Volume 14 | Issue 4 |

 Abstract

The rapid growth of e-commerce platforms has resulted in the generation of large volumes of transactional data. Analyzing this data is essential for understanding business performance and improving decision-making processes. This study focuses on applying exploratory data analysis (EDA) techniques to evaluate e-commerce sales data using Python. The analysis includes monthly sales trends, category-wise and sub-category-wise performance, profit distribution, and customer segment behavior. Special emphasis is placed on the sales-to-profit ratio to evaluate the efficiency of converting sales into profit. Python libraries such as Pandas, NumPy, and visualization tools are used to process and represent the data. The results highlight that sales performance varies across different months and categories, and higher sales do not always correspond to higher profit. The study demonstrates how simple data analysis techniques can provide meaningful insights for improving business strategies.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Consumer Behaviour, Purchase Intention, E-commerce, Machine Learning, E-commerce, Data Analysis, Sales Analysis, Profit Analysis, Data Visualization, Python, EDA.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

GoSafe is a data-driven travel safety platform designed to provide personalized risk assessments through a dynamic scoring algorithm. By transforming complex global safety data into a clear visual score out of 10, the application offers tailored advice based on specific traveler profiles, such as solo, family, or inexperienced users. Built as a high-performance static Single-Page Application using HTML5, Vanilla JavaScript, and Tailwind CSS, it utilizes a simulated client-side backend to ensure speed and security. The project addresses critical industry gaps where over 40% of travelers report disappointment due to insufficient research, ultimately empowering users to plan journeys with greater confidence.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Travel Safety , Personalized Risk Assessment , Dynamic Scoring Algorithm , Single-Page Application (SPA) , Client-Side Data Processing , User Experience (UX) Design , Front-End Development.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper seeks to examine the nuanced layers of socio-cultural exclusion in Nergis Dalal's novel Skin Deep (2005) through the lens of intersectionality and double marginalization. Set against the backdrop of the dwindling Parsi community in India, the novel moves beyond a mere domestic saga of twin rivalry to critique the systemic displacement of the female subject. By utilizing Gayatri Chakravorty Spivak's framework of the "doubly marginalized" and Naomi Wolf's "Beauty Myth," this study argues that the protagonist, Naaz, is simultaneously sidelined by her status as a member of a micro-minority and by an internal patriarchal hierarchy that commodifies female aesthetics.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Parsi Diaspora, Double Marginalization, Nergis Dalal, Postcolonial Feminism, The Beauty Myth, Minority Identity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Kamala Das stands as one of the most confessional and provocative voices in Indian English poetry, whose works foreground the complexities of identity, belonging, and emotional dislocation. This paper explores the intricate interplay of space and displacement in her poetry, situating her within feminist and postcolonial frameworks. It argues that Kamala Das transforms poetry into a dynamic site where personal experience intersects with broader socio-cultural tensions shaped by patriarchy and colonial legacy. The study examines how different forms of "space"--domestic, linguistic, bodily, and emotional--are continuously negotiated, revealing the fragmented and evolving nature of the self. The domestic sphere, often idealized in traditional discourse, is reconfigured as a restrictive and alienating space where the female subject struggles for autonomy and self-expression. The paper further highlights how linguistic space becomes central to identity formation, as Kamala Das's use of English alongside her cultural roots reflects both assertion and displacement. Additionally, the female body emerges as a contested site where desire, vulnerability, and resistance coexist, challenging normative expectations while intensifying the sense of isolation. Emotional estrangement and fractured relationships further contribute to the experience of dislocation, emphasizing the poet's persistent search for authentic connection and belonging. Memory and nostalgia are also examined as unstable spaces that simultaneously anchor and unsettle the self. Through close reading of select poems, this study demonstrates that dislocation in Kamala Das's poetry functions not only as a condition of loss but also as a creative and critical strategy that enables the redefinition of identity. Ultimately, her work reflects an ongoing negotiation of selfhood within shifting cultural and personal landscapes, making it highly relevant to contemporary discussions of gender, identity, and belonging.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Kamala Das, identity, dislocation, belonging, space, feminism, postcolonialism, female subjectivity, language, selfhood

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Lichen plano pilaris (LPP) is a rare inflammatory disorder characterized by lymphocytic destruction of hair follicles leading to cicatricial alopecia and permanent hair loss. We report a case of a 14-year-old female who presented with progressive hair loss, pruritus, and hyperpigmented lesions over the scalp and multiple body sites. Clinical examination revealed patchy alopecia with perifollicular erythema and scaling, and dermoscopic findings suggested scarring alopecia. The diagnosis was confirmed by histopathological examination of a scalp biopsy. The patient was managed with a combination of systemic hydroxychloroquine, oral corticosteroids, and immunosuppressants, along with topical therapies and adjunct platelet-rich plasma (PRP). Follow-up showed symptomatic improvement with reduction in itching and stabilization of disease progression; however, residual scarring alopecia persisted. This case highlights the importance of early diagnosis and prompt management to prevent irreversible hair loss and improve patient outcomes in LPP.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Lichen Plano Pilaris, Cicatricial Alopecia, Adolescent, Hair Loss, Biopsy, Hydroxychloroquine.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

MindPulse is a privacy-first, locally-operated, AI-powered mental wellness prediction platform built with Python (Flask), Scikit-learn, and HTML/CSS/JavaScript. The system leverages a Voting Ensemble model combining Gradient Boosting and Random Forest classifiers to categorize users' mental states across five wellness levels: Excellent, Good, Moderate Concern, High Concern, and Critical. The model is trained on 3,000 synthetically generated samples calibrated to established clinical instruments--the PHQ-9, GAD-7, and WHO-5 Wellbeing Index. Users rate ten behavioral and emotional wellness indicators on a 1-10 scale through an animated web interface, receiving a composite Wellness Score (0-100), Canvas-rendered Radar Chart, probability breakdown, and personalized therapeutic insights. Operating entirely on a local Flask server without any external API keys or cloud transmission ensures complete data privacy. Rigorous testing comprising 29 test cases across unit, integration, boundary value, and user acceptance testing yielded a 100% pass rate.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords Mental Wellness Prediction; Ensemble Learning; Gradient Boosting; Random Forest; Flask REST API; PHQ-9; GAD-7; WHO-5; Privacy-First AI; Canvas Radar Chart; Wellness Analytics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The crises of Rohingya refugee children are the most severe humanitarian challenges in contemporary South Asia. Rohingya refugee children are a significant section of the displaced Rohingya population. This paper examines the role of digital governance in enhancing human security for Rohingya refugee children. It also focuses on access to essential services such as education, healthcare, protection, and identity. Drawing upon the human security framework, the study explores how digital tools including biometric registration, digital identity systems, data-driven governance, and e-service delivery can improve the efficiency and inclusiveness of humanitarian responses. The paper highlights the contribution of state actors, international organizations, and non-governmental agencies in integrating digital technologies into refugee management systems, particularly in the host country like Bangladesh. At the same time, it critically evaluates the challenges posed by digital exclusion, data privacy risks, and infrastructural limitations. The findings suggest that while digital governance offers transformative potential in addressing the Rohingya children's crises, its effectiveness depends on inclusive implementation, ethical safeguards, and strong institutional coordination. The study argues that aligning digital governance with human security principles is essential for ensuring sustainable and equitable outcomes for refugee children.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Governance; Human Security; Rohingya Refugees Children; Migration Governance; Digital Inclusion

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Type 2 Diabetes Mellitus (T2DM) is a chronic disease that can lead to kidney damage. Many patients do not achieve proper blood sugar control with metformin and glimepiride alone. So, a third drug like a DPP-4 inhibitor is often added to improve treatment outcomes. Teneligliptin and linagliptin are commonly used options that are generally safe for kidney patients. Both drugs helped in lowering blood sugar levels and improving kidney function. However, linagliptin showed better results in reducing HbA1c and improving kidney markers. Overall, linagliptin may be a more effective and safer choice for T2DM patients with kidney problems.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Type 2 Diabetes Mellitus, Teneligliptin, Linagliptin, Add-on Therapy, Glycaemic Control, Renal Safety, DPP-4 Inhibitors

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study aimed to compare the Work Ability Index (WAI) among academic female staff across different age groups--young, middle-aged, and senior in in polytechnic colleges Bhopal. Work ability is a crucial determinant of productivity and occupational well-being, especially in academic settings where mental and physical demands coexist. A total of ninety (N=90) academic female staff members were selected using purposive sampling, with 30 participants in each age group. The Work Ability Index questionnaire was used to assess work ability. Statistical techniques such as mean, standard deviation, and one-way ANOVA were employed to analyze the data. The findings revealed significant differences in WAI among the three age groups, indicating a decline in work ability with increasing age. The study highlights the need for age-specific interventions to maintain and improve work ability among academic female professionals.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Work Ability Index, Academic Female Staff, Age Groups, Occupational Health, Physical Activity.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper proposes a secure federated learning framework enhanced with blockchain technology for use in edge computing environments. The system introduces decentralized trust management, encrypted aggregation of model updates, smart contract-based validation, a reputation-based client scoring mechanism, and tamper-resistant auditing to ensure transparency and security. It effectively addresses major threats such as model poisoning, Sybil attacks, and data integrity issues while maintaining scalability and low latency. Experimental results show that the proposed framework achieves better accuracy and stronger attack resistance compared to traditional federated learning approaches.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Block-chain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing

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Creative Commons Attribution 4.0 and The Open Definition