bluuebunny/crossref_metadata_2025 huggingface dataset:
New Technology and Method for Monitoring the Status of Power Systems to Improve Power Quality—A Case Study
Authors: Ildarabadi Rahim , Zadehbagheri Mahmoud
Published: August 2023

The identification and analysis of harmonics, frequency, and transient events are essential today. It is necessary to have available data relating to harmonics, frequency, and transient events to understand power systems and their proper control and analysis. Power quality monitoring is the first step in identifying power quality disturbances and reducing them and, as a result, improving the performance of the power system. In this paper, while presenting different methods for measuring these quantities, we have made some corrections to them. These reforms have been obtained through the analysis of power network signals. Finally, we introduce a new monitoring system capable of measuring harmonics, frequency, and transient events in the network. In addition, these values are provided for online and offline calculations of harmonics, frequency, and transient events. In this paper, two new and practical methods of the “algebraic method” are used to calculate network harmonics and wavelet transform to calculate transient modes in the network. Furthermore, the proposed monitoring system is able to reduce the amount of data-storage memory. The results of the simulations performed in this article show the superiority of using the new method presented for online and offline monitoring of power quality in electric power systems.
Detection of Large Foreign Objects on Coal Mine Belt Conveyor Based on Improved
Authors: Huang Kaifeng , Li Shiyan , Cai Feng , Zhou Ruihong
Published: August 2023

An algorithm based on the YOLOv5 model is proposed to address safety incidents such as tearing and blockage at transfer points on belt conveyors in coal mines caused by foreign objects mixed in with the coal flow. Given the tough underground conditions and images acquired with low quality, recursive filtering and MSRCR image enhancement algorithms were utilized to preprocess the dynamic images collected by underground monitoring devices, substantially enhancing image quality. The YOLOv5 model has been improved by introducing a multi-scale attention module (MSAM) during the channel map slicing, thereby increasing the model’s resistance to interference from redundant image features. Deep separable convolution was utilized in place of conventional convolution to detect, identify, and process large foreign objects on the belt conveyor as well as to increase detection speed. The MSAM-YOLOv5 model was trained before being installed on the NVIDIA Jetson Xavier NX platform and utilized to identify videos gathered from the coal mine belt conveyor. According to the experimental findings, the upgraded MSAM-YOLOv5 model has a greater recognition accuracy than YOLOv5L, with an average recall rate for different foreign objects of 96.27%, an average detection accuracy of 97.35%, and a recognition speed of 44 frames/s. The algorithm assures detection accuracy while increasing detection speed, satisfying the requirements for large foreign object detection on belt conveyors in coal mines.
Catalytic Pyrolysis of Waste Low-Density Polyethylene (LDPE) Carry Bags to Fuels: Experimental and Exergy Analyses
Authors: Rajan Krishna Prasad , Mustafa Ibrahim , Gopanna Aravinthan , Thomas Selvin P.
Published: August 2023

The present investigation reports the results of experiments related to the conversion of low-density polyethylene (LDPE) waste carry bags to fuel through an economic catalytic pyrolysis method in a batch reactor using zinc oxide (ZnO) as the catalyst. Plastics are highly beneficial for the day-to-day activities of human beings; however, their decomposition is limited due to their strong covalent bonding. Degradation of these big molecules into smaller ones or monomers has been attempted by several researchers in recent decades, with limited success. Pyrolysis is one of the ideas used to convert plastics, with the crowded structure of polymers, into fuel rather than small molecules. Among these plastics, LDPE is widely used as carry bags throughout the world, and, herein, the results of catalytic pyrolysis of the conversion of LDPE into fuel are reported. A compact laboratory-scale batch reactor, specially designed at our laboratory, was used to carry out the pyrolysis process. Different dosages of ZnO were used as a catalyst to carry out the pyrolysis at a specific temperature. The optimal dosage of ZnO for a 50 g waste LDPE batch was found to be 0.6 g to get the maximum oil yield. The yielded oil was analyzed chemically through Fourier transform infrared spectroscopy (FTIR) and a Reformulyzer M4 Hydrocarbon Group Type Analyzer. Evaluation of physical and chemical exergy along with exergetic efficiency of the process was carried out. The described experiments and the results represent a small but significant step toward curbing the menace of plastic solid wastes, which are degrading the environment and human life worryingly, and allowing them to be utilized for generating low-cost fuel for transportation and other applications.
The Systematic Unity of the Theoretical and Axiotic in Salomon Maimon’s Late Philosophy
Authors: Franz Timothy
Published: August 2023

By a close reading of Salomon Maimon’s 1794 Essay on a New Logic or Theory of Thinking, this article shows, first, how Maimon radically criticized his previous metaphysical systems while painstakingly reestablishing Kantian transcendental philosophy on a theory of reflexive cognition. Second, it shows how he employed this theory to ground innovative accounts of both formal and transcendental logic, including a reformulation of Kant’s schematism. Third, it shows how he employed it to ground his axiotic philosophy. Specifically, he argued that his reflexive theory of cognition constituted the necessary condition for the theories of Kantian morality, natural rights, works of art, and finally for a metaphysics according to which God creates the world ex nihilo. Maimon’s achievement is impressive and unique. It is a theory of the systematic unity of theoretical and axiotic philosophy that rivals other Enlightenment systems and, if anything, anticipates later works of Hans Wagner and Werner Flach.
Pseudolite Multipath Estimation Adaptive Mitigation of Vector Tracking Based on Ref-MEDLL
Authors: Zhang Bo , Wang Qing , Xia Wenqing , Sun Yu , Wang Jinling
Published: August 2023

Among many indoor positioning technologies, pseudolite positioning technology has become an important supplement to GNSS. In indoor open environments, pseudolite positioning technology can usually perform high-precision positioning. However, in a complex environment, the pseudolite receiver is seriously interfered by multipath and other interference signals, which will lead to a serious decline in the observation accuracy, signal lock loss or even no positioning results. Therefore, this work proposes a pseudolite indoor anti-multipath receiver based on reference multipath estimating delay lock loop (Ref-MEDLL). It adds the Ref-MEDLL multipath estimator module and the multipath mitigation module to the traditional receiver signal processing architecture. In the multipath mitigation module, the multipath estimation adaptive mitigation of vector tracking (MEAM-VT) method and the multipath estimation direct mitigation (MEDM) method for multipath mitigation is proposed. Experimental results show that the Ref-MEDLL multipath estimation method has good adaptability to multipath signals that have different time delays and different amplitudes; both the MEDM receiver and the MEAM-VT receiver have good multipath mitigation performance. The MEAM-VT method performs better than the MEDM method in multipath mitigation and tracking, but the stability of the pseudorange observations of the MEAM-VT method is not as good as that of the MEDM method. The positioning accuracy of the MEDM receiver and the MEAM-VT receiver has been improved to different degrees in static positioning experiments and dynamic positioning experiments.
Snow Cover on the Tibetan Plateau and Topographic Controls
Authors: Chu Duo , Liu Linshan , Wang Zhaofeng
Published: August 2023

Snow cover plays a critical role in global energy and water cycles. Snow cover on the Tibetan Plateau (TP) provides vital water sources in western China and Himalayan regions, in addition to its weather and climate significance. The massive high mountain topography of the TP is the main condition for the presence and persistence of snow cover on the plateau at the mid-low latitudes of the Northern Hemisphere (NH). However, how the mountain topography controls snow-cover distribution on the TP remains largely unclear, and the relationship is not well quantified. Here, the spatial distribution and the topographic controls of snow cover on the TP are examined based on snow cover frequency (SCF) derived from MODIS snow cover product (MOD10A2 v005) and digital elevation model (DEM) data. The results show that snow cover on the TP is spatially unevenly distributed, and that it is characterized by rich snow and high SCF on the interior and the surrounding high mountain ranges, with less snow and low SCF in inland basins and river valleys. Snow cover on the TP presents elevation dependence: the higher the altitude, the higher the SCF, the longer the snow cover duration, and the more stable the intra-annual variation. The annual mean SCF below 3000 m above sea level (m a.s.l) is less than 4%, and it reaches 77% above 6000 m a.s.l. The intra-annual snow cover variation below 4000 m a.s.l features a unimodal distribution, while above 4000 m a.s.l it presents a bimodal distribution. The mean minimum SCF below 6000 m a.s.l occurs in summer, while above 6000 m a.s.l it occurs in winter. Due to differences in solar radiation and moisture condition caused by the mountain slope and aspect, the mean SCF generally increases with mountain slopes, and it is the highest on the north-facing aspect and the lowest on the south-facing aspect.
A Method for Extracting Lake Water Using ViTenc-UNet: Taking Typical Lakes on the Qinghai-Tibet Plateau as Examples
Authors: Zhao Xili , Wang Hong , Liu Li , Zhang Yao , Liu Jiahao , Qu Tengfei , Tian Haozhe , Lu Yuting
Published: August 2023

As the lakes located in the Qinghai-Tibet Plateau are important carriers of water resources in Asia, dynamic changes to these lakes intuitively reflect the climate and water resource variations of the Qinghai-Tibet Plateau. To address the insufficient performance of the Convolutional Neural Network (CNN) in learning the spatial relationship between long-distance continuous pixels, this study proposes a water recognition model for lakes on the Qinghai-Tibet Plateau based on U-Net and ViTenc-UNet. This method uses Vision Transformer (ViT) to replace the continuous Convolutional Neural Network layer in the encoder of the U-Net model, which can more accurately identify and extract the continuous spatial relationship of lake water bodies. A Convolutional Block Attention Module (CBAM) mechanism was added to the decoder of the model enabling the spatial information and spectral information characteristics of the water bodies to be more completely preserved. The experimental results show that the ViTenc-UNet model can complete the task of lake water recognition on the Qinghai-Tibet Plateau more efficiently, and the Overall Accuracy, Intersection over Union, Recall, Precision, and F1 score of the classification results for lake water bodies reached 99.04%, 98.68%, 99.08%, 98.59%, and 98.75%, which were, respectively, 4.16%, 6.20% 5.34%, 4.80%, and 5.34% higher than the original U-Net model. Compared to FCN, the DeepLabv3+, TransUNet, and Swin-Unet models also have different degrees of advantages. This model innovatively introduces ViT and CBAM into the water extraction task of lakes on the Qinghai-Tibet Plateau, showing excellent water classification performance of these lake bodies. This method has certain classification advantages and will provide an important scientific reference for the accurate real-time monitoring of important water resources on the Qinghai-Tibet Plateau.
Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0
Authors: Chataut Robin , Phoummalayvane Alex , Akl Robert
Published: August 2023

The Internet of Things (IoT) technology and devices represent an exciting field in computer science that is rapidly emerging worldwide. The demand for automation and efficiency has also been a contributing factor to the advancements in this technology. The proliferation of IoT devices coincides with advancements in wireless networking technologies, driven by the enhanced connectivity of the internet. Today, nearly any everyday object can be connected to the network, reflecting the growing demand for automation and efficiency. This paper reviews the emergence of IoT devices, analyzed their common applications, and explored the future prospects in this promising field of computer science. The examined applications encompass healthcare, agriculture, and smart cities. Although IoT technology exhibits similar deployment trends, this paper will explore different fields to discern the subtle nuances that exist among them. To comprehend the future of IoT, it is essential to comprehend the driving forces behind its advancements in various industries. By gaining a better understanding of the emergence of IoT devices, readers will develop insights into the factors that have propelled their growth and the conditions that led to technological advancements. Given the rapid pace at which IoT technology is advancing, this paper provides researchers with a deeper understanding of the factors that have brought us to this point and the ongoing efforts that are actively shaping the future of IoT. By offering a comprehensive analysis of the current landscape and potential future developments, this paper serves as a valuable resource to researchers seeking to contribute to and navigate the ever-evolving IoT ecosystem.
A Mechanical Defect Localization and Identification Method for High-Voltage Circuit Breakers Based on the Segmentation of Vibration Signals and Extraction of Chaotic Features
Authors: Cao Shi , Zhao Tong , Wang Gang , Zhang Tigui , Liu Chenlei , Liu Qinzhe , Zhang Zhenming , Wang Xiaolong
Published: August 2023

To address the problem of mechanical defect identification in a high-voltage circuit breaker (HVCB), this paper studies the circuit breaker vibration signal and proposes a method of feature extraction based on phase-space reconstruction of the vibration substages. To locate mechanical defects in circuit breakers, vibration signals are divided into different substages according to the time sequence of the parts of the circuit breakers. The largest Lyapunov exponent (LLE) of the vibration signals’ substages is calculated, and then the substages are reconstructed in high-dimensional phase space. The geometric features of the phase trajectory mean center distance (MCD) and vector diameter offset (VDO) are calculated, and the LLE, MCD, and VDO are selected as the three fault identification features of the vibration substages. The eigenvalue anomaly rate of each substage of the vibration signal under defect state are calculated and analyzed to locate the vibration substage of the mechanical defect. Finally, a fault diagnosis model is constructed by a support vector machine (SVM), and the common mechanical defects of circuit breakers simulated in the laboratory are effectively identified.
Scaled-Model Radar Cross-Section Measurement: The Influence of the Scattered Field under Gaussian Beam Illumination—A Theoretical Analysis
Authors: Ang Yi Xuan , Lui Hoi-Shun
Published: August 2023

At microwave frequencies, radar cross-section (RCS) measurements are usually performed by placing the target in the far-field region of the antenna. The wavefront of the radiating field from the antenna can be approximated as planar, ensuring that the incident field and the power interact with the target independently of the antenna. However, for electrically large targets, the required distance becomes significant, posing challenges for implementation. Scaled-model RCS measurements offer an alternative solution. RCS measurements at terahertz and optical frequencies typically require a collimated beam as the source, where the intercepted power and RCS become dependent on the excitation. To address this dependency, researchers have proposed modifying the RCS definition to account for the intercepted power and to analytically formulate the scattering problem. However, such modifications require prior knowledge of the target’s geometry and material properties, which are often not readily available in practice. This also limits the study to only canonical targets. In this paper, we propose an alternative approach for modelling the intercepted power. The Gaussian beam is decomposed into a number of plane waves travelling to different directions using the theory of plane wave spectrum. The scattering problem is solved using the full-wave method of moment. Through theoretical proofs and numerical examples involving spheres and a non-canonical target, with a scaled-model aircraft, we demonstrate that the original RCS definition can serve as a good approximation for scaled measurements, provided that the beam waist is approximately four times the target’s dimensions. These findings provide valuable guidelines for radar engineers when performing scaled measurements using collimated beams. The results, which match those obtained from full-model measurements, enable us to predict the RCS of full-scale targets. This capability facilitates various target-related applications, such as target characterization, classification, detection, and even recognition.
A Multi-Classifiers Based Algorithm for Energy Efficient Tasks Offloading in Fog Computing
Authors: Alasmari Moteb K. , Alwakeel Sami S. , Alohali Yousef A.
Published: August 2023

The IoT has connected a vast number of devices on a massive internet scale. With the rapid increase in devices and data, offloading tasks from IoT devices to remote Cloud data centers becomes unproductive and costly. Optimizing energy consumption in IoT devices while meeting deadlines and data constraints is challenging. Fog Computing aids efficient IoT task processing with proximity to nodes and lower service delay. Cloud task offloading occurs frequently due to Fog Computing’s limited resources compared to remote Cloud, necessitating improved techniques for accurate categorization and distribution of IoT device task offloading in a hybrid IoT, Fog, and Cloud paradigm. This article explores relevant offloading strategies in Fog Computing and proposes MCEETO, an intelligent energy-aware allocation strategy, utilizing a multi-classifier-based algorithm for efficient task offloading by selecting optimal Fog Devices (FDs) for module placement. MCEETO decision parameters include task attributes, Fog node characteristics, network latency, and bandwidth. The method is evaluated using the iFogSim simulator and compared with edge-ward and Cloud-only strategies. The proposed solution is more energy-efficient, saving around 11.36% compared to Cloud-only and approximately 9.30% compared to the edge-ward strategy. Additionally, the MCEETO algorithm achieved a 67% and 96% reduction in network usage compared to both strategies.
Harmonic Stability Assessment of Commercially Available Single-Phase Photovoltaic Inverters Considering Operating-Point Dependencies
Authors: Kaufhold Elias , Meyer Jan , Myrzik Johanna , Schegner Peter
Published: August 2023

The growth of renewables in the energy sector, e.g., in public low-voltage networks, leads to an increasing share of installed power electronic devices, e.g., inverters for photovoltaic applications. To rely on these devices, suitable analyses have to be performed. This includes studies of the device stability in the harmonic frequency range, i.e., above 50 Hz up to 2 kHz. State-of-the-art time-domain studies for harmonic stability analyses require detailed knowledge about the inverter design. Black-box studies must identify the inverter characteristics in the laboratory, which can differ depending on specific operating points, i.e., specific operating powers. This study analyzes the operating-point dependency of inverters on the critical inductance values of the network impedance, e.g., the inductances at which the inverter is expected to become unstable. Measurements are performed for three operating powers of an unknown, commercially available single-phase inverter to validate the critical inductances. Two further commercially available inverters and four simulative implementations are analyzed as well with regard to the critical inductance and the critical frequency. The results demonstrate the importance of considering a representative range of operating powers of the inverter for the small-signal stability analysis.
Functional and Morphological Adaptations in the Heart of Children Aged 12–14 Years following Two Different Endurance Training Protocols
Authors: Rafailakis Lefteris , Deli Chariklia K. , Fatouros Ioannis G. , Tsiokanos Athanasios , Draganidis Dimitrios , Poulios Athanasios , Soulas Dimitrios , Jamurtas Athanasios Z.
Published: August 2023

This study investigated the cardiac functional and the morphological adaptations because of two endurance training protocols. Untrained children (N = 30, age: 12–14 years) were divided into three groups (N = 10/group). The first group did not perform any session (CONTROL), the second performed ventilatory threshold endurance training (VTT) for 12 weeks (2 sessions/week) at an intensity corresponding to the ventilatory threshold (VT) and the third (IT) performed two sessions per week at 120% of maximal oxygen uptake (VO2max). Two other sessions (30 min running at 55–65% of VO2max) per week were performed in VVT and IT. Echocardiograms (Left Ventricular end Diastolic Diameter, LVEDd; Left Ventricular end Diastolic Volume, LVEDV; Stroke Volume, SV; Ejection Fraction, EF; Posterior Wall Thickness of the Left Ventricle, PWTLV) and cardiopulmonary ergospirometry (VO2max, VT, velocity at VO2max (vVO2max), time in vVO2max until exhaustion (Tlim) was conducted before and after protocols. Significant increases were observed in both training groups in LVEDd (VTT = 5%; IT = 3.64%), in LVEDV (VTT = 23.7%; ITT = 13.6%), in SV (VTT = 25%; IT = 16.9%) but not in PWTLV and EF, after protocols. No differences were noted in the CONTROL group. VO2max and VT increased significantly in both training groups by approximately 9% after training. Our results indicate that intensity endurance training does not induce meaningful functional and morphological perturbations in the hearts of children.
Consumer Attitudes and Preferences towards Traditional Food Products in Vojvodina
Authors: Peulić Tatjana , Marić Aleksandar , Maravić Nikola , Novaković Aleksandra , Kalenjuk Pivarski Bojana , Čabarkapa Ivana , Lazarević Jasmina , Šmugović Stefan , Ikonić Predrag
Published: August 2023

The objective of this study was to identify consumers’ attitudes about the consumption and certification of traditional food products, special characteristics to which they pay attention when buying food products, and their opinions regarding what traditional food products are to them. The research was based on an online questionnaire conducted on a sample of 540 respondents in the Autonomous Province of Vojvodina. The results showed that 98.3% of the respondents consume traditional food products in their households, 95.2% of the consumers decide to buy food products based on their quality, and 68.2% of the consumers believe that certain types of certification can improve product placement on the market. The specific characteristics that consumers mostly prioritize when buying food products are products with no added sugar (41.2%), traditional production processes (38.8%), GMO-free products (36.9%), organic products (36.4%), and additive-free products (34.9%). The results of this research indicate that consumers primarily perceive traditional food products as items produced using traditional methods (72.8%), characterized by the absence of additives (53.2%), specific to a certain geographic area (49.9%), sourced from small farms or facilities (49.5%), and products with long production tradition (49%).
Fuel Economy Energy Management of Electric Vehicles Using Harris Hawks Optimization
Authors: Rezk Hegazy , Abdelkareem Mohammad Ali , Alshathri Samah Ibrahim , Sayed Enas Taha , Ramadan Mohamad , Olabi Abdul Ghani
Published: August 2023

Fuel cell hybrid electric vehicles (FCEVs) have gained significant attention due to their environmentally friendly nature and competitive performance. These vehicles utilize a fuel cell system as the primary power source, with a secondary power source such as a battery pack or supercapacitor. An energy management strategy (EMS) for FCEVs is critical in optimizing power distribution among different energy sources, considering factors such as hydrogen consumption and efficiency. The proposed EMS presents an optimized external energy maximization strategy using the Harris Hawks Optimization to reduce hydrogen consumption and enhance the system’s efficiency. Through a comparative simulation using the Federal Test Procedure (FTP-75) for the city driving cycle, the performance of the proposed EMS was evaluated and compared to existing algorithms. The simulation results indicate that the proposed EMS outperforms other existing solutions in terms of fuel consumption reduction, with a potential reduction of 19.81%. Furthermore, the proposed energy management strategy also exhibited an increase in system efficiency of 0.09%. This improvement can contribute to reducing the reliance on fossil fuels and mitigating the negative environmental impacts associated with vehicle emissions.
Integrated Traditional Water Knowledge in Urban Design and Planning Practices for Sustainable Development: Challenges and Opportunities
Authors: Asad Rumana , Vaughan Josephine , Ahmed Iftekhar
Published: August 2023

In the context of flood research, scholars and practitioners have recognised that Western-knowledge-driven engineering-based flood management techniques are insufficient for successful water use and management in urban design and planning practices, while ideas, practices, and knowledge from local people are essential. Traditional water knowledge (TWK) explains people’s profound understanding of natural processes and the ecological dependencies of water systems and connections with their local water system and the land, beliefs, sense, and practices that are an integral part of their culture. However, the concept of traditional knowledge may differ from scientific knowledge, as it represents a different worldview perspective from a modern Westernised world. Considering Khulna City, Bangladesh, as a case, this paper investigates the salient challenges and opportunities to integrate TWK with present urban design and planning practices. Interviews were conducted with key stakeholders, including relevant government officials, NGO workers, researchers, urban professionals, and local elders. This study finds that TWK can contribute to urban design and planning practices by identifying helpful ecosystem services and site-specific information; by sharing strategies for surface water protection, open-space design, and rainwater harvesting; and encouraging design of spaces for psychological benefit, and ensuring sustainability and building flood resilience in an urban context. Furthermore, this research demonstrates how these elements relate to the Sustainable Development Goals (SDGs). However, issues with knowledge transmission, the identification of the actual knowledge holders, poor governance, weak urban planning, minimal institutional capacity, and perceived cultural inferiority are significant challenges restricting the integration of TWK, despite its relevance to sustainability. This paper suggests that considering traditional water use and management is necessary to develop flood resilience in an urban context in a sustainable way.
Digital Ability and Livelihood Diversification in Rural China
Authors: Li Danyang , Kojima Daizo , Wu Laping , Ando Mitsuyoshi
Published: August 2023

Livelihood diversification is an important strategy for rural households in developing countries, especially in China, which has the largest rural population in the world. In the current digital age, the existing literature lacks sufficient research on the influence of digital ability on livelihood diversification. Using survey data from 1914 rural households in China, this study evaluates the digital ability of rural households through item response theory. Additionally, the livelihood diversification of rural households is analyzed from two aspects: work type and industry. Finally, IV-Tobit models are set up to test the impact of digital ability on livelihood diversification. The results show that: (1) engaging in both agricultural production and employed work concurrently is the key strategy for rural households to diversify their livelihoods; (2) digital ability significantly promotes livelihood diversification, regarding both work type and industry; (3) digital ability’s capacity to diversify livelihood is particularly notable for low-income households, followed by the medium-income group, then the high-income group. These findings are meaningful for the sustainable improvement of rural households’ livelihoods.
Industrial Agglomeration and Corporate ESG Performance: Empirical Evidence from Manufacturing and Producer Services
Authors: Guo Xuemeng , Guo Ke , Kong Lingpeng
Published: August 2023

Global climate change has emerged as a persistent global crisis. Under the dual pressures of industrial structure upgrading and ecological environment improvement, enhancing enterprise ESG (Environmental, Social, and Governance) performance can contribute to achieving sustainable development of the global economy. Selected a sample of 285 prefecture-level cities in China from 2005 to 2020 and panel data of listed companies to empirically examine the impact of industrial agglomeration on corporate ESG performance and its heterogeneity effects. We found that industrial agglomeration generally positively affects corporate ESG performance, with the significant promotion of ESG performance in manufacturing and a “U”-shaped relationship between producer services. Influence channel analysis found that industrial agglomeration acts on corporate ESG performance through the micro-transmission mechanisms of financing constraints, investment levels, market competitiveness, and internal control. Heterogeneity research found that the impact of manufacturing agglomeration on corporate ESG performance is more significant in capital-intensive and high-end technology industries, while producer service agglomeration has a more significant effect on ESG performance for knowledge-intensive industries. This study contributes to a better understanding of the microeconomic consequences of industrial agglomeration and expands the research perspective on the internal mechanisms and external incentives of corporate ESG performance. It provides a basis for local governments to analyze the different characteristics and microeconomic consequences of industrial agglomeration and provide empirical evidence for listed companies to adjust their ESG performance structure dynamically.
New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution
Authors: Kamalov Firuz , Santandreu Calonge David , Gurrib Ikhlaas
Published: August 2023

The recent high performance of ChatGPT on several standardized academic tests has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. As deep learning is poised to shift the teaching paradigm, it is essential to have a clear understanding of its effects on the current education system to ensure sustainable development and deployment of AI-driven technologies at schools and universities. This research aims to investigate the potential impact of AI on education through review and analysis of the existing literature across three major axes: applications, advantages, and challenges. Our review focuses on the use of artificial intelligence in collaborative teacher–student learning, intelligent tutoring systems, automated assessment, and personalized learning. We also report on the potential negative aspects, ethical issues, and possible future routes for AI implementation in education. Ultimately, we find that the only way forward is to embrace the new technology, while implementing guardrails to prevent its abuse.
A Dispatching Method for Large-Scale Interruptible Load and Electric Vehicle Clusters to Alleviate Overload of Interface Power Flow
Authors: Ye Xi , Li Gan , Zhu Tong , Zhang Lei , Wang Yanfeng , Wang Xiang , Zhong Hua
Published: August 2023

The study of dispatching methods for large-scale interruptible loads and electric vehicle clusters is of great significance as an optional method to alleviate the problem of overload in interface power flow. In this paper, the distribution model and transfer capacity of large-scale interruptible load and electric vehicle in two dimensions of time and space were firstly introduced. Then, a large-scale interruptible load and electric vehicle dispatching model considering transmission interface power flow balance was established. Finally, a case study was carried out with the city power grid as the research object. Studies show that by dispatching large-scale interruptible load and electric vehicle, the overload rate of interface power flow can be reduced by 12–17%, while the proportion of clean energy generation increased by 4.19%. Large-scale interruptible load and electric vehicles are quite different in terms of the role they play in grid regulation. The regulation cost of electric vehicles is higher than that of large-scale interruptible load, but it also has the advantages of promoting the consumption of clean energy and improving the overall operating economy. Which type of resource should be given priority is based on the actual state of the grid. In addition, the cost of electricity has a significant impact on the load response behavior of electric vehicles. It should be determined according to various factors, such as interface power flow control requirements, regulation costs, and power grid operation costs.
Research on the Influencing Factors of University Students’ Learning Ability Satisfaction under the Blended Learning Model
Authors: Wang Xingyang , Chen Xiaohui , Wu Xinyi , Lu Jia , Xu Bin , Wang Hanxi
Published: August 2023

At present, the learning ability satisfaction of university students under the blended learning mode is low, and this has an impact on the effect of teaching and students’ learning experiences. In order to effectively improve learning ability satisfaction, empirical research and a structural equation model were used to explore the influencing factors of university students’ learning ability satisfaction. This study identified the influencing factors of university students’ learning ability satisfaction under the blended learning model, and constructed a structural equation model of these factors based on their relationship with learning ability satisfaction. The model was verified and optimized to determine the weight of factors that affected university students’ learning ability satisfaction. The study showed that the external and internal factors with the greatest effect on university students’ learning ability satisfaction were resource support and learning self-efficacy, respectively. Internal influencing factors had a greater impact on the satisfaction of university students’ learning abilities than external factors. This study will expand the existing research perspective on learning ability satisfaction, provide important references for improving curriculum design and teaching effectiveness, and provide a theoretical basis for solving various practical questions caused by low learning ability satisfaction in teaching practice.
Meta-Analysis of Implementation Intentions Interventions in Promoting Physical Activity among University Students
Authors: Peng Sanying , Othman Ahmad Tajuddin , Khairani Ahmad Zamri , Zhou Zhuang , Zhou Xiaogang , Yuan Fang , Liang Jinghong
Published: August 2023

Implementation intentions (II) have demonstrated their efficacy in promoting physical activity (PA) among various populations, including adults, the general population, and those with chronic conditions. However, there is a dearth of meta-analyses examining this efficacy among university students. This meta-analysis aims to determine the effectiveness of II interventions in improving PA among university students. Six online databases (PubMed, Embase, Web of Science, Cochrane Central, PsycINFO, and PsycArticle) were comprehensively searched. Recursive searching and grey literature collection strategies were employed to identify relevant studies. The meta-analysis employed a random-effects model to combine effect sizes for different PA outcomes. The Cochrane Risk of Bias tool was used to assess the quality of the included studies, and sensitivity analysis was performed to assess the robustness of the results. Twelve studies involving 1916 participants met the inclusion criteria. The findings indicated that II interventions significantly increased PA among university students compared to control groups (standardized mean difference [SMD] = 0.31, 95% confidence interval [CI]: 0.12, 0.50, p < 0.001). Subgroup analyses revealed larger effect sizes in the following groups: publication year after 2013, inactive university students, the reinforcement group, the action planning group, and the intervention period of fewer than six weeks. The above findings offer compelling evidence that II interventions can effectively promote PA among university students. The integration of IIs with e-health platforms and the implementation of individualized and multifaceted intervention models exhibit promising sustainability for promoting PA on campus.
The Modified Soil Moisture Constraint Scheme Significantly Enhances the Evapotranspiration Simulation Accuracy of the MOD16 Model
Authors: Guo Mengjing , Huang Yujia , Li Jing , Luo Zelin
Published: August 2023

Remotely sensed (RS) evapotranspiration (ET) models can make full use of the land surface information retrieved using remote sensing and are therefore widely used in large-scale ET estimates. The MODIS Global Evapotranspiration model (MOD16) is one of the most commonly used remote sensing ET models. MOD16 parameterizes the moisture constraints on soil evaporation (Es) using atmospheric vapor pressure deficit (VPD) and relative humidity (RH). This moisture constraint algorithm has been criticized by many studies due to the weak correlation between soil moisture and VPD or RH over short timescales (e.g., hourly and daily). In this study, we introduce a modified moisture constraint algorithm of ET, based on the ratio of antecedent accumulated precipitation to soil equilibrium evaporation, in order to improve the ET simulation capabilities of the MOD16 model. The original and modified MOD16 models are evaluated at 14 ChinaFlux sites and 286 basins in China, using eddy covariance measurements and water-balance-based ET estimates. The results show that the modified MOD16 model outperforms the original MOD16 model at both the site and basin scales. Compared with the original model, the modified model increases the value of KGE by an average of 0.17 at the flux site scale and by 0.01 at the basin scale. Using soil moisture measurements from flux sites as a reference, we further found that the modified MOD16 model also has a better soil moisture simulation capacity than the original model. This study highlights the importance of reliable soil moisture constraints in remotely sensed ET models.
Evaluation of the Reduced Protocol for the Assessment of Rate of Force Development Scaling Factor
Authors: Stefanović Života , Kukić Filip , Knežević Olivera M. , Šarabon Nejc , Mirkov Dragan M.
Published: August 2023

The rate of force development scaling factor (RFD-SF) has been used to assess neuromuscular quickness. However, the common protocols are lengthy. This study evaluated the validity and reliability of the reduced protocol to assess the RFD-SF and its validity in detecting inter-limb asymmetries. Eighteen participants (five females and thirteen males; mean age = 20.8 ± 0.6 years) performed the common and reduced RFD-SF protocols (five isometric pulse knee extensions at 30 and 70% of maximal voluntary contraction). A repeat measure design was employed including one test session of the common protocol and two test sessions of the reduced protocol. Correlation analysis was conducted to investigate the association between the two protocols, while a paired-sample t-test and a Bland–Altman plot assessed whether the reduced protocol provided valid results. The between-day reliability was assessed using an intra-class correlation coefficient, coefficient of variation, typical error of measurement, and paired-sample t-test. The validity to detect asymmetries was checked with the paired-sample t-test. The correlation between RFD-SF obtained using two protocols was significant (p < 0.001) and very large for the dominant (r = 0.71) and non-dominant (r = 0.80) legs. No significant difference occurred between protocols in the RFD-SF for the dominant (p = 0.480, d = 0.17) and non-dominant legs (p = 0.213, d = 0.31). The reliability was acceptable for both legs, with no between-day difference for the dominant (p = 0.393) and non-dominant legs (p = 0.436). No significant difference between the two protocols (p = 0.415, d = 0.19) was found in the detection of inter-limb asymmetries. The results of this study suggest that the reduced protocol could be used as a valid and reliable alternative to the common protocol, as well as to identify interlimb asymmetries.
Rapid Assessment of Ocular Toxicity from Environmental Contaminants Based on Visually Mediated Zebrafish Behavior Studies
Authors: Yi Jia , Ma Yilei , Ma Jiahui , Yu Haiyang , Zhang Kun , Jin Libo , Yang Qinsi , Sun Da , Wu Dejun
Published: August 2023

The presence of contaminants in the environment has increased in recent years, and studies have demonstrated that these contaminants have the ability to penetrate the blood–retinal barrier and directly affect the visual systems of organisms. Zebrafish are recognized as an ideal model for human eye diseases due to their anatomical and functional similarities to the human eye, making them an efficient and versatile organism for studying ocular toxicity caused by environmental contaminants in the field of environmental toxicology. Meanwhile, zebrafish exhibit a diverse repertoire of visually mediated behaviors, and their visual system undergoes complex changes in behavioral responses when exposed to environmental contaminants, enabling rapid assessment of the ocular toxicity induced by such pollutants. Therefore, this review aimed to highlight the effectiveness of zebrafish as a model for examining the effects of environmental contaminants on ocular development. Special attention is given to the visually mediated behavior of zebrafish, which allows for a rapid assessment of ocular toxicity resulting from exposure to environmental contaminants. Additionally, the potential mechanisms by which environmental contaminants may induce ocular toxicity are briefly outlined.
Quality of Electronic TB Register Data Compared with Paper-Based Records in the Kyrgyz Republic
Authors: Shauer Daniil , Petrosyan Ofelya , Gemilyan Manik , Kamau Edward M. , Thekkur Pruthu , Goncharova Olga , Gulmira Kalmambetova , Kyrbashov Bolot , Istamov Kylychbek , Kadyrov Meder , Wilkinson Ewan
Published: August 2023

This study evaluated the effectiveness of an electronic system for managing individuals with drug-sensitive pulmonary tuberculosis in the Kyrgyz Republic. This cohort study used programmatic data. The study included people registered on the paper-based system in 2019 and 302 people registered on both the electronic and the paper-based systems between June 2021 and May 2022. The data from the 302 individuals were used to assess the completeness of each form of record and the concordance of the electronic record with the paper-based system. This study showed that for most variables, the completeness and concordance were 85.3–93.0% and were lowest for nonmandatory fields such as medication side effects (26.8% vs. 13.6%). No significant difference was observed in the time taken from symptom onset to diagnosis and treatment initiation between the two systems. However, the electronic system had a significantly higher percentage of subjects who initiated treatment on the day of diagnosis (80.3% vs. 57.1%). The proportion with successful outcomes was similar in both groups, but the electronic system had a significantly lower proportion of individuals with outcomes that were not evaluated or recorded (4.8% vs. 14.3%, p < 0.001). This study highlights the potential advantages and gaps associated with implementing an electronic TB register system for improving records.
VP4/VP56/VP35 Virus-like Particles Effectively Protect Grass Carp (Ctenopharyngodon idella) against GCRV-II Infection
Authors: Tian Qingqing , Huo Xingchen , Liu Qian , Yang Chunrong , Zhang Yongan , Su Jianguo
Published: August 2023

Grass carp reovirus (GCRV) seriously threatens the grass carp (Ctenopharyngodon idella) industry. Prophylactic GCRV vaccines prepared by virus-like particle (VLP) assembly biotechnology can improve effectiveness and safety. The highly immunogenic candidate antigens of GCRV vaccines that have been generally considered are the outer capsid proteins VP4, VP56, and VP35. In this study, VP4, VP56, and VP35 were expressed in an Escherichia coli expression system and a Pichia pastoris expression system. The successful assembly of uniform, stable, and non-toxic VP4/VP56/VP35 VLPs was confirmed through various assays. After vaccination and GCRV infection, the survival rate in the VLPs + adjuvant Astragalus polysaccharide (APS) group was the highest (62%), 40% higher than that in control group (22%). Through the antibody levels, tissue viral load, and antioxidant immunity assays, the P. pastoris VLP vaccine effectively improved IgM levels, alleviated tissue virus load, and regulated antioxidant immune-related indicators. The treatment with P. pastoris VLPs enhanced the mRNA expression of important immune-related genes in the head kidney, as measured by qRT-PCR assay. Upon hematoxylin-eosin staining examination, relatively reduced tissue pathological damage was observed in the VLPs + APS group. The novel vaccine using P. pastoris VLPs as an effective green biological agent provides a prospective strategy for the control of fish viral diseases.
Detection of Venezuelan Equine Encephalitis Virus from Brain Samples of Equines with Encephalitis
Authors: León Bernal , Estrella-Morales Josimar , Jiménez Carlos
Published: August 2023

Alphavirus species are globally distributed zoonoses primarily transmitted by arthropods. The Venezuelan equine encephalitis virus (VEEV) and Eastern equine encephalitis virus (EEEV) are endemic in Costa Rica. This study aims to detect these viruses in brain samples from equines displaying nervous signs. For this purpose, four published Universal RT-PCR methods were compared. The most sensitive and specific RT-PCR method was used to test a total of 70 brain samples, including 40 from bovines and 30 from equines, all exhibiting nervous signs. In the positive cases, eight different brain regions were extracted and tested using this RT-PCR. Positive cases were confirmed through sequencing. Torii RT-PCR demonstrated the highest sensitivity and specificity for diagnosing VEEV and EEEV/Sind among the four Universal RT-PCR assays. Not all assessed brain regions showed DNA amplification. None of the bovine brains was positive, and out of the 30 equine brain samples, only four tested positive, and sequencing confirmed two of these samples as VEEV subtype IE. Torii RT-PCR successfully detected VEEV in pools of the hippocampus, spinal cord, and basal nuclei, making these brain regions suitable for diagnosing this virus. None of the samples were positive for EEEV or WEEV.