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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. -
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. -
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). -
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 -
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. -
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. -
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. -
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. -
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 -
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). -
Efficient neighbour feedback based trusted multi authenticated node routing model for secure data transmission
The Mobile Ad Hoc Network (MANET) is a network that does not have a fixed infrastruc-ture. Migratory routes and related hosts that are connected via wireless networks self-configure it. Routers and hosts are free to wander, and nodes can change the topology fast and unexpectedly. In emergencies, such as natural/human disasters, armed conflicts, and emergencies, the lowest configuration will ensure ad hoc network applicability. Due to the rapidly rising cellular service requirements and deployment demands, mobile ad-hoc networks have been established in numerous places in recent decades. These applications include topics such as environmental surveillance and others. The underlying routing protocol in a given context has a significant impact on the ad hoc network deployment power. To satisfy the needs of the service level and efficiently meet the deployment requirements, developing a practical and secure MANET routing protocol is a critical task. However, owing to the intrinsic characteristics of ad hoc networks, such as frequent topology changes, open wireless media and limited resources, developing a safe routing protocol is difficult. Therefore, it is vital to develop stable and dependable routing protocols for MANET to provide a better packet delivery relationship, fewer delays, and lower overheads. Because the stability of nodes along this trail is variable, the route discovered cannot be trusted. This paper proposes an efficient Neighbour Feedback-based Trusted Multi Authenticated Node (NFbTMAN) Routing Model. The proposed model is compared to traditional models, and the findings reveal that the proposed model is superior in terms of data security. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Effect of food insecurity on the cognitive problems among elderly in India
Background: Food Insecurity (FI) is a crucial social determinant of health, independent of other socioeconomic factors, as inadequate food resources create a threat to physical and mental health especially among older person. The present study explores the associations between FI and cognitive ability among the aged population in India. Methods: To measure the cognitive functioning we have used two proxies, word recall and computational problem. Descriptive analysis and multivariable logistic regression was used to understand the prevalence of word recall and computational problem by food security and some selected sociodemographic parameters. All the results were reported at 95% confidence interval. Results: We have used the data from the first wave of longitudinal ageing study of India (LASI), with a sample of 31,464 older persons 60 years and above. The study identified that 17 and 5% of the older population in India experiencing computational and word recall problem, respectively. It was found that respondents from food secure households were 14% less likely to have word recall problems [AOR:0.86, 95% CI:0.310.98], and 55% likely to have computational problems [AOR:0.45, 95% CI:0.290.70]. We also found poor cognitive functioning among those experiencing disability, severe ADL, and IADL. Further, factors such as age, education, marital status, working status, health related factors were the major contributors to the cognitive functioning in older adults. Conclusion: This study suggest that food insecurity is associated with a lower level of cognition among the elderly in India, which highlight the need of food policy and interventional strategies to address food insecurity, especially among the individuals belonging to lower wealth quintiles. Furthermore, increasing the coverage of food distribution may also help to decrease the burden of disease for the at most risk population. Also, there is a need for specific programs and policies that improve the availability of nutritious food among elderly. 2021, The Author(s). -
Boundary layer flow of magneto-nanomicropolar liquid over an exponentially elongated porous plate with Joule heating and viscous heating: a numerical study
Micropolar fluids are used in lubrication theory, thrust bearing technologies, cervical flows, lubricants, paint rheology, and the polymer industry. This study develops the numerical simulation of the magneto-Darcy flow of a polarized nanoliquid with Joule heating and viscous heating mechanisms on an exponentially elongated surface. The effects of linearized Rosseland radiation and temperature-dependent heat generation are considered. The flow is generated by an exponential form of elongation of a flexible sheet. The porous matrix and nanoparticle effects are characterized by the Darcy expression and the two-component Buongiorno model correspondingly. The resulting partial differential systems are solved numerically using the RungeKutta-based shooting technique to interpret the importance of key parameters in physical quantities. A direct comparison is made to validate the results. Our results demonstrated that arbitrary movement of the nanoparticles significantly advances the temperature profile by reducing the concentration of nanoparticles. Both Joule heating and viscous heating mechanisms improve the structure of the thermal boundary layer. The porous matrix reduces the velocity of the nanoliquid and thus the width of the velocity boundary layer is reduced. 2021, King Fahd University of Petroleum & Minerals. -
Indias Outward FDI: Macro-economic Determinants of Home Country
Nevertheless, a gap in the literature remains on the choice of investment destination and rationale backing the investment of Indian MNEs. The study examines the diverse home country determinants of outward FDI from low-and middle-income economies also the motive behind the investment of MNEs, which gained little attention in empirical studies. The role of home country determinants investigated for the most recent period, 1991-2019, using a panel data econometric framework. Results indicate that the home country's economic development level, globalization, political risk and science and technology investments significantly correspond to outward FDI from low-and middle-income countries. The present study analysis recommended that low and middle income governments provide incentivesto attract and retain FDI. Indian Institute of Finance. -
Effects of aggregation on TiO2ethylene glycol nanoliquid over an inclined cylinder with exponential space-based heat source: sensitivity analysis
The current study investigates the impact of nanoparticle (NP) aggregation on nanoliquid flow over an inclined elongating cylinder with an exponential space-related heat source. The dynamic viscosity and thermal conductivity for aggregation structure are modeled by utilizing the Modified Krieger-Dougherty Model and Bruggeman Model correspondingly. The governing equations are solved numerically. Further, the regression model for friction coefficient and heat transport rate is obtained by utilizing the Response Surface Methodology for various space-based heat source parameter (0.5 ? QE? 1.5), mixed convection parameter (1 ? ?? 3) and NPs volume fraction (0.01 ? ?? 0.05). The velocity profile exhibited dual features for different values of curvature parameter and NPs volume fraction. The space-based exponential heat source and mixed convection have an enhancing impact on the skin friction coefficient. It is noticed that the heat transport augments with the addition of nanoparticles. The coefficient of friction is found to be more sensitive to the NPs volume fraction. Further, the heat transport rate is more sensitive toward exponential heat source than NPs volume fraction and mixed convection. 2021, Akadiai Kiad Budapest, Hungary. -
Farmers' Protests, Death by Suicides, and Mental Health Systems in India: Critical Questions
Ongoing farmers' protests have once again brought back the spotlight on the agrarian crisis in India. Even though upstream factors that perpetuate farmers' suffering, including the role of the state in promoting agrocapitalism, have been discussed extensively by scholars and activists across the spectrum, mental health discourses almost always frame it as a mental health problem to be addressed by increasing access to psychopharmaceuticals. Drawing on developments around farmers' protests and analysis of articles published in flagship journals of largest professional bodies of clinical psychologists and psychiatrists in India, I highlight the intimate relationship between neoliberal state and farmers' distress to which the mental health system shuts its ears and eyes obscuring and downplaying socio-structural determinants of farmers' mental health. Copyright 2021 Springer Publishing Company, LLC. -
Azole-Based Antibacterial Agents: A Review on Multistep Synthesis Strategies and Biology
This article reviews current multistep synthesis strategies of azole-based antibacterial agents. In recent years, extensive use of chemical agents in treating different diseases resulted in the development of drug resistance. The war on multidrug resistance has resulted in the most significant loss to the worlds economy. Thus, the expansion of development of novel and potential candidates such as azoles and its derivatives is an escalating area in the field of medicinal chemistry. Azole compounds are increasingly being considered necessary in drug discovery paradigms as a number of them serve as lead compounds for the discovery of potent therapeutic agents. They have been used to treat bacterial, fungal, malarial, viral, and other general infections. They have also been known for their anticancer and anti-inflammatory activities. Their efficacy has been attributed to their electron-rich property, resulting in the formation of non-covalent bonds to the receptor proteins. Current research has given us a significant collection of synthetic strategies in the progress of azole compounds. This review article describes the survey of literature regarding multistep synthetic methods in the preparation of azole-based compounds and their antibacterial properties in the last 5 years. 2021 Taylor & Francis Group, LLC. -
ILeHCSA: an internet of things enabled smart home automation scheme with speech enabled controlling options using machine learning strategy
Nowadays, communication schemes and the related automation logics have improved drastically, and people are moving from classical to intelligent applications. This naturally raises the growth ratio of the automation industry and enables researchers to work accordingly. The field of automation is essential in specific unavoidable environments such as hospitals, industrial units, individual residences, disaster areas, etc. In this paper, a novel machine-learning enabled speech-based home automation system is designed, called Intelligent Learning-enabled Home Controlling with Speech Assistance (ILeHCSA). This scheme integrates several latest technologies to control the home intelligently, including machine learning, speech assistance technology, and Internet of Things (IoT) support. Based on these advanced technologies, the logic of smart home automation systems has been designed in this approach, and it provides intellectual home controlling options to people. The following are the devices and sensors which are essential to control the electronic devices embedded into the home environment: Node Microcontroller Unit (MCU) Wi-Fi enabled Microcontroller, Relay Unit, Voice Capture Module with Mic, Speech-to-Text (STT) Converter Module, and Global Positioning System (GPS) to identify the location of the device. The machine-learning logic is utilized to provide a statistical analysis of device usage and to provide a clear summary and traces to maintain the device accordingly. These smart technologies can innovatively change the living atmosphere with sufficient support and comfort. The main intention of this paper is to provide a robust home automation system to support people efficiently, especially the people who are physically suffering from illness and the aged ones. The proposed work provides a 96.5% accuracy ratio when compared with other methods. 2021 Nismon Rio Robert et al. -
Gut Homeostasis; Microbial Cross Talks In Health and Disease Management
The human gut is a densely populated region comprising a diverse collection of microorganisms. The number, type and function of the diverse gut microbiota vary at different sites along the entire gastrointestinal tract. Gut microbes regulate signaling and metabolic pathways through microbial cross talks. Host and microbial interactions mutually contribute for intestinal homeostasis. Rapid shift or imbalance in the microbial community disrupts the equilibrium or homeostatic state leading to dysbiosis and causes many gastrointestinal diseases viz., Inflammatory Bowel Disease, Obesity, Type 2 diabetes, Metabolic endotoxemia, Parkinsons disease and Fatty liver disease etc. Intestinal homeostasis has been confounded by factors that disturb the balance between eubiosis and dysbiosis. This review correlates the consequences of dysbiosis with the incidence of various diseases. Impact of microbiome and its metabolites on various organs such as liver, brain, kidney, large intestine, pancreas etc are discussed. Furthermore, the role of therapeutic approaches such as ingestion of nutraceuticals (probiotics, prebiotics and synbiotics), Fecal Microbial Treatment, Phage therapy and Bacterial consortium treatment in restoring the eubiotic state is elaborately reviewed. 2021 The Author(s). Published by Enviro Research Publishers. -
Role of Silk Fiber Loading on Physico-Mechanical Properties of Epoxy Composites
Researchers have suggested the usage of lightweight materials in the automotive and other engineering components which has proven to be one of the potential ways to meet demand for fuel efficiency and eliminate greenhouse gas emissions generated by the manufacturing industries. In this study, silk fiber (Bombyx-mori) reinforced epoxy biocomposites were fabricated by hand layup method with different loadings of fiber and their physico-mechanical properties were studied following acceptable ASTM standards. The properties of the epoxy matrix were significantly enhanced with the silk fiber loading, displaying optimum properties at 50wt. % silk fiber loading. The findings also led that morphology of silk fiber and surface adhesion with the epoxy matrix affects the properties of biocomposites. Such findings provide perspective into the benefits of fiber reinforcements to the physio-mechanical performance of the epoxy resin. The mechanism of failure and consequently the adhesion between fibers and matrix were analyzed by observing the photomicrographs of the damaged coupons. 2021 Taylor & Francis.