Volume 13 | Issue 3 |

 Abstract

Transdermal drug delivery systems (TDDS) represent a progressive approach for administering medications through the skin, offering sustained therapeutic effects while enhancing patient compliance. This review categorizes TDDS into reservoir, matrix and micro reservoir systems, each facilitating controlled drug release. Various formulation methods are explored including the asymmetric TPX membrane method, circular Teflon mold technique and innovative approaches like microneedles and nanocarriers, which enhance skin permeability and stabilize active ingredients. The evaluation parameters for TDDS include thickness, weight uniformity, folding endurance and in vitro release tests, ensuring the quality and efficacy of formulations. The review also outlines the contact times for different TDDS types with patches typically worn for 24 hours to several days, while sprays deliver shorter durations of drug effects. Applications of TDDS are diverse, spanning pain management with fentanyl patches, hormone replacement therapies and nicotine cessation to innovative vaccine delivery systems. However, adverse reactions such as skin irritation and allergic responses necessitate careful monitoring and patient education. Recent advancements in TDDS focus on enhancing drug delivery through techniques such as iontophoresis, sonophoresis and smart transdermal systems equipped with sensors. The future of TDDS lies in optimizing adhesive technologies and incorporating novel excipients to improve drug permeation and stability aiming for individualized treatment solutions. Overall, TDDS offers a practical alternative to traditional drug administration methods, addressing various medical needs while highlighting the importance of ongoing research and innovation in formulation science for improved therapeutic outcomes .

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 Keywords

Transdermal Drug Delivery Systems (TDDS), Types Of TDDS, Evaluation Parameters, Mechanism of Action, Formulations, Regulatory And Market Perspective

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Diabetic Retinopathy (DR) is a leading cause of blindness in diabetic patients. Manual screening by ophthalmologists is time-consuming and labor-intensive. Deep Learning-based classification of DR stages from high-resolution fundus images using MobileNet and ResNet models offers a promising solution. The models were trained on the Kaggle dataset to enhance the efficiency and accuracy of DR diagnosis, detection, and prevention of vision loss. Deep Learning models detect and classify five DR stages (0-4) from fundus eye images with high accuracy. Input images are processed to extract features, which are then used to output the corresponding DR stage using an activation function. Utilizing Artificial Intelligence, the system analyzes large datasets and makes accurate predictions, reducing the workload of ophthalmologists and improving patient outcomes. This technology has the potential to revolutionize DR diagnosis, enabling timely and accurate detection, and preventing vision loss. Deep Learning in medical image analysis demonstrates effectiveness in improving healthcare outcomes, enabling enhanced patient care and treatment.

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 Keywords

Diabetic Retinopathy (DR), Deep Learning (DL), MobileNet, ResNet, fundus images.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The adoption of Agile methodologies has gained immense popularity in the IT industry due to its ability to enhance productivity, foster collaboration, and streamline project management. This research paper explores the impact of Agile methodologies on employees working in IT companies in the Mumbai region. By examining employee satisfaction, productivity, and collaboration, this study seeks to understand the transformation Agile brings to workplace culture and performance. Through qualitative and quantitative analysis, this paper presents insights into how Agile methodologies influence employee experience in terms of workload, team dynamics, stress, and overall job satisfaction.

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 Keywords

Agile methodologies, IT companies, Mumbai, employee impact, productivity, collaboration, software development, employee satisfaction, team dynamics.

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 Abstract

Sarkari Ev Gair Sarkari Uchtar Madhyamik Vidhyalyo Me Adhyanrat Vithyarthiyo Ki Naithik Vikash Ke prati Jagrukta Ka Ling Ke Sandarbh Me Tulnatmak Adhyan

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Sarkari Ev Gair Sarkari Uchtar Madhyamik Vidhyalyo Me Adhyanrat Vithyarthiyo Ki Naithik Vikash Ke prati Jagrukta Ka Ling Ke Sandarbh Me Tulnatmak Adhyan

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Customer satisfaction plays a vital role in the success of retail businesses, shaping consumer loyalty and influencing brand perception. This study examines customer satisfaction with Zudio shopping in Coimbatore City, focusing on key factors such as product quality, pricing, store ambiance, customer service, and overall shopping experience. Through surveys and data analysis, the research aims to assess customer preferences, expectations, and levels of satisfaction with Zudio's offerings. The findings will provide valuable insights into consumer behaviour, helping Zudio enhance its retail strategies to better serve its customers in Coimbatore. This study contributes to the broader understanding of customer satisfaction in the budget fashion retail sector.

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A STUDY ON CUSTOMER SATISFACTION ON ZUDIO SHOPPING IN COIMBATORE CITY

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The project focuses on enhancing low-resolution images using advanced super-resolution techniques. By reconstructing high-resolution images from their low-resolution counterparts, the system significantly improves visual clarity and detail. Traditional interpolation techniques, such as bilinear or bicubic interpolation, produce limited improvements, often resulting in blurred images. The abstract concept of image super-resolution can be represented as an artistic depiction where low-resolution pixelated images evolve into higher resolution, more detailed versions. In such an image, you might see a blurry or pixelated image gradually becoming sharper and more defined, with details like textures, edges, and color becoming clearer as the resolution increases. This could be visualized as a transition or transformation, with smooth gradients of pixels enhancing into a crisp, high-quality image. Deep learning-based methods, such as convolutional neural networks (CNNs) and generative adversarial networks (GANs), have revolutionized super-resolution by learning patterns from large datasets. These models analyze textures, edges, and structural information, allowing them to reconstruct high-quality images with remarkable accuracy. Unlike traditional interpolation, which relies solely on mathematical approximations, deep learning techniques infer missing details based on learned features, significantly enhancing image fidelity.

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 Keywords

AI, Image Processing, High resolution, Image super resolution.

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By putting ludonarrative dissonance in Detroit: Become Human in conversation with the non-linear structure of Cloud Atlas and the understated yet poignant metafictional elements of Never Let Me Go, this study explores how these texts redefine narrative forms and engage audiences in unique, thought-provoking ways through different mediums. The study delves into video-game studies projecting how these works shift conventional storytelling by foregrounding reader/player participation, questioning notions of free will/complete player control, and deconstructing linear storytelling. It also explores thematic overlaps in ludology and narratology. The theories in play are cybertext and player agency theory, Huizinga's Homo Ludens, Propp's narrative functions, ludonarrative dissonance and Hutcheon's adaptation theory. The project seeks to uncover new insights into the overlapping of video-game criticism with literature to deepen our understanding of storytelling across mediums.

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 Keywords

Metafiction, Ludonarrative Dissonance, Cybertext, Player Agency, Adaptation Theory, Transmedia Storytelling, Ludology, Narratology.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Yoga is a Science of Body, Mind, Consciousness and Soul. It is a traditionalmethod of meditation developed by the saints of ancient India. They practiced yoga as an effective method of controlling their mind and bodily activities. Yoga in daily Life is a system of practice consisting of eight levels of development in the areas of physical, mental, social and spiritual health. When the body is physically healthy, the mind is clear, focused and stress is under control. This gives the space to connect with loved ones and maintain socially healthy relationships. Even today athletes spent hours practicing and improving their performance. Every day records are set and the bar is raised. Every new record set means more stress on the athletes to achieve the top spot or maintain their position there. It has been emphasized that each exercise be practiced slowly, coordinating movement with the breath, pausing motionless in each position and always with full concentration.Pole-vaulters,sprints. javelin-throwers and all others are always at a risk of sustaining injuries that might hamper their performance So how does one keep raising the bar and keep away from the pitfalls.

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 Keywords

Keywords Yoga, Daily life, Sports, Physical health, Social, Spiritual health, Skillful, Spiritual aspects, Strength

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Federated Learning (FL) has emerged as a transformative paradigm for distributed machine learning while ensuring data privacy [2]. However, the integration of robust privacy-preserving mechanisms remains a key challenge. This paper presents an enhanced FL framework that incorporates Differential Privacy (DP) to strengthen data security while maintaining model accuracy [3]. A novel adaptive noise injection mechanism is proposed to optimize the balance between privacy protection and learning performance. Experimental evaluations on multiple real-world datasets demonstrate the efficacy of the proposed approach, showcasing improved resilience against privacy attacks without significant accuracy degradation [6].

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 Keywords

Federated Learning, Differential Privacy, Secure Machine Learning, Data Privacy, Privacy-Preserving AI.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

By utilizing BIND, the proposed DNS administration system enhances automation, performance, and security features to improve domain name resolution. Authoritative DNS, which ensures accurate and secure domain record management, and Recursive DNS, which efficiently resolves domain names by caching queries and reducing search times, are both included. Another system feature that improves network security and authentication is reverse DNS, which converts IP addresses to domain names. This capability is particularly useful for email validation and anti- spoofing. Using AXFR/IXFR protocols and TSIG authentication, the system provides Secure Zone Transfer to ensure safe data synchronization between DNS servers while preventing data interception and unauthorized access. Additionally, RNDC (Remote Name Daemon Control) provides remote administrative control for maintaining server performance, reloading zones, and upgrading DNS configurations via secure communication channels. In order to deliver a scalable, secure, and automated DNS infrastructure, the solution integrates these elements to maximize network speed and defend against DNS-based threats.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DNS Management, Recursive DNS, Secure Zone Transfer, BIND Server

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Creative Commons Attribution 4.0 and The Open Definition