Volume 13 | Issue 1 |

 Abstract

This study explores how organic farming affects soil health and crop nutritional quality in Nanded. Organic farming avoids synthetic chemicals and relies on natural practices like composting and crop rotation. By examining soil samples and crop data from organic farms, the study aims to evaluate changes in soil properties, such as improved nutrient content and increased microbial activity, which are key indicators of soil health. Additionally, the study measures the levels of essential nutrients and antioxidants in crops grown organically to see if they are higher compared to conventionally farmed crops. The goal is to determine whether organic farming provides tangible benefits for both soil quality and crop nutrition, offering useful information for local farmers to consider when choosing farming practices.

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 Keywords

Organic farming, Soil health, Nutritional quality of crops, Nanded, Composting, Crop rotation, Organic fertilizers, , Soil nutrients, Antioxidants, Soil fertility, Sustainable farming practices, Environmental sustainability, Organic inputs

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Pesa Adhiniyam Ka Aadivasi Samudayo Ke Samajik Sashtikaran Per Prabhav

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pesa Adhiniyam Ka Aadivasi Samudayo Ke Samajik Sashtikaran Per Prabhav

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project is centered on how to use Augmented Reality (AR) for demonstrating and visualizing furniture. The core idea is to develop an AR-based system with which users can interact with virtual furniture within a real- world environment. By adding 3D models of furniture to an AR platform, users can manipulate, view, and customize pieces of furniture in their own dwelling spaces, providing experience-rich practicality than can be obtained via the online catalogues or in-store display. Users are enabled to change position, size features and orientation of furniture models and visualize in real time how they will fit and look at home. The undertaking also offers color and material personalization, which completes an entire interior design planning tool. Implementation involves the creation of high- fidelity 3D models of various types of furniture, their optimization for AR applications, and developing a user-friendly interface that supports intuitive interaction. The productiveness of the system is quantified through user testing and focuses on user-friendliness, accuracy of placement, and overall user satisfaction. This AR/VR Furniture Visualization demonstration system certainly tries to provide a connection between online shopping and the analogue experience of using furniture: it can allow consumers to visualize and choose products more flexibly and excitingly, making decisions better.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Virtual Reality, Furniture Modelling, Furniture Visualization, Augmented Reality

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this study, the Upper Ganga Plain's habitation pattern and cultural adaptations are reviewed. Human interactions with technology, the environment, and sociopolitical institutions are reflected in the Upper Ganga Plain's settlement patterns and cultural adaptations. Numerous cultural sequences throughout the history of human civilizations have been uncovered by archaeological investigations in the Upper Ganga plain. Excavations over the past few decades have shown the existence of Painted Grey Ware and Northern Black Painted Ware cultures in the Upper Ganga Valley, as well as prehistoric culture. The interaction of various civilizations, sociocultural customs, and technological developments is reflected in the pottery produced in this area. There is evidence of a robust ceramic culture that is profoundly ingrained in the Upper Ganga Plain's ancient history.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Settlement Pattern, Cultural adaptation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research examines the thematic and psychological dimensions of the poetry of Sylvia Plath, Emily Dickinson, John Clare, and T.S. Eliot, focusing on the potential presence of schizophrenia symptoms in their works. Schizophrenia, a complex mental disorder, manifests through symptoms like delusions, hallucinations, disorganized thinking, and emotional instability. By analyzing selected poems, the study identifies instances of these symptoms, exploring how mental health challenges influence artistic expression. This paper draws upon both psychiatric literature on schizophrenia and literary criticism to explore the possible manifestation of symptoms within the poems of Sylvia Plath, Emily Dickinson, John Clare, and T.S. Eliot. Each poet brings unique psychological struggles to their work. Sylvia Plath's vivid imagery and fragmented structures suggest cognitive disturbances. Emily Dickinson's reclusive life and symbolic language, as seen in I Felt a Funeral in My Brain, reflect hallucinatory experiences. John Clare's disjointed thoughts and profound isolation, shaped by his time in asylums, align with schizophrenia's negative symptoms. T.S. Eliot's modernist works, particularly The Waste Land and The Hollow Men, mirror disorganized thinking and emotional fragmentation. Through close readings, the research highlights how psychological distress informs creativity, using schizophrenia as a lens to deepen literary analysis. While none of these poets were formally diagnosed, their works reveal recurring patterns tied to schizophrenia, emphasizing the profound intersection of mental health and artistic expression.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

schizophrenia, hallucinations, delusion, isolation, perception

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Tilda Vikashkhand Me Bhumi Upyog Ev Krushi Pratiroop

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Creative Commons Attribution 4.0 and The Open Definition

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Tilda Vikashkhand Me Bhumi Upyog Ev Krushi Pratiroop

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social media is a weapon that is capable of construction as well as destruction. The real power of the prevailing social media platforms becomes evident by witnessing the influence created by these platforms on a large scale. It plays a significant role in everyday life. The rising popularity due to its ability to make people attached with kith and kin have paved the way for the world to share photos, feelings, videos, which bears a high-security concern. However, most social media users do not know the underlying security level(s) of the respective account(s), including which features of these social media have to be considered if there is a risky situation. Hence, this would help the police to identify the type of people who would create more crimes. These results would help the police to narrow down their search on criminals for better surveillance. The police must focus on those with these factors while monitoring social media.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

social media, cyber crime ,cyber criminals

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The early detection of sexually transmitted diseases (STDs) and sexually transmitted infections (STIs) is critical for effective treatment and prevention of complications. With advancements in artificial intelligence, machine learning algorithms offer promising tools for accurate and efficient diagnostics. This study presents a comparative analysis of tree-based algorithms, with an initial focus on Random Forest, for the detection of STDs/STIs using publicly available datasets. The model achieved an accuracy of 96%, demonstrating the effectiveness of tree-based methods in medical diagnostics. A detailed evaluation of the model's performance, including a confusion matrix and feature importance analysis, is included. Future work will focus on implementing deep learning algorithms to enhance detection accuracy and generalizability. This paper serves as Phase One of an ongoing study aimed at leveraging machine learning for improved healthcare diagnostics.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tree Learning, Deep learning, Sexually Transmitted Disease (STD) Prediction, Random Forest.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study reviews the changes in the Gulpha Sandhi Sharir, with a specific focus on Amavata. Gulpha Sandhi Sharir refers to the ankle joint in Ayurveda, which is crucial for movement. Amavata is a chronic inflammatory disorder that resembles rheumatoid arthritis and primarily affects the joints, leading to pain, swelling, stiffness, and limited mobility.The review examines key structures in the Gulpha Sandhi, including bones, ligaments, tendons, and synovial membranes, and explains how Amavata impacts these structures. By analyzing classical Ayurvedic texts alongside modern medical literature, this study clarifies the development of Amavata, highlighting the accumulation of Ama (toxins) and its interaction with Vata dosha. The study discusses significant issues such as joint tissue damage, abnormalities in synovial fluid, and inflammation. It aims to link Ayurvedic principles with modern anatomical understanding, providing valuable insights for the management and treatment of this challenging condition.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gulpha Sandhi, Sharir, Amavata, Synovial Fluid

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Potato diseases, such as late blight and early blight, pose significant threats to global agricultural productivity. Manual disease detection is time-intensive and error-prone, necessitating automated solutions. This study proposes a deep learning-based system using Convolutional Neural Networks (CNNs) for identifying potato leaf diseases. The model was trained and tested on an augmented dataset, achieving a classification accuracy of 97%. It effectively distinguishes healthy leaves from diseased ones. The system's robustness is validated through cross-validation and practical testing. Key advantages include high accuracy and scalability for agricultural applications. The approach can be extended for real-time use through IoT devices. This work aims to assist farmers in early disease detection, reducing crop losses and enhancing productivity.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Potato disease identification, deep learning, CNNs, late blight, early blight, image classification, agricultural technology.

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Creative Commons Attribution 4.0 and The Open Definition