bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nucleoside reverse transcriptase inhibitors are the major class of HIV antiretroviral therapeutics that induce neuropathic pain in mice
Authors: Bush Keegan , Wairkar Yogesh , Tang Shao-Jun 
Published: January 2022

AbstractThe development of combination antiretroviral therapy (cART) has transformed human immunodeficiency virus (HIV) infection from a lethal diagnosis into a chronic disease, and people living with HIV on cART can experience an almost normal life expectancy. However, these individuals often develop various complications that lead to decreased quality of life, one of the most significant of which is neuropathic pain and development of painful peripheral sensory neuropathy (PSN). Critically, although cART is thought to induce pain pathogenesis, the relative contribution of different classes of antiretrovirals has not been systematically investigated. In this study, we measured development of pathological pain and peripheral neuropathy in mice orally treated with distinct antiretrovirals at their translational dosages. Our results show that only nucleoside reverse transcriptases (NRTIs), but not other types of antiretrovirals, such as proteinase inhibitors, non-nucleoside reverse transcriptase inhibitors, integrase strand transfer inhibitors, and CCR5 antagonists, induce pathological pain and PSN. Thus, these findings suggest that NRTIs are the major class of antiretrovirals in cART that promote development of neuropathic pain. As NRTIs form the essential backbone of multiple different current cART regimens, it is of paramount clinical importance to better understand the underlying mechanism to facilitate design of less toxic forms of these drugs and or potential mitigation strategies.
Interconversion between Serum Amyloid A native and fibril conformations
Authors: Yasar Fatih , Sheridan Miranda S. , Hansmann Ulrich H. E. 
Published: January 2022

AbstractOverexpression of Serum Amyloid A (SAA) can lead to a form of amyloidosis where the fibrils are made of SAA fragments, most often SAA1−76. Using Replica-Exchange-with-Tunneling, we study the conversion of a SAA1−76 chain between a the folded conformation and a fibril conformation. We find that the basins in the free energy landscape corresponding to the two motifs are separated by barriers of only about 2-3 kBT. Crucial for the assembly into the fibril structure is the salt bridge 26E-34K that provides a scaffold for forming the fibril conformation.
The phloem-resident OCTOPUS protein is a novel regulator of flg22-induced responses in Arabidopsis thaliana
Authors: Greenwood Kaitlyn N. , King Courtney L. , Melena Isabella , Stegemann Katherine A. , Collins Carina A. 
Published: January 2022

AbstractPhloem is a critical tissue that transports photosynthates and extracellular signals in vascular plants. Although a functional phloem is necessary for plant health, it is also an ideal environment for pathogens to access host nutrients to promote pathogenesis. Even though many vascular pathogens induce economically relevant crop damage, very little is known about the mechanism(s) by which phloem cells detect potential pathogens and signal to minimize damage. Our lab searched existing phosphoproteomic databases, mining for proteins that were phosphorylated in response to the defense-elicitor flagellin, or flg22, AND were expressed in vascular cells, and we identified Octopus (OPS). OPS is polarly associated with the plasma membrane (PM) of sieve element cells and promotes their differentiation from procambial precursor cells by inhibiting the function of BIN2 in brassinosteroid-related signaling. The observation that OPS is differentially phosphorylated in response to flg22 led us to the examine whether OPS may function in flg22-induced signaling using Arabidopsis T-DNA insertion mutants lacking a functional OPS. In wild-type (WT) seedlings, flg22 binds to the PM receptor flagellin sensing 2 (FLS2) to initiate three branches of a signaling cascade that culminates in increased expression of distinct marker genes. Ultimately these signaling pathways lead to the restriction of pathogen growth. Two independent alleles of ops were treated with 100 μM flg22 and marker genes from all three branches of FLS2 signaling exhibited higher expression than WT. We also found that in the absence of any flg22, ops mutants displayed increased flg22 signaling responses. Our results indicate that OPS may function as a negative regulator of flg22-induced signaling events and is one of very few phloem-resident proteins with a documented role in flg22 signaling. These results indicate that the phloem may be able to sense and response to the threat of bacterial pathogens in a unique way.
TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data
Authors: Pielawski Nicolas , Andersson Axel , Avenel Christophe , Behanova Andrea , Chelebian Eduard , Klemm Anna , Nysjö Fredrik , Solorzano Leslie , Wählby Carolina 
Published: January 2022

AbstractBackground and ObjectivesSpatially resolved techniques for exploring the molecular landscape of tissue samples, such as spatial transcriptomics, often result in millions of data points and images too large to view on a regular desktop computer, limiting the possibilities in visual interactive data exploration. TissUUmaps is a free, open-source browser-based tool for GPU-accelerated visualization and interactive exploration of 107+data points overlaying tissue samples.MethodsHerein we describe how TissUUmaps 3 provides instant multiresolution image viewing and can be customized, shared, and also integrated into Jupyter Notebooks. We introduce new modules where users can visualize markers and regions, explore spatial statistics, perform quantitative analyses of tissue morphology, and assess the quality of decoding in situ transcriptomics data.ResultsWe show that thanks to targeted optimizations the time and cost associated with interactive data exploration were reduced, enabling TissUUmaps 3 to handle the scale of today’s spatial transcriptomics methods.ConclusionTissUUmaps 3 provides significantly improved performance for large multiplex datasets as compared to previous versions. We envision TissUUmaps to contribute to broader dissemination and flexible sharing of large-scale spatial omics data.
Argumentative practices and patterns in debating climate change on Twitter
Authors: Foderaro Antonella , Lorentzen David Gunnarsson 
Published: January 2022

PurposeThe purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.Design/methodology/approachConversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.FindingsAmong the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.Originality/valueWhile Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.
Measuring competitiveness with data-driven principal component analysis: a case study of Chinese international construction companies
Authors: Guo Hui , Lu Weisheng 
Published: January 2022

PurposeDefining and measuring competitiveness has been a major focus in the business and competition literature over the past decades. The paper aims to use data-driven principal component analysis (PCA) to measure firm competitiveness.Design/methodology/approachA “3Ps” (performance, potential, and process) firm competitiveness indicator system is structured for indicator selection. Data-driven PCA is proposed to measure competitiveness by reducing the dimensionality of indicators and assigning weights according to the endogenous structure of a dataset. To illustrate and validate the method, a case study applying to Chinese international construction companies (CICCs) was conducted.FindingsIn the case study, 4 principal components were derived from 11 indicators through PCA. The principal components were labeled as “performance” and “capability” under the two respective super-components of “profitability” and “solvency” of a company. Weights of 11 indicators were then generated and competitiveness of CICCs was finally calculated by composite indexes.Research limitations/implicationsThis study offers a systematic indicator framework for firm competitiveness. The study also provides an alternative approach to better solve the problem of firm competitiveness measurement that has long plagued researchers.Originality/valueThe data-driven PCA approach alleviates the difficulties of dimensionality and subjectivity in measuring firm competitiveness and offers an alternative choice for companies and researchers to evaluate business success in future studies.
Evolution modeling of stakeholder performance on relationship management in the dynamic and complex environments of megaprojects
Authors: Xue Jin , Shen Geoffrey Qiping , Deng Xiaomei , Ogungbile Adedayo Johnson , Chu Xiaoling 
Published: January 2022

PurposeRelationship management evolves with dynamic and complex environments of megaprojects. However, studies on the longitudinal measurement of relationship management performance for each stakeholder in dynamic and complex project environments are lacking. The purpose of this research is to propose an NK-network evolution model to evaluate stakeholder performance on relationship management in the development of megaprojects.Design/methodology/approachThe model input includes the stakeholder-associated issues and stakeholders' relational strategies, the co-effects of which determine the internal effects of relationship management in megaprojects. The model processing simulates the stakeholder performance of relationship management under the dynamic and complex nature of megaprojects. The NK model shows the dynamic stakeholder interactions on relationship management, whereas the network model presents the complex stakeholder structures of the relationships between stakeholders and relevant issues. The model output is the evolution graph to reveal the weak stakeholder performance on relationship management in the timeline of the project duration.FindingsThe research finding reveals that all stakeholders experience the plunge of stakeholder performance of relationship management at the decision-making moment of the planning stage. Construction, environmental and pressure groups may experience the hardship of relationship management at the start of the construction stage. The government is likely to suffer difficulties in relationship management in the late construction stage. Local industry groups would face challenges in relationship management in the middle of the construction stage and handover stage.Originality/valueThe research provides a useful approach to measuring weak moments of relationship management for each stakeholder in various project phases, considering the dynamic and complex environments of megaprojects. The proposed model extends the current knowledge body on how to make project stakeholder analysis by modelling dynamic and complex environments of megaprojects, with bridging the knowledge domains of evolution modeling techniques and network methods.
Sharp schedule compression in urgent emergency construction projects via activity crashing, substitution and overlapping: a case study of Huoshengshan and Leishenshan Hospital projects in Wuhan
Authors: Lu Hui , Wang Hongwei , Yu Dihua , Ye Jian 
Published: January 2022

PurposeTo meet the rapidly increasing demand for medical treatment during the outbreak of COVID-19, Huoshengshan and Leishenshan Hospital are rapidly built (9–12 days) in Wuhan. These two urgent emergency projects are unprecedented. In general, substantial literature suggests that the possibility of shortening a schedule by more than a quarter of its original duration is implausible. By contrast, the two projects had successfully compressed the schedules from months and years to about ten days. This study aims to investigate how this was done and provide references for future projects.Design/methodology/approachThe study uses qualitative case study techniques to analyze the project practices in two urgent emergency projects. Data were gathered through semi-structured interviews and archival research. During interviews, interviewees were asked to describe the project practices adopted to overcome the challenges and freely share their experiences and knowledge.FindingsThe results illustrate that a high degree of schedule compression is achievable through tactful crashing, substitution and overlapping applications. The successful practices heavily rely on the high capacity of participants and necessary organization, management and technology innovations, such as three-level matrix organizational structure, reverse design method, site partition, mock-up room first strategies and prefabricated construction technology. For instance, the reverse design method is one of the most significant innovations to project simplification and accelerate and worthy of promotion for future emergency projects.Practical implicationsThe empirical findings are significant as they evoke new thinking and direction for addressing the main challenges of sharp schedule compression and provide valuable references for future emergency projects, including selecting high-capacity contractors and replacing the conventional design methods with reverse design.Originality/valueSubstantial studies indicate that the maximum degree of schedule compression is highly unlikely to exceed 25%, but this study suggests that sharp compression is possible. Although with flaws in its beauty (i.e. compressing schedule at the expense of construction cost and quality), it is also a breakthrough. It provides the building block for future research in this fertile and unexplored area.
Entrepreneurship, gender and success in Lebanon
Authors: Tlaiss Hayfaa 
Published: January 2022

PurposeThe aim of this paper is to explore how men entrepreneurs construe their success and the influence of the socio-cultural context and political and economic turbulence on their construals of success in the context of the Arab country of Lebanon.Design/methodology/approachTo achieve the objective, the author draw on intersectionality theory and capitalise on twenty in-depth, semi-structured interviews with men entrepreneurs.FindingsThe findings reveal how construals of success by men entrepreneurs occur at the nexus between patriarchy, gendered expectations and adverse economic and political conditions. As a result, success is construed through the perseverance and legitimacy of their business and their compliance with expected family roles. These construals unfold as the men hold themselves accountable for and do gender and success per the ideal expectations indoctrinated by patriarchy.Originality/valueThe originality of this study lies in its theoretical contributions. First, it is the first study to explore the construals of success by men entrepreneurs in an Arab Middle Eastern country. Second, it contributes to a growing body of work that explores gender as a situated practice and demonstrates how it is performed by men entrepreneurs while construing their success. Third, it contributes to research on intersectionality in entrepreneurship and sheds light on the interconnections of gender, patriarchal socio-cultural values, economic and political conditions and entrepreneurship in Arab countries.
Do guanxi and harmonious leadership matter in the sociocultural integration by Chinese multinational enterprises in The Netherlands?
Authors: Sun Zhe , Zhao Liang , Wei Hongji , Wang Xiaoming , Riemersma Rosanne Rosalie 
Published: January 2022

PurposeThe study aims to examine the effects of guanxi and harmonious leadership on acquisition performance and the role of sociocultural integration as a mediating mechanism impacting the above links, with a focus on Chinese cross-border acquisitions in The Netherlands.Design/methodology/approachData were collected through survey questionnaire with 91 respondents who work in Dutch-acquired companies. Regression analysis was used for exploring the relationship.FindingsThe study finds that both guanxi and harmonious leadership are positive to acquisition performance, and sociocultural integration represents a significant mediating mechanism by which guanxi and harmonious leadership can result in improved acquisition performance.Originality/valueThis study contributes to culture research by emphasizing the clarification of specific Chinese cultural values and cultural practices in cross-border acquisitions and examining the role of guanxi and harmonious leadership in acquisition performance. Meanwhile, this study helps to unveil Chinese cross-border acquisitions in The Netherlands by examining the mediating force – sociocultural integration.
Machine learning-based control charts for monitoring fraction nonconforming product in smart manufacturing
Authors: Acosta Simone Massulini , Oliveira Sant'Anna Angelo Marcio 
Published: January 2022

PurposeProcess monitoring is a way to manage the quality characteristics of products in manufacturing processes. Several process monitoring based on machine learning algorithms have been proposed in the literature and have gained the attention of many researchers. In this paper, the authors developed machine learning-based control charts for monitoring fraction non-conforming products in smart manufacturing. This study proposed a relevance vector machine using Bayesian sparse kernel optimized by differential evolution algorithm for efficient monitoring in manufacturing.Design/methodology/approachA new approach was carried out about data analysis, modelling and monitoring in the manufacturing industry. This study developed a relevance vector machine using Bayesian sparse kernel technique to improve the support vector machine used to both regression and classification problems. The authors compared the performance of proposed relevance vector machine with other machine learning algorithms, such as support vector machine, artificial neural network and beta regression model. The proposed approach was evaluated by different shift scenarios of average run length using Monte Carlo simulation.FindingsThe authors analyse a real case study in a manufacturing company, based on best machine learning algorithms. The results indicate that proposed relevance vector machine-based process monitoring are excellent quality tools for monitoring defective products in manufacturing process. A comparative analysis with four machine learning models is used to evaluate the performance of the proposed approach. The relevance vector machine has slightly better performance than support vector machine, artificial neural network and beta models.Originality/valueThis research is different from the others by providing approaches for monitoring defective products. Machine learning-based control charts are used to monitor product failures in smart manufacturing process. Besides, the key contribution of this study is to develop different models for fault detection and to identify any change point in the manufacturing process. Moreover, the authors’ research indicates that machine learning models are adequate tools for the modelling and monitoring of the fraction non-conforming product in the industrial process.
The impact of COVID-19 outbreak on the Mauritian export trade: a disaggregated analysis
Authors: Khan Jaffur Zameelah , Seetanah Boopen , Tandrayen-Ragoobur Verena , Fauzel Sheereen , Teeroovengadum Viraiyan , Ramsohok Sonalisingh 
Published: January 2022

PurposeThis study aims at evaluating the effect of the COVID-19 pandemic on the export trade system for Mauritius during the first half of 2020 (January 2020–June 2020).Design/methodology/approachAn initial analysis of the monthly export time series data proves that on the whole, the series have diverged from their actual trends after the outbreak of the COVID-19 pandemic: observed values are less than those predicted by the selected optimal forecast models. The authors subsequently employ the Bayesian structural time series (BSTS) framework for causal analysis to estimate the impact of the COVID-19 pandemic on the island's export system.FindingsOverall, the findings show that the COVID-19 pandemic has a statistically significant and negative impact on the Mauritian export trade system, with the five main export trading partners and sectors the most affected. Despite that the impact in some cases is not apparent for the period of study, the results indicate that total exports will surely be affected by the pandemic in the long run. Nevertheless, this depends on the measures taken both locally and globally to mitigate the spread of the pandemic.Originality/valueThis study thus contributes to the growing literature on the economic impacts of the COVID-19 pandemic by focussing on a small island economy.
Analysis of effective recall in radio advertising
Authors: Pedreño-Santos Ana , Garcia-Madariaga Jesus 
Published: January 2022

PurposeThe purpose of this research is to determine the relationship between frequency and recall in radio advertising by studying the main features of reach and frequency.Design/methodology/approachThe authors consider the outcome of a frequency model specifically designed for radio campaigns that gives the probability distribution of recall as a function of weekly exposures and GRPs over a dataset of 1,117 radio campaigns broadcast in Spain.FindingsAn increase in factors such as advertising format and creativity are more significant to achieve effective recall than increasing the number of advertising exposures.Practical implicationsThis study has important managerial implications regarding radio campaigns' planning: (1) Effective frequency is a range between 4 and 17 impressions (being 7 the optimal average). (2) The way to optimize the campaign is by using the following factors: live read format (∆ 4.4%), good creativity (∆ 2.8%), endorsement format (∆ 2%), sponsorship format (∆ 1.8%), increase the length of the spot (∆ 1.5%), place the ad in first (∆ 0.8%) or last (∆ 0.7%) positions in the pod. From the results we conclude that the format is at least as important as the creativity itself.Originality/valueThis study contributes to the effective repetition literature in two ways: giving specific clues to the effective frequency in the radio medium and setting advertising factors that predict the effective frequency in radio.