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Micro Borrowing an Amalgam of Structure and Strategy: Evidence from India
Micro borrowing was either an outcome of structure in the credit environment (termed the outreach stream), or a strategic response of the borrowers (termed the sustainability stream). Furthermore, borrower personal effects drove borrowing behaviour. This study draws variables from both the streams of literature and tests them against the amount borrowed and purposes loans are borrowed for. Results show how borrowing behaviour is neither an outcome of pure structure nor pure strategy, but rather, is an interplay of both, and further influenced by personal effects. The survey data (consisting of 839 rural borrower responses, from four districts of erstwhile Andhra Pradesh in South India) was subjected to a rigorous statistical analysis. Results show how a larger number of banks in the villages (a structural constraint), enabled the borrowers to receive larger loans, who defaulted more (a strategic response). Men borrowed larger sums (a personal effect). A similar amalgam of structure, strategy and personal effects drive borrowing behaviour even after controlling for loan purpose and district fixed effects. Yet, when district effects are introduced, amount borrowed is agnostic to personal effects, and is driven purely by structure and strategy. JEL Classifications: C25, C83, G51, Z13 The Author(s) 2022 -
Heat transfer in the flow of blood-gold Carreau nanofluid induced by partial slip and buoyancy
Dynamics of blood containing gold nanoparticles on a syringe and other objects with a nonuniform thickness is of importance to experts in the industry. This study presents the significance of partial slip (i.e. combination of linear stretching and velocity gradient) and buoyancy on the boundary layer flow of blood-gold Carreau nanofluid over an upper horizontal surface of a paraboloid of revolution (uhspr). In this report, the viscosity of the Carreau fluid corresponding to an infinite shear-rate is assumed as zero, meanwhile, the viscosity corresponding to zero shear-rate, density, thermal conductivity, and heat capacity were assumed to vary with the volume fraction of nanoparticles. The governing equation that models the transport phenomenon were non-dimensionalized and parameterized using suitable similarity variables and solved numerically using classical RungeKutta method with shooting techniques and MATLAB bvp4c package for validation. The results show that temperature distribution across the flow decreases more significantly with buoyancy-related parameter when the influence of partial slip was maximized. Maximum velocity of the flow is ascertained at larger values of partial slip and buoyancy parameters. At smaller values of Deborah number and large values of volume fraction, maximum local skin friction coefficient, and local heat transfer rate are ascertained. 2018 Wiley Periodicals, Inc. -
Challenges to state control of territory: Comparative analysis of Yemen, Afghanistan and Myanmar
States around the world have lost control over their territory to armed non-state actors, including states like Yemen, Afghanistan and Myanmar in the Asian region. This article aims to understand why these states are unable to exercise control over all of their territory. The study identifies and examines four major challenges faced by states in maintaining control over their territory lack of state legitimacy and effectiveness, strategic motives of armed non-state actors, socio-economic motives of armed non-state actors and external intervention. A comparative analysis of the cases of Yemen, Afghanistan and Myanmar illustrates the wide relevance of these challenges faced by the states with respect to territorial control. The Author(s) 2021. -
Inclusive business approaches in tourism: Stakeholder engagement
The link between inclusivity and sustainability transcends economic considerations, extending into various dimensions such as gender equality, accessibility, cultural sensitivity, and community engagement. These dimensions underline that inclusivity is central to how tourism interacts with societies and ecosystems. This understanding prompts stakeholders to broaden their perspectives and integrate diverse viewpoints to create a more balanced and resilient industry. A central theme running through the chapters is the essential role of inclusivity in achieving a sustainable tourism sector. As the industry evolves, so do the expectations of travelers and communities. This heightened awareness and connectivity era demands that tourism entities proactively adapt strategies to foster inclusivity. Whether by creating accessible infrastructure, respecting local cultures, or integrating fairness into business models, inclusivity emerges as a foundation for lasting sustainability. The chapters compiled in this book offer a comprehensive exploration of inclusive tourism and sustainable development. In the context of the evolving global tourism landscape, these chapters illuminate various facets that shape the industry's present and future trajectories. These chapters reveal common themes and key insights, highlighting the importance of proactive measures, collaboration, and innovation to establish a more inclusive, equitable, and sustainable tourism sector. A prominent revelation throughout these chapters is the interconnectedness of inclusivity and sustainability in tourism. It becomes increasingly evident that sustainable tourism cannot be achieved without an inclusive framework that embraces diverse communities, stakeholders, and perspectives. The chapters illustrate how sustainability efforts lacking inclusivity can lead to inequality and overlook crucial factors shaping destinations' social and environmental aspects. 2024 by Nova Science Publishers, Inc. All rights reserved. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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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. -
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. -
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. -
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. -
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. -
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. -
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. -
Selfipendant and Extremal Pendant Graphs
[No abstract available]