Volume 13 | Issue 6 |

 Abstract

Medicinal plants, which continue to be an essential source of bioactive compounds for modern therapeutic applications, have been a major component of traditional medical systems around the world. In order to verify traditional claims, identify new therapeutic possibilities, and ensure the effectiveness, safety, and quality of herbal remedies, the pharmacological evaluation of these botanicals is crucial. Given the growing interest in plant-based medications worldwide, there is an urgent need for scientifically sound methods that incorporate in vitro, in vivo, and ex vivo processes to evaluate the pharmacological activity of herbal extracts and their constituents. Specifically, this research focusses on the systematic approaches used in the pharmacological evaluation of medicinal plants in the context of Herbal Drug Technology (HDT). Hepatoprotective, anti-inflammatory, antibacterial, antioxidant, antidiabetic, and anticancer properties are among the biological activities that are evaluated using a variety of models. The review also emphasises the importance of standardisation, quality control, and regulatory norms to ensure the safety and repeatability of plant-based formulations. Recent advances in experimental pharmacology, bioassay-guided fractionation, and molecular docking have greatly enhanced the scientific validation of ethnopharmacological claims. The paper's conclusion highlights the challenges and future directions in combining traditional herbal knowledge with modern pharmacological research to produce safe and effective phytomedicines.

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 Keywords

Medicinal plants, Herbal drugs, Pharmacology, Herbal medicine, Plant extracts, Natural medicine, Traditional medicine, Drug evaluation, Herbal treatment, Plant-based drugs, Phytochemicals, Herbal research, Bioactive compounds, Herbal drug testing, Herbal formulations

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 Abstract

This study presents a deep learning approach for automated lung cancer classification using a custom-labeled dataset of CT scan images. The system leverages a Convolutional Neural Network (CNN) to detect and classify lung conditions into six categories: adenocarcinoma, benign cases, large cell carcinoma, malignant cases, normal, and squamous cell carcinoma. The model was trained, validated, and tested on this custom dataset, achieving high classification accuracy and robust performance across all classes. This implementation paves the way for scalable, early-stage detection tools in medical imaging.

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 Keywords

CNN, Lung Cancer, CT Scan, Deep Learning, Image Classification, Medical Imaging

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 Abstract

In this work, we introduce an advanced intelligent system designed to use deep learning techniques to identify and distinguish between human tissue status and vitamin defi- ciencies effectively. Our approach begins with the use of image aggregation techniques to isolate and better focus lesion areas in images. The large amount of data available on the image databases is used to fine-tune the pre-trained networks to obtain color, texture, and structure features related to the pathologies. This approach is effective and provides an oppor- tunity to detect vitamin deficiencies quickly and unequivocally even to expose patients to invasive procedures. The system aims to conduct an image analysis of physical characteris- tics associated with deficiency diseases, which include pale skin, smooth tongue, and dry eyes. Our primary objectives are to thoroughly evaluate the effectiveness of the proposed segmentation procedure, determine which aspects are most critical for exact classification, and compare the effectiveness of our grouping results with those achieved using alternative methods. This method aims to enhance the precision and reliability of identifying and distinguishing between various tissue types and deficiencies, thereby advancing diagnostic capabilities in medical imaging significantly.

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 Keywords

Vitamin Deficiency, Deep Learning, CNN, ResNet, Medical Imaging.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) refers back to the application of smart algorithms and device gaining knowledge of techniques to decorate the detection, prevention, and response to cyber threats. AI empowers cybersecurity systems to investigate sizable amounts of information, identify styles, and make knowledgeable choices at speeds and scales beyond human abilities. The function of AI in bolstering safety features is multifaceted. It revolutionizes danger detection, automates responses, and strengthens vulnerability management. AI-powered structures can hit upon threats in real time, allowing rapid response and mitigation. by way of analyzing behaviors, detecting phishing, and adapting to new threats, AI allows proactive protection and safeguards touchy information. Additionally, AI can automate ordinary cybersecurity duties including log evaluation and vulnerability scanning, freeing up human analysts to consciousness on more complex and strategic activities. AI constantly learns from new statistics, adapting and evolving to enhance its capacity to pick out and counter rising threats.

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 Keywords

Keywords: Artificial Intelligence, Cyber Security, Detection, Prevention

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Attendance System performs image and class training that enables OpenCV data extraction functionality. The central objective behind this project involves building Face Recognition technology for attendance management to transform existing manual procedures into new automated systems. The system operates within the classroom space to train student with information that consists of name along with roll number and class details and sections and images. The extraction of images occurred through OpenCV software. When the corresponding class period began students would approach the machine for a photo capture session against the registered database photos. The development of a facial recognition-based attendance solution through Raspberry Pi forms the main objective of this project. The integration of face recognition algorithms in this system removes the requirement for manual user contact and achieves better precision levels together with enhanced dependability. The system first recognizes faces through its capture function and then creates records about attendance while determining presence as well as absence based on time spent in front of the system. The application features Face Detection and Face Recognition functionalities conducted through the Haar Cascade classifier using Open CV algorithms executed on Raspberry Pi hardware.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Face Detection, Face Recognition, Haar Cascade classifier, Open CV, Raspberry Pi.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research investigates the influence of Titanium Oxide nanoparticles as an additive into the magnetorheological fluid experimentally. The optimization parameters were considered based on their significance in achieving the magnetorheological effect such as density, sedimentation rate, shear stress, viscosity so as to enhance the stability of magnetorheological fluid and to achieve better damping in case of magnetorheological damper. Different volume percentage of Titanium Oxide nanoparticles viz;0.2%,0.4%,0.6%. have been blended with the magnetorheological fluid and the developed composites have been ranked using most preferred MCDM technique, TOPSIS. The experimental results revealed that 0.2 weight %TiO2 (Titanium Oxide) indicates highest relative closeness and ranking.

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 Keywords

TiO2, nanoparticle, TOPSIS, magnetorheological fluid, MR Damper

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study focuses on improving the engineering properties of clay soil a commonly used but moisture-sensitive material in construction by using eggshell powder, an industrial waste, as a stabilizer. Eggshell powder was mixed with clay soil in varying proportions to evaluate changes in index properties, compaction, and shear strength. The aim was to enhance soil strength while promoting environmental sustainability by reusing waste materials, thus reducing disposal issues and environmental hazards. Experimental results were compared to untreated soil to assess effectiveness.

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 Keywords

Stabilization, Soil, Eggshell powder.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Crumb rubber modification has gained significant attention in the field of bituminous materials and asphalt mixtures. This abstract provides an overview of the key aspects related to regular bitumen (RM) and Crumb Rubber Modified Bituminous Mix (CRMB Mix). CRMB is a novel asphalt binder that incorporates recycled rubber particles, offering improved performance characteristics and sustainability. CR Mix, on the other hand, represents the use of CRMB in bitumen mixtures, which enhances their durability, resistance to cracking, and reduced environmental impact. This abstract discusses the composition, production methods, properties, benefits, and challenges associated with CRMB and CR Mix, highlighting their potential to revolutionize the road construction industry by promoting eco-friendly and high-performance pavement solutions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crumb rubber, modified bitumen, Marshall Stability Mix, Bituminous Mix, Specimen

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Formulation and Development of Herbal Skin Whitening Cream. Cream is o/w or w/o emulsion which contain aqueous and oily. Herbal whitening creams are topical products that aim to lighten and even out skin tone, reducing the appearance of dark spots, hyperpigmentation, and melanin content. The benefits of using herbal whitening cream are assist in minimizing pigmentation and fine wrinkles, nourishes skin and encourages immediate luminosity, optimises skin tone and hydration throughout the day, shield the skin from damaging UV radiation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skin lightening, Dark spot reduction, Anti-aging, Anti-inflammatory, Antibacterial, Antioxidant

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The National Education Policy (NEP) 2020 marks a transformative shift in the Indian education system by integrating physical education and sports as essential components of holistic development. This paper explores the provisions of NEP 2020 related to physical education, their implications on school and higher education, and the role of sports in fostering physical, mental, and social well-being. Additionally, it examines the challenges in implementation and suggests measures to ensure the effective integration of physical education into the academic framework.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

National Education Policy 2020, Physical Education, Sports, Holistic Development, School Education, Higher Education, Well-being, Policy Implementation, Educational Reform.

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Creative Commons Attribution 4.0 and The Open Definition