Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking

A typical architecture for end-to-end entity linking systems consists of three steps: mention detection, candidate generation and entity disambiguation. In this study we investigate the following questions: (a) Can all those steps be learned jointly with a model for contextualized text-representations, i.e. BERT? (b) How much entity knowledge is already contained in pretrained BERT? (c) Does additional entity knowledge improve BERT’s performance in downstream tasks? To this end we propose an extreme simplification of the entity linking setup that works surprisingly well: simply cast it as a per token classification over the entire entity vocabulary (over 700K classes in our case). We show on an entity linking benchmark that (i) this model improves the entity representations over plain BERT, (ii) that it outperforms entity linking architectures that optimize the tasks separately and (iii) that it only comes second to the current state-of-the-art that does mention detection and entity disambiguation jointly. Additionally, we investigate the usefulness of entity-aware token-representations in the text-understanding benchmark GLUE, as well as the question answering benchmarks SQUAD~V2 and SWAG and also the EN-DE WMT14 machine translation benchmark. To our surprise, we find that most of those benchmarks do not benefit from additional entity knowledge, except for a task with very small training data, the RTE task in GLUE, which improves by 2%.
About time A motivation-based complementary framework for temporal dynamics in Web personalization

Purpose – The purpose of this paper seeks to develop a motivation-based complementary framework for temporally dynamic user preferences to facilitate optimal timing in web personalisation. It also aims to highlightthebene ﬁ ts of considering user motivation when addressing issues intemporal dynamics. Design/methodology/approach – Through theory, a complementary framework and propositions for motivation-based temporal dynamics for further testing are created. The framework is validated by feeding back ﬁ ndings,whereassome of thepropositions arevalidated through anexperiment. Findings – The suggested framework distinguishes two ways (identifying/learning and shifting) of using a motive-based approach to temporal dynamics in web personalisation. The suggested outcomes include enhanced timing in matching current preferences and improved conversion. Validation measures predominantly support both the framework and the tested propositions. The theoretical basis for the approach paves a pathtowards re ﬁ ned psychologicalusermodels; however,currently ona complementary level. Research limitations/implications – While the framework is validated through feeding back ﬁ ndings, and someofthepropositionsare validated through basicexperimentation,further empirical testing isrequired. Practical implications – A generalised approach for complementing personalisation procedures with motivation-basedtemporaldynamicsisoffered,withimplicationsforbothusermodellingandpreferencematching. Originality/value – This paper offers novel insights to web personalisation by considering the in-depth effects of user motivation.
Doerfel Consecutive Proline Residues EFP Is Essential for Rapid Synthesis of Proteins Containing

clicking here. colleagues, clients, or customers by , you can order high-quality copies for your If you wish to distribute this article to others here. following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles ): January 4, 2013 www.sciencemag. org (this information is current as of The following resources related to this article are available online at http://www.sciencemag. org/content/339/6115/85.full. html version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag. org/content/suppl/2012/12/12/science.1229017. DC1.html can be found at: Supporting Online Material http://www.sciencemag. org/content/339/6115/85.full. html#related found at: can be related to this article A list of selected additional articles on the Science Web sites http://www.sciencemag. org/content/339/6115/85.full. html#ref-list-1 , 13 of which can be accessed free: cites 33 articles This article http://www.sciencemag. org/content/339/6115/85.full. html#related-urls 1 articles hosted by HighWire Press; see: cited by This article has been
LIQUIDITY CONSTRAINTS AND THE BALANCE SHEET CHANNEL OF MONETARY POLICY TRANSMISSION

The balance sheet channel used to be perceived as a minor channel of monetary policy transmission but has become important since the interest rates faced the zero lower bound. This paper analyzes monetary policy impact on the relation between liquidity and fi xed asset investments of the US non-fi nancial companies in the decade between 2005 and 2014. Two hypotheses were proposed: 1) tight monetary policy limited companies’ access to liquidity, and 2) quantitative easing infl uenced the level of fi xed asset investment. Three random effects and three fi xed effects models were constructed for each hypothesis, controlling for size and the level of fi nancial leverage. It was found that, fi rstly, relative tightening of monetary policy seemed unrelated to liquidity constraints. A company’s size and its debt-to-equity ratio determined its ability to raise external funds. Secondly, the validity of the balance sheet channel could not be dismissed when considering unconventional monetary policy. The results corroborated the existence of a positive correlation between the liquid asset ratio and fi xed asset investments.
Foreign focused mutual funds and exchange traded funds : Do they improve portfolio management ?

Approximately one third of all actively managed foreign equity mutual funds hold exchange traded funds (ETFs). We show that, dependent on the type of ETF held, mutual funds with large ETF positions experience noticeable improvements in the management of their portfolios. In particular, when large positions in ETFs are taken, mutual fund performance marginally increases, and cash holdings, portfolio risk, and turnover all decrease. We also observe that foreign equity mutual funds tend to hold ETFs within their investment objective during periods of large flows.
The Effects of the Affordable Care Act Medicaid Expansion on Subjective Well-Being

This study analyzes the effects of the 2014 Affordable Care Act (ACA) Medicaid expansion on the subjective well-being of individuals in the United States. Using data from the Panel Study of Income Dynamics, we find that the expansion has significantly improved the overall life satisfaction of low-income non-elderly adults. Various sensitivity checks and falsification tests confirm the internal validity. Our findings imply that, without considering psychological benefits, the actual benefits of the ACA Medicaid expansion may be underemphasized.
How Do Auditors View Corporate Culture? The Effect of Collaboration Culture on Audit Fees

This study examines how auditors view their clients’ corporate culture – collaboration culture. We construct a novel measure of collaboration culture using textual analysis on public firms’ 10-K reports. We find that firms with collaboration culture pay lower audit fees. These firms emphasize on communication and produce high-quality information, which lowers auditors’ risk. Auditors do not significantly change their effort for these firms but may charge lower risk premium. The low audit fees in these firms is not associated with clients’ business strategies. It suggests that auditors may not quantify the effect of culture on business outcome for audit pricing.
TIME-VARYING FORECASTS OF DEFAULTED BOND RECOVERIES

Fuelled by evolving regulatory capital requirements for banks and other financial institutions and heightened competitive pressures in the market for distressed securities, many recent studies and practitioner efforts have sought to establish how best to forecast recoveries on defaulted investments. We benchmark the inter-temporal and cross-validation based forecasting performance of recently developed models of recovery on defaulted debt exposures and we specify a fast and flexible approach to maximum likelihood estimation of recovery distributions using mixtures of Gaussian distributions. Our model explicitly accounts for characteristic information and covariates capturing changing market conditions and compare its forecasting performance to that of parametric and non-parametric regression models. Our inter-temporal forecasting comparisons suggest that non-parametric regression trees are generally outperformed by our semi-parametric mixture model, and in some instances, by simple regression models, while regression trees dominate cross-validation tests. More generally, we show that the performance of flexible forecasting models with reference to popular cross-validation tests may provide misleading indications of practical (intertemporal) forecasting performance when recovery distributions are time-varying.
Cinema Author’s Embodied Simulatorium – a Systems Intelligence Approach

The essay relates the cinema author’s creative processes to the systems intelligence approach. The underpinning assumption is that cinema stands forth as an intersubjective frame of sensemaking. This idea is reflected against the early systemic views of the Russian filmmaker and theoretician Sergei M. Eisenstein. In its unfolding, the cinema author’s creative processes are described from a particular point of view, that is, that of the enactive mind point by means of introducing the neuroscientific concept of embodied simulation as the bodily basis of these processes. This is applied in the hypothetical model of cinema author’s mental workspace, the embodied simulatorium as it is termed. In this paper it will be discussed how embodied processes constitute what in this volume is referred to as systems intelligence.
Creating Friction: Infrastructuring Civic Engagement

This paper introduces the theoretical lens of the everyday to intersect and extend the emerging bodies of research on contestational design and infrastructures of civic engagement. Our analysis of social theories of everyday life suggests a design space that distinguishes ‘privileged moments’ of civic engagement from a more holistic understanding of the everyday as ‘product-residue. ’ We analyze various efforts that researchers have undertaken to design infrastructures of civic engagement along two axes: the everyday-ness of the engagement fostered (from ‘privileged moments’ to ‘product-residue’) and the underlying paradigm of political participation (from consensus to contestation). Our analysis reveals the dearth and promise of infrastructures that create friction— provoking contestation through use that is embedded in the everyday life of citizens. Ultimately, this paper is a call to action for designers to create friction. Author
Project acronym: ENERGISE Title: European Network for Research, Good Practice and Innovation for Sustainable Energy Grant Agreement number: 727642

Acknowledgments: We are grateful to the following people for their work, which contributed greatly to the quality of this report: Patrick Naef (UNIGE) for his review of qualitative comparative methods; Orlane Moynat (UNIGE) for NVivo coding; Alice Guilbert (UNIGE) for quantitative data analysis; Tania Pereira (UNIGE) for ELL1 and ELL2 comparison; Tuija Kajoskoski (University of Helsinki) for data preparation and quantitative analysis.
THE SURPRISING BEHAVIOR

We highlight a lack of understanding of the behaviour of Convolutional Graph Neural Networks (GNNs) in various topological contexts. We present 4 experimental studies which counter-intuitively demonstrate that the performance of GNNs is weakly dependent on the topology, sensitive to structural noise and the modality (attributes or edges) of information, and degraded by strong coupling between nodal attributes and structure. We draw on the empirical results to recommend reporting of topological context in GNN evaluation and propose a simple (attribute-structure) decoupling method to improve GNN performance.
The Impact of Environmental Policies on Competition and Competition Policy

In this article we use the notion of “National Competition Policy” as a unifying framework for the assessment of the legislative and institutional structures that promote the existence of effective competition in and for the product and services markets and services. Firstly, we provide a review of the theoretical and empirical literature which examines the relation between competition and competitiveness. Then, we note why and how a National Competition Policy becomes even more important when the country applies a strategy for “green” growth. Finally, we illustrate the ways in which a number of environmental policies and measures can hinder competition.
An Investigation of Using Monte-Carlo Tree Search for Creating the Intelligent Elements of Rise of Mitra

Games have been used as a good test environment for AI. This paper describes the outcomes of Monte-Carlo Tree Search (MCTS) in the AI of Rise of Mitra(RoM), a discrete world turn-based game. This algorithm consists of Selection, Simulation, Expansion and Backpropagation phases. MCTS had successful outcomes in twoplayer games with perfect information like Go, where it managed to win some competitions. Therefore, the main goal of this work is to reach a challenging AI that can contribute to creating a more realistic and immersive game, besides being capable to consider uncertainty elements. Some strategies like OMC and UCB were used. Both of them resulting in a good win rate, approximately 70% for OMC and 60% for UCT. Therefore, this algorithm can win against normal players, but not at a point where a player can get frustrated, in other words, it allows the player to be challenged and more immersed in the game world.
Discourses and Understandings of Employability in Vocational Education A Comparison of Swedish and Catalan Policies and Student Perspectives

The concept of ‘employability’ is an important aspect of the link between education and the labour market. This thesis describes, in the Swedish and Catalan contexts, the conceptualization of employability in the discourses of vocational educational policy trough the analytical categories of representations of the world, social order, and social identity. It then examines vocational education students’ understandings of the concept through the themes of career building, experiences, and, employment outlook. Using critical discourse analysis, I collected and examined data from policy documents to analyse policy discourses regarding employability. On the other hand, I interviewed six vocational education students and used thematic analysis to build students’ understandings of employability. The results portray different pictures for the two contexts examined. While Swedish policy discourse includes on its account of employability some ‘humanistic’ values, such as democracy and human rights, the Catalan policy discourse focuses mainly in ‘market’ values such as competitivity and productivity. On the other hand, students in both contexts understand apprenticeships and personal attributes as key elements of employability. Two main conclusions are drawn from this study. First, the world represented in policy documents strives to reproduce relations of economic production and cultural hegemony. Second, by placing emphasis on apprenticeships and personal attributes vocational students have adapted to the goals of policy documents. Further research on the topic should explore the existing material contradictions between labour policy and vocational
Edinburgh Research Explorer Facilitating healthy dietary habits

This paper tests an intervention aimed at facilitating (cognitively) the adoption of healthy dietary habits. We provide easy-to-understand information about the risks of developing diabetes or heart diseases and give easy-to-follow dietary recommendations to minimize these risks. We implement two variations, one consisting of generic information, the other consisting of information tailored to the individual, the latter resembling newly developed on-line health assessment tools. On top of the information treatment, we implement a second experimental variation encouraging people to spend more time thinking about their decisions. We ﬁnd evidence that the information intervention leads to healthier choices in the short run, but mostly in the generic treatment. Surprisingly, we ﬁnd that people are on average pessimistic about their health, and therefore receive good news on average when the information is tailored to them. We ﬁnd no evidence that increasing the time available to make choices leads to healthier choices, and ﬁnd no evidence of long-term changes in habits. These results do not support a bounded rationality explanation for poor dietary choices.
Characterization of hydatid cyst antigens by crossed immunoelectrophoresis and its implications for the serodiagnosis of hydatid disease in livestock

Kydatidosis is a disease of major worldwide public health importance and with considerable economic consequences for the livestock industry. It shows a variable geographic distribution but reaches its highest levels in certain areas of Kenya and in South America. Meat inspection reports show that the disease is common in livestock in Kenya. A small survey carried out in this study showed a 14% prevalence of hydatid cysts in animals slaughtered in two abattoirs in Nairobi. In an attempt to find a specific antigen that can be used in an in vivo diagnostic test for livestock hydatidosis, it was considered appropriate to study the antigenic composition of hydatid cyst fluid (HCF), the stage of the parasite which is found in livestock. Hydatid cyst fluid was harvested from cysts which were collected from cattle, sheep and goats. A reference pool of concentrated HCF was made by mixing various preparations of HCF from these animals. In order to study the cross-reactivity of HCF antigens and other livestock parasites, saline homogenates of common parasites were also prepared. Polyvalent antisera against HCF and various parasites were raised in calves, sheep.
Bayesian Estimation of Recurrent Changepoints for Signal Segmentation and Anomaly Detection

Signal segmentation is a generic task in many time series applications. We propose approaching it via Bayesian changepoint algorithms, i.e., by assigning segments between changepoints. When successive signals show a recurrent change-point pattern, estimating changepoint recurrence is beneficial for two reasons: While recurrent changepoints yield more robust signal segment estimates, non-recurrent changepoints bear valuable information for unsupervised anomaly detection.This study introduces the changepoint recurrence distribution (CPRD) as an empirical estimate of the recurrent behavior of observed changepoints. Two generic methods for incorporating the estimated CPRD into the process of assessing recurrence of future changepoints are suggested. The knowledge of non-recurrent changepoints arising from one of these methods allows additional unsupervised anomaly detection.The quality both of changepoint recurrence estimation via CPRD and of changepoint-related signal segmentation and un-supervised anomaly detection are verified in a proof-of-concept study for two exemplary machine tool monitoring tasks.
PROGRAMA DE MAESTRÍA Y DOCTORADO EN INGENIERÍA INGENIERÍA ELÉCTRICA – CONTROL TRANSPARENT TELEOPERATION WITH UNKNOWN SURFACES AND FORCE ESTIMATION TESIS

Teleoperation means operating at a distance. In the context of robotics, teleoperation is commonly carried out by means of robotic arms and a human–machine interface. To exploit to the maximum the capabilities of a teleoperation system, the control engineering discipline analyzes, through the development of mathematical models, the system dynamics to design algorithms in order to improve the performance or to induce some predefined behavior. In the present work, a robotic teleoperation system is studied, which is composed of two manipulators called master and slave, a human operator that moves the master, a remote environment over which the slave operates, and a communication channel between the controllers of each robot. The main objective of this work is to design a control algorithm for a master–slave teleoperation system that operates over rigid surfaces with unknown geometry. Additionally, it is desired that the designed algorithm does not require velocity nor force sensors at the slave side, i.e., using only joint position measurements for the slave robot. To achieve this objective, a dynamic extension and a high–gain observer were employed, which jointly are known in the literature as Generalized Proportional Integral (GPI) observers. For the movement control and force tracking, a hybrid position/force controller based on an orthogonal decomposition of the task space was employed. The GPI observer allows, besides simultaneous estimation of slave robot joint velocity and the contact force over the remote environment, to reconstruct the geometry of the remote surface by means of an on line estimator. In other words, the proposed algorithm achieves movement of the slave robot over the surface and simultaneous application of a force desired by the human operator, while at the same time it performs an estimation of the velocity and force signals, and the gradient of the unknown surface. A mathematical analysis was carried out, which guarantees locally uniform ultimate boundedness of all signals. Furthermore, it was formally proven that the final bound of the tracking and estimation errors can be made arbitrarily small, which means approximate but arbitrarily close position and force tracking and also arbitrarily close estimation of slave joint velocities, contact force, and the gradient of the surface.
Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding U.S. Gun Violence

Different news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, and yet a third might focus on mental health issues. In communication research, these different perspectives are known as “frames”, which, when used in news media will influence the opinion of their readers in multiple ways. In this paper, we present a method for effectively detecting frames in news headlines. Our training and performance evaluation is based on a new dataset of news headlines related to the issue of gun violence in the United States. This Gun Violence Frame Corpus (GVFC) was curated and annotated by journalism and communication experts. Our proposed approach sets a new state-of-the-art performance for multiclass news frame detection, significantly outperforming a recent baseline by 35.9% absolute difference in accuracy. We apply our frame detection approach in a large scale study of 88k news headlines about the coverage of gun violence in the U.S. between 2016 and 2018.