Volume 13 | Issue 12

 Abstract

Quality control plays a great role in the assurance of integrity, safety, and performance of a product within various industrial sectors such as pharmaceuticals, food processing, materials science, and chemicals. The commonly used traditional QC methods include titrimetric analysis, chromatography, and gravimetry among others. Though these methods are well known for their accuracy they involve destructive testing, elaborate sample preparation as well as long analysis time hence high operation cost and added environmental burden. Recent developments in different spectroscopic techniques have remodeled the analytical quality control area with their non-destructive, reagentless real-time molecular characterization capabilities. Available methods include FTIR, NIR, Raman, NMR, UV-Vis, THz, and LIBS which permit very selective and sensitive rapid determination of physical and chemical properties. These methods have not only enhanced analytical throughput but are also compliant with the current state of regulation which puts a spotlight on the PAT and QbD paradigms. This paper reviews the principles and foundations, instruments, applications, benefits, and practical challenges of advanced spectroscopic techniques. It discusses trends fueled by artificial intelligence in spectral interpretation, miniaturized and portable spectrometers, data fusion strategies, and hybrid spectroscopic platforms leading to intelligent automated sustainable QC systems. All these are integrated with the promise to bring a new dawn in modern manufacturing via predictive analytics as well as compliance that is not harmful to the environment while assuring quality.

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Keywords: Quality Control, Spectroscopy, FTIR, Raman, NMR, Process Analytical Technology, Non-Destructive Testing, Chemometrics, AI-driven Analysis.

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In every field of life, nanotechnology has an impact. Researchers expend their interests on gold nanoparticles synthesis as they provide superior properties for various types of applications. Different physical and chemical methods have synthesized conventionally nanoparticles that have a negative impact on the environment. Due to their unique properties, small size and high area-to-volume ratio, gold nanoparticles show special advantages in this field among nanoparticles. Because of their inert nature, stability, high dispersity, non- cytotoxicity and biocompatibility, these particles have been widely used in various biomedical applications and drug delivery systems. This paper shows the comparison and survey of all the methods. Gold nanoparticles are widely used in many fields As preferred materials for their unique optical and physical properties, such as surface plasmon oscillations for labeling, imaging, and sensing. Recently, many advancements were made in biomedical applications with better biocompatibility in disease diagnosis and therapeutics. Au-NPs could be prepared and conjugated with many functionalizing agents, such a polymers, surfactants, ligands, derailments, drugs, DNA, RNA, proteins. Peptides and oligonucleotides. This review addressed the use of gold nanoparticles and the surface functionalization with a wide range of molecules expanding and improving gold nanoparticles in targeting drugs for photothermal therapy with reduced cytotoxic effects in various cancers gene therapy and many other diseases.

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 Keywords

Gold nanoparticles, Nanotechnology, drug delivery, biomedical Applications, cytotoxicity, cancer, drug delivery.

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In today's fast-paced digital environment, businesses are increasingly employing chatbots to enhance customer support services. This research paper explores the functionalities of chatbots in customer support, their impact on operational efficiency, customer satisfaction, and challenges associated with their implementation. We also examine various case studies that highlight successful chatbot deployments across different industries.

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 Keywords

AWS, Azure, GCP, Intent, Entities, Utterances, Natural Language Processing (NLP), Fallback, Human Handoff (or Transfer), Artificial Intelligence, Knowledge Base, Conventional Flow

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Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by persistent difficulties in communication, social interaction, and adaptive behavior. The increasing prevalence of autism worldwide has intensified the demand for innovative, inclusive, and evidence-based educational strategies that address the diverse learning needs of children with autism. Traditional instructional methods often fail to accommodate the heterogeneity of autism, necessitating flexible and learner-centered approaches. This paper presents a comprehensive review of innovative learning strategies designed to enhance the academic, social, and emotional development of children with autism. The study explores technology-assisted instruction, structured teaching models, adaptations of Applied Behavior Analysis (ABA), play-based and sensory integration approaches, peer-mediated interventions, and the Universal Design for Learning (UDL) framework. Additionally, emerging innovations such as gamification and artificial intelligence-driven personalized learning platforms are examined. The paper also discusses challenges including teacher preparedness, limited resources, and variability in learner profiles. The findings emphasize the need for collaboration among educators, parents, therapists, and policymakers to foster inclusive educational environments and ensure equitable learning opportunities for children with autism.

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Autism Spectrum Disorder, Innovative Learning, Inclusive Education, Assistive Technology, Teaching Strategies

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Biometric attendance systems are widely used to automate employee tracking and minimize manual intervention. However, ensuring single recording of attendance during both check-in and check-out remains a challenge due to issues like duplicate entries, spoofing, and improper biometric capture. This research proposes a robust algorithm that enforces one attendance entry per shift per user, using time-based locking and intelligent recognition. The proposed system significantly reduces redundancy and improves attendance accuracy with efficient time threshold management and real-time feedback. Experimental results demonstrate a strong improvement in preventing multiple submissions and reducing administrative overhead

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Biometric Attendance, Single Attendance, Time Threshold

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ABSTRACT: 'Knowing- Self' plays a prominent role in the human journey. To build harmonious society 'understanding between self and world' is important. A sympathetic awareness on the issue or ability to understand something in life is called understanding. When man understands truth in life, the possibility of mental and physical sufferings like unknown fear, anxiety, and depression may not exist in human life. In 'As You Like It', Shakespeare's quote "All the world's a stage and all men and women merely players" depicts human connection with drama. In the journey of human life, everyone has to face sufferings without a chance of escape. The philosophical theory of absurdity states that human life is a clash between self and world. It claims that human life is meaningless, hopeless and uncertain in the modern world. Nihilism stood as a profound philosophical phenomenon to challenge individual's identity for social well-being. Moreover, Nietzsche's Nihilism is a response to the erosion of traditional values and Christian beliefs. Passive nihilist can be called pessimistic because he lives in suffering with a psychological trauma. But Active nihilist tries to make his suffering into a meaningful suffering by creating hope in hopeless conditions. The paper is aimed to explore how Nietzsche's views on human sufferings with reference to Nietzsche's Thus Spoke Zarathustra Samuel Beckett's Endgame and Badal Sircar's Procession

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Key Words: Absurd Life, Nihilism, Sufferings, Self, Positive Attitude

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Abstract: The modern era is very important for Arabic language and literature. It is full of the art, the novel, the story, and the play. Many sciences and knowledge have developed in it. Novelists from different countries have fought in a variety of ways in the creativity of the novel, its techniques, and the types of plots. The Arabic novel passed through many stages until it reached maturity and perfection and developed the last forms of narrative. Raja'a Muhammad 'Alem (Arabic: ???? ????) is one of the foremost modern Arabic novelists from Saudi Arabia. Through her personal experiences, Alem provides a glimpse into the private lives of local women who experience pressures very different from those faced by typical female visitors to Mecca. Her novels delve into the social restraints of society, which often forbid the voicing of issues and concerns such as women's rights, forced marriages, and emotional issues like love and relationships between the sexes, as these topics are deemed objectionable. 'Alem addresses the problem of women seeking to identify their identity by illustrating the reality of being continually veiled and unable to express themselves through visible methods. She is an active writer of prose, and her unique style, blending modern elements with traditional themes, sets her apart among Saudi authors. This article attempts to depict the position of Raja'a 'Alem and her contributions to Arabic novels.

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modern era, personal experiences, glimpse into the private lives, social restraints, forced marriages.

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Keywords: Cord Blood Stem Cells, Knowledge, Structured Teaching Programme, Nurses, Collection and Preservation, In-Service Education.

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Keywords: Breast Engorgement, Lukewarm Water Compress, Postnatal Mothers, Non-Pharmacological Therapy, Breastfeeding.

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Keywords: Thermoregulation, mothers, under-five children, planned teaching programme, knowledge, practice.

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Fucoidan (I) have been modelled using SwissADME web tool and physicochemical, pharmacokinetics, drug-likeness and medicinal properties of I were analyzed. The results reveal that the selected candidate (I) possesses high gastrointestinal (GI) absorption and positive result to Lipinski's rule. It exhibits good bioavailability score and notable synthetic accessibility.

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Fucoidan, Theoretical analysis, ADME properties, Pharmacology and SwissADME web tool

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This research paper examines the transformative evolution of visual effects (VFX) in Tamil cinema between 2020 and 2025, a period marked by unprecedented technological advancement and creative innovation. The study identifies key trends, technological shifts, and creative approaches that have redefined the visual storytelling landscape in Kollywood. Through comprehensive analysis of industry practices, technological adoption, and aesthetic developments, this research reveals how Tamil cinema has progressively integrated sophisticated VFX across diverse genres, from historical epics to contemporary science fiction. The findings demonstrate a significant shift from VFX as mere spectacle to narrative-integrated visual storytelling, with Tamil films achieving global technical standards while maintaining cultural authenticity. The COVID-19 pandemic initially disrupted production but accelerated digital transformation, leading to increased reliance on virtual production techniques and remote collaboration tools. Major studios like PhantomFX, Makuta VFX, and Mindstein Studios have emerged as industry leaders, driving quality enhancement while fostering local talent development. The period also witnessed the strategic integration of artificial intelligence and machine learning in VFX pipelines, revolutionizing pre-visualization and post-production processes.

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Visual Effects, Tamil Cinema, Virtual Production, CGI, Digital Transformation

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This paper analyzes the implementation and effectiveness of Plagiarism Detection Software (PDS) in Indian Higher Education Institutions (HEIs) amidst a rapidly evolving digital landscape. It examines the impact of the University Grants Commission (UGC) Regulations (2018) and the recent All India Council for Technical Education (AICTE) guidelines (2025). Statistical data from the Ministry of Education's ShodhShuddhi initiative and independent audits reveals a massive scale of adoption, with over 3.5 million documents scanned via state-sponsored tools.1 However, the study identifies a critical "integrity crisis" driven by Generative AI (Gen AI), with 86% of students reportedly using AI tools, challenging the efficacy of traditional detection mechanisms. The paper concludes with an assessment of the "cat-and-mouse" dynamic between detection software and AI-generated content.

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Academic Integrity, Educational Technology, Higher Education Policy, Plagiarism Detection Software

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In Ayurveda, Bala means strength, which refers to both physical and mental power, and is frequently used interchangeably with Ojas. Ojas is the subtle, vital essence or nectar of the body, the ultimate byproduct of healthy digestion and tissue formation, representing peak vitality, immunity (Vyadhikshamatva), and spiritual strength., Bala is a multifaceted concept that encompasses both physical and psychological strength, as well as the capacity developed in reaction to antigen exposure and the body's resistance to disease manifestation. Additionally, it is often used interchangeably with elements that contribute to strength, nourishment, and stability within the body, including Oja, Vyadhikshamatva, Balya, Sara, Balavriddhikara Bhava, and Prakrita Sleshma. Ojas is the component within the body that provides strength, energy, and vitality, enhances immune function, and supports overall health.This article focused on the relation beteween Oja and Bala concept in Ayurveda

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Ayurveda, Bala,Ojas, Vyadhikshamatva, Sara, Balavrudhikar Bhava

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Wildlife conservation requires consistent and accu rate monitoring of animal populations and behaviors. Tradi tional manual methods are time-consuming, error-prone, and unsuitable for large-scale ecological studies. This paper presents InstaWild, an autonomous wildlife monitoring system powered by YOLOv8 object detection and Convolutional Neural Networks (CNN) for behavior recognition. The system identifies multiple animal species including deer, elephants, and zebras, analyzes behavioral patterns, generates automated reports, and provides actionable insights for conservation professionals. The proposed framework achieves high accuracy and reliability even under variable lighting, occlusions, and environmental disturbances. The system integrates a responsive web interface built with ReactJS, a robust Flask backend, and MongoDB database for scalable data storage and retrieval. Experimental results demon strate significant improvements in species recognition efficiency and behavioral inference accuracy, establishing the system as a comprehensive digital solution for ecological monitoring and biodiversity research with practical applications for conservation teams worldwide.

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Computer Vision, YOLOv8, Wildlife Moni toring, Behavior Recognition, Conservation Technology, Deep Learning, Object Detection, Real-Time Analysis

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Abstract :- Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has become a transformative force in drug discovery and medicinal chemistry. Unlike traditional rule-based or physics-driven models, ML techniques learn directly from large datasets, enabling efficient prediction, optimization, and design of chemical structures. Early applications of AI in drug discovery mainly involved quantitative structure-activity/property relationship (QSAR/QSPR) models, which were limited by linear assumptions and sparse data. Recent advances in computing power, algorithm development, and the availability of large chemical databases such as ChEMBL have significantly expanded AI capabilities. Today, AI is widely applied in QSAR modeling, virtual screening, ADMET and toxicity prediction, and bioactivity assessment across drug development pipelines. Generative models, including recurrent neural networks and variational autoencoders, support de novo molecular design by creating novel compounds with desired properties. AI has also improved synthetic route planning through deep learning-based retrosynthesis, producing efficient and practical synthesis pathways. Additionally, active learning enhances the design-make-test cycle by reducing experimental redundancy and cost. Despite challenges related to data quality, interpretability, reproducibility, and extrapolation beyond known chemical space, AI functions best as a supportive tool that complements human expertise. Overall, AI is becoming an essential component of modern pharmaceutical research and drug development.

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Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Drug Discovery, Medicinal Chemistry, QSAR/QSPR, Virtual Screening, ADMET Prediction, De novo Molecular Design, Synthetic Route Planning, Active Learning

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Urban growth, especially small and medium-sized towns in India, is a crucial sign of socio-economic development. In Bolpur Municipality, which is situated in Birbhum district of West Bengal, this study investigates the nature and traits of urban expansion. Cultural significance of Bolpur town and its educational institutions (particularly Visva-Bharati University), and growing tourism activities have made it a significant urban centre. The study examines population growth, spatial expansion, changes in land use, and the town's functional development using secondary data from municipal sources and Census records. The results show consistent population growth, urban area development, and increasing strain on municipal services and infrastructure. The report emphasizes that to properly manage future growth, urban development must be planned and sustainable.

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Urban growth, Population growth, Spatial expansion, Land use, Urban development.

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Gastric headache, also referred to as a "stomach headache," is a functional disorder characterized by dull, throbbing frontal head pain arising from digestive disturbances such as indigestion, trapped gas, or acid reflux. The condition reflects a close connection between the gut and brain, mediated through neural pathways such as the vagus nerve, and is commonly observed in the paediatric age group. This case study presents an 8-year-old boy suffering from recurrent gastric headache associated with nausea and vomiting. Conventional and acute homoeopathic management provided only temporary relief, with recurrence of symptoms. A detailed case analysis based on homoeopathic principles of individualization led to the selection of a constitutional remedy, which resulted in complete and sustained relief without recurrence. This case emphasizes the effectiveness of constitutional homoeopathic treatment in the management of gastric headache in children.

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Gastric Headache; Homoeopathy; Alumina; Gut-Brain Axis; Paediatric Case Study; Constitutional Remedy.

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Tuberculosis, caused by Mycobacterium Tuberculosis (Mtb), is a leading cause of death, with 10.7 million new cases and 1.23 million deaths expected worldwide by 2024. The Hypoxanthine guanine phosphoribosyltransferase protein (hpt) belongs to the purine/pyrimidine phosphoribosyl transferase (PRTase) family and is used to discover active ligand molecules that inhibit the purine salvage pathway. The homology simulated 3D model was created with modeler 9.13 software. The final structure was validated, and the active site was identified using pre-requisite predictitions. The protein's three-dimensional structure consists of nine sheets and twelve helices. The grid was built on the active site, followed by virtual screening using the drug bank ligand database. The majority of the lead compounds acquired contain imidazole moieties and derivatives as pharmacophore groups in their structures. The target protein amino acid residues identified by virtual screening are Val69, Asp74, Arg77, Ile79, and Pro80, which are critical for ligand binding. The chosen lead compounds have permitted ADME characteristics and can inhibit the purine salvage pathway in Mtb. The imidazole structural scaffolds can be found in the ligand molecules of docked complexes Lig1, Lig 2, and Lig 3.

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Mycobacterium tuberculosis, Purine salvage pathway, Modeller, Virtual screening, ADME.

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Lower- or higher-education students always desire an enjoyable, dynamic, active, and vivid learning environment. Technological development and its assistance in education help offer a dynamic learning environment. Digitalization in education also brings drastic changes to the educational scene. The latest trends are artificial intelligence, augmented reality, and virtual reality. This study focuses on the extent of computer science faculty knowledge of applying the latest digital trends in education. One hundred fifty computer science faculties were selected as the sample for this study. The researcher developed the knowledge Inventory of Computer Science Faculties on AI, AR, and VR. The collected data were subjected to statistical analysis to test the formulated hypothesis. An independent sample t-test and an ANOVA were applied to the data. The study found that gender, locality of the respondent, educational qualification, and the faculty's teaching experience do not have a differential effect on their knowledge of AI, AR, and VR.

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 Keywords

Artificial intelligence, augmented reality, computer science teachers, higher education, knowledge, virtual reality

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