Volume 14 | Issue 4 |

 Abstract

The swift expansion of digital media has significantly transformed the contemporary workplace. Its impact extends beyond communication, affecting how employees perceive and feel about their jobs. From perspectives in human resources and sociology digital platforms such as social networking sites professional discussion forums, and online content ecosystems increasingly shape employees view and evaluations of their workplace experiences stop this shift has left a concerning issue that is employees are increasingly forming their ideas about workplace wellbeing from external narratives rather than from the companies practices often based on stories that may be idolised fragmented or misaligned the actual situation within the company. next line in this regard the present study aims to create a conceptual framework that clarifies how exposure to digital media fix employees view on workplace wellbeing. This framework includes 4 key variables - digital media, employee perception, workplace well-being and organizational culture- to Explore their relationships. It emphasis the digital media serves as a primary means through which individuals interpret information, while employee perception refers to the cognitive processes used to comprehend these influences. Additionally organizational culture is regarded as a moderating factor that can either enhance or diminish the impact of external media The study contributes to our existing knowledge by proposing a theoretical model that integrates concepts from human resource management, sociology and media studies this model provides a more detailed understanding of well-being in the workplace in the context of digital era.

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 Keywords

Digital media, Workplace wellbeing, Employee perception, Organizational culture, Human resource management, Workplace dynamics.

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The article seeks to explore emotional silence and repression as key psychological patterns in the novel The Kite Runner by Khaled Hosseini with a focus on the role of suppressed emotions of guilt, fear and desire in guiding individual behavior. The article relies on Sigmund Freud's model of the human psyche consisting of the id, ego and superego to explain emotional silence. According to this model, emotional silence can be seen as the product of the interplay between instinctual drives and the limitations posed by moral and social constraints. The theory of human psychology helps to understand why characters behave emotionally silent and how this behavior creates tension within them. The article implies that emotional silence contributes to a psychological burden and confronting suppressed emotions is vital for personal growth and redemption. The article concludes that the balance between the id, ego, and superego is a crucial factor in resolving inner conflicts emphasizing the significance of emotional expression for psychological healing.

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 Keywords

Emotional silence, Repression, Psychoanalysis, Redemption

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Businesses and professionals often rely on Google Sheets for storing and managing data, but analyzing this data manually is time-consuming and requires significant technical expertise. This project introduces an AI-powered analytics dashboard that seamlessly integrates Google Drive, AI-based analysis, and dynamic visualization to make data insights accessible to users without technical skills. The platform enables Google OAuth2 authentication, spreadsheet browsing, and automatic data import with a chat-based AI query interface for intelligent insights and interactive chart generation. Built using Python, Django/Flask, React, and integrated with the Gemini API, the system automates data understanding, reduces dependency on technical analysts, and democratizes data-driven decision-making for businesses, students, researchers, and professionals across domains.

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 Keywords

Artificial Intelligence, Analytics Dashboard, Google Drive Integration, Natural Language Processing, OAuth2 Authentication, Data Visualization, Gemini API, Predictive Analytics, React, Python

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This research explored how ghosting behavior and Consideration of Future Consequences (CFC) predict the frequency of creating positive and negative romantic relationships among young adults. As digital disengagement strategies such as ghosting become more common, understanding how cognitive orientation and relational behaviors affect romantic relationships is very important. A sample of 100 young adults between the ages of 19 and 29 were surveyed using the Consideration of Future Consequences Scale, the Romantic Ghosting Scale, and the Positive-Negative Relationship Quality Scale. Data was analyzed using Pearson correlation and multiple regression analysis. The results suggested that CFC is not related to positive or negative relationship quality and does not predict relationship outcomes. On the other hand, ghosting behaviours, such as being ghosted, were significantly related to lower levels of positive relationship quality and higher levels of negative relationship quality. Being the victim of ghosting is the most significant and consistent predictor of relationship quality than ghosting others when controlling for ghosting victimisation. The model presented an overall predictive value of approximately 25 to 27% of the variance of relationship quality. The research showed that an individual's interpersonal experiences, particularly those involving rejection via ghosting, have a greater impact on the quality of intimate relationships among young adults than any type of prospective, future-focused, cognitive style. The findings indicate how communication and relational behavior patterns shape the romantic relationships of young adults.

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 Keywords

Consideration of Future Consequences, Ghosting Behavior, Relationship Quality, Young Adults, Romantic Relationships

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Medicinal plants play a vital role in traditional and modern healthcare systems. Accurate identification of these plants is essential for their effective utilization, yet manual identification requires domain expertise. This paper presents an end-to-end deep learning-based system for identifying medicinal plants using leaf images and providing their medicinal uses through an intelligent assistant. The proposed system utilizes a Convolutional Neural Network (CNN) based on MobileNetV2 with transfer learning for efficient image classification. The model is trained on a dataset containing 19 medicinal plant species and achieves high classification accuracy. The system is integrated into a web application developed using Flask, enabling users to upload leaf images and obtain real-time predictions along with confidence scores. Additionally, an AI-powered chatbot is incorporated using LangChain and Groq API to provide context-aware responses about plant uses, preparation methods, and safety information. The system demonstrates the effective combination of computer vision, machine learning, and conversational AI for real-world applications in healthcare and agriculture.

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 Keywords

Deep Learning, Convolutional Neural Network (CNN), MobileNetV2, Medicinal Plants, Image Classification, Transfer Learning, Flask, AI Chatbot

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Colon cancer is one of the most life- threaten- ing and highly spreadable cancers. The old technologies and methods used for identifying colon cancer were done by doctors using scan images or histopathological images, and it needs expertise in the field to identify the cancer, which may take hours or days. Some may even result in errors, leading to delayed diagnosis, and some may even miss early- stage detection. To reduce these problems, we have created a website that can find the cancer and its percentage in an instant, and to obtain this, we use a CNN (Convolutional Neural Network), which helps in extracting the spatial and needed features from scan images or histopathological images. The image pro- cessing technique includes resizing t he image, noise removal, normalisation, and data augmentation. Then the model will be trained to detect whether the image is cancer- ous or non-cancerous, and the percentage of cancer.

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 Keywords

Colon Cancer Detection, Colorectal Cancer, Deep Learning, Convolutional Neural Networks (CNN), Medical Image Processing, Histopathology Images, Colonoscopy Images, Image Classification, Computer-Aided Diagnosis, Early Cancer Detection, Artificial Intelligence in Healthcare.

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Agricultural modernization encompasses the adoption of improved technologies, mechanized farm equipment, micro-irrigation systems, high-yielding variety (HYV) seeds, and institutional credit mechanisms to enhance farm productivity and farmer income. Kolhapur district of Maharashtra, characterised by fertile black and laterite soils, abundant river networks, and a dominant sugarcane-agro-industrial complex, presents a compelling case for studying the economic impact of modernization at the district level. The district has witnessed a measurable growth in area under cultivation from 250,000 ha in 2018 to 288,000 ha in 2022, while food grain production rose from 1.2 million to 1.58 million tonnes during the same period. Irrigation coverage expanded from 60% to 80%, and aggregate farmer income grew from INR3,500 crore to INR5,500 crore. Sugarcane, the dominant cash crop, demonstrated a yield surge from 27 MT per acre under traditional flood irrigation to 55-60 MT per acre under automated drip irrigation, as documented from the Karbharwadi model village in Karveer taluka. Drawing entirely on secondary data from official Government of Maharashtra records, the NABARD Potential Linked Credit Plan for Kolhapur (2023-24), the Ministry of Agriculture and Farmers Welfare Annual Report (2024-25), and peer-reviewed journal articles, this paper evaluates five dimensions of agricultural modernization: irrigation expansion, mechanization, credit access, crop diversification, and government scheme penetration. The findings affirm a strong positive relationship between technology adoption and farmer income, while identifying persistent structural constraints, including land fragmentation, smallholder credit gaps, and post-harvest infrastructure deficits.

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Agricultural Modernization, Kolhapur District, Farmer Income, Sugarcane, Drip Irrigation, NABARD, Maharashtra, Micro-irrigation, High-Yielding Varieties.

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Jaundice is a caused by increased level of bile pigments, typically bilirubin and its conjugates, characterized by yellow discoloration of eyes and skin. In this article, metabolism of bilirubin, types, causes and patho-physiology of jaundice, clinical symptoms, investigations and management of jaundice with totality of symptoms in homoeopathy giving it a holistic approach has been reviewed.

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Jaundice, Holistic, Homoeopathy, Individualization, Totality of symptoms

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Obesity is a modern lifestyle disease caused due to excessive accumulation of fat in the body occurs when BMI is >= 25 in a person according to his/her age, sex, height, weight, or often considered as an important risk factor for the development of diabetes, non-alcoholic fatty liver disease, hypertension. Obesity is a major health concern because of its increasing prevalence. This article describes causes clinical classification, types complications, management of obesity along with review of homoeopathic medicines indicated for obesity,

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Obesity, Fat metabolism, Homoeopathic Medicines, Non - Alcoholic Fatty Liver Disease.

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ABSTRACT Background: Chronic bronchitis is a major component of Chronic Obstructive Pulmonary Disease (COPD) and is strongly associated with long-term smoking. Smoking cessation is the most effective intervention to slow disease progression. However, knowledge and attitude toward smoking cessation among patients remain inadequate in many settings. Objectives: 1. To assess the knowledge regarding smoking cessation among chronic bronchitis patients. 2. To assess the attitude toward smoking cessation among chronic bronchitis patients. 3. To determine the association between knowledge and attitude scores with selected demographic variables. Methods: A descriptive cross-sectional study was conducted among 100 chronic bronchitis patients in selected hospitals of Indore, Madhya Pradesh. A structured knowledge questionnaire and Likert attitude scale were used. Data were analyzed using descriptive and inferential statistics. Results: The findings revealed that 58% of patients had moderate knowledge, 28% had inadequate knowledge, and 14% had adequate knowledge. Regarding attitude, 62% showed a favorable attitude, 25% moderately favorable, and 13% unfavorable attitude. A significant association was found between knowledge and education level (p < 0.05). Conclusion: The study concludes that although patients have a moderately favorable attitude toward smoking cessation, knowledge levels remain insufficient. Structured educational interventions are recommended.

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 Keywords

Keywords: Chronic bronchitis, Smoking cessation, Knowledge, Attitude, COPD

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Creative Commons Attribution 4.0 and The Open Definition