Volume 14 | Issue 7 |

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Keywords: Nurse-patient ratio, Hospital performance, Structural Equation Modeling, Patient safety, Nursing workload, Private hospitals.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Nursing workforce adequacy, Hospital quality outcomes, Patient safety, Job satisfaction, Nursing workload, Structural Equation Modeling.

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The integration of traditional Ayurvedic therapies with contemporary physiotherapy offers a holistic functional metabolic approach to rehabilitation. While physiotherapy excels in biomechanical correction and neuroplasticity, Ayurveda addresses the biological environment [Dhatu and Dosha] necessary for tissue repair. This paper explores the clinical rationale for integration, proposes a combined treatment protocol and discusses the potential for improved patient outcomes in chronic pain and stroke rehabilitation.

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CO-OPERATIVE REHABILITATION: A FRAMEWORK FOR INTEGRATION OF PHYSIOTHERAPY AND AYURVEDA IN NEUROMUSCULAR DISORDERS

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Background & Objectives Following a caesarean section, many mothers commonly experience pain, postpartum depression, and stress. Non-pharmacological interventions offer an accessible, cost-effective, and safe approach to managing these challenges. Benson's relaxation therapy, a non-pharmacological method, promotes physical and mental relaxation and improves overall recovery. To assess the effect of Benson relaxation therapy on post-caesarean pain and stress among postnatal mothers. To find out the association between pre-interventional level of c-section pain and stress among postnatal mother who underwent c-sections with their selected demographic variable. Methods A quasi-experimental study was conducted on 108 post-caesarean mothers in the post-natal ward of Queen Mary Hospital, KGMU, Lucknow, India. The experimental group received an intervention twice daily for three days. Post-interventional pain and stress were assessed by using a numerical pain rating scale & modified Hung postpartum stress scale. Results & conclusions The study reflected that BRT effectively reduced pain and stress levels in the experimental group. The mean pain score for the experimental group reduced from 5.79 to 2.64 while in the control group, it was 6.62 at pre-intervention and 5.09 at follow-up. The mean stress score for the experimental group reduced from 148.63 to 91.61 while in the control group, it was 159.41 at pre-intervention and 147.45 at follow-up. Also, there was no significant association between pre-interventional level of c-section pain and stress among post-natal mothers with their selected socio-demographic variables (p<0.05). This study reflected the positive effect of Benson's relaxation therapy in reducing pain and stress levels among post-caesarean section mothers.

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Benson's Relaxation Therapy, Post-Cesarean Pain, Postnatal Stress, Postpartum Period, Complementary Therapies, Maternal Health, Pain Management

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A Study on the Impact of the Use of ICT-Based Resources and Effective Teaching by Experienced Teachers on Students' Achievement

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A Study on the Impact of the Use of ICT-Based Resources and Effective Teaching by Experienced Teachers on Students' Achievement

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India's augmentation of online learning offers a special chance to improve inclusive education for students with disabilities, especially those who are deaf or hard of hearing and visual impairment. Digital platforms have emerged as crucial instruments for removing the obstacles that students with disabilities have historically encountered in a nation featuring an extensive array of socioeconomic backgrounds and notable educational disparities. Online learning provides braille-compatible devices, screen readers, and text-to-speech technology to pupils who are visually impaired, allowing them to have more independence and interact with the material. Online education has a great deal of promise to promote inclusive learning, but there are still obstacles to overcome. These include the dearth of using assistive technology in underprivileged and rural locations, gaps in accessible material, and instructors' inability to use digital literacy to successfully apply inclusive pedagogies. Targeted governmental measures, enhanced infrastructure and continuous teacher training are thus necessary to remove these obstacles and guarantee that pupils with hearing and vision problems have equitable access to high-quality education if internet learning is to be genuinely all-encompassing. This work investigates the part of internet education in overcoming obstacles related to cost, teacher scarcity, and geographical distance, while also considering the importance of digital literacy and infrastructure development in ensuring effective implementation. By synthesizing existing research and policy perspectives, this paper highlights the vital role of online education in shaping India's learning future, advocating for targeted interventions and collaborative efforts to harness its full potential for empowering inclusion and driving social transformation.

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Inclusive education, online learning, assistive technology, digital literacy, India, visual impairment, hearing impairment

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Dhatura (Datura metel Linn.), classified as an Upavisha (secondary poison) in the classical Ayurvedic texts, is one of the most pharmacologically significant yet toxicologically complex plants in the Ayurvedic Materia Medica. This research document presents a comprehensive study of Dhatura with a focused emphasis on its therapeutic applications in Kushtha Roga (skin diseases). Kushtha, an umbrella term in Ayurveda encompassing a wide spectrum of dermatological disorders, is caused by the vitiation of Tridosha (Vata, Pitta, and Kapha) along with the involvement of Sapta Dushyas (seven body tissues). Dhatura, by virtue of its unique Rasa-Guna-Virya-Vipaka-Prabhava (pharmacological properties), exerts profound Krimighna (antimicrobial), Kandughna (antipruritic), Shothahara (anti-inflammatory), and Vrana Shodhana (wound-cleansing) actions, making it highly relevant in the management of various types of Kushtha. The document traces the classical description of Dhatura across foundational texts including Charaka Samhita, Sushruta Samhita, Ashtanga Hridayam, and Raj Nighantu, and correlates its phytochemical constituents -- primarily tropane alkaloids such as Hyoscine, Atropine, and Scopolamine -- with its documented Ayurvedic actions. Furthermore, the critical process of Shodhana (purification/detoxification) as a prerequisite to safe therapeutic use is elaborated. This paper aims to provide a holistic, humanized, and academically structured understanding of Dhatura's place in Ayurvedic dermatology.

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Dhatura, Kushtha Roga, Upavisha, Krimighna, Shodhana, Datura metel, Kandughna, Ayurvedic Dermatology, Lepa, Vicharchika, Kitibha, Dadru

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INTRODUCTION Bio medical waste management has recently emerge as an issue of major concern for all the hospitals, nursing homes and environment. Improper segregation and disposal of hospital waste poses a serious threat to our environment and health care.Bio medical waste management is an essential component of quality health care assurance in hospitals. Meticulous biomedical waste disposal management is obligatory to reduce the hospital acquired infections to a great extent. Proper management of Biomedical waste (BMW) generated in a healthcare facility is one of the most important functions of a healthcare worker (HCW) as its improper management not only poses risk to human beings and environment, but may also invite legal action against HCW as well as hospital administration. This study was carried out to surveillance of Bio- medical waste practices in kims hospital its Evaluation and audit In Srikakulam, Andhra pradesh. OBJECTIVES : 1. To assess biomedical waste management practices among health-care workers at KIMS Hospital. 2. To evaluate compliance with biomedical waste management rules. 3. To audit segregation, color-coding, storage, and disposal practices. METHODOLOGY quantitative descriptive cross-sectional study was conducted to evaluate and audit biomedical waste management practices in a Kims hospital. A total of 100 health-care workers directly involved in biomedical waste handling were selected using convenience sampling. Data were collected using a structured observation checklist and questionnaire developed in accordance with Biomedical Waste Management Rules. The assessment focused on segregation at source, color-coding compliance, use of personal protective equipment, storage, internal transportation, disposal practices, and documentation. Ethical approval was obtained, informed consent was secured from all participants, and confidentiality was maintained. Data were analyzed using descriptive statistics, including frequencies and percentages. RESULTS The study revealed that 82% of participants followed correct segregation practices, while 76% used appropriate color-coded bins. Proper use of personal protective equipment was observed in 70% of participants. Documentation and labelling practices were satisfactory in 65% of the observed areas. However, gaps were identified in staff training and compliance consistency across departments. CONCLUSION The study concludes that biomedical waste management practices at KIMS Hospital are satisfactory but require continuous surveillance, regular audits, and periodic training programs to address existing gaps. Strengthening evaluation and monitoring mechanisms will improve compliance, enhance infection control, and ensure a safe hospital environment. KEY WORDS Biomedical waste management, Surveillance, Evaluation, Audit, Hospital practices, Infection control RECOMMENDATIONS o Regular in-service education and training programs o Periodic biomedical waste audits o Strict supervision and monitoring mechanisms. ETHICAL CONSIDERATIONS Ethical clearance was obtained from the institutional ethics committee. Written informed consent was obtained from all participants, and confidentiality was ensured.

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Biomedical waste management, Surveillance, Evaluation, Audit, Hospital practices, Infection control

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Precision agriculture has emerged as a critical response to mounting global pressures on food and water security, and the convergence of the Internet of Things (IoT) with Artificial Intelligence (AI) - collectively termed the Artificial Intelligence of Things (AIoT) - has become the dominant technological paradigm for realising this vision. Over the past decade, and with particular acceleration between 2018 and 2025, researchers have proposed a wide array of sensor architectures, data-fusion strategies, machine-learning and deep-learning predictors, irrigation decision-support mechanisms, and edge-to-cloud deployment blueprints aimed at reducing agricultural water consumption while sustaining or improving crop yield. However, this body of work remains fragmented across disciplinary boundaries, sensor modalities, and evaluation protocols, making it difficult for researchers and practitioners to identify consistent trends, reliable performance benchmarks, and outstanding gaps. This paper presents a structured, comprehensive review of AIoT-based precision agriculture research, organised around a six-part taxonomy: sensing and monitoring, multi-sensor data fusion, predictive analytics, irrigation decision-support systems, edge/cloud deployment architectures, and explainable artificial intelligence (XAI). Drawing on more than two dozen peer-reviewed studies published primarily between 2018 and 2025, the review synthesises reported sensor configurations, communication protocols, feature-engineering strategies, machine-learning algorithm performance, water-saving outcomes, deployment latencies, and explainability practices. Comparative analysis reveals that deep-learning architectures - particularly Long Short-Term Memory (LSTM) networks - consistently achieve the highest reported soil-moisture prediction accuracy (93-97%), that predictive and reinforcement-learning-based irrigation scheduling outperforms reactive threshold control by 25-44% in water savings, and that fewer than one in five reviewed studies incorporate any form of model explainability despite documented adoption benefits. The review further identifies four persistent research gaps - reliance on physical sensor infrastructure that limits reproducibility, the absence of standardised multi-algorithm benchmarking, limited integration of explainability, and the scarcity of holistic frameworks spanning sensing through cloud deployment - and proposes future research directions including federated learning, transformer-based architectures, digital twins, and simulation-based reproducible frameworks. This review is intended to orient new researchers entering the field and to establish the literature foundation for subsequent experimental work on AIoT-driven smart irrigation systems.

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AIoT, Precision Agriculture, Internet of Things, Machine Learning, Deep Learning, Multi-Sensor Data Fusion, Smart Irrigation, Decision Support Systems, Edge Computing, Explainable AI, Survey, Review.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Ventilator-Associated Pneumonia, Nurse-led intervention, ICU care, Ventilator bundle, Patient safety

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