Volume 14 | Issue 3 |

 Abstract

Artificial intelligence is increasingly becoming an integral part of children's everyday play through smart toys that can interact, learn, and adapt to their users. These innovations offer unprecedented educational and recreational opportunities, fostering creativity, problem-solving, and personalized learning experiences. At the same time, AI toys collect a range of sensitive data, including children's voices, behavioural patterns, and personal information, which, if mismanaged, can expose minors to privacy risks and potential exploitation. Despite the rapid adoption of such technologies, current legal and regulatory frameworks are fragmented and often lag behind technological advancements, leaving critical gaps in the protection of children's digital rights. This study investigates the legal vacuum surrounding AI-enabled toys and examines the ethical and child-rights considerations that arise in this context. By critically analysing existing privacy laws and their limitations, the research proposes a conceptual framework for the responsible design, deployment, and oversight of AI play devices. The study underscores the unique vulnerabilities of children in digital environments, highlighting the need for regulatory interventions that balance innovation with protection. Ultimately, this paper aims to provide a theoretical foundation to guide policymakers, designers, and stakeholders in establishing privacy safeguards, ethical standards, and child-centric governance models for AI technologies targeting minors.

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Artificial Intelligence (AI) Smart Toys Children's Digital Rights Privacy Risks Data Collection in AI Toys Child Protection Ethical Considerations Privacy Laws

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The Middle class family working woman are being financially independent, hence, she want to investment for family wellness and future welfare. Investment of working women in different sectors is play important role in their income, which affect G.D.P. of the nation. Mostly working women in Muzaffarpur can also make financial planning to achievement of financial growth, which is self decision of working women, no other person influences. It is important to observed that participation of the working women in investment is great planning, because their economic under plot is changing. The main aim of our study is the detailed description of investment in different sectors of working women's in Muzaffarpur districts, which affects by various factors. Our study illustrates that the Muzaffarpur working womens investment is greatly influenced by information factor, social factor, educational factor, psychological factors, firms image etc. Out study supports educational programs, financial programs, policy formulation etc, which makes the women investors, more involvement in various sectors investment.

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Working women in Muzaffarpur, Behaviour of investment, self investment decision, social factors, psychological factors, educational factors, information factors etc.

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Maladaptive daydreaming (MD) is a psychological phenomenon characterized by excessive, immersive, and often compulsive daydreaming that significantly interferes with an individual's daily functioning, productivity, emotional regulation, and social interactions. Individuals suffering from MD may spend hours engaged in vivid fantasy worlds, which can lead to difficulties in academic, occupational, and interpersonal domains. Traditional therapeutic interventions, such as cognitive behavioral therapy (CBT) and mindfulness-based strategies, often require substantial human involvement and lack scalability, real-time monitoring, and personalized adaptation to individual user behavior. This paper introduces Daydream Detox, an innovative AI-driven therapeutic platform designed to detect, predict, and manage maladaptive daydreaming using advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). The system architecture integrates a Flutter-based mobile application for user interaction, a MERN (MongoDB, Express.js, React.js, Node.js) web dashboard for administrative and analytical oversight, a Python-based AI analytics module for emotion and behavior analysis, and a MongoDB database for secure data storage. Daydream Detox collects multidimensional user data, including activity patterns, text-based journals, mood logs, and user interaction metrics. This data is processed using NLP and ML algorithms to detect early signs of maladaptive daydreaming and generate predictive models of user behavior. The platform delivers personalized therapy plans, focus-enhancing routines, and context-aware recommendations tailored to individual needs. Furthermore, a real-time AI chatbot provides interactive interventions, motivational support, and reminders, thereby enhancing user engagement and adherence to therapy routines. Experimental evaluation involving multiple participants demonstrates that Daydream Detox significantly improves focus, reduces the frequency and duration of maladaptive daydreaming episodes, enhances emotional self-awareness, and promotes consistent adherence to personalized routines. The platform's AI-driven approach highlights the potential of digital therapeutics in providing scalable, adaptive, and real-time mental health support. This study emphasizes the importance of integrating AI, ML, and DL into digital wellbeing platforms and showcases how such technologies can address modern cognitive and emotional challenges effectively. Future work aims to expand the system with multimodal data inputs, such as speech and physiological signals, to further enhance predictive accuracy and therapeutic effectiveness.

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 Keywords

Maladaptive Daydreaming, Artificial Intelligence, Machine Learning, Deep Learning, Flutter, MERN, Natural Language Processing, Emotion Recognition, Therapeutic Chatbot, Digital Wellbeing, Personalized Therapy

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Preeti Shenoy, one of the most recent and prominent Indian women writers effectively portrays the issues of women and their inner trauma. Her contribution towards women empowerment and the realistic depiction of their lives is undeniable. She boldly depicts and explicitly challenges the male domination and the pressures experienced by the women in the society. She proves herself as a responsible social reformer through her writings and strives to establish gender equality even in the so-called developed, scientifically advanced modern world. Most of the women's lives are still vulnerable and conservative when compared with few modern women in the society. Women are still not capable to express their sexual desire and their own opinions regarding their lives. But now, women have been slowly trying to stand for their self without any discrimination and inequality. The women in the past struggled in their own way and now women are still struggling to get freedom from patriarchal domination. Their issues are same but the experiences they face are totally different from one another. Shenoy's, It Happens for a Reason realistically depicts the sufferings of women. This paper focuses on the need and the importance of women emancipation and the inequalities they face both in their families and in the society.

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Inner trauma, Women empowerment, Gender equality, Gender discrimination, patriarchal domination.

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Asansol is India's 11th fastest-growing city in India and 42nd fastest-growing city in the world, known as the 'Land of Black Diamonds'. Two wings (Cole and iron industries) are the city's most influential factors for flourishing. After the extraction of the coal mine and installation of heavy industry, it made an excellent employment site and massive population attracted from neighbouring states. It got metropolitan dignity within a very few decades. Asansol belongs to a complex mosaic of economic, language, and cultural characteristics due to the migration of people from different parts of the country. This assimilation of the multi-lingual, multi-religious, multi-cultural populations from different parts of India makes it a coal mining and heavy industry-based cosmopolitan city.

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Asansol; Cosmopolitan city; Coal Mining; Industry; Cultural assimilation

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This research paper presents different perspectives on migrants' experiences of the Partition and its impact on those who migrated from Pakistan during the 1947 Partition. The study compares fictional representations of these experiences with the lived experiences of former migrants as recorded in their oral narratives. It provides an account of the challenges they faced and reflects on how these refugees created space for themselves in India, transforming it into a home and a place to earn their livelihood. A key feature of this research is the juxtaposition of the literary portrayal of Partition in Chaman Nahal's Azadi with the real-life experiences of refugees who migrated from Pakistan to India during Partition.

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Partition of India, Migration, Displacement, Refugee, Politics and Religion, Communal violence, Azadi, Hindu-Muslim relations, Pakistan, Punjab, Indian National Congress

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This article examines the revolutionary epistemological shift introduced by Immanuel Kant in his seminal work Critique of Pure Reason. Kant characterizes his philosophical approach as a "Copernican Revolution" in philosophy, drawing an analogy with the scientific transformation initiated by Nicolaus Copernicus. Prior to Kant, philosophical tradition generally assumed that human knowledge must conform to objects, implying that the mind passively receives information from the external world. Kant challenges this assumption by proposing that objects of experience must conform to the cognitive structures of the human mind. According to this view, the mind actively organizes and interprets sensory data through its inherent forms and categories, making knowledge possible. By shifting the focus from objects to the conditions of human cognition, Kant redefines the nature of epistemological inquiry. This article highlights the significance of Kant's philosophical revolution and explains how his theory reoriented modern philosophy toward an investigation of the subject's role in shaping experience and knowledge.

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: Copernican Revolution in Philosophy, Epistemology, Transcendental Idealism, Subject-Object Relationship, Human Cognition, Structure of Knowledge, Modern Philosophy.

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Histopathological Evaluation Of Thyroid Lesions Dr Nisarg Shah, 3rd-year Resident Dr Shivani Divecha, 3rd-year Resident Dr Ayushi Shah, 2nd-year Resident Dr. Shashikant Mavadiya, Professor Dr. Vaibhavi Thacker, 2nd-year Resident Department of Pathology, Dhiraj Hospital, SBKS Medical Institute & Research Centre. Corresponding Author - Dr Nisarg Shah Email ID: nisargshah96ns@gmail.com Contact number - 8511348204 BACKGROUND: Histopathological evaluation is essential for the definitive diagnosis of thyroid lesions, particularly in differentiating follicular adenoma from follicular carcinoma, which significantly influences patient management and prognosis. OBJECTIVES: To study the spectrum of thyroid lesions and evaluate their histopathological patterns and to analyze their distribution across age and sex. METHODS: A retrospective observational study was conducted in the Histopathology section of the Department of Pathology, Dhiraj Hospital, SBKS MI & RC, Vadodara, from September 2024 to October 2025. A total of 58 specimens--including tru-cut biopsies, lobectomies, hemithyroidectomies, subtotal, and total thyroidectomies--were included. Inadequate or autolysed specimens were excluded. Tissue samples were fixed in 10% neutral buffered formalin, stained with hematoxylin and eosin, and examined microscopically. Data were analyzed using Microsoft Excel. RESULTS: Patients ranged from 22-66 years, with a marked female predominance (M:F = 1:7). Non-neoplastic lesions were more common than neoplastic lesions. Among neoplasms, benign tumors predominated. Follicular adenoma was the most frequent benign lesion, while papillary thyroid carcinoma was the most common malignant tumor. CONCLUSION: This study highlights that non-neoplastic and benign neoplastic thyroid lesions are more prevalent than malignant lesions. Despite the availability of preoperative diagnostic tools, histopathology remains the gold standard for accurate diagnosis and optimal management of thyroid diseases.

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Thyroid lesions, Histopathological evaluation, Thyroidectomies, Hematoxylin and Eosin, Papillary thyroid carcinoma, Follicular adenoma

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Brain tumor diagnosis using magnetic resonance imaging (MRI) remains a challenging clinical task due to heterogeneous tumor appearance, overlapping intensity distributions, and significant interpatient variability. Accurate tumor segmentation and classification are essential for effective treatment planning and prognosis; however, manual analysis is time-consuming and subject to observer bias. This work presents an enhanced deep learning framework that integrates advanced preprocessing, an improved UNet-based segmentation network with Squeeze-and-Excitation (SE) blocks and Gaussian Error Linear Unit (GeLU) activation, and a comparative evaluation of three deep convolutional neural network architectures--ResNet50, ResNet101, and DenseNet121--for multi-class brain tumor classification. The segmentation module provides precise tumor localization, enabling the classification models to focus on clinically relevant regions and suppress background interference. The framework is evaluated on the Figshare brain tumor MRI dataset containing glioma, meningioma, and pituitary tumor classes. Experimental results demonstrate strong segmentation performance with a Dice coefficient of 91.8% and classification accuracy of up to 98.04% on unseen test data. Comparative analysis indicates that ResNet50 achieves the best balance between accuracy, generalization capability, and computational efficiency among the evaluated models. These results highlight the effectiveness of enhanced segmentation guided deep learning for reliable and real-time brain tumor diagnosis.

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Brain Tumor Classification, MRI, Deep Learning, ResNet, DenseNet, Ensemble Learning, ROC Curve, Precision-Recall Analysis

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Abstract Background: Root canal treatment (RCT) is a commonly performed endodontic procedure aimed at eliminating infection from the root canal system and preserving the natural tooth. Despite the advancement in endodontic techniques and materials, post-operative pain remains one of the most common complications experienced by patients after root canal treatment. Awareness regarding postoperative pain and its management is essential for dental students as they play an important role in providing proper patient care during clinical practice. Aim: The aim of the present study was to evaluate the awareness and knowledge regarding postoperative pain management following root canal treatment among undergraduate students. Materials and Methods: A cross-sectional questionnaire-based survey was conducted among 400 undergraduate students. A structured questionnaire consisting of questions related to post-operative pain following root canal treatment, its causes, duration, and management strategies was distributed among the participants. The responses were collected and analyzed using descriptive statistical methods. Results: The results of the present study revealed that the majority of students were aware that postoperative pain can occur after root canal treatment. Female students showed slightly higher awareness levels compared to male students. Students belonging to the age group of 21-23 years demonstrated greater awareness regarding post-operative pain and its management. Conclusion: Within the limitations of the study, it can be concluded that undergraduate students possess a moderate level of awareness regarding post-operative pain management in root canal treatment. However, additional educational programs and clinical training are required to improve their knowledge and enhance patient care

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Keywords: Root canal treatment, Post-operative pain, Pain management, Awareness, Undergraduate students, Endodontics. Introduction

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