bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study
Authors: Nguyen Hung-Cuong , Nguyen Thi-Hao , Scherer Rafał , Le Van-Hung
Published: May 2023

Human activity recognition (HAR) is an important research problem in computer vision. This problem is widely applied to building applications in human–machine interactions, monitoring, etc. Especially, HAR based on the human skeleton creates intuitive applications. Therefore, determining the current results of these studies is very important in selecting solutions and developing commercial products. In this paper, we perform a full survey on using deep learning to recognize human activity based on three-dimensional (3D) human skeleton data as input. Our research is based on four types of deep learning networks for activity recognition based on extracted feature vectors: Recurrent Neural Network (RNN) using extracted activity sequence features; Convolutional Neural Network (CNN) uses feature vectors extracted based on the projection of the skeleton into the image space; Graph Convolution Network (GCN) uses features extracted from the skeleton graph and the temporal–spatial function of the skeleton; Hybrid Deep Neural Network (Hybrid–DNN) uses many other types of features in combination. Our survey research is fully implemented from models, databases, metrics, and results from 2019 to March 2023, and they are presented in ascending order of time. In particular, we also carried out a comparative study on HAR based on a 3D human skeleton on the KLHA3D 102 and KLYOGA3D datasets. At the same time, we performed analysis and discussed the obtained results when applying CNN-based, GCN-based, and Hybrid–DNN-based deep learning networks.
The Analytical and Clinical Validity of the pfSTEP Digital Biomarker of the Susceptibility/Risk of Declining Physical Function in Community-Dwelling Older Adults
Authors: Schoenfelder Alexander , Metcalf Brad , Langford Joss , Stathi Afroditi , Western Max J. , Hillsdon Melvyn
Published: May 2023

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83–0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53–0.68 and 0.55, 95% CI 0.46–0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32–0.74). We have validated a digital susceptibility/risk biomarker—pfSTEP—that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.
A Linearly Polarized Wavelength-Tunable Q-Switched Fiber Laser with a Narrow Spectral Bandwidth of 112 MHz
Authors: Zhu Chengjie , Yang Xuezong , Liu Yuxuan , Li Muye , Sun Yuxiang , You Wei , Dong Peng , Chen Dijun , Feng Yan , Chen Weibiao
Published: May 2023

A tunable and narrow-bandwidth Q-switched ytterbium-doped fiber (YDF) laser is investigated in this paper. The non-pumped YDF acts as a saturable absorber and, together with a Sagnac loop mirror, provides a dynamic spectral-filtering grating to achieve a narrow-linewidth Q-switched output. By adjusting an etalon-based tunable fiber filter, a tunable wavelength from 1027 nm to 1033 nm is obtained. When the pump power is 1.75 W, the Q-switched laser pulses with a pulse energy of 10.45 nJ, and a repetition frequency of 11.98 kHz and spectral linewidth of 112 MHz are obtained. This work paves the way for the generation narrow-linewidth Q-switched lasers with tunable wavelengths in conventional ytterbium, erbium, and thulium fiber bands to address critical applications such as coherent detection, biomedicine, and nonlinear frequency conversion.
Analysis of Polarization Detector Performance Parameters on Polarization 3D Imaging Accuracy
Authors: Dai Pengzhang , Yao Dong , Ma Tianxiang , Shen Honghai , Wang Weiguo , Wang Qingyu
Published: May 2023

Three-dimensional (3D) reconstruction of objects using the polarization properties of diffuse light on the object surface has become a crucial technique. Due to the unique mapping relation between the degree of polarization of diffuse light and the zenith angle of the surface normal vector, polarization 3D reconstruction based on diffuse reflection theoretically has high accuracy. However, in practice, the accuracy of polarization 3D reconstruction is limited by the performance parameters of the polarization detector. Improper selection of performance parameters can result in large errors in the normal vector. In this paper, the mathematical models that relate the polarization 3D reconstruction errors to the detector performance parameters including polarizer extinction ratio, polarizer installation error, full well capacity and analog-to-digital (A2D) bit depth are established. At the same time, polarization detector parameters suitable for polarization 3D reconstruction are provided by the simulation. The performance parameters we recommend include an extinction ratio ≥ 200, an installation error ∈ [−1°, 1°], a full-well capacity ≥ 100 Ke−, and an A2D bit depth ≥ 12 bits. The models provided in this paper are of great significance for improving the accuracy of polarization 3D reconstruction.
Multi-Sensor Platform for Predictive Air Quality Monitoring
Authors: Rescio Gabriele , Manni Andrea , Caroppo Andrea , Carluccio Anna Maria , Siciliano Pietro , Leone Alessandro
Published: May 2023

Air quality monitoring is a very important aspect of providing safe indoor conditions, and carbon dioxide (CO2) is one of the pollutants that most affects people’s health. An automatic system able to accurately forecast CO2 concentration can prevent a sudden rise in CO2 levels through appropriate control of heating, ventilation and air-conditioning (HVAC) systems, avoiding energy waste and ensuring people’s comfort. There are several works in the literature dedicated to air quality assessment and control of HVAC systems; the performance maximisation of such systems is typically achieved using a significant amount of data collected over a long period of time (even months) to train the algorithm. This can be costly and may not respond to a real scenario where the habits of the house occupants or the environment conditions may change over time. To address this problem, an adaptive hardware–software platform was developed, following the IoT paradigm, with a high level of accuracy in forecasting CO2 trends by analysing only a limited window of recent data. The system was tested considering a real case study in a residential room used for smart working and physical exercise; the parameters analysed were the occupants’ physical activity, temperature, humidity and CO2 in the room. Three deep-learning algorithms were evaluated, and the best result was obtained with the Long Short-Term Memory network, which features a Root Mean Square Error of about 10 ppm with a training period of 10 days.
Multisensor Data Fusion in IoT Environments in Dempster–Shafer Theory Setting: An Improved Evidence Distance-Based Approach
Authors: Hamda Nour El Imane , Hadjali Allel , Lagha Mohand
Published: May 2023

In IoT environments, voluminous amounts of data are produced every single second. Due to multiple factors, these data are prone to various imperfections, they could be uncertain, conflicting, or even incorrect leading to wrong decisions. Multisensor data fusion has proved to be powerful for managing data coming from heterogeneous sources and moving towards effective decision-making. Dempster–Shafer (D–S) theory is a robust and flexible mathematical tool for modeling and merging uncertain, imprecise, and incomplete data, and is widely used in multisensor data fusion applications such as decision-making, fault diagnosis, pattern recognition, etc. However, the combination of contradictory data has always been challenging in D–S theory, unreasonable results may arise when dealing with highly conflicting sources. In this paper, an improved evidence combination approach is proposed to represent and manage both conflict and uncertainty in IoT environments in order to improve decision-making accuracy. It mainly relies on an improved evidence distance based on Hellinger distance and Deng entropy. To demonstrate the effectiveness of the proposed method, a benchmark example for target recognition and two real application cases in fault diagnosis and IoT decision-making have been provided. Fusion results were compared with several similar methods, and simulation analyses have shown the superiority of the proposed method in terms of conflict management, convergence speed, fusion results reliability, and decision accuracy. In fact, our approach achieved remarkable accuracy rates of 99.32% in target recognition example, 96.14% in fault diagnosis problem, and 99.54% in IoT decision-making application.
Comparison of Grip Strength, Forearm Muscle Activity, and Shock Transmission between the Forehand Stroke Technique of Experienced and Recreational Tennis Players Using a Novel Wearable Device
Authors: Rigozzi Chantelle Jean , Vio Gareth A. , Poronnik Philip
Published: May 2023

Upper limb tennis injuries are primarily chronic, resulting from repetitive overuse. We developed a wearable device which simultaneously measures risk factors (grip strength, forearm muscle activity, and vibrational data) associated with elbow tendinopathy development resulting from tennis players’ technique. We tested the device on experienced (n = 18) and recreational (n = 22) tennis players hitting forehand cross-court at both flat and topspin spin levels under realistic playing conditions. Using statistical parametric mapping analysis, our results showed that all players showed a similar level of grip strength at impact, regardless of spin level, and the grip strength at impact did not influence the percentage of impact shock transfer to the wrist and elbow. Experienced players hitting with topspin exhibited the highest ball spin rotation, low-to-high swing path brushing action, and shock transfer to the wrist and elbow compared to the results obtained while hitting the ball flat, or when compared to the results obtained from recreational players. Recreational players exhibited significantly higher extensor activity during most of the follow through phase compared to the experienced players for both spin levels, potentially putting them at greater risk for developing lateral elbow tendinopathy. We successfully demonstrated that wearable technologies can be used to measure risk factors associated with elbow injury development in tennis players under realistic playing conditions.
Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence
Authors: Kashani Zadeh Hossein , Hardy Mike , Sueker Mitchell , Li Yicong , Tzouchas Angelis , MacKinnon Nicholas , Bearman Gregory , Haughey Simon A. , Akhbardeh Alireza , Baek Insuck , Hwang Chansong , Qin Jianwei , Tabb Amanda M. , Hellberg Rosalee S. , Ismail Shereen , Reza Hassan , Vasefi Fartash , Kim Moon , Tavakolian Kouhyar , Elliott Christopher T.
Published: May 2023

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and quadratic discriminant analyses, k-nearest neighbors, random forest, support vector machine, and linear regression, as well as ensemble and majority voting methods, were used to explore spectroscopy data measured on fillets and to train classification models to predict freshness. Our results show that multi-mode spectroscopy achieves 95% accuracy, improving the accuracies of the FL, VIS-NIR and SWIR single-mode spectroscopies by 26, 10 and 9%, respectively. We conclude that multi-mode spectroscopy and data fusion analysis has the potential to accurately assess freshness and predict shelf life for fish fillets and recommend this study be expanded to a larger number of species in the future.
A User-Centered Design Exploration of Factors That Influence the Rideshare Experience
Authors: Gangadharaiah Rakesh , Su Haotian , Rosopa Elenah B. , Brooks Johnell O. , Kolodge Kristin , Boor Lisa , Rosopa Patrick J. , Jia Yunyi
Published: May 2023

The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factor analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = −0.63) and comfort/ease of use (B = −0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.
Corn Cropping System and Nitrogen Fertilizers Technologies Affect Ammonia Volatilization in Brazilian Tropical Soils
Authors: Santos César , Pinto Sheila Isabel do Carmo , Guelfi Douglas , Rosa Sara Dantas , da Fonseca Adrianne Braga , Fernandes Tales Jesus , Ferreira Renato Avelar , Satil Leandro Barbosa , Nunes Ana Paula Pereira , e Silva Konrad Passos
Published: May 2023

The adoption of technologies for N fertilization has become essential for increasing the N use efficiency in no-till (NT) systems in Brazil. Thus, this study aimed to quantify ammonia losses, N removal in grains, and second crop season yield in no-till and conventional (T) areas that received the application of different N fertilizers and their technologies. Ammonia volatilization, N extraction in grains, and corn yield in response to the application of conventional fertilizers were compared to urea treated with urease inhibitors in NT and conventional systems. The treatments were: no-N (Control); Prilled urea (PU); urea + N-(n-Butyl) thiophosphoric triamide (UNBPT); urea + Cu + B (UCuB); ammonium nitrate (AN), and ammonium sulfate (AS). In the NT system, the N-NH3 losses were 49% higher than in the conventional; without differences in corn yield. The fertilizers AN and AS had the lowest N-NH3 losses, regardless of the tillage system. UNBPT reduced the mean N-NH3 loss by 33% compared to PU. UNBPT (1200 mg kg−1) and UNBPT (180 mg kg−1) reduced the N-NH3 losses by 72% and 22%, respectively, compared to PU in the NT system. We noticed that the NBPT concentration to be used in soils under NT should be adjusted, and a reduction of N-NH3 losses does not directly reflect an increase in yield and N extraction by corn.
Investigating the Impact of Green Natural Resources and Green Activities on Ecological Footprint: A Perspective of Saudi Vision 2030
Authors: Aziz Ghazala , Waheed Rida , Alsaggaf Majid Ibrahim
Published: May 2023

The purpose of this study was to develop a deep understanding of the interactions between the ecological footprint, forest resources, land resources, environmental technology, and renewable energy consumption in Saudi Arabia. The study uses the data from 1980 to –2019 for econometric analysis. The findings of nonlinear ARDL estimates have reported the significance of forest and land resources to curtail the ecological footprint. Environmental technology and renewable energy empirical outcomes are insignificant in pre-Vision 2030 analyses, but become negative and significant in positive shock analyses. These results underscore that Saudi Vision 2030 has proposed workable and practical policies to address environmental challenges. Considering these findings, policymakers should implement beneficial policies that manage the country’s natural resources to reduce the ecological footprint and achieve the goals of Vision 2030.
The Influence of Islamic Values on Sustainable Lifestyle: The Moderating Role of Opinion Leaders
Authors: Mohamad Saleh Mohamad Saifudin , Mehellou Ali , Omar Bahiyah
Published: May 2023

Influential and trusted opinion leaders play a crucial role in society, particularly in influencing the public about values and lifestyle aspects. However, studies that have explored the impact of opinion leaders on a sustainable lifestyle and Islamic values in a Muslim-majority country such as Malaysia are scarce. Hence, this present study investigated the moderating effect of opinion leaders on the relationship between Islamic values derived from Maqasid Shariah and a sustainable lifestyle in Malaysia. The two methods deployed in this study were survey and in-depth interviews. Data retrieved from 682 questionnaires completed by Malaysian respondents were analysed using Smart PLS. The outcomes showed that, among the five proposed hypotheses, only one was accepted—the moderating effect of opinion leaders on the relationship between preserving intellect and a sustainable lifestyle. In-depth interview sessions were held with 18 respondents encompassing Islamic figures, environmentalists, and survey respondents. Most respondents claimed that the role of opinion leaders is important, and a healthy mind (preserving intellect) should be the priority to achieve a sustainable lifestyle. The study outcomes may serve as a reference for the Malaysian government to devise effective plans for sustainable lifestyle education by incorporating the Islamic framework.
The Protection of the Capacity for Resilience in the Provision of Drinking Water from Hybrid Environmental Policy Instruments
Authors: Vargas-Cano John Harvey , Tobón-Orozco David , Vasco-Correa Carlos
Published: May 2023

The use of hybrid environmental policy instruments is an open research topic, particularly in the case of water resources protection. We analyzed the influence of hybrids between command-and-control regulation (CAC) and environmental taxes where the body of water’s capacity for resilience and drinking water supply are critically affected by pollution accumulation over time. We used a general equilibrium model in which it is assumed that a representative company pollutes water bodies with its production and can use pollution abatement technologies to comply with environmental regulations. These water bodies are used by a public utility that provides drinking water to the economy. This paper focuses on the review of the Colombian CAC environmental regulation, which moved from controlling a percentage of pollution to defining specific amounts of pollutants discharged, and its interaction with an environmental tax, which makes it a hybrid policy. Although the new CAC is stricter in principle, we conclude that for different values of the model parameters, a hybrid environmental policy requires periodic revision of pollutant discharge limits as well as a complementary environmental tax that approximates the Pigouvian tax to ensure water bodies’ resilience.
Interdisciplinary Teaching Reform of Financial Engineering Majors Based on the Analytic Hierarchy Process in the Post-Pandemic Era
Authors: Xiong Lihui , Dong Ximiao , Fang Jiaqi
Published: May 2023

In the post-epidemic era, the labor market has become increasingly complex, making it even more crucial to incorporate sustainability into employment demand. As we enter the post-pandemic era, a globalization trend has become more apparent. It is crucial to modernize employability through educational reform in order to assist employees in enhancing their professional skills. This study began by analyzing the importance of financial engineering practice instruction and graduate employability in the post-epidemic era. Second, the study proposed the content and a plan for inter-disciplinary teaching reform to address talent cultivation needs based on labor market requirements. Third, a face-to-face survey and interview were conducted with students affected by changes in teaching, and the results were analyzed and summarized. On this basis, the impact of education reform was evaluated using both the expert scoring method and the analytic hierarchy approach. The results indicated that the suggested financial engineering teaching reform program improved the school’s discipline strength, enrollment rate, employment rate, and competition awards, especially discipline strength. This research can be used to inform the teaching of financial engineering majors in various countries, assist job candidates in enhancing their professional skills, and build a formidable talent pool for the labor market.
Integrated Thermodynamic and Control Modeling of an Air-to-Water Heat Pump for Estimating Energy-Saving Potential and Flexibility in the Building Sector
Authors: Kumar Dhirendran Munith , Catrini Pietro , Piacentino Antonio , Cirrincione Maurizio
Published: May 2023

Reversible heat pumps are increasingly adopted for meeting the demand for space heating and cooling in buildings. These technologies will play a key role not only in the decarbonization of space air conditioning but also in the development of 100% renewable energy systems. However, to assess the achievable benefits through the adoption of these technologies in novel applications, reliable models are needed, capable of simulating both their steady-state operation and dynamic response at different conditions in terms of heating loads, outdoor temperatures, and so on. The operation of heat pumps is often investigated by highly simplified models, using performance data drawn from catalogs and paying scarce attention to the critical influence of controllers. In this respect, this paper proposed an integrated thermodynamic and control modeling for a reversible air-to-water heat pump. The study considered a heat pump alternatively equipped with variable-speed compressors and constant-speed compressors with sequential control. The developed modeling was then used to investigate the operation of an air-to-water heat pump serving an office building in Italy. Results show that the model provided insights into the transient operation of variable-speed heat pumps (e.g., the settling time). Regarding constant-speed heat pumps, the model provided hints of interest to the control engineer to prevent, in the examined case study, the risk of quick compressors cycling on low-load heating days or when low-temperature heating devices are supplied. Finally, using a control strategy based on a heating curve for the variable-speed heat pump, results show the potential for a sensible increase in the average coefficient of performance, from 17% up to 50%.
Environmental and Social Performance of the Banking Industry in Bangladesh: Effect of Stakeholders’ Pressure and Green Practice Adoption
Authors: Islam Md. Shajul , Rubel Mohammad Rabiul Basher , Hasan Md. Mahedi
Published: May 2023

The concepts of Stakeholders’ Pressure (SP), Environmental Performance (EP), and Corporate Social Performance (CSP) are well established in the business of progressive firms. However, firms are yet to examine the effects of Stakeholders’ Pressure (SP) on environmental performance (EP) and Corporate Social Performance (CSP) by connecting the missing linkage of Green Practice Adoption (GPA). The present study explored the association between Stakeholders’ Pressure (SP), Environmental Performance (EP), and Corporate Social Performance (CSP) through the mediating effect of Green Practice Adoption (GPA). The study’s objective was to determine the factors to propose a model for the environmental and social performance of the banking industry in the Bangladesh context. The study assessed the hypotheses using partial least squares-based structural equation modeling with data from 540 line managers from 30 private commercial banks. The results indicate that SP significantly improves EP, CSP, and GPA. On the other hand, GPA showed a substantial accepted effect on EP and CSP. Furthermore, mediation analysis showed that GPA mediates the relationship between SP with EP and CSP. This research fills the gap in the domain of the Environmental and Social Performance of the Banking Industry in Bangladesh. From this study, the academicians may get fresh antecedents of the environmental performance management approach. Thus, the study’s outcomes may give valuable insights to policymakers and managers and provide them with practical evidence to proactively implement SP in firms because such practices positively impact EP and CSP through the mediation of GPA. This result may improve operational efficiency and provide firms with a superior reputation.
Structural Relationship between Ecotourism Motivation, Satisfaction, Place Attachment, and Environmentally Responsible Behavior Intention in Nature-Based Camping
Authors: Kim Kyungsik , Wang Yongdi , Shi Jianmin , Guo Wangda , Zhou Zixiang , Liu Zhaoyong
Published: May 2023

This study aims to make an investigation on the relationship between ecotourism motivation (EM), satisfaction (SA), place attachment (PA), and environmentally responsible behavior intention (ER) based on the analysis of camping tourism andstudy the mediating roles of SA and PA in the relationship between EM and ER. A questionnaire-based survey was conducted on 400 camping tourists who visited the Yunnan Province of China within the last year. The distribution of survey questionnaires range from 12 February 2023–24 February 2023. The results reveal that EM positively influences SA, PA, and ER, whereas, although SA positively impacts PA, it does not significantly affect ER. In contrast, PA positively affects ER. Furthermore, PA has a positive mediating impact on the relationship between EM and ER, whereas, SA does not significantly mediate this relationship. Finally, SA and PA act as chain mediators between EM and ER. The findings contribute to the tourism literature by shedding light on the complex relationships between EM, SA, PA, and ER in the context of camping tourism, thereby, enhancing tourist satisfaction and promoting environmentally responsible behavior, thus, contributing to the growth of a sustainable camping industry.
The Impact of Ecological Governance on Industrial Structure Upgrading under the Dual Carbon Target
Authors: You Siqing , Zhao Han , Zhou Hongli , Zhang Chaoyu , Li Zican
Published: May 2023

Under China’s goal of “carbon neutrality”, appropriate ecological governance is crucial for upgrading the industrial structure, and too strict or loose governance will have a negative effect. In order to find the optimal range for ecological governance efforts, the concept of the industrial low-carbon index was defined based on the comparison of industrial carbon emissions and output value. The industrial structure was measured from two dimensions: overall upgrading and internal optimization of the industry. We innovatively use multiple indicators to represent the core explanatory variables and use the coefficient of variation method to calculate them. A threshold regression model for ecological governance and industrial structure based on the above indicator system was built, using indicator data from 288 cities in China over the past 15 years for empirical analysis. The study found that (1) ecological governance has a threshold effect on the overall upgrading and internal optimization of the industrial structure, and overall efforts need to be increased for ecological governance; (2) the governance intensity for different cities needs to be determined according to their economic levels and local conditions; and (3) the industrial structure gap among cities will gradually narrow, and the overall development tends to be balanced.
The Potential of Battery Electric Taxis in Santiago de Chile
Authors: Yushimito Wilfredo F. , Moreno Sebastian , Miranda Daniela
Published: May 2023

Given the semi-private nature of the mode, the conversion of taxi vehicles to electric requires a feasibility analysis, as it can impact their operations and revenues. In this research, we assess the feasibility of taxi companies in Santiago de Chile operating with battery electric vehicles (BEVs), considering the current electric mobility infrastructure of the city. We used a large database of GPS pulses provided by a taxi app to obtain a complete picture of typical taxi trips and operations in the city. Then, we performed an assessment of the feasibility of the fleet conversion by considering battery capacity, driving range, proximity to recharging stations, and charging power. The results are promising, as the number of completed trips ranges from 87.35% to 94.34%, depending on the BEV driving range. The analysis shows the importance of installing fast charging points in the locations or BEV driving ranges.
Comparative Experiment and Analysis of a Base-Isolated Structure with Small Aspect Ratio on Multi-Layered Soft Soil Foundation and Rigid Foundation
Authors: Yu Xu , Shan Zhicheng , Zhuang Haiyang , Chen Guoxing
Published: May 2023

Through conducting a comparative experimental study of small-aspect-ratio isolated structure models on multi-layered soft soil foundations and rigid foundations, this paper investigates the influence of soil–structure interaction (SSI) effects on the seismic response of small-aspect-ratio isolated structures on multi-layered soft soil foundations. An energy balance equation for isolated structure systems considering SSI effects is proposed, and the impact of SSI effects on the energy dissipation response of small-aspect-ratio isolated structures on multi-layered soft soil foundations is analyzed in depth. The analysis results reveal that SSI effects on multi-layered soft soil foundations reduce the first-order natural frequency of the isolated structure system and significantly increase the damping ratio of the system. Furthermore, the rotational effect of the isolated structure foundation is significant on multi-layered soft soil foundations, and the isolation layer has a certain amplification effect on the rotational effect of the foundation. The study shows that SSI effects on multi-layered soft soil foundations may either increase or decrease the seismic response of isolated structures. Moreover, due to the influence of SSI effects, the ratios of kinetic energy, damping energy dissipation, and hysteresis deformation energy dissipation of the isolated structure on multi-layered soft soil foundations are significantly different from those on rigid foundations. The research concludes that the influence of SSI effects is more significant during large earthquakes, where the ratios of kinetic energy and damping energy dissipation of the isolated structure increase, the hysteresis deformation energy dissipation ratio of the isolation layer decreases, and the magnitude of the decrease is related to the characteristics of the input seismic motion. This research has significant implications for improving the seismic design theory of small-aspect-ratio isolated structures on multi-layered soft soil foundations.
Has Digital Village Construction Improved Rural Family Resilience in China? Evidence Based on China Household Finance Survey
Authors: Cai Zheng , Li Shengsheng , Cheng Di
Published: May 2023

The development of digital village construction to improve rural family resilience (RFR) is emerging as a key focus area and target of China’s rural revitalization strategy. However, there is limited evidence available on the impacts of digital village construction on RFR measures. This paper aimed to examine the effect and mechanism of digital village construction on rural family resilience based on the micro panel data of the China Household Finance Survey (CHFS) from 2015 to 2019 to empirically test the effect and mechanism of targeted digital village construction on the resilience of rural family. This research also examined the role of farmers’ entrepreneurial dynamism in the process. Unlike previous studies, we included family welfare into the measurement framework of RFR. Therefore, RFR was represented by the probability that household welfare exceeds a certain standard. The research found that rural communities quickly transformed from one stable state to another when the external shocks exceeded the threshold of rural resilience. The development of digital village construction can effectively reduce the probability of changing the existing steady state when rural families face shocks. At the national level, farmers’ entrepreneurial dynamism had a positive moderating effect on the RFR of the digital village. In the more developed eastern region, digital village construction was relatively advanced and had a significant effect on farmers’ income growth. Conversely, the digital village construction in the central, northeastern, and western regions was less developed; moreover, it had a weaker impact than that in the eastern area. Therefore, the regional reality and gap should be fully considered when constructing a digital village.
The Impact of Corporate Social Responsibility on Speed of OFDI under the Belt and Road Initiative
Authors: Wang Xianjing , Chen Shouming , Wang Yueqi
Published: May 2023

Since the implementation of the Belt and Road Initiative (BRI), Chinese firms have actively responded to the government’s call to accelerate outward foreign direct investment (OFDI). Based on resource dependence theory and institutional theory, this study investigates the impact of corporate social responsibility (CSR) on the speed of OFDI under BRI and its boundary conditions. The results show that CSR can promote the speed of OFDI under BRI because CSR can help a firm accumulate strategic resources, including external benefits such as a good corporate image, and internal resources such as human capital and dynamic capabilities, and thus enhance legitimacy in host countries and its ability to resist potential risks. We also find that both state ownership and CEO political connections weaken the positive effect of CSR, and if the firm is in the key provinces or key industries of BRI, the positive relationship between CSR and the speed of OFDI under BRI will decrease. Our study contributes to the literature on international business and provides suggestions for firms participating in BRI.
Insights into the Distribution of Soil Organic Carbon in the Maoershan Mountains, Guangxi Province, China: The Role of Environmental Factors
Authors: Wang Hailun , Wang Jiachen , Wang Jinye , Yan Wende
Published: May 2023

The forest ecosystem is the largest carbon reservoir in the terrestrial ecosystem, with soil organic carbon (SOC) being its most important component. How does the distribution of forest SOC distribution change under the influence of regional location, forest succession, human activities, and soil depth? It is the basis for understanding and evaluating the value of forest SOC reservoirs and improving the function of forest soil carbon sinks. In this paper, soil organic carbon concentrations (SOCCs) and environmental factors were measured by setting 14 experimental plots and 42 soil sampling sites in different forest communities and different elevations in the Maoershan Mountains. The redundancy analysis (RDA) method was used to study the relationship between SOC distribution and external factors. The results show that SOC distribution was sensitive to elevation, forest community, and soil layer. It had obvious surface aggregation characteristics and increased significantly with the increase in elevation. Among them, SOCCs increase by 1.80 g/kg with every 100 m increase in elevation, and that decreased by 5.43 g/kg with every 10 cm increase in soil depth. The SOC distribution in natural forests is greater than that in plantations, and the spatial variation in SOC distribution in plantations is higher due to the effect of cutting and utilization. SOC distribution is the result of many environmental factors. The response of SOC distribution to the forest community indicates that the development of plantations into natural forests will increase SOC, and excessive interference with forests will aggravate SOC emissions. Therefore, strengthening the protection of natural forests, restoring secondary forests, and implementing scientific and reasonable plantation management are important measures for improving the SOC reservoir’s function.
An Asymmetric Collision-Free Optimal Trajectory Planning Method for Three DOF Industrial Robotic Arms
Authors: Wu Wenhao , Jiang Aipeng , Mao Kai , Wang Haodong , Lin Yamei
Published: May 2023

To improve the speed and dynamic adaptability of robotic arm trajectory planning, a collision-free optimal trajectory planning method combining non-uniform adaptive time meshing and bounding box collision detection was proposed. First, the dynamics and objective function of the asymmetric industrial robotic arm with three degrees of freedom (DOF) was formulated in the form of the dynamic optimization problem. Second, the control vector parameterization (CVP) was improved to enhance the computational performance of the problem. The discrete grid was adaptively adjusted according the trend of control variables. Then, a quick and effective collision detection strategy was used to avoid obstacles and to speed up calculation efficiency. The non-collision constraint is built by transforming the collision detection into the distance between two points, and then is combined into the dynamic optimization problem. The solution of the new optimization problem with the improved CVP leads to the higher calculation performance and the avoidance of obstacles. Lastly, the Siemens Manutec R3 robotic arm is taken as an example to verify the effectiveness of the planning method. The approach not only reduces computation time but also maintains accurate calculations, so that optimal trajectory can be selected from symmetric paths near the obstacles. When weights were set as λ1 = λ2 = 0.5, the solution efficiency was improved by 33%, and the minimum distance between the robotic arm and obstacle could be 0.08 m, which ensured that there was no collision.
Estimation of Ricci Curvature for Hemi-Slant Warped Product Submanifolds of Generalized Complex Space Forms and Their Applications
Authors: Al-Dayel Ibrahim
Published: May 2023

In this paper, we estimate Ricci curvature inequalities for a hemi-slant warped product submanifold immersed isometrically in a generalized complex space form with a nearly Kaehler structure, and the equality cases are also discussed. Moreover, we also gave the equivalent version of these inequalities. In a later study, we will exhibit the application of differential equations to the acquired results. In fact, we prove that the base manifold is isometric to Euclidean space under a specific condition.
A Novel Cluster Matching-Based Improved Kernel Fisher Criterion for Image Classification in Unsupervised Domain Adaptation
Authors: Khan Siraj , Asim Muhammad , Chelloug Samia Allaoua , Abdelrahiem Basma , Khan Salabat , Musyafa Ahmad
Published: May 2023

Unsupervised domain adaptation (UDA) is a popular approach to reducing distributional discrepancies between labeled source and the unlabeled target domain (TD) in machine learning. However, current UDA approaches often align feature distributions between two domains explicitly without considering the target distribution and intra-domain category information, potentially leading to reduced classifier efficiency when the distribution between training and test sets differs. To address this limitation, we propose a novel approach called Cluster Matching-based Improved Kernel Fisher criterion (CM-IKFC) for object classification in image analysis using machine learning techniques. CM-IKFC generates accurate pseudo-labels for each target sample by considering both domain distributions. Our approach employs K-means clustering to cluster samples in the latent subspace in both domains and then conducts cluster matching in the TD. During the model component training stage, the Improved Kernel Fisher Criterion (IKFC) is presented to extend cluster matching and preserve the semantic structure and class transitions. To further enhance the performance of the Kernel Fisher criterion, we use a normalized parameter, due to the difficulty in solving the characteristic equation that draws inspiration from symmetry theory. The proposed CM-IKFC method minimizes intra-class variability while boosting inter-class variants in all domains. We evaluated our approach on benchmark datasets for UDA tasks and our experimental findings show that CM-IKFC is superior to current state-of-the-art methods.
Sexual Dimorphic Rightward Lateralization of Cerebral Sulcal Infolding in Cynomolgus Monkeys (Macaca fascicularis)
Authors: Sawada Kazuhiko , Saito Shigeyoshi
Published: May 2023

Cerebral sulcal infolding exhibits unique species-related lateralization patterns. The present investigation aimed to characterize the asymmetric patterns of sulcal infolding in cynomolgus monkeys and their sexual dimorphism. Three-dimensional magnetic resonance (MR) images were acquired at 7-Tesla from the fixed brains of adult male (n = 5) and female (n = 5) monkeys. The gyrification index (GI) was estimated on MR images throughout the cerebral cortex (global-GI) or in the representative primary sulci (sulcal-GI). The global-GI did not differ between the sexes when the ipsilateral sides were compared. Although there was no sex difference in the sulcal-GI of the ipsilateral sides of any primary sulci, a significant right bias of the sulcal-GI was noted in the inferior rams of the arcuate sulcus and circular sulcus in males but not in females. Secondary sulcal emergence was examined to assess sulcal infolding asymmetry at the individual and population levels. Nonbiased asymmetric emergence was noted in the posterior supraprincipal dimple in both sexes and the rostral sulcus in females. Notably, the emergence of the superior postcentral dimple was significantly right-lateralized in females. The findings revealed right-biased sulcal infolding in male and female cynomolgus monkeys, although the lateralized cortical regions differed between the sexes.
Utilization of Artificial Neural Networks for Precise Electrical Load Prediction
Authors: Pavlatos Christos , Makris Evangelos , Fotis Georgios , Vita Vasiliki , Mladenov Valeri
Published: May 2023

In the energy-planning sector, the precise prediction of electrical load is a critical matter for the functional operation of power systems and the efficient management of markets. Numerous forecasting platforms have been proposed in the literature to tackle this issue. This paper introduces an effective framework, coded in Python, that can forecast future electrical load based on hourly or daily load inputs. The framework utilizes a recurrent neural network model, consisting of two simpleRNN layers and a dense layer, and adopts the Adam optimizer and tanh loss function during the training process. Depending on the size of the input dataset, the proposed system can handle both short-term and medium-term load-forecasting categories. The network was extensively tested using multiple datasets, and the results were found to be highly promising. All variations of the network were able to capture the underlying patterns and achieved a small test error in terms of root mean square error and mean absolute error. Notably, the proposed framework outperformed more complex neural networks, with a root mean square error of 0.033, indicating a high degree of accuracy in predicting future load, due to its ability to capture data patterns and trends.
Contamination Levels and Phenotypic and Genomic Characterization of Antimicrobial Resistance in Escherichia coli Isolated from Fresh Salad Vegetables in the United Arab Emirates
Authors: Habib Ihab , Al-Rifai Rami H. , Mohamed Mohamed-Yousif Ibrahim , Ghazawi Akela , Abdalla Afra , Lakshmi Glindya , Agamy Neveen , Khan Mushtaq
Published: May 2023

Contaminated fresh produce has been identified as a vehicle for human foodborne illness. The present study investigated the counts, antimicrobial resistance profile, and genome-based characterization of Escherichia coli in 11 different types of fresh salad vegetable products (n = 400) sampled from retailers in Abu Dhabi and Dubai in the United Arab Emirates. E. coli was detected in 30% of the tested fresh salad vegetable items, with 26.5% of the samples having an unsatisfactory level (≥100 CFU/g) of E. coli, notably arugula and spinach. The study also assessed the effect of the variability in sample conditions on E. coli counts and found, based on negative binominal regression analysis, that samples from local produce had a significantly higher (p-value < 0.001) E. coli count than imported samples. The analysis also indicated that fresh salad vegetables from the soil-less farming system (e.g., hydroponic and aeroponic) had significantly (p-value < 0.001) fewer E. coli than those from traditional produce farming. The study also examined the antimicrobial resistance in E. coli (n = 145) recovered from fresh salad vegetables and found that isolates exhibited the highest phenotypic resistance toward ampicillin (20.68%), tetracycline (20%), and trimethoprim-sulfamethoxazole (10.35%). A total of 20 (13.79%) of the 145 E. coli isolates exhibited a multidrug-resistant phenotype, all from locally sourced leafy salad vegetables. The study further characterized 18 of the 20 multidrug-resistant E. coli isolates using whole-genome sequencing and found that the isolates had varying numbers of virulence-related genes, ranging from 8 to 25 per isolate. The frequently observed genes likely involved in extra-intestinal infection were CsgA, FimH, iss, and afaA. The β-lactamases gene blaCTX-M-15 was prevalent in 50% (9/18) of the E. coli isolates identified from leafy salad vegetable samples. The study highlights the potential risk of foodborne illness and the likely spread of antimicrobial resistance and resistance genes associated with consuming leafy salad vegetables and emphasizes the importance of proper food safety practices, including proper storage and handling of fresh produce.