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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. -
On path-induced signed graphs
The path decomposition of a graph G is the process of decomposing it into edge-disjoint paths. An induced signed graph is a signed graph formed from an ordinary unsigned graph by assigning signs to its edges according to some protocol. In this paper, we introduce the notion of a path-induced signed graph as an induced signed graph whose edges receive a sign according to whether its end vertices are the end vertices of a path in a path decomposition of G. We also discuss some characteristics of this type of signed graph. The Author(s), under exclusive license to Sapientia Hungarian University of Transylvania 2026. -
The Pendant Number ofLine Graphs andTotal Graphs
The parameter, pendant number of a graph G, is defined as the least number of end vertices of paths in a path decomposition of the given graph and is denoted as ? p(G). This paper determines the pendant number of regular graphs, complete r-partite graphs, line graphs, total graphs and line graphs of total graphs. We explore the bougainvillea graphs, e-pendant graphs and v-pendant graphs. If the pendant number is 2, then the number of paths in the path decomposition of the given graph is at most ? (G), the maximum degree of the graph. Hence, a large class of graphs give a more reasonable solution to Gallais conjecture on number of paths in the given path decomposition. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Graph Theory and Decomposition
The book Graph Theory and Decomposition covers major areas of the decomposition of graphs. It is a three-part reference book with nine chapters that is aimed at enthusiasts as well as research scholars. It comprehends historical evolution and basic terminologies, and it deliberates on decompositions into cyclic graphs, such as cycle, digraph, and K4-e decompositions. In addition to determining the pendant number of graphs, it has a discourse on decomposing a graph into acyclic graphs like general tree, path, and star decompositions. It summarises another recently developed decomposition technique, which decomposes the given graph into multiple types of subgraphs. Major conjectures on graph decompositions are elaborately discussed. It alludes to a comprehensive bibliography that includes over 500 monographs and journal articles. It includes more than 500 theorems, around 100 definitions, 56 conjectures, 40 open problems, and an algorithm. The index section facilitates easy access to definitions, major conjectures, and named theorems. Thus, the book Graph Theory and Decomposition will be a great asset, we hope, in the field of decompositions of graphs and will serve as a reference book for all who are passionate about graph theory. 2024 Jomon Kottarathil, Sudev Naduvath and Joseph Varghese Kureethara. -
Selfipendant and Extremal Pendant Graphs
[No abstract available] -
Exploring electric vehicle consumer behavior: impact of digital innovation, environmental concern, perceived value, and social influence on purchase intentions
Background: Understanding the drivers and boundary conditions of electric vehicle (EV) adoption is critical to fostering sustainable transportation. Building on perceived value and planned behavior theories, this study proposes a moderated mediation model in which perceived value influences both sustainability perception and purchase intentions, with household income, technology trust, and environmental knowledge serving as moderators. Methods: A cross-sectional survey of 496 licensed drivers familiar with EVs was conducted using validated multi-item scales. Data were analyzed in R using confirmatory factor analysis and structural equation modeling (lavaan), incorporating product-indicator interactions and 5,000-sample bootstrapping to test the direct, moderating, and mediating effects. Results: Consumers perceived value has a positive effect on sustainability perception (0.122, p?<?0.001) and purchase intentions (0.002, p?<?0.001). Household income also strengthens the relationship between perceived value and purchase intention (0.043, p?<?0.001). Digital innovation (0.285, p?<?0.001) and environmental concerns (0.411, p?<?0.001) dynamically influenced the perception of sustainability at a significant level, although social influence was not significant. Compared with other variables, sustainability perception had the greatest effect on consumers intention to buy an electric car (0.624, p?<?0.001) and served as a mediator in three out of four indirect connections between perceived value and purchase intention. The moderating effects of technology trust and environmental knowledge were not supported. Conclusion: These findings highlight the central roles of value and sustainability perceptions in EV adoption and identify income as a key boundary condition. Practical implications include tailoring incentives by income segment, investing in user-centric digital platforms, and emphasizing both economic and environmental benefits. Theoretically, this study extends technology acceptance models by integrating sustainability constructs and underscores the nuanced impact of socioeconomic factors on green consumer behavior. Copyright 2025 Kottala, Chanagala, Balaji, Reddy and Babu. -
A Mental Health Epidemic?: Critical Questions on the National Mental Health Survey
Questions are raised about an approach towards psychiatric epidemiology, which directly imports models in medicine to count disorders of the mind to produce staggering evidence to the effect that 11% of Indians suffer from mental disorders. An alternative psychiatric epidemiology is needed, which relies on the principles of slow research, is value-based, and which defines mental health as an ethical and political problem. 2022 Economic and Political Weekly. All rights reserved. -
Farmers' Protests, Death by Suicides, and Mental Health Systems in India: Critical Questions
Ongoing farmers' protests have once again brought back the spotlight on the agrarian crisis in India. Even though upstream factors that perpetuate farmers' suffering, including the role of the state in promoting agrocapitalism, have been discussed extensively by scholars and activists across the spectrum, mental health discourses almost always frame it as a mental health problem to be addressed by increasing access to psychopharmaceuticals. Drawing on developments around farmers' protests and analysis of articles published in flagship journals of largest professional bodies of clinical psychologists and psychiatrists in India, I highlight the intimate relationship between neoliberal state and farmers' distress to which the mental health system shuts its ears and eyes obscuring and downplaying socio-structural determinants of farmers' mental health. Copyright 2021 Springer Publishing Company, LLC. -
LGBTQIA+ rights, mental health systems, and curative violence in India
This commentary examines the spaceattitudeadministrative complex of mainstream mental health systems with regard to its responses to decriminalisation of nonheteronormative sexual identities. Even though the Supreme Court, in its 2018 order, instructed governments to disseminate its judgment widely, there has been no such attempt till date. None of the governmentrun mental health institutions has initiated an LGBTQIA+ rights-based awareness campaign on the judgment, considering that lack of awareness about sexualities in itself remains a critical factor for a noninclusive environment that forces queer individuals to end their lives. That the State did not come up with any awareness campaign as mandated in the landmark judgment reflects an attitude of queerphobia in the State. Drawing on the concept of biocommunicability, analysing the public interfaces of staterun mental health institutions, and the responses of mental health systems to the death by suicide of a queer student, I illustrate how mental health institutions function to further antiLGBTQIA+ sentiments of the state by churning out customerpatients out of structural violence and systemic inequalities, benefitting the mental health economy at the cost of queer citizens on whom curative violence is practised. Indian Journal of Medical Ethics 2022. -
Measuring Customer Perception on Promotion of Tourism Destinations Using AR and VR Applications: Model Testing and Validation
The study aims to propose and develop a model to measure the customer perception toward promotional videos created using Augmented Reality (AR) and Virtual Reality (VR) technologies to promote tourism places. Using judgment sampling, 400 tourists were chosen, all of whom had visited various tourist spots in Visakhapatnam and had seen at least two promotional movies highlighting various tourist attractions using AR/VR technology. A properly written questionnaire was produced ahead of time to gather visitors perception for the qualities of augmented and virtual reality advertising attempts. The study revealed that passengers expect full information and appropriate motivation from digital marketing efforts that promote specific tourist locations using Augmented Reality and Virtual Reality. Furthermore, visitors anticipate high-quality visual and audio features in digital advertising materials for tourist destinations, with the goal of improving the entire customer experience and inspiring future visits. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Detecting Student Depression Using Non-Clinical Measures with Explainable Predictive Modeling
Depression among students is a serious global mental health concern, affecting academic performance, emotional wellbeing, and long-term development. While traditional diagnostic tools like self-reported questionnaires and clinical interviews are useful, they often suffer from subjectivity, recall bias, and limited scalability. This study introduces a data driven, interpretable machine learning approach to predict student depression using both academic and nonacademic factors, without relying on clinical indicators. The dataset comprises student information on demographics, academic workload, lifestyle habits, social interactions, financial stress, and emotional state. Following thorough preprocessing including handling missing values, encoding variables, correlation-based feature reduction, and SMOTE to address class imbalance, ten supervised machine learning models were trained and assessed. Among them, a SMOTE enhanced XGBoost model achieved the highest test ROC AUC score of 0.95. To maintain transparency, SHAP (Shapley Additive Explanations) was employed to interpret the model's predictions, highlighting key risk factors such as academic pressure, poor sleep quality, financial difficulties, and low social support. These findings can help guide early interventions and build trust with stakeholders. Future work may involve incorporating longitudinal and multimodal data, deploying real time solutions in educational settings, and addressing ethical considerations around privacy, fairness, and consent in AI based mental health systems. 2025 IEEE. -
Impact of social-emotional learning intervention on emotional intelligence of adolescents
Adolescents face a variety of challenges, some of which include social, emotional, cognitive, and interpersonal. In order to help them with their emotions, adolescents should be taught a variety of skills to regulate and handle emotions better. With this intent in mind, a social-emotional learning (SEL) intervention module was developed by the researchers. This module covered aspects related to self-awareness, social awareness, responsibility, empathy and decision-making. These components also form the basis for emotional intelligence (EI) which is defined as the ability to perceive, understand, and regulate emotions of oneself and others. The present study aimed to understand if there arises any difference in scores of EI post the SEL intervention. Second, the gender differences with respect to EI were also be analyzed. The EI Scale (2014) was administered to 80 students between the age group of 13-14 years, from a CBSE school in Chennai. These adolescents were selected through the convenience sampling, and the four subscales were also analyzed. The findings from the study revealed a significant difference in scores from pretest to posttest (t = -4.66, P < 0.05). With respect to gender, no significant difference was found. On the subscales, two of four subscales showed significant difference in understanding emotions (Z = -4.63, P < 0.05) and handling emotions (Z = -4.023, P < 0.05). Indian Journal of Social Psychiatry. All Rights Reserved. -
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An efficient scheme for water leakage detection using support vector machines (SVM)-Zig
Water is one of the most essential and valuable resources for all living beings, yet in the present day, there is a scarcity of it. Half of the water loss in large cities and industries is due to leaks and illegal lines. 10%-20% of water loss can be reduced by detecting leaks but without the presence of advanced monitoring systems, this problem is typically worsened. Monitoring the consumption and leak detection for such large areas is a challenging task. To overcome this issue a small prototype is prepared called Zig. Zig is designed for both household and industrial purposes. Its main aim is to monitor the flow and consumption of water at different levels of a building like a first-floor and so on which may represent some industrial and household situation. This work focuses on pressure/flow monitoring method to reduce the operational cost and also to detect leakage. One of the machine learning algorithms, Support Vector Machines (SVM) has been applied to detect the leakage and it is compared with Random Forest algorithm to show that proposed scheme is detecting water leakage better. BEIESP. -
FORTIFICATION OF LAUNDRY WATER WITH BACTERIA CAPABLE OF SODIUM DODECYL SULFATE (SDS) REMEDIATION AND PLANT GROWTH PROMOTION. A SUSTAINABLE WAY TO REUSE WATER FOR IRRIGATION
Anionic surfactant sodium dodecyl sulfate (SDS) is used in cosmetics and cleaning goods. It discharges into the environment and waterways due to its extensive use. Basal media with 0.05% SDS as the sole carbon source was used to isolate bacteria that can utilize SDS. The isolates survived nitrogen-free medium and solubilized potassium and phosphate. Using 16S rRNA sequencing, Enterobacter cloacae strain MSK86 (OR136425) was identified. Stains-all dye was used to test the bacteria's SDS-utilizing capability. A 49% drop in SDS levels in the broth was observed after 7 days of 24-hour analysis. The bacteria exhibited tolerance to heavy metals like Cd (II), Ar (III), and Zn (II) at concentrations up to 2000 ppm, whereas they were susceptible to Cu (II), Cr (II), and Pb (II) at minimum concentrations of 200, 600, and 1000 ppm, respectively. The bacteria effectively reduced SDS levels in the laundry wash water. The treated water was reused for the irrigation of Capsicum annum L. and Solanum lycopersicum L. until the 45th day of growth. The plants' morphological and phytochemical properties were also analyzed. The potential of bacteria for SDS degradation and plant growth enhancement has been extensively explored independently; however, these traits have not been studied together in a single bacterial strain. In the present study, multifaceted Enterobacter cloacae MSK86 was isolated with these capabilities together, which may help in SDS remediation, making the water reusable for irrigation. (2025), (Slovak University of Agriculture). All Rights Reserved. -
Deciphering the plant growth-promoting traits of bacteria capable of sodium dodecyl sulfate removal from graywater: a sustainable approach for water reuse for irrigation
Sodium dodecyl sulfate (SDS), an anionic detergent found in cleaning products and cosmetics, is one of the chemical pollutants in waterways. SDS-utilizing bacteria were isolated from soil and water samples using 0.05% SDS basal medium. Three bacterial isolates were selected for 16S rRNA sequencing based on their ability to solubilize phosphate, potassium, and zinc, and they were identified as Pseudomonas putida MSK86 OR192890, Klebsiella pneumoniae NET12 OR345422, and Enterobacter sp. MSK86 OR398804. Enterobacter sp. MSK86 and K. pneumoniae NET12 lowered the SDS concentration in the sample 84.78% and 75.65%, respectively, while P. putida MSK86 reduced it 33.43% on the sixth day of incubation. A phosphate-potassium-zinc co-inoculum was prepared using Enterobacter and Pseudomonas species. Laundry wash water was added with the bacteria, individually and co-inoculum, and the fortified water was used to irrigate the Capsicum annuum L. seedlings. On the 45th day, the plants were harvested, and total glucose, protein, chlorophyll, and proline were checked by comparing control plants. Enterobacter sp. MSK86 increased carbohydrate and proline levels by 37.22mg/g ( 0.54 SE) and 2.44mg/g ( 0.1 SE), while K. pneumoniae NET12-treated plants showed an increase in chlorophyll by 1.95mg/g ( 0.02 SE) and total protein by 1.94mg/g ( 0.03 SE). The bacteria in this study showed they could lower SDS levels in graywater and improve farming by adding nutrients to the soil and plants, offering a sustainable way to tackle detergent pollution, fertilizer use, and water scarcity. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Challenges and solutions in securing AI algorithms in healthcare
The paper discusses existing challenges that, based on the legal framework, the regulatory change must affect in order to ensure interest coverage in the health sector. Massive opportunities lie in the role that AI plays in healthcare in the forms of diagnostics and personalized care, while major challenges arise. AI models like machine learning, deep learning, and neural networks have improved healthcare outcomes, but they raise concerns on the privacy of patient data, explainability, and cyber threats such as adversarial attacks. Sensitive data must be protected for patients to trust AI-driven diagnosis. Bias in algorithms, the obtaining of informed patient consent, and the accountability of the AI decisions are some ethical and regulatory issues. Regulations like HIPAA(Health Insurance Portability and Accountability Act) and GDPR(General Data Protection Regulation) are the most important while considering data protection.This includes better encryption and anonymisation of patient data, interpretable models, and stronger defences against cyber-attacks. 2025, IGI Global Scientific Publishing. All rights reserved. -
Human resource aiding system by handling numerous data /
Patent Number: 202241004856, Applicant: Manabhanjan Sahu.
Human resource aiding system by handling numerous data Abstract: Numerous businesses have implemented human resource information systems over the last decade due to their ability to reduce costs, accelerate the flow of information, and assist human resource managers in making sound decisions. Human resource information systems can assist employees in improving their performance at work. In recent years, human resource information systems have developed into a highly effective tool. -
Impact of management - Information - system (MIS) on effective HRM in a business /
Patent Number: 202241006289, Applicant: Dr.K.Santhana Lakshmi.
Impact of Management- Information- System (MIS) on effective HRM in a business Abstract: Human resource management is now recognised as a critical component of business. The human resources department of an ERP system has a transaction processing layer that handles tasks such as attendance tracking and wage calculation. Tracking employees is also a component of operational work. This serves as the jumping-off point for strategic work. With the increasing importance of human resource management and the growing size of businesses, maintaining employee data and producing accurate reports have become critical components of any business's operations and strategy. -
Digitalization of Online Classes Among Higher Secondary Students in the Emerging Shift of Post Covid-19 (Second Wave)
The second wave of COVID-19 in India has left higher secondary school students befuddled, unhappy, and unsure about their future. During the second wave of the COVID-19 epidemic, a number of factors influence the effectiveness of online learning. Hence, the main objective of this research paper is focused on understanding the factors influencing online learning among higher secondary students. Researchers identified variables such as attitude, tools and technology, and quality of teaching and social support through extensive literature review. The research study adopted snowball sampling technique and used a survey-based online questionnaire for collecting the data; responses were obtained from 394 respondents from the state of Kerala in India. PLS-SEM was used to test the proposed hypotheses. The results of the study indicate that quality of teaching is the only factor that impacts the effectiveness of online classes among higher secondary students. Attitude, technology and tools, and social support are observed to have insignificant impact on online learning effectiveness. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.