Volume 13 | Issue 11 |

 Abstract

Artificial Intelligence (AI) in diagnostic imaging has progressed from proof-of-concept classifiers to clinically integrated, regulated software that augments radiologists across screening, triage, quantification, and care coordination workflows, with multiple FDA-cleared products in routine use and nationwide prospective evaluations demonstrating increased detection without higher recalls in mammography screening programs. This expanded paper details model families (CNNs, vision transformers, foundation models), clinical performance in breast imaging, chest radiography, neuroimaging, cardiothoracic CT, and MRI, integration into PACS/EHRs, governance and bias mitigation, federated learning for privacy-preserving collaboration, and future trajectories including imaging foundation models, multimodal decision support, and physics-informed reconstruction at scale.

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 Keywords

Artificial Intelligence (AI), Diagnostic Imaging, Medical Image Analysis, Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Imaging Foundation Models, Federated Learning, Computer-Aided Diagnosis (CAD), Radiology Workflow Integration, Chest Radiography (CXR), Mammography Screening, MRI Enhancement, CT-Based Detection, Explainable AI (XAI), Saliency Maps, Grad-CAM, Data Annotation, Bias Mitigation, Model Governance, Software as a Medical Device (SaMD), PACS/EHR Integration, Real-W

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid escalation of cyber threats, characterized by sophisticated zero-day exploits and polymorphic attacks, mandates a transition from traditional reactive security postures to proactive, AI-driven defense mechanisms. This paper presents a comprehensive systematic review of the state-of-the-art applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in enhancing cybersecurity resilience. We analyze core defensive architectures, focusing on Network Intrusion Detection Systems (NIDS) and advanced malware classification, providing a quantitative comparative analysis of model performance across critical metrics such as Accuracy and Inference Duration. Our findings highlight the superior detection capability of Deep Learning models, specifically Transformer architectures, which achieve up to 98.4% accuracy in NIDS benchmarking. Furthermore, this review critically investigates the dual use challenge, examining emergent adversarial risks, including data poisoning, evasion attacks, and unique vulnerabilities introduced by Generative AI (GenAI), such as prompt injection and the phenomenon of feedback loop security degradation during automated code generation. Finally, we establish the mandate for Explainable AI (XAI) and robust governance frameworks as essential components for ensuring transparency, accountability, and trustworthy deployment of autonomous security systems.

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 Keywords

Intelligence, Cybersecurity, Deep Learning, Network Intrusion Detection System (NIDS), Adversarial AI, Explainable AI (XAI), Systematic Review, Zero-Day Detection.

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT: Acne vulgaris remains one of the most common dermatological disorders worldwide, affecting adolescents and adults and significantly impacting quality of life. Although conventional therapies such as retinoids, antibiotics, and hormonal agents are widely used, their limitations--including antimicrobial resistance, skin irritation, high cost, and systemic side effects--have driven increasing interest toward herbal alternatives. Herbal medicines contain diverse phytochemicals such as flavonoids, terpenoids, phenolics, and alkaloids that offer multi-target actions including antimicrobial, anti-inflammatory, antioxidant, and sebum-regulating effects. This review presents a comprehensive exploration of the etiology and pathophysiology of acne, the role of phytochemicals in its management, and the therapeutic benefits of medicinal plants such as aloe vera, neem, turmeric, green tea, tea tree oil, basil, chamomile, calendula, licorice, and rosemary. Emphasis is placed on the scientific evidence supporting their anti-acne potential, mechanisms of action, safety characteristics, and formulation approaches. The review concludes by highlighting current challenges, gaps in clinical validation, and emerging future prospects in integrating herbal therapeutics into mainstream acne management

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 Keywords

Herbal medicine; Acne vulgaris; Natural remedies; Anti-inflammatory agents; Antibacterial phytochemicals; Sebum regulation; Antioxidants; Aloe vera; Neem; Turmeric; Tea tree oil; Green tea; Basil; Witch hazel; Licorice; Rosemary; Chamomile; Calendula; Cutibacterium acnes; Phytochemicals; Dermatology; Plant-based skincare.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

21st sadi mein mahilao ke prati badhte cyber apradh

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21st sadi mein mahilao ke prati badhte cyber apradh

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Creative Commons Attribution 4.0 and The Open Definition

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: Amitav Ghosh's Gun Island (2019) presents a powerful literary engagement with climate-induced migration, situating the contemporary ecological crisis within historical and socio-economic contexts. By foregrounding the legacies of colonial exploitation, capitalist expansion, and systemic inequality, Ghosh demonstrates that climate migration is not solely a natural disaster but a human-made crisis. Using postcolonial ecocriticism and the framework of eco-imperialism, this study examines how the novel critiques global environmental inequities, amplifies marginalized voices, and exposes the structural roots of ecological degradation. The blending of myth, history, and contemporary reality underscores the ethical imperatives of planetary stewardship and climate justice. Ultimately, Gun Island exemplifies the capacity of literature to foster ecological consciousness, moral reflection, and collective responsibility, highlighting the urgent need for social and environmental justice in an era of escalating climate crises.

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Creative Commons Attribution 4.0 and The Open Definition

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Eco-imperialism, Climate migration, Postcolonial ecocriticism, environmental justice

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract Effective listening is a foundational element of successful communication. While much attention is often given to speaking and writing skills, listening is equally vital, especially in academic, professional, and interpersonal contexts. This paper explores the concept of effective listening, its types, barriers, and role in enhancing communication. It also highlights practical strategies for improving listening skills in various settings. Emphasizing that active and empathetic listening fosters better understanding, collaboration, and problem-solving, the paper concludes that listening is not a passive activity but a powerful tool for meaningful human interaction.

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Creative Commons Attribution 4.0 and The Open Definition

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Listening skills, active listening, communication, barriers to listening, interpersonal skills, professional success, effective communication.

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Creative Commons Attribution 4.0 and The Open Definition

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Plagiarism detection is a critical task in academic and professional settings. Traditional methods often struggle to identify sophisticated forms of plagiarism, such as paraphrasing and structural reorganization. This paper proposes a novel, multi-stage architecture for an improved and advanced plagiarism checker. Our hybrid model integrates three distinct techniques: (1) an efficient, hash-based document fingerprinting algorithm for initial large-scale screening, (2. a precise string-matching algorithm for detailed syntactic analysis, and (3) a deep learning model with an attention mechanism for capturing semantic similarities. By combining these methods, the proposed system aims to achieve high accuracy and efficiency, effectively identifying a wide spectrum of plagiarism, from literal copying to semantic paraphrasing.

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Creative Commons Attribution 4.0 and The Open Definition

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Plagiarism detection, hybrid model, multi-stage architecture, document fingerprinting, Winnowing algorithm, k-gram hashing, hash-based screening, suffix automaton, exact string matching, syntactic similarity, structural reorganization detection, semantic similarity, deep learning, Attention-based Bi-LSTM, neural attention mechanism, text embeddings, paraphrasing detection, contextual analysis, source code similarity, natural language processing, precision, recall, F1-score, semantic plagiarism d

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Creative Commons Attribution 4.0 and The Open Definition

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Women's Economic Independence and Class Struggle in Alka Saraogi's Novels

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Creative Commons Attribution 4.0 and The Open Definition

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Women's Economic Independence and Class Struggle in Alka Saraogi's Novels

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Creative Commons Attribution 4.0 and The Open Definition

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The production and sale of Indian two-wheeler automobiles play a crucial role in the automobile market within India. Two-wheeler automobiles constitute, on an average, 79.5% of total automobile sales in the country since 2001. The average number of two-wheelers per 1000 people in India is 31. India is the second-largest two-wheeler market in the world next to China, with annual sales of about 16 million units in 2022-23. A multiple linear regression model has been adopted to examine the impact of macroeconomic variables on demand for two-wheelers. Ordinary least square method is used to estimate the impact of macroeconomic factors after duly taking care of the assumptions of linearity, normality, multi-collinearity, homoscedasticity and autocorrelation to have consistent and efficient estimates of the regression parameters. The regression model initially considers 13 macroeconomic factors as explanatory variables. After dropping certain macro-economic variables which do not satisfy the tests of linearity, normality, multicollinearity, homoscedasticity and autocorrelation, it is found that per capita income, interest rate of borrowing, vale added in retail trade sector and two-wheeler prices have significant impact on the demand for two-wheelers.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

macro-economic variables, two-wheelers, multiple regression, least square method. Linearity, normality, multicollinearity, homoscedasticity, autocorrelation.

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Creative Commons Attribution 4.0 and The Open Definition