Journal Name: Fuel Cells Bulletin ISSN: 1464-2859 Journal E-mail: editor@fuelcellsbulletin.org Paper Publication Fee: 1500 USD At Fuel Cells Bulletin Journal, we are at the forefront of the transition to a sustainable energy future. Our mission is to deliver cutting-edge research, expert insights, and comprehensive analysis on the latest developments in the field of fuel cells. We are dedicated to serving the global community of scientists, engineers, policymakers, and industry professionals who are driving innovation and progress in this dynamic sector. Our Vision Our vision is to be the leading source of knowledge and discussion in the fuel cells arena, fostering advancements that will revolutionize how we generate and use energy. We are committed to promoting the adoption of fuel cell technology as a key component of a cleaner, more efficient, and sustainable energy landscape. What We Offer Fuel Cells Bulletin Journal is dedicated to advancing the field of fuel cell technology through high-quality, peer-reviewed content that encompasses a wide array of topics and disciplines. Our scope includes fundamental research, applied engineering, industry trends, and policy developments related to fuel cell systems and their applications. We aim to serve as a comprehensive resource for researchers, engineers, industry professionals, and policymakers involved in the fuel cell community. Research Areas Fundamental Science and Engineering: Electrochemical fundamentals of fuel cells Advances in fuel cell materials, including catalysts, membranes, and electrodes Thermodynamics and kinetics of fuel cell reactions Innovations in fuel cell design and performance optimization Technology Development and Innovation: Emerging fuel cell technologies (e.g., solid oxide, proton exchange membrane, direct methanol) Novel manufacturing techniques and materials processing Improvements in fuel cell durability, efficiency, and scalability Integration of fuel cells with renewable energy sources and hybrid systems Application and Deployment: Case studies of fuel cell applications in transportation, stationary power, and portable energy solutions System design and integration for specific applications Performance analysis and benchmarking of fuel cell systems in real-world conditions Advancements in hydrogen production, storage, and distribution Industry Trends and Market Dynamics: Market analysis and forecasts for fuel cell technologies Policy and regulatory impacts on fuel cell adoption and development Strategic insights into industry developments, including key players and innovations Economic and environmental assessments of fuel cell systems Societal Impact and Policy: Contributions of fuel cell technology to energy sustainability and climate goals Policy frameworks and incentives supporting fuel cell research and deployment Public perception and acceptance of fuel cell technologies International collaborations and global initiatives in fuel cell research Submission Guidelines We welcome a diverse range of submissions including original research articles, review papers, technical notes, case studies, and opinion pieces. All submissions are subject to rigorous peer review to ensure the highest standards of scientific and technical quality. Audience Our journal targets a broad audience, including: Academics and researchers in fuel cell science and engineering Industry professionals and engineers working with fuel cell technologies Policymakers and regulatory bodies involved in energy and environmental policy Investors and stakeholders interested in the fuel cell market Editorial Policy Fuel Cells Bulletin Journal is committed to publishing content that is original, high-quality, and relevant to the field of fuel cell technology. We uphold principles of academic integrity and strive for impartiality and fairness in the review process.
The Suppression of Thrust Ripple and Electromagnetic Vibration in A Double-sided Flux Switching Permanent Magnet Linear Motor by Optimizing the Stator Structure
The Double-Sided Flux Switching Permanent Magnet Linear Motor (DLFSPM) is being increasingly and extensively employed in various fields due to its merits of high efficiency and high power density. Nevertheless, the DLFSPM suffer from significant thrust ripple, which exacerbates electromagnetic vibration. To effectively reduce thrust ripple and electromagnetic vibration, this paper aims to significantly enhance its performance by optimizing the stator structure. Firstly, establish the finite element analysis model of the DLFSPM, and based on theoretical methods, derive the electromagnetic thrust equation and the equation of electromagnetic vibration, clarifying the key indicators. Secondly, effective suppression of thrust ripple is achieved by optimizing the radius of the arc fillet in the stator slot. Subsequently, auxiliary slots are introduced on the stator tooth surface, and their optimal dimensions are determined using the finite element model and response surface methodology, with the objective functions of enhancing electromagnetic thrust and reducing thrust ripple. Finally, a comparative analysis is conducted between the comprehensively optimized DLFSPM and the initial structure motor regarding electromagnetic thrust, thrust ripple, and electromagnetic vibration. The simulation results demonstrate that the optimized DLFSPM not only significantly improves electromagnetic thrust but also effectively suppresses thrust ripple and electromagnetic vibration, thereby validating the effectiveness of the optimization method.
Wei Du, Haonan Cui, Cheng Wen, Zengqiang Ma
Nighttime Light Data and Spatial Modeling for Land-Use Carbon Emissions: Insights from Northeast China
Carbon emissions are a critical global issue requiring detailed spatial analyses to support regional carbon peak and neutrality strategies. This study investigates the spatiotemporal evolution and spatial differentiation of county-level land-use carbon emissions (CELU) in the Changchun-Jilin-Tumen (CJT) region from 2012 to 2021 by integrating land use data, nighttime light imagery, and socio-economic statistics with the Optimal Parameter Geodetector (OPGD) model. The analysis identifies key drivers of spatial emission variability, including construction land proportion (q-value: 0.8882), land area per capita (q-value: 0.7609), and urbanization rate (q-value: 0.5875), underscoring the significant role of land-use patterns and urbanization. Results show a 21.2% increase in CELU, from 67,594.46×104 t in 2012 to 81,942.35×104 t in 2021, with emissions concentrated in industrially active and urbanized western and southern counties, while forest-rich central and eastern counties exhibit lower emissions. Using the Grey Model (GM (1,1)), the study forecasts that CELU will rise from 78,484.364×104 t in 2022 to 88,985.198×104 t by 2030, reflecting a 14% increase over the forecast period. This trajectory highlights the misalignment between current trends and the region's goals of creating a "low-carbon industrial zone" and "livable cities," emphasizing the need for transitioning to renewable energy, optimizing industrial structures, and implementing sustainable land-use practices such as brownfield redevelopment and ecological land protection. By combining advanced remote sensing with nonlinear spatial analysis, this study offers a replicable high-resolution framework for understanding carbon emission drivers and spatial patterns, providing actionable insights for refining carbon reduction strategies and achieving sustainable development goals at both national and global scales.
Jie Wang, Qiuyun Liu, Lulu Zhang, Mingyu Li
Intrinsically High Refractive Index Silicone Polymers Containing S and P Heteroatoms
There is growing interested in high refractive index polymers due to their numerous applications in optical materials. In current work, we reported a facile strategy to improve the refractive index of the optical materials. The new asymmetric binary thiol dopants containing high molar refractive index heteroatoms (S and P) and large conjugated groups were successfully designed and synthesized. Using these additives, the high refractive index silicone polymers were developed from these dopants and vinyl silicones simply via the light-cured reaction. The effects of dopants’ structure and content on the thermal and optical properties of cured silicone polymers were systematically investigated. The results show that the asymmetry structure of the dopants can not only effectively offset the accumulated trend of the large conjugated groups but also improve the refractive index of cured silicone polymers. Even with 5% dopant’s loading, the refractive index of the SOV-5 increased from 1.5773 to 1.5803 without notably sacrificing its the light transmittance. The glass transition temperature of the cured silicone polymers decreases, even though their crosslink density increase with the growing of the dopants’ loading.
Meiqi Yang, Qinxue Han, Yulin Ding, Junfeng Li, Wenmu Li
Exploration on the Role, Function and Cultural Mission of Art Think Tanks in the "Digital Communication of Intangible Cultural Heritage"
As an important part of the new type of think tank with Chinese characteristics, art think tanks play an important role in enhancing the accuracy of the inheritance of intangible cultural heritage and art, and improving the foresight of the development of intangible cultural heritage and art. As one of the main dissemination paths of intangible cultural heritage today, the accuracy and efficiency of "digital communication" cannot be separated from the active participation of art think tanks. [Method/Process] Starting from the positive role of art think tanks in "digital communication of intangible cultural heritage", this paper explores the necessity of art think tanks participating in the new type of intangible cultural heritage dissemination path through literature research, comparative analysis, induction and summary, as well as the positioning, function and cultural mission of art think tanks in it. [Result/ Conclusion] The positive impact of art think tanks on the dissemination of intangible cultural heritage and other important cultural dissemination in China is mostly in macro-guidance, and they rarely play an important role in the "new dissemination method" of a certain culture. "Digital dissemination" has gradually become the mainstream method of cultural and artistic dissemination with its advantages of "fast speed", "wide range", "large content" and "high public participation". The study believes that exploring the role of art think tanks in the process of "digital dissemination of intangible cultural heritage" will help solve the problems of "uneven quality of dissemination content" and "low participation intention of young groups", and thus disseminate intangible cultural heritage and enhance China's cultural soft power in a more accurate and efficient way.
Spatiotemporal Distribution Characteristics of Ancient Settlement Sites in Shandong Province Since the Neolithic Period
Using ArcGIS10.2, a spatial database was constructed for 8.5-2.2 ka historical and cultural sites in Shandong Province. Using a combination of statistical and superposition analysis, the spatial and temporal distribution of ancient settlement sites in Shandong Province since the Neolithic period was studied, and the factors influencing their spatial and temporal distribution were investigated. The study found that as human civilisation has evolved since the Neolithic, the number of ancient settlement culture sites in Shandong province has also been changing, going through four periods: rising, surging, declining and rising. In the HouLi culture period, the settlement sites were mostly concentrated in the plain area in front of the mountains in Luzhong; in the Beixin culture period, Luzhong was the main settlement area of the settlement; in the Dawenkou culture period, there were settlement sites in Luzhong and southeast Luzhong; in the Longshan culture period, there were settlement sites in Luzhong and northwest Luzhong; in the Yueshi culture period, the distribution scale of the settlement sites was obviously reduced and scattered in the plain in front of the mountains. During the Shang culture period, the distribution of settlement sites increased, mostly in the central, southern and northwestern Lu areas; during the Zhou culture period, the distribution of settlement sites increased sharply, mostly in the central, southern and northwestern Lu and Jiaozhou peninsula areas. 8.5-7.5 ka B.P., in general, the natural climate during this time period was warm and humid, with good natural resources, and the Houli from 7.0 to 4.0 ka B.P., climatic conditions remained generally mild, with minor fluctuations but a steady general trend, and the Beixin, Dawenkou and Longshan cultures developed sequentially under stable, excellent climatic conditions during this time period. The Longshan culture gradually declined, and after a more stable period the Yueshi culture emerged. Changes in the overall climatic environment had a great impact on social, cultural and economic development, and the formation and development of Early Neolithic culture is strongly linked to climate, but the influence of many factors, including social productivity, led to spatial changes.
Spatial and Temporal Evolution of Rural Settlement Landscape and Influencing Factors in the Border Areas of China, North Korea and Russia-Taking Hunchun City as an Example
Rural settlements are the basic spatial units of compact communities in rural areas, and scientific exploration of their spatio-temporal evolution and their influencing factors is an important prerequisite for the rationalization of spatial layout, and such an analysis can guarantee the rational planning and sustainable development of rural settlements in China and promote rural revitalization. Taking Hunchun City in Jilin Province as the research object, the spatial and temporal evolution characteristics of rural settlements in the region were analyzed by landscape index and spatial structure during the period of 1990-2020 by using ArcGIS spatial analysis tools. The results show that: (1) during the period of 1990-2020, the land scale of rural settlements in Hunchun City is characterized by expansion and then a small decrease, and the spatial distribution is in the state of agglomeration, and the density change is not significant. (2) The spatial and temporal evolution of rural settlement landscape is influenced by various factors such as nature, society and human beings. (3) Based on the ecological security protection pattern of the study area, the landscape pattern optimization of rural settlements was carried out, which was divided into four types of settlement landscape optimization.
An Aeromagnetic Compensation Algorithm based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and a Physics-Guided Neural Network
Aeromagnetic exploration is a magnetic field exploration method that detects changes in the spatial magnetic field by carrying a magnetometer on an aircraft. However, during the measurement process, the magnetic field data is often interfered by the aircraft’s own ferromagnetic materials and maneuvers. The role of aeromagnetic compensation is to eliminate this part of the interference, which is crucial to improving the quality of aeromagnetic exploration data. In this study, we introduce a novel method for aeromagnetic compensation, which is employed to eliminate the interference from aircraft platforms. The proposed method utilizes complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the magnetic field data into multiple feature components. These decomposed features are subsequently input into a physics- guided neural network (PGNN), which was designed to remove magnetic interference from the data. The core idea behind this method is that CEEMDAN effectively decomposes magnetic field data into features that are more easily learned by the neural network. The method leverages both data-driven and model-driven advantages by embedding the Tolles–Lawson (T-L) model into the neural network, thereby compensating for both linear and nonlinear interference. The results of simulation and real experiments show that the proposed method outperforms traditional model-driven and data-driven techniques, especially when the quantity and quality of data are limited.
The Impact of Environmental Pollution Liability Insurance on Firms’ Green Total Factor Productivity: Evidence from China
Improving green total factor productivity (GTFP) is crucial for firms to enhance competitiveness and sustainable development capacity. Environmental pollution liability insurance (EPLI) facilitates firms better manage environmental risks and encourages firms to enhance GTFP. This study examines the impact of EPLI coverage on GTFP using data from Chinese heavy-polluting firms. Results show that EPLI enhances GTFP, with the effect persisting over time. Further mechanisms study suggests that EPLI enhances GTFP through external stakeholders’ pressure and internal incentive mechanisms. Finally, the magnitude of EPLI’s impact depends on the quality of firms’ human capital.
An Analytical Study of The Impact of Visual Arts on the Design of The Theatrical Scene (Scenography)
This research aims to analyze the impact of visual arts on stage design, recognizing visual arts as a fundamental element that enhances the aesthetic and expressive aspects of theatrical performances. Through this study, the focus was on how the use of colors, lighting, and graphic designs can create the desired effect on the audience and convey the performance's message more effectively. Visual arts play a crucial role in transforming theatrical scripts into integrated visual experiences that interact with other elements of the performance, such as acting and scenography. Additionally, the research explored the impact of modern technologies in visual design, which have led to significant advancements in the field, offering theater designers broader opportunities for experimentation and innovation. The study also analyzed several notable theatrical works that used visual arts in exceptional ways, helping to clarify the profound importance of these elements in enhancing the artistic and social message of the play. The study concluded that visual arts are not merely decorative tools but are an integral part of the theatrical production. They have the power to alter the understanding and interaction with the script itself.
Optimization of Induction Electricity in Buildings by Ultra High Voltage Transmission Lines
With the rapid development of China's economy, the demand for electricity, as the lifeline of the economy, is naturally increasing year by year. At the same time, China's market-oriented reform of electricity has shown initial results, a diversified competitive pattern is forming, and the commodity attributes of electricity have been further improved. The role of allocating electricity resources is also gradually strengthening, and there is a clear growth trend in market-oriented trading of electricity. There is an imbalance in the distribution and load centers of energy in China, and the corresponding resource points and load centers are also relatively far away. Due to the shortage of transmission corridors in China, a considerable portion of ultra-high voltage lines are distributed in residential areas. At this time, the impact of buildings close to residential areas on high-voltage transmission lines, as well as more in-depth guidance for transmission line installation and distribution in residential areas, will play a certain guiding role. Therefore, it is particularly important to study the influence of electric field distribution under different conditions on transmission lines. This article reasonably simplifies the three-dimensional model of transmission lines and introduces a line charge unit model to simulate the three-dimensional electric field near ultra-high voltage transmission lines. At the same time, simulation research is conducted on the three-dimensional electric field in different situations, namely in buildings of different materials.
Leveraging Machine Learning to Analyze and Predict Cultural Trends in Global Tourism
Cultural trends, economic factors, and digital transformations shape fast-evolving global tourism. Machine learning is used in this study to analyze and predict cultural shifts in tourism on the basis of the fusion model by combining the architectures of EfficientNet and DiCENet. The model also integrates diverse data sources, which include online travel reviews, social media content, and macroeconomic indicators, to create a detailed framework to explain new travel behavior. The results indicate a strong recovery in positive traveler sentiment post-pandemic, alongside significant growth in sustainable travel, digital nomadism, and wellness tourism. The major influence on tourism demand was the level of economic stability, specifically GDP per capita and unemployment rates. In comparison, machine learning baseline models showed an accuracy rate of 92.5% in detecting and predicting trends under the EfficientNet-DiCENet fusion model. These results provide a basis for stakeholders in the industry, including policymakers and businesses, to make decisions that take advantage of evolving passenger air travel preferences in order to align the strategies. Even though the study showcases the impact of machine learning in tourism analytics, a number of shortcomings, such as data bias and the unpredictability of external disturbances, have been identified as research areas for the future. In general, this work contributes to the use of AI-driven models for data-driven tourism forecasting and cultural trend analysis.
Modern Approaches to Diagnosis and Treatment of Atherosclerosis: From Pathogenesis to Clinical Solutions
Atherosclerosis remains a leading cause of cardiovascular morbidity and mortality worldwide, characterized by the progressive accumulation of lipids and inflammatory cells within the arterial walls. Recent advancements in molecular biology, nanotechnology, and RNA-based therapeutics have provided new insights into the pathophysiological mechanisms of atherosclerosis and novel strategies for diagnosis and treatment. This review explores modern diagnostic modalities, including advanced imaging techniques, circulating biomarkers, and genomic profiling, which offer improved early detection and risk assessment. Additionally, emerging therapeutic strategies, such as PCSK9 inhibitors, anti-inflammatory agents, RNA-based therapies, nanomedicine, and CRISPR gene editing, hold promise for more targeted and effective treatment. Furthermore, the role of lifestyle interventions, including diet, physical activity, and gut microbiota modulation, is discussed in the context of atherosclerosis prevention. While these innovations present significant opportunities, challenges remain in translating experimental findings into clinical practice, necessitating further research and interdisciplinary collaboration. Future developments in precision medicine and artificial intelligence may further enhance the management of atherosclerosis, offering patient-specific preventive and therapeutic strategies.
Molecular Pathways of Glaucoma Progression: Current Perspectives
Glaucoma is a progressive optic neuropathy characterized by retinal ganglion cell (RGC) degeneration and irreversible vision loss. Despite extensive research, the molecular mechanisms underlying glaucoma pathogenesis remain incompletely understood. Recent studies highlight the crucial role of non-coding RNAs (ncRNAs) in modulating key pathways associated with trabecular meshwork (TM) dysfunction, retinal neurodegeneration, and fibrotic remodeling. This review provides a comprehensive analysis of the involvement of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in glaucoma progression. We discuss their regulatory influence on pathways such as the TGF-β, PI3K/AKT, MAPK, and Wnt/β-catenin signaling cascades, which are implicated in oxidative stress, extracellular matrix (ECM) remodeling, apoptosis, and fibrosis. Notably, ncRNAs such as miR-29b, miR-200a, and MALAT1 exhibit differential expression patterns in glaucomatous tissues and modulate critical cellular processes that impact intraocular pressure (IOP) regulation and RGC survival. Furthermore, we explore the potential of ncRNAs as diagnostic biomarkers and therapeutic targets for glaucoma. While ncRNA-based therapies hold promise, challenges such as delivery efficiency, immune responses, and target specificity must be addressed before clinical translation. Future research should focus on elucidating the precise molecular interactions of ncRNAs, optimizing drug delivery systems, and conducting large-scale clinical studies to validate their therapeutic potential. Understanding the intricate network of ncRNA-mediated regulation in glaucoma could pave the way for novel, targeted treatment strategies, ultimately improving patient outcomes and preserving vision.
Numerical Simulation on Flue Gas Desulfurization by Activated Carbon Absorption in Circulation Fluidized Bed
Using standard k-e model, Euler model, mass transport and finite rate chemical reaction model to simulate the flow and chemical reaction in the CFD reactor. Theoretical knowledge was applied to analyze the simulation results, verified the feasibility of the numerical simulation. Researched the reaction temperature, O2 content in the flue gas and the molar ratio of carbon -sulfur of affection on the desulfurization, obtained preferably operating parameters, expects to provide valuable reference for industrial production of later.
Harnessing AI, Deep Learning, and Machine Learning for Sustainable Tourism Development: Innovations in Management and Economics
This study focuses on the changes brought out by Artificial Intelligence (AI), Deep Learning (DL), and Machine Learning (ML) in the management of tourism within the two dimensions of economic and environmental sustainability. The research identifies from a meta-analysis of peer-reviewed studies and industry reports how AI-driven computational models optimize demand forecasting, anomaly detection, and resource allocation. Our findings show that AI adoption in tourism businesses has grown considerably, resulting in increased operational efficiency, cost savings, and revenue generation. The EfficientNet-DiCENet fusion model for anomaly detection in IoT-based tourism networks is introduced in the study with an accuracy of 96.7% and outperforms conventional AI models. Economic analysis shows 20-25% savings in operational costs with a revenue increase of up to 23%. Moreover, AI applications promote environmental sustainability through energy optimization, waste management, and reduced carbon footprint. Although advances have been made in this area, the study notes such limitations as real-world validation and recommends future research on hybrid AI models made up of blockchain and reinforcement learning. However, in conclusion, AI holds promise to lead sustainable tourism into the next phase, delivering data for informed decision-making, the economic resilience needed to withstand the impacts of climate change, and its ecological balance.
Exploring Opportunities and Challenges of Artificial Intelligence in College Students for Personalized Training
Artificial intelligence (AI) has empowered personalized training for each higher-education student. This study's meta-analysis and computational evaluation of AI frameworks understand the impact of AI-driven learning models on Student Engagement, Aggregation Rate, and Learning Efficiency. Findings show that AI-based learning can significantly contribute to better educational outcomes than conventional methods. The engagement rates were upped to 77%, and hybrid models share the highest rates at 85.3% versus traditional learning models at 69%. Regardless, 85.6% of the knowledge was retained immediately, and 74.2% was still retained after four weeks of training, with conventional training delivering only 72.1% and 54.3% of retention, respectively. Additionally, improving learning efficiency by 28.9 reduced the course completion time from 14.5 to 10.3 hours.
Impact of Promoting Fuel Cell Vehicles on Urban Air Quality and Health Benefits
Fuel cell vehicles (FCVs) are considered a promising clean energy transportation option with significant potential to alleviate urban air pollution. However, their environmental benefits are not fixed but are influenced by various factors, including vehicle usage patterns and road conditions, which in turn affect air quality and public health. This study takes Xi’an as a case study and employs the COPERT model to develop a 2020 emission inventory for FCVs. Future vehicle ownership in 2035 is projected under low, medium, and high electrification scenarios using multiple models. The WRF-SMOKE-CMAQ modeling system is utilized to simulate air quality changes, while the BenMap-CE model is applied to assess health benefits. The results indicate that under the high electrification scenario, pollutant emissions are reduced by 64.59%–88.86% compared to 2020 levels, with pollutant concentrations exhibiting a gradient distribution along the road network. In winter, CO, NO₂, and PM₂.₅ concentrations are significantly higher than in summer. Improved air quality leads to substantial health benefits related to PM₂.₅, with the high electrification scenario preventing an estimated 770 premature deaths and generating up to 400 million CNY in economic benefits. These findings demonstrate that the widespread adoption of FCVs can effectively reduce urban traffic-related pollution burdens and yield significant environmental and health co-benefits, providing a scientific basis for clean transportation policymaking.
Land Use Changes on Both Sides of the Tumen River Basin (China and North Korea) over the Past 20 Years
This study selects the Tumen River Basin as the research area. By downloading Global30 land use data for 2000, 2010, and 2020, we utilized ArcGIS for mask extraction, raster reclassification, and data integration to standardize land categories and facilitate comparative analysis. Subsequently, we systematically analyzed the area, change magnitude, and dynamic degree of land use on both sides of the Tumen River Basin over the past two decades. Through spatial operations such as overlay analysis in ArcGIS, we further employed land use transfer matrices and transition probability matrices to examine the characteristics of land use type conversions. Key findings include: 1.Forest reduction: Forest areas on both sides of the basin decreased, primarily due to insufficient environmental awareness and overexploitation of resources in the early 2000s. 2.Water body expansion: China’s water conservancy projects increased total water area by approximately 66.39 km², while North Korea’s water bodies remained stable. 3.Policy-driven shifts: Land use changes were closely linked to national policies and human activities, with recent improvements attributed to sustainable development initiatives
Electric Field Optimization Analysis for Live Opera-Tion of UHV Transmission Line
At present, China's economy is in a period of rapid development, and the pace of urbanization construction is constantly accelerating, followed by the soaring demand for electricity. Especially in densely populated areas where construction land is scarce, it is difficult to balance transmission capacity with the increasing demand for electricity. The problem of insufficient conveying capacity is solved well by the double-return conveying scheme of the same tower and frame. In the process of transmission line operation, it needs to be repaired and maintained, and a considerable part of the work needs to be live. Therefore, this paper studies the surface electric field changes of UHV live line workers, in order to reduce the operating risk of operators, and then make theoretical and practical contributions to ensure the safe and effective implementation of live line work and improve the operation quality and standardization degree. In this paper, SolidWorks modeling software is used to model a 500KV transmission line, and a human body model is placed in the model. The finite element simulation software COMSOL is used to calculate the surface electric field when the personnel are located at the typical position of the line, and its influencing factors are analyzed.
Effects of Land Use Change on Habitat Quality in the Tumen River Basin
Habitat quality is one of the important factors to measure ecosystem services, and its quality is directly related to regional ecosystem service capacity. The Tumen River Basin is located in the border area of China, Korea and Russia. The temporal and spatial evolution of habitat quality in Tumen River Basin is of great significance to the ecological security and sustainable development of Northeast Asia. Based on InVEST model and spatial autocorrelation, this study analyzed the temporal and spatial changes of habitat quality and the interaction of elevation in Tumen River Basin (Chinese side). The results showed that: 1) Land transfer mainly occurred from cultivated land to construction land and grassland, and from forest land to cultivated land from 2000 to 2018. 2) In the past 20 years, habitat quality in the study area fluctuated, showing an upward trend and then a downward trend, but the overall fluctuation was not significant, with an average value of 0.87. 3) The elevation effect of habitat quality and degradation degree was obvious on elevation. The distribution of low-grade habitat quality was consistent with that of cultivated land and construction land, while that of high-grade habitat quality was consistent with that of forest land. Overall, the habitat quality index increased with elevation. The results can provide some reference for biodiversity conservation and ecological sustainable development in Northeast Asia.
Analysis, Assessment, and Remediation of Highway Rockfall
Preventing geological disasters such as highway rock collapses is crucial for ensuring traffic safety and social stability. Traditional research often relies on on-site investigations to identify collapses, which can delay the remediation process. In this study, we focused on a highway rock collapse case in Shuangfeng Town, Longchang City. Using a combination of remote sensing imagery analysis, on-site verification, and surveying, we comprehensively obtained the geological characteristics and surrounding environmental information of the dangerous rock mass. Through detailed analysis of the lithology, structure, weathering degree, and other features of the dangerous rock mass, and considering geological structures, climatic conditions, human activities, and other internal and external factors, we explored the formation mechanism of the rock collapse in depth. Subsequently, we assessed the potential threat level of the dangerous rock mass to provide a scientific basis for the design of the remediation plan. The results indicate that the dangerous rock mass in this area is primarily composed of gray thick-bedded to blocky fine-grained sandstone from the Middle Jurassic Shaximiao Formation, with two sets of steeply dipping "X" joints. Stability analysis reveals that under natural conditions, the dangerous rock mass is relatively stable, but its stability significantly decreases under heavy rainfall conditions, becoming unstable. Based on these findings, we proposed a "manual rock clearance" plan. Testing confirmed that this plan.achieved the intended goals and ensured the safety of the area.
Xiaojing Hu, Jiaoli Fang, Daming Zhu, Sixuan He
The Role of Environmental Pollutants in Exacerbating Pediatric Asthma: A Health Security, Epidemiological, and Health Information Perspective
This study explores the growing prevalence of pediatric asthma in Saudi Arabia, focusing specifically on Jeddah city, and examines the significant role of environmental pollutants in exacerbating the condition. Asthma, a chronic inflammatory respiratory disease, affects millions of children worldwide and is influenced by genetic and environmental factors. This study surveyed 400 children diagnosed with asthma and their caregivers in Jeddah, highlighting household allergens like dust mites and environmental pollutants such as vehicle emissions, industrial fumes, and airborne dust particles, as key contributors to the exacerbation of asthma symptoms. Findings indicate that children living in areas with high pollution levels, including heavy traffic zones and industrial vicinities, exhibit increased asthma prevalence and severity. Additionally, the study highlights the influence of sociodemographic factors, such as parental education and household hygiene, on asthma incidence. Public health implications emphasize the need for targeted interventions to reduce exposure to harmful pollutants and allergens, as well as increased awareness among caregivers and the broader community. The research advocates for stronger environmental regulations, improved healthcare systems, and community awareness programs to mitigate the impact of asthma on Saudi children, particularly in urban areas with significant industrial and traffic-related pollution.
Optimisation Study of Green Evaluation System of Port Logistics Considering Economic Development
To establish an evaluation system for the green development of ports, we integrated insights from multiple expert groups using a comprehensive evaluation method. The indicators were screened using the Spearman correlation coefficient and principal component analysis. Subsequently, an ANP model was adopted, and Super Decisions software was utilized to determine the weights of each indicator and construct the model. This model comprehensively evaluates both the economic and green development aspects of ports, providing accurate assessments of their green development status. This model comprehensively evaluates both the economic and green development aspects of ports, providing accurate assessments of their green development status. Additionally, the ideal solution method (TOPSIS) was employed to conduct empirical analysis on ten selected ports. The results indicate that Shanghai Port has largely achieved balanced economic and green development, while other ports exhibit issues in specific areas, aligning The results indicate that Shanghai Port has largely achieved balanced economic and green development, while other ports exhibit issues in specific areas, aligning with real-world observations. These findings validate the effectiveness of the evaluation model and offer recommendations for enhancing port green development. These findings validate the effectiveness of the evaluation model and offer recommendations for enhancing port green development.
A Fast Numerical Method for Magnetic Field Analysis of Coaxial Magnetic Gears with Bridge-Connected Modulators Considering Magnetic Saturation
This paper presents a novel approach for calculating the magnetic field distribution of magnetic gears(CMGs) with bridge connection in modulator. The modulator and bridge connection regions were divided into several unit modules to derive a convolution matrix of permeability. The magnetic field distribution was then calculated using spatial harmonic modeling method(SHMM). To accurately account for the influence of nonlinear permeability and saturation on the magnetic field distribution, the permeability curve of the material was incorporated, and the permeability distribution function was modified using an iterative method. To verify the method, the magnetic field distribution of two sets of magnetic gears with different bridge parameters was calculated. The proposed method for accurately calculating the magnetic field distribution of CMGs with bridge connections is validated by comparing it with the results obtained from finite element analysis(FEA).
Firm Entry and the Growth of The Science Parks based on Energy Innovation: Evidence from Beijing Zhongguancun Science Park in China
Understanding the micro-level dynamic mechanism of economic growth of the science park is of great significance to the theory of regional economics and the policies to promote innovation. Based on the novel firm-level data from 2005 to 2015 on Beijing Zhongguancun Science Park (Z Park for short) in China, this paper investigates the dynamic impacts of firm entry on Z Park’s growth, measured by productivity and size, respectively, and an extended analysis is conducted from the perspective of energy utilization and innovation. By employing the DOP and EEKT decomposition methods, we first find that new entrants have a lower TFP and output than incumbent firms. However, in the following years, the relative growth rates of them are faster and gradually converge to or even exceed the latter in both the TFP and output level. Second, the new enterprises do not significantly promote the annual TFP growth of Z Park in the year of entry but finally enhance the TFP growth on average during these ten years. Third, different from the impact on the growth of TFP in Z Park, new entrants contribute substantially to the annual output growth of Z Park in the year of entry, and this effect has further increased on average. The analysis combined with energy utilization shows that with the entry and growth of new enterprises, they are gradually showing potential in improving energy efficiency and innovating energy technology. These findings provide valuable insights into the dynamics of economic growth in science parks and suggest potential strategies for promoting innovation for policymakers.
Jianguo Wang, Hongchun Yu, Jingjing Wang
The Impact of Green Credit on Carbon Emission Reduction in China — A Case Study of Six Major Energy-Intensive Industries
The development of a high-quality economic system in China critically hinges on green finance, particularly green credit as an integral part of the carbon finance framework. This study analyzes panel data from 30 provinces and municipalities across China between 2008 and 2019, employing a dynamic panel model to explore the impact of green credit on carbon emission reduction in six major energy-intensive industries. Results reveal that green credit significantly curtails carbon emissions within these sectors. Notably, the effectiveness varies regionally, with eastern regions demonstrating superior performance compared to their central and western counterparts. This research underscores the necessity for expanding green credit scale, enhancing support mechanisms, and fostering deeper integration and liberalization of green finance nationwide. Special attention should be directed towards advancing green credit initiatives in central and western regions to achieve balanced development. This study innovatively quantifies regional disparities in green credit efficacy, providing actionable insights for policymakers.
The Application of Energy Consumption Prediction Model for Fresh Air System based on PSO-BP and BO-BP
With the fast progress of deep learning and neural network technology, neural networks are now being used in lots of different subjects. They have been especially popular in predicting energy use in fresh air systems, because of their ability to fit nonlinear data. However, the performance of neural networks largely depends on the selection of their hyperparameters, and how to effectively optimize these hyperparameters has become a key issue to improve the prediction accuracy of the model. This paper discusses the methods of optimizing the hyperparameters of neural networks and compares several optimization methods, and finally finds that the Bayesian optimization algorithm performs optimally in neural network optimization. In the experiment, firstly, the relevant data of the new wind system were collected and data preprocessing was carried out, including missing value interpolation and outlier detection. The key factors affecting the energy consumption of the fresh air system were then used to train a prediction model. Then, PSO and BO were used to improve the neural network's hyperparameters. A Monte Carlo simulation showed the Bayesian algorithm identifies the global optimum more quickly, improving prediction accuracy. Experimental findings show that factors like indoor-outdoor temperature, humidity and air quality influence the energy consumption of fresh air systems.The BP neural network model, optimised by the Bayesian optimisation algorithm, performs better when predicting energy consumption. Research results offer an effective energy consumption prediction method for fresh air systems and important experimental support for related energy prediction tasks.
Molecular Dynamics Simulations of Precursor Ceramic with Sil-Ma Composite
Molecular dynamics (MD) simulations were used to investigate the interfacial interactions of hydroxyapatite, β tricalcium phosphate, sil-ma, and filin protein (SF) in the composite. This study analyzed the interface binding energy and radial distribution function between hydroxyapatite (HA), β triccalcium phosphate (β -tcp), sil-ma and bio-polymer SF. The study found that the interface binding energy of Sil-MA hybrid system is higher than that of SF hybrid system, indicating that the Sil-MA hybrid system is more stable, which makes the mechanical properties of this system better.
Scope of the Applicability of Criminal Law to Crimes Committed on Board Ships: A Comparative Study Between International Treaties and National Legislation of Islamic States
The topic of the scope of applicability of criminal law to crimes committed on board ships is a significant issue in criminal law. It focuses on examining the extent to which national and international laws address offenses occurring on ships, particularly in international waters. This study aims to conduct a comparative analysis between international treaties and national legislation in Islamic states to clarify the legal framework governing such crimes. Ships represent a unique legal environment where national and international jurisdictions overlap in a complex manner. With the growth of maritime traffic and international trade, the need for a clear legal framework defining criminal jurisdiction becomes increasingly important to ensure justice and combat crimes. This study seeks to answer the key question: To what extent do national criminal laws apply to crimes committed on board ships, and what role do international treaties play in regulating these jurisdictions? The central focus of this research revolves around: How can national legislation in Islamic states be reconciled with international treaties in defining the scope of criminal law applicability to crimes committed on ships. A descriptive-analytical approach has been adopted in this study, involving the analysis of international and national legal texts, with a particular focus on Islamic states. These texts have been compared to identify their strengths and weaknesses. Additionally, legal precedents and jurisprudential interpretations related to the subject have been examined. The study has reached several important conclusions based on an analysis of the national legislation of various Islamic states. The key findings include:
Design and Manufacturing of Ultra-Thin Square Power Battery Aluminum Shell Forming Die
Increased demands on lightweight and high-performance battery casings of electric vehicles (EVs) and energy storage systems require cutting-edge forming technology to overcome challenges of conventional deep drawing and stamping, where usually thickness inhomogeneity, residual stress, and defects would be caused. The research deals with the designing and optimization of an ultra-thin square aluminum shell power battery forming die utilizing roll forming technology for improving size accuracy and mechanical reliability. A finite element model for simulation to optimize roll forming parameters, such as rolling force and pass geometry, was established and verified experimentally for thickness distribution assessment, defect minimization, and spring back minimization. The comparative study against deep drawing and stamping techniques reveals that roll forming results in 50% thickness variation reduction, 63% dimensional accuracy improvement, and 75% defect rate minimization. Furthermore, spring back effects were decreased by 42–60%, and shape retention and structural stability were improved. The results confirm that roll forming enhances production accuracy, reduces human errors, and improves overall efficiency, making it a good candidate for scalable next-generation production of batteries. From the data, it can be deduced that roll forming is a better alternative when compared to traditional forming as it helps in achieving better sustainability, less material waste, and increased reliability for future energy storage technologies.
Genetic Algorithm-based Model Predictive Control for Partial Shading Mitigation on PV Array
Photovoltaic (PV) energy harvesting systems experience performance deterioration and efficiency drops mostly due to mismatching and partial shading conditions (PSCs). Although different algorithms have been established to mitigate the negative impact due to PSCs, there are still some challenges concerning the algorithms’ robustness, accuracy, and reliability. To alleviate the effects of partial shading and enhance output power, PV array reconfiguration techniques emerged as solutions to this challenge. The purpose of this paper is to introduce the genetic algorithm (GA) based model predictive control (MPC) in order to mitigate the impact of PSCs on the PV array. This algorithm is considered due to its capability of taking multiple inputs and generating multiple output predictive signals. The proposed algorithm is implemented and simulated on MATLAB/Simulink for PV array performance optimization under PSCs. The results show that the GA-based MPC does not only mitigate the effects of PSCs but optimizes the PV array’s performance as well. From the simulation results, the GA-based MPC significantly increased the overall power output from 562.0 W (under PSCs) to 852.6 W which is almost the maximum power (under normal conditions), making an improvement of 290.6 W which is technically 51.17 % of the overall power generated by the system.
Effect of Cultural Change for Social Women Entrepreneurs with Special Reference to Tuensang District
This study aims to investigate the effect of cultural change for social women entrepreneurs with special reference to Tuensang district in the Nagaland state. This paper discusses the impact of cultural and societal factors on the entrepreneurial aspirations and outcomes of Tuensang women. The study highlights that rural entrepreneur face both internal and external barriers, such as limited access to capital, social biases, and the work-life balance dilemma, although they also possess sole asset, including flexibility, and strong want for individuality. Furthermore, it highlights the role of rural women as agents of social change, promoting inclusivity and empowerment within their communities.
The Impact of Implementing the International Financial Reporting Standard for Insurance Contracts (IFRS 17) On the Financial Performance of Insurance Companies Listed on the Amman Stock Exchange (Jordan)
This study aimed to identify the impact of implementing the International Financial Reporting Standard for Insurance Contracts (IFRS 17) on the financial performance of insurance companies listed on the Amman Stock Exchange (Jordan).** To achieve this objective, the study adopted a descriptive-analytical approach, which aligned with the nature of the research. Financial statement data from insurance companies was analyzed both before and after the implementation of IFRS 17, with a comparative analysis conducted between the two periods. The researchers utilized appropriate statistical methods through STATA software. The results demonstrated that the independent variable—the implementation of IFRS 17—had a positive impact on the financial performance of insurance companies listed on the Amman Stock Exchange. The study concluded that IFRS 17 represents one of the most significant developments in Jordan's insurance sector. To ensure its continued successful implementation, greater preparation, planning, and execution of the standard are required. Jordanian insurance companies must monitor the effects of this new standard on their financial data, related systems, controls, processes, and outputs. Necessary improvements should be made to enhance the quality of these companies' financial performance and the reliability of their financial reports and statements. This, in turn, will positively impact users of financial statements in particular and investment activities in general.
Investigation on the Structure and Optical Properties of Fe2+:ZnSe Quantum Dots Synthesized by Microemulsion Method
ZnSe quantum dots (QDs) have intensively studied because of their unique optical properties and enormous applications. By doping transition metal ions in ZnSe QDs, their properties can be further optimized and new functions can be given. In this work, Fe2+ doped ZnSe QDs were successfully prepared using inverse microemulsion-assisted hydrothermal method, and advanced characterization methods were used to systematically study their structure and optical properties. The research results showed that Fe2+ was successfully doped into the ZnSe lattice, and with the increase of Fe2+ doping concentration, the particle size of QDs gradually decreased. The actual doping ratio of Fe2+ was about 41% of the initial concentration. Optical properties studies showed that Fe2+ doping reduced the band gap width of ZnSe QDs from 2.43 eV to 1.96 eV. The synthesis of Fe2+ doped ZnSe QDs provides new possibilities for its application in optoelectronic devices and photocatalysis.
Performance Analysis of Solar Still for Potable Water Under Different Pressure Conditions
The present work is an outlook to enhance the productivity of a basin type double slope Solar Still with variant pressure. In India three fourth of its rural population is not having access to piped and clean drinking water and the scenario is not much different even in metropolitan cities. Only in Hyderabad, government spent 1450 crores as drinking water project and also provided 20 kiloliter per month to its consumers. The need of drinking water availability is rising and becoming too expensive. Various filtration techniques are available in the market. Solar desalination proves to be one of the most sustainable filtration techniques. The current work deals with the fabrication and experimentation of double slope solar still of 2m2 aperture area for portable drinking water. The composition of the water to be desalinate is not the sewage water but the normal ground water having a TDS level of more than 500PPM. The material for the basin is taken to be Fibre Reinforced Plastic (FRP) for ease in manufacturing and capability to attach to acrylic sheet for transparent walls from south east and west. The basin absorber is metallic sheet of 20 gauge. . The finding is indicate that the transparent sheet used as the walls of the still leads to higher yield and thus can further be increased if different pressure levels of 0.5 to 0.75 atm be applied.
N. Srinivasa Rajneesh, S. Nawazish Mehdi, B. Hadya
Adaptive Risk Management in Regulatory Operations: A Digital Twin Framework for Submission Readiness and Scenario Planning
In a world where regulatory environments are more and more often complex, organisations need intelligent systems that are agile and designed to deal with compliance risk. The study seeks to examine how Digital Twin technology can be applied to regulatory operations within a framework of Adaptive Risk Management intended to improve the state of submission readiness and more advanced scenario planning. Based on the literature, case studies, and secondary data analysis, the study demonstrates that there is an existing non-utilisation of digital twins in compliance functions. The research results point to the possibility of using them in the simulation of regulatory processes, risk forecasting, and delay minimisation. They propose a conceptual framework that merits themes in implementation throughout the product lifecycle. The paper highlights the criticality of dynamic, real-time, data-driven systems to enhance the efficacy of regulatory efforts in replacing the outmoded staid models of compliance.