bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Driven Virtual Counterparts for Climate Change Modeling
Authors: Soosai Anandaraj A. Peter , Sethuraman Dinesh Dhanabalan , Marimuthu Pitchaimuthu , Mohammed S. Hashim , Subramaniam Sangeetha , Regula Thirupathi
Published: July 2024

Climate change modeling is a critical endeavor in understanding and mitigating the impacts of environmental shifts. This research introduces a novelist methodology named ClimateNet, leveraging machine learning on creation virtual counterparts (digital twin) for enhanced climate change modeling. The primary objective is to augment traditional models with dynamic, data-driven simulations, offering a more nuanced understanding of climate variables and their interactions. By utilizing extensive real time datasets and advanced algorithms, ClimateNet generates virtual counterparts that not only simulate real-world conditions but also adapt to emerging patterns. The proposed system findings reveal a substantial improvement in the accuracy and predictive capabilities of climate models when integrated with ClimateNet.
Role of Predictive Analytics for Enhanced Decision Making in Business Applications
Authors: Naga Malleswari T. Y. J. , Ushasukhanya S. , Karthikeyan M. , Cherian Aswathy K. , Vaidhehi M.
Published: July 2024

Predictive analytics, an integral facet of advanced analytics, employs statistical, machine learning, and artificial intelligence techniques to forecast future events. This chapter explores the diverse applications and implications of predictive analytics, with a focus on enhancing decision-making processes. Drawing examples from industries such as e-retailing, insurance, banking, and healthcare, predictive analytics emerges as a versatile tool for proactive decision-making, customer engagement, and operational efficiency. The evolution of data science and decision-making dynamics is discussed, highlighting the transformative role of predictive analytics in leveraging data for success. It also delves into proactive forecasting methods, stages of predictive analysis, and the advantages these methods offer. Looking toward the future, potential enhancements in the field are outlined, encompassing advanced technologies, real-time analytics, explainable AI, cross-domain models, privacy-preserving methods, and more.
The Joker
Authors: Popov Vladimir
Published: July 2024

This academic paper explores the transmedia narrative of the comic book character of the Joker across various media platforms. It delves into the complex creation and evolution of the Joker, highlighting the collaborative efforts of Bob Kane, Bill Finger, and Jerry Robinson, and the character's profound impact on cultural and societal norms. By examining the Joker's transmedial storytelling, the paper underscores the character's ability to adapt and resonate across different contexts, from comics to films and beyond. It further investigates the Joker's role as a mirror to societal dynamics, embodying themes of chaos, resistance, and critique of biopolitical control. The paper concludes that the Joker's enduring appeal and multifaceted nature exemplify the transformative potential of narrative characters within the transmedial landscape, serving as agents of critique and catalysts for discourse on identity, power, and resistance.
Blockchain-Based Quantum Resistant Electoral Management System for the Post-Pandemic Era
Authors: Banerjee Bannishikha , Sarkar Dhrubasish
Published: July 2024

The recent pandemic crisis has caused widespread worry for the community. Stay at Home and Large-Scale Social Restrictions implementation in various locations have been strongly advocated by the government. One of the points of contention is when regional leaders will be elected to the position of general chairman. Even though a protective legislation existed, it was not deemed safe in the outbreak. The implementation of a blockchain-based E-voting system to combat election in this kind of situations is the solution proposed in this study. Many countries have been acquiring blockchain technology under their control for reasons of reliability and security, especially in the quantum era, when all the traditional security approaches would become outdated. Because it uses a decentralised system and the full database is held by multiple users, blockchain technology is one of the best options when it comes to trust-less transactions. Recently blockchain gained momentum and advancement as a result of digitalization applications. One such application is digital voting system. Elections can be extremely costly in India, but the expenses can be substantially reduced by using a blockchain-based digital voting mechanism. Although it appears to be simple, there are additional considerations to be made, such as privacy and security concerns. Efficiency and reliability should also be maintained because it applies to a humongous number of people or areas. Furthermore, a single flaw can result in a considerable quantity of vote manipulation. When compared to electronic voting, a blockchain-based quantum resistant voting system is more accurate, secure, and convenient.
Enhancing Face Recognition Accuracy Using Digital Twins
Authors: Kondekar Sarika , Dashore Pankaj
Published: July 2024

In today's scenario face recognition systems have become increasingly prevalent in various domains, including security, surveillance, and identity verification. However, challenges persist in achieving high accuracy, especially in scenarios with variations in lighting, pose, and facial expressions. Digital twins, virtual representations of physical objects or entities, offer a promising avenue to address these challenges by providing a simulated environment for training and testing face recognition algorithms. This research explores the potential of digital twins in enhancing face recognition accuracy. Specifically, we investigate the effectiveness of incorporating digital twins into deep learning approaches for face recognition. Through a comparative study of different techniques and architectures, we assess the impact of digital twins on recognition performance across diverse datasets and conditions. The findings of this study contribute to advancing the state-of-the-art in face recognition technology and offer insights into leveraging digital twins to improve accuracy and robustness in real-world applications.
Empowering Maternal Health Through Soft Computing
Authors: Bondhopadhyay Banashree , Bansal Hina , Aggarwal Navya , Sen Shinjini , Kaur Gurleen
Published: July 2024

This chapter explores the integration of soft computing techniques into maternal healthcare, aiming to enhance outcomes and revolutionize care delivery. It delves into the theoretical foundations of soft computing and its applicability to maternal health, emphasizing its potential to address the multifaceted challenges inherent in maternal care. From preconception to postpartum, various soft computing applications, including predictive analytics, personalized medicine, and telehealth services, offer innovative solutions to optimize maternal health services. Through an interdisciplinary lens, this chapter integrates insights from computer science, medicine, and public health to provide a comprehensive overview of the role of soft computing in maternal care. By fostering collaboration between stakeholders, this chapter lays the groundwork for subsequent discussions on specific applications and advancements in maternal health initiatives worldwide.
Revolutionizing Prenatal Care
Authors: Eswaran Ushaa , Eswaran Vivek , Murali Keerthna , Eswaran Vishal
Published: July 2024

The integration of telemedicine and soft computing technologies has revolutionized prenatal care, enabling remote consultations, continuous monitoring, and personalized interventions. This chapter explores the application of telemedicine platforms, remote monitoring devices, AI-driven decision support systems, and predictive modeling in enhancing maternal and fetal health outcomes. It discusses ethical considerations, such as data privacy, algorithmic bias, and informed consent, and highlights successful case studies. The chapter also examines emerging trends, including virtual reality for childbirth education, tele-ultrasound imaging, and precision prenatal care. Ultimately, these innovative approaches aim to empower expectant mothers, improve access to care, and ensure safer and healthier pregnancies.
Technology Adoption Roadmap for Delivering Superior Services in the Healthcare Industry
Authors: Singh Nripendra , Shalender Kumar , Singla Babita , Sharma Sandhir
Published: July 2024

The application of technology in the healthcare sector is rising by the day. This chapter specifically focuses on the utility of technology adoption for stakeholders in the healthcare ecosystem so that maximum advantage could be given to the underserved population. With a specific focus on the LLMs, AI, ML, and Blockchain, the study focused on the benefits of these technologies for the betterment of healthcare services. This is followed by the adoption roadmap for the technology tools with a special focus on the healthcare industry, technology developers, and policymakers. Combining these three important stakeholders will lead to better adoption of the technology tools in the healthcare sector with a focus on enhancing the efficiency and effectiveness of functional procedures and operational mechanisms of the industry. The conclusion and discussion sections towards the end discuss the important inside generated by the study and lay down the foundation for future developments that could mark the adoption of technology in the healthcare ecosystem.
Building Blocks
Authors: Nagarajan Harikumar , Tamilarasan B. , M. Thanjaivadivel
Published: July 2024

This work specifically examines the analysis of building blocks structures that experience finite displacements. The analysis was conducted with incremental sequential techniques. The Newton-Raphson iteration approach is used to load structural stages that have the ability to either soften or harden. A modified Newton-Raphson iteration technique is employed for loading stages in which the determinant of the global stiffness matrix is near 0 or negative, as observed in the snap-through scenario. The advanced computer language Fortran is used for structural analysis. To ensure the program's integrity, SAP (structural analysis program) is used for verification. The software is then used in several structural systems case studies. To accomplish this, the authors compare the axial stiffness of panels and jack elements as well as the height-to-span ratios of various structures. The structural responses were modelled using stiffening, snap-through, and softening load-displacement curves.
Handling Irregular and Complex Geometries
Authors: Sivaparthipan C. B. , Al-Azzawi WaleedKhalid
Published: July 2024

In the analysis using the finite element method (FEM) of structural components under multiple loading conditions, these are studied individually to obtain the individual structural responses of each of them. In a standard h-adaptive analysis process, different meshes would be generated with each applied load. Therefore, an extensive analysis would be necessary to obtain the stiffness matrix for each case. A solution to this approach is based on receiving a mesh that can be used for all cases and that, in turn, allows the user to achieve the desired error. This work defines a practical method that allows obtaining the optimal mesh in linear static refinement problems for multiple load cases about the size relationships of the elements and the expressions that relate the estimated errors between successive meshes. The suggested method is numerically validated through two-dimensional examples.
Mathematical Foundations and Principles Behind These Methods
Authors: Kadhim Noor Mohammed , Hamad Abdulsattar Abdullah
Published: July 2024

This work addresses the definition and historical introduction to numerical methods and the need for their application in engineering. Likewise, the basic concepts of accuracy, precision, convergence, and stability are established, as are the definitions of the different types of errors and how to quantify them. Finally, the Taylor polynomial is a resource for approximating mathematical functions. A subfield of mathematics known as “numerical analysis” uses iterative algorithms to produce numerical solutions to issues where analytical or symbolic mathematics is unable to solve or is inefficient. These algorithms are specifically referred to as numerical methods.
Regulatory Landscapes
Authors: Sachdeva Channi , Grover Veena , Kaur Prabhjeet , Gangwar Veer P.
Published: July 2024

The study focused on the commercialization of basic sciences that offer immense potential to transform research into practical solutions. However, the qualitative approach will be used to navigate the complex regulatory landscapes, which poses significant challenges in the process. The review from previous research can act as a highlighting aspect to look into interdisciplinary collaboration in ensuring regulatory adherence throughout the commercialization process. The methodology for the study has been comprised of a qualitative approach that includes extraction of the database from various sources, news, company reports, and qualitative analysis of interviews to get a complete scenario of the topic. From the analysis, it has been observed that there are pervasive regulatory bodies among various industries and compliance to use proactive strategies. The implication of the study states that before implementing a regulatory body it is necessary to adopt an interdisciplinary approach to have a better understanding of future challenges and opportunities in various associated sectors.
Channeling Basic Sciences for Innovation and Growth Insights From AI Integration in Education and Business
Authors: Verma Ajay , Wani Nahida Majeed
Published: July 2024

Artificial intelligence (AI) has rapidly advanced in recent years, poised to revolutionize various aspects of human life. Despite its potential, many educators are unaware of its broad impact. However, AI integration in education is expanding, aiming to improve teaching and learning quality through diverse methodologies leveraging data analytics and machine learning. This study explored AI's role in massive open online courses (MOOCs) using a bibliometric approach applied to Scopus databases from 2012 to 2024, analyzing 366 articles. While interest in the topic is growing, the literature remains in its early stages. Meanwhile, in business, the influence of basic sciences is often overlooked, yet they provide the foundation for innovation. Integrating these principles into business strategies uncovers new growth paths and fosters a culture of curiosity, collaboration, and innovation. This integration drives technological progress and inspires innovation in supply chain optimization and healthcare solutions.
Adapting to Remote Work
Authors: Mukherjee Sayantan , Neogi Shromona , Verma Ajay
Published: July 2024

The trend towards remote and hybrid work patterns in India's IT companies could have beneficial and bad consequences on the industry's survival. This study aims to synthesise the latest management research and case studies and offer practical conclusions, supported by relevant basic science principles. In response to the COVID-19 pandemic, several Indian companies have adopted remote and hybrid work arrangements. This study report seeks to understand the relationship between sustainability performance, new ways of working, workspace consumption patterns, and methods for reducing physical workspace use by individuals and businesses, supported by psychological and environmental evidence. Polls of Indian IT firm managers and executives found that innovative working practices reduce office space, improving sustainability metrics. Keywords Basic Sciences in business, Hybrid Workspaces, Indian IT Sector, Sustainability, Sustainability Challenges, Sustainability performance
Analyzing the Influence of Sustainable Voluntourism on Community Development and Empowerment
Authors: Yadav Suraj Jaywant
Published: July 2024

This study examines the influence of sustainable voluntourism on community development and empowerment. Findings indicate positive impacts but highlight areas needing improvement. Future initiatives should prioritize genuine cultural exchange, local stakeholder collaboration, and robust job creation linked with local entrepreneurship. Environmental sustainability must be enforced through stringent standards. A key to success is building local capacity for self-sufficiency via leadership development and knowledge transfer. Moving beyond service delivery to an empowerment-based approach is essential for holistic development and respecting local autonomy. This reimagined voluntourism can significantly enhance economic, socio-cultural, environmental, and human capital outcomes.
Publication Trends of Millennial and Post-Millennial Travellers Through Bibliometric Analysis
Authors: Sneha N. , Saha Sangita , Saha Saibal Kumar
Published: July 2024

The travel behaviour of millennials has become a topic of increasing interest among researchers and industry practitioners. This study explores the travel behaviour of millennials (born 1981-1996) and Generation Z (born 1997-2012) using bibliometric analysis. The research aims to identify and summarize the current state of knowledge on this topic, and to identify the trends and gaps in the literature. The study used a bibliometric analysis of the Scopus database, covering the period from 2010 to 2022. The analysis resulted in a total of 470 articles, which were analyzed in terms of publication year, author, country, source title, and keywords. The results showed that the majority of the studies were published during the period of 1993-2023, and that the most cited authors are Bilghami and Alemi in this field. This is the first study that provides insights into the current state of knowledge on the travel behaviour of millennials and Generation Z and highlights the trends and gaps in the literature using bibliometric analysis which can be useful for future research in this field.
Analysis of Impact Investment for Sustainable Development in India
Authors: Takkar Sanjana , Gupta Chabi
Published: July 2024

Impact investment is a form of investing the purpose of which is to generate not just financial returns, but positive social or environmental impacts also. The objective of this research is to observe the trends that are being followed in the Indian impact investing landscape and draw the comparisons and/or similarities with the data published by the Global Impact Investing Network (GIIN), a nonprofit organisation committed to expanding the scope of impact investing globally. For the objective of gauging the Indian impact investment movement, primary data was collected through a survey of 238 Indian impact investors, and the data collected was analysed descriptively and compared with secondary data available on the GIIN's website. The insights that are provided by this study shall aid investors as they are encouraged to review the implications for their own strategies and patterns of investing and investigate these actionable measures so as to facilitate a sustained responsible industry growth, improve market transparency, and reinforce the patterns of investment decision-making.
Sustainable Development for Society 5.0
Authors: Sisinyize Nico L.
Published: July 2024

Society 5.0 requires a shift from traditional growth models to a more holistic approach that embraces the delicate balance between economic prosperity, environmental health, and social inclusivity. The reader will need to understand the key concepts indicating sustainable development and Society 5.0. In addition, they need to understand the key principles underpinning sustainable development in the context of Society 5.0. From fostering innovation for environmental conservation to promoting inclusive economic systems, each facet contributes to a vision of progress that transcends traditional boundaries. The author unravels the layers of sustainable development within the framework of Society 5.0, where technology becomes a catalyst for positive change, and the well-being of society is intricately interwoven with the health of the planet.
Amalgamation of Optimization Algorithms With IoT Applications
Authors: Dubey Vandana , Kumari Priti , Patel Kavita , Singh Shikha , Shrivastava Sarika
Published: July 2024

The integration of optimization algorithms with IoT (internet of things) applications presents numerous benefits and diverse applications. Optimization algorithms help enhance the efficiency, scalability, and cost-effectiveness of IoT systems. This powerful combination offers advantages such as improved resource allocation, reduced energy consumption, enhanced decision-making, and better resource utilization. It finds applications in smart cities, agriculture, healthcare, manufacturing, and more, optimizing traffic management, precision agriculture, healthcare resource allocation, and supply chain management, among others. In summary, the union of optimization algorithms with IoT unlocks a wide array of opportunities for optimizing processes, conserving resources, and improving the quality of services in various domains. Optimization algorithms are used to find the best solution to a given problem, and when applied to IoT, they can help in various ways, including improving resource allocation, energy efficiency, data analysis, and more. Here the authors discuss some ways in which optimization algorithms can be combined with IoT applications such as resource allocation, energy efficiency, data routing and processing, quality of service (QoS), improvement, etc. The choice of the specific optimization algorithm depends on the nature of the problem and the application. Algorithms like genetic algorithms, particle swarm optimization, simulated annealing, and machine learning techniques (e.g., deep reinforcement learning) can be applied to various IoT optimization problems. Basically, the combination of optimization algorithms with IoT applications can lead to more efficient, cost-effective, and reliable IoT systems across a wide range of domains. It's essential to carefully assess the specific requirements of your IoT application and select the appropriate optimization techniques to achieve the goals.
Innovative Approaches for a Sustainable Future
Authors: Eegunjobi Ruth , Tafirenyika Blessing , Adeyanju Adetunji Anthony
Published: July 2024

Research and development (R&D) and its contribution to innovation is critical for sustainable development and Society 5.0. This chapter investigates the intricate relationship between expenditure in R&D and sustainable development in light of socio-environmental issues with a panel of 38 OECD countries spanning 2000-2021. The variables of interest in this study include R&D expenditure as a percentage of gross domestic product (GDP) and economic growth. Real gross domestic product per capita serves as the proxy to measure sustainable economic growth, while social sustainability and environmental sustainability are measured by the social progress index and environmental sustainability index, respectively. The findings of this chapter show that the effect of expenditure in R&D on environmental sustainability is negative, which is influenced by the crowding out effect due to socio-environmental issues. This chapter suggests innovative approaches to sustainable development through a holistic approach incorporating human and social aspects.
Whether English Proficiency and English Self-Efficacy Influence the Credibility of ChatGPT-Generated English Content of EMI Students
Authors: Mai Duong Thi Thuy , Van Hanh Nguyen
Published: July 2024

This study investigated whether English proficiency (EP) and English self-efficacy (ESE) influence the credibility of ChatGPT-generated English content (CCGEC) of college students in the English-medium instruction (EMI) courses. We observed a college-level EMI course called “Technical Writing and Presentation”, where instructors encouraged their students of non-English majors to use ChatGPT for discovery learning in their EMI learning tasks. A survey of 800 students showed that ChatGPT was primarily used for providing explanations, suggesting ideas and structures, and preparing presentations. Analyzing the survey data with the MANCOVA procedure revealed that students' EP levels did not influence their CCGEC, and ESE did not moderate the relationship between EP and CCGEC in the EMI course context. These findings suggest that ChatGPT can be a valuable tool for EMI students regardless of their EP or ESE.
Interior Design Based on Internet Thinking
Authors: Nie Min
Published: July 2024

With the continuous development of society and economy, Internet thinking is gradually integrated into interior design, bringing new possibilities for interior design. This paper takes the interior design of general hospital outpatient department based on Internet thinking as an example to explore the interior design based on Internet thinking. Through the questionnaire survey and interview method and other scientific research methods, the author collected relevant data and carried out statistics and analyses, and concluded that the field of interior design should be combined with the current way of thinking about the Internet to innovate, and integrate the interior space into the combination of modern science and technology and interior design, so as to enable the interior design industry to develop rapidly. Under the influence of Internet thinking, interior design pays more attention to the interactive relationship between users and space. This mode of thinking enables designers to better understand user needs and provide users with more personalised and comfortable space design.
ChatGPT and Health Communication
Authors: Li Min , Guenier Amily W.
Published: July 2024

This systematic review aims to provide insight into ChatGPT's application in health communication. The review, based on seven academic databases, employed Boolean operators to connect keywords, refining search results. Selection criteria and quality assessment ensured a comprehensive evaluation. Fourteen articles were included, focusing on the application of ChatGPT in interpersonal health communication. Survey research methods were mostly used, revealing four main application advantages and ten application risks, such as providing inaccurate and incomplete health information. At present, ChatGPT is still not suitable for widespread application in health communication. Diverse linguistic and cultural contexts, interdisciplinary collaboration, real patient experiences, integration of ChatGPT with existing healthcare information systems, and some ethical factors must be considered to ensure ChatGPT effectively empowers health communication.
Online Surveillance of IoT Agents in Smart Cities Using Deep Reinforcement Learning
Authors: Alenezi Ahmad
Published: July 2024

In the context of today's smart cities, the effective operation of online surveillance of IoT agents is crucial for maintaining public safety and security. To achieve this, collaboration and cooperation among these autonomous IoT agents are indispensable. While the existing research has focused on collaboration amongst the neighboring agents or implicit cooperation, real-world scenarios often necessitate broader forms of collaboration. In response to this need, we introduce a novel framework that leverages visual signals and observations to facilitate collaboration among online surveillance. Our proposed framework incorporates the Multi-Agent POsthumous Credit Assignment (MA-POCA) algorithm as a training mechanism. The empirical results demonstrate that our framework consistently outperforms the base model in various performance metrics. Specifically, it exhibits superior performance in group cumulative reward, cumulative reward, and episode length. Furthermore, our proposed model excels in policy loss performance measures when compared to base model.
Research on Irregular Flight Recovery Strategy Under Different Flight Route Types With Big Data Computing
Authors: Fan Wei , Xu Yanfei , Lu Liang , Zhang Honghai , Wu Xuecheng , Jiang Yan , Zhang Yingfeng
Published: July 2024

During periods of extreme weather conditions, airport closures, or other unforeseen circumstances, air-lines frequently encounter disruptions in their flight schedules, posing flight recovery as a recurrent operational challenge. This paper aims to explore the impact of passenger transfer costs on flight recovery across various route types. Drawing on established methods used to calculate aircraft maintenance and crew assignment costs, this study utilizes an improved large-scale neighborhood search algorithm to perform a large number of calculations on a realistic dataset of airlines, meticulously analyzes the amalgamation of passenger transfer costs across different route types and proposes tailored strategies to mitigate disruptions. Through simulation experiments, the research evaluates the influence of various passenger transfer methods on flight recovery across diverse route types, with the goal of furnishing airlines with more adaptable and targeted decision support.
A Fault Recovery Method for Distribution Networks With Distributed Power Sources Based on 5G Smart Terminal
Authors: Guo Qingrui , Tuxun Alimire Maimaiti
Published: July 2024

Firstly, a smart terminal is designed based on 5G communication technology, which is embedded with various protection measurement devices to form a 5G smart terminal. A distributed control model for the distribution network is constructed based on 5G smart terminals, and an objective function is designed taking into account factors such as restoring important loads, surplus power supply in the distribution network, network losses, and the number of switch actions. Finally, the Sparrow Search Algorithm (SSA) is improved using elite reverse learning strategy and dynamic sine perturbation strategy, and it is used to solve the objective function. Based on the IEEE33 distribution network node system, experimental tests are conducted, and the results show that the average delay of 5G smart terminals is about 30ms. Taking 14:00 as an example, the proposed method achieves network loss, number of switch actions, recovered important load power, and power supply surplus of 46.39 kW, 3 times, 185.65 kW, 240.28 kW, respectively. The fault recovery effect of the distribution network is ideal.
Revisiting the Extended IoT Use Behavior Model Among Senior NCD Patients for Smart Healthcare in Malaysia
Authors: Malarvizhi Chinnasamy Agamudai Nambi , Manzoor Shamima Raihan , Haque Rasheedul
Published: July 2024

The growth of the senior population and the rise in chronic illnesses such as non-communicable diseases (NCDs) are placing significant strain on modern healthcare systems. The demand for resources from hospital beds to doctors and nurses is high in Upper-Middle-Income countries like Malaysia. The use of IoT technologies can give aged people at home uninterrupted access to healthcare resources and better control over their health. This study aims to analyze the key antecedents of the actual behavior of IoT technologies among aged NCD patients in Malaysia under a framework covering the unified theory of acceptance and use of technology model, technology acceptance model, and theory of planned behavior. This cross-sectional study used a purposive sampling technique and data were analyzed using SmartPLS. The outcome is expected to help the government and healthcare policymakers develop awareness among the senior community on the use of IoT-based smart wearables for routine self-monitoring of NCDs.
Enhancing Biology Teachers' Professional Development
Authors: Bariushaa Oyuntuya , Balgan Altangerel
Published: July 2024

The purpose of the study is to identify the necessary knowledge to be developed by biology teachers using the TPACK model for each of the five topics that are difficult to teach in Mongolian high schools. Five groups—“respiration,” “regulation of the living body,” “biotechnology, genetic engineering,” “enzymes,” and “immunity”—were selected as difficult groups for teaching according to the TPACK model. The study questioned 113 school biology teachers for content knowledge (CK), pedagogical content knowledge (PCK), technology content knowledge (TCK), and technological pedagogical content knowledge (TPCK). For each topic, TCK is the heaviest and CK the lightest compared to other types of knowledge for biology teachers. In terms of the correlation coefficient, for the groups, TCK and TPCK had the highest correlations. This research proposes the development of TCK and TPCK content modules for specific groups of secondary school biology teachers is crucial.
A Learning Measurement Model for English Comprehensive Ability Based on the Background of Educational Informatization
Authors: Yang Ting
Published: July 2024

The purpose of this study is to explore the learning measurement model of English comprehensive ability based on the background of educational informatization. With the rapid development of educational information technology, English education is facing unprecedented opportunities and challenges. Under the background of information technology, this study discusses the application of educational information technology in English teaching, the composition and evaluation criteria of English comprehensive ability, the role change of teachers and students in the information environment and the ability training. Through in-depth research and empirical research, this study aims to provide theoretical support and practical experience for the innovation and promotion of English education, promote the wide application of educational information technology in English teaching, and provide more effective support and guidance for the development of students' comprehensive English ability.
A cross-sectional survey amongst young adults in Nigeria on their personal experience of injury and violence
Authors: Mariere Ulunma , Oguche Obielumani , Adesina Adedotun , Ekeria Oyetola , Israel Sample , Owoupele Ebiakpo , Edeki Sandra
Published: July 2024

Introduction: Injuries and violence are increasingly being recognized as a major public health problem that greatly impacts young people with potentially far-reaching consequences for their physical, reproductive, and mental health. Despite the rising incidence, there is still a high level of under-reporting.Objectives: This study sought to report the experiences of unintentional injury and violent incidents and their gender variations amongst young adults in Bayelsa state.Methods: A cross-sectional study amongst 209 randomly selected young adults. Using a self-administered questionnaire adapted from the WHO STEPwise manual on non-communicable disease, data on socio-demographic characteristics, experiences with violence and injury was obtained.Result: Mean age was 25.7 years; 51.7% were females.  In the 12 months preceding the study, about 1 in 3 respondents had an unintentional injury that required medical attention and 21.5% had been involved in a Road Traffic accident. Most threats were from close relatives and friends. A little over 3 in 5 (64.4%) respondents reported physical abuse, 25.8% had experienced sexual abuse in childhood and 24.4% experienced sexual abuse as adults; this was higher in females than males (27.8% vs 20.7%). Non-RTA injuries were significantly higher (χ2=3.58; p–0.040) in females. Except RTA injuries/violence, more females than males experienced physical/sexual violence; though no statistically difference(p>0.05).Conclusion & Recommendations: A large number of young adults experience varied forms of injury and violence in the course of life during childhood and adulthood. Females experience these more than males highlighting the need for a gender-responsive approach in addressing this public health problem
A legacy of 75 years in advancing health and wellbeing
Authors: Senarath Upul
Published: July 2024

No abstract available
The role of immunotherapy in patients with lung cancer and brain metastases: a narrative review of the literature
Authors: Eleftheriadou Eleni D. , Saroglou Maria , Syrigos Nikolaos , Kotteas Ellias , Kouvela Marousa
Published: July 2024

Worldwide, approximately half of the patients diagnosed with lung cancer (LC) will develop, simultaneously or asynchronously, brain metastases (BMs). The existence of BMs negatively affects the quality of life and constitutes a poor prognostic factor, linked with high mortality. Locoregional therapy with surgery or radiation is, until now, the treatment of choice, especially for symptomatic patients; however, both options are linked to a high complication rate. The question arising here is whether, in asymptomatic patients, the benefit outweighs the risk and whether an alternative method can be used to treat this special category of patients. Over the last decade, immune checkpoint inhibitors (ICIs) have represented a major breakthrough in the field of oncology, and several molecules have been approved as a treatment option for LC. This review tried to analyze the tumor microenvironment of both the primary lung tumor and the BMs in order to evaluate the intracranial activity of ICIs, outline the main challenges of including these agents in the treatment of LC with BMs, highlight the available information from the main clinical trials, and mark the potential positive effect of choosing a combination therapy. In conclusion, it appears that immunotherapy has a positive effect, inhibiting the progression of BMs, but more data should be published specifically for this category of patients.
A Scientometrics-based Systematic Analysis to Understand the Research Status of Leptospirosis in India during 1965–2019
Authors: Krishnan Baby Karpagam , Sivaprakasam Satish , Balasubramanian Ganesh
Published: July 2024

Introduction:

Leptospirosis is one of the neglected zoonotic diseases of public health importance due to its surge in emergence and reemergence in India. There is a lack of information on critical areas of the disease such as epidemiology, disease dynamics, infection status, and poor management. This study aimed to critically review the status of leptospirosis over time with a holistic review utilizing scientometrics and systematic analysis techniques to quantify the research activities with available evidence from existing databases and address the research gap in the Indian subcontinent.

Methods:

The analysis was conducted using the keywords “Leptospirosis” and “India” from the Web of Science database, and the research output was explored through a scientometric analysis. We searched research articles related to leptospirosis in India from the science citation index expanded database of Thomson Reuters Web of Science from 1965 to 2019 (54 years). The Bibliometrix package of R software, online Word cloud, and VOS Viewer were used to conduct a formal scientometric analysis of 50 articles and systematic analysis for the qualitative data obtained from the available 37 articles.

Results:

A total of 50 articles were obtained. These articles were extensively analyzed to extract the qualitative and quantitative research data. The results of the analysis concerning the research gap were extensively discussed in this scientometric analysis.

Conclusion:

Our research outcomes help contemplate the research status in India where there has been a slight increase in publication rates in recent years. There is a significant need for an increase in the articles, authors, collaboration, patent registration, and interdisciplinary research in the field of leptospirosis in India. Even now, more than five decades after the first report of the disease in India, basic data are scarce, notably on epidemiology, disease burden, morbidity, etc., This article extensively reviewed research lacunae and credible interpretation.
Multisystem Inflammatory Syndrome in Children: A Multicenter Retrospective Study
Authors: Al Rawahi Hatem , Al Ismaili Rahima , Al Zeidi Ahmed , Al Farsi Ahmed , Al Waili Badria , Al Noobi Balqees , Al Othmani Farhana Ishaq , Al Shueili Hamood , Al Hajri Hind Salim , Al Mukhaini Kholoud Said , Al Reesi Mohammed , Al Rahbi Najwa , Al Maskari Nawal , Al Tahir Nuha , Abdwani Reem , Al Abrawi Safiya , Al Hashami Hilal , Mohamed Ozayr , Al Awaidy Salah
Published: July 2024

Background:

Multisystem inflammatory syndrome in children (MIS-C) is an uncommon but serious condition that occurs in association with the coronavirus disease 2019 infection in children. We assessed the clinical characteristics and outcomes of children hospitalized with MIS-C in Oman.

Methods:

A retrospective cross-sectional multicenter study implemented among patients under the age of 13 years from May 2020 to September 2021 who met the World Health Organization diagnostic criteria for MIS-C sequentially. Clinical, laboratory investigations, management, and short-term outcomes were collected.

Results:

One hundred and twenty-nine patients were diagnosed with MIS-C. The mean age of the cohort was 6.33 years, among whom 95% and 60% were Omani citizens and males, respectively. All patients were previously healthy. Seventeen percent of the patients had severe MIS-C. Gastrointestinal symptoms, namely, abdominal pain (72%), vomiting (57%), diarrhea (56%), and cough (23%) (P = 0.002), were the most commonly presenting symptoms. In addition to the gastrointestinal system, cardiac organs were the most affected, with 18% (n = 23) patients having mitral regurgitation and 14% (n = 18) (P < 0.001) having pericardial effusion. The mean duration of fever was 5.19 days, with patients with mild and moderate MIS-C having a longer mean duration of fever than those with severe MIS-C. Forty-two percent of the patients were admitted to an intensive care unit. Most of the patients received antibiotics (93%), intravenous immunoglobulin (95%), and fluid boluses (58%). Lymphopenia, D-dimer, and thrombocytopenia were elevated in 83%, 86%, and 60% of the patients, respectively. Four patients died (3%); all others were discharged from the hospital after having completely recovered.

Conclusion:

The study found that most of the children had mild illness. The clinical features and outcomes of our cohort are similar to those reported in other regions and countries. The low mortality rate may indicate that early identification and prompt medical therapy are crucial to the effectiveness of MIS-C treatment.
Acute Recurrent Pancreatitis in a Child with Pancreas Divisum
Authors: Okasha Ammar A. , Abbas Areeg K. , Alenazi Rahaf S. , Okasha Abdelhadi A.
Published: July 2024

Acute recurrent pancreatitis (ARP) is defined as two distinct episodes of acute recurrent pancreatitis. Acute recurrent pancreatitis in children is rare, with an incidence rate of approximately one in 500000. The most common causes of acute recurrent pancreatitis in children are infection, blunt abdominal trauma, drug toxicity, biliary stones or cystolithiasis, systemic disease, anatomic anomalies, sphincter of Oddi dysfunction, and hereditary and idiopathic causes. ARP is a precursor to develop chronic pancreatitis. We report one case of ARP with pancreas divisum, which could be an important etiology for ARP.
A Review of Recent Cluster of Hospitalization-related Respiratory Syncytial Virus Infection Post-COVID-19: A Cross-sectional Study
Authors: Al Dhuhli Khalid , Al Mujeini Sami , Al Malki Rashid , AL Hattali Nouman , AL Shaqsi Nasser , Al Hadhrami Faisal , Al Dhawyani Iman , Al Salti Maya , Al Balushi Aaisha , Al Farsi Fatma , Al Farsi Yousuf , Al Awaidy Salah T.
Published: July 2024

Introduction:

Respiratory syncytial virus (RSV) is a major cause of viral respiratory illnesses in children, typically presenting during the winter. The sudden increase in RSV patients admitted to Rustaq Hospital in Oman between October and December 2023 was investigated to determine the factors associated and recommend countermeasures.

Methods:

A retrospective cross-sectional study was conducted using the demographic, clinical, and laboratory data from the Al Shifa system. Bivariate and multivariate analysis to determine the association between predictors and severity was performed using the Statistical Package for the Social Sciences software version 23.0.

Results:

Eighty-seven RSV-positive patients were hospitalized; the median age was 2 (1–5) months. Men comprised 52% of the cases, children aged <4 months represented 62% of the cases, 20% of the patients were aged 4–7 months, and 13.8% were aged ≥12 months. Among these patients, 93% presented with shortness of breath, 93% had a cough, and 77% had a fever. Preterm babies represented 26% of the cases, of which 52% and 26% were on non-invasive ventilation and intubation, respectively. Patients aged <4 months (adjusted odds ratio = 35.84, P = 0.02) versus those aged >12 months and a high level of C-reactive protein (adjusted odds ratio = 0.480, P = 0.02) compared to a normal level associated with higher risk of admission to the pediatric intensive care unit. There is no comparable RSV data from the same hospital or Oman.

Conclusions:

Severe RSV infection was frequently observed among younger infants who have a high C-reactive protein. Younger children will benefit from RSV vaccination and treatment with monoclonal antibodies that may reduce the severity of RSV infection.
Development and validation of words in babble test in the modern Greek language
Authors: Markatos Nikolaos , Bibas Athanasios , Pastiadis Konstantinos , Bamiou Doris-Eva , Dimitriadis Dimitrios , Kikidis Dimitrios
Published: July 2024

Purpose:

The aim of this paper is to present and describe the development and validation of new Words in the Babble test in modern Greek.

Materials and Methods:

Four 50-word phonemically balanced lists in babble noise were administered to 44 normal hearing subjects and 53 patients with hearing loss (HL) ears with mild and moderate sensorineural HL (SNHL). The word lists were monoaurally presented (i.e., separately for the right and left ears) at 11 signal-to-noise (babble) intensity levels, from −12 to +12 dB. The signal remained constant at 65 dB for all participants with normal hearing and at 20 dB SL for participants with SNHL, whereas the multitalker babble stimulus varied according to the desired signal-to-noise ratio (SNR).

Results:

The results showed that word recognition scores were negatively affected by HL and were negatively related to the degree of HL. There was a statistically significant difference for all scores in all SNRs, both between participants with normal hearing and those with mild HL as well as between participants with mild and moderate HL, except for −3 dB SNR and −6 dB SNR between mild and moderate HL. In addition, there were no statistically significant differences between the right and left ears in any of the SNRs.

Conclusions:

The existing literature suggests that the use of monosyllabic words produces recognition performance in multitalker babble tests, as observed in languages such as Spanish, Estonian, and Arabic, whereas the present study provides evidence that a similar effect is produced when disyllabic words are used.