Browse Items (16488 total)
Sort by:
-
Controlling RayleighBard Magnetoconvection in Newtonian Nanoliquids by Rotational, Gravitational and Temperature Modulations: A Comparative Study
The effect of three different types of time periodic modulations on the RayleighBard magnetic system involving Newtonian nanoliquids is studied. Multiple-scale analysis (homogenization method) is used to arrive at the GinzburgLandau equation. The curiosity in the work is to know the individual effects of (1) rotation, (2) gravity and (3) temperature modulations on RayleighBard magnetoconvection in weakly electrically conducting Newtonian nanoliquids. A significant effort in this research is devoted toward linear and nonlinear stability analyses as well as the homogenization method which leads to the GinzburgLandau evolution equation. Although several studies have concluded similar results for nanoliquids compared with those of pure base fluids, many fundamental issues like the choice of phenomenological models for the thermo-physical properties and the best type of nanoparticles are not well understood. This research focuses on several important issues involving mathematical and computational problems arising in heat transfer analysis in the presence of nanoliquids. Effects of various nanoliquid parameters, frequency and amplitude of modulation on heat transport are analyzed. This investigation focuses on five nanoliquids, with water as a carrier liquid and five nanoparticles, viz. copper, copper oxide, silver, alumina and titania. Enhanced heat transport was observed for rotation, gravity and temperature modulations. In the case of rotation modulation, it is found that increase in the amplitude of modulation results in a decrease in the critical Rayleigh number and thereby to an increase in the mean Nusselt number. The increase in the amplitude of the gravity modulation is shown to enhance the heat transport, whereas increase in frequency is to inhibit the heat transport. Two types of temperature modulations are considered, viz. in-phase (synchronous) and out-of-phase (asynchronous) temperature modulations with the assumption that the boundary temperatures vary sinusoidally with time. The amplitudes of modulation are considered to be very small. In the case of in-phase modulation, there is no significant difference between the heat transports in the presence and in the absence of temperature modulation. On this reason, out-of-phase temperature modulation is used to either enhance or diminish heat transport by suitably adjusting the frequency and phase difference of the modulated temperature. The effect of magnetic field, in all three cases of modulations, is to inhibit the onset of convection and thereby diminish the heat transport. 2022, King Fahd University of Petroleum & Minerals. -
Fluorescent imidazole derived sensor for selective in vitro and in vivo Fe2+ detection and bioimaging in zebrafish with DFT studies
Herein, we have developed imidazole derivatized fluorescent probes IM-1 and IM-2 for extremely selective detection of Fe2+ with rapid response (LOD: 3.245 ?M for IM-1 and 0.297 ?M for IM-2) and excellent binding constants (0.214 105 M?1 and 1.004 105 M?1). Aqueous ethanol system was employed to assess the sensing potency of the probes both in vitro and in vivo in zebrafish is the main highlight of this work. The synthesized fluorophores possess admirable quantum yields of 0.61 and 0.78. The 1:1 binding mechanism of ligands with Fe2+ ions is supported by Job's plot and ESI-Mass spectrum. The synthesized probes demonstrated limited cytotoxicity both in vitro (MDA-MB-231 cells) and in vivo (zebrafish, Danio Rerio) studies. These results prompted us to employ the probes IM-1 and IM-2 to trace out intra cellular Fe2+ ions in zebrafish embryos. 2024 Elsevier B.V. -
Significance of Suffering: A Neuroscience Perspective
Pain and suffering are inevitable realities of life. Not only do humans suffer from physical pain but animals too. Recently, the advent of the covid-19 pandemic has led to a global rise in suffering. The significance of physical pain and the emotional dimension of pain is long understood. Here we are trying to understand the significance of suffering pathway in the human brain. The recent advancement in neuroscience related to insights into pain perception, mirror neuron networks, suffering and compassion has created an appeal to revisit the pain and suffering from a contemporary neuroscience perspective. This article analyzes the benefits of suffering from an evolutionary and neuroscientific approach. Suffering affects people differently as some may become more compassionate and/or resilient while others develop depression. Here we are attempting to explain the underlying neural circuitry involved in suffering, empathy and compassion and to point out the interconnectedness among them. Subsequently, the article proposes a neuroscientific perspective to manage the emotional overdrive associated with suffering. 2025, Imprint Academic. All rights reserved. -
Psychoneuroimmunology of yoga and meditation
Yoga and meditation were integral to Ayurveda and were prevalent from 1500 BC to 400 AD. The psychoneuroimmunology of yoga and meditation has been of interest in recent times, and much research is focused on the influence of meditation and yoga on cell telomerase activity, neuroendocrine system, cells of the immune system, oxidative stress, cell aging, and cancer recovery. Yoga and meditation reduce stress and depression and improve sleep quality. Stress-immune relationship influences all age groups, especially individuals with clinical diagnoses, and is a factor in lifestyle diseases and cancer. Elevated levels of oxytocin, serotonin, and dopamine were associated with bliss and positivity, which contribute to the reduction in inflammation and pain perception among practitioners. The present chapter focuses on the psychoneuroimmunology of the effects of yoga and meditation on improving immunity and fast and efficient recovery. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Footloose Culture: Migrant Workers and Cultural Meanings of Labour
[No abstract available] -
Jet-driven AGN feedback on molecular gas and low star-formation efficiency in a massive local spiral galaxy with a bright X-ray halo
It has long been suspected that powerful radio sources may lower the efficiency with which stars form from the molecular gas in their host galaxy, however so far, alternative mechanisms, in particular related to the stellar mass distribution in the massive bulges of their host galaxies, have not been ruled out. We present new, arcsecond-resolution Atacama Large Millimeter Array (ALMA) CO(1-0) interferometry, which probes the spatially resolved, cold molecular gas in the nearby (z=0.08), massive (Mstellar= 4 1011 M?), isolated, late-type spiral galaxy 2MASSX J23453269-044925, which is outstanding for having two pairs of powerful, giant radio jets, and a bright X-ray halo of hot circumgalactic gas. The molecular gas is in a massive (Mgas=2.0 1010 M?), 24 kpc wide, rapidly rotating ring, which is associated with the inner stellar disk. Broad (FWHM=70-180 km s-1) emission lines with complex profiles associated with the radio source are seen over large regions in the ring, indicating gas velocities that are high enough to keep the otherwise marginally Toomre-stable gas from fragmenting into gravitationally bound, star-forming clouds. About 1-2% of the jet kinetic energy is required to power these motions. Resolved star-formation rate surface densities derived from Galaxy Evolution Explorer and Wide-Field Infrared Survey Explorer fall by factors of 30-70 short of expectations from the standard Kennicutt-Schmidt law of star-forming galaxies, and near gas-rich early-type galaxies with signatures of star formation that are lowered by jet feedback. We argue that radio Active Galactic Nucleus (AGN) feedback is the only plausible mechanism to explain the low star-formation rates in this galaxy. Previous authors have already noted that the X-ray halo of J2345-0449 implies a baryon fraction that is close to the cosmic average, which is very high for a galaxy. We contrast this finding with other, equally massive, and equally baryon-rich spiral galaxies without prominent radio sources. Most of the baryons in these galaxies are in stars, not in the halos. We also discuss the implications of our results for our general understanding of AGN feedback in massive galaxies. N. P. H. Nesvadba et al. 2021. -
Blockchain enabled energy efficient red deer algorithm based clustering protocol for pervasive wireless sensor networks
Energy efficiency and security are considered as important issues in the design of pervasive wireless networks. Since the nodes in pervasive wireless networks are battery-operated, it becomes essential to develop an energy-efficient method to minimize energy consumption and prolong the network lifetime. This paper presents new energy-efficient and secure clustering based data transmission in pervasive wireless networks using red deer algorithm (RDA) based clustering technique with blockchain enabled secured data transmission, named as RDAC-BC. The proposed RDAC-BC technique undergoes node initialization and performs the clustering process using the RDAC technique. The clustering technique performs cluster head (CH) selection and cluster construction process is carried out. Once the CHs are chosen, blockchain enabled secure data transmission takes place among cluster members (CMs) as well as CHs. The application of RDAC and blockchain technology helps to achieve energy efficiency and security. The experimental validation of the RDAC-BC technique is assessed under several aspects and the results are compared with existing methods. The obtained results ensured that the RDAC-BC technique has shown superior results interms of energy, network lifetime, packet delivery ratio (PDR), and throughput. 2020 Elsevier Inc. -
Engine behavior analysis on a conventional diesel engine combustion mode powered by low viscous cedarwood oil/waste cooking oil biodiesel/diesel fuel mixture An experimental study
Binary biofuel is the best alternative source that completely replaces petroleum-based fuel. In this study, we have experimented with the waste cooking oil and cedarwood oil as biofuel in a DI CI engine for various proportions and related its combustion, emission, and performance characteristics to those of base diesel. This study aims to eliminate the utilization of fossil fuel in a diesel engine by introducing green binary fuel (low viscous fuel resulting from the blending of cedarwood oil with WCO biodiesel) successfully. The objective of the study is to convert cedarwood WCO into green binary fuel and investigate its performance, emission, and combustion properties. The transesterification process is utilized for the enhancement of WCO as biodiesel. It occasioned a reduction in brake thermal efficiency as the addition of waste cooking oil in the blend increased. At the same time, the maximum value of BTE of 27.8% was attained for B10C90 (10% transesterified waste cooking oil and 90% cedarwood oil in volume), whereas it was 28.1% for diesel at maximum load conditions. The BSEC was 15.4 MJ/kW-hr for B10C90 and 12.8 MJ/kWhr for diesel. The emission characteristics, CO, HC, NOx, CO2, and smoke for B10C90 were 17.93 g/kWhr, 0.55 g/kWhr., 20.09 g/kWhr, 2210.9 g/kWhr, and 25.55%. Combustion features such as NHRR, burn duration, MPRR, combustion efficiency, Ignition delay, and coefficient of variance for B10C90 were 53.74 bar, 29.38 CAD, 4.71 bar/CAD, 99.7%, 7.01 CAD, and 4.73% respectively. It showed that B10C90 had comparable performance (BTE) and combustion values to mineral diesel with better emission characteristics. 2024 The Institution of Chemical Engineers -
A catechism of pentecostal schisms and the efficacy of management in the stabilization of the church in zimbabwe
The Pentecostal church in Zimbabwe has of late experienced a rude awakening with the mushrooming of these incessant schisms which threaten the unity of purpose that should prevail in a religious set up. The current newlineincrease in schisms is of great concern to the Christian community. Are such schisms embedded in its original design, or are there other factors at play. The problem necessitated the commissioning of this study in order to explore the schism scourge with view to arresting it and bring stability to the splintering Pentecostal church. The conceptualization of the study began by identifying six hypothetical perspectives as the root hypothetical causes of church schisms, i.e., doctrinal, controversial relationship, secularization, institutionalism, leadership and management perspectives. Theoretical frameworks in the newlineexisting literature were reviewed to establish knowledge gaps that informed the newlinestudy approach. Using focus group discussion, document analysis, survey questionnaires, and interviews, the study sought causal and remedial validation on the problem at hand. To unveil the intricacies of the problem, an explorative mixed study framework was preferred. In order to generate a desired rich understanding and interpretation of schisms, a more qualitative catechism inquiry based on a combined ethno-methodology and hermeneutics paradigm was adopted. The study proposition was that church schisms are a result of management challenges in the Pentecostal church. The theoretical frame of the study was therefore modeled to explore newlinehow management protocols could be harnessed to induce real growth and stability. The Pentecostal church is renowned for shunning management, considering it secular and hence worldly. On one hand, the church is the most newlinecomplex institution, multifaceted and with multi-bottom lines, yet on the other hand, management is all about dealing with such complexities. -
-
Explainable AI for Diabetic Retinopathy Screening: Enhancing Clinician Trust in Deep Learning Predictions
Diabetic retinopathy (DR) remains a leading cause of preventable blindness worldwide, with early detection being critical for effective intervention. While deep learning models have demonstrated exceptional performance in automated DR screening, their black box nature has limited clinical adoption due to concerns about interpretability and trust. This paper presents a comprehensive explainable AI (XAI) framework that integrates multiple visualization techniques, including Gradient-weighted Class Activation Mapping (Grad-CAM), attention mechanisms, and feature attribution methods, to provide clinically meaningful explanations for DR predictions. We evaluate our approach on the publicly available EyePACS and Messidor-2 datasets, achieving 94.3% accuracy while generating interpretable heatmaps that highlight lesion-specific regions. A clinical validation study involving 15 ophthalmologists demonstrates that our XAI-augmented system increases diagnostic confidence by 23% and reduces review time by 31% compared to non-explainable models. Our findings suggest that transparent AI systems can effectively bridge the gap between algorithmic performance and clinical trust, paving the way for broader adoption of AI-assisted DR screening in healthcare settings. 2026 IEEE. -
Tailoring natural rubber properties through CaO nanoparticle integration and curing technique
The present study investigates the development of natural rubber nanocomposites reinforced with calcium oxide nanoparticles and cured using pentane-1,5-diylidenediamine, a green crosslinker derived from glutaraldehyde and ammonia. calcium oxide nanoparticles (0.020.16wt%) were incorporated via latex blending, and composites were evaluated in both uncured and pentane-1,5-diylidenediamine -cured forms. Fourier-transform infrared spectroscopy confirmed that the calcium oxide nanoparticles were well dispersed and actively involved in crosslinking with the rubber matrix. Scanning electron microscopy showed that the cured composites had a more uniform surface and better distribution of nanoparticles. Mechanical testing revealed a remarkable tenfold increase in tensile strength from 0.217MPa to 8.478MPa and a significant improvement in elongation at break, rising from 666 to 1317% in the pentane-1,5-diylidenediamine -cured samples. The best mechanical performance was achieved at 0.10wt% calcium oxide. Dielectric measurements further highlighted an increase in permittivity and AC conductivity, especially in the cured composites, attributed to interfacial polarization and the formation of nanoparticle networks. Altogether, these results underline the synergistic benefits of calcium oxide nanoparticles and pentane-1,5-diylidenediamine curing in enhancing the structural, mechanical, and dielectric properties of natural rubber, making it a strong candidate for advanced elastomeric and dielectric applications. The Author(s), under exclusive licence to the Institute of Chemistry, Slovak Academy of Sciences 2026. -
Properties, Synthesis and Emerging Applications of Graphdiyne: A Journey Through Recent Advancements
Graphdiyne (GDY) is a new variant of nano-carbon material with excellent chemical, physical and electronic properties. It has attracted wide attention from researchers and industrialists for its extensive role in the fields of optics, electronics, bio-medics and energy. The unique arrangement of spsp2 carbon atoms, linear acetylenic linkages, uniform pores and highly conjugated structure offer numerous potentials for further exploration of GDY materials. However, since the material is at its infancy, not much understanding is available regarding its properties, growth mechanism and future applications. Therefore, in this review, readers are guided through a brief discussion on GDYs properties, different synthesis procedures with a special focus on surface functionalization and a list of applications for GDY. The review also critically analyses the advantages and disadvantages of each synthesis route and emphasizes the future scope of the material. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Spectroscopic study of Herbig Ae/Be stars in the Galactic anti-centre region from LAMOST DR5
We study a sample of 119 Herbig Ae/Be stars in the Galactic anti-centre direction using the spectroscopic data from large sky area multi-object fiber spectroscopic telescope survey program. Emission lines of hydrogen belonging to the Balmer and Paschen series, and metallic lines of species such as Fe ii, O i, Ca ii triplet are identified. A moderate correlation is observed between the emission strengths of H? and Fe ii 5169 suggesting a possible common emission region for Fe ii lines and one of the components of H?. We explored a technique for the extinction correction of the HAeBe stars using diffuse interstellar bands present in the spectrum. We estimated the stellar parameters such as age and mass of these HAeBe stars, which are found to be in the range 0.1-10 Myr and 1.5-10 M, respectively. We found that the mass accretion rate of the HAeBe stars in the Galactic anti-centre direction follows the relation ?acc ? M?3.12-0.34+0.21, which is similar to the relation derived for HAeBe stars in other regions of the Galaxy. The mass accretion rate of HAeBe stars is found to have a functional form of ?acc ? t-1.10.02 with age, in agreement with previous studies. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Estimation of stellar parameters and mass accretion rate of classical TTauri stars from LAMOST DR6
Classical T Tauri stars (TTS) are low-mass pre-main sequence stars with an active circumstellar environment. In this work, we present the identification and study of 260 classical TTS using LAMOST Data Release 6, among which 104 stars are newly identified. We distinguish classical TTS from giants and main-sequence dwarfs based on the log g values, and the presence of H ? emission line and infrared excess that arises from the circumstellar accretion disk. We estimated the mass and age of 210 stars using the Gaia colormagnitude diagram. The age is from 0.1 to 20 Myr, where 90% of the stars have age <10 Myr and the mass ranges between 0.11 and 1.9 M? . From the measured H ? equivalent widths, we homogeneously estimated the mass accretion rates for 172 stars, with most values ranging from 10 - 7 to 10 - 10M? yr - 1 . The mass accretion rates are found to follow a power law distribution with the mass of the star, having a relation of the form M?acc?M?1.430.26 , in agreement with previous studies. 2023, Indian Academy of Sciences. -
Green synthesis of silver nanoparticles using calendula officinalis and its anti-bacterial studies /
Mapana Journal of Sciences, Vol.17, Issue 2, pp.11-17, ISSN No: 0975-3303. -
-
Artificial Intelligence Based Computational Framework for Identification and Classification of Interstitial Lung Diseases Using HRCT Images
Interstitial Lung Diseases (ILDs) refer to a wide array of respiratory disorders characterised via infection and scarring of the lung's interstitial tissue. These conditions affect the space within the air sacs, compromising the lungs' ability to expand and contract properly. ILDs manifest with a range of symptoms, including persistent cough, shortness of breath, and fatigue. Diagnosis of ILDs often involves imaging methods, mainly High-Resolution Computed Tomography (HRCT), to assess lung abnormalities. ILDs can have lasting effects on respiratory function, leading to progressive fibrosis. The primary obstacle in identifying ILDs lies in the diverse array of symptoms they present, making it challenging to distinguish them from other pulmonary disorders. The HRCT is a commonly employed method in ILD diagnosis. These images provide a detailed depiction of lung tissue, revealing its size, shape, and any notable abnormalities or changes. Moreover, HRCT plays a crucial role in monitoring disease progression over time. Deep Learning (DL) excels in detecting patterns in intricate medical images that may pose challenges for traditional methods. Moreover, DL algorithms exhibit the ability to identify subtle changes in medical images indicative of pathology, and they can automate object detection tasks. The application of DL in medical contexts can enrich the precision and rapidity of diagnoses. In this research aimed at improving the accuracy of artificial intelligence AI-based ILD identification, we harnessed the benefits of deep learning, employing full-training, Transfer Learning (TL), and ensemble voting techniques. Our approach involved the construction of three Convolutional Neural Networks (CNNs) from scratch for ILD detection. Additionally, we customized models named InceptionV3, VGG16, MobileNetV2, VGG19, and ResNet50 for both full-training and TL strategies. This comprehensive methodology aimed to take benefits of DL architectures to enhance the precision of ILD identification in medical imaging. Both the first dataset consisting of HRCT images and the second dataset comprising Chest X-ray were employed in our study. However, during the initial training phase of the TL models, we utilized pre-trained ImageNet weights. To enhance performance, modifications were made to the classification layers of all five models for both TL and full-training processes. To further improve training outcomes, a soft-voting ensemble approach was employed. The ensemble, combining the predictions of all three newly developed CNN models (ILDNetV1, ILDNetV2 and ILDNetV3), and ILDNetV1 achieved the highest test accuracy at 98.14%. Additionally, we incorporated machine learning (ML) models, including Logistic Regression, BayesNet, RandomForest, Multilayer Perceptron (MLP), and J48, using statistical measurements derived from HRCT images. Our study introduces a novel AI-based system for predicting ILD categories. This system demonstrated superior performance on unseen data by leveraging the results from the newly constructed CNNs, transfer learning, and ML models. This comprehensive approach holds promise for advancing ILD category prediction, providing a more robust and accurate tool for medical diagnosis and decision- making. -
The Impact of Virtuous Organizational Practices on Flow at Work Among Kitchen Employees in Bengaluru
Chefs arent mere cooks; they are culinary artisans who create art in the form of dishes. Flow among kitchen employees enhances creativity, focus, and efficiency where he flourishes at his work. This study on kitchen employees in Bengaluru aims to analyze the organizational practices that have impacted the state of flow and led to employee well-being. A quantitative method was adopted to collect data from the samples. The sample includes kitchen employees at all levels of management and operation from various hotels and stand-alone restaurants. The implications of the findings are discussed in terms of how virtuous practices in the organization lead to the state of immersion. The studys findings contribute to the overall efficiency of human resource management in chefs mainly focusing on employee well-being, performance, and creativity. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.