julilili42/papers huggingface dataset:
Understanding the Aftermath of Unethical Behavior: Theoretical and Empirical Advances
2020-07-29

High profile scandals (e.g., Johnson & Johnson, Boeing, Wells Fargo, Volkswagen) have put a spotlight on unethical behavior in organizations. Not surprisingly, scholarly interest on behavioral ethics has also risen in hopes of explaining and identifying causes and consequences of unethical behavior in organizations. Although the literature has revealed quite a bit as to why unethical behavior occurs, a growing sentiment in the literature and significant implication from narrative reviews is that far more research is needed to understand the aftermath of unethical behavior — the consequences to the larger social environment, as well as for the actors themselves. This symposium addresses this research agenda by (1) examining different qualities of unethical behaviors (i.e., cheating, moral distress, pro–group/organization/coworker unethical behavior); identifying (2) psychological (i.e., trust, indebtedness, shared accountability, shared responsibility), (3) affective (i.e., shame), and (4) behavioral mechanisms (i.e., complicity, defiance, self–protective, strategic) that explain consequences of unethical behavior; and (5) highlighting moderators (i.e., collectivism vs. individualism, organizational identity) that influences the nature of the consequences of unethical behavior.
Sustainability in Management Education: Where It Has Been, Is Now, and Is/Can Be Headed
2020-07-29

This 2020 Academy of Management Symposium (AoM) intends to build on our understanding of, and advance the progress that has been made in, incorporating Sustainability in Management Education (SiME), over the past three decades. To accomplish this, we have assembled a dynamic team of multidisciplinary academics, scholars and leaders who are shaping a story of sustainability within their institutions, classrooms, and communities. These academics have been invited to present on their current research as their work extends a variety of stakeholders’ perceptions examining the topic of SiME metrics and assessment. They represent different demographics, a variety of collaborative research efforts, and membership to different AOM divisions. Together, these presentations will make an attempt to: a) advance a greater understanding of the range and extent of SiME teaching practices, including evidence of effective methods and techniques, b) provide a discussion on reported challenges in course and program design and integration, and c) share research on business students experience with SiME and the professionalization of the field and its reported impacts. We aim to facilitate an invigorating and interactive learning experience and exchange for those interested in SiME integration at multiple interfaces. Civic Responsibility in Higher Education – Are Socially-Engaged Students Any Different from Others? Presenter: Michael Wihlenda; Global Ethic Institute Presenter: Taiga Brahm; U. of Tuebingen Teaching Strong Sustainability: An Experiential Course on Leadership in the Anthropocene Presenter: Rae Andre; Northeastern U. Designing Effective Sustainability Assignments: How and Why Definitions of Sustainability Impact Presenter: Matthew Urdan; PhD Student Presenter: Patrice Luoma; Quinnipiac U. Sustainability in Management Education: Theoretical Lenses and Research Discourses Presenter: Shelley F. Mitchell; Hult International Business School Presenter: Jorge Alexis Arevalo; William Paterson U. We Academics Should Walk Our Sustainability Talk Presenter: Patricia Kanashiro; Loyola U. Maryland Presenter: Gordon P. Rands; Western Illinois U. Presenter: Mark Starik; Walden U.
Contextualizing Unethical Prosocial Behaviors from Relational Perspectives
2020-07-29

A burgeoning literature examines a fairly recent area of research - unethical pro-social behavior (UPB), that is, unethical behavior motivated by the desire to benefit other individuals or entities (e.g., group, organization) (Chen, Chen, & Sheldon, 2016; Umpress & Bingham, 2011; Umpress, Bingham & Mitchell, 2010) - has drawn the attention of scholars to a number of important antecedents, such as organizational culture, organizational norms, and leader behavior. This symposium is designed to further the field’s knowledge in this realm by examining UPB from various relational perspectives. The four papers included in the symposium shed novel light on UPB as a relational phenomenon by using a variety of research designs, study populations, and methods. Taken together, our symposium highlights relational contexts, intermediary mechanisms, and outcomes of UPB. Systematic Injustice and Preference for Unethical and Ethical Leaders Presenter: Carolyn Thi Dang; Pennsylvania State U. Presenter: Elizabeth Eve Umphress; U. of Washington Felt Obligation as a Driver of Immoral Decisions in Triadic Social Exchanges Presenter: Liuba Belkin; Lehigh U. Presenter: Dejun Kong; U. of South Florida Does Justice Make Us More or Less Ethical? How Fair Treatment Can Lead to Unethical Behavior Presenter: Oliver Sheldon; Rutgers U. Presenter: Batia Mishan Wiesenfeld; New York U. Weighing Commitment and Liability in the Selection of Rule Breakers Presenter: S Wiley Wakeman; Stockholm School of Economics Presenter: Philip Yang; U. of Tuebingen
Corrigendum: Every-Other-Day Feeding Decreases Glycolytic and Mitochondrial Energy-Producing Potentials in the Brain and Liver of Young Mice
2020-07-29

In the original article, there was a mistake in Figure 6 as published. The incorrect data on the level of ketone bodies in the liver and the cortex ofmice fed ad libitum(control) or subjected to an every- other-day feeding regimen (EODF) over 1month were placed instead of the corresponding data on b-hydroxybutyrate dehydrogenase activity. The corrected Figure 6 and the legend appear below. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Pairing Bacteroides vulgatus LPS Structure with Its Immunomodulatory Effects on Human Cellular Models
2020-07-30

The gut microbiota guide the development of the host immune system by setting a systemic threshold for immune activation. Lipopolysaccharides (LPSs) from gut bacteria are able to trigger systemic and local proinflammatory and immunomodulatory responses, and this capability strongly relies on their fine structures. Up to now, only a few LPS structures from gut commensals have been elucidated; therefore, the molecular motifs that may be important for LPS-mammalian cell interactions at the gut level are still obscure. Here, we report on the full structure of the LPS isolated from one of the prominent species of the genus <i>Bacteroides</i>, <i>Bacteroides vulgatus</i>. The LPS turned out to consist of a particular chemical structure based on hypoacylated and <i>mono</i>-phosphorylated lipid A and with a galactofuranose-containing core oligosaccharide and an O-antigen built up of mannose and rhamnose. The evaluation of the immunological properties of this LPS on human <i>in vitro</i> models revealed a very interesting capability to produce anti-inflammatory cytokines and to induce a synergistic action of MD-2/TLR4- and TLR2-mediated signaling pathways.
Can we predict real‐time fMRI neurofeedback learning success from pretraining brain activity?
2020-07-30

Abstract Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
d-Amino Acids in Plants: Sources, Metabolism, and Functions
2020-07-30

Although plants are permanently exposed to d-amino acids (d-AAs) in the rhizosphere, these compounds were for a long time regarded as generally detrimental, due to their inhibitory effects on plant growth. Recent studies showed that this statement needs a critical revision. There were several reports of active uptake by and transport of d-AAs in plants, leading to the question whether these processes happened just as side reactions or even on purpose. The identification and characterization of various transporter proteins and enzymes in plants with considerable affinities or specificities for d-AAs also pointed in the direction of their targeted uptake and utilization. This attracted more interest, as d-AAs were shown to be involved in different physiological processes in plants. Especially, the recent characterization of d-AA stimulated ethylene production in Arabidopsis thaliana revealed for the first time a physiological function for a specific d-AA and its metabolizing enzyme in plants. This finding opened the question regarding the physiological or developmental contexts in which d-AA stimulated ethylene synthesis are involved in. This question and the ones about the transport characteristics of d-AAs, their metabolism, and their different physiological effects, are the focus of this review.
Frictional Segmentation of the Chilean Megathrust from a Multivariate Analysis of Geophysical, Geological and Geodetic Data
2020-07-30

Great subduction earthquakes rupture similar regions of the megathrust during successive events separated by centuries. Mapping these regions (asperities) and their boundaries (barriers) is important for our understanding of processes controlling megathrust segmentation and for seismic hazard assessment. We present a formal seismic segmentation model of the Chile Margin derived from a multivariate analysis of gravity anomalies, basal friction from critical taper and interplate locking from GPS velocities. These proxies integrate over timescales of 10 to 10 years and we analyze their combined spatial covariance using Principal Component Analysis (PCA), from which the Empirical Orthogonal Functions (EOFs) and Principal Components (PCs) are extracted. We find that the 1 and 1+2 PCA modes explain 44% and 67% of the total variance, respectively, suggesting a high degree of spatial correlation. Comparing our results with rupture areas of earthquakes and using the rate-and-state friction theory, we infer that trench-perpendicular PCs reflect the limits of the velocity-weakening (VW) seismogenic zone. Polarity changes in along-trench EOFs (mostly for gravity) are related to changes between unstable and conditionally-stable frictional regimes inside the VW zone and we used them to define the boundaries of 17 unitary segments. These segments correlate with first-order tectonic features of the Andes at >10-km scales as well as with zones of multi-segment ruptures at 10-km scale. We analyze the combined influence of subducting and upper-plate geologic features on the nature of persistent seismic barriers. Our results have implications for understanding seismotectonic processes along the Andean margin and elsewhere
Acupuncture for menopausal symptoms in Chinese women: a systematic review
2020-07-30

Menopause-related symptoms are common problems of middle-aged women that can seriously affect their quality of life. Menopausal hormone therapy (MHT) for climacteric symptoms is the first choice recommended by the International Menopause Society and likewise by other societies and institutions covering this field. However, non-hormonal therapies can be an alternative effective option, especially for women who are not suitable for MHT. Acupuncture is one of the most important methods. With deepening experience of the use of traditional Chinese acupuncture and moxibustion in the improvement of menopause symptoms, more clinical evidence has been obtained to support the effectiveness and safety of this treatment concept that is very often used in China. This review summarizes the evidence for effective treatment of climacteric complaints by acupuncture in recent years, shares the clinical experience of the authors of this review, all of whom head or work in units with daily large numbers of outpatients, and includes, in particular, results from studies performed in the Department of Acupuncture--Moxibustion of Tsinghua University Chuiyangliu Hospital, Beijing, China. In addition, there is a summary about the safety of acupuncture treatment in traditional Chinese medicine.
Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge
2020-07-30

Abstract Humans are highly attuned to patterns in the environment. This ability to detect environmental patterns, referred to as statistical learning, plays a key role in many diverse aspects of cognition. However, the spatiotemporal neural mechanisms underlying implicit statistical learning, and how these mechanisms may relate or give rise to explicit learning, remain poorly understood. In the present study, we investigated these different aspects of statistical learning by using an auditory nonlinguistic statistical learning paradigm combined with magnetoencephalography. Twenty-four healthy volunteers were exposed to structured and random tone sequences, and statistical learning was quantified by neural entrainment. Already early during exposure, participants showed strong entrainment to the embedded tone patterns. A significant increase in entrainment over exposure was detected only in the structured condition, reflecting the trajectory of learning. While source reconstruction revealed a wide range of brain areas involved in this process, entrainment in areas around the left pre-central gyrus as well as right temporo-frontal areas significantly predicted behavioral performance. Sensor level results confirmed this relationship between neural entrainment and subsequent explicit knowledge. These results give insights into the dynamic relation between neural entrainment and explicit learning of triplet structures, suggesting that these two aspects are systematically related yet dissociable. Neural entrainment reflects robust, implicit learning of underlying patterns, whereas the emergence of explicit knowledge, likely built on the implicit encoding of structure, varies across individuals and may depend on factors such as sufficient exposure time and attention.
Comparison of Self-Reported Sexual Activity Among Heterosexuals with Sexual Spread of Poorly Transmittable Agents: A Minimalistic Approach to Estimating Sexual Activity Based on HIV Incidence
2020-07-30

The aim of this study was to assess whether epidemics of sexually transmitted infections caused by poorly transmittable agents corresponded to self-reported sexual activity in a distinct population. To exemplify this, a model was used to investigate whether HIV infection incidences corresponded to the extent of sexual activity as assessed by a questionnaire-based study. The model suggested between 97 and 486 sexual contacts per German individual during a sexually active lifetime based on the annual HIV incidence of 680 among the heterosexual population reported by the German National Health Authority. This is in line with the estimated 296 sexual contacts during one’s lifetime, which was indicated by questionnaire respondents. The model confirms the correspondence of self-reported sexual activity with HIV incidence as reported by the German National Health Authority. Accordingly, HIV incidence- and prevalence-based modeling of sexual activity in a population provides crude estimations in situations where a range of uncertainty is acceptable. The model’s veracity is limited by a number of assumptions necessitated by the paucity of data. Nevertheless, the model may be suitable in settings where severe reporting bias has to be expected for legal or socio-cultural reasons.
Interpreting Islamic Dream Books of the Cairo Genizah
2020-07-30

Abstract This article is the result of a first-hand exploration of the relevance of the Cairo Genizah as a source for Intellectual history of the Middle Ages. It is not only significant for understanding Jewish thought, previously documented in numerous studies, but also to the Islamic world. Whereas S.D. Goitien’s oeuvre and the groundbreaking work of his disciples widely demonstrated the importance of Genizah documents as historical sources on the Mediterranean region, the relevance of its Islamic/Arabic literature is less often acknowledged. This topic will be addressed in the light of my doctoral research, which examined the legacy of dream interpretation preserved in Genizah fragments of dream books written in Judeo-Arabic during the pre-modern period. After a brief introduction to the history of dream books—manuals for dream interpretation—in the Near East, and to the epistemology of Jewish and Islamic dream interpretation, the main findings of the research will be listed and summarized. Finally, in a detailed case study, a synoptic edition of texts representing the Taʿbīr al-ruʾyā , a brief dream manual attributed to al-Kirmānī, demonstrates the importance of Cairo Genizah manuscripts to the literary history of the composition.
When are Neural ODE Solutions Proper ODEs
2020-07-30

A key appeal of the recently proposed Neural Ordinary Differential Equation(ODE) framework is that it seems to provide a continuous-time extension of discrete residual neural networks. As we show herein, though, trained Neural ODE models actually depend on the specific numerical method used during training. If the trained model is supposed to be a flow generated from an ODE, it should be possible to choose another numerical solver with equal or smaller numerical error without loss of performance. We observe that if training relies on a solver with overly coarse discretization, then testing with another solver of equal or smaller numerical error results in a sharp drop in accuracy. In such cases, the combination of vector field and numerical method cannot be interpreted as a flow generated from an ODE, which arguably poses a fatal breakdown of the Neural ODE concept. We observe, however, that there exists a critical step size beyond which the training yields a valid ODE vector field. We propose a method that monitors the behavior of the ODE solver during training to adapt its step size, aiming to ensure a valid ODE without unnecessarily increasing computational cost. We verify this adaption algorithm on two common bench mark datasets as well as a synthetic dataset. Furthermore, we introduce a novel synthetic dataset in which the underlying ODE directly generates a classification task.
Direct Experimental Evidence of Surface-induced Protein Unfolding at the Single-molecule Level
2020-07-30

Journal Article Direct Experimental Evidence of Surface-induced Protein Unfolding at the Single-molecule Level Get access Evgeny Dubrovin, Evgeny Dubrovin FRCC of Physical-Chemical Medicine of FMBA; Lomonosov Moscow State University; NUST MISIS, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Nikolay Barinov, Nikolay Barinov FRCC of Physical-Chemical Medicine of FMBA; Lomonosov Moscow State University; NUST MISIS, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Tilman Schäffer, Tilman Schäffer University of Tübingen, Tübingen, Baden-Wurttemberg, Germany Search for other works by this author on: Oxford Academic Google Scholar Dmitry Klinov Dmitry Klinov FRCC of Physical-Chemical Medicine of FMBA; Lomonosov Moscow State University; NUST MISIS, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 26, Issue S2, 1 August 2020, Pages 312–313, https://doi.org/10.1017/S1431927620014178 Published: 01 August 2020
Forty-Two or Two-and-Forty: Learning Maths in Different Languages
2020-07-30

&lt;div&gt;Doing basic maths seems to be a pretty common thing. 2 + 2 equals 4, both in France and in China. 7 × 8 equals 56, both in the United States of America and in Germany. Although most of us use the same symbols to write down numbers (1, 2, 3, 4 ...), we use very different words for these numbers simply because we speak different languages. In this article, we will give examples of what number words in different languages look like. We also show how the way multi-digit number words are built can make learning maths and dealing with large numbers easier or more difficult. &lt;/div&gt;
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence
2020-07-31

We define hybrid intelligence (HI) as the combination of human and machine intelligence, augmenting human intellect and capabilities instead of replacing them and achieving goals that were unreachable by either humans or machines. HI is an important new research focus for artificial intelligence, and we set a research agenda for HI by formulating four challenges.
Big Five Personality Traits Predict Successful Transitions From School to Vocational Education and Training: A Large-Scale Study
2020-07-31

Educational transitions play a pivotal role in shaping educational careers, and ultimately social inequality. Whereas parental socioeconomic status (SES) and cognitive ability have long been identified as key determinants of successful educational transitions, much less is known about the role of socio-emotional skills. To address this gap, the present study investigated whether Big Five personality traits predict success in the transition from secondary school to vocational education and training (VET) above and beyond SES, cognitive ability, and other covariates. Using data from Starting Cohort 4 of the German National Educational Panel Study (NEPS; <i>N</i> = 4,137), we defined seven indicators of successful transition: obtaining a VET position, number of acceptances for VET positions, starting a VET position, (the absence of) dropout intentions and actual dropout, final VET grade, and satisfaction with VET. The results revealed that some Big Five traits were incrementally associated with several indicators of transition success. Conscientiousness emerged as the single most relevant trait, predicting all the transition success indicators but 1 (dropout intentions). The other Big Five traits had much weaker and less consistent links with transition success. Extraversion predicted the final VET grade and obtaining a VET position; Agreeableness was linked to a higher risk of dropout. Openness and Emotional Stability had no incremental effects on transition success. There was also some evidence for both compensatory and synergistic interactive effects, with Openness moderating mainly the effects of parental SES (on dropout intentions, actual dropout, and number of acceptances), and Agreeableness moderating the effects of cognitive ability (on obtaining a VET position, number of acceptances, and satisfaction with VET). Although individual effect sizes were small, the Big Five's joint contribution to transition success was non-negligible, and often larger than that of sociodemographic characteristics and cognitive ability. Our results suggest a hitherto underappreciated contribution of personality to successful transitions to VET.