantly to wider social and cultural changes, more than to internal theological debates. In Scotland, extensive discursive attention was devoted to the place and role of women in the church for over a century before the Church of Scotland extended eligibility for ordination to women. Questions about the ministry and authority of women have particularly exercised ecclesiastical institutions during heightened periods of campaigning for reforms to women’s status and rights in society. The first wave of feminist activism culminated in their enfranchisement (1918 and 1928). Many Protestant churchwomen were deeply engaged in the struggle to become equal citizens. They believed that it was a profoundly Christian obligation to exercise their citizenship to build a better world. They also contended that women should not be prevented from exercising the ordained ministry of word and sacraments, as a matter of justice and as a gospel imperative. This article considers the progress of efforts to that end in some Scottish Protestant churches between 1918 and 1968, and their framing in the contemporary discourses of citizenship and equality, particularly during the interwar years. It discusses factors which impeded or facilitated that innovation, and the major societal changes from the 1950s which created a conducive context for the Church of Scotland decision.
Snow Cover in the Three Stable Snow Cover Areas of China and Spatio-Temporal Patterns of the Future
Authors: Zou Yifan , Sun Peng , Ma Zice , Lv Yinfeng , Zhang Qiang
Published: June 2022

In the context of global warming, relevant studies have shown that China will experience the largest temperature rise in the Qinghai–Tibet Plateau and northwestern regions in the future. Based on MOD10A2 and MYD10A2 snow products and snow depth data, this study analyzes the temporal and spatial evolution characteristics of the snow cover fraction, snow depth, and snow cover days in the three stable snow cover areas in China, and combines 15 modes in CMIP6 snow cover data in four different scenarios with three kinds of variables, predicting the spatiotemporal evolution pattern of snow cover in China’s three stable snow cover areas in the future. The results show that (1) the mean snow cover fraction, snow depth, and snow cover days in the snow cover area of Northern Xinjiang are all the highest. Seasonal changes in the snow cover areas of the Qinghai–Tibet Plateau are the most stable. The snow cover fraction, snow depth, and snow cover days of the three stable snow cover areas are consistent in spatial distribution. The high values are mainly distributed in the southeast and west of the Qinghai–Tibet Plateau, the south and northeast of Northern Xinjiang, and the north of the snow cover area of Northeast China. (2) The future snow changes in the three stable snow cover areas will continue to decline with the increase in development imbalance. Snow cover fraction and snow depth decrease most significantly in the Qinghai–Tibet Plateau and the snow cover days in Northern Xinjiang decrease most significantly under the SSPs585 scenario. In the future, the southeast of the Qinghai–Tibet Plateau, the northwest of Northern Xinjiang, and the north of Northeast China will be the center of snow cover reduction. (3) Under the four different scenarios, the snow cover changes in the Qinghai–Tibet Plateau and Northern Xinjiang are the most significant. Under the SSPs126 and SSPs245 scenarios, the Qinghai–Tibet Plateau snow cover has the most significant change in response. Under the SSPs370 and SSPs585 scenarios, the snow cover in Northern Xinjiang has the most significant change.
Adaptive DDK Filter for GRACE Time-Variable Gravity Field with a Novel Anisotropic Filtering Strength Metric
Authors: Qian Nijia , Chang Guobin , Gao Jingxiang , Shen Wenbin , Yan Zhengwen
Published: June 2022

Filtering for GRACE temporal gravity fields is a necessary step before calculating surface mass anomalies. In this study, we propose a new denoising and decorrelation kernel (DDK) filtering scheme called adaptive DDK filter. The involved error covariance matrix (ECM) adopts nothing but the monthly time-variable released by several data centers. The signal covariance matrix (SCM) involved is monthly time-variable also. Specifically, it is parameterized into two parameters, namely the regularization coefficient and the power index of signal covariances, which are adaptively determined from the data themselves according to the generalized cross validation (GCV) criterion. The regularization coefficient controls the global constraint on the signal variances of all degrees, while the power index adjusts the attenuation of the signal variances from low to high degrees, namely local constraint. By tuning these two parameters for the monthly SCM, the adaptability to the data and the optimality of filtering strength can be expected. In addition, we also devise a half-weight polygon area (HWPA) of the filter kernel to measure the filtering strength of the anisotropic filter more reasonably. The proposed adaptive DDK filter and filtering strength metric are tested based on CSR GRACE temporal gravity solutions with their ECMs from January 2004 to December 2010. Results show that the selected optimal power indices range from 3.5 to 6.9, with the corresponding regularization parameters range from 1 × 1014 to 5 × 1019. The adaptive DDK filter can retain comparable/more signal amplitude and suppress more high-degree noise than the conventional DDK filters. Compared with the equivalent smoothing radius (ESR) of filtering strength, the HWPA has stronger a distinguishing ability, especially when the filtering strength is similar.
Assessment of Moraine Cliff Spatio-Temporal Erosion on Wolin Island Using ALS Data Analysis
Authors: Winowski Marcin , Tylkowski Jacek , Hojan Marcin
Published: June 2022

The aim of the article is to present the temporal and spatial variability of the cliff coast erosion of the Wolin Island in 2012–2020 in three time periods (2012–2015, 2015–2018, 2018–2020). The research used data from airborne laser scanning (ALS), based on which DEM models were made. Based on the differences between the models, the amount of sediment that was eroded by the sea waves was determined. The conducted research showed that, in the analyzed period, the dynamics of the Wolin cliffs were characterized by high variability. The greatest erosion was observed on sandy cliffs, and the smallest on clay cliffs and on cliffs that are densely covered with vegetation. In the sediment budget studies, two seashore erosivity indicators were proposed: length-normalized sediment budget (LB) (m3/m) and area-normalized sediment budget (AB) (m3/m2). The average annual dynamics of the cliff edge erosion on the Wolin Island was found to be LB = 6.6 ± 0.3 m3/m/a, AB = 0.17 ± 0.01 m3/m2/a. The results obtained are comparable with other postglacial cliffs. The use of the differential analysis of DEM models allows for the determination of the dynamics of the cliff coast and may be used in spatial development and planning of seashore protection zones.
Correction: Bulsink et al. Oxygen Saturation Imaging Using LED-Based Photoacoustic System. Sensors 2021, 21, 283
Authors: Bulsink Rianne , Kuniyil Ajith Singh Mithun , Xavierselvan Marvin , Mallidi Srivalleesha , Steenbergen Wiendelt , Francis Kalloor Joseph
Published: June 2022

The authors wish to make the following corrections to this paper [...]
VirtLAB: A Low-Cost Platform for Electronics Lab Experiments
Authors: Ruo Roch Massimo , Martina Maurizio
Published: June 2022

The recent SARS-CoV2 pandemic has put a great challenge on university courses. Electronics teaching requires real laboratory experiences for students, which cannot be realized if access to physical infrastructures is prohibited. A possible solution would be to distribute to students, at home, electronics equipment suitable for laboratory experiments, but no reasonable product is currently available off-the-shelf. In this paper, the design and development of a very-low-cost experimental board tailored to these needs is presented. It contains both programmable prototyping circuitry based on a microcontroller and an FPGA and a set of measurement instruments, similar to the ones found on a typical lab desk, such as a digital storage oscilloscope, multimeter, analog signal generator, logic state analyzer and digital pattern generator. A first board, suitable for analog and digital electronics experiments, has been designed and manufactured, and is described in this paper. The board has been successfully used in master’s degrees and PhD courses.
Evolution and Applications of Recent Sensing Technology for Occupational Risk Assessment: A Rapid Review of the Literature
Authors: Fanti Giacomo , Spinazzè Andrea , Borghi Francesca , Rovelli Sabrina , Campagnolo Davide , Keller Marta , Borghi Andrea , Cattaneo Andrea , Cauda Emanuele , Cavallo Domenico Maria
Published: June 2022

Over the last decade, technological advancements have been made available and applied in a wide range of applications in several work fields, ranging from personal to industrial enforcements. One of the emerging issues concerns occupational safety and health in the Fourth Industrial Revolution and, in more detail, it deals with how industrial hygienists could improve the risk-assessment process. A possible way to achieve these aims is the adoption of new exposure-monitoring tools. In this study, a systematic review of the up-to-date scientific literature has been performed to identify and discuss the most-used sensors that could be useful for occupational risk assessment, with the intent of highlighting their pros and cons. A total of 40 papers have been included in this manuscript. The results show that sensors able to investigate airborne pollutants (i.e., gaseous pollutants and particulate matter), environmental conditions, physical agents, and workers’ postures could be usefully adopted in the risk-assessment process, since they could report significant data without significantly interfering with the job activities of the investigated subjects. To date, there are only few “next-generation” monitors and sensors (NGMSs) that could be effectively used on the workplace to preserve human health. Due to this fact, the development and the validation of new NGMSs will be crucial in the upcoming years, to adopt these technologies in occupational-risk assessment.
Fusion Poser: 3D Human Pose Estimation Using Sparse IMUs and Head Trackers in Real Time
Authors: Kim Meejin , Lee Sukwon
Published: June 2022

The motion capture method using sparse inertial sensors is an approach for solving the occlusion and economic problems in vision-based methods, which is suitable for virtual reality applications and works in complex environments. However, VR applications need to track the location of the user in real-world space, which is hard to obtain using only inertial sensors. In this paper, we present Fusion Poser, which combines the deep learning-based pose estimation and location tracking method with six inertial measurement units and a head tracking sensor that provides head-mounted displays. To estimate human poses, we propose a bidirectional recurrent neural network with a convolutional long short-term memory layer that achieves higher accuracy and stability by preserving spatio-temporal properties. To locate a user with real-world coordinates, our method integrates the results of an estimated joint pose with the pose of the tracker. To train the model, we gathered public motion capture datasets of synthesized IMU measurement data, as well as creating a real-world dataset. In the evaluation, our method showed higher accuracy and a more robust estimation performance, especially when the user adopted lower poses, such as a squat or a bow.
Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain
Authors: Diez Francisco J. , Correa-Guimaraes Adriana , Chico-Santamarta Leticia , Martínez-Rodríguez Andrés , Murcia-Velasco Diana A. , Andara Renato , Navas-Gracia Luis M.
Published: June 2022

This study evaluates the predictive modeling of the daily ambient temperature (maximum, Tmax; average, Tave; and minimum, Tmin) and its hourly estimation (T0h, …, T23h) using artificial neural networks (ANNs) for agricultural applications. The data, 2004–2010, were used for training and 2011 for validation, recorded at the SIAR agrometeorological station of Mansilla Mayor (León). ANN models for daily prediction have three neurons in the output layer (Tmax(t + 1), Tave(t + 1), Tmin(t + 1)). Two models were evaluated: (1) with three entries (Tmax(t), Tave(t), Tmin(t)), and (2) adding the day of the year (J(t)). The inclusion of J(t) improves the predictions, with an RMSE for Tmax = 2.56, Tave = 1.65 and Tmin = 2.09 (°C), achieving better results than the classical statistical methods (typical year Tave = 3.64 °C; weighted moving mean Tmax = 2.76, Tave = 1.81 and Tmin = 2.52 (°C); linear regression Tave = 1.85 °C; and Fourier Tmax = 3.75, Tave = 2.67 and Tmin = 3.34 (°C)) for one year. The ANN models for hourly estimation have 24 neurons in the output layer (T0h(t), …, T23h(t)) corresponding to the mean hourly temperature. In this case, the inclusion of the day of the year (J(t)) does not significantly improve the estimations, with an RMSE = 1.25 °C, but it improves the results of the ASHRAE method, which obtains an RMSE = 2.36 °C for one week. The results obtained, with lower prediction errors than those achieved with the classical methods, confirm the interest in using the ANN models for predicting temperatures in agricultural applications.
Modeling and Analysis of a Composite Structure-Based Soft Pneumatic Actuators for Soft-Robotic Gripper
Authors: Yu Ming , Liu Wenwen , Zhao Jian , Hou Yanyan , Hong Xuewu , Zhang Hongjie
Published: June 2022

Soft pneumatic actuators are extensively used in soft robots, and their bending angles and kinematic rules at different pressures play a crucial role in practical applications. This investigation aims to model the bending angle and motion of a new type of soft pneumatic actuator that adopts a composite structure consisting of two kinds of pneumatic networks. Based on the structural and deformation characteristics of the proposed soft actuator, the constitutive model is established, and then the moment equilibrium and virtual work principle are combined to model the bending angle of two pneumatic modules. The kinematic model of the proposed soft actuator is co-opted from the kinematic modeling of rigid robots. By employing the piecewise constant curvature method and coordinate transformation, the location of any chamber of the soft actuator can be calculated. The effectiveness of the developed analytical models is then tested, and the calculated results show good agreement with the experimental results. Finally, three soft actuators are used to constitute a soft gripper, and the pinching and enveloping grasping performance are examined. All experimental test results demonstrate that the developed bending angle and kinematic models can explain the bending principle of the proposed soft actuators well.
The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise
Authors: Lin Bin , Hu Guoping , Zhou Hao , Zheng Guimei , Song Yuwei
Published: June 2022

Due to the discontinuity of ocean waves and mountains, there are often multipath propagation effects and obvious pulse characteristics in low-altitude detection. If the conventional direction of arrival (DOA) estimation method is directly used for direction finding, it will lead to a large error. In view of serious misalignment in the DOA estimation of multipath signals under the background of impulse noise, a DOA estimation method based on spatial difference and a modified projection subspace algorithm is proposed in this paper. Firstly, the covariance matrix of the received data vector is used for spatial difference to eliminate the multipath effects of low-altitude targets. Secondly, the modified projection matrix is constructed using the signal source estimated with the least squares criterion and then used for modifying the covariance matrix, thus eliminating the cross-covariance matrices that affect the estimation accuracy. Finally, the modified covariance matrix is used for the DOA estimation of targets. Simulations show that the proposed algorithm achieves a higher accuracy in the DOA estimation of low-altitude targets than conventional algorithms under two common impulse noise models, without requiring prior knowledge of impulse noise.
Design of a Robust Tool for Deploying Large-Area Stretchable Sensor Networks from Microscale to Macroscale
Authors: Ransom Elliot , Chen Xiyuan , Chang Fu-Kuo
Published: June 2022

An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the surface of large structures at macroscale to create “smart” structures with embedded distributed sensor networks. Integrating a large network of distributed sensors with structures has been a major challenge in the design of so-called smart structures or devices for cyber-physical applications where a large amount of usage data from structures or devices can be generated for artificial intelligence applications. Indeed, many “island-and-serpentine”-type distributed sensor networks, while promising, remain difficult to deploy. This study aims to enable such networks to be deployed in a safe, automated, and efficient way. To this end, a scissor-hinge controlled system was proposed as the basis for a deployment mechanism for such stretchable sensor networks (SSNs). A model based on a kinematic scissor-hinge mechanism was developed to simulate and design the proposed system to automatically stretch a micro-scaled square network with uniformly distributed sensor nodes. A prototype of an automatic scissor-hinge stretchable tool was constructed during the study with an array of four scissor-hinge mechanisms, each belt-driven by a single stepper motor. Two micro-fabricated SSNs from a 100 mm wafer were fabricated at the Stanford Nanofabrication Facility for this deployment study. The networks were designed to be able to cover an area 100 times their manufacturing size (from a 100 mm diameter wafer to a 1 m2 active area) once stretched. It was demonstrated that the proposed deployment tool could place sensor nodes in prescribed locations efficiently within a drastically shorter time than in current labor-intensive manual deployment methods.
Semi-ProtoPNet Deep Neural Network for the Classification of Defective Power Grid Distribution Structures
Authors: Stefenon Stefano Frizzo , Singh Gurmail , Yow Kin-Choong , Cimatti Alessandro
Published: June 2022

Power distribution grids are typically installed outdoors and are exposed to environmental conditions. When contamination accumulates in the structures of the network, there may be shutdowns caused by electrical arcs. To improve the reliability of the network, visual inspections of the electrical power system can be carried out; these inspections can be automated using computer vision techniques based on deep neural networks. Based on this need, this paper proposes the Semi-ProtoPNet deep learning model to classify defective structures in the power distribution networks. The Semi-ProtoPNet deep neural network does not perform convex optimization of its last dense layer to maintain the impact of the negative reasoning process on image classification. The negative reasoning process rejects the incorrect classes of an input image; for this reason, it is possible to carry out an analysis with a low number of images that have different backgrounds, which is one of the challenges of this type of analysis. Semi-ProtoPNet achieves an accuracy of 97.22%, being superior to VGG-13, VGG-16, VGG-19, ResNet-34, ResNet-50, ResNet-152, DenseNet-121, DenseNet-161, DenseNet-201, and also models of the same class such as ProtoPNet, NP-ProtoPNet, Gen-ProtoPNet, and Ps-ProtoPNet.
Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model
Authors: Kim Jungi , Seo Haneol , Naseem Muhammad Tahir , Lee Chan-Su
Published: June 2022

Walking is an exercise that uses muscles and joints of the human body and is essential for understanding body condition. Analyzing body movements through gait has been studied and applied in human identification, sports science, and medicine. This study investigated a spatiotemporal graph convolutional network model (ST-GCN), using attention techniques applied to pathological-gait classification from the collected skeletal information. The focus of this study was twofold. The first objective was extracting spatiotemporal features from skeletal information presented by joint connections and applying these features to graph convolutional neural networks. The second objective was developing an attention mechanism for spatiotemporal graph convolutional neural networks, to focus on important joints in the current gait. This model establishes a pathological-gait-classification system for diagnosing sarcopenia. Experiments on three datasets, namely NTU RGB+D, pathological gait of GIST, and multimodal-gait symmetry (MMGS), validate that the proposed model outperforms existing models in gait classification.
Quality Models for Artificial Intelligence Systems: Characteristic-Based Approach, Development and Application
Authors: Kharchenko Vyacheslav , Fesenko Herman , Illiashenko Oleg
Published: June 2022

The factors complicating the specification of requirements for artificial intelligence systems (AIS) and their verification for the AIS creation and modernization are analyzed. The harmonization of definitions and building of a hierarchy of AIS characteristics for regulation of the development of techniques and tools for standardization, as well as evaluation and provision of requirements during the creation and implementation of AIS, is extremely important. The study aims to develop and demonstrate the use of quality models for artificial intelligence (AI), AI platform (AIP), and AIS based on the definition and ordering of characteristics. The principles of AI quality model development and its sequence are substantiated. Approaches to formulating definitions of AIS characteristics, methods of representation of dependencies, and hierarchies of characteristics are given. The definitions and harmonization options of hierarchical relations between 46 characteristics of AI and AIP are suggested. The quality models of AI, AIP, and AIS presented in analytical, tabular, and graph forms, are described. The so-called basic models with reduced sets of the most important characteristics are presented. Examples of AIS quality models for UAV video navigation systems and decision support systems for diagnosing diseases are described.
GEF Innovative Forest Management Plan—Taking Grassland Forest Farm in Fengning County as an Example
Authors: Liu Ziye , Feng Zhongke , Chang Chen
Published: June 2022

Currently, China’s forest ecosystem focus is shifting from a single management objective to multiple management objectives, aiming to improve forest quality and maximize the benefits of ecosystem services. Many difficulties and problems are encountered in the long-term development of most northern state-owned forest farms—for example, the fragmentation and degradation of forest landscapes caused by poor forest management and extensive land use—resulting in an ecosystem that is unable to provide optimal services. This research was conducted on the Fengning Grassland Forest Farm, which is based on the GEF project of state-owned forest farms. We applied lessons from international advanced concepts, such as landscape restoration, and combinecombined all types of existing data and supplementary survey data on forest farms. In addition, we used multivariate statistical analysis and geostatistical analysis methods to optimize spatial layout and forest landscape structure. Strategies of landscape restoration and optimization, forest quality improvement, and grassland ecological restoration were proposed. A forest growth model was established to predict the annual growth of forests, calculate sustainable levels of annual cutting, calculate biomass and carbon sequestration in the management period, and evaluate the value of the ecological service functions of forest ecosystems in forest farms. Finally, a set of forest management methods was developed to effectively improve the sustainable management level of state-owned forest farms and enhance the service function of forest ecosystems.
Sustaining the Well-Being of Wearable Technology Users: Leveraging SEM-Based IPMA and VIKOR Analyses to Gain Deeper Insights
Authors: Chuang Huan-Ming , Chen Chien-I
Published: June 2022

Wearable technology is a self-contained computer system that can record muscular activity data. Wearable technologies are rapidly evolving that have the potential to enhance the well-being of healthier lives. However, wearable technologies are finding slow adoption rates relative to mainstream technologies such as smartphones. Consequently, both designers and manufacturers are increasingly interested in key decision factors that influence the acceptance of these technologies. As discussions relating to wearable technologies are often approached from different perspectives, a general framework featuring not only a synthesis of general acceptance issues but also with consideration of contingent factors would be a useful research undertaking. Furthermore, wearable technology acceptance studies are insufficient to supplement practical implementation and promotion issues. In this regard, methods for further analysis of results from structural equation modeling (SEM), such as importance-performance map analysis (IPMA) and VIKOR for multi-criteria optimization and compromise solution, can be used to derive greater insights. The primary research findings are extensively discussed, and practical promotion strategies for wearable technologies for health care are suggested.
Comparison of Consuming Habits on Organic Food—Is It the Same? Hungary Versus China
Authors: Wu Yue , Takács-György Katalin
Published: June 2022

Organic food, a name for healthy food and sustainable or green food consumption, has become popular worldwide. Especially due to the COVID-19 pandemic, the demand for healthy food is increasing worldwide. In order to better understand consumer behavior toward organic food between different countries in different adoption stages of organic food and provide valuable information for industrial practitioners and researchers. We conducted a comparative study between Hungary and China. The organic food market is well developed in Hungary, while the market is starting to be popular in China. What factors can affect consumers buying organic food in Hungary and China? And what can be an efficient marketing tool for consumers to buy organic food in Hungary and China? The English and Chinese version surveys were conducted from 374 Chinese respondents and 207 Hungarian respondents by convenient sampling methods from March 2021 to April 2021, and the data were analyzed by SPSS software for correlation analysis. The statistical analysis results concluded that personal characteristics influence consumer behavior in Hungary and China, such as age, education level, occupation, living area scale, income, and gender. The dominant reason for Hungarian and Chinese respondents to buy organic food is food safety and health and environmentally friendly. And the reason for them to refuse organic food purchases is the high price, which is different from the previous study in Hungary. The most welcomed organic food product is organic fruits and organic vegetables in Hungary and China. The most efficient marketing tool for them to buy organic food is social media. And different marketing tools combination varies in Hungary and China. Hungarian respondents are more willing to buy organic food, while Chinese respondents are happier to recommend organic food to other consumers.
Design of Robust Integral Terminal Sliding Mode Controllers with Exponential Reaching Laws for Solar PV and BESS-Based DC Microgrids with Uncertainties
Authors: Yeasmin Sabrina , Roy Tushar Kanti , Ghosh Subarto Kumar
Published: June 2022

In this paper, an integral terminal sliding mode controller (ITSMC) based on a modified exponential reaching law (MERL) is developed for providing large-signal DC-bus voltage stability while smoothing power flow in DC microgrids (DCMGs). It is worth mentioning that this control approach is not employed in DCMG applications yet to adjust the DC-bus voltage while preserving power balance. The proposed DCMG is made up of a solar photovoltaic (PV) unit, a battery energy storage system (BESS), and DC loads. A DC-DC boost converter (DDBC) and a bidirectional DC-DC converter (BDDC) are employed to connect the solar PV and BESS, respectively, with the DC-bus, which not only controls the output power of these units but also regulates the DC-bus voltage. First, a detailed dynamical model including external disturbances is developed for each component, i.e., the solar PV and BESS. Then, the proposed control approach is employed on these units to get their corresponding control signals. Afterward, the overall stability of each unit is ensured using the Lyapunov stability theory. Moreover, to ensure the robustness of the proposed controller, external disturbances are also bounded based on the value of user-defined constants. Finally, simulation results are used to evaluate the effectiveness of the proposed control approach in a variety of operational scenarios. Additionally, simulation results of the proposed control strategy are compared to those of existing controllers to demonstrate its superiority.
Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution
Authors: Mhlanga David
Published: June 2022

Artificial intelligence (AI) is currently being developed by large corporations, and governments all over the world are yearning for it. AI isn’t a futuristic concept; it is already here, and it is being implemented in a range of industries. Finance, national security, health care, criminal justice, transportation, and smart cities are all examples of this. There are countless examples of AI having a substantial impact on the world and complementing human abilities. However, due to the immense societal ramifications of these technologies, AI is on the verge of disrupting a host of industries, so the technique by which AI systems are created must be better understood. The goal of the study was to look at what it meant to be human-centred, how to create human-centred AI, and what considerations should be made for human-centred AI to achieve sustainability and the SDGs. Using a systematic literature review technique, the study discovered that a human-centred AI strategy strives to create and implement AI systems in ways that benefit mankind and serve their interests. The study also found that a human-in-the-loop concept should be used to develop procedures for creating human-centred AI, as well as other initiatives, such as the promotion of AI accountability, encouraging businesses to use autonomy wisely, to motivate businesses to be aware of human and algorithmic biases, to ensure that businesses prioritize customers, and form multicultural teams to tackle AI research. The study concluded with policy recommendations for human-centred AI to help accomplish the SDGs, including expanding government AI investments, addressing data and algorithm biases, and resolving data access issues, among other things.
Historic Churches and Their Hygrothermal Environment: A Review of Criteria Related to Building Fabric, Artefacts, Artwork and Occupants
Authors: Talbot Robin , Picco Marco , Greenfield David , Ashton Philip , Arbuthnot Emma , Hashemi Arman
Published: June 2022

Regarded as important cultural heritage, historic churches have been utilised over hundreds of years for worship and community benefit. Simple on/off space heating systems are installed in many churches to increase human comfort. However, the conservation of the important historic artefacts and artwork contained within may not have been fully considered. This review attempts to appraise the standards in place for artefacts and artwork. A consensus of 15–25 °C and 40–65% relative humidity is established as safe from the standards reviewed. Consideration is given to the environment within the church to understand if such exacting conditions can be met. The review finds that the conservation and preservation of artefacts and buildings are aligned goals, although striving to meet specified target ranges for artefact types is not fully compatible with historic churches. The stability of the internal environment is clearly an important factor in conservation and benefits human comfort expectations. Churches may contain microclimates throughout the building, complicating the use of target ranges for artefacts, artwork and comfort. The findings of this study can assist historic churches in managing the change, alteration or installation of heating systems.
Research on the Load Transfer Law of Cross-Sections of Pile-Supported Reinforced Embankments Based on the Finite Element Method
Authors: Wang Xin , Wang Xizhao , Yang Guangqing , Yang Xiang , Zhang Da
Published: June 2022

Combining field test research with finite element numerical analysis, this paper studies the mechanical behavior of pile-supported reinforced embankments in soft soil areas. We analyze and compare the variation law of load transfer efficacy at the subgrade center, the right side of the centerline, and the road shoulder; the variations of the load sharing ratios of the soil arching effect and the load sharing ratios of the membrane effect; and the load variation law of wide subgrade cross-sections. Then, the model calculation results are compared with the calculation results of the five theoretical methods and the applicability of the various methods is evaluated. The results show that: increasing the pile length, pile cap width, and embankment height and reducing the pile spacing will increase the pile load transfer efficacy; pile cap width has the greatest influence on the load transfer efficacy; regarding the variation law of the load sharing ratios of subgrade cross-sections, the load-sharing ratio of the soil arch effect at the shoulder is smaller than that at the center of the subgrade, indicating that the deformation of the geogrid at the shoulder is large and the membrane effect is significant; and, regarding the load variation law of subgrade cross-sections, from the subgrade center to the shoulder direction, the pile load transfer efficacy decreases gradually and the load transfer efficacy at the shoulder decreases significantly.
Islands as Playing and Breeding Grounds for Incumbents, Entrepreneurial Technologists, Policymakers, and Engaged Citizens: The Case of Energy Transition on Ameland
Authors: van Dam Karin I. M. , van der Windt Henny J.
Published: June 2022

Increasingly, discussions on sustainability, in particular in relation to energy transition, are finding their way to the regional and local political arena. Although for analysing transition pathways on these sub-national scales, conceptual frameworks such as the multi-level perspective may be helpful, some issues remain relatively unaddressed: the relevance of citizens and their social networks and the precise interactions between place, the local context, and external conditions. This paper aims to better understand energy transition processes on the local and regional scale by analysing the case of the Dutch island of Ameland. Since 2006, Ameland has been on a sustainability pathway towards self-sufficiency, in particular in terms of reducing CO2 emissions. In this case study, we conducted in-depth empirical analysis, using a mixed-methods approach, including document analysis and ethnographic techniques. In a five-stage development process, a combination of place-related niche development, regime developments, and the involvement of citizens have created a protective space for several socio-technological innovations to emerge. The unique combination of specific local conditions, in particular political and cultural, and external influences, national policy, and ‘enlightened’ companies have shaped ideal conditions for Ameland to become an inspiring example of innovation in regional transition processes.
Consumer Behavior in Online-to-Offline (O2O) Commerce: A Thematic Review
Authors: Yao Pinyi , Osman Syuhaily , Sabri Mohamad Fazli , Zainudin Norzalina
Published: June 2022

Online-to-offline (O2O) commerce is a popular business model which links offline business activities with online channels. Consumer behavior in O2O commerce is more complex than in other traditional business models as both online and offline channels are involved. Despite the growing number of publications focused on this issue, no review paper has discussed the current research trends and factors influencing consumer behavior in O2O commerce. Therefore, this review aimed to synthesize literature on O2O commerce from 2015 to April 2022, focusing on consumer behavior. A set of inclusion and exclusion criteria was developed for searching and screening articles from two dominant databases (i.e., WOS and Scopus), and 53 eligible articles were included in this review. A thematic review approach using ATLAS.ti 9 software was conducted. Quantitative results presented the research trends of O2O commerce. Qualitative analyses generated eight main clusters of factors which influence consumers’ O2O behavior: (1) service and product quality, (2) technical and utilitarian factors, (3) emotional and hedonic factors, (4) trust and risk, (5) price and cost (6), social factors, (7) online content, and (8) habit. This paper also highlighted promising future research directions. The findings are expected to benefit the sustainable management and the future research of O2O commerce.