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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. -
Exploring the motivating factors for opportunity recognition among social entrepreneurs: aqualitative study
Purpose This paper explores the motivating factors that lead to opportunity recognition among social entrepreneurs in India. Design/methodology/approach The study followed an exploratory, qualitative design based on thematic analysis of the interview data collected from 13 Indian social entrepreneurs. Findings The study identifies two aggregate factors that motivate social entrepreneurs: personal and contextual. Personal factors include life experiences, social awareness, social inclination since childhood, spiritual motives, the need for a meaningful career and entrepreneurial intention. Contextual factors included institutional voids, community development, the presence of a role model and volunteer experiences. Research limitations/implications This study contributes to the social entrepreneurship literature by providing a model for motivating factors that lead to opportunity recognition. This study enables policymakers and social entrepreneurship educators to identify aspiring social entrepreneurs and provide target-specific support to them. Practical implications This study enables policymakers and social entrepreneurship educators to identify aspiring social entrepreneurs and provide target-specific support to them. Originality/value The study uniquely contributes to the social entrepreneurship field by offering deep qualitative insights into the motivational and opportunity recognition patterns of social entrepreneurship. 2024 Parvathy Viswanath and A. Sadananda Reddy -
The Role of Cognitive Appraisal in Informed Decision-Making among Social Entrepreneurs: A Thematic Analysis
Social entrepreneurship (SE) is gaining momentum by providing innovative solutions to economic, social, and environmental problems by generating jobs and social inclusion. However, it involves different challenges that may lead to a negative appraisal. This study aimed to explore cognitive appraisal processes social entrepreneurs use to make informed decisions in their entrepreneurial journey. Interviews were conducted with 13 Indian social entrepreneurs, and the data were subjected to thematic analysis. The main themes were; appropriateness, implications, coping potential, and normative significance. The study proposes a cognitive model for the appraisal of SE. The study is important for aspiring social entrepreneurs to understand the evaluation components of appraisal to decide how appropriate SE is as a career for them. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Opportunity Recognition, Career Decision-Making, Self-Efficacy and Social Entrepreneurial Intention among Higher Education Students
Building on the entrepreneurship cognition literature, the present research aims to develop a model to examine the direct and indirect effects of opportunity recognition, career decisionmaking and self-efficacy on social entrepreneurial intention. The research adopted a crosssectional design. The research was divided into three distinct studies, each conducted with a specific objective. The data collected for three studies included higher education students newlineacross India. Studies 1 and 2 aimed to develop and validate two scales, namely social entrepreneurial opportunity recognition and social entrepreneurial career decision-making following steps in tool construction. The sample size was 600 for study 1 and 845 for study 2. The social entrepreneurial opportunity recognition scale had 24-items that measures opportunity recognition with six motivating factors as the lower order constructs which are life experiences, social awareness, social inclination, community development, institutional voids, and natural option for a meaningful career. The social entrepreneurial career decision scale had 20 items focusing on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources, and normative significance. Study 3 examined the direct and indirect effects of opportunity recognition, career decision-making and self-efficacy on social newlineentrepreneurial intention using a sample of 605 students. The findings show that opportunity recognition influences social entrepreneurial intention and is partially mediated by career decision-making. Furthermore, self-efficacy moderates the mediating role of career decisionmaking between opportunity recognition and intention. This research facilitates a profound understanding of social entrepreneurial cognition and pre-entry decision-making. -
Exploring the motivating factors for opportunity recognition among social entrepreneurs: aqualitative study
Purpose: This paper explores the motivating factors that lead to opportunity recognition among social entrepreneurs in India. Design/methodology/approach: The study followed an exploratory, qualitative design based on thematic analysis of the interview data collected from 13 Indian social entrepreneurs. Findings: The study identifies two aggregate factors that motivate social entrepreneurs: personal and contextual. Personal factors include life experiences, social awareness, social inclination since childhood, spiritual motives, the need for a meaningful career and entrepreneurial intention. Contextual factors included institutional voids, community development, the presence of a role model and volunteer experiences. Research limitations/implications: This study contributes to the social entrepreneurship literature by providing a model for motivating factors that lead to opportunity recognition. This study enables policymakers and social entrepreneurship educators to identify aspiring social entrepreneurs and provide target-specific support to them. Practical implications: This study enables policymakers and social entrepreneurship educators to identify aspiring social entrepreneurs and provide target-specific support to them. Originality/value: The study uniquely contributes to the social entrepreneurship field by offering deep qualitative insights into the motivational and opportunity recognition patterns of social entrepreneurship. 2024, Parvathy Viswanath and A. Sadananda Reddy. -
The Role of Cognitive Appraisal in Informed Decision-Making among Social Entrepreneurs: A Thematic Analysis
Social entrepreneurship (SE) is gaining momentum by providing innovative solutions to economic, social, and environmental problems by generating jobs and social inclusion. However, it involves different challenges that may lead to a negative appraisal. This study aimed to explore cognitive appraisal processes social entrepreneurs use to make informed decisions in their entrepreneurial journey. Interviews were conducted with 13 Indian social entrepreneurs, and the data were subjected to thematic analysis. The main themes were; appropriateness, implications, coping potential, and normative significance. The study proposes a cognitive model for the appraisal of SE. The study is important for aspiring social entrepreneurs to understand the evaluation components of appraisal to decide how appropriate SE is as a career for them. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Social entrepreneurial opportunity recognition among higher education students: scale development and validation
Purpose: This study aims to develop and validate a multidimensional scale to measure the motivating factors that lead to opportunity recognition in social entrepreneurship among higher education institute (HEI) students. Design/methodology/approach: The scale was developed through two phases; in phase 1, semi-structured interviews with social entrepreneurs and aspiring students were conducted to explore themes for item generation. Phase 2 included developing and validating the scale using exploratory (EFA) and confirmatory factor analysis (CFA). The sample included HEI students (n = 300 for EFA, n = 300 for CFA) with either academic background or volunteering experiences in social entrepreneurship. Findings: A 24-item scale is developed in the study, with six factors measuring the motivating factors influencing opportunity recognition in social entrepreneurship: life experiences, social awareness, social inclination, community development, institutional voids and natural option for a meaningful career. Research limitations/implications: The scale facilitates the development of theories and models in social entrepreneurship. The scale also enables policymakers and social entrepreneurship educators to understand the motivating factors that lead to opportunity recognition among students. It would help them to provide target-specific support to students. Originality/value: To the best of the authors knowledge, this study is the first attempt to develop a scale that measures opportunity recognition in social entrepreneurship based on specific motivating factors. The study used the model by Yitshaki and Kropp (2016) as the conceptual framework. This study is the first attempt to triangulate the models findings using a quantitative methodology and through the development of a measurement scale. Besides, the scale adds value to social entrepreneurship research, which lacks empirical research on HEI students. 2024, Emerald Publishing Limited. -
Are Narrow-line Seyfert 1 Galaxies Powered by Low-mass Black Holes?
Narrow-line Seyfert 1 galaxies (NLS1s) are believed to be powered by the accretion of matter onto low-mass black holes (BHs) in spiral host galaxies with BH masses M BH ? 106-108 M o. However, the broadband spectral energy distribution of the ?-ray-emitting NLS1s are found to be similar to flat-spectrum radio quasars. This challenges our current notion of NLS1s having low M BH. To resolve this tension of low M BH values in NLS1s, we fitted the observed optical spectrum of a sample of radio-loud NLS1s (RL-NLS1s), radio-quiet NLS1s (RQ-NLS1s), and radio-quiet broad-line Seyfert 1 galaxies (RQ-BLS1s) of ?500 each with the standard Shakura-Sunyaev accretion disk (AD) model. For RL-NLS1s we found a mean log() of 7.98 0.54. For RQ-NLS1s and RQ-BLS1s we found mean log() of 8.00 0.43 and 7.90 0.57, respectively. While the derived values of RQ-BLS1s are similar to their virial masses, for NLS1s the derived values are about an order of magnitude larger than their virial estimates. Our analysis thus indicates that NLS1s have M BH similar to RQ-BLS1s and their available virial M BH values are underestimated, influenced by their observed relatively small emission line widths. Considering Eddington ratio as an estimation of the accretion rate and using , we found the mean accretion rate of our RQ-NLS1s, RL-NLS1s, and RQ-BLS1s as , and , respectively. Our results therefore suggest that NLS1s have BH masses and accretion rates that are similar to BLS1s. 2019. The American Astronomical Society. All rights reserved. -
A Statistical Search for Star-Planet Interaction in the Ultraviolet Using GALEX
Most (?82%) of the over 4000 confirmed exoplanets known today orbit very close to their host stars, within 0.5 au. Planets at such small orbital distances can result in significant interactions with their host stars, which can induce increased activity levels in them. In this work, we have searched for statistical evidence for star-planet interactions in the ultraviolet (UV) using the largest sample of 1355 Galaxy Evolution Explorer (GALEX) detected host stars with confirmed exoplanets and making use of the improved host-star parameters from Gaia DR2. From our analysis, we do not find any significant correlation between the UV activity of the host stars and their planetary properties. We further compared the UV properties of planet host stars to that of chromospherically active stars from the RAdial Velocity Experiment (RAVE) survey. Our results indicate that the enhancement in chromospheric activity of host stars due to star-planet interactions may not be significant enough to reflect in their near- and far-UV broadband flux. 2020. The American Astronomical Society. All rights reserved.. -
Exploring the relationship between esg performance and profitability in Indian power companies
This study aims to assess the relationship and impact of Indian power companies' environment, social, governance (ESG) scores on firm performance. Since 2022, CRISIL Ratings Ltd publishes yearly ESG scores for 225 companies in India. The final 'ESG' score is a composite of individual scores for the three metrics: 'Environment', 'Social', and 'Governance'. This study intends to examine the influence of ESG scores on financial profitability measured by both net profit ratio and return on investment. The existence and degree of association between the variables is measured using correlation and simple linear regression analyses, respectively. The findings suggest that the overall ESG composite score is positively and significantly associated with firm profitability and moderately associated with returns. The 'Governance' metric stands out which has a strong and positive relationship with profitability in particular. These findings advocate that by investing in ESG initiatives, the chances of better financial performance are improved. 2024, IGI Global. All rights reserved. -
Exploring The Dynamic Relationship between Macroeconomic Variables on Indias Premier Benchmark Sensex 30 Index
The purpose of the study is to examine the impact of macroeconomic indicators on the closing prices of the BSE Sensex 30, a key benchmark index in India known for its volatility in response to economic conditions. This research is particularly relevant in the context of economic shocks, as it aims to recommend the adoption of appropriate economic policies that could benefit the stock market index, ultimately advancing growth in the capital market. Using the ordinary least squares (OLS) method, the study analyzes the effect of various macroeconomic variables on the BSE Sensex. Additionally, the complex relationship between these variables is explored using the Johansen Cointegration test and evidenced through the Vector Error Correction (VECM) model. The findings reveal that GDP, the Index of Industrial Production (IIP), Indias foreign trade, gold prices, Foreign Direct Investment (FDI), and money supply significantly influence the BSE Sensex. However, External Commercial Borrowing, the Consumer Price Index (CPI), exchange rates, and foreign exchange, which showed the highest Variance Inflation Factors (VIF), were excluded from the study based on OLS results. In conclusion, the study advocates for the implementation of suitable economic policies that support the stock market, thereby aligning with investors interests and promoting capital market growth. Vishweswarsastry V. N. et al. -
Molecular and electronic structure of 5-coordinated [Fe(CO)?(X?)] complexes: A quantum chemical study
Quantum mechanical DFT calculations were performed on Fe(CO)5 and for the axial and equatorial isomers of 5-coordinated [Fe(CO)4(X2)] (where X = N, P, As, and Sb) complexes. The equatorially substituted complexes of 5-coordinated [Fe(CO)4(X2)] are more stable than the axially substituted complexes, as seen from their energy values. These complexes were further studied to understand their bonding nature using results from Natural population analysis (NPA) and energy decomposition analysis (EDA) calculations. The Wiberg bond indices (WBI) analysis provides the bond index of the bond between Fe and X2. The Frontier molecular orbital (FMO) studies show these complexes have a HOMO-LUMO energy gap in the values ranging from 1.99 to 5.04 eV, which is less than that of [Fe(CO)5]. From the Natural bond order (NBO) analysis, the contribution of the X?-atom is smaller in the ? bond formation compared to X? in P2, As2, and Sb2. Similar contributions are seen with the carbonyl group (in the Fe[sbnd]C bond), although the contribution of the carbon atom is larger than that of the X atom. 2025 Elsevier B.V. -
Kannada translation and validation of Wellman and Liu's theory of mind scale and children's social understanding scale in preschoolers
Background: Assessing theory of mind (ToM) in children is crucial for understanding social cognition. Wellman and Liu's ToM scale and the Children's Social Understanding Scale (CSUS) have been used to study ToM in children but are not available in the local language. Aim: This study aims to translate both scales into Kannada and validate them in preschool children. Methods: Following the rigorous WHO protocol, we meticulously translated and back-translated Wellman and Liu's ToM and CSUS into Kannada with the help of bilingual experts. Validation involved administering both scales to 118 preschool children aged 3 to 6 years from diverse urban and rural backgrounds in a cross-sectional study, ensuring the scales' applicability across different settings. Results: The Cronbach's alpha values for Wellman and Liu's ToM and the CSUS were 0.769 (95% CI 0.698 to 0.828) and 0.983 (95% CI 0.978 to 0.987), respectively, indicating high internal consistency. The test-retest reliability for Wellman and Liu's ToM scale domains ranged from 0.74 to 0.95, and for the CSUS, it was 0.99, demonstrating good reliability. Pearson's correlation between the domains of two scales ranged from 0.32 to 0.69, suggesting a moderate relationship. Conclusion: Our study findings demonstrate that Kannada translations of Wellman and Liu's ToM and CSUS have good internal consistency, test-retest reliability, and construct validity. These tools will be valuable for understanding social cognition in preschool children. 2024 Indian Journal of Psychiatry. -
Pattern of acquisition of theory of mind in pre-schoolers: A cross-sectional study from South India
Background: Theory of Mind (ToM) is an important part of children's social cognitive development. The pattern of ToM acquisition depends on many factors including culture, the number of family members, and siblings. This study aimed to examine the pattern of ToM acquisition in Indian culture. Methods: We conducted a cross-sectional study among preschool children (three to six years) (N = 118) from rural and urban backgrounds. ToM development was assessed using the Wellman and Liu Theory of Mind Scale and the Children's Social Understanding Scale (parent report). Results: The order of acquisition of ToM in Indian children was as follows: diverse desire> diverse belief> knowledge access> explicit false belief> content false belief> hidden emotion. The number of siblings positively correlated with the total ToM task score, and the number of adults in the family did not show any positive correlation. Conclusions: Although India is a collectivistic country, the acquisition pattern of ToM in our population was like that of individualistic countries such as the United States. 2023 Elsevier B.V. -
EV Service Stations for Future Smart Cities
The market for electric vehicles (EVs) has been growing at a fast pace in recent years. It is expected to continue growing at a much faster pace in the coming decades. The emerging EV technology is increasingly gaining a high demand for continued good transport connections in smart cities. Most of the Smart Cities' charging infrastructure and future growth revolve around its public transport network, especially an EV service station. New technologies, therefore, need to be complemented with new and versatile charging options to cater to different types of charging options available for charging Li-ion Batteries with newer materials and charging capacity. Building an EV service station in the ongoing scenario anticipates smart engineering knowledge to complement innovative charging methods. An EV service station needs hardware, software, and test equipment before charging, during charge, and post-charge states. It is expected to inform the user of available options to choose and select from. This paper investigates the challenges and suggests solutions to meet the EV service station support for EV vehicles in present and future smart cities. It also highlights the demand for a skilled workforce to maintain these service stations, including updating their skills. Examples of a few smart cities in developed as well as developing countries have been quoted. These developments will contribute to the transport infrastructure needed for future smart cities. The paper paves the way for future research in this area. The Institution of Engineering & Technology 2023. -
Machine Learning with Data Science-Enabled Lung Cancer Diagnosis and Classification Using Computed Tomography Images
In recent times, the healthcare industry has been generating a significant amount of data in distinct formats, such as electronic health records (EHR), clinical trials, genetic data, payments, scientific articles, wearables, and care management databases. Data science is useful for analysis (pattern recognition, hypothesis testing, risk valuation) and prediction. The major, primary usage of data science in the healthcare domain is in medical imaging. At the same time, lung cancer diagnosis has become a hot research topic, as automated disease detection poses numerous benefits. Although numerous approaches have existed in the literature for lung cancer diagnosis, the design of a novel model to automatically identify lung cancer is a challenging task. In this view, this paper designs an automated machine learning (ML) with data science-enabled lung cancer diagnosis and classification (MLDS-LCDC) using computed tomography (CT) images. The presented model initially employs Gaussian filtering (GF)-based pre-processing technique on the CT images collected from the lung cancer database. Besides, they are fed into the normalized cuts (Ncuts) technique where the nodule in the pre-processed image can be determined. Moreover, the oriented FAST and rotated BRIEF (ORB) technique is applied as a feature extractor. At last, sunflower optimization-based wavelet neural network (SFO-WNN) model is employed for the classification of lung cancer. In order to examine the diagnostic outcome of the MLDS-LCDC model, a set of experiments were carried out and the results are investigated in terms of different aspects. The resultant values demonstrated the effectiveness of the MLDS-LCDC model over the other state-of-The-Art methods with the maximum sensitivity of 97.01%, specificity of 98.64%, and accuracy of 98.11%. 2023 World Scientific Publishing Company. -
Fluorescence switching via competitive ESIPT and spirolactam ring opening in a multifunctional rhodamine B probe for selective detection of Cu2+ and OCl?: theoretical insights with anticancer and biosensor activity
A multifunctional ESIPT-based rhodamine-derived probe (BHS) was synthesized and developed as a colorimetric and fluorometric sensor for the selective detection of copper (Cu2+) and hypochlorite (OCl?) in aqueous solutions. Initially, BHS exhibits intense whitish blue fluorescence due to the active excited-state intramolecular proton transfer (ESIPT) mechanism within the molecule. However, upon interaction with Cu2+ and OCl?, noticeable changes in absorption and fluorescence occur, attributed to the inhibition of ESIPT resulting from analyte binding with BHS, leading to spirolactam ring opening. Furthermore, significant Stokes shifts in absorption (?? = 34 nm and 170 nm for Cu2+, and 163 nm for OCl?) and emission (?? = 67 nm for both Cu2+ and OCl?) further confirm this transformation. The spirolactam ring opening is induced by Cu2+ coordination, whereas for OCl?, it is triggered by oxidative cleavage. To explore potential biological applications, fluorescence titration experiments were conducted to study the interactions of the BHS-Cu2+ complex with ct-DNA and the transport protein bovine serum albumin (BSA). Additionally, molecular docking studies were performed to assess these interactions, while DFT calculations were employed to optimize the structures of BHS and its Cu2+ complex. The fluorescence changes of BHS in the presence of Cu2+ and OCl? in biological samples have been examined by the anticancer and biosensor activity of BHS in HCT-116 colorectal cancer cells. 2025 RSC. -
Qualitative and quantitative test of digital micromirror device for next generation UV multi-object spectroscopy
The coming decade in astronomy focuses on large wide field imaging and spectroscopic surveys. No wide field imaging facility extends to the UV region, which represents an important window into a wide variety of astrophysical problems. Also, spectroscopy would be essential to understand the physical and chemical properties of several stars, star forming regions and galaxies. Multi object spectroscopy (MOS) would be an efficient way to obtain these parameters for a large number of objects at a much shorter timescale. Digital Micromirror Device (DMD) acts as a programmable slit mask and can be used to achieve this goal in an MOS. This paper discusses different ground tests conducted on DMD to be used for the above said application. Numerical simulations for the diffraction effects on DMD is also carried out and the results are shared in this paper. 2020 SPIE -
A versatile sensor capable of ratiometric fluorescence detection of trace water and turn-on detection of Cu2+ modulating the binding interaction of a Cu(ii) complex with BSA and DNA complemented by docking studies
A fluorescent molecule, pyridine-coupled bis-anthracene (PBA), has been developed for the selective fluorescence turn-on detection of Cu2+. Interestingly, the ligand PBA also exhibited a red-shifted ratiometric fluorescence response in the presence of water. Thus, a ratiometric water sensor has been utilized as a selective fluorescence turn-on sensor for Cu2+, achieving a 10-fold enhancement in the fluorescence and quantum yield at 446 nm, with a lower detection limit of 0.358 ?M and a binding constant of 1.3 106 M?1. For practical applications, sensor PBA can be used to detect Cu2+ in various types of soils like clay soil, field soil and sand. The interaction of the PBA-Cu(ii) complex with transport proteins like bovine serum albumin (BSA) and ct-DNA has been investigated through fluorescence titration experiments. Additionally, the structural optimization of PBA and the PBA-Cu(ii) complex has been demonstrated by DFT, and the interaction of the PBA-Cu(ii) complex with BSA and ct-DNA has been analyzed using theoretical docking studies. 2024 The Royal Society of Chemistry.