bluuebunny/crossref_metadata_2025 huggingface dataset:
Safety, Efficiency, and Mental Workload in Simulated Teledriving of a Vehicle as Functions of Camera Viewpoint
Authors: Musicant Oren , Botzer Assaf , Richmond-Hacham Bar
Published: September 2024

Teleoperation services are expected to operate on-road and often in urban areas. In current teleoperation applications, teleoperators gain a higher viewpoint of the environment from a camera on the vehicle’s roof. However, it is unclear how this viewpoint compares to a conventional viewpoint in terms of safety, efficiency, and mental workload. In the current study, teleoperators (n = 148) performed driving tasks in a simulated urban environment with a conventional viewpoint (i.e., the simulated camera was positioned inside the vehicle at the height of a driver’s eyes) and a higher viewpoint (the simulated camera was positioned on the vehicle roof). The tasks required negotiating road geometry and other road users. At the end of the session, participants completed the NASA-TLX questionnaire. Results showed that participants completed most tasks faster with the higher viewpoint and reported lower frustration and mental demand. The camera position did not affect collision rates nor the probability of hard braking and steering events. We conclude that a viewpoint from the vehicle roof may improve teleoperation efficiency without compromising driving safety, while also lowering the teleoperators’ mental workload.
Beamforming for Multi-Bit Intelligent Reflecting Surface with Phase Shift-Dependent Power Consumption Model
Authors: Zhang Huimin , Wu Qiucen , Zhu Yu
Published: September 2024

In recent years, the intelligent reflecting surface (IRS) has attracted increasing attention for its capability to intelligently reconfigure the wireless propagation channel. However, most existing works ignore the dynamic power consumption of IRS related to the phase shift configuration. This relationship gets even more intractable for a multi-bit IRS because of its nonlinearity and implicit form. In this paper, we investigate the beamforming optimization for multi-bit IRS-aided systems with the practical phase shift-dependent power consumption (PS-DPC) model, aiming at minimizing the power consumption of the system. To solve the implicit and nonlinear relationship, we introduce a selection matrix to explicitly represent the power consumption and the phase shift matrix of the IRS, respectively. Then, we propose a generalized Benders decomposition-based beamforming optimization algorithm in the single-user scenario. Furthermore, in the multi-user scenario, we design a coordinate descent-based algorithm and a genetic algorithm for the beamforming optimization. The simulation results show that the proposed algorithms significantly decrease the power consumption of the multi-bit IRS-aided systems.
Dual-Band Passive Beam Steering Antenna Technologies for Satellite Communication and Modern Wireless Systems: A Review
Authors: Nabeel Maira I. , Singh Khushboo , Afzal Muhammad U. , Thalakotuna Dushmantha N. , Esselle Karu P.
Published: September 2024

Efficient beam steerable high-gain antennas enable high-speed data rates over long-distance networks, including wireless backhaul, satellite communications (SATCOM), and SATCOM On-the-Move. These characteristics are essential for advancing contemporary wireless communication networks, particularly within 5G and beyond. Various beam steering solutions have been proposed in the literature, with passive beam steering mechanisms employing planar metasurfaces emerging as cost-effective, power-efficient, and compact options. These attributes make them well-suited for use in confined spaces, large-scale production and widespread distribution to meet the demands of the mass market. Utilizing a dual-band antenna terminal setup is often advantageous for full duplex communication in wireless systems. Therefore, this article presents a comprehensive review of the dual-band beam steering techniques for enabling full-duplex communication in modern wireless systems, highlighting their design methodologies, scanning mechanisms, physical characteristics, and constraints. Despite the advantages of planar metasurface-based beam steering solutions, the literature on dual-band beam steering antennas supporting full duplex communication is limited. This review article identifies research gaps and outlines future directions for developing economically feasible passive dual-band beam steering solutions for mass deployment.
Study of Acoustic Emission Signal Noise Attenuation Based on Unsupervised Skip Neural Network
Authors: Wulan Tuoya , Li Guodong , Huo Yupeng , Yu Jiangjiang , Wang Ruiqi , Kou Zhongzheng , Yang Wen
Published: September 2024

Acoustic emission (AE) technology, as a non-destructive testing methodology, is extensively utilized to monitor various materials’ structural integrity. However, AE signals captured during experimental processes are often tainted with assorted noise factors that degrade the signal clarity and integrity, complicating precise analytical evaluations of the experimental outcomes. In response to these challenges, this paper introduces an unsupervised deep learning-based denoising model tailored for AE signals. It juxtaposes its efficacy against established methods, such as wavelet packet denoising, Hilbert transform denoising, and complete ensemble empirical mode decomposition with adaptive noise denoising. The results demonstrate that the unsupervised skip autoencoder model exhibits substantial potential in noise reduction, marking a significant advancement in AE signal processing. Subsequently, the paper focuses on applying this advanced denoising technique to AE signals collected during the tensile testing of steel fiber-reinforced concrete (SFRC), the tensile testing of steel, and flexural experiments of reinforced concrete beam, and it meticulously discusses the variations in the waveform and the spectrogram of the original signal and the signal after noise reduction. The results show that the model can also remove the noise of AE signals.
Compact VHF/UHF Ultrawideband Discone Antenna with Consistent Pattern
Authors: Li Guang , Zhang Fushun , Wang Bingnan
Published: September 2024

A compact VHF/UHF ultrawideband discone antenna with consistent patterns is proposed in this article. The proposed antenna consists of a disk, a modified cone, an inverted cone, four shorting probes, and two sleeves. To improve the radiation angular distortion at high frequencies, two sleeves are inserted into the discone antenna. Higher-order modes are suppressed, and ultrawideband consistent patterns are obtained without antenna size increasing. An inverted cone and four shorting probes are introduced to achieve broadband and profile reduction. An antenna prototype is fabricated and measured. The proposed antenna possesses consistent patterns in a 11.36:1 bandwidth. The pattern nulls is improved by 26.1 dB. The antenna occupies a cylindrical volume of 0.227 λ0 (D) and 0.096 λ0 (H). It is a competitive candidate for future in-vehicle communication systems.
From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management
Authors: Hasan Mohd. Rahil , Mughees Mohd , Shaikh Shifa , Choudhary Furqan , Nizam Anam , Rizwan Amber , Ansari Onaiza , Iqbal Yusra , Pilloton Roberto , Wajid Saima , Narang Jagriti
Published: September 2024

Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than one-third of all cancer cases affecting women. It causes aberrant cell development, which can assault or spread to other sections of the body, perhaps leading to the patient’s death. Based on research findings, timely detection can diminish the likelihood of mortality and enhance the quality of healthcare provided for the illness. However, current technologies can only identify cancer at an advanced stage. Consequently, there is a substantial demand for rapid and productive approaches to detecting breast cancer. Researchers are actively pursuing precise and timely methods for the diagnosis of breast cancer, aiming to achieve enhanced accuracy and early detection. Biosensor technology can allow for the speedy and accurate diagnosis of cancer-related cells, as well as a more sensitive and specialized technique for generating them. Additionally, numerous treatments for breast cancer are depicted such as herbal therapy, nanomaterial-based drug delivery, miRNA targeting, CRISPR technology, immunotherapy, and precision medicine. Early detection and efficient therapy are necessary to manage such a severe illness properly.
Signal Quality in Continuous Transcutaneous Bilirubinometry
Authors: Crivellaro Fernando , Costa Anselmo , Vieira Pedro
Published: September 2024

Bilirubin is a product of the metabolism of hemoglobin from red blood cells. Higher levels of bilirubin are a sign that either there is an unusual breaking down rate of red blood cells or the liver is not able to eliminate bilirubin, through bile, into the gastrointestinal tract. For adults, bilirubin is occasionally monitored through urine or invasive blood sampling, whilst all newborns are routinely monitored visually, or non-invasively with transcutaneous measurements (TcBs), due to their biological immaturity to conjugate bilirubin. Neonatal jaundice is a common condition, with higher levels of unconjugated bilirubin concentration having neurotoxic effects. Actual devices used in TcBs are focused on newborn populations, are hand-held, and, in some cases, operate in only two wavelengths, which does not necessarily guarantee reliable results over all skin tones. The same occurs with visual inspections. Based on that, a continuous bilirubin monitoring device for newborns is being developed to overcome visual inspection errors and to reduce invasive procedures. This device, operating optically with a mini-spectrometer in the visible range, is susceptible to patient movements and, consequently, to situations with a lower signal quality for reliable bilirubin concentration estimates on different types of skin. Therefore, as an intermediate development step and, based on skin spectra measurements from adults, this work addresses the device’s placement status prediction as a signal quality indication index. This was implemented by using machine learning (ML), with the best performances being achieved by support vector machine (SVM) models, based on the spectra acquired on the arm and forehead areas.
A Mixed Approach for Clock Synchronization in Distributed Data Acquisition Systems
Authors: Manduchi Gabriele , Rigoni Andrea , Trevisan Luca , Patton Tommaso
Published: September 2024

Proper timing synchronization is important when data from sensors are acquired by different devices. This paper proposes a simple but effective solution for System on Chip (SoC) architectures that integrates a general-purpose Field Programmable Gate Array (FPGA) with a CPU. The proposed approach relies on a network synchronization protocol implemented in software, such as Network Time Protocol (NTP) or Precision Time Protocol (PTP), and uses the FPGA to generate a clock reference that is maintained in step with the synchronized system clock. The clock generated by the FPGA is obtained from the FPGA oscillator via appropriate fractional clock division. Clock drift is avoided via a software program that periodically compares the FPGA and the system counters, respectively, and adjusts the fractional clock divider in order to slightly adjust the FPGA clock frequency using a Proportional Integral controller. A specific implementation is presented on the RedPitaya platform, generating a 1 MHz clock in step with the NTP synchronized system clock. The presented system has been used in a distributed data acquisition system for fast transient recording in the neutral beam test facility for the ITER nuclear fusion experiment.
Design, Simulation and Functional Testing of a Novel Ankle Exoskeleton with 3DOFs
Authors: Sergazin Gani , Zhetenbayev Nursultan , Tursunbayeva Gulzhamal , Uzbekbayev Arman , Sarina Aizada , Nurgizat Yerkebulan , Nussibaliyeva Arailym
Published: September 2024

This paper presents a study on developing a new exoskeleton for ankle joint rehabilitation with three degrees of freedom (3 DOFs). The primary attention is paid to the process of designing and modelling the device aimed at restoring the lost functions of joint mobility. The authors conducted a complex analysis of the functional requirements of the exoskeleton based on research into the potential user’s needs, which allowed for the development of a conceptual model of the proposed device. In this study, a prototype of the exoskeleton is designed using modern additive technologies. The prototype underwent virtual testing in conditions maximally close to reality, which confirmed its effectiveness and comfort of use. The main results of this study indicate the promising potential of the proposed solution for application in rehabilitation practices, especially for patients with ankle joint injuries and diseases.
Accelerating the Diagnosis of Pandemic Infection Based on Rapid Sampling Algorithm for Fast-Response Breath Gas Analyzers
Authors: Prokopiuk Artur , Wojtas Jacek
Published: September 2024

This paper presents a novel technique for extracting the alveolar part of human breath. Gas exchange occurs between blood and inhaled air in the alveoli, which is helpful in medical diagnostics based on breath analysis. Consequently, the alveolar portion of the exhaled air contains specific concentrations of endogenous EVOC (exogenous volatile organic compound), which, among other factors, depend on the person’s health condition. As this part of the breath enables the screening for diseases, accurate sample collection for testing is crucial. Inaccurate sampling can significantly alter the composition of the specimen, alter the concentration of EVOC (biomarkers) and adversely affect the diagnosis. Furthermore, the volume of alveolar air is minimal (usually <350 mL), especially in the case of people affected by respiratory system problems. For these reasons, precise sampling is a key factor in the effectiveness of medical diagnostic systems. A new technique ensuring high accuracy and repeatability is presented in the article. It is based on analyzing the changes in carbon dioxide concentration in human breath using a fast and compensated non-dispersive infrared (NDIR) sensor and the simple moving adjacent average (SMAA) algorithm. Research has shown that this method accurately identifies exhalation phases with an uncertainty as low as 20 ms. This provides around 350 ms of breath duration for carrying out additional stages of the diagnostic process using various types of analyzers.
TW-YOLO: An Innovative Blood Cell Detection Model Based on Multi-Scale Feature Fusion
Authors: Zhang Dingming , Bu Yangcheng , Chen Qiaohong , Cai Shengbo , Zhang Yichi
Published: September 2024

As deep learning technology has progressed, automated medical image analysis is becoming ever more crucial in clinical diagnosis. However, due to the diversity and complexity of blood cell images, traditional models still exhibit deficiencies in blood cell detection. To address blood cell detection, we developed the TW-YOLO approach, leveraging multi-scale feature fusion techniques. Firstly, traditional CNN (Convolutional Neural Network) convolution has poor recognition capabilities for certain blood cell features, so the RFAConv (Receptive Field Attention Convolution) module was incorporated into the backbone of the model to enhance its capacity to extract geometric characteristics from blood cells. At the same time, utilizing the feature pyramid architecture of YOLO (You Only Look Once), we enhanced the fusion of features at different scales by incorporating the CBAM (Convolutional Block Attention Module) in the detection head and the EMA (Efficient Multi-Scale Attention) module in the neck, thereby improving the recognition ability of blood cells. Additionally, to meet the specific needs of blood cell detection, we designed the PGI-Ghost (Programmable Gradient Information-Ghost) strategy to finely describe the gradient flow throughout the process of extracting features, further improving the model’s effectiveness. Experiments on blood cell detection datasets such as BloodCell-Detection-Dataset (BCD) reveal that TW-YOLO outperforms other models by 2%, demonstrating excellent performance in the task of blood cell detection. In addition to advancing blood cell image analysis research, this work offers strong technical support for future automated medical diagnostics.
Dual-Path Large Kernel Learning and Its Applications in Single-Image Super-Resolution
Authors: Su Zhen , Sun Mang , Jiang He , Ma Xiang , Zhang Rui , Lv Chen , Kou Qiqi , Cheng Deqiang
Published: September 2024

To enhance the performance of super-resolution models, neural networks frequently employ module stacking. However, this approach inevitably results in an excessive proliferation of parameter counts and information redundancy, ultimately constraining the deployment of these models on mobile devices. To surmount this limitation, this study introduces the application of Dual-path Large Kernel Learning (DLKL) to the task of image super-resolution. Within the DLKL framework, we harness a multiscale large kernel decomposition technique to efficiently establish long-range dependencies among pixels. This network not only maintains excellent performance but also significantly mitigates the parameter burden, achieving an optimal balance between network performance and efficiency. When compared with other prevalent algorithms, DLKL exhibits remarkable proficiency in generating images with sharper textures and structures that are more akin to natural ones. It is particularly noteworthy that on the challenging texture dataset Urban100, the network proposed in this study achieved a significant improvement in Peak Signal-to-Noise Ratio (PSNR) for the ×4 upscaling task, with an increase of 0.32 dB and 0.19 dB compared with the state-of-the-art HAFRN and MICU networks, respectively. This remarkable result not only validates the effectiveness of the present model in complex image super-resolution tasks but also highlights its superior performance and unique advantages in the field.
Sustainability in Site Remediation: Occupational Health and Safety Assessment of Techniques for Groundwater Remediation
Authors: Pietrangeli Biancamaria , Lauri Roberto , Incocciati Emma
Published: September 2024

The remediation of contaminated groundwater is a critical component of environmental management. In situ bioremediation (ISB) is a technique used to treat contaminated groundwater by promoting the activity of microorganisms, which transform harmful substances into less toxic or non-toxic forms. The present study investigates social issues regarding the sustainability approach applied to the remediation of contaminated sites by analyzing occupational health and safety (OH&S) impacts on workers involved in the remediation process. Occupational chemical risk is analyzed by comparing two techniques for the remediation of groundwater contaminated by chlorinated aliphatic hydrocarbons (CAHs): the pump-and-treat system and biological barriers. A contaminated Italian site, located near an industrial waste disposal site, was analyzed, applying a quantitative approach for chemical risk assessment. This approach is based on the use of a validated algorithm (SNPA software) and environmental measurement campaigns of chemical agents. This study (as far as the authors know) is the first research carried out in this field and shows that the adoption of bio-barriers for remediation is intrinsically safer in terms of OH&S impacts on workers.
Cannabigerol Reduces Acute and Chronic Hypernociception in Animals Exposed to Prenatal Hypoxia-Ischemia
Authors: Rezende Bismarck , Marques Kethely Lima , de Carvalho Filipe Eloi Alves , Gonçalves Vitória Macario de Simas , de Oliveira Barbara Conceição Costa Azeredo , Nascimento Gabriela Guedes , dos Santos Yure Bazilio , Antunes Fernanda , Barradas Penha Cristina , Fontes-Dantas Fabrícia Lima , Montes Guilherme Carneiro
Published: September 2024

Cannabigerol (CBG), a phytocannabinoid, has shown promise in pain management. Previous studies by our research group identified an increase in pain sensitivity as a consequence of prenatal hypoxia-ischemia (HI) in an animal model. This study aimed to investigate the efficacy of CBG in acute and chronic hyperalgesia induced by prenatal HI. A pharmacological screening was first conducted using hot plate and open-field tests to evaluate the antinociceptive and locomotor activities of animals administered with a 50 mg/kg oral dose of cannabis extract with a high CBG content. Prenatal HI was induced in pregnant rats, and the offspring were used to evaluate the acute antinociceptive effect of CBG in the formalin-induced peripheral pain model, while chronic antinociceptive effects were observed through spinal nerve ligation (SNL) surgery, a model used to induce neuropathic pain. Our results show that CBG exhibited an antinociceptive effect in the hot plate test without affecting the animals’ motor function in the open-field test. CBG significantly reduced formalin-induced reactivity in HI offspring during both the neurogenic and inflammatory phases. CBG treatment alleviated thermal and mechanical hypernociception induced by SNL. Biomolecular analysis revealed CBG’s ability to modulate expression, particularly reducing TNFα and Nav1.7 in HI male and female rats, respectively. These results highlight CBG as a potential antinociceptive agent in acute and chronic pain models, suggesting it as a promising therapeutic option without inducing motor impairment. Further research is needed to fully elucidate its mechanisms and clinical applications in pain management.
Prevalence of Eating Disorders among Competitive Rowers
Authors: Keczeli Viola , Kisbenedek Andrea Gubicskóné , Verzár Zsófia , Hulman Anita , Petrov Iván , Ihász Ferenc , Alföldi Zoltán
Published: September 2024

Internationally, few studies have been written on the prevalence of eating disorders among rowers, and there is no research on the subject in Hungary. This is particularly important in weight-related sports such as rowing. The aim of this study is to assess the prevalence of eating disorders among rowers. A quantitative cross-sectional study was conducted in the summer of 2023. In a non-random convenience sampling, our target population consisted of certified competitive rowers (n = 222). In addition to socio-demographic, performance-related questions, the anonymous, self-completed questionnaire used the validated The Eating Disorder Inventory (EDI). Results were considered significant when p < 0.05. A total of 57 lightweight (25.67%) and 165 openweight (74.33%) rowers participated in the study. On the perfectionism subscale and the interoceptive awareness subscale, rowers competing in the lightweight category scored significantly higher (p = 0.03; p = 0.05). Scores on the EDI subscales, gender and BMI data did not show significant relationships. Overall, rowers in the openweight group scored higher on the bulimia subscale, but no rowers who met all criteria and could be identified as having eating disorders. Rowers who have only competed in national championships and not in international competitions were more likely to reduce stress levels by eating. The study showed that the prevalence of eating disorders among rowers is no higher than in the general population. However, continued assessment, further extensive research and education of rowers is essential in this area, as weight-related sports will always be a risk group for eating disorders.
How Can Safety Contribute to Working Conditions in the Construction Industry? A Conceptual Framework
Authors: Alejo Ayodele , Aigbavboa Clinton , Aghimien Douglas
Published: September 2024

Studies have demonstrated the critical role that safety plays in preserving favourable working conditions in the construction industry, which is necessary to accomplish goals. The aim of this research was to inform stakeholders in the construction industry in developing nations about the value of safety and possible strategies for influencing their opinions regarding safety protocols. The importance of safety to the construction sector, which is crucial to the advancement of the country, has also been emphasised. However, due to a lack of adequate safety understanding among stakeholders in the construction sector, the construction industry is characterised by a great deal of instability and hazard. To determine what factors affect productive working conditions in construction production, this study examined safety. We studied what is obtainable in developed countries through a literature review and then making recommendations for developing countries. A systematic review approach was used to examine 81 research articles on construction safety that were released between 2004 and 2022. There were not many articles on construction safety before 2004. The person dimension, environmental factors, safety behaviour, organisation features, technology, and safety incentives were the six construction safety categories into which the results of this study were classified from the in-depth review of the health and safety literature. Additionally, these construction safety variables were developed into a conceptualised framework. To solve different construction safety issues related to working conditions in the construction sector, this study adds to the body of knowledge by systematically classifying and defining the often-utilised safety variables. It is now imperative to bring in these dimensions to improve the safe working conditions in the construction industry, particularly in developing countries. By putting these safety factors into practice, the construction industry can reduce safety risks, lower the number of accidents and fatalities, cut expenses related to subpar safety performance, safeguard the reputation of construction companies, boost employee morale and satisfaction with their work, enhance employee retention, reduce absenteeism, and enhance sustainability goals. Furthermore, it is certain that the conceptual framework that has been suggested would be novel and well-liked in developing countries. The conceptual framework was created with this supposition in mind.
Biochar Derived from Sewage Sludge: The Impact of Pyrolysis Temperature on Chemical Properties and Agronomic Potential
Authors: Kujawska Justyna , Wojtaś Edyta , Charmas Barbara
Published: September 2024

The rising volume of sewage sludge from urbanization poses substantial environmental and public health concerns, underscoring the urgency for the implementation of effective waste management strategies. The objective of this study was to evaluate the influence of pyrolysis temperature on the chemical composition and agronomic potential of biochar derived from sewage sludge. The pyrolysis process was conducted at temperatures ranging from 400 °C to 800 °C, and the resulting biochar was analyzed for pH, electrical conductivity, metal content, and carbon fractions. Additionally, phytotoxicity tests were conducted to assess the impact of the biochar on plant germination. The findings indicated that elevated pyrolysis temperatures resulted in an elevated alkalinity, electrical conductivity, and concentration of alkali metals in the biochar. Conversely, these processes resulted in a reduction in total organic carbon content and an increase in heavy metal content, which may limit the potential for biochar to be used in agricultural applications. The phytotoxicity tests indicated that the biochar produced at lower temperatures (400 °C) exhibited positive effects on plant growth when administered at doses of 5 and 10 t·ha−1. Conversely, the biochar produced at higher temperatures (800 °C) demonstrated significant toxicity. The findings indicate that the pyrolysis temperature is a critical factor in determining the suitability of biochar for agricultural applications. The production of biochar at lower temperatures may offer agronomic benefits, whereas the use of higher temperatures increases stability but is associated with the risk of higher heavy metal concentrations.
Does Renewable Energy Convey Information to Current Account Deficit?: Evidence from OECD Countries
Authors: Ozkan Canan , Okay Nesrin
Published: September 2024

Energy trade balance has been the main factor behind current account imbalances in many developed and developing countries. This study investigates whether or not renewable energy conveys information to the current account deficit of selected OECD countries. Utilizing a dataset spanning from 1990 to 2021, we apply a Panel Autoregressive Distributed Lag (ARDL) estimator to determine the interrelation of current account deficit (CAB) as a percentage of GDP with selected indicators, namely, net energy import in total final energy consumption (NEI), the share of renewable energy in total electricity production (REN_TEO), and fiscal deficit as a percentage of GDP (FAB). The results of long-term estimations reveal that as net energy import increases, the current account deficit deteriorates. On the other hand, in the case that countries utilize more of renewable energy in their total electricity generation, their current account deficits improve. Thus, we conclude that energy policy matters for the current account balances and subsequently for the well-being of OECD economies. Finally, we find strong evidence for the twin deficit hypothesis, as fiscal deficit is negatively interrelated with current account deficit both in the short-run and long run. In other words, an increase in the level of budget deficit is associated with an upsurge in the current account deficit problem. Furthermore, the Dumitrescu-Hurlin causality test reveals that there is bidirectional heterogeneous causality between current account deficit and budget deficit. Additionally, when the countries in the sample are grouped by their per capita GDP levels, estimations reveal that the direction of interaction between CAB and energy-related indicators (NEI and REN_TEO) does not differ between Group 2 (the ones whose per capita incomes are over USD 25,000 but below USD 50,000) and Group 3 (the ones having more than USD 50,000 per capita income) countries. However, the coefficients of energy-related indicators for Group 2 countries are higher than those of Group 3 ones, suggesting that energy policy matters more for Group 2 countries’ current account imbalances in the long-term.
The Innovative Construction of Provinces, Regional Artificial Intelligence Development, and the Resilience of Regional Innovation Ecosystems: Quasi-Natural Experiments Based on Spatial Difference-in-Differences Models and Double Machine Learning
Authors: Hu Ruiyu , Bao Zemenghong , Lin Zhisen , Lv Kun
Published: September 2024

Based on the theory of regional innovation niches, this study calculates the resilience of regional innovation ecosystems and constructs a comprehensive evaluation index system for regional artificial intelligence development, resulting in a panel dataset for 30 provinces in China from 2009 to 2021 (excluding Tibet, Hong Kong, Macao, and Taiwan). Within the framework of the construction of innovative provinces, regional artificial intelligence, and the resilience of regional innovation ecosystems, spatial double-difference and double machine learning models are employed for a quasi-natural experiment. The main research conclusions are as follows: (1) Both the construction of innovative provinces and artificial intelligence have a significant positive impact on the resilience of regional innovation ecosystems. (2) However, regional artificial intelligence exhibits a negative spatial spillover effect on the resilience of regional innovation ecosystems. (3) The construction of innovative provinces can positively moderate the effect of artificial intelligence on the resilience of regional innovation ecosystems. (4) Through the promotion of regional artificial intelligence, the construction of innovative provinces can indirectly enhance the diversity, evolutionary potential, buffering capacity, fluidity, and coordination of regional innovation ecosystems, thereby driving a leap in resilience. (5) The mechanisms by which the construction of innovative provinces stimulates regional intelligent input, application, innovation, and market dynamics to further enhance the resilience of regional innovation ecosystems are effective not only in the treatment group but also in the control group.
An Empirical Study on the Structural Assurance Mechanism for Trust Building in Autonomous Vehicles Based on the Trust-in-Automation Three-Factor Model
Authors: Yang Yanlu , Wang Yiyuan , Liu Jun , Lee Kidong
Published: September 2024

The development of the Autonomous vehicle industry contributes to achieving the environmental, economic, and social sustainability goals. Autonomous vehicles (AVs) involve highly autonomous and complex intelligent driving technology, and their large-scale commercial application depends on the level of public trust in their safety and reliability. Therefore, how to establish and enhance public trust in AVs has become the key to the development of the AV industry. This study discusses the impact of technical structural assurance, social structural assurance, and individual cognitive factors on trust in AVs. This study uses a structural equation model to analyze a valid sample of 548 participants from China. The results show that autonomy has a negative impact on trust, and currently, personal cognitive factors exert a greater influence on trust compared to technical and social structural assurance factors in China. In theory, this study combines the trust-in-automation three-factor model with the concept of structural assurance to reveal subjective controllable factors that can promote public trust. In practice, this study reveals the important role of structural assurance factors in enhancing trust before fully automatic driving technology is officially launched.
Technological Use from the Perspective of Cultural Heritage Environment: Augmented Reality Technology and Formation Mechanism of Heritage-Responsibility Behaviors of Tourists
Authors: Chen Songhong , Tian Yuanshu , Pei Siyun
Published: September 2024

This paper explores the integration of augmented reality (AR) technology within the realm of cultural heritage tourism, particularly its influence on the development of tourists’ heritage-responsibility behaviors. Addressing the recovery and development of Chinese domestic tourism in the post-pandemic period, smart tourism technology innovations have been explored. The research demonstrates that AR, by surpassing physical and temporal constraints, fosters a deeper synthesis of traditional and contemporary cultures, thereby enriching the comprehension of national history and cultural heritage. Employing the stimulus–organism–response (SOR) theory, a theoretical framework is established to elucidate the causal links from AR attributes to perceived usefulness, enjoyment, and behavioral intentions. The analysis reveals that the interactivity, vividness, and novelty of AR significantly augment perceived usefulness and enjoyment, although augmentation quality does not notably impact enjoyment. Both perceived usefulness and enjoyment significantly drive the intention to recommend. This study offers valuable theoretical insights and practical recommendations for the strategic deployment of AR in the sustainable development of cultural heritage tourism.
A Qualitative Study of the Experiences and Perceptions of Korean Undergraduates Regarding Two-Stage Examinations
Authors: Jang Hyewon , Rashid Junaid , Lee Joohee
Published: September 2024

Researchers have recognized collaborative problem-solving as a key competency for addressing sustainability challenges through creative and holistic approaches. Nevertheless, transforming traditional individual assessments into collaborative examinations to improve collaborative problem-solving is challenging. This study examines the experiences and perceptions of Korean undergraduates regarding two-stage examinations comprising individual and team components. Semi-structured interviews with nine students yielded results in eighteen subthemes categorized into four themes: process, positive aspects, negative aspects, and action items for support. Participants experienced a dynamic, collaborative problem-solving process through two-stage examinations; reported positive aspects, such as improved grades, learning opportunities, immediate feedback, and reduced test anxiety; and negative aspects, such as the burden of teamwork. As the first qualitative study of students’ perceptions of two-stage exams, this research explores transformative assessment practices that enhance collaborative problem-solving skills crucial for addressing global sustainability challenges. Furthermore, to promote collaborative assessments, this study discusses implications for educators planning to use two-stage examinations and offers suggestions for future research.
AI and Human-Centric Approach in Smart Cities Management: Case Studies from Silesian and Lesser Poland Voivodships
Authors: Skubis Ida , Wolniak Radosław , Grebski Wiesław Wes
Published: September 2024

The presented paper examines the integration of Artificial Intelligence (AI) in the management of smart cities, focusing on the Silesian and Lesser Poland Voivodships in Poland. This research addresses a notable gap in the analysis of regional AI strategies within urban management, providing a comparative analysis of AI implementation in these two distinct regions. The Silesian Voivodship, with its emphasis on traditional industries such as manufacturing and energy, contrasts with the broader approach of the Lesser Poland Voivodship, which includes applications in life sciences and ICT. The paper explores how AI technologies enhance urban efficiency, sustainability, and livability through practical applications in traffic management, healthcare, energy efficiency, and environmental management. It highlights the importance of a human-centric approach in smart city development, emphasizing inclusivity, transparency, and ethical considerations. The paper also delves into the socio-technical dynamics of AI deployment, illustrating how these technologies can transform urban environments while ensuring that the benefits are equitably distributed and that urban developments are sustainable and resilient. By analyzing specific case studies, the authors aim to provide empirical evidence and insights that contribute to the academic and practical understanding of AI’s role in smart cities, ultimately advocating for the design of AI applications that prioritize human well-being and environmental health.
Research Advancement in Forest Property Rights: A Thematic Review over Half a Decade Using Natural Language Processing
Authors: Beriozovas Olegas , Perkumienė Dalia , Škėma Mindaugas , Saoualih Abdellah , Safaa Larbi , Aleinikovas Marius
Published: September 2024

This paper proposes a thematic literature review of advances in the literature on forest property rights over the first half of this decade. From a methodological point of view, we exploited a corpus of scientific articles published between 2019 and 2023, extracted from the Scopus and Web of Science databases. We then performed a co-word analysis using the Louvain algorithm to reveal thematic clusters. This approach enabled us to identify seven distinct trends over the past half-decade, each highlighting specific aspects and geographical diversity of forest property rights, which were then evaluated using a thematic map. The main findings revealed that (policies, livelihoods and agroforestry) and (institutions, sustainability and non-timber forest products) stand out as central and influential themes, which have a significant impact and present notable advances that have shaped recent discussions and practices. Furthermore, themes (forest policy and resource management) and (conservation and the rights of indigenous communities) are well developed, which have a solid research base, offering an in-depth understanding of the relevant research questions. Conversely, themes (institutional change and forest conservation) and (deforestation, indigenous rights and community management) represent emerging themes, which are receiving increasing attention and are likely to become major of focus. In contrast, (forest governance, community management and land conflict resolution) which indicates a waning influence in terms of miscellaneous implications. The findings of this thematic literature review will help guide policymakers, researchers, and practitioners based on recent developments in international forest property rights, during a half-decade marked by a break with previous trends, leading to legislative changes and strategic adaptations essential for the sustainable management of forest resources, bolstered by technological advancements and environmental efforts.
Impact of Natural Gas Peak Shaving on High-Quality Economic Development
Authors: Xu Xiaomin , Li Chenhao
Published: September 2024

As energy demand continues to grow, the enhancement of natural gas storage and peaking capacity has become an important measure to ensure national energy security and to achieve the goals of carbon peaking and carbon neutrality. Gas storage and peaking have mature development models in the international arena, and China is making every effort to develop this system. This study reveals the impact and promotion of natural gas storage and peaking technology on high-quality economic growth in different regional economic environments through sample data from 30 provinces in China, from 2006 to 2022. The results show that natural gas storage and peaking directly promote high-quality economic development and have a positive spatial spillover effect on high-quality development in neighboring regions, a finding verified by the robustness test and endogeneity test. A heterogeneity analysis further revealed that there are significant differences among eastern, central, and western regions in terms of natural gas storage and peaking capacity and quality of economic development. The eastern region has a stronger gas storage and peaking capacity, while the central and western regions have a weaker capacity. Mechanism analysis shows that R and D technology (RDT) efficiency and green finance have a positive moderating effect on the benchmark effect. This has significant implications for policymakers and business leaders, suggesting that peak gas storage and peaking can drive improvements in broader regional corporate sustainability practices and increase regional levels of high-quality development.
A Multivariate Model and Correlation Study on the Impact of Typical Residential Spatial Forms in the Middle Reaches of the Hanjiang River on the Thermal Environment and Thermal Comfort
Authors: Liu Yue , Yang Liu , Qiao Yuhao , Cao Qimeng , Han Bing
Published: September 2024

Different spatial forms affect the indoor thermal environment and human thermal comfort. A good living environment largely depends on the flexibility of spatial forms, and spatial scale and proportion are the key factors affecting these forms. We selected typical residential houses in the middle reaches of the Hanjiang River in the hot summer and cold winter climate area as an example. Through on-site measurements and questionnaire surveys, we studied the impact of residential form indicators on the thermal environment and thermal comfort. We also established a multivariate model to explore the correlation among various parameters. The results showed that the spatial-real ratio of the residential spatial form index in the middle reaches of Hanjiang River was 5–58%. The height from the ground was 2.23–6.92 m. The open-space ratio was 0.04–4.55. The explanatory power of the spatial form index to indoor air temperature was 57.5%, with a strong correlation (R2 = 0.675). The explanatory power for humidity was 38.2%, with a weak correlation (R2 = 0.525). The explanatory power of SET was 30.6–50.1%, with a weak correlation (R2 = 0.466). The explanatory power of PMV was 6.5–31.7%, and PMV1.0 was weakly correlated (R2 = 0.474). The explanatory power for PPD was 15.5%, where PPD 1.0 was close to a weak correlation (R2 = 0.508). The results of this study provide reference values for the design methods of and decision-making process for green and energy-saving regional buildings.
Selecting the Most Sustainable Phosphorus Adsorbent for Lake Restoration: Effects on the Photosynthetic Activity of Chlorella sp.
Authors: Álvarez-Manzaneda Inmaculada , Castaño-Hidalgo Álvaro , de Vicente Inmaculada
Published: September 2024

To promote the conservation of aquatic ecosystems, it is essential to delve into restoration techniques for selecting the most sustainable option for combating eutrophication. Hence, we study the effects of novel phosphorus (P) adsorbents (magnetic carbonyl iron particles, HQ, and two non-magnetic P adsorbents: CFH-12® and Phoslock®) on the growth and photosynthetic activity of Chlorella sp. More specifically, the intrinsic photochemical efficiency of PSII (ΦPSII) and the nonphotochemical quenching (NPQ) were measured in Chlorella sp. after different contact times with different concentrations of these adsorbents. Our initial hypothesis was that non-magnetic P adsorbents have more effects on the organisms than magnetic ones. However, our results did not show strong evidence of inhibitory effects caused by HQ nor CFH-12® (no significant effect size on ΦPSII), while Phoslock® showed inhibitory effects on the photosynthetic activity of Chlorella sp. for any of its concentrations (NPQ = 0). Lastly, we compared the effect of the studied P adsorbents in a real application scenery (Honda wetland, Spain). For this study case, it is likely that CFH-12® and HQ doses would not cause any negative effects on photosynthetic efficiency while Phoslock®, by limiting light availability, will drastically reduce it.
Spatial–Temporal Development Trends and Influencing Factors of Government Environmental Information Disclosure: Empirical Evidence Based on China’s Provincial Panel Data
Authors: Xin Boda , Lv Lianhong , Dong Jingjing
Published: September 2024

Government environmental information disclosure (GEID) plays an important role in promoting the digital transformation of environmental governance, leading the concept of sustainable development, enhancing public oversight capacity, and promoting democratic decision-making governance. Using provincial panel data from China spanning from 2009 to 2021, we conducted spatial data exploratory analysis and used the dynamic spatial panel model to investigate the spatial–temporal development trends and influencing factors of GEID. The results show that (1) GEID in China exhibits significant spatial agglomeration characteristics, with an “H-H” (High-High aggregation type) agglomeration characteristic observed in three national strategic development regions: Yangtze River Delta, southeast coastal areas, and Beijing–Tianjin–Hebei region. (2) The spillover effect from the southeast coastal provinces gradually radiates to the northwest, resulting in an overall westward movement of GEID. (3) GEID exhibits a significant path-dependency feature in the temporal dimension and a “peer effect” in the spatial dimension. (4) Population size has the greatest impact on GEID. Population size, public participation, and the industrial and transportation sectors positively influence GEID improvement at the local level. However, they generate negative spillover effects to neighbouring provinces. Environmental status and the size of the Real Estate sector have no significant effect. Therefore, China should strengthen regional cooperation, narrow regional disparities, cultivate new quality productive forces, establish a government-led proactive disclosure mechanism under public supervision, and improve the level of GEID at the national level.