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Characterization of thermal damage of skin tissue subjected to moving heat source in the purview of dual phase lag theory with memory-dependent derivative
This investigation is devoted to exhibit the thermal damage of skin tissue exposed to a moving heat source. Modelling of the problem is performed by adopting dual phase lag theory of bio heat transfer in context of memory dependent derivative. Laplace transform technique has been adopted to represent the analytical solutions of temperature and thermal damage of skin tissue. Thermal damages to the tissues are calculated by the extent of the denatured protein employing with the Arrhenius equation. In order to predict the significance of memory dependent derivative approach, computational results of temperature and thermal damage are evaluated in the frame of different kernel functions as well as time-delay. For the purpose of exhibiting the attractiveness of the present model, obtained results are compared with the results corresponding to the absence of memory dependent derivative. Also, the impact of the velocity of moving heat source has been precisely investigated on temperature variation and thermal damage of skin tissue using quantitative results. Authors believe that this study will be helpful to study the thermal treatment of several diseases such as hyperthermia. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Characterization, molecular docking, and therapeutic properties of biomaterial obtained from Pangasianodon hypopthalmus
The therapeutic properties of fish have been recognized since ancient times because of the presence of various fatty acids. Oleic acid, which is a mono-unsaturated fatty acid, is known for curing heart-related diseases and promoting brain health. Our study is a first attempt to evaluate the Anti-inflammatory activity, Anti-oxidant activity and perform characterization studies on mucus obtained from Pangasianodon hypopthalmus and explore its therapeutic properties. Anti-inflammatory property evaluation was performed via, albumin denaturation assay showing an 81% inhibition rate and RBC hemolysis assay with a 76.79% inhibition rate, anti-oxidant activity evaluation performed using the DPPH assay showed an 80% radical scavenging activity at 150?g/mL concentration. Overall results showed that anti-inflammatory was highest at 100mg/mL concentration and anti-oxidant activity was highest at 150?g/mL concentration. Characterization studies involved FTIR, NMR and GCMS analysis. Simulation study was performed on selected compound (ligand) against selected targets. From GC-MS analysis, C18 H34 O2 (Oleic acid), was found to be present at higher concentration. Docking studies revealed good binding energy and strong hydrogen bonding between oleic acid and TNF-?, with a binding energy of ?5.3 kcal/mol, thereby demonstrating strong anti-inflammatory activity and wound-healing potency. Further in-vitro and in-vivo analysis has to be performed to develop potential drug for therapeutic purpose. 2026 Visagaa Publishing House. -
Characterizations of some parity signed graphs
We describe parity labellings of signed graphs: equivalently, cuts of the underlying graph that have nearly equal sides. We characterize the bal-anced signed graphs which are parity signed graphs. We give structural characterizations of all parity signed stars, bistars, cycles, paths and com-plete bipartite graphs. The rna number of a graph is the smallest cut size that has nearly equal sides; we find this for a few classes of graphs. The author(s). -
Characterizing Context-Dependent Biochar Effects: An ANOVA-Based Study on Soil Properties and Microbial Diversity
Contemporary intensive agriculture has improved food security, but is a detriment to soil health, biodiversity, and long-term sustainability. Biochar is an exciting product derived from the pyrolysis of biomass that possesses great potential to be a soil amendment that can improve soil chemical, physical and biological properties and sequester carbon. This paper summarizes recent international studies (2024-2025) and contains experimental analyses showing how biochar had an effect on soil systems. Considering soil pH, hydrophobicity, porosity, and particle size were emphasized. Our findings indicate that biochar improves soil structure, water retention, nutrient retention, and diversity in microbes, all of which increase crop resilience under abiotic stress conditions. However, there is a context-sensitivity to the utilization of biochar - often changing with soil types, feedstock, pyrolysis, and application rates. By using standardized and characterizing methods in soil characteristics and ANOVA based statistical analysis, this study presents the rationale and insights, opportunities and limitations of biochar as a sustainable soil conditioner. Further, the findings suggest to tailor "designer biochars". It seems plausible that these could be optimized for targeted soil and crop systems, and be a vital tool in developing climate-resilient and sustainable. 2026 IEEE. -
Characterizing Ultimatum Game responders: a scoping review of factors that influence decision-making through an evolutionary lens
The Ultimatum Game is a widely used tool for studying conflict resolution within a bargaining framework. This scoping review aims to comprehensively examine the various internal and external factors influencing the responders behavior in this game and compile the status quo of the knowledge space. 31 pertinent research articles were identified from databases like Google Scholar, PubMed and JStor, using the following keywords ultimatum game, responder behavior, emotions and the ultimatum game, fairness in the ultimatum game, social norms and the ultimatum game, punishment game, impunity game, outside options in the ultimatum game. An analysis of the same yielded two broad domains of influencing factors: internal and external. Internal factors encompassed emotions, personality traits, and cognitive capabilities, showcasing their significant influence on decision-making. External factors, including ownership, social norms, power dynamics, outside options, gender, and attraction, revealed how the context of the game shaped responder choices. This review investigates how internal and external factors influence bargaining behavior within the Ultimatum Game, distinguishing between typical and atypical responder behavior. Invoking Kahnemans dual system theory offer insights into the evolutionary roots and modern cognitive processes guiding decision-making. The interplay between these systems reveals nuanced responses to fairness, reciprocity, and self-interest, challenging traditional economic models. While acknowledging the oversimplification of brain dynamics in these studies and also the need for cultural integration, the current review compiles a framework that advances our understanding of human behavior across disciplines, particularly for economics, psychology, and evolutionary biology. Refining this model promises deeper insights into decision-making processes amidst societal complexities. Copyright 2026 Chowdhury, Rangaswamy and Kolte. -
CHARM: Context-based Hierarchical Association Rule Mining for Analyzing Purchase Patterns
Data mining is now an essential part of business intelligence, specially in the retail analytics, allowing companies to derive meaningful insights out of big volumes of transaction data. This paper uses Context-Based Hierarchical Association Rule Mining to study purchase behavior in Indian retail outlets through Apriori algorithm that helps to take effective decissions. The available literature primarily employs flat item association models and lacks contextual dimensions and profit-oriented outcomes of rules, which also creates an evident gap in the current research. The study combines various contextual aspects, including product category, sub-category, region, and state, to produce the multilevel association rules indicating the product relationship under different sales levels of the products following an hierarchy. The Lift and Conviction metrics are applied along with support and confidence to eliminate the coincidental patterns and make the rules in business reliable. Support-based filtering and a minimum threshold of confidence of 0.1 are used to determine separate patterns of co-purchase that are significant. In order to make business relevant, the level of profit is involved as a result which puts into emphasis rules which lead directly to financial performance. The findings show that context-enriched rules offer a better insight into customer buying behavior and retailers have the opportunity to identify profitable cross-selling opportunities that more traditional flat associated analysis might otherwise miss. The hierarchical structure allows improving interpretability through associating items with larger contextual properties, which will be useful in designing the promotion, product placement, and optimizing the regional strategy. Overall, this paper presents the combination of contextual and profit-driven parameters as a concept that can be used to provide a data-driven basis of strategic retail decision-making and sustainable competitive advantage. 2026 IEEE. -
Charting Industry 4.0 Routes Incubation Centers: A Study on Atal Incubation Centre
Start-ups have garnered significant attention in India, as well as many other areas of the world, in the past few years. Start-ups may produce significant solutions through innovative and adaptable technology, acting as vehicles for socioeconomic growth and transformation. Some businesses were created in recent times, but the ecosystem was still in its infancy, with just a few investments and a limited number of support programs such as incubators. As business environments have evolved, there are signs that the function of incubators has shifted and extended to a center giving training, with over 20, 000 start-ups and a year-on-year growth rate of 10-12%, India boasts the worlds second largest start-up ecosystem. Since business settings have changed, there are indications that the purpose of incubators has moved and expanded to a center for training and support, connecting, and consulting to new enterprises in all fields of specialization rather than just a business center with office space. According to incubators, the major worry or problem was establishing suitable infrastructure with specialized technology that met the demands of the companies. In terms of investment, incubators were concerned about the schemes rigidity. Some incubators opted to extend financing or make grants rather than make equity investments. This issue originated largely from the regulatory complexities of incubators at educational institutions that make equity-based investments in businesses. Start-ups do not exist in isolation, but rather as a component of the larger economy. In terms of the regulatory framework, it is thought that enhancing the execution of existing start-up regulations and eliminating inefficiency within the administration is critical to making it easier for start-ups to do business. Start-ups would benefit from less paperwork and documentation, improved access to information, more standardized operational processes, and clear criteria. 2023 Taylor and Francis Group, LLC. -
Charting the Complexity of Diabetes Risk using Network-based Exploration of Nonlinear Interactions
Diabetes mellitus is a global health challenge shaped by complex clinical, demographic, and socioenvironmental factors. Traditional linear models often overlook the non-linear dependencies that drive diabetes risk. This study adopts a systems-thinking approach by integrating mutual information (MI)-based network modeling with machine learning to improve prediction, interpretability, and fairness. Using a nationally representative CDC dataset, we build a weighted undirected network where variables are nodes connected by MI-derived edges. Centrality analysis identifies age, HbA1c, and BMI as key hubs. Community analysis reveals clinical, demographic, and racial modules, reflecting the multidimensional nature of diabetes risk. These network insights inform feature selection for training logistic regression, random forest, and XGBoost models. XGBoost achieves the highest accuracy (95.3%) and AUC (0.939), while logistic regression offers the best calibration (Brier score = 0.045), enhancing clinical usability. Subgroup analysis shows stable predictions across racial groups, supporting fairness. This integrated framework uncovers latent, non-linear associations and offers a robust, interpretable, and equitable tool for precision diabetes risk modeling. 2025 IEEE. -
Charting the Course of Leadership Through the Digital Era: A Synergy of Leadership Styles, Technology Integration, and Deep Learning
This chapter aims to provide actionable strategies for empowering leaders in leveraging technology to amplify their leadership efficacy in contemporary business environments by employing extensive literature review and deep learning models, a method in Artificial Intelligence (AI). It investigates the effectiveness of three leadership approachesTransformational, Transactional, and Servant Leadershipin meeting high-performance expectations within organizational contexts. The performance of these leadership styles based on their effectiveness scores have been analyzed using data analysis techniques and neural network models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Furthermore, Deep Convolutional Generative Adversarial Networks (DCGANs), have been utilized to visualize complex leadership dynamics. The findings from this comprehensive analysis provide valuable insights into the strengths and limitations of each leadership approach, guiding strategic leadership development initiatives and organizational decision-making processes. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Charting the Future of Fintech: Unveiling Finoracle through an In-depth Comparison of LLAMA 2, FLAN, and GPT-3.5
The research paper compares three Large Language Models (LLMs): LLAMA 2, FLAN, and GPT-3.5, in summarizing financial technology (fintech) news. Using 100 articles and the Rouge scoring system, it focuses on LLAMA 2's superior performance in creating concise and precise summaries. The study also introduces FinSage, a new framework utilizing LLAMA 2, promising to enhance fintech text analysis and decision-making. It concludes that LLAMA 2 sets a new standard for AI in financial data processing and analysis. 2024 IEEE. -
Chatbot Service Quality in Banking : Analyzing Indian Banking Customer Perceptions and Influence on Customer Satisfaction and Value
Purpose: The study has two objectives: first, to determine the quality of chatbot services provided by Indian banks; second, to assess the influence of chatbot service quality variables on customer satisfaction and customer value. Research Methodology: The study used a quantitative methodology, selecting individuals at random from a group of Indian banking clients. We used a questionnaire to collect data from the selected sample as part of a causal research investigation. We made use of SPSS and Python for this analysis. Customer satisfaction and value were taken into account as the dependent variables in our study. The seven elements of service qualityfunctionality, convenience, security, design, customization, enjoyment, and assurancemade up the independent variables. Findings: According to this study, client satisfaction and value were significantly shaped by the quality of the services provided. Customers value was significantly impacted by functionality and enjoyment, and their satisfaction was greatly influenced by assurance, design, and personalization. The unexpected negative impact assurance had on customer value is noteworthy and calls for more research. Practical Implications: In the highly competitive banking industry, this research has important ramifications for banks. It highlighted how important service quality is, which led banks to give priority to customer pleasure and think about making strategic changes. Banks could obtain a competitive advantage by improving the quality of their services, improving chatbot services, and implementing a customer-centric strategy by utilizing the research findings that have been presented. Our research helped banks evolve with the needs of their customers in mind, enabling them to gain credibility, repeat business, and long-term success in the ever-changing banking services market. Originality/Value: This study examined how consumers in Indian banks perceive the value and satisfaction of chatbot services and how they use them. The study provided useful recommendations and concepts to improve the general consumer experience. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Chatbots as tools for psychoeducation and self-help in mental health
The chapter highlights the role of mental health chatbots in solving problems in global mental health. It aims to explore how AI-powered conversational agents bridge the gap between growing demand and limited availability of mental health services. The authors explain advantages of chatbots, including accessibility, affordability, and user anonymity. They investigate the effectiveness of chatbots in improving treatment outcomes, meeting user needs, and improving operational efficiency. In addition, the chapter highlights the ability of chatbot as a knowledge sharer that seamlessly integrates information from various sources and keeps professionals up to date with current events. It deals with psychoeducation in clinical and non- clinical populations, covering biological, cognitive, emotional, and behavioural aspects. The authors also discuss the potential of chatbots in screening and self- help. Finally, they emphasise the importance of collaboration between psychologists, physicians, and engineers to optimise the development of chatbots to respond dynamically to user needs. 2025, IGI Global Scientific Publishing. All rights reserved. -
Chatbots in Banking: Transforming Customer Interaction and Service Efficiency Through AI
The advent of Artificial Intelligence (AI) and chatbot technologies has brought drastic transformative changes to the banking sector which has reshaped customer engagement, enhanced efficiency and provided 24/7 assistance to the customers. The paper investigates the usage and impact of AI-powered chatbots on the customer experience and overall performance of the banking institutions through thorough analysis of recent advancements in technology, the study explores how chatbots which are leveraging machine learning (ML) and natural language processing (NLP) are used to address customer enquiries, facilitate transactions and offer customized financial guidance. Additionally, the current study also examines the influence of chatbots on customer satisfaction, regulatory compliance and measures of security highlighting both the advantages and challenges of such systems. Hence, the aim is to contribute to a comprehensive understanding of chatbots' role in banking providing insights into their effectiveness and potential for the future refinement to meet evolving customer expectations. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Chatbots in health care: AI-based personalization and EHR integration in patientdoctor communication
The artificial intelligence (AI)-driven chatbots in healthcare integration revolutionizes patientprovider interactions for real-time support, communication streamline, and patient engagement. These chatbots connected to natural language processing (NLP) and machine learning provide medical queries resolution, chronic condition management, and scheduling appointments. Despite the advancements, there are gaps remain in the chatbot personalization interactions and Electronic Health Records (EHR) seamless integration. Personalization is crucial for satisfied patient and medical advice. EHR integration enables context-aware responses, error reduction, and better healthcare outcomes. This study effectiveness fosters the evaluation of AI-driven chatbots in healthcare communication personalization and potential benefits examination and EHR integration challenges. Using a mixed-methods approach includes sentiment analysis for patient satisfaction sentiments understanding, thematic analysis for key themes and findings from Patient Message, regression analysis for personalization, EHR integration, and patient outcomes understanding, and structural equation modeling (SEM) highlights the personalization and EHR integration impact on patient satisfaction, engagement, and trust in chatbot technology. The findings reinforcing the healthcare providers need to adopt AI-driven solutions and personalized communication priorities and seamless data integration for patient experience improvement and overall healthcare efficiency. 2026 Elsevier Inc. All rights reserved. -
ChatGPT and Academia: Exploring the transformations and transitions
Since its launch in November 2022, this tool has brought massive transformations in almost every imaginable field. Among those fields, academia is perhaps the most discussed domain. However, much of what ChatGPT can do is still understudied. Therefore, this chapter aims to investigate the potential impact of ChatGPT in the domain of academia while exploring the possibilities for the future. The study emphasizes the theories that link ChatGPT's presence to its effects on academia and research. 2024, IGI Global. All rights reserved. -
ChatGPT and Me: A Dual Factor Examination
ChatGPT advances human-like conversations based on prompts and has been popular among students. ChatGPT offers advantages, but students have also experienced disadvantages, which affect their intention to use it. Drawing on this concern, this research uses a mixed-method approach. For study 1, 45 semi-structured interviews were conducted. Based on these responses, 10 constructs were identified. Using a Dual-factor approach, we categorized convenience, perceived enjoyment, perceived interactivity, learner autonomy, personalization and AI quality as Enablers and technological insecurity, poor information quality, diminishing critical thinking, and plagiarism as Inhibitors. For Study 2, data was collected through a questionnaire from 525 respondents. Structural equation modeling was employed to find support for all the Enablers and Inhibitors except plagiarism. The study also tested the moderating role of FOMO between enablers and students ChatGPT usage intention. This study contributes to the theoretical underpinnings of ChatGPT usage and provides practical implications for educators, learners and developers. 2025 International Association for Computer Information Systems. -
ChatGPT and virtual experience: Student engagement in online script writing-An experimental investigation among media students
To study and assess the immersive virtual environment experience of ChatGPT on student engagement in online script writing among media students, an experiment was conducted at the VR Experiential Lab, Christ University, between September 2023 and January 2024. The media students were tasked with writing a script for a short film within a VR environment, with ChatGPT displayed using an Oculus HMD (head-mounted display). A total of 180 students were recruited for the study through purposive sampling, and experiment photos are provided in the appendix. The data collection tool utilized was the virtual experience questionnaire developed by Tcha-Tokey. 2024, IGI Global. All rights reserved. -
ChatGPT in education: Augmenting learning experience or dehumanizing education?
This chapter critically examines the potential of ChatGPT, an AI language model, to revolutionise education. It presents a comprehensive analysis of the advantages and disadvantages of using ChatGPT in education, including its ability to enhance the learning experience and the potential loss of essential skills due to over-reliance on technology. The chapter also raises ethical concerns about using ChatGPT in education, including data privacy and bias. Ultimately, the chapter concludes that ChatGPT should be used with human teachers to create a learning environment combining technology and human interaction. It highlights the importance of using ChatGPT responsibly to enhance, rather than dehumanise, education. 2024, IGI Global. All rights reserved. -
Chemical castration: Justice for victims or justice for the rapist /
American Journal of Criminal Law, Vol.3, pp.1-5, ISSN No: 2581-5504. -
Chemical Demineralization of High Volatile Indian Bituminous Coal by Carboxylic Acid and Characterization of the Products by SEM/EDS
Journal of Environmental Research and Development, Vol-6 (3A), pp. 653-659. ISSN-0973-6921