bluuebunny/crossref_metadata_2025_split huggingface dataset:
How media coverage of corporate social responsibility and irresponsibility influences cross‐border acquisitions
Authors: Hawn Olga 
Published: June 2020

AbstractResearch SummaryThis study contributes to the growing strategic corporate social responsibility (CSR) literature by examining the intersection of acquisition studies and international expansion research and highlighting the unexplored impact of media coverage of CSR and corporate social irresponsibility (CSI) in shaping completion and duration outcomes of cross‐border acquisitions. A quantitative analysis of 4,087 cross‐border acquisition announcements by firms from Brazil, Russia, India, China, and South Africa (1990–2011) shows that while media coverage of CSR is not important, media coverage of CSI is associated with lower likelihood of and longer duration till acquisition completion. By theoretically and empirically distinguishing media coverage of CSR from CSI, this paper pushes the existing literature to acknowledge these distinct concepts and their varying effects. In sum, managers should beware media coverage of CSI when acquiring abroad.Managerial SummaryCross‐border acquisitions by firms from emerging markets often do not reach completion or are badly delayed, damaging the firms' attempts to expand. A key barrier to completing deals is that employees, customers, regulators, media, and other stakeholders in the target market are suspicious of these firms, fearing that they will be poor corporate citizens. I examine whether media coverage of acquirers' social activities helps overcome these suspicions. I find that media coverage of socially responsible activities does not facilitate deal completion. Strikingly, however, media coverage of irresponsible actions, such as labor or environmental issues, delays or blocks deal completion. The implication is that firms from emerging markets, which increasingly are expanding abroad, need to avoid activities that people outside their country will interpret as inappropriate.
Coronavirus and international business: An entrepreneurial ecosystem perspective
Authors: Ratten Vanessa 
Published: June 2020

AbstractCovid‐19 (Coronavirus) is a health pandemic that has significantly affected the global economy and fundamentally changed society. The impacts of coronavirus are most apparent at the international business level due to the restrictions on travel and mobility of labor. This has necessitated an entrepreneurial outlook for businesses in order to survive in the current market environment. The aim of this article is to discuss the implications of the coronavirus for international business by taking an entrepreneurial ecosystem point of view. This enables a reflection on how the pandemic has impacted various entities of the ecosystem in terms of stakeholder engagement. Suggestions for acting in a more dynamic and innovative manner are provided that highlight the importance of utilizing entrepreneurial ecosystems in times of crises.
The study of questions
Authors: Moyer Morgan C. , Syrett Kristen 
Published: June 2020

AbstractAsking questions is a fundamental aspect of human nature. Languages all around the world encode interrogative constructions. It is therefore incumbent upon semanticists to capture the meaning of questions. However, achieving this goal faces a challenge under a truth conditional approach to meaning, since questions cannot easily be assigned a truth value. Moreover, it is not sufficient to focus only on the questions themselves; one must also determine what counts as a felicitous and informative answer, and how this relates to a speaker's intention in posing a question in a discourse context. How then do semanticists approach an investigation of questions? In this article, we present the core issues inherent to question‐answer dynamics, review the main approaches to question‐answer meaning, highlight how questions are situated in a discourse context, and explore extensions of questions that highlight the connection between semantics, pragmatics, and human reasoning.This article is categorized under:Linguistics > Linguistic Theory
Aggregating predictions from experts: A review of statistical methods, experiments, and applications
Authors: McAndrew Thomas , Wattanachit Nutcha , Gibson Graham C. , Reich Nicholas G. 
Published: June 2020

AbstractForecasts support decision making in a variety of applications. Statistical models can produce accurate forecasts given abundant training data, but when data is sparse or rapidly changing, statistical models may not be able to make accurate predictions. Expert judgmental forecasts—models that combine expert‐generated predictions into a single forecast—can make predictions when training data is limited by relying on human intuition. Researchers have proposed a wide array of algorithms to combine expert predictions into a single forecast, but there is no consensus on an optimal aggregation model. This review surveyed recent literature on aggregating expert‐elicited predictions. We gathered common terminology, aggregation methods, and forecasting performance metrics, and offer guidance to strengthen future work that is growing at an accelerated pace.This article is categorized under:Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and ClassificationStatistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data AnalysisStatistical Learning and Exploratory Methods of the Data Sciences > Modeling MethodsStatistical and Graphical Methods of Data Analysis > Multivariate Analysis
Spiritual Capital: A Framework for Spirituality‐Infused Leadership Education and Organizational Spirituality
Authors: Noghiu Alain Adrian 
Published: June 2020

AbstractThis chapter introduces the spiritual capital discourse and spiritual capital theory (SCT). By extending the leadership‐spirituality intersect with the notion of “capital,” it confirms the value proposition of spirituality for leadership development and extends the discourse to include “structure,” an aspect with which leadership theory struggles.
Spirituality and Leadership: Research Supports the Connection
Authors: Komives Susan R. , Mackie Michele Matteo , Shalka Tricia R. , Smith Meredith 
Published: June 2020

AbstractResearch demonstrates the consistent and significant positive connection between spirituality and leadership. The concluding chapter focuses on studies of the social change model of leadership development and select spirituality scales from the University of California, Los Angeles Higher Education Research Institute's spirituality project.
Characterization of metal oxide gas sensors via optical techniques
Authors: Glöckler Johannes , Jaeschke Carsten , Tütüncü Erhan , Kokoric Vjekoslav , Kocaöz Yusuf , Mizaikoff Boris 
Published: June 2020

AbstractMetal oxide (MOX) sensors are increasingly gaining attention in analytical applications. Their fundamental operation principle is based on conversion reactions of selected molecular species at their semiconducting surface. However, the exact turnover of analyte gas in relation to the concentration has not been investigated in detail to date. In the present study, two optical sensing techniques—luminescence quenching for molecular oxygen and infrared spectroscopy for carbon dioxide and methane—have been coupled for characterizing the behavior of an example semiconducting MOX methane gas sensor integrated into a recently developed low-volume gas cell. Thereby, oxygen consumption during MOX operation as well as the generation of carbon dioxide from the methane conversion reaction could be quantitatively monitored. The latter was analyzed via a direct mid-infrared gas sensor system based on substrate-integrated hollow waveguide (iHWG) technology combined with a portable Fourier transform infrared spectrometer, which has been able to not only detect the amount of generated carbon dioxide but also the consumption of methane during MOX operation. Hence, a method based entirely on direct optical detection schemes was developed for characterizing the actual signal generating processes—here for the detection of methane—via MOX sensing devices via near real-time online analysis.
Adverse intraoperative events during surgical repair of ruptured cerebral aneurysms: a systematic review
Authors: Muirhead William R. , Grover Patrick J. , Toma Ahmed K. , Stoyanov Danail , Marcus Hani J. , Murphy Mary 
Published: June 2020

AbstractCompared with endovascular techniques, clipping of ruptured cerebral aneurysms has been shown to associate with increased morbidity in several studies. Despite this, clipping remains the preferred option for many aneurysms. The objective of this study is to describe the reported adverse events of open repair of ruptured cerebral aneurysms and their impact on patient outcome. The PubMed, Embase and Cochrane databases were searched between June 1999 and June 2019 to identify original studies of at least 100 patients undergoing surgical repair of ruptured cerebral aneurysms and in which adverse event rates were reported. Thirty-six studies reporting adverse events in a total of 12,410 operations for repair of ruptured cerebral aneurysms were included. Surgical adverse events were common with 36 event types reported including intraoperative rupture (median rate of 16.6%), arterial injury (median rate of 3.8%) and brain swelling (median rate 5.6%). Only 6 surgical events were statistically shown to associate with poor outcomes by any author and for intraoperative rupture (the most frequently analysed), there was an even split between authors finding a statistical association with poor outcome and those finding no association. Even with modern surgical techniques, the technical demands of surgical aneurysm repair continue to lead to a high rate of intraoperative adverse events. Despite this, it is not known which of these intraoperative events are the most important contributors to the poor outcomes often seen in these patients. More research directed towards identifying the events that most drive operative morbidity has the potential to improve outcomes for these patients.
TEASER: early and accurate time series classification
Authors: Schäfer Patrick , Leser Ulf 
Published: June 2020

AbstractEarly time series classification (eTSC) is the problem of classifying a time series after as few measurements as possible with the highest possible accuracy. The most critical issue of any eTSC method is to decide when enough data of a time series has been seen to take a decision: Waiting for more data points usually makes the classification problem easier but delays the time in which a classification is made; in contrast, earlier classification has to cope with less input data, often leading to inferior accuracy. The state-of-the-art eTSC methods compute a fixed optimal decision time assuming that every times series has the same defined start time (like turning on a machine). However, in many real-life applications measurements start at arbitrary times (like measuring heartbeats of a patient), implying that the best time for taking a decision varies widely between time series. We present TEASER, a novel algorithm that models eTSC as a two-tier classification problem: In the first tier, a classifier periodically assesses the incoming time series to compute class probabilities. However, these class probabilities are only used as output label if a second-tier classifier decides that the predicted label is reliable enough, which can happen after a different number of measurements. In an evaluation using 45 benchmark datasets, TEASER is two to three times earlier at predictions than its competitors while reaching the same or an even higher classification accuracy. We further show TEASER’s superior performance using real-life use cases, namely energy monitoring, and gait detection.
Two Polynomial Time Graph Labeling Algorithms Optimizing Max-Norm-Based Objective Functions
Authors: Malmberg Filip , Ciesielski Krzysztof Chris 
Published: June 2020

AbstractMany problems in applied computer science can be expressed in a graph setting and solved by finding an appropriate vertex labeling of the associated graph. It is also common to identify the term “appropriate labeling” with a labeling that optimizes some application-motivated objective function. The goal of this work is to present two algorithms that, for the objective functions in a general format motivated by image processing tasks, find such optimal labelings. Specifically, we consider a problem of finding an optimal binary labeling for the objective function defined as the max-norm over a set of local costs of a form that naturally appears in image processing. It is well known that for a limited subclass of such problems, globally optimal solutions can be found via watershed cuts, that is, by the cuts associated with the optimal spanning forests of a graph. Here, we propose two new algorithms for optimizing a broader class of such problems. The first algorithm, that works for all considered objective functions, returns a globally optimal labeling in quadratic time with respect to the size of the graph (i.e., the number of its vertices and edges) or, for an image associated graph, the size of the image. The second algorithm is more efficient, with quasi-linear time complexity, and returns a globally optimal labeling provided that the objective function satisfies certain given conditions. These conditions are analogous to the submodularity conditions encountered in max-flow/min-cut optimization, where the objective function is defined as sum of all local costs. We will also consider a refinement of the max-norm measure, defined in terms of the lexicographical order, and examine the algorithms that could find minimal labelings with respect to this refined measure.
Roads to Necessitarianism
Authors: Mandelkern Matthew , Rothschild Daniel 
Published: June 2020

AbstractWe show that each of three natural sets of assumptions about the conditional entails necessitarianism: that anything possible is necessary. Since most agree that this conclusion is obviously false, this shows that at least one member of each set of assumptions must be rejected. All of these assumptions are, however, widely accepted and well-motivated. This creates a puzzle which we leave open.
On the Torsion Function with Mixed Boundary Conditions
Authors: Berg M. van den , Carroll Tom 
Published: June 2020

AbstractLet D be a non-empty open subset of $\mathbb {R}^{m}, m\ge 2$

ℝ

m

,
m
≥
2
, with boundary ∂D, with finite Lebesgue measure |D|, and which satisfies a parabolic Harnack principle. Let K be a compact, non-polar subset of D. We obtain the leading asymptotic behaviour as ε↓ 0 of the $L^{\infty }$

L

∞

norm of the torsion function with a Neumann boundary condition on ∂D, and a Dirichlet boundary condition on ∂(εK), in terms of the first eigenvalue of the Laplacian with corresponding boundary conditions. These estimates quantify those of Burdzy, Chen and Marshall who showed that D ∖ K is a non-trap domain.
The Honeybee Venom Major Allergen Api m 10 (Icarapin) and Its Role in Diagnostics and Treatment of Hymenoptera Venom Allergy
Authors: Jakob Thilo , Rauber Michèle Myriam , Perez-Riverol Amilcar , Spillner Edzard , Blank Simon 
Published: June 2020

Abstract
Purpose of Review
In Hymenoptera venom allergy, the research focus has moved from whole venoms to individual allergenic molecules. Api m 10 (icarapin) has been described as a major allergen of honeybee venom (HBV) with potentially high relevance for diagnostics and therapy of venom allergy. Here, we review recent studies on Api m 10 characteristics as well as its role in component-resolved diagnostics and potential implications for venom-specific immunotherapy (VIT).

Recent Findings
Api m 10 is a major allergen of low abundance in HBV. It is an obviously unstable protein of unknown function that exhibits homologs in other insect species. Despite its low abundance in HBV, 35 to 72% of HBV-allergic patients show relevant sensitization to this allergen. Api m 10 is a marker allergen for HBV sensitization, which in many cases can help to identify primary sensitization to HBV and, hence, to discriminate between genuine sensitization and cross-reactivity. Moreover, Api m 10 might support personalized risk stratification in VIT, as dominant sensitization to Api m 10 has been identified as risk factor for treatment failure. This might be of particular importance since Api m 10 is strongly underrepresented in some therapeutic preparations commonly used for VIT.

Summary
Although the role of Api m 10 in HBV allergy and tolerance induction during VIT is not fully understood, it certainly is a useful tool to unravel primary sensitization and individual sensitization profiles in component-resolved diagnostics (CRD). Moreover, a potential of Api m 10 to contribute to personalized treatment strategies in HBV allergy is emerging.
Deep Learning for Cardiovascular Risk Stratification
Authors: Schlesinger Daphne E. , Stultz Collin M. 
Published: June 2020

Abstract
Purpose of review
Although deep learning represents an exciting platform for the development of risk stratification models, it is challenging to evaluate these models beyond simple statistical measures of success, which do not always provide insight into a model’s clinical utility. Here we propose a framework for evaluating deep learning models and discuss a number of interesting applications in light of these rubrics.

Recent findings
Data scientists and clinicians alike have applied a variety of deep learning techniques to both medical images and structured electronic medical record data. In many cases, these methods have resulted in risk stratification models that have improved discriminatory ability relative to more straightforward methods. Nevertheless, in many instances, it remains unclear how useful the resulting models are to practicing clinicians.

Summary
To be useful, deep learning models for cardiovascular risk stratification must not only be accurate but they must also provide insight into when they are likely to yield inaccurate results and be explainable in the sense that health care providers can understand why the model arrives at a particular result. These additional criteria help to ensure that the model can be faithfully applied to the demographic for which it is most accurate.
Preisaufschläge für die sportliche Relevanz
Authors: Woratschek Herbert , Kaiser Mario , Durchholz Christian , Ströbel Tim 
Published: June 2020

ZusammenfassungFür die Finanzierung von Sportevents ist das Ticketing eine zentrale Einnahmequelle. Es liegen in diesem Bereich jedoch weder in Praxis noch Forschung valide Erfahrungsdaten vor. Der vorliegende Beitrag greift diese Forschungslücke auf und identifiziert die Bereitschaft von Sporteventzuschauern für Preisaufschläge (bzw. -abschläge) im Rahmen von Wettbewerben mit unterschiedlicher sportlicher Relevanz in unterschiedlichen Sitzkategorien am Beispiel des Frauenfußballs. Der Beitrag zeigt auf, dass die Conjoint-Analyse eine geeignete Methode ist, um Preisbereitschaften für Sportevents in Abhängigkeit ihrer sportlichen Relevanz zu schätzen, insbesondere für Sportevents für die bislang noch keine Erfahrungswerte aus der Vergangenheit vorliegen. Auf Basis einer Befragung von 278 Stadionbesuchern eines Spiels der deutschen Frauen Fußball-Nationalmannschaft zeigt sich, dass die Präferenzen der Zuschauer sehr unterschiedlich sind. Für die Hälfte der Probanden ist die sportliche Relevanz des Wettbewerbs der dominierende Einflussfaktor auf die Preisbereitschaft. Diese sind bereit, einen hohen Preisaufschlag für sportlich relevante Wettbewerbe in Kauf zu nehmen. Die Ergebnisse helfen Sportmanagern, ihre Preisstrategien zu optimieren und gleichzeitig an den Präferenzen und Preisbereitschaften der Zuschauer auszurichten.
The “Three Italy” of the COVID-19 epidemic and the possible involvement of SARS-CoV-2 in triggering complications other than pneumonia
Authors: Prezioso Carla , Marcocci Maria Elena , Palamara Anna Teresa , De Chiara Giovanna , Pietropaolo Valeria 
Published: June 2020

AbstractCoronavirus disease 2019 (COVID-19), first reported in Wuhan, the capital of Hubei, China, has been associated to a novel coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In March 2020, the World Health Organization declared the SARS-CoV-2 infection a global pandemic. Soon after, the number of cases soared dramatically, spreading across China and worldwide. Italy has had 12,462 confirmed cases according to the Italian National Institute of Health (ISS) as of March 11, and after the “lockdown” of the entire territory, by May 4, 209,254 cases of COVID-19 and 26,892 associated deaths have been reported. We performed a review to describe, in particular, the origin and the diffusion of COVID-19 in Italy, underlying how the geographical circulation has been heterogeneous and the importance of pathophysiology in the involvement of cardiovascular and neurological clinical manifestations.
Two-scale coupling for preconditioned Hamiltonian Monte Carlo in infinite dimensions
Authors: Bou-Rabee Nawaf , Eberle Andreas 
Published: June 2020

AbstractWe derive non-asymptotic quantitative bounds for convergence to equilibrium of the exact preconditioned Hamiltonian Monte Carlo algorithm (pHMC) on a Hilbert space. As a consequence, explicit and dimension-free bounds for pHMC applied to high-dimensional distributions arising in transition path sampling and path integral molecular dynamics are given. Global convexity of the underlying potential energies is not required. Our results are based on a two-scale coupling which is contractive in a carefully designed distance.
A numerical model for simulating the effect of strain rate on eutectic band thickness
Authors: Draxler J. , Åkerström P. , Edberg J. , Lindgren L.-E. , Singh S. , Raza T. , Andersson J. 
Published: June 2020

AbstractLarge tensile strains acting on the solidifying weld metal can cause the formation of eutectic bands along grain boundaries. These eutectic bands can lead to severe liquation in the partially melted zone of a subsequent overlapping weld. This can increase the risk of heat-affected zone liquation cracking. In this paper, we present a solidification model for modeling eutectic bands. The model is based on solute convection in grain boundary liquid films induced by tensile strains. The proposed model was used to study the influence of strain rate on the thickness of eutectic bands in Alloy 718. It was found that when the magnitude of the strain rate is 10 times larger than that of the solidification rate, the calculated eutectic band thickness is about 200 to 500% larger (depending on the solidification rate) as compared to when the strain rate is zero. In the paper, we also discuss how eutectic bands may form from hot cracks.