Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Future Use of BMI

The brain-machine interface (BMI) could just be one of the most helpful technological breakthroughs of our time. This technology comes in the form of a micro-processor installed in the brain that can assist mental processes, just as the name suggests. Its current uses are in rehabilitating people who suffer from various nerve-related ailments where in the case of stroke victims, it would allow them to regain control over regions of their body previously lost [1], whether limbs, neck or facial muscles and in the case of aphasia victims, BMI would provide speech synthesis [2], where the damaged Brocha and/or Wernicke regions normally responsible for linguistic processing are bypassed. These applications present the already available uses of BMI thus far, but can BMI technology offer other forms of processing assistance to the brain, even contributing to enhanced brain performance? One mental capacity that would be ideal to have is the ability for cross-linguistic processing; and so, we wonder whether BMI can be used for linguistic augmentation and enhancement. In this paper I consider BMI in its potential application in providing real-time translation.
Encefalopatías Espongiformes Transmisibles

Las encefalopatías espongiformes transmisibles (EET) son enfermedades neurodegenerativas causadas por priones. Si bien estas infecciones por lo general permanecen asintomáticas por años, la enfermedad es siempre progresiva y mortal , una vez que se han desarrollado los signos clínicos. Las TSE que afectan a los animales incluyen scrapie (Tembladera,Temblante du mouton, Rida), encefalopatía espongiforme bovina (EEB, “enfermedad de la vaca loca”), encefalopatía espongiforme felina (EEF), encefalopatía transmisible del visón (EEV, scrapie del visón) y enfermedad debilitante crónica (EDC). Si bien algunas enfermedades causadas por priones a menudo aparecen en una especie o en unas pocas especies relacionadas, otros priones pueden cruzar barreras inter-especies. La EEB tiene un rango de huésped particularmente amplio. El ganado bovino es el huésped más importante para esta enfermedad, pero también se pueden infectar otros rumiantes, gatos, lémures y humanos; en los gatos la enfermedad es conocida como encefalopatía espongiforme felina, y en los humanos es llamada variante de la enfermedad de Creutzfeldt–Jakob (vECJ). Hay evidencia reciente que sugiere que las EET también pueden ser causadas por una variante del agente de la EEB. El descubrimiento de que la EEB puede atravesar barreras inter-especies y que es zoonótica, ha originado preocupación sobre todas las EET. Las enfermedades causadas por priones en el ganado también pueden ocasionar sanciones comerciales. Por este motivo, muchos países están llevando a cabo programas de control o erradicación de estas enfermedades. Estados Unidos tiene programas de erradicación y de certificación de rodeos para scrapie (tembladera), un programa de certificación para la enfermedad debilitante crónica de cérvidos en cautiverio y un programa de vigilancia para EEB.
Semantic N-Gram Topic Modeling

In this paper a novel approach for effective topic modeling is presented. The approach is different from traditional vector space model-based topic modeling, where the Bag of Words (BOW) approach is followed. The novelty of our approach is that in phrase-based vector space, where critical measure like point wise mutual information (PMI) and log frequency based mutual dependency (LGMD)is applied and phrase’s suitability for particular topic are calculated and best considerable semantic N-Gram phrases and terms are considered for further topic modeling. In this experiment the proposed semantic N-Gram topic modeling is compared with collocation Latent Dirichlet allocation(coll-LDA) and most appropriate state of the art topic modeling technique latent Dirichlet allocation (LDA). Results are evaluated and it was found that perplexity is drastically improved and found significant improvement in coherence score specifically for short text data set like movie reviews and political blogs.
Creating an Annotated Corpus for Aspect-Based Sentiment Analysis in Swedish

Aspect-Based Sentiment Analysis constitutes a more ﬁne-grained alternative to traditional sentiment analysis at sentence level. In addition to a sentiment value denoting how positive or negative a particular opinion or sentiment expression is, it identiﬁes additional aspects or ‘slots’ that characterize the opinion. Some typical aspects are target and source, i.e. who holds the opinion and about which entity or aspect is the opinion. We present a large Swedish corpus annotated for Aspect-Based Sentiment Analysis. Each sentiment expression is annotated as a tuple that contains the following ﬁelds: one among 5 possible sentiment values, the target, the source, and whether the sentiment expressed is ironic. In addition, the linguistic element that conveys the sentiment is identiﬁed too. Sentiment for a particular topic is also annotated at title, paragraph and document level. The documents are articles obtained from two Swedish media (Svenska Dagbladet and Aftonbladet) and one online forum (Flashback), totalling around 4000 documents. The corpus is freely available and we plan to use it for training and testing an Aspect-Based Sentiment Analysis system.
Taming Behavioral Backward Incompatibilities via Cross-Project Testing and Analysis

In modern software development, software libraries play a crucial role in reducing software development effort and improving software quality. However, at the same time, the asynchronous upgrades of software libraries and client software projects often result in incompatibilities between different versions of libraries and client projects. When libraries evolve, it is often very challenging for library developers to maintain the so-called backward compatibility and keep all their external behavior untouched, and behavioral backward incompatibilities (BBIs) may occur. In practice, the regression test suites of library projects often fail to detect all BBIs. Therefore, in this paper, we propose DeBBI to detect BBIs via cross-project testing and analysis, i.e., using the test suites of various client projects to detect library BBIs. Since executing all the possible client projects can be extremely time consuming, DeBBI transforms the problem of cross-project BBI detection into a traditional information retrieval (IR) problem to execute the client projects with higher probability to detect BBIs earlier. Furthermore, DeBBI considers project diversity and test relevance information for even faster BBI detection. The experimental results show that DeBBI can reduce the end-to-end testing time for detecting the first and average unique BBIs by 99.1% and 70.8% for JDK compared to naive cross-project BBI detection. Also, DeBBI has been applied to other popular 3rd-party libraries. To date, DeBBI has detected 97 BBI bugs with 19 already confirmed as previously unknown bugs.
Reducing the income tax burden for households with children

This paper analyses the impact of the implementation of a child tax credit in Austria in 2019, not only on micro, but also on macro level by using a dynamic scoring methodology. First, we assess the fiscal and distributional impact of this reform using the microsimulation model EUROMOD. Second, we estimate labour supply impacts of the reform based on a structural discrete choice framework. Third, we evaluate the macroeconomic impacts of the reform, by calibrating and shocking QUEST, the DSGE model of the European Commission, with the micro-based results for the implicit tax rate, the non-participation and the labour supply elasticities. We show that the child tax credit reform in Austria reduces inequality, lowers the poverty rate in general, but by definition only for households with children. Overall the reform has a positive impact on labour supply, both on the extensive and on the intensive margin, especially for women. On the macro-level (and in the long-run), our model suggests a positive impact on employment. Additionally, we find that parts of the tax decrease can be potentially captured by the employer, meaning that gross wages would fall slightly. However, we find small but positive effects on GDP, investment and consumption, although the longrun macroeconomic effects depend crucially on how the government compensates the missing tax revenues after the reform. Accounting for these feedback effects at the micro level with a new methodology, we show that the second round effects are important to take into account, because they provide insights into the medium-term distributional impact of the reform.
Modeling Sequential Bargaining Game Agents towards Human-like Behaviors : Comparing Experimental and Simulation Results

The objective of this paper is to clarify whether the two types of agent-modeling (i.e. Roth’s three parameter RE learning agent and Q-learning agent) are valid in terms of the reproduction of human-like behaviors or not. Specifically, we discuss it from both superficial viewpoint (i.e. simulation results) and internal viewpoint (i.e. simulation modeling). Concretely, we conducted subject experiments of sequential bargaining game and compared two types of simulation results (agents employ two types of learning mechanisms) with experimental results. An intensive comparison of experimental results and simulation results has revealed the following implications: (1-a) from superficial viewpoint, Q-learning agents reproduce human-like behaviors well against Roth’s learning agent; (1-b) even Q-learning agents cannot reproduce the decreasing trend of negotiation size shown in subject experiments; (2-a) from internal viewpoint, the combination with Q-learning and boltzmann distribution selection has the possibility to reproduce human-like behavior which predicts the intention of the opponent; (2-b) even this combination cannot reproduce the decreasing trend of the negotiation size; and (2-c) the maximum limit of Q-values makes the differences of the converged Q-values for all actions in the same state smaller, which contributes to the acquisition of sequential negotiations.
First-order substructural logics So different , yet so familiar

Substructural logics are a prominent family of non-classical logics whose complete semantics is given by classes of residuated lattices. While there is a vast literature on all thinkable aspects of propositional substructural logics (see e.g. monographs [4, 10, 13] and the references therein), the works focusing on first-order predicate substructural logics are few and far between (with most prominent contributions by Hiroakira Ono, see e.g. [9]). Classical predicate logic interprets n-ary predicates as mappings from the n-th power of a given domain into the two-valued Boolean algebra 2. The idea of replacing 2 by a more general structure is very natural and was shown to lead to very interesting results: prime examples are the Boolean-valued or Heyting-valued models of set theory [1] (or even more general models proposed e.g. by Takeuti and Titani [14] or by Hájek and Haniková [6]). There exists a stream of research, by Mostowski [8], Rasiowa [11], Sikorski [12], Horn [7], and Hájek [5] to give just a few names, studying logics where predicates can take values in lattices (with operators) from a certain class. This talk presents a general framework for studying predicate substructural logics (based on even more general framework developed in cooperation with Carles Noguera [3]). Given a substructural logic L, we add the usual axioms of classical/intuitionistic logic to obtain predicate logic L∀m and easily prove its completeness w.r. t. models built over algebras from Alg∗(L) (the class of residuated lattices providing the equivalent algebraic semantic of L). It is easy to see that we can restrict to complete lattices from Alg∗(L) if (but not only if) Alg∗(L) admits Dedekind–MacNeille completions. In classical logic we can however improve this completeness theorem much more: we can restrict to models built over the algebra 2 only. Analogous result for substructural logics would be the completeness w.r. t. models over algebras which are (finitely) subdirectly irreducible relative to Alg∗(L). This however is rarely the case. We show which axioms/rules has to be added to L∀m to obtain this completeness result for a rather wide family of substructural logics. The core of our proof is an appropriate generalization of the classical Henkin method. We present its modular version which allows to prove not only the desired completeness theorem, but also certain (natural) form of Skolemization and certain (perhaps not so natural) form of the omitting type theorem (a joint work with Denisa Diaconescu [2]). Throughout the talk we will see that sometimes we have to twist the classical notions quite a lot to obtain the analogs of the classical results. To show that it is not always so bad we conclude the talk by presenting the (almost) classical proof of the fact that already a very weak variant of Robinson arithmetic is essentially undecidable when formulated in any substructural logic which still obeys the structural rule of weakening (a work in progress with Guillermo Badia and Andrew Tedder).
Can Summarization Improve Que s tion Quality ?

—This project focuses on the generation of questions based on Wikipedia articles, as well as the ranking of the questions based on the content therein. A Wikipedia article was ﬁrst processed through a question generator, which ranked questions generated based on grammatical correctness and comprehensibility of the question. Named entities throughout the Wikipedia article were counted, consolidated, and ranked based on the number of times the entities occurred in the article. Then each question was ranked based on the number and signiﬁcance of named entities within the sentence. The score given to a question for content relevance was averaged with the score for grammar and comprehensibility, and then a ﬁnal ranking was done. Another system was also done where the Page Rank algorithm was used on the questions with presence of named entities used as the feature vector, and then the score given to a sentence for page rank was averaged with the grammar score and ranking was done based on the resulting scores. The resulting set of ranked questions were compared against each other and against the results of the Question Generator itself.
Stigma towards Patients with Mental Illness among Nursing Students

Stigma towards patients with mental illness is a worldwide and multifaceted phenomenon and there is a support that stigma and discrimination are also prevalent among health care team and health care students. Aim: To assess stigma toward patients with mental illness among nursing students. Methods: Descriptivecorrelation research design was used in this study. The sample consisted of 309 nursing students in the academic year 20142015 they were chosen by systematic random sampling using official students' listing. Tools: The data collected by the following tools, 1) Socio-Demographic characteristics of the students 2) Devaluation-Discrimination Scale, 3) Social Distance Scale, 4) Perceptions of Stigmatization by Others for Seeking Help and 5) Self-Stigma of Seeking Help. Results: The percentage of items showing signs of discrimination of mental patients in which 60.2% of the students refuse to accept a previous mental patient as their friends Conclusion: The present study revealed that stigma is common among nursing students and there was no difference in stigma toward patients with mental illness among nursing students in the different academic years. Recommendation: Reorient the education system in such a way that during learning psychiatric nursing course, an issue like stigma is also effectively dealt with.
Faut je t’apporte quelque chose: Complementizer drop in Quebec French

Natural languages often provide speakers with various options to express the same meaning, and identifying which social, linguistic and cognitive factors determine speakers’ preferences is an active area of theoretical and empirical linguistics. In this paper, we test the Uniform Information Density hypothesis (Jaeger and Levy, 2007; Jaeger, 2010) through a study on complementizer drop in French complement clauses, aiming to bring more crosslinguistic evidence for this account. Complementizer drop (1) is a well-studied feature of English ; however, it also appears in many dialects of French, such as those spoken in Quebec, Canada (2).
The Effects of Intermittent Fasting on Chronic Disease in Adults: A Systematic Review

This systematic review investigated thirteen primary and secondary research studies from the past 20 years to determine the effects of intermittent fasting on chronic disease in adults through evaluation of biological markers pertaining to inflammation, oxidative stress, and the cardiovascular system. The dependent variables examined included heart rate, blood pressure, and cholesterol levels for cardiovascular risk; leptin and TNF- for inflammatory risk; and F2-Isoprostanes and free radicals for oxidative stress biomarkers. The reviewed studies found that there was a decrease in resting heart rate, systolic and diastolic blood pressure, blood LDL and total cholesterol levels, inflammatory cells, like leptin, TNF-, and insulin, and oxidative stress (isoprostanes and free radicals); and an increase in HDL cholesterol levels and insulin sensitivity in human and animal subjects engaged in various forms of intermittent fasting. The reviewed effects in both human and animal trials point to beneficial health effects of intermittent fasting in preventing and resisting chronic disease risk factors. In the short-term, it can be implicated that intermittent fasting could be successful in preventing chronic disease from a holistic perspective. This review is limited due to its narrow examination of only thirteen studies, minimal intervention time, and small population size for tested subjects.
End-to-end optimization of a lensless imaging system

Lensless imaging systems have been designed to capture photorealistic images with features such as depth and 3D structure at a fraction of the camera volume. This information can be captured through encodings generated from propagating light through a pseudorandomly coded mask placed directly in front of the camera sensor. However, current reconstruction algorithms for lensless imaging systems typically require solving a well-posed inverse problem with respect to the pre-designed phase mask, which limits the solution space of image reconstruction. We propose an end-to-end optimization framework that optimizes the phase mask and reconstruction algorithm jointly. Our re-sults demonstrate a deep learning approach to improving lensless imaging capture and reconstruction.
Active Learning for Robot Exploration Bayesian Optimization for Object Grasping

—Safe and robust grasping of unknown objects is a major challenge in robotics, which has no general solution yet. A promising approach relies on haptic exploration, where active optimization strategies can be employed to reduce the number of exploration trials. Two critical problems one must consider are non-convex and typically varying smoothness properties of the exploration score and that certain optimal grasps discovered by the optimization procedure may be very sensitive to small deviations of the parameters from their nominal values (unsafe grasps 3 ). To reduce the risk of grasp failure, safe grasps should be favored. Therefore, we use Treed Gaussian Processs (TGPs) to model the exploration metric more correctly and propose a new algorithm, Unscented Bayesian Optimization (UBO), that performs efﬁcient optimization while considering uncertainty in the input space, leading to the discovery of safe optima. The results highlight how our method outperforms the classical Bayesian optimization both in synthetic problems and in realistic robot grasp simulations, ﬁnding robust and safe grasps after a few exploration trials.
New Foundations of Ethical Multiagent Systems

Ethics is inherently a multiagent concern. However, research on AI ethics today is dominated by work on individual agents: (1) how an autonomous robot or car may harm or (differentially) benefit people in hypothetical situations (the so-called trolley problems) and (2) how a machine learning algorithm may produce biased decisions or recommendations. The societal framework is largely omitted. To develop new foundations for ethics in AI, we adopt a sociotechnical stance in which agents (as technical entities) help autonomous social entities or principals (people and organizations). This multiagent conception of a sociotechnical system (STS) captures how ethical concerns arise in the mutual interactions of multiple stakeholders. These foundations would enable us to realize ethical STSs that incorporate social and technical controls to respect stated ethical postures of the agents in the STSs. The envisioned foundations require new thinking, along two broad themes, on how to realize (1) an STS that reflects its stakeholders’ values and (2) individual agents that function effectively in such an STS.
Inferior Vena Cava Assessment

Bedside assessment of intravascular volume status plays an important role in the management of critically ill patients, guiding fluid replacement therapy and the use of vasopressor agents. Despite controversy in the existing evidence, many clinicians advocate the use of inferior vena cava ultrasound (IVC-US) in the assessment of intravascular volume status in critically ill patients. Respirophasic variation in IVC diameter may provide useful information regarding intravascular volume status, particularly in patients with high and low caval indices. However, due to conflicting results of small-scale clinical trials of divergent sample populations, there is insufficient evidence to support routine US assessment of the IVC to determine fluid responsiveness in spontaneous breathing with circulatory compromise. Additional large-scale clinical trials are required to determine the accuracy of IVC-US measurements in diverse populations and to ascertain the effects on IVC dimensions that result from cardiac dysfunction and intra-abdominal hypertension. The authors report no relationships that could be construed as a conflict of interest. From the *Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, MA, USA; and the yDepartment of Emergency Medicine, Icahn Bedside assessment of intravascular volume status plays an important role in the management of critically ill patients, guiding fluid replacement therapy and the use of vasopressor agents. Clinical assessment of volume status using physical examination findings is inaccurate [1], and clinicians have historically relied on information obtained from invasive hemodynamic monitoring, specifically central venous pressure (CVP) and pulmonary capillary wedge pressure (PCWP), to help guide fluid management. Mechanical complications associated with invasive hemodynamic monitoring, as well as a lack of proven efficacy for traditional strategies [2,3] have led to interest in the use of point-of-care ultrasound assessment of the inferior vena cava (IVC-US) as a potentially useful noninvasive, rapid technique to assess intravascular volume status. Whereas studies in the critical care [4], emergency medicine [5], and cardiology [6] literature have supported the use of IVC-US for the assessment of volume status, other studies [7,8] have contradicted these findings. Despite controversy in the existing evidence, many clinicians continue to advocate [9] the use of IVC-US in the assessment of intravascular volume status in critically ill patients. School of Medicine at Mount Sinai, New York, NY, USA. Correspondence: