Volume 13 | Issue 5 |

 Abstract

This paper presents a deep learning-based solution for the detection of diseases in apple leaves. The proposed system leverages convolutional neural networks (CNNs) to classify images of apple leaves into healthy or diseased categories. A custom-built GUI enables users to interact with the system by uploading leaf images for instant diagnosis. The model has been trained on a publicly available dataset of apple leaf images, ensuring robust performance across different disease types such as apple scab, black rot, and cedar apple rust. The tool is designed for offline deployment to support usage in remote agricultural areas, offering farmers and agriculturalists a practical solution for timely disease management.

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 Keywords

Apple Leaf Disease, Deep Learning, Convolutional Neural Network, Image Classification, Agriculture, Offline AI Tool

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 Abstract

A fascinating class of microorganisms and plants known as heavy metal resistant organisms have developed special adaptations to survive in environments where high concentrations of heavy metals are present. The goal of the current study was to identify heavy metal-tolerant bacteria from Kanjikode soil samples that had been industrially contaminated and to evaluate the heavy metal resistance of the chosen bacterial isolates. A quantitative analysis of heavy metal-tolerant organisms was also conducted using morphological, biochemical, molecular identification, and assessment of heavy metal-tolerance in order to isolate and characterize the total heterotrophic population. Bacillus flexus and Bacillus aryabhattai were identified as the two chosen bacterial isolates following 16S RNA sequencing. Because of their resistance to and potential for degrading heavy metals, the identified bacteria suggest potential for bioremediation efforts. As per previous studies, the potential of Bacillus flexus was maintained.in arsenic-contaminated environments, whereas Bacillus aryabhattai promotes plant development and has a high resistance to heavy metals. The present investigation presents light on heavy metal resistant soil bacteria in industrial pollution scenarios, revealing possible uses in bioremediation methods in the future.

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 Keywords

Heavy metal resistance, Bacillus flexus, Bacillus aryabhattai, Industrial pollution

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Money laundering and corruption are closely interconnected concerns in India, presenting substantial difficulties to the country's economic integrity and governance. Corruption serves as a catalyst for money laundering, allowing illicit cash to be assimilated into the legitimate economy. Prominent incidents of public officials illustrate how bribery and embezzlement facilitate laundering activities, frequently including intricate financial transactions that conceal the Sources of illicit funds. The Prevention of Money Laundering Act (PMLA) and multiple anti-corruption frameworks have been developed to address these concerns. Nonetheless, enforcement is inconsistent, frequently obstructed by political influence and bureaucratic inefficiencies. This dynamic sustains a cycle in which corrupt practices generate further corruption, facilitating the reintegration of laundered monies into corrupt systems, thereby eroding public trust and hindering economic development. Moreover, the connection between organised crime and corrupt officials intensifies the issue, resulting in diminished government revenue and worsening socio-economic inequalities. Confronting these interconnected concerns necessitates extensive reforms, enhanced openness, and strong accountability measures to break the loop of corruption and money laundering. By comprehending this relationship, authorities can formulate focused policies to improve governance and reinstate integrity inside India's financial systems.

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anti-corruption, reintegration, money laundering, etc.

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Chalcones, known as open chain flavonoids, are a unique class of compounds characterized by an ?, ?- carbonyl configuration. The versatile nature of chalcone hybrids suggests broader pharmacological applications. This review emphasizes the structural variation of chalcones, their biosynthetic pathways and their comprehensive pharmaceutical applications including as anti-carcinogenic, anti-inflammatory, anti-bacterial and antioxidant activities. Generally, in the management of microbial infections and oxidative-stress related diseases chalcone derivatives representing a promising revenue for pharmaceutical discovery and development, fostering potential for advanced therapies and improved results.

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 Keywords

Chalcone, flavonoids, structural variations, pharmaceutical applications

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Creative Commons Attribution 4.0 and The Open Definition

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Agriculture remains the backbone of global food security, yet plant diseases pose a persistent threat to crop yields and farmer livelihoods. Conventional disease detection methods are often costly, slow, and inaccessible to small-scale farmers. To bridge this gap, this study leverages Convolutional Neural Networks (CNNs) for automated plant disease recognition using leaf image classification. CNNs, renowned for their ability to extract intricate features from visual data, offer a scalable solution for real-time disease detection. By training and optimizing CNN models on diverse datasets, this research enhances predictive accuracy while ensuring computational feasibility for deployment on resource-constrained devices. The proposed framework empowers farmers with early disease identification, enabling timely intervention and reducing economic losses. Beyond technological innovation, this work underscores the human spirit's resilience--merging scientific advancement with the innate drive to protect and sustain the natural world. In doing so, it reinforces the harmony between technology and agriculture, advocating for sustainable farming practices that safeguard both food security and farmer well-being.

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 Keywords

CNN, plant disease detection, agriculture, machine learning, Sustainability

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Creative Commons Attribution 4.0 and The Open Definition

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The increasing emphasis on diversity and inclusion in Hollywood, particularly post-2020, has sparked extensive debate surrounding the authenticity and effectiveness of representation. With major franchises like Marvel embracing a more 'woke' agenda, the industry appears to be responding to long-standing demands for inclusivity. However, these efforts are frequently criticized for devolving into tokenism--where minority characters are inserted superficially rather than integrated meaningfully. This paper investigates the distinction between genuine representation and performative inclusion in major Hollywood productions, focusing on Marvel films and Disney+ shows released after 2020. Through detailed textual analysis and examination of critical and audience reception, the research highlights the implications of forced representation, diminishing box office returns, and alienation of core fanbases. The study argues that while the intent behind diverse casting is commendable, its execution often undermines narrative integrity and alienates viewers, ultimately threatening the cultural and commercial sustainability of iconic franchises.

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Representation, Tokenism, Wokeism, Marvel, Diversity, Inclusion, Hollywood, Identity Politics, Pop Culture, Box Office

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Technologies like virtual reality (VR) and augmented reality (AR) are revolutionizing education, particularly in the area of media studies. This study investigates how to improve the teaching and learning process in media studies by integrating virtual reality (VR) and augmented reality (AR). As immersive technologies develop quickly, VR and AR provide fresh chances to revolutionize conventional teaching methods by creating dynamic, captivating, and hands-on learning experiences. The study looks at how these technologies are used to mimic actual media production situations, support experiential learning, and provide students the chance to study difficult media ideas in a realistic environment. By examining current case studies and experimental implementations, the study determines the possible advantages of VR and AR in fostering critical thinking and visualization. It also looks at issues with technology constraints, accessibility, and the necessity of successful curricular integration

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 Keywords

Virtual Reality, Augmented Reality, Education, Media studies, Visualization, Case Studies

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Creative Commons Attribution 4.0 and The Open Definition

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The extract of the red mud waste prepared in the laboratory is almost equivalent to the lechate leaking from red mud pond of the contaminated site. The red mud waste extract is deadly toxic to the germinating crop seeds. Experiments were conducted at sub-lethal concentrations to study the impact of lechate waste. The total chlorophyll, pheophytin and carotene content of green gram plant leaves decreased significantly with the increase in lechate concentration compared to their respective control values after 144hr of germination. The photosynthetic rate, respiration rate and GPP values significantly decreased in the exposed green gram seedlings with the application of lechate compared to control green gram seedlings in Petri plate culture. Little insignificant increment in the photosynthetic rate was noted at sub-lethal concentration of the lechate. The ATPase enzyme activity decreased in the exposed green gram seedlings with the application of lechate compared to control green gram seedlings in petriplate culture. No increment in the enzyme activity was observed even at sub-lethal concentration of the lechate and at lower exposure period. The residual alumina accumulation increased with the increase in toxicant (lechate) concentration in the leaves and roots. Lechate exposed roots accumulated more amount of alumina than the leaves of the exposed seedlings/ plants. The study on seed biology indicated that the red mud waste dumped by the industry is deadly toxic and if released accidentally even into the environment, will cause environmental havoc. Present study aims at understanding the impact of RMP (red mud pond) lechate on the physiological and enzymological activity of a crop seed germinating under stress.

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 Keywords

RMP lechate, Alumina, Pigments, RR, GPP, NPP, ATPase.

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Creative Commons Attribution 4.0 and The Open Definition

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Augmented Reality (AR) is a rapidly growing technology [1] that enhances how we perceive and interact with our surroundings. It has the potential to transform industries such as education, healthcare, military, manufacturing, gaming, and more. This paper reviews the challenges of AR adoption, including human factors and legal issues [4], and explores how AR is becoming a cornerstone in education and other sectors. AR's ability to improve learning motivation, engagement, and behavior has been widely studied, particularly in developing interactive and immersive environments. Recent advancements demonstrate how AR can improve knowledge delivery in subjects [1] like mathematics, physics, chemistry, and history, offering new opportunities for educators and learners. The findings aim to inspire further innovation in creating interactive AR experiences for learning and beyond

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Augmented Reality, AR adoption challenges, human factors, legal issues, education, healthcare, military, manufacturing, gaming, immersive environments, interactive learning, knowledge delivery, innovation.

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Creative Commons Attribution 4.0 and The Open Definition

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This study investigates the financial performance of India's telecom industry through an in-depth analysis of financial statements using Principal Component Analysis (PCA). Utilizing secondary data from three leading telecom companies--Bharti Airtel, Reliance Jio, and Vodafone Idea--over a ten-year period (2013-14 to 2022-23), fourteen key financial ratios covering profitability, leverage, liquidity, operational efficiency, and market valuation were examined. PCA reduced these variables into four principal components, collectively explaining approximately 78% of the variance, highlighting critical dimensions shaping financial health: profitability and operational efficiency, leverage and solvency, liquidity, and market valuation. The findings underscore the importance of profitability as a key driver of sustainability, the necessity of prudent debt management, and the role of liquidity in maintaining operational stability in this capital-intensive sector. Practical recommendations for corporate management, investors, and policymakers are discussed to enhance financial decision-making and industry resilience. This research demonstrates PCA's effectiveness as a tool for simplifying complex financial data and provides valuable insights for stakeholders navigating India's competitive telecom landscape.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial Statement Analysis, Principal Component Analysis (PCA), Telecom Industry, Financial Ratios, India, Profitability, Leverage, Liquidity, Market Valuation

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Creative Commons Attribution 4.0 and The Open Definition