bluuebunny/crossref_metadata_2025 huggingface dataset:
Megha-Tropiques : un satellite franco-indien pour l'étude du cycle de l'eau et de l'énergie dans les tropiques
Authors: Picon Laurence , Desbois Michel , Cloché Sophie , Brogniez Hélène , Capderou Michel , Chomette Olivier , Roca Rémy , Sèze Geneviève , Szantai André
Published: February 2025

Dans les années 1990, Michel Desbois, responsable de l’équipe CET du laboratoire de météorologie dynamique (LMD), propose le concept d’une mission dédiée à l’étude des pluies, des nuages, de la vapeur d’eau et leurs impacts sur le bilan radiatif terrestre dans les tropiques. Le satellite est lancé en 2011 et produit des données jusqu’en 2023. Cet article décrit l’évolution de ce projet, de sa conception à son exploitation scientifique. Il montre comment Megha-Tropiques s’insère dans les thématiques historiques du LMD et, plus largement, quelles sont les principales avancées scientifiques de cette mission.
Beyond Gridlock
Authors: Ramjit Dana-Marie
Published: February 2025

As traditional approaches to global governance face increasing gridlock due to institutional inertia and divergent national interests, non-state actors have emerged as vital catalysts for change. Drawing on Ostrom's (2010) theoretical framework, this chapter explores how polycentric governance—characterized by multiple, semi-autonomous decision-making centers—offers a promising alternative to conventional monocentric or anarchic systems. Through analysis of recent scholarship and case studies across climate change, resource management, and sustainable development initiatives, this research examines how polycentrism's adaptability and emphasis on diverse governance structures fosters innovation and enhances resilience. The findings demonstrate that polycentric approaches enable locally tailored yet globally coordinated responses to transnational challenges, contributing to our understanding of how international cooperation can evolve beyond current governance limitations to address the multifaceted challenges of our increasingly interdependent world.
Effective Leadership Strategies for Enhancing Student Success in Higher Education
Authors: Ayyaswamy Kathirvel , Kathirvel Naren , Gobinath V. M. , Maheswaran C. P.
Published: February 2025

This chapter examines the instrumental role effective leadership plays in enhancing student success in higher education. As colleges and universities face mounting pressures to demonstrate outcomes around retention, progression, attainment, career readiness and more, leadership has become mission critical to driving systemic reforms that enable these student achievement aims. The chapter provides higher education administrators, teams and policymakers research-backed principles to translate leadership vision, strategy and capabilities into tangible initiatives and cultural change that help all students thrive. Concluding insights discuss emerging challenges leaders must creatively navigate, such as demographic shifts, funding constraints, remote learning and calls for even greater equity or reform. With pressure on higher education mounting, the need for strategic leadership committed to student advancement has never been more acute or consequential. This chapter seeks to inform this charge.
Digital Transformation in the Smart Healthcare Canvas of Augmented and Virtual Reality
Authors: Singh Bhupinder
Published: February 2025

The healthcare landscape is undergoing a revolutionary shift, driven by the relentless march of digital transformation. There are emerging technologies like Augmented Reality (AR) and Virtual Reality (VR) poised to reshape how it delivers and experience healthcare across the globe. AR superimposes digital information onto the real world, offering real-time guidance and visualization during medical procedures. Imagine surgeons viewing 3D anatomical models overlaid on a patient during surgery, or dentists using AR-powered apps to guide dental implant placement with precision. VR immerses users in simulated environments, enabling applications like phobia therapy, pain management and even surgical training in highly realistic scenarios. The true potential of AR and VR unfolds when woven into the fabric of smart healthcare ecosystems. This chapter dives into the exciting possibilities these technologies offer, exploring their integration into smart healthcare ecosystems and the creation of transformative health gateways within a global context.
Case Study
Authors: Bradford Arthur D. , Burrell Darrell N.
Published: February 2025

Employee retention is crucial for organizational success, particularly in healthcare. The nurse retention and shortage crisis in the U.S. is marked by turnover rates exceeding the national average, with 57% of nurses leaving within two years. High turnover disrupts organizational stability, exacerbates burnout, and compromises patient safety and care quality, thereby exposing organizations to financial, legal, regulatory, reputational, and clinical risks. The chapter identifies key factors driving the crisis, including an aging workforce, burnout, fewer new nurse graduates, and rising demand due to population health trends. These factors contribute to increased medical errors and adverse patient outcomes. Using AMG as a healthcare provider archetype, the chapter integrates the DMAIC problem-solving model, the COSO enterprise risk management framework, and Kotter's change management model to propose actionable retention strategies to address these challenges. The resulting recommendations aim to stabilize the nursing workforce, enhance patient outcomes, and mitigate enterprise risks.
Support and Preparedness of Healthcare Workers' Wellbeing in a Haemodialysis Facility During the Coronavirus Pandemic, KwaZulu-Natal, South Africa
Authors: Ramnarain Rakhee , Gerwel Proches Cecile Naomi
Published: February 2025

The purpose of the qualitative study was to determine the impact of the Coronavirus (COVID-19) on the wellbeing of the clinical haemodialysis healthcare workers of an organisation specialising in renal care and dialysis in KwaZulu-Natal, South Africa. This study spanned over four outpatient locations from a private practice in South Africa. Online semi-structured and in-depth interviews of nine clinical haemodialysis healthcare workers and findings from the thematic analysis revealed that wellbeing was negatively impacted. Psychological wellbeing support was lacking and evident from all decision-makers, inclusive of the workplace, Government, medical aid funders and higher educational training. Participants expressed various types of emotional support that were needed and felt that this will help them to enjoy what they do and to offer a better quality of care to their patients. Recommendations are provided.
Balancing Urban Renewal, Eco-Gentrification, and Social Justice in the Gowanus Canal
Authors: Yarish Mark , Richardson Kevin
Published: February 2025

Urban renewal projects aim to revitalize neglected neighborhoods but often result in gentrification and displacement. This study examines the ongoing revitalization of Brooklyn's Gowanus Canal, a Superfund site since 2010. Using David Harvey's spatial dialectics and Giorgio Agamben's concept of bare life, it explores how environmental restoration can unintentionally drive gentrification, displacing long-term residents and attracting wealthier newcomers. Interviews with local residents, housing advocates, and real estate professionals reveal the tension between ecological improvements and social equity. While cleanup efforts have boosted property values and neighborhood appeal, they have also heightened housing pressures on low-income residents. This paper argues that equitable urban renewal requires policies balancing ecological progress with protections for vulnerable communities.
Protection
Authors: Gibbs Thomas C.
Published: February 2025

This study investigates minority COVID-19 infections in construction and minority construction worker survival post-pandemic. This qualitative study explores individuals' perceptions and experiences using phenomenology. The first questionnaire was distributed to 20 California minority construction professionals (MCP). Ten self-identifying construction minorities were recruited for this study based on the questionnaire. The ten participants then shared their stories in semi-structured interviews. As a result, this study's themes and patterns demonstrate that the participant's interviews uncover valuable evidence-based model knowledge. The construction industry can use this research to 1) mitigate MCP issues, 2) use the collective impact model to form transformational alliances with place-based initiatives, major construction industry players, and academia, and 3) gather undetermined data, connect key stakeholders, and form coalitions through data gathering campaigns.
Harnessing Technology and Leadership for Sustainable Agri-Food Supply Chains
Authors: Roy Mallika
Published: February 2025

The agri-food supply chain is undergoing a shift towards sustainability through technology, leadership, and circular economy practices. This chapter explores how advanced technologies like IoT, blockchain, AI, and precision agriculture enhance sustainability. It examines leadership's role in fostering circular economy principles and addresses challenges such as high costs and complex integration. Case studies from various countries demonstrate successful technology-driven sustainability. Key findings reveal both significant challenges and opportunities for innovation, collaboration, and policy support. The chapter concludes with recommendations for supply chain actors and policymakers and suggests future research directions to advance sustainability in the agri-food sector.
Navigating the Mobile Learning Landscape in Education
Authors: Joshi Richa , Bhatia Raino , Kour Jagneet
Published: February 2025

The goal of this proposed chapter is to look deeply into mobile learning (m-learning) and give teachers, school leaders, and policymakers helpful ideas to lead well in the digital age. In a time when mobile devices are everywhere and people want more flexible ways to learn, it's really important for school leaders to understand m-learning. This chapter wants to give leaders lots of practical tips to help them use mobile technology in schools. Also, making sure everyone can use mobile devices, finding better ways to teach, using technology well, being sensitive to different cultures, keeping things going for the long term, checking how well things are working, and involving everyone who's interested. This chapter hopes to give school leaders a big toolbox they can use to make m-learning work really well in schools. will provide light on innovative management approaches that incorporate educators, families, and the broader community in designing and carrying out of m-learning programs.
Advancing Supply Chain Innovation
Authors: Taghipour Atour , Lu XiaoWen
Published: February 2025

Supply chains, the intricate networks connecting raw materials, manufacturing, distribution, and consumption, have evolved into complex systems that significantly influence organizational performance. This chapter is a literature review that delves deeper into the conceptualization of supply chain innovation, its theoretical foundations, key dimensions, research findings, and contemporary advancements. It identifies research gaps and provides actionable insights for researchers and practitioners seeking to drive innovation in their supply chain operations.
Navigating the Artificial Intelligence Era
Authors: Taghipour Atour , Lu XiaoWen
Published: February 2025

Artificial intelligence (AI) has rapidly evolved from a theoretical concept to an integral part of daily life. This chapter examines AI's impact on the development of critical thinking, consumption habits, career prospects, mental health, and ethical considerations among younger generations. The easy accessibility of AI-generated responses raises concerns that youth may increasingly depend on AI, potentially diminishing independent reasoning skills. This reliance has led educational systems to implement AI-detection tools to limit overuse in assignments, aiming to promote students' critical thinking and academic integrity. The chapter concludes with recommendations for ethical AI use and suggests perspectives for future developments.
Revolutionizing the Sustainable Supply Chain of Medical Product With AI-Driven Drone Delivery
Authors: Gowsalya M. , K. N. Mayuri
Published: February 2025

The integration of artificial intelligence with drone technology is transforming sustainable supply chain management in the field of healthcare, addressing significant difficulties in medical product delivery. This chapter explores the connections between AI and drones, emphasizing developments such as autonomous navigation, real-time monitoring, and enhanced path planning to optimize delivery routes and increase sustainability. AI-integrated drone technology helps to promote sustainability by reducing emissions and energy consumption while providing cost-effective alternatives to existing transportation modes. A mathematical framework is proposed to optimize cost, time, emissions, and energy consumption, resulting in efficient and sustainable healthcare supply chains. Future improvements, such as autonomous drone swarms, renewable energy integration, and improved AI-driven decision making, promise to significantly transform this field. By utilizing the transformative potential of AI-powered drone delivery systems improves sustainability and scalability in the healthcare sector.
The Role of Governments, Employers, and Platforms to Cope With the Skill Gaps in Industry 4.0
Authors: Mood Mohammad Mirkazemi , Ghamary Mohammadhosein , Youshanlouei Hossein Rahmany
Published: February 2025

Industry 4.0 transformations are exacerbating the skills gap, but they also present technological solutions to help bridge this disparity. Successfully taking advantage of Industry 4.0 to reduce the skills gap requires preparedness and the implementation of strategic initiatives by key actors. This chapter provides an overview of research that offers potential solutions for addressing the skills gap in the context of Industry 4.0. The methodology used is a systematic literature review. Fourteen solutions have been identified for addressing the skills gap among the three main stakeholders: governments, employers, and HR techs. These initiatives were categorized into 37 sub-themes. Based on primary and secondary themes, mappings were created to align the identified solutions from the literature, providing a roadmap for future research efforts. In the end, comprehensive recommendations were made for addressing the skills gap within the Industry 4.0 landscape, tailored to each respective stakeholder.
AI Methodologies in Upcoming Modern Warfare Systems
Authors: Gaikwad Swapnali Pravin , Davda Yatri
Published: February 2025

Modern AI methodologies are changing the face of warfare by enabling militaries to enhance their operational capabilities and, more importantly, their decision-making in executing the operations. Advanced technology with machine learning, natural language processing, and autonomous systems enable real-time data analysis, predictive modeling, and increased situational awareness on the battlefield. With such problematic challenges facing the military forces, AI integration provides strategic advantages over military departments for rapid responses to emerging threats and resources distribution. However, this evolution raises issues on accountability, bias, and implication of autonomy in decision-making for combat scenarios. Overall, therefore, AI methodologies are going to redefine the nature of warfare and hence it becomes highly important for military leadership to navigate through these opportunities along with the risks arising from such technologies.
Exploring Information Technology (IT) Acceptance Among Supply Chain Stakeholders in Morocco's Pharmaceutical Industry
Authors: El Moussaoui Taoufiq , Chakir Loqman , Eddine El Moussaoui Alaa
Published: February 2025

This chapter explores the determinants of information technology (IT) acceptance in Moroccan supply chains within the pharmaceutical sector, focusing on the role of digital transformation in fostering collaboration and information sharing. To address this objective, a quantitative methodological approach was employed, combining descriptive analysis and logistic regression. The findings reveal a limited adoption of digital technologies in supply chain activities. However, they underscore that these digital transformation initiatives are essential prerequisites for enhancing cooperation and improving the sharing of logistics information. Practical implications, study limitations, and directions for future research are discussed at the end of the chapter.
Extended Reality and Security
Authors: Kathole Atul B. , Davda Yatri , Soitkar Nupur
Published: February 2025

VR, AR, and MR are evolving XR technologies impacting industries like healthcare, education, and collaboration. However, XR's integration of real and digital worlds introduces unique security challenges due to the handling of sensitive data, including biometrics and behavioral patterns. Emerging technologies like AI, edge computing, and 5G increase XR's potential but also its vulnerability to cyber threats. XR security, combining traditional and innovative measures, is critical to safeguarding these platforms as they become more widely adopted.
Predicting E-Consumer Preferences for Collection and Delivery Points Using Deep Learning
Authors: Eddine El Moussaoui Alaa
Published: February 2025

Collection and delivery points (CDPs) are crucial for addressing last-mile logistics challenges, particularly with the rapid growth of e-commerce. This study examines factors influencing e-consumers' preferences for CDPs in Morocco, using deep learning (DL) algorithms to develop a predictive model. A dataset of 3,000 responses, including age, income, and accessibility to CDPs, was used to train the models. Convolutional neural networks (CNN), long short-term memory (LSTM), and FT-transformer were employed to classify preferences. Hyperparameter tuning optimized these models, with the FT-transformer achieving 92% accuracy, outperforming CNN and LSTM. The findings offer actionable insights for logistics providers to better meet consumer needs, enhancing satisfaction and operational efficiency. The chapter also discusses the study's limitations and suggests future research directions in last-mile logistics.
The AI Revolution Implications for Workforce Dynamics and Employment in Supply Chains
Authors: Chandratreya Abhijit
Published: February 2025

This chapter examines the impact of artificial intelligence (AI) on workforce dynamics and employment within supply chains. As AI technologies become increasingly integrated into supply chain operations, they are reshaping job roles, skill requirements, and organizational structures. The chapter explores the dual nature of AI's influence, highlighting both the opportunities for efficiency and innovation and the challenges related to job displacement and workforce adaptation. Through case studies and analysis of current trends, the chapter provides insights into how businesses can strategically manage the transition toward AI-enhanced supply chains. Emphasis is placed on the importance of upskilling and reskilling initiatives to ensure workforce resilience and sustainability in this new era.
Leveraging Digital Tools to Enhance School Counselling
Authors: Ansarullah Syed Immamul , Islam Muhammad Idreesul , Begum Gazala , Bhat Nayeem Ahmad
Published: February 2025

Digital technology transformed the field of school counselling and offered new opportunities to enhance the accessibility, effectiveness, and inclusivity of services provided to students. Digital tools like artificial intelligence, virtual reality, augmented reality, data analytics, and social media are explored into school counselling practices. The examination of case studies and emerging trends highlight the potential of these technologies to identify at-risk students, provide timely and personalised interventions, and expand access to counselling services. This research discusses the ethical and legal challenges that accompany the use of these technologies. Moreover, the chapter provides actionable recommendations for school counsellors, educators, and policymakers, focussing on the need for collaboration, reliable technology infrastructure, and ongoing evaluation of digital tools to ensure they meet the evolving needs of students.
Educational Application and Games for Specific Skills Development
Authors: Özmen Erhan
Published: February 2025

This chapter addresses the transformative role of educational apps and games in the development of cognitive, social, emotional, motor and technological skills. Digitalised education promotes 21st century competences such as problem solving, critical thinking and collaboration, while increasing interactivity, motivation and individualised learning. Applications such as Duolingo and Kahoot make learning interactive and fun with reward and challenge systems. Tools such as virtual reality contribute to the development of motor skills, while platforms such as Tynker support cognitive growth. Social-emotional learning applications such as ClassDojo develop empathy and self-regulation skills. The chapter highlights the theoretical underpinnings of these innovations, such as constructivism and motivation theories, while also highlighting challenges such as the need for pedagogical alignment and cultural adaptation. It also sheds light on the potential of educational apps and games to create engaging, motivating learning environments.
The Impact of Social Media on Mental Health
Authors: Premavathi T. , Jain Rituraj , Parmar Kumar J. , Palaniappan Damodharan
Published: February 2025

The article investigates the complicated link between social media and the psychological well-being of this cohort, bringing out both positive and negative aspects. Social media acts as a source of connection, self-expression as well as education while it is also associated with effects such as anxiety, depression, cyberbullying and distorted body image. Due to constant comparison with others, exposure to unrealistic ideals and opportunities for negative relationships among peers; children are highly susceptible to its adverse effects. This paper looks at how digital technology can be used in counselling and supporting students dealing with these challenges related to mental health. Some of these platforms include online counselling sites, m-Health apps, and AI-driven tools which have been identified in recent research studies or theories that make it easier for children to get personal support when they need it through offering accessible professional help early enough not only at affordable costs but also on time.
Leveraging Social Networks to Foster Peer Support Among Individuals With Disabilities
Authors: Madeline Amelie
Published: February 2025

Social networking platforms have greatly changed the way individuals interact, relate to, and share information. This chapter explores the different roles social networks play in facilitating peer support for individuals with disabilities, both at a conceptual and practical level. The discussion begins with a historical timeline that traces the emergence of social learning theories from digital platform development, where various categories of social networks directed towards peer support are delineated. The text also elaborates on the numerous benefits brought about by social networks as well as the risks this integration may cause. Besides, it gives an idea of successful implementations of social networks through case studies. The proposed analysis empowers policymakers with useful insights and action plans for implementing social networks that can facilitate persons with disabilities in order to encourage more interactive, collaborative, and digitally literate online environments.
Philosophical Counseling for the Modern Dilemma
Authors: Maurya Sooraj Kumar
Published: February 2025

In the modern digital age, where technology permeates every aspect of human life, individuals confront unique existential crises related to identity, meaning, & authenticity. As traditional boundaries between the physical and virtual worlds blur, the search for purpose and self-understanding becomes increasingly complex and multi-layered. The article deals with the potential of digital platforms to facilitate philosophical counseling, providing a framework for addressing these modern dilemmas. By integrating the traditional philosophical tools and techniques to digital mediums, counselors can offer more accessible and effective support, helping clients navigate the challenges of the digital era. The article compares the efficacy of digital and traditional counseling methods, emphasizing the role of philosophical counseling in promoting digital well-being. Along with this the article demonstrates that philosophical counseling is well-equipped to help individuals achieve meaningful, balanced lives in a hyperconnected world.
Secure Video Conferencing for Virtual Counseling Sessions
Authors: Singha Ranjit
Published: February 2025

This chapter explores the integration of secure video conferencing in school counseling, emphasizing its benefits, challenges, and ethical considerations. Video conferencing enhances accessibility, allowing counselors to support students regardless of location, while fostering engagement through interactive tools. Key issues such as maintaining confidentiality, adhering to privacy regulations, and ensuring informed consent are addressed, alongside the importance of professional boundaries and ethical digital record-keeping. Training for counselors and students is highlighted as essential for effective implementation. The chapter underscores the significance of secure, inclusive virtual counseling in modern schools, balancing technological innovation with human connection. Thoughtful implementation ensures that counseling services remain accessible, secure, and tailored to students' diverse needs, advancing mental health support in evolving educational environments.
Generalized bullous drug eruption triggered by ceftriaxone: a case report and literature overview
Authors: Alfalah Khuzama , Nagshabandi Khalid Nabil , Almusa Hala Abdullah
Published: February 2025

Ceftriaxone is a widely used third-generation cephalosporin antibiotic known for its efficacy and safety. However, hypersensitivity reactions, including rare cases of generalized bullous fixed drug eruption (GBFDE), have been reported. We present the case of a 68-year-old female with a history of multiple comorbidities who developed a generalized bullous drug eruption two days after initiating intravenous ceftriaxone for a suspected respiratory infection. Clinical evaluation revealed extensive bullae and erythematous patches sparing mucous membranes, with histopathology confirming drug-induced epidermal changes. Direct immunofluorescence ruled out autoimmune bullous disorders. Prompt discontinuation of ceftriaxone, systemic corticosteroids, and supportive topical treatments led to marked clinical improvement. This case underscores the importance of recognizing rare but severe cutaneous reactions to ceftriaxone. Early diagnosis and intervention are crucial to minimizing complications and ensuring favorable outcomes.
Rethinking interdisciplinary research ethics in the age of complexity and transformative change
Authors: Preiser Rika
Published: February 2025

No abstact applicable.
Topometric Characterization of Type Spaces in Continuous Logic
Authors: Hanson James
Published: February 2025

We show that a topometric space $X$ is topometrically isomorphic to a type space of some continuous first-order theory if and only if $X$ is compact and has an open metric (i.e., satisfies that $\{p : d(p,U) \e\}$ is open for every open $U$ and $\e 0$). Furthermore, we show that this can always be accomplished with a stable theory.
Klebsiella pneumoniae isolated from the intestines of Tenebrio molitor larvae (Coleoptera: Tenebrionidae) that consume expanded polystyrene
Authors: Caruajulca-Marin Luis , Huamán-Ventura Katherin , Sánchez-Purihuamán Marilín , Caro-Castro Junior , Barturén-Quispe Ada , Vásquez-Llanos Segundo , Carreño-Farfán Carmen
Published: February 2025

Plastics such as polystyrene are resistant to biodegradation, pollute the environment, and negatively impact the health of living organisms. However, several organisms, such as the larvae of Tenebrio molitor (Coleoptera: Tenebrionidae) and their associated gut microbiome, contribute to its degradation. The aim of this research was to determine the efficiency of degradation of expanded polystyrene (EPS) by gut bacteria isolated from larvae of T. molitor. To achieve this, a set of EPS-degrading bacteria was selected based on the time required to utilize the polymer as a carbon and energy source. Additionally, EPS degradation efficiency was compared, and the most efficient degrading bacterium was identified at the molecular level. Results showed that 95.13% of the bacteria isolated on nutrient agar and 86.57% of those isolated on MacConkey agar were able to grow on EPS. Five selected bacteria were able to degrade the polymer after 36 hours of incubation. The efficiency of EPS degradation, expressed as the percentage of weight loss by the degrading bacteria, ranged from 5.29% to 12.68%, with a reduction rate of 0.0005 to 0.0013 g per day and a half-life of 533.15 to 1386.20 days. Finally, 16S rRNA gene analysis identified the bacterium as Klebsiella pneumoniae. Cultivable gut bacteria from T. molitor larvae have demonstrated potential as candidates for EPS degradation, and biotechnological techniques can further enhance the efficiency of the degradation process.
Keywords: biotechnological techniques, gut microbiome, polystyrene degradation.
Secure nonorthogonal multiple access with energy harvesting‐assisted full‐duplex receivers
Authors: Le‐Thanh Toi , Ho‐Van Khuong
Published: February 2025

This paper investigates securing nonorthogonal multiple access (NOMA) by leveraging receivers equipped with full‐duplex (FD) communication and energy harvesting (EH) capabilities. These receivers decode their intended information while simultaneously jamming eavesdroppers using harvested energy, aiming to achieve high security, energy efficiency, and spectral efficiency. The study analyzes the proposed NOMA scheme with EH‐assisted FD receivers across various key performance metrics for a quick performance assessment. The proposed analysis is validated through simulations, which demonstrate the influence of the proposed model on multiple specifications. Furthermore, the proposed model is shown to be considerably more secure than the conventional orthogonal multiple access (OMA) with EH‐assisted FD receivers, revealing the advantages of NOMA over OMA.
Study of Dermal Nerve Pathology in Upgrading and Downgrading Type 1 and Type 2 Leprosy Reactions
Authors: Sharath Savitha , Ahuja Arvind , Sinha Surabhi , Sardana Kabir
Published: February 2025

Nerve destruction is central to the pathogenesis and clinical manifestation of leprosy reactions (LRs). However, pathological changes in dermal nerves in LRs have not been clearly elucidated. Hematoxylin and eosin (H&E) staining may fail to accurately identify fragmented nerves, and special stains may be required. We recruited 56 patients with clinically diagnosed LRs as cases and 30 patients with nonreactional leprosy as controls. Number and level of nerves, nerve edema, relation of granulomas to nerves, perineuritis, pattern of nerve involvement, and quantification of each nerve pattern were noted on H&E stain and S-100 immunostain on skin biopsy sections. Most of the cases were borderline tuberculoid (BT; 32.8%) and lepromatous leprosy (32.8%) types, whereas most controls were classified as BT (44.8%). We found greater dermal nerve infiltration, fragmentation, and destruction during reactions when compared with nonreactional leprosy (fragmented nerves on S-100: P <0.0001). Nerve fragmentation (P = 0.037), subcutaneous nerve involvement (P = 0.014), and severe nerve edema (P = 0.0005) were higher in type 2 reaction (T2R) compared with type 1 reaction (T1R; on S-100), mostly attributed to the higher number of severe T2Rs (n = 23/25) among our cases. Intact nerves were higher in downgrading T1R compared with upgrading T1R (P = 0.038 on H&E and P = 0.004 on S-100). Thus, the identification and quantification of different patterns of nerves using special stains, such as S-100, may shed more light on nerve fiber involvement and destruction in LRs and may help us predict the prognosis of such cases.
Association of Diabetes Mellitus with Presentation and Treatment Outcomes among Adult Patients with Pulmonary Tuberculosis
Authors: Kumar Rakesh , Singh Urvashi B , Chandra Ankit , Kandasamy Devasenathipathy , Krishnan Anand
Published: February 2025

This prospective study was done to compare the initial presentation and treatment outcomes of tuberculosis among adult patients who have diabetes mellitus with those without diabetes mellitus. In this study, all adult patients (age 18 years old or older) with microbiologically confirmed drug-sensitive pulmonary tuberculosis who were put on treatment in Ballabgarh block in Haryana were enrolled. Information on clinical, radiological, and microbiological parameters at baseline was obtained by interview or record review. Symptom score was calculated by assigning one point for each symptom from zero to seven. Patients were followed for 6 months from the start of treatment to assess treatment outcomes. Data were analyzed using the χ2 or Fisher exact test. Logistic regression was used to assess the factors associated with death or unfavorable outcomes. In total, 412 patients were included in the study, of which 17.5% had diabetes mellitus. The mean symptom scores among those with and without diabetes were 3.7 (SD 1.3) and 3.6 (SD 1.4), respectively. Treatment success was achieved in 83.6% of patients with diabetes and 86.4% of patients without diabetes. Death was observed in 12.3% of patients with diabetes compared with 7.1% of patients without diabetes. There was no significant difference in clinical presentation, radiology, or sputum smear grade at baseline between patients with or without diabetes. Although treatment success rate was less and death rate was higher in patients with tuberculosis who had diabetes compared with those who did not have diabetes, the difference was not statistically significant.
Vehicle Trajectory and Traffic Conflict Prediction at Urban
Expressway Confluence
Authors: Liu Tiansheng , Xiang QiaoJun
Published: February 2025

The urban expressway ramp entrance has always been one of the traffic accident
prone areas. At present, most of the traffic safety research focuses on the
intersection traffic conflict prediction analysis, so it is necessary to conduct
related research on the urban expressway ramp entrance traffic safety. In this
paper, we focus on trajectory prediction and traffic conflict analysis between
straight vehicles and ramp vehicles on main roads for small data sets. Firstly,
the transformer model and LSTM model were used to predict the trajectories of
the straight vehicle on the main road and the vehicle at the entrance of the
ramp respectively. TTC is calculated from the predicted trajectories of straight
vehicles on the main road and confluence vehicles on the ramp. Then, the
historical features are used to predict the future TTC by using LSTM plus
self-attention mechanism, and the two conflict prediction methods are compared.
The results show that in the case of small data sets, the prediction results are
better using neural networks.
Tunnel Traffic Anomaly Detection via Multi-Modal LLMs
Authors: Liu Hongyu , Zhou Ruohan , Bai Jiayang , Li Yuanqi
Published: February 2025

Tunnels play a crucial role in urban transportation, yet they frequently
encounter various incidents during operation. Manual video inspections and
sensor-based systems are inefficient and limited in accurately detecting and
addressing these issues. The emergence of artificial intelligence has led to the
development of object detection models such as YOLO, which have shown promise in
real-time anomaly detection. However, these single-modality models achieve
suboptimal results when dealing with complex events. Multi-modal large language
models (LLMs) offer a potential solution, with their ability to process and
understand information from different modalities. This paper develops a novel
tunnel traffic anomaly detection method that combines single-modal models and
multi-modal LLMs. The proposed system first employs YOLO for an initial
detection round and then utilizes a specially designed LLM with an effective
prompt and a data filtering strategy tailored for traffic tunnel scenarios. This
two-step approach enables the system to detect anomalies such as fires and
ponding water, facilitating real-time monitoring of tunnel conditions and
maintaining traffic flow. We are the first to introduce a well-designed
multi-modal LLM into tunnel traffic anomaly detection, for real-time and
accurate detection. We create a tunnel-specific algorithm that covers model
design, prompt strategy, and detection logic, effectively handling complex
weather and traffic scenarios. The system has demonstrated an accuracy rate of
up to 90% in detecting numerous surveillance cameras simultaneously, reducing
labor costs and potential economic losses associated with tunnel incidents. Our
research thus aims to enhance tunnel safety and efficiency through an innovative
and effective anomaly detection system.
Regulatory and Policy Framework for Urban Drone Logistics
Systems
Authors: Ma Jie , Yang Junjie , Diao Weile , Du Yiling , Chen Weiqi
Published: February 2025

The swift and relentless progression of drone technology has ushered in novel
opportunities within the realm of urban logistics, especially for the potential
of drones to modify last-mile delivery and improve customer fulfillment through
mobile application integration, offering the potential for delivery systems that
are both efficient and environmentally sustainable. This development is not just
a technological leap but a transformative shift in how goods are moved within
urban spaces, potentially reducing traffic congestion and emissions from
traditional vehicles. Nevertheless, the safety issues of drone flights in cities
are becoming increasingly serious, and the accountability related to drone
accidents is not clear, raising concerns in society regarding the use and safety
of drones. Therefore, to fully utilize the potential of drones in urban
logistics, the incorporation of drones into the urban airspace environment
necessitates the establishment of a strong regulatory and policy framework, one
that is capable of addressing a multitude of concerns, including safety,
security, environmental impact, and social equity. This particular research
paper undertakes a detailed examination of the existing regulatory landscape
that pertains to urban drone logistics systems. It aims to pinpoint the primary
challenges that are currently faced in this domain, and subsequently proposes a
comprehensive policy framework designed to facilitate the effective
implementation of urban drone logistics. To achieve a thorough understanding of
the subject matter, this study meticulously reviews and analyzes more than 30
scholarly articles, industry reports, and policy documents, synthesizing the
insights gained to provide a well-rounded perspective and policy framework
suggestions on the topic.
Vehicle Positioning Technology Based on Stereo Vision
Authors: Feifei Li , Haoping Qi , Yi Wei
Published: February 2025

Vehicle localization in enclosed environments, such as indoor parking lots,
tunnels, and confined areas, presents significant challenges and has garnered
considerable research interest. This paper proposes a localization technique
based on an onboard binocular camera system, utilizing binocular ranging and
spatial intersection algorithms to achieve active localization. The method
involves pre-deploying reference points with known coordinates within the
experimental space, using binocular ranging to measure the distance between the
camera and the reference points, and applying the spatial intersection algorithm
to calculate the camera’s center coordinates, thereby completing the
localization process. Experimental results demonstrate that the proposed
algorithm achieves sub-meter level localization accuracy. Localization accuracy
is significantly influenced by the calibration precision of the binocular camera
and the number of reference points. Higher calibration precision and a greater
number of reference points contribute to improved localization accuracy. Through
experiments, the feasibility and effectiveness of the proposed algorithm are
validated, and key factors affecting localization accuracy are analyzed. This
technology is an active localization technique, particularly suitable for indoor
environments where GNSS signals are obstructed. Its advantages include low
deployment costs and ease of implementation, providing an effective solution for
indoor localization. This approach holds significant theoretical and practical
value for addressing object localization challenges in obstructed
environments.
Study on the Minimum Diversion Decision Distance of Autonomous
Vehicle on Freeway Based on Lane-Changing Trajectory Modelling
Authors: Li ZhenFa , Luo BaoGuo , Yang Qi , Chen Xu , Pan BingHong
Published: February 2025

Most autonomous vehicles employ a relatively conservative lane-changing strategy
in freeway system. In the diversion areas, autonomous vehicles typically
initiate lane-changing to curb lanes at lower speeds at a considerable distance
from the diversion point, resulting in a decrease in the overall traffic
efficiency within the diversion areas. However, lane-changing decision points
excessively close to exit ramps can exacerbate the urgency of the lane-changing
process, prompting irrationally forced lane-changing and increasing the
collision risk. To provide decision-making references for the safe and rapid
diverging of autonomous vehicles in freeway diversion areas, this study proposes
a minimum diversion decision distance (MDDD) model for autonomous vehicles
through microscopic lane-changing trajectory data. Specifically, the
lane-changing process was divided into waiting for the acceptable gap stage and
executing the lane-changing stage in this model. Subsequently, UAV aerial
photography and YOLOv5 target detection algorithm were used to measure traffic
flow data and lane-changing trajectory data in diversion areas. The shifted 2nd
Erlang model was used to fit the probability distribution of the time headway in
diversion areas, and the acceptable gap waiting acceptable gap distance
prediction model was constructed by analyzing the microscopic lane-changing
behavior. A modified hyperbolic tangent model was utilized to fit the
lane-changing trajectories of vehicles, used to estimate the distance for
autonomous vehicles executing a lane-changing under different conditions. By
defining the critical parameters of the model, the minimum diversion decision
distance for autonomous vehicles for freeway with different design speed was
obtained. The results indicate that the minimum diversion decision distance is
related to the vehicle lane-changing trajectory and time headway distribution,
and when the distance between the autonomous vehicle and the starting point of
the ramp gradient section is farther than the MDDD, the diversion decision needs
to be completed as soon as possible.
Space-Time Evolution of Temperature of Asphalt Mixture during
Transportation
Authors: Cheng Hao , Ma Tao , Tang Fanlong , Fan Jianwei
Published: February 2025

Temperature segregation significantly affects the compaction of asphalt mixtures
and the durability of the asphalt pavement layer. Uneven cooling of the mixture
during transportation is a key factor contributing to temperature segregation.
This study uses finite element simulations to analyze the temporal and spatial
temperature evolution during the transportation of asphalt mixtures. A
temperature segregation evaluation index (TSIv) is proposed to
assess the significance of various factors affecting segregation. Support vector
regression (SVR), random forest regression (RFR), and extreme gradient boosting
(XGBoost) models are employed to predict temperature changes during
transportation and optimize the predictive models. The results indicate that the
proportion of areas with a temperature difference of less than 10°C is
consistently the highest, followed by areas with a temperature difference
greater than 25°C, and then those with temperature differences in the ranges of
10-16°C and 16-25°C. Higher discharge temperatures, higher convective heat
transfer coefficients, and lower air temperatures are associated with greater
temperature segregation. In the early stages of transportation, the discharge
temperature has a slightly greater effect than air temperature and convective
heat transfer, whereas in the later stages, convective heat transfer plays the
most significant role. Both the SVR and RFR models can effectively predict the
distribution of various temperature ranges during asphalt mixture
transportation.
Design of a Ship Path Planning Scheme Incorporating Wind and Current
Effects with COLREGS Compliance
Authors: Shangqing Feng , Jinli Xiao , Langxiong Gan , Geng Chen , Hui Li , Guanliang Zhou
Published: February 2025

Path planning algorithms are critical technologies for intelligent ship systems,
as scientifically optimized paths enable safe navigation and efficient avoidance
of waterborne obstacles. To address the limitations of current ship path
planning models, which often fail to adequately consider the combined effects of
wind, current, and the International Regulations for Preventing Collisions at
Sea (COLREGS), this study proposes an enhanced path planning method. The method
integrates environmental factors, such as wind and current, and COLREGS into an
improved Artificial Potential Field(APF) framework. Specifically, the influence
of wind and current is modeled as "environmental forces," while the navigation
constraints imposed by COLREGS are transformed into virtual obstacles,
generating corresponding repulsive forces to refine the algorithm. Simulation
experiments conducted under both single-ship and multi-ship scenarios validate
the feasibility and effectiveness of the proposed approach, demonstrating its
potential to align planned paths more closely with real-world navigational
conditions.
Interaction of the economies of Asia-Pacific region in the AUKUS alliance
Authors:   Diplomatic Academy of the Ministry of Foreign Affairs of Russia, Kharlanov Aleksey S. , Molchanov Ivan ,   Diplomatic Academy of the Ministry of Foreign Affairs of Russia
Published: February 2025

Introduction. The relevance of the present research lies in the importance of the Asia-Pacific region (APAC), an international trade and investment hub, making its transformation significant for the world economy. Increasing economic growth and strengthening the Asia-Pacific community in the context of the AUKUS alliance is essential for understanding contemporary global processes and their impact on the future.

The article aims: to study the interaction of the economies of APAC in the conditions of the AUKUS alliance.

Materials and Methods. Publications in peer-reviewed journals on economics, international relations, security, and politics were used. Research methods included analyzing official documents and comparing AUKUS with other blocs and alliances to assess differences and similarities in approaches to security.

Results. Construction of a new economic order in the countries of the modern Silk Road becomes a determining factor for forming anti-Western financial space, attracting investments, and spreading the Celestial Empire’s soft power.

Conclusion. The AUKUS alliance significantly affects the economic interaction between the countries of APAC, creating new opportunities and causing potential threats for both the alliance members and independent countries of the area.