bluuebunny/crossref_metadata_2025 huggingface dataset:
La gestion des obstacles juridiques dans l’établissement de corpus connexes de genres spécialisés : l’exemple de TACATrad et DisTrAs sur l’activité de traducteur assermenté
Authors: Serrano Florence
Published: January 2025

Les résultats issus de l’analyse des corpus spécialisés TACATrad et DisTrAs ont pour vocation de converger vers une vaste compréhension de l’activité des traducteurs assermentés. À l’issue du travail préliminaire à la constitution des corpus TACATrad et DisTrAs, il apparaît que le respect du RGPD et les termes juridiques de la relation contractuelle entre un prestataire de service (réseau social) et un client usager contraignent nos recherches. Les données textuelles sont anonymisées dès collecte et nous avons renoncé à collecter des TACATs médicaux pour être en conformité avec le RGPD. Par ailleurs, au vu de la diffusion non publique de posts sur des réseaux sociaux que nous collecterons pour constituer le sous‑corpus DisTrAsR et du volume textuel raisonnable (qualitatif), nous optons pour une extraction manuelle ciblée de posts, à partir d’un compte personnel d’utilisateur dédié à cette recherche, et pour une anonymisation simultanément à la collecte. À l’issue de cet article, il apparaît que la mise en conformité avec différents dispositifs législatifs de protection des données peut constituer un biais scientifique pour la constitution de corpus spécialisés, même s’il est possible d’en limiter l’impact en développant d’autres outils, comme une taxinomie et une base de données et en modulant l’extraction des données.
Les coulisses de l’énergie dans les Chroniques italiennes : croyance, incroyance et surhumanité
Authors: Huttenberger-Revelli Charlène
Published: February 2025

Comment lire les Chroniques italiennes ? Sommes-nous face à une œuvre religieuse ou antireligieuse ? Comme c’est bien souvent le cas chez Stendhal, il n’y a pas de réponse univoque à cette question. En effet, qu’il s’agisse pour eux de croire de manière démesurée ou au contraire de ne pas croire et de haïr la religion, les personnages des Chroniques déploient dans tous les cas des trésors d’énergie qui outrepassent les bornes de la morale et s’épanouissent dans le scandale et la transgression. Ainsi, c’est à travers la peinture des extrêmes, de la révolte athée et anticléricale à un héroïsme de la croyance, que Stendhal, ce « catholique-athée » pleinement romantique, exprime une admiration jamais démentie pour les individus forts, passionnés et excessivement énergiques.
Topo-esthétique de Suora Scolastica
Authors: Bourdenet Xavier
Published: February 2025

Avec Suora Scolastica, ultime « chronique italienne », Stendhal affronte un problème de poétique : comment, selon ses propres termes, « inventer quelque chose d’honnête qui ne soit pas plat et illisible » ? L’hypothèse que défend cet article est que cet intérêt passe prioritairement dans Suora Scolastica par la scénographie de la nouvelle. Il tient à la construction de l’espace et à son pouvoir évocateur, à la manière dont les lieux, leur organisation et leur description, tout comme les positions et interactions des acteurs dans ces lieux, agissent sur la sensibilité du lecteur et favorisent son immersion dans l’histoire. C’est ce qu’on entend par topo-esthétique : le caractère multidimensionnel de l’espace qui, articulé à la donnée affective de l’intrigue, détermine la qualité de l’expérience sensible du lecteur.
Du « triste résultat de la manie de régner ». L’Abbesse de Castro ou la représentation mouvante des tyrannies patriarcales
Authors: Nizard Lucie
Published: February 2025

L’Abbesse de Castro, qui raconte les amours d’une jeune fille intrépide et d’un brigand, s’attaque entre les lignes aux actes et aux discours qui prétendent instaurer un contrôle viril sur les corps des femmes. Aux marges de la masculinité toute-puissante et meurtrière, Stendhal ménage des espaces de transgression. La nouvelle fait apparaître, dans des rapports de pouvoir en apparence figés, du trouble et du mouvement. Mais dans L’Abbesse de Castro dominent les jeux de renversement : la sape souterraine des discours d’autorité s’élabore au sein d’une prose ironique destinée à interroger le lecteur sur l’instabilité de tous les systèmes.
Vanina et les hommes. Genre et classe
Authors: Vanoosthuyse François
Published: February 2025

Vanina Vanini est la première des nouvelles que Stendhal a publiées dans la presse. On envisage ici les enjeux idéologiques de ce texte. Trois difficultés retiennent plus particulièrement l’attention : sa signification politique, au regard de la situation de l’Italie et de la France en 1829, le motif du travestissement, qui ambiguïse le genre des deux personnages principaux, mais aussi celui du père, dans un contexte social aristocratique et patriarcal, et la dureté des rapports de classe et des rapports de genre au sein du couple.
Variations sur le thème de l’ennui dans Le Rouge et le Noir. Enjeux éthiques et sociopolitiques
Authors: Cavaliere Emiliano
Published: February 2025

Le thème de l’ennui est un lieu commun de la littérature du XIXe siècle : Chateaubriand, Musset, Baudelaire ont parmi beaucoup d’autres contribué à approfondir l’héritage de la lecture déjà rousseauiste du mal du siècle – lecture déterministe, qui en fait le plus souvent le malaise de la classe aristocratique en crise après la Révolution. Cet article s’attache cependant à étudier la singularité des figurations de l’ennui dans Le Rouge et le Noir : Stendhal, une référence moins prise en considération à l’égard de ce motif, en propose en effet une variation intéressante, qui déconstruit ce cliché littéraire sans en anéantir les contours. Loin d’être exclusivement le résultat d’un déterminisme de classe, l’ennui devient parfois le moteur de l’action des protagonistes stendhaliens : au lieu d’apparaître comme un malaise purement historico-social, il se transforme alors en instrument éthique dans les mains du sujet moderne.
Camille Pernon à la cour d’Espagne, un nouveau regard
Authors: García Pilar Benito
Published: February 2025

Pour évaluer le succès commercial de la manufacture de Camille Pernon en Espagne et sa continuité sous la direction de Grand frères, il est nécessaire d’examiner d’autres personnalités françaises qui se sont établies en Espagne, notamment avant et après la guerre franco-espagnole déclenchée à la mort de Louis XVI et la rupture des relations commerciales entre les deux pays entre 1793 et 1795. Parmi elles, Claudio Bodoy, marchand installé en Espagne depuis plusieurs années, ainsi que Jean-Antoine Michel - Juan Antonio Miquel - qui a été envoyé par Pernon pour établir, avec l’appui royal, une manufacture à Valence, une ville à la longue tradition de tissage en Espagne depuis le Moyen Âge. Ces relations franco-espagnoles ont permis l’arrivée précoce du mécanisme Jacquard en Espagne en 1818. Les relations de ces figures avec la cour de Madrid, les commissions royales réparties entre Lyon et les manufactures espagnoles font partie de cette étude et éclairent l’état actuel de la recherche.
An Examination of the Impact of Artificial Intelligence on Maritime Port Efficiency and Businesses
Authors: Osundiran Adeola Oluwatoyin , Makgopa Tshehla
Published: January 2025

This study examines the impact of AI on the Port efficiency of selected ports in Europe, Asia, and North America. Inefficiency at the Ports has a detrimental effect on importers and exporters. The study framework relies on the Benchmarking theory. Research has shown that port delays have a negative multiplier effect on the economy. This study examines the implications of AI on the port efficiency of selected smart ports in the industry, such as Singapore, Rotterdam, Hamburg, Antwerp Bruges, Montreal, Long Beach, Valencia, and Barcelona. These ports serve as a benchmark for traditional sub-Saharan African ports. The implication of AI on Port Efficiency will serve as an impetus and a benchmark for other ports in Africa to consider AI a plausible solution to the long-standing inefficiency problems plaguing ports in sub-Saharan Africa. The Malmquist Productivity Index measures these ports' efficiency and productivity for 2017-2023. The result showed that four ports, Hamburg, Singapore, Valencia, and Rotterdam, had a Malmquist Productivity Index greater than 1. These ports can be used as a benchmark for sub-Saharan African Ports that have yet to transform into smart ports. The research developed a generic transformational framework to guide traditional ports.
Effect of Sustainability Practices on Financial Performance
Authors: Gambrah James , Akoto Richard Kofi , Gachara Ng'ang'a , Awunyo-Vitor Dadson
Published: January 2025

This study examines the effect of sustainability practices on the financial performance of non-financial firms listed on the Johannesburg Stock Exchange (JSE). Using secondary data from the 2017 annual and sustainability reports of JSE-listed firms, specific indicators were selected as proxies for sustainability practices based on the firm's sustainability disclosures applying Global Reporting Initiative (GRI) standards. A cross-sectional dataset was constructed, and ordinary least squares (OLS) regression analysis was performed on data from 273 non-financial firms. The findings reveal a significant positive effect of total sustainability practices on financial performance, with each of the three sustainability dimensions. The study further observes that overall sustainability practices and disclosures among the firms analyzed are moderate, with a predominant focus on economic issues, followed by social and environmental considerations. Given these results, it is recommended that firms intensify their sustainability initiatives across all three dimensions to enhance financial performance.
The Impact of Corporate Environmental Performance on Consumer Purchasing Patronage
Authors: Siwela Witness
Published: January 2025

South African companies are perceived to be ceding their competitiveness to their global counterparts partly due to their reluctance to embrace effective corporate environmental practices. Probing the responsiveness of one key stakeholder (consumers), the study aimed to determine if corporate environmental performance lures stakeholder support. Adopting a positivist stance, a quantitative research design was employed in the study. Archival data were collected from companies listed in the FTSE/JSE Responsible Investment Index, to compute a short panel data set for statistical panel data analysis. The study adopted the first differenced econometric models in data analyses. Findings reveal that all explanatory variables for corporate environmental performance yielded a significant positive effect on consumer purchasing patronage. The findings contribute immensely to existing literature and current environmental practices while initiating a novel agenda for future research.
Gamification and Virtual Reality
Authors: Tariq Muhammad Usman
Published: January 2025

This chapter examines the ways in which digital tools like virtual reality (VR) and gamification are changing how young children learn languages. In early childhood education, especially in language development, it highlights the growing significance of digital pedagogy. While virtual reality (VR) creates immersive learning environments that make language acquisition more contextual and dynamic gamification which turns lessons into enjoyable interactive games motivates kids and encourages deeper engagement. As it highlights the cognitive social and emotional advantages of digital play the chapter addresses the theoretical underpinnings of the use of these technologies. It also offers case studies and real-world illustrations of how gamification and virtual reality have been effectively incorporated into early childhood education settings. There is discussion of issues like teacher preparation and accessibility along with solutions to common problems.
Use of Media in Preschool Education
Authors: Ponomarenko Tatyana , Proshkin Volodymyr , Shynkar Tetiana , Holovatenko Tetiana
Published: January 2025

The article discusses the peculiarities of using media in preschool education amidst the war in Ukraine. It analyses scholarly research on using traditional and innovative media in teaching preschool children. The research employs a pre-test and post-test study design. The paper aims to study the features and level of development of cognitive activity in six-year-old children and the ability of educators to use media. It presents the experience of using media in various forms of interaction between educators and children and professional training of educators on the possibilities of using media. The main findings indicate positive outcomes of the experimental intervention on the cognitive development of six-year-old children. The use of various media tools by educators significantly contributed to improvements in all three criteria of cognitive activity: emotional-motivational, cognitive-activity, and personality-volitional. It proves the effectiveness of using media to increase the level of development of cognitive activity of six-year-old children.
Inclusive Digital Pedagogy
Authors: Magaya Marilyne Zivanai , Petro Fortunate
Published: January 2025

Early childhood education is vital for children's foundational development as it lays the foundation for cognitive, social, and emotional development. The main research questions focused on how teachers incorporate inclusive digital pedagogy into their teaching practices and challenges encountered in implementing inclusive digital pedagogy. This was an empirical study based on explanatory mixed methods sequential approach using closed questionnaires, in-depth interviews and lesson observations. Most of the ECD teachers interviewed showed preference towards traditional, physical activities and interactions. In conclusion, there are two contradictory findings (progressive and regressive philosophies) among teachers The study advocates for teachers' mastery of a variety of inclusive digital pedagogical skills. It also advocates for teachers to be familiar with current research on learner diversity and addressing their language development in the classroom. It is important to adopt universal design principles in implementing inclusive digital pedagogy.
SmartMeds Hub
Authors: K. S. Divya , Sim Eldhose P. , Raguraj Ashwin , Devanand Gayathri , Thomas Antony
Published: January 2025

In an aging global population, the management of medication regimens for elderly individuals presents an increasingly critical healthcare challenge. The aim of this chapter is to design and develop an automated pill dispenser system that ensures precise medication administration for elderly individuals at home, fostering medication adherence and improving health outcomes. This system is versatile and can be effectively employed in old-age homes as well as nuclear elderly households, addressing the diverse healthcare needs of this demographic. This system leverages face detection to identify patients, ensuring the right pills are dispensed to the correct individual. The audio interaction system enhances the user experience by providing audible medication reminders. The system introduces a feature that allows doctors to remotely edit medication prescriptions. These innovative features collectively establish a comprehensive and patient-centric approach to medication management for elderly individuals, significantly improving their well-being.
A Deep Learning Algorithm for Multiple Disease Prediction Using the IoT and Its Implications
Authors: Gopinath N. , Vijayakumar S. , Tamilarasan P. , Pallan Maria Pius , Jadhav Swati Dhondiram
Published: January 2025

Popular culture portrays chronic disease patients as unable to perform daily tasks and needing constant medical attention. Chronic diseases like cardiovascular disease, pneumonia, renal disease, and diabetes cause the most death and disability worldwide. These diseases are difficult to detect with regular clinical data analysis. Predicting chronic diseases earlier could save many lives. Thanks to healthcare IoT, we can monitor, assess, identify, and control many chronic diseases and provide chronic disease prevention methods. New technologies like deep learning are emerging to overcome the internet of things (IoT)'s restrictions on what can be used for the aforementioned purposes. This chapter attempts chronic disease prediction using deep learning. The authors use deep learning, feature augmentation, and convolutional neural networks to predict chronic kidney disease, diabetes, heart disease, and pneumonia. For chronic disease prediction, an integrated model using the algorithms is suggested.
The Role of Data Visualization in Industry Development
Authors: Mariadoss Kriushanth , Kumar Ashok
Published: January 2025

The digital age has ushered in a period of extraordinary data growth, reshaping industries and enabling unprecedented opportunities for innovation and business development. Sectors such as manufacturing, healthcare, finance, and retail stand at the forefront of this transformation, generating and analyzing vast volumes of data. As organizations strive to capitalize on the wealth of information available, data-driven decision-making has emerged as an essential strategy for driving growth, streamlining operations, and fostering innovation. However, the sheer scale and complexity of modern data landscapes often present significant challenges that hinder organizations from fully leveraging their data resources. These challenges range from managing diverse datasets to extracting actionable insights efficiently. In this context, data visualization has become a cornerstone of effective data utilization. It serves not merely as a means of making data visually appealing but as a critical tool for simplifying complex information and enabling stakeholders to interpret and act on data insights.
Foundations and Obstacles of Deep Learning in Healthcare
Authors: S. Lakshmi Devi , P. S. Vijaya Lakshmi , Nataraj Satheesh Kumar
Published: January 2025

Proven results show that deep learning (DL) plays a key role in smart manufacturing and logistic supply chain management. DL was effective in the healthcare sector because of its capacity to manage vast amounts of complex data with little assistance from humans. To improve the quality of care and health for patients, physicians, and other healthcare workers, deep learning (DL) is being implemented in the current healthcare system. It was discovered that DL was useful for diagnosing illnesses, detecting acute diseases, analyzing images, finding new drugs, delivering drugs, and monitoring smart health. This chapter offers a cutting-edge analysis of the DL foundations, challenges, and applications in healthcare systems to meet multi-objective aims.
Analysis on Implantable IoT Sensors
Authors: Gangadhar C. H. , Kolikipogu Ramakrishna , Santarao K. , Christopher Benita , M. S. Nidhya
Published: January 2025

Miniaturization has allowed for greater efficiency and increased power in implantable electronic devices. Glucose levels, blood pressure, and cerebral activity are just few of the many physiological characteristics that may be tracked with the use of biomedical sensors. A body area network, also known as a wireless sensor network, is primarily comprised of a set of sensors operating in tandem inside a human body. The present status of the workmanship in remote biomedical sensor correspondence and controlling frameworks are talked about in this chapter, alongside their expected applications. Additionally, up-to-date integration techniques are outlined for making the sensors smaller and well suited for implantation. For a collection of sensors to function as a BAN, they must first join forces to establish a network. At long last, versatility approaches for embedded sensors are provided, along with details on the challenges that must be overcome throughout the development of such networks.
Attacks in IoT Healthcare Wearable Sensors
Authors: Murthy A. Sampath Dakshina , M. S. Nidhya , Gurumoorthi E. , Tiwari Mohit
Published: January 2025

The internet of things (IoT) concept has recently received a lot of attention in the IT industry. It makes it easier to share data and connect to the internet. Smart surveillance, environmental monitoring, smartphones, and body sensors all make use of the internet of things (IoT). However, serious new threats to consumers' safety and privacy have emerged as a result of the internet of things' rapid growth. Due to the millions of IoT devices that are at risk, an attacker could quickly hack into an application, render it unreliable, and steal valuable user data and information. Both the architecture of the internet of things and the many forms of cyberattacks on these devices are examined in this chapter. It aims to advance IoT research by shedding light on the numerous security issues IoT is currently facing and the available security solutions we can use to make IoT devices safer. To uncover appropriate security solutions for securing IoT devices, the authors analyse them in this research across three categories: secure authentication, secure communications, and application security.
Exploring Holistic Development and HRD 5.0 in English-Medium Instruction
Authors: Bruton Charlton
Published: January 2025

This research investigates the challenges faced by Second Language students using English-Medium Instruction in a B.A. program at a Thai international college. Employing an insider practitioner research approach with an autoethnographic lens, the study examines the experiences of local L2 students as developing practitioners. Findings reveal significant language barriers, cultural differences, and limited awareness of holistic development opportunities. These challenges vary across CEFR levels, with A1 students facing the most severe difficulties and B1 students experiencing minimal challenges. To address these issues, the study recommends implementing language-sensitive development practices grounded in HRD 5.0 principles, fostering development frameworks, leveraging technology, and fostering collaboration among stakeholders. By implementing these recommendations, international programs with L2 learners using EMI can create more inclusive and effective programs that support the holistic development of international students and prepare them for success in the global job market.
The Impact of Service Automation and Robotics on Hospitality Business Models
Authors: Kumari Madhu , Kumar Suneel , Devi Nisha
Published: January 2025

This study aims to comprehensively evaluate research on the role of service automation and robots in changing business models in the hospitality industry as well as identifying research gaps and future research initiatives. To investigate how automatic services and robotics have an effect on hospitality business models and provider enterprise models, this examination uses bibliometric analysis. The findings show that service automation enhances operational reduces labor costs, improves consumer experience, and increases operational consistency and efficiency. However, challenges include initial investment costs, technological maintenance, and potential reductions in the human touch that some customer's value. This study emphasizes the use of service robots in hospitality while noting limitations and making recommendations for further research.
Digital Empowerment and Competitiveness in Businesses
Authors: Çelik Derya
Published: January 2025

The acceleration of digital transformation, the rise of technologies such as generative artificial intelligence and big data are forcing businesses to reshape the way they work. As a result of the continuous development of new technologies and the integration of these technologies into every aspect of life, it has become necessary for individuals to have digital competencies and strengthen their existing skills. For this reason, digital empowerment has become one of the main drivers of competitiveness in rapidly changing markets. The main purpose of this book chapter is to examine the impact of digital empowerment on the competitiveness of businesses from the Resource-Based View (RBV) perspective. In this context, the study examines the importance of digital transformation for employees, managers and businesses, and how businesses can use digital empowerment as a tool to gain competitive advantage.
Exploring the Role of Social Capital, Digital Transformation, and Entrepreneurial Orientation in the Sustainable Development of Creative Industries
Authors: Hosseini Elahe , Salamzadeh Aidin , Rahman Md. Mizanur
Published: January 2025

This chapter explores the effect of digital transformation and entrepreneurial orientation on the sustainable development of creative industries with the mediating role of social capital. The study's statistical population includes managers of creative industries during 2022, and the sample size is 221 managers of these companies. The data collected through a questionnaire were analyzed with PLS4 software. Results show that businesses adapt to survive in a competitive market by reducing negative impacts on society and the environment. By focusing on social capital, companies can improve relationships between team members and gain access to resources. Many businesses are investing in digital transformation, which allows creative industries to enhance relationships with the community and boost economic performance.
Digital Financial Inclusion and Entrepreneurship Growth
Authors: Erondu Ihunanya Ngozi , Ndigwe Chinedu Izuchukwu , Nnamdi Kelechi Chijindu , Oyeniran Tolulope Tolulope , Ilesanmi Helen , Maiyaki Sheneni Felix , Ekpemuaka Enameguono
Published: January 2025

This chapter examines how digital financial inclusion boosts African entrepreneurship and competitiveness. Using Esusu Africa—a FinTech company that solves the problems of informal savings schemes and financial exclusion across the African continent—as a case study, we reveal insights into how businesses across the continent can harness digital financial tools for growth. We start with Esusu Africa's approach to digital financial inclusion's fundamentals, then evaluate empirical and theoretical research. We illustrated how financial technology is increasing financial access, how digital financial inclusion affects entrepreneurship, and how financial literacy and digital finance adoption interact. We explore how digital financing boosts SME competitiveness, informal economies, and inclusive economic growth. The chapter also discusses government policies behind digital financial inclusion, the problems and possibilities it brings for informal sector enterprises, and how financial literacy may maximise these benefits.
The Use of Digital Dentistry and Invisalign in the Asansol-Durgapur Industrial Area
Authors: Mukhopadhyay Labonie
Published: January 2025

This paper examines how digital dentistry is integrated into orthodontic practices in Asansol-Durgapur industrial area, India, focusing on its effects on treatment outcomes, patient satisfaction, and practice efficiency. Using a case study approach with patient interviews and treatment records, this study highlights the benefits and challenges of digital dentistry in this industrial area. The study also investigates the influence of behavioural habits on the progression of orthodontic disorders among 310 patients, considering socio-demographic factors like age, education, sports activities, and parental income. Behavioural habits such as digit sucking, bruxism, mouth breathing, and nail biting are analyzed for their impact on orthodontic conditions. Statistical analysis shows that behavioural habits have a significantly higher influence (0.81) on the development of orthodontic diseases compared to socio-demographic variables (0.41). The research highlights the importance of incorporating behavioral assessments into orthodontic treatment planning to address challenges.
Navigating Leadership and Technology Integration in the Digital Age
Authors: Badada Bayissa , Delina G. , Krishnaraj Ramaswamy , Thiruthuvanathan Michael Moses
Published: January 2025

This chapter explores the importance of leadership in building an environment that encourages technological innovations and developments, the role of organizational leaders in inspiring employees to accept and use new technologies and the future for business organizations concerning technological advancements. Through a comprehensive literature review analysis, the need for technology embracing leaders who can adopt and help adapting to intelligent communication technologies for facilitated communication, manage the new change and implement strategic solutions have been emphasized. The chapter also includes two case analysis of Cleveland Clinic and Arizona State University demonstrating successful leadership and technology integration and a machine learning approach based on correlation matrix using SUV to assess the relationship between transformational leadership, knowledge-based work passion and organizational citizenship behaviour. The implications of this study are beneficial as it explores the multi-facets of successful technology- integrated leadership in the digital age.
Advanced Text Analysis, Simplification, Classification, and Synthesis Techniques
Authors: Vettriselvan R. , Deepan A. , Garg Prem Kumar , Suresh N. V. , Velmurugan Palanivel Rathinasabapathi
Published: January 2025

This chapter examines the significant impact of artificial intelligence (AI) on medical education, focusing on advanced text analysis, simplification, classification, and synthesis techniques. As healthcare information becomes increasingly complex, AI tools can enhance students' learning experiences by making intricate concepts more accessible. The chapter presents a conceptual and theoretical framework for integrating AI into medical curricula, emphasizing the relevance of educational methodologies and learning theories. Recommendations are provided for effectively implementing AI technologies in medical training, highlighting the importance of continuous assessment and interdisciplinary collaboration. Additionally, future research directions are discussed to explore the long-term effects of AI on educational outcomes in healthcare settings. Ultimately, this chapter advocates for a strategic approach to AI integration, ensuring that future healthcare professionals are well-equipped with the skills necessary to navigate an evolving medical landscape.
Using Artificial Intelligence in Learning Vocabulary by EFL Undergraduate Syrian Students
Authors: Kheder Khalefa
Published: January 2025

Artificial Intelligence has recently attracted the attention of academics and researchers in the field of education as a potential tool to help and improve language acquisition, notably in the improvement of learners' communication skills. The purpose of this study is to investigate students' perspectives on using AI tools in learning English vocabulary. A quantitative research design was employed by administering a questionnaire to obtain the data; 8 items were adopted from Alharbi and Khalil (2023), whereas 12 items were adopted from a study by Jomaa (2024). Then, the data was analyzed using the SPSS software application. The respondents of this study were 171 undergraduate students from English Language and Literature department at Idlib and Al-Shahbaa Aleppo universities. The findings will help attain valuable insights into how Syrian undergraduate students are leveraging AI tools for English language learning, including with regard to lexical acquisition and overall improvement in the language.
Research on Improving Preschool Teachers' Educational Research Ability Supported by Big Data Technology
Authors: Li Aiqun , Li Jiaye , Nong Lihua
Published: February 2025

The application of big data technology has brought revolutionary changes to the field of education. For preschool teachers, improving the ability of educational research not only helps to improve the quality of teaching, but also effectively promotes the all-round development of children. Firstly, this paper summarizes the application of big data technology in the field of early childhood education. Then it analyzes the current situation and existing problems of preschool teachers' educational research ability. In order to solve these problems, a series of strategies are put forward simultaneously, including strengthening the training of big data technology, establishing a data sharing platform, stimulating teachers' research interest and establishing a feedback mechanism. This study can help preschool teachers to make better use of big data technology for educational research, improve their educational research ability to a certain extent, and provide useful exploration and enlightenment for the innovative development in the future education field.
Unfolding the Potential of Generative Artificial Intelligence
Authors: Bonnet Severin , Teuteberg Frank
Published: February 2025

Scholars are increasingly using generative artificial intelligence (AI) chatbots, like ChatGPT, in research, though concerns remain about ethics, data privacy, bias, and intellectual property. This study adopts a design science research approach to explore how generative AI chatbots can support academic teaching and research, bridging theory and practice. A literature review and expert interviews identified key requirements and design principles that support virtues such as uniqueness, generalizability, and reproducibility. We also introduce a prototype, “AcademiaBot,” to demonstrate these principles in action. Our findings suggest that AI chatbots can significantly aid scholarly work if users are informed and ethical concerns are addressed. Responsible usage can help AI augment human research efforts without compromising integrity. This study provides valuable design knowledge, ensuring AI-based chatbots remain a beneficial tool for scholars.
Prognostics optical coherence tomography biomarker in macular oedema secondary to retinal vein occlusion
Authors: Silitonga Andrea R. , Silitonga Hanna T.H. , Virgana Rova , Sovani Iwan , Kartasasmita Arief , Iskandar Erwin , Ihsan Grimaldi , Indra Made
Published: January 2025

Background: Identifying biomarkers predictive of future best-corrected visual acuity (BCVA) in macular oedema secondary to retinal vein occlusion (RVO-MO) is crucial for improving risk assessment, management strategies and patient consultations.Aim: This study aimed to identify baseline optical coherence tomography (OCT) predictors of visual prognosis in RVO-MO following intravitreal bevacizumab (IVB) injection.Setting: The study was conducted at Cicendo Eye Hospital, Bandung, Indonesia.Methods: Retrospective study of 36 treatment-naïve eyes with RVO-MO (22 eyes with central retinal vein occlusion and 14 eyes with branch retinal vein occlusion). Each eye received at least three monthly IVB injections with a minimum follow-up of 4 months. Assessment of baseline OCT images focused on a 3-mm-wide retinal area centred on the fovea. Univariate and multivariate regression analyses were performed.Result: There was a significant improvement in mean BCVA from 1.15 ± 0.42 logMAR to 0.80 ± 0.55 logMAR (P  0.001) and a reduction in mean central macular thickness (CMT) from 732.2 μm ± 298.9 μm to 437.7 μm ± 352.9 μm (P  0.001). Univariate regression analysis highlighted worse baseline BCVA and higher baseline CMT as factors correlating with poorer outcomes post-treatment. Several OCT biomarkers such as disorganisation of the retinal inner layer (DRIL) and disruption of the ellipsoid zone (EZ) and the external limiting membrane (ELM) were identified but did not show significant associations with final BCVA after multivariate analysis.Conclusion: Baseline OCT biomarkers may elucidate the extent of vision loss; however, they may not be reliable in predicting treatment outcomes.
Kidney disease among adults on tenofovir-based second-line antiretroviral therapy in Dar es Salaam, Tanzania
Authors: Mugusi Sabina F. , Shayo Grace A. , Sasi Philip G. , Fundikira Lulu S. , Aris Eric A. , Sudfeld Christopher R. , Mugusi Ferdinand M.
Published: February 2025

Background: Kidney disease is a growing non-AIDS-related comorbidity among people living with HIV (PLWH). Tenofovir disoproxil fumarate (TDF) can result in proximal tubulopathy and acute tubular injury, whereas atazanavir/ritonavir (ATV/r) can cause interstitial nephritis and renal stones, both of which can lead to chronic kidney disease.Objectives: To examine the relationship between second-line combination antiretroviral therapy (ART) and the risk of kidney disease and morphological changes among PLWH in Dar es Salaam, Tanzania.Method: A cross-sectional study of adult PLWH receiving TDF-based second-line ART. Socio-demographic and clinical data were gathered, and laboratory tests were conducted to determine the estimated glomerular filtration rate (eGFR). Ultrasonography was performed to visualise the kidneys.Results: A total of 323 patients were enrolled (67.8% women), with a median age of 44 (interquartile range [IQR]: 39–51) years. Patients were on second-line ART for a median of 49 [IQR: 25–73] months, and 60% received ATV/r. Low eGFR ( 90 mL/min per 1.73 m2) was found in 22% of patients, proportionately higher among patients on ATV/r compared to those on a lopinavir/ritonavir (LPV/r) (P  0.05). Nearly one-third (32.2%) of patients had a triad of renal calcinosis, renal calculi, and nephritis on ultrasonography. Patients using ATV/r had significantly smaller kidney volumes and greater proportions of renal calculi and nephritis compared to those on LPV/r (P  0.05).Conclusion: Adults on second-line ART containing TDF were found to have a high prevalence of renal kidney disease in the Tanzanian context. Predictors of kidney disease were older age, proteinuria, and ATV/r-based regimen as compared to LPV/r.
Evaluation of Efficacy of Ultrasound Scan in Diagnosis of Mandibular Fracture
Authors: Ahmad Mukhtar Modibbo , James Olutayo , Farate Abubakar , Olasoji Hector Oladapo , Suleiman Ibrahim Kayode , Abdullahi Mohammed Adam Sheikh , Umar Farouk Kabir , Bala Mujtaba
Published: January 2025

Background:

The mandible is the most common fractured facial bone following trauma to the craniofacial complex. Clinical diagnosis is mostly straightforward, complementary diagnostic imaging is, however, essential for confirmation, classification, treatment plan, and medicolegal reasons. Various modalities of imaging are available each with its advantages and disadvantages.

Objectives:

This study aimed to evaluate the efficacy of ultrasound scan (USS) in the diagnosis of mandibular fractures.

Materials and Methods:

Fifty patients with clinical and radiological diagnoses of fracture in tooth-bearing region of the mandible were recruited. Ultrasound scanning of the fractured site(s) was performed for each patient. A sensitivity test was performed using 2 × 2 contingency table.

Results:

Fifty patients with 59 fracture sites were evaluated and USS showed 100% sensitivity in locating fracture lines in all the patients including displaced fractures. Incidentally, the facial artery crossing the inferior border of the mandible is recognized as the fixed landmark for fracture that is closer to it.

Conclusions:

USS has 100% sensitivity in diagnosing mandibular fracture in tooth-bearing regions. It is therefore suitable for bedside evaluation patients and pregnant women. Further studies may be needed to evaluate nontooth-bearing mandibular regions.
Steady-State and Dynamic Characteristics of Secondary Loop
CO
2
Thermal System for Electric Vehicles
Authors: Zong Shuo , He Yifan , Guan Yan , Dong Qiqi , Yin Xiang , Cao Feng
Published: January 2025

With the rapid adoption of new energy vehicles (NEVs), effective thermal
management has become a crucial factor for enhancing performance, safety, and
efficiency. This study investigates the steady-state and dynamic characteristics
of a secondary loop CO₂ (R744) thermal management system designed for electric
vehicles. The secondary loop system presents several benefits, such as improved
safety through reduced refrigerant leakage and enhanced integration capabilities
with existing vehicle subsystems. However, these advantages often come at the
cost of decreased thermodynamic efficiency compared to direct systems.
Experimental evaluations were conducted to understand the effects of varying
coolant flow rates, discharge pressure, and dynamic startup behaviors. Results
indicate that while the indirect system generally shows a lower coefficient of
performance (COP) than direct systems, optimization of key parameters like
coolant flow rate and discharge pressure can significantly enhance performance.
Specifically, optimizing the coolant flow rate resulted in a COP increase of up
to 92.6% under certain conditions, while proper management of discharge pressure
improved the heating capacity and system efficiency. Additionally, dynamic
analysis of startup behaviors revealed the importance of effectively managing
refrigerant distribution to achieve stable system operation and minimize energy
losses. These findings provide valuable insights into the engineering
feasibility and potential improvements of secondary loop systems. By focusing on
the optimization of flow rate, pressure management, and startup control, this
study supports the development of more sustainable and energy-efficient
solutions for the thermal management of NEVs, ultimately contributing to the
wider adoption of environmentally friendly transportation technologies.
Analysis of Traction Battery Damage Value Based on Frontal
Impact
Authors: Yan Pengfei , Wang Fang , Ma Tianyi , Han Ce , He Gaiyun
Published: January 2025

As the adoption of new energy vehicles expands globally, the safety performance
of their traction batteries has garnered significant attention due to the
potential hazards posed by road debris and collisions. These safety concerns
have become a major impediment to the advancement of these vehicles. This paper
aims to analyze the impact resilience of traction batteries under frontal
collision scenarios to evaluate their safety under specific conditions. A
multi-level evaluation model for traction batteries is developed and integrated
with computer tomography system analysis to investigate the extent of damage
sustained by the battery system during frontal impacts. Utilizing a structured
battery system damage assessment method, the study provides a quantitative
analysis of the damage severity resulting from collisions. This offers both
theoretical insights and practical guidance for the testing and evaluation of
traction batteries.
Correlation Analysis of Automotive Battery State-of-Health Indicators
for Advanced Battery Management Systems
Authors: Long Tianfeng , Shang Huaqing , Liu Xiaoqi , Zhang Pengcheng , Yue Meiling , Meng Jianwen
Published: January 2025

With increasing global attention on environmental issues and the greenhouse
effect, electric vehicles (EVs) have become a focal point for sustainable
transportation solutions. Lithium-ion batteries are integral to EVs due to their
high energy density, elevated operating voltage, and long service life. However,
their performance is highly influenced by factors such as ambient temperature,
charge and discharge rates, and aging processes. To enhance the safety,
reliability, and efficiency of lithium-ion battery systems, it is critical to
develop a robust and advanced battery management system (BMS) that can monitor
battery states accurately and in real-time. A key aspect of BMS design is the
estimation and prediction of the battery's state of health (SOH). Accurately
characterizing SOH during actual usage conditions is essential for optimal
battery performance and longevity. This study investigates various SOH indicator
extraction methods reported in the literature, including features related to
voltage, temperature, and incremental capacity (IC) curves. Correlation analyses
of these indicators are conducted using two experimental datasets. The results
demonstrate that the selected indicators have strong correlations with battery
SOH, confirming their effectiveness for SOH estimation and prediction. By
validating the effectiveness of specific SOH indicators, this research
contributes to the development of more reliable and efficient battery management
strategies, offering significant practical application value in the advancement
of electric vehicle technologies.
Optimization of Low-Temperature Fast-Charging Strategy for Power
Battery of Pure Electric Heavy-Duty Truck
Authors: Lin Jiewei , Jiang Feifan , Dai Huwei , Sun Lei , Liu Baoguo , Li Shibo , Zhang Junhong
Published: January 2025

In cold environments, it is slow and risky for charging rate of electric
heavy-duty trucks due to lithium plating. Common heating-charging methods
overlook the complex dynamics between current, temperature, and battery aging,
which need to be further improved. This study presents a tailored thermal
management strategy for low-temperature battery charging, analyzing heating
performance and battery improvement effect on the fast-charging performance. The
data-driven multi-tiered power heating strategy based on a customer
electro-thermal-aging model was proposed to minimize charging time and costs.
The heating power combinations have been optimized by a particle swarm
optimization algorithm, which outperforms conventional methods that aim to reach
a set temperature. The optimized strategy reduced charging time by 11% and
battery life degradation by only 0.0512%, enhanced the efficiency of
cold-weather fast charging for electric trucks.
Multi-step Prediction of Battery Temperature and Thermal Fault
Diagnosis Based on Informer
Authors: Sun Yefan , Zhu Xiaopeng , Zhang Zhengjie , Peng Zhaoxia , Yang Shichun , Liu Xinhua
Published: January 2025

Lithium-ion batteries are prone to thermal failures under extreme conditions,
leading to thermal runaway and safety risks such as fire or explosion.
Therefore, effective temperature prediction and diagnosis are crucial. This
paper proposes a thermal fault diagnosis method based on the Informer time
series model. By extracting temperature-related features and conducting
correlation analysis, a 9-dimensional input parameter matrix is constructed.
Experimental results show that the model can maintain an absolute temperature
prediction error within 0.5°C when predicting 10 seconds in advance, with higher
accuracy than the LSTM model. Additionally, a three-level warning mechanism
based on the forgetting coefficient further enhances diagnostic accuracy.
Validation using test data and real vehicle data demonstrates that this method
can efficiently diagnose and locate thermal faults in batteries, with low
computational costs, making it suitable for online applications.