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Computational screening of natural compounds from Salvia plebeia R. Br. for inhibition of SARS-CoV-2 main protease
The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to ? 8.0kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of ? 9.1kcal/mol and ? 8.9kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected proteinligand complexes to confirm their stability at 300ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Graphic abstract: [Figure not available: see fulltext.] 2021, Society for Plant Research. -
Dual-mode chemosensor for the fluorescence detection of zinc and hypochlorite on a fluorescein backbone and its cell-imaging applications
Fluorescein coupled with 3-(aminomethyl)-4,6-dimethylpyridin-2(1H)-one (FAD) was synthesized for the selective recognition of Zn2+ over other interfering metal ions in acetonitrile/aqueous buffer (1 : 1). Interestingly, there was a significant fluorescence enhancement of FAD in association with Zn2+ at 426 nm by strong chelation-induced fluorescence enhancement (CHEF) without interrupting the cyclic spirolactam ring. A binding stoichiometric ratio of 1 : 2 for the ligand FAD with metal Zn2+ was proven by a Jobs plot. However, the cyclic spirolactam ring was opened by hypochlorite (OCl?) as well as oxidative cleavage of the imine bond, which resulted in the emission enhancement of the wavelength at 520 nm. The binding constant and detection limit of FAD towards Zn2+ were determined to be 1 104 M?1 and 1.79 ?M, respectively, and the detection limit for OCl? was determined as 2.24 ?M. We introduced here a dual-mode chemosensor FAD having both the reactive functionalities for the simultaneous detection of Zn2+ and OCl? by employing a metal coordination (Zn2+) and analytes (OCl?) induced chemodosimetric approach, respectively. Furthermore, for the practical application, we studied the fluorescence imaging inside HeLa cells by using FAD, which demonstrated it can be very useful as a selective and sensitive fluorescent probe for zinc. 2022 The Royal Society of Chemistry. -
Implementing strategic responses in the COVID-19 market crisis: a study of small and medium enterprises (SMEs) in India
Purpose: The COVID-19 pandemic presents unprecedented challenges for small and medium enterprises (SMEs) in emerging economies. This paper aims to examine how India's SMEs implement their strategic responses in this crisis. Design/methodology/approach: The study uses dynamic capability theory to explore the strategic responses of SMEs. Strategy implementation theory helps to explain how they implement innovative practices for outcomes. A research model defines the COVID-19 challenges, strategic responses and performance outcomes. The study reports the findings of an initial pilot study of 75 firms and follow-up case study results in the context of COVID-19. Findings: Firms choose their approaches according to their perceived market risks. Case studies illustrate that firms display diverse attitudes depending on their strategic direction, leadership vision and organizational culture. They achieve different outcomes by implementing specific styles of risk management practices (e.g. risk-averting, risk-taking and risk-thriving). Research limitations/implications: Although the study context is Indian SMEs, the findings suggest meaningful lessons for other emerging economies in similar crisis events. The propositions may be extended to future research in broad contexts. Practical implications: Even in the extraordinary COVID-19 market crisis, SMEs with limited resources display their strategic potential by recognizing their unique capabilities, translating them into effective actions and achieving desirable outcomes. Social implications: In the COVID-19 pandemic, top leaders' mental attitude, strategic perspective and routine practices are contagious. Positive leadership motivates both internal and external stakeholders with an enormous level of collaboration. Originality/value: This rare study of Indian SMEs provides a theoretical framework for designing a pilot survey and conducting a case study of multiple firms. Based on these findings, testable propositions are articulated for future research in diverse organizational and national contexts. 2021, Emerald Publishing Limited. -
Sterlite Technologies Ltd.: To Buy or Not to Buy is the Question
[No abstract available] -
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. -
TD?DNN: A Time Decay?Based Deep Neural Network for Recommendation System
In recent years, commercial platforms have embraced recommendation algorithms to provide customers with personalized recommendations. Collaborative Filtering is the most widely used technique of recommendation systems, whose accuracy is primarily reliant on the computed similarity by a similarity measure. Data sparsity is one problem that affects the performance of the similarity measures. In addition, most recommendation algorithms do not remove noisy data from datasets while recommending the items, reducing the accuracy of the recommendation. Further-more, existing recommendation algorithms only consider historical ratings when recommending the items to users, but users tastes may change over time. To address these issues, this research presents a Deep Neural Network based on Time Decay (TD?DNN). In the data preprocessing phase of the model, noisy ratings are detected from the dataset and corrected using the Matrix Factorization approach. A power decay function is applied to the preprocessed input to provide more weight-age to the recent ratings. This non?noisy weighted matrix is fed into the Deep Learning model, con-sisting of an input layer, a Multi?Layer Perceptron, and an output layer to generate predicted rat-ings. The models performance is tested on three benchmark datasets, and experimental results con-firm that TD?DNN outperforms other existing approaches. 2022 by the authors. Li-censee MDPI, Basel, Switzerland. -
Analysis of determinants of voter turnout in Indian states for election years 19912019
Elections, considered the flagship to the emergence of a new government and a new era is a platform replete with exuberance and vibrancy in all forms. No election is complete without its voters who form the backbone behind the success of democracy. Democracy means elections and free and fair elections mean democracy. The present study is a focus on economic determinants of voter turnout in India since 1991 till date (2019 elections). Economics of voting is a study that encompasses analysis of both economists and political scientists in an attempt to study the economic forces influencing political outcome of the country. In this study, relevant forces determining voter turnout and their impact on political outcomes have been emphasized upon. The data are collected across regions and is characterized using panel regression. Economic factors influencing voter turnout are explored using pooled regression and fixed effect model. Results suggest that as India goes to vote, factors such as income employment influence turnout. Literacy (GER) and urban voter turnout do not influence voter turnout. Lack of efficient governance, bureaucratic loopholes, corruption, large-scale migration and others are some of the potent causes of low turnout. 2022, The Author(s), under exclusive licence to Institute for Social and Economic Change. -
IoT-based smart healthcare video surveillance system using edge computing
Managing distributed smart surveillance system is identified as a major challenging issue due to its comprehensive aggregation and analysis of video information on the cloud. In smart healthcare applications, remote patient and elderly people monitoring require a robust response and alarm alerts from surveillance systems within the available bandwidth. In order to make a robust video surveillance system, there is a need for fast response and fast data analytics among connected devices deployed in a real-time cloud environment. Therefore, the proposed research work introduces the Cloud-based Object Tracking and Behavior Identification System (COTBIS) that can incorporate the edge computing capability framework in the gateway level. It is an emerging research area of the Internet of Things (IoT) that can bring robustness and intelligence in distributed video surveillance systems by minimizing network bandwidth and response time between wireless cameras and cloud servers. Further improvements are made by incorporating background subtraction and deep convolution neural network algorithms on moving objects to detect and classify abnormal falling activity monitoring using rank polling. Therefore, the proposed IoT-based smart healthcare video surveillance system using edge computing reduces the network bandwidth and response time and maximizes the fall behavior prediction accuracy significantly comparing to existing cloud-based video surveillance systems. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Interactions of Environmental Pollutant Aromatic Amines With Photo Excited States of Thiophene Substituted 1,3,4-Oxadiazole Derivative: Fluorescence Quenching Studies
In the present work, the fluorescence quenching of novel thiophene substituted1,3,4-oxadiazole derivative 2-(4-(4-vinylphenyl) phenyl)-5-(5-(4-vinylphenyl)thiophen-2-yl)-1,3,4-oxadiazole (TSO) by five different environmental pollutant aromatic amine derivatives like 2,4-dimethylaniline, 3-chloroaniline, 4-chloroaniline, o-anisidine, and m-toluidine has been studied at room temperature through steady-state and time-resolved methods. It is observed that, the quenching efficiency is highest in the case of o-anisidine and least in the case of 3-chloroaniline. The fluorescence quenching mechanism between TSO and aromatic amines is analysed through different quenching models. The results suggest that, the fluorescence quenching is due to diffusion assisted dynamic or collisional quenching according to the sphere of action static quenching model and according to the finite sink approximation model, the bimolecular quenching reactions are due to the collective effect of dynamic and static quenching. Further, cyclic voltammetry and DFT studies suggest that the fluorescence quenching is due to electron transfer. Binding equilibria analysis confirms the 1:1 stoichiometric ratio between fluorophore and the quencher. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Complete analysis of beam analyzing powers in d + ? ? ? n + p at near threshold energies
Focusing attention on the photon spin in d ( ? ? , n ) p at near threshold energies of interest to Big Bang Nucleosynthesis, a complete analysis of beam analyzing powers in d ( ? ? , n ) p reaction is carried out. A complete analysis of the reaction needs not only measurements using one state of linear polarization of photon but also measurements using another state of linear polarization inclined to the first at ?/4 and the two states of circular polarization of the photon. A discussion on the complete characterization of the states of photon polarization is presented. The beam analyzing powers with respect to photon polarization are discussed theoretically, using model independent irreducible tensor formalism. 2022 IOP Publishing Ltd. -
SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans
In this paper, we propose a novel squeeze M-SegNet (SM-SegNet) architecture featuring a fire module to perform accurate as well as fast segmentation of the brain on magnetic resonance imaging (MRI) scans. The proposed model utilizes uniform input patches, combined-connections, long skip connections, and squeezeexpand convolutional layers from the fire module to segment brain MRI data. The proposed SM-SegNet architecture involves a multi-scale deep network on the encoder side and deep supervision on the decoder side, which uses combined-connections (skip connections and pooling indices) from the encoder to the decoder layer. The multi-scale side input layers support the deep network layers extraction of discriminative feature information, and the decoder side provides deep supervision to reduce the gradient problem. By using combined-connections, extracted features can be transferred from the encoder to the decoder resulting in recovering spatial information, which makes the model converge faster. Long skip connections were used to stabilize the gradient updates in the network. Owing to the adoption of the fire module, the proposed model was significantly faster to train and offered a more efficient memory usage with 83% fewer parameters than previously developed methods, owing to the adoption of the fire module. The proposed method was evaluated using the open-access series of imaging studies (OASIS) and the internet brain segmentation registry (IBSR) datasets. The experimental results demonstrate that the proposed SM-SegNet architecture achieves segmentation accuracies of 95% for cerebrospinal fluid, 95% for gray matter, and 96% for white matter, which outperforms the existing methods in both subjective and objective metrics in brain MRI segmentation. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
DarcyForchheimer Nanoliquid Flow and Radiative Heat Transport over Convectively Heated Surface with Chemical Reaction
Abstract: Improving the heat transport of energy transmission fluids is a vital challenge in numerous engineering applications such as photovoltaic thermal management, heat exchangers, transport and energy-saving processes, solar collectors, automotive refrigeration, electronic equipment refrigeration, and engine applications. Nanofluids address the challenges of thermal management in engineering applications. The DarcyForchheimer flow of magneto-nanofluid initiated by a stretched plate is investigated with application of the Buongiorno model. The features of the nth order chemical reaction, Rosseland thermal energy radiation, and non-uniform heat sink/source are also scrutinized. The Buongiorno nanoliquid model is implemented, which includes the frenzied motion of the nanoparticles and the thermal diffusion of the nanoparticles (NPs). Thermal and solutal convection heating boundary conditions are also incorporated. Boundary layer approximations are used in the mathematical derivation. The non-linear control problem is deciphered with application of the RungeKutta shooting method (RKSM). The results for the relevant parameters are analyzed in dimensionless profiles. In addition, the friction factor on the plate, the heat transport rate, and the mass transport rate of the nanoparticles are calculated and analyzed. 2022, Pleiades Publishing, Ltd. -
The study of algal diversity from fresh water bodies of Chimmony Wildlife Sanctuary, Kerala, India
The algal diversity of the freshwater ecosystem is very significant because they are the primary energy producers in the food web. The study for the algal diversity was conducted at Chimmony Wildlife Sanctuary, Thrissur, Kerala, India, from selected sampling sites (Pookoyil thodu, Kidakkapara thodu, Viraku thodu, Nellipara thodu, Anaporu thodu, Kodakallu thodu, Odan thodu, Mullapara thodu, Payampara thodu, Chimmony dam). The identified algal species belong to four different classes: Chlorophyceae, Euglenineae, Rhodophyceae, and Cyanophyceae. Sixty-one algal species were identified, represented by 37 genera, 22 families, and 14 orders. Among the four, Chlorophyceae was the dominant class. Jose & Xavier 2022. Creative Commons Attribution 4.0 International License. JoTT allows unrestricted use, reproduction, and distribution of this article in any medium by providing adequate credit to the author(s) and the source of publication. -
Audit Tenure, Audit Fee, and Audit Quality: Evidence from India
This paper examined the relationship between the tenure of the auditor and the audit quality of Indian companies, particularly in the wake of two significant regulations in the financial reporting, the implementation of Ind AS (the IFRS compliant accounting standards) and mandatory auditor rotation. Using Discretionary Accruals as a proxy for audit quality, the study took the data of all the companies listed on the NSE for 11 financial years, from 2009 2019 (totaling 8,171 firm-year observations). It deployed panel data regression with a random-effects model. The results showed that audit quality improved up to specific auditors tenure, particularly with the IFRS compliance and Big 4 auditors. The higher audit fee is positively significantly associated with lower earnings quality. The study suggested that mandatory auditor rotation might provide the full benefit only along with other regulations on IFRS, auditor reputation, and audit fee. The study provided an impetus to the regulators, audit fraternity, and companies to improve the relevance of financial statements. This is one of the first longitudinal studies examining the interaction effects of different audit regulations. Robustness checks with other proxies of audit quality provided the same results. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
SETTING NARRATIVE THROUGH INSTAGRAM POSTS: A STUDY OF BBC'S REPORTAGE ON AFGHANISTAN
Media organizations have an immense role to play in disseminating informa-tion and shaping perspectives across borders. Though the information revolution pro-vides us with many new opportunities, it also helps in establishing a single narrative through the cultural cultivation of popular media over time. Orientalism, in this manner, presents an image that the West created of the Near East centuries ago and these second-hand experiences are enhanced over the years by the powerful states and media organi-zations to maintain the established hegemony. This current study focuses on understanding the British Broadcasting Corporation's narrative and its ability to include and exclude certain historical facts while reporting on the Taliban's takeover of Afghanistan through Instagram posts. The study found BBC portraying a favorable image for the role played by the NATO allies in Afghanistan and described the Taliban as a sheer group of terror, barbaric, and inhumane organization, following extreme Sharia laws. 2022 Pluto Journals. All rights reserved. -
Strength and durability properties of geopolymer paver blocks made with fly ash and brick kiln rice husk ash
In India the generation of agro waste rice husk ash is abundant. The utilization of rice husk ash in development of geopolymer binders can be suitable to alleviate the environmental problems associated with disposal of rice husk ash. Further, the utilization of rice husk ash generated from the stacks of brick kilns has not been addressed in past, particularly in development of geopolymer binders. This study proposes development of geopolymer paver (GEOPAV) blocks utilizing brick kiln rice husk ash (BKRHA). It presents fresh, mechanical and durability properties of GEOPAV blocks blended with fly ash, BKRHA, natural aggregates, NaOH and Na2SiO3 solution, and cured in both sundry and room temperature conditions. Microstructural analysis using scanning electron microscope (SEM) and X-ray diffraction (XRD) was adopted to study the influence of BKRHA on hardened properties of GEOPAV blocks. The results show that addition of BKRHA reduce the workability of GEOPAV mixes due to micro porous surface with honeycombed structure of BKRHA particles. The addition of BKRHA showed negligible improvement in compressive strength of GEOPAV blocks. However, the major advantage was observed with improved split tensile strength and flexural strength for GEOPAV blocks with BKRHA. Further, the durability properties in terms of resistance to acid and frost attack was significantly improved with the addition of BKRHA in GEOPAV blocks. Such improvements can be attributed to high amounts of amorphous silica in BKRHA which contribute towards dissolution and formation of polymeric gel, and thereby serve as a binder to enhance the geopolymer matrix making it dense. Finally, all the developed GEOPAV blocks satisfy the IS 156582021 specification requirements and perform much better when compared to commercially available paver blocks. 2021 The Authors -
Solutions for time-fractional coupled nonlinear Schringer equations arising in optical solitons
In this work, an efficient novel technique, namely, the q-homotopy analysis transform method (q-HATM) is applied to obtain analytical solutions for a system of time-fractional coupled nonlinear Schringer (TF-CNLS) equations with the time-fractional derivative taken in the Caputo sense. This system of equations incorporate nonlocality behaviors which cannot be modeled under the framework of classical calculus. With numerous important applications in nonlinear optics, it describes interactions between waves of different frequencies or the same frequency but belonging to different polarizations. We first establish existence and uniqueness of solutions for the considered time-fractional problem via a fixed point argument. To demonstrate the effectiveness and efficiency of the q?HATM, two cases each of two time-fractional problems are considered. One important feature of the q?HATM is that it provides reliable algorithms which can be used to generate easily computable solutions for the considered problems in the form of rapidly convergent series. Numerical simulation are provided to capture the behavior of the state variables for distinct values of the fractional order parameter. The results demonstrate that the general response expression obtained by the q?HATM contains the fractional order parameter which can be varied to obtain other responses. Particularly, as this parameter approaches unity, the responses obtained for the considered fractional equations approaches that of the corresponding classical equations. 2021 The Physical Society of the Republic of China (Taiwan) -
Responding to pandemic challenges: leadership lessons from multinational enterprises (MNEs) in India
Purpose: The business sector plays a major role in achieving comprehensive economic development goals in emerging economies. Consequently, the effects of business responses to the COVID-19 pandemic are receiving increasing research attention from an organizational management development perspective. This article aims to examine the role of leadership in charting the course in an extraordinary crisis context. Design/methodology/approach: Using institutional leadership theory, leadership contingency theory and dynamic leadership capability theory, the authors present a research framework that defines macrochallenges and organizational level responses and outcomes. The article adopts a case study approach, which includes the identification of four target companies and conducting in-depth interviews with senior management professionals within those companies at different time periods. Findings: Based on the interviews, the steps that Indian companies adopted to respond to the COVID-19 challenge are identified. Expanding the insight from the case study, the findings suggest that although feeling overwhelmed at first, organizational leaders combine prudent (i.e. timely and speedy actions for survival first) and bold (i.e. future envisioning for expansion and growth) actions enabling these firms to weather two waves of the COVID-19 pandemic in India. Originality/value: These multiple case studies are unique in exploring MNEs from different industries. This study also highlights the dynamic relationships between leadership practices, risk management strategies and performance outcomes based on a sound theoretical model and rigorous study methods. 2022, Emerald Publishing Limited. -
Evaluation of Clove Phytochemicals as Potential Antiviral Drug Candidates Targeting SARS-CoV-2 Main Protease: Computational Docking, Molecular Dynamics Simulation, and Pharmacokinetic Profiling
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus can cause a sudden respiratory disease spreading with a high mortality rate arising with unknown mechanisms. Still, there is no proper treatment available to overcome the disease, which urges the research community and pharmaceutical industries to screen a novel therapeutic intervention to combat the current pandemic. This current study exploits the natural phytochemicals obtained from clove, a traditional natural therapeutic that comprises important bioactive compounds used for targeting the main protease of SARS-CoV-2. As a result, inhibition of viral replication effectively procures by targeting the main protease, which is responsible for the viral replication inside the host. Pharmacokinetic studies were evaluated for the property of drug likeliness. A total of 53 bioactives were subjected to the study, and four among them, namely, eugenie, syzyginin B, eugenol, and casuarictin, showed potential binding properties against the target SARS-CoV-2 main protease. The resultant best bioactive was compared with the commercially available standard drugs. Furthermore, validation of respective compounds with a comprehensive molecular dynamics simulation was performed using Schringer software. To further validate the bioactive phytochemicals and delimit the screening process of potential drugs against coronavirus disease 2019, in vitro and in vivo clinical studies are needed to prove their efficacy. Copyright 2022 Chandra Manivannan, Malaisamy, Eswaran, Meyyazhagan, Arumugam, Rengasamy, Balasubramanian and Liu. -
Vapor growth and optimization of supersaturation for tailoring the physical properties of stoichiometric Sb2Se3 crystalline habits
The evolution of different morphologies (fibers, whiskers, needles, and spherulites) of antimony selenide (Sb2Se3), devoid of foreign chemical elements, was explored by the physical vapor deposition (PVD) method, employing an indigenously assembled tubular furnace, which showed layer growth mode as per the metallurgical and scanning electron micrographs. Supersaturation for crystallization was optimized by precisely controlling the difference in temperatures of nutrient and growth zones, ?T = TN ? TG, where ?T = 125 to 350C. The strain and dislocation density of the crystals were evaluated from the crystallographic data. Monophase nature has been confirmed by Rietveld refinement analysis of the PXRD findings, using Full Proof software. UVVis-NIR and PL spectra of the morphologies revealed band gap, Eg in the range, 1.151.18eV. Among these habits, good-quality whiskers bearing flat faces of appreciable crystallinity, stoichiometry, thermal stability and mechanical strength were produced due to the periodic deposition of atoms associated with the progression of smooth vaporsolid (v?) interface as evident from PXRD, EDAX, XPS, TGA and microindentation analyses. Hall effect measurements resulted in obtaining appreciable values of electrical parameters, ? = 145.36 ? cm and n = 7.39 1018cm?3 for PV applications. Moreover, optical studies justified direct transition with adequate photon absorption which promises the suitability of whiskers as absorbers in the energy conversion process. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.