Volume 12 | Issue 7 |

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 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.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 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

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cleanness in the food label has attracted consumer interest and has quickly transformed into the Clean Label Movement that impacts the production of food items. The major consumer trends explored include emerging demand for natural and minimally processed foods as consumers look for more transparency for simplicity and sustainability. It also outlines the development of the Clean Label Movement and how it has set the tone for consumers' demands and reshaped the menu in the food and drinks sector. Regarding the topics, it analyzes the problems brands encounter when searching for ways to reformulate products according to clean-label demands and how brands can capitalize on if they support the values consumers believe in, such as health, sustainability, and authenticity. This paper explores features of the Clean Label Movement's future, including technology, personalization, and sustainability. Because of increasing consumer knowledge, clean-label principles are expected to move beyond the food industry, offering fresh chances in other spots. Therefore, the article is useful in understanding the Shifts in the Clean Label Movement and how they will impact future decisions on products and consumers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Clean Label Movement, consumer expectations, product development, transparency, sustainability, natural ingredients, food industry, ethical sourcing, innovation, personalized nutrition, functional foods.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The current Convergent parallel mixed method study is a result of a pilot study conducted on 5 subjects by using in-depth interviews for qualitative data to explore lived experiences and 25 subjects for quantitative data to assess the health consequences of female sex workers registered with selected NGOs. A purposive sampling technique was used to allocate the samples and data were collected with the help of a quantitative Interview Schedule. The findings of the study revealed that according to General Health Assessment, most of the women are anaemic and also have systemic health-related issues like hypertension, diabetes, skin infections, and urinary tract infections, and for Mental Health Assessment - DASS-42 depict that 95.3% of respondents (261 individuals) are in the severe stress category (scores 85-126), 4.7% (13 individuals) are moderate (43-84), and no one is in the mild category (0-42). For Qualitative data collection, a Semi-structured Interview guide (Audio-tape recorder) was used to determine factors that forced or influenced them to enter into sex work. After the guided interview, the researcher found the facts that low income, Influence of peers or social networks, Human trafficking or exploitation, Desire for financial independence, History of trauma, abuse, or exploitation, Mental health issues (e.g., depression, anxiety), Substance abuse or addiction, Family or relationship problems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

lived experiences, health consequences, female sex workers, NGOs

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

B2B customer support is on the horns of choosing how to deliver right and speedy answers to complicated questions. In this knowledge creation paper, the author presents a new Generative AI framework that enables the creation and constant update of knowledge bases using information from product documentation, CRM data, and customer feedback. The model saves considerable amounts of response time and support accuracy since the creation and the maintenance of the knowledge resources are automated. This in turns delivers real-time contextual insights to support the teams. Reduced ticket resolution time by 30% and uplifted customer satisfaction score by 20% in a pilot phase with a SaaS firm. Due to these results, it can be stated that the implementation of AI solutions in B2B customer support can significantly contribute to the development of mechanisms for further expansion, thereby meeting the requirements of evolving B2B business environments. The study stresses the importance of the adoption of Generative AI as an enhancement tool for the customer support subsystem.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Generative AI, Customer Support, Knowledge Base, CRM Integration, AI Framework, Customer Satisfaction

  License

Creative Commons Attribution 4.0 and The Open Definition