Volume-11, Issue-4

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Volume-11, Issue-4

July-August, 2025

Review Paper

1. Myocardial Infarction with Non-Obstructive Coronary Artery (Minoca): A Systematic Review

Myocardial infarction with nonobstructive coronary arteries (MINOCA), which is characterized by clinical evidence of myocardial infarction (MI) with normal or near-normal coronary arteries on angiography (stenosis 50%), continues to be a perplexing clinical entity. Recent years have seen significant progress in our understanding of this illness. It is being researched and further analyzed because the precise pathophysiology is unclear. Recommendations state that MINOCA is a group of different illnesses with a range of pathological underlying causes. Given the variety of possible pathogenic reasons, it is unclear if the conventional secondary prevention and treatment strategy for MI with obstructive coronary artery disease (MI-CAD) is the best choice for those with MINOCA. There are currently no recognized predictors or prognoses for MINOCA patients. There are currently no documented vaticinations or predictors for MINOCA cases. According to guidelines, MINOCA is a collection of many illnesses with distinct pathogenic processes. Since there are multiple possible pathological mechanisms, it isn't certain that the classical secondary forestallment and treatment strategy for MI with obstructive coronary artery complaint (MI-CAD) is optimal for MINOCA cases. Uncertainty surrounds the prognosis and predictors for the MINOCA case. Although the prognosis is slightly better for MINOCA cases than for MI-CAD cases, MINOCA is not always benign.

Published by: Richa Sinha, Manroop Kaur BajwaResearch Area: Cardiology

Organisation: Rayat Bahra University, Mohali, PunjabKeywords: Myocardial Infarction, Minoca, Myocardial Infarction with Nonobstructive Coronary Artery Stenosis, Myocarditis, Coronary Artery Disease, Atherosclerosis, Plaque Rupture, Takotsubo Cardiomyopathy, Reperfusion Therapy, Biomarkers, Microvascular Spasm, Angiography.

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Thesis

2. A Study to Assess the Knowledge and Attitude Regarding Integration of Artificial Intelligence in B.Sc Nursing Curriculum among 4th Year Students of B.Sc Nursing in Selected Colleges of Nursing in the City

To assess the knowledge regarding the integration of artificial intelligence in the nursing curriculum.To assess the attitude regarding the integration of artificial intelligence in the nursing curriculum.To correlate the level of knowledge and attitude regarding the integration of artificial intelligence in the nursing curriculum. Result: the level of Knowledge among 4th year B.Sc. Nursingstudents’’ majority of the samples 50(50%) moderate knowledge, 44(44%) hava Inadequate knowledge, and 6(6%) have Adequate knowledge. the level of attitude among 4th year B.Sc. The majority of the nursing students ' samples, 86(86%) Positive attitudes, and 14(14%) have negative attitudes. There were 100 compressions between Comparisons between the Level of Knowledge and Attitude Regarding the Integration of AI in Nursing Curriculum. Each of them had answered 30 questions and an attitude scale. They assessed the knowledge and attitude regarding the integration of AI in the nursing curriculum among 4th year B.Sc students of B.Sc nursing, and correct answers were recorded as mean and standard deviation of the level of Knowledge and attitude. The paired t-test was applied to compare the difference between the Level of Knowledge and Attitude Regarding the Integration of AI Into Nursing Curriculum. It was found that the Level of Knowledge and Attitude Regarding the Integration of AI in the Nursing Curriculum, the paired’ test value was 23.350* at the level of P 0.05. Since the P value is less than 0.05 (P value = 0.0001) difference in scores is statistically significant. The researcher concludes at a 5% level of significance and 198 degrees of freedom that the above data gives sufficient evidence to conclude that Comparison between Knowledge and Attitude Regarding Integration of AI In Nursing Curriculum, hence rejects the null hypothesis the research hypothesis.

Published by: Anamika Satyaprem Bobade, Bidyarani YumnamResearch Area: Nursing

Organisation: MGM, Institute of Nursing Education Chh.Sambhajinagar, Aurangabad, MaharashtraKeywords: Artificial Intelligence, Nursing, Knowledge, Attitude, Curriculum, Education, Healthcare, Integrate, Practice, Future, Applications, Technology.

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Thesis

3. A Study to Assess the Effectiveness of a Structured Teaching Programme on Knowledge Regarding Laparoscopic Transabdominal Cervical Cerclage among Fourth Year Basic B.Sc Nursing Students at Selected Nursing Colleges in the City

A transabdominal cerclage is highly effective in reducing both fetal loss and premature birth. It can be placed before (interval) and during pregnancy and by laparoscopic (LC) or open laparotomy (AC) procedure. The Fourth-year BSc nursing students often come in close contact with patients and know the complete obstetrics history of the woman; hence assess the knowledge regarding laparoscopic transabdominal cervical cerclage (LCTAC) among fourth-year BSc Nursing students. The objectives of the study were: 1. To assess the knowledge regarding laparoscopic transabdominal cervical cerclage. 2. To assess the effectiveness of a structured teaching program regarding laparoscopic transabdominal cervical cerclage. 3. To compare the level of knowledge between the pre-test and post-test. Students with selected sociodemographic variables. The material and methods of study were developed in the form of three sections as demographic variables, general knowledge regarding laparoscopic transabdominal cervical cerclage. The non-probability purposive sampling technique was used for selecting 60 students from nursing colleges. Results of the study indicated that findings of demographic variable reveals that, there was no one variable found statistically significant association with knowledge score about Laparoscopic Transabdominal Cervical Cerclage with selected demographic variables. The finding of the study reveals that, in the pre-test majority of the samples, 35 (58.33%), had inadequate knowledge, 25(41.66%) had Moderate knowledge, and none of the samples had adequate knowledge regarding laparoscopic transabdominal cervical cerclage. With regard s the post-test knowledge majority of the samples, 30(50%), had Moderate knowledge, 20(33.33%) had adequate knowledge, and 10(16.66%) had inadequate knowledge regarding laparoscopic transabdominal cervical cerclage. The study concludes that students, after receiving knowledge on Laparoscopic Transabdominal Cervical Cerclages higher knowledge scores in the post-test than pre-test. The findings of the present study indicated that nursing students have adequate knowledge regarding Laparoscopic Transabdominal Cervical Cerclages.

Published by: Bidyarani Yumnam, Anamika Satyaprem BobadeResearch Area: Nursing

Organisation: MGM, Institute of Nursing Education Chh.Sambhajinagar, Aurangabad, MaharashtraKeywords: Knowledge, Laparoscopic Transabdominal Cervical Cerclage, Preterm Birth, Cervical Insufficiency.

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Research Paper

4. AI-Powered Dashboard for SLA Monitoring and Team Performance in JIRA

This paper introduces a visual analytics dashboard powered by AI and Python that helps technical support teams monitor SLA compliance, ticket trends, and team performance in real time. Built for JIRA-based environments, the dashboard collects and processes ticket metadata to visualize SLA breaches, categorize ticket flows, and highlight areas of delay. Designed with open-source libraries and scalable for small to medium support teams, the solution empowers stakeholders with actionable insights, improving service delivery and operational transparency.

Published by: Arooj JavedResearch Area: Computer Science – Artificial Intelligence / Software Engineering

Organisation: Queen Mary University of London, East London, EnglandKeywords: SLA Monitoring, JIRA Analytics, Dashboard Visualization, Python Automation, Support Team Metrics, ITSM Intelligence, Open-Source Support Tools, AI in Customer Support

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Research Paper

5. Optimizing Jira-Based Support Operations With AI: A Lightweight Framework for Smart Ticket Routing and SLA Breach Prediction

This paper introduces a lightweight AI-powered framework designed to enhance technical support operations within JIRA-based environments. By integrating Python scripts and machine learning models, the system automates ticket classification based on urgency and predicts potential SLA breaches before they occur. The framework uses historical ticket data to train classification algorithms, enabling proactive routing and escalation through JIRA’s REST API and Automation Rules. In real-world testing, the solution demonstrated a 34% reduction in ticket resolution time and improved SLA adherence by 40%. This approach eliminates the need for expensive plugins or enterprise licenses, making it a scalable and cost-effective automation strategy for small to mid-sized IT support teams.

Published by: Arooj JavedResearch Area: Artificial Intelligence, Software Engineering

Organisation: Queen Mary University of London, East London, EnglandKeywords: Artificial Intelligence, JIRA Automation, SLA Breach Prediction, Ticket Classification, Machine Learning, Python Integration, IT Support Automation, Workflow Optimization, Technical Support Systems, Smart Ticket Routing.

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Research Paper

6. Computational Study on Airfoil Flow Control Using Gurney Flap

Enhancing the performance of airfoils can help in improving the performance of many devices such as Darrieus Vertical Axis Wind Turbines (VAWTs.) Several methods have been proposed in the literature to control the flow over airfoils. These included using Gurney flap, using leading edge flap, slotted airfoils as well as others. The Gurney flap is a fixed flap installed normal to the airfoil surface at its trailing edge. The length of the Gurney flap, its position and its orientation are important design parameters investigated in the present work. The effect of Gurney flap parameters on the lift and drag forces as well as the lift to drag ratio (glide ratio) are assessed for different angles of attack. The present study was performed using Computational Fluid Dynamics (CFD) technique. The computational model was validated and mesh sensitivity tests were carried out to ensure accurate model results. The SST k-ω model of turbulence was used to close the Reynolds averaged Navier Stokes equations. The results showed that locating the Gurney flap on the top orientation of the airfoil has bad effect on lift and drag, while locating it on the lower side improved lift to drag ratio. Based on the significance increase of the glide ratio of airfoil with Gurney flap compared to the baseline airfoil, the best length of Gurney flap is 2% of chord length and the best position of Gurney flap to be added is to the airfoil trailing edge while the best orientation of the Gurney flap is down aligned with the airfoil pressure side. The lift coefficient is increased significantly by an average of 30%, also the drag coefficient is slightly increased by an average of 15% compared to the lift and drag generated by the baseline airfoil.

Published by: Ahmed K. Etman, Ahmed M.R. ElbazResearch Area: Renewable Energy - Wind Turbines - VAWTs

Organisation: The British University in Egypt, Cairo, EgyptKeywords: CFD, VAWT, Separation Control, Darrieus Turbine

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Research Paper

7. Which FDI Fuels Growth? A Comparative Analysis of Greenfield and Brownfield Investment in BRICS Economies

This study investigates the differential impact of greenfield and brownfield Foreign Direct Investment (FDI) on economic growth across BRICS nations from 2003 to 2023. Recognising the discrete economic mechanisms through which each form of FDI operates, the study employs a fixed-effects panel data regression model to analyse their respective contributions to GDP per capita growth. Initial findings from the full BRICS bloc show limited statistical significance, likely arising from structural and economic heterogeneity, particularly China’s status as a higher-income economy and state-directed FDI patterns, which differ markedly from the more market-driven systems of the other member countries. A refined model excluding China (focusing on the BRIS subgroup) shows that greenfield FDI has a statistically significant and positive impact on economic growth, while Brownfield FDI remains insignificant. These results highlight the importance of disaggregating FDI by entry mode to more accurately assess its developmental impact. The findings suggest that emerging economies may derive greater growth benefits by prioritising greenfield investments, which are more likely to stimulate capital formation, employment, and domestic linkages.

Published by: Akanksha MehtaResearch Area: International Finance

Organisation: University of Delhi, New DelhiKeywords: Foreign Direct Investment, Greenfield FDI, Brownfield FDI, Economic Growth, BRICS, Panel Data Analysis, International Economics

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Research Paper

8. The Psychological Effects of Emotional Neglect in Childhood

Childhood emotional neglect (CEN) is not a result of physical abuse or visible injury, but rather stems from a deficiency of essential emotional care and affection. This essay examines the significant and enduring effects of emotional neglect on a child's development, emotional health, and the lasting emotional trauma it inflicts. It distinguishes emotional neglect from emotional abuse by emphasising its invisibility and the psychological harm it inflicts. The study underscores that such neglect can lead to enduring feelings of unworthiness and transdiagnostic mental health disorders, including anxiety, depression, and personality disorders. The study looks at the underlying causes, which are typically the product of emotionally immature or apathetic carers. It uses scholarly research to do this. Lastly, the study claims that recovery from emotional neglect is not only achievable but also fundamental, as it encourages increased awareness, early intervention, and the validation of experiences that are frequently overlooked.

Published by: Ambika SinghResearch Area: Pyschology

Organisation: St. Xavier's High School, HaryanaKeywords: Childhood, Emotional, Psychological Trauma, Transdiagnostic, Neglect

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Research Paper

9. An In-depth Analysis of the Green Architecture Movement

Green architecture produces environmental, social, and economic benefits. Environmentally, green architecture helps reduce pollution, conserve natural resources, and prevent environmental degradation. Economically, it reduces the amount of money that the building's operators have to spend on water and energy and improves the productivity of those using the facility. And, socially, green buildings are meant to be beautiful and cause only minimal strain on the local infrastructure. Traditional building materials are to be adapted to meet code-required standards for health and safety in contemporary buildings. Not only are they cost-effective and environmentally friendly, but when used correctly, these natural alternatives match the strength and durability of many mainstream construction materials. New building technologies, and in particular ICT automation,3d printing etc are to constantly be introduced to enhance the sustainable building process to reduce the impact of the building on the surrounding environment by using resources more efficiently (e.g. energy, water); enhancing and protecting the health and well-being of the occupants; and reducing any negative impacts.

Published by: Guransh Singh SoniResearch Area: Architecture

Organisation: Indraprastha International School, DelhiKeywords: Sustainable, Green Architecture, Renewable Energy, Material Selection,Water Management, Climate Responsive Design

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Research Paper

10. On the Turning Away: A Critical Look into Brands’ Engagement towards Ethics

This paper takes a bird's-eye view of the prevalent and urgent misuse of the ethics of representation, with a special focus on fashion imagery in the contemporary world. Utilising a detailed literature review, the Paper looks at three specific themes: gender, race, and exoticism. It includes a critical analysis of marketing rhetoric, and questions are raised to bring into focus the cost of ‘bad faith’. The Paper also explores and interprets case studies and real-life examples of how brands can market themselves, even expand their customer base, without compromising trust or ethics.

Published by: Tara OhlanResearch Area: Fashion Branding

Organisation: The Heritage Xperiential Learning School, HaryanaKeywords: Ethics, Race, Gender, Marketing, Colonialism, Imagery, Responsibility

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Research Paper

11. Mapping the Learning Path: Integrating Multi-Modal AI, Agentic AI, and MAB Reinforcement Learning to Create a Planner for Self-Paced Learning

We present an intelligent, emotion-aware educational planner designed to deliver a highly personalized, self-paced learning experience. The system integrates task decomposition, graph-based reasoning, utility-driven scheduling, and affective state modeling into a cohesive, adaptive framework. High-level learner goals are broken down into actionable tasks via language models and structured into graph representations, which are analyzed using graph neural networks. A utility function—modulated by affective and cognitive state—guides task prioritization, while a contextual multi-armed bandit model dynamically schedules daily activities. The system also incorporates agentic AI to support user autonomy, mid-session adaptation, and long-term engagement. By merging planning, emotional intelligence, and explainable automation, this work proposes a modular architecture for learner-centric, holistic task management.

Published by: Varun IyerResearch Area: Artificial Intelligence

Organisation: Symbiosis Skills and Professional University, MaharashtraKeywords: Emotion-Aware Scheduling, Utility-Based Task Management, Graph Neural Networks, Affective Computing, Human-In-The-Loop AI, Multi-Armed Bandit, Agentic AI, Personalized Planning Systems, Edge AI, Task Decomposition

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Research Paper

12. SmartFurnace IoT: AI-Powered Monitoring and Predictive Maintenance System for DRI Kilns

Abstract: This paper presents SmartFurnace IoT, an intelligent system designed for real-time monitoring and predictive maintenance of Direct Reduced Iron (DRI) kilns. It integrates temperature, gas, and material flow sensors with edge devices and cloud-based AI algorithms to enhance safety, reduce downtime, and improve energy efficiency. The system provides live dashboards, automated alerts, and historical data logging, enabling proactive interventions and pollution control compliance. The approach targets cost-effective modernization of sponge iron plants, particularly in industrial regions like Odisha and Chhattisgarh.

Published by: Aryeman DalmiaResearch Area: IoT In Industrial Automation / Smart Manufacturing / Industry 4.0

Organisation: KIIT International School, Bhubaneswar, OdishaKeywords: DRI Kiln, SmartFurnace, IoT, Predictive Maintenance, Industrial Automation, Edge Computing, Industry 4.0, Sponge Iron

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