bluuebunny/crossref_metadata_2025 huggingface dataset:
Host’s Specific SARS-CoV-2 Mutations: Insertion of the Phenylalanine in the NSP6 Linked to the United Kingdom and Premature Termination of the ORF-8 Associated with the European and the United States of America Derived Samples
Authors: Khalid Mohammad , Al-ebini Yousef , Murphy David , Shoai Maryam
Published: December 2020

The coronavirus belongs to the order Nidovirales, which is known for the longest RNA genome virus. The polymerase enzyme of SARS-CoV-2 has proofreading functions, but still, the RNA viruses have a higher mutation rate than DNA viruses. The mutations in the viral genome provide a replication advantage in any population/geographical location and that may have profound consequences in the outcome and pathogenesis, diagnosis and patient management of the viral infection. In the present study, we have analysed full-length SARS-CoV-2 genome sequences, derived from symptomatic/asymptomatic COVID-19 patients from all six continents to investigate the common mutations globally. Our results revealed that SARS-CoV-2 is mutating independently, we identified total 313 mutations and some (21 mutations) of them are prevailing over time irrespective of geographical location. Another important finding, we are reporting here is, the mutation rate of the virus varies in different geographical locations suggesting the virus is adapting different strategies in the infected populations, having different genetic backgrounds across the globe. We have identified 11085TTT insertion (insertion of the Phenylalanine in NSP6 at position 38) mutation, which is mainly linked to the UK derived SARS-CoV-2 samples, we have also discovered non-sense mutation in ORF-8 after 17 amino acid is linked to the European and the USA derived SARS-CoV-2 samples.
LazySampling and LinearSampling: Fast Stochastic Sampling of RNA Secondary Structure with Applications to SARS-CoV-2
Authors: Zhang He , Zhang Liang , Li Sizhen , Mathews David H. , Huang Liang
Published: December 2020

Many RNAs fold into multiple structures at equilibrium. The classical stochastic sampling algorithm can sample secondary structures according to their probabilities in the Boltzmann ensemble, and is widely used. However, this algorithm, consisting of a bottom-up partition function phase followed by a top-down sampling phase, suffers from three limitations: (a) the formulation and implementation of the sampling phase are unnecessarily complicated; (b) the sampling phase repeatedly recalculates many redundant recursions already done during the partition function phase; (c) the partition function runtime scales cubically with the sequence length. These issues prevent stochastic sampling from being used for very long RNAs such as the full genomes of SARS-CoV-2. To address these problems, we first adopt a hypergraph framework under which the sampling algorithm can be greatly simplified. We then present three sampling algorithms under this framework, among which the LazySampling algorithm is the fastest by eliminating redundant work in the sampling phase via on-demand caching. Based on LazySampling, we further replace the cubic-time partition function by a linear-time approximate one, and derive LinearSampling, an end-to-end linear-time sampling algorithm that is orders of magnitude faster than the standard one. For instance, LinearSampling is 176× faster (38.9s vs. 1.9h) than Vienna RNAsubopt on the full genome of Ebola virus (18,959nt). More importantly, LinearSampling is the first RNA structure sampling algorithm to scale up to the full-genome of SARS-CoV-2 without local window constraints, taking only 69.2 seconds on its reference sequence (29,903nt). The resulting sample correlates well with the experimentally-guided structures. On the SARS-CoV-2 genome, LinearSampling finds 23 regions of 15ntwith high accessibilities, which are potential targets for COVID-19 diagnostics and drug design.

See code:https://github.com/LinearFold/LinearSampling
Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution
Authors: Trevino Alexandro E. , Müller Fabian , Andersen Jimena , Sundaram Laksshman , Kathiria Arwa , Shcherbina Anna , Farh Kyle , Chang Howard Y. , Paşca Anca M. , Kundaje Anshul , Paşca Sergiu P. , Greenleaf William J.
Published: December 2020

Genetic perturbations of cerebral cortical development can lead to neurodevelopmental disease, including autism spectrum disorder (ASD). To identify genomic regions crucial to corticogenesis, we mapped the activity of gene-regulatory elements generating a single-cell atlas of gene expression and chromatin accessibility both independently and jointly. This revealed waves of gene regulation by key transcription factors (TFs) across a nearly continuous differentiation trajectory into glutamatergic neurons, distinguished the expression programs of glial lineages, and identified lineage-determining TFs that exhibited strong correlation between linked gene-regulatory elements and expression levels. These highly connected genes adopted an active chromatin state in early differentiating cells, consistent with lineage commitment. Basepair-resolution neural network models identified strong cell-type specific enrichment of noncoding mutations predicted to be disruptive in a cohort of ASD subjects and identified frequently disrupted TF binding sites. This approach illustrates how cell-type specific mapping can provide insights into the programs governing human development and disease.
Environmental Dependence of the Structure of the C-terminal Domain of the SARS-CoV-2 Envelope Protein
Authors: Gadhave Kundlik , Kumar Ankur , Kumar Prateek , Kapuganti Shivani K. , Garg Neha , Vendruscolo Michele , Giri Rajanish
Published: December 2020

The SARS-CoV-2 envelope protein (E) is involved in a broad spectrum of functions in the cycle of the virus, including assembly, budding, envelope formation, and pathogenesis. To enable these activities, E is likely to be capable of changing its conformation depending on environmental cues. To investigate this issue, here we characterised the structural properties of the C-terminal domain of E (E-CTD), which has been reported to interact with host cell membranes. We first studied the conformation of the E-CTD in solution, finding characteristic features of a disordered protein. By contrast, in the presence of large unilamellar vesicles and micelles, which mimic cell membranes, the E-CTD was observed to become structured. The E-CTD was also found to display conformational changes with osmolytes. Furthermore, prolonged incubation of the E-CTD under physiological conditions resulted in amyloid-like fibril formation. Taken together, these findings indicate that the E-CTD can change its conformation depending on its environment, ranging from a disordered state, to a membrane-bound folded state, and an amyloid state. Our results thus provide insight into the structural basis of the role of E in the viral infection process.

Highlights

The E-CTD of SARS-CoV-2 is intrinsically disordered in solution

The E-CTD folds into an ordered structure in presence of membrane mimetics

The E-CTD displays conformational changes in the presence of osmolytes

Prolonged incubation of the E-CTD leads to its self-assembly into amyloid-like fibrils

Graphical Abstract

Structural heterogeneity of the E-CTD.

The E-CTD shows a disordered secondary structure in an aqueous solution and converts into an ordered structure in the presence of membrane mimetics (neutral and negative lipids) and natural osmolytes (TMAO). Incubation at physiological condition shows typical amyloid-like fibrils. The yellow-colored structure represents a predicted structure of the E-CTD by PEP-FOLD.
C1q/CTRP1 exerts neuroprotective effects in TBI rats by regulating inflammation and autophagy
Authors: Pei Ming , Wang Chaoqun , Li Zhengdong , Zhang Jianhua , Huang Ping , Wang Jiawen , Huang Jiang , Zou Donghua , Chen Yijiu
Published: December 2020

Objective

C1q/CTRP1 is a newly discovered adiponectin protein, which is highly expressed in adipose and heart tissues. Recent studies have revealed that C1q/CTRP1 can regulate metabolism and inhibit inflammation. CTRP1 is also expressed in brain tissues and vascular cells of human and rat, and research on cerebral hemorrhage and cerebral ischemia-reperfusion injury demonstrates that the CTRP family can attenuate secondary brain injury and exert neuroprotective effects. Thus, this study was designed to explore the role of CTRP1 in traumatic brain injury (TBI) and the underlying mechanism.

Main methods

Rats were assigned into rCTRP1 group, vehicle group, and sham group. Modified Feeney’s method was used to establish a closed traumatic brain injury model. Morris water maze was used for directional navigation, reverse searching and space exploration tests in rats. In addition, Golgi-Cox staining was utilized to visualize neurons, dendrites and dendritic spines. ELISA was conducted to detect the levels of inflammatory factors (IL-6 and TNF-α). Finally, Western blot was adopted to detect the relative expression ofp-mTOR and autophagy-related proteins (Beclin-1 and LC3-II).

Results

CTRP1 improved the behavioral and histopathological outcomes, inhibited the inflammatory response, activated mTOR and decreased autophagy-associated protein synthesis in TBI rats.

Conclusion

CTRP1 exerts neuroprotective effects in TBI rats by regulating inflammation and autophagy and has potential therapeutic properties after TBI.
Heterologous expression of methylxanthine synthesis enzymes in mammalian cells and their use as reporter proteins
Authors: Cisneros Brandon T. , Devaraj Neal K.
Published: December 2020

This work demonstrates the reconstitution of active methylxanthine synthesis enzymes in human cells and their potential use as inducible reporter enzymes. A variety of plant enzymes involved in caffeine synthesis have been characterizedin vitroand several of these methylxanthine synthesis enzymes have been heterologously-expressed in yeast or bacteria. In this work, enzymes fromCoffea arabica, Camellia sinensis, andPaullinia cupanahave been heterologously-expressed in human cells. We demonstrate that the enzymes tested exhibit similar patterns of activity with a set of xanthine substrates in human cells when compared to previous reports ofin vitroactivity. We demonstrate that the activity of these enzymes can be used as a reporter for juxtacrine signaling using synNotch-induced expression in the presence of an appropriate substrate. When used in combination with synthetic caffeine receptors, this work has potential for use as anin vivoreporter (e.g. enabling non-invasive monitoring of cell-cell interactions after a cellular transplant) or in synthetic intercellular signaling a methylxanthine, such as caffeine, acting as a synthetic paracrine hormone.
A Sequential Niche Multimodal Conformation Sampling Algorithm for Protein Structure Prediction
Authors: Xia Yu-Hao , Peng Chun-Xiang , Zhou Xiao-Gen , Zhang Gui-Jun
Published: December 2020

Motivation

Massive local minima on the protein energy surface often causes traditional conformation sampling algorithms to be easily trapped in local basin regions, because they are difficult to stride over high-energy barriers. Also, the lowest energy conformation may not correspond to the native structure due to the inaccuracy of energy models. This study investigates whether these two problems can be alleviated by a sequential niche technique without loss of accuracy.

Results

A sequential niche multimodal conformation sampling algorithm for protein structure prediction (SNfold) is proposed in this study. In SNfold, a derating function is designed based on the knowledge learned from the previous sampling and used to construct a series of sampling-guided energy functions. These functions then help the sampling algorithm stride over high-energy barriers and avoid the re-sampling of the explored regions. In inaccurate protein energy models, the high- energy conformation that may correspond to the native structure can be sampled with successively updated sampling-guided energy functions. The proposed SNfold is tested on 300 benchmark proteins and 24 CASP13 FM targets. Results show that SNfold is comparable with Rosetta restrained by distance (Rosetta-dist) and C-QUARK. SNfold correctly folds (TM-score ≥ 0.5) 231 out of 300 proteins. In particular, compared with Rosetta-dist protocol, SNfold achieves higher average TM- score and improves the sampling efficiency by more than 100 times. On the 24 CASP13 FM targets, SNfold is also comparable with four state-of-the-art methods in the CASP13 server group. As a plugin conformation sampling algorithm, SNfold can be extended to other protein structure prediction methods.

Availability

The source code and executable versions are freely available athttps://github.com/iobio-zjut/SNfold.

Contact

zgj@zjut.edu.cn
A molecular clock controls periodically driven cell migration in confined spaces
Authors: Lee Sung Hoon , Hamidzadeh Archer , Yousafzai M. Sulaiman , Ajeti Visar , Chang Hao , Murrell Michael , Levchenko Andre
Published: December 2020

Navigation through dense, physically confining extracellular matrix is common in invasive cell spread and tissue re-organization, but is still poorly understood. Here, we show that this migration is mediated by cyclic changes in the activity of a small GTP-ase RhoA, dependent on the oscillatory changes in the activity and abundance of the RhoA Guanine Exchange Factor, GEF-H1, triggered by a persistent increase in the intracellular Ca2+levels. We show that the molecular clock driving these cyclic changes is mediated by two coupled negative feedback loops, dependent on the microtubule dynamics, with the frequency that can be experimentally modulated based on a predictive mathematical model. We further demonstrate that an increasing frequency of the clock translates into a faster cell migration within physically confining spaces. This work lays the foundation for a better understanding of the molecular mechanisms dynamically driving cell migration in complex environments.
Hsp70 chaperons TDP-43 in dynamic, liquid-like phase and prevents it from amyloid aggregation
Authors: Gu Jinge , Wang Chen , Hu Rirong , Li Yichen , Zhang Shengnan , Sun Yunpeng , Wang Qiangqiang , Li Dan , Fang Yanshan , Liu Cong
Published: December 2020

TAR DNA binding protein 43 kDa (TDP-43) undergoes liquid-liquid phase separation (LLPS) and forms reversible, cytoprotective nuclear bodies (NBs) in response to stress in cells. Abnormal liquid-to-solid phase transition condenses TDP-43 into irreversible pathological fibrils, which is associated with neurodegenerative disorders including amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). However, the mechanisms how cells maintain the dynamics of TDP-43 NBs in stressed conditions are not well understood. Here, we show that the molecular chaperon heat shock protein 70 (Hsp70) is recruited into TDP-43 NBs in stressed cells. It co-phase separates with TDP-43 and delays the maturation of TDP-43 dropletsin vitro. In cells, downregulation of Hsp70 not only diminishes the formation but also reduces the dynamics of TDP-43 NBs especially during prolonged stress, which potentiates the cytotoxicity of TDP-43. Using NMR, we reveal that Hsp70 binds to the highly aggregation-prone, transient α-helix of TDP-43 via its nucleotide-binding domain, which keeps TDP-43 in the highly dynamic, liquid-like phase and prevents pathological aggregation of TDP-43 bothin vitroand in cells. Collectively, our findings demonstrate a crucial role of Hsp70 in chaperoning TDP-43 in the liquid-like phase, which provides a novel layer of the molecular mechanism how chaperons help proteins to remain functional and protect cells from stressed and/or diseased conditions.
Sex differences in learning from exploration
Authors: Chen Cathy S. , Knep Evan , Han Autumn , Ebitz R. Becket , Grissom Nicola M.
Published: December 2020

Sex-based modulation of cognitive processes could set the stage for individual differences in vulnerability to neuropsychiatric disorders. While value-based decision making processes in particular have been proposed to be influenced by sex differences, the overall correct performance in decision making tasks often show variable or minimal differences across sexes. Computational tools allow us to uncover latent variables that define different decision making approaches, even in animals with similar correct performance. Here, we quantify sex differences in mice in the latent variables underlying behavior in a classic value-based decision making task: a restless 2-armed bandit. While male and female mice had similar accuracy, they achieved this performance via different patterns of exploration. Male mice tended to make more exploratory choices overall, largely because they appeared to get “stuck” in exploration once they had started. Female mice tended to explore less, but learned more quickly during exploration. Together, these results suggest that sex exerts stronger influences on decision making during periods of learning and exploration than during stable choices. Exploration during decision making is altered in people diagnosed addictions, depression, and neurodevelopmental disabilities, pinpointing the neural mechanisms of exploration as a highly translational avenue for conferring sex-modulated vulnerability to neuropsychiatric diagnoses.
COVID-19 pivot: a reflection on assessments
Authors: Wong Leon , Zhang Yichelle
Published: December 2020

Purpose

The purpose of this paper is to describe certain choices in assessments, in the digital pivot in response to COVID-19.

Design/methodology/approach

This paper is a discursive reflection about one’s personal experience and response to COVID-19.

Findings

Communicating suggestions of the changes in advance for feedback, consistency in maintaining the same assessment formats and styles, and being available in real-time during key assessment tasks are important in providing assurance and certainty to students in a time of great uncertainty and stress. Anticipating resource constraints will help to avoid potential system fails. Developing assessments that are authentic in using real-world company filings, the answers to which cannot be readily searched on the internet can significantly reduce the risk of cheating, especially where examination supervision resources are unavailable.

Research limitations/implications

Course assessment choices may be specific to a particular course and may not be applicable to all courses.

Practical implications

Course assessment choices and the rationales for them, may be of applicability to other educators.

Originality/value

This note describes the authors’ personal experiences in adapting to the learning and teaching in the COVID environment.
Lead firm’s reconfiguration decision and performance of the value chain
Authors: Gelei Andrea , Sass Magdolna
Published: December 2020

Purpose

This paper aims to trace the performance consequences of within-lead firm reconfigurations of global value chains with respect to business performance and upgrading.

Design/methodology/approach

The study is based on two detailed company case studies which are analysed in an organizational design approach.

Findings

Lead firms systematically separate and internalize high value-added activities in otherwise low value-added processes leading to constant reconfigurations and reorganizations of the production processes in global value chains. The study finds that similar reconfigurations may trigger different changes and changes and performance consequences may differ considerably according to the level of analysis. The two cases help to understand the specific roles of the outsourcing and offshoring decisions in shaping actual global value chain structures.

Originality/value

The consequences of within-lead firm reconfigurations are rarely analysed in the literature.
Assessment of national innovation capabilities of OECD countries using trapezoidal interval type-2 fuzzy ELECTRE III method
Authors: Selvaraj Geetha , Jeon Jeonghwan
Published: December 2020

Purpose

For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.

Design/methodology/approach

In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.

Findings

This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.

Originality/value

The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.
Multi-objective optimization design of a centrifugal impeller considering both aerodynamic efficiency and structural machinability
Authors: Xie Xing , Li Zhenlin , Zhu Baoshan , Wang Hong
Published: December 2020

Purpose

This study aims to complete the optimization design of a centrifugal impeller with both high aerodynamic efficiency and good structural machinability.

Design/methodology/approach

First, the design parameters were derived from the blade loading distribution and the meridional geometry in the impeller three-dimensional (3D) inverse design. The blade wrap angle at the middle span surface and the spanwise averaged blade angle at the blade leading edge obtained from inverse design were chosen as the machinability objectives. The aerodynamic efficiency obtained by computational fluid dynamics was selected as the aerodynamic performance objective. Then, using multi-objective optimization with the optimal Latin hypercube method, quadratic response surface methodology and the non-dominated sorting genetic algorithm, the trade-off optimum impellers with small blade wrap angles, large blade angles and high aerodynamic efficiency were obtained. Finally, computational fluid dynamics and computer-aided manufacturing were performed to verify the aerodynamic performance and structural machinability of the optimum impellers.

Findings

Providing the fore maximum blade loading distribution at both the hub and shroud for the 3D inverse design helped to promote the structural machinability of the designed impeller. A straighter hub coupled with a more curved shroud also facilitated improvement of the impeller’s structural machinability. The preferred impeller was designed by providing both the fore maximum blade loading distribution at a relatively straight hub and a curved shroud for 3D inverse design.

Originality/value

The machining difficulties of the designed high-efficiency impeller can be reduced by reducing blade wrap angle and enlarging blade angle at the beginning of impeller design. It is of practical value in engineering by avoiding the follow-up failure for the machining of the designed impeller.
Numerical analysis of a hybrid tubular and cavity air receiver for solar thermal applications
Authors: Sasidharan Sayuj , Dutta Pradip
Published: December 2020

Purpose

This paper aims to deal with characterisation of the thermal performance of a hybrid tubular and cavity solar thermal receiver.

Design/methodology/approach

The coupled optical-flow-thermal analysis is carried out on the proposed receiver design. Modelling is performed in two and three dimensions for estimating heat loss by natural convection for an upward-facing cavity. Heat loss obtained in two dimensions by solving coupled continuity, momentum and energy equation inside the cavity domain is compared with the loss obtained using an established Nusselt number correlation for realistic receiver performance prediction.

Findings

It is found that radiation emission from a heated cavity wall to the ambient is the dominant mode of heat loss from the receiver. The findings recommend that fluid flow path must be designed adjacent to the surface exposed to irradiation of concentrated flux to limit conduction heat loss.

Research limitations/implications

On-sun experimental tests need to be performed to validate the numerical study.

Practical implications

Numerical analysis of receivers provides guidelines for effective and efficient solar thermal receiver design.

Social implications

Pressurised air receivers designed from this method can be integrated with Brayton cycles using air or supercritical carbon-dioxide to run a turbine generating electricity using a solar heat source.

Originality/value

The present paper proposes a novel method for coupling the flux map from ray-tracing analysis and using it as a heat flux boundary condition for performing coupled flow and heat transfer analysis. This is achieved using affine transformation implemented using extrusion coupling tool from COMSOL Multiphysics software package. Cavity surface natural convection heat transfer coefficient is obtained locally based on the surface temperature distribution.
Single- and double-kink solutions of a one-dimensional, viscoelastic generalization of Burgers’ equation
Authors: Ramos J.I.
Published: December 2020

Purpose

The purpose of this paper is to determine both analytically and numerically the kink solutions to a new one-dimensional, viscoelastic generalization of Burgers’ equation, which includes a non-linear constitutive law, and the number of kinks as functions of the non-linearity and relaxation parameters.

Design/methodology/approach

An analytical procedure and two explicit finite difference methods based on first-order accurate approximations to the first-order derivatives are used to determine the single- and double-kink solutions.

Findings

It is shown that only two parameters characterize the solution and that the existence of a shock wave requires that the (semi-positive) relaxation parameter be less than unity and the non-linearity parameter be less than two. It is also shown that negative values of the non-linearity parameter result in kinks with a single inflection point and strain and dissipation rates with a single relative minimum and a single, relative maximum, respectively. For non-linearity parameters between one and two, it is shown that the kink has three inflection points that merge into a single one as this parameter approaches one and that the strain and dissipation rates exhibit relative maxima and minima whose magnitudes decrease and increase as the relaxation and nonlinearity coefficients, respectively, are increased. It is also shown that the viscoelastic generalization of the Burgers equation presented here is related to an ϕ8−scalar field.

Originality/value

A new, one-dimensional, viscoelastic generalization of Burgers’ equation, which includes a non-linear constitutive law and relaxation is proposed, and its kink solutions are determined both analytically and numerically. The equation and its solutions are connected with scalar field theories and may be used to both studies the effects of the non-linearity and relaxation and assess the accuracy of numerical methods for first-order, non-linear partial differential equations.
Revisiting economic burdens of malaria in the face of climate change: a conceptual analysis for Ethiopia
Authors: Yalew Amsalu Woldie
Published: December 2020

Purpose

Climate change affects the geographic and seasonal range of malaria incidence, especially, in poor tropical countries. This paper aims to attempt to conceptualize the potential economic repercussions of such effects with its focus on Ethiopia.

Design/methodology/approach

The paper is conceptual and descriptive in its design. It first reviews existing literature and evidence on the economic burdens of malaria, and the impacts of climate change on malaria disease. It then draws the economic implications of the expected malaria risk under the future climate. This is accompanied by a discussion on a set of methods that can be used to quantify the economic effects of malaria with or without climate change.

Findings

A review of available evidence shows that climate change is likely to increase the geographic and seasonal range of malaria incidence in Ethiopia. The economic consequences of even a marginal increase in malaria risk will be substantial as one considers the projected impacts of climate change through other channels, the current population exposed to malaria risk and the country’s health system, economic structure and level of investment. The potential effects have the potency to require more household and public spending for health, to perpetuate poverty and inequality and to strain agricultural and regional development.

Originality/value

This paper sheds light on the economic implications of climate change impacts on malaria, particularly, in Agrarian countries laying in the tropics. It illustrates how such impacts will interact with other impact channels of climate change, and thus evolve to influence the macro-economy. The paper also proposes a set of methods that can be used to quantify the potential economic effects of malaria. The paper seeks to stimulate future research on this important topic which rather has been neglected.
Significant household factors that influence an IT employees’ job effectiveness while on work from home
Authors: Sridhar Vivek , Bhattacharya Sanjay
Published: December 2020

Purpose

The purpose of this study is to find out the significant factor/s relating to an information technology (IT) employee’s household that determines the job effectiveness of an employee.

Design/methodology/approach

The approach involves surveying IT employees from across levels of work-experience, companies and cities on household factors that affect their job effectiveness while they work from home and uses discriminant analysis to find out important factor/s that determines if an employee’s job effectiveness remains constant or is better at the workplace that at home.

Findings

The number of elderly staying in the house, age of the eldest member of the household, observable power cuts at home and number of cars owned by individuals were found to be significant factors affecting an IT employees’ job effectiveness.

Originality/value

The study targets a very niche area of the impact of household factors on an IT employee. The findings of this research enable IT organizations from India with insights and enable them to come up with innovative interventions to manage employees on a personalized basis to improve an employees’ job effectiveness and drive organizational effectiveness on a whole, during and post the COVID-19 pandemic.
Prediction of longitudinal facial crack in steel thin slabs funnel mold using different machine learning algorithms
Authors: Thakkar Kushalkumar , Ambekar Suhas Suresh , Hudnurkar Manoj
Published: December 2020

Purpose

Longitudinal facial cracks (LFC) are one of the major defects occurring in the continuous-casting stage of thin slab caster using funnel molds. Longitudinal cracks occur mainly owing to non-uniform cooling, varying thermal conductivity along mold length and use of high superheat during casting, improper casting powder characteristics. These defects are difficult to capture and are visible only in the final stages of a process or even at the customer end. Besides, there is a seasonality associated with this defect where defect intensity increases during the winter season. To address the issue, a model-based on data analytics is developed.

Design/methodology/approach

Around six-month data of steel manufacturing process is taken and around 60 data collection point is analyzed. The model uses different classification machine learning algorithms such as logistic regression, decision tree, ensemble methods of a decision tree, support vector machine and Naïve Bays (for different cut off level) to investigate data.

Findings

Proposed research framework shows that most of models give good results between cut off level 0.6–0.8 and random forest, gradient boosting for decision trees and support vector machine model performs better compared to other model.

Practical implications

Based on predictions of model steel manufacturing companies can identify the optimal operating range where this defect can be reduced.

Originality/value

An analytical approach to identify LFC defects provides objective models for reduction of LFC defects. By reducing LFC defects, quality of steel can be improved.
Application of fuzzy DEMATEL and fuzzy CODAS for analysis of workforce attributes pertaining to Industry 4.0: a case study
Authors: Vinodh S , Wankhede Vishal Ashok
Published: December 2020

Purpose

The aim of this study is to analyze workforce attributes related to Industry 4.0 using fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy combinative distance-based assessment (CODAS).

Design/methodology/approach

Technological trends stipulate various revolution in industries. Industry 4.0 is a vital challenge for modern manufacturing industries. Workforce adoption to such challenge is gaining vital importance. Therefore, such workforce-related attributes need to be identified for enhancing their performance in Industry 4.0 environment. In this context, this article highlights the analysis of 20 workforce attributes for Industry 4.0. Relevant criteria are prioritized using fuzzy DEMATEL. Workforce attributes are prioritized using fuzzy CODAS.

Findings

The key attributes are “Skills/training in decision-making (WA2)”, “Competences in complex system modelling and simulation (WA1)” and “Coding skills (WA20)”.

Research limitations/implications

In the present study, 20 workforce attributes are being considered. In future, additional workforce attributes could be considered.

Practical implications

The study has been conducted based on inputs from industry experts. Hence, the inferences have practical relevance.

Originality/value

The analysis of workforce attributes for Industry 4.0 using MCDM methods is the original contribution of the authors.
Forecast of China’s economic growth during the COVID-19 pandemic: a MIDAS regression analysis
Authors: Gunay Samet , Can Gökberk , Ocak Murat
Published: December 2020

Purpose

This study aims to examine the effect of the COVID-19 pandemic in comparison to the global financial crisis (GFC) on the gross domestic product (GDP) growth rate of China.

Design/methodology/approach

Empirical analyses are conducted through alternative methods such as ordinary least squares, Markov regime switching (MRS) and mixed data sampling (MIDAS) regressions. The flexibility of MIDAS regression enables us to use different variables with quarterly (GDP), monthly (export sales and foreign-exchange reserves) and daily frequencies (foreign exchange rates and Brent oil price).

Findings

The results indicate that the COVID-19 pandemic has had a considerable negative effect on China’s GDP growth, while the dummy variables used for the GFC are found to be insignificant. Further, the forecast accuracy test statistics exhibited a superior performance from MIDAS regression compared to the alternative models, such as MRS regression analysis. According to the forecast results, the authors expect a recovery in China’s economic growth in the second quarter of 2020.

Originality/value

This is one of the earliest studies to examine the effect of the COVID-19 pandemic on the Chinese economy, and to compare the impact of COVID-19 with the GFC. The authors provide further evidence regarding the performance of MIDAS regression analysis vs alternative methods. Findings obtained shed light on policymakers, corporations and households to update their consumption, saving and investment decisions in the chaotic environment of this pandemic.
Risk factors associated with hypertension in Bhutan: findings from the National Health Survey
Authors: Dendup Tashi , Tshering Pandup , Dorji Tandin
Published: December 2020

Purpose

This study examined the risk factors associated with hypertension in Bhutan.

Design/methodology/approach

The cross-sectional data of 30,889 adults from the National Health Survey of Bhutan was used in this study. Multivariable regression accounting for the complex survey design was performed to identify the risk factors. The backward elimination approach was applied in the multivariable analysis.

Findings

The prevalence of hypertension was 17%. Increasing age, being female, being previously married, higher wealth status, past alcohol use, having diabetes, loneliness, health service use and low vegetable intake was associated with increased hypertension risk, whereas, higher education level, being employed and residing in the eastern region was associated with reduced risk. Age, gender, education, wealth status, diabetes status, loneliness and health service use were common factors in all the regions. Marital status and vegetable intake were associated with hypertension in the western and central regions, and alcohol use in the eastern and central regions.

Originality/value

Affecting around one-sixth of the population, hypertension is a significant public health problem in Bhutan. Interventions to improve health education and access, motivate healthy lifestyles, and reduce harmful alcohol use, and strategies to create health-promoting social and built environments are needed to curb the hypertension epidemic and its consequences.
The role of leadership and engagement in call center performance: answering the call in Peru
Authors: Gabel Shemueli Rachel , Sully de Luque Mary F. , Bahamonde Danae
Published: December 2020

Purpose

To examine the effects of leadership style on in-role performance through feedback seeking behavior (FSB) and engagement using the job demands resource theory (JD-R).

Design/methodology/approach

The sample consisted of 152 employees working in a Peruvian call center. Structural equation modeling (SEM) was used to test the research hypotheses.

Findings

Transformational leadership was significantly related to in-role performance, with FSB and engagement sequentially mediating the relationship.

Originality/value

This study highlights the motivational processes that can lead to employee engagement and performance within a call center and identifies the contribution of feedback seeking within this environment.
How exploitative leadership influences employee innovative behavior: the mediating role of relational attachment and moderating role of high-performance work systems
Authors: Wang Zhining , Sun Chuanwei , Cai Shaohan
Published: December 2020

Purpose

The purpose of this research is to examine the relationship between exploitative leadership and employee innovative behavior and explore the mediating role of relational attachment and the moderating role of high-performance work systems (HPWSs).

Design/methodology/approach

This research collected data from 374 employees and their direct supervisors in 75 teams and tested a cross-level moderated mediation model using multilevel path analysis.

Findings

The results suggest that (1) exploitative leadership has a negative impact on employee innovative behavior; (2) relational attachment mediates the relationship between exploitative leadership and employee innovative behavior; (3) HPWS positively moderates the relationship between exploitative leadership and relational attachment and (4) HPWS moderates the mediating mechanism from exploitative leadership to employee innovative behavior.

Practical implications

The empirical findings suggest that organizations should make efforts to prevent exploitative leadership. Moreover, managers should pay attention to the important role of relational attachment in promoting employee innovative behavior and realize the role of HPWSs in facilitating the negative effects of exploitative leadership.

Originality/value

This research identifies relational attachment as a key mediator that links exploitative leadership to innovative behavior and reveals the role of HPWSs in strengthening the negative effects of exploitative leadership on employee innovative behavior.
Feel free to use my personal data: an experiment on disclosure behavior when shopping online
Authors: Gómez-Barroso José Luis
Published: December 2020

Purpose

The goal of the article is twofold: to determine the effectiveness of monetary incentives for disclosing personal information and to confirm the existence of a “bite the bullet” effect whereby people more easily accept providing personal data if they become aware of the requirement when the purchasing decision is almost taken.

Design/methodology/approach

An experiment in which participants made a real purchase on the AliExpress marketplace was carried out. They were asked to login either via the Facebook button or by creating a username and password. A different reimbursement of the price paid for their purchase was offered in each case. This information was presented either at the beginning of the purchasing process or just before completing the purchase order.

Findings

The monetary incentive proved to work well. The “bite the bullet” effect could not be assessed because many participants willingly gave their data to the company even if they had decided not to buy anything.

Practical implications

From a managerial perspective, this is good news. This is a calamity from a policy perspective. More experiments carried out in real settings are needed as a first step for reconsidering public action.

Social implications

While people continue to publicly declare that they have privacy concerns, their behavior could not be further removed from such concerns.

Originality/value

Experiment in a completely real setting, in which participants made a purchase using their own credit card.
Sensitivity and depth of investigation from Monte Carlo ensemble statistics
Authors: Bobe Christin , Keller Johannes , Vijver Ellen Van De
Published: December 2020

For many geophysical measurements, such as direct current or electromagnetic induction methods, information fades away with depth. This has to be taken into account when interpreting models estimated from such measurements. For that reason, a measurement sensitivity analysis and determining the depth of investigation are standard steps during geophysical data processing. In deterministic gradient‐based inversion, the most used sensitivity measure, the differential sensitivity, is readily available since these inversions require the computation of Jacobian matrices. In contrast, differential sensitivity may not be readily available in Monte Carlo inversion methods, since these methods do not necessarily include a linearization of the forward problem. Instead, a prior ensemble is used to simulate an ensemble of forward responses. Then, the prior ensemble is updated according to Bayesian inference. We propose to use the covariance between the prior ensemble and the forward response ensemble for constructing sensitivity measures. In Monte Carlo approaches, the estimation of this covariance does not require additional computations of the forward model. Normalizing this covariance by the variance of the prior ensemble, one obtains a simplified regression coefficient. We investigate differences between this simplified regression coefficient and differential sensitivity using simple forward models. For linear forward models, the simplified regression coefficient is equal to differential sensitivity, except for the influences of the sampling error and of the correlation structure of the prior distribution. In the non‐linear case, the behaviour of the simplified regression coefficient as sensitivity measure is analysed for a simple non‐linear forward model and a frequency‐domain electromagnetic forward model. Differential sensitivity and the simplified regression coefficient are similar for prior intervals on which the forward model response is approximately linear. Differences between the two sensitivity measures increase with the degree of non‐linearity in the prior range. Additionally, we investigate the correlation between prior ensemble and forward response ensemble as sensitivity measure. Correlation yields a normalized version of the simplified regression coefficient. We propose to use this correlation and the simplified regression coefficient for determining depth of investigation in Monte Carlo inversions.
Achieving sustainable development goals through participatory forest management: Examples from South‐Eastern Bangladesh
Authors: Nath Tapan Kumar , Jashimuddin Mohammed , Inoue Makoto
Published: December 2020

Forests managed through peoples' participation can help to achieve a number of sustainable development goals (SDGs). This paper, drawing data from four participatory forest management (PFM) projects in south‐eastern Bangladesh, explored: (a) the factors that influenced the outcomes of PFM; and (b) contribution of PFM towards achieving selected SDGs. The research used observation, semi‐structured household interviews, group discussions, vegetation survey and Ostromʼs design principles for data collection, Divergent forest conditions and factors in four PFM sites have had differential contribution to SDGs. Heterogeneity of user groups, insufficient coordination, absence of motivation, and land tenure conflicts had affected the attainment of SDGs. The PFM helped to achieve 9–11 SDGs comprising poverty reduction (Goal 1), improving food security (Goal 2), maintaining health and well‐being (Goal 3), enhancing childrensʼ education (Goal 4), fair access to jobs and committees (Goals 5 and 10), sources of clean drinking water (Goal 6), affordable energy for cooking (Goal 7), increased household economy (Goal 8), climate change through carbon sequestration (Goal 13), forest conservation (Goal 15), and partnerships with relevant institutions (Goal 16). In order to achieve SDGs, PFM could be viewed as an integral part of government development strategies, which needs sectoral coordination and integration of relevant policies.
Where biotic and abiotic stress responses converge: Common patterns in response to salinity and Plum pox virus infection in pea and peach plants
Authors: Hernández Jose A. , Diaz‐Vivancos Pedro , Acosta‐Motos José Ramón , Barba‐Espín Gregorio
Published: December 2020

Herbaceous and woody plants display specific mechanisms allowing them to adapt and survive to a broad variety of environmental stresses. Nevertheless, all plant species share certain basic physiological and biochemical mechanisms. Under both abiotic and biotic challenges, the extent to which reactive oxygen species (ROS) accumulate relies on the antioxidative system, which is in charge to maintain cellular homeostasis and prevent ROS damage. Moreover, a tight control of ROS production is crucial so that they perform their signalling function. Thus, antioxidative metabolism and redox biology are key players in the physiological response to stress. However, little attention has been paid to the overlapping mechanisms and convergent pathways of antioxidant metabolism between abiotic and biotic stress responses. In the present review, the responses of an herbaceous plant (Pisum sativum L.) and a woody plant (Prunus persica L.) against two forms of stress—salinity and infection by Plum pox virus—were compared, placing emphasis on common response patterns. This information may serve to devise agronomic approaches conferring stress tolerance to many economically relevant crops.