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A qualitative causal analysis on incremental behavioural complexities due to fomo (Fear of missing out) in indian youth
FOMO (Fear of Missing Out), a new threatening dampener of youth is prevalent across the world, and is shaping up as a wicked problem to Indian youth, especially in the category of Teens, Adolescents, including educated youth. The vulnerability is getting deeper and severe in terms of behavioural problems that turns as outcome. This qualitative paper contemplates on the human behavior with invasive nature of a newer and stronger, psychological stimulus to youth via, the digital connectivity, social media and mobile phones, called, or abbreviated as FOMO. Why FOMO has become a huge discomfort to almost all the organizations even, at times, separate teams are set to put things at control. This article qualitatively with the secondary statistics carried out across the world, and contemporary research outcome on the FOMO, tries to correlate, how the other countries are impacted, and tries to find a feasible practical moderating factors, that can wane down the impact or pull down the severity, the FOMO is causing in the life of youth. What are the strategies that can be adopted to bring down the level of damages, with suggestions for handling and managing the situation, rather than controlling, as most of the worlds work life balance is happening because of the FOM O. Also this study tries to validate the utilities of JOMO, and will it be possible in the Indian environment, since the youth are not in a position to bring d own the situation. Is NOMO too is growing up vividly across silently, is what the study concludes. 2019 ETA-Florence Renewable Energies. -
A Qualitative Enquiry of the Experience of Music Professionals during the COVID-19 Pandemic
Introduction: The COVID-19 pandemic became a new normal in todays world and has changed the consumption pattern and absorption of music and music apps in India. The music industry is relatively non-telecommutable, making working from home difficult during the imposed lockdown and social distancing norms. These conditions had adverse effects on the physical and mental health of music professionals. Therefore, it was crucial to understand the differential impact of COVID-19 on music professionals to find effective solutions and plan for future careers in a changed music industry. Method: The current paper qualitatively explored the experiences of the music professionals participating in this research during the COVID-19 pandemic in India. Twelve participants having 8 years of average professional experience (comprising singers, instrumentalists, music teachers, composers, YouTube content creators) were telephonically interviewed during the second wave of COVID-19 in India. The interviews were analysed using thematic content analysis. Results: The thematic content analysis resulted in the emergence of two major themes identified from the participants narratives were impact on participating music professionals and coping reactions. Conclusion: The themes emerged from analysis highlighted the impact of COVID-19 on these music professionals and the coping reactions utilized by them. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
A Qualitative Exploration of the role of intersectionality in health disparities faced by Indian transgender persons
Transgender persons in India represent a minority and are subjected to varying levels of disparities, including those in health. These disparities for a transgender person are multi-axial and have a complex origin and manifestation that can only be assessed and explored through an intersectional lens where efforts are made to understand the collision of multiple and different identities and the role these identities play in a transgender person's life. This study aimed to explore the role of intersectionality in the health disparities as experienced by Indian transgender persons. Twelve transgender persons from rural, semi-rural, and urban residences were interviewed. The data was analysed through interpretative phenomenological inquiry. Following the same, five sub themes were emerged. 'Social and health disparities among Indian transgender persons' emerged as a group experiential theme in the analysis. The sub- themes were religion, place of residence, age, socio-economic status, and colour, which play a role in disparities of their physical as well as mental health treatment, henceforth resulting in the development of 'pervasive transphobia' in the Indian healthcare system as per the experiences lived by the participants. Following the findings of this study, we may assert that Indian transgender people perceive that they are disproportionately affected by health disparities. Henceforth, there is an urgency to unfold such disparities in health through the lens of intersectionality. 2024 Sapienza Universita Editrice. All rights reserved. -
A qualitative study on the reasons for online product
return in India /International Journal For Research In Engineering Application & Management, Vol.4, Issue 12, pp.152-154, ISSN No: 2454-9150. -
A Qualitative Study to Understand the Nature of Abuse Experienced by Persons with Severe Mental Illness
Persons with Severe Mental Illness (PwSMI) living in the community are considered high-risk groups for victimization. However, the nature of violence experienced by PwSMI is not well understood in India, which limits the effectiveness of clinical interventions to prevent revictimization. The Key Informant Interviews (KIIs) and Focused Group Discussion guides were developed, content validated, and pilot tested. A total of 27 KIIs and 5 focus groups were conducted with 14 PwSMIs, 19 experts, and 18 caregivers. Thematic analysis was done using Braun and Clarke's six stages of thematic analysis. The saturation of themes was determined using the Comparative Method for Themes Saturation (CoMeTS). Some of the themes and subthemes that emerged were (1) Physical Abuse (physical restraining, hitting, spitting), (2) Psychological Abuse (living in a controlling environment, criticized, neglected, scapegoated, symptomization of emotions and behavior),(3) Sexual Abuse (sexual assault, reproductive coercion, sexual exploitation), (4) Social Abuse (teased or labeled, social deprivation, abandonment, discrimination, and exclusion), and (5) Trauma in formal care (Coercive treatment practices, seclusion, negative attitude of staff, surreptitious prescribing of medicines, patronizing behavior). Abuse experienced by PwSMI has significant treatment and health care costs and an increased burden on families and society, so comprehensive psychosocial care and support are needed to prevent revictimization. Copyright 2023, Mary Ann Liebert, Inc., publishers 2023. -
A Quality of Service Study for Downlink Scheduling Algorithms in Mobile Networks
Internet usage and the number of applications/users growth is going in an unprecedented manner. In these days, lot of users are changed themselves to use internet-based applications rather than traditional voice service. The fundamental of voice-based communication is shifted to packet data access for satisfying the human needs through internet based mobile applications. 4G network is an IP supported rising technology for the past decade and at present also because of un availability service of 5G in all the places. Still, 4G is ruling the globe and the number of subscribers kept growing only. In these days, this remains on the list of latest research topics. Under 4G technology lot of research problems are exist like QoS, Uplink and Downlink Scheduling, Security, Mobility etc., Inspite of discussing that several issues, this paper mainly focusing the QoS in Downlink scheduling algorithms. Also, it presents the issues of various existing QoS downlink scheduling algorithms, names, QoS aware/unaware, parameters used/simulated, drawbacks of those algorithms and result verifications etc. Packet scheduling plays a crucial role for providing Quality of Service (QoS) to the mobile users. Ultimately, it gives some suggestions to explore more further about QoS based research work in Mobile Networks. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A Quantitative Analysis of Trading Strategy Performance Over Ten Years
This study conducts a comparative analysis of two trading strategies over a ten-year period to assess their profitability and risk. Strategy 1 operates on a simple buy at close and sell at open principle, while Strategy 2 trades only when the closing price is above the 200-day moving average, introducing a conditional filter for market entry. Through the evaluation of performance metrics including total PNL, drawdown, standard deviation, and Sharpe ratio, the research highlights the differences in risk and return between the strategies. Results indicate Strategy 1 achieves higher profitability but at the cost of greater risk, as shown by larger drawdowns. Conversely, Strategy 2's conditional approach yields slightly lower returns but demonstrates a superior risk-adjusted performance. The findings emphasize the significance of risk management and the potential benefits of conditional filters in trading strategies, offering valuable insights for traders and investors in making informed strategy selections. 2024 IEEE. -
A Quantum-Inspired Self-Supervised Network model for automatic segmentation of brain MR images
The classical self-supervised neural network architectures suffer from slow convergence problem and incorporation of quantum computing in classical self-supervised networks is a potential solution towards it. In this article, a fully self-supervised novel quantum-inspired neural network model referred to as Quantum-Inspired Self-Supervised Network (QIS-Net) is proposed and tailored for fully automatic segmentation of brain MR images to obviate the challenges faced by deeply supervised Convolutional Neural Network (CNN) architectures. The proposed QIS-Net architecture is composed of three layers of quantum neuron (input, intermediate and output) expressed as qbits. The intermediate and output layers of the QIS-Net architecture are inter-linked through bi-directional propagation of quantum states, wherein the image pixel intensities (quantum bits) are self-organized in between these two layers without any external supervision or training. Quantum observation allows to obtain the true output once the superimposed quantum states interact with the external environment. The proposed self-supervised quantum-inspired network model has been tailored for and tested on Dynamic Susceptibility Contrast (DSC) brain MR images from Nature data sets for detecting complete tumor and reported promising accuracy and reasonable dice similarity scores in comparison with the unsupervised Fuzzy C-Means clustering, self-trained QIBDS Net, Opti-QIBDS Net, deeply supervised U-Net and Fully Convolutional Neural Networks (FCNNs). 2020 Elsevier B.V. -
A Quasi-Experimental Study on the Effectiveness of Integrated Electroencephalogram Neurofeedback Training and Group Psychotherapy for Harmful Alcohol Use: Neurocognitive and Clinical Outcomes
Introduction. This study investigates the efficacy of integrating electroencephalogram (EEG) neurofeedback training and group psychotherapy for individuals with harmful alcohol use (AUDIT-10 scores 1013). Methods. Seventy-six participants were purposively sampled and divided into treatment (EEG neurofeedback training and group psychotherapy) and control groups. Baseline assessments measured alcohol consumption (AUDIT-10), stress (perceived stress scale [PSS]), neurocognition (NIMHANS neuropsychological battery), craving (PACS), and visual analog scale. The treatment group underwent 20 sessions of EEG neurofeedback (Peniston-Kulkosky and Scott-Kaiser modification protocols) and four sessions of group psychotherapy (motivational interviewing [MI], psychoeducation). Result/Discussion. A repeated measures ANOVA showed significant improvement in postcondition scores for the treatment group compared to controls, who exhibited deterioration over time. The study provides evidence supporting the efficacy of integrated EEG neurofeedback training and group psychotherapy in mitigating harmful alcohol use progression. Conclusion. By addressing stress, cognition, and cravings, this intervention offers crucial support to individuals with problematic drinking. 2024. Panicker et al. -
A rapid and selective on-off fluorescence detection of lethal pulmonary agent phosgene supplemented with theoretical approach: a cost-effective sensing tool for household bleach and soil analysis
A fluorescent probe, 4-(di-phenylamino)-benzaldehyde oxime (DPBO), was developed comprising 4-(diphenylamino) benzaldehyde as the fluorophore and hydroxyl amine, where the resultant oxime group leads to the formation of a recognition site for the selective on-off fluorescence detection of lethal phosgene with the dimer formation of DPBO through carbonate linkage generated from phosgene. The probe DPBO also exhibits notable spectrofluorometric response in different solvents, as demonstrated by SEM analysis. The detection limit of the probe DPBO towards phosgene was calculated as 21.53 ?M, with a fast reaction response time within 30 s and the fluorescence quenching efficiency of DPBO by phosgene was measured through the Stern-Volmer quenching constant (KSV) estimated at 1.03 104 M?1. Confirmation of the sensing mechanism was achieved through various spectroscopic techniques such as UV-vis, emission spectroscopy, mass spectrometry, and computational studies. For practical applications, the sensor DPBO can be utilized for the detection of phosgene in household bleach, soil analysis and dipstick method. 2024 The Royal Society of Chemistry. -
A rapid investigation of near-infrared (NIR) fluorescent switch-on probes for detection and in cellulo tracking of G-quadruplex and double-stranded DNA
This review provides a comprehensive overview of the recent advancements in Near Infrared (NIR) fluorescence switch-on probes designed for the detection and in cellulo tracking of G-quadruplex and double-stranded DNA (dsDNA). G-quadruplexes, non-canonical DNA structures, play pivotal roles in regulating various biological processes, making them critical targets for therapeutic and diagnostic applications. The unique properties of NIR fluorescence probes, such as deep tissue penetration, minimal photodamage, and low autofluorescence background, offer significant advantages for bioimaging. We critically analyze the design strategies, photophysical properties, and binding mechanisms of various NIR fluorescence switch-on probes. Additionally, we discuss their efficacy and specificity in identifying G-quadruplexes and dsDNA within cellular environments. Key challenges and future directions for improving the sensitivity, selectivity, and biocompatibility of these probes are also highlighted. This review aims to underscore the potential of NIR fluorescence probes in advancing our understanding of DNA dynamics and their applications in biomedical research. 2024 The Royal Society of Chemistry. -
A ratiometric fluorescent sensor based on dual-emissive carbon dot for the selective detection of Cd2+
Cadmium (Cd2+), a heavy metal ion used in numerous industries, has toxic adverse effects on the environment; it is crucial to develop a quick and reliable method for Cd2+ determination. Fluorescent biomass-derived carbon quantum dots (CD) with rich carboxyl groups on the surface were synthesized using water amaranth leaves by hydrothermal method with a 12.1% quantum yield. The surface of CD was further modified with 1-pyrene carboxaldehyde (PC) to synthesize pyrene carboxaldehyde-carbon quantum dots (PC-CD). This study developed a fluorescent ratiometric nanosensor using a covalently functionalized CD with pyrene derivative and demonstrates highly selective identification capability towards Cd2+ over competing metal ions. The Nano sensor has significant selectivity towards Cd2+ in an excellent linear range of 0-70 ?M with a detection limit as low as 15 nM and demonstrates excellent water solubility and biocompatibility. Transmission electron spectroscopy (TEM), Fourier Transform infrared spectroscopy (FT-IR), and X-ray photon spectroscopy (XPS) were used to identify the surface functionalization of PC-CD. Finally, the developed ratiometric sensor was used for detecting Cd2+ metal ions from various water effluents. 2023 Elsevier Ltd. -
A ratiometric luminescence thermometer based on lanthanide encapsulated complexes
Lanthanide-containing complexes have been widely developed as ratiometric luminescence thermometers, which are non-invasive, contactless and accurate. The synthesis of these Ln complexes generally requires high temperatures, multiple steps and other harsh conditions. Moreover, bimetallic lanthanide complexes, which have been reported to be better thermometers, are even more challenging to synthesize. This complexity can be simplified by preparing a host-guest complex of lanthanides. In this work, Tb or both Tb and Eu are encapsulated in an MOF host, making them emissive. The ratio of Tb/Eu was also easily tuned by simply changing their ratio in the solution, resulting in a tunable emission. Accordingly, we were able to synthesise both the emissive Tb complex and Tb/Eu complexes at different ratios using a single host. The complexes were found to be suitable as ratiometric luminescent thermometers in the temperature range of 160-380 K, with reasonably good sensitivity and uncertainty. The thermometer's sensitivity and uncertainty were significantly improved using bimetallic Tb and Eu host-guest complexes. Calculations using the host and Eu emission ratio were found to provide better thermometer parameters than the commonly reported Tb and Eu emission ratio. Thus, using a single host, we were able to synthesise different lanthanide complexes that can sense temperature, and we improved the thermometer parameters by incorporating multiple lanthanides in a single host. This research will enable the scientific community to reexamine the applicability of unexplored host-guest lanthanide complexes. 2025 The Royal Society of Chemistry. -
A real time fog computing applications their privacy issues and solutions
Edge Computing (EC) has brought cloud technology to the channel's edge. It inherits some qualities from cloud services, but it also has some distinctive features such as geo-distribution, network connectivity, and reduced power. Along with the genetic inheritance, it also acquires the issues and concerns cloud computing services, such as renewable energy and resource allocation. This work provides a critical analysis of the fog architectural design in terms of security. Since 2018, the state of the artwork has been critically analyzed in terms of security mechanisms and security threats. The existing security methods are classified based on the security objectives they achieved. It would provide a complete and coherent difference between both the security areas investigated and those that have not. 2021 IEEE. -
A Real-Time Approach with Deep Learning for Pandemic Management
It has never been so critical to managing pandemic situations created by a virus like COVID-19, which has brought the world almost to a standstill, claiming millions of lives. Learning from all earlier viruses and building a quick tackling mechanism is a need of the hour. There is a greater need for technology to collaborate with healthcare and leverage each of the domains expertise. With less time in hand, this collaboration must happen in a short time. There is a need to study the exiting progression in technology and the healthcare landscape to bring them to a common path for practical solutions. In the chapter, an attempt was made to put together some thoughts in both fields to relate them to pandemic managements frequent subject. Caution is drawn towards some crucial aspects, such as security and transparency, that cannot be compromised in this journey. Artificial intelligence (AI), being at the forefront of the technology supporting lives, provides a greater hope in this direction. Some of the prominent approaches can be looked at from a pandemic management point of view, which can start a more in-depth discussion on AI and healthcare going hand in hand in managing this pandemic situation. Essential areas of pandemic management, such as building on the knowledge gathered over a period, plugging in the real-time data from the society, building efficient data management systems and building transparent and interpretable solutions are the focus areas of exploration in this chapter. 2022, Springer Nature Switzerland AG. -
A reconfigurable integrated level shifted carrier based PWM method for modular multilevel converters
This article presents a reconfigurable integrated level shifted carrier-based pulse width modulation (ILSC-PWM) method for modular multilevel converters (MMCs). The principles of basic level shifted carrier-based PWM (LSC-PWM) methods such as phase disposition PWM (PD-PWM), phase opposition disposition PWM (POD-PWM) and alternate phase opposition disposition PWM (APOD-PWM) methods are combined to develop the concept of reconfigurable ILSC-PWM method. The main objectives of the proposed reconfigurable ILSC-PWM method is to develop the pulse width modulated output voltage with both half-wave and quarter-wave symmetries and to reduce the total harmonic distortion (THD). A simplified mathematical approach is developed to formulate reconfigurable single ILSC wave for MMC with N number of submodules (SMs) per arm. The functionality and performance of the reconfigurable ILSC-PWM method are carried out on three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of single-phase five-level MMC is designed for experimental validation. The proposed ILSC-PWM method is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field programmable gate array (FPGA). Computer Simulations and laboratory experimental results are presented. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. -
A Reconfigurable Multilevel Inverters with Minimal Switches for Battery Charging and Renewable Energy Applications
In recent years, classical inverters such as the H-bridged cascaded multilevel inverter, flying capacitor, and flying capacitor multilevel inverter have contributed in electric vehicle and non-conventional energy applications. Due to higher switching and conduction losses, as well as a greater number of power switches and driver circuits, conventional multilevel inverters do not achieve the highest performance. To obtain higher performance while reducing power losses and total harmonic distortion, individual switches are controlled by logic gates. In this proposed work, one of the inverters is considered symmetrical voltage another is asymmetrical voltage for implementing these effective topologies. The proposed single-phase seven-level voltage output and current for both symmetric and asymmetric multilevel inverters are employed to test the intended computation. The MATLAB/Simulink tool is used to implement and investigate the various parameters of proposed topologies. 2022 IEEE. -
A refined mechanism for human face recongnition from video footages
Undoubtedly homeland security is a noteworthy concern in today's increasingly connected world and there is a bevy of IT-based security solutions and services emerging and evolving to guarantee the safety and security of people and properties. Security and surveillance cameras are the prominent security solutions. People movements, gestures, and activities are being minutely monitored, captured as images and videos, and subjected to a variety of investigations in order to extract anything uncommon. As videos capture the movement, there is no requirement for the user to coordinate with the camera; video arrangements need not contain face images alone despite the fact that human appearances are vital articles in video sequences. Henceforth recognising a face from the sequence of a video turns into an essential undertaking in PC vision applications. As the user is not totally coordinating with the camera, it is not necessary that the face captured in the video sequence is the frontal face. At times, it need not be a human face. Hence, it is necessary to detect the human face region in a frame. If a human face is detected in a video sequence, there are chances that the detected face can be masked. It is also possible that the faces can be captured in various poses. There is also a difficulty in identifying a face subjected to various illuminations. The above natural possibility of not capturing the frontal face of a human in a frame makes the identification task difficult. This problem prompts researchers working under face recognition technology to design an improved framework that increases the recognition rate in the above situations. From the above-mentioned possibilities that deteriorate the recognition rate of a face, in this thesis work, two major problems namely face with varying pose and partially occluded faces are considered for recognition from a captured video. -
A Reflection on the Current Status of Animal-Assisted Therapy in India
The field of animal-assisted therapy is advancing quickly throughout the world gaining popularity as a complementary therapy. Several countries, especially in the East, are still in their nascent phase in utilizing animal-assisted therapy and a more realistic presentation of their status should drive them towards effective initiatives to promote the field. The primary objective of this paper is to throw light on the current scenario of animal-assisted therapy in India. The relevant databases such as Scopus, Google Scholar, Proquest, PubMed, and JSTOR were searched to identify the research literature. The organizational websites, news, and blog articles, as well as institutional repositories, were explored to maximize the evidence. A total of 24 articles were found which included published research articles as well as unpublished conference papers. Results found a dearth of practice and research throughout the country indicating an urgent need to direct steps in promoting the growth of the field. The contemporary issues in the implementation of animal-assisted therapy such as cultural and religious beliefs, lack of awareness, lack of practising organizations and therapists warrant immediate attention. Reducing the research and practice gap alongside focusing on creating awareness, changing public perception, introducing coursework in educational institutions, the publication of evidence-based research will help in the acceptance and growth of this novel therapeutic field. 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques
Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning. 2021 IEEE.