bluuebunny/crossref_metadata_2025 huggingface dataset:
Blockchain Security Enhancement Through Cybersecurity
Authors: Mulambia Chindika , Varshney Sudeep , Suman Amrit
Published: July 2024

Defending blockchain technology from cyber dangers is essential in today's age of advances in technology and also increase in usage of Blockchain Technology. Due to the ever-changing nature of these dangers, people as well as businesses now seriously worry about protecting sensitive data and digital assets. Blockchain structure and cybersecurity are two essential elements of modern digital security that work together to increase the safety of Blockchain Technology. By utilising cybersecurity techniques, Blockchain Technology can be secured. However, cybersecurity refers to a variety of techniques and procedures used to protect systems, networks, and data from risks and attacks that arise online. Therefore, the primary inquiry that is the aim is to answer is: How can cybersecurity techniques be used to improve Blockchain Technology? This chapter will provide significant insights into this vital collaboration between technology and security as we thoroughly examine how blockchain technology may be improved and secured against the cyberattacks.
Cybersecurity and Threat Mitigation in Blockchain and Digital Twin Ecosystems
Authors: Dashore Prince , Dashore Pankaj , Dashore Rachana
Published: July 2024

The combination of digital twin ecosystems as well as the blockchain technology discussed in this research work introduces new cyber security opportunities and challenges in the continually evolving digital landscape. The complex aspects of securing these advanced systems, underscoring the crucial need for robust threat mitigation strategies. The unexpected cyber-attacks can also compromise sensitive data and disrupt operations in digital twins, which provide real-time virtual replicas of physical assets and processes. In this chapter we presents a comprehensive examination of the current threat landscape, identifies vulnerabilities specific to blockchain and digital twin systems, and proposes effective strategies to protect the integrity, confidentiality, and availability of data. Through this analysis, we aim to contribute to the ongoing efforts to enhance cyber security measures and ensure the secure deployment and operation of these transformative technologies.
Enhancing Cloud-Based Search Efficiency and Privacy Through Blockchain and Digital Twin Integration
Authors: Joshi Narendra Shyam , Sambrekar kuldeep P. , Patankar Abhijit J. , Dashore pankaj J. , Jadhav Archana J.
Published: July 2024

Now a days Cloud-based search systems have become critical tools for accessing and processing massive amounts of data with efficiency, privacy, and security . This research paper suggests a novel approach to addressing these issues by incorporating blockchain technology and digital twin concepts into cloud-based search systems. Blockchain, provides unique capabilities for improving privacy, security, and data integrity. Digital twins, or virtual representations of physical entities or systems, allow us to model and simulate real-world scenarios, resulting in more accurate and efficient search operations. Using both technologies, this chapter aims to investigate novel solutions for improving the performance and privacy of cloud-based search systems. We provide a comprehensive overview of blockchain technology, digital twin concepts, and potential applications in cloud based search.
Precision Profiling
Authors: Nayak Manjushree , Pattnayak Shreekta , Sharma Subham , Pattnaik Omkar
Published: July 2024

In the current economic landscape, small businesses play a significant role in global economies, making it essential to understand the dynamics of tax optimization for sustaining economic growth. This study examines the intricate details of tax planning and optimization by utilizing digital twins, innovative technologies that replicate small business behaviors within a virtual environment. Digital twins emerge as a transformative technology in the landscape of small business tax optimization, offering unparalleled capabilities. They function as virtual duplicates of real-world small business entities, meticulously replicating their behaviors, operations, and interactions within a virtual space. By leveraging digital twins, small businesses gain access to a sophisticated platform for analyzing financial data and devising tax optimization strategies. These virtual replicas provide a dynamic and interactive representation of business processes, allowing for thorough exploration and experimentation without real-world constraints. We delve into the potential trade-offs inherent in small businesses' endeavors to minimize taxes and achieve broader fiscal objectives, emphasizing the importance of striking a delicate balance between taxpayer interests and considerations of public finance. Additionally, we explore the integration of smart contracts, self-executing contracts with predefined rules and conditions, into digital twin platforms using blockchain technology. These smart contracts can automate various aspects of tax compliance and optimization, such as calculating tax liabilities, managing deductions, and executing tax payments. The transparent and immutable nature of blockchain technology simplifies the auditing process for small businesses, facilitating compliance with tax regulations. Auditors can easily access and verify transaction records stored on the blockchain, streamlining the auditing process and reducing the likelihood of errors or discrepancies. In this paper, we introduce the innovative concept of integrating digital twins with blockchain technology to optimize small business operations, particularly in tax management. Through our exploration, we underscore the potential of this integration to revolutionize how small businesses handle financial transactions, track assets, and manage tax obligations.
Empowering Prenatal Care Using AI Image Processing for Early Detection of Pregnancy Complications
Authors: Bansal Kanishk
Published: July 2024

AI image processing has emerged as a transformative tool in the realm of maternal healthcare, particularly in the early detection of pregnancy complications. By harnessing the power of artificial intelligence, healthcare providers can now leverage advanced algorithms to analyze medical images such as ultrasound scans, MRI images, and fetal monitoring data with unprecedented accuracy and efficiency. These AI-based systems excel at detecting subtle abnormalities and anomalies that may indicate potential risks to maternal and fetal health, including markers of fetal growth restriction, placental abnormalities, and congenital anomalies. By facilitating earlier detection and intervention, AI image processing empowers healthcare providers to proactively manage pregnancy complications, thereby improving outcomes for both mother and baby. These predictive models enable healthcare providers to assess the risk of complications early in pregnancy and tailor interventions accordingly.
Sakhi
Authors: Narvekar Meera , Kansara Vidhi , Harkare Vijay
Published: July 2024

Opportunities for women in the healthcare sector have significantly improved during the past 10 years. However, Indian rural women still have barriers to healthcare access due to cultural and traditional norms. One of the main issues is the societal stigma that keeps these women from openly discussing their health. This study presents Sakhi, a chatbot created with the goal of assisting women in these areas by offering simple solutions to a range of physical and mental issues, with a focus on maternity care in particular. Sakhi is equipped to handle issues pertaining to both serious and small injuries, first aid situations, mental health issues, and women's health, including prenatal and postnatal treatment. It can converse in the user's preferred regional language, which enhances accessibility to medical information. Sakhi emphasizes the revolutionary potential of technology in empowering rural women, especially in the area of maternal care, and ignites broader conversations about equal access to information and communication by promoting a more inclusive and connected society.
Smart Ultrasound Imaging and Soft Computing Analysis
Authors: Khadkikar Prajakta Ajay , Purandare Radhika , Jadhav Pratibha Vijay , Patil Rutuja Rajendra , Mahajan Rupali Atul , Rathod Seema Babusing
Published: July 2024

Smart ultrasound images mixed with soft computing analysis is a cutting-edge method for medical diagnosis that promises to make healthcare more accurate, efficient, and open to everyone. Combining ultrasound technology with computer programs will completely change medical imaging analysis. Smart ultrasound imaging uses cutting-edge tools, like high-resolution sensors and real-time processing, to get clear, fast images of body parts. It makes it possible for machines to find trends, oddities, and minor problems that humans might miss. This makes diagnostic accuracy and reliability better all the time. It helps doctors find problems with a baby early in obstetrics, so they can fix them quickly and give the mother better prenatal care. It makes it easier to see how the heart works and find abnormalities that helps doctors make more accurate evaluations and create personalized treatment plans. This makes it easier for more people to get good healthcare, especially in places with few resources. This union has the power to make medicine better and patient care better all over the world.
Exploring Augmented Reality, Virtual Reality, and Machine Learning for Delivering Better Value in the Healthcare Sector
Authors: Punamiya Zeenal , Gupta Navita , Patil Sagar Anil
Published: July 2024

Technological advancements have revolutionized the field of healthcare by offering innovative methods to enhance patient care. With changing demands, it is essential to align them with current advancements. Thus, we explore the strategic utilization of advanced technologies like Artificial Intelligence (AI), Augmented Reality (AR), Virtual Reality (VR), and Machine Learning (ML) to deliver better healthcare. The current challenges are vast and integration of such technologies can help in solving the pain points. Some applications include AR for medical training and surgery, VR for pain relief and patient education, ML for image analysis and predictive analytics, AI for clinical decision support, and process optimization. As we highlight the role of technology in healthcare, addressing ethical and regulatory considerations is essential to navigate challenges and guide future implementation directions. Thus, embracing these technologies positively can enhance healthcare value delivery.
Redefining Healthcare
Authors: Kaur Simanpreet , Anjali
Published: July 2024

This chapter explores how artificial intelligence (AI) is revolutionising healthcare, with a focus on how AI may improve operational effectiveness, individualised care, and diagnostic accuracy. It examines AI uses in personalised medicine, medical imaging analysis, and predictive analytics, highlighting the profound shifts these technologies bring to the provision of healthcare. Examined are the ethical, privacy, and regulatory issues, emphasising the significance of a responsible and balanced approach to innovation. The chapter also discusses how AI may lessen healthcare inequalities and increase accessibility everywhere. In order to guarantee AI maximises advantages while addressing social problems, it argues for a collaborative approach, recommending continual research, multidisciplinary cooperation, and strong ethical frameworks. Researchers, policymakers, and medical practitioners who are navigating the changing terrain of AI in healthcare.
Mapping the AI Landscape in Healthcare Quality
Authors: S. Baranidharan , Narayanan Raja
Published: July 2024

This study explores the application of Artificial Intelligence (AI) in healthcare quality improvement through a bibliometric analysis of 222 documents retrieved from the Scopus database using the keywords “healthcare,” “quality,” and “AI.” By examining bibliographic coupling, citations, co-citations, author keywords, and co-occurrence networks, the research unveils the key themes, prominent authors, and emerging trends in this field. The analysis reveals a focus on areas like machine learning for disease prediction, clinical decision support systems, and patient safety improvement. Leading authors and research groups are identified, and promising future directions such as explainable AI and integration with electronic health records are highlighted. This study contributes to understanding the current landscape of AI in healthcare quality improvement and guiding future research for maximizing its impact.
Generative AI Revolution
Authors: Arunachalam Manikandan , Chiranjeev Chitransh , Mondal Barshan , T. Sanjay
Published: July 2024

A scarcity of data within the healthcare sector can present considerable obstacles for a range of applications, most notably in the implementation and advancement of machine learning models. Sometimes, inadequate data sets may also lead to the wrong interpretation of data with wider patient populations, forcing the models to be biased. Overfitting, where a model acquires knowledge about the features of the training data rather than underlying patterns. In cases of overfit, the models perform well on the training data, but they face difficulty with novel and unknown data. Generative adversarial networks (GANs) play a vital role in healthcare by accelerating medical research and diagnosis. Though GAN has evidenced, genuineness of the data they provide, need to adjust to the regulations to ensure the privacy and security of patient information. This chapter provides an overview of current research and mutual efforts between the medical and artificial intelligence (AI) communities to maximize the potential of GANs to address healthcare challenges.
Solving Linear Problems
Authors: Tayyeh Alnoman Mundher , Shather Akram H. , Jasim Firas Tarik , Anaz Saja Sumiea
Published: July 2024

Problems associated with heat exchange between a gas and a packed bed are quite common in several branches of industry. To properly study this type of phenomenon, a good prediction of the flow dynamics through the bed is necessary. Based on this, this work presents a study of the flow in a packed bed through computer simulation. The packed bed considered in this study is cylindrical and made up of spheres. The simple cubic sphere arrangement was considered to generate the bed geometry. To make the simulation feasible, some simplifications were necessary. The first was flow periodicity in the axial direction of the bed. Another simplification was symmetry in relation to one-eighth of the bed. A very simplified case, considering a single simple cubic cell of spheres, was also simulated. The geometry and mesh of the packed bed were generated in the Gambit software and the flow simulation was carried out in the Fluent software.
Time-Dependent Problems
Authors: Al-Hamido Riad
Published: July 2024

In this chapter, the authors study for the first time in the world the notion of new types of temporal open (closed) sets such as temporal semi open (closed) sets, temporal pre open (closed) sets, quasi temporal semi open (closed) sets, and quasi temporal pre open (closed) sets. Also, they studied the relationship between them and temporal open (closed) sets in the temporal topological space. They also created some properties that are achieved in temporal topological space, but are not achieved in topological space or vice versa. Moreover, they prove some remarks, theorems in temporal topological space.
Catalysts of Innovation
Authors: Jain Priyanka , Roy Ankur
Published: July 2024

India's development trajectory hinges upon its ability to leverage technological advancements, foster innovation, harness scientific assessments to address pressing societal challenges and translate them into sustainable commercial success. Prioritized investments in basic science research offer valuable, diverse, tailored and evidence-based perspectives that drive commercial payoffs. It paved pathways to new business models and encompassed sustainability transformations. The three-dimensional sustainable development goals, i.e., economic, environmental, and social, are the core of this endeavour. This chapter explores the pivotal role of funding basic science in India, underlining its potential to catalyse long-term sustainable commercial payoffs and propel the nation towards economic prosperity.
Is a Blue Flag Beach Sustainable?
Authors: Seal Partho Pratim
Published: July 2024

The Blue Flag program is run by an independent non-profit organization that assures tourists regarding the environmental quality of the beaches. The program is to encourage local administration and tourism stakeholders to continuously develop the environmental quality of the destination. A Blue Flag Beach Award scheme is adopted to manage beaches and attract tourism to be more responsive to the environment and the community. The study aims to analyze the Blue Flag beach of Padubidri and to what extent it contributes to the sustainable management of coastal resources and development of tourism. The study undertakes a netnographic approach to observe the reviews of tourists visiting the beach. The findings of the study do confirm that the Blue Flag certification program is perceived as having more tourism potential to attract tourists rather than sustainable tourism development.
Volunteering for Dark Tourism, Social Action, and Disorientation in Tragedy-Stricken Places
Authors: Liow Melissa
Published: July 2024

Dark tourism, characterised by visits to sites associated with death and tragedy, often becomes a platform for social action. However, current literature lacks a comprehensive exploration of potential social action outcomes, particularly concerning human rights advocacy. This chapter introduces a new conceptualisation of volunteer travellers' experiences, distinguishing disorientation as a unique state separate from transitional and permanent liminality. By exploring social action outcomes in dark tourism volunteering, the chapter highlights the transformative potential of such experiences. While volunteering offers opportunities for personal growth and social engagement, it also presents challenges that may hinder social action. Theoretical frameworks like the framing theory of social action and the critical incident technique serve as valuable tools for understanding the complexities of dark tourism volunteering.
Expanding Horizons
Authors: Sabharwal Dhruv
Published: July 2024

Sustainable tourism development is now a global goal shared by all countries. It represents a comprehensive and integrated approach that requires participation from individuals, groups, organizations, and governments at many levels—from local to international. The ultimate goal of sustainable tourism developments in the long-term health of the entire planet, not just its borders or its time restrictions. As a result, it calls for people to behave locally while embracing a global viewpoint. The efficient implementation of initiatives aimed at alleviating poverty and the promotion of environmental conservation activities in daily life are contingent upon informed and concerned citizens. Relationship-building procedures have been made easier by the growth of information and communication technology, especially mediated communication, which has also broadened the conversation on sustainable development.
Tourism in Transition in Sustainable World
Authors: Chakraborty Partha Pratim
Published: July 2024

The COVID-19 pandemic has fundamentally reshaped global tourism, revealing vulnerabilities and opening pathways for transformative change. As the sector transitions into a post-pandemic era, embracing technological innovation and sustainable practices becomes imperative for resilience and responsiveness. Advanced technologies like artificial intelligence (AI), the internet of things (IoT), and robotics promise to revolutionize tourism by enhancing operational efficiency, traveler experience, and resource optimization. Simultaneously, heightened awareness of tourism's environmental and societal impacts underscores the need for sustainability. Integrating eco-friendly practices, reducing carbon emissions, promoting eco-tourism, and supporting local communities are crucial steps.
Solid Waste Management Policy Framework and Implementation Strategies at a Local Authority in Namibia
Authors: Villet Hylton James , Kruger Mahne Haroldt , Atiku Sulaiman Olusegun
Published: July 2024

Local authorities in Namibia face the daunting task of executing the mammoth solid waste management function to ensure public and environmental health for their inhabitants. Local authorities experience a lack of resources and buy-in from important stakeholders. The solid waste management function was not prioritized during budgetary allocations. This study examines Namibia's solid waste management policy framework to identify factors influencing effective implementation of solid waste management strategies at a local authority. A qualitative research approach was adopted. Twenty local authority staff members were selected for face-to-face interviews using the purposive sampling method. The study unearthed a void regarding the management of solid waste at the local authority. Evidently, resource allocation for solid waste management must be prioritized, and public awareness should be intensified. The managerial implications include waste production reduction and the principles of circularity, as well as making use of change agents and stakeholder engagement for buy in.
Fishing Vessel Type Recognition Based on Semantic Feature Vector
Authors: Yuan Junfeng , Zhang Qianqian , Zhang Jilin , Li Youhuizi , Liu Zhen , Xue Meiting , Zeng Yan
Published: July 2024

Identifying fishing vessel types with artificial intelligence has become a key technology in marine resource management. However, classical feature modeling lacks the ability to express time series features, and the feature extraction is insufficient. Hence, this work focuses on the identification of trawlers, gillnetters, and purse seiners based on semantic feature vectors. First, we extract trajectories from massive and complex historical Vessel Monitoring System data that contain a large amount of dirty data and then extract the semantic features of fishing vessel trajectories. Finally, we input the semantic feature vectors into the LightGBM classification model for classification of fishing vessel types. In this experiment, the F1 measure of our proposed method on the East China Sea fishing vessel dataset reached 96.25, which was 6.82% higher than that of the classical feature-modeling method based on fishing vessel trajectories. Experiments show that this method is accurate and effective for the classification of fishing vessels.
Exploration on Innovation Path of Precise Ideological and Political Work in Colleges and Universities Under the Background of Big Data Driving
Authors: Luo Xiong
Published: July 2024

However, although existing models for evaluating the effectiveness of universities provide a large number of modeling solutions, it is difficult to objectively evaluate dynamic coefficients based on the differences in precision ideological and political work systems of different types of universities in the evaluation process of innovative paths for precision ideological and political work. In this context, this article proposes an innovative path for the precision of ideological and political work in universities under the background of big data driving, and constructs a complex system discrete dynamic modeling technology. This model quantitatively describes the consistency between different precise ideological and political work models, the similarity of research strategies for precise ideological and political work, and expected evaluation indicators using multiple transformation dynamic coefficients. This study provides new ideas and methods for innovative research in the field of ideological and political work in universities.
A Comparison of the Validity of Online Courses Quality Evaluation Models
Authors: Wang Jingwen , Yang Xiaohong , Liu Dujuan
Published: July 2024

The large scale expansion of online courses has led to the crisis of course quality issues. In this study, we first established an evaluation index system for online courses using factor analysis, encompassing three key constructs: course resource construction, course implementation, and teaching effectiveness. Subsequently, we employed factor analysis and entropy weight TOPSIS multi-attribute decision analysis methods to comprehensively evaluate 541 courses. Later on, we conducted correlation and regression analyses between the evaluation results of these two methods and that of experts. The results reveal that the comprehensive evaluation scores derived from both factor analysis and entropy weight TOPSIS models exhibit a significant positive correlation with the experts'. Furthermore, the factor analysis model outperforms the entropy weight TOPSIS model in predicting experts' evaluation scores. The application of this model will help achieve timely and accurate course evaluation, and provide novel idea and approach for real-time monitoring of online courses quality.
Enhanced SVM Algorithm-Based Dynamic Early Warning System for College English Ideological and Political Course Education Using Machine Learning
Authors: Pan Aiqin
Published: July 2024

This study explores the use of an enhanced Support Vector Machine (SVM) algorithm to address challenges faced by students with lower academic performance in college English education, particularly in integrating ideological and political education. It develops a dynamic early warning system to provide timely support, employing targeted English courses and practical teaching methods. Methodologically, an improved SVM algorithm constructs a robust early warning model, enhancing monitoring and support in college English courses. The system's application contributes to advancements in machine learning and AI, emphasizing data-driven decision-making in education. Future research could explore scalability, long-term impacts, and further refinements to the SVM algorithm. In summary, the study successfully applies machine learning techniques to devise an innovative dynamic early warning system for English ideological and political education in college, offering valuable insights for practitioners and researchers alike in the realm of AI-assisted pedagogy.
The Effect of Brand Heritage on Social Commerce Site Privacy Risk, Brand Equity, and Brand Advocacy
Authors: Al Haddad Hadeel B. , Al-Amad Amjad H. , AlSmadi Sami , Hailat Khaled Qassem , Galib Mohammad Hasan , Herzallah Fadi A. T.
Published: July 2024

This study applies the Stimuli-Organism-Response (S-O-R) Theory to examine the impact of brand heritage of social commerce sites on consumers' perceived privacy risk, and the impact of this perceived risk on brand equity and brand advocacy. This study extends brand heritage research by exploring brand heritage in a new context (social commerce sites). To test the hypotheses, an online survey was conducted, and a total of 321 responses were collected from Amazon users in the US. The data were analyzed by using the Partial Least Squares-Structural Equation Modelling (PLS-SEM). Findings revealed that the brand heritage of social commerce sites has a significant negative influence on consumers' perceived privacy risk, which in turn has a significant negative impact on brand equity and brand advocacy.
Directive vs. Commissive Illocutionary Acts?
Authors: Peng Lifang , Wang Suli , Jiang Hui , Wang Kaichao , Li Gang
Published: July 2024

Governments sometimes release information implicitly, and citizens have to understand their illocutionary acts. The present study examines when and how illocutionary acts encourage citizens to disseminate government information. Based on the Speech Act Theory, Study 1 demonstrates that commissive illocutionary acts make citizens in a low-power distance culture more likely to disseminate information. In contrast, directive illocutionary acts make citizens in a high-power distance culture more likely to disseminate information. Study 2 confirms the underlying mechanism of perceived social exchange relationship by looking at the interaction effects between illocutionary acts and power distance perception in a single cultural setting. By crawling 10,000 government microblogs, Study 3 provides objective evidence for the interaction between illocutionary acts and power distance perception on citizens dissemination behavior of information. Finally, we discuss theoretical implications for government information dissemination, managerial implications, and future research directions.
A mixed method evaluation of the quasi-experimental yoga-based intervention for the behavioural issues of school-going early adolescents in Jaffna, Sri Lanka
Authors: Sivashanakar Josephine Thirumagal , Surenthirakumaran Rajendra , Sathyakumar Nalini , Coonghe P. A. Dinesh
Published: July 2024

Introduction: Behavioural problems of adolescents, such as anger, impulsivity, hyperactivity and emotional problems is a cross-cutting issue among all communities, religions and cultures around the world. An influx of internet, social media, alcohol and illegal substances in the post-conflict period has led to the existing adolescent behaviour problems in Jaffna, Sri Lanka.Objectives: To find out the quantitative and qualitative impact of a yoga-based intervention in the personal lives of grade 8 children in selected schools in Jaffna, Sri LankaMethods: A non-randomized controlled trial was carried out in four educational zones over six months during 2017-2018. The trial implemented a yoga-based intervention package: 1) slow breathing for 5-6 minutes, 2) Surya namaskar for 6-8 minutes and 3) mindfulness meditation for 5-6 minutes. The intervention was designed by relevant experts through a desk review. In both intervention and control groups, pre/post quantitative assessments were conducted using the Strength and Difficulty Questionnaire (SDQ) of parents, teachers and students; and three focus group discussions (FGD). Thematic analysis was performed from the recordings of both FGDs.Results: The quantitative analysis indicated that according to parents’ assessments, the emotional issues (p=0.001) along with the total difficulty score (p=0.001) were reduced in the intervention group (n=584). Within the control group (n=499), teachers’ assessments indicated an increase in emotional problems (p=0.001) and a reduction in pro-social scores (p=0.001). The FGD results indicated that most of the students felt that their mind got quietened and that completing school homework was a relatively easy task after the yoga intervention.Conclusions & Recommendations: This yoga-based intervention package appeared to be effective quantitatively in reducing their externalizing and internalizing behaviour issues and qualitatively to motivate them to focus on their studies.
 Menstrual hygiene management among government school going adolescent girls in Tumakuru District, Karnataka in India: a comparative cross-sectional study
Authors: Achalkar Kusuma
Published: July 2024

Introduction: Menstruation topic remains a taboo subject shrouded  with secrecy and shame among adolescent girls, which leads to lack of discourse and dialogue. Improving menstrual hygie ne management (MHM) practices during adolescent phases reduces reproductive morbidity in future. Objectives: To estimate and compare MHM among urban and rural  government high school adolescent girls Methods: A cross-sectional comparative study was conducted am ong adolescent girls studying in 8th to 10th standard in government high schools. One urban and two rural schools were invol ved in the study to meet the required sample size. In total, 464 girls were assessed using an interviewer-administered que stionnaire. Knowledge and hygienic practices, school absenteeism, restrictions during menses and socio- demographic fa ctors were compared between the two groups. Chi-squared test was used to calculate statistical significance at p<0.05. Results: The girls were in the age group of 12-17 years; mean age of  14.6 (SD=0.92) years with the mean age of attainment of menarche 12.6 (SD=0.94) years. Knowledge on MHM was good  in 157 (62.6%) rural girls compared to 116 (54.5%) urban girls. Pads were the main type of absorbents used by girls (r ural- 128, 51.0%; urban- 167, 78.4%), however, 43% (n=108) rural girls used both cloth and pads during menstruation c ompared to 16.4% (n=35) urban girls. Dysmenorrhea was the common complaint for being absent from school. This  difference between the two groups was significant (p<0.0006). More than 50% of girls in both groups complained that t hey were not permitted to enter ritual places; however, 13.14% (n=28) urban and 22.3% (n=56) rural girls had no restrictions  during menstruation. Conclusions & Recommendations: Girls have less knowledge on m enstruation; many are still using cloth as sanitary pads and do not practice the correct method of washing and drying. A mul ti-pronged approach to improve MHM is essential.
Prevalence and correlates of anxiety disorders among school children aged 13-15 years in Colombo District, Sri Lanka
Authors: De Silva Sinha , Senaviratne Sudharshi , Samaranayake Dulani
Published: July 2024

Background: Anxiety disorders (AD) being the most prevalent psychological problem among children and adolescents remain largely unrecognized due to their nature. If untreated, AD could lead to many adverse outcomes. The aim of this study was to assess the prevalence and correlates of anxiety disorders among children aged 13-15 years attending government Sinhala medium schools in Colombo district, Sri LankaMethods: A school based cross-sectional study was conducted among 1524 children in Sinhala-medium government schools aged 13-15 years old selected by stratified cluster sampling. The presence of “any anxiety disorder” and its correlates were assessed using a pre-tested self-administered questionnaire that included validated Screen for Child Anxiety Related Disorders (SCARED). Multivariable analysis with binary logistic regression was carried out using backward elimination method to determine the association between anxiety disorders and selected correlates identified at bivariate analysis at p<0.05 level.Results: The adjusted prevalence of anxiety disorders was 12.3% (95% CI: 9.8% to 14.9%) Factors significantly associated with having any anxiety disorders at the multivariable analysis  included  being female (OR=3.0, 95% CI:2.0-4.4,p<0.001), residing away from the family (OR= 4.6, 95%:1.2-17.8, p=0.027), low to moderate self-esteem (OR=1.6, 95% CI: 1.1-2.5, p=0.022), having Stress (OR=2.3, 95%, CI: 1.5-3.6, p= <0.001), having Depression (OR= 2.5, 95% CI: 1.4-4.5, p<0.001), attending tuition classes for 5-7 days per week (OR=2.9, 95% CI: 1.9-4.3, p<0.001), non-engagement in sports activities (OR=1.6, 95%CI: 1.1-2.6, p=0.028), having a sibling/s less than one year of age ( OR=2.9, 95% CI: 1.2-6.6, p=0.015), father’s low level of education (OR=2.0, 95% CI: 1.1-3.8 p=0.044) and mother engaged in foreign employment (OR=5.3 , 95% CI: 2.0-13.9,p= 0.001), having an insecure attachment style (OR=2.7, 95% CI: 1.8-4.0, p<0.001).Conclusions: The prevalence of AD is high in this community and is associated with multiple personal, family, and educational factors. Screening for ADs need to be considered at routine mental health services.
Crystal Structures of DNA-bound Fish IRF10 and IRF11 Reveal the Determinants of IFN Regulation
Authors: Wang Zhao-Xi , Liu Bin , Xie Haizhou , Liu Xin , Li Xiangliang , Shi Fuqiang , Ouyang Songying , Zhang Yong-An
Published: July 2024

IFN regulatory factors (IRFs) are transcription factors that mediate homeostatic mechanisms of host defense against pathogens. In addition to IRF1–9, which are conserved across vertebrates, teleost fishes have two other IRFs, IRF10 and IRF11. In zebrafish (Danio rerio), IRF10 represses the expression of IFNφ1 and IFNφ3, whereas IRF11 exerts the opposite effect. In this study, we found IRF10 could significantly inhibit the expression of IFNφ1 and IFNφ3 induced by IFN11 to synergistically regulate type I IFN expression. To clarify the synergistically regulatory mechanism of IRF10 and IRF11 in type I IFN expression, we determined and analyzed the crystal structures of the DNA-binding domains (DBDs) of zebrafish IRF10 and IRF11 bound to DNA, as well as IRF11 DBD in apo form. The interactions of IRF10-DBD and IRF11-DBD with DNA backbone were elaborated in detail. Further analysis showed that IRF10 and IRF11 have the same binding patterns and comparable affinities with the IFN-sensitive response elements of IFNφ1 and IFNφ3 promoters. Therefore, IRF10 could function as a controlling factor for IRF11 by competitive binding of the IFN-sensitive response elements to coregulate the host IFN response. Accordingly, similar to IRF1 and IRF2 in mammals, IRF10 and IRF11 act as another pair of negative and positive regulators to balance the antiviral responses in fish.
An in-depth investigation of serum Krebs von den Lungen-6 and other biomarkers in COVID-19 severity and mortality
Authors: Witarto Andro Pramana , Rosyid Alfian Nur , Witarto Bendix Samarta , Pramudito Shidi Laras , Putra Achmad Januar Er
Published: July 2024

Krebs von den Lungen-6 (KL-6) is a glycoprotein mainly expressed by type II pneumocytes and recently known as a lung injury biomarker. However, the number of studies is still limited, especially in Indonesian COVID-19 populations. Therefore, we aim to provide correlation, sensitivity, and specificity analyses of KL-6 and other biomarkers in Indonesian COVID-19 severity and mortality. We conducted a cross-sectional study involving adult COVID-19 patients at Universitas Airlangga Hospital, Surabaya, East Java, Indonesia, between March 26, 2021, and August 25, 2021. KL-6 and other biomarker levels were compared according to severity (severe versus non-severe) and mortality (non-survivor versus survivor). We also included the receiver operating characteristic analysis to define the optimal cut-off, sensitivity, and specificity of KL-6 to determine COVID-19 severity and mortality. We enrolled 78 COVID- 19 patients (23 non-survivors), including 39 non-severe and 39 severe patients. There was no significant difference in serum KL-6 levels, neither in severity nor mortality groups. KL-6 had the strongest positive correlations with ferritin in severe patients (r=0.313) and non-survivors (r=0.467). We observed that the best sensitivity was KL-6 combined with platelet-to- lymphocyte ratio (PLR) (0.818) in severe patients and with neutrophil-to-lymphocyte ratio (NLR)/PLR/ferritin/C-reactive protein (0.867) in non-survivors. In contrast, the best specificity was found when KL-6 was combined with NLR/D-dimer (0.750) in severe patients and with D-dimer (0.889) in non-survivors. Serum KL-6 is a useful auxiliary laboratory evaluation index for COVID-19 lung injury to depict its severity and mortality.
Survival among patients with lung cancer managed at a tertiary care center in North India
Authors: Kumar Rahul , Gothi Dipti , Anand Shweta , Khan Shazia , Malhotra Nipun
Published: July 2024

Though there has been advancement in the management of lung cancer, it is not well utilized due to its limited availability and high cost. This is a prospective observational study done at a tertiary care center from January 2014 to December 2022, involving patients with primary lung cancer. After tumor-node-metastasis staging and molecular testing, the patients received chemotherapy, radiotherapy, surgery, targeted therapy, and immunotherapy in various combinations as per the prevailing National Comprehensive Cancer Network Guidelines. 92 patients were enrolled in the study, with the mean age being 58.94±10.33 and 72 (78.26%) being males. 69 (75%) patients were either current or former smokers. 78 (84.78%) patients had an Eastern Cooperative Oncology Group (ECOG) score of 0-2 while the remaining had an ECOG of 3-4. 80 (86.95%) patients had non-small cell lung cancer (NSCLC) [44 (47.83%) adenocarcinoma, 25 (27.17%) squamous cell carcinoma, and 11 (11.95%) NSCLC: not otherwise specified], while 12 (13.04%) patients had small cell lung cancer. One (1.08%) patient each presented in stage I and stage II, 31 (33.69%) patients presented in stage III, and 59 (64.13%) patients presented in stage IV. 44 patients with adenocarcinoma were subjected to mutational analysis, and an epidermal growth factor receptor mutation was found in 13 (29.5%) patients. None of the patients had ALK mutation, ROS-1 rearrangement, or BRAF mutation. PD-L1 expression was evaluated in 9 patients with NSCLC, and it was found in 6 (66.66%) patients. The overall mean survival was 12.7 months. The mean survival for patients with stages I, II, III, and IV was 70, 96, 8.1, and 12.7 months, respectively. Survival in stage IV was better than in stage III, as the eligible patients received targeted therapy and immunotherapy. Targeted therapy and immunotherapy have improved survival. Molecular analysis should be done whenever indicated, and eligible patients must be administered targeted therapy and immunotherapy.
Unilateral Hypoplastic Ovary with Ipsilateral Partial Hypoplastic Fallopian Tube on Laparoscopy – An Incidental Finding in a Parous Woman
Authors: Jacob Olivia Marie , Sharmila Vijayan , Garikapati Kavitha
Published: July 2024

ABSTRACT

Asymptomatic unilateral hypoplastic ovary in a parous fertile woman is rare. Hypoplastic or streak ovaries are usually associated with subfertility or premature menopause. We report a rare case of a fertile parous woman who approached us for sterilization procedure. Her ultrasonogram was found to be normal. During laparoscopy, unilateral ovary and tube were hypoplastic.
Obstructive sleep apnea risk among adults with type 2 diabetes mellitus in an urban primary care setting of Mangalore, India
Authors: Narayan Anusha , Raghuveer Pracheth
Published: July 2024

ABSTRACT

Background:

Obstructive sleep apnea (OSA) is an under-evaluated and under-treated problem, particularly among individuals with type 2 diabetes mellitus (T2DM). Therefore, in this study, we aim to determine the risk of OSA among adults with T2DM residing in an urban area of Mangalore and to elucidate the determinants of OSA among the study participants.

Materials and Methods:

A cross-sectional study was conducted for a period of 2 months among adult patients (≥ 18 years) with T2DM seeking health care at a primary care setting located in an urban area of Mangalore. Face-to-face interviews were conducted using a semi-structured proforma. STOP-BANG questionnaire was used to assess the risk of OSA among the study participants. The measurements, such as height, weight, and neck circumference, were conducted using standard techniques

Results:

The mean age of the study participants was 58.12 ± 11.60 years. The majority, (58.30%), were males, and 45.0% reported a family history of T2DM. A total of 108 (60.0%) experienced loud snoring while asleep, while 149 (82.80%) experienced tiredness during daytime. The mean body mass index (BMI) was 24.64 ± 4.9 kg/m2, while a neck circumference of >40 cms was found in 28.90%. A total of 69 (38.30%) had a high risk of OSA with a STOP-BANG score ranging from 5 to 8, while 71 (39.40%) had a score ranging from 3 to 4 (intermediate risk). The statistically significant associations were found between age >50 years, male gender, and diabetes for ≥ 7 years and high risk of OSA (P < 0.001).

Conclusion:

More than a third of the study participants had a high risk of OSA. Age > 50 years, male gender, and diabetes for ≥7 years were the factors associated with OSA.
Satisfaction of mothers with supplementary nutritional services through Anganwadi centres in an urban area of Meerut, India
Authors: Pandey Gargi , Chopra Harivansh , Bano Tanveer , Jain Seema , Singh Ganesh
Published: July 2024

ABSTRACT

Background:

Undernutrition in children under 5 years of age is still a great public health burden. Integrated child development services (ICDS) were launched with an idea of making a dent on this age-old issue. Various studies in the past have been done to identify lacunae in the programme, but very few studies are done focussing on the satisfaction of mothers with the supplementary nutrition provided through ICDS programme. The utilisation of the programme depends on various factors, one of which is client satisfaction.

Methods and Material:

The Anganwadi centres of urban areas of Meerut were line-listed after taking a list of Anganwadis from the Child Development Office. There are 297 Anganwadis in urban areas of Meerut. With help of random number tables, three Anganwadis were selected, and to complete the sample of 152, 51 children from two Anganwadis and 50 from one Anganwadi centre were selected with help of simple random tables. The data thus collected were analysed using Epiinfo version 7.2.3.1

Results:

The prevalence of underweight was found to be 34.2%, wasted 19.7%, and stunted 11.2%. Among the characteristics assessed, a majority of mothers, 58.5%, were dissatisfied with the frequency at which supplementary nutrition was provided from the Anganwadis. All children were provided Take Home Ration, and 100.0% of mothers reported using it for all family members. Still 63.2% of mothers were unaware about the iron supplementation in childhood and only 65.8% of mothers had satisfactory handwashing practices

Conclusions:

In this study, a majority of mothers were dissatisfied with the frequency at which supplementary nutrition was provided to their children. Also, the prevalence of underweight children was significantly higher when mothers were not aware about the factors affecting nutrition in children. The Take Home Ration given for children was shared among family members in 100.0% families.
Comparative analysis of nutritional status among institutionalised and community-dwelling elderly women and its association with mental health status and cognitive function
Authors: Shakil Somaiya , Ghosh Joyeta , Singh Khusboo , Chaudhury Sudrita Roy
Published: July 2024

ABSTRACT

Introduction:

Population pyramids are significantly impacted by the global phenomena of ageing. It has been reported that depression and cognitive function have an impact on the nutritional status of older adults. Depression is the most common psychiatric problem in old age, and cognitive deterioration is frequently observed in this age group.

Objective:

This descriptive and comparative study set out to compare the cognitive abilities, nutritional health and depression status of older adults who lived in community settings and in assisted living facilities.

Materials and Methods:

A total of 250 older women (125 from institutionalised old age home and 125 from community) participated in a cross-sectional study (residing at Rajarhat, Newtown area). The lengthy version of the Mini Nutritional Assessment tool (MNA®) was used to evaluate the participants’ nutritional status. The Geriatric Depression Scale (GDS 30) was used to evaluate the severity of the depression. Using the Folstein Mini-Mental State Examination (MMSE), cognitive function was assessed. Using SPSS software, the Chi-square, Kruskal–Wallis test, and Spearman’s rho correlation coefficient were computed.

Results:

In the present study, it was observed that only 30.4% of the respondents who are community-dwelling elderly had normal MNA score, whereas 69.6% were at risk of malnutrition or already malnourished. Considering institutionalised elderly it was observed that only 7.2% were normal and 92.8% were malnourished/at risk of malnutrition. Statistically significant association was observed between nutritional status and mental health status (P = 0.00) as well as cognitive function (P = 0.00) among old age home residing elderly. Among the community-dwelling elderly mental health status has significant association with their nutritional status (P = 0.00) and cognitive function (P = 0.00) as well.

Conclusions:

Community-dwelling elderly were relatively healthy compared to old age home residents. Maintaining the nutritional, cognitive, and mental health of institutionalised and community-dwelling elderly women requires the implementation of physical and cognitive stimulation activities as well as interventions targeted at improving a healthy diet.