Volume 12 | Issue 5 |

 Abstract

In this Research Paper, a sample of 100 participants' psychological resilience, conformance to masculine standards, and perceived social support were all examined. Data were collected using self-report measures, and correlations were examined to assess the associations between variables. The findings revealed a negligible negative correlation between perceived social support and conformity to masculine norms (r = -0.009, p > 0.01), indicating that social support was not significantly associated with adherence to traditional masculinity. However, a moderate positive correlation was observed between perceived social support and psychological resilience (r = 0.462, p < 0.01), highlighting the importance of social support in fostering resilience. Additionally, a weak positive correlation was found between conformity to masculine norms and psychological resilience (r = 0.265, p < 0.01), suggesting a modest association between adherence to masculine norms and resilience.

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 Keywords

Perceived Social Support, Masculine Norms, Resilience

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research article presents a detailed case study on the mechanical properties of clay bricks, specifically examining their density, compressive strength, and flexural strength. The study involves collecting clay brick samples and conducting laboratory tests to measure these properties. The primary objective is to assess the quality of the clay bricks by analysing the correlations between density, compressive strength, and flexural strength. The results of this study provide insights into the strength characteristics of clay bricks, enabling a comprehensive evaluation of their quality and classification.

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 Keywords

Clay brick samples, density, Compressive strength and flexural strength.

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 Abstract

Gas Monitoring & Ventilation System In the Underground Coal Mine" presents the design and implementation of a Gas Monitoring & Ventilation System for underground coal mines using an Arduino Nano board, MQ2 gas sensors, flame sensors, and ventilation fans. The system monitors hazardous gases and flames in real-time, triggering ventilation fans to mitigate risks when dangerous levels are detected. The goal is to enhance miner safety, reduce the risk of accidents, and ensure compliance with safety regulations. The paper also discusses the advancements in underground gas testing and reviews significant mine disasters to highlight the system's importance.

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 Keywords

Risk Factors ,Gas Monitoring , Gas Alerting , Automatic Ventilation System.

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In today's world, conscious consumers increasingly favor companies dedicated to social and environmental good. Recognizing this, Corporate Social Responsibility (CSR) initiatives are gaining traction. But do they truly strengthen brand loyalty and organizational sustainability? Research suggests a resounding "yes." Effective CSR initiatives can cultivate positive brand reputation, trust, and loyalty, leading to higher customer engagement and market share. Additionally, attracting and retaining talented employees through strong CSR practices fosters a positive work environment and boosts productivity. Furthermore, sustainable practices inherent to CSR can reduce costs, mitigate risks, and improve operational efficiency, contributing to long-term organizational sustainability. However, it's crucial to avoid greenwashing - inauthentic CSR efforts that damage brand reputation. Transparency and genuine commitment are key. Studies show a positive correlation between perceived CSR and brand loyalty, with consumers actively choosing and remaining loyal to responsible brands. Moreover, strong CSR practices are often associated with higher profitability and shareholder value. While measuring the impact of CSR on brand loyalty and sustainability can be complex, the potential benefits are undeniable. Further research will explore the long- term impact across various industries and demographics, refine communication strategies, and develop robust metrics to measure CSR's true impact on stakeholders. In conclusion, well-designed and authentic CSR initiatives hold significant potential to build brand loyalty, contribute to organizational sustainability, and create a positive impact on society and the environment.

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 Keywords

corporate social responsibility ; sustainability ; brand loyalty ; consumer ; practises

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 Abstract

Waste management is an essential part of health care. Poor management of health care waste exposes health care workers, waste handlers and the community to infections, toxic effects and injuries, and risks that pollute the environment. Of the total amount of waste generated by health care activities, 15% is considered hazardous material that may be infectious, chemical or radioactive. In 2010, unsafe injections were responsible for as many as 33 800 new HIV infections, 1.7 million hepatitis B infections and 315 000 hepatitis C infections.

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B.Sc. nursing students bio medical waste management, Nursing College

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As per new CBME pattern there are many teaching- learning methods, some of them are new methods like role play. This study was conducted to know the effectiveness of Role-Play versus conventional lectures. Students do not find conventional methods like lectures, chalk and board and other teaching methods interesting hence this study was conducted to find out whether a new method will create an interest among students which will also increase their understanding of the subject along with learning.

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 Keywords

Role-Play, Teaching Method, Learning Method, Conventioonal Method, Lectures.

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Creative Commons Attribution 4.0 and The Open Definition

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The SCADA system, crucial for monitoring smart grid performance, faces cyber threats due to weak communication protocol protection. Hackers exploit these vulnerabilities to inject false data, causing delayed detection and posing risks of infrastructure damage and fatalities. This study proposes the MSPPNet algorithm to identify and classify cyber attacks, utilizing deep learning and metaheuristic optimization. Evaluation on a dataset from Mississippi State University's Oak Ridge National Laboratory compares MSPPNet with traditional supervised learning methods. Results reveal MSPPNet's superior performance, achieving an 82% accuracy in binary classification. This algorithm enhances security in SCADA systems, mitigating risks of false data injection and deceptive manipulation by attackers. By leveraging advanced machine learning techniques, this research contributes to safeguarding critical infrastructure and ensuring the reliability and safety of smart grids.

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Artificial neural network, artificial root foraging, cyber security, deep learning, machine learning, metaheuristic algorithm, supervisory control and data acquisition, smart grid.

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Creative Commons Attribution 4.0 and The Open Definition

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Hegemonic Masculinity, Emphasised Femininity, Naga women, Naga culture, violence.

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Staff turnover in the hospitality industry, particularly in hotels, remains a persistent challenge with significant implications for organizational performance and service quality. This paper delves into the complexities of this phenomenon, aiming to uncover its underlying causes, consequences, and potential solutions. Through a comprehensive review of existing literature, this research seeks to shed light on the factors contributing to high turnover rates among hotel staff, including job dissatisfaction, low morale, inadequate compensation, and limited opportunities for career advancement. Additionally, it explores the ripple effects of staff turnover on organizational effectiveness, guest satisfaction, and overall reputation. By understanding the multifaceted nature of turnover in the hospitality sector, this study aims to provide valuable insights and practical strategies for hotel management to mitigate turnover rates, enhance employee retention, and ultimately foster a more stable and productive workforce.

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"Navigating the Revolving Door: Understanding Annual Staff Turnover in the Hospitality Industry"

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Image manipulation has become increasingly prevalent in today's society, with powerful editing tools allowing for easy and sophisticated changes to be made to digital images. However, this has also led to the misuse of digitally manipulated images for fraudulent, propaganda, and deceptive purposes. In response, deep learning algorithms, such as Convolutional Neural Networks (CNNs) have been developed accurately and efficiently for detecting various types of image forgeries, such as copy-move, splicing, retouching, and more. This paper outlines the key elements of the powerful image editing tools available, the misuse of digitally manipulated images, and the potential of deep learning algorithms for detecting image forgeries. Industry-standard image editing software like Adobe Photoshop and GIMP, have revolutionized the way digital images are edited and manipulated. These tools offer advanced features such as layers, filters, and masks, allowing precise and sophisticated changes to be made to images. For example, layers allow for different elements of an image to be edited separately, while filters provide a range of effects that can be applied to an image. As image manipulation techniques continue to evolve, the integration of deep learning with image processing holds great promise in ensuring the authenticity and credibility of images in the digital era.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image Image Tampering, Machine Learning, Convolutional Neural Networks, Deep Learning, Tampering Methods, Detection Tools

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Creative Commons Attribution 4.0 and The Open Definition