Volume 13 | Issue 8 |

 Abstract

Margaret Atwood's speculative fiction presents a harrowing exploration of ecological collapse, patriarchal violence, and corporate exploitation through richly imagined dystopian landscapes. This paper examines The Handmaid's Tale, Oryx and Crake, and The Year of the Flood through an ecofeminist lens, tracing how Atwood intertwines environmental degradation with the subjugation of women. Drawing on key ecofeminist theorists such as Vandana Shiva and Greta Gaard, the article argues that Atwood's fictional worlds reveal a deeply gendered ecology in which the exploitation of nature and the domination of women emerge from shared patriarchal ideologies. These texts highlight the commodification of female bodies and the environment under systems of control, while also portraying resistant female subjectivities that reclaim agency and envision posthuman futures. Through a comparative analysis of these novels, the article reveals how Atwood crafts a speculative ecofeminist critique that is urgent and transformative, calling for both ecological and gender justice in a time of planetary crisis.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Ecofeminism, Environmental Dystopia, Gendered Ecologies, Patriarchal Capitalism, Biopolitics

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The South Asian diasporic author, Meera Syal creates a unique portrayal of the women characters in her novels where the protagonists invariably women have acculturated and have carved a niche in their hostland. However the homeland remains an important subject not only for discussion but also for their existence. The cultural ties with the members of the community and people of the homeland observing the same rituals or believing in similar sentiments bring people together, which is evinced in the lives of the women protagonists in the diaspora. The characters of Meera Syal, mostly women come together in combating the attacks faced by the South Asian community in Britain and they resort to their community- existence or their sisterhood as their strength in their Asian Britishness.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Identity, Diaspora, emancipation, acculturation, homeland, hostland

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract Introduction: In today's fast-paced world, where unhealthy habits are often the order of the day, cardiovascular diseases have become a thorn in the side of public health. Cardiac patients frequently find themselves between a rock and a hard place, struggling to juggle medical treatments and lifestyle changes. It is said that prevention is better than cure, and in this light, lifestyle modification stands out as a silver lining in the battle against heart disease. However, without proper guidance, many patients are left in the dark, unaware of the profound impact their daily choices can have on their heart health. This study aims to turn the tide by evaluating the effectiveness of a planned teaching program designed to shed light on lifestyle modification and its role in improving cardiovascular health among cardiac patients admitted in the cardiac unit of BTCT Hospital, helping them take the bull by the horns and lead healthier lives. Aims: To evaluate the effectiveness of a planned teaching program on knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients admitted in the cardiac unit of BTCT Hospital. Objectives: 1) To assess the pretest level of knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients admitted in the cardiac unit of BTCT Hospital. 2) To develop a structured teaching program to improve knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients. 3) To administer the structured teaching program among cardiac patients admitted in the cardiac unit of BTCT Hospital. 4) To assess the post-test level of knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients admitted in the cardiac unit of BTCT Hospital. 5) To find out the effectiveness of the structured teaching program on knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients. 6) To determine the association between the pretest level of knowledge and selected demographic variables of cardiac patients. Materials and Methods: A pre-experimental one-group pre-test and post-test design was adopted to evaluate the effectiveness of a planned teaching program on knowledge regarding the impact of lifestyle modification on cardiovascular health among cardiac patients admitted to the cardiac unit of BTCT Hospital, Sagar (M.P.). A total of 30 cardiac patients were selected using a purposive non-probability sampling technique based on specific inclusion and exclusion criteria. Data collection tools included a self-structured knowledge questionnaire comprising 30 multiple-choice questions, and a structured teaching program developed by the researcher. The tool's content validity was established by six nursing experts, and reliability was tested using Karl Pearson's split-half method, yielding a correlation coefficient of r = 0.75. The study was conducted after obtaining formal permission from hospital authorities and informed consent from participants. Data were collected through pre-test administration, followed by implementation of the teaching program, and then a post-test. The pilot study was conducted prior to the main study to assess feasibility. Data analysis involved descriptive statistics such as frequency, percentage, mean, and standard deviation, and inferential statistics including paired t-test to assess effectiveness, and chi-square test to determine the association between pre-test knowledge scores and selected demographic variables. Ethical considerations were observed throughout the study to maintain participant confidentiality and rights. Findings: The study revealed that prior to the planned teaching program, the majority of cardiac patients (73.33%) had inadequate knowledge regarding the impact of lifestyle modification on cardiovascular health, with a mean pre-test score of 10.56 and standard deviation of 5.39. Following the administration of the structured teaching program, there was a marked improvement in knowledge, with 90% of participants achieving an adequate knowledge level in the post-test, yielding a mean score of 22.53 and standard deviation of 2.403. The paired t-test value of 5.105 indicated a statistically significant difference between pre- and post-test scores at the 0.05 level, confirming the effectiveness of the teaching intervention. Furthermore, chi-square analysis demonstrated a significant association between marital status and pre-test knowledge scores, while no significant associations were found with other demographic variables such as age, gender, religion, education, income, diet preference, smoking, or exercise habits. Overall, the findings support the positive impact of structured educational interventions in enhancing knowledge among cardiac patients. Conclusion: The study concludes that the structured teaching program was effective in significantly enhancing the knowledge of cardiac patients regarding the impact of lifestyle modification on cardiovascular health. The marked improvement in post-test scores compared to pre-test scores highlights the importance of planned educational interventions in empowering patients to make informed lifestyle choices. While most demographic variables showed no significant association with knowledge levels, marital status was found to have a significant influence. These findings underscore the need for regular, targeted health education as part of cardiac care to promote better health outcomes and prevent further complications related to cardiovascular disease.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Lifestyle modification, Cardiovascular health, Cardiac patients, Structured teaching program, Knowledge assessment, Pre-test and post-test, Health education, Patient awareness, Behavior change, BTCT Hospital.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The field of portfolio construction has evolved significantly, driven by the increasing complexity of financial markets, investor behavior, and emerging risks. Traditional models such as the Markowitz Mean-Variance framework and the Sharpe Single Index Model, while foundational, often fall short in volatile and illiquid environments, particularly in emerging markets. This study explores optimum portfolio construction by integrating both classical and modern approaches across multiple industries and market contexts. Using Sharpe ratio optimization, cut-off rate methods, and statistical tools such as t-tests, correlation matrices, and risk-return analysis, the research identifies the most efficient portfolio combinations from 20 companies spanning four sectors. The study is supported by extensive literature, ranging from early beta-based models to modern advancements incorporating machine learning, Bayesian inference, ESG filters, and risk-aware rebalancing strategies. Empirical findings confirm that diversified, data-driven portfolios significantly outperform traditional allocation methods in terms of Sharpe ratio, total risk reduction, and sectoral balance. The research contributes to a deeper understanding of how modern tools can adapt classical theories for more robust and resilient portfolio performance. It provides a strategic roadmap for investors navigating uncertain, high-risk markets with the goal of achieving superior risk-adjusted returns through scientifically grounded portfolio construction.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Optimum Portfolio, Mean-Variance Optimization, Sharpe Ratio, CVaR (Conditional Value at Risk), Asset Allocation, Portfolio Risk Management, Indian Stock Market.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Driver fatigue significantly contributes to road accidents, but current detection methods often rely on intrusive sensors or computationally heavy models. We propose a vision-based driver alertness monitoring system using a standard webcam. The system analyzes facial cues by calculating the Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), and head pose from Dlib facial landmarks. These metrics indicate signs of drowsiness. We compare our approach with recent deep learning solutions (YOLOv8-Face, MobileNetV3-based keypoint regression, and ResNet50-LSTM classifiers). On a standard CPU, our lightweight method achieves ~92.6% detection accuracy and ~94.1% sensitivity with an average latency of 1.1 seconds, while being 30% faster and 45% smaller than the MobileNetV3 model. These results suggest our system is well-suited for low-power, real-time deployment in smart vehicles for enhanced driver safety.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Driver drowsiness detection, Eye Aspect Ratio, Mouth Aspect Ratio, Head-pose estimation, Real-time monitoring, Facial landmark tracking, Computer vision.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the impact of Unified Payments Interface (UPI) and digital payment systems on the financial behaviour of small retailers across five districts in Karnataka. As digital payment adoption accelerates in India, understanding the behavioural patterns and satisfaction levels of small business users is critical for driving financial inclusion and digital transformation. The study aims to identify the key factors influencing behavioural intention, actual usage, and user satisfaction with UPI services. A descriptive research design was adopted, utilizing primary data collected from 400 small retailers through structured questionnaires, supported by secondary data from RBI, NPCI, and economic reports. Statistical tools such as descriptive statistics, one-sample t-tests, and ANOVA were used for analysis. Results show that ease of use, smartphone comfort, cashback incentives, and peer recommendations significantly impact adoption. User satisfaction is influenced by app usability, transaction speed, customer support, and trust in service providers. Gender and location emerged as major demographic influencers, while age had limited effects. The study concludes that strengthening digital infrastructure and enhancing service quality are vital to encourage consistent UPI usage among small retailers. Future research can explore UPI usage among other business segments, assess the long-term impact of digital incentives, and compare adoption patterns between rural and urban markets to guide policy and fintech innovations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

UPI, Digital Payments, Small Retailers, Behavioral Intention, User Satisfaction, Karnataka

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper highlights how the Chamba Princely State changed after British colonial rule. Through this paper, an attempt has been made to find out how agriculture changed, how the kings of Chamba adopted pro-British policies. New canals and kuhls were built for irrigation. The changes made in this by the British government were studied systematically. Through this research paper, an attempt has been made to know that land and revenue reforms were done during the British era. Through this study, an attempt will also be made to understand the revenue historical background of Chamba.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agriculture, Horticulture, Chamba, Princely State, and British Period

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Accurately predicting flight delays is a key challenge in aviation analytics, with significant implications for airline operations and passenger satisfaction. This project presents a machine learning-based system for predicting flight delays using historical U.S. domestic flight data. The dataset is extensively preprocessed, including the imputation of missing values, encoding of categorical variables, and generation of time-based features such as scheduled departure hour and total delay duration. A binary classification approach is adopted, labeling flights as delayed when the arrival delay exceeds 15 minutes. Three models--Random Forest, Decision Tree, and Logistic Regression--are developed and evaluated. Both the Random Forest and Decision Tree classifiers achieved 100% accuracy on the test set, while Logistic Regression reached 98.4%, indicating the strong predictive capability of the selected features. However, such perfect accuracy suggests potential data leakage or overfitting, as the delay-related columns used in training directly influence the target variable. A user-friendly graphical interface, built with Tkinter, allows users to input flight number, tail number, origin, and destination to receive real-time delay predictions and reasons. Additionally, visual analytics generated using Seaborn highlight delay trends by departure hour and weekday. The system demonstrates how machine learning, combined with rich flight data, can support operational decisions in aviation, although care must be taken to ensure model generalization and reliability

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Flight delay prediction, machine learning, Random Forest, Decision Tree, Logistic Regression, data preprocessing, binary classification, aviation analytics, graphical user interface, Tkinter, overfitting, data leakage, visual analytics, Seaborn

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Forests and wildlife are vital resources that have played a crucial role in human beings' social, economic, and religious life since the beginning. Forests were essential for the livelihoods of forest dwellers who depended on them for food, shelter, fodder, fuelwood, and other daily necessities. Humans hunted animals in forests and obtained meat for food from wild animals; however, over time, they cleared forests for agriculture, which put pressure on soil and water resources. They were unfamiliar with agriculture and relied on animal flesh, but some wild fruits and vegetables grew in abundance in the forests, as well as leaves and fur for clothing. They didn't have fixed houses; they might have made huts from tree leaves. Forests and wildlife play a crucial role in maintaining environmental balance. Every species plays a vital role in maintaining an ecological balance among the Earth's living systems. This research paper highlights the hunting practices in the hills of Himachal during the British period. This paper also highlights the relation between wildlife and Human activities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hunting, Wildlife, Forest, Hilly State, and British Period.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid integration of digital devices into children's daily lives has raised serious concerns about the adverse effects of screen time on pediatric health. From sleep disturbances and obesity to behavioral and developmental delays, the implications are multifaceted and growing. Artificial Intelligence (AI) offers a promising solution for early detection, personalized monitoring, and evidence-based interventions. This paper explores the role of AI in identifying screen time-related health risks in children and how AI-powered tools can assist pediatric nurses, parents, and healthcare systems in managing these challenges effectively. The study highlights recent advancements, ethical considerations, and practical applications of AI in pediatric care. A multidisciplinary approach, combining AI technology with pediatric nursing, can potentially mitigate the "digital danger" and promote healthier screen habits among children

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital danger, AI, health issue

  License

Creative Commons Attribution 4.0 and The Open Definition