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A Critical Study: The Transactional Concept of Coping through Electronic Media during the COVID-19 Pandemic
Introduction: Numerous individuals worldwide experienced grief during the COVID-19 pandemic. Due to the imposed isolation and limited accessibility of external resources, media was used extensively as a coping mechanism in several forms. Purpose: In the fast-moving world with the emergence of technology, this chapter articulates the emerging trends of media and its impact. The study aims to explore how grief is handled and resolved with the help of electronic media. Methodology: The study reviews existing literature to explore media-related coping strategies by applying the Lazarus-Folkman transactional coping theory as a lens. Results: During the COVID-19 pandemic, there was an increase in media usage among individuals. Based on a review of existing research, media-based coping was used for a range of stressors, including isolation, misinformation and time wastage, work-life disruption, and personal loss. Media is a potential source of readily available, accessible, and effective coping. It can be harnessed to support the rising number of individuals whose mental health needs cannot be catered to by the limited number of qualified mental health professionals. Conclusion: Grief can be handled and resolved in different ways with the assistance of the media. The media can also be used to override the taboo that prevents individuals from seeking support to cope with their grief. Researchers and practising mental health professionals can explore the utility of media-based coping mechanisms and formulate plans to use them effectively. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
Patent Dispute settlement through Arbitration and the public policy concerns
India is a developing nation, which had shown both progress and decline in economy over the years. Intellectual property rights are considered as an important asset of a nation. National legislations are made in par with the international conventions and treaties, more concentration on the industry and investments are needed for the development of the nation. Patent legislations changed on basis of the national and international needs. The monopoly right granted for an invention is on the basis of their intellectual skill. Patent dispute settlement mechanisms are mainly patent office through controller of patent, District Court & High Court and the patent tribunals. Patent is granted for 20years in India. The patent holder can utilize the same within this short span of time. Hence all the patent holders and the public challenging the validity of the patent, expect a speedy justice in patent disputes. This research paper addresses the question as to whether subject matters that can be referred for arbitration can be limited on grounds of public policy. Further the paper will address the issues as to whether arbitration can be effective mechanism for settling patent disputes in India. 2023 Brazilian Center for Mediation and Arbitration - CBMA. All Rights Reserved. -
Starting from the roots of teacher education: Inclusion of educational neuroscience in teacher training in India
Educational neuroscience has warranted much research and showed much promise in recent times. However, there is a lack of effective bridging between research in this field and its implementation in actual classroom settings. In order to bridge this gap, a key strategy is to include educational neuroscience in teacher training and education. The current study uses a survey method to assess student-teachers' awareness, opinions, and openness toward educational neuroscience concepts and techniques. This study examines a snowball sample of 83 Indian student-teachers who joined the Bachelor of Education program in 2018, 2019, and 2020. The results of this study indicate that although most student-teachers are aware of certain techniques, they are unaware that it is part of educational neuroscience. Further, the student-teachers also showed interest in learning such techniques and considered it relevant and useful in classroom teaching. Finally, this study also highlights the role of decision-makers in including educational neuroscience in the B.Ed. program, possibly as an optional paper. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Exploring the dream pattern among the nightshift workers: A qualitative study
Nightshift workers are increasing day by day, but many times, people forget the health and sleep effects caused by the nightshift. One such impact is the altered circadian rhythm, which is very important for proper functioning of the body and a good sleep. This altered circadian rhythm can have an impact on waking and sleep life of the nightshift workers. This qualitative study is to find the dream pattern among the nightshift workers and to find the frequency in dreaming among this group. Dreams are the reflections of the waking life and dream patterns are seen among groups sharing similar wake life experiences. This study is conducted with nine nightshift and nine dayshift workers, dream journal was used to collect the dreams from the participants. The frequency of dreaming is seen more among the nightshift workers. The dream patterns among both the groups are similar but there are dreams that make the nightshift group different from the dayshift. The dreams of the nightshift group includes mainly their friends and the feelings of being stuck/in danger. Also, their dreams were more fantastic in nature and have more emotional content. The study shows that sexual dreams are seen majorly among the nightshift group. This finding can be further used to conduct researches on the impact of nightshift on the sexual health and overall well being of nightshift workers and the reflection of the same in their dreams. 2020. All Rights Reserved. -
Saraca asoca (Roxb.) de Wilde, a sacred tree: its nutritional value, elemental composition and anti-nutritional content
The sacred Saraca asoca (Roxb.) de Wilde tree holds significant medicinal value and is utilized in ayurvedic preparations to treat various health conditions. This research investigated the nutritional, elemental and antinutritional properties of S. asoca leaves and flowers. The nutritional qualities of the tree parts were examined using the muffle furnace and micro-Kjeldahl techniques. Titration techniques were used to assess the antinutritional content of plants, whereas EDX (Energy dispersive X-ray) was used to determine the mineral content. Phytochemical analysis revealed the presence of tannins, phenols and flavonoids, along with antioxidant properties that could neutralize free radicals generated by metabolic processes in the body. Nutritional analysis indicated that the floral parts of S. asoca had higher moisture, carbohydrate and crude fat content than the leaves. Conversely, the leaves had elevated ash levels, crude fiber and protein. Leaf samples showed higher concentrations of minerals like calcium, phosphorus, sodium, iodine, iron and manganese compared to the floral samples. In contrast, flower samples exhibited higher potassium, copper, silicon and zinc levels. These findings highlight the rich nutritional profile, abundant phytochemicals and essential minerals in both tree parts, with low anti-nutrient content. This information could be instrumental in developing phytopharmaceuticals and nutritious food products. Additionally, utilizing these tree parts could offer a cost-effective way to enhance nutrient intake and address nutritional deficiencies in humans and animals. Copyright: The Author(s). -
Surface modified CaO nanoparticles with CMC/D-carvone for enhanced anticancer, antimicrobial and antioxidant activities
The rising prevalence of antimicrobial resistance and the continued challenge to cancer therapy are in desperate need of developing innovative therapeutic strategies. In this regard, the present research work focuses on the development of CaO NPs and CaO-CMC-Dcar nanocomposites for enhanced antimicrobial and anti-cancer activities. CaO nanoparticles were synthesized by facile one pot chemical approach and eventually functionalized with CMC and D-carvone biomolecules. XRD analysis revealed that the crystallite size for CaO and CaO-CMC-Dcar nanoparticles was found to be 21.18 nm and 17.02 nm respectively. The band gap values obtained for CaO and CaO-CMC-Dcar nanoparticles were 4.44 eV, and 4.25 eV respectively. The CaO-CMC-Dcar nanoparticles show absorption maxima at 292 nm, slightly red-shifted from bare CaO nanoparticles. HRTEM and SEM analysis revealed that the prepared samples were roughly spherical and agglomerated in nature. Antimicrobial activity was evaluated against methicillin-resistant Staphylococcus aureus (MRSA) and Candida albicans. The zone of inhibition (ZOI) for CaO-CMC-Dcar nanoparticles against MRSA and C. albicans was 20.1 0.3 mm and 21.1 0.2 mm, respectively, significantly higher than that of pure CaO nanoparticles (14.1 0.2 mm and 13.2 0.1 mm) and comparable to standard anti-bacterial streptomycin and antifungal fluconazole discs. Anticancer activity was assessed via MTT assay against MOLT-4 blood cancer cells, where the IC50 values for CaO and CaO-CMC-Dcar nanoparticles were 22.6 ?g/mL and 21.54 ?g/mL, respectively. Additionally, CaO-CMC-Dcar nanoparticles exhibited enhanced antioxidant activity (80 %) compared to CaO (70 %) at 20 ?g/mL, with performance comparable to that of Vitamin C. Experimental results revealed that the CaO-CMC-Dcar nanoparticles exhibited superior biological activity compared to pure CaO nanoparticles. 2025 Indian Chemical Society -
Migration, threats to identity and diminishing human dignity /
RESEARCH REVIEW International Journal of Multidisciplinary, Vol.5, Issue 2, pp.49-52, ISSN No. 2455-3085. -
Prior Cardiovascular Disease Detection using Machine Learning Algorithms in Fog Computing
The term latent disease refers to an infection that does not show symptoms but remains forever. In this paper, proposed a novel methodology for addressing latent diseases in machine learning by integrating fog computing techniques. Here there is a link between HIV to heart disease, that is when a person progresses to the next stage of HIV, a plague infection develops, causing cholesterol deposits to form. Plaque development causes the inside of the arteries to constrict over time, which may stimulate the release of numerous heat shock proteins and immune complexes into the bloodstream, potentially leading to heart disease. Heart disease has long been considered as a significant life-threatening illness in humans. Heart disease is driven by a range of factors including unhealthy eating, lack of physical exercise, gaining overweight, tobacco, as well as other hazardous lifestyle choices. Five different classifiers are used to perform the precision; they are Support vector machine, K-nearest neighbor, decision tree, and random forest, after we have used the classifier, the recommended ideal will split disease into groups which is created based on their threat issues. This will be beneficial to doctors assisting doctors in analyzing the risk factors associated with their patients. 2023 IEEE. -
Analyzing Market Factors for Stock Price Prediction using Deep Learning Techniques
This paper presents a comprehensive study on stock price predictions by integrating market factors and sentiment analysis of news headlines. The research is divided into two modules, each employing distinct methodologies to enhance the accuracy of stock price forecasts. In the first module, market factors are investigated using three advanced algorithms: Long Short-Term Memory (LSTM), Gradient Boosting Decision Trees (GBDT), and Facebook Prophet (FBPROPHET). These algorithms are evaluated based on metric scores such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The analysis focuses on predicting high and low values of market prices for the period from January to June 2021. The comparative assessment of these algorithms provides insights into their effectiveness in capturing market trends and making precise predictions. In the second module, the paper explores the impact of news headlines on stock prices by extracting sentiment using three distinct algorithms: lexical-based analysis, Naive Bayes, and FinBERT. The sentiment analysis aims to gauge the market sentiment reflected in news articles and assess its influence on stock price movements. Prediction accuracy is calculated for each algorithm, highlighting their strengths in capturing sentiment patterns. 2024 IEEE. -
Leveraging Model Distillation as a Defense Against Adversarial Attacks Based on Deep Learning
Adversarial attacks on deep learning models threaten machine learning system security and reliability. The above attacks use modest data alterations to produce erroneous model results while being undetected by humans. This work suggests model distillation to prevent adversarial perturbations. The student model is taught to emulate the teacher model in model distillation. This is done using teacher model soft outputs. Our idea is that this strategy organically strengthens the student model against adversarial assaults by keeping the teacher model's essential knowledge and generalization capabilities while reducing weaknesses. Distilled models are more resilient to adversarial assaults than non-distilled models, according to experiments. These models also perform similarly on undamaged, uncorrupted data. The results show that model distillation may be a powerful defense against machine learning adversaries. This method protects model resilience and performance. 2023 IEEE. -
Design and Implementation Bidirectional DC-AC Converter for Energy Storage System
This article proposes a bidirectional single-phase dc-ac converter with triple port converter (T-PC) for application of energy storage. This proposed converter provides three ports such as ac port, dc port, and dc bus port to achieve three power interfacing ports. For the direct conversion process, dc port is directly connected to T-PC, and direct power will be exchanged between energy storage device (ESD) and grid when the ESD voltage peak amplitude is lower than the ac voltage. Thus, a dc-dc converter downstream power process gets reduced, and power loss is decreased considerably. Due to multilevel characteristics, switching losses in the T-PC can be reduced. The efficiency of the overall bidirectional dc-ac conversion process can be increased significantly. The circuit model, working principle, and modulation control of T-PC-based bidirectional dc-ac conversion concepts are analyzed. A 1.5-kW test-bench model is developed and its effectiveness is verified to find the merits of suggested conversion. 2021 IEEE. -
Design and implementation of a universal converter for microgrid applications using approximate dynamic programming and artificial neural networks
This paper introduces a novel design for a universal DC-DC and DC-AC converter tailored for DC/AC microgrid applications using Approximate Dynamic Programming and Artificial Neural Networks (ADP-ANN). The proposed converter is engineered to operate efficiently with both low-power battery and single-phase AC supply, utilizing identical side terminals and switches for both chopper and inverter configurations. This innovation reduces component redundancy and enhances operational versatility. The converter's design emphasizes minimal switch usage while ensuring efficient conversion to meet diverse load requirements from battery or AC sources. A conceptual example illustrates the design's principles, and comprehensive analyses compare the converter's performance across various operational modes. A test bench model, rated at 3000W, demonstrates the converter's efficacy in all five operational modes with AC/DC inputs. Experimental results confirm the system's robustness and adaptability, leveraging ADP-ANN for optimal performance. The paper concludes by outlining potential applications, including microgrids, electric vehicles, and renewable energy systems, highlighting the converter's key advantages such as reduced complexity, increased efficiency, and broad applicability. The Author(s) 2024. -
Encapsulated 3converter for power loss minimization in a grid-connected system
A newly designed DCAC three phase bidirectional converter (DATBC) with an encapsulated DCDC converter (EDC) for the energy storage system (ESD) is analysed and investigated in this research paper. By using encapsulated or embedded or hidden DCDC converter a stable and constant DC bus is developed between the encapsulated DCDC converter and DCAC three phase bidirectional converter. The proposed converter is entirely different from the traditional dual-stage DCAC converter, because it takes less than 20% of power used for the DCAC conversion process. So, this reduced power consumption increases efficiency to a considerable value. A new control technique for zero sequence has been adopted components are inserted in the modulating signal based on carrier pulse width modulation (CPWM). Working principle, implementation and characteristics of the DCAC three phase bidirectional converter are analysed. Effectiveness and feasibility of the developed converter are examined with a proto-type model. 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
IPWM Based IBMSC DC-AC Converter Using Solar Power for Wide Voltage Conversion System; [Convertisseur DC-AC IBMSC bassur l'IPWM et utilisant l'ergie solaire pour un syste de conversion large tension]
This article proposes isolated bidirectional micro dc-ac single phase controlled (IBMSC) converter based on in-phase-voltage pulsewidth modulation (IPWM). This resonant IPWM converter, ratio of voltage conversion can be controlled from 0 to ?. So, this converter is highly referred for huge range voltage conversion. However, voltage conversion ratio determines power transfer direction and duty ratio. Power flow direction and duty cycle value can be varying smoothly, so it is suitable for dc-ac bidirectional power conversion application. Inverter mode and also rectifier mode are possible from bidirectional operation, which is controlled by a unified current controller. The proposed solution can achieve smooth switching grid operation with high efficiency. Working principle, design procedure, control strategy, and characteristics of the proposed converter are implemented with a prototype model of power rating 500 W with a voltage range of 20-50 V to test the ability of withstanding. Performance, feasibility, and effectiveness of the proposed converter are tested with this hardware test-bench model. 2022 IEEE. -
Design and implementation of dual-leg generic converter for DC/AC grid integration
A newly designed generic photo-voltaic (PV) DC-DC/DC-AC converter is for direct current (DC) grid or single-phase alternating current (AC) grid integration. Main concept of the proposed converter is universal power conversion, and the same converter is used for DC-DC/DC-AC applications which also aiming for minimum redundancy because the proposed converter can be able to produce DC and AC output from the fixed/variable DC source. The proposed converter is designed with single-stage dual leg topology, with a designed filter, and protection circuits are connected in output/grid side. The proposed circuit is compared with existing topologies, and comparative analyses are made in both chopper (DC-DC) and inverter (DC-AC) modes for universal or generic operation. Real-time implementation of the proposed model is prepared for the power rating of 3.5 KW during inverter mode and 4 KW when same circuit working in chopper mode. Hardware results are obtained from the model from both chopper and inverter modes. Finally, correct applications, advantages, and future work are concluded in the last section. 2023 John Wiley & Sons Ltd. -
Newly designed single-stage dual leg DC-DC/AC buck-boost converter for grid connected solar system
This paper proposes a novel single-stage buck-boost inverter based on dual leg. Modulation techniques, working principle, guidelines for components design, and guidelines are discussed and presented. A theoretical concept is initially tested in Simulink platform and practically verified with a test bench model. A practical model is developed to verify the simulation model and tested different modes of operation are analyzed. The main advantages of the proposed work are as follows: The number of passive components is less, switching frequency components are not high so leakage current is very less, and voltage control in a wide range is achieved without using a DC link capacitor. High efficiency can be achieved due to multi-stage operation. This proposed work is suitable for high/low voltage PV-based energy conversion. Electromagnetic interference is also reduced due to continuous input current. 2023 John Wiley & Sons Ltd. -
Fault Analysis and Clearance in FL-APC DC-AC Converter; [Analyse et imination des dauts dans le convertisseur CC-CA FL-APC]
The traditional active neutral-point-clamped (APC) dc-ac converter maintains great common-mode voltage with high-frequency (CMV-HF) reduction capability, so it has limited voltage gain. This article presents a new five-level APC (FL-APC) dc-ac converter capable of voltage step-up in a single-stage inversion. In the suggested design, a common ground not only reduces the CMV-HF but also improves dc-link voltage usage. While comparing with traditional two-stage FL-APC dc-ac converter, the proposed design has lower voltage stresses and greater uniformity. While improving overall efficiency, the suggested clamped dc-ac converter saves three power switches and a capacitor. Modeling and actual tests have proven the suggested APC inverter's overall operation, efficacy, and achievability. The proposed circuit is finally tested with fault clearance capability. 2023 IEEE. -
ITBC Controlled IPWM for Solar Based Wide Range Voltage Conversion System
This paper presents an isolated tiny or micro-bidirectional DCAC converter (ITBC) that operates in a single-phase, single-stage, bidirectional, and isolated configuration. The converter utilises a voltage-in-phase PWM (IPWM) control scheme to regulate the potential conversion ratio of the converter, enabling it to handle a wide voltage range. The converter also enables smooth power flow direction changes and can achieve soft switching, resulting in high efficiency. A unidirectional current controller can be used for both DCAC and ACDC modes. The paper provides detailed information about the micro-inverter's working principles, design procedure, characteristics, and control strategy. The proposed solution is verified by a 500-watt test bench model with a voltage input range of 30 volts to 50 volts. 2024 IETE. -
The Role of Machine Learning Analysis and Metrics in Retailing Industry by using Progressive Analysis Pattern Technique
Analyzing customer purchasing data has been a challenging task for data analyzers. Even though lots of methods are introduced in this kind of research but still many barriers are there to finding the optimal pattern. Consider customer buying data is used to examine the types of parameters which is influence the customer. In this proposed work, Progressive Analysis Pattern Technique (PAPT) to predict future customer buying patterns in online shopping. We incorporated dynamic data handling prior to the proposed methodology. It will give ample purpose for the organization's perspective because the proposed work primarily focused on customer features related to the number of product quantities and product price variations of the previous purchase. Marketing strategies are most effective if they are focused to the exact client requirements. A Significant mission in campaign planning is deciding which customer to target. This research paper focusses on empirical targeting models. 2023 IEEE. -
Hybrid Bayesian and modified grey PROMETHEE-AL model-based trust estimation technique for thwarting malicious and selfish nodes in MANETs
Cooperation among mobile nodes during the routing process is indispensable for attaining reliable data delivery between the source and destination nodes in the Mobile ad hoc networks (MANETs). This cooperation between mobile nodes sustains the performance of the network especially when they are been deployed for handling an emergency scenario like forest fire, flooding, and military vehicle monitoring. In specific, the criteria considered for determining the cooperation degree of mobile nodes attributed towards the routing proves is dynamic and uncertain. In this paper, Hybrid Bayesian, and Modified Grey PROMETHEE-AL Model-based Trust Estimation (MGPALTE) technique is proposed for thwarting Malicious and Selfish Nodes for enforcing cooperation between the mobile nodes in MANETs. It specifically utilized Bayesian BestWorst Method method for generating the set of weights related to objective group criteria. It is also used for aggregating the judgements of cooperation determined during indirect monitoring process. Moreover, Grey theory is integrated with the classical PROMETHEE for improving its efficacy in terms of accuracy with respect to ranking of mobile nodes participating in the process of routing. This proposed MGPALTE technique isolated the malicious mobile nodes from the routing path depending on the threshold of detection. The simulation results of the proposed MGPALTE technique confirmed better packer delivery rate of 19.21%, improved throughput of 22.38%, minimized delay of 23.19%, and reduced end-to-end delay of 21.36%, better than the competitive cooperation enforcement strategies with different number of mobile nodes in the network. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.