Volume 13 | Issue 5 |

 Abstract

Heart disease is a leading global cause of death, making early detection essential. This project uses AWS SageMaker to build a predictive model based on key health indicators like age, cholesterol, and blood pressure. A robust pipeline handles preprocessing, feature selection with Random Forest, and model training using XGBoost. Hyperparameter tuning improves performance across accuracy, precision, and AUC. The model is deployed to a real-time endpoint for fast predictions, and a Streamlit app offers a simple interface for healthcare professionals and patients to assess heart disease risk.

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 Keywords

AWS SageMaker, XGBoost, Random Forest, Feature Selection, Cardiovascular Risk Assessment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The formulation of herbal face serum using with Mulberry (Morus Alba) and Jasmine (Jasminum Sambac) have investigated in this study both are rich in bioactive compound and offering the benefits such as antioxidant, anti aging and skin lightening property today most of serum are available made from synthetic and herbal remedies but they give sometime unwanted side effects like skin rashes and allergic reaction. The aim of this research was to develop and evaluate natural effective and safe face serum the formulation is evaluated using various physiochemical test include pH viscosity stability spraydability additionally the serum evaluated for anti microbial activity and skin irritation result showed that the herbal face serum exhibited excellent properties and provide effective and natural care for various skin types .

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 Keywords

Herbal face serum, Morus Alba, Jasminum Sambac, Antioxidant, Anti-ageing, Stability,Spreadability.

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Creditors are considered as a lifeline of a company and companies are considered as a lifeline of every country's economy. Similar inference can be taken from the recently developed Insolvency and Bankruptcy Code 2016 (IBC). The code was developed with a view to easing the process of Insolvency resolution and giving the companies and individual's another financial lifeline. Hence, promoting ease of doing business. One of the major features of IBC 2016 was the formation of a custodian body under its provisions, namely, Information Utility (IU). IU is regulated by Insolvency and Bankruptcy Board of India (Information Utilities) Regulations 2017, with the sole purpose of easing the process of collection of reliable and readily accessible financial records of solvent and insolvent entities. However it is noteworthy, owing to the provisions of the Act, it casts an empty obligation on the financial creditors and debtors as it does not provide for any penalty incase of non fulfillment of such obligation. Thus defeating the purpose of these provisions. It has been observed that IU's have a huge potential to help play a key role in not just speedy resolution process but also for the smooth functioning of companies and credit houses nationwide. This paper analyzes the immutable potential and limitations of Information Utilities on a micro and macro level -- formulated under IBC 2016.

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 Keywords

Insolvency and bankruptcy code (IBC), Information Utility (IU), Asymmetric Information, stochastic game

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 Abstract

Abstract Heavy metal contamination of industrial effluent by lead (Pb), Nickel (Ni) chromium (Cr) presents major risks to human health and the environment. This study aims to screen the bacterial isolates (available at P2BL, Osmania University) from rice rhizosphere for tolerance to heavy metals such as lead, nickel, chromium. The strains that were identified previously as Mesobacillus subterraneus GHM58, Pseudomonas migulae GHK43, Microbacterium hydrocarbonoxydans GHQ55, Brevundimonas nasdae GHM62, were isolated from rice rhizosphere. The bacterial isolate's growth and lead tolerance were monitored at concentrations of 125 ppm, 250 ppm, and 500 ppm of lead. Growth measurements were taken at 8, 16, 24, and 32 hours. The bacteria strain GHM58, GHQ55. and showed the strongest resistance to lead, using minimum inhibitory concentration (MIC) tests to tolerate doses as high as 500 ppm/L key functional groups involved in metal biosorption, including hydroxyl, carboxyl, phosphate, and amide, were identified by FTIR analysis of the supernatants were collected after 24 and 48 hours. These results demonstrate bacterial strains. and remarkable lead tolerance and demonstrate its potential for use in bioremediation.

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Keywords: Heavy metals, lead, bioremediation, Industrial effluents, UV-visible spectrophotometer, FTIR.

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Abstract Disability and inclusion are central issues in the social work field, addressing the rights, challenges, and opportunities for individuals with disabilities in society. Inclusion refers to creating environments where individuals with disabilities are valued, included, and supported to participate in all aspects of life. This paper explores the relationship between disability and inclusion, examining the historical and social context, challenges faced by individuals with disabilities, and the role of social workers in promoting inclusive practices. It highlights key theoretical frameworks, policies, and strategies for inclusion and advocates for a more integrated approach to disability services. The study emphasizes the importance of raising awareness, breaking down barriers, and enhancing social participation for people with disabilities in all aspects of life.

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Disability and Inclusion

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Accurate monitoring of daily calorie intake is crucial for managing a healthy lifestyle and preventing obesity-related diseases. This project introduces an AI-powered food calorie detection system using image recognition and machine learning techniques. The system is built using Python, Flask, and a frontend developed with HTML, CSS, and JavaScript. By uploading a food image, the model predicts its type and estimates its calorie content based on a trained deep learning classifier. This paper details the development process, system architecture, and the technology stack behind the system. A user-friendly web interface allows users to upload images, view predicted results with nutritional information, and track previous predictions. The system is designed to be scalable and modular for future integrations such as mobile applications and wearable device compatibility.

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 Keywords

AI, Calorie Detection, Image Recognition, Machine Learning, Web Application, Health Monitoring

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Creative Commons Attribution 4.0 and The Open Definition

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Nickel-zinc ferrites are the magnetic materials that shows diverse industrial applications especially in the photo catalysis owing to their magnetic coactivity and eddy current loss with low value electrical resistivity with high value that affects and tailor these soft magnetic nano ferrites structural and morphological characteristics. In existing study, we have synthesized zinc doped nickel ferrites Ni1-xZnxFe2O4 nanoparticles (NPs) with variation in nickel and zinc concentration simultaneously as (x = 0.0, 0.2, 0.4, 0.6 ,0.8,1.0)) via Sol-Gel auto combustion technique. The structural analysis of the NPs was carried out by XRD technique. We compare our results with JCPDS #01-073-1963. From this study we conclude that the synthesized NPs are cubic spinel structure with preferential orientation along the (311) plane. D-spacing for (311) plane varies from 2.48 to 2.53 A0. We have determined the crystallite size using the Debay-Scherer Formula and we observed crystallite size in between the 22nm to 29nm. Investigations by XRD revealed that all the prepared samples demonstrate a pure phase. Alterations in the lattice parameters and micro-strain observed due to introduction of Zn in the crystal structure. Morphology of the synthesized NPs analyzed using the FESEM. We have observed that synthesized NPs are porous in nature. With concentration of nickel and zinc, this porosity varies. Stoichiometry of the NPs was studied with the help of EDS spectra. It confirms the presence of the nickel, zinc, iron and oxygen in the NPs. With change in the concentration, we observed the variation in the atomic % of Zinc and Nickel.

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Nickel-zinc ferrites; FESEM; nanoparticles; XRD; EDS; Sol-gel Method

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Solar-powered water fountains have gained significant attention due to their eco-friendly nature and sustainability. This paper proposes the design and implementation of a solar-powered water fountain system, which utilizes a Variable Frequency Drive (VFD) to control the water pump's speed, providing energy efficiency and adaptability to fluctuating solar irradiance levels. The system operates without the need for batteries, making it simpler and reducing the maintenance costs commonly associated with energy storage systems. The proposed system directly converts solar energy into mechanical work for the fountain pump by adjusting the motor's frequency to maintain optimal performance. By incorporating a VFD, the water flow can be dynamically controlled based on solar intensity, ensuring consistent operation while minimizing energy waste. This system provides an efficient and reliable solution for renewable energy applications, especially in off-grid locations. Experimental results demonstrate the effectiveness of the system, showing stable fountain operation with variable solar conditions. The paper also discusses the benefits, challenges, and potential for future advancements in such solar-powered systems.

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Solar power, water fountain, Variable Frequency Drive (VFD), renewable energy, pump control, off-grid systems.

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StudMeet is an intelligent video conferencing platform that uses hybrid deep learning (CNN + RNN) to monitor student engagement in real-time. It analyzes facial expressions to classify attentiveness (engaged, bored, sleepy, distracted) with 89.2% accuracy. The system features role-specific dashboards for instructors and students, powered by WebRTC for seamless video communication. Educators receive live engagement analytics via heatmaps and attention scores, with AI-driven intervention prompts (e.g., pop quizzes) when disengagement is detected. Built with a Supabase backend, it ensures secure data storage (PostgreSQL) and privacy compliance. StudMeet bridges the gap in virtual learning by providing actionable insights into student involvement.

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 Keywords

AI in education, real-time engagement tracking, student attention monitoring, adaptive interventions.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nanotechnology applications in energy sector have potential to bring a paradigm shift in energy production, security and conservation. Nanomaterials can find potential applications in solar, wind, and bioenergy systems for enhanced energy conversion, storage, and utilization. In the previous few decades, tremendous advancement has been made in nanomaterials (e.g. quantum dots, nanotubes, and nanocrystals) that can be utilized to boost the photoelectric efficiency of solar cells and speed up energy storage in batteries and supercapacitors. In addition, the application of nanotechnology for harvesting energy, like triboelectric nanogenerators or nanostructured wind turbines, exhibited higher energy conversion rates which offer renewable energy sources greater viability, and make them more efficient. Moreover, nanostructured catalysts have been crucial in the invention of advanced biofuels and hydrogen generation methods. These approaches could be effective in improving the efficiency and longevity of energy harvesting systems, ultimately enhancing their performance and reliability. The overview highlights recent advances in the application of nanotechnology to renewable energy systems and discusses prevailing obstacles and future perspectives in order to improve the practical application of nanostructures to sustainable energy conversion and storage. Overall, the results indicate that future renewable energy systems can be transformative via nanotechnology and contribute to a global energy transition.

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 Keywords

Nanotechnology, Renewable Energy, Solar Cells, Wind Energy, Biofuels, Energy Storage, Nanomaterials, Sustainability

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