bluuebunny/crossref_metadata_2025 huggingface dataset:
ESG's Global Dissemination and Impact: A Cross-Cultural Perspective
Authors: Ren Junlin Ren
Published: October 2024

This study explores the global dissemination and impact of ESG (Environmental, Social, and Governance) from a cross-cultural perspective. By comparing practices and feedback across different cultural backgrounds, the study reveals the similarities and differences in ESG concepts among various countries and regions. It finds that cultural factors significantly influence the implementation and acceptance of ESG, with diverse attitudes and behaviors towards ESG across cultures. The dissemination of ESG is constrained by cultural differences, leading to varying degrees of emphasis and methods in ESG practices, which in turn produce different impacts and outcomes. This research delves into the mechanisms and pathways of ESG dissemination in a cross-cultural context, providing crucial references for multinational enterprises in formulating ESG strategies and policies. By analyzing and comparing ESG practices and effects across different cultural backgrounds, the study offers new insights and methods for promoting the global dissemination and implementation of ESG principles.
The Development of Characteristic Towns in China - Take Yangzhou as an Example
Authors: Zhang Qi
Published: October 2024

The construction of characteristic towns has been popular in recent years. These towns are trying to utilize their distinctive features to create competitive advantages and foster local economic growth. Among all types of towns, its evident that significant opportunities exist for developing tourism-focused characteristic towns in China. This paper's primary case study centers on Yangzhou, a town renowned for its rich tourism tradition in China. Also, a comparative case of Xi'an provides insights into the operational patterns and strategic advantages in tourism development. Methodologically, a hybrid approach is employed, including direct observations and a tailored survey to assess the impact of tourism on Yangzhou's residents. The findings from this research are anticipated to offer targeted recommendations for enhancing tourism development and resident satisfaction in characteristic towns like Yangzhou. Overall, this essay provides a comprehensive analysis of the factors contributing to the success of characteristic towns in China, with a focus on tourism, cultural and technological integration, and sustainable community development.
A Study on the Brand Marketing Strategy of Luckin Coffee Based on SWOT Analysis
Authors: Song Jinnan
Published: October 2024

Using a SWOT analysis, this study investigates the brand marketing approach of Luckin Coffee, a well-known Chinese coffee company. With the backdrop of the rapid evolution of marketing strategies driven by the Internet and new media, this study aims to address the gap in understanding how marketing strategies can be tailored to a specific company's unique characteristics. Specifically, it investigates Luckin Coffee's strengths, weaknesses, opportunities, and threats based on an analysis of its current marketing efforts across channels and relevant brand topics. The findings provide insights into how Luckin Coffee can optimize its marketing strategy to seize opportunities and mitigate threats, ultimately contributing to the enhancement of the brand's competitiveness and relevance in the market. This research is a valuable reference for other coffee brands seeking to formulate effective marketing strategies in today's dynamic business environment.
Research on Innovation of Food Logistics Supply Chain Management
Authors: Chen Zhipeng
Published: October 2024

In the context of globalization and constantly changing consumer demand, the management of food logistics supply chains has become increasingly complex and important. This paper mainly studies the problems and innovative methods in food logistics supply chain management, aiming to improve the efficiency and adaptability of the supply chain by optimizing management strategies. This paper adopts literature analysis and case analysis methods to analyze in detail the problems of information asymmetry, cost control, transportation efficiency, and inventory management in the food logistics supply chain. It proposes innovative supplier management models, digital management, modern supply chain management concepts, inter chain cooperation, and risk management solutions. Research has found that adopting information-sharing mechanisms and advanced information technology, as well as strengthening collaboration among various links in the supply chain, can effectively improve management efficiency and reduce operating costs. This study provides some useful references for food logistics enterprises in practical operation, helping them improve service quality and reduce operating costs in a fiercely competitive market environment, enhance market competitiveness, ensure food safety and freshness, and meet the growing needs of consumers.
The Impact of Changes in the RMB Exchange Rate on the Export Competitiveness of China's Textiles and Clothing Industry
Authors: Li Tao
Published: October 2024

In recent years, the export volume of China's textiles and clothing industry and its international market share have increased year by year. Under such circumstances, studying the export status of China's textiles and clothing is conducive to further promoting the development of its textiles and clothing industry. This paper establishes a model based on the annual Revealed Comparative Advantage Index of China's textiles and clothing industry from 2000 to 2021, the nominal exchange rate of RMB against the US dollar, and the annual data of GDP. This paper then tests its stability, and continues to carry out the co-integration test and Granger-Causality under the condition that the data is stable in the same order to judge the relationship between the change of RMB exchange rate and the Revealed Comparative Advantage Index of China's textiles and clothing. Research shows that for every 1% appreciation of the nominal exchange rate of the RMB against the US dollar, the Revealed Comparative Advantage Index of China's textiles and clothing industry will increase by 0.0009647%. The rise of the RMB exchange rate has a certain effect on the RCA of China's textiles and clothing industry, and the results of Granger-Causality also show that the RMB exchange rate is the reason for RCA in China's textiles and clothing industry.
Review of ESG Information Disclosure under the New Development Concept
Authors: Liu Xinyao , Wang Yue , Zhang Zhihao
Published: October 2024

Abstract: With continuous development in the ESG (Environmental, Social, and Governance) field in China, the understanding of the concept and role of ESG by Chinese enterprises and related scholars has been deepening. However, issues such as the lack of uniform standards and frameworks for information disclosure, poor quality of information, and even greenwashing have gradually emerged in ESG information disclosure. The new development concept serves as a guiding principle for Chinas development, providing scientific direction for economic growth. The three major components of ESG closely align with the five principles of the new development concept, and the deficiencies and problems in ESG information disclosure profoundly affect the new development concept. Therefore, this paper aims to comprehensively review related research on ESG information disclosure and propose solutions to the identified problems based on the context of the new development concept.
Analysis of the Harmonious Development Path of Urban Management and Internet Celebrity Cities under Digital Perspective
Authors: Li Xiaoyu
Published: October 2024

Technological advances and the Internet's rapid development have fueled the rapid rise of Internet celebrity cities, providing a unique impetus to urban development (mainly tourism) and economic vitality. However, the ensuing controversies have been persistent. In order to promote a thriving urban tourism industry and alleviate urban economic and employment pressures, it is essential to address the issue of Internet celebrity cities and fully realize their economic and social potential. This study summarizes the multiple problems in the operation of traditional Internet celebrity cities, reveals their challenges to urban management, and proposes ways to build a digital Internet celebrity city system using "digital" technologies. These digital tools can effectively overcome the difficulties faced by traditional Internet celebrity cities and provide strategic guidance for the long-term and healthy development of the Internet celebrity city economy.
Impact and Prospects of Prepared Meals on the Catering Market
Authors: Li Woxue
Published: October 2024

The increasing pace of modern life has catalyzed the rise of the prepared meals industry, reshaping consumer behaviors and market dynamics in the global catering sector. This study examines the impact of prepared meals on the catering market, focusing on consumer behavior, market dynamics, technological innovations, and sustainability issues. The prepared meals industry has seen exponential growth, driven by consumer demands for convenience, health, and environmentally friendly options. Technological advancements in food preservation, distribution, and packaging have played a pivotal role in improving product quality and safety while extending market reach. Financial analyses of key industry players like Tyson Foods, Inc., Nissin Foods Holdings Co., Ltd., and Nestl S.A. reveal varied strategies for capitalizing on this growth, highlighting significant contributions to their overall business performance. The sector faces challenges including environmental sustainability, health and nutritional scrutiny, and intense market competition. Strategic responses to these challenges, such as investing in sustainable practices, focusing on health and nutrition, leveraging new technologies, and enhancing consumer engagement, are essential for future success. This research provides critical insights into the evolution of the prepared meals market, offering a comprehensive overview that could guide stakeholders in navigating this dynamic landscape.
The Impact of the Development of Artificial Intelligence on Unemployment Rates
Authors: Liu Jiaxin
Published: October 2024

Abstract: The proliferation of artificial intelligence (AI) is a transformative force in global labor markets, presenting dual possibilities: the displacement of traditional jobs and the creation of new employment opportunities. This paper explores the dynamic relationship between AI development and unemployment rates, using empirical data and regression analysis from 2012 to 2022. It examines the impact of AI across various sectors, highlighting how technological advancements and public engagement with AI via platforms like Google Trends influence employment patterns. In addition, it also reveals that AI development has a generally negative correlation with unemployment rates, suggesting that increased AI adoption may be linked to lower unemployment levels. The findings also underscore the importance of adaptive policies and education systems to harness AIs potential for job creation, which contributes to the discourse on AIs economic implications by providing a nuanced analysis of its influence on employment, essential for policymakers and stakeholders in navigating the challenges and opportunities presented by AI technologies.
Research on the Internationalization Strategy of Country Garden Holdings Company Limited
Authors: Xu Jirui
Published: October 2024

Abstract: For years, China's real estate industry has been in fierce competition. With the development of economic globalization, the domestic market is about to reach saturation gradually. Under these circumstances, Chinas real estate enterprises were obliged to go out to obtain more opportunities to improve their profits and ensure their position in the market. Country Garden Holdings Company Limited, as one of the leading enterprises in the real estate industry, started to invest and expand in overseas markets in 2011. With its forward-looking strategic planning, it has successfully launched projects in many countries and regions, which are worth studying. This paper analyzes the development status of international projects of Country Garden and its internationalization strategy, and explores the reasons for its successful investment, which can provide more information and guidance for Chinas real estate enterprises to invest overseas in the future.
The Impact of COVID-19 Shocks on the U.S. Unemployment Rate
Authors: Sun Xing
Published: October 2024

Abstract: The COVID-19 pandemic has had a profound impact on the U.S. labor market, resulting in significant fluctuations in unemployment rates across various demographic and educational groups. This paper examines the trends in unemployment from January 2020 to December 2021, a period characterized by intense economic upheavals due to public health measures and subsequent economic recovery initiatives. Utilizing data from the U.S. Bureau of Labor Statistics, the study explores how unemployment rates varied among different racial groups and levels of educational attainment, identifying which groups were most vulnerable to job losses and which experienced more resilient employment patterns. The findings reveal that the pandemic exacerbated existing disparities in the labor market, with particularly severe impacts on Black or African American individuals and those with lower educational levels. The paper also discusses the gradual recovery observed in unemployment rates as the economy began to stabilize, though noting that full recovery was not uniform across all groups and make a conclusion that there are significant differences in the impact of different racial groups and levels of education on unemployment rates. Through this analysis, the research provides insights into the structural weaknesses in the labor market exposed by the pandemic and offers recommendations for targeted policy measures aimed at fostering a more equitable economic recovery. This study contributes to the broader understanding of the economic implications of global health crises and the critical role of inclusive policy interventions in mitigating these effects.
Optimization and Application Analysis of the UAV "Last Mile" Mobile Terminal Distribution Station in Rural Area under the Background of E-Commerce
Authors: Luo Zhongsheng
Published: October 2024

With the booming demands of global consumers, the grand total of international e-commercial procurement in 2024 will be expected to exceed 6.3 trillion USD. Under the pressure of huge orders and shipping lag, figuring out a cost-effective last mile delivery achieving real door-to-door service, especially in rural areas, has become one of the focuses in the international e-commercial market. To better solve this problem, this paper starts with the analysis of international e-commercial status and the feasibility of UAV mobile terminal station launch, taking good account of drone delivery route setting, time schedule, and costs spent to optimize the mobile station moving. Based on a series of experiments to iterate the Unmanned Aerial Vehicle (UAV) mobile terminal station delivery mode, it will provide some insights to the market about how the last mile delivery will develop in the next decade. This paper will focus on applying the hybrid ant colony algorithm to improve truck-drone collaborative last mile delivery route settings and figure out the best delivery route combo for cost saving.
Xiaomi: An Analysis of Market Strategy under the High Cost-Performance Ratio
Authors: Hou Yueting
Published: October 2024

Abstract: Xiaomi Corporation, which was established in 2010 in Beijing, is well-known for its smartphones along with other smart hardware as well as IoT devices. It is the second-largest manufacturer of smartphones in the world, behind Samsung, with a market share of about 12%, most of which run on the MIUI (now HyperOS) operating system. It mainly focuses on providing products that are of excellent quality and performance but still maintain affordability which attracts customers from around the world. This research delves into Xiaomi's adaptive marketing tactics as a reaction to evolving market dynamics and changing consumer demands, and examines Xiaomis market plan by looking at three clear instances. The first is how Xiaomi keeps its strong position in the smartphone market by bringing out improved models every year with a steady price tag. This helps to maintain their image of being very good value for money. Second, the choice of the company to put $300,000 for three years into remaking its logo with Japanese designer Kenya Hara. This highlights how redesigning has a strategic effect on brand image and worldwide identification. Thirdly, this study talks about Xiaomis start in the car industry when it introduced the first car model called Xiaomi SU7 in month April. It shows a major shift from making only smartphones to also producing electric cars.
The Overview of Vertical Take-Off and Landing Technology
Authors: Yuan Dajun
Published: October 2024

Vertical takeoff and landing (VTOL) technology is garnering significant attention in the aviation industry due to its distinct benefits and wide range of potential applications. A long runway is not necessary when using VTOL technology, which allows aircraft to take off and land vertically straight from the ground. Air mobility in cities, military activities, and emergency response are just a few of the areas where this technology is beneficial. This essay will provide an overview of the development, application, and future of vertical takeoff and landing technology. The technologys operating principles, advantages and limitations will also be explored. Overall, VTOL technology offers a tremendous leap in aircraft technology, with numerous possible uses. Even though there are still difficulties, more research and development will probably result in improvements and broader use.
Non-orthogonal unicast and multicast transmission with IRS-assisted Rate-Splitting Multiple Access in multiuser MISO systems
Authors: Li Kuiliang , Xue Rui , Jin Tianle
Published: October 2024

Abstract. In MISO systems, novel communication technologies such as NOMA and multicast transmission have attracted widespread attention to meet the diverse needs of users. However, traditional NOMA and multicast transmission schemes have certain limitations in dynamic interference management and resource allocation. To resolve this issue, this paper proposes a RSMA scheme assisted by phase quantized Intelligent Reflecting Surface (IRS) for downlink MISO systems with nonorthogonal transmission of unicast and multicast signals. In this scheme, through reconfiguring unicast and multicast signals and combining them into a super-common stream and partial unicast messages, RSMA achieves dynamic interference management of multi-user while effectively separating unicast and multicast streams. To maximize the weighted sum rate(WSR), we put forward an alternating optimization(AO) algorithm that utilizes Weighted Minimum Mean Square Error (WMMSE) estimation and convex set intersection representation, which jointly optimizes the equivalent beamforming matrix,rate allocation and phase shift matrix. Simulation results illustrate that the proposed single-layer RSMA exhibits performance closer to that of DPC encoding compared to traditional NOMA and MULP schemes. Furthermore, we extensively investigate the relationship between the WSR of RSMA and system parameters, providing important guidance for practical engineering applications.
Occluded facial expression recognition based on deep learning
Authors: Zhao Xuetong
Published: October 2024

Abstract. When employing Convolutional Neural Networks (CNNs) for facial expression recognition, several challenges are often encountered, such as facial occlusions, the limited size of reliable expression datasets, and inadequate precision in recognition outcomes. This paper preprocesses the dataset to enhance its reliability. By leveraging data synthesis and augmentation techniques, it employs a method of randomly generating occlusion blocks to integrate and expand the dataset. Based on the ResNet-18 network, the model is optimized by incorporating an attention mechanism, thereby improving the network's precision and robustness in recognizing facial expressions.
Low-cost guide dog robot navigation using Dueling DQN
Authors: Fang Feiran
Published: October 2024

Abstract. Traditional aids for the visually impaired, such as guide dogs, have limitations. They are expensive to train, require a long preparation time, and are not accessible to most people. Guide robots have the potential to address these issues. However, most existing navigation methods focus solely on the robot's trajectory, neglecting the movement of the person. As a result, the paths of the visually impaired individual and the robot may not overlap or may intersect with obstacles.To overcome these challenges, we propose an intelligent guide dog system based on a Deep Q-network (DQN). First, a kinematic model is constructed to calculate the relative positions of the guide robot and the human. Then, the reward function is designed based on this kinematic model. Finally, the Dueling DQN is trained to plan a path and predict the human's possible trajectory, ensuring collision avoidance for both the robot and the human.Our experiments demonstrated that our system performs well in both simulated environments and in real-world scenarios, such as climbing stairs. The robot can accurately find a safe path that considers the trajectories of both the robot and the human, successfully completing tasks safely.
AnimeSketchNet: Integrating traditional sketching and anime art via an innovative dataset
Authors: Xie Jiyang , Li Qiling
Published: October 2024

Abstract. Recent advancements in text-to-image synthesis have shown promise, yet many models struggle with generalizability and adaptability, particularly in specialized genres like anime sketches. To overcome these challenges, we introduce AnimeSketchNet, a novel framework designed to enhance model performance by effectively capturing the complexity and stylistic variability unique to anime. AnimeSketchNet leverages a diverse collection of anime sketch styles with varying levels of detail, enabling the model to learn and adapt to the distinct artistic style of anime. Our dual-branch architecture, featuring a decoupled attention mechanism, seamlessly assimilates textual descriptions along with visual features, producing high-quality anime sketch that are both detailed and faithful the reference sketch. Experimental results demonstrate that AnimeSketchNet surpasses existing state-of-the-art models in both qualitative and quantitative evaluations. This work significantly advances text-to-image synthesis by offering a powerful and flexible tool tailored specifically to the unique demands of anime art.
Robot intelligent perception and control
Authors: Ma Suhang
Published: October 2024

Abstract. In recent years, with the rapid development of robotics, intelligent perception and control has become the core research direction in the field of robotics. This technology plays a key role in many fields such as industrial automation, medical assistance, and autonomous driving, significantly improving production efficiency and service quality, and also promoting the intelligent processes of various industries. On the basis of an in-depth analysis of robot intelligent perception and control technology, this paper systematically reviews the development of visual and non-visual perception technology and discusses the application of multi-modal perception in complex environments. The latest development of motion control and force control technology is analyzed, and its importance in fine operation is expounded. The future development direction of robot intelligent perception and control technology is proposed, and the necessity of enhancing real-time robustness and system integration is emphasized, which provides theoretical support and technical reference for promoting the continuous innovation of robot intelligent perception and control technology.
AI-empowered Search Drone: Advanced AI-based Tiny Object Search Drone for Broad Areas
Authors: Zhou Changhui , Yu Tianyue
Published: October 2024

Abstract. Detecting the garbage distribution and position in broad terrains(beaches, grasslands, squares, etc) is extremely important for environmental protection and urban image. Manually screen these terrains is time-consuming and ineicient. Autonomous robot may find the wastes automatically, but they may hinder and even endanger the pedestrians. Unmanned aerial systems(UAS) are ideal tools for monitoring broad areas and detecting garbage. In this project we create an AI-empowered Search Drone for extensive garbage search in broad regions. The camera on our drone and the external image transmission module on the computer receive and process top-view image from the sky. The images from high altitude lead to the reduction in target size and object distortion. We innovately modified the network structure of the oicial YOLOv5 model by adding layers specifically for small object detection, enhancing its adaptability to small targets captured by drones.To address camera image distortion, we leveraged the OpenCV (cv2) library to obtain and apply a distortion correction matrix. Furthermore, we devised an algorithm that calculates the real-world location of targets based on their pixel positions, the drones height, and the ratio between pixel and real-world dimensions.To strengthen the models garbage search capabilities, we simulated various garbage search scenarios in open environments and collected image datasets using drones for specialized training. Finally, we utilized the PyQt library to develop a simplistic front-end interface for data analysis and comparison of the detection performance between the original and optimized models. Experimental results demonstrate that the optimized model outperforms the original model, effectively enhancing garbage search eiciency in extensive areas. This project represents a significant step forward in leveraging technology to combat environmental pollution.
Advances in deep learning-based intelligent receivers
Authors: Hu Jiaming , Li Meimei
Published: October 2024

Abstract. This paper presents a summary of the progress of deep learning in the research of intelligent receivers and predicts its future development direction. First, the background of the era of intelligent receivers is introduced. With the rapid development of communication technology, intelligent receivers show insufficient flexibility, low accuracy, and spectral efficiency in detecting current radio signals. This is a challenge that is difficult to overcome in order to meet the needs of modern signal recovery. With the advent of artificial intelligence technologies such as deep learning, academia and industry began to explore the potential of applying these techniques to the field of communication receivers, leading to the emergence of intelligent receivers. This paper then introduces the fundamentals of wireless communication systems and deep learning neural networks, laying the groundwork for a deeper understanding of the subsequent content. Chapter 3 provides a comprehensive overview of the application of intelligent receivers in signal reception, including channel estimation, signal detection, modulation identification, demodulation and decoding. Finally, the paper considers the practical applications of intelligent receivers and speculates on their future development.
The application and challenges of different face recognition technologies in the three major fields of security, social media, and medical care
Authors: Li Haoying
Published: October 2024

Abstract. Face recognition technology is a very important part of modern technology, which can not only be used to ensure security, but also can be used in the field of information organization and content division. However, with the popularization and application of face recognition technology, many problems that need to be solved urgently have emerged: excessive computing resources are consumed in order to pursue high-precision recognition, which brings computing pressure; The basis for improving recall is the need for a lot of power and memory; If security is not guaranteed, it can cause problems such as data breaches. The demand for face recognition technology is different in different use fields, so the purpose of this study is to combine the scene requirements and technical advantages more reasonably. The research results are as follows: the high accuracy and recall rate of 3D convolutional neural networks (3DCNNs) ensure that it can be used safely in high-precision and high-security scenarios. Lightweight Convolutional Neural Network (MobileNetV2) is suitable for resource-constrained environments due to its low memory consumption and low communication cost. Edge computing real-time face recognition (EC-RFERNet) is the most suitable for large-scale popularization and application among the three because of its lowest power consumption and latency. This study deeply explores the advantages and disadvantages of different facial recognition technologies and finds solutions to their shortcomings. According to their unique advantages combined with the requirements of commonly used scenarios, it provides a scientific basis for the deployment of face recognition technology in different fields. However, due to limited information, this paper cannot cover all application scenarios and the latest technologies, so it is hoped that in the future, we can combine the advantages of different technologies to develop more comprehensive face recognition technology and make more reasonable technical planning.
Personalized Super Resolution with Face Prior
Authors: Lu Hanzhang , Qi Ji
Published: October 2024

Face Super-Resolution (FSR) is a critical technology in computer vision that aims to reconstruct high-resolution facial images from low-resolution inputs. Despite recent advancements, current FSR methods struggle to accurately reconstruct personalized and detailed features. This paper proposes a novel FSR approach that addresses these challenges through a personalized feature extraction and fusion framework. Our method integrates a U-Net based downsampling mechanism to extract individual- specific features from high-resolution reference images, which are then fused with a pre-trained Generative Adversarial Network (GAN) for enhanced reconstruction. We introduce a comprehensive loss function that combines reconstruction, adversarial, facial component, and identity preservation losses to guide the learning process. Extensive experiments on the augmented FFHQ dataset demonstrate that our approach significantly improves the reconstruction of rich facial features, particularly for older individuals, outperforming existing state-of-the-art methods in both quantitative metrics and qualitative visual assessments.
Enhanced robustness in machine learning: Application of an adaptive robust loss function
Authors: Wan Jiuyang , Wang Tianyi , Li Wancheng , Wang Ziyao
Published: October 2024

In the field of machine learning, the selection of a loss function plays a pivotal role in determining the training dynamics and generalization capability of models. Traditional loss functions such as mean square error (MSE) and cross-entropy are often not equipped to handle noisy and anomalous data effectively, which can result in models that perform poorly in practical scenarios. To address these shortcomings, this study introduces a novel adaptive robust loss function, enhanced by a tunable parameter , which allows for flexibility in adjusting the robustness of the function according to the nature of the data being processed. Our research demonstrates that this new loss function significantly improves the performance of linear regression and multilayer perceptron models, particularly in environments laden with noisy and anomalous data. By adapting the parameter , the function can cater to varying levels of data irregularities, thus enhancing the models accuracy and reliability across diverse and complex data environments. This adaptive mechanism not only offers a substantial theoretical contribution to the understanding of robust loss functions but also provides a practical tool for machine learning practitioners to develop models that are resilient to data imperfections. The implications of this research are profound, suggesting a shift towards more adaptive and robust approaches in machine learning model development.
Evaluation of three kinetic energy storage systems
Authors: Mosely Philip Nelson
Published: October 2024

Abstract. This paper investigates recent advances in energy recovery systems (ERS) in automotive vehicles to reduce air pollution and impact on climate change. The three ERS systems: mechanical flywheel, regenerative braking, and regenerative electrically assisted (REAT) turbocharger are evaluated for their potential to reclaim energy wasted by the automobile thereby increasing range and efficiency of the vehicle. The methods of comparison are based on data sourced from current literature relevant to total energy recovery, system configuration, and application feasibility. This will identify regenerative braking as best for new vehicles to decrease fuel consumption and regenerative electrically assisted turbocharges (REAT) as best for retrofitting older vehicles. The paper will use the results to identify the energy recovery system with the greatest potential for immediate application and further research to overcome remaining challenges.
Coordination of NPCs in multi-agent systems based on behavior trees
Authors: Hu Chenyu , Wu Ruiyuan , Deng Xiaojie
Published: October 2024

Abstract. This paper addresses the design and coordination challenges of controlling non-player characters' (NPCs) behaviors in multi-agent systems (MAS) using behavior trees (BTs), which are preferred over finite state machines (FSMs) due to their hierarchical structure and ease of maintenance. While BTs effectively resolve the question of "What to do next?" for individual NPCs, their application in MAS, particularly with the integration of a blackboard system for central control, reveals limitations in efficiency, robustness, and heuristic capacity as system complexity increases. To explore solutions to these challenges, this study analyzes various algorithms that enhance the functionality of behavior trees within MAS. The research focuses on three primary areas: the optimization of behavior trees, the development of behavior tree search algorithms, and the improvement of communication algorithms within BTs. Methods involve a comparative analysis of existing and new algorithmic approaches to identify and address inefficiencies in NPC coordination. The findings indicate that advanced behavior tree configurations, when combined with innovative search and communication strategies, significantly improve the coordination, robustness, and operational efficiency of MAS. These enhancements allow for more dynamic and responsive NPC interactions in complex gaming environments.
Advances in cell therapy research
Authors: Li Fang , Li Quan , Fu Xue , Hui Lihua , Mao Xuewei , An Ran , Wang Lingfeng
Published: October 2024

Cell therapy represents an important area of biotechnology, with the potential to treat and even cure a variety of diseases that cannot be cured by traditional therapies. Cell therapy is currently a widely studied treatment in both preclinical and clinical settings, and many cell therapy products are undergoing clinical trials. This article reviews the application of cell therapy in a variety of diseases and the policy of stem cell therapy in China.
Prevalence of Vitamin B12 Deficiency in Libyan Type 2 Diabetic Patients Treated with Metformin
Authors: Elmabruk Gamag
Published: October 2024

Metformin is the most-used drug in type 2 diabetes mellitus management and its long-term use may consequent to vitamin B12 deficiency. The lack of studies from Libya investigating the risk of association between these two presents a gap in our understanding of this issue. Our study aimed to estimate the prevalence of vitamin B12 deficiency in metformin treated diabetic patients and non-metformin treated patients and its correlation with diabetic duration and gender. Specifically, we tested the hypothesis that T2DM patients treated with metformin exhibit a decrease in vitamin B12 levels and are considered at risk for developing B12 deficiency depending on the diabetic duration and metformin use. A total of 81 samples of metformin treated diabetic patients (N=58) and non-metformin diabetic treated patients (N=23) were collected and underwent assessment of F.B.S, HbA1c and B12 level. The total mean age was 46.4± 8.27 (47.25± 9.22 for males and 45.55± 7.32 for males respectively). Total mean and standard deviation of blood glucose level was 173.93± 29.87 mg/dl (158.25± 27.35 and 184.18± 27.06 for males and females, respectively). Total mean and standard deviation HbA1c level was 6.81± 1.98% (5.94± 1.31 and 7.37± 2.14 for males and females, respectively). Total mean and standard deviation of vitamin B12 level was 435.53± 251.31 (575.62± 250.21 and 342.76± 205.91 for males and females, respectively). Our study indicated that the shortage of vitamin B12 was generally found in our population, insufficient vitamin B12 level was frequently reported in metformin administration to patients with T2DM and could progress into deficiency. Further larger studies are required to assess vitamin B12 level in those patients.
Impact of Vitamin C and Hydroxyurea on the Reproductive System Health in Male Rats
Authors: Ebtesam Abdulhadi
Published: October 2024

Hydroxyurea (HU) is a medication used to treat various diseases and is also being studied for its effects on spermatogenesis. Vitamin C (VC), an antioxidant, has been shown to protect sperm cells from oxidative stress, potentially improving fertility and sperm quality. In a study involving twenty-four adult male albino rats divided into four groups, Group 1 served as the control, Group 2 received 5 mg of vitamin C, Group 3 received 100 mg of hydroxyurea per body weight, and Group 4 received a combination of vitamin C and hydroxyurea to assess essential functions of the reproductive system, including hormone levels, antioxidant markers, oxidative stress indicators, histopathology, and identification of DNA damage. The study found that hydroxyurea significantly reduced testicular weight, SOD, CAT, and GSH while increasing FSH and MDA levels and causing abnormalities in sperm morphology. Hydroxyurea also caused apparent alterations in the histological structure of the testes and comet parameters. Rats treated with vitamin C showed a significant increase in absolute and relative epididymis weight compared to the control group. Moreover, vitamin C intervention reversed the adverse effects observed in rats fed hydroxyurea, indicating that low doses of vitamin C can protect against testicular damage.
Պղնձի և ցինկի ռենտգենառադիոչափական նմուշարկումը դիֆերենցիալ զտիչների կիրառմամբ
Authors: Թամրազյան Արտյուշա
Published: October 2024

Բարդ նյութական կազմ ունեցող հանքանյութում պղնձի և ցինկի ռենտգենառադիոչափական նմուշարկման ժամանակ նրանց անալիտիկ գծերի անջատման համար կիրառվում է դիֆերենցիալ զտիչների մեթոդը: Արգելակման ճառագայթմամբ ռադիոակտիվ աղբյուրով առաջնային գրգռման ժամանակ զտիչների պատուհան են անցնում ինչպես աղբյուրի առաջնային, այնպես էլ ուսումնասիրվող միջավայրի երկրորդական ցրման ճառագայթները, ինչի արդյունքում էապես նվազում է անալիզի ճշտությունը: Նախկինում այդ ճառագայթներից զտիչների պատուհանը «մաքրելու» համար առաջարկվում էր չափումներ կատարել դատարկ ապարների վրա և ստացված արժեքը հանել հիմնական չափման արժեքից: Սակայն ուսումնասիրվող միջավայրի նյութական կազմի, խտության, կառուցվածքի և ցրման ճառագայթների փոփոխմանը բերող այլ գործոնների առկայության դեպքում այս եղանակը կիրառելի չէ: Հոդվածում առաջարկվում է ցրման ճառագայթների ազդեցության հաշվի առնման նոր եղանակ:
При рентгенорадиометрическом опробовании меди и цинка в рудах сложного вещественного состава для выделения аналитических линий этих элементов обычно применяются дифференциальные фильтры. При первичном возбуждении с радиоактивным источником тормозного излучения в окно дифференциальных фильтров входят рассеянные излучения как от источника первичного излучения, так и вторичные рассеянные излучения от исследуемых сред, что приводит к существенному уменьшению точности опробования. Для учета вклада мешающих излучений, т.е. для очистки окна дифференциальных фильтров от рассеянных излучений, сначала измеряются разности счета на пробе, не содержащий определяемый элемент и полученное значение вычитается из основного измерения. Однако, изменения вещественного состава, плотности, структуры исследуемой среды, а также наличие других факторов, приводящих к изменению рассеянных излучений, этот способ неприменим. В данной статье предлагается новый способ учета влияния рассеянных излучений, свободный от указанных недостатков.
In X-ray radiometric testing of copper and zinc in ores with complex compositions, differential filters are typically used to isolate the analytical lines of these elements. During the primary excitation with a radioactive source of bremsstrahlung, both the scattered radiation from the primary source and the secondary scattered radiation from the studied materials enter the window of the differential filters, which significantly reduces the accuracy of the testing. To account for the contribution of interfering radiation and to clean the window of the differential filters from scattered radiation, the count differences are first measured on a sample that does not contain the element being determined, and the obtained value is subtracted from the main measurement. However, this method is not applicable due to changes in the material composition, density, structure of the studied material, as well as the presence of other factors that lead to changes in scattered radiation. This article proposes a new method for considering the influence of scattered radiation, free from the mentioned drawbacks.
Navigating overtourism destinations: Leveraging smart tourism solutions for sustainable travel experience
Authors: Mohammad Shafiee Majid
Published: October 2024

This paper explores the integration of artificial intelligence (AI) and smart tourism technologies to address the multifaceted challenges of overtourism in tourist destinations. Overtourism leads to significant environmental degradation, strains local resources, and diminishes visitor satisfaction, ultimately threatening the sustainability of these destinations. Destinations can enhance sustainability and tailor travel experiences by utilizing cutting-edge technologies like the Internet of Things (IoT), augmented reality (AR), virtual reality (VR), and big data analytics. These technologies offer innovative solutions to optimize resource use, enhance visitor engagement, and promote responsible tourism practices. The study underscores the potential of smart tourism technologies to manage tourist flows, reduce environmental impacts, and improve the overall quality of life for local communities. Strategic planning, substantial investment, and collaboration among various stakeholders, including government agencies, local communities, and the private sector, are essential for the successful implementation of these solutions. The findings highlight the critical role of technological innovation in fostering a balanced and sustainable future for tourism, ensuring that destinations can thrive economically while preserving their cultural and natural heritage. This research provides valuable insights for policymakers and tourism managers aiming to mitigate the adverse effects of overtourism through the adoption of AI and smart tourism technologies.
Méthodes d’analyses élémentaires : revue comparée des techniques utilisables à la caractérisation des poussières fines
Authors: Guegan Hervé
Published: October 2024

L’objectif de cet article est de présenter les principales techniques d’analyse élémentaire de particules fines utilisées à la problématique de la recherche des sources. Cette présentation s’attachera à décrire leurs fondements pour mieux comprendre leurs qualités intrinsèques et leurs limitations, afin de les replacer dans le foisonnement des méthodes d’analyse physico-chimique. On pourra être ainsi à même de saisir la pertinence de l’utilisation de l’une ou l’autre en fonction de la problématique posée.
Utilisation de la modification de la biodiversité lichénique sur résineux pour détecter la pollution azotée d’origine routière
Authors: Remy Claude
Published: October 2024

Plusieurs études réalisées dans le département des Hautes-Alpes par lʼassociation Arnica Montana, basées sur une cartographie et un inventaire de la végétation lichénique, ont abouti à mettre en évidence lʼexposition aux oxydes dʼazote des milieux naturels. Ainsi, la présence et le développement de la végétation lichénique nitrophile sur résineux et la disparition dʼespèces sensibles à lʼazote semblent bien être dus à une eutrophisation de lʼécorce par les oxydes dʼazote due à la circulation routière. Pour un coût financier réduit, cette méthode permet une mise en évidence globale de la pollution azotée sur une surface importante sur laquelle il serait difficile financièrement dʼimplanter un nombre suffisant de capteurs. Des propositions de gestions des espaces naturels peuvent être faites sur la base de ces résultats.
La biosurveillance dans les Associations agréées pour la surveillance de la qualité de lʼair
Authors: Signoret Jonathan , Schmitt Jean-Pierre
Published: October 2024

Simple, efficace et peu onéreuse, la biosurveillance de la pollution atmosphérique apparaît comme une démarche complémentaire des mesures physiques et chimiques. En plein développement, la normalisation des méthodes de biosurveillance, française par l’AFNOR et européenne par le CEN, renforce cette approche et offre un cadre plus attractif pour les utilisateurs potentiels que sont les Associations agréées pour la surveillance de la qualité de l’air (AASQA) regroupées au sein de la fédération ATMO France. Deux enquêtes menées en 2008 et 2011 avec le concours des réseaux de surveillance de la qualité de l’air, montrent que, malgré l’importance des ressources dédiées par certaines de ces associations pour la mise en œuvre des méthodes de biosurveillance, la généralisation de cette approche reste plus que difficile, en raison des différences d’intégration dans les programmes et les plans réglementaires, de sensibilisation et d’accès à la compétence. Cet article met en lumière le potentiel de la biosurveillance dans les AASQA pour éclairer les politiques dans le domaine de la surveillance de la qualité de l’air.
Le dispositif BRAMM : un outil de biosurveillance de la qualité de l’air
Authors: Leblond Sébastien , Laffray Xavier , Galsomiès Laurence , Gombert-Courvoisier Sandrine
Published: October 2024

Le dispositif BRAMM (Biosurveillance des retombées atmosphériques métalliques par les mousses) est un dispositif français de surveillance de la qualité de l’air à partir des mousses terrestres. Il permet de cartographier, à l’échelle nationale (France métropolitaine), les niveaux de concentrations en contaminants (éléments métalliques et azote) accumulés dans des mousses prélevées en milieu rural et forestier. Il suit aussi les évolutions temporelles des dépôts grâce à des données d’observation longue durée (sur quinze ans). Quatre campagnes françaises ont été réalisées à ce jour (1996, 2000, 2006 et 2011 en cours), portant sur environ 500 sites de collecte répartis sur l’ensemble du territoire. Le dispositif BRAMM est également la participation française à un programme européen de suivi des métaux dans les mousses (UNECE-LRTAP).