Volume 13 | Issue 1 |

 Abstract

Alzheimer's Disease (AD) is a neurodegenerative disorder that impairs memory, cognition, and daily functioning, with early diagnosis being essential for managing its progression. This research explores a deep learning-based approach to detect Alzheimer's stages from MRI scans, using several neural network architectures: Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), and a transfer learning model based on InceptionV3. To address the challenge of class imbalance inherent in medical datasets, this study employs Synthetic Minority Oversampling Technique (SMOTE) and extensive data augmentation. The models classify MRI images into four categories: Non-Demented, Very Mild Demented, Mild Demented, and Moderate Demented. Experimental results demonstrate that the InceptionV3 model achieves the best performance, with significant improvements in classification metrics due to data augmentation and synthetic data generation. This study highlights the potential of deep learning frameworks in early Alzheimer's detection, providing insights into the application of advanced machine learning techniques in medical imaging.

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 Keywords

Alzheimer's Disease, neurodegenerative disorder, MRI scans, deep learning, Artificial Neural Networks, Convolutional Neural Networks, transfer learning, InceptionV3 model, class imbalance, Synthetic Minority Oversampling Technique, SMOTE, data augmentation, Alzheimer's stages classification, medical imaging, early diagnosis, feature extraction, validation accuracy, loss metrics, cognitive decline, model interpretability, data preprocessing techniques, CNN architecture, ANN, AUC (Area U

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In ancient Indian knowledge systems, women held a significant place as contributors, practitioners, and preservers of knowledge across disciplines such as philosophy, science, medicine, literature, and the arts. Their wisdom was revered, and many women earned recognition as scholars, sages, and artists. In ancient Indian civilization, women were not only active participants in the social and cultural domains but also made significant contributions to the various intellectual and spiritual fields. From philosophy and science to literature and the arts, the role of women in shaping Indian knowledge systems is profound and often underappreciated. While the historical narrative has been dominated by male scholars and practitioners, numerous women in Indian history have been recognized as philosophers, scholars, scientists, and artists in their own right. Their works and influence continue to inspire contemporary thought in multiple disciplines, illustrating the richness and diversity of India's intellectual heritage. Philosophy and Spirituality Women have always been central to the philosophical and spiritual traditions in India. In the Vedic and post-Vedic periods, women were acknowledged for their philosophical and spiritual insights. The Upanishads, which are among the oldest philosophical texts, feature several women philosophers. Gargi Vachaknavi, one of the prominent sages, was known for her intellectual prowess in philosophical debates with great male scholars like Yajnavalkya. Similarly, Maitreyi, another wise woman from the Upanishadic tradition, is credited with profound philosophical ideas about the nature of the self and reality. These women were not only revered for their intellect but also played a pivotal role in shaping the spiritual discourse of the time.

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WOMEN IN INDIAN KNOWLEDGE SYSTEMS: CONTRIBUTIONS AND REPRESENTATION

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This study explores feminist perspectives in the works of Asif Currimbhoy, an eminent Indian playwright whose plays delve deeply into socio-political issues and human relationships. By examining select plays such as The Refugee, The Doldrummers, and Monsoon, the paper highlights how Currimbhoy portrays the struggles, resilience, and agency of women in patriarchal settings. It investigates the nuanced ways in which his female characters challenge societal norms, embodying themes of empowerment, resistance, and self-assertion. The study further examines the relevance of these feminist themes in contemporary times, particularly in the context of ongoing debates around gender equality, intersectionality, and women's rights in India and beyond. By linking Currimbhoy's feminist undertones to modern feminist movements, the paper aims to underscore the enduring significance of his plays as a source of critical insight and social commentary. This research contributes to the broader discourse on feminist literary criticism, situating Currimbhoy's works as both a reflection of and a response to evolving gender dynamics.

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 Keywords

Gender equality, Patriarchal structures, Post-colonial theory, Intersectionality, Subaltern voices, Women's agency, Socio-political struggles, Economic independence

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The increasing prevalence of invasive fungal infections in nosocomial settings is attributed to a rise in immunocompromised individuals, including patients with HIV, cancer, and those undergoing transplant procedures. This review categorizes various oral fungal and protozoal infections, outlining their clinical features and management strategies. Oral candidiasis, including hyperplastic, erythematous, and pseudomembranous types, often presents as white, scrapable plaques, particularly in immunocompromised individuals. Aspergillosis, primarily caused by Aspergillus species, arises from spore inhalation, leading to serious respiratory tract infections and potentially necessitating surgical intervention alongside antifungal therapy. Cryptococcosis, stemming from Cryptococcus gattii and C. neoformans, can lead to severe CNS symptoms and requires ongoing monitoring post-treatment. Histoplasmosis, driven by Histoplasma capsulatum, and blastomycosis, caused by Blastomyces dermatitidis, commonly manifest in respiratory symptoms and involve intricate treatment regimens. Mucormycosis, often linked to COVID-19 complications, is an aggressive infection requiring swift identification and surgical intervention. Geotrichosis presents with oral mucosal lesions and necessitates antifungal treatment for severe cases. Rhinosporidiosis, a chronic granulomatous disease, primarily affects the nose, and effective management usually involves surgical excision. Other infections like toxoplasmosis and leishmaniasis exhibit diverse symptoms, necessitating tailored therapeutic approaches. Fungal infections show rising trends in healthcare settings, emphasizing the importance of recognition and management to improve patient outcomes in increasingly susceptible populations.

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 Keywords

Fungal disease, protozoal disease, oral cavity.

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Modern African poetry focuses on issues the Poets have faced in Africa and highlights how indigenous cultures have nourished literature with substance for future scope. Emerging poets such Morgan Parker is changing the landscape of poetry with their unique forms of writing and storytelling. Morgan Parker, an American poet and novelist is the author of Magical Negro. Morgan considered Poetry as one of the most universal weapons of human expression since it epitomises diverse human experiences in a comprehensive and well-documented manner.

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Modern, African Poetry, Black Ethos, Condemnation, Black Culture

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The evolution of 5G technology demands antennas with superior performance to meet the requirements of high data rates, low latency, and enhanced energy efficiency. This paper presents a detailed study on the enhancement of a 5G MIMO antenna using metamaterials. Three antenna designs were analyzed: a quarter-wavelength (?/4) antenna, a half-wavelength (?/2) antenna, and a half-wavelength antenna integrated with metamaterials. The performance metrics, including resonance frequency (Fr), return loss (S11), transmission coefficient (S12), and gain, were systematically compared. The ?/4 antenna achieved an S11 of -24.07 dB, an S12 of -33.29 dB, and a gain of 5 dB at 2.44 GHz. The ?/2 antenna showed an S11 of -24.57 dB, an S12 of -25.04 dB, and a gain of 3.59 dB at 2.43 GHz. Notably, the ?/2 antenna with metamaterial integration demonstrated a significant improvement in performance, with an S11 of -18.16 dB, an S12 of -33.40 dB, and a gain of 6.43 dB at 2.4 GHz. These results highlight the potential of metamaterials to enhance antenna performance in terms of gain and isolation, making them a promising solution for next-generation 5G MIMO systems.The evolution of 5G technology demands antennas with superior performance to meet the requirements of high data rates, low latency, and enhanced energy efficiency. This paper presents a detailed study on the enhancement of a 5G MIMO antenna using metamaterials. Three antenna designs were analyzed: a quarter-wavelength (?/4) antenna, a half-wavelength (?/2) antenna, and a half-wavelength antenna integrated with metamaterials. The performance metrics, including resonance frequency (Fr), return loss (S11), transmission coefficient (S12), and gain, were systematically compared. The ?/4 antenna achieved an S11 of -24.07 dB, an S12 of -33.29 dB, and a gain of 5 dB at 2.44 GHz. The ?/2 antenna showed an S11 of -24.57 dB, an S12 of -25.04 dB, and a gain of 3.59 dB at 2.43 GHz. Notably, the ?/2 antenna with metamaterial integration demonstrated a significant improvement in performance, with an S11 of -18.16 dB, an S12 of -33.40 dB, and a gain of 6.43 dB at 2.4 GHz. These results highlight the potential of metamaterials to enhance antenna performance in terms of gain and isolation, making them a promising solution for next-generation 5G MIMO systems.

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5G MIMO, metamaterials, antenna design, return loss (S11), transmission coefficient (S12), gain enhancement, ?/4 antenna, ?/2 antenna, resonance frequency, next-generation wireless systems

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This study offers a comprehensive overview of the tea supply chain that exists in Assam. In addition, it also deals with the adoption of green practices within the tea industries of Assam, showcasing the region's unwavering commitment to sustainability and environmental stewardship. Emphasizing the significance of green practices, particularly in light of the prevailing climate circumstances, the research delves into the current state of adoption in selected tea estates scattered across Assam, with a focus on operational and logistical functionality. The findings reveal that while some tea estates have embraced green practices, ample opportunities for advancement and broader adoption still exist. Notably, the study highlights the growing utilization of renewable sources of energies, such as solar power, to operate tea factories and reduce dependence on fossil fuels. This paper also tries to highlight the tea supply chain in context of Assam. The tea supply chain is constructed based on inputs from various managers, tea board members, and other important stakeholders. To the best of our knowledge, no such specific work has been done in documenting the supply chain of the tea industry in the context of Assam and this is the novelty of this paper. It divides the supply chain of tea industries in three categories. In conclusion, the abstract emphasizes the challenges and future prospects for the adoption of green practices in the tea industry of Northeast India. It recognizes the necessity for ongoing collaboration among stakeholders, including government agencies, tea estates, and local communities, to overcome barriers and expand sustainable initiatives. Moreover, the abstract underscores the potential for sharing best practices and knowledge with other tea-producing regions worldwide.

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Tea Supply Chain, Green Practices, Tea Industry, Logistics, Operations, Sustainability

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Stroke remains one of the key public health problems in the modern world, being the second most common cause of mortality and a leading cause of disability, which makes the primary prevention of this disease and its complications extremely important. The purpose of this research is to predict the outcomes of the stroke with the help of the machine learning algorithms. A convolutional neural network was suggested to be coupled with a well designed long short term memory. Also, seven more classifiers were also used as baseline models: logistic regression, random forest, extreme gradient boosting, k-nearest neighbour, artificial neural network, long short-term memory, and convolution neural networks. Utilising a health care dataset that comprises health characteristics of 5,110 individuals, systematic training was conducted. To address data imbalance, minority class synthetic over sampling techniques have been used

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 Keywords

Convolution Neural Network (CNN), Transformers, Medical Image Analysis, Image, Deep Learning

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India's population expansion and urbanization have created a huge solid waste management problem, with legacy dumpsites continuing to be a major cause of pollution and environmental damage. This study focuses on the thorough remediation of the Ekla Bandha legacy site in Gorakhpur, where biomining was used to methodically treat 1,96,000 MT of legacy waste. The study demonstrates how a hazardous dumpsite has been converted into a green urban asset through resource recovery and sustainable approaches, such as turning excavated materials into useable resources. The study examines the remediation operations' effects on the environment, society, and economy, noting major reductions in methane emissions, enhanced soil and water quality, and the establishment of an urban forest with 50,000 planted trees. It also presents a conceptual framework for coordinating waste rehabilitation efforts with India's Green Credit Program, a ground-breaking program that was introduced in 2023 to encourage environmental sustainability. Gorakhpur exemplifies how cities may combine economic incentives and climate action by utilizing green credits for initiatives like solid waste management and afforestation. By reintegrating waste stream outputs into value chains, Gorakhpur is positioned as a leader in the shift to a circular economy, which lessens reliance on new resources. The study emphasizes the value of community involvement, public-private partnerships, and scalable approaches for other cities dealing with legacy waste issues. This study provides a reproducible methodology for attaining sustainable urban development, increasing India's net-zero promises, and building resilience in urban ecosystems by coordinating remediation with the Green Credit Program.

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dumpsite, remediation, bio-mining, green credit, circular economy, sustainability, plantation.

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 Abstract

Background & Objectives Tuberculosis (TB) is an ancient disease, with evidence of skeletal TB found in mummies in both the Old and New World. The causative agent is Mycobacterium tuberculosis, a fastidious, aerobic, acid-fast bacillus. In the wake of human immunodeficiency virus (HIV) infection, the number of children and adults afflicted with TB has escalated tremendously worldwide in the past 25 years. Control of TB in children often has been neglected because children are ineffective transmitters of the bacillus and frequently escape the attention of TB control programs. However, much of the morbidity and mortality of TB occurs in childhood, and acquisition of TB infection during childhood contributes to the future reservoir of cases. Risk factor based screening of children for TB infection, appropriate implementation of chemoprophylaxis. Aim of the study is to find "Effectiveness of a Self Instructional Module (SIM) On Knowledge Regarding Prevention and Management of Child Hood Tuberculosis among Final Year B Sc Nursing Students. Methods An evaluative approach with pre-experimental one group pre-test post-test design was used with purposive sampling technique to select the sample (N=40). A structured knowledge questionnaire was used to assess the knowledge and SIM was administered to find its effectiveness. The collected data was analyzed by using descriptive & inferential statistics. Results The mean percentage of post-test knowledge score (56.19%) was higher than the mean percentage of pre-test knowledge score (32.87%). The calculated't' value (43.18) is greater than the table value (0.05, 39df) = 2.57. It showed a significant difference between mean pre and post- test knowledge scores. Calculated ? 2 values is more than the table value with respect age and gender hence it showed significant association between age, and gender with post-test knowledge scores. Interpretation & Conclusion The findings of the study showed that there was a deficit in knowledge of final year students before administration of SIM. The results indicated that the SIM is effective in increasing the knowledge of final year students regarding the prevention and management child hood TB.

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 Keywords

Effectiveness; SIM; Knowledge; Tuberculosis Prevention; Management; Students

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