nils-herrmann/clean_scirepeval huggingface dataset:
Ternary Weight Networks
Venue: ArXiv

We introduce ternary weight networks (TWNs) neural networks with weights constrained to +1, 0 and 1. The Euclidian distance between full (float or double) precision weights and the ternary weights along with a scaling factor is minimized. Besides, a threshold based ternary function is optimized to get an approximated solution which can be fast and easily computed. TWNs have stronger expressive abilities than the recently proposed binary precision counterparts and are thus more effective than the latter. Meanwhile, TWNs achieve up to 16$\times$ or 32$\times$ model compression rate and need fewer multiplications compared with the full precision counterparts. Benchmarks on MNIST, CIFAR 10, and large scale ImageNet datasets show that the performance of TWNs is only slightly worse than the full precision counterparts but outperforms the analogous binary precision counterparts a lot.
A Web Based and Mobile Health Social Support Intervention to Promote Adherence to Inhaled Asthma Medications: Randomized Controlled Trial
Venue: Journal of medical Internet research

Online communities hold great potential as interventions for health, particularly for the management of chronic illness. The social support that online communities can provide has been associated with positive treatment outcomes, including medication adherence. There are few studies that have attempted to assess whether membership of an online community improves health outcomes using rigorous designs.  Our objective was to conduct a rigorous proof of concept randomized controlled trial of an online community intervention for improving adherence to asthma medicine.  This 9 week intervention included a sample of asthmatic adults from the United Kingdom who were prescribed an inhaled corticosteroid preventer. Participants were recruited via email and randomized to either an "online community" or "no online community" (diary) condition. After each instance of preventer use, participants (N=216) were required to report the number of doses of medication taken in a short post. Those randomized to the online community condition (n=99) could read the posts of other community members, reply, and create their own posts. Participants randomized to the no online community condition (n=117) also posted their medication use, but could not read others' posts. The main outcome measures were self reported medication adherence at baseline and follow up (9 weeks postbaseline) and an objective measure of adherence to the intervention (visits to site) Results In all, 103 participants completed the study (intervention: 37.8% 39/99; control: 62.2% 64/117) MANCOVA of self reported adherence to asthma preventer medicine at follow up was not significantly different between conditions in either intention to treat (P=.92) or per protocol (P=.68) analysis. Site use was generally higher in the control compared to intervention conditions.  Joining an online community did not improve adherence to preventer medication for asthma patients. Without the encouragement of greater community support or more components to sustain engagement over time, the current findings do not support the use of an online community to improve adherence. ClinicalTrial International Standard Randomized Controlled Trial Number (ISRCTN) 29399269; http:/www.isrctn.com/ISRCTN29399269/29399269 (Archived by WebCite at http:/www.webcitation.org/6fUbEuVoT)
Short communication: Effect of oregano and caraway essential oils on the production and flavor of cow milk.
Venue: Journal of dairy science

Many essential oils and their terpene constituents display antimicrobial properties, which may affect rumen metabolism and influence milk production parameters. Many of these compounds also have distinct flavors and aromas that may make their way into the milk, altering its sensory properties. Essential oils from caraway (Carum carvi) seeds and oregano (Origanum vulgare) plants were included in dairy cow diets to study the effects on terpene composition and sensory properties of the produced milk, as well as feed consumption, production levels of milk, and methane emissions. Two levels of essential oils, 0.2 and 1.0g of oil/kg of dry matter, were added to the feed of lactating cows for 24d. No effects on feed consumption, milk production, and methane emissions were observed. The amount and composition of volatile terpenes were altered in the produced milk based on the terpene content of the essential oils used, with the total amount of terpenes increasing when essential oils were added to the diet. Sensory properties of the produced milk were altered as well, and milk samples from animals receiving essential oil treatment were perceived as having a fresher aroma and lower stored aroma and flavor. The levels of essential oils used in this study mimic realistic levels of essential oils in herbs from feed, but were too low to affect milk production and methane emissions, and their inclusion in the animal diet did not adversely affect milk flavor.
Neural Machine Translation in Linear Time
Venue: ArXiv

We present a novel neural network for processing sequences. The ByteNet is a one dimensional convolutional neural network that is composed of two parts, one to encode the source sequence and the other to decode the target sequence. The two network parts are connected by stacking the decoder on top of the encoder and preserving the temporal resolution of the sequences. To address the differing lengths of the source and the target, we introduce an efficient mechanism by which the decoder is dynamically unfolded over the representation of the encoder. The ByteNet uses dilation in the convolutional layers to increase its receptive field. The resulting network has two core properties: it runs in time that is linear in the length of the sequences and it sidesteps the need for excessive memorization. The ByteNet decoder attains state of the art performance on character level language modelling and outperforms the previous best results obtained with recurrent networks. The ByteNet also achieves state of the art performance on character to character machine translation on the English to German WMT translation task, surpassing comparable neural translation models that are based on recurrent networks with attentional pooling and run in quadratic time. We find that the latent alignment structure contained in the representations reflects the expected alignment between the tokens.
HIVE COTE: The Hierarchical Vote Collective of Transformation Based Ensembles for Time Series Classification
Venue: 2016 IEEE 16th International Conference on Data Mining (ICDM)

There have been many new algorithms proposed over the last five years for solving time series classification (TSC) problems. A recent experimental comparison of the leading TSC algorithms has demonstrated that one approach is significantly more accurate than all others over 85 datasets. That approach, the Flat Collective of Transformation based Ensembles (Flat COTE) achieves superior accuracy through combining predictions of 35 individual classifiers built on four representations of the data into a flat hierarchy. Outside of TSC, deep learning approaches such as convolutional neural networks (CNN) have seen a recent surge in popularity and are now state of the art in many fields. An obvious question is whether CNNs could be equally transformative in the field of TSC. To test this, we implement a common CNN structure and compare performance to Flat COTE and a recently proposed time series specific CNN implementation. We find that Flat COTE is significantly more accurate than both deep learning approaches on 85 datasets. These results are impressive, but Flat COTE is not without deficiencies. We improve the collective by adding new components and proposing a modular hierarchical structure with a probabilistic voting scheme that allows us to encapsulate the classifiers built on each transformation. We add two new modules representing dictionary and interval based classifiers, and significantly improve upon the existing frequency domain classifiers with a novel spectral ensemble. The resulting classifier, the Hierarchical Vote Collective of Transformation based Ensembles (HIVE COTE) is significantly more accurate than Flat COTE and represents a new state of the art for TSC. HIVE COTE captures more sources of possible discriminatory features in time series and has a more modular, intuitive structure.
Relaxing moral reasoning to win: How organizational identification relates to unethical pro organizational behavior.
Venue: The Journal of applied psychology

Drawing on social identity theory and social cognitive theory, we hypothesize that organizational identification predicts unethical pro organizational behavior (UPB) through the mediation of moral disengagement. We further propose that competitive interorganizational relations enhance the hypothesized relationships. Three studies conducted in China and the United States using both survey and vignette methodologies provided convergent support for our model. Study 1 revealed that higher organizational identifiers engaged in more UPB, and that this effect was mediated by moral disengagement. Study 2 found that organizational identification once again predicted UPB through the mediation of moral disengagement, and that the mediation relationship was stronger when employees perceived a higher level of industry competition. Finally, Study 3 replicated the above findings using a vignette experiment to provide stronger evidence of causality. Theoretical and practical implications are discussed.
Moderating effects of moral reasoning and gender on the relation between moral disengagement and cyberbullying in adolescents

This study examined both the moderating effects of moral reasoning and gender on the relation between moral disengagement and cyberbullying in Chinese adolescents. Four hundred and seventeen adolescents completed the measures of Machiavellianism, moral disengagement, moral reasoning, and cyberbullying. The findings revealed that moral disengagement was significantly associated with cyberbullying even when Machiavellianism was controlled. Moral reasoning moderated the association between moral disengagement and cyberbullying. When adolescents reported a low level of moral reasoning, those with high moral disengagement reported higher scores in cyberbullying than those with low moral disengagement. However, the high and low moral disengagement group had a low level of cyberbullying when moral reasoning was high. Moreover, gender also moderated the link between moral disengagement and cyberbullying. Specifically, the relation between MD and cyberbullying tended to be stronger in boys than in girls.
Consumers' Responses to Public Figures' Transgression: Moral Reasoning Strategies and Implications for Endorsed Brands

Public figures' transgressions attract considerable media attention and public interest. However, little is understood about the impact of celebrity endorsers' transgressions on associated brands. Drawing on research on moral reasoning, we posit that consumers are not always motivated to separate judgments of performance from judgments of morality (moral decoupling) or simply excuse a wrongdoer (moral rationalization) We propose that consumers also engage in moral coupling, a distinct moral reasoning process which allows consumers to integrate judgments of performance and judgments of morality. In three studies, we demonstrate that moral coupling is prevalent and has unique predictive utilities in explaining consumers' evaluation of the transgressor (Studies 1 and 2) We also show that transgression type (performance related vs. performance unrelated) has a significant impact on consumers' choice of moral reasoning strategy (Study 2) Finally, we demonstrate that consumers' support for (or opposition toward) a brand endorsed by a transgressor is a direct function of moral reasoning choice (Study 3) Findings suggest that public figure's immoral behavior and its spillover to an extended brand is contingent on consumers' moral reasoning choices.
Neural foundation of human moral reasoning: an ALE meta analysis about the role of personal perspective
Venue: Brain Imaging and Behavior

Moral sense is defined as a feeling of the rightness or wrongness of an action that knowingly causes harm to people other than the agent. The large amount of data collected over the past decade allows drawing some definite conclusions about the neurobiological foundations of moral reasoning as well as a systematic investigation of methodological variables during fMRI studies. Here, we verified the existence of converging and consistent evidence in the current literature by means of a meta analysis of fMRI studies of moral reasoning, using activation likelihood estimation meta analysis. We also tested for a possible neural segregation as function of the perspective used during moral reasoning i.e. first or third person perspectives. Results demonstrate the existence of a wide network of areas underpinning moral reasoning, including orbitofrontal cortex, insula, amygdala, anterior cingulate cortex as well as precuneus and posterior cingulate cortex. Within this network we found a neural segregation as a function of the personal perspective, with 1PP eliciting higher activation in the bilateral insula and superior temporal gyrus as well as in the anterior cingulate cortex, lingual and fusiform gyri, middle temporal gyrus and precentral gyrus in the left hemisphere, and 3PP eliciting higher activation in the bilateral amygdala, the posterior cingulate cortex, insula and supramarginal gyrus in the left hemisphere as well as the medial and ventromedial prefrontal cortex in the right hemisphere. These results shed some more light on the contribution of these areas to moral reasoning, strongly supporting a functional specialization as a function of the perspective used during moral reasoning.
Coping With Athlete Endorsers' Immoral Behavior: Roles of Athlete Identification and Moral Emotions on Moral Reasoning Strategies

Athlete endorsers' transgressions pose a dilemma for loyal fans who have established emotional attachments toward the individual. However, little is known regarding how fans maintain their support for the wrongdoer. Drawing on moral psychology and social identity theory, the current study proposes and examines a conceptual model incorporating athlete identification, moral emotions, moral reasoning strategies, and consumer evaluations. By using an actual scandal involving an NFL player (i.e. Ray Rice) the results show that fan identification suppresses the experience of negative moral emotions but facilitates fans' moral disengagement processes, which enables fans to support the wrongdoer. Moreover, negative moral emotions motivate the moral coupling process. Findings contribute to the sport consumer behavior literature that highly identified fans seem to regulate negative emotions but deliberately select moral disengagement reasoning strategies to maintain their positive stance toward the wrongdoer and
Embeddedness as a multilevel problem: A case study in economic sociology
Venue: Soc. Networks

Economic sociology has established the interdependencies between economic and social structures using the notion of embeddedness of the former in the latter. However research usually studies inter organizational commercial networks and inter individual informal networks separately. In this article we use a multilevel framework to analyze jointly economic networks between firms and informal networks between their members in order to reframe this embeddedness hypothesis. Based on a network study of a trade fair for television programmes in Eastern Europe we show that while each level has its own specific processes they are partly nested. Beyond this result, we observe that these levels of agency emerge in different contexts and in different temporalities. To conclude, we show that in order to understand performance on a market one needs to look at this dual positioning of individuals and organizations.
Toward Economic Sociology/Socio Economics? Sociological Components in Contemporary Economics and Implications for Sociology

The paper argues and shows that much of contemporary economics undergoes a certain trend toward economic sociology or socio economics, in virtue of increasingly acknowledging and incorporating various sociological components and influences. The paper identifies and considers at least four major related indicators of such a trend. These are, first, the revival of economic sociology or social economics; second, the renewal of the economic sociology of the market; third, the return of socio economic institutionalism; and the rediscovery of cultural factors in the economy and markets. The paper suggests that in virtue of such a tendency at least in part contemporary economics appears increasingly congruent with modern economic sociology rather than with sociological rational choice theory. It aims to contribute to a more adequate account and understanding of pertinent recent tendencies in economics in respect of their implications for contemporary economic and other sociology. The paper infers that the renewal of economic sociology both within contemporary economics and sociology provides the fertile ground for interdisciplinary collaboration between economists and sociologists today, just as its early version did in the past.
Potential Impact of Climate Change on Food Security

In view of the fact that climate related disasters are already taking a heavy toll, causing massive damage to crops and infrastructure and forcing some people to flee their homes, however, the potential impacts of climate change are likely to trigger adaptive responses that influence environmental and socio economic drivers of food system performance in positive as well as negative ways. This paper was conducted through the collection of some research materials with the projected balance of these various climate impacts on food system performance and food security outcomes at the local and global levels. More so that, food security is likely to be affected by climate change in several ways: food security depends not only on the direct impact of climate change on food production but also on its indirect impact on human nutrition and health, economic growth, trade flows and food aid policy. The paper further examined the effectiveness of managing new risks and uncertainty, improving the quality of information and its use, monitoring weather and improving scientific understanding of climate change, promoting insurance schemes, maintaining biodiversity and access to fund as some of the crucial measures for adaptation. The large amount of resources that would be necessary to avoid the worst case scenario suggests the necessity of continued support from the international community to improve food security at the local and global levels as a whole.
A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies
Venue: J. Biomed. Informatics

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF) a unified framework and software system for deriving, visualizing, and exploring partial area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g. OWL and SNOMED CT's relational format) A Protege plugin for deriving "live partial area taxonomies" is demonstrated.
Maritime security governance in the Indian Ocean region

This paper considers arrangements for providing maritime security in the Indian Ocean Region (IOR) at both the national and regional levels. The main requirement at the regional level is a mechanism or mechanisms for cooperation on maritime security concerns both between regional countries themselves and between these countries and the extra regional countries that have a legitimate interest in IOR maritime security. At a national level the necessary capacity for providing maritime security includes arrangements for coordination between the various agencies involved and the operational capabilities for maritime law enforcement to provide good order at sea. The paper discusses the relative attributes of a navy or a coast guard to provide these capabilities. It concludes with ideas about how maritime security governance in the IOR might be improved.
Social Bots Distort the 2016 US Presidential Election Online Discussion
Venue: First Monday

Social media have been extensively praised for increasing democratic discussion on social issues related to policy and politics. However, what happens when this powerful communication tools are exploited to manipulate online discussion, to change the public perception of political entities, or even to try affecting the outcome of political elections? In this study we investigated how the presence of social media bots, algorithmically driven entities that on the surface appear as legitimate users, affect political discussion around the 2016 U.S. Presidential election. By leveraging state of the art social bot detection algorithms, we uncovered a large fraction of user population that may not be human, accounting for a significant portion of generated content (about one fifth of the entire conversation) We inferred political partisanships from hashtag adoption, for both humans and bots, and studied spatio temporal communication, political support dynamics, and influence mechanisms by discovering the level of network embeddedness of the bots. Our findings suggest that the presence of social media bots can indeed negatively affect democratic political discussion rather than improving it, which in turn can potentially alter public opinion and endanger the integrity of the Presidential election.
Language and Intercultural Citizenship Education for a Culture of Peace:The Malvinas/Falklands Project

In recent decades the critical turn in language education has gained tremendous teaching and research attention. Within this context, this chapter describes an online international project with university language students in Argentina and England as an approach to create a culture of peace through the discussion of the Malvinas/Falklands Conflict. Given the sensitive nature of this topic, the chapter examines the active political engagement and civic participation of the students to promote self and social change. It also offers an analysis of the levels of criticality achieved and the intercultural citizenship competences developed. An overview of the implementation of IT tools used in the online intercultural communication phase of the project is also provided, such as Wiki, Facebook, Skype and Elluminate Live! (a virtual classroom made available for the project by the University of East Anglia) This chapter reveals that the confrontation the students experienced with linguistic and cultural otherness stimulated their critical analysis, whilst focusing on developing a respectful understanding of the event and the need for cooperative conflict resolution.