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Scientific basis for the preparation and characterization of iron based traditional drug annabhedi sindooram: A materialistic approach
Iron based traditional Ayurvedic drug Annabhedi Sindooram is used therapeutically for the treatment of diseases like Anaemia, Leucoderma, Prolapse of rectum and uterus, Spleenic disorders. The preparation method of iron based Indian traditional drug Annabhedi Sindooram involves conversion of a pure metal into its mixed oxide by drying and incineration. Commercially available ferrous sulphate is used as the source of iron for the preparation of Annabhedi. The structural and textural properties of the starting materials and the prepared drug were characterized systematically by different characterization techniques like PXRD, Zeta Potential Analysis, particle analysis, FTIR, ICP -AES, SEM and BET surface area analysis. The results obtained by characterization of the samples clearly explain the formation of Fe2O3, reduction in particle size, modification of surface energy and formation of metal complex with organic moieties. The strict post and pre preparation conditions followed play an important role in the morphology and medicinal activity of the drug Annabhedi Sindooram. -
Scientific competence and acquisition challenges in education managed by analytics
Integration of instructional, informational, and communication technology underpins modern higher education. After decades without computer networks, these technologies have transformed learning. E-learning has transformed the education sector, solving its problems. The similarities between technology and cognition make this change noteworthy. Artificial intelligence-inspired model-based reinforcement learning lets agents predict states and outcomes across activities and settings to modify their behaviour. The human brain has similar mechanisms, especially in model selection, which is a fascinating mystery. This study examined the brains model selection process and found that sensory prediction errors motivate the brain to choose between computational models. The theory was contrasted with internal modelling and incentive predictive performance to show how prediction errors influence computational model selection. The brain can choose an internal validation learning model based on incentive prediction mistakes, as empirical evidence demonstrates that the policy gradient method matches these models. These models were intended to address higher education issues like administration, academic delivery, instructional design, and ethics. The report also suggested that e-learning could help solve industry issues like student concentration on campuses, brain drain, and resource shortages. This research shows how technology can change higher education and the future of learning. Copyright 2025 Inderscience Enterprises Ltd. -
Scientific Social Responsibility: A Means to Sustainability and Environmental Fairness
Science and scientific research lead any country in its journey of progress. At some point in history there are instances where scientific discoveries resulted in global disasters. We are living in an era of enormous threats to sustainable development. Multitudes of our brethren remain to live in poverty and are denied a life of dignity. There are growing disparities within and among nations. This made a rethinking on the entire process of scientific education and research in terms of its social commitment which resulted in government of India coming up with a policy document. This paper takes a close look at this policy document released by the department of science and technology government of India apart from looking at some of the global practices and suggestions. 2026 National Science Teaching Association. -
SCN1A Genetic Alterations and Oxidative Stress in Idiopathic Generalized Epilepsy Patients: A Causative Analysis in Refractory Cases
Single Nucleotide Polymorphisms (SNPs) have found it be associated with drug resistance in epilepsy. The purpose of this study was to determine the role of SCN1A gene polymorphism in developing drug resistance in idiopathic generalized epilepsy (IGE) patients, along with increased oxidative stress. The study was conducted at a tertiary care hospital in Delhi, India. We recruited 100 patients diagnosed with IGE patients, grouped as drug-resistant and drug-responsive, and then further compared the SCN1A SNP rs10167228 A*/T analysis between the two groups. We utilized the PCR-RFLP technique to investigate the association between polymorphisms and refractory epilepsy. Serum HMGB1 levels were estimated using the ELISA technique to analyze oxidative stress in both groups. rs10167228 A*/T polymorphism genotypes AT and AA genotypes are significantly associated with an increased risk of developing drug resistance. Serum HMGB1, IL-1?, and IL-6 levels were significantly higher in drug-resistant cases, compared to the drug-responsive group. The association of SCN1A gene polymorphisms, in conjunction with raised oxidative stress, may be predictive of the development of drug-resistant epilepsy. The AT and AA genotypes of rs10167228 may pose a risk factor for developing drug-resistant epilepsy. 2023, The Author(s), under exclusive licence to Association of Clinical Biochemists of India. -
SCN1A Genetic Alterations and Oxidative Stress in Idiopathic Generalized Epilepsy Patients: A Causative Analysis in Refractory Cases
Single Nucleotide Polymorphisms (SNPs) have found it be associated with drug resistance in epilepsy. The purpose of this study was to determine the role of SCN1A gene polymorphism in developing drug resistance in idiopathic generalized epilepsy (IGE) patients, along with increased oxidative stress. The study was conducted at a tertiary care hospital in Delhi, India. We recruited 100 patients diagnosed with IGE patients, grouped as drug-resistant and drug-responsive, and then further compared the SCN1A SNP rs10167228 A*/T analysis between the two groups. We utilized the PCR-RFLP technique to investigate the association between polymorphisms and refractory epilepsy. Serum HMGB1 levels were estimated using the ELISA technique to analyze oxidative stress in both groups. rs10167228 A*/T polymorphism genotypes AT and AA genotypes are significantly associated with an increased risk of developing drug resistance. Serum HMGB1, IL-1?, and IL-6 levels were significantly higher in drug-resistant cases, compared to the drug-responsive group. The association of SCN1A gene polymorphisms, in conjunction with raised oxidative stress, may be predictive of the development of drug-resistant epilepsy. The AT and AA genotypes of rs10167228 may pose a risk factor for developing drug-resistant epilepsy. The Author(s), under exclusive licence to Association of Clinical Biochemists of India 2023. -
Scope and Future Trends in 6G
Imagine a cosmos where your devices communicate with each other at light speed, remote medical procedures take place effortlessly, and entire cities function seamlessly with interconnected, intelligent systems. Such is 6G, a preview of what the forthcoming wireless communication technology revolution will encompass. With 5G only just starting to be rolled out globally, researchers and technology leaders are already involved in a frantic race to create 6G, a network that will offer even faster speeds, nearly zero latency, and flawless integration for artificial intelligence (AI) and quantum computing. This chapter, Scope and Future Trends in 6G, will investigate thoroughly what distinguishes 6G from its predecessors, its fundamental technologies driving it, and its impacts in the real world. Looking ahead to the prospective future of this innovative technology, we will also consider how it can be utilized responsiblyhow its advancement can be aligned with human progress with the least damage to our planet possible. 2025 by IGI Global Scientific Publishing. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. -
SCREEN TIME BEYOND GAMING AND SOCIAL MEDIA: EXCESSIVE AND PROBLEMATIC USE OF OVER THE TOP (OTT) PLATFORMS AMONG COLLEGE STUDENTS DURING COVID-19 PANDEMIC
There is a gap in existing literature regarding Over the Top (OTT) platform use contributing to the excessive and problematic screen time. We aimed to assess OTT platform use among college students and its associations with increased screen time, mental well-being, COVID-19 related anxiety and personality traits. A total of 1039 students from a college in India were invited to participate in this web-based survey. A majority of participants used OTT platforms regularly. Subscription to paid OTT platforms, poor mental well-being were associated with problematic OTT use; whereas personality trait of conscientiousness seemed to offer protection against problematic OTT use. 2021 Medicinska Naklada Zagreb. All rights reserved. -
Screen Time to Severity: Machine Learning Models for Teen Smartphone Dependency Prediction
This study presents a systematic comparison of fourteen supervised classifiers trained to predict binned smartphone addiction levels (Low/Medium/High) in a cohort of 300 teenagers, using demographic, usage, academic, and health related features. After cleaning and binning the continuous Addiction_Level score into three categories, we encoded all categorical variables and standardized inputs, then stratified into 80 % training and 20 % test splits. Our expanded model suite comprised: Logistic Regression, Gaussian Naive Bayes, K-Nearest Neighbors, Decision Tree, Random Forest, Extra Trees, AdaBoost, Gradient Boosting, XGBoost, LightGBM, CatBoost, Support Vector Machine, and a multilayer perceptron (MLP). Each classifier was evaluated on accuracy, precision, recall, macro-averaged F1-score, and multiclass ROC AUC; confusion-matrix entries were flattened into nine 'Actual_i to Pred_j' columns per model for granular error analysis. Logistic Regression achieved the highest test accuracy (98.83%) , outstanding ROC AUC (0.9982) and perfect precision in discriminating the majority class ('High' addiction), despite modest recall for minority classes. MLP followed (96.33 % accuracy, 0.9878 AUC), indicating that a shallow neural network can capture nonlinear patterns but struggles on underrepresented labels. Gradient Boosting, CatBoost, and LightGBM all exceeded 95% accuracy with strong F1-scores (?0.72-0.73) and AUCs above 0.96, demonstrating the power of tree-based ensembles on mixed data types. Simpler methods (e.g., GaussianNB, KNN, Decision Tree) performed moderately (86-91% accuracy, AUC 0.84-0.98), while AdaBoost lagged (77.5 % accuracy, AUC 0.867), suggesting sensitivity to noisy features. Confusion-matrix summaries revealed that most models rarely misclassify Low-addiction teens, but confusion arises between Medium and High classes important for targeted interventions. 2025 IEEE. -
Screening, isolation, characterization, and optimization of BSH activity from potential probiotic isolates from various sources
Bile salt hydrolase (BSH)-producing probiotics can assimilate cholesterol from the body through de novo synthesis. The BSH enzyme was found in 23 of 513 isolates accessed from various sources. Five of the 23 BSH-positive strains have been selected for further study, based on their BSH activity, compared to two positive controls, Lactobacillus acidophilus and Enterococcus lactis. The Grams nature of the strains was determined and further examined for hemolytic activity, gelatinase, and catalase assay as per Indian Council for Medical ResearchDepartment of Biotechnology recommendations. Two Enterococcus faecalis (CGz3 and CGz4) strains with ?-hemolytic, negative catalase, and gelatinase activity are selected for probiotic characterization, evaluating the organisms surface hydrophobicity, autoaggregation tests, tolerance to lysozyme, gastric acidity, bile salt and gastric juices (pepsin and pancreatin). The strain which withstands the harsh gastrointestinal conditions was considered for further experiments. To establish a standardized method to quantify the BSH activity of the potential probiotic isolate, substrate utilization was performed by screening sodium glycocholate (GCA) and taurocholic acid (TCA) at different concentrations. The optimal BSH activity was observed at the 16th hour and 0.1% (v/v) GCA. Based on the standardized protocol, factorial optimization of process parameters, such as pH, inoculum percentage, temperature, and revolutions per minute (RPM) was carried out for increased BSH activity. The optimal BSH activity was observed at pH 5.5 and 1% inoculum (v/v). The highest BSH activity was obtained at 40C and 200 RPM. Among the other BSH-positive strains, E. faecalis CGz3 shows the best probiotic potential. The strain would be further studied for its ability to alleviate symptoms associated with non-alcoholic fatty liver disease (NAFLD), using a cell line-based study and associated gene regulation. In conclusion, E. faecalis CGz3 would have the potential to be used as a dietary supplement to treat metabolic disorders, such as hypercholesterolemia and NAFLD/metabolic-associated fatty liver disease. 2025 Koushik Koujalagi and Alok Kumar Malaviya. -
Screens and scars: SEM analysis of the relationship between childhood trauma, emotion regulation, and social media addiction
Background: Addiction is an increasingly significant global public health concern, affecting individuals across diverse age groups and demographics. With the rapid rise of digital technology, social media addiction has emerged as a growing behavioral issue, impacting mental health, interpersonal relationships, and daily functioning. Methods: This study employed an online cross-sectional self-report questionnaire, with university students aged 1635?years as the target population. Data were collected using Google Forms questionnaires, accessible via the university registration system, and sent to the participating students smart phones. The data collection instruments included the Social Media Addiction Scale (SMAS), the Childhood Trauma Scale (CTS), and the Difficulty in Emotion Regulation Scale (DERS). Results: Data from 318 university students were analyzed. The analysis of sociodemographic data revealed a mean participant age of 21.2?years, with 87.3% being female. An analysis of the relationship between social media addiction and childhood trauma revealed that participants with childhood trauma had higher social media addiction. The linear regression model, including childhood traumas and emotion regulation difficulties for social media addiction scores, was statistically significant. A positive correlation was observed between social media addiction and difficulty in emotion regulation. Conclusion: These findings suggest that individuals who struggle with emotion regulation tend to use social media more frequently. Furthermore, the negative effects of childhood trauma on emotion regulation capabilities during adulthood contribute to the development of social media addiction. Copyright 2025 Elkin, Mohammed Ashraf, K?l?nl, K?l?nL, Ranganathan, Sakarya and Soydan. -
Screens and scars: SEM analysis of the relationship between childhood trauma, emotion regulation, and social media addiction
Background: Addiction is an increasingly significant global public health concern, affecting individuals across diverse age groups and demographics. With the rapid rise of digital technology, social media addiction has emerged as a growing behavioral issue, impacting mental health, interpersonal relationships, and daily functioning. Methods: This study employed an online cross-sectional self-report questionnaire, with university students aged 1635?years as the target population. Data were collected using Google Forms questionnaires, accessible via the university registration system, and sent to the participating students smart phones. The data collection instruments included the Social Media Addiction Scale (SMAS), the Childhood Trauma Scale (CTS), and the Difficulty in Emotion Regulation Scale (DERS). Results: Data from 318 university students were analyzed. The analysis of sociodemographic data revealed a mean participant age of 21.2?years, with 87.3% being female. An analysis of the relationship between social media addiction and childhood trauma revealed that participants with childhood trauma had higher social media addiction. The linear regression model, including childhood traumas and emotion regulation difficulties for social media addiction scores, was statistically significant. A positive correlation was observed between social media addiction and difficulty in emotion regulation. Conclusion: These findings suggest that individuals who struggle with emotion regulation tend to use social media more frequently. Furthermore, the negative effects of childhood trauma on emotion regulation capabilities during adulthood contribute to the development of social media addiction. Copyright 2025 Elkin, Mohammed Ashraf, K?l?nl, K?l?nL, Ranganathan, Sakarya and Soydan. -
Scribble and Learn-A Leaner Centric Approach
This innovative practice full paper describes a creative learning method that support collaborative, creative visual leaning by improving the happiness index in classroom environment. Teamwork and creativity are limited in traditional classrooms that emphasize individual learning and technology dependence. This study offers 'Scribble and Learn,' a novel instructional tool for Cognitive Psychology and artificial intelligence courses to fill this need. 'Scribble and Learn' uses unique scribbling to encourage active participation and collaboration. Team research with limited technology is done by students. This constraint promotes teamwork and communication as they uncover and study memory performance determinants. Teams use keywords and images to communicate their findings on a huge writing surface after this research phase. This 'scribbling' approach accommodates varied learning styles and stimulates creative knowledge expression, creating a dynamic learning environment beyond lectures. Teams present and discuss their findings in a moderated class discussion. This conversation improves Cognitive Psychology and AI memory performance theory knowledge. 'Scribble and Learn' improves teamwork, creativity, and memory. Positive student feedback shows that the exercise promotes active learning and participation. In a class discussion that is moderated, teams present and discuss the discoveries that they have uncovered. The knowledge of cognitive psychology and artificial intelligence memory performance theory is improved by this discourse. The fact that the activity gets positive feedback from students demonstrates that it encourages active learning and involvement. 2025 IEEE. -
Scripts About Happiness Among Urban Families in South India
The ways in which parents socialize positive emotions have important implications for youth wellbeing, though little is known about parental goals and responses to adolescents happiness in culturally diverse families. Using an open-ended qualitative methodology, we explored parent and adolescent views about situations leading to happiness, responses and justifications to the expression of happiness, and what parents would like to teach their children about happiness in a sample of 209 parent (56.3% fathers; Mage = 42.79years) and adolescent (85.2% girls, Mage = 14.95years) dyads in Bengaluru, India. When prompted to identify adolescents recent experiences of happiness, both parents and adolescents primarily described academic and extracurricular achievements, followed by special events and receipt of tangible items, social interactions, and overcoming difficult situations. The two most common parent responses to adolescents happiness were responding with appreciation or encouragement of the achievement and providing further instruction or advice, with fewer responses focusing on enhancing/maintaining the emotional state of happiness itself. A substantial proportion of participating parents reported that their child should focus on task improvement when feeling happy, followed by affect maintenance (i.e., the child should be happy), or express their emotion with restraint. The findings contribute to developing a culturally-informed understanding of socialization of happiness in diverse families. 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Scripts influence on reading processes and cognition: a preamble
[No abstract available] -
Scrutinization of joule heating and viscous dissipation on MHD flow and melting heat transfer over a stretching sheet
The present paper deals with an analysis of the combined effect of Joule heating and viscous dissipation on an MHD boundary layer flow and melting heat transfer of a micro polar fluid over a stretching surface. Governing equations of the problem are transformed into a set of coupled nonlinear ordinary differential equations by applying proper transformations and then they are solved numerically using the RKF-45 method. The method is verified by a comparison with the established results with limiting solution. The influence of the various interesting parameters on the flow and heat transfer is analyzed in detail through plotted graphs. 2018 K.G. Kumar et al., published by Sciendo. -
Scrutinization of thermal radiation, viscous dissipation and Joule heating effects on Marangoni convective two-phase flow of Casson fluid with fluid-particle suspension
The impact of Marangoni convection on dusty Casson fluid boundary layer flow with Joule heating and viscous dissipation aspects is addressed. The surface tension is assumed to vary linearly with temperature. Physical aspects of magnetohydrodynamics and thermal radiation are also accounted. The governing problem is modelled under boundary layer approximations for fluid phase and dust particle phase and then Runge-Kutta-Fehlberg method based numeric solutions are established. The momentum and heat transport mechanisms are focused on the result of distinct governing parameters. The Nusselt number is also calculated. It is established that the rate of heat transfer can be enhanced by suspending dust particles in the base fluid. The temperature field of fluid phase and temperature of dust phase are quite reverse for thermal dust parameter. The radiative heat, viscous dissipation and Joule heating aspects are constructive for thermal fields of fluid and dust phases. The velocity of dusty Casson fluid dominates the velocity of dusty fluid while this trend is opposite in the case of temperature. Moreover qualitative behaviour of fluid phase and dust phase temperature/velocity are similar. 2018 -
Scrutiny In-Utero to recognize Fetal Brain MRI Anomalies
In utero MRI distinguishes fbrain irregularities high precisely compared to ultrasonography as well as gives extra medical data during the pregnancies. fMRI is medically performed to get the knowledge of the brain in conditions where the inconsistency are perceived with the help of pre-birth sonography. These are common regularly solidify ventriculomegaly, not regular of the corpus callosum, and oddities of the back fossa. Fbrain inconsistencies can cause authentic brain hurt. Therefore, it is vital to recognize them from the get-go in their course so treatment can be managed to the mother, if conceivable. The job of imaging is to decide the presence, assuming any, and the degree of brain harm in the contaminated hatchling. Even though MRI is most generally utilized as a subordinate to sonography when clinical doubt is high in the setting of a typical ultrasound or to all the more likely characterize irregularities recognized by ultrasound, MRI is regularly utilized in toxoplasmosis seroconversion to conclusively preclude brain injuries, in any event, when the ultrasound examination is viewed as ordinary. X-ray is likewise utilized sequentially all through the pregnancy to check for the improvement of brain anomalies; clinical treatment brings about the astounding clinical result if the brain is typical. Intracranial irregularities are ordinarily speculated discoveries on antenatal US that are needed for assessment which is used by MRI. This audit portrays numerous irregularities imaged as a way to direct clinicians' inappropriate determination. 2021 IEEE. -
SCSLnO-SqueezeNet: Sine Cosine-Sea Lion Optimization enabled SqueezeNet for intrusion detection in IoT
Security and privacy are regarded as the greatest priority in any real-world smart ecosystem built on the Internet of Things (IoT) paradigm. In this study, a SqueezeNet model for IoT threat detection is built using Sine Cosine Sea Lion Optimization (SCSLnO). The Base Station (BS) carries out intrusion detection. The Hausdorff distance is used to determine which features are important. Using the SqueezeNet model, attack detection is carried out, and the network classifier is trained using SCSLnO, which is developed by combining the Sine Cosine Algorithm (SCA) with Sea Lion Optimization (SLnO). BoT-IoT and NSL-KDD datasets are used for the analysis. In comparison to existing approaches, PSO-KNN/SVM, Voting Ensemble Classifier, Deep NN, and Deep learning, the accuracy value produced by devised method for the BoT-IoT dataset is 10.75%, 8.45%, 6.36%, and 3.51% higher when the training percentage is 90. 2023 Informa UK Limited, trading as Taylor & Francis Group.