Volume 14 | Issue 7 |

 Abstract

ANALYTICAL STUDY OF THE RELATIONSHIP BETWEEN CONSUMPTION OF FORTIFIED RICE AND ITS UTILITY IN HUMAN NUTRITION: WITH SPECIAL REFERENCE TO RAJNANDGAON DEVELOPMENT BLOCK

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ANALYTICAL STUDY OF THE RELATIONSHIP BETWEEN CONSUMPTION OF FORTIFIED RICE AND ITS UTILITY IN HUMAN NUTRITION: WITH SPECIAL REFERENCE TO RAJNANDGAON DEVELOPMENT BLOCK

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The purpose of this research paper is sharing assets is just dividing library assets by specific partaking libraries among them based on the rule of participation. This is pertinent while sharing records, work, administrations, space and gear. This report principally features what are you sharing assets? Why share assets? Structures, means and techniques: definition, Goals, needs, areas of collaboration and tradeoff assets, parts, prerequisites, Idea, benefits, analysis, obstruction, moves toward advance the trading of assets through the network, Library Consortium and its sorts and works.

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Digital resources, Knowledge, Teaching and learning

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A Self-Learning AIoT Digital Twin for Predictive Urban Flood Resilience Using Dynamic Sensor Fusion and Counterfactual Intervention Analysis

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A Self-Learning AIoT Digital Twin for Predictive Urban Flood Resilience Using Dynamic Sensor Fusion and Counterfactual Intervention Analysis

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Abstract Artificial intelligence (AI), particularly the rapid development of generative artificial intelligence (GenAI), is reshaping the knowledge, competencies, and professional practices expected of contemporary teachers. Teacher education consequently faces a dual responsibility: it must prepare teachers to use AI productively in pedagogical practice while simultaneously developing their capacity to question, evaluate, and regulate its educational use. This paper critically reviews the emerging role of AI in teacher education, with particular attention to pre-service teacher preparation, pedagogical design, assessment and feedback, reflective practice, professional learning, and AI literacy. Moving beyond technologically deterministic accounts of AI-driven educational transformation, the review examines the conditions under which AI may strengthen rather than diminish teacher agency and professional judgement. Particular attention is given to generative AI because its capacity to produce text, images, instructional materials, assessment tasks, explanations, and feedback has created qualitatively different opportunities and challenges for teacher preparation. The review also examines concerns relating to algorithmic bias, hallucinated information, data privacy, academic integrity, unequal access, transparency, accountability, and overdependence on automated systems. Drawing on contemporary scholarship and international competency frameworks, the paper proposes an AI-Enabled Teacher Education Framework (AI-TEF) organized around five interconnected dimensions: AI Understanding, AI-Supported Pedagogy, Critical Evaluation, Ethical Responsibility, and Human-AI Professional Agency. The framework positions AI competence not as technical proficiency alone but as the capacity to make pedagogically justified, ethically responsible, and context-sensitive decisions concerning AI. The paper argues that the future of teacher education should not be organized around replacing teacher expertise with automated intelligence, but around preparing teachers who can critically orchestrate human and artificial intelligence while preserving the relational, ethical, creative, and professional foundations of teaching.

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Keywords: Artificial Intelligence; Generative AI; Teacher Education; Pre-Service Teachers; AI Literacy; Teacher Competence; AI Pedagogy; Professional Development; Ethical AI

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Abstract: Olfaction is a specialized sensory function that enables perception of smell and plays a vital role in environmental awareness, food selection, and emotional responses. In modern physiology, olfaction begins when odorant molecules interact with olfactory receptor neurons in the olfactory epithelium, followed by transmission of impulses through the olfactory nerve to higher cortical centers, where smell is consciously perceived. [1,2] Philosophical textbook of ayurveda, Tarka Sangraha, gives certain basics facts of olfaction. Ayurveda explains smell perception (Gandha Jnana) through the coordinated action of Ghranendriya, Gandha Tanmatra, Prana Vayu, Manas, and Atma further explains Gandha as the specific quality (Guna) of Prithvi Mahabhuta, thereby establishing the elemental basis of olfactory perception. [3]. The present article attempts to analyze the physiology of olfaction from an Ayurvedic perspective and correlate it with contemporary understanding of olfactory physiology.

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Ayurveda, Ghranendriya, Gandha, Olfaction, Prana Vayu, Indriya Vigyana

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In analog and mixed-signal integrated circuits, this type of Bandgap (BGR) reference circuits is a critical element that supplies a reference voltage that is relatively constant across temperature, supply, and process. Low temperature coefficient (TC) is important for high precision uses like data converters, voltage regulators or sensor interfaces. Nevertheless, as BGR parameters are complex, nonlinear, and involve multiple design variables, traditional simulation-based methods are inefficient and sub-optimal to optimize BGR parameters. This is addressed by this work, which proposes an artificial intelligence based optimization framework, comprising of a neural network model and Particle Swarm Optimization (PSO). To validate the proposed AI optimization framework, a synthetic dataset of the bandgap reference circuit parameters was created. The methodology shows the practicality of combination of neural networks with Particle Swarm Optimization for automatic parameter optimization process. Validation by circuit simulation data is reserved for future work, and a feed-forward neural network (7-17-17 architecture) is used to train the network for accurate prediction of the temperature coefficient. The model is trained with the mean squared error loss function in order to learn nonlinear relations well. Results of experiments conducted on a synthetic dataset show that the proposed hybrid approach can learn the relationships between the underlying parameters and enhance the optimization efficiency. The results confirm that the proposed AI framework is a proof of concept. The methodology is a scalable solution for automatic analog circuit optimization and can be extended to other complex electronic design problems

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- Bandgap Reference (BGR) Circuit, Temperature Coefficient (TC), Artificial Intelligence (AI), Machine Learning, Feed-Forward Neural Network, Particle Swarm Optimization (PSO), Analog Circuit Optimization, Mixed-Signal Integrated Circuits, Parameter Optimization

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Resource depletion has emerged as one of the most critical challenges confronting modern businesses in the 21st century. The rapid consumption of natural resources such as fossil fuels, water, forests, and minerals due to industrialization, urbanization, and increasing consumer demand has created significant economic, environmental, and social concerns. This paper examines whether resource depletion represents a threat or an opportunity for contemporary businesses. On one hand, diminishing resources lead to rising production costs, supply chain disruptions, environmental degradation, and stricter government regulations, posing serious risks to business sustainability and profitability. On the other hand, resource scarcity encourages innovation, technological advancement, sustainable practices, and the development of green business models. Companies are increasingly investing in renewable energy, recycling, circular economy strategies, and efficient resource management to gain competitive advantages and improve long-term resilience. The study highlights how businesses that adapt to sustainable practices can transform environmental challenges into opportunities for growth, brand value, and market leadership. Ultimately, the paper concludes that resource depletion can be both a threat and an opportunity, depending on how effectively organizations respond to the changing global economic and environmental landscape. We will need to produce 70% more food by 2050 to meet the demands of the world's massively expanding population, according to the United NationsImagine a world of spiraling food prices, water shortages and soaring energy costs.For many living in the world today, this nightmare scenario is already a reality. Even for the well-off living in developed economies, it's becoming all too familiar and on current projections, it's going to get a whole lot worse. Short-term fluctuations in supply and demand aside, a global population explosion combined with finite resources means the planet cannot sustain ever-increasing levels of consumption using current models of production.

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Spiraling food prices, soaring energy, global population explosion

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Background: The patient was a 24-year-old archer diagnosed with right supraspinatus tendinopathy associated with mild subacromial bursitis due to repetitive overuse during intensive training of the sport. The patient opted for conservative physiotherapy management with the main and important goal of returning to the sport. Rehabilitation was planned using clinical evidence and patient-centered care. Materials & Methodology: The patient underwent a 6-week physiotherapy intervention programme following pre and post intervention assessment, consisting of Cryotherapy, Muscle Energy technique (MET), progressive therapeutic exercises, neuromuscular rehabilitation, scapular stabilization, and a well-structured home exercise programme. Initially, cryotherapy was used to reduce pain and inflammation, and further MET was applied to reduce muscle tightness and improve mobility of the shoulder joint. Progressive strengthening and various sports-specific exercises were also included and incorporated to improve dynamic stability of the shoulder, restore rotator cuff strength and to enhance functional performance. Results: The patient showed significant improvements through rehabilitation; the pain decreased from 6/10 to 1/10 on the Visual Analogue Scale (VAS). There was an improvement in shoulder pain and disability index (SPADI) from 48% to 10 % and improved grades of rotator cuff muscle strength. After the completion of the rehabilitation programme, the patient successfully returned to competitive archery. Conclusion & Discussion: This case highlights the effectiveness of a conservative rehabilitation programme combining various therapeutic approaches in managing rotator cuff tendinopathy in an archer. The integration of evidence-based practice, clinical expertise and patient consistency successfully contributed to his return to sport.

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Muscle Energy Technique, Cryotherapy, Archery

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Abstract: The chapter of Sushruta Samhita presents a philosophical explanation of the human body by tracing its origin to the unmanifest source (Avyakta or Prakriti) and by describing the ordered evolution of the cosmos through Mahat, Ahamkara, Tanmatras, senses, and the gross elements. The Sankhya Sutra tradition also explains reality through the dual principles of Prakriti and Purusha, the three gunas, and the gradual unfolding of the manifest world. The study shows that Sarvabhuta Chinta Sharira Adhyaya is not simply a medical chapter. It is a philosophically informed literary text that adapts Sankhya metaphysics to Ayurvedic thought. Its significance lies in the way it connects cosmology with physiology, and metaphysical speculation with practical knowledge of the body

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Key words: Sankhya Darsana, Sushruta Samhita, Health

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PURPOSE: To find out Physiotherapist perspective on Artificial intelligence: awareness, feasibility, readiness, and effectiveness in practice and understanding physiotherapist view on AI in practice. MATERIAL AND METHOD: 273 Physiotherapist participated in an online and cross-sectional study. A customized questionnaire was developed and validated by an expert panel of 10 Physiotherapist (S-CVI/Ave = 0.938). Data was collected using Google form and analyzed using descriptive statistics. RESULT: The study included 273 practicing Physiotherapist, predominantly early- to mid-career clinicians with under ten years of experience, working across hospital and private clinic settings. A majority reported awareness of AI in physiotherapy, with a large proportion has observed its direct application in clinical practice. Most participants agreed that AI could improve care standards and patient outcomes, identifying personalized treatment plans and predictive analytics as the primary benefits. Roughly seven out of ten clinicians reported felt prepared for AI integration and had utilized AI software, though data privacy issues and a lack of technical understanding were identified as the primary implementation barriers. Key concerns centered on the potential loss of human touch and data privacy risks, though well over half of respondents maintained that AI would serve to support clinical practice or have minimal impact rather than replace human therapists. CONCLUSION: Physiotherapist have high level pf awareness, positive attitude and willingness towards including AI technologies into clinical practice. However successful integration requires formal education, training programs, structured clinical guidelines, strong data privacy frameworks, and approach that preserves the important human-centric relationship in physiotherapy care.

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Artificial intelligence, Physiotherapy, Physiotherapist

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