Volume 13 | Issue 12 |

 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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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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patriarchy, gender, Marxist feminism, Mrs., resistance

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

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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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Machine Learning and Deep learning-based software tools has facilitated the creation of credible face exchanges in videos and images that leave few traces of manipulation, in what they are known as "DeepFake"(DF) videos. Manipulations of digital videos have been demonstrated for several decades through the good use of visual effects, recent advances in deep learning have led to a drastic increase in the realism of fake content and the accessibility in which it can be created. These so-called AI-synthesized media (popularly referred to as DF).Creating the DF using the Artificially intelligent tools are simple task. But, when it comes to detection of these DF, it is major challenge. Because training the algorithm to spot the DF is not simple. We have taken a step forward in detecting the DF using Convolutional Neural Network and Recurrent neural Network. System uses a convolutional Neural network (CNN) to extract features at the frame level. These features are used to train a recurrent neural network (RNN) which learns to classify if a video has been subject to manipulation or not and able to detect the temporal inconsistencies between frames introduced by the DF creation tools. Expected result against a large set of fake videos collected from standard data set.

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: Deepfake Detection , Kaggle Dataset, convolutional Neural network (CNN), recurrent neural network (RNN), Machine Learning.

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Vikara Vighatakara Bhavas represent protective parlance in Ayurvedic pathogenesis that proactively inhibit disease manifestation. These elements modulate the interaction of triad of Nidana (Doshas, Dhatus, Malas etc, the etiological factors) Visheshas, preventing Samprapti (pathogenic processes). Vikara Vighatkara Bhavas act as barriers against Vyadhi (disease) by opposing the association of causative factors like Naidan, Doshas, Dhatus, Malas etc. Their Bhavas (presence) strengthens Vyadhikshamatva (immunity), while Abhavas (absence) facilitates pathogenesis, as described in Charaka Samhita's Prameha Nidana. These Bhavas include Ojas, balanced Doshas, Prashashta (strong) Dhatus, and Sattvic mental states that neutralize Nidana's impact. Proactively, these Bhavas enhance resilience through Dinacharya, Ritucharya, and Rasayana therapies, fortifying the body pre-exposure to pathogens. Bala (strength), Sattva (psyche), and Abhyantara Hetus (internal causative factors) play key roles in averting Dosha vitiation. This aligns with Ayurveda's Swasthavritta emphasis on prevention over cure. Protectively, they disrupt Samprapti by limiting Dosha-Dooshya Sammurchana, influencing Rogamarga and Krama. Factors like Prativishesha (counter-specifics) determine disease severity, onset, and prognosis. In modern terms, they parallel immunity modulators, explaining individual disease resistance variations. Understanding these Bhavas guides Chikitsa towards Samprapti-Vighatana and Nidana-Parivarjana. Enhancing them via Ahara-Vihara and Ojasya-Rasayanas offers holistic prophylaxis.

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Vikara Vighatkara Bhavas, Ayurvedic pathogenesis, Samprapti-Vighatana, Vyadhikshamatva, Nidana-Visheshas, protective factors, Ojas, diseases etc.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Acute respiratory infections, video teaching programme, mothers, under-five children, preventive measures, rural health.

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Quality control plays a great role in the assurance of integrity, safety, and performance of a product within various industrial sectors such as pharmaceuticals, food processing, materials science, and chemicals. The commonly used traditional QC methods include titrimetric analysis, chromatography, and gravimetry among others. Though these methods are well known for their accuracy they involve destructive testing, elaborate sample preparation as well as long analysis time hence high operation cost and added environmental burden. Recent developments in different spectroscopic techniques have remodeled the analytical quality control area with their non-destructive, reagentless real-time molecular characterization capabilities. Available methods include FTIR, NIR, Raman, NMR, UV-Vis, THz, and LIBS which permit very selective and sensitive rapid determination of physical and chemical properties. These methods have not only enhanced analytical throughput but are also compliant with the current state of regulation which puts a spotlight on the PAT and QbD paradigms. This paper reviews the principles and foundations, instruments, applications, benefits, and practical challenges of advanced spectroscopic techniques. It discusses trends fueled by artificial intelligence in spectral interpretation, miniaturized and portable spectrometers, data fusion strategies, and hybrid spectroscopic platforms leading to intelligent automated sustainable QC systems. All these are integrated with the promise to bring a new dawn in modern manufacturing via predictive analytics as well as compliance that is not harmful to the environment while assuring quality.

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Keywords: Quality Control, Spectroscopy, FTIR, Raman, NMR, Process Analytical Technology, Non-Destructive Testing, Chemometrics, AI-driven Analysis.

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In every field of life, nanotechnology has an impact. Researchers expend their interests on gold nanoparticles synthesis as they provide superior properties for various types of applications. Different physical and chemical methods have synthesized conventionally nanoparticles that have a negative impact on the environment. Due to their unique properties, small size and high area-to-volume ratio, gold nanoparticles show special advantages in this field among nanoparticles. Because of their inert nature, stability, high dispersity, non- cytotoxicity and biocompatibility, these particles have been widely used in various biomedical applications and drug delivery systems. This paper shows the comparison and survey of all the methods. Gold nanoparticles are widely used in many fields As preferred materials for their unique optical and physical properties, such as surface plasmon oscillations for labeling, imaging, and sensing. Recently, many advancements were made in biomedical applications with better biocompatibility in disease diagnosis and therapeutics. Au-NPs could be prepared and conjugated with many functionalizing agents, such a polymers, surfactants, ligands, derailments, drugs, DNA, RNA, proteins. Peptides and oligonucleotides. This review addressed the use of gold nanoparticles and the surface functionalization with a wide range of molecules expanding and improving gold nanoparticles in targeting drugs for photothermal therapy with reduced cytotoxic effects in various cancers gene therapy and many other diseases.

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Gold nanoparticles, Nanotechnology, drug delivery, biomedical Applications, cytotoxicity, cancer, drug delivery.

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In today's fast-paced digital environment, businesses are increasingly employing chatbots to enhance customer support services. This research paper explores the functionalities of chatbots in customer support, their impact on operational efficiency, customer satisfaction, and challenges associated with their implementation. We also examine various case studies that highlight successful chatbot deployments across different industries.

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 Keywords

AWS, Azure, GCP, Intent, Entities, Utterances, Natural Language Processing (NLP), Fallback, Human Handoff (or Transfer), Artificial Intelligence, Knowledge Base, Conventional Flow

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