Volume 14 | Issue 1 |

 Abstract

The socio-economic conditions of the Fisher folk are shaped by the interplay of economic, social, and environmental factors. Fisheries provide livelihoods for millions globally, especially in coastal and rural communities, contributing to food security, employment, and income generation. However, the sector often faces challenges such as overfishing, resource depletion, and climate change, which threaten sustainability and economic viability. Small-scale fishers, who dominate the sector, frequently operate in vulnerable conditions with limited access to capital, technology, and markets. Their incomes are often irregular and insufficient to meet basic needs, exacerbating poverty and inequality. Social issues such as inadequate education, poor healthcare, and gender disparities further compound challenges within fishing communities. Conversely, the demand for fish and seafood around the world has created ample economic opportunities, promoting trade and exports. Developing and testing a measurement tool to accurately evaluate the underlying dimensions found through Exploratory Factor Analysis (EFA) is the process of validating a scale in the context of researching the socioeconomic circumstances of the fishing industry. The validated scale ensures that the constructs such as economic stability, social well-being, environmental sustainability, and institutional support are accurately measured and interpreted.

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 Keywords

Fisher folk, food security, sustainability, economic viability, global demand, Exploratory Factor Analysis

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The growing adoption of data driven personalization has reshaped digital marketing practice, yet its relationship with long term customer retention remains under-explored relative to short term engagement outcomes. This study examines the association between data driven personalization strategies and customer retention outcomes across digital marketing contexts. Using a quantitative, observational research design, the study conducts a secondary comparative analysis of seven published case studies and peer reviewed empirical sources drawn from both academic and practitioner literature. Personalization initiatives are classified by intensity, and retention outcomes are assessed using reported metrics including retention rate, churn reduction, and repeat purchase behavior. The findings indicate a consistent positive association between analytics driven personalization and improved customer retention outcomes across multiple industries, including retail, subscription based services, and digital platforms. Higher intensity personalization approaches, such as predictive analytics and recommendation systems, are associated with stronger retention improvements than rule based or static personalization methods. Reported outcomes include retention rate increases of approximately 5 to 15 percentage points and churn reductions of 8 to 14 percent over observation periods ranging from 90 days to twelve months. The study contributes to marketing analytics research by shifting focus from engagement metrics toward retention based performance outcomes and by synthesizing fragmented evidence across academic and practitioner sources. From a managerial perspective, the findings highlight data driven personalization as a strategic capability for improving customer retention and long term value rather than a short term engagement tactic.

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 Keywords

data driven personalization, customer retention, marketing analytics, CRM, digital marketing

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IAN injuries are caused by dental surgical procedures or accidents resulting when the procedure does not go well or an unexpected complication arises. The first thing to remember regarding the potential progression of an injury from acute to chronic is to have an accurate diagnosis and classification of the injury. Furthermore, if there is evidence of nerve damage and persistent symptoms, the earlier these injuries are diagnosed, the better the chances of recovery. This review will also look at the different types of chronic IAN injuries, their treatment options, and the relative outcomes of patients with different presentations of IAN injuries.Prevention strategies for the risk of injury to the inferior alveolar nerve through pre-operative imaging, guided implant placement, proper anaesthesia management and surgical practice have been highlighted as the main strategies to decrease the number of injuries. The final section of the article provides an overview of the newest advancements in regenerative strategies for treating IAN injuries, as well as recommendations for future clinical practice and research.

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 Keywords

Inferior alveolar nerve injury, Paresthesia, Neurosensory deficit, CBCT, Microsurgical repair.

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The Ahom kingdom witnessed a series of capital shifts over the period of nearly six centuries, reflecting the dynamic interplay of geography, security, administration, demography and political exigencies. This study examines the evolution of Ahom capitals from Charaideo to Jorhat, highlighting the underlying reasons for each relocation. Charaideo, established by Sukapha in 1253 C.E., was chosen for its elevated, flood-free terrain, fertile agricultural land and central location, symbolising both spiritual sanctity and political authority. Subsequent shifts to Charagua under Sudangpha were driven primarily by security concerns, particularly the perceived threat from the Chutiyas, while retaining Charaideo's cultural significance. The establishment of Gargaon by Suklenmung marked a strategic and administrative consolidation, with fortified structures, advantageous transportation links and fertile surroundings enhancing state control. Later, Rudra Singha's transfer of the capital to Rangpur in 1699 A.D. responded to demographic growth, economic expansion and spatial constraints at Gargaon. Finally, the shift to Jorhat in 1794 A.D. under Gaurinath Singha was compelled by internal instability and the Moamaria rebellions, reflecting the declining strength of the Ahom monarchy and the prioritisation of immediate security over geographical advantages. The study also notes the symbolic continuity and legitimacy of capitals, as seen in the Moamaria rebels' decision to retain Rangpur as the seat of power. Overall, the shifting of capitals illustrate how environmental suitability, military strategy, administrative convenience and political legitimacy shaped state formation and governance in pre-colonial Assam.

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 Keywords

Ahom, Capital, Buranji, Swargadeo, Charaideo, Charagua, Gargaon, Rangpur, Jorhat

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Proconnect presents a novel Multi-Agent System (MAS) designed to automate and enhance the traditional recruitment workflow, addressing the inefficiencies and biases inherent in manual candidate screening and interviewing. The Proconnect system utilizes a specialized quartet of interconnected AI agents to manage the talent acquisition process end-to-end. First, the Resume Processing Agent employs a Large Language Model (LLM) to extract and structure critical data from unstructured resumes (PDF/DOCX), storing it in a query-able database. Next, the Candidate Selection Agent efficiently filters and shortlists applicants by matching recruiter-specified keywords and experience requirements against the structured data. Following this, the Questionnaire Preparation Agent dynamically generates job-specific and highly relevant interview questions. Finally, the Interviewer Agent conducts a conversational interview, analyzes the candidate's responses, and provides a final quantitative score and qualitative summary. By dividing the complex hiring task into specialized, modular functions, Proconnect delivers a transparent, scalable, and highly effective framework for automated talent acquisition, significantly reducing time-to-hire while improving the quality and consistency of candidate assessment.

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Proconnect, Multi-Agent System, AI Agents, Professional Profiles, Talent Acquisition, Resume Parsing, Automated Interviewing, Career Development, Personalization.

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The present study aim was to find out the impact of step aerobic training on selected endurance variables among badminton players. To attain the purpose of this study, 20 male badminton were selected as subjects at randomly in Pudukkottai District, Tamilnadu, India and the subject age were ranged from of 18 to 23 years and they were divided into two group and each group ten number of subjects. The selected participants were randomly divided into two groups such as group 'I' underwent aerobic training (n=10) for eight weeks and group II (n=10) acted as control they was not exposed to any specific training but they were participated in regular activities. The data on selected criterion variables such as vo2 Max and muscular endurance; it was assessed by Queens College Step Test and NHL push-and Pull Strength test respectively. The collected data were statistically analyzed by using dependent-'t' test and Analysis of Covariance (ANCOVA) was fixed at 0.05 level of confident. It was concluded that the Step aerobic training is an effective method for enhancing endurance variables in badminton players. Coaches and trainers should consider incorporating this training modality into structured programs to optimize player fitness and overall performance.

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Step Aerobics, Endurance, Badminton, Vo2 Max, Muscular Endurance

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Since independence in 1947, India has constitutionally committed itself to democracy, fundamental rights, and civil liberties. At the same time, the Indian state has enacted a range of extraordinary laws in the name of national security, public order, development, and social control. Many of these laws--often termed anti-people laws--have been criticized for curtailing civil liberties, enabling state excesses, and disproportionately affecting political dissenters, minorities, workers, and marginalized communities. This paper presents a historical and analytical overview of anti-people laws in independent India from 1947 to 2022, examining their origins, evolution, justifications, and impact on civil liberties. It also reviews judicial responses, civil society resistance, and contemporary debates, arguing that the tension between security and liberty has been a persistent feature of Indian democracy.

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Civil Liberties, Anti-People Laws, Indian Constitution, Preventive Detention, Emergency, UAPA, AFSPA, Democratic Rights

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Over the last decade, India has undertaken an unprecedented expansion in public infrastructure investment, recognising its central role in boosting gross domestic product (GDP), generating employment, and producing strong multiplier effects across the economy. Central government capital expenditure on infrastructure increased more than fivefold--from approximately INR2 trillion in 2014 15 to INR11.1 trillion in 2024-25. This article examines the institutional innovation of PRAGATI (Pro Active Governance and Timely Implementation) as a governance mechanism that enhances the efficiency, timeliness, and economic impact of large scale infrastructure spending. Drawing on official Government of India data, PRAGATI review outcomes, and sectoral evidence from transport, energy, and urban infrastructure, the paper empirically analyses the relationship between infrastructure capital expenditure, project execution efficiency, GDP growth, and employment creation. The findings suggest that PRAGATI, complemented by the PM Gati Shakti National Master Plan, has significantly reduced coordination failures, mitigated cost and time overruns, and strengthened the growth multiplier of public investment.

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 Keywords

PRAGATI, infrastructure investment, capital expenditure, GDP growth, employment, governance, PM Gati Shakti

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Human Robot Interaction (HRI) is an emerging research area focused on enabling robots to interact naturally and intelligently with humans. Most commercially available social robots are either expensive or limited to a single interaction mode, restricting their use in educational and research environments. This paper presents the design and implementation of a multi-touch sensing robot capable of real-time human interaction through touch, motion, vision, and voice inputs.The proposed system integrates touch sensors, ultrasonic sensors, a camera module, a microphone, and a gyroscope with a Raspberry Pi-based control architecture. Multiple sensory inputs are processed using an AI-based decision module to generate expressive outputs such as emotional eye animations, sound responses, and physical movements through servo motors and a four-wheel drive system. The robot demonstrates behaviors such as touch reaction, lift detection, obstacle avoidance, and person following.The developed robot serves as a low-cost, modular, and interactive platform suitable for STEM education, classroom demonstrations, and future research in affordable social robotics.

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Human Robot Interaction

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Ovarian cancer remains a leading cause of gynaecological cancer mortality, with treatment outcomes heavily dependent on accurate subtype classification. Manual interpretation of gigapixel Whole Slide Images (WSIs) is labour-intensive and challenged by extreme resolution, background noise, and class imbalance, particularly in large datasets such as UBC-OCEAN. This study presents a novel framework for ovarian cancer subtype classification that integrates a Vision Transformer (ViT-B/16) encoder within an attention-based Multi-Instance Learning (MIL) architecture. A hierarchical preprocessing pipeline incorporating texture-aware patch sampling is introduced to prioritize diagnostically informative regions by ranking patches using variance and edge density. The ViT encoder extracts context-rich representations from these selected patches, which are aggregated through single-head attention for slide-level prediction. The proposed system demonstrates strong classification performance across all five subtypes, achieving a balanced accuracy of 0.750, and offers a scalable, objective solution for computational pathology. These results highlight the effectiveness of combining transformer-based feature extraction with targeted sampling strategies to address key challenges in high-resolution medical image analysis and support more accurate personalized diagnostics.

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 Keywords

Ovarian Cancer, Subtype Classification, Multi-Instance Learning (MIL), Vision Transformer (ViT), Whole Slide Images (WSI), Computational Pathology, Texture-Aware Sampling

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