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Phytochemicals and Biological Activities of Flowers of Hibiscus x rosa-sinensis (Chinese Rose)
The flowers of Hibiscus rosa-sinensis L., are a flowering shrub of Malvaceae family. The plant is commonly known as a Chinese rose or shoe flower. The plant is distributed in the tropical and sub-tropical regions of the world and crossing has led to a large number of cultivars with varying patterns in size, shape, and colour. This chapter provides a comprehensive analysis of the distribution, traditional uses, phytochemical composition, and diverse biological activities associated with the flowers of this ornamental plant. The flowers have played a significant role in various traditions, as a remedy for various ailments and as a source of food. A rich profile of bioactive compounds was observed during phytochemical phytochemical investigations. These bioactive compounds included anthocyanins, flavonols, flavan-3-ols, flavanonols, flavanone, flavones, other phenolic compounds, essential oil, etc. which contributed to the medicinal properties of the flowers. The flower extracts demonstrated various biological activities like Hypolipidemic, Cardioprotective, Hypotensive, Anticancer, Antidiabetic, Cytotoxicity, Antimutagenic, Larvicidal, Anti-inflammatory, Anticonvulsive, Wound Healing, Hepatoprotective, Antioxidant, Antimicrobial, Antifertility, Antispermatogenic, antipyretic among other activities. This chapter bridges ethnopharmacological knowledge with scientific research, showcasing the potential of H. rosa-sinensis flowers in the development of novel therapeutic drugs as well as natural product development. 2026 Hosakatte Niranjana Murthy. -
A study on induced path decompositions of graphs
A graph is a discrete structure consisting of a set of objectscalled vertices and another set of objects called edges depicting the relationship between pairs of vertices. Therefore, graphs serve as effective models to study networks of all types such as computer networks, telecommunication networks and social networks. The concept of a graph possesses the unique combination of features like simplicity, visibility, beauty, clarity, elegance and effectiveness
in studying problems dealing with network structures. It might be a simple structure like that of an organizational structure in a college, a complex structure like the world wide web (www) or just an abstract structure consisting of objects that are inter-connected according to some rule. -
Green Synthesis of Nano Carbon-Infused Polymer for The Detection of Toxic Heavy Metals
The global population is marching towards greener ways of life. Green nanotechnology, newlinewhich uses carbon nanomaterials for environmental remediation, is the pioneer among the existing strategies for the production, characterization, and applications of carbon nanomaterials derived from sustainable and renewable energy resources. Additionally, easily available natural ingredients are effective carbon precursors for producing carbon dots with newlineenthralling physical and chemical properties. Compared to other approaches, plant-based newlinesynthesis of nanomaterials is more dependable because it is simple, fast, ecologically newlinefriendly, and does not require particular conditions. We report for the first time, the use of a fluorescent nanocarbon material synthesised from plant, Indigofera Tinctora (L.) (IBLH), for the detection of metal ions. This nanomaterial developed using a green synthesis method that aided hydrothermal processing from the leaf extract of IBLH. The IBLH sensor used to detect hazardous metal ions (Pb2+) was very sensitive and selective. Considering the concentration from 1 nM to 100 mM and 100 mM to 1M, developed sensor displayed broad, dual linearity. The limit of detection (LOD) for the sensor appreciable low with 14.74 nM as the detection limit, with a wide and linear response spanning from 1 nM to 1M Cd2+ concentration range. Utilising Ruta Graveolens as the carbon source, we developed ARH-CDs from agricultural waste using chemical-free, one-step hydrothermal procedures that are safe for the environment. The synthesized ARH-CDs showed nano particle size, outstanding water newlinesolubility, great biocompatibility, and appreciable optical characteristics. The FTIR and XPS findings validated the existence of functional groups. such as C-O, C-C, and O-H with various oxygen functional groups, with predominating hydroxyl group, supporting the newlineexistence of CDs. For the selective detection of Hg2+, the synthesized ARH-CDs are employed as a biocompatible fluorescence sensor. -
Development of Green Synthesized Novel Carbon Dots from Ruta Graveolens L. for Fluorescent and Intracellular Sensing of Mercury Ions in Pico-molar (pm) Concentration
Green nanotechnology, which uses carbon nanomaterials for environmental remediation, is the pioneer among the prevailing approaches for the production and characterization. In the present study, highly fluorescent carbon dots (CDs) from Ruta Graveolens (ARH-CD) is developed, and its efficacy as a fluorescent sensor and biomarker is investigated. They act as a fluorescence sensor for Hg2+ over an extensive concentration range of 1 picomolar (pm) to 1 molar (m), with a detection limit as low as 26.75 pm. The studies reveal ARH-CD as an effective biomarker for intracellular toxicity analysis and a fluorescent probe for multi-colored (blue, green, and red) imaging of HEK293 cell lines. After 24 h of incubation, it is found that the ARH material reveals noticeable biocompatibility and visible fluorescence, with a viability of 98.88% at 5 gmL?1 and over 78.33% even at a concentration of 100 gmL?1. The IC50 value for the MTT assay for cell viability results is calculated to be 224.56 4.67 g, which further confirms the appreciable biocompatibility of the ARH-CD. The obtained samples are effective in being inspected for the intracellular detection of Hg2+ and serve as a possible candidate for cell imaging. 2024 Wiley-VCH GmbH. -
A predictive system for determining the probability of transfer of viruses from animals to humans /
Patent Number: 202141012175, Applicant: Rajesh R.
The study of viruses transmission from animal to human beings is vital since more outbreaks are happing frequently and from a veterinary viewpoint these viruses causes diseases that are economically devastating. The emergence of animal virus in the human population seeks the importance of animals in harbouring infectious agents. Zoonosis is the scientific term referring to any diseases that are transmitted to people by animals. -
Hijab row verdict in India: A sentimental analysis of user responses on Facebook
The hijab controversy, a hot topic in India since January 2022, emerged from a clash between students and college authorities in Karnataka, a state in India. The dispute made its way to Karnatakas High Court, which, on 15 March 2022, ruled that the hijab was not mandatory for religious practices. This decision stirred widespread debates, especially on social media platforms like Facebook. This study is focused on user reactions in The Times of India Dailys official Facebook page, employing sentiment analysis to decipher public emotions, attitudes, and opinions. Nearly 200 comments posted on the verdict day were analyzed, utilizing the routine activity theory (RAT), spiral of silence theory, and online disinhibition effect. The research introduced a unique model, RAT+A, to enhance analysis. As a significant platform for public discourse, Facebook played a crucial role in capturing diverse societal sentiments and reactions regarding this social issue. 2025, First Monday. All rights reserved. -
UVIT data release version 7: Regenerated high-level UVIT data products
Ultra-Violet Imaging Telescope (UVIT) on board AstroSat is an active telescope capable of high-resolution far-ultraviolet imaging (<1.5??) and low-resolution (?/???100) slitless spectroscopy with a field-of-view as large as ? 0.5?. Now almost a decade old, UVIT continues to be operational and generates valuable data for the scientific community. UVIT is also capable of near-ultraviolet imaging (<1.5??); however, the near-ultraviolet channel stopped working in August 2018 after providing data for nearly 3years. This paper gives an overview of the latest version (7.0.1) of the UVIT pipeline and UVIT data release version 7. The high-level products generated using pipeline versions having a major ver. no. 7 will be called UVIT data release version 7. The latest pipeline version overcomes two limitations of the previous version (6.3), namely: (a) inability to combine all episode-wise images; and (b) failure of the astrometry module in a large fraction of the observations. The procedures adopted to overcome these two limitations as well as a comparison of the performance of this new version over the previous one, are presented in this paper. The UVIT data release version 7 products are available at the Indian Space Science Data Center of the Indian Space Research Organization for archival and dissemination from 1 June 2024. New pipeline version is open source and made available on GitHub. Indian Academy of Sciences 2025. -
JivaCare: A Smart Health Care Application Integrating Home Remedies for Holistic Well-Being
JivaCare is a smart health care application that aims to diagnose common illnesses and recommend home remedies by leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). Initially, a custom dataset of diseases and symptoms was used to develop a disease-diagnoses chatbot. However, challenges such as limited accuracy and rigid disease-symptom mapping were identified. To address these, GPT-3.5 API was integrated via RapidAPI, enhancing conversational quality without requiring extensive training while improving response quality. A MySQL database was implemented to store conversational history and session-based memory. Subsequently, the focus transitioned to a text classification approach using a 5,634-sample dataset from HuggingFace. This enabled flexible symptom-to-disease classification, overcoming the limitations of the initial dataset. Five machine learning models were evaluated, with Logistic Regression achieving the highest accuracie of 85 % after fine-tuning its hyperparameters. Additionally, neural network architectures such as GRU, RNN and CNN were also employed, achieving validation accuracies of 76%, 82% and 84%, respectively. The results demonstrate the effectiveness of integrating ML and deep learning techniques for accurate disease prediction and remedy recommendation. This work can establish the foundation for a scalable and user-friendly healthcare system, bridging the gap between AI and personalised natural health benefits. 2025 IEEE. -
JivaCare: A Smart Health Care Application Integrating Home Remedies for Holistic Well-Being
JivaCare is a smart health care application that aims to diagnose common illnesses and recommend home remedies by leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). Initially, a custom dataset of diseases and symptoms was used to develop a disease-diagnoses chatbot. However, challenges such as limited accuracy and rigid disease-symptom mapping were identified. To address these, GPT-3.5 API was integrated via RapidAPI, enhancing conversational quality without requiring extensive training while improving response quality. A MySQL database was implemented to store conversational history and session-based memory. Subsequently, the focus transitioned to a text classification approach using a 5,634-sample dataset from HuggingFace. This enabled flexible symptom-to-disease classification, overcoming the limitations of the initial dataset. Five machine learning models were evaluated, with Logistic Regression achieving the highest accuracie of 85 % after fine-tuning its hyperparameters. Additionally, neural network architectures such as GRU, RNN and CNN were also employed, achieving validation accuracies of 76%, 82% and 84%, respectively. The results demonstrate the effectiveness of integrating ML and deep learning techniques for accurate disease prediction and remedy recommendation. This work can establish the foundation for a scalable and user-friendly healthcare system, bridging the gap between AI and personalised natural health benefits. 2025 IEEE. -
Predicting Stock Market Trends: Machine Learning Approaches of a Possible Uptrend or Downtrend
This paper delves into a statistical analysis of the stock market, emphasizing the significance of accuracy in stock predictions. Large data sets can be handled by machine learning algorithms, which can also forecast outcomes based on past data and spot intricate patterns in financial data. They assist control risks, automate decision-making procedures, and adjust to changing circumstances. Multi-source data can be combined by ML models to provide a comprehensive picture of market circumstances. They can manage intricate, nonlinear interactions, provide impartial analysis, and lessen human bias. Models are able to adjust to shifting market conditions through ongoing learning and retraining. They must, however, exercise caution when deploying models in real-world situations and ensure that they are validated. Although machine learning has advantages for stock market analysis, it must be carefully evaluated for dangers and validated before being used in practical situations. The traditional machine learning model, Logistic Regression has been used in order to predict stock prices. It focuses on binary classification based on the trend of the stock. Through the model training and evaluation and additional analysis done on the results, this research contributes towards obtaining predictions and studying reasons of a possible uptrend or downtrend to further assist companies. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A mixed methods study on factors associated with relapse of alcohol use disorder
Background: Alcohol use disorder (AUD) is one of the most concerning mental health issues in India. According to the recent survey, Magnitude of Substance Use in India, 2019, 160 million of the countrys population consumes alcohol. About 35.6% are problem drinkers among those who drink, of which 18% are alcohol dependent. Despite the greater understanding of alcohol use disorder (AUD) and the scientific advancements in treatment, relapse remains to be the main challenge in managing AUD. This study aimed at investigating various factors associated with relapse of AUD and presenting an in-depth understanding of it. Methods: A Sequential Explanatory Mixed Methods design was used. In the quantitative phase, 72 relapsed individuals with AUD currently undergoing treatment were compared with 72 individuals previously treated for AUD who maintain total abstinence for a minimum period of one year. Relapsed participants were selected from three private de-addiction centers in Bangalore and abstaining participants were recruited from various Alcoholics Anonymous meetings in Bangalore. The relapsed and sober groups were matched on gender, AUD diagnosis, and previous inpatient alcohol de-addiction treatment. Cloninger's Temperament and Character Inventory-Revised was used to assess the personality profiles of the participants. A sociodemographic and clinical information form was also used to collect data. Six participants were selected purposively from the same sample for in-depth interviews. Data analysis was conducted using SPSS and NVivo for quantitative and qualitative data, respectively. The study protocol was approved by the institutional ethics committee. Results: Bivariate analyses showed a significant difference in Novelty Seeking, Persistence, Self-Directedness, and Self-Transcendence traits between the relapsed and sober participants. Results also suggested that reported use of other substances, post- discharge follow-ups, and living with drinking or drug-using individuals are significantly associated with relapse. Logistic regression displayed incomplete treatment, use of other substances, and no post-discharge follow-up as predictors of relapse. The qualitative thematic analysis revealed preparedness, motivation, personal exceptionalism, meaning and purpose, and social and interpersonal as the main relapse-related themes. Conclusions: The findings highlight the importance of treatment engagement, discharge planning, aftercare, and special attention to those presenting with multiple substance use. It also displays a few culture-specific aspects to be considered during treatment, such as preparing the individuals entering treatment to effectively engage, assessing and working with their motivation, and addressing the relationship dynamics. -
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Effectiveness of the Services Delivered by Special Schools for Children with Intellectual Disability
Special schools are the most widespread in the country among the various models for the education of children with intellectual disabilities. In India, there are large number of special schools for children with intellectual disabilities, implementing special education programme using various methods and materials. The present research attempts to determine the effectiveness of special schools rendering services for children with intellectual disability. A comprehensive understanding of the practices followed by different special schools would provide more insight into the functioning of special schools that serve children with intellectual disability. This study explores the various practices in special schools and the progress of children in self-care, behaviour and communication after receiving special education. The study also focused on understanding the progress of children with mild, moderate, and severe intellectual disability. The study used mixed research method. A causal design was used to assess special schools' effectiveness with a focus on self-care, behaviour, and communication of children. Both quantitative and qualitative method of data collection and interpretation were done to conclude the study. The self-structured interview schedule was used for qualitative research and collected information from 12 special schools. Cases were developed based on the qualitative data. Within-case and cross-case analysis with thematic analysis were used for analyzing the data. Quantitative data was collected from caretakers of 98 children, using a standardized tool Behavioural Assessment scale for Indian Children with Mental Retardation (BASIC- MR). The impact of special education on the self-care, communication and behaviour of Children with Intellectual Disabilities were analyzed with Wilcoxon Signed Rank test using the baseline data and their progress of the children after five years in special school. The result shows that there are changes in behaviour, self-care and communication of children with ID after they joined special school. The results also highlighted that there is a difference in children's progress based on the level of intellectual disability (mild, moderate and severe). The qualitative analysis explained the best practices exhibited by special schools for children with ID. -
Understanding the impact of designs in visual aids in education /
Visual aids have played a significant role in understanding various messages. Visual aids serve as multipurpose effective tool in understanding concepts that are complex in nature. Not only does visual aids serve as classroom technique in the field of education but also enable the designers to collaborate with the academicians to create deigns that would bridge the gap between study material and better understandings. -
Psychosocial Well-Being of Adolescents : A Social Group Work Intervention
Social work practice with children and families is one of the most challenging, skilled and rewarding areas of social work practice. Social workers believe that safeguarding children and preventing them from significant harm is a rewarding and challenging way to make a difference in the life of a child, which involves the corporation, consultation and collaboration of many people working effectively together. As highlighted by the United Nations' data disaggregation against the goal of "no one left behind," the absence of data on adolescents needs research on the "second decade." Furthermore, because India has the world's largest adolescent population, studies and policies aimed at developing adolescents' competencies are critical to the country's development; interventions aimed at instilling confidence in underprivileged adolescents to strive for a better future are critical for mitigating inequity. Adolescents from disadvantaged families and whose parents are no longer able to provide adequate care to children are having various psychosocial problems, high risk of violence, exploitation, abuse and neglect and their psychosocial well-being is often insufficiently monitored. This intervention study adopted a quasi-interventional design to measure the effectiveness of social group work in raising the psychological well-being, self-esteem and coping orientation of adolescents in child sponsorship programs. Social group work intervention with 20 sessions was designed in response to the information garnered through the pilot study and administered to the intervention group (n=20). Conducted pre-test and post-test for both intervention group and control group (n=20) and two follow up tests in three months intervals for the intervention group (n=20) using 42 item version of Ryffs scale for psychological well-being, Rosenbergs 10 item self-esteem scale and 54 items A-COPE scale; and data analyzed using SPSS. Comparison between pre and post measurements carried out using paired sample t-test for the intervention group and control group separately, gave out a p value < 0.05 for the intervention group and, > 0. 05 for the control group. Thus, it was proved that the psychological well-being, self-esteem and coping orientation of participants in the intervention group were raised significantly due to the social group work intervention. Applying refined granularity, this research adds data specifically on adolescents enrolled in child sponsorship programs and sets a blueprint for social group work to raise their psychological well-being, self-esteem and coping orientation. Proposing a conceptual framework for child sponsorship programs, this study recommends the need for operational tie-ups, sustained youth support, training of trainers (ToT) for community animators, preparing individual care plans and training to school social workers and the need of starting walk-in counselling centres and mentoring services. Furthermore, this study suggests additional research in all aspects of its operation, as well as interventions at the group, family, and community levels, for the well-being and empowerment of marginalised adolescents. -
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From Vulnerabilities to Social Protection for Migrant Workers: Exploring the Missing Links
The article attempts to explore the formal and informal social protection strategies available to the migrant workers in Kerala in the context of the vulnerabilities faced by them. We conducted in-depth qualitative interviews with plywood industry workers in Ernakulam district, which accounts for the highest proportion of migrant workers in Kerala. The narratives obtained from the plywood workers reveal their workplace vulnerabilities, highlighting the failure of private capital in providing decent work and social protection. The Kerala government has attempted to bridge the gap by extending social protection schemes like Aawaz and Roshni exclusively for the welfare of migrant workers. These programmes highlight a progressive approach to policy, recognising these workers as a distinct group within the social protection framework. However, there are some gaps in the implementation of these schemes owing to inadequate coverage, institutional barriers and language constraints. Findings from the study suggest that a comprehensive and collaborative approach must involve an active role of the employer, along with state support, to address the vulnerabilities of the migrant workers. 2026 Institute for Human Development -
Impact of Integrated Explicit Instruction on Development of Critical Thinking Skills and Dispositions among Adolescents
Critical thinking is an essential skill that is required for survival in the twenty first newlinecentury. Educational institutions are gearing up to align their curriculum to ensure the development of critical thinking skills and dispositions among their candidates. However, there are few empirical studies that layout a clear road map of instructional strategies for the teaching of critical thinking. Given that adolescents are the most receptive to neurobiological skill and disposition development and that Literature is one of the best platforms that connects to real life, this research uses the educational design research method to develop an Integrated Explicit Instruction (IEI) module that could be used in English classes to teach adolescents critical thinking skills and develop in them critical thinking dispositions. This research not only bridges the gap in an empirically tested instructional strategy to teach critical thinking but also lays the foundation for further longitudinal studies that could measure the development of critical thinking skills and dispositions long term in participants who have been exposed to the intervention. -
Design and development of an efficient model for handwritten modi script recognition
Machine simulation of human reading has caught the attention of computer science newlineresearchers since the introduction of digital computers. Character recognition, a branch of pattern recognition and computer vision, is the process of identifying either printed or handwritten text from document images and converting it into machinecoded text. Character recognition has been successfully implemented for various foreign language scripts like English, Chinese and Latin. In the case of Indian language scripts, the character recognition process is comparatively difficult due to various complexities such as the presence of the vowel modifiers and a large number of characters (class). MODI script is a shorthand form of Devanagari script and it was used as an official script for writing Marathi until 1952. Presently the script is not used officially, but has historical importance. MODI script is a cursive script and the character recognition task is difficult due to various reasons such as variations in the shapes of a character with different individuals and the presence of identical looking characters. MODI documents do not have any word demarcation symbols and that adds to the complexity of the task. The advances in various Machine Learning newlinetechniques have greatly contributed to the success of optical character recognition. newlineThe proposed work is aimed at exploring various Machine Learning techniques/ newlinemethods which can be effectively used in(to) recognizing(recognize) MODI script and newlinebuild a reliable and robust character recognition model for handwritten MODI script. This research work also aims at the development of a Machine Transliteration and text recognition system for MODI manuscripts.