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Radiation effects on 3D rotating flow of Cu-water nanoliquid with viscous heating and prescribed heat flux using modified Buongiorno model
In this article, the three-dimensional (3D) flow and heat transport of viscous dissipating Cu-H2O nanoliquid over an elongated plate in a rotating frame of reference is studied by considering the modified Buongiorno model. The mechanisms of haphazard motion and thermo-migration of nanoparticles along with effective nanoliquid properties are comprised in the modified Buongiorno model (MBM). The Rosseland radiative heat flux and prescribed heat flux at the boundary are accounted. The governing nonlinear problem subjected to Prandtls boundary layer approximation is solved numerically. The consequence of dimensionless parameters on the velocities, temperature, and nanoparticles volume fraction profiles is analyzed via graphical representations. The temperature of the base liquid is improved significantly owing to the existence of copper nanoparticles in it. The phenomenon of rotation improves the structure of the thermal boundary layer, while, the momentum layer thickness gets reduced. The thermal layer structure gets enhanced due to the Brownian movement and thermo-migration of nanoparticles. Moreover, it is shown that temperature enhances owing to the presence of thermal radiation. In addition, it is revealed that the haphazard motion of nanoparticles decays the nanoparticle volume fraction layer thickness. Also, the skin friction coefficients found to have a similar trend for larger values of rotation parameter. Furthermore, the results of the single-phase nanoliquid model are limiting the case of this study. 2021, The Author(s). -
Sonochemical assisted impregnation of Bi2WO6 on TiO2 nanorod to form Z-scheme heterojunction for enhanced photocatalytic H2 production
In this work, Bi2WO6/TiO2 nanorod heterojunction was prepared by sonochemical assisted impregnation method. After loading 2 wt% Bi2WO6 on TiO2 nanorods, the photocatalytic hydrogen production rate of 2026 mol/h/g was achieved. Compared to commercial P25 and TiO2 nanorods, ?13 and ?3 folds enhanced activity was observed. The excellent photocatalytic performance of Bi2WO6/TiO2 nanorod photocatalyst was mainly attributed to i) reduction of bandgap due to heterojunction formation, ii) quick transport of photogenerated charge carriers, and iii) efficient charge carrier separation supported by UV-DRS, photocurrent measurement, Impedance study, and photoluminescence spectra analysis. The Z-scheme band alignment for Bi2WO6/TiO2 nanorod heterojunction was proposed based on the Mott-Schottky measurement. This result demonstrated the effective utilization of Z-scheme heterojunction of Bi2WO6/TiO2 for photocatalytic reduction application. 2021 The Society of Powder Technology Japan -
Bioconversion of Feather Composts using Proteolytic Bacillus mycoides for their Possible Application as Biofertilizer in Agriculture
Proteolytic Bacillus strains were screened for highest protease production amongst which Bacillus mycoides (G2) was chosen as an assuring protease producer. Enzyme activity was maximum at 37C, pH-7, when the medium was supplemented with 0.5 and 0.75% of sucrose and beef extract respectively. Tapioca flour and soybean meal were capable of replacing commercial carbon and nitrogen sources respectively. Feather degradation studies revealed 62% of degradation with Quail feather (QF), followed by Chicken feather (CF) (58%), Guinea fowl feather (51%) and Pigeon feather (43%). Biodegradation of feather samples in soil evidenced degradation of Quail feather and Chicken feather at the following patternQF Treatment 1 (5%) ? CF Treatment 1 (5%) ? QF Treatment 2 (10%) ? CF Treatment 2 (10%). Maximum degradation of QF and sufficient release of free amino acids into the feather compost was obvious with Field Emission Scanning Electron Microscopic (FE-SEM) and High Performance Thin Layer Chromatographic (HPTLC) analyses respectively. In vitro plant growth studies of tomato and chilly plants were accomplished with feather composts. Maximum growth of 26.44cm (shoot length) was achieved when feather compost prepared with degraded QF (5%) was utilized as plant growth substrate, than other treatment pots (P < 0.05). Plant growth was exemplary in the case of tomato when compared to that of chilly. Sound degradation of QF, followed by CF using Bacillus mycoides could strengthen the efficacy of microbial fermentation processes. This significant attempt could support poultry farms as well as organic agricultural sectors ecologically. Graphic Abstract: [Figure not available: see fulltext.] 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Training multi-layer perceptron with enhanced brain storm optimization metaheuristics
In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing gradient issue. As an alternative approach, stochastic optimization algorithms, such as nature-inspired metaheuristics are more reliable for complex optimization tax, such as finding the proper values of weights and biases for neural network training. In this work, we propose an enhanced brain storm optimization-based algorithm for training neural networks. In the simulations, ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization algorithm. The results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-the-art approaches on the majority of datasets in terms of classification accuracy and convergence speed, due to the capability of balancing the intensification and diversification and avoiding the local minima. The proposed approach obtained the best accuracy on eight out of ten observed dataset, outperforming all other algorithms by 1-2% on average. When mean accuracy is observed, the proposed algorithm dominated on nine out of ten datasets. 2022 Tech Science Press. All rights reserved. -
Tailoring the properties of tin dioxide thin films by spray pyrolysis technique
Nanostructured transparent conducting SnO2 thin films have been grown on glass substrates via an environmentally benign chemical route viz spray pyrolysis. All samples were grown for various concentrations of precursor solution with the substrate kept at 350 C maintaining a spray rate of 10 mL/min. The characterizations revealed orthorhombic crystal structure with preferential growth in (112) plane for all samples. Ellipsometric analysis confirmed the good quality of the films. The sample prepared at 0.2 M concentration of precursor solution showed average transmission of 60% in the visible region with maximum conductivity of 24.86 S/cm. As synthesized samples exhibited overall Photoluminescence (PL) emission colours of green, greenish white and bluish white depending on the intensities of excitonic and oxygen vacancy defect level emissions. 2021 Elsevier B.V. -
On (k) -coloring of generalized Petersen graphs
The chromatic number, ?(G) of a graph G is the minimum number of colors used in a proper coloring of G. In an improper coloring, an edge uv is bad if the colors assigned to the end vertices of the edge is the same. Now, if the available colors are less than that of the chromatic number of graph G, then coloring the graph with the available colors leads to bad edges in G. In this paper, we use the concept of (k)-coloring and determine the number of bad edges in generalized Petersen graph (P(n,t)). The number of bad edges which result from a (k)-coloring of G is denoted by bk(G). 2022 World Scientific Publishing Company. -
Sensitivity computation of nonlinear convective heat transfer in hybrid nanomaterial between two concentric cylinders with irregular heat sources
Heat exchangers, hot rolling, heat storage systems, and nuclear power plants utilize hybrid nanoliquid flow through an annulus for heat transport. The linear Boussinesq approximation is no longer suitable as these devices work at both moderate and extremely high temperatures. Hence, the salient features of quadratic convection on the hybrid nanoliquid flow in an inclined porous annulus are analyzed. The heat transport phenomenon is examined with an exponential space-related heat source (ESHS), the convective boundary conditions, and temperature-related heat source (THS). The significance of various shapes of nanoparticles (blades, spherical, platelets, bricks, and cylinders) on the heat and fluid flow characteristics has been explored. The complicated governing equations are solved numerically. Additionally, a statistical study (response surface methodology (RSM) and sensitivity analysis) is performed. The consequence of key parameters on the non-dimensional velocity, skin friction coefficient, temperature, and Nusselt number fields are presented through two-dimensional and surface plots. The irregular heat sources increase the magnitude of velocity and temperature fields. The quadratic and mixed convection mechanism favors the flow structure. The temperature and velocity fields are greater for platelet-shaped nanoparticles followed by cylinder, brick, and spherical-shaped nanoparticles. Further, the Nusselt number is more influenced by THS and less by the total nanoparticle volume fraction 2021 Elsevier Ltd -
The mobility paradigm in higher education: a phenomenological study on the shift in learning space
The study, through the framework of mobility and space, explores the phenomenon of multiple shifts in learning spaces induced by COVID-19. The Interpretative Phenomenological Approach (IPA) is adopted to document the experiences and perceptions of learners caught within these spatial shiftsphysical, online, and hybrid. Online interviews were conducted with six first-year undergraduate and three first-year postgraduate students enrolled at the department of English and Cultural Studies in a Southern Indian University. Some of the dominant patterns emerging from the accounts of the participants are (1) the changing perception of conducive learning space, (2) the changing perceptions and roles of various classroom actors, and (3) the evolving nature of the learners and the learning process. The study utilizes the framework of mobility to locate the stage of embodied skill acquisition of the participants within the online learning space and illuminates the possibilities offered by this paradigm within the context of higher education. Some of the insights gained through the study include a changing perception of the conventional built classroom space, a notable preference towards a complete online or offline mode as opposed to the hybrid mode, and a transition towards self-directed learning. The study argues that these implications are highly pertinent and can significantly shape the way pedagogues and researchers engage with the various modes of learningphysical, online, and hybridand the future of higher education that is shaped by technology-enabled learning. 2021, The Author(s). -
A hybrid approach for COVID-19 detection using biogeography-based optimization and deep learning
The COVID-19 pandemic has created a major challenge for countries all over the world and has placed tremendous pressure on their public health care services. An early diagnosis of COVID-19 may reduce the impact of the coronavirus. To achieve this objective, modern computation methods, such as deep learning, may be applied. In this study, a computational model involving deep learning and biogeography-based optimization (BBO) for early detection and management of COVID-19 is introduced. Specifically, BBO is used for the layer selection process in the proposed convolutional neural network (CNN). The computational model accepts images, such as CT scans, X-rays, positron emission tomography, lung ultrasound, and magnetic resonance imaging, as inputs. In the comparative analysis, the proposed deep learning model CNN is compared with other existing models, namely, VGG16, InceptionV3, ResNet50, and MobileNet. In the fitness function formation, classification accuracy is considered to enhance the prediction capability of the proposed model. Experimental results demonstrate that the proposed model outperforms InceptionV3 and ResNet50. 2022 Tech Science Press. All rights reserved. -
Effectiveness of Farmers Risk Management Strategies in Smallholder Agriculture: Evidence from India
Smallholder farmers in developing countries are more vulnerable to climate risks, and most of them, because of a lack of access to institutional risk management measures such as crop insurance, rely on traditional measures to offset the adverse effects of such risks on agricultural production. Employing a multinomial endogenous switching regression technique to the farm-level data, this study first identifies the determinants of farmers own risk management measures and then evaluates their impacts on farm income and downside risk exposure. There are three key highlights of this analysis. One, farmers, based on their past exposures to climate risks, endowments of resources, and access to credit and information, often use more than one measure or strategy to mitigate, transfer, and cope with the climate risks. Two, all the risk management strategies are found to be effective in improving farm income and reducing risk exposure, but it is their joint implementation that yields larger payoffs. Three, the joint adoption of different adaptation strategies is positively associated with farm size, but with liquidity and information constraints relaxed, the probability of their joint adoption is expected to increase further. These findings impinge on the concept of climate-smart agriculture and suggest the need to identify and integrate traditional farm management practices with science-based innovations to provide an effective solution to climate risks. 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
On the discrete weibull marshallolkin family of distributions: Properties, characterizations, and applications
In this article, we introduce a new flexible discrete family of distributions, which accommo-dates wide collection of monotone failure rates. A sub-model of geometric distribution or a discrete generalization of the exponential model is proposed as a special case of the derived family. Besides, we point out a comprehensive record of some of its mathematical properties. Two distinct estimation methods for parameters estimation and two different methods for constructing confidence intervals are explored for the proposed distribution. In addition, three extensive Monte Carlo simulations studies are conducted to assess the advantages between estimation methods. Finally, the utility of the new model is embellished by dint of two real datasets. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Effect of a novel sintering technique: hot coining on microstructure and mechanical properties of MWCNT reinforced Al metal matrix nanocomposite
Fabrication of MWCNT-reinforced nanocomposites with uniform distribution is still remaining as a challenge. Even for researchers who achieved uniform distribution in powder, boundary agglomerations are observed after sintering. Hot coining (HC) a novel technique for bulk sampling can achieve uniform distribution during sintering. Several mechanical testing and characterisation methods are applied closely to explore the mechanical properties and structural features of the hot coined AA2219-MWCNT composites. Hot coining results in significant improvement of mechanical properties when reinforced with 0.75wt.% MWCNT shows 38.8 % (Rockwell hardness), 106% (UTS), 183 % (impact strength) and 76% (radial crushing strength). But retardation in mechanical properties was observed above 0.75wt. %. During HC particle rearrangement and pushing of MWCNT towards particle boundary is not taking place as in other conventional and advanced sintering technology. The fracture surface of HC tensile specimen shows uniform dispersion and MWCNT alignment in the matrix. The fracture surface shows the mixed mode of fracture (ductile-brittle), and ductility is found to be decreasing with increased MWCNT concentration. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Perceived stress among information technology professionals in India during the COVID-19 pandemic
The Information Technology (IT) industry in India is an integral part of the nations economy. The COVID-19 pandemic is a cause of disquietude and is probably the gravest challenge encountered by the IT industry at present. Although the IT industry has contributed to varied sectors globally amid the crisis, IT professionals encounter a profusion of mental health challenges. Despite this, there have as yet been limited studies focusing on the mental health impact on IT professionals during this period. This study strives to explore the role of socio-demographic factors on perceived stress and to examine the association between gratitude and perceived stress among IT professionals in India during the pandemic. Data from 219 participants were included for analysis in this cross-sectional, correlational study. Findings suggest that there exists a significant difference in perceived stress based on gender, marital status, and parental status. Furthermore, the results demonstrate a significant negative association between gratitude and perceived stress. The study contributes to the field of cognitive ergonomics and broadens the theoretical knowledge base of perceived stress based on socio-demographic elements. Findings also have positive implications for organisational psychologists as they suggest that encouraging a focus on gratitude could aid in lower perceived stress. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Geographical and Gender Disparities in Financial Inclusion Diffusion in India
Financial inclusion is providing an opportunity to use essential banking and financial services to the less-privileged people and their businesses in order to accomplish an inclusive society and the inclusive economy. The efforts of policy makers towards achieving financial inclusion in India yielded fruitful results. Numbers of savings accounts, numbers of credit accounts, numbers of deposits, numbers of ATMs, and loan distribution to the micro and small enterprises have significantly improved in recent times. This study intends to provide answer to the question raised by examining the penetration of financial inclusion area wise, region wise and based on gender. This study has employed descriptive research design and has used secondary data for analysis. The study has found that there are geographical and gender disparities in financial inclusion penetration and financial inclusion penetration varies in terms of gender as well in India. Indian Institute of Finance. -
Novel approach to the analysis of fifth-order weakly nonlocal fractional Schringer equation with Caputo derivative
The main goal of this study is to find solutions for the fractional model of the fifth-order weakly nonlocal Schringer equation incorporating nonlinearity of the parabolic law and external potential using a recent modification of the homotopy analysis method (HAM) called the q-homotopy analysis transform method (q-HATM). A mixture of q-HAM and Laplace transform is the projected solutions procedure. The method contributes approximate and exact (for some special cases) solutions such as the bright soliton, dark soliton, and exponential solutions. The simulation results using Mathematica package software, demonstrate that only a few terms are enough to achieve precise, effective, and reliable approximate solutions. In addition, in terms of plots for varying fractional order, the physical behavior of q-HATM solutions has been depicted and the numerical simulation is also exhibited. The results of q-HATM reveal that the projected method is competitive, reliable, and powerful for studying complex nonlinear models of fractional type. 2021 The Authors -
Quantum fractional order Darwinian particle swarm optimization for hyperspectral multi-level image thresholding
A Hyperspectral Image (HSI) is a data cube consisting of hundreds of spatial images. Each captured spatial band is an image at a particular wavelength. Thresholding of these images is itself a tedious task. Two procedures, viz., Qubit Fractional Order Particle Swarm Optimization and Qutrit Fractional Order Particle Swarm Optimization are proposed in this paper for HSI thresholding. The Improved Subspace Decomposition Algorithm, Principal Component Analysis, and a Band Selection Convolutional Neural Network are used in the preprocessing stage for band reduction or informative band selection. For optimal segmentation of the HSI, modified Otsu's criterion, Masi entropy and Tsallis entropy are used. A new method for quantum disaster operation is implemented to prevent the algorithm from getting stuck into local optima. The implementations are carried out on three well known datasets viz., the Indian Pines, the Pavia University and the Xuzhou HYSPEX. The proposed methods are compared with state-of-the-art methods viz., Particle Swarm Optimization (PSO), Ant Colony Optimization, Darwinian Particle Swarm Optimization, Fractional Order Particle Swarm Optimization, Exponential Decay Weight PSO and Heterogeneous Comprehensive Learning PSO concerning the optimal thresholds, best fitness value, computational time, mean and standard deviation of fitness values. Furthermore, the performance of each method is validated with Peak signal-to-noise ratio and SensenDice Similarity Index. The KruskalWallis test, a statistical significance test, is conducted to establish the superiority in favor of the proposed methods. The proposed algorithms are also implemented on some benchmark functions and real life images to establish their universality. 2021 Elsevier B.V. -
Cross-layer hidden Markov analysis for intrusion detection
Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based on intrusion detection methods. First, the clustering process based on storage and search optimization was formulated for clustering and route maintenance in ad hoc mobile cloud computing networks. Moreover, delay, energy consumption, network lifetime, and link accomplishment are highly addressed by the proposed algorithm. The hidden Markov model is used to maintain the data transition and distributions in the network. Every data communication network, like ad hoc mobile cloud computing, faces security and confidentiality issues. However, the main security issues in this article are addressed using the storage and search optimization approach. Hence, the new algorithm developed helps detect intruders through intelligent cross layer analysis with the Markov model. The proposed model was simulated in Network Simulator 3, and the outcomes were compared with those of prevailing methods for evaluating parameters, like accuracy, end-to-end delay, energy consumption, network lifetime, packet delivery ratio, and throughput. 2022 Tech Science Press. All rights reserved. -
Heat and mass transfer of triple diffusive convection in viscoelastic liquids under internal heat source modulations
The influence of sinusoidal (trigonometric cosine [TC]) and nonsinusoidal waveforms (square, sawtooth, and triangular) of internal heat source modulation on triple diffusive convection in viscoelastic liquids is investigated. An Oldroyd-B type model is taken into account for viscoelastic liquids. Nonlinear analysis is carried out using a truncated representation of the Fourier series. To analyze the heat and mass transfer over a triply diffusive liquid layer, expressions for average Nusselt and average Sherwood numbers are derived using 8-mode generalized Lorenz equations. The transient behavior of Nusselt and Sherwood numbers is analyzed on different parameters of the problem. From the results, it is found that the internal heat source enhances the heat transfer and diminishes the mass transfer while the heat sink diminishes the heat transfer and enhances the mass transfer. The results for respective waveforms are obtained for each parameter and it is found that the maximum heat and mass transfer occurs due to TC waveform. The limiting cases of viscoelastic liquids (Newtonian, Oldroyd-B, Maxwell, and RivlinEricksen) have been tabulated and corresponding results for each of the waveforms onheat and mass transfer have been shown. 2021 Wiley Periodicals LLC -
An efficient privacy-preserving model based on OMFTSA for query optimization in crowdsourcing
Crowdsourcing is now one of the most important and transformative paradigms, with great success in a variety of application tasks. Crowdsourcing obtains knowledge and information to solve cognitive or intelligence-intensive tasks from an evolving group of participants via the Internet. Unfortunately, providing a hard privacy guarantee and query optimization is incompatible when a higher task acceptance rate needs to be accomplished and this case is common in most existing crowdsourcing solutions. The state of art systems suffered from different complexities such as lack of crowdsourcing optimization techniques, increased cost, latency, security, and scalability issues. In this paper, we have proposed a crowdsourcing model to optimize the cost and latency, issues that occur while query optimization using the Moth Flame and Tunicate Swarm Algorithm (MF-TSA). The TSA algorithm is added to the MF algorithm to enhance its exploitation capability and yield fast convergence. The data privacy concerns of the worker and the requestor are addressed using homomorphic encryption that simultaneously enhances the efficiency of the crowdsourcing framework. The main aim of this work is to optimize the cost and latency for query plan selection along with security. Initially, the homomorphic encryption model is used to encrypt the data. In query design, two kinds of crowd-controlled administrators, that is, Crowd Powered Selection (CSelect) and Crowd Powered Join (CJoin) are connected for assessing query. The proposed framework utilizes MF-TSA to optimize the selection and join queries with low cost and latency. Finally, the experimental results demonstrate better query optimization performance than other existing algorithms such as sequential, parallel, and CrowdOp. 2021 John Wiley & Sons Ltd. -
Identification of potential ZIKV NS2B-NS3 protease inhibitors from Andrographis paniculata: An insilico approach
Andrographis paniculata is a widely used medicinal plant for treating a variety of human infections. The plant's bioactives have been shown to have a variety of biological activities in various studies, including potential antiviral, anticancer, and anti-inflammatory effects in a variety of experimental models. The present investigation identifies a potent antiviral compound from the phytochemicals of Andrographis paniculata against Zika virus using computational docking simulation. The ZIKV NS2B-NS3 protease, which is involved in viral replication, has been considered as a promising target for Zika virus drug development. The bioactives from Andrographis paniculata, along with standard drugs as control were screened for their binding energy using AutoDock 4.2 against the viral protein. Based on the higher binding affinity the phytocompounds Bisandrographolide A (-11.7), Andrographolide (-10.2) and Andrographiside (-9.7) have convenient interactions at the binding site of target protein (ZIKV NS2B-NS3 protease) in comparison with the control drug. In addition, using insilico tools, the selected high-scoring molecules were analysed for pharmacological properties such as ADME (Absorption, Distribution, Metabolism, and Excretion profile) and toxicity. Andrographolide was reported to have strong pharmacodynamics properties and target accuracy based on the Lipinski rule and lower binding energy. The selected bioactives showed lower AMES toxicity and has potent antiviral activity against zika virus targets. Further, MD simulation studies validated Bisandrographolide A & Andrographolide as a potential hit compound by exhibiting good binding with the target protein. The compounds exhibited good hydrogen bonds with ZIKV NS2B-NS3 protease. As a result, bioactives from the medicinal plant Andrographis paniculata can be studied in vitro and in vivo to develop an antiviral phytopharmaceutical for the successful treatment of zika virus. Communicated by Ramaswamy H. Sarma. 2021 Informa UK Limited, trading as Taylor & Francis Group.