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Entropy generation and heat transport analysis of Casson fluid flow with viscous and Joule heating in an inclined porous microchannel
The combined effects of the magnetic field, suction/injection, and convective boundary condition on heat transfer and entropy generation in an electrically conducting Casson fluid flow through an inclined porous microchannel are scrutinized. The temperature-dependent heat source is also accounted. Numerical simulation for the modelled problem is presented via RungeKuttaFelhberg-based shooting technique. Special attention is given to analyze the impact of involved parameters on the profiles of velocity (u(?)), temperature (?(?)), entropy generation (Ns), and Bejan number (Be.) It is established that entropy generation rate decreases at the walls with an increase in Hartmann number (M), while it increases at the center region of the microchannel. IMechE 2019. -
Probing the formation of megaparsec-scale giant radio galaxies: I. Dynamical insights from magnetohydrodynamic simulations
Context. Constituting a relatively small fraction of the extended-jetted population, giant radio galaxies (GRGs) form in a wide range of jet and environment configurations. This observed diversity complicates the identification of the growth factors that facilitate their attainment of megaparsec scales. Aims. This study aims to numerically investigate the hypothesized formation mechanisms of GRGs extending ?1 Mpc in order to assess their general applicability. Methods. We employed tri-axial ambient medium settings to generate varying levels of jet frustration and simulated jets with a low and a high power from different locations in the environment. This approach formulated five representations evolving under a relativistic magnetohydrodynamic framework. Results. The emergence of distinct giant phases in all five simulated scenarios suggests that GRGs may be more common than previously believed. This prediction can be verified with contemporary and forthcoming radio telescopes. We find that different combinations of jet morphology, power, and evolutionary age of the formed structure hold the potential to elucidate different formation scenarios. In all of these cases, the lobes are overpressured, prompting further investigation into pressure profiles when jet activity ceases, potentially distinguishing between relic and active GRGs. We observed a potential phase transition in GRGs marked by differences in lobe expansion speed and pressure variations compared to their smaller evolutionary phases. This suggests the need for further investigation across a broader parameter space to determine if lobe evolution in GRGs fundamentally differs from smaller radio galaxies. The axial ratio analysis reveals self-similar expansion in rapidly propagating jets, while there is a notable deviation when the jet forms wider lobes. Overall, this study emphasizes that multiple growth factors simultaneously at work can better elucidate the current-day population of GRGs, including scenarios such as the growth of GRGs in dense environments, GRGs extending several megaparsecs, development of GRGs in low-powered jets, and the formation of morphologies such as GRG-XRGs. The Authors 2025. -
Automated and Interpretable Fake News Detection With Explainable Artificial Intelligence
Fake news is a piece of misleading or forged information that affects society, business, governments, etc., hence is an imperative issue. The solution presented here to detect fake news involves purely using rigorous machine learning approaches in implementing a hybrid of simple yet accurate fake text detection models and fake image detection models to detect fake news. The solution considers the text and images of any news article, extracted using web scraping, where the text segment of a news article is analyzed using an ensemble model of the Nae Bayes, Random Forest, and Decision Tree classifier, which showed improved results than the individual models. The image segment of a news article is analyzed using only a Convolution Neural Network, which showed optimal accuracy similar to the text model. To better train the text models, data preprocessing and aggregation methods were used to combine various fake-real news datasets to have ample amounts of data. Similarly, the CASIA dataset was used to train the image model, over which Error Level Analysis was performed to detect fake images. model results are represented as confusion matrices and are measured using various performance metrics. Also, to explain predictions from the hybrid model, Explainable Artificial Intelligence is used. 2024 Taylor & Francis Group, LLC. -
Exploring the Psychosocial Challenges and Strengths of Indigent Adolescents: A Reflexive Thematic Analysis of Counsellors Insights
Background: The Bronfenbrenner bioecological model of human development provides a comprehensive framework for understanding the complex interactions between individual factors and environmental influences on adolescent mental health, such as limited access to resources, exposure to violence and trauma, and parental neglect. While discussing the challenges faced by at-risk adolescents, it is important to focus on the strengths of resilient adolescents living in similar conditions. These individual differences are the precursors in determining their futures. Methods: The present study aimed to explore the psychosocial challenges and strengths of indigent adolescents. Eight counselors who had been working with indigent adolescents for at least three years in school or NGO settings were identified through a snowball sampling design and interviewed using a semi-structured interview schedule. Results: Reflexive thematic analysis of the interviews was done using Braun and Clarks protocol to identify themes. Challenges faced by indigent adolescents were a lack of parental supervision, vulnerability to cybercrime, emotional dysregulation, engagement in drug use, ambiguity in life aspirations and career goals, and societal mistrust and bias. The strengths identified were empathy, reconciliation dynamics and forgiveness, a yearning for change, a love of learning, help-seeking and help-providing behavior, attachment to religion and festivals, and a sense of gratitude and hopefulness, which indigent resilient adolescents display to navigate through their challenging lives. A detailed discussion of these challenges and strengths, along with their various dynamics, has also been provided. Conclusion: Identifying both the difficulties and strengths of indigent adolescents would promote more strength-based approaches to preventive and promotive mental health programs. 2024 The Author(s). -
Evaluating the role of soil EPS in modifying the toxicity potential of the mixture of polystyrene nanoplastics and xenoestrogen, Bisphenol A (BPA) in Allium cepa L.
The coexistence of emerging pollutants like nanoplastics and xenoestrogen chemicals such as Bisphenol A (BPA) raises significant environmental concerns. While the individual impacts of BPA and polystyrene nanoplastics (PSNPs) on plants have been studied, their combined effects are not well understood. This study examines the interactions between eco-corona formation, physicochemical properties, and cyto-genotoxic effects of PSNPs and BPA on onion (Allium cepa) root tip cells. Eco-corona formation was induced by exposing BPA-PSNP mixtures to soil extracellular polymeric substances (EPS), and changes were analyzed using 3D-EEM, TEM, FTIR, hydrodynamic diameter, and contact angle measurements. Onion roots were treated with BPA (2.5, 5, and 10 mgL-1) combined with plain, aminated, and carboxylated PSNPs (100 mgL-1), with and without EPS interaction. Toxicity was assessed via cell viability, oxidative stress markers (superoxide radical, total ROS, hydroxyl radical), lipid peroxidation, SOD and catalase activity, mitotic index, and chromosomal abnormalities. BPA alone increased cytotoxic and genotoxic parameters in a dose-dependent manner. BPA with aminated PSNPs exhibited the highest toxicity among the pristine mixtures, revealing increased chromosomal abnormalities, oxidative stress, and cell mortality with rising BPA concentrations. In-silico experiments demonstrated the relationship between superoxide dismutase (SOD), catalase enzymes, PSNPs, BPA, and their mixtures. EPS adsorption notably reduced cyto-genotoxic effects, lipid peroxidation, and ROS levels, mitigating the toxicity of BPA-PSNP mixtures. 2024 Elsevier B.V. -
Mayfly Algorithm for Optimal Integration of Hybrid Photovoltaic / Battery Energy Storage / D-STATCOM System for Islanding Operation
In today's power system design studies, autonomous and self-healing capabilities are becoming increasingly important. Renewable energy (RE) integration, on the other hand, is geared at long-term sustainability. In this regard, a hybrid energy system consisting of a photovoltaic (PV) source, battery energy storage (BESS), and distribution-static synchronous compensator (D-STATCOM) is proposed for optimal design and integration in the electrical distribution network (EDN) when short-term islanding operational requirements are taken into account. When considering grid-connected mode, the PV system is initially optimally allocated towards loss minimization. Following that, the capacities of BESS and D-STATCOM are assessed in the context of a short-term islanding scenario. The optimization problem is tackled utilising a recent meta-heuristic mayfly optimization algorithm (MOA) in both stages. The simulations are run on an IEEE 33-bus EDN network. By having optimal PV system in grid-connected mode, it is observed that real power losses are reduced to 111.03 kW from 210.998 kW and reactive power losses are reduced to 81.684 kVAr from 143.033 kVAr. In addition, the minimum voltage in the network is raised to 0.9424 p.u. from 0.9038 p.u. On the other hand, by designing hybrid energy systems using PV, BESS, and D-STATCOM, the network is able to serve the entire load even under islanding conditions. MOA's competitiveness in solving difficult non-linear multivariable optimization problems was demonstrated in comparative research with literature publications. In addition, the proposed hybrid energy system can cope with the uncertainties and other requirements of current grids. 2022. All Rights Reserved. -
Spectral and temporal features of GX 13+1 as revealed by AstroSat
GX 13+1, a neutron star low-mass X-ray binary that exhibits the properties of both atoll and Z sources, is studied using data from Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) onboard AstroSat. The source traces a ? shaped track in its hardness-intensity diagram (HID). Spectral modelling of the data in the 0.7-30.0 keV energy range, with the model-+, yields orbital inclination angle (?) of 77. Flux resolved spectral analysis reveals the ? shaped pattern in the plots of spectral parameters kTe, kTbb, and ? versus Fbol, closely resembling the pattern traced in LAXPC HID. This indicates changes in the spectral properties of the corona and the boundary layer/accretion disc. Assuming that the accretion disc truncates at the AlfvCrossed D sign n radius, the upper limit of the magnetic field strength (B) at the poles of neutron star in GX 13+1 is calculated to be 5.10 108 G (for kA = 1 and ? = 0.1), which is close to that of atoll sources. Furthermore, thickness of the boundary layer is estimated to be 5.70 km, which results in the neutron star radius value of 14.50 km. Quasi-periodic oscillations (QPOs) at 56 4 and 54 4 Hz are detected in Regions D and E of HID, respectively. The frequencies of these QPOs are similar to the characteristic frequency of horizontal branch oscillation and these do not exhibit a positive correlation with mass accretion rate. -
Mining the web data for classifying and predicting users' requests
Consumers are the most important asset of any organization. The commercial activity of an organization booms with the presence of a loyal customer who is visibly content with the product and services being offered. In a dynamic market, understanding variations in client?s behavior can help executives establish operative promotional campaigns. A good number of new consumers are frequently picked up by traders during promotions. Though, several of these engrossed consumers are one-time deal seekers, the promotions undeniably leave a positive impact on sales. It is crucial for traders to identify who can be converted to loyal consumer and then have them patronize products and services to reduce the promotion cost and increase the return on investments. This study integrates a classifier that allows prediction of the type of purchase that a customer would make, as well as the number of visits that he/she would make during a year. The proposed model also creates outlines of users and brands or items used by them. These outlines may not be useful only for this particular prediction task, but could also be used for other important tasks in e-commerce, such as client segmentation, product recommendation and client base growth for brands. Copyright 2018 Institute of Advanced Engineering and Science. All rights reserved. -
Toxic waste colonialism : A re-evaluation of global management of transboundary hazardous waste /
Journal On Environment Law Policy And Development, Vol.3, pp.85-119, ISSN: 2348-7046. -
Parental Psychological Distress of Missed Diagnosis of Down Syndrome at Antenatal Screening: A Rare, but Still Real Occurrence-A Case Report and Review of Literature
Introduction: Prenatal screening programs are important components for pregnant women care and are often linked with grief and shock based on gestational age or the diagnosis. Lower/no sensitivity is also associated with these screening programs leading to providing false-negative outputs. Case Presentation: Present work shows a case of missed antenatal diagnosis of Down syndrome and its persistant medical and psychological impact on the family members. We have also discussed the relevant economic and medical-legal issues related to the context and aimed to maintain an adequate awareness among healthcare to discuss properly these investigations (difference between screening and diagnostic testing), their possible outcome (chances of false results) and enabled the pregnant women/couple to take informed decision on early pregnancy. Conclusion: These programs are considered as routine clinical practice in many countries from last few years and are necessary to assess the pros and cons of these programs. One of the prime cons involves the likeliness of obtaining a false-negative result due to lack of 100% sensitivity and specificity. 2023 S. Karger AG, Basel. -
Quadratic convective transport of Cu-Al2O3 hybrid nanoliquid with Hall current, variable suction, and exponential heat source
The time-dependent slip flow and heat transport of the Cu-Al2O3 hybrid nanofluid through a vertical permeable plate with Hall current and variable suction is investigated. An exponential heat source and quadratic convection effects are considered. The dimensionless governing equations are solved analytically using the regular perturbation method. The graph of variation of the different flow fields with respect to the distance from the plate is drawn for the analysis. It is established that the exponential heat source aspect increased the temperature profile while the quadratic convection aspect decreased the temperature profile. The applied magnetic field and nonlinear convection aspects reduce the axial velocity field. The quadratic convection and exponential space-dependent heat source phenomena are favorable to friction factors. Furthermore, the global heat transfer is increased in the presence of an exponential space dependent heat source and hybrid nanoparticles. 2021 John Wiley & Sons, Ltd. -
QSPR Analysis On Octane Isomers Using Degree-Based Topological Indices?
Octane isomers are structures with the chemical formula C8H18. Despite having the same formula, they have variations in the way their atoms are arranged, leading to differences in their chemical and physical properties. In this paper, we conduct a QSPR analysis on various isomers of octane, focusing on specific degree-based topological indices. In QSPR studies, these measures, known as topological indices, are helpful in understanding and quantifying the biological effects of chemical compounds. We specifically look at how certain properties of octane, such as complexity, acentric factor, standard enthalpy of vaporization, entropy, and enthalpy of vaporization, are connected to these topological indices. Our research provides valuable insights into how these indices can predict the behavior of octane isomers, contributing to a better overall understanding of their properties. 2024, Tsing Hua University. All rights reserved. -
COMPUTATION OF b-CHROMATIC TOPOLOGICAL INDICES OF SOME GRAPHS AND ITS DERIVED GRAPHS
The two fastest-growing subfields of graph theory are graph coloring and topological indices. Graph coloring is assigning the colors/values to the edges/vertices or both. A proper coloring of the graph G is assigning colors/values to the vertices/edges or both so that no two adjacent vertices/edges share the same color/value. Recently, studies involving Chromatic Topological indices that dealt with different graph coloring were studied. In such studies, the vertex degrees get replaced with the colors, and the computation is carried out based on the topological index of our choice. We focus on b-Chromatic Zagreb indices and b-Chromatic irregularity indices in this work. This paper discusses the b-Chromatic Zagreb indices and b-Chromatic irregularity indices of the gear graph, star graph, and its derived graphs such as the line and middle graph. 2023, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
RAINBOW CHROMATIC TOPOLOGICAL INDICES OF CENTRAL GRAPHS OF SOME GRAPHS
The chromatic topological indices concept was introduced recently. Many other variations concerning the chromatic topological indices have been studied lately. In this paper, we have calculated the first and second rainbow chromatic Zagreb indices and rainbow chromatic irregularity indices for central graph of some standard graph classes. Palestine Polytechnic University-PPU 2024. -
Decision Tree Based Routing Protocol (DTRP) for Reliable Path in MANET
In mobile ad hoc network due to node movements, there exists route failure in active data transmission which results in data loss and communication overheads. Hence, in such a dynamic network, routing through reliable path is one of the tedious tasks. In this paper, we propose a novel Decision Tree based Routing Protocol (DTRP) a data mining technique in route selection process from source to destination. The proposed DTRP protocol selects the one hop neighbors based on the parameters such as speed, Link Expiration Time, trip_time and node life time. Thus the performance of a route discovery mechanism is enhanced by selecting the stable one-hop neighbors along the path to reach the destination. The simulated results show that the lifetime of the route is increased and hence the data loss and end to end delay are minimized thereby increasing the throughput of the network using the proposed DTRP routing protocol compared to existing routing protocols. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
IoT enabled lung cancer detection and routing algorithm using CBSOA-based ShCNN
The Internet of Things (IoT) has tremendously spread worldwide, and it influenced the world through easy connectivity, interoperability, and interconnectivity using IoT devices. Numerous techniques have been developed using IoT-enabled health care systems for cancer detection, but some limitations exist in transmitting the health data to the cloud. The limitations can be accomplished using the proposed chronological-based social optimization algorithm (CBSOA) that effectively transmits the patient's health data using IoT network, thereby detecting lung cancer in an effective way. Initially, nodes in the IoT network are simulated such that patient's health data are collected, and for transmission of such data, routing is performed in order to transmit the health data from source to destination through a gateway based on cloud service using CBSOA. The fitness is newly modeled by assuming the factors like energy, distance, trust, delay, and link quality. Finally, lung cancer detection is carried out at the destination point. At the destination point, the acquired input data is fed to preprocessing phase to make the data acceptable for further mechanism using data normalization. Once the feature selection is done using Canberra distance, then the lung cancer detection is performed using shepard convolutional neural network (ShCNN). The process of routing as well as training of ShCNN is performed using the CBSOA algorithm, which is devised by the inclusion of the chronological concept into the social optimization algorithm. The proposed approach has achieved a maximum accuracy of 0.940, maximum sensitivity of 0.941, maximum specificity of 0.928, and minimum energy of 0.452. 2022 John Wiley & Sons Ltd. -
Forecasting NIFTY 50 in Volatile Markets Using RNNLSTM: A Study on the Performance of Neural Network Models During the COVID-19 Pandemic
The COVID-19 pandemic has shown us how the market can be highly uncertain and volatile at certain times. This brings a new level of challenges to all the investors and active traders in the market, as they have not seen such a movement in the past. However, as technology is evolving, highly sophisticated tools and techniques are being used by hedge funds and other investment banks to track down these movements and turn this into an opportunity. In this paper, we try to analyse how recurrent neural network (RNN) with long- and short-term memory architecture performs under volatile market conditions. For this study, we tried to perform a comparative analysis between two models within two successive time periods, where one is trained in a volatile market condition and the other in a relatively low volatile market condition. The results showed that the RNN model is less accurate in predicting the prices in a volatile market compared to a relatively low volatile market. We also compared these two models to a separate model where we trained using the combined data from the two successive time periods. Even though the addition in data points for the neural network produced a better result compared to the model trained under volatile conditions, it did not significantly perform better than the model, which was trained in the low volatile period. 2022 Management Development Institute. -
Smartphone based indoor localization and tracking model using bat algorithm and Kalman filter
In recent days, accurate localization becomes essential for enabling smartphone-based navigation to attain maximum accuracy in the construction of the real world.Fingerprint-based localization is the widespread solution to achieve and assure effective performance. In this study, a new fingerprint-based localization model using a bat algorithm (BA) is presented stimulated by the echolocation nature of microbats. The presented model adapts BA for estimating the location information. Initially, the presented model applies a Bayesian-rule based objective function. Then, the BA is used for improving the accuracy and analyzing the effects of the initial position of the bats on the localization outcome. For mitigating the estimation error, the Kalman filter is employed for updating the initially determined position using the BA for tracking purposes. The experimental analysis indicated an improvement in real-time performance and decrease in computation complexity. The presented model also obtained maximum localization accuracy with minimum localization error over the compared methods. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Understanding the antecedents of service decisions: An integration of service promiscuity and customer citizenship behaviour
Promiscuity being casual and unrestrained towards any kind of service, the purpose of this article is to contribute to service literature by investigating the influence of customer citizenship behaviour and service promiscuity in the decision-making process in the context of public house services. This paper empirically draws a historic sum-up on the roots of service promiscuity towards the decision-making process. A questionnaire was administered to 1,509 pub customers using retrospective experience sampling technique. The proposed hypotheses were tested using structural equation modelling. Results from this research yielded novel insights into the dual antecedents extending to customer decision making process through customer citizenship behaviour and service promiscuity. The findings have implications for the ongoing argumentation on the practicality of customer promiscuity, thereby broadening the theoretical understanding of 'why customers' decision-making process establishes such an efficacious effect in the service environment? Further, these new and interesting results enlighten the insights of consumer behaviour and more importantly contribute substantially to the existing knowledge of service marketing literature. The results provide managers with specific decision-making process variables and substantial service strategies. 2019 Inderscience Enterprises Ltd. -
An analysis of policy prospective of taxi aggregators and consumers in digital eco-system
The term digital trade is becoming more prevalent in the modern era. Newer company structures have evolved to replace traditional methods with online companies as digitalisation has become the standard. Taxi aggregators are one of the most prevalent digital business concepts. With this particular model, which is now known as taxi aggregators, you may quickly book a cab using your smartphone for transportation inside and outside the city limits. They are also inexpensive to use. Nevertheless, as lawmakers created new and revised rules to control these business models, the last two years have been very difficult for application-based taxi providers like Ola and Uber. The regulations are being developed by legislators in several nations, but the pace and the scope are much slower than necessary. This essay will examine past and present taxi market scenarios before suggesting ways to enhance them in the future. Copyright 2024 Inderscience Enterprises Ltd.