Volume 13 | Issue 8 |

 Abstract

Abstract The Pur??as, often regarded as religious and mythological texts, also serve as vital sources for reconstructing the history and culture of ancient India. While primarily intended to convey religious teachings, cosmological ideas, and ethical principles, they preserve accounts of dynasties, rulers, and political traditions that illuminate the evolution of early state systems and collective memory. Genealogical lists and descriptions of succession, particularly in the Vi??u, Matsya, Bh?gavata, and V?yu Pur??as, provide historical insights despite inconsistencies and legendary embellishments. Beyond politics, these texts reveal the socio-cultural life of early India. They describe rituals, festivals, var?a and ??rama frameworks, and customary practices that governed society. Environmental attitudes appear in myths about rivers, mountains, and forests, reflecting deep links between nature and human life. Economic references--agriculture, irrigation, trade, and resource use--highlight the material basis of society. Methodological challenges remain, as myth and history often intertwine, and later interpolations complicate chronology. Yet, when critically examined alongside archaeology, epigraphy, and other traditions such as the R?m?ya?a, Mah?bh?rata, Buddhist J?takas, and Jain texts, the Pur??as emerge as hybrid records--part myth, part history. They function as cultural archives, preserving political memory, ethical ideals, and everyday realities, thereby enriching early Indian historiography.

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 Keywords

Pur??as, Ancient India, Historical Sources, Society, Culture, Historiography

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Bone fracture and bone tumor diagnosis are among the most important issues in orthopedic and oncological practice, especially in areas with low expertise in radiological diagnosis. This paper presents a deep learning based framework for the automated detection of fractures and tumors in radiographic and MRI images using the YOLOv11n object detection model. The system was trained on a combination of two curated sets of 1,500 tumor specimens including osteosarcoma and benign lesions and 3,000 fracture samples including transverse fractures, oblique fractures, and comminuted fractures. Grazing conversion, normalising, and worsening strategies were applied to improve dataset variety and robohardness. The model showed good performance with an accuracy of 92.8%, precision of 92.4%, recall of 90.1%, and mean average precision (mAP) at detection threshold of 0.5 for tumor detection (90.8% mAP), and 94.3% accuracy, 93.2% precision and 94.9% recall for fracture detection. To enable real-world applicability, the framework was deployed through a Streamlit-based web application offering role-specific access for patients and doctors, real-time image uploads, annotated visualizations, heatmap-based interpretability, and multi-format report exports (CSV, PDF, JSON). By offering strong detection accuracy while keeping the interface approach easy to use, the proposed system offers reliable assistance to minimize delay in diagnosis, error rates and enhance patient outcome in both orthopaedic and oncological treatment.

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 Keywords

Tumor Detection, Fracture Detection, YOLOv11n, Deep Learning, Medical Imaging, X-ray, MRI, Streamlit, PyTorch, Computer Vision, Object Detection, Healthcare AI, SQLite, Diagnostic Reports.

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Metal oxide nanoparticles (MONPs) are a class of nanomaterials known for their unique physical, chemical, and biological properties. Due to their high surface-to-volume ratio, stability, and functional versatility, MONPs have found wide spread applications in medicines, environmental remediation, food packaging, cosmetics, and catalysis. Commonly studied metal oxide include zinc oxide (ZnO), titanium dioxide (TiO2), iron oxide (Fe3O4), and copper oxide (CuO), each offering distinct functionalities. These nanoparticles can be synthesized through various methods such as sol-gel, co-precipitation, hydrothermal, and green synthesis, which influence their size, morphology, and reactivity. Characterization techniques like XRD, SEM, TEM, and FTIR are essential to understand their structural and functional properties. The promising biomedical and industrial applications of MONPs are balanced with ongoing research into their toxicity, environmental impact, and safe use. This review aims to provide an overview of the synthesis, characterization, and emerging applications of metal oxide nanoparticles, highlighting their role in advancing nanotechnology-based solutions.

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Metal oxide nanoparticles, Metal oxide synthesis, Characterization, Inorganic nanoparticle, Biomedical applications.

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Soil is a critical factor for a successful agriculture. The Growth of Crops is affected by the chemical features of soil. Choosing the right type of crops for that particular type of soil is also important. Machine Learning techniques can be used to classify the soil series data. The results of such classification can further be combined with crop dataset to predict the crops that are suitable for the soil series of a particular region and its climatic conditions. Predicting a crop well in advance requires a systematic study of huge data coming from various variables like soil quality pH, N, P, K etc. As Prediction of crop deals with large set of database thus making this prediction system a perfect candidate for application of data science. The success of any crop prediction system heavily relies on how accurately the features have been extracted and how appropriately classifiers have been employed.

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Index Terms - Soil classification, Crop prediction, Machine learning, Data science, Soil quality analysis, Feature extraction, Soil-crop suitability, Precision agriculture, Crop recommendation system

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Charles Dickens's Hard Times (1854) stands as a seminal work of Victorian literature, offering a stark, realistic portrayal of industrial society, utilitarianism, and class struggles in mid-19th-century England. This research paper examines how Dickens employs realism to critique the dehumanizing effects of industrialization, the rigid, fact-based education system, and the exploitation of the working class in the fictional town of Coketown. Through characters like Thomas Gradgrind, Josiah Bounderby, Stephen Blackpool, and Louisa Gradgrind, Dickens illustrates the conflict between fact and fancy, heart and head, highlighting the emotional and social toll of a mechanized world. Key quotations, such as Gradgrind's insistence on "Facts alone are wanted in life" (Dickens 1), underscore the novel's critique of utilitarianism. Drawing on close textual analysis and scholarly perspectives, the paper argues that Dickens's realism not only reflects historical realities but also advocates for human compassion and imagination as antidotes to societal ills. Findings reveal the novel's enduring relevance in discussions of capitalism and education, with suggestions for future research including comparative studies with other industrial novels.

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Realism, Hard Times, Charles Dickens, Industrial Society, Utilitarianism, Class Struggle, Victorian Literature, Coketown

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After covid 19 everyone starts using social media as it is very friendly and includes less cost. Recruitment is the process of acquiring the best talent for the organization. So social media helps organization to attract many applications and select the best one for the Job. This paper explains the influence of social media on recruitment practices and how organizations will select personnel. The study is based on secondary data, and the objective of the study is to know about recruitment practices through social media. social media is more used after pandemic. Because it includes very little time to apply and to give full information of personal through social media application. As everyone gives full information on their feeds, it includes pictures and background of their study. Which helps organizations to easily watch the details and send quick notifications for applying for jobs. Using facebbok,twitter, linkedin, indeed helps us to search for a good job according to our qualifications and standards. Keywords: -Social media, pandemic, organisation, linkedin

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Social media, pandemic, organisation, linkedin

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Mutual fund industry is rapidly growing from all ways. Whether it is in terms of investment, number of investors, AUM or any other terms. It is making its way across all the investors' minds. As per the official website of AMFI the average asset under management of mutual fund industry in the July month has marked at 77 lakh crores. Which is almost 6 times in comparison to AUM of July 2015. It has grown 6 folds in just 10 years. This shows their incredible growth in terms of quality as well quantity. Because mutual fund industry provides numerous schemes to investors as per their financial goals and risk appetite. This study mainly focuses on one of the popular investment funds namely mid-cap funds. Investors with higher potential growth and risk capabilities choose mid-cap fund as their go to investment. So, this study has considered 5 popular mid-cap direct growth schemes to analyse their performance of past 5 years using performance metrics like Sharpe ratio, Treynor ratio, Jensen's alpha. The data for analysis purpose is collected from the official website of AMFI and Nifty index. The study concludes that all the funds have outperformed the benchmark fund. Amongst all the fund it can be concluded that Motilal Oswal midcap fund is best to invest to get higher return along with taking a little risk.

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Mid-cap fund, Performance ratios, Risk-return, Compound Annual Growth Rate (CAGR), Nifty Index

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D.malerkotliana, like other Drosophila species, is a powerful model organism widely used to investigate conserved molecular pathways relevant to human conditions such as cancer, neurodegeneration, and cardiovascular disease thanks to high genetic conservation and versatile genetic tool. This study evaluates the effects of 50 Hz LF-EMF exposure on a spectrum of behavioural traits in D. malerkotliana, including larval crawling, adult locomotion, climbing, courtship behaviour, and aggression. Flies were subjected to LF-EMF exposure administered via a Holzmolt coil for both short- and long-term time frames. Behavioural metrics were recorded using established methods, including larval crawling grid tracking, the Rapid Iterative Negative Geotaxis (RING) climbing assay, and time-based interaction assays for courtship and aggression. LF-EMF exposure induced significant, exposure duration dependent reductions in larval crawling and adult climbing ability, with male flies exhibiting heightened sensitivity. Courtship behaviours declined progressively with prolonged exposure, suggesting reproductive disruption, while aggression displayed an initial surge (particularly in males) followed by a decline, possibly due to neuromodulator depletion. Collectively, these findings suggest that LF-EMF exposure impairs neural and behavioural function in D. malerkotliana, potentially through mechanisms involving oxidative stress, neurotransmitter dysregulation, and sex-specific resilience differences. These results underscore the value of D. malerkotliana as a model for assessing EMF-induced neurobehavioral toxicity and environmental stress responses.

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D. malerkotliana, LF-EMF, larval crawling, RING assay, courtship behaviours, aggression, Neurobehavioral toxicity.

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Due to changing market trends, consumer tastes, and technology breakthroughs, the automotive industry is one of the most competitive and dynamic sectors of the global economy. Kia Motors Corporation is a well-known and creative automaker that distinguishes out among the major participants in this changing market. Customers preferences and satisfaction with Kia Motors in Coimbatore City are examined in this study. Both primary and secondary data will be used, a randomsampling method is used for collecting questionnaires from 150 respondents. Majority of the respondents are purchasing KIA SELTOS and they are highly satisfied with the performance of the car.

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Kia Motors, Customer satisfaction, KIA SELTOS

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This study evaluates the effectiveness of a structured teaching programme on selected health problems namely head lice infestation, scabies, typhoid fever, worm infestation, hepatitis A, and iron deficiency anemia among orphan children in Nagpur Maharashtra.. Using a pre-experimental one-group pre-test and post-test design, the knowledge and practices of 100 orphan children aged 12-15 years were assessed before and after the intervention. Data were collected through self-administered questionnaires and dichotomous practice questionnaires. The findings revealed that the majority of children had inadequate knowledge and practices before the intervention, but showed significant improvement after exposure to the structured teaching programme. Statistical analysis using paired 't' test confirmed a highly significant difference (p < 0.05) between pre-test and post-test scores. The study concludes that structured teaching programmes can effectively improve knowledge and practices among orphan children, thereby contributing to better health outcomes and well-being.

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Structured Teaching Programme, Health Problems, Knowledge and Practice, Orphan Children, Health Education, Nagpur, Maharashtra.

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