AISECT University

This study investigates the synthesis and evaluation of glycine-conjugated 5.0G polypropyleneimine dendrimers as an advanced nanocarrier system for the selective delivery of chloroquine. 5.0G PPI dendrimers were synthesized via a divergent method and subsequently conjugated with glycine. Comprehensive characterization confirmed the successful modification and an increase in nanocarrier size. Drug loading studies demonstrated a significantly enhanced entrapment of chloroquine (57.5

Aspect Based Sentiment Analysis (ABSA) has emerged as a crucial research area in Natural Language Processing (NLP), offering fine-grained insights into opinions by identifying sentiment towards specific aspects of a given entity. This paper presents a comprehensive overview of ABSA, detailing the interactions between core components such as aspect term extraction, sentiment classification, opinion-target association, and domain adaptation. By tracing the evolution of sentiment analysis from early machine learning techniques to contemporary transformer-based models such as BERT, RoBERTa, and GPT, the paper provides a clear framework for understanding the progression of the field. A systematic categorization of ABSA’s fundamental components is offered, alongside an in-depth discussion of datasets and benchmarking strategies commonly used in ABSA research. Applications in industries such as e-commerce, healthcare, finance, education, and social networks are explored, with particular attention to the role of ABSA in distinguishing human-generated and AI-generated content. We have also identified and addressed significant challenges in ABSA, including managing implicit aspects, handling sentiment drift, developing multilingual and code-mixed solutions, and scaling for real-world deployment. Actionable recommendations emphasize the integration of ABSA with explainable AI, multimodal sentiment analysis, and prompt-based learning to advance the field. To the best of our knowledge, this is the first comprehensive state-of-the-art review on ABSA. The paper concludes with insights into future research directions, highlighting the need for innovative approaches to overcome current limitations and harness ABSA’s full potential in large-scale industrial applications, which might serve as a valuable resource for researchers and practitioners aiming to develop robust, accurate, and adaptable sentiment analysis systems.

The present review critically synthesizes electrochemical technologies for early detection of food allergens and spoilage biomarkers, addressing critical gaps in the food safety paradigms. Unlike previous reviews, this work uniquely integrates both topics under a unified framework, demonstrating shared analytical challenges including matrix interference, cross-reactivity, and field deployment while proposing solutions through nanomaterial modifications and molecularly imprinted polymers (MIPs) aspects. Globalization intensifies and encourages the food diversity, necessitating rapid, sensitive, and portable detection methods. The review systematically compares amperometric, voltammetric, and impedimetric techniques across diverse food matrices, providing quantitative benchmarks (detection limits, response times, matrix effects), which are currently very rarely available in the existing literature. Advanced nanomaterials such as graphene, CNTs, MOFs, and MIPs enhances sensor selectivity, sensitivity, and stability in the complex environments milieu. Through case studies spanning smart packaging, portable devices, and IoT monitoring, this review demonstrates translational potential in the real-world applications. Critical analysis identifies persistent challenges and limits multi-analyte capabilities, regulatory barriers, and field validation gaps and challenges. We propose the electrode array designs, international harmonization frameworks, and industry-academia collaborations aspects. It is with the amalgamation of allergen-spoilage monitoring matters and shared detection chemistries, overlapping vulnerabilities, unified regulatory frameworks. this review provides a strategic insights for the advancement in the global food security through recent research synthesis.

This study establishes a genotype-specific transformation system for indica rice cultivars Ranjit, Mahsuri, and Kon Joha using 35S:RUBY and CRISPR/LbCas12a constructs, enabling functional genomics studies and genetic improvement. The indica rice subspecies generally faces challenges in functional genomics and genetic improvement due to its recalcitrance to tissue culture and Agrobacterium-mediated transformation. Three indica rice varieties, Ranjit, Mahsuri, and Kon Joha, cultivated in Assam (India) were selected to optimize callus induction, regeneration, and genetic transformation. Ranjit and Mahsuri are high-yielding cultivars, whereas Kon Joha is an indigenous aromatic landrace of high commercial value. Initially, key steps, such as callus induction and regeneration, were optimized for Ranjit and Kon Joha using mature seed. Thereafter, for transformation, immature embryos were selected as explants because of their competence for agro-infection. The highest callus induction frequency of 70.33

The baking system serves as the backbone of a country’s economy and plays a crucial role in its development. The banking system supports economic growth by mobilizing savings, granting loans, handling payments, supporting government policies, and maintaining financial stability. A distressed bank is one facing financial hardship due to high Non-Performing Assets, losses, mismanagement, or liquidity problems. Such banks often require regulatory assistance from a healthy, operating bank (an undistressed bank) to regain stability. Due to the interconnectedness of banks, the failure of one bank may trigger financial instability in others, a phenomenon known as systemic risk, and may lead to a banking crisis. So, it is important to have effective policies that can mitigate the spread of banking crises and thereby stabilize the country’s overall economy. This paper aims to develop an optimal strategy to eliminate systemic risk contagion in the banking sector. For this purpose, we propose a mathematical model consisting of four ordinary differential equations with two controls: measures taken by undistressed banks to provide liquidity and to guide risk management. In contrast, the other control represents financial support extended by the central bank, such as emergency credit lines, strengthening monitoring and supervision, and strict guidelines to reduce NPA. The model’s basic properties, such as non-negativity and boundedness of solutions, are established to demonstrate its financial feasibility. The basic reproduction number (ℛ_0) of the model is calculated using the next generation matrix method. The local and global stability results are obtained for both risk-free and risk equilibrium points. It is found that there is no chance of systemic risk contagion if ℛ_0<1 . Further, a delay model has been formulated and studied to investigate the impact of time delay in declaring an exposed bank as a distressed bank using numerical simulation. A semi-relative sensitivity analysis is performed to examine the most influential parameters affecting undistressed and distressed banks. Moreover, an optimal control problem is formulated to obtain a strategy that minimizes the number of contagious banks while incurring minimal associated costs. The existence of the optimal controls is shown, and the optimality conditions are obtained analytically. Finally, the proposed model is simulated to substantiate the analytical results, and the optimal control problem is solved numerically using a forward-backwards iterative method. This study provides an optimal control approach to mitigate the banking crisis by minimizing the number of distressed banks while incurring minimal investment.