Volume 13 | Issue 6 |

 Abstract

Artificial Intelligence (AI) is changing the way companies hire people by making it possible to automatically screen resumes, predict who will get the job, and assess behaviour. In addition to making things much more scalable and efficient, these new technologies also bring up significant ethical concerns, particularly the potential for algorithmic bias.This research presents a practical study on identifying and reducing bias in AI-powered recruitment systems.The research investigated how unfair decisions may occur due to bias in training data or decision-making models,especially with respect to sensitive attributes like gender.Using a dataset of resumes ,the system first detects bias and then applies three types of techniques to reduce it:before training (pre-processing),during model learning(in-processing) and after predictions(post-processing).Methods like Reweighing and Adversial Debiasing were used to improve fairness without significantly affecting accuracy.The fairness of the system was measured using metrics such as demographic parity difference and results showed that debiasing techniques can reduce discrimination in predictions. Additionally ,tools like LIME and SHAP were used to explain the model's decisions, helping users understand why certain resumes were favoured. This research supports the development of fair and transparent AI models for hiring.

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 Keywords

Artificial Intelligence in Recruitment, Algorithmic Bias, Ethical AI, Fairness in Machine Learning, Bias Mitigation Techniques

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Liver transplantation is a high-risk surgical procedure typically performed as a last resort to save patients' lives. The risk of complications arising from liver transplantation begins immediately after surgery and can persist for years thereafter. Rejection is the most serious and ongoing complication, which can potentially lead to the patient's death. This study aimed to assess the knowledge of staff nurses regarding complications and their management in liver transplantation patients and to determine the association between the knowledge levels with their selected demographic variables. To achieve this objective, a descriptive survey design was employed. A convenience sampling method was used to recruit 30 staff nurses, who participated in the study by completing a self-developed knowledge questionnaire. The data collected were subsequently analyzed using descriptive and inferential statistical methods. The pre-test results revealed that 20% of the staff nurses possessed adequate knowledge, while 36.66% demonstrated a moderate level of knowledge, and 43.33% exhibited low knowledge levels. The study concluded that the staff nurses' knowledge scores were inadequate, highlighting the need for further research to investigate the variables and determinants influencing their perceptions. This would facilitate a deeper understanding of the theoretical and practical aspects of transplantation and aftercare.

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 Keywords

Liver Transplantation, Rejection, Immune suppressants, Graft loss, Donor Organ

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This research analyzes the effectiveness and problems of supply chain management (SCM) in the water supply industry in the case of Coimbatore city. Owing to fast industrialization and population expansion, Coimbatore is experiencing growing pressure on its water supply system. The study seeks to explore the present SCM operations in water purchase, storage, movement, and delivery, as well as the role played by technology, policy, and customer feedback. Based on primary data gathered through standardized questionnaires and supplemented by secondary data from reports and journals, the research determines major inefficiencies and prescribes measures to enhance the operational performance, customer satisfaction, and sustainability.

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supply chain management

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Microneedle (MNs) technology is a recent advancement in biomedical science across the globe. The current limitations of drug delivery, like poor absorption, low bioavailability, inadequate skin permeation, and poor biodistribution, can be overcome by MN-based drug delivery. Nanotechnology made significant changes in fabrication techniques for microneedles (MNs) and design shifted from conventional to novel, using various types of natural and synthetic materials and their combinations. Nowadays, MNs technology has gained popularity worldwide in biomedical research and drug delivery technology due to its multifaceted and broad-spectrum applications. This review broadly discusses MN's types, fabrication methods, composition, characterization, applications, recent advancements, and global intellectual scenarios.

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MICRONEEDLES TECHNOLOGY FOR PAIN LESS DRUG DELIVERY

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 Abstract

Janjatiya vikas mein sarkari yojanao ki bhoomika

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Janjatiya vikas mein sarkari yojanao ki bhoomika

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Introduction: Protein Energy Malnutrition is a common and widely prevalent type of malnutrition in children residing in rural and urban slums, especially in developing countries. There are various factors influence the risk of under nutrition. Malnutrition plays a important role in morbidity and mortality of children. Objectives: 1. To find the prevalence of Protein Energy Malnutrition (PEM) among the children between 3-5 years and 2. to determine the association between the Protein Energy Malnutrition among the children between 3-5 years with their selected demographic variables. Method: A descriptive study was conducted to the children between 3-5 years in selected community areas of Bhubaneswar. Multi-stage random and convenience sampling technique was used to collect the samples. Data were collected by using structured interview technique. Data were analyzed by utilizing descriptive and inferential statistics. Result: According to IAP classification, Majority of children 48.9 % were in normal nutritional status, remaining children were suffering with grade I PEM (33.5%), grade II PEM (15.7%), grade III PEM (1.5%) and grade IV PEM (0.4%). Conclusion: This study concluded that, many children had Protein-Energy Malnutrition due to their low-socio economic status. Health education should be given to the mothers of under-five children suffering with PEM.

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 Keywords

Assess, Prevalence, Protein-Energy Malnutrition (PEM), Children and Community areas.

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This study analyses how artificial intelligence (AI) may enhance digital marketing strategies to increase revenue generation and compliance with the Goods and Services Tax (GST) in India. Effective GST implementation is hampered by issues including poor taxpayer participation, procedural complexity, and low awareness, especially among small and medium-sized businesses (SMEs). AI offers a game-changing solution to these problems. The study looks at how artificial intelligence (AI) techniques such as chatbots, machine learning, predictive analytics, and automated content delivery may enhance filing accuracy, promote real-time monitoring, and encourage personalized interaction. It also examines global viewpoints on AI-driven tax reforms and emphasizes the significance of ethical governance, tailored strategies for specific sectors, and adaptable policy frameworks. Drawing on secondary data and literature analysis, the study offers practical recommendations for incorporating AI into the GST ecosystem. It concludes that strategic adoption of AI, backed by transparency and collaboration between the public and private sectors, can modernize tax administration, minimize evasion, and promote inclusive economic growth.

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Artificial Intelligence, GST Compliance, Digital Marketing, Tax Revenue, Predictive Analytics, India, Fiscal Policy, Automation

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Magical realism, which was very much present in The House of the Spirits, is not present in my second book, Of Love and Shadows. And that's because my second book was based on a political crime that took place in Chile after the assassination of Salvador Allende, so it is a journalistic history. There is no magical realism in The Infinite Plan, Aphrodite, Daughter of Fortune or Portrait in Sepia, yet there is plenty of it in my first novel for children, City of the Beasts. The term magical realism has become quite popular and controversial since the 1980s. The term is a combination of an oxymoron. What the narrative mode offers is a way to discuss alternative views of reality. It was first used to refer to the German painterly movement that tried to capture the mystery of life behind superficial reality. It was later introduced in the 1940s as an expression of a blend of realistic and magical view of life in Latin America, expressed through its art and literature in the context of Latin America's various cultures. In the 1950s it was used in relation to Latin American fiction, but has since been adopted as the main term used to refer to all narrative fiction that includes magical events in realistic factual narrative. Haruki Murakami is a Japanese author who uses magical realism to explore themes such as loneliness and self-discovery in his works. Magical realism is a writing style that combines realistic elements with fantasy elements, and focuses on the effects of magical elements on characters.

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Magical Realism, Isabel Allende, Otalo Calvino, Haruki Murakam, Real and fantastical threads

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This study examines the political perspectives of Generation Z voters (aged 18-25) in Tamil Nadu, especially in the Chengalpattu district, focusing on their engagement with digital politics, party preferences, and vision for future governance. Using qualitative analysis of open-ended surveys with 70 urban college students with both first-time and registered voters. The study highlights how this digitally native generation is reshaping Tamil Nadu's political landscape by merging Tamil identity consciousness with globalized policy expectations. The study also enlightens the social media influence of shaping the opinions of the Gen Z voters. The findings suggest political parties must urgently adapt to Gen Z's digital engagement patterns and substantive governance demands to remain electorally relevant. This research contributes to understanding Tamil Nadu's changing youth political behaviour in the social media era, with implications for democratic participation in regional politics.

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Gen Z voters, Tamil Nadu politics, social media influence, youth political engagement, digital democracy

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Abstract This research explores the study skills of senior secondary students with a focus on gender comparison. A sample of 120 students (60 boys and 60 girls) from various senior secondary schools was selected. The study employed a quantitative survey method using a standardized Study Skills Inventory. Findings revealed no significant gender differences in most areas, except for memorizing and comprehension, where boys performed slightly better. The research underscores the need for gender-neutral academic support strategies to improve study skills and academic outcomes.

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Study Skills, Academic Achievement, Gender Comparison, Senior Secondary Education

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