Vannan Livelihood Carried in " Koveru Kazhuthaigal" (Mules)

Narratives are a literary form that records contemporary events. From time to time, authors record the realities of life through stories in Tamil literature. Especially in the lives of the people of the lower classes, they express external attitudes such as beliefs, customs, rituals, food habits, occupations, and internal attitudes such as love, anger, mercy, happiness, suffering, and poverty through stories. In this regard, writer Imaiyam has written novels like Sedal, Arumugam, En Kathe and short stories like Manbaram, Video Mariyamman, Kolacheval, Saavuu Soru, Narumanam, etc. Another of his novels, "Mules", chronicles the lives of Vannan (Washermen) people. This article presents some of its parts. The daily events, problems, speech patterns, diet, occupations, marriage events, death rituals, festivals, proverbs they follow in practice, and omens spoken in front of them are explored in this article based on this novel

Nanotechnology applications in medical diagnosis, imaging, and therapy

Tremendous advances in molecular and personalized medicine also present challenges for translation of innovative experimental approaches into clinically relevant strategies. To overcome some of these challenges, nanotechnology offers interesting solutions for disease prevention, diagnosis, and treatment. For many systemic diseases, overcoming biological barriers and target specific delivery are the key challenges. Additionally, newer generation of molecular therapies, such as gene therapy, oligonucleotides, and RNA interference (RNAi) require robust and highly specific intracellular delivery strategies for effective and clinically meaningful therapeutic outcomes. In this presentation, I will cover several of our approaches for development of multifunctional engineered nano-systems for targeted therapies in the treatment of cancer, pain, and inflammatory diseases. Specific examples will include: (1) use of combinatorial-designed engineered nano-systems for RNA interference therapy in treatment of tumor multidrug resistance and genetic modulation of macrophage phenotype to promote anti-inflammatory effect in the treatment of autoimmune disorders. In each of the above examples, we focus on challenging medical problems with innovative solutions that use safe materials and scalable fabrication methods in order to facilitate clinical translation and improve patient outcomes

Language learning strategies : a narrative literature review

Language Learning Strategies (LLS) are the steps or actions that a learner consciously takes to improve and regulate his or her language learning (Cohen & Macaro, 2009; Griffiths, 2013; Oxford, 2011). This chapter focuses on a narrative review of the use and effectiveness of LLS in second language learning (L2) contexts. This investigation provides teachers and researchers with a thorough understanding of LLS besides highlighting research gaps

Test Center Location Problem: A bi-objective Model and Algorithms

The optimal placement of healthcare facilities, including the placement of diagnostic test centers, plays a pivotal role in ensuring efficient and equitable access to healthcare services. However, the emergence of unique complexities in the context of a pandemic, exemplified by the COVID-19 crisis, has necessitated the development of customized solutions. This paper introduces a bi-objective integer linear programming model designed to achieve two key objectives: minimizing average travel time for individuals visiting testing centers and maximizing an equitable workload distribution among testing centers. To address this problem, we propose a customized local search algorithm based on the Voronoi diagram. Additionally, we employ an $\epsilon$-constraint approach, which leverages the Gurobi solver. We rigorously examine the effectiveness of the model and the algorithms through numerical experiments and demonstrate their capability to identify Pareto-optimal solutions. We show that while the Gurobi performs efficiently in small-size instances, our proposed algorithm outperforms it in large-size instances of the problem