Volume 12 | Issue 11 |

 Abstract

This research paper details an experimental investigation into the design, construction, and testing of a novel prototype detachable afterburner employing butane combustion. The motivation behind this study stems from the pursuit of innovative solutions to enhance the efficiency and environmental sustainability of jet engine afterburners. The prototype incorporates a fan with a 12V motor, a glow plug, and a carefully designed arrangement within an acrylic pipe to channel butane combustion. The study explores the stability of butane combustion, its impact on flame characteristics, and the potential for thrust augmentation. Preliminary results provide insights into the feasibility and performance of the detachable afterburner design, opening avenues for further research and development in advanced propulsion systems. This experimental study contributes to the evolving landscape of afterburner technology, offering a unique perspective on the use of alternative fuels for aerospace applications.

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 Keywords

Detachable afterburner, Butane combustion, Advanced propulsion systems, Environmental sustainability, Thrust augmentation

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Chromatography is commonly used in the pharmaceutical industry for the quantification of drugs and other pharmaceuticals. Among the various chromatographic techniques, High Performance Thin Layer Chromatography (HPTLC) has gained popularity due to its speed, versatility, applicability, and ability to analyze more than 100 samples simultaneously. Given its potential applications, researchers worldwide have utilized this technique for pharmaceutical analysis. This review summarizes research conducted on 63 formulations, of which 38 contain one active ingredient, while 25 contain two active substances. This review aims to provide a comprehensive understanding of the utility of this technique in pharmaceutical analysis and to assist scientists interested in using HPTLC for their analytical purposes.

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 Keywords

HPTLC, Pharmaceutical analysis, Method development, Active ingredient, Pharmaceutical formulation.

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Samuel Taylor Coleridge's The Rime of the Ancient Mariner is a profound exploration of the themes of sin, remorse, and forgiveness. The poem follows the journey of an unnamed mariner who commits the grave sin of killing an albatross, a symbol of nature's harmony. This action triggers a series of catastrophic events, leading to the suffering and death of his fellow crew members. The mariner is burdened with guilt, symbolized by the dead albatross hung around his neck, which represents his spiritual and moral transgression. As the poem unfolds, the mariner's suffering reflects the consequences of violating natural and divine laws, and his eventual redemption emerges from his sincere expression of remorse. The mariner's moment of realization occurs when he acknowledges the sanctity of life in all its forms, particularly in his blessing of the water snakes, which signifies his true repentance. The poem's treatment of sin and forgiveness mirrors broader theological and moral reflections found in religious and philosophical traditions. Coleridge's depiction of the mariner's penitence aligns with the Christian concepts of repentance, redemption, and divine forgiveness, drawing parallels to the process of atonement for sin. Through his journey, the mariner learns that forgiveness is not simply an external act of absolution but an internal transformation of the self. The poem highlights that genuine remorse and the recognition of one's faults are necessary for redemption. This paper examines The Rime of the Ancient Mariner as a representation of the cyclical nature of sin, remorse, and forgiveness, offering insights into the moral consequences of human actions and the possibility of spiritual renewal through self-reflection and divine grace.

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 Keywords

committing sins, forgiveness, guilt, redemption, remorse, sufferings

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Image Colorization involves colorizing grayscale image and giving the image a deeper meaning. This is a sophisticated task that requires prior knowledge of image content. Also, since the objects in the image may have several colors, it consists of numerous possible techniques to add colors to the pixels of the image, which shows there is no distinctive solution to this problem. Deep Learning techniques like Convolutional Neural Networks (CNN) and General Adversarial Networks (GANs) have been used to colorize grayscale images. This paper delves into analyzing and comparing the effectiveness of the two approaches (i.e., Convolutional Neural Networks and General Adversarial Networks) to colorize grayscale images. First, a dataset of images was created, which was subsequently converted to a dataset of grayscale images in the initial dataset. The grayscale images were then colorized using the two deep learning techniques of CNN (Convolutional Neural Networks) and GANs (Generative Adversarial Networks). The resultant colorized images were compared and analyzed with the original colorized images with their corresponding image histograms using comparison methods like 'Chi-Squared test' and 'Correlation distance'. The results obtained were then explained in the paper.

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Comparative study, colorization, CNN, GANs

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Ficus benghalensis also known as banyan tree is a large, evergreen tree native to the Indian subconstituent and southeast asia. It belongs to the family moraceae. Acacia nilotica also called as Babool or gum arabic, is a tropical tree native to africa, Asia and Australia, belong to family fabaceae. The ficus benghalensis and Acacia nilotica linn bark powder was converted into batches on the basis of their particle size. It has observed that, batch A (sieve no.44) passes all the preformulation parameter. This batch was finally used to prepare the antipyretic & analgesic capsule with different concentration. After that F2 batch was checked for weight variation, disintegration test, moisture content, pH. It has been observed that disintegration test F1, F2, F3 and F4 was 9.58 sec, 8.12 sec, 8.48 sec, 9.40 sec respectively Also, batch f1 passes the weight variation test. The antimicrobial test against E.coli, C.albicans and S.aureus was performed that, it shows zone of inhibition around -ve, 21mm, 19mm after 24 hrs.

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ficus benghalensis, Acacia nilotica, antipyretic and analgesic capsule, moraceae, fabaceae.

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Flue Gas Desulphurization (FGD) system is required to be provided for all operational thermal power plants and the new plants being operational in future for meeting the new guidelines laid by Ministry of Environment Forest and Climate Change (MoEF&CC). FGD system provides the "Environmental Sustainability" by reducing the SO2 gas liberated to the atmosphere, which is a health hazard causing respiratory infections, eye irritation, breathing difficulty, asthma, etc. FGD is a system which reduces the SOx in flue gas through chemical treatment converting the captured SOx into a by-product which is used by some other industry. To achieve acceptable dispersion of SOx emission from thermal power plants, Chimney height criteria has been adopted in India based on the emission rate of the SOx. This paper highlights the sustainable design aspects considered in the design of 125m tall Chimney with structural frames for a 2x600MW power plant.

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Flue Gas De-Sulphurisation, FGD, SOx, MOEF, Air-pollution, Chimney, Sustainability, Flue Can

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Creative Commons Attribution 4.0 and The Open Definition

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The integration of Information and Communication Technologies (ICT) has transformed teaching and learning in educational institutions, offering benefits like improved communication, better resource access, and enhanced efficiency. However, this technological shift has also introduced significant challenges for teachers, notably in the form of technostress. Technostress, which refers to the psychological and physical strain caused by the complexities of ICT use, has become a major obstacle to effective technology adoption in education. Factors like information overload, techno-complexity, and techno-insecurity contribute to these challenges, often leading to burnout, anxiety, and decreased job satisfaction for educators. This article examines the impact of technostress on teachers, focusing on how the perceived usefulness of ICT can help reduce its negative effects. It looks into key moderators such as ICT literacy, technical support, and organizational support, which can alleviate technostress and create a more supportive teaching environment. Additionally, the study integrates models like the Technology Acceptance Model (TAM) and the Job Demands-Resources (JD-R) model to offer insights into how educational institutions can enhance teacher well-being through targeted interventions. The findings stress the importance of a balanced approach that addresses ICT-related challenges while also harnessing its potential to improve teaching and learning outcomes.

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ICT Usefulness, Technostress, ICT Adoption, ICT Literacy, Technical Support, Organizational Support, Teacher Well-Being

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 Abstract

In order to forecast TATA Chemicals' stock prices over the next ten days, we use machine learning and deep learning techniques. The Root Mean Square Error (RMSE) is used to assess the model's accuracy. In order to achieve prediction accuracy, we employ time series forecasting techniques and historical stock price data, specifically using models like GRU, LSTM, Linear Regression(LR), Random Forest Regression(RFR), and XGBoost. To predict future patterns, these models are trained on historical stock values. We may evaluate the effectiveness of the prediction model by using RMSE as a statistic to quantify the difference between the actual and forecasted stock prices. The outcomes show how well the model captures transient changes in stock prices, making it a useful tool for analysts and investors.

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GRU, LSTM, XGboost, RMSE, RFR, LR

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This research focuses on leveraging Artificial Intelligence (AI) to enhance energy efficiency in smart homes. By integrating advanced techniques such as load disaggregation, Energy Management Systems (EMS), and demand forecasting, AI-driven smart homes optimize energy consumption while ensuring user comfort. The proposed model demonstrates the potential of AI to dynamically adapt energy use, minimize costs, and reduce environmental impact. Case studies like Tesla's Power Wall and IoT-based smart lighting solutions underscore the practical implementation of these technologies. The paper highlights challenges such as data privacy and infrastructure limitations while envisioning future advancements in AI-enabled energy-efficient solutions.

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 Keywords

Artificial Intelligence (AI), Smart Homes, Energy Efficiency, Energy Management Systems (EMS), Load Disaggregation, Forecasting Engine, Internet of Things (IoT), Renewable Energy, Smart Lighting Solutions, Non-Intrusive Load Monitoring (NILM), AI-Driven Energy Optimization, Home Energy Consumption, Machine Learning, Energy Forecasting, Smart Meters.

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This research paper examines the interplay between curiosity and consequence of characterization of Gothic protagonists in William Beckford's Vathek, Matthew Gregory Lewis's The Monk, Mary Shelley's Frankenstein, Robert Louis Stevenson's Dr. Jekyll and Mr. Hyde, and H.G. Wells's The Island of Dr. Moreau. Through a comparative analysis, the study explores how each protagonist's insatiable curiosity leads to their eventual downfall of their journeys. The paper will explore how curiosity leads to downfall in Gothic protagonists. It examines how their insatiable curiosity drives them to cross natural and moral boundaries, resulting in tragic consequences. These gothic fictions serve as cautionary tales about the dangers of unrestrained ambition, unchecked desires, and scientific hubris. The aim of this research paper is to analyze the role of curiosity and its consequences of selected gothic fictions in shaping the Gothic protagonists.

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 Keywords

Comparative analysis of protagonist, Curiosity Scientific Hubris Supernatural Elements Tragic Consequence Decadence.

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