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Sensitivity analysis of nonlinear radiated heat transport of hybrid nanoliquid in an annulus subjected to the nonlinear Boussinesq approximation
The main emphasis of the current study is to analyze the novel feature of the quadratic convective and nonlinear radiative flow of MHD hybrid nanoliquid (CuAl2O3H2O) in an annulus with sensitivity analysis. The significance of exponential space-related heat source, movement of annuli and a new radiation parameter corresponding to an asymptotic nature are also comprehended in the existing study. The dimensionless governing nonlinear equations are treated numerically by employing shooting technique. Impact of effective parameters on the flow and heat transport features has been scrutinized. The optimization procedure is implemented to analyze the influence of three effective parameters (1.5?Rf?5.5,1?QE?3and1%??Cu?3%) on skin friction and Nusselt number by utilizing response surface methodology and sensitivity analysis. The obtained results portray that the nonlinear convection parameter is more favorable for the skin friction coefficient. Further, a comparison of sensitivity depicts that the skin friction coefficient is more sensitive to Rf and QE, whereas Nusselt number is more sensitive to ?Cu. 2020, Akadiai Kiad Budapest, Hungary. -
Mutual Information Pre-processing Based Broken-stick Linear Regression Technique for Web User Behaviour Pattern Mining
Web usage behaviour mining is a substantial research problem to be resolved as it identifies different user's behaviour pattern by analysing web log files. But, accuracy of finding the usage behaviour of users frequently accessed web patterns was limited and also it requires more time. Mutual Information Pre-processing based Broken-Stick Linear Regression (MIP-BSLR) technique is proposed for refining the performance of web user behaviour pattern mining with higher accuracy. Initially, web log files from Apache web log dataset and NASA dataset are considered as input. Then, Mutual Information based Pre-processing (MI-P) method is applied to compute mutual dependence between the two web patterns. Based on the computed value, web access patterns which relevant are taken for further processing and irrelevant patterns are removed. After that, Broken-Stick Linear Regression analysis (BLRA) is performed in MIP-BSLR for Web User Behaviour analysis. By applying the BLRA, the frequently visited web patterns are identified. With the identification of frequently visited web patterns, MIP-BSLR technique exactly predicts the usage behaviour of web users, and also increases the performance of web usage behaviour mining. Experimental evaluation of MIP-BSLR method is conducted on factors such as pattern mining accuracy, false positives, time requirements and space requirements with respect to number of web patterns. Outcomes show that the proposed technique improves the pattern mining accuracy by 14%, and reduces the false positive rate by 52%, time requirement by 19% and space complexity by 21% using Apache web log dataset as compared to conventional methods. Similarly, the pattern mining accuracy of NASA dataset is increased by 16% with the reduction of false positive rate by 47%, time requirement by 20% and space complexity by 22% as compared to conventional methods. 2020. All Rights Reserved. -
SAARC Regional Disaster Law: Need for Progressive Development
[No abstract available] -
On m-quasi Einstein almost Kenmotsu manifolds
In this article, we consider m-quasi Einstein structures on two class of almost Kenmotsu manifolds. Firstly, we study a closed m-quasi Einstein metric on a Kenmotsu manifold. Next, we proved that if a Kenmotsu manifold M admits an m-quasi Einstein metric with conformal vector field V, then M is Einstein. Finally, we prove that a non-Kenmotsu almost Kenmotsu (?,?)' -manifold admitting a closed m-quasi Einstein metric is locally isometric to the Riemannian product Hn+1Rn, provided that ?-?(2n+m)/2m = 1. 2021 Universita degli Studi di Parma. All rights reserved. -
A molecular docking study of SARS-CoV-2 main protease against phytochemicals of Boerhavia diffusa Linn. for novel COVID-19 drug discovery
SARS-CoV-2, the causative virus of the Corona virus disease that was first recorded in 2019 (COVID-19), has already affected over 110 million people across the world with no clear targeted drug therapy that can be efficiently administered to the wide spread victims. This study tries to discover a novel potential inhibitor to the main protease of the virus, by computer aided drug discovery where various major active phytochemicals of the plant Boerhavia diffusa Linn. namely 2-3-4 beta-Ecdysone, Bioquercetin, Biorobin, Boeravinone J, Boerhavisterol, kaempferol, Liriodendrin, quercetin and trans-caftaric acid were docked to SAR-CoV-2 Main Protease using Molecular docking server. The ligands that showed the least binding energy were Biorobin with ? 8.17kcal/mol, Bioquercetin with ? 7.97kcal/mol and Boerhavisterol with ? 6.77kcal/mol. These binding energies were found to be favorable for an efficient docking and resultant inhibition of the viral main protease. The graphical illustrations and visualizations of the docking were obtained along with inhibition constant, intermolecular energy (total and degenerate), interaction surfaces and HB Plot for all the successfully docked conditions of all the 9 ligands mentioned. Additionally the druglikeness of the top 3 hits namely Bioquercetin, Biorobin and Boeravisterol were tested by ADME studies and Boeravisterol was found to be a suitable candidate obeying the Lipinskys rule. Since the main protease of SARS has been reported to possess structural similarity with the main protease of MERS, comparative docking of these ligands were also carried out on the MERS Mpro, however the binding energies for this target was found to be unfavorable for spontaneous binding. From these results, it was concluded that Boerhavia diffusa possess potential therapeutic properties against COVID-19. 2021, Indian Virological Society. -
Socio-economic development of Darjeeling Himalayas: Categorical principal component analysis (CATPCA) and ordinal logistic regression (OLR)
The measurement of regional development plays a crucial role in improving the quality of life of local communities. However, the process of analyzing the regional progress was challenging as regional development was presented as a multidimensional concept. Nonetheless, the study's primary objective was to understand the indicators that genuinely reflect the development process's various dimensions in the northernmost district of West Bengal, Darjeeling Himalayas. Seven dimensions of development, namely psychological well-being, health, education, governance, safety and crime, energy and environment and standard of living were identified for analyzing the socio-economic development of the Darjeeling Himalaya. A questionnaire was framed and circulated in the region for the collection of data. By applying Categorical Principal Component Analysis (CATPCA), the data collected was aggregated into the above mentioned seven dimensions of development and analyzed the relationship between these development indicators through the Ordinal Logistic Regression model (OLR). The results showed that education and governance indicators had a significant impact on psychological wellbeing. Governance was affected by psychological wellbeing, while the standard of living was affected by psychological wellbeing and health indicators in the region. 2021 The Society of Economics and Development, except certain content provided by third parties. -
Structure and biological properties of exopolysaccharide isolated from Citrobacter freundii
This study aimed to investigate the molecular characterization, antioxidant activity in vitro, cytotoxicity study of an exopolysaccharide isolated from Citrobacter freundii. Firstly, the culture conditions were standardized by the Design of experiments (DoE) based approach, and the final yield of thecrude exopolysaccharide was optimized at 2568 169 mg L?1. One large fraction of exopolysaccharide was obtained from the culture filtrate by size exclusion chromatography and molecular characteristics were studied. A new mannose rich exopolysaccharide (Fraction-I) with average molecular weight ~ 1.34 105 Da was isolated. The sugar analysis showed the presence of mannose and glucose in a molar ratio of nearly 7:2 respectively. The structure of the repeating unit in the exopolysaccharide was determined through chemical and 1D/2D- NMR experiments as:[Formula presented] Finally, the antioxidant activity, and the cytotoxicity of the exopolysaccharide were investigated and the relationship with molecular properties was discussed as well. 2020 Elsevier B.V. -
Linear and non-linear analyses of double-diffusive-Chandrasekhar convection coupled with cross-diffusion in micropolar fluid over saturated porous medium
Purpose: The problem aims to find the effects of coupled cross-diffusion in micropolar fluid oversaturated porous medium, subjected to Double-Diffusive Chandrasekhar convection. Design/methodology/approach: Normal mode and perturbation technique have been employed to determine the critical Rayleigh number. Non-linear analysis is carried out by deriving the Lorenz equations using truncated Fourier series representation. Heat and Mass transport are quantified by Nusselt and Sherwood numbers, respectively. Findings: Analysis related to the effects of various parameters is plotted, and the results for the same are interpreted. It is observed from the results that the Dufour parameter and Soret parameter have an opposite influence on the system of cross-diffusion. Originality/value: The effect of the magnetic field on the onset of double-diffusive convection in a porous medium coupled with cross-diffusion in a micropolar fluid is studied for the first time. 2020, Emerald Publishing Limited. -
Discovery of an M-type companion to the Herbig Ae Star V1787 Ori
The intermediate-mass Herbig Ae star V1787 Ori is a member of the L1641 star-forming region in the Orion A molecular cloud. We report the detection of an M-type companion to V1787 Ori at a projected separation of 6.66 arcsec (corresponding to 2577 au), from the analysis of VLT/NACO adaptive optics Ks-band image. Using astrometric data from Gaia DR2, we show that V1787 Ori A and B share similar distance (d ?387 pc) and proper motion, indicating that they are physically associated. We estimate the spectral type of V1787 Ori B to be M5 2 from colour-spectral type calibration tables and template matching using SpeX spectral library. By fitting PARSEC models in the Pan-STARRS colour-magnitude diagram, we find that V1787 Ori B has an age of 8.1$^{+1.7}_{-1.5}$ Myr and a mass of 0.39$^{+0.02}_{-0.05}$ M. We show that V1787 Ori is a pre-main-sequence wide binary system with a mass ratio of 0.23. Such a low-mass ratio system is rarely identified in Herbig Ae/Be binary systems. We conclude this work with a discussion on possible mechanisms for the formation of V1787 Ori wide binary system. 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
An effective face recognition system based on Cloud based IoT with a deep learning model
As of late, the Internet of Things (IoT) innovation has been utilized in applications, for example, transportation, medical care, video observation, and so on. The quick appropriation and development of IoT in these segments are producing an enormous measure of information. For instance, IoT gadgets, for example, cameras produce various pictures when utilized in medical clinic reconnaissance sees. Here, face acknowledgement is one of the most significant instruments that can be utilized for clinic affirmations, enthusiastic discovery, and identification of patients, location of fake gadgets. patient, and test clinic models. Programmed and shrewd face acknowledgement frameworks are profoundly precise in an overseen climate; notwithstanding, they are less exact in an unmanaged climate. Additionally, frameworks must keep on running on numerous occasions in different applications, for example, insightful wellbeing. This work presents a tree-based profound framework for programmed face acknowledgement in a cloud climate. The inside and out pattern have been proposed to cost less for the PC without focusing on unwavering quality. In the model, the additional size is isolated into a few sections, and a stick is made for each part. The tree is characterized by its branch area and stature. The branches are spoken to by a leftover capacity, which comprises of a twofold layer, a stack game plan, and a non-direct capacity. The proposed technique is assessed in an assortment of generally accessible information bases. An examination of the method is likewise finished with top to bottom craftsmanship models for the eye to eye connection. The aftereffects of the tests indicated that the example was considered to have accomplished a precision of 98.65%, 99.19%, and 95.84%. 2020 -
Skincare Products as Sources of Mutagenic Exposure to Infants: An Imperative Study Using a Battery of Microbial Bioassays
Infant skin is highly absorptive and sensitive to exposure from external agents (microbes, toxicants, heat, cold, etc.). Many specialized infant skincare products are currently commercially available. Although the manufacturers claim that their products are mild enough to suit the infant skin, these products need to be studied for their safety. Using animal models to examine the safety of the ever-increasing number of skincare products is not economically or logistically feasible. To overcome this problem, we suggest using a battery of microbial bioassays as a robust system for monitoring the mutagenic potential of skincare products. We picked popular infant skincare products from the Indian market and assessed them by using a battery of three microbial mutagenicity bioassays. Most of them showed significant and reproducible mutagenic potential. Our study results raise concerns about regular use of infant products and emphasize the need to enforce strict regulations for the manufacturing and safety assessment of infant products. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Ultrahigh Power Factors in Ultrawide-Band-Gap GaB3N4and AlB3N4for High-Temperature Thermoelectric Applications
With recent thermoelectric studies concentrating too much on low- and mid-temperature applications, an interesting question is, "are there any materials suitable for high-temperature thermoelectric operations?"To answer this, we have demonstrated in this work the viability of the ternary ultrawide-band-gap materials GaB3N4 and AlB3N4 for high-temperature thermoelectric applications using the first-principles calculation method. Our accurate transport calculations, considering both elastic and inelastic scattering mechanisms, reveal the ultrahigh power factors as high as 1821 ?W m-1 K-2 in GaB3N4 and 1876 ?W m-1 K-2 in AlB3N4 at 2000 K. The power factors are calculated from the Seebeck coefficients and electrical conductivities for both electron and hole carrier concentrations between 1018 and 1021 cm-3. For the figure-of-merit (ZT) calculation, the obtained power factors along with the electronic thermal conductivities determined from the definite Lorenz numbers and the lattice thermal conductivities from the phonon vibrations were used. The calculated ZT values seem to be appreciable for high-temperature applications considering the materials' stability factor and the temperature range within the optimum electron carrier concentration of 1021 cm-3. Although the lattice thermal conductivities are higher, which decrease the values of ZT, considering the ultrahigh power factors instead of the ZT factor could be the right choice for high-temperature thermoelectric applications. -
A multi-scale and rotation-invariant phase pattern (MRIPP) and a stack of restricted Boltzmann machine (RBM) with preprocessing for facial expression classification
In facial expression recognition applications, the classification accuracy decreases because of the blur, illumination and localization problems in images. Therefore, a robust emotion recognition technique is needed. In this work, a Multi-scale and Rotation-Invariant Phase Pattern (MRIPP) is proposed. The MRIPP extracts the features from facial images, and the extracted patterns are blur-insensitive, rotation-invariant and robust. The performance of classification algorithms like Fisher faces, Support Vector Machine (SVM), Extreme Learning Machine (ELM), Convolutional Neural Network (CNN) and Deep Neural Network (DNN) are analyzed. In order to reduce the time for classification, an OPTICS-based pre-processing of the features is proposed that creates a non-redundant and compressed training set to classify the test set. Ten-fold cross validation is used in experimental analysis and the performance metric classification accuracy is used. The proposed approach has been evaluated with six datasets Japanese Female Facial Expression (JAFFE), Cohn Kanade (CK +), Multi- media Understanding Group (MUG), Static Facial Expressions in the Wild (SFEW), Oulu-Chinese Academy of Science, Institute of Automation (Oulu-CASIA) and ManMachine Interaction (MMI) datasets to meet a classification accuracy of 98.2%, 97.5%, 95.6%, 35.5%, 87.7% and 82.4% for seven class emotion detection using a stack of Restricted Boltzmann Machines(RBM), which is high when compared to other latest methods. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
Identification of new classical Ae stars in the Galaxy using LAMOST DR5
We report the first systematic study to identify and characterize a sample of classical Ae stars in the Galaxy. The spectra of these stars were retrieved from the A-star catalogue using the Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST) survey. We identified the emission-line stars in this catalogue from which 159 are confirmed as classical Ae stars. This increases the sample of known classical Ae stars by about nine times from the previously identified 21 stars. The evolutionary phase of classical Ae stars in this study is confirmed from the relatively small mid- and far-infrared excess and from their location in the optical colour-magnitude diagram. We estimated the spectral type using MILES spectral templates and identified classical Ae stars beyond A3, for the first time. The prominent emission lines in the spectra within the wavelength range 3700-9000 are identified and compared with the features present in classical Be stars. The H ? emission strength of the stars in our sample show a steady decrease from late-B type to Ae stars, suggesting that the disc size may be dependent on the spectral type. Interestingly, we noticed emission lines of Fe ii, O i, and Paschen series in the spectrum of some classical Ae stars. These lines are supposed to fade out by late B-type and should not be present in Ae stars. Further studies, including spectra with better resolution, is needed to correlate these results with the rotation rates of classical Ae stars. 2021 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
A novel multi functional multi parameter concealed cluster based data aggregation scheme for wireless sensor networks (NMFMP-CDA)
Data aggregation is a promising solution for minimizing the communication overhead by merging redundant data thereby prolonging the lifetime of energy starving Wireless Sensor Network (WSN). Deployment of heterogeneous sensors for measuring different kinds of physical parameter requires the aggregator to combine diverse data in a smooth and secure manner. Supporting multi functional data aggregation can reduce the transmission cost wherein the base station can compute multiple statistical operations in one query. In this paper, we propose a novel secure energy efficient scheme for aggregating data of diverse parameters by representing sensed data as number of occurrences of different range value using binary encoded form thereby enabling the base station to compute multiple statistical functions over the obtained aggregate of each single parameter in one query. This also facilitates aggregation at every hop with less communication overhead and allows the network size to grow dynamically which in turn meets the need of large scale WSN. To support the recovery of parameter wise elaborated view from the multi parameter aggregate a novelty is employed in additive aggregation. End to end confidentiality of the data is secured by adopting elliptic curve based homomorphic encryption scheme. In addition, signature is attached with the cipher text to preserve the data integrity and authenticity of the node both at the base station and the aggregator which filters out false data at the earliest there by saving bandwidth. The efficiency of the proposed scheme is analyzed in terms of computation and communication overhead with respect to various schemes for various network sizes. This scheme is also validated against various attacks and proved to be efficient for aggregating more number of parameters. To the best of our understanding, our proposed scheme is the first to meet all of the above stated quality measures with a good performance. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Variations in andrographolide content, phytochemical constituents and antioxidant activity of leaves of andrographis paniculata (L.) nees collected from different locations of Southern India
In present study, the samples collected from different locations of Southern India viz., Yellapur Beltargadde, Siddapur, Joida, Ankola, Sirsi Kangod, Yellapur Shalabail, Sirsi Bairumbe, Karwar of Karnataka and Kasaragod from Kerala were analyzed for the andrographolide content, total phenolic and flavonoid content and screened for their antioxidant potential. The A. paniculata leaves were extracted with three different solvents (chloroform, methanol and water) and methanolic extract of Siddapur showed highest (8.82 0.25 mg/g DW) amount of phenolic content whereas, aqueous extract of Ankola (3.00 1.18 mg/g DW) showed the least amount. Chloroform extract of Yellapur Beltargadde village showed highest quantity i.e. 1.87 0.50 mg/g DW of flavonoid content and aqueous extract of Yellapur Beltargadde showed 0.30 0.20 mg/g DW which was least among all the tested samples. The sample collected from Karwar was found to have highest andrographolide content (9.36 0.02 mg/g DW) followed by Yellapur Beltargadde sample with 7.29 0.01 mg/g DW and Sirsi Kasaragod has the lowest contents of 1.54 0.1 mg/g DW when analyzed through HPLC. Among the nine locations, methanol extract from Joida showed highest percentage of scavenging activity (91.95%) followed by methanol extract of Ankola (90.42%) and chloroform extract of Siddapur (77.31%) which was the lowest value of all samples tested. 2021 Chemical Publishing Co.. All rights reserved. -
P(III)-Mediated Cascade C-N/C-S Bond Formation: A Protocol towards the Synthesis of N,S-Heterocycles and Spiro Compounds
A P(III)-mediated entry towards construction of C?N/C?S bond has been devised. The developed heterocyclization method was exercised for the synthesis of a diverse range of N,S-heterocycles and related spiro molecules. P(NMe2)3 revealed the maximum efficacies under the aerobic reaction conditions and a spectrum of bis-nucleophiles, and isothiocyanates were tolerated well to serve the access of manifold immense molecules. (Figure presented.). 2020 Wiley-VCH GmbH -
Lean Six Sigma competitiveness for micro, small and medium enterprises (MSME): an action research in the Indian context
Purpose: The aim of the article is to ascertain the challenges, lessons learned and managerial implications in the deployment of Lean Six Sigma (LSS) competitiveness to micro, small and medium Enterprises (MSME) in India and to establish doctrines to strengthen the initiatives of the government. Design/methodology/approach: The research adopts the Action Research methodology to develop a case study, which is carried out in the printing industry in a Tier III city using the LSS DMAIC (Define-Measure-Analyze-Improve-Control) approach. It utilizes LSS tools to deploy the strategy and to unearth the challenges and success factors in improving the printing process of a specific batch of a product. Findings: The root cause for the critical to quality (CTQ) characteristic, turn-around-time (TAT) is determined and the solutions are deployed through the scientifically proven data-based approach. As a result of this study, the TAT reduced from an average of 1541.21303.36min, which in turn, improved the sigma level from 0.55 to 2.96, a noteworthy triumph for this MSME. The company realizes an annual savings of USD 12,000 per year due to the success of this project. Top Management Leadership, Data-Based Validation, Technical Know-how and Industrial Engineering Knowledge Base are identified as critical success factors (CSFs), while profitability and on-time delivery are the key performance indicators (KPIs) for the MSME. Eventually, the lessons learned and implications indicate that LSS competitiveness can be treated as quality management standards (QMS) and quality tools and techniques (QTT) to ensure competitive advantage, sustainable green practices and growth. Research limitations/implications: Even though the findings and recommendations of this research are based on a single case study, it is worth noting that the case study is executed in a Tier III city along with novice users of LSS tools and techniques. This indicates the applicability of LSS in MSME and thus, the modality adopted can be further refined to suit the socio-cultural aspects of India. Originality/value: This article illustrates the deployment of LSS from the perspective of novice users, to assist MSME and policymakers to reinforce competitiveness through LSS. Moreover, the government can initiate a scheme in line with LSS competitiveness to complement the existing schemes based on the findings of the case study. 2020, Emerald Publishing Limited. -
Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance
Anomaly detection (AD) is an important aspect of various domains and title insurance (TI) is no exception. Robotic process automation (RPA) is taking over manual tasks in TI business processes, but it has its limitations without the support of artificial intelligence (AI) and machine learning (ML). With increasing data dimensionality and in composite population scenarios, the complexity of detecting anomalies increases and AD in automated document management systems (ADMS) is the least explored domain. Deep learning, being the fastest maturing technology can be combined along with traditional anomaly detectors to facilitate and improve the RPAs in TI. We present a hybrid model for AD, using autoencoders (AE) and a one-class support vector machine (OSVM). In the present study, OSVM receives input features representing real-time documents from the TI business, orchestrated and with dimensions reduced by AE. The results obtained from multiple experiments are comparable with traditional methods and within a business acceptable range, regarding accuracy and performance. 2020, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature. -
"Workplace ostracism, complacency and career plateau impediment in the career path of a dignified clerk"
Learning outcomes: The case study intends to depict the career plateau of an old committed and loyal employee of an organization. The deliberation on the case enables participants to understand the vitality of career planning for employees and organizations. The case helps to develop reflections on workplace ostracism, to arrive at the solutions to address the issues of career planning, to value the experience of the employee and give him a sense of satisfaction. Overall, to understand the importance of career planning for applying HR and OB concepts at the workplace. Case overview/synopsis: It is an account of a real scenario in the automation industry, with slight modifications to hide the identity. The essence of the case study is when a loyal employee is branded as a dignified clerk and gets a feeling of ostracism. The employees makes the organization, terminations because of outdated skills shall be a debatable topic. However, such practices have a profound impact on the other employees who stays in the organization and affect their productivity level. Career adaptability helps to overcome termination issues; adaptability is a psychological process of assisting an individual in coping with the challenges of automation technologies (Zhang Wenguang et al., 2019), it is a process of showing concerns, providing controls, solving curiosity and developing confidence during the transition process. When technologies are implemented the employer needs to address specific challenges access to technology, access to information, provide required skills and competencies to use technology, integrate people, these challenges support the successful implementation of technology (Kettunen and Sampson Jr., 2019). Career planning is a joint effort of employee and employer that sets the development target and path; the process sets demands for both the parties; it places an irreplaceable role for individual growth and corporate strategy (Zhai Meng et al., 2018). The Findings are the frequent review of job analysis and career planning that are critical for the organization's success; if done inappropriately, it would make one's roles obsolete. The critical implications of this case are the essence of career planning and the upskilling of employees. The case is useful for teaching job analysis, career planning concepts. The story is original and explains the transition of an automation industry from labor to capital intensive. The transition to automation makes a loyal employee feel ostracized due to a lack of skill sets. Complexity academic level: Post graduate students studying in business and management and working professional of human resources can use this case. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 6: Human resource management. 2021, Emerald Publishing Limited.