Volume 12 | Issue 1

 Abstract

After independence, in 1947, 1965, 1971 and 1999 India faced four major wars with Pakistan; in 1962 an unfortunate war with China and faced many anti-terrorist operations. Near our surroundings of us, Pakistan and China are continuously developing their defence power. India's defence analysts were always creating awareness and guided to nations' security, modernisation of armed forces equipment, indigenous defence production and upliftment of advanced modern equipment for defence on the border in land, air and sea of our nation. India wanted to protect its homeland from external threats so, she signed a defence deal with 20 foreign countries including France, Russia, Israel etc. Particularly Indo-France defence relations are in four phases and the move forward to defence cooperation is in the fifth phase. In this fifth phase, India collaborates with France and will create the defence potential for self-reliance, leading global power, more concentrating on indigenous production and exporting defence goods to foreign countries. Regarding the Indo-France Defence various phases, this paper concentrates in the succeeding paragraph.

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P-75 Scorpene, Rafale, Project Shakti, VARUNA, 6.5 Generation AMCA.

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The human body relies on the healthy liver to perform over 500 essential functions, and any dysfunction can have severe consequences, potentially leading to fatality. Timely identification and treatment of liver diseases can significantly enhance the chances of survival. In this regard, machine learning (ML) emerges as a valuable resource that can aid healthcare experts in diagnosing hepatic patients. The conventional ML framework encompasses various techniques such as data pre-processing, feature extraction, and classification, which collectively contribute to accurate diagnoses. Liver disease is a matter of great concern in the global health landscape, impacting a vast number of people across the world. The timely and precise identification of liver disease plays a pivotal role in ensuring successful treatment and averting potential complications. Over the past few years, the advent of machine learning has revolutionized the healthcare sector, empowering the creation of predictive models that aid in diagnosing and forecasting diverse medical ailments, liver disease being one of them. The proposed approach incorporates several ML algorithms, including logistic regression (LR), random forest (RF), and confusion matrix. The results indicate that the suggested system has the potential to complement the diagnosis of liver disease made by a physician

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Liver disease, Machine learning, Prediction, Data analytics, Healthcare, Autoencoders

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Abstract: Background of the study: Type II diabetes mellitus is called as life style disease as it is more common in people who don't do enough exercise, have an unhealthy diet and obese so it is very important to have a knowledge about prevention and management of type II diabetes mellitus through life style modification like exercise, diet. It also helps in prevention of complications of diabetes mellitus. Objectives: 1. To assess the knowledge and attitude of diabetes management. 2. To associate between the level of knowledge and attitude of diabetes management among adults with type II diabetes mellitus with their bio socio demographical variables. Method: A study was conducted by using the descriptive design. The setting of the study was in a selected community area, Harohalli. Sample size of 30 adults with type II diabetes mellitus were selected by probability simple random sampling technique. A proforma for collection of baseline data and structured questionnaire was used to assess the level of knowledge and attitude of diabetes management among adults with type II diabetes mellitus. Results: The findings of the study shows that majority of the samples that is 16(53.3%) had moderate level of knowledge, 14(46.7%) had inadequate level of knowledge of diabetes management. The majority of the samples that is 15(50%) had moderate attitude level 15(50%) had unfavorable attitude level. There was significant association between level of knowledge and attitude of diabetes management with bio socio demographic variables.

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Index Terms - Type II diabetes mellitus, knowledge, attitude, management.

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This paper mainly focus on the World Trade Organisation (WTO), which promotes and supports free and fair trade among its member countries and has been instrumental in influencing the nature of international trade. This research explores the WTO's complex role in advancing free and fair trade by examining its institutional structure, historical development, and current global concerns. An important turning point in the history of international trade relations was the establishment of the WTO in 1995. This paper says that the WTO's institutional framework, which consists of a set of agreements and regulations, is the cornerstone of its work to promote free and fair trade. This paper also mentions the Most-Favoured-Nation (MFN) and National Treatment principles, which mandate that members provide equitable trade conditions to all other members and refrain from discriminating between domestic and foreign goods and services, which form the foundation of WTO operations. These principles advance equity by prohibiting preferential treatment that can stifle trade. Global trade barrier reduction has been fuelled in large part by the WTO. The organization has successfully cut tariffs and quotas, streamlined customs procedures, and removed non-tariff barriers via successive rounds of negotiations, including the Uruguay Round and the Doha Development Agenda. These achievements have made it easier for goods and services to move across borders. Furthermore, the WTO's goal of promoting free and fair trade is in jeopardy due to the growth of protectionism in certain member nations, as shown by trade disputes and tariffs. Opponents of the organization's rules argue that they unfairly benefit rich countries and multinational firms, potentially undermining the interests of smaller and developing nations. The World Trade Organisation plays a diverse role in advancing free and fair trade, involving removing trade obstacles and advancing equal treatment. Its institutional structure, historical development, and dispute resolution procedures are essential to accomplish these goals. To remain relevant and effective in promoting free and fair trade worldwide, the organization must continue negotiating and reforming in the face of persistent difficulties and controversies in adjusting to a fast-changing global economic landscape.

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(Key Words: World Trade Organization (WTO), Free Trade, Fair Trade, Trade agreements, Trade Liberalisation)

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Life skills is a term used to describe a set of basics skills acquired through learning and direct life experience that enable individuals and groups to effectively handle issues and problems commonly encountered in daily life. The present study aims to compare the life skills of Non-Muslim and Muslim girls and to study the effect of their family background factors on life skills. For this purpose 200 girls from Dist. (U.S.N.), Uttarakhand were selected through systematic random sampling. Life Skills scale constructed by Dr. Raina Tiwari was used. The collected data was analyze using ANOVA and POST HOC test. Result revealed that Non-Muslim girls possess better life skills scores and life skills of Non-Muslim and Muslim girls differ in respect to their socioeconomic consciousness.

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Life skills, Non-Muslim And Muslim Girls ,socioeconomic consciousness

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ABSTRACT Recent worldwide catastrophes like the COVID-19 epidemic have brought attention to the complex relationship between public health regulations and international commerce law. This study examines the complex interdependencies, conflicts, and overall effects on the world well-being of the two fields of international trade law and public health. The World Trade Organisation (WTO) is emphasised as the cornerstone of global trade governance as the paper opens by clarifying the essential foundations of international trade law. It highlights the significance of trade agreements and treaties, which frequently conflict with national public health imperatives. The article explores how access to necessary drugs and vaccines has been impacted by international trade agreements like the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement. One prominent illustration of these interactions is the continuing discussion regarding the waiver of intellectual property rights for the COVID-19 vaccines. The complex effects of public health policies, which cover crisis management and regular laws intended to protect people's health and well-being, are also explored in this study. Trade agreements and public health regulations frequently clash, creating conflicts that need careful balancing. The study also analyses the contradictory link between commerce and health, showing how trade may mobilise resources and provide access to medical technology while contributing to the spread of infectious illnesses. For the resilience of global health, these factors must be balanced. This study highlights the changing landscape of international trade law and public health policies by analysing recent case studies and emerging legal frameworks. It emphasises the necessity of egalitarian, flexible, and collaborative solutions to solve the world's health issues while promoting economic development. The study highlights the need for the international community to adopt a comprehensive strategy to balance these forces that appear to be at odds. To establish a conducive climate for both economic growth and health security, it promotes the harmonisation of international trade law with public health imperatives. The interaction between public health initiatives and international trade legislation is crucial for the welfare of both countries and individuals. The international community can better position itself to navigate future global challenges, from pandemics to non-communicable diseases, by acknowledging the interdependencies and resolving conflicts through cooperative and forward-thinking approaches, ensuring a healthier and more prosperous world.

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International Trade Law, Public Health Measures, World Trade Organization (WTO), Trade Agreements, Access to Medicines.

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A real object is produced using the additive manufacturing technique of three-dimensional (3D) printing from a digital design. Thin layers of material, such as liquid or powered plastic, metal, or cement, are first laid down, and then the layers are fused together. Recent years have seen a surge in interest in fused deposition modelling due to its revolutionary impact on the quick production of customized polymer-based composite parts. Understanding these printed components' fundamental mechanical characteristics is crucial to make engineering applications for them easier. In this project, the mechanical properties of samples made by fused deposition modelling with various additives, such as wood, ceramic, copper, aluminum, and carbon fibers based Polylactic acid composites, are thoroughly investigated. These properties include tensile, hardness, and impact properties. A thorough comparison and analysis is done of the impacts of various Polylactic composites, construction orientations, and raster angles on mechanical reactions. In this work, we examine the mechanical characteristics of 3D-printed Wood mixed PLA filament, including tensile strength, impact strength, and hardness. The FDM process is used to create the specimen. In this project, an 8:2 blend ratio of PLA and the wood addition was chosen since it is thought to have mechanical properties that are successfully adjusted when compared to pure PLA. Types of printing pathways are created with the parameters of raster angles, infill density, and speed for each printing orientation.

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3D,FDM,PLA

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This Study, Analysis and Development of a Biogas Run Generator of 50 KW capacity at Pachane Taluka Mawal, District Pune is done for the production of electricity from the Diesel Engine which is run on biogas. The engine has to be modified with the use of 4 spark plugs for the combustion chamber so that biogas can be used as the substitute fuel. The other modification required to be done is to reduce the compression ratio of 16:1 for the diesel engine to 8:1 for the biogas run engine. This reduction of the compression ratio is achieved by grooving the piston to increase the volume of the combustion chamber and reduce the compression ratio of the engine. We also need to filter the gas as the raw gas contains CO2 which is a non-combustive gas and NOx and Sulphur which causes a lot of corrosion in the combustion chamber and thus causes problems of knocking etc. Thus we have a filter installed in between and also we have a gas pump that pumps the gas after the filtration process is over and thus achieves continuous flow of the gas. This avoids the knocking effect on the engine. We have also studied that the major gas generated is methane which is around 67-70 % and the rest are other gasses like CO2, NOx, and SO2 etc. 1.72 KWH is the output recorded for the generator output for the biogas having 63% of methane.

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Study, Analysis and Development of Biogas Run Generator of 50 KW capacity at Pachane Taluka Mawal, District Pune.

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The patent protection in the automobile industry plays a prominent role in increasing innovations and safeguarding the rights of the manufacturers and companies. The Standard Essential Patents (SEP's) involves the process of standardization which ensures that the various technical advancements are compatible with one another. There is a necessity to comprehend the relationship between these standards and the patents. The Standard Essential Patents are not explicitly documented though it forms an essential part in the Automobile Industry. The technology producers adopt the Fair, Reasonable and Non-Discriminatory (FRAND) principles in order to obtain patent for their technologies. The Standard Essential Patents enables the automobile manufacturers to use the cutting edge technology at a reduced cost which is beneficial. The patent pools and compliance with the FRAND Principles creates a difficulty on the implementation of Standard Essential Patents where the automobile manufacturers have adopted few strategies in order to enable the implementation. The trade secrets have a great prominence in the patent protection of automobile industry as violation of trade secrets in the technologies can affect the patent protection. The suitable trade secret approach is required to be used by the automobile companies in order to obtain patent protection. Over the recent years, there has been a tremendous increase in the trade secret litigations around the world. The initiatives of protecting a design patent have been reduced on a legal basis due to the subjectivity in determining the design patents in countries like U.S and India. The registration of design patents becomes challenging while determining the innovation or novelty in the designs pertaining to the automobile industry.

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Patents, Legal Compliance, Standard Essential Patents, Trade Secrets, Designs, Confidential, Automakers, Advanced Technologies, Standardized Technologies.

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With the increasing complexity and volume of network traffic, ensuring the security and reliability of computer networks has become a critical challenge. This research focuses on leveraging machine learning techniques for the analysis of network traffic and the detection of anomalies, aiming to enhance the proactive identification of potential security threats. The study begins by exploring the current landscape of network security, emphasizing the limitations of traditional rule-based approaches and the need for more adaptive and intelligent solutions. Machine learning algorithms, specifically supervised and unsupervised learning models, are then applied to analyze historical network traffic data, enabling the system to learn patterns of normal behavior and identify deviations indicative of potential security breaches. The research employs feature engineering to extract relevant information from network data, enhancing the effectiveness of machine learning models in distinguishing between normal and anomalous activities. Various algorithms, such as Support Vector Machines, Random Forests, and Neural Networks, are implemented and compared to determine their suitability for different types of network anomalies. Furthermore, the study investigates the scalability and real-time processing capabilities of the proposed machine learning-based anomaly detection system. Special attention is given to the integration of these models into existing network infrastructures, ensuring seamless deployment and minimal disruption to network performance. The evaluation of the system's performance involves the use of benchmark datasets and simulated attack scenarios, allowing for a comprehensive assessment of its accuracy, precision, recall, and false positive rates. The results demonstrate the potential of machine learning in enhancing network security by efficiently detecting and mitigating anomalous behavior. Ultimately, this research contributes to the advancement of network security methodologies by providing insights into the practical application of machine learning for analyzing network traffic and proactively identifying security threats, thereby bolstering the resilience of modern computer networks against evolving cyber threats.

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Adhoc-Wireshark-machine learning

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In today's digital era, social media marketing has emerged as a powerful tool for promoting garment industry. The first step to understanding digital marketing versus social media marketing is learning what digital marketing entails. Digital marketing is an online marketing strategy that depends on digital technology, including the internet. Digital marketing includes social media marketing, video marketing, affiliate marketing, pay-per-click advertising, and more. Social media marketing is a type of digital marketing. This study will explore the significance of social media marketing in the growth of garments, highlighting its impact on brand awareness, customer engagement and sales. By leveraging the vast reach and targeting capabilities of social media platforms, garment industries can effectively connect with their target audience and establish a strong online presence.

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Digital marketing, Social media marketing, Garments, Customer engagement.

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Agriculture is a critical sector for sustaining human life, and the demand for increased crop yield, quality, and resource efficiency has never been higher. To address these challenges, this research presents a novel approach to crop growth monitoring through the integration of system adaptivity and edge Artificial Intelligence (AI) technologies. The proposed system leverages a combination of advanced sensors, edge computing, and AI algorithms to provide real-time monitoring and analysis of crop growth. Traditional approaches to crop monitoring rely heavily on centralized data processing, which can lead to latency issues, data security concerns, and increased operational costs. In contrast, our approach utilizes edge AI to process data directly at the source, reducing latency and ensuring data privacy.The system's adaptability is achieved through a smart system management mechanism that dynamically adjusts cryptographic functions based on security needs and resource constraints. This approach ensures that the system can safeguard sensitive sensor data without compromising performance or energy efficiency.

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Agriculture, Crop growth monitoring, Edge Artificial Intelligence (AI), Advanced sensors, Edge computing, Adaptability

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Azo-Dyes, Toxicity, Treatment, P. aeruginosa, Biological Degradation

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The study was a in a descriptive mode in hospital. The study was conducted over a period of one year on 150 samples. Total 150 samples were enrolled in the study. Both serum and pleural fluid samples were collected and quantitatively analysed using semi-automated analyser. It was concluded that Biochemical parameters play important role in diagnosing Pleural effusions. These markers when used collectively their diagnostic efficacy is greatly increased. Patients with pleural effusion is to determine whether the effusion is a transudate or an exudate. An exudative effusion is diagnosed if the patient meets Light's criteria. The serum to pleural fluid protein or albumin gradients may help better categorize the occasional transudate misidentified as an exudate by these criteria. If the patient has a transudative effusion, therapy should be directed toward the underlying heart failure or cirrhosis. If the patient has an exudative effusion, attempts should be made to define the etiology. Pneumonia, cancer, tuberculosis, and pulmonary embolism account for most exudative effusions. Many pleural fluid tests are useful in the differential diagnosis of exudative effusions. The SEAG is superior to Light's criteria in identifying the transudative effusions. It is also observed that Light's criteria identified exudative effusions better than SEAG. The aim of present study was to analyse various biochemical parameters (LDH, pH, Glucose, Triglycerides, Cholesterol, Creatinine, Amylase and ADA) in pleural fluid and to correlate these Biochemical parameters with diagnosis of the patients.

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Pleura, Effusion, Transudate, Exudate, biochemical parameters

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Moringa?oleifera?is one of?the?popular?plants?that have?shown?significant?health?benefits.?Certainly,?preclinical?evidence?(predominantly?from?animal?models)?summarized?in the?current?review?supports?the?beneficial?effects of?Moringa?oleifera?leaf?extracts?in?combating?the?prominent?characteristic?features?of?diabetes?mellitus.?This?includes?effective?control of?blood?glucose or?insulin?levels,?enhancement?of insulin?tissue?sensitivity,?improvement?of blood?lipid?profiles,?and?protecting?against?organ?damage?under?sustained?conditions?of?hyperglycemia.?Interestingly,?as major?complications?implicated?in the?progression?of?diabetes,?including?organ?damage,?Moringa?oleifera?leaf and?seed?extracts?could?efficiently?block the?detrimental?effects of?oxidative?stress and?inflammation?in these?preclinical?models.?Notably,?these?extracts?(especially?leaf?extracts)?showed?enhanced?effects in?strengthening?intracellular?antioxidant?defences?like?catalase,?superoxide?dismutase,?and?glutathione?to lower?lipid?peroxidation?products?and reduce?prominent?pro-inflammatory?markers?such as?tumor?necrosis?factor-?,?interleukin?(1L)-?,?IL-6,?monocyte?chemoattractant?protein-1?and nitric?oxide?synthase.?From?animal?models of?diabetes,?the common?and?effective?dose of?leaf?extracts?of Moringa?oleifera?was?100-300?mg/kg,?within the?treatment?duration?of 2-8?weeks.?Whereas?supplementation?with?approximately?20 g leaf?powder of?Moringa?oleifera?for at?least 2?weeks?could?improve?postprandial?blood?glucose in?subjects?with?prediabetes?or?diabetes.?Although?limited?clinical?studies?have been?conducted?on the?antidiabetic?properties?of Moringa?oleifera,?current?findings?provide an?important?platform?for future?research?directed?at?developing?this plant?as a?functional?food to?manage?diabetic?complications

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diabetes complications, oxidative stress, inflammation, moringa (Moringa oleifera), therapeutic targets

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The COVID-19 virus severely affected the educational system in all over the world. During the pandemic, most of the educational institutions were remained closed which degraded the learning level of the students at the school level. The objective of the present research article is to find out the impact of school closures on the learning level of school students in the Indian context. In this research article researchers have explored the secondary sources that demonstrated the pre-pandemic and after-pandemic learning levels of the students. After analyzing the secondary sources, investigators found the impact of school closures on the learning level; a significant decline was observed in the learning level of students at the school level after the pandemic period.

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learning level, pandemic, COVID-19, school closer, educational institution

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Sentiment analysis is a popular topic in the big data era. In the business world, there is an increasing need for analyzing and characterizing the public's attitude towards new products. Therefore, sentiment analysis with real-time social data can be a useful tool for business marketing. In this project, a sentiment analysis was performed with real-time Social site data that contains customized keywords. There are three parts of this article: i) fetching real-time data online with keywords; ii) applying sentiment analysis with Twitter data and visualize each sentimental category with word clouds; iii) for ease of use, wrapping the sentiment analysis into an interactive dashboard, so users can customize keywords and get the real-time application data.

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Face Detection, Word Processing & Analysis, Video Processing, Machine Learning.

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Road traffic and maintenance induce chronic heavy metal pollution in the atmosphere and roadside soil. A portion of these pollutants could be dispersed into the air or deposited onto soils as a result of wind dispersion. The main objective of this research was to determine the level of Pb, Fe, Zn, Ni, Cd, Cr, and Cu in dust samples collected near industrial, residential, commercial and rural streets in the Jamshedpur city during March- April 2023. The concentrations of heavy metals were analyzed using an inductively coupled plasma-mass spectrometer (ICP-MS). The result shows metal concentrations Pb, Fe, Zn, Ni, Cd, Cr, and Cu are varied from 14.08-145.25 ng/m3, 129.30-687.09ng/m3, 51.21-302.01 ng/m3, 10.08-31.09 ng/m3, 29.52-165.28 ng/m3, 18.25-68.38 ng/m3 and 19.39-64.01 ng/m3 respectively. Overall, the rank of risk contribution to the local environments among the six heavy metals was Fe (375.54) > Zn (180.21) > Cd (98.48) > Pb (76.54) > Cu (41.48) > Cr (40.86) > Ni (18.90). These values were compared with results from various cities/countries world-wide. This study suggests that earth crust and anthropogenic activities such as motor vehicles were the main sources of heavy metal contamination in the study areas.

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Heavy metals, Vehicle emission, Road dusts, ICP-MS.

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This experimental study aims to investigate the effectiveness of bitumen emulsion in stabilizing the sub-base layer of road construction. The sub-base layer plays a crucial role in providing structural support and preventing deformation of the road surface. In this research, bitumen emulsion is introduced as a stabilizing agent to enhance the mechanical properties of the sub-base layer. The study involves laboratory testing of different sub-base materials treated with varying concentrations of bitumen emulsion. The mechanical characteristics, including strength, durability, and moisture susceptibility, are evaluated through standard testing procedures. The experimental results will provide insights into the optimal dosage of bitumen emulsion required for achieving the desired stabilization effects. The findings of this research have implications for the improvement of road construction practices, especially in areas where sub-base layer stability is a critical factor. The use of bitumen emulsion as a stabilizing agent offers a potential sustainable solution, contributing to the longevity and performance of road infrastructure.

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