Volume 12 | Issue 7 |

 Abstract

Digital payment systems have revolutionized the retail sector, significantly influencing small retail businesses. This study examines the impact of digital payment systems on operational efficiency, customer satisfaction, and revenue growth in small retail businesses in Shivamogga. It identifies challenges and opportunities faced by retailers in adopting these systems and highlight the role of technology and government initiatives in promoting digital adoption. Data collected from 150 retailers through surveys and interviews reveal increased operational efficiency and customer reach but also underline persistent barriers such as technological illiteracy and infrastructure constraints. The study emphasizes the need for enhanced support systems to improve the effectiveness and inclusivity of digital payment platforms for small retail businesses.

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 Keywords

Digital Payment Systems, Small Retail Businesses, Customer Satisfaction, Operational Efficiency, Revenue Growth, Technological Barriers INTRODUCTION

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High-tech tools are changing fast, creating new ways to grow but also new risks that businesses don't know about. Cyber risk is one of the most significant risks in the financial sector of companies as online financial services and finance operations are part of everyday life. According to the survey conducted by the National Bank of Lithuania in late 2018, the possibility of cyber threats and their possible effects on the financial system of Lithuania is one of the most serious problems and should be given the highest priority. So, it's crucial to know which cyber threats in financial companies are the worst and most probable. Also, to know how companies in the financial sector rank their readiness and willingness to deal with this kind of cyber risk management and control. This research is important for financial institutions as a way to improve their cyber risk management processes, improve preparedness and cyber security and identify potential threats to the organization.

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 Keywords

-- Cybersecurity, Financial Sector, Risk Management, Machine Learning, Threat Detection, Data Protection,

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 Abstract

Aarakshit Varg tatha Anaarakshit Varg ke Gramin evam Shahri Vidyarthiyon ki Sanvegatmak Buddhi ka Tulanatmak Adhyayan

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Aarakshit Varg tatha Anaarakshit Varg ke Gramin evam Shahri Vidyarthiyon ki Sanvegatmak Buddhi ka Tulanatmak Adhyayan

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Teaching Arabic phonetics to non-native speakers has emerged as a critical research field due to increased global demand for the Arabic language for educational, professional and religious purposes. Despite this growing interest, learners struggle to identify, differentiate and articulate Arabic phonemes accurately--particularly emphatic, uvular, pharyngeal and glottal sounds not found in many Indo-Aryan and European languages. These difficulties often lead to phonological interference, communication barriers, and semantic distortion. The current study investigates the linguistic, cognitive, sociocultural and pedagogical constraints faced by learners during phonetic acquisition. The research follows descriptive and analytical methods to examine classroom experiences and phonetic learning outcomes. Findings reveal that lack of systematic phonetic instruction, inadequate exposure to authentic Arabic pronunciation, and dependency on memorization-based learning significantly hinder phonetic mastery. This study proposes a multi-layered classroom framework integrating articulatory phonetics, audio-visual pronunciation tools, minimal-pair drills, peer-interaction exercises and corrective feedback mechanisms. Results demonstrate that structured phonetic instruction substantially enhances pronunciation accuracy, fluency, and learner confidence.

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 Keywords

Arabic phonetics; non-native speakers; pronunciation accuracy; phonological interference; articulatory phonetics; classroom solutions; minimal-pair drills; audio-visual learning; phoneme acquisition; second language pedagogy.

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Delhi, as India's national capital and a Union Territory with partial statehood, presents a unique case in the country's federal framework. This asymmetric federal arrangement, governed by Article 239AA of the Constitution, creates a complex governance model where the elected government shares power with the centrally appointed Lieutenant Governor (LG). This paper examines how Delhi's asymmetric federalism challenges India's federal unity and cooperative federalism, focusing on administrative conflicts, legislative limitations, judicial interventions, and their broader implications. By analysing constitutional provisions, historical developments, and recent disputes, it argues that the ambiguous division of powers undermines effective governance and federal harmony. Recommendations are proposed to align Delhi's governance with the principles of cooperative federalism while respecting its role as the national capital.

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 Keywords

Cooperative Federalism, Asymmetric Federalism, Administrative Conflicts, Legislative Constraints, Judicial Interventions

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Creative Commons Attribution 4.0 and The Open Definition

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The evolving environmental landscape demands a fundamental reorientation of public administration toward sustainability-driven governance. This study investigates how administrative frameworks can embed ecological principles within institutional structures, policy processes, and service delivery mechanisms. It examines the strategic integration of sustainability into governance models, identifies persistent challenges impeding the adoption of green policies--such as bureaucratic inertia and resource limitations--and explores innovative approaches that enhance eco-conscious public services. Special emphasis is placed on digital governance as a transformative tool, enabling transparency, data-driven decision-making, and citizen engagement in environmental policy implementation. The study concludes by advocating for administrative reforms and capacity-building strategies that position public institutions as key agents in shaping a resilient and sustainable future.

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Sustainable Public Administration, Green Governance, Environmental Policy Integration, E-Governance, Climate-Responsive Governance

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There are many enzymes produced by microorganisms having potential applications in industrial sectors. Out of which keratinase is one of the major enzymes having applications in tanning industry. The exact role of keratinase in cleaving keratin substrate has not been well studied. In present study, an attempt is made to understand the amino acid residues of keratinase interacting with keratin. The predicted model of keratinase was validated by Ramchandran plot and Verify-3D to check the quality of model. The docked complex of keratinase with keratin revealed the stable hydrogen bonding interactions. After molecular dynamics (MD) simulation studies it has observed that the amino acid residues such as PRO74, VAL158 and THR262 of keratinase from Streptomyces badius showed stable hydrogen bonding interactions with GLU390, GLN393 GLU394, ASN395, TYR398 of keratin substrate. Hence, MD analysis supports that keratinase from Streptomyces badius.strain shashi can efficiently cleave keratin. Thus, the present study would be useful to understand the enzymatic mechanism of keratinase to cleave keratin in detail at molecular level.

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 Keywords

Streptomyces badius. strain shashi ,keratinase, Homology modelling, Ramchandran plot, Molecular Dynamic Simulation.

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The role of financial technology (fintech) in enhancing financial inclusion has garnered significant attention in recent years, especially in emerging markets. Fintech innovations, such as mobile banking, digital wallets, peer-to-peer (P2P) lending, and microfinance platforms, have the potential to bridge the gap between the unbanked and underbanked populations and the formal financial system. This paper explores how fintech is transforming access to financial services, reducing barriers to entry, and improving the overall economic well-being of underserved communities. By leveraging mobile technology and data analytics, fintech is enabling financial services that are more affordable, accessible, and tailored to the needs of marginalized groups. However, challenges such as digital literacy, regulatory frameworks, and cybersecurity risks must be addressed to fully realize the benefits of financial inclusion. This research presents an overview of the fintech landscape, case studies of successful fintech initiatives, and discusses the potential for future growth in the field of financial inclusion.

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 Keywords

Financial Technology (Fintech), Financial Inclusion, Mobile Banking, Digital Wallets, Economic Development and Regulatory Challenges

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The rising climate-induced threats in coastal zones, such as sea-level rise, storm surges, and extreme weather events, create major challenges for marine engineering projects by affecting their feasibility and construction durations. The traditional scheduling methods show limited effectiveness when managing these regions' elevated uncertainty and environmental variability. The research focuses on adaptive scheduling models that address high-risk marine engineering projects operating within climate-vulnerable coastal areas. The analysis reviews various scheduling methods, including dynamic probabilistic systems and scenario-based and buffer-driven approaches, by examining global infrastructure projects affected by climate change. The review demonstrates traditional scheduling tools have weaknesses and emphasizes the necessity of scheduling models that merge time-sensitive climate information with risk assessment capabilities. The results indicate that mixed and adaptable scheduling systems create reliable systems that will become vital for coastal engineering project management in the future. The paper ends by providing implementation suggestions and outlining future research pathways.

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Adaptive Scheduling, Marine Engineering, Climate Change, Coastal Infrastructure, Risk Management, Project Planning, Dynamic Scheduling, Scenario Analysis

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The rapid advancements in machine learning, big data analytics, and cyber-physical systems have significantly influenced diverse fields, including healthcare, manufacturing, and artificial intelligence. In healthcare, machine learning models have demonstrated promising capabilities in identifying gene biomarkers for breast cancer prognosis and treatment decisions, leveraging genomic and transcriptomic data. Circulating microRNAs and gene expression signatures have emerged as crucial diagnostic and prognostic biomarkers, facilitating personalized medicine approaches. In manufacturing, the integration of big data analytics and Industry 4.0 technologies has revolutionized defect detection, predictive maintenance, and flexible manufacturing systems. Cyber-physical systems and artificial intelligence have enabled intelligent decision-making, optimizing production processes and resource management. Virtualization and the Internet of Things (IoT) further enhance the interconnectedness of manufacturing ecosystems, promoting sustainability and efficiency. The evolution of artificial intelligence, particularly deep learning and support vector machines, has propelled advancements in data-driven decision-making. Techniques such as random forests, synthetic minority over-sampling (SMOTE), and Bayesian classification have enhanced predictive analytics across multiple domains. The application of big data in healthcare and manufacturing underscores the transformative potential of data-driven methodologies, ensuring improved outcomes, cost efficiency, and innovation. This study synthesizes research on machine learning, big data analytics, and cyber-physical systems, highlighting their implications in healthcare, manufacturing, and artificial intelligence. The findings provide insights into emerging trends, challenges, and future opportunities in these domains, emphasizing the role of advanced technologies in shaping modern industries.

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 Keywords

Machine Learning, Big Data Analytics, Cyber-Physical Systems, Artificial Intelligence, Predictive Analytics, Industry 4.0, Smart Manufacturing, Healthcare AI, Personalized Medicine, Genomic Data Analysis, Medical Imaging, Deep Learning, Support Vector Machines, Random Forest Algorithm, SMOTE, Bayesian Classifier, Ensemble Learning, IoT in Manufacturing, Cloud Computing, Digital Twin Technology, Predictive Maintenance, Quality Control Automation, Risk Assessment, Cybersecurity, Ethical AI, Data P

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