bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two new threatened species of Rinorea (Violaceae), forest trees from East and South Regions, Cameroon
Authors: Achoundong Gaston , Cheek Martin 
Published: November 2021

SummaryTwo tree species are described as new to science: Rinorea spongiocarpa Achound. sp. nov (placed in Rinorea [unranked] Brachypetalae) and Rinorea dimakoensis Achound. sp. nov.( placed in Rinorea [unranked] Ilicifolieae). Both species are endemic to Cameroon, occurring south of the Sanaga river, the first from South and East Regions, occurring in evergreen forest from Ebolowa to Dja, while the second occurs in the northern part of East Region in semi-deciduous forest towards the interface with woodland habitats in the Dimako-Bertoua area. The two species are illustrated, and their affinities and conservation status according to the 2012 IUCN categories and criteria are discussed. Both species are threatened with extinction due to habitat destruction, the first is assessed as Vulnerable, the second Endangered.
Rational Designed Hybrid Peptides Show up to a 6-fold Increase in Antimicrobial Activity and Demonstrate Different Ultrastructural Changes as the Parental Peptides measured by BioSAXS
Authors: Hilpert Kai , Gani Jurnorain , Rumancev Christoph , Simpson Nathan , Lopez-Perez Paula Matilde , Garamus Vasil M. , von Gundlach Andreas Robert , Markov Petar , Scocchi Marco , Mikut Ralf , Rosenhahn Axel 
Published: November 2021

AbstractAntimicrobial peptides (AMPs) are a promising class of compounds being developed against multi-drug resistant bacteria. Hybridization has been reported to increase antimicrobial activity. Here, two proline-rich peptides (consP1: VRKPPYLPRPRPRPL-CONH2 and Bac5-v291: RWRRPIRRRPIRPPFWR-CONH2) were combined with two arginine-isoleucine-rich peptides (optP1: KIILRIRWR-CONH2 and optP7: KRRVRWIIW-CONH2). Proline-rich antimicrobial peptides (PrAMPs) are known to inhibit the bacterial ribosome, shown also for Bac5-v291, whereas it is hypothesized a “dirty drug” model for the arginine-isoleucine-rich peptides. That hypothesis was underpinned by transmission electron microscopy and biological small-angle X-ray scattering (BioSAXS). The hybrid peptides showed a stronger antimicrobial activity compared to the proline-rich peptides, except when compared to Bac5-v291 against E. coli. The increase in activity compared to the arginine-isoleucine-rich peptides was up to 6-fold, however, it was not a general increase but was dependent on the combination of peptides and bacteria. BioSAXS experiments revealed that proline-rich peptides and arginine-isoleucine-rich peptides induce very different ultrastructural changes in E. coli, whereas a hybrid peptide (hyP7B5GK) shows changes, different to both parental peptides and the untreated control. These different ultrastructural changes indicated that the mode of action of the parental peptides is different from each other as well as from the hybrid peptide hyP7B5GK. All peptides showed very low haemolytic activity, some of them showed a 100-fold or larger therapeutic window, demonstrating the potential for further drug development.
Sequence conservation, domain architectures, and phylogenetic distribution of the HD-GYP type c-di-GMP phosphodiesterases
Authors: Galperin Michael Y. , Chou Shan-Ho 
Published: November 2021

ABSTRACTThe HD-GYP domain, named after two of its conserved sequence motifs, was first described in 1999 as a specialized version of the widespread HD phosphohydrolase domain that had additional highly conserved amino acid residues. Domain associations of HD-GYP indicated its involvement in bacterial signal transduction and distribution patterns of this domain suggested that it could serve as a hydrolase of the bacterial second messenger c-di-GMP, in addition to or instead of the EAL domain. Subsequent studies confirmed the ability of various HD-GYP domains to hydrolyze c-di-GMP to linear pGpG and/or GMP. Certain HD-GYP-containing proteins hydrolyze another second messenger, cGAMP, and some HD-GYP domains participate in regulatory protein-protein interactions. The recently solved structures of HD-GYP domains from four distinct organisms clarified the mechanisms of c-di-GMP binding and metal-assisted hydrolysis. However, the HD-GYP domain is poorly represented in public domain databases, which causes certain confusion about its phylogenic distribution, functions, and domain architectures. Here, we present a refined sequence model for the HD-GYP domain and describe the roles of its most conserved residues in metal and/or substrate binding. We also calculate the numbers of HD-GYPs encoded in various genomes and list the most common domain combinations involving HD-GYP, such as the RpfG (REC–HD-GYP), Bd1817 (DUF3391– HD-GYP), and PmGH (GAF–HD-GYP) protein families. We also provide the descriptions of six HD-GYP–associated domains, including four novel integral membrane sensor domains. This work is expected to stimulate studies of diverse HD-GYP-containing proteins, their N-terminal sensor domains and the signals to which they respond.IMPORTANCEThe HD-GYP domain forms class II of c-di-GMP phosphodiesterases that control the cellular levels of the universal bacterial second messenger c-di-GMP and therefore affect flagellar and/or twitching motility, cell development, biofilm formation, and, often, virulence. Despite more than 20 years of research, HD-GYP domains are insufficiently characterized; they are often confused with ‘classical’ HD domains that are involved in various housekeeping activities and may participate in signaling, hydrolyzing (p)ppGpp and c-di-AMP. This work provides an updated description of the HD-GYP domain, including its sequence conservation, phylogenetic distribution, domain architectures, and the most widespread HD-GYP-containing protein families. This work shows that HD-GYP domains are widespread in many environmental bacteria and are predominant c-di-GMP hydrolases in many lineages, including clostridia and deltaproteobacteria.
An Entropy-based Directed Random Walk for Pathway Activity Inference Using Topological Importance and Gene Interactions
Authors: Hui Tay Xin , Sutikno Tole , Kasim Shahreen , Md Fudzee Mohd Farhan , Halim Shahliza Abd , Hassan Rohayanti , Sen Seah Choon 
Published: November 2021

AbstractThe integration of microarray technologies and machine learning methods has become popular in predicting pathological condition of diseases and discovering risk genes. The traditional microarray analysis considers pathways as simple gene sets, treating all genes in the pathway identically while ignoring the pathway network’s structure information. This study, however, proposed an entropy-based directed random walk (e-DRW) method to infer pathway activity. This study aims (1) To enhance the gene-weighting method in Directed Random Walk (DRW) by incorporating t-test statistic scores and correlation coefficient values, (2) To implement entropy as a parameter variable for random walking in a biological network, and (3) To apply Entropy Weight Method (EWM) in DRW pathway activity inference. To test the objectives, the gene expression dataset was used as input datasets while the pathway dataset was used as reference datasets to build a directed graph. An equation was proposed to assess the connectivity of nodes in the directed graph via probability values calculated from the Shannon entropy formula. A direct proof of calculation based on the proposed mathematical formula was presented using e-DRW with gene expression data. Based on the results, there was an improvement in terms of sensitivity of prediction and accuracy of cancer classification between e-DRW and conventional DRW. The within-dataset experiments indicated that our novel method demonstrated robust and superior performance in terms of accuracy and number of predicted risk-active pathways compared to the other DRW methods. In conclusion, the results revealed that e-DRW not only improved prediction performance, but also effectively extracted topologically important pathways and genes that are specifically related to the corresponding cancer types.
How to maximize the effectiveness of stealing thunder in crisis communication: the significance of follow-up actions and transparent communication
Authors: Kim Soo-Yeon , Lee Jeong-Hyeon 
Published: November 2021

PurposeThis study aims to explore consumers' perceptions of stealing thunder and to investigate significant factors for maximizing its effect.Design/methodology/approachThis study used a mixed-methods approach. First, qualitative responses from 286 Korean participants were collected and analyzed (Study 1). Second, the experiment employed a randomized 2 (crisis communication timing: stealing thunder vs thunder) × 2 (transparent vs nontransparent communication) × 2 (follow-up actions: good vs poor) between-subjects experimental design with 426 Korean participants to investigate and confirm the results of Study 1.FindingsQualitative data showed that the participants' evaluation of corporations' stealing thunder strategy is complicated. Some do not perceive corporate use of stealing thunder at face value, but rather view it as yet another hopeless, selfish and irresponsible crisis communication strategy, distrusting it based on strong cynicism toward all corporations. An experiment confirmed that stealing thunder was significantly more effective in eliciting consumers' ethical judgment (EJ) and word-of-mouth (WOM) on corporations than the thunder strategy. Significant two-way interaction effects between crisis timing and follow-up actions showed that the stealing thunder strategy should be accompanied by follow-up actions to increase consumers' credibility and WOM intentions.Originality/valueThis study investigated how consumers evaluate stealing thunder by adopting both a qualitative and quantitative approach to explore how they make meaning out of this phenomenon.
Project portfolio risk analysis with the consideration of project interdependencies
Authors: Bai Libiao , Shi Huijing , Kang Shuyun , Zhang Bingbing 
Published: November 2021

PurposeComprehensive project portfolio risk (PPR) analysis is essential for the success and sustainable development of project portfolios (PPs). However, project interdependency creates complexity for PPR analysis. In this study, considering the interdependency effect among projects, the authors develop a quantitative evaluation model to analyze PPR based on a fuzzy Bayesian network.Design/methodology/approachIn this paper, the primary purpose is to comprehensively evaluate project portfolio risk considering the interdependency effect using a systematical model. Accordingly, a fuzzy Bayesian network (FBN) is developed based on the existing studies. Specifically, first, the risks in project portfolios are identified from the project interdependencies perspective. Second, a fuzzy Bayesian network is adopted to model and quantify the interaction relationships among risks. Finally, the model is implemented to analyze the occurrence situation and characteristics of risks.FindingsThe interdependency effect can lead to high-stake risks, including weak financial liquidity, a lack of cross-project members and project priority imbalance. Furthermore, project schedule risks and inconsistency between product supply and market demand are relatively sensitive and should also be prioritized. Also, the validity of this risk evaluation model has been proved.Originality/valueThe findings identify the most sensitive risks for guaranteeing portfolio implementation and reveal interdependency effect can trigger some specific risks more often. This study proposes for the first time to measure and analyze project portfolio risk by a systematical model. It can help systematically assess and manage the complicated and interdependent risks associated with project portfolios.
Supply chain risk factors in green construction of residential mega projects – interactions and categorization
Authors: Marandi Alamdari Ardalan , Jabarzadeh Younis , Samson Daniel , Sanoubar Naser 
Published: November 2021

PurposeGreen construction has begun implementing sustainable and environmentally friendly practices, but there has not yet been an assessment for green construction supply chain risks in the literature. Identification and assessment of potential risks will result in more appropriate risk mitigation strategies to overcome disruptions affecting higher performance. Thus, this study aims to identify green construction supply chain risks of residential mega-projects.Design/methodology/approachInterpretive structural modeling (ISM) provided a hierarchical model composed of seven layers that elucidated the driving influences between the elements. Matrice d’impacts croises-multiplication appliqúe an classement (MICMAC) analysis classified the elements into the driver, linkage and dependent variables based on their dependence and driving powers, providing a clearer understanding of risk factors and their influential characteristics. Using experts' knowledge and experience is compatible with the subjective nature of ‘supply chain risks’ and is more suitable while collecting pertinent quantitative data which is far more challenging.FindingsTenable output, using an international expert group, addressed key risk factors. Technical expertise and skilled labor, key customers, and corporate culture are found as elements with most driving power, and the final product and logistics coordination and supply chain configuration found as the most dependent risk factors. Managerial implications addressed the most fundamental risk sources and suggested practical proactive risk management approaches to maximize green supply chain performance.Originality/valueIdentified supply chain oriented key risk factors of the residential green mega projects add novelty to the context of green construction projects' supply chain management. And eliciting the influential relations of the key risk factors provide a bigger picture of key risks in green residential mega projects that can be extended by sub-risks related to process activities. Assessing supply chain risks' interactions in the context of green residential mega projects is a novel contribution to mega construction-project management's body of knowledge. Also, the key risk factors were categorized based on the characteristics known as driving power and dependence.
Identifying high quality ideas in the online context: evidence from a meta-analysis
Authors: Hu Suya , Xu Di 
Published: November 2021

PurposeWith the rapid development of web-based ideation platforms, firms are increasingly reaching outside their boundaries to obtain ideas, which makes idea evaluation tricky and ineffective. Numerous studies have investigated the antecedents of idea quality, but few have focused on the fragmented and contradictory conclusions these studies have drawn. Thus, the purpose of this paper is to disentangle conflicting findings regarding factors affecting idea quality.Design/methodology/approachA total of 41 independent samples from 40 articles published between 2009 and 2020 were retrieved and encoded to conduct a meta-analysis. By using Comprehensive Meta-analysis 3.0 (CMA 3.0) software, the relationship between identified influencing factors and idea quality, and the moderating effects of potential variables were investigated.FindingsFactors affecting idea quality were summarized and divided into three categories: idea-related factors, ideator-related factors and platform-related factors. The results indicated that all proposed factors (idea length, supporting evidence, past success, past submissions, past comments, votes received and comments received) had significant positive effects on idea quality. Moreover, the measurement of idea quality and idea type was the causative factor for the inconsistent findings, whereas the moderating effect of platform type was not significant.Originality/valueThis study systematically synthesized the existing research on the factors influencing idea quality and helped to reconcile the mixed results. The findings serve to enrich current knowledge of idea evaluation in the online context, which could have important implications for both scholars and practitioners.
Measure of nonlinearity for underwater target tracking using hull-mounted sensor
Authors: Omkar Lakshmi Jagan B. , Koteswara Rao S. 
Published: November 2021

PurposeDoppler-Bearing Tracking (DBT) is commonly used in target tracking applications for the underwater environment using the Hull-Mounted Sensor (HMS). It is an important and challenging problem in an underwater environment.Design/methodology/approachThe system nonlinearity in an underwater environment increases due to several reasons such as the type of measurements taken, the speeds of target and observer, environmental conditions, number of sensors considered for measurements and so on. Degrees of nonlinearity (DoNL) for these problems are analyzed using a proposed measure of nonlinearity (MoNL) for state estimation.FindingsIn this research, the authors analyzed MoNL for state estimation and computed the conditional MoNL (normalized) using different filtering algorithms where measurements are obtained from a single sensor array (i.e. HMS). MoNL is implemented to find out the system nonlinearity for different filtering algorithms and identified how much nonlinear the system is, that is, to measure nonlinearity of a problem.Originality/valueAlgorithms are evaluated for various scenarios with different angles on the target bow (ATB) in Monte-Carlo simulation. Computation of root mean squared (RMS) errors in position and velocity is carried out to assess the state estimation accuracy using MATLAB.
COVID-19 and supply chain risk mitigation: a case study from India
Authors: Dohale Vishwas , Verma Priyanka , Gunasekaran Angappa , Ambilkar Priya 
Published: November 2021

PurposeThis study prioritizes the supply chain risks (SCRs) and determines risk mitigation strategies (RMSs) for the Indian apparel industry to mitigate the shock of the COVID-19 pandemic disruption.Design/methodology/approachInitially, 23 SCRs within the apparel industry are identified through an extant literature review. Further, a fuzzy analytical hierarchy process (FAHP) is utilized to prioritize the SCRs considering the epidemic situations to understand the criticality of SCRs and determine appropriate RMSs to mitigate the shock of SCRs during COVID-19.FindingsThis study prioritized and ranked the SCRs within the Indian apparel industry based on their severity during the COVID-19 disruption. Results indicate that the demand uncertainty and pandemic disruption risks are the most critical. Based on the SCRs, the present work evaluated and suggested the flexibility and postponement mitigation strategies for the case under study.Research limitations/implicationsThis study has novel implications to the existing literature on supply chain risk management in the form of the FAHP framework. Supply chain practitioners from the other industrial sectors can extend the proposed FAHP framework to assess the SCRs and identify suitable mitigation strategies. The results aid the practitioners working in an apparel industry to benchmark and deploy the proposed RMSs in their firm.Originality/valueThe present study is a unique and earlier attempt to develop a quantitative framework using FAHP to evaluate and determine the risk mitigation strategy for managing the SCRs during the coronavirus epidemic.
The role of operations and supply chains in mitigating social disruptions caused by COVID-19: a stakeholder dynamic capabilities view
Authors: Devi Yashoda , Srivastava Abhishek , Koshta Nitin , Chaudhuri Atanu 
Published: November 2021

PurposeThe disruption caused by COVID-19 exhorts to reiterate the role of operations and supply chain management (OSCM) in achieving social sustainability. Therefore, the present study aims to develop a conceptual understanding of the OSCM ecosystem's role in enabling the world to accelerate towards social sustainability.Design/methodology/approachThe study uses the integrative review method to achieve the stated objectives. The study first identifies the societal disruptions caused by COVID-19. Then based on dynamic capabilities (DC) theory, stakeholder theory and real-life examples, the study puts forward the stakeholder dynamic capabilities (SDC) view as an approach to overcome these social challenges.FindingsTaking the SDC view, the study identified ten social challenges aggravated by the COVID-19. Response actions for OSCM have been proposed to mitigate these challenges.Research limitations/implicationsThe pandemic has brought new challenges to the OSCM to achieve social sustainability. Therefore, the study's proposed response actions aim to assist OSCM managers in leveraging their expertise to do good for society and create a better world. Moreover, the study also provides avenues for future research on the topic.Originality/valueBased on the SDC view, the study attempts to conceptualise social sustainability for OSCM during a pandemic. The SDC view helps capture internal and external social challenges emerging due to COVID-19 and utilise firms' capabilities to overcome these challenges.
(A) Symmetric impacts of crime rate on total factor productivity: evidence from Nigeria
Authors: Ajide Folorunsho M. 
Published: November 2021

PurposeIn this study, an investigation into the asymmetric impacts of crime rate on total factor productivity (TFP) in Nigeria is conducted.Design/methodology/approachThe study employs linear and non-linear autoregressive distributed lag (ARDL) modelling techniques to analyse Nigerian data spanning over a period of 1986–2017. In addition, Granger causality tests are conducted under error correction technique.FindingsThe study establishes that crime rate has a significant impact on TFP in the short and long run. In addition, the positive component of crime rate has positive impacts on TFP in the short run while the negative shocks have negative impacts on TFP. However, in the long run, both positive and negative components have negative impacts on TFP in Nigeria.Originality/valueThis study is the first to analyse the asymmetric impact of crime rate on TFP. The study also advances the literature by examining the symmetric impact of crime rate on TFP in an African country (Nigeria) where crime-related activities are rampant. The study is one of the few studies that shed light on nonlinearities in criminal behaviour.
Understanding the boundary decision of digital platform enterprises
Authors: Lou Shuzhen , Wang Jiexiang , Xia Ji 
Published: November 2021

PurposeBoundary decision is an important but underexplored theme in digital platform research. The boundary decision of digital platform enterprises (DPEs) differs from traditional organizations because of cross-side network effects (CNEs). This study intends to investigate whether transaction cost economics (TCE) and resource-based view (RBV), as classical organization boundary mechanisms, are still applicable for DPEs.Design/methodology/approachTo unfold the research problem, this study conducts a fuzzy-set qualitative comparative analysis (fsQCA) on the samples of 21 platform business units.FindingsThe results show that the classical boundary decision theory still applies in the context of DPEs, but the cross-side network effects will affect boundary decision of DPEs.Originality/valueThis study provides a new framework – integrates TCE, RBV and CNEs – to analyze boundary decision of DPEs. This paper also contributes to research on both organization boundary decision and platform governance.