bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Ice Phenology of Middle and Large Lakes on the Tibetan Plateau
Authors: Sun Lijun , Wang Binbin , Ma Yaoming , Shi Xingdong , Wang Yan
Published: February 2023

Considered as a sensitive indicator of climate change, lake ice phenology can have significant influences on regional climate by affecting lake-atmosphere energy and water exchange. However, in situ measurements of ice phenology events are quite limited over high-elevation lakes on the Tibetan Plateau, where satellite monitoring can make up such deficiency. In this study, by a combination of AMSR-E (2002–2011) and AMSR-2 (2012–2021) passive microwave data, MODIS optimal products and in situ measurements of temperature profiles in four lakes, the ice phenology events of 40 high-elevation large lakes were derived and their inter-annual trends and influencing factors were analyzed. The freeze-up start date (FUS) mainly occurs in November-December with an average date of 9 December and the break-up end date (BUE) is concentrated in April-May with a multi-year average of 5 May. Under climate warming, 24 of the 34 (70.6%) lakes show delayed FUS at an average trend of 0.35 days/year, and 7 (20.6%) lakes show advanced BUE (rate of change CR = −0.17 days/year). The average ice coverage duration (ID) was 147 days, and 13 (38.2%) lakes shortened ID at an average rate of −0.33 days/year. By synthesizing other ice phenology products, we obtained the assembled products of lake ice phenology, and found that air temperature dominates during the freeze-thaw process, with a higher dependence of BUE than that of FUS on air temperature.
Convolution, Correlation and Generalized Shift Operations Based on the Fresnel Transform
Authors: Vilardy Juan M. , Alfaro Eder , Mendoza Johonfri
Published: February 2023

The Fresnel transform (FrT) is commonly used to describe the free-space propagation of optical waves. In this work, we present new definitions for the convolution, correlation and generalized shift operations based on the FrT. The generalized shift operation is defined by using simultaneous space and phase shifts. The generalized shift operation is useful for centred optical systems in the Fresnel domain (FrD) when the data distributions at the input plane of the optical system are shifted. The new convolution and correlation operations defined in terms of the FrT, the wavelength and the propagation distance, can be considered as a generalization of the usual convolution and correlation operations. The sampling theorem for distributions, whose resulting FrT has finite support, is formulated by using the new convolution operation introduced in this work and a new definition of the Dirac comb function. These new definitions and results could be applied to describe, design and implement optical processing systems related to the FrT. Finally, we present a centred optical systems used in holography and optical security systems that can be described or modelled by the new definitions of the operations proposed in this paper.
Automated Operational Modal Analysis for Rotating Machinery Based on Clustering Techniques
Authors: Dreher Nathali Rolon , Storti Gustavo Chaves , Machado Tiago Henrique
Published: February 2023

Many parameters can be used to express a machine’s condition and to track its evolution through time, such as modal parameters extracted from vibration signals. Operational Modal Analysis (OMA), commonly used to extract modal parameters from systems under operating conditions, was successfully employed in many monitoring systems, but its application in rotating machinery is still in development due to the distinct characteristics of this system. To implement efficient monitoring systems based on OMA, it is essential to automatically extract the modal parameters, which several studies have proposed in the literature. However, these algorithms are usually developed to deal with structures that have different characteristics when compared to rotating machinery, and, therefore, work poorly or do not work with this kind of system. Thus, this paper proposes, and has as its main novelty in, a new automated algorithm to carry out modal parameter identification on rotating machinery through OMA. The proposed technique was applied in two different datasets to enable the evaluation of the robustness to different systems and test conditions. It is revealed that the proposed algorithm is suitable for the accurate extraction of frequencies and damping ratios from the stabilization diagram, for both the rotor and the foundation, and only one user defined parameter is required.
SAR Target Recognition with Limited Training Samples in Open Set Conditions
Authors: Zhou Xiangyu , Zhang Yifan , Liu Di , Wei Qianru
Published: February 2023

It is difficult to collect training samples for all types of synthetic aperture radar (SAR) targets. A realistic problem comes when unseen categories exist that are not included in training and benchmark data at the time of recognition, which is defined as open set recognition (OSR). Without the aid of side-information, generalized OSR methods used on ordinary optical images are usually not suitable for SAR images. In addition, OSR methods that require a large number of samples to participate in training are also not suitable for SAR images with the realistic situation of collection difficulty. In this regard, a task-oriented OSR method for SAR is proposed by distribution construction and relation measures to recognize targets of seen and unseen categories with limited training samples, and without any other simulation information. The method can judge category similarity to explain the unseen category. Distribution construction is realized by the graph convolutional network. The experimental results on the MSTAR dataset show that this method has a good recognition effect for the targets of both seen and unseen categories and excellent interpretation ability for unseen targets. Specifically, while recognition accuracy for seen targets remains above 95%, the recognition accuracy for unseen targets reaches 67% for the three-type classification problem, and 53% for the five-type classification problem.
Age-Related Reliability of B-Mode Analysis for Tailored Exosuit Assistance
Authors: Gionfrida Letizia , Nuckols Richard W. , Walsh Conor J. , Howe Robert D.
Published: February 2023

In the field of wearable robotics, assistance needs to be individualized for the user to maximize benefit. Information from muscle fascicles automatically recorded from brightness mode (B-mode) ultrasound has been used to design assistance profiles that are proportional to the estimated muscle force of young individuals. There is also a desire to develop similar strategies for older adults who may have age-altered physiology. This study introduces and validates a ResNet + 2x-LSTM model for extracting fascicle lengths in young and older adults. The labeling was generated in a semimanual manner for young (40,696 frames) and older adults (34,262 frames) depicting B-mode imaging of the medial gastrocnemius. First, the model was trained on young and tested on both young (R2 = 0.85, RMSE = 2.36 ± 1.51 mm, MAPE = 3.6%, aaDF = 0.48 ± 1.1 mm) and older adults (R2 = 0.53, RMSE = 4.7 ± 2.51 mm, MAPE = 5.19%, aaDF = 1.9 ± 1.39 mm). Then, the performances were trained across all ages (R2 = 0.79, RMSE = 3.95 ± 2.51 mm, MAPE = 4.5%, aaDF = 0.67 ± 1.8 mm). Although age-related muscle loss affects the error of the tracking methodology compared to the young population, the absolute percentage error for individual fascicles leads to a small variation of 3–5%, suggesting that the error may be acceptable in the generation of assistive force profiles.
Design, Implementation, and Empirical Validation of a Framework for Remote Car Driving Using a Commercial Mobile Network
Authors: Saez-Perez Javier , Wang Qi , Alcaraz-Calero Jose M. , Garcia-Rodriguez Jose
Published: February 2023

Despite the fact that autonomous driving systems are progressing in terms of their automation levels, the achievement of fully self-driving cars is still far from realization. Currently, most new cars accord with the Society of Automotive Engineers (SAE) Level 2 of automation, which requires the driver to be able to take control of the car when needed: for this reason, it is believed that between now and the achievement of fully automated self-driving car systems, there will be a transition, in which remote driving cars will be a reality. In addition, there are tele-operation-use cases that require remote driving for health or safety reasons. However, there is a lack of detailed design and implementation available in the public domain for remote driving cars: therefore, in this work we propose a functional framework for remote driving vehicles. We implemented a prototype, using a commercial car. The prototype was connected to a commercial 4G/5G mobile network, and empirical experiments were conducted, to validate the prototype’s functions, and to evaluate its performance in real-world driving conditions. The design, implementation, and empirical evaluation provided detailed technical insights into this important research and innovation area.
Traceability Management System Using Blockchain Technology and Cost Estimation in the Metrology Field
Authors: Takegawa Naoki , Furuichi Noriyuki
Published: February 2023

Metrological traceability is essential to ensure the reliability of calibration tests. Calibration certificates usually include information on only one upper-level reference standard. As metrological traceability is multi-layered, generally there is no method available for end users to instantly confirm the traceability from the reference standard to a primary standard. This study focuses on the Ethereum blockchain, which has both tamper resistance and high availability, as a digital data management method. To improve the transparency and reliability of calibration tests, a smart contract that traces back to the primary standard is proposed. Consequently, it is confirmed that end users can instantly obtain traceability information. In addition, the execution of smart contracts requires transaction fees. Here, the calculation of the transaction fees is organized, and the traceability management system is discussed from a cost-effective perspective in the field of metrology.
Child–Robot Interactions Using Educational Robots: An Ethical and Inclusive Perspective
Authors: Tarrés-Puertas Marta I. , Costa Vicent , Pedreira Alvarez Montserrat , Lemkow-Tovias Gabriel , Rossell Josep M. , Dorado Antonio D.
Published: February 2023

The Qui-Bot H2O project involves developing four educational sustainable robots and their associated software. Robots are equipped with HRI features such as voice recognition and color sensing, and they possess a humanoid appearance. The project highlights the social and ethical aspects of robotics applied to chemistry and industry 4.0 at an early age. Here, we report the results of an interactive study that involved 212 students aged within the range of 3–18. Our educational robots were used to measure the backgrounds, impact, and interest of students, as well as their satisfaction after interacting with them. Additionally, we provide an ethical study of the use of these robots in the classroom and a comparison of the interactions of humanoid versus non-humanoid educational robots observed in early childhood learning. Our findings demonstrate that these robots are useful in teaching technical and scientific concepts in a playful and intuitive manner, as well as in increasing the number of girls who are interested in science and engineering careers. In addition, major impact measures generated by the project within a year of its implementation were analyzed. Several public administrations in the area of gender equality endorsed and participated in the Qui-Bot H2O project in addition to educational and business entities.
Strategic Bidding of Retailers in Wholesale Markets: Continuous Intraday Markets and Hybrid Forecast Methods
Authors: Algarvio Hugo , Lopes Fernando
Published: February 2023

The deregulation process of the electricity sector has led to competition in wholesale and retail markets. In particular, retailers submit bids to wholesale markets to satisfy the energy needs associated with portfolios of end-use customers. This paper describes a strategic process for retailers bidding in a wholesale market composed of a day-ahead market, an intraday market, and a balancing market. It considers a market design that involves a hybrid model for the intraday market, based on daily auctions and a continuous procedure. The paper also presents a computational study to illustrate and test both the market design and the strategic bidding process of retailers. The results confirm the advantages of considering a continuous intraday market, show that bidding in short-term markets is more beneficial than bidding in medium-term markets, and indicate important aspects to consider when selecting customers to add to the portfolios of retailers.
Helmet-Wearing Tracking Detection Based on StrongSORT
Authors: Li Fufang , Chen Yan , Hu Ming , Luo Manlin , Wang Guobin
Published: February 2023

Object detection based on deep learning is one of the most important and fundamental tasks of computer vision. High-performance detection algorithms have been widely used in many practical fields. For the management of workers wearing helmets in construction scenarios, this paper proposes a framework model based on the YOLOv5 detection algorithm, combined with multi-object tracking algorithms, to monitor and track whether workers wear safety helmets in real-time video. The improved StrongSORT tracking algorithm of DeepSORT is selected to reduce the loss of the tracked object caused by the occlusion, trajectory blur, and motion scale of the object. The safety helmet dataset is trained with YOLOv5s, and the best result of training is used as the weight model in the StrongSORT tracking algorithm. The experimental results show that the mAP@0.5 of all classes in the YOLOv5s model can reach 95.1% in the validation dataset, mAP@0.5:0.95 is 62.1%, and the precision of wearing helmet is 95.7%. After the box regression loss function was changed from CIOU to Focal-EIOU, the mAP@0.5 increased to 95.4%, mAP@0.5:0.95 increased to 62.9%, and the precision of wearing helmet increased to 96.5%, which were increased by 0.3%, 0.8% and 0.8%, respectively. StrongSORT can update object trajectories in video frames at a speed of 0.05 s per frame. Based on the improved YOLOv5s combined with the StrongSORT tracking algorithm, the helmet-wearing tracking detection can achieve better performance.
Exploring Coumarin-Based Boron Emissive Complexes as Temperature Thermometers in Polymer-Supported Materials
Authors: Pedro Gonçalo , Duarte Frederico , Cheptsov Dmitrii A. , Volodin Nikita Yu. , Ivanov Ivan V. , Santos Hugo M. , Capelo-Martinez Jose Luis , Cuerva Cristián , Oliveira Elisabete , Traven Valerii F. , Lodeiro Carlos
Published: February 2023

Three coumarin-based boron complexes (L1, L2 and L3) were designed and successfully incorporated into polymeric matrixes for evaluation as temperature probes. The photophysical properties of the complexes were carried out in different solvents and in the solid state. In solution, compound L1 exhibited the highest fluorescence quantum yield, 33%, with a positive solvatochromism also being observed on the absorption and emission when the polarity of the solvent increased. Additionally in the presence of anions, L1 showed a colour change from yellow to pink, followed by a quenching in the emission intensity, which is due to deprotonation with the formation of a quinone base. Absorption and fluorescence spectra of L1 were calculated at different temperatures by the DFT/B3LYP method. The decrease in fluorescence of compound L1 with an increase in temperature seems to be due to the presence of pronounced torsional vibrations of the donor and acceptor fragments relative to the single bond with C(carbonyl)-C (styrene fragment). L1, L2 and L3, through their incorporation into the polymeric matrixes, became highly emissive by aggregation. These dye@doped polymers were evaluated as temperature sensors, showing an excellent fluorescent response and reversibility after 15 cycles of heating and cooling.
ECG Classification Using an Optimal Temporal Convolutional Network for Remote Health Monitoring
Authors: Ismail Ali Rida , Jovanovic Slavisa , Ramzan Naeem , Rabah Hassan
Published: February 2023

Increased life expectancy in most countries is a result of continuous improvements at all levels, starting from medicine and public health services, environmental and personal hygiene to the use of the most advanced technologies by healthcare providers. Despite these significant improvements, especially at the technological level in the last few decades, the overall access to healthcare services and medical facilities worldwide is not equally distributed. Indeed, the end beneficiary of these most advanced healthcare services and technologies on a daily basis are mostly residents of big cities, whereas the residents of rural areas, even in developed countries, have major difficulties accessing even basic medical services. This may lead to huge deficiencies in timely medical advice and assistance and may even cause death in some cases. Remote healthcare is considered a serious candidate for facilitating access to health services for all; thus, by using the most advanced technologies, providing at the same time high quality diagnosis and ease of implementation and use. ECG analysis and related cardiac diagnosis techniques are the basic healthcare methods providing rapid insights in potential health issues through simple visualization and interpretation by clinicians or by automatic detection of potential cardiac anomalies. In this paper, we propose a novel machine learning (ML) architecture for the ECG classification regarding five heart diseases based on temporal convolution networks (TCN). The proposed design, which implements a dilated causal one-dimensional convolution on the input heartbeat signals, seems to be outperforming all existing ML methods with an accuracy of 96.12% and an F1 score of 84.13%, using a reduced number of parameters (10.2 K). Such results make the proposed TCN architecture a good candidate for low power consumption hardware platforms, and thus its potential use in low cost embedded devices for remote health monitoring.
Research on Recognition of Road Hypnosis in the Typical Monotonous Scene
Authors: Shi Huili , Chen Longfei , Wang Xiaoyuan , Wang Bin , Wang Gang , Zhong Fusheng
Published: February 2023

Road traffic safety can be influenced by road hypnosis. Accurate detection of the driver’s road hypnosis is a very important function urgently required in the driver assistance system. Road hypnosis recurs frequently in a certain period, and it tends to occur in a typical monotonous scene such as a tunnel or a highway. Taking the scene of a tunnel or a highway as a typical example, road hypnosis was studied through simulated driving experiments and vehicle driving experiments. A road hypnosis recognition model based on principal component analysis (PCA) and a long short-term memory network (LSTM) was proposed, where PCA was used to extract various parameters collected by the eye tracker, and the LSTM model was constructed to identify road hypnosis. The accuracy rates of 93.27% and 97.01% in simulated driving experiments and vehicle driving experiments were obtained. The proposed method was compared with k-nearest neighbor (KNN) and random forest (RF). The results showed that the proposed PCA-LSTM model had better performance. This paper provides a novel and convenient method to realize the driver’s road hypnosis detection function of the intelligent driver assistance system in practical applications.
Antioxidant-Activity-Guided Purification and Separation of Octocrylene from Saussurea heteromalla
Authors: Saboon  , Bibi Yamin , Ayoubi Samha Al , Afzal Tayyiba , Gilani Sobia , Malik Khafsa , Qayyum Abdul , Hussain Mubashar , Kumar Sunjeet
Published: February 2023

Plants have been a source of medicine since ancient times, and such traditional medications are widely practiced nowadays. Saussurea heteromalla is widely used in traditional medicine in the Himalayan region for the treatment of different ailments. However, despite its traditional uses, it is not widely explored for its free radical scavenging abilities and other biological activities. Thus, the current study is aimed at exploring the free radical scavenging ability of S. heteromalla extracts, along with the isolation and evaluation of its compound through bioassay-guided purification. From different solvent fractions, an n-hexane extract of a whole plant is found to be most active; thus, it is processed for large-scale extraction and column chromatography. Further, the purification of an active fraction is performed using HPLC–DAD, which led to the isolation of an active peak, identified by GC/MS, as 2-ethylhexyl 2-cyano-3, 3-diphenylprop-2-enoate. This compound, commonly known as octocrylene, is widely recommended for UV-B filter, to be used in the cosmetic industry as photoprotection products. The presence of free radical scavenging activity enhances the sun protection factor of octocrylene. The present study presents the first report on the isolation of this compound from the family Asteraceae. The compound has good free radical scavenging activity and is widely used in the cosmetic industry as a sun protectant and is much less reported from botanical sources.
It Is Home: Perceptions, Community, and Narratives about Change
Authors: Cope Michael R. , June Haylie M. , Sanders Scott R. , Asay Greta L. , Hendricks Hannah Z. , Long-Meek Elizabeth , Ward Carol
Published: February 2023

Utah’s Heber Valley has experienced rapid and (relatively) sustained growth since the 1990s, in part due to being chosen as a host venue for the 2002 Winter Olympics. As conditions in the Valley changed by virtue of this growth, individuals had to redefine their relationship with their community at large, as well as what community means to them individually. As individuals integrate new conditions into their imagined communities, they are also required to imagine communities in ways they never have before. The community’s story is rewritten simultaneously along with individuals’ own stories. These changing stories are shaped and indicated by the reconstruction of residents’ narratives about their community, i.e., their community stories. In this paper, we (1) explore how Heber Valley residents’ narratives change as a result of preparing for, participating in, and recovering from the Olympics, (2) verify these findings using survey data gathered during the same time period, and (3) examine how changes in residents’ narratives in Heber Valley impacted the subjective evaluation of community. To do so, we rely on longitudinal data gathered among principal communities in Heber Valley with additional data generated from a hermeneutic content analysis of archival data found in the area’s community newspaper (The Wasatch Wave). Survey data were gathered once a year over a five-year period from February 1999 through February 2003, with additional waves gathered in February 2007, 2012, and 2018. Our results indicated that the community narratives did change as a result of the Olympics, our survey data verified these community changes over time, and changes in residents’ community stories impacted survey responses when residents were asked about community sentiments.
Calculation of Sustainability Indicators for Water Objects based on the Example of Water Use in the Arctic Basin of the Yenisei River
Authors: Nasonov Andrey , Tsvetkov Ilya , Nikonorov Sergey , Krivichev Alexander
Published: February 2023

In the article, the fractal approach to the description of nonequilibrium water ecosystems in their exploitation conditions is considered. The article demonstrates clearly that, in these conditions, the management of the development of water objects should be a precautionary provision, which should furthermore be reduced to the management of potential anthropogenic risks arising from a violation of the coevolution of anthropogenic and natural processes equivalent to the disruption in sustainability of the ecosystem in its exploitation conditions. The fractal approach opens up new opportunities for the assessment of water management based on the calculation of the fractal sustainability indicator (anthropogenic transformation) for water ecosystems that is directly related to the maximum permissible environmental load (MPEL).
Simplified Life Cycle Cost Estimation of Low-Rise Steel Buildings Using Fundamental Period
Authors: Noureldin Mohamed , Kim Jinkoo
Published: February 2023

In the current study, a simplified seismic life cycle cost (LCC) estimation procedure is proposed utilizing the mean values of the structure’s main input variables. The main input variables of the building are used for constructing a relationship between the structural fundamental period (T) and an average estimation of the LCC (LCCavg). Using the actual building properties related to damage probability, the T–LCCavg relationship is used to obtain the final LCC (LCCfin). The equivalent single degree of freedom (ESDOF) model and SAC-FEMA framework are utilized for damage probability calculation. The dispersion measure in demand is approximately calculated based on the mean plus one standard deviation of the seismic hazard response spectrum, and, then, verified through nonlinear time history (NLTH) analyses of the original structure. Five and three-story steel buildings are used as case studies for verification of the proposed method. The analysis results indicate that the proposed procedure provides reasonable LCC estimations for low-rise buildings dominated by the fundamental mode of vibration.
A Knowledge-Based AI Framework for Mobility as a Service
Authors: Rajabi Enayat , Nowaczyk Sławomir , Pashami Sepideh , Bergquist Magnus , Ebby Geethu Susan , Wajid Summrina
Published: February 2023

Mobility as a Service (MaaS) combines various modes of transportation to present mobility services to travellers based on their transport needs. This paper proposes a knowledge-based framework based on Artificial Intelligence (AI) to integrate various mobility data types and provide travellers with customized services. The proposed framework includes a knowledge acquisition process to extract and structure data from multiple sources of information (such as mobility experts and weather data). It also adds new information to a knowledge base and improves the quality of previously acquired knowledge. We discuss how AI can help discover knowledge from various data sources and recommend sustainable and personalized mobility services with explanations. The proposed knowledge-based AI framework is implemented using a synthetic dataset as a proof of concept. Combining different information sources to generate valuable knowledge is identified as one of the challenges in this study. Finally, explanations of the proposed decisions provide a criterion for evaluating and understanding the proposed knowledge-based AI framework.
Analysis of the Effect of Providing Pedestrian Crossing Information at the Blind Spots of Intersections on Vehicle Traffic
Authors: Hong Ki-Man , Kim Jong-Hoon , Ha Jung-Ah , Kim Gwang-Ho , Kim Jong-Hoon
Published: February 2023

In this study, we conducted an analysis of the pedestrian safety system for crosswalks introduced in Korea to improve sustainable traffic safety. The pedestrian crossing information provision system provides information to a driver in advance when a pedestrian is detected in the driver’s blind spot when the latter is turning right at an intersection. The location analyzed was the three-way intersection in front of Yungheung Elementary School in Jeollabuk-do, and vehicle speed information for 150–160 min before and after system installation was collected. As a result of comparing and analyzing the change in the compliance rate of the spot speed and the speed limit, it was found that there was no statistical difference in the change in the spot speed, but in the absence of pedestrians, the speed increased slightly compared with that before installation. The change in the speed limit compliance rate was found to improve when pedestrian crossing information was provided. In addition, a chi-square test found that there was a difference in the speed limit compliance rate before and after system installation where pedestrians existed (when information was provided), while there was no difference in the situation where pedestrians did not exist (when information was not provided).
Promoting or Inhibiting? Digital Inclusive Finance and Cultural Consumption of Rural Residents
Authors: Shi Yuting , Cheng Qiuwang , Wu Yizhen , Lin Qiaohua , Xu Anxin , Zheng Qiujin
Published: February 2023

Improving the cultural consumption level of rural residents is of great practical significance to help revitalize rural culture and achieve common prosperity. Based on this, this study empirically examines the role and impact mechanism of digital inclusive finance on enhancing the cultural consumption of rural residents using panel data of 30 provinces across China from 2011 to 2020. The results show that: (1) Digital inclusive finance can significantly improve the cultural consumption level of rural residents. After a robustness test and endogenous analysis, this conclusion is still stable. (2) Digital inclusive finance significantly improves the cultural consumption level of rural residents through three paths: raising the income level of farmers, promoting the level of urbanization, and improving the level of financial development. (3) Heterogeneity analysis shows that the breadth of digital inclusive financial coverage can significantly improve the cultural consumption level of rural residents, but the depth of digital inclusive financial use and the degree of digitization do not show an enhancing effect; the development of digital inclusive finance in the eastern area has a significant role in promoting the cultural consumption level of rural residents, but the role is not significant in the central and western areas.
Teaching Methodology for Understanding Virtual Reality and Application Development in Engineering Major
Authors: Kim Jihyung , Kim Kyeong-sun , Ka Jonghyeon , Kim Wooksung
Published: February 2023

This study proposed a virtual reality (VR) course that addresses the overall understanding and application of VR technology. After investigating previous studies, we found that two technologies must be applied to design a VR course that fits the latest trends. One is hardware technology dealing with the technical background, while the other is software utilization and development using the merits of VR technology. To accommodate these needs, we designed a VR course consisting of three steps: VR-related theory, TA-led content creation training, and team projects. Through this course, students will improve their ability to develop applications that apply to their research fields after studying the technical background and courses of VR. We conducted a semester-long study with nine students to verify the proposed method and then evaluated them through an in-depth interview and a questionnaire with a five-point Likert scale consisting of nine items. Considering this feedback, we have added several steps to improve the educational effect among students.
Systemic Risk with Multi-Channel Risk Contagion in the Interbank Market
Authors: Jiang Shanshan , Wang Jie , Dong Ruiting , Li Yutong , Xia Min
Published: February 2023

The systematicness of banks is an important driver of financial crisis. Overlapping portfolios and assets correlation of banks’ investment are important reasons for systemic risk contagion. The existing systemic risk models are all analyzed from one aspect and cannot reflect the real situation of the banking system. In the present paper, considering the overlapping portfolios and assets correlation, a contagion network model with multi-channel risk is proposed, which is with interbank lending (direct contagion channel), overlapping portfolios (indirect contagion channel), and assets correlation (indirect contagion channel). In addition, the model takes investment risk as an impact factor and learns the operation rules of the banking system to help banks compensate for liquidity through asset depreciation. Based on the proposed model, the effects of assets correlation, assets diversity, assets investment strategy, interbank network structure, and the impact of market density on risk contagion are studied and analyzed quantitatively. The method in this paper can more truly reflect the banking system risk than the existing model. This paper provides a solution for quantitative analysis of systemic risk, which provides powerful tools for macroprudential stress testing and a reference for regulatory authorities to prevent systemic risk.
The Value Relevance of ESG Practices in Japan and Malaysia: Moderating Roles of CSR Award, and Former CEO as a Board Chair
Authors: E-Vahdati Sahar , Wan-Hussin Wan Nordin , Mohd Ariffin Mohd Shazwan
Published: February 2023

This study examines the impact of ESG practices and its three pillars on the stock price, and the moderating role of CSR award, and having an ex-CEO as a chairman on the ESG-value nexus in Japan and Malaysia. Based on a large sample of 538 observations from 2015–2019, we find a positive valuation effect of ESG practices in both countries, which are in line with stakeholder theory. We observe that the value relevance of ESG practice is significantly higher in Malaysia than in Japan. However, the market does not significantly value all three ESG pillars equally in Japan and Malaysia. Our study reveals that the social pillar is more dominant in Japan; whereas, in Malaysia, it is the environmental pillar that strongly influences market value. According to signaling theory, we find CSR award only moderates the market valuation of ESG in Malaysia. Based on positive synergy theory, we further suggest that when an ex-CEO sits as a chairman, it moderates the value relevance of ESG in Japan. Our study has practical implications for stakeholders including investors, policymakers, and managers. Our results suggest investors and regulators in the Indo-Pacific region need to distinguish between the three pillars of ESG practices and their consequences on the market price, before making an investment decision.
Framework of New Poverty Decomposition: An Application to the Evolution of Income Distribution
Authors: Feng Xing , Zhao Zhe , Jia Zhanhua , Tian Zhenxing , Chen Haiting
Published: February 2023

Ending poverty in all its forms is the first of the 17 sustainable development goals (SDGs) of the 2030 Agenda for Sustainable Development. Therefore, it is of great significance to study poverty in the context of sustainable development. At present, the effect of income growth on poverty reduction is becoming less evident, whereas the effect of inhabitant heterogeneity on poverty reduction is becoming increasingly significant in China. Based on the original two-dimensional poverty decomposition of income growth and redistribution, this study introduces the heterogeneity effect to decompose rural poverty in China from three dimensions. It first decomposes the change in income distribution into mean, variance, and residual effects using counterfactual analysis. Then, it introduces the Foster–Greer–Thorbecke index decomposition to decompose China’s rural poverty under the different poverty line. In addition, this paper employs mathematical statistics to analyze the effects of poverty’s growth, dispersion, and heterogeneity. This study finds that the three-dimensional poverty decomposition method can measure the trajectory and trend of poverty more precisely and comprehensively. Moreover, it found that the contradiction between economic growth and poverty regression is due to the fact that the poverty reduction effect of the growth effect and the poverty alleviation effect of the discrete effect have asymmetrical characteristics, whereas the discrete effect and the heterogeneous effect have symmetrical characteristics; that is, the poverty reduction effect of income growth is insufficient to compensate for the poverty deepening effect brought about by the widening income gap, and that the heterogeneous poverty reduction effect plays an increasingly important role. Therefore, to prevent residents from falling back into poverty after being lifted out of it, we must reduce the widening income gap. Moreover, residents’ ability to reduce poverty on their own must be strengthened.
The Influence of Responsible Leadership on Strategic Agility: Cases from the Taiwan Hospitality Industry
Authors: Chang Ariana , Lee Tian-Shyug , Lee Hsiu-Mei , Wang Jing
Published: February 2023

The COVID-19 pandemic has taken business uncertainty to an unprecedented level and put business agility and leadership under harsh tests, confronting a diverse and complicated stakeholder reality. Through original interview data and case studies from the hospitality industry in Taiwan collected and compiled since the beginning of the COVID-19 pandemic in 2020, the present research explores how strategic agility can be built, fostered, and enhanced through responsible leadership and CSR initiatives during a time of grand challenges in the hospitality industry. We also discuss and highlight the role played by one stakeholder, namely, the local government, in contributing to strategic agility through reinforcing and possibly enabling responsible leadership during hardships. This paper sheds light both empirically and theoretically on the roles played by business leaders in contributing to strategic agility, which, in turn, helps to build a more socially responsible organization.
Electric Vehicle Participation in Regional Grid Demand Response: Potential Analysis Model and Architecture Planning
Authors: Wang Qian , Yang Xiaolong , Yu Xiaoyu , Yun Jingwen , Zhang Jinbo
Published: February 2023

When a large-scale random charging load is connected to the regional power grid, it can negatively affect the safe and stable operation of the power grid. Therefore, we need to study its charging load and response potential in advance so that electric vehicles can interact well with the grid after being connected to the regional grid. Firstly, after analyzing the influencing factors of regional electric vehicle ownership, an electric vehicle ownership prediction model based on the sparrow search algorithm-improved BP neural network (SSA-BPNN) is established. On this basis, an electric vehicle charging load prediction model is established based on the sparrow search algorithm-improved BP neural network and Monte Carlo algorithm (SSA-BPNN-MC). Secondly, the charging behavior of different types of electric vehicles is analyzed and modeled, and the data from a certain area are taken as an example for the prediction. Then, according to the load forecasting results, the potential of electric vehicles participating in demand response in the region in the future is deeply analyzed using the scenario analysis method. Finally, with the aim of resolving the problems of massive multi-source heterogeneous data processing and the management of electric vehicles participating in the regional power grid demand response, a basic framework of electric vehicles participating in the regional power grid demand response is developed, which provides effective support for promoting electric vehicles to participate in regional grid demand response.
Urban Honey: A Review of Its Physical, Chemical, and Biological Parameters That Connect It to the Environment
Authors: Quiralte David , Zarzo Inmaculada , Fernandez-Zamudio Maria-Angeles , Barco Héctor , Soriano Jose M.
Published: February 2023

Humans mainly use the land for agriculture and housing, resulting in the loss of natural habitat and a decrease in the number of species, including wild bees. The reduction of wild bees generates several negative consequences for the agricultural and ecosystem contexts, although sometimes the farming reduces the probability of abandonment of the land. In parallel, urban beekeeping has emerged and consolidated as one of the current trends, while the consumption of honey from urban environments is also growing. Current scientific literature establishes different physical, chemical, and biological parameters which evaluate the quality of honey products and its environment. The review carried out here collects the various compounds contained in this source-dependent food matrix from anthropogenic activities in the sampling area. Using gas and liquid chromatography and spectrometry, the main physicochemical parameters have been detected, 27 chemical elements, of which 6 are heavy elements, 16 polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and pesticides (organochlorine pesticides and neonicotinoids). Additionally, their total phenolic and microbiological content has been typified. This analysis can help to frame the main characteristics to evaluate this universal product, whose consumption began with the first settlers of the world, and its properties have been evolving as well as the characteristics of the production systems.
Some Considerations on the Implications of Protected Areas for Sustainable Development
Authors: Rodríguez-Darias Alberto Jonay , Díaz-Rodríguez Pablo
Published: February 2023

This essay raises some reflections on the implications of protected areas in the processes of social construction related to the conception of nature, its limitations as a strategy for environmental policies (related to ecosystem connectivity and over the management of human activities linked to its functioning), and its public use (encouraging contemplative and tourist uses over productive activities). This essay focuses on some aspects of protected areas as a territorial management model, with the aim of provoking reflection on their implications to sustainable development.
The Environmental, Economic and Social Welfare Impacts of the CCREW Project in China: A Study Based on the CGE Model
Authors: Feng Ze , Huang Yingfei , Kong Zhaoyang
Published: February 2023

Countries around the world have carried out digital transformations to improve their economic resilience. As the largest developing country, China put forward the “channeling computing resources from the East to the West (CCREW)” project in 2022 to balance and promote the development of various regions. This paper constructs a three-region computable general equilibrium model covering the eastern, western, and other regions and evaluates the impact of the project on economic development, social welfare, and carbon emissions in different regions. By simulating the transfer share of the CCREW project, this paper attempts to further reveal the impact of the policy both on regional differences and national development. The results show that the effects of the project are quite different among regions. Our findings can be summarized as follows. (1) In terms of carbon dioxide emissions, the policy will cause emissions to shift from the East to the West. (2) In terms of economic development, the policy will lead to an overall downward trend in the GDP of the eastern and other regions, whereas for the western region, the policy will promote the development of the regional economy. Regional differences may affect the implementation of the policy and its effects. (3) In terms of social welfare, the policy will result in an inverted U-shaped change in social welfare at the national level, which first rises and then falls, and will change from positive to negative when the transfer share exceeds 20%. At the regional level, social welfare in the eastern and other regions will decline, whereas that in the western region will show an inverted U-shaped change that first increases and then decreases. (4) In the short term, the project at the national level has reduced carbon emissions at the expense of economic development and incurred a loss in social welfare.
Effect of Sludge Content on the Decomposition of Different Types of Food Waste
Authors: Latif Mumtahina Binte , Islam Md Azijul , Hossain Md Sahadat , Aurpa Sehneela Sara
Published: February 2023

Food waste, which is the second largest component in landfills, generates excessive amounts of leachate and greenhouse gas. As a result, it has recently become a severe concern, mostly in the developing countries for its adverse impact on the environment. The addition of nutrients to organic waste limits the accumulation of volatile fatty acid (VFA) and accelerates the production of energy from food waste. The objective of the current study is to find out the effects of sludge addition on the decomposition and gas generation of separate components of food waste. This study was conducted for four combinations of reactors: two pairs containing meat and grain with the addition of a sludge content of 20% and 30%, respectively, as inoculum; another two pairs of reactors containing fruits and vegetables with a sludge content of 20% and 30%, respectively. Over the operation period, pH, volume, COD, and VFA tests were conducted for leachate while composition and volume measurements were done for the generated gas. Based on the results, it is observed that addition of sludge accelerated the decomposition of fruit and vegetable waste due to limited VFA accumulation compared to meat and grain. The maximum methane production was found in fruits and vegetable reactors at a rate of 6.7 L of methane per pound of food waste. For fruit and vegetable reactors, the CH4:CO2 ratio increased to as high as 8.5. On the other hand, for the meat and grain reactors, the increase in CH4:CO2 ratio was insignificant as they were in the lag phase.
A Comprehensive Analysis of In-Line Inspection Tools and Technologies for Steel Oil and Gas Pipelines
Authors: Parlak Berke Ogulcan , Yavasoglu Huseyin Ayhan
Published: February 2023

The transportation of oil and gas through pipelines is an integral aspect of the global energy infrastructure. It is crucial to ensure the safety and integrity of these pipelines, and one way to do so is by utilizing an inspection tool called a smart pig. This paper reviews various smart pigs used in steel oil and gas pipelines and classifies them according to pipeline structure, anomaly-detection capability, working principles, and application areas. The advantages and limitations of each sensor technology that can be used with the smart pig for in-line inspection (ILI) are discussed. In this context, ultrasonic testing (UT), electromagnetic acoustic transducer (EMAT), eddy current (EC), magnetic flux leakage (MFL), and mechanical contact (MC) sensors are investigated. This paper also provides a comprehensive analysis of the development chronology of these sensors in the literature. Additionally, combinations of relevant sensor technologies are compared for their accuracy in sizing anomaly depth, length, and width. In addition to their importance in maintaining the safety and reliability of pipelines, the use of ILI can also have environmental benefits. This study aims to further our understanding of the relationship between ILI and the environment.
Gravitational Baryogenesis: Problems and Possible Resolution
Authors: Arbuzova Elena , Dolgov Alexander , Dutta Koushik , Rangarajan Raghavan
Published: February 2023

The coupling of baryonic current to the derivative of the curvature scalar, R, inherent to gravitational baryogenesis (GBG), leads to a fourth-order differential equation of motion for R instead of the algebraic one of general relativity (GR). The fourth-order differential equation is generically unstable. We consider a possible mechanism of stabilization of GBG by the modification of gravity, introducing an R2 term into the canonical action of GR. It is shown that this mechanism allows for the stabilization of GBG with bosonic and fermionic baryon currents. We establish the region of the model parameters leading to the stabilization of R. Still, the standard cosmology would be noticeably modified.