Volume 13 | Issue 12 |

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Bharat Me Siksha Ka Adhikar Ka Etihashik Vishleshan : Prachin Kal Se Vartaman Tak

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Bharat Me Siksha Ka Adhikar Ka Etihashik Vishleshan : Prachin Kal Se Vartaman Tak

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Pharmaceutical impurity detection and analysis represent critical quality assurance components directly impacting drug safety, therapeutic efficacy, and regulatory compliance throughout the product lifecycle. The escalating complexity of contemporary pharmaceutical formulations--including biologics, antibody-drug conjugates, and advanced therapeutics--demands analytical methodologies exceeding capabilities of conventional manual approaches. Automation technologies enable real-time monitoring, high-throughput sample processing, and standardized methodology execution with minimal human intervention, while artificial intelligence and machine learning algorithms excel at pattern recognition, predictive modeling, and decision support in complex analytical data. Integration of automation and artificial intelligence creates pharmaceutical quality control systems substantially more powerful than either technology alone, enabling transition from reactive, manual quality control toward proactive, data-driven quality management systems. Convolutional neural networks achieve 6-24% improvements in peak detection accuracy compared to conventional algorithms, with particular advantages in deconvoluting overlapping chromatographic peaks and identifying trace-level impurities. Recurrent neural networks and long short-term memory architectures provide exceptional capabilities for time-series analysis, enabling prediction of impurity formation kinetics and degradation pathways. Deep learning models achieve automated peak detection accuracy exceeding 95%, with average error in peak area determination approximately 4% compared to conventional approaches. Machine learning models demonstrate toxicity prediction accuracy exceeding 90% in external validation sets, enabling early identification of genotoxic impurities and hazardous degradation products. Process analytical technology integration with artificial intelligence enables unprecedented real-time manufacturing process monitoring, transitioning pharmaceutical manufacturing from batch-release testing toward real-time quality assurance. Persistent challenges include data quality management, model validation, regulatory acceptance frameworks, computational infrastructure requirements, and explainability of deep learning black-box models. Current regulatory frameworks emphasize risk-based validation approaches with proportionate testing based on model criticality and complexity. Harmonized global regulatory frameworks remain essential objective requiring ongoing collaboration between pharmaceutical manufacturers, technology developers, and regulatory agencies. Future advancement focuses on generative artificial intelligence applications, advanced impurity profiling strategies, real-time release testing implementation, and establishment of globally consistent validation standards and performance acceptance criteria.

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Artificial Intelligence, Machine Learning, Automation, Impurity Detection, Pharmaceutical Analysis, Process Analytical Technology, Quality Control, Deep Learning, Regulatory Compliance

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In 1986, India's first educational policy was approved and put into effect. On July 29,2020, India's National Educational Policy (NEP) was revised and approved after 34 years. The move marks a significant turning point for India's educational system,which will undoubtedly increase India's appeal as a global destination for higher education . The policy will turn India into a thriving knowledge hub and is founded on the principles of "Access,Equality,Quality,Affordability,and Accountability." The current paper provides an outline of the National Education Policy(NEP) 2020,highlights its key components,and identifies its advantages and disadvantages

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Features,advantages, access,quality,affordability,accountability

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The increasing integration of technology in school education has necessitated a rethinking of conventional teaching practices. This study investigates the effectiveness of techno-pedagogical strategies in teaching Social Science at the secondary school level. Techno-pedagogy combines appropriate technological tools with pedagogical principles to enhance students' understanding, engagement, and academic achievement. Using a quasi-experimental design, the study involved 80 secondary school students and 10 Social Science teachers. Data were collected through achievement tests. The results revealed a significant improvement in students' academic performance, classroom participation, and learning motivation when techno-pedagogical methods were employed. However, challenges such as inadequate infrastructure, limited professional training, and time constraints in lesson preparation were also identified. The study concludes that techno-pedagogy can serve as an effective instructional approach in Social Science education and offers practical implications, limitations, and directions for future research.

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Techno-Pedagogy, Social Science Teaching, Secondary Schools

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Online education has become an integral part of modern education systems, offering secondary school students a broad range of opportunities to explore vocational interests and career pathways. With the flexibility and accessibility of online learning, students can access a variety of resources and courses that help them better understand their potential career options. This paper examines the role of online education in shaping vocational interests among secondary school students and investigates the challenges that limit its full effectiveness. Drawing on established career development theories, including Holland's Vocational Personalities, Super's Self-Concept Theory, and Bandura's Social Cognitive Theory, the paper explores how online education can influence students' career choices, self-efficacy, and personal development. These theories provide a framework for understanding how online platforms can facilitate career exploration, promote skill development, and contribute to the shaping of students' vocational identities. However, despite the potential benefits, significant challenges exist. The digital divide, limited access to technology, and disparities in socioeconomic conditions prevent some students from fully engaging with online learning opportunities. Moreover, the absence of structured mentorship and personalized career guidance on many platforms hinders students' ability to make informed career decisions. This paper also discusses the integration of career guidance frameworks into online platforms and suggests strategies for overcoming these barriers. By addressing these challenges, online education can be a powerful tool in helping students navigate career decisions, refine their self-concept, and develop the skills needed for future success.

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Online education, vocational interests, secondary School students, digital divide.

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Agriculture remains a cornerstone of India's economy, sustaining over half of rural households and contributing major part of the national GDP. Despite significant post-independence efforts to enhance productivity through high-yielding varieties, irrigation, fertilizers, and modern machinery, small and marginal farmers often face financial constraints in accessing these inputs. Agricultural input subsidies have been implemented to reduce costs, encourage adoption of modern technologies, enhance farm incomes, and stimulate economic growth. Subsidies have been shown by numerous studies to positively influence productivity and reduce input costs; however, their impact on the alleviation of loan dependency has been found to be limited, with significant gaps in awareness being reported among resource-constrained farmers. Consequently, a need has been emphasized for targeted policy interventions, the establishment of efficient subsidy delivery mechanisms, and the implementation of comprehensive awareness programs, through which inclusive growth, sustainable agricultural development, and the enhancement of rural livelihoods may be achieved.

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Marginal farmers, Agricultural productivity, Input subsidies , Loan dependency, Policy interventions, Subsidy awareness, Rural livelihoods, Sustainable agriculture

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Learning about the various techniques to solve this higher power Diophantine equation in successfully deriving their solutions helps us understand how numbers work and their significance in different areas of mathematics and science. This paper first focused on studying infinitely many integer solutions of generalized quadratic Diophantine equation ?k(x-?)?^2+(y-?)^2=(z-?)^2 ,which is having ellipse equation form of ?k((x-?)/(z-?))?^2+((y-?)/(z-?))^2=1; Also, concentrate on studying Reciprocal form of above Diophantine Equation k/p^2 +1/q^2 =1/h^2 , Which is having different sets of integer solutions of p=(y-?)(z-?), q=(x-?)(z-?) and h=(x-?)(y-?). Also, introduces to study of binary operation on above Set of quadratic Diophantine Equation. P_1.P_2={?((kx_1 ?x_2?^2,y_1 (?y_2?^2+?z_2?^2 )+2y_2 z_1 z_2,?z_1 (?y_2?^2+?z_2?^2 )+2y_1 y?_2 z_2 )@(kx_2 ?x_1?^2,y_2 (?y_1?^2+?z_1?^2 )+2y_1 z_1 z_2,?z_2 (?y_1?^2+?z_1?^2 )+2y_1 y?_2 z_1 ) )}.

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Diophantine Equations, Ellipse, Reciprocal ellipse equations.

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The outcome of prosthodontic rehabilitation in partially edentulous individuals is highly dependent on an accurate appraisal of the available prosthetic space. Tooth loss initiates a series of biological and occlusal alterations, including resorption of the alveolar ridge, supraeruption of opposing teeth, and positional changes of adjacent teeth, all of which can negatively influence restorative space. In addition, neuromuscular adaptation and variations in occlusal vertical dimension further modify spatial relationships within the oral cavity. Inadequate evaluation of these changes may result in compromised function, esthetics, phonetics, and reduced longevity of prosthetic restorations. This narrative review outlines the concept of prosthetic space, factors responsible for its alteration, conventional and digital methods of assessment--including intraoral scanning--and their relevance in prosthodontic treatment planning.

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Prosthetic space, partial edentulism, interocclusal space, intraoral scanner, prosthodontic evaluation

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This research examines the application of classical Kavya Shastra principles--particularly Dandin's K?vy?dar?a and selected v?tti frameworks from Sanskrit poetics--within the kavittas attributed to Pt. Narayan Prasad of the Jaipur Gharana Kathak tradition. Treating kavitta as a performative poetic form rather than a fixed literary text, the study analyzes three representative compositions: a Chakkardar kavitta (rhythmic v?ra structure), K?liya Daman (misra-j?ti narrative kavitta), and Gol Kapol Adhar Bimbaphal (r?pa-var?ana ???g?ra-bhakti kavitta). Through qualitative analysis, the research identifies how vritti behaviour (m?du, vivara?a, bh?va, and laya vritti) and selective alamk?ras (anupr?sa, upam?, r?paka, and ati?ayokti) operate functionally rather than decoratively. The findings demonstrate that these kavittas enact a shabda-artha (sound-meaning) alignment consistent with Kavya Shastra, realised through rhythm, abhinaya, tala structure, and rasa progression. The study concludes that Pt. Narayan Prasad's compositions represent an embodied continuation of classical poetic theory, positioning kavitta as applied aesthetics within Kathak pedagogy and performance. This research contributes to filling a scholarly gap by bridging textual Sanskrit poetics with practical dance methodology, offering a framework for further academic analysis of gharana-specific repertoire.

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Kavya Shastra, vritti, alamkara, kavitta, Jaipur Gharana, Pt. Narayan Prasad, Kathak pedagogy, Rasa structure.

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Mark Haddon's The Curious Incident of the Dog in the Night-Time (2003) is widely recognized for its sensitive portrayal of neurodivergence through the perspective of Christopher Boone, a fifteen-year-old protagonist. While much critical attention has focused on Christopher's voice and unique worldview, this paper shifts its lens to the often-overlooked struggles of his parents. It seeks to explore how the novel portrays the realities of parenting a neurodivergent child, emphasizing the fragile balance between care, sacrifice, and human vulnerability. The discussion highlights the emotional, social, and relational challenges faced by Christopher's parents, ranging from patience and compassion to frustration, guilt, and marital strain. Beyond challenges, the paper also examines the sacrifices embedded in their roles as caregivers, including personal compromises, emotional endurance, and the reshaping of their identities as both individuals and parents. These struggles show that parenting a neurodivergent child demands not only resilience but also the acceptance of imperfection and the ability to endure love in its most difficult forms. By foregrounding these experiences, the paper argues that Haddon's narrative not only illuminates the complexities of neurodivergence but also broadens our understanding of family dynamics and the resilience of caregivers. Ultimately, the novel invites readers to reflect on the intertwined struggles of children and parents, reminding us that the story of neurodivergence is also a story of shared endurance and love

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Neurodivergence, Parenting, Sacrifice, Family Dynamics

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