Volume 12 | Issue 6 |

 Abstract

A hookworm belonging to the genus Ancylostoma (Dubini,1843) isolated from the small intestine of a canid Canis aureus (Linnaeus) which was found dead from a new host locality, village Kandraur district Bilaspur Himachal Pradesh. The worm is bent dorsally, cuticle transversely striated; buccal capsule large with three pairs of ventro-lateral teeth and two lancets in the deep of the buccal capsule; dorsal ray forked distally each branch further trifurcates; genital cone oboid with two pairs of genital papillae; spicules equal, long filamentous, 0.650-0.765 mm long with tapering tips; gubernaculum 0.144-0.180 mm long; vulva in the posterior third of the body 3.240-3.510 mm from the tip of tail; tail conical with a spine at the tip 0.006 mm long . This zoonotic worm is transmitted orally or percutaneously, causing a disease ancylostomiasis in humans, domestic and wild animals. The main symptoms of ancylostomiasis are mucous haemorrhagic diarrhoea and anaemia.

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 Keywords

hookworm, Ancylostom caninum, canid Canis aureus, Himachal Pradesh

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Dentifrices are the product which is used to maintain the oral hygiene such as Freshness of mouth and to avoid tooth decay. The oral hygiene can be maintained throughout the day by using various dentifrices prepared by herbal and synthetic ingredients. This work was carried out to prepare Tooth powder which can be used as a tool for proper oral hygiene and to overcome the side effect of the conventional Tooth powder prepared by synthetic ingredients. Dentifrices are important in our daily life to maintain good oral health and hygiene. Gingivitis, plaque, Periodontal diseases are the crucial problems related to tooth. These major issues are due to poor oral hygiene and negligence in good caring of tooth. This negligence encourages plaque formation on teeth, by causing inflammation of gum tissues which ultimately leads to gingivitis and tooth loss. Most of the synthetic preparations of dentifrices, such as toothpowder and toothpaste cause side effects such as gum irritation, burning sensation and inflammation due to usage of chemicals. In this study an attempt is made to dispense an alternative to the users by formulating herbal toothpowder using Clove, Ginger, Amla, Neem Bark, Accacia Bark, Mentha Leaf, Rock Salts, Cinnamon Powder, Guava Tree Leaf and Alum. In the present work, the herbal toothpowder was formulated and standardized by analysing necessary evaluation parameters such as organoleptic, physical and phytochemical evaluation of herbal toothpowder.

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 Keywords

Herbal, Accacia Bark, Cinnamon, Synthetic, Oral hygiene

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A few centuries ago, the English language consisted of a collection of dialects spoken mainly by monolinguals within the shores of a small island. However, English serves many purposes throughout the world now-a-days. At the beginning there was only one variety of English existed that is the native variety. There are so many varieties of English worldwide. Even within the native land of English i.e. the British Isles, one can find so many variants of English. It is not an exaggeration to state that English is a language- the language on which the Sun does not set, whose users never sleep (Quirk, 1985:1).

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Varieties, British Isle, Native, England, Received Pronunciation.

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 Abstract

Road accidents remain a significant public health concern worldwide, leading to loss of lives, injuries, and economic losses. To address this issue, researchers have increasingly turned to machine learning techniques for analyzing road accident data to understand contributing factors, predict accident occurrences, and propose preventive measures. This paper provides a comprehensive review of the state-of-the-art machine learning-based approaches for road accident analysis. We systematically categorize and summarize the various machine learning methods employed in accident detection, severity prediction, causality analysis, and risk assessment. Additionally, we discuss the challenges associated with these approaches, including data availability, feature selection, model interpretability, and scalability. By highlighting the recent advancements, limitations, and future directions in road accident analysis using machine learning, this review aims to provide insights for researchers, policymakers, and practitioners working in the field of road safety.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Road accidents, public health, severity prediction, road safety, machine learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Sleep is essential for health but gender differences might impact the sleep patterns. Extensive study has revealed physiological and behavioral differences in sleep cycles between men and women including duration, phases and rhythms. Community actions are critical for increasing awareness and teaching about gender-specific sleep requirements. Creating comfortable sleeping conditions and managing stress are also critical. Communities that promote sleep awareness can empower individuals to priorities their sleep health, hence enhancing overall quality of life. Objectives: To study the difference between the sleep cycles of males and females along with the factors affecting it. To make people aware about the importance and benefits of adequate sleep and measures to maintain regular sleep cycles. Methodology: 400 participants were taken for the data collection. Global Sleep Assessment Questionnaire (GSAQ) which contained 11 questions regarding sleep experiences of an individual was used. Patients were prescribed with various relaxation techniques and recommendations to improve their sleeping habits. For the very purpose data has been collected from January 2024 to April 2024. Results: The analysis of the GSAQ Score showed that sleep cycle of Males is more disturbed than that of Females. The average score of males was 7.3 while as in females it was 6.65. Conclusion: The study concluded that on gender differences in sleep patterns, with males experiencing more interrupted sleep cycles than females. This highlights the importance of targeted therapies to improve sleep quality, particularly among men. Community sleep awareness projects can empower people to priorities their sleep health, resulting in a higher quality of life overall.

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 Keywords

Sleep Cycle, Global Sleep Assessment Questionnaire, Sleep Quality, Sleep Disorder, Health

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Eye sight plays a major role in collecting most of the information from the real world and that information will be processed by brain. Many people around the world are blind or not able to see clearly or recognisation the objects properly. Visually impaired people suffer inconveniences in their daily and social life with respect to challenges during commuting. This condition leads to the loss of the valuable sense of vision. The need for assistive devices was and will be continuous. There is a wide range of navigation systems and tools existing for visually impaired individuals. The blind person truly requires an aid in identifying objects. Smart Blind Stick is an interactive device which mainly aims at helping the blind to navigate easily and in a safer manner. In a normal day to day situation a blind person waves the blind stick ahead of them in order to check for any objects or obstacles. The smart stick helps them in this by detecting if any obstacle is blocking the path being taken by the subject. The device detects the obstacle with the help of a camera attached to the front of the stick. On detection of the obstacle, it is identified and appropriate instructions are provided to the user. The instructions to the blind person are sent over earphones. Thus, the stick provides a safer and a better navigation experience for the visually challenged.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Object detection, Machine Learning, IoT, Raspberry pi, pi Camera, YOLO algorithm.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The prevalence of skin diseases, particularly skin cancer, presents a global health challenge an increasing impact on the economy and workforce. Melanoma, arising from dysfunctional melanocytes, is the most aggressive form of skin cancer, in constrast non-melanoma skin cancers (NMSC) like squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) account for the majority of cases. The incidence of NMSC has risen significantly, with men being at higher risk due to genetic, phenotypic, and environmental factors. Advances in polymeric micro/nano carrier-based therapies offer promising avenues for skin cancer management, including drug and gene delivery, and combination therapies. These innovative approaches hold the potential for overcoming current treatment limitations and advancing both research and clinical applications in the field. Nisosomes can be important nanomolecules For the cancer management and drug delivery. In this review, we are discussing the nisosomes as a nanocarrirer for drug delivery in skin cancer.

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Skin cancer, niosomes, drug carrier, nanocarrier, cancer treatment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project details the design, development, and evaluation of a prototype cycloidal gearbox. Cycloidal gear systems are known for their high torque transmission, compact size, and low noise levels. The main goal of this study is to create a functional prototype to demonstrate the feasibility and effectiveness of cycloidal gearboxes for various applications. The project starts with a comprehensive literature review to understand the principles, benefits, and challenges associated with cycloidal gearing. Utilizing this information, a thorough design process is conducted, including CAD modeling and finite element analysis (FEA) for optimization. Special focus is placed on the design of the cycloid disk and pins to ensure efficient power transmission and minimal wear. After the design phase, the prototype is manufactured using precision machining techniques. Rigorous testing is performed to evaluate its performance characteristics, including torque transmission efficiency, speed variability, and noise levels. Comparative analyses with conventional gear systems are conducted to highlight the unique advantages of the cycloidal design. The findings of this project contribute to the advancement of cycloidal gearbox technology, offering valuable insights into their practical implementation and performance capabilities. Additionally, the prototype serves as a foundation for further research and development in the field of mechanical power transmission systems

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 Keywords

Cycloidal Gearbox, Speed Reduction, Cycloidal Gearing System, Gear Design, High Torque Transmission, Gearbox Manufacturing, CAD Modeling, Cycloid Disk, Precision Machining, Power Transmission Efficiency, Gearbox Optimization, Gearbox Testing, Noise Reduction, Comparative Analysis, Mechanical Power Transmission.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Predicting future sales accurately is crucial for businesses to optimize inventory management, plan marketing strategies, and enhance overall profitability. In this paper, we propose a comprehensive analysis of predictive sales analytics for variable timeframes utilizing machine learning models, specifically XGBoost, Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) networks. Through empirical evaluation and comparative analysis, we demonstrate the efficacy of XGBoost in forecasting sales for different timeframes, namely daily, weekly, and monthly. Our findings highlight the superior performance of XGBoost in terms of accuracy and robustness, making it an ideal choice for businesses seeking reliable sales predictions across diverse temporal scales.

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 Keywords

Predictive analytics, Sales forecasting, XGBoost, Random Forest, Linear Regression, LSTM, Variable timeframes, Streamlit.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid advancement of intelligent transportation systems (ITS) has necessitated the development of efficient and accurate methods for accident detection and impact evaluation. This review paper examines the latest image processing approaches utilized in the detection and analysis of traffic accidents. We explore a variety of techniques, including machine learning algorithms, deep learning models, and traditional computer vision methods, assessing their effectiveness in real-time accident detection, severity estimation, and post-accident analysis. The paper discusses the strengths and limitations of each approach, highlighting key innovations and their practical applications within ITS. Additionally, the review addresses the integration of image processing with other sensor technologies, such as LiDAR and radar, to enhance the reliability and accuracy of accident analysis. Current challenges, including data quality, computational demands, and implementation in diverse traffic environments, are also considered. Finally, we outline potential future research directions aimed at improving the robustness and scalability of image processing techniques for comprehensive accident impact evaluation. This review serves as a valuable resource for researchers and practitioners seeking to advance the field of traffic accident analysis through image processing innovations.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

accident detection, impact evaluation, image processing, machine learning (ML).

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Creative Commons Attribution 4.0 and The Open Definition