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Digital financial literacy among adults in India: measurement and validation
The ongoing COVID-19 pandemic has considerably promoted the usage of Digital Financial Services (DFS) in India. Therefore, exploring the various determinants influencing the DFS users is crucial for the DFS providers to understand their customers better. This study aims to identify, measure, and validate the determinants of Digital Financial Literacy (DFL) from the Indian adults who use Digital Financial Services. A sample of 384 adult DFS users from India was surveyed using a self-administered questionnaire in 2021. A multidimensional scale was developed to measure the Digital Financial Literacy in this study. The results exhibit that Digital Knowledge, Financial Knowledge, Knowledge of DFS, Awareness of Digital Finance Risk, Digital Finance Risk Control, Knowledge of Customer Right, Product Suitability, Product Quality, Gendered Social Norm, Practical Application of Knowledge and Skill, Self-determination to use the Knowledge and Skill and Decision Making are the determinants of DFL among the adults in India. Further, the users of DFS without DFL will face numerous challenges such as inability to com-plete the transaction, financial loss and privacy breach, etc. Hence, the study concludes that DFL is prerequisite to use DFS effectively. 2022 The Author(s). This open access article is distributed under a Creative. -
Impact of digital payments on economic growth: Evidence from India
In recent years, economic transactions are carried out through electronic or online or cashless means all over the world especially in developed countries and developing countries like India. As a result of increased digital means of payment has brought down usage of cash transactions in the economy. Digital transactions have the features of speed, less cost, and comfort. A well functioning digital payment system has much relevance on overall economic activity, monetary policy, and financial stability of a country. This study tries to verify the impact of digital payments on the economic growth of India. The economic growth is measured through a proxy real Gross Domestic Product. Digital payments are measured using Real Time Gross Settlement (RTGS), Clearing Corporation of India Ltd (CCIL) operated systems, paper clearing, retail electronic clearing, Card payments, and Prepaid Payment Instruments (PPIs). Data for digital payments and real GDP are collected from the year 2011 to 2019. Ordinary Least Square Regression, Auto-Regressive Distributed Lag (ADRL) co-integration approach and ARDL Bounds test are employed for the analysis. The study results reveal that digital payments impact economic growth significantly in the short run. But, digital payments dont impact economic growth in the long-run. BEIESP. -
Strategic retention for sustainable growth: Integrating employee retention with long-term organizational success
The research investigates how employee retention approaches fuel business expansion through their contribution to operational sustainability and market solidity and organizational endurance. Businesses that adopt official retention strategies diminish turnover rates and develop innovative approaches to expand global markets. Businesses which merge HR and leadership insights with data analytics make workforce management match organizational goals thus creating an environment where retention acts as a performance driver. Active retention programs in dynamic business environments produce operational improvements along with enhanced innovation because they empower workers to address business challenges successfully. Through this study researchers demonstrate why organizations need full-scale support measures that include workforce development alongside mentoring services along with workplace flexibility policies for maintaining employee involvement. 2026, IGI Global Scientific Publishing. All rights reserved. -
A comprehensive literature review on financial inclusion /
Asian Journal Of Research In Banking And Financial, Vol.7, Issue 8, pp.119-133, ISSN: 2249-7323. -
Digital Financial Inclusion and Financial Resilience of Micro and Small Entrepreneurs in Post-COVID-19 in Karnataka
In India, Micro, Small, and Medium Enterprises contribute 29% of the GDP and create millions of works. However, MSMEs have continuously been facing numerous issues and further, micro and small enterprises are hardly hit by the COVID-19 pandemic. The traditional financial system has certain limitations. The new-age technology-enabled digital finance overcomes the supply-side constraints and they serve even the financially excluded individuals and businesses through its innovative business strategies, models, products, and services which are designed and delivered by "Artificial Intelligence", "Machine Learning", "Big Data Analytics", and "Blockchain Technology". Digital Finance Adoption (DFA) depends on the digital financial literacy (DFL) of the users. This study analyses the role of DFA and DFL on the "Digital Financial Inclusion" (DFI) and "Financial resilience" (FR) of MSEs in Karnataka, India. 2025, Indian Institute of Finance. All rgihts reserved. -
A Compact Multi-Input DC-DC Converter for Smart Grid and Electric Mobility Applications
This paper presents the design and simulation of a compact multi-input DC-DC boost converter intended for renewable energy integration and electric mobility applications. The proposed architecture allows the simultaneous interfacing of photovoltaic panels, fuel cells, and battery banks to a common DC bus, enabling seamless energy management and hybrid source utilization. A maximum power point tracking (MPPT) algorithm is embedded to optimize PV energy extraction under varying environmental conditions. MATLAB/Simulink models are developed to analyze performance parameters including voltage gain, current ripple, power stability, and total harmonic distortion (THD). The converter achieves a stable DC output of 400 V from input ranges of 24-48 V while maintaining efficiency above 95%. Results confirm reduced current ripple (<50 mV) and THD below 3%, in compliance with IEEE standards for grid-connected power systems. The duty cycle modulation strategy minimizes diode voltage stress and optimizes transient response. Furthermore, grid synchronization tests validate the converter's capability for three-phase AC output with minimal distortion, making it suitable for smart grid integration and electric vehicle charging infrastructure. The proposed converter presents a viable alternative for sustainable and high-performance power electronic systems due to its compact size, reduced component count, and enhanced efficiency. 2025 IEEE. -
An Empirical Examination of the Factors of Big Data Analytics Implementation in Supply Chain Management and Logistics
Numerous companies have effectively exploited Big Data Analytics (BDA) potential to enhance their effectiveness in the Big Data period. Given that big data application in logistics and supply chain management (SCM) is nevertheless in its early stages, assessments of BDA could differ from various viewpoints, producing certain difficulties in comprehending the significance and potential of big data. Based on past research on BDA and SCM, this work examines the factors that influence organizations' willingness to implement BDA in their everyday activities. This research divides potential elements into 4 groups: technical, firm, ecological, and supply chain issues. A framework consisting of direct factors like technical, firm, and mediators was presented based on the technology diffusion hypothesis. The experimental findings demonstrated that anticipated advantages and high-level management assistance might have a considerable impact on intended adoption. Furthermore, ecological variables like competitive adoption, administration legislation, and supply chain connection can greatly alter the direct connections between influencing causes and intended adoption. 2023 IEEE. -
Unveiling Powerful Machine Learning Strategies for Detecting Malware in Modern Digital Environment
Machine learning has emerged as formidable instrument in realm of malware detection exhibiting capacity to dynamically adapt to ever-shifting topography of digital hazards. This study presents an exhaustive comparative analysis of four intricate machine learning algorithms namely XGBoost Classifier, K-Nearest Neighbors (KNN) Classifier, Binomial Logistic Regression and Random Forest with primary objective of assessing their effectiveness in domain of malware detection. Conventional signature-based detection methodologies have struggled to synchronize with rapid mutations exhibited by malware variants. In sharp contrast machine learning algorithms proffer data-centric approach adept at unraveling intricate data patterns thereby enabling identification of both well-known and hitherto uncharted threats. To meticulously appraise efficacy of these machine learning models we employ stringent set of evaluation metrics. Precision, recall, F1 Score, testing accuracy and training accuracy are meticulously scrutinized to ascertain distinctive strengths and frailties of these algorithms. By providing comparative analysis of machine learning algorithms within milieu of malware detection this research engenders significant contribution to ongoing endeavor of fortifying cybersecurity. Resultant analysis elucidates that each algorithm possesses its unique competencies. XGBoost Classifier showcases remarkable precision (Benign files: 99%, Malicious files: 99%), recall (Benign files: 97%, Malicious files: 99%) and F1 Score (Benign files: 98%, Malicious files: 99%) implying its aptitude for precise malware identification. KNN Classifier excels in discerning benign software exhibiting precision (Benign files: 90%) and recall (Benign files: 91%) to mitigate likelihood of erroneous positives. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A characterization of star-perfect graphs
Motivated by Berge perfect graphs, we define star-perfect graphs and characterize them. For a finite simple graph G(V, E), let (Formula presented.) denote the minimum number of induced stars contained in G such that the union of their vertex sets is V(G), and let (Formula presented.) denote the maximum number of vertices in G such that no two of them are contained in the same induced star of G. We call a graph G star-perfect if (Formula presented.), for every induced subgraph H of G. A graph G is star-perfect if and only if G is (Formula presented.) -free, for every (Formula presented.). A bipartite graph G is star-perfect if and only if every induced cycle in G is of length (Formula presented.). The minimum parameter (Formula presented.) and the maximum parameter (Formula presented.) have been extensively studied in various contexts. 2024 The Author(s). Published with license by Taylor & Francis Group, LLC. -
ODD SUN-FREE TRIANGULATED GRAPHS ARE S-PERFECT
For a graph G with the vertex set V (G) and the edge set E(G) and a star subgraph S of G, let ?S(G) be the maximum number of vertices in G such that no two of them are in the same star subgraph S and ?S(G) be the minimum number of star sub-graph S that cover the vertices of G. A graph G is called S-perfect if for every induced subgraph H of G, ?S(H) = ?S(H). Motivated by perfect graphs discovered by Berge, Ravindra in-troduced S-perfect graphs. In this paper we prove that a trian-gulated graph is S-perfect if and only if G is odd sun-free. This result leads to a conjecture which if proved is a structural char-acterization of S-perfect graphs in terms of forbidden subgraphs. 2025, Diogenes Co. Ltd.. All rights reserved. -
Effect of Heat Treatment on Fatigue Characteristics of En8 Steel
Fatigue failure is an important factor in most of the engineering applications, especially in steel materials, and among the steel materials, it is an important phenomena in medium carbon steels like EN8, which is very commonly used in components like shaft, gears etc., since it is prone to fatigue failure. Hence, without changing the composition, an attempt is made to enhance the fatigue strength by different heat treatment techniques. In this study, the investigation is carried out on heat treatment of EN8 steel material. Various kinds of heat treatment techniques like quench and temper, normalizing and annealing are performed on EN8 steel. After exposure to the heat treatment, the EN 8 steel material specimens are machined as per the ASTM standards and are subjected to RR MOORE test and SN-curves are plotted from the obtained results; the obtained results from the fatigue tests are further analyzed with the help of ANSYS software. Fatigue life and Factor of Safety (FOS) comparisons for EN 8 steel material is made with the structural steel material and it is found from the comparisons, that the heat treatment process enhances the fatigue strength and endurance limit. Published under licence by IOP Publishing Ltd. -
Bibliometric Analysis of AI Research in Sustainable Smart Cities
Smart cities have the potential to improve city-wide governance, environmental sustainability, sustainable transportation, and economic growth. Urban areas may find these advantages useful in their pursuit of SDG-11 objectives. A key component of smart city architecture is the addition of artificial intelligence (AI) and other smart technology into urban areas. The Artificial Neural Network (ANN) is a major machine learning approach. A number of review studies have already been published, reflecting the substantial interest in artificial neural networks (ANN) for smart city applications. In the past, researchers have shown an interest in studying structural monitoring applications, transportation systems, cybersecurity, and the Internet of Things (IoT). But knowledge about how ANN can help Smart Cities achieve SDG-11 is limited. This paper provides a systematic bibliometric analysis of present research trends on artificial neural networks for smart cities, with an emphasis on SDG-11. The research employed a keyword-based search to obtain 131 papers for content analysis and 743 papers for descriptive analysis. Both the amount of interest in the topic and the tendency for related topics to cluster have increased exponentially, according to the findings. Urbanization, Transportation, and Eco-friendly were identified as the main topics of this study. Specifically, this evaluation focuses on particular SDG-11 issues and provides insights on research trends and thematic importance. 2025 Saravanan Krishnan, A. Jose Anand and Raghvendra Kumar. -
Secured Health Insurance Management
Many Low- and Middle-Income Countries (LMICs) have expanded their healthcare coverage over the past decade thanks to reforms and investments motivated by Universal Health Coverage (UHC). UHC strives to guarantee that all individuals have access to high-quality healthcare, protecting them from public health hazards and financial hardship caused by the need to treat sick family members. With UHC as its end objective, this study examines health insurances function as a policy instrument to address health funding. Here, researchers study the laws to ensure that all Indians have access to health care and how technology facilitates quicker participation in health insurance programs. The data was collected between August and October of 2022. The study was designed as a cross-sectional case study: (i) the research on the effects of UHC, (ii) documents about Indias health insurance systems (HIS), and (iii) a discussion of the benefits and challenges of using MedStrat, a homegrown digital Health Insurance Management System (HIMS), to run health insurance programs across different states in India. Data from research and document evaluations, as well as health insurance statistics, were triangulated with modern technology adoption models to determine (i) factors that influence the rate at which digital insurance plans are adopted, (ii) the effect of technology on increasing peoples access to health insurance; and (iii) the potential for the digital insurance intervention to be scaled further. Digital insurance administration systems can increase insurance enrolment, especially among low-income households. There are three enabling contexts for digital insurance plan adoption: supportive regulation, public-private partnerships, and ongoing stakeholder contact and education. There are three essential requirements for digital health insurance programs to be widely adopted in India and other similar situations. (i) user-friendliness; (ii) an established network for digital insurance policies; and (iii) confidence, which may be shown through measures like encrypted data storage, complete audit trails, and built-in fraud protection. Our results prove that digital health technologies hold great promise for achieving UHC in LMICs. 2024 Scrivener Publishing LLC. -
Impact of Childhood Trauma on Psychological Distress and Personality Pathology in Young Adults
Adulthood is a time of change, thus stressful. A predetermining factor to this is a provision for a safe environment during the crucial years of life (childhood). Children make meanings of everything and are more dynamic in the early developmental years. It is a basis for their overall development and defines their coping mechanisms during adulthood. Therefore, if they develop faulty meanings of themselves, others, and the world at large, it can alter their abilities to function during adulthood. It is fundamental to understand the psychological well-being and personality traits in adulthood by this very nature of traumatic experiences in childhood. This paper is a conceptual framework discussing a three-tier model to retrospectively understand the impact of childhood trauma on psychological distress and personality pathology in adulthood. This paper suggests future research to focus on developing intervention and prevention models for young adults (childhood trauma survivors) on positive parenting practices. The Electrochemical Society -
Perceived Reality of Self and Others with Two Childhood Trauma Survivors - An Idiographic Case Study
Impacts of childhood trauma can be crucial in understanding personality traits and psychological distress. However, it could be hard to predict if these individuals develop posttraumatic stress or growth. Several quantitative research studies have concluded the connections between childhood trauma and psychopathology or maladaptive personality traits. Various researchers have discovered the negative consequences of early childhood trauma and its long-term effects which may be rudimentary in understanding the causation of life-long psychological and medical deficiencies. This has been very elementary in understanding trait patterns and psychopathology for outcome generalizability and implementing prevention and intervention models. However, these studies still fail to spotlight the importance of the lived experiences of trauma survivors. Nevertheless, the present study is an idiographic single-case study research design used in the exploration of the lived experiences and perceived reality of self and others with two childhood trauma survivors. The Electrochemical Society -
Green Fuel Combustion Synthesis of CeO2 and Ag/CeO2 Nanoparticles for Photocatalytic and Antibacterial Applications
Silver-doped cerium oxide nanoparticles (Ag/CeO2 NPs) were synthesized using Ricinus communis seed extract as a bio-derived fuel in a solution combustion method. The combustion reaction, carried out at 450C with AgNO3 and (NH4)2[Ce (NO3)6] as metal precursors, produced CeO2 and Ag/CeO2 NPs. Their structure and morphology were estimated by P-XRD and TEM, which confirmed the formation of cerianite with cubic fluorite CeO2 crystal structure, while SEM revealed a porous morphology characteristic of combustion-driven gas evolution. EDS revealed the presence of Ce, O, and Ag in the Ag/CeO2 NPs. Optical studies, including UVVis and PL, showed that Ag incorporation narrowed the band gap and improved charge-carrier separation, contributing to enhanced visible-light activity. XPS analysis verified the successful incorporation of Ag species into the CeO2 lattice. Among the investigated NPs, the 0.3 wt% Ag/CeO2 sample exhibited the lowest PL intensity, indicating improved charge-carrier separation, which was further supported by its high quantum yield (0.789). These results correlate with its enhanced photocatalytic activity. The nanomaterials were evaluated for dye degradation, Cr (VI) reduction, photocatalytic H2 evolution, and antibacterial activity. The influences of pH, catalyst dosage, dye concentration, light intensity, radical scavengers, and recyclability were also systematically assessed. Overall, the study presents a sustainable synthesis approach for high-performance Ag/CeO2 NPs with broad potential in environmental remediation and antimicrobial applications. 2026 The Author(s). Asia-Pacific Journal of Chemical Engineering published by Curtin University and John Wiley & Sons Ltd. -
Impact of Ionic Liquids on the Crystal Growth and Surface Morphology of Ruthenium-doped TiO2 Nano Heterojunction Structures for Improved Photocatalytic Degradation of Evans Blue Dye and the Associated Antibacterial Activities
Novel Ru-doped TiO2 nanocomposites (Ru/TiO2 NCs) were synthesized at a 130 C temperature and 24-h incubation period using hydrothermal methods with and without ionic liquids (ILs). NCs were synthesized using 1-butyl-2,3-dimethylimidazolium tetrafluoroborate as the ILs and titanium(IV) isopropoxide and ruthenium(III) nitrate as the precursors. The presence of Ru in the NCs was analyzed using different characterization techniques. Powder X-ray diffraction and transmission electron microscopy confirmed the presence of anatase and rutile phases as well as the nanocrystalline texture of the prepared Ru/TiO2 NCs. The presence of Ru, Ti, and O was confirmed via energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy. The optical properties and bandgap energies of Ru/TiO2 NCs were determined via ultraviolet (UV)visible (Vis) diffuse reflectance spectroscopy; the optical properties exhibited a redshift in the optical response toward the visible region owing to the reduced bandgap energy of Ru/TiO2 NCs in the visible region after doping Ru into the TiO2 nanocrystalline structure. Scanning electron microscopy images revealed a highly voluminous and porous network of Ru/TiO2 NCs. Moreover, different concentrations of Ru were doped into the TiO2 matrix to investigate the photocatalytic and antibacterial activities. Among all the synthesized NCs, 0.3-wt% Ru/TiO2 NCs exhibited high photocatalytic degradation efficiency and was therefore considered the optimum concentration. Moreover, it exhibited the highest BET surface area and quantum efficiency compared with other Ru/TiO2 NCs. Results revealed that Ru/TiO2 NCs synthesized via IL-assisted hydrothermal method, i.e., R3TL, exhibited considerably enhanced photocatalytic and antibacterial activities compared to the NCs synthesized without the ILs, i.e., R3TH. The inhibition pattern showed an excellent zone of inhibition (p < 0.001) in several strains with both NCs (R3TL and R3TH). However, Gram-positive Staphylococcusaureus exhibited a remarkably increased zone of inhibition (35 mm) compared with all the other strains used for R3TH. In contrast, Bacillus sp. exhibited the second largest zone of inhibition (21 mm) for R3TL after S. aureus (34 mm). In summary, this study emphasized the role of ILs and reaction mechanisms. The author(s) 2025. -
Eco-friendly synthesis of NiO and Ag/NiO nanoparticles: Applications in photocatalytic and antibacterial activities
Herein, NiO and Ag/NiO NPs were produced via the solution combustion method using nickel nitrate and silver nitrate as oxidizers and Cocos nucifera water as a fuel at 450C. The study also explores their applications in photocatalytic dye degradation, H 2 production and antibacterial properties. The primary advantage of using C. nucifera water as a green fuel in the solution combustion method is that it serves a dual purpose - both as a fuel and as a solvent. This eliminates the need for additional water to create a homogeneous redox mixture of fuel and oxidant in the experimental procedure. X-ray diffraction confirmed the existence of Ag in the bunsenite form of rhombohedral structure with a simple cubic system, with particles sized at 31-44 nm. Energy-dispersive X-ray spectroscopy revealed Ni, O and Ag weight percentages of 48.2, 44.5 and 7.3%, respectively. X-ray photoelectron spectroscopy confirmed the formation of Ag in NiO nanostructure. UV-visible spectrometry showed reduced band gap energy of Ag/NiO NPs (3.03-2.87 eV) compared to the bare NiO NPs (3.21 eV), red shift of the optical response towards the visible region after doping Ag into the NiO. The 0.3 wt% Ag/NiO NPs showed the highest quantum efficiency (0.781) among the other synthesized NPs. Fourier-transform infrared spectroscopy revealed absorption bands in the range of 460-900 cm -1 stretching vibrations of Ni-O and Ag-O. Photoluminescence spectroscopy indicated that a doping concentration of 0.3 wt% Ag effectively introduces donor levels, defect levels and surface trap states within the NiO nanocrystalline structure, enhancing charge carrier separation and reducing recombination. Scanning electron microscopy revealed a voluminous, porous surface morphology characterized by numerous voids, resulting from the release of various combustible gases during the combustion process. Transmission electron microscopy images showed that most particles were spherical, irregular in size and well-distributed, with minimal aggregation with an average particle size of 25.8 nm. BET analysis of both NiO and 0.3 wt% Ag/NiO NPs exhibited type IV adsorption isotherms, indicating mesoporous structures and a clear monolayer-multilayer adsorption process, 0.3 wt% Ag/NiO NPs showed the highest surface area (170 m2 g-1) compared to the NiO (130 m2 g-1) NPs. Ag/NiO NPs has demonstrated a promising H2 evolution rate of 1212 ?mol g-1 under visible light illumination in a water/ethanol system. The trypan blue dye degradation reaches up to 98% and has moderate stability for the reusable photocatalysis process. The synthesized NPs exhibited significantly enhanced antibacterial activity against a range of bacterial strains. 2025 The Authors. -
Role of Ionic Liquids in Hydrothermal Synthesis of Li-Doped CuO Nanoparticles: Improved Photocatalytic, Electrochemical, and Antibacterial Properties
Lithium-doped copper oxide nanoparticles (Li-CuO NPs) were synthesized via an ionic-liquid-assisted hydrothermal method to examine the role of ionic liquids in tailoring structural and functional properties. PXRD analysis confirmed phase-pure monoclinic CuO (JCPDS/PDF No. 45-0937), with a reduction in crystallite size from 46nm (CuO) to 39nm upon Li incorporation. BET analysis revealed mesoporous characteristics with a specific surface area of 85m2 g?1 and an average pore diameter of 10nm. Optical studies showed a red shift in absorption and a band gap narrowing from 2.61eV (CuO) to 2.35eV (Li-CuO), indicating enhanced visible-light absorption. The photocatalytic performance of Li-CuO NPs was evaluated using Evans Blue dye under visible-light irradiation, achieving 96.67% degradation within 2h, along with good stability over repeated fourth cycles. The effects of various parameters, including pH, catalyst loading, dye concentration, illumination intensity, and the recyclability and reusability of the catalyst, were also investigated. Electrochemical studies demonstrated enhanced redox activity and improved charge-transfer behavior for dye sensing. In addition, Li-CuO NPs exhibited significant antibacterial activity, attributed to lithium-induced defects, and increased surface reactivity. These findings highlight ionic-liquid-assisted lithium doping as an effective approach for improving the multifunctional performance of CuO-based nanomaterials. 2026 Wiley-VCH GmbH. -
Wear rate prediction of hybrid composites: A comparative study using experimental analysis, finite element simulation and machine learning prediction
This study evaluates wear rate predictions by comparing experimental results with Finite Element Analysis (FEA) simulations, focusing on the influence of track radius. Regression models were developed to analyze the trends, while residual analysis identified deviations between the two approaches. A correlation matrix highlighted significant relationships between wear rate, pressure, and sliding distance. Confidence interval analysis confirmed the reliability of both models, though polynomial regression provided a more accurate representation of wear rate trends than linear models. While FEA predictions are closely aligned with experimental data, some discrepancies suggest the need for further refinement in computational modeling to improve accuracy. Future work will focus on enhancing FEA simulations and expanding experimental validation for better predictive reliability. 2025, Malaysian Tribology Society (Mytribos). All rights reserved.