Volume 13 | Issue 6 |

 Abstract

Alzheimer's Disease (AD) is one of the top causes of death in the world. Prompt prediction of Alzheimer's using traditional methods is not very efficient due to their dependency on subjective assessments, slow progression of the disease, and the invasive or costly nature of biomarker tests. It highlights the need to implement AI models as they can identify patterns in large and complex datasets, thereby enabling earlier, non-invasive diagnosis. The models utilized in AD diagnosis include Convolutional Neural Networks (CNN), an Autoencoder-based Support Vector Machine (SVM) and Logistic Regression. These models have the potential to extract and learn features from MRI scans, resulting in better prediction for AD patients.

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Alzheimer Disease Prediction, AD diagnosis, dementia, MRI scans, Convolutional Neural Networks, Autoencoder

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In the hyperconnected era, digital platforms have transformed interpersonal and professional communications into lightning-quick exchanges across time zones and cultural borders. However, the growing dependence on instant messaging, email, and virtual collaborative tools has provided an opportunity for a less investigated but far-reaching consequence: digital silence--the breakdown or lack of timely responses in virtual interactions. This paper examines the psychological, emotional, and relational implications of digital silence, with a focus on how it leads to communication apprehension, dissipation of trust, and the reconfiguration of human interactions in both personal and workplace spaces. Based on Uncertainty Reduction Theory, Expectancy Violation Theory, and Media Richness Theory, the current analysis utilizes a mixed-methods framework combining questionnaires and qualitative interviews with professionals and students from diverse cultural backgrounds. Results show that extended response times tend to precipitate adverse cognitive evaluations such as fear of rejection, misperception of rejection, and sense of disrespect--even in cross-cultural and hierarchical relationships. Cultural norms of conduct, digital etiquette assumptions, and message context play a significant role in the mediation of the perceived influence of silence. This paper concludes with the suggestion of practical methods and digital communication standards and protocols for mitigating misinterpretation, improving clarity, as well as incorporating healthier loops of communication in digitally mediated interactions. These findings have rich implications for the management of teleworking teams, intercultural communication training, as well as digital well-being.

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Digital Silence, Communication Anxiety, Uncertainty Reduction Theory, Expectancy Violation Theory, Media Richness Theory

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Bone fracture is a partial or complete break in the continuity of bone tissue, commonly resulting from trauma, falls, sports injuries, or underlying medical conditions such as osteoporosis. Accurate and timely identification of fractures is essential for proper treatment and recovery. Traditional diagnostic approaches rely heavily on manual examination of X-ray images by medical professionals, which can be time-consuming and susceptible to human error. To address these limitations, a deep learning-based system has been developed for automatic detection and classification of bone fractures using a transfer learning approach with the VGG19 convolutional neural network architecture. The model is trained on a labeled dataset containing various fracture types along with normal images, employing preprocessing techniques such as resizing, normalization, and augmentation. A Flask-based web interface enables real-time predictions from uploaded X-ray images. Experimental results demonstrate high accuracy and reliability, indicating strong potential for clinical and diagnostic applications.

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Bone Fracture Detection, X-ray Classification, Deep Learning, VGG19, Transfer Learning, Convolutional Neural Network, Medical Image Analysis, Fracture Classification.

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Uchtar Madhyamik Vidhyalay Me Adhaynrat Vidhyarthiyo Ki Uplabdhi Per Abhibhavak Bhagidari Ke Prabhav Ka Adhayan ( Raipur Shahar Ke Sandharbh me )

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Uchtar Madhyamik Vidhyalay Me Adhaynrat Vidhyarthiyo Ki Uplabdhi Per Abhibhavak Bhagidari Ke Prabhav Ka Adhayan ( Raipur Shahar Ke Sandharbh me )

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Behavioral research relies heavily on statistical methods to uncover the patterns, relationships, and effects underlying human cognition, emotion, and behavior. Among these, Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA) are particularly powerful tools used in experimental psychology to compare group means and multivariate group profiles, respectively. This paper presents a detailed exploration of ANOVA and MANOVA, including their statistical models, underlying assumptions, application contexts, and interpretation strategies, supported by synthetic data simulations and case-based illustrations. For instance, in a one-way ANOVA example involving three groups subjected to different cognitive stimuli (e.g., neutral, positive, negative), simulated data of mean reaction times were analyzed: Group A (M=450ms), Group B (M=410ms), Group C (M=520ms), with a total sample size of n=90. The F-statistic calculated was F(2,87) = 7.32, p<0.01, indicating a significant effect of stimulus type on reaction time. In a MANOVA scenario involving three therapy groups and two dependent outcomes (depression and anxiety scores), Wilks' Lambda = 0.768, F (4,174) = 4.23, p < 0.01, suggested significant multivariate differences across groups. Post hoc univariate ANOVAs confirmed the group effect on both depression and anxiety separately. This paper is designed to serve multiple purposes: (1) it provides experimental psychologists with a clear and practical roadmap for applying these methods to research design and analysis; (2) it clarifies when to prefer ANOVA over MANOVA based on the number and intercorrelation of dependent variables; (3) it reinforces the importance of testing assumptions (e.g., normality, homogeneity, independence) to ensure validity of inference; and (4) it provides R code templates and flow diagrams to visualize decision paths in choosing and applying these methods. The strength of the paper lies in its application-oriented approach, rather than only focusing on mathematical formulations, it situates these methods in realistic psychological experiments, including therapy outcome evaluations, cognitive interference studies, and stress-resilience experiments. Researchers, educators, and graduate students can directly apply the examples and templates to design their studies or teach the statistical foundations of psychological research. Ultimately, this paper aims to enhance methodological rigor in behavioral sciences by demystifying the statistical logic behind ANOVA and MANOVA and promoting more informed, accurate, and replicable research practices in experimental psychology.

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India's Journey from the colonial law of the Land Acquisition Act (LAA) enacted in 1894, to the enactment of Land Acquisition, Rehabilitation and Resettlement (LARR) Act of 2013, has been an experience of understanding the development, displacement and redressal discourses of the multiple stakeholders including the Tribal communities. The process of Land acquisition in India was based on the LAA of 1894, which interpreted and aimed to utilize the forests and land resources for 'public good' and did not recognize the customary rights of tillers. It prescribed mere cash compensation to those who owned land titles through the legitimacy of the State. The Socio-anthropological discourse on the resources including land, cattle, mountains, hills and water bodies intertwined with the communities of the respective regions, was not provided any attention until the Sardar Sarovar Project (SSP) (initiated in 1961) built on Narmada River, in the state of Gujarat, which led to one of the first socio- environmental movements namely the Save Narmada Movement. The Development model incorporated in the economic policies in the first few decades of the post-independence period, focused largely on 'land' as a phenomenal economic utility tied to the dynamic market needs, and the relationships of the human communities with natural resources was not perceived as a natural customary right of people, by the political class, bureaucracy and the judiciary. Further, under the benign impact of globalization and liberalization from 1991, stress increased at the fault lines of the tribal belt, where large scale industrial projects and investments have been projected as economic and institutional necessities. The legal tangles with all possible complexities was experienced with the LAA of 1894, as it stipulated only individual landowners entitled for compensation in case of displacement, and all other customary owners of the land are classified as 'encroachers'. Also, it took an utilitarian approach with all the public resources such as bio-diversity parks, other natural resources, and land without titles, and ignored the anthropological and sociological realities of common land, water bodies, common land, grazing lands, mountains and hills, agrarian lands, stone quarries etc. as integrated part of socio-economic and religious lifeline of several communities including the Tribes of India. Some of the prominent socio-environmental movements namely the Save Narmada Movement against Sardar Sarovar Project (SSP) in Gujarat, the anti-Coco-Cola struggle in Kerala, contributed to the establishment of discourses in understanding the multidimensional, inherent and integrated relationships between land and communities, against the linear version of development necessitating displacements. The legal battles of various stakeholders associated with these socio-environmental movements, provided the impetus to change the LAA of 1894 and enact the LARR in 2013. The present paper focuses on the various aspects of historical and socio-legal journey from LAA of 1894 to the establishment LARR Act 2013 in the backdrop of Save Narmada Movement of Gujarat and anti-Coco-Cola struggle of Kerala that collectively helped the Indian academics, political class and importantly the judiciary in redefining the community-land relationships and resources. With the enactment of LARR Act of 2013, the possibilities of a dialogues between the stakeholders, land owners and the land acquirers has begun, as the LARR Act of 2013, has clearly provided the space at least in procedures Resettlement and Rehabilitation (R&R), Fair Compensation, Transparency, Consent, Social Impact Assessment and dispute resolution, which was not available earlier. But the LARR Act of 2013 also has witnessed several deficits in terms of operational reality such as Land use changes, delays in compensation, inadequate compensation etc., which provides the opportunity for the stake holders, academicians, legal fraternity and the political class to revisit and improvise the provisions of LARR Act of 2013 further, and also solve the operational challenges.

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Key words: Development, Displacements, Land Acquisition Act, Land Acquisition Process, Social Movements

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Abstract Cassia fistula L., commonly known as the golden shower tree, is a well-documented medicinal plant in traditional Ayurvedic medicine. This study aimed to extract and characterize the phytochemical constituents of Cassia fistula seed oil and evaluate its biological activities, including antioxidant and antimicrobial properties. The seed oil was extracted using Soxhlet extraction with n-hexane and analyzed through preliminary phytochemical screening, GC-MS (Gas Chromatography-Mass Spectrometry), and FTIR (Fourier Transform Infrared Spectroscopy). The GC-MS analysis revealed the presence of bioactive fatty acids such as oleic acid, linoleic acid, and palmitic acid, among other phytoconstituents with potential pharmacological properties. FTIR spectra confirmed the presence of functional groups like hydroxyl, carbonyl, and aliphatic chains. Biological evaluation of the oil demonstrated significant antioxidant activity in DPPH, ABTS, and FRAP assays, with IC50 values comparable to standard ascorbic acid. The antimicrobial activity was tested against both Gram-positive and Gram-negative bacteria, with moderate to strong zones of inhibition observed against Staphylococcus aureus and Escherichia coli. The findings suggest that Cassia fistula seed oil is a promising natural source of bioactive compounds with potential applications in pharmaceutical, nutraceutical, and cosmetic formulations.

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Keywords o Cassia fistula o Seed oil o Phytochemical characterization o GC-MS analysis o FTIR spectroscopy o Antioxidant activity o Antimicrobial activity o Medicinal plants o Bioactive compounds o Natural products

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OBJECTIVES OF THE STUDY 1. To assess the level of awareness regarding Poshan Abhiyan among women in reproductive age group of selected rural areas of Udaipur. 2. To find out association between awareness regarding Poshan Abhiyan among women in reproductive age group of selected rural areas of Udaipur with their selected socio demographic variables. 3. To develop a leaflet regarding Poshan Abhiyan among women in reproductive age group of selected rural areas of Udaipur HYPOTHESIS H1: There will be a significant association between awareness regarding Poshan Abhiyan among women in reproductive age group and their selected demographic variables at 0.05 level of significance. H01: There will be no significant association between awareness regarding Poshan Abhiyan among women in reproductive age group and their selected demographic variables at 0.05 level of significance. METHODOLOGY The study aimed to assess the awareness of Poshan Abhiyan among women in the reproductive age group in rural areas of Udaipur, Rajasthan. A descriptive non-experimental research design was used, and data were collected using a structured interview schedule with two sections: socio-demographic variables and awareness of Poshan Abhiyan. A pilot study was conducted in Mavli block with 30 women, and the reliability of the tool was established with a coefficient of 0.86. The main study involved 100 women from Girwa and Gogunda blocks. Data analysis included both descriptive and inferential statistics, with chi-square tests used to examine associations between awareness and socio-demographic variables. Results: The results revealed that 58% of the women had low awareness, 42% had moderate awareness, and only 1% had good awareness regarding Poshan Abhiyan. Socio-demographic factors such as education, occupation, family income, and hearing about Poshan Abhiyan were significantly associated with awareness levels. However, variables like age, family type, marital status, number of children, and diet had no significant influence. Conclusion: The present study was undertaken "a study to assess the awareness regarding Poshan Abhiyan among women in reproductive age group of selected rural areas of Udaipur, Rajasthan with a view to develop a leaflet" The present study concluded that a majority of women had low awareness about Poshan Abhiyan, and certain socio-demographic factors influenced their level of awareness. It recommended focusing on educational interventions and community health programs to improve awareness, particularly in rural areas. Additionally, the study emphasized the importance of integrating Poshan Abhiyan into nursing education and practice, advocating for proactive nurse-led awareness campaigns, and involving community health workers to enhance outreach and effectiveness.

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Women in reproductive age group, Poshan Abhiyan, Leaflet.

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This study examines the impact of fiscal policy on inflation and economic growth in India from 2000 to 2024, using quantitative data from published sources like the Reserve Bank of India (RBI) and Ministry of Finance. Fiscal policy, encompassing government spending and taxation, plays a critical role in shaping macroeconomic outcomes. The research analyzes how fiscal deficits, public expenditure, and tax revenues influence inflation rates and GDP growth. Employing econometric models, including "Vector Autoregression (VAR)" and Granger causality tests, the study finds that expansionary fiscal policies, while boosting short-term growth, often exacerbate inflationary pressures. Conversely, fiscal consolidation tends to stabilize inflation but may dampen growth temporarily. The analysis reveals a bidirectional causality between fiscal deficits and inflation, with weaker evidence for growth. Data from RBI's annual reports and World Bank indicators highlight India's fiscal challenges, including high debt-to-GDP ratios. The study underscores the need for balanced fiscal strategies to achieve sustainable growth without triggering inflation. Policy implications include prioritizing productive expenditure and improving tax compliance. This research contributes to understanding fiscal policy dynamics in a developing economy, offering insights for policymakers aiming to navigate India's complex macroeconomic landscape.

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Keywords: Fiscal Policy, Inflation, Economic Growth, India, Fiscal Deficit, Public Expenditure, Taxation.

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A thorough understanding of various terminologies mentioned in Ayurveda is essential for their effective application in clinical practice and research. Kalaa sharir is a significant aspect of sharir necessitating a detailed study and exploration of the concept to uncover its significance. 'Kalaa' refers to the distinct layers, sheath or membranes that envelop and protect various internal structures of the body. These are not only structurally significant but also hold considerable functional importance. The seven types of kalaa i.e. Mamsadhara, Raktadhara, Medodhara, Shleshmadhara, Purishadhara, Pittadhara Shukradhara Kalaa described in Ayurvedic texts represent specific anatomical and physiological structure and functions. There appears to be a possible correlation between the classical descriptions of kalaa in Ayurveda and modern anatomical structures. Also Kalaa is closely associated with Dhatu, its origin, and Dosha interactions, forming a strong foundational basis for understanding the applied aspects of Kalaa in clinical practice. So, this article aims to present a comprehensive review of the concept of Kalaa Sharir, its relation with various components of body and hence to simplify its clinical applicability.

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Keywords: Kalaa, dhatu, layers, membrane, sheath

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