Volume 13 | Issue 12 |

 Abstract

Capsules are one of the most versatile and widely accepted oral dosage forms used in pharmaceutical practice due to their ease of administration, rapid disintegration, and ability to accommodate a broad range of drug substances. Their manufacturing involves specialized processes that differ for hard gelatin capsules and soft gelatin capsules, each requiring precise control of materials and operating conditions to achieve consistent quality. Hard gelatin capsules are produced through sequential steps such as dipping, drying, trimming, and filling, while soft gelatin capsules are typically manufactured using techniques like the rotary die process, which enables simultaneous forming, filling, and sealing. To ensure the safety, efficacy, and uniformity of the final product, capsules must undergo rigorous quality control tests, including disintegration, weight variation, dissolution, assay, content uniformity, and moisture permeation testing. These evaluations verify the structural integrity of the shell, accuracy of the fill weight, and performance of the dosage form under physiological conditions. This review summarizes the manufacturing processes of both hard and soft gelatin capsules and highlights the essential quality control parameters required to comply with pharmacopeial standards, thereby ensuring reliable therapeutic outcomes.

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 Keywords

Capsules; Gelatin; Hard Gelatin Capsules; Soft Gelatin Capsules; Capsule Filling Machines; Advantages and Disadvantages; Types of Capsule Filling Machines; Working Principles of Capsule Filling

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Rhinoplasty is considered to be one of the most challenging procedures in otolaryngology & head and neck surgery.

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 Keywords

RHINOPLASTY- PATIENT'S SATISFACTION AFTER SURGERY BOTH FUNCTIONAL AND COSMETIC

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 Abstract

The AI-Mock-Interview project aims to transform the traditional interview process by utilizing artificial intelligence to automate and enhance candidate evaluations. This AI-powered system assesses candidates across multiple dimensions, such as verbal responses, body language, eye contact, and emotional expressions. By incorporating cutting-edge technologies like machine learning, natural language processing (NLP), and facial recognition, it offers a more efficient and objective approach to candidate assessment. The project seeks to overcome the inherent biases and subjectivity often present in traditional interviews by adopting a data-driven, impartial evaluation process. The methodology centers around real-time video and audio analysis, leveraging emotion recognition and sentiment analysis through Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models.

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 Keywords

AI-Driven Interview Simulation Intelligent Mock Interview Platform Virtual Interview Assistant Automated Interview Engine Smart Interview Bot

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 Abstract

Phishing websites have emerged as one of the most prevalent cyber threats, deceiving users into revealing sensitive credentials and causing significant financial losses. Detecting these malicious websites automatically and accurately is crucial for online security. This paper presents a machine learning-based phishing website detection system that analyzes multiple data modalities including URL lexical features, HTML structure, and WHOIS information to identify phishing attempts. The system extracts key features such as domain age, URL length, special character patterns, SSL certificate validity, and embedded script behaviors, which are then processed using ensemble learning models such as Random Forest and XG Boost for classification. The proposed model achieves an overall accuracy of 96.4%, precision of 95.8%, and F1score of 96.1% on benchmark datasets, demonstrating superior performance compared to existing methods. The model is lightweight and optimized for real-time deployment, making it suitable for browser extensions and online verification systems. The key contributions include the integration of diverse feature sets, enhanced detection accuracy, and a scalable implementation for real-world phishing prevention.

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 Keywords

Phishing Website Detection, Machine Learning, Cybersecurity, Web Security, Feature Extraction, Classification Algorithms, Supervised Learning, URL Analysis, Malicious Website Detection, Data Mining.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this project we will develop an IoT Based Solar Power Monitoring System using ESP32 WiFi Module. The ESP32 connects to the WiFi Network and uploads the Solar Sensing parameters like Solar Panel Voltage, Temperature, and Light Intensity on Thingspeak Server.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT based solar tracker, solar power

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid expansion of Internet of Things (IoT) devices has been transformed into modern infrastructure around healthcare, industrial reformation, smart cities, and consumer applications. However, this rapid multiplication has never created security challenges, making IoT networks attractive targets for sophisticated cyberattacks [1]. Traditional signature-based intrusion detection systems (IDS) struggle to keep pace with the evolving nature of attacks, particularly botnet-based threats that exploit the inherent resource constraints of IoT devices. Deep learning has emerged as a promising solution for developing robust, adaptive intrusion detection systems capable of identifying both known and novel attack patterns in IoT environments [2]. The BoT-IoT dataset has become a critical standard for evaluating these advanced detection approaches, providing researchers with realistic network traffic data that captures the complexity of modern botnet attacks in IoT infrastructures.

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 Keywords

Internet of Things (IoT), Intrusion Detection System, Deep Learning, Cybersecurity, BoT-IoT Dataset, Botnet Attacks.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Access to safe drinking water remains a critical public health challenge, particularly in developing regions with limited laboratory infrastructure. This paper presents Purifix H2O, an intelligent Internet of Things (IoT) system for real- time water quality monitoring that integrates low-cost sensors (pH, TDS, turbidity, and temperature) with an Arduino UNO microcontroller and cloud-enabled mobile/web interfaces. The system employs sensor calibration, multi-parameter processing, rule-based safety classification, and an optional machine learning module for AI-driven waterborne disease risk prediction. Experimental evaluations on diverse water sources including tap, borewell, packaged drinking, pond, and contaminated samples demonstrate that the system reliably discriminates water quality categories and predicts health risks based on sensor patterns. Results show that the proposed approach is cost-effective, feasible for large-scale deployment, and significantly improves accessibility to continuous water quality assessment compared to traditional laboratory-based methods.

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 Keywords

IoT, water quality monitoring, low-cost sensors, Arduino, machine learning, disease risk prediction, Android Application, real-time monitoring.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The concept of gender in Indian families and society needs no introduction, as the age-old gender discrimination has been so deeply internalized that it doesn't come as a surprise if a woman becomes a victim of such discrimination. The paper attempts to study a woman's world bound by patriarchy, class, and gender exploitation, followed by the subsequent resistance in Indian society as portrayed in Arati Kadav's film Mrs. (2024). A Marxist feminist literary approach guides the analysis of the cinematic text. The film projects a quietly powerful and thought-provoking portrayal of a woman caught between her aspirations and the weight of deeply rooted patriarchal expectations. At the heart of the film is Richa, played with striking vulnerability by actress Sanya Malhotra--a middle-class housewife whose routine existence is upended by an unexpected event. What unfolds is not just a story of disruption, but of awakening and resistance. The findings conclude that many Indian married women, like the female lead in the film, are trapped in the endless cycle of domestic chores and constant patriarchal scrutiny. The identity that the woman protagonist had is lost in transition and remains a victim of patriarchy, class, and gender discrimination. It is through passion for a fulfilling work or economic independence that paves the way to the protagonist's ultimate freedom and empowerment.

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 Keywords

patriarchy, gender, Marxist feminism, Mrs., resistance

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT A 60-year-old post-hysterectomy woman presented with a one-year history of vaginal mass protrusion, difficulty walking, and incomplete micturition. Examination revealed vault prolapse with cystocele and enterocele. She was hemodynamically stable with mild pallor and pedal edema. Investigations showed hemoglobin 11 g%, platelet count 1.24 lakh/cumm, and normal renal, liver, thyroid, and viral profiles. Conservative management included lifestyle modification, pelvic floor exercises, multivitamins, antihypertensives, and topical estrogen. She was advised sexual abstinence for three months and follow-up for thyroid and fecal occult blood tests. Surgical correction such as sacrocolpopexy was planned if symptoms persisted. This case emphasizes early recognition, supportive care, and individualized management of post-hysterectomy vault prolapse with cystocele and enterocele.

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 Keywords

Keywords: Vault prolapse, cystocele, enterocele, hysterectomy complications, pelvic organ prolapsed

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 Abstract

Summarizes Jatharagni's role in Grahani-IBS pathogenesis, linking Mandagni-Ama to dysbiosis. Outlines review methodology, key findings (doshic-IBS mapping), and integrative therapeutic superiority. Aim To establish the mechanistic role of Jatharagni dysregulation in Grahani pathogenesis and its correlation with IBS pathophysiology. Objectives 1. Analyze classical Jatharagni physiology and Grahani classification from Ayurvedic texts. 2. Map tridoshic Grahani types to IBS subtypes. 3. Correlate Mandagni-Ama with modern dysbiosis and gut dysfunction. Introduction Defines Grahani Roga via classical Shloka, introduces Jatharagni physiology. Correlates with IBS prevalence/Rome IV, states research scope for Ayurvedic-modern synthesis. Methodology PRISMA-adapted systematic review of Ayurvedic texts/databases (2000-2025). Details inclusion criteria, qualitative dosha-IBS mapping, bias assessment via Jadad scale. Results Presents Jatharagni functions (Paka-Vibhajana), Grahani classification table (Vataja->IBS- C etc.). Shows Deepana-Pachana efficacy (70-80% relief) with Samprapti diagram.Discussion Elaborates Mandagni->Ama parallels (dysbiosis, leaky gut, motility chaos).Pathophysiological mechanism of Grahani and IBS and it's integrated interpretation Conclusion Affirms Jatharagni restoration as root-cause therapy outperforming IBS palliation. Recommends multicentric trials for global validation.

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 Keywords

Keywords: Jatharagni, Grahani Roga, Irritable Bowel Syndrome, Agni, Mandagni, Digestive Fire, Ayurveda, Ama, Dysbiosis

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Creative Commons Attribution 4.0 and The Open Definition