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                <text>From my research to our research: moving toward titi as an Indigenous method in Mizo research</text>
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                <text>Mizos (an Indigenous community in North-East India) have a form of communication called titi (conversation based on looking out for one another and laughing together). In Mizo academia, there have not been attempts made to establish titi as a Mizo Indigenous method. This article aims to situate titi as a Mizo Indigenous method by locating it within the Mizo Indigenous Paradigm through the Mizo Indigenous Standpoint. Indigenous scholars have stated how relationality sums up the Indigenous Paradigm. This article further looks at the roots of relationality by exploring the values and ethics of Indigenous communities as something that creates a special bond in the research process through titi. In doing this, it also looks at the Mizo Indigenous worldview through humor. In this way, we argue that Mizo Indigenous peoples feel accountable to the research, thereby making participants feel like the research belongs to them and acting like researchers themselves.  The Author(s) 2025</text>
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                <text>From physical to digital: what drives generation Z for mobile commerce adoption?</text>
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                <text>Attitude; Buying intention; Generation Z; M-commerce; Perceived behavioral control; Subjective norm; Theory of planned behavior</text>
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                <text>Purpose: This study aims to identify factors affecting generation Z as the early adopters of mobile commerce (m-commerce). The research seeks to explore their behavioral intention to adopt m-commerce in India with consideration of gender differences while providing empirical validation for the theory of planned behavior (TPB). Design/methodology/approach: In this study, a modified TPB model has been used to explain generation Zs intention to adopt m-commerce. The proposed model was tested using a survey method with a sample of 245 students from a private university in Northern India. Subgroup analysis was performed to find gender differences in the process of adopting m-commerce. Findings: All three independent constructs have a positive influence on the behavioral intention of generation Z to adopt m-commerce. Further, the male subgroup has a lower beta value for attitude and higher beta value for subjective norm in comparison to the female subgroup. For perceived behavioral control, no significant difference in beta value across gender could be established. Practical implications: A better understanding of generation Z behavioral intentions will be of great use to telecom companies, marketers and electronic commerce companies to formulate strategies to expedite the use of m-commerce. As gender plays an important role in attitude and subjective norms, companies are advised to target their communication tactics in accordance to gender. Originality/value: To the best of the authors knowledge, this study is one of the first to test TPB and generation Z association in the context of m-commerce adoption in India. Data regarding the difference between the two genders has also shed light on the uniqueness of the context.  2021, Emerald Publishing Limited.</text>
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                <text>Verma D.; Tripathi V.; Singh A.P.</text>
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                <text>Journal of Asia Business Studies, Vol-15, No. 5, pp. 732-747.</text>
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                <text>Emerald Group Holdings Ltd.</text>
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                <text>&lt;a href="https://doi.org/10.1108/JABS-05-2020-0207" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1108/JABS-05-2020-0207&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114452818&amp;amp;doi=10.1108%2FJABS-05-2020-0207&amp;amp;partnerID=40&amp;amp;md5=9f7a18ef6a27e72c175aa475aadca7a6" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114452818&amp;amp;doi=10.1108%2fJABS-05-2020-0207&amp;amp;partnerID=40&amp;amp;md5=9f7a18ef6a27e72c175aa475aadca7a6&lt;/a&gt;</text>
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                <text>ISSN: 15587894</text>
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                <text>Verma D., Institute of Business Management, GLA University, Mathura, India; Tripathi V., School of Business and Management, Christ (Deemed to be) University, Delhi NCR Campus, Ghaziabad, India; Singh A.P., Department of Applied Psychology VBS, Purvanchal Univerisity, Jaunpur, India</text>
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                <text>Monson, Merlin; Sabarmathi, G.</text>
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                <text>From Prediction to Action: Counterfactual Explanations and Ensemble Learning for Explainable Maternal Health Risk Modelling</text>
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                <text>2025 2nd International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2025;</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICCAMS65118.2025.11234042" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICCAMS65118.2025.11234042&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105030065420?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105030065420?origin=resultslist&lt;/a&gt;</text>
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                <text>Monson M., Christ (University), School of Business and Management, Karnataka, Bengaluru, India; Sabarmathi G., Christ (University), School of Business and Management, Karnataka, Bengaluru, India</text>
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                <text>Maternal health is critical to women's well-being, particularly during pregnancy, delivery, and postpartum. Early prediction and prevention of health risks are essential for reducing complications and improving outcomes. This research introduces a stacking ensemble model for maternal health risk prediction, combining the strengths of Random Forest, XGBoost, and Gradient Boosting with XGBoost as the meta-model. The ensemble approach enhances accuracy and reliability, achieving a classification accuracy of 91.13%, with precision, recall, and f1-scores exceeding 85% across all risk categories.Beyond accurate prediction, this study emphasizes model interpretability through Diverse Counterfactual Explanations (DiCE), an Explainable AI (XAI) method that provides actionable insights for risk reduction. Counterfactual analysis identifies the minimal changes needed in the patient features to shift a high- or medium-risk classification to low-risk, offering clinically relevant recommendations. These counterfactuals are generated to ensure feasibility, preserving physiological plausibility and practical applicability for healthcare professionals. This work bridges the gap between black-box machine learning models and actionable decision-making by integrating predictive power with explainability, supporting more transparent and patient-centric maternal health interventions.   2025 IEEE.</text>
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            <description>The topic of the resource</description>
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                <text>Counterfactual explanations; DiCE; Ensemble model; Explainable AI; Maternal health; Stacking model</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISBN: 979-833159610-1;</text>
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            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="283756">
                <text>Siju, Marbin; Bose, Shreya; Vijayalakshmi, A.</text>
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                <text>From Preprocessing to Prediction: An Analytical Study on Diabetes Data</text>
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                <text>01-01-2026</text>
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              <elementText elementTextId="283759">
                <text>Artificial Intelligence for Predictive Healthcare: Towards Personalized Treatment and Disease Prevention;pp.33-62</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003674542-3" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003674542-3&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105034236743?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105034236743?origin=resultslist&lt;/a&gt;</text>
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                <text>Siju M., Department of Statistics and Data Science, CHRIST University, Bangalore, India; Bose S., Department of Statistics and Data Science, CHRIST University, Bangalore, India; Vijayalakshmi A., Department of Statistics and Data Science, CHRIST University, Bangalore, India</text>
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            <description>An account of the resource</description>
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                <text>Early detection of diabetes is crucial for improving a patients long-term health. In this chapter, we study diabetes and diabetes-related factors. We also delve into various imputation techniques used to address missing data. Missing data is generally a very critical issue in healthcare analytics, as a limited history of clinical records often leads to biased analysis and suboptimal model representation. This chapter gives a detailed literature review of data imputation methods. In this chapter, we have done two case studies. In the first case study, mean, median, and mode imputation techniques are applied to artificially created missing values to examine their effect on the structure and distribution of the data. The second case study captures a prediction model for a diabetes diagnosis using the same dataset. Here, a random forest prediction model is created to predict the possible presence of diabetes. An accuracy of 97.07% is achieved on the test data, which shows that diabetes can be predicted by considering other dependable variables.  2026 selection and editorial matter, Syed Nisar Hussain Bukhari; individual chapters, the contributors.</text>
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              <elementText elementTextId="283763">
                <text>CRC Press</text>
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                <text>ISBN: 978-104058017-2; 978-100367454-2;</text>
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              <elementText elementTextId="283767">
                <text>Restricted Access; Hardcopy may be available in the library</text>
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                <text>Abhay Bhaskaran, M.T.; Joseph, Akash Varughese; Thomas, Romal; Kavitha, S.</text>
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                <text>Proceedings of the 2025 International Conference on Technology Enabled Economic Changes, InTech 2025;pp.489-496</text>
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                <text>&lt;a href="https://doi.org/10.1109/InTech64186.2025.11198226" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/InTech64186.2025.11198226&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105024920196?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105024920196?origin=resultslist&lt;/a&gt;</text>
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                <text>Abhay Bhaskaran M.T., Christ University, Department of Computer Science, Bangalore, India; Joseph A.V., Christ University, Department of Computer Science, Bangalore, India; Thomas R., Christ University, Department of Computer Science, Bangalore, India; Kavitha S., Christ University, Department of Computer Science, Bangalore, India</text>
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                <text>The blockchain is transforming the way supply chains operate. It is a decentralized peer-to-peer system that ensures safe and transparent data interchange. Because there is no central authority, blockchain technology can't be hacked; the data are dispersed throughout numerous nodes. Therefore, more openness, safety, and resistance to tampering are assured as opposed to conventional centralized database systems that depend on a single authority to manage all the data. This would ensure the immutability of the transaction log, which accurately traces the products from origin to destination. The supply chain refers to the transportation and distribution of goods when transactions are verified in real time and integrated into a secure, cryptographic ledger. This decentralized framework provides better tracking of various manufacturers, reduced chances of fraud, and greater trust among the participants. The early understanding based on tracking will definitely helps the stakeholders to improve the blockchain activities, reliability, it will minimize risks, and enhances efficiency. This will parallelly help those who are involved within supply chain management giving high accountability and seamlessness in the movement of details.  2025 IEEE.</text>
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                <text>AI; Anomaly detection; Autoencoders; Blockchain technology; Classification; Forest; Isolation; Optimization; Supply chain; SVM</text>
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              <elementText elementTextId="275547">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>From Public Awareness to Phygital Action: Health Literacy, Economics, and Leadership in Indias Healthcare Reform</text>
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                <text>Nadampalli B., Christ University, India; Jain S.A., Christ University, India</text>
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                <text>Over seven decades, Indias health reform has transitioned from traditional awareness programs to participatory phygital (physical + digital) models. This paper traces the evolution of health literacy governance through successive Five- Year Plans (19512017), analyzing how economic priorities, marketing strategies, and leadership paradigms shaped reform outcomes. It highlights the shift from rural welfare and communicable disease control to challenges of lifestyle disorders, digital health equity, and nutrition security. Persistent gaps in efficiency, communication, and leadership integration across the phygital ecosystem are identified. The study concludes with recommendations to embed health literacy, digital inclusion, and collaborative leadership within Indias public health framework, advancing equitable, action- oriented, and sustainable healthcare reform.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Change initiatives often encounter resistance from employees, impeding successful implementation. Leveraging insights from neuroscience can provide valuable guidance in navigating this resistance and promoting readiness for change. Social experiences in a work environment affect the brain positively or negatively. By understanding the brain's response to change, change managers can create a supportive environment and communicate accordingly. This study examines the impact of social experiences on readiness to change among employees in the manufacturing sector from a neuroscience perspective. SCARF is a neuroscience-based model that evaluates five dimensions of social experiences such as status, certainty, autonomy, relatedness, and fairness. This quantitative study is based on data collected from different manufacturing organisations. The results of this study provide insights into how change managers can address these social domains to promote successful change initiatives and improve employee readiness to change.  2023 by IGI Global. All rights reserved.</text>
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                <text>Using Organizational Culture to Resolve Business Challenges, pp. 222-246.</text>
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                <text>Lopez A.F., CHRIST University (Deemed), India; Joy S., CHRIST University (Deemed), India; Kumar A.A., CHRIST University (Deemed), India</text>
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                <text>From Sensors to Action: Human-Centred Approaches to Communicating Earthquake and Flash-Flood Warnings</text>
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                <text>Building Resilience through Multi-Hazard Early Warning Systems;pp.367-403</text>
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                <text>Singha R., Christ University, India; Singha S., Kristu Jayanti University, India; Mookambigai G., Sathyabama Institute of Science and Technology, India; Ruben V.M., Christ University, India; Haokip A.D., Don Bosco College, Maram, India</text>
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                <text>Multi-hazard early warning systems (MHEWS) are critical instruments for reducing disaster-related losses in an era marked by intensifying seismic and hydrometeorological risks. Despite advances in sensor technologies and predictive analytics, the effectiveness of early warning systems depends largely on how warnings are communicated, interpreted, and acted upon by diverse populations. This chapter examines the transition from sensor-based detection to actionable public response, focusing on emerging technologies and human-centred dissemination strategies for earthquake and flash-flood warnings. Integrating perspectives from disaster risk reduction, communication theory, and socio-technical systems, the chapter highlights gaps between technological capability and social uptake. It proposes an integrative framework that aligns real-time sensing, decision support, and inclusive communication to strengthen resilience across vulnerable communities.  2026 by IGI Global Scientific Publishing.</text>
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                <text>From Text to Action: NLP Techniques for Washing Machine Manual Processing</text>
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                <text>BERT; Extraction; Hugging Face; Ontology; Q/A Pipeline; Segmentation of text; Text Summarization; Translation</text>
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                <text>This scientific research study focuses on the advancements in Natural Language Processing (NLP) driven by large-scale parallel corpora and presents a comprehensive methodology for creating a parallel, multilingual corpus using NLP techniques and semantic technologies, with a particular focus on washing machine manuals. The study highlights the significant progress made in NLP through the utilization of large-scale parallel corpora and advanced NLP techniques. The successful creation of a parallel, multilingual corpus for washing machine manuals, coupled with the integration of semantic technologies and ontology modeling, demonstrates the broad applicability and potential of NLP in diverse domains.The research covers various aspects, including text extraction, segmentation, and the development of specialized pipelines for question-answering, translation, and text summarization tailored for washing machine manuals. Translation experiments using fine-tuned models demonstrated the feasibility of providing washing machine manuals in local languages, expanding accessibility and understanding for users worldwide. Additionally, the study explored text summarization using a powerful transformer-based model, which exhibited remarkable proficiency in generating concise and coherent summaries from complex input texts. The implementation of a question-answering pipeline showcased the effectiveness of various language models in handling question-answering tasks with high accuracy and effectiveness.Additionally, the article discusses the processes of data collection, information preparation, ontology creation, alignment strategies, and text analytics. Furthermore, the study addresses the challenges and potential future developments in this field, offering insights into the promising applications of NLP in the context of washing machine manuals.  2024 Elsevier B.V.. All rights reserved.</text>
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                <text>Biju V.G.; Babu B.; Asghar A.; Prathap B.R.; Reddy V.</text>
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                <text>Procedia Computer Science, Vol-235, pp. 1903-1919.</text>
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                <text>Biju V.G., THWS, Germany, Germany; Babu B., THWS, Germany, Germany; Asghar A., THWS, Germany, Germany; Prathap B.R., CHRIST Deemed to Be University, Bangalore, India; Reddy V., CHRIST Deemed to Be University, Bangalore, India</text>
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                <text>From Text to Ticker: A Comprehensive Survey and Methodological Guide to Named Entity Recognition in Finance</text>
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                <text>Vidhani N., Christ University, Department of Computer Science, Bangalore, India; Ramasamy G., Christ University, Department of Computer Science, Bangalore, India; Syam Mohan E., Christ University, Department of Computer Science, Bangalore, India</text>
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                <text>The financial industry generates vast volumes of unstructured textual data from sources such as regulatory filings, news articles, social media, and earnings call transcripts. Extracting structured and actionable intelligence from this data remains a significant challenge. Named Entity Recognition (NER) is a fundamental task in natural language processing that supports this process by identifying and categorizing key information within text. However, the linguistic complexity, contextual ambiguity, and domain-specific terminology of financial text require specialized approaches that extend beyond general-purpose NER models. This paper presents a comprehensive survey and methodological guide to Financial Named Entity Recognition (Fin-NER). It begins by introducing the core concepts of NER while highlighting the unique challenges posed by financial text. The paper then reviews the evolution of Fin-NER approaches, ranging from rule-based systems and classical machine learning techniques to modern deep learning architectures. Furthermore, it analyzes the distinction between fine-tuned transformer-based models and general-purpose large language models in the current research. The study also examines commonly used datasets and evaluation metrics for benchmarking Fin-NER systems. Finally, it discusses key findings, existing methodological limitations, and future research directions, including hybrid modeling strategies, cross-lingual datasets, and the development of more reliable and explainable systems. Overall, this work serves both as a scholarly review of the Fin-NER field and as a practical guide for researchers and practitioners seeking to transform unstructured financial text into structured and informative representations.  2026 IEEE.</text>
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                <text>Benchmark Analysis; Deep Learning; Domain Adaptation; Financial Natural Language Processing (Fin-NLP); Financial Text Mining; FinBERT; Information Extraction; Large Language Models (LLMs); Named Entity Recognition (NER); Transformer Models</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>From the homestead to centerstage: A journey of empowerment; [De la granja al centro de escena: Un viaje de empoderamiento]</text>
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                <text>Gender Equality; Government Interventions; Political Participation; Women Empowerment</text>
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                <text>The Kerala Model of Development has been widely acclaimed for its contribution in generating favourable social indices at par with Scandinavia. The central issue to the development in almost all underdeveloped and developing countries is the empowerment of women constituents. In Kerala, the story of empowerment of women is not just economic, but psychological too. Under Article 243(D) of the Constitution of India, there is a mandate to provide 50% reservation for women in Local Self-Government Institutions (LSGIs). This constitutional amendment is regarded as a path-breaking move to empower women at the grassroots level. This article portrays the impact of government interventions for ensuring the participation of women in decision-making as well as in the power structure in LSGIs. The researcher(s) used multiple case study design and adopted purposive sampling. The data was collected through in-depth interviews and focus group discussions were used for triangulation. The finding of the study shows that how the women are empowered though various government interventions such as Kudumbashree (the name of Keralas Poverty Eradication Mission), Mahatma Gandhi National Rural Employment Guarantee Act (the job guarantee scheme in India), Accredited Social Health Activist Scheme (a scheme of National Rural Health Mission) and Local Self-Government Institutions.  2020, Hipatia Editorial. All rights reserved.</text>
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                <text>Babu A.; Jose S.</text>
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                <text>International and Multidisciplinary Journal of Social Sciences, Vol-9, No. 3, pp. 230-259.</text>
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                <text>ISSN: 20143680</text>
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                <text>Babu A., Christ (Deemed to be University), Bangalore, India; Jose S., Loyola College of Social Sciences, Trivandrum, India</text>
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                <text>From the local to the global: the journey of Suguna Foods</text>
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                <text>Business development; Corporate growth; Diversification; Innovation; Marketing strategy; Supply chain strategy</text>
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                <text>Learning outcomes: On completion of this case study, students will be able to understand collaboration and synergy between farmers and organisations through value creation, like fundraising, based on the comprehension of the resource-based theory; understand the overview and concept of the value chain and supply chain management in the agribusiness to reduce costs of inventories; understand the concept of segmentation and positioning to increase revenue for organisations by leveraging existing resources  human and financial; and understand the branding strategy to create a sustainable competitive advantage for Suguna Foods. Case overview/synopsis: Suguna was started by two brothers, B. Soundararajan and G.B. Sundararajan, to help other farmers. Suguna, with just 200 broilers in 1984, grew to be the number 1 poultry company across India. Soundararajan was a pioneer and innovator who started contract farming in India in 1991. This model helped both the farmers and the company to became successful. The farmers always struggled to pay the cost of feed and other materials, as credit was not readily and easily available from financial institutions. Suguna helped farmers by providing feed, medicines, etc., free of cost in return for the good rearing of chickens. Because of the success of this venture, they decided to continue with it. Today, Suguna is a successful company that sells chicken, eggs and processed meat. They modernised the retail chain to supply consumers with fresh, healthy and hygienic meat. Sugunas vision was to Energize rural India by helping farmers succeed. They helped over 40,000 farmers from 15,000+ villages in 18+ Indian states. Although the growth helped both farmers and Suguna, the increased cost of raw materials for Suguna and increased input costs/power costs for farmers had to be tackled on a war footing so that both could have good income despite the increased inflation. Moreover, the retail price of live chicken was more or less stagnant in the past five years, especially after the start of the COVID-19 pandemic. Complexity academic level: This case can be used as the basis for a 90-min class discussion. This case study is suitable for use in an master of business administration course module or in an executive education program on developing an understanding of value creation in the business model in a rural market and also how the supply chain works. This case study can also be used to teach pricing, segmentation in marketing and supply chain perspectives and decision-making skills. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing.  2023, Emerald Publishing Limited.</text>
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                <text>A S.; Kumar S.; Khanna S.</text>
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                <text>Emerald Emerging Markets Case Studies, Vol-13, No. 4, pp. 1-23.</text>
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                <text>Peanut-shell-based polymer composites have gained significant attention as sustainable and cost-effective materials with potential applications as food packaging films, ceiling tiles, insulation panels, supercapacitors, and electrodes in various industries like the packaging industry, construction, furniture, and electronics. This review article presents a systematic roadmap of the mechanical properties of peanut-shell-based polymer composites, analyzing the influence of factors such as filler content, surface modification techniques, interfacial adhesion, and processing methods. Through an extensive literature review, we highlight the mechanical properties of peanut-shell-based polymer composites. Furthermore, challenges and ongoing research efforts in this field are discussed. This comprehensive review provides valuable insights for researchers, industry professionals, and policymakers, promoting the development and utilization of peanut-shell-based polymer composites for various applications.  2023 by the authors.</text>
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                <text>Mandala R., Department of Mechanical Engineering, Vignan Institute of Technology &amp;amp; Science, Deshmukhi, Telangana, Hyderabad, 508284, India; Hegde G., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India, Centre for Advanced Research and Development, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Kodali D., Department of Mechanical Engineering, Christian Brothers University, Memphis, 38104, TN, United States; Kode V.R., Department of Chemical and Biochemical Engineering, Christian Brothers University, Memphis, 38104, TN, United States</text>
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                <text>In this challenging, demanding, daunting, and competitive business world, the rise, and growth of cybercrimes are very high. With the proliferation of Cloud Computing techniques, usually in industrial arenas, business information and important clients data are stored and managed using cloud platforms. Application programs are developed to handle such valuable information assets of the organizations. Cloud backups are provided for these client data where security is the most concerning aspect. There are many vulnerabilities in the current scenario where intruders can cause havoc. Destruction of the product can happen by exploiting vulnerabilities that can put the company and the product in jeopardy. It may create a bad impression about the organization among the customers, competitors, and the public world. This paper shows the work done by a cyber security team whose main objective is to run vulnerability analysis and mitigate threats on an application that backs up the clients data to the cloud. Cyber Security is an important aspect in all types of businesses because it protects all categories of data such as fragile data, private information, intellectual property data, and other data including governmental and industrial information systems from theft and damage which concludes in huge financial loss and loss of client data.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-660 LNNS, pp. 187-196.</text>
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                <text>Covid has changed our lives in many ways. People are scared to even step out of their houses, but health care workers have no option but to continue to work and care for the sick. Health care workers play a vital role in providing care to the infected persons, working beyond their capacities and risking their own lives. There is a lot of stress involved in the medical profession, and the pandemic made it worse. Each frontline health worker is at risk of getting infected with Covid during work and carrying it to their families, causing a lot of anxiety and mental health issues among the health care workers. According to a recent by the US Centers for Disease Control and Prevention (CDC), more than half of public health workers have reported symptoms of at least one mental health condition like depression, anxiety, and post-traumatic stress disorder (PTSD) in the recent past. A recent study among 422 doctors revealed 63.5% symptoms of depression, and 45% symptoms of stress, among frontline COVID-19 doctors. Physicians who perceived organizational problems related to procedural and informational justice were exposed to high levels of occupational stress. Every physician should have a personal doctor, and he or she has to seek suitable help as needed. The health care workers' stress is mainly associated with work stress as they are expected to work on a war footing and get very little time to spend with their families. There is a need to set up good psychiatric care for the medical professionals in the hospitals. The administrators of the hospitals should frequently check on the health and well-being of their employees. This article attempts to provide strategies to hospital administrators to help medical professionals reduce their stress levels.  2022</text>
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                <text>Aranha R., Asst. Professor, School of Business &amp;amp; Management, Christ (Deemed to be University), Bangalore, India; Saldanha A., Asst. Professor, St. Joseph's Institute of Management, Bangalore, India; Aranha S., Sr. Resident, Department of Anaesthesiology, Fr. Muller Charitable Hospital, Thumbay, Mangalore</text>
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