Volume 12 | Issue 12 |

 Abstract

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Climate change, Adaptation, Agriculture, Global warming, Acid Rain

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Quadratic equations, a fundamental mathematical concept, play a vital role in agricultural planning and optimization. This paper explores their applications in areas such as determining crop yield, optimizing land use, and predicting cost-profit relationships. By applying mathematical modeling, quadratic equations help farmers make informed decisions to increase efficiency and productivity. Practical examples, case studies, and graphical representations demonstrate the utility of this approach in modern agriculture.

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 Keywords

Quadratic Equations, Agriculture, Crop Yield, Optimization, Mathematical Modeling

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Vespa velutina, Apis mellifera, Seasonal variation, Predatory behaviour

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Water scarcity poses a critical challenge in urban households, necessitating efficient water management systems. This paper introduces a comprehensive IoT-enabled solution for real-time water monitoring, leveraging smart sensors and predictive analytics to enhance water sustainability. The proposed system employs a flow sensor to track daily water usage and a Total Dissolved Solids (TDS) sensor to assess water quality, ensuring both quantity and quality are monitored effectively. Utilizing an ESP32 microcontroller, the system seamlessly transmits data to a cloud platform for advanced processing and visualization. A web application, developed using Web development languages, serves as the user interface, enabling households to monitor water consumption trends, predict water availability, and receive notifications when water level goes below the threshold level. Additional features include actionable insights for water conservation and an option to pre-book water tankers, promoting responsible water usage and ensuring uninterrupted supply. This innovative system integrates predictive analytics with real-time tracking to address the pressing need for sustainable water management. It not only offers households the convenience of managing water resources efficiently but also supports conservation efforts by raising awareness about usage patterns and water quality

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Water Management, IoT, Smart Sensors, Water Quality, Web Application

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Basti Karma (enema therapy) is considered as integral component of the treatment protocol in professional practice and known as Ardha Chikista or Poorna Chikitsa in Kaya Chikitsa. This practice aims to cleanse the colon, remove toxins, and restore balance in the body according to Ayurvedic principles. The physiology of Basti Karma revolves around several mechanisms, including the action of Basti may be because of endocolonic action, encolonic action and diacolonic action. The influence of Basti over body can be studied under the broad headings of action based on its Veerya, action over Pakwashaya, action over Dosha, and action over Dhatu, Absorption mechanism, Colon cleansing and excretory function, On the basis of microbiome gut brain axis, Through enteric nervous system, System biology theory. Through an in-depth exploration of the physiological mechanisms, this article elucidates how Basti Karma influences overall equilibrium of the body. By unravelling the intricate connections between Basti Karma and body's physiological dynamics, this article contributes to a comprehensive understanding of Ayurvedic principles and their applications in contemporary healthcare.

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KEYWORDS: Basti, Physiology, Action, Karmukata,

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The present work has been undertaken with the aim to determine the antifungal and antibacterial activity of dried extract obtained from the plant Piper nigrum. Two extracts of the Piper nigrum were prepared by Soxhlet extraction using ethanol and chloroform. Phytochemical screening of plant extracts showed the presence of alkaloids, glycosides, and carbohydrates. The work has also emphasized determining the antifungal activity of each plant extract against Candida albicans (fungi). Zone of inhibition of plant extracts with respect to three concentrations viz. 0.25 ?g/ml, 0.5 ?g/ml, and 1.0 ?g/ml have been done and the zone of inhibition were observed. Comparing the above three concentrations for anti-fungal activity 0.5?g/ml shows maximum activity for ethanolic extract of piper nigrum and 0.25 ?g/ml shows maximum activity for chloroform extract of Piper nigrum. Zone of inhibition of plant extracts with respect to three concentrations viz. 0.25? g/ml, 0.5?g/ml, 1.0?g/ml were performed and the zone of inhibition was observed. Comparing the above three concentrations for anti-bacterial activity 0.5?g/ml shows maximum activity for ethanolic extract of Piper nigrum and ?g/ml shows maximum activity for chloroform extract of Piper nigrum. The result obtained were promising for the management of bacterial and fungal infections.

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Piper nigrum, Candida albicans; Esherichia coli, Staphylococcus aureus; Antifungal activity; Anti-bacterial activity

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The mechanical properties of aluminum wire rods--such as conductivity, elongation, and ultimate tensile strength--play a vital role in various industrial applications. However, traditional methods for assessing these properties can be time-intensive and require complex experimental setups. To address this, our research introduces a predictive model powered by Artificial Neural Networks (ANNs) to estimate these properties based on three key parameters: cooling temperature, casting speed, and rolling speed. By training the ANN model with an extensive dataset of experimental measurements, we were able to capture the intricate nonlinear relationships between the processing conditions and the resulting material properties. The model proved to be highly accurate and reliable in predicting conductivity, elongation, and tensile strength, offering a practical and efficient alternative to conventional testing methods. Adopting this predictive model in industrial settings has the potential to transform operations, improve efficiency, reduce costs, and streamline quality control. This study highlights the value of machine learning in metallurgy, opening the door to smarter and more automated manufacturing processes. Moving forward, we aim to refine the model further, expand the dataset to include a wider range of processing scenarios and integrate the model into real-time monitoring systems to optimize operational performance.

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Aluminum wire rod, Conductivity prediction Elongation, Ultimate tensile strength, Artificial Neural Networks (ANNs), Cooling temperature, Casting speedRolling speed, Metallurgical properties, Machine . learning. Predictive modeling, Industrial applications, Quality control.

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Mandalas, intricate geometric designs originating from Hinduism and Buddhism, hold deep significance as symbols of cosmic harmony and interconnectedness within the universe. They are primarily utilized for meditation and spiritual development, serving as powerful tools in Vajrayana Buddhism to illustrate impermanence through the meticulous creation and subsequent dissolution of sand mandalas. In Hinduism, mandalas symbolize the cosmic order and aid practitioners on the path towards self-realization. The spread of Buddhism along the Silk Road played a pivotal role in disseminating mandalas across Asia, where they became integral to various religious and cultural traditions, enriching their symbolism and spiritual importance. Rich in symbolic meaning, mandalas often incorporate elements such as the Eightfold Path, promoting mental clarity and facilitating spiritual awakening. They also play a significant role in Ayurvedic and Tibetan Medicine, symbolizing the harmonious balance of elements within both the human body and the universe, thus promoting holistic well-being. The selection of colors within mandalas is purposeful, chosen for their symbolic meanings and their potential to evoke specific emotional responses, thereby enhancing their effectiveness in meditation and spiritual practices. Beyond their spiritual roles, mandalas find applications in diverse fields including fashion, education, therapy, architecture, and personal development. Recent research has explored their integration into yoga products, which has been met with positive reception from consumers, indicating promising market potential. The mandalas continue to inspire spiritual growth, encourage artistic expression, and contribute to holistic health practices globally. Their enduring cultural relevance and versatility across various domains underscore their profound impact on human experience and well-being.

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Mandalas, Hinduism and Buddhism, Symbolize, Vajrayana Buddhism, Tibetan and Monks, Sand mandala, Yoga Product Development.

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Biophilic design, emphasizing the integration of natural elements into built environments, has gained prominence for its ability to enhance human well-being. This study explores the incorporation of greenery in art galleries, focusing on its impact on visitor well-being and artwork perception. By analyzing Bharat Bhavan in Bhopal and two other case studies--the Chichu Art Museum in Naoshima, Japan, and the Fondation Beyeler in Basel, Switzerland--this paper investigates how greenery influences spatial ambiance, visitor engagement, and artistic interpretation. A survey conducted among visitors to these spaces reveals insights into their emotional, cognitive, and sensory experiences. The findings aim to guide future design strategies for art galleries, bridging art and nature harmoniously.

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Biophilic Design, Greenery Integration, Art Galleries, Visitor Well-being, Artwork Perception, Cultural Spaces, Sustainable Design, Natural Elements, Indoor Greenery, Visitor Experience, Charles Correa, Bharat Bhavan, Chichu Art Museum, Fondation Beyeler, Nature and Art, Green Architecture, Environmental Sustainability, Human Psychology, Natural Light, Spatial Ambiance.

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Stroke is a dangerous medical disorder that occurs when blood flow to the brain is disrupted, resulting in neurological impairment. It is a big worldwide threat with serious health and economic implications. To solve this, researchers are developing automated stroke prediction algorithms, which would allow for early intervention and perhaps save lives. The number of people at risk for stroke is growing as the population ages, making precise and effective prediction systems increasingly critical. wo In a comparison examination with six well-known classifiers, the effectiveness of the proposed ML technique was explored in terms of metrics relating to both generalization capability and prediction accuracy. To give insight into the black-box machine learning models, we also studied two kinds of explainable techniques, namely SHAP and LIME, in this study. SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-agnostic Explanations) are well-established and reliable approaches for explaining model decision making, particularly in the medical industry. The findings of the experiment revealed that more complicated models outperformed simpler ones, with the top model obtaining almost 91% accuracy and the other models achieving 83-91% accuracy. The proposed framework, which includes global and local explainable methodologies, can aid in standardizing complicated models and gaining insight into their decision-making, which can enhance stroke care and treatment.

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 Keywords

Stroke prediction, Explainable Machine Learning, SHAPE, LIME

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Creative Commons Attribution 4.0 and The Open Definition