Unveiling the Role of FinTech in Advancing Sustainable Development Goals: A Structural Equation Modeling Approach

The integration of financial technology (FinTech) into modern economic systems has sparked significant interest regarding its potential to accelerate progress toward the United Nations Sustainable Development Goals (SDGs). This study investigates the structural relationship between FinTech adoption and five selected SDGs—Economic Growth, Quality Education, Gender Equality, Reduced Inequalities, and Climate Action—mediated through Financial Inclusion and Digital Literacy. Using a Structural Equation Modeling (SEM) framework, we surveyed participants across diverse socio-economic backgrounds to assess how FinTech-driven financial inclusion and digital capability influence sustainable development outcomes. The model reveals that Digital Literacy is the strongest mediating factor, significantly enhancing Economic Growth (β = 0.904), Quality Education (β = 0.829), and Reduced Inequalities (β = 0.859). In contrast, Financial Inclusion plays a more moderate yet targeted role, particularly in addressing inequality and gender-based financial access. These findings suggest that while FinTech infrastructure is foundational, its real developmental impact is realized through empowerment mechanisms—especially digital literacy. Policymakers and stakeholders are urged to focus on user education and inclusivity when deploying FinTech solutions to ensure alignment with global sustainability objectives

Design and Implementation of AHB to APB Bridge using Verilog

Efficient on-chip communication is vital in modern embedded and System-on-Chip (SoC) architectures. This project presents the design and implementation of an AHB (Advanced High-performance Bus) to APB (Advanced Peripheral Bus) bridge using Verilog Hardware Description Language (HDL). The bridge serves as an interface between high-speed AHB masters and low-speed APB peripherals, with a Finite State Machine (FSM) governing the control flow—including address decoding, data transfer, and handshake signal management. The Verilog-based design emphasizes modularity, timing accuracy, and hardware compatibility, making it well-suited for both FPGA prototyping and ASIC integration. Functional simulation and synthesis validate the bridge’s correctness, performance, and efficient resource utilization. The FSM-based control ensures predictable and reliable communication across the AHB and APB domains, fulfilling the structured connectivity demands of AMBA-based SoC designs [1]

Reexamining the Equation of State: A Crucial Advancement in Practical Thermodynamics

Thermodynamics has been wrestling with finding a single equation that ties together pressure, volume, and temperature for ages. The usual suspects, such as the ideal gas law and the van der Waals equation, often struggle when conditions become extremely extreme. However, Xue and Guo arrived in 2025 with a different approach. They developed a macroscopic model, based entirely on the laws of thermodynamics, without needing to delve into molecular details. What\u27s neat is how their approach links up what gases do when they\u27re sparse with how dense matter acts when crammed together, all thanks to a smooth, continuous mathematical expression that needs no extra tweaking. We are diving into that equation. We\u27ll examine the theory behind it, its performance, and the extent to which it can be applied. It turns out that the model aligns well with real-world data for a wide range of gases, solids, and liquids.  It’s simple, accurate, fast to compute, and holds solemn promise in engineering, maybe even planetary science, education, and, definitely, more complex systems down the road

A Conceptual Enquiry on the Role of Academic Incubators in Nurturing Entrepreneurship among Students

Educated youth of India are finding it difficult to secure jobs and have an economically viable livelihood. To help the economy grow and create new jobs, the government needs to encourage new ideas and put money into the education of the next generation of workers. Entrepreneurship development can be a big part of the fight against unemployment and the growth of the economy as it makes possible conversion of innovative ideas into new businesses or start-ups resulting in creation of jobs. The government and the higher education institutes (HEIs) should work together to create an environment that is conducive to the launch of new businesses and shift the mindset of educated young people towards the pursuit of self-employment rather than job hunting. Many state governments, in conjunction with the central government, have enacted legislation to provide assistance to newly founded firms in their respective areas. And higher education institutions have also established incubation centers to nurture and assist entrepreneurial fervor among students. In a start-up ecosystem, in addition to the government, there are a wide variety of other institutions and ecosystem facilitators that provide assistance to start-up units. Some examples of these ecosystem facilitators and institutions include incubators, accelerators, educational institutions, research institutions, investors, and mentors (NGOs).  Higher education institutions and universities are playing a significant role in the promotion of new business ventures and the provision of platforms for enterprise creation. The study hypotheses, given the current entrepreneurial ecosystem in India, that entrepreneurship among students can be directly linked to the support offered to them by the academic incubators. The current study proposes a model for the establishment and operation of startup incubators within academic institutions, so that entrepreneurial fervour can be nurtured among students

Ecological Finance and Sustainable Environmental Management in Listed Nigerian Real Estate Institutions

As environmental challenges intensify globally, ecological finance has emerged as a transformative instrument to promote eco-conscious practices, particularly in sectors with high environmental footprints such as real estate. This study investigates ecological finance on sustainable environmental management within Nigeria’s listed real estate institutions. The study categorizes ecological finance into ecological funds, ecological support, ecological rights and ecological interests. Drawing from the Triple Bottom Line and Environmental Economics theories. A quantitative ex-post facto design was adopted using panel data from ten listed Nigerian real estate firms between for the period of ten (10) years 2015 to 2024. The results, analyzed using STATA, reveal that all ecological finance components have significant positive effects on sustainable environmental management, with ecological rights exerting the strongest influence. Correlation and regression analyses affirm the robustness of the findings, while heteroskedasticity and multicollinearity checks validate the model’s reliability. The study concludes that ecological finance is vital for enhancing environmental resilience and aligning real estate development with national and global sustainability targets. It recommends regulatory reforms, stakeholder education and tailored ecological finance products to strengthen adoption and drive green urban transformation in Nigeria’s real estate sector

A Prediction of The Air Quality Index: An Analysis of Ghaziabad City

PM10 is one of the main air pollutants that causes air pollution. This study used Artificial Neural Networks (ANN), a common learning technique, to estimate the impact of this contaminant on human health and the environment using data between 2019 and 2023. The Pollution Control Board of Uttar Pradesh (UPPCB)\u27S air observation center obtained information related to the center of industry of Ghaziabad and finished the simulation and optimization procedures required using SPSS programming. Before being compared with the real data, the obtained air quality estimation results underwent a multilayer perceptron analysis. Moreover, there have been instances where the Ghaziabad province\u27s Air Quality Index (AQI) values have exceeded the allowable limit, especially during times of great output

Integrating Deep Residual Learning and Thematic Analysis in a Hybrid Framework for Precision Oncology: Advancing Cancer Diagnosis and Personalized Treatment

This study presents a novel hybrid framework that integrates deep residual learning with thematic analysis to enhance diagnostic accuracy and treatment personalization in oncology. By combining quantitative imaging features extracted via ResNet-50 with qualitative thematic embeddings derived from unstructured electronic health record (EHR) narratives, the system models both morphological tumor characteristics and patient-centered contextual factors. The framework was evaluated in a controlled simulation environment using synthetic multimodal datasets for breast and lung cancer. Results demonstrated that the hybrid approach significantly outperformed conventional image-only models. The late fusion model achieved an accuracy of 93.1%, F1-score of 91.3%, and an AUC of 0.96, compared to 87.4%, 84.9%, and 0.91, respectively, for the image-only baseline. Error rates were reduced by 45.2%, and thematic embeddings influenced classification decisions in 21% of cases—78% of which led to improved diagnostic correctness. Furthermore, the model exhibited strong calibration, with predicted probabilities aligning within ±3% of actual outcomes across all confidence bins. Attention-based mechanisms enabled dynamic prioritization of modalities, emphasizing thematic content in over 60% of clinically ambiguous scenarios. These findings provide compelling evidence for the integration of deep learning and thematic analysis in precision oncology. The hybrid framework not only improves predictive performance but also brings artificial intelligence systems closer to the interpretive and patient-centered standards of real-world clinical practice

Biometric Identification using Facial Vein Patterns

Biometric systems play a crucial role in personal identification, leveraging the reliability and distinctiveness of physiological or behavioral traits. Among these, vein patterns in the face have gained attention for their stability and security, offering a robust method for biometric identification. This paper focuses on advancing the field with a Face Veins Based MCMT Technique. This technique utilizes a Multi-Channel Multi-Threshold approach to enhance accuracy and reliability in identifying individuals based on their unique vein patterns. By exploring the development and application of this innovative technique, the research aims to contribute to the evolution of biometric systems, addressing challenges and improving the efficacy of personal identification technologies

Consumer Buying Behavior towards Organic Food Products among Urban Households

The organic food industry is rapidly gaining traction in urban markets due to increasing consumer awareness around health, sustainability, and food safety. As people grow more conscious about the harmful effects of pesticides, synthetic additives, and genetically modified organisms, organic food has emerged as a healthier and more ethical alternative. This research examines the behavior of urban households in Ludhiana, Punjab—a fast-growing Tier-2 city-towards the consumption of organic food products. The study shows how consumer awareness, health motivations, pricing, accessibility, trust in certification, and socio-cultural factors shape purchasing decisions. The research is grounded in a descriptive design and employs a quantitative methodology to gather insights through structured questionnaires. Statistical tools such as factor analysis and regression modeling are used to examine the significance and impact of various influencing factors. Findings reveal that internal drivers like health consciousness and environmental concern are positively associated with higher purchase intent, while barriers such as price sensitivity and limited product availability hinder consistent consumption. Additionally, trust in certification and digital marketing influence purchase behavior significantly, especially among younger, socially aware consumers. This study provides critical insights for producers, marketers, and policymakers in the organic food sector. It emphasizes the importance of transparent labeling, strategic pricing, and targeted communication to build trust and improve accessibility. The findings aim to guide stakeholders in creating more effective, consumer-centric strategies to boost organic food adoption in urban markets. By focusing on Ludhiana as a case study, the research adds valuable understanding to the broader narrative of sustainable consumption in emerging Indian cities

Number Plate Detection using Deep Learning and Automatic Gate Control

In the realm of increasing security and automation, this research paper presents a novel approach to automatic gate control using number plate detection with OpenCV. The system leverages an Arduino microcontroller paired with a camera to identify and verify vehicle license plates at entrance gates, streamlining access control processes without human intervention. Building on methodologies and findings from existing literature, such as the use of PIC microcontrollers and MATLAB in previous systems, our approach integrates modern image processing techniques to enhance accuracy and reliability. Our system is designed to improve convenience and security at various premises requiring restricted access, including industrial facilities, academic institutions, and residential complexes. The camera captures vehicle images, which are then processed using OpenCV to extract and recognize the license plate numbers. Verified numbers trigger the Arduino to control a servo motor and buzzer, ensuring that only authorized vehicles gain entry. This study demonstrates the efficacy of combining hardware and software solutions to create an automatic gate control system that not only reduces the need for human oversight but also increases the speed and accuracy of vehicle entry management. The implementation highlights a significant reduction in processing time, aligning with contemporary needs for efficient and secure vehicle identification mechanisms in a world of growing vehicular traffic and security concerns