bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: A systematic review and meta-analysis
Authors: Matthies Ashley K. , Trauer Michael M. , Chopra Karl , Jarman Robert 
Published: October 2021

AbstractBackgroundPoint-of-care (POC) lung ultrasound (LUS) is widely used in the emergency setting and there is an established evidence base across a range of respiratory diseases, including previous viral epidemics. The necessity for rapid testing combined with the limitations of other diagnostic tests has led to the proposal of various potential roles for LUS during the COVID-19 pandemic. This systematic review and meta-analysis focused specifically on the diagnostic accuracy of LUS in adult patients presenting with suspected COVID-19.MethodsTraditional and grey-literature searches were performed on June 1st2021. Two authors independently carried out the searches, selected studies and completed the Quality Assessment Tool for Diagnostic Test Accuracy Studies (QUADAS-2). Meta-analysis was carried out using established open-source packages inR. We report overall sensitivity, specificity, positive and negative predictive values and the hierarchical summary receiver operating characteristic curve for LUS. Heterogeneity was determined using the I2statistic.ResultsTwenty studies were included, providing data from a total of 4,314 patients. The prevalence and admission rates were generally high across all studies. Overall LUS was found to be 87.2% sensitive (95% CI 83.6-90.2) and 69.5% specific (95% CI 62.2-72.5) and demonstrated overall positive and negative predictive values of 3.0 (95% 2.3-4.1) and 0.16 (95% 0.12-0.22) respectively. Separate analyses for each reference standard revealed similar sensitivities and specificities for LUS. Heterogeneity between studies was found to be high, and QUADAS-2 assessment identified risks of bias in many studies.ConclusionDuring a period of high prevalence, LUS is a highly sensitive diagnostic test for COVID-19. However, more research is required to confirm these results in more generalisable populations, including those less likely to be admitted to hospital.
Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks
Authors: Beal Jacob , Teague Brian , Sexton John T. , Castillo-Hair Sebastian , DeLateur Nicholas A. , Samineni Meher , Tabor Jeffery J. , Weiss Ron 
Published: October 2021

AbstractReliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parameterize the models, and the tolerance of biological devices for imperfections in modeling and measurement. To better understand this relationship, we have derived an Engineering Error Inequality that provides a quantitative mathematical bound on the relationship between predictability of results, model accuracy, measurement precision, and device characteristics. We apply this relation to estimate measurement precision requirements for engineering genetic regulatory networks given current model and device characteristics, recommending a target standard deviation of 1.5-fold. We then compare these requirements with the results of an interlaboratory study to validate that these requirements can be met via flow cytometry with matched instrument channels and an independent calibrant. Based on these results, we recommend a set of best practices for quality control of flow cytometry data and discuss how these might be extended to other measurement modalities and applied to support further development of genetic regulatory network engineering.
Extremely thermophilic endospores germinate and metabolise organic carbon in sediments heated to above 80°C
Authors: Bell Emma , Rattray Jayne E. , Sloan Kathryn , Sherry Angela , Pilloni Giovanni , Hubert Casey R. J. 
Published: October 2021

AbstractEndospores of thermophilic bacteria are widespread in cold seabed environments where they remain dormant during initial burial in accumulating sediments. The temperature increase during sedimentation can be simulated in experimental heating of sediments, resulting in the temperature-dependent activation of different endospore populations from the microbial seed bank. Here we investigated the response of endospore populations to heating at extreme high temperature (80– 99°C). Metabolites for germination and organic matter degradation (dipicolinic acid and organic acids) revealed both endospore germination and subsequent metabolism at ≥80°C. Endospore-forming Firmicutes with the genomic potential for organic carbon and nitrogen transformation were recovered by genome-resolved metagenomics. Genomes from Symbiobacteriales, Thermosediminibacteriales, Moorellales and Calditerricolales encode multiple mechanisms for high temperature degradation of sedimentary organic carbon and features of necromass that accumulate during sediment burial including saccharides, amino and nucleic acids. The results provide insight into the metabolism of novel carbon cycling microorganisms activated at high temperature, and suggest that extremely thermophilic Firmicutes dispersed in the ocean are poised to germinate in response to sediment heating during burial and transform a wide range of organic substrates.
Cell Adhesion-Dependent Biphasic Axon Outgrowth Elucidated by Femtosecond Laser Impulse
Authors: Yamada Sohei , Baba Kentarou , Inagaki Naoyuki , Hosokawa Yoichiroh 
Published: October 2021

AbstractAxon outgrowth is promoted by the mechanical coupling between F-actin and adhesive substrates via clutch and adhesion molecules in an axonal growth cone. In this study, we utilized a femtosecond laser-induced impulse to break the coupling between the growth cone and the substrate, enabling us to evaluate the strength of the binding between the growth cone and a laminin on the substrate, and also determine the contribution of adhesion strength to axon outgrowth and traction force for the outgrowth. We found that the adhesion strength of axonal L1 cell adhesion molecule (L1CAM)-laminin binding increased with the laminin density on the substrate. In addition, fluorescent speckle microscopy revealed that the retrograde flow of F-actin in the growth cone was dependent on the laminin density such that the flow speed reduced with increasing L1CAM-laminin binding. However, axon outgrowth and the traction force did not increase monotonically with increased L1CAM-laminin binding but rather exhibited biphasic behavior, in which the outgrowth was suppressed by excessive L1CAM-laminin binding. Our quantitative evaluations suggest that the biphasic outgrowth is regulated by the balance between traction force and adhesion strength. These results imply that adhesion modulation is key to the regulation of axon guidance.
The effect of audit fees, audit quality and board ownership on tax aggressiveness: evidence from Thailand
Authors: Madah Marzuki Marziana , Muhammad Al-Amin Muhammad Syukur 
Published: October 2021

PurposeThe purpose of this study is to investigate the effect of audit fees, auditors' quality and board ownership on tax aggressiveness in Thailand.Design/methodology/approachThe sample of this study is based on 215 firm-year observations of SET-100 listed companies in Thailand during the 2010–2018 periods. This study employs a panel least square regression with period fixed effects. The study retrieved the corporate governance variables from the downloaded annual reports, whilst the remaining data were collected from the EMIS database.FindingsThis study provides evidence that audit fees reduce tax aggressiveness and board ownership enhance tax aggressiveness among the firms. Nonaudit services provided by auditors impair auditors' independence and lead to higher tax aggressiveness. The result supports the agency theory, which explains that managers and blockholders may enjoy private benefits of control at the expense of other shareholders in the absence of market control. Thus, firms need good governance practices such as incentives paid for the effort of auditors and nonaudit services monitoring to curb such exploitation.Research limitations/implicationsThe results provide implications to the firms and regulators that incentives to the monitoring parties such as auditors can reduce tax aggressiveness among the firms. Nevertheless, higher ownership given to boards as incentives may lead to concentrated ownership and thus lead to the type 2 agency problem, which is between majority and minority shareholders. The result also provides caution to the regulators to monitor the nonaudit services provided by the auditors as it might impair their independence and compromise the tax paid to IRB.Originality/valueThis study is pioneer research discussing tax avoidance in Thailand. The Thai Government has been noticing that tax avoidance is being performed in the country, but academic discussion on this topic had never been elaborated.
Systems approach to cloud computing adoption in an emerging economy
Authors: Sharma Mahak , Gupta Ruchita , Acharya Padmanav , Jain Karuna 
Published: October 2021

PurposeCloud computing (CC) services have given a tremendous boost to the creation of efficient and effective solutions. With developing countries at a slow pace of adoption, this research aims to identify factors and their interrelationships influencing the adoption of CC in a developing country context. The developing countries are enjoying numerous benefits from CC services; however, its low adoption is still a question in developing economies; hence, the authors have selected the context of information and communication technology (ICT) firms in India.Design/methodology/approachThe qualitative research method is used where experts from thirteen ICT firms in India are interviewed.FindingsSixteen factors, twenty-eight subfactors, and 25 interrelationships are revealed through content analysis. Further, causal loop diagrams are proposed to display the behavior of cause and effect of these factors from a system's perspective. This will help to understand the relationships among the factors in order to enhance the speed of CC adoption. Possible financial loss and resistance to change are found as the key barriers to adoption. The proposed interrelationships can guide both policymakers and service providers for designing effective CC policies.Originality/valueThis is the first scholarly work that identifies interrelationships among factors and subfactors, thereby providing a holistic picture to decision-makers while making a choice on whether to adopt cloud services or continue with on premise data centers and servers.
Corrosion-induced degradation assessment of steel beam using vibration-based scheme
Authors: Paral Animesh , Samanta Amiya Kumar , Shandilya Amarendra Nath 
Published: October 2021

PurposeCatastrophe of steel-structured bridges due to progressive localized corrosion may lead to a major loss in terms of life and cost if not monitored continuously or periodically. The purpose of this paper is to present a vibration-based strategy to assess the severity and monitor the deterioration caused by corrosion-induced localized damage in a simply-supported steel beam.Design/methodology/approachThe threshold damage level is defined up to the yield limit of a simply supported steel beam of size ISMB 150 × 8 × 5 under three-point bending test and the progressive damage is induced through a continuous accelerated corrosion test. Change in the fundamental natural frequency due to localized damage in the experimental beam and the modulus of elasticity (E) in the corroded zone of an updated finite element (FE) model is evaluated.FindingsThe updated FE model of the damaged beam shows a clear trend with the progressive damage of the beam and, hence, can be used to monitor the severity of damage and remaining capacity assessment of the monitored beam.Originality/valueSteel-structured bridges are prone to localized corrosion attack, and there are no standardized process or predictive model available by international steel design codes on how to consider corrosion damage in the condition assessment analysis. The vibration-based methods have gained popularity for condition assessment, and are mostly confined to damage assessment of corroded reinforced concrete (RC) beams. In this work, a vibration-based approach is presented for degradation assessment of steel beam due to progressive localized corrosion using modal hammer test.
Digital transformation to mitigate emergency situations: increasing opioid overdose survival rates through explainable artificial intelligence
Authors: Johnson Marina , Albizri Abdullah , Harfouche Antoine , Tutun Salih 
Published: October 2021

PurposeThe global health crisis represents an unprecedented opportunity for the development of artificial intelligence (AI) solutions. This paper aims to integrate explainable AI into the decision-making process in emergency scenarios to help mitigate the high levels of complexity and uncertainty associated with these situations. An AI solution is designed to extract insights into opioid overdose (OD) that can help government agencies to improve their medical emergency response and reduce opioid-related deaths.Design/methodology/approachThis paper employs the design science research paradigm as an overarching framework. Open-access digital data and AI, two essential components within the digital transformation domain, are used to accurately predict OD survival rates.FindingsThe proposed AI solution has two primary implications for the advancement of informed emergency management. Results show that it can help not only local agencies plan their resources for timely response to OD incidents, thus improving survival rates, but also governments to identify geographical areas with lower survival rates and their primary contributing factor; hence, they can plan and allocate long-term resources to increase survival rates and help in developing effective emergency-related policies.Originality/valueThis paper illustrates that digital transformation, particularly open-access digital data and AI, can improve the emergency management framework (EMF). It also demonstrates that the AI models developed in this study can identify opioid OD trends and determine the significant factors improving survival rates.
The impact of institutional ownership on the value relevance of accounting information: evidence from Egypt
Authors: Diab Ahmed , Abdelazim Samir Ibrahim , Metwally Abdelmoneim Bahyeldin Mohamed 
Published: October 2021

Purpose
This paper aims to examine the value relevance (VR) of accounting information (AI) presented by Egyptian listed non-financial companies. Further, the study investigates the influence of institutional ownership on the value relevance of AI in a developing market, namely, the Egyptian market.

Design/methodology/approach
The study uses data from 2014 to 2017 with a total of 248 observations and analyses the data using regression analysis. Data are collected from the nonfinancial companies listed on the Egyptian Stock Exchange.

Findings
The authors found that the AI reported by the Egyptian listed non-financial companies is value relevant. Regarding the influence of institutional ownership, it is found to significantly impact the VR of AI reported by the sample companies. This model investigated the effect of corporate size and financial leverage as controlling variables and found that they have an insignificant influence on the VR of AI.

Originality/value
The current study findings enrich the literature by enhancing the understanding regarding institutional owners’ impact on corporate value. Further, bringing evidence from an emerging market can have implications for accounting researchers interested in addressing other emerging markets with similar contextual and institutional environments.
Dynamics between trade openness, FDI and economic growth: evidence from an emerging economy
Authors: Rakshit Bijoy 
Published: October 2021

PurposeThis paper aims to examine the dynamics between trade openness, foreign direct investment (FDI) and economic growth in India over the period 1979 to 2017. This study further considers the role of pre and post-economic reforms in the analysis of these dynamics.Design/methodology/approachThe authors apply the autoregressive distributed lag model to investigate the possible long-run associations among the variables. Zivot-Andrew unit root test was applied to detect the structural breaks present in the data series. Toda-Yamamoto causality approach has been applied to examine the direction of causality among the variables.FindingsFindings show that trade openness exerts a negative impact on economic growth in the long-run. Although FDI inflow promotes economic growth in the long-run, FDI inflow does not seem to affect growth in the short-run. As far as causality analysis is concerned, findings confirm a unidirectional causality is flowing from FDI inflow and labour force to per capita gross domestic product growth in India.Practical implicationsThe negative impact of trade openness on growth suggests that policymakers should implement more export-oriented policies to boost economic growth in the long-run. The ratio of exports to the total volume of trade has not increased satisfactorily over the years. Additionally, appropriate policies should aim at extracting the benefits of FDI inflow in the long-run.Originality/valueAlthough several theoretical and empirical literature has investigated the nexus between FDI (or trade) and growth, this study, as a fresh attempt, investigates the long-run dynamics between trade openness, FDI, capital formation, labour force and economic growth in India.
Measuring robustness: sustainable success factors affecting professional football clubs
Authors: Cruz Jacqueline Marie , Schregel Johannes Philipp , Zülch Henning 
Published: October 2021

PurposeMany factors influence success at a professional football club, as each club has an exclusive definition and interpretation of success. Using the Football Management Q-Score as a foundation, the authors set out to prove the framework's robustness in the industry's current environment.Design/methodology/approachTo determine the purpose, the authors conducted interviews with Bundesliga experts. Using the Gioia Method, the authors could condense interview feedback into aggregate themes reflecting the main findings of the analysis process.FindingsFrom 1,025 codes, three main contributions resulted – the concept of intercorrelation, a more balanced and dynamic framework, and four new key drivers.Originality/valueExpert feedback validated the framework as robust, and the further main contributions gave the framework a wider application to a larger range of clubs, allowing the users of the framework to infer a greater context. Interview results proved the inclusion of Kaplan and Norton's original framework with vision and strategy.
Prognostic impact of immune inflammation biomarkers in predicting survival and radiosensitivity in patients with non‐small‐cell lung cancer treated with chemoradiotherapy
Authors: Delikgoz Soykut Ela , Kemal Yasemin , Karacin Cengiz , Karaoglanoglu Ozden , Kurt Mumin , Aytac Arslan Suheyla 
Published: October 2021

AbstractIntroductionThe purpose of this retrospective study was to investigate the prognostic impact of neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR), derived NLR (dNLR) and systemic immune‐inflammation index (SII) in predicting outcomes for patients with locally advanced non‐small‐cell lung cancer (NSCLC). The secondary endpoint was to evaluate the radiosensitivity in terms of response rate.MethodsNewly diagnosed locally advanced NSCLC patients were enrolled. Immune inflammation biomarkers were calculated from baseline blood samples. Patients were stratified in two groups based on optimal cut‐off values for each biomarker. The associations between biomarkers and overall survival (OS), progression‐free survival (PFS), local regional recurrence‐free survival (LRRFS), and also response to radiotherapy were analysed.ResultsA total of 392 patients were included. Five‐year OS, PFS and LRRFS rates were 14.6%, 12.1%, and 13.4% respectively. Optimal cut‐off values for NLR, PLR, dNLR and SII were 3.07, 166, 2.02 and 817 respectively. Low NLR (HR 1.73, 95% CI 1.34–2.24, P < 0.001), low PLR (HR 1.37, 95% CI 1.06–1.76, P = 0.013), low dNLR (HR 1.66, 95% CI 1.29–2.13, P < 0.001) and low SII (HR 1.63, 95% CI 1.18–2.04, P < 0.001) were independent prognostic factors for OS. Low NLR, PLR, dNLR and SII were also significant prognostic factors for PFS and LRRFS. Low NLR, low dNLR and low SII groups had better radiosensitivity than compared with high NLR, high dNLR and high SII groups (P = 0.001, P = 0.001 and P = 0.012).ConclusionNLR, PLR, dNLR and SII were independently associated with improved OS, PFS and LRRFS. Low NLR, dNLR and SII groups had better radiosensitivity. Immune inflammation biomarkers are promising prognostic predictors which can be obtained easily and inexpensively.
Behavioral Economics of Accounting: A Review of Archival Research on Individual Decision Makers*
Authors: Hanlon Michelle , Yeung Kelvin , Zuo Luo 
Published: October 2021

ABSTRACTThis paper develops a unified framework to synthesize the growing stream of positive research on the role of individual decision makers in shaping observed accounting phenomena. This line of research recognizes two central ideas in behavioral economics. First, individual behavior depends not only on economic incentives and accessible information but also on individual preferences, abilities, experiences, and other characteristics. Second, the constraints that structure human interactions encompass both formal institutions (e.g., rules, laws, constitutions) and informal institutions (e.g., norms, conventions, rituals). Our review covers a broad set of individuals who are of interest in accounting research: managers, directors, audit partners, analysts, standard setters, politicians, judges, journalists, loan officers, financial advisors, and investors. We aim to understand the systematic effects of individual characteristics on a wide spectrum of accounting phenomena, including financial reporting, disclosure, tax planning, auditing, and corporate social responsibility. We highlight the importance of personal characteristics not only for an individual's own behavior but also for others' perceptions. Our review mainly focuses on archival research in accounting and provides some thoughts about opportunities for archival empiricists going forward. We also, when feasible, highlight opportunities for future field, survey, and experimental research. A central takeaway from our review is that individual‐level factors significantly improve our ability to explain and predict accounting phenomena beyond firm‐, industry‐, and market‐level factors.