AI-Driven Portfolio Optimisation Strategies in High-Inflation Macroeconomic Conditions
High inflation significantly affects asset prices, risk premiums, and investor behaviour, making traditional portfolio optimisation models less effective. This study explores the application of artificial intelligence (AI) techniques—specifically machine learning (ML) models and heuristic optimisation algorithms—to enhance portfolio performance during periods of high inflation. Using historical macroeconomic and financial market data, the project trains models to identify inflation-sensitive assets, predict returns, and construct optimal asset allocations. Methods such as Random Forest regression, LSTM neural networks, and Genetic Algorithms are compared with classical approaches like Modern Portfolio Theory (MPT). Performance is evaluated using metrics including Sharpe ratio, risk-adjusted returns, and inflation-adjusted returns. The findings aim to determine whether AI-driven strategies can outperform traditional models when inflation is elevated. This project contributes to the growing domain of AI-based financial modelling and offers practical insights for investors seeking resilience against inflationary volatility. In addition to evaluating performance during inflationary spikes, the study examines how AI models respond to shifting macroeconomic signals such as interest rate hikes, currency fluctuations, and commodity price volatility. By incorporating these variables into the learning framework, the models aim to provide more stable predictions and adaptive asset allocation decisions. This helps assess whether AI can truly capture inflation-driven market distortions better than conventional statistical models, which often assume linear relationships and stable correlations. Furthermore, the project highlights the practical implications of AI-driven optimisation for investors, financial planners, and policymakers operating in inflation-sensitive economies. By demonstrating how machine learning outputs can be integrated into investment decision-making, the study contributes to the growing domain of predictive financial analytics. The broader goal is to understand whether AI can create more resilient and inflation-hedged portfolios in real-world scenarios. The findings are expected to offer valuable insights into designing future-ready investment strategies that remain robust even during prolonged periods of macroeconomic uncertainty.
Published by: Aadya Goyal
Author: Aadya Goyal
Paper ID: V11I6-1310
Paper Status: published
Published: December 24, 2025
Evaluating the Proliferative and Inhibitory Effects of Selected Indian Spices and Herbs on Vigna Radiata Cell Growth
Scientists have always been on the hunt for a therapeutic chemical with the potential to treat deadly diseases. There is a growing interest in using natural compounds derived from plants as a natural cancer cell treatment. Herbs and spices such as turmeric, garlic, cinnamon, clove, and tulsi are rich in bioactive compounds and have long been studied for their medicinal value in humans. However, their potential role in modulating cancer cell proliferation is underutilized. By exploring the proliferative and inhibitory effects of these traditional Indian herbs on Vigna radiata, this study contributes new knowledge to medical science and phytochemistry. It also opens new avenues for applying culturally significant, easily accessible, sustainable and inexpensive natural resources in modern cancer treatments. This study focuses on finding the specific herb extracts which are potent inhibitors of cell proliferation, in turn reducing the cancerous cell growth, leading to an invaluable impact on cancer treatment worldwide. Furthermore, this research aligns with global goals for sustainable development, particularly those related to accessible, low-cost and sustainable healthcare.
Published by: Seema Bajpai, Aarav Chetan Jain, Dhairya Milin Shah, Nishka Sachin Koneri, Pahal Kayur Shah, Ms. Ranjana Yadav
Author: Seema Bajpai
Paper ID: V11I6-1309
Paper Status: published
Published: December 23, 2025
Women at Work: The Economics of Gender Inequality
In the last two decades, there has been a significant change in the social and economic horizon of India, with the Female Labor Force participation rate reaching 41.7% in 2023-2024. While the growing FLFPR indicates increased economic participation of women, it does not always mean that women are getting quality employment opportunities or becoming empowered. In fact, this boost in FLFPR is because most women, especially rural women, are compelled to work because of unfavorable circumstances and not because there are doors opening for them. As FLFPR is an inadequate economic metric, this study also explores other economic indicators like the global gender gap index, female entrepreneurship rate, access to financial services, women’s asset management, female unemployment rate, etc. While the participation of women is increasing exponentially across all professions, they still have to face an uphill battle to move forward in their careers and gain respect. To collect empirical evidence on workplace barriers, this study has circulated a survey filled out by 121 anonymous women belonging to all age groups from both the formal and informal sectors. The FLFPR of India has also been compared with that of emerging economies to evaluate India’s current scenario in light of global standards. Secondary data has been collected from sources such as the World Bank, the World Economic Forum, and Indian National newspapers. Thematic patterns of gender pay gap, pre-conceived notions, hostile work environment, negative and prejudiced attitude towards women, lack of mentorship programmes, and inadequate provision of childcare and maternity benefits have emerged. These become obstructions not just for women but also for organizations, India, its economy, and the Gross Domestic Product of this country. If half of the populace remains dormant in the workforce, the Indian economy will never be able to reach its maximum potential.
Published by: Myra Khurana
Author: Myra Khurana
Paper ID: V11I6-1315
Paper Status: published
Published: December 23, 2025
How Might Behavioural Economic Principles Be Applied to Encourage Sustainable Consumer Behaviour in Product Design?
Sustainable consumer behaviour has become a priority worldwide as unsustainable consumption patterns continue to accelerate environmental degradation. While traditional economic models often assume rational decision-making, evidence shows us that consumers tend to rely on cognitive shortcuts, their emotions, as well as social influences. These factors help shape their everyday choices in ways that are not purely reasoned. Scholars in behavioural economics highlight how defaults (Thaler and Sunstein), emotions and social norms (Cialdini, Opower studies), and simplified design approaches (eco-labelling, minimalist packaging) can significantly influence behaviour without restricting the freedom of choice, which consumers usually consider a strong determining factor of consumption. However, these insights are rarely connected systematically to product design, which is where the problem arises. Building on this foundation, this paper explores how behavioural economic principles can be applied to encourage sustainable consumer behaviour through design. This research paper is limited to secondary data collection, peer-reviewed literature, and behavioural theories rather than primary data, which could include biases in such a sensitive topic. It also includes case studies such as Alibaba’s “no cutlery” default, energy-saving appliance settings, and the EU energy label. These real-world examples help me demonstrate how defaults, emotional and social reinforcement, and simplicity can guide consumers toward sustainability by embedding these behaviours into everyday interaction with products. Therefore, I argue that by strategically integrating behavioural economic principles into product design, firms can make sustainable behaviour the most effortless, emotionally rewarding, and socially reinforced choice, thereby generating lasting environmental and economic value.
Published by: Amaira Singh Chhabra
Author: Amaira Singh Chhabra
Paper ID: V11I6-1314
Paper Status: published
Published: December 23, 2025
Effectiveness of Structured Teaching Programme on Knowledge Regarding Telemedicine among Nursing Students in Selected Nursing Colleges of District Mandi, H.P.
Good health is central to human happiness and well-being that contributes significantly to prosperity and wealth and even economic progress, as healthy populations are more productive, save more and live longer. Telemedicine is the exchange of medical information from one location to another using electronic communication, which improves patient health status. This study aimed to assess the effectiveness of structured teaching programme in improving the knowledge regarding telemedicine among nursing students. Objectives: To assess the level of knowledge regarding telemedicine among nursing students. To evaluate the effectiveness of structured teaching program on knowledge regarding telemedicine among nursing students. To find out the association between level of knowledge score regarding telemedicine among nursing students and their selected socio-demographic variables. Material and Method: Investigator adopted a quantitative research approach with the Quasi-experimental research design (non-randomized control trial design). The subject were 100 nursing students and the non-probability purposive sampling method was used for selection criteria. Data was collected using socio-demographic data profile and self-structured knowledge questionnaire regarding telemedicine. A structured teaching programme regarding telemedicine was implemented in the experimental group after the pre-test, followed by the post-test after seven days. Data were analyzed using descriptive and inferential statistics. Result: In experimental group the mean knowledge score increased significantly from 20.26 (SD= 4.818) to 25.90 (SD = 1.446). this shows that the result was highly significant (t = 8.067, p < 0.001), indicating the intervention was effective. Whereas in control group there was no significant change in the knowledge score (Pre: 19.660, Post: 19.70, t = 0.096, p = 0.924), showing no impact without intervention. Conclusion: In the present study majority of the nursing students had Average level of knowledge regarding telemedicine in pretest. After implementing structured teaching program majority of the nursing students had good level of knowledge. Which indicates that the structured teaching programme was effective in enhancing the knowledge of nursing students regarding telemedicine.
Published by: Nikita Sharma, Sunita Devi, Priyanka Sharma
Author: Nikita Sharma
Paper ID: V11I6-1308
Paper Status: published
Published: December 22, 2025
Clinical Evaluation Report on Aswini Hiran Strong Pain Oil
Aswini Hiran Strong Pain Oil is a topical Ayurvedic pain-relieving preparation used for knee pain, joint pain, muscular pain, shoulder pain, and backache. The product claims a rapid onset of relief within minutes of application and significant improvement within 14 days of regular use. A prospective, open-label, Phase 4 clinical study was conducted on adult subjects (n = 30) experiencing musculoskeletal pain. Pain severity was measured using a Visual Analogue Scale (VAS: 0–4) at baseline (Day 0) and after 14 days of regular application (Day 14). The study demonstrated significant improvement across all pain categories, with p < 0.001 for every parameter evaluated through a two-tailed paired t-test analysis. Mean pain reduction at Day 14 was 81.25% for knee pain, 78.13% for back pain, 89.29% for shoulder pain, and 78.57% for calf/muscle pain. Onset-of-relief assessments showed 80% of participants experienced noticeable relief within 10 minutes, with 10% reporting relief as early as 3 minutes. No adverse reactions or tolerability issues were reported. These findings substantiate the claims of Aswini Hiran Strong Pain Oil and confirm its effectiveness as a topical remedy for musculoskeletal pain.
Published by: Dr Gandhimathi, Mr.Anil Kumar
Author: Dr Gandhimathi
Paper ID: V11I6-1302
Paper Status: published
Published: December 22, 2025
