Volume 13 | Issue 3 |

 Abstract

Kshara is extensively discussed in Ayurvedic texts, detailing its preparation, types, qualities, indications, contraindications, and potential complications. It is classified as both an Upayantra and an Anushastra, and is regarded as one of the most important tools among Shastra and Anushastra due to its properties such as Chedana, Bhedana, Lekhana, and Tridoshahara. The medicine possesses unique Ksharana and Kshanana properties, which help eliminate unhealthy tissues and unwanted growths. According to Vagbhatta, diseases that cannot be treated through Shastra karma should be addressed using Kshara Karma. Kshara is categorized into two types based on its preparation and use- Paneeya and Pratisarniya Kshara. Paneeya Kshara is taken orally and is particularly beneficial in treating chronic conditions where surgery is not an option. This review focuses on the preparation and clinical applications of Paneeya Kshara as described in classical Ayurvedic texts

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Kshara, Chedana, Bhedana, Lekhana, Paneeya Kshara.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Diet can be an important factor in the prevention and treatment of chronic (COPD). The American Lung Association obstructive pulmonary disease (COPD). The recommends eating 20-30 grams of fiber per day, from nuts, seeds, fruits, vegetables, bread, and pasta. Good sources of protein, like milk, eggs, cheese, meat, fish, poultry, nuts, and dried beans or peas, can help maintain strong respiratory muscles. Other foods and nutrients that may be beneficial for COPD include: Whole grains, Minerals, Vitamin D, Coffee, and Fish and n-3 polyunsaturated fatty acids. Objectives: 1. To assess the knowledge regarding COPD among patients. 2. To evaluate the effectiveness of Nutritional counseling on knowledge regarding COPD. 3. To find the association between knowledge scores with selected socio demographic variables. Hypothesis: H1: There is significant difference between pre-test and post-test knowledge score regarding Nutritional counseling among COPD patients at 0.05 level of significance. H2. There is significant association between level of knowledge with selected socio demographical variables of COPD patients at 0.05 level of significance. Methodology: The research design consisted of pre-experimental research design of one group pretest and post-test design. The population selected for the study was COPD Patients of selected areas at Vijayapur district. The study samples were 60 COPD Patients and were selected by using purposive sampling technique. The development of the tool involved steps of test construction i.e. preparing the blue print, selection of items, content validation and establishment of reliability. The content validity of the questionnaire was done and modifications were done according to the suggestions given by the experts. Pre-testing and reliability of the tools were done. The reliability coefficient of the knowledge questionnaire was found to be 0.893.The tool was found to be reliable. Results: In the pretest, level of knowledge of COPD patients living in selected areas at Vijayapur district before using Nutritional counseling. In that Majority 57(95.0%) of the COPD patients. had Inadequate knowledge and 3(5.0%) of the COPD patients had moderately adequate knowledge and there were no COPD patients having adequate knowledge regarding Nutritional counseling of COPD patients. After Nutritional counseling majority 47(78.3%) had adequate knowledge regarding Nutritional counseling, 6(10.0%) had moderately adequate knowledge and only 7(11.7%) remained with inadequate knowledge. The mean paired difference in knowledge score was -18.8 with t-value=-22.7 with p-value less than 0.0001 indicates that Nutritional counseling was effective in enhancing knowledge among COPD patients. The mean pretest knowledge score was 6.12 and mean post score was 24.8 and the difference in knowledge score was 18.8 with percentage improvement in knowledge was 75.8.Hence Nutritional counselling among COPD patients was effective in enhancing their knowledge. Conclusion: The study was concluded that, there was a significant improvement obtained following Nutritional counselling on Nutritional counseling. The study was recommended that there is an immense need for educational programme in areas to improve the knowledge of COPD Patients regarding Nutritional counseling.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key words: Effectiveness, Nutritional counseling, COPD Patients.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an intelligent amenity detection system for hospitality platforms using Detectron2. A fine-tuned RetinaNet model, trained on a curated Open Images dataset, is employed to detect household amenities such as coffeemakers and fireplaces. Data preprocessing, annotation formatting, and model training were conducted with GPU acceleration to enhance performance. The model was evaluated using mean Average Precision (mAP), achieving high accuracy and robust generalization to unseen images. Despite challenges like class imbalance and overlapping objects, it outperforms generic detection models. This work establishes a scalable pipeline for real-time deployment, with future enhancements focused on dataset expansion and hyperparameter optimization.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Object detection, Detectron2, deep learning, hospitality platforms, computer vision, RetinaNet.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Alopecia areata (AA) is an autoimmune disorder causing patchy, non-scarring hair loss. It can progress to alopecia totalis or universalis. Conventional treatments include corticosteroids, but homeopathy offers promising individualized remedies. This article examines homeopathic approaches in managing AA, focusing on personalized treatments targeting both physical symptoms and underlying factors. Case summary- A 17-year-old male presented with alopecia areata. The patient was treated with individualised homoeopathic medicine over a period of 6 months. There was significant improvement with homoeopathic treatment, with complete disappearance of symptomatology without any recurrence.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Alopecia Areata, Autoimmune Disorder, Homoeopathy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Change of direction (COD) speed is a critical performance factor in field hockey, influencing an athlete's ability to react swiftly to opponents and game dynamics. This study examined the effects of a four-week strength training intervention on the COD ability of a junior-level male field hockey athlete. Pre-testing assessments included the T-test (COD), 1RM back squat (lower limb strength), vertical jump (lower limb power), and 40m sprint (straight-line speed). Initial results indicated that the athlete lacked lower limb strength relative to normative values. A structured four-week strength training program, incorporating unilateral and eccentric-focused exercises, was implemented alongside regular skill and conditioning sessions. Post-testing results showed improvements in COD speed (T-test time reduced by 0.12s), 1RM back squat (+5kg), and vertical jump height (+1cm), while 40m sprint performance slightly declined (+0.06s). These findings highlight the importance of lower limb strength development in enhancing COD speed. Future research should explore longer intervention periods and include additional components such as reactive strength and biomechanical analysis to further optimize COD performance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Change of direction speed, Field Hockey, Strength Training, Lower limb Strength, Reactive Strength, Unilateral Training, Ecentric Training, Performance Enhancement.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Breast Cancer continues to be a major health concern for women worldwide, causing significant illness and death. Early detection is crucial because it increases the chances of successful treatment, making accurate diagnosis vital. In this approach, a hybrid predictive model was developed that leverages deep learning and machine learning techniques. Convolutional Neural Network (CNN) extracts features and captures intricate patterns from mammographic images, while Support Vector Machine (SVM) serves as the classification model to differentiate between Benign and Malignant cases. If malignant, the hybrid model further analyses extracted features to predict the cancer stage, aiding in severity assessment and treatment planning. The model's performance is evaluated using standard metrics, demonstrating superior accuracy and reliability compared to traditional methods. This integrated approach assists radiologists in making more precise and timely diagnoses, ultimately leading to better patient outcomes.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SVM, CNN, Mammography, Classifiers.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Addressing critical problems such as range anxiety and charging-infrastructure limitations, Wireless Power Transfer (WPT) technology has emerged as an innovative method to enhance plug-in electric vehicle (EV) adoption. To enable seamless on-road energy interaction of mobile vehicles, the design and implementation of a high-efficiency wireless powering transferred (WPT) system for dynamic roads-side electric vehicle (EV) charging lanes is studied in this paper. Using state-of-the-art resonant inductive coupling, optimized coil geometries, and advanced power electronics, the envisioned system achieves high efficiency of energy transfer over a wide variety of speed and alignment conditions. This study proposes novel guarantees for reducing energy losses due to misalignment and drifting vehicle dynamics using machine learning based models and adaptive control strategies. The system's architecture ensures optimum user safety and low electromagnetic interference (EMI) by operating within regulatory safety limits. The charging lane infrastructure incorporates renewable energy integration and modular design ideas to improve cost-effectiveness and scalability. A thorough examination of dynamic charging lane performance in practical settings, the creation of energy management plans for grid stability, and a feasibility study for widespread implementation in urban and highway settings are some of the major contributions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

wireless power transfer, dynamic charging, electric vehicles, resonant coupling, energy efficiency, adaptive control, electromagnetic interference, renewable integration, grid stability, smart mobility.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In artificial intelligence, creating intelligent question-answering (QA) systems that facilitate organic human-machine communication is still a major problem. Since efficient QA models need a thorough comprehension of syntax, semantics, and contextual linkages, the lack of domain-specific data has historically impeded development. Natural language processing (NLP) has been transformed by the introduction of pre-trained language models like BERT and GPT, which provide contextualized word embeddings that improve understanding and response creation. These models are extremely useful for creating sophisticated chatbot systems because of their exceptional ability to capture language patterns, long-term interdependence, and hierarchical linkages. The latest developments in transformer-based language models and their uses in QA-driven conversational AI are examined in this paper. We examine their design, methods of training, and effects on enhancing chatbot systems' precision and contextual awareness. We also address issues like domain-specific job fine-tuning, data efficiency, and ambiguity resolution. Our results demonstrate how pre-trained models may improve chatbot interaction, flexibility, and human-like engagement. Improving model efficiency, adding multimodal inputs, and tackling ethical issues in AI-driven dialogues are some future research avenues.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Natural Language Processing (NLP), Transformer Models, Pre-trained Language Models, Question Answering (QA) Systems, Contextual Chatbots, BERT (Bidirectional Encoder Representations from Transformers), GPT (Generative Pre-trained Transformer), Machine Comprehension (MC), Conversational AI, Deep Learning, Neural Networks, Fine-tuning, Transfer Learning, Stanford Question Answering Dataset (SQuAD), Information Retrieval (IR), Multi-turn Dialogue Systems, Natural Language Understanding (NLU), Dialo

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The continuous use of chemical fertilizers for a long period of time deteriorates the nutrient status of soil. Even if balanced doses are used it leaves a residual effect for the next crops grown in the same arable land. This change in soil becomes more problematic for a vulnerable crop. In this regard a field experiment was carried out during Kharif season of 2010 and 2011. To study the effect of Farmyard Manure and Zinc along with optimum dose of NPK on the productivity of rice variety Pant Dhan 4. The studies so far reveal that the application of essential plant nutrients particularly macro and micronutrient in optimum quantity and right proportion is the key to increased and sustained crop production. An application of NPK with FYM and Zn proved to be superior in recording the highest number of tiller, panicle length, leaf area index, test weight and grain yield. This study demonstrates that the combined application of inorganic fertilizers and organic manures along with Zn has the potential to reduce chemical fertilizer usage without decreasing the yield of rice verity pant Dhan 4. In addition, excessive use of chemical fertilizers in agriculture has led to a variety of environmental problems and in the future fertilizers will be a major source of heavy metals and radionuclides accumulating as inorganic pollutants in plants.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rice, NPK, FYM, number of the tiller.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Planktonic communities play a crucial role in assessing the quality of water bodies. These communities consist of two main types: Zooplankton and Phytoplankton. Zooplankton, in turn, can be classified into four primary groups: Rotifera, Cladocera, Ostracoda, and Copepoda. This study mainly focuses on Copepoda in Washim region. Copepods are abundant and serve as key components in marine food webs, acting as major grazers of phytoplankton and contributing to microbial loops. Smaller copepods utilize various reproductive and feeding strategies to maximize their population size, which helps them counteract the high predation losses they face. During the study, a total of ten genera and two species of Copepoda were identified across four sampling sites. As a pollution indicator species, the study is concentrated solely on Copepoda rather than other types of zooplankton.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Copapoda, Quantitative Estimation, Washim District

  License

Creative Commons Attribution 4.0 and The Open Definition