Miracle-dz/UniFAR-FTUs huggingface dataset:
A mutation in the cytosolic O-acetylserine (thiol) lyase induces the genome-dependent old3-1 early leaf death phenotype in Arabidopsis

The Arabidopsis onset of leaf death3-1 (old3-1) mutant shows a temperature dependent premature leaf death phenotype. The old3-1 mutation segregates as a monogenic co-dominant trait when backcrossed to its wild type accession Landsberg erecta (Ler-0). In contrast, F2 progeny of old3-1 backcrossed to Col-0 segregates in an 11:4:1 (wild type: co-dominant: mutant) ratio demonstrating that the early leaf death phenotype depends on two loci. The second locus that determines the old3-1 early leaf death phenotype is referred to as ODD (for old3 determination). The old3-1 mutation is caused by a point mutation in the cytosolic O-acetylserine (thiol) lyase OAS-TL gene causing a single amino acid change from Gly to Glu. OAS-TL enzymes catalyse the formation of cysteine and mitochondrial and plastidic OAS-TL enzymes are believed to contribute primarily to cysteine biosynthesis as well. The old3-1 protein has no detectable in vitro OAS-TL activity. In order to distinguish the direct effects of the mutated OAS-TL we isolated a T-DNA insertional OAS-TL mutant and designated as old3-2. The cytosolic OAS-TL was found to function in providing resistance against cadmium-induced stress and for maintaining sulphur and thiols levels, independent of the ODD gene. The old3-1 early leaf death phenotype is associated with high expression of defence response and oxidative stress marker genes. Further analysis placed the ODD gene within a ~ 50-kb genome region on chromosome 3 which carries a recently integrated copia-like retrotransposon gene that is present in the Ler-0, but not in the Col-0 genome. The insertion is associated with a high genetic diversity including SNPs, insertions/deletions and altered gene structures. Thus, the old3-1 mutation causes genome dependent and independent
How soccer players would do stream joins

In spite of the omnipresence of parallel (multi-core) systems, the predominant strategy to evaluate window-based stream joins is still strictly sequential, mostly just straightforward along the definition of the operation semantics. In this work we present handshake join, a way of describing and executing window-based stream joins that is highly amenable to parallelized execution. Handshake join naturally leverages available hardware parallelism, which we demonstrate with an implementation on a modern multi-core system and on top of field-programmable gate arrays (FPGAs), an emerging technology that has shown distinctive advantages for high-throughput data processing. On the practical side, we provide a join implementation that substantially outperforms CellJoin (the fastest published result) and that will directly turn any degree of parallelism into higher throughput or larger supported window sizes. On the semantic side, our work gives a new intuition of window semantics, which we believe could inspire other stream processing algorithms or ongoing standardization efforts for stream query languages.
Model and Algorithm for Linkage Disequilibrium Analysis in a Non-Equilibrium Population

The multilocus analysis of polymorphisms has emerged as a vital ingredient of population genetics and evolutionary biology. A fundamental assumption used for existing multilocus analysis approaches is Hardy–Weinberg equilibrium at which maternally- and paternally-derived gametes unite randomly during fertilization. Given the fact that natural populations are rarely panmictic, these approaches will have a significant limitation for practical use. We present a robust model for multilocus linkage disequilibrium analysis which does not rely on the assumption of random mating. This new disequilibrium model capitalizes on Weir’s definition of zygotic disequilibria and is based on an open-pollinated design in which multiple maternal individuals and their half-sib families are sampled from a natural population. This design captures two levels of associations: one is at the upper level that describes the pattern of cosegregation between different loci in the parental population and the other is at the lower level that specifies the extent of co-transmission of non-alleles at different loci from parents to their offspring. An MCMC method was implemented to estimate genetic parameters that define these associations. Simulation studies were used to validate the statistical behavior of the new model.
Automatic assessment of articulation disorders using confident unit-based model adaptation

This paper presents an approach to automatic assessment on articulation disorders using unsupervised acoustic model adaptation. Prior knowledge is obtained via the phonological analysis of the speech data from 453 articulation disordered children. A confusion matrix of the recognition units for a specific subject is re-estimated based on the prior knowledge and the recognition results to choose the confident units for adaptation. The adapted acoustic models can effectively improve the recognition performance of the disordered speech and thus used for articulation assessment. In the experiments, the proposed unsupervised adaptation method achieved a significant performance improvement of 9.1% for disordered speech on syllable recognition rate. Automatic assessment also shows encouraging consistency to the assessment from the therapist.
Neuroprotection in Vascular Dementia

Vascular dementia (VaD) is the second most common form of dementia after Alzheimer’s disease (AD), and one of the major causes of mental and physical disability in developed countries. As such, the identification and implementation of strategies which prevent the development of the condition or enable improvements in patients with VaD are healthcare objectives of the first order. VaD is now regarded as a combined group of clinical-pathological entities rather than one disease, that is, multiple pathogenic mechanisms and lesion types underlie a cognitive impairment of vascular origin. The clinical diagnosis of VaD is complex and difficult because of the heterogeneous nature of its clinical presentation and progression and the low sensitivity of existing clinical criteria. Moreover, there is growing evidence of the epidemiological significance of mixed forms of dementia, and that ischemic processes may precipitate and exacerbate cognitive impairment in AD. Numerous compounds have been proposed as potentially useful in the treatment of patients with VaD, comprising vasodilatative, antithrombotic, hemorrheological, nootropic, antiserotoninergic and, most recently, antiglutamatergic and cholinergic approaches. In spite of some initially favorable reports based on the use of memantine, donepezil and galantamine, there is as yet no conclusive evidence of a definitive treatment for VaD. Unsatisfactory results from VaD drug trials may be attributed in part to the diversity of the patients included (underlying pathogenic mechanisms, number, type, and location of vascular lesions), and to methodological limitations in the design of the trials (outcome measures, end-points, size, follow-up period). The treatment of modifiable vascular risk factors – hypertension, diabetes mellitus, hypercholesterolemia and heart disease – is an important strategy for the reduction of the risk of dementia, and is likely to slow the progress of cognitive decline.
Unusual Strong Ground Motion Across Japan From the 680 km Deep 30 May 2015 Ogasawara Islands Earthquake

The Mw 7.9 earthquake beneath the Ogasawara Islands on 2015 May 30 at 680 km depth (about 100 km deeper than other seismicity in the vicinity) produced significant shaking over a broad area of Japan in the epicentral distance range 1,000–2,000 km. Usually, deep earthquakes in the subducting Pacific slab develop a band of large ground motion along the east coast of northern Japan, due to efficient guiding of high‐frequency (>1 Hz) waves in the subducting slab. However, for this very deep earthquake, the large ground acceleration arises from relatively low‐frequency (<1 Hz) S wave pulses with a long tail of long‐period (<0.1 Hz) signals. The arrival of the slab‐guided high‐frequency signal was very late, and weak, compared with normal Pacific slab events. Numerical simulation of seismic wave propagation reveals that the observed low‐frequency pulses are the direct S wave from the very deep source followed by a large SV‐to‐P conversion at the free surface with near‐critical S wave incidence. These phases produce a long‐period shear‐coupled PL (S‐PL) wave by constructive interference between wide‐angle P and S reflections in the crust and incoming S wave to the crust. The S‐PL wave travels several hundred kilometers at regional distances with reinforcement from continuing S wave input from the very deep source. Such an unusual observation of strong low‐frequency ground motion was due to its very great source depth, outside the main slab, so the high‐frequency Pacific‐slab guided wave was weak.
Explorer Phase 2 Randomised Controlled Trial and Feasibility Study of Future Care Planning in Patients with Advanced Heart Disease

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Google matrix and Ulam networks of intermittency maps

We study the properties of the Google matrix of an Ulam network generated by intermittency maps. This network is created by the Ulam method which gives a matrix approximant for the Perron-Frobenius operator of dynamical map. The spectral properties of eigenvalues and eigenvectors of this matrix are analyzed. We show that the PageRank of the system is characterized by a power law decay with the exponent beta dependent on map parameters and the Google damping factor alpha . Under certain conditions the PageRank is completely delocalized so that the Google search in such a situation becomes inefficient.
An Optimistic Posterior Sampling Strategy for Bayesian Reinforcement Learning

We consider the problem of decision making in the context of unknown Markov decision processes with finite state and action spaces. In a Bayesian reinforcement learning framework, we propose an optimistic posterior sampling strategy based on the maximization of state-action value functions of MDPs sampled from the posterior. First experiments are promising. Introduction. The design of algorithms for planning in the context of unknown Markov Decision Processes (MDPs) remains challenging. In particular, one of the main difficulties is to address the so-called Exploration versus Exploitation (E/E) dilemma: at every time-step, the algorithm must both (i) take a decision which is of good quality regarding information that has been collected so far (the exploitation part) and (ii) open the door to collecting new information about the (unknown) underlying environment in order to take better decisions in the future (the exploration part). At the end of the eighties, the popularization of Reinforcement Learning (RL) [20] gave a new impulse to the research community working on this old problem, and the E/E dilemma was re-discovered in the light of the RL paradigm. Among the approaches that have been proposed to address the E/E dilemma in the RL field, one can mention approaches based on optimism in the face of uncertainty [12, 3, 4, 13, 6, 15] and Bayesian approaches [7, 19, 17, 9, 8]. In the last few years, posterior sampling approaches have received a lot of attention, in particular for solving multi-armed bandits problems [5, 11, 10]. Very recently, posterior sampling has also been proved theoretically and empirically to be efficient for solving MDPs in [16]. Our contribution lies at the crossroads between posterior sampling approaches and optimistic approaches. We propose a strategy based on two main assumptions: (i) a posterior distribution can be maintained over the set of all possible transition models, and (ii) one can easily sample and solve MDPs drawn according to this posterior. These two conditions are easily satisfied in the context of finite state and action space MDPs. Inspired from the principle of the Bayes-UCB algorithm proposed in the context of multi-armed bandit problems [10], our strategy works as follows: at each time-step, a pool of MDPs is drawn from the posterior distribution, and each MDP is solved. We finally take an action whose value is maximized over the set of state-action value functions of sampled MDPs. After observing a new transition, the posterior distribution is updated according to the Bayes rule. We illustrate empirically the performances of our approach on a standard benchmark. Model-based Bayesian Reinforcement Learning. Let M = (S,A, T,R) be a Markov Decision Process (MDP), where the set S = { s, . , sS } denotes the finite state space and the set A = { a, . , aA } the finite action space of the MDP. When the MDP is in state st ∈ S at time t ∈ N, an action at ∈ A is selected and the MDP moves toward a new state st+1 ∈ S , drawn
Paradoxes of the Web: The Ethical Dimensions of Credibility

This essay review the issues surrounding determinations of the credibility of online materials. The author argues, first, that the World Wide Web, and the larger Internet, comprise some very difficult and distinctive features that make conventional ways of assessing credibility adequate only within a fairly bounded frame; second, that beyond this bounded frame, standard credibility measures encounter some paradoxical and self-undermining consequences; third, that this picture is complicated further by the fact that credibility actually covers several very different sorts of factors, not all of them matters of judging truth and falsity per se; and therefore, fourth, that the assessment of credibility needs to address the social and normative factors that actually shape the character and quality of online information. These considerations combine to reveal an ethical dimension to many credibility assessments.
Amygdala hypersensitivity in response to emotional faces in Tourette's patients

Abstract Objectives. Tourette's syndrome is characterised by motor and vocal tics as well as a high level of impulsivity and emotional dysregulation. Neuroimaging studies point to structural changes of the basal ganglia, prefrontal cortex and parts of the limbic system. However, there is no link between behavioural symptoms and the structural changes in the amygdala. One aspect of daily social interaction is the perception of emotional facial expressions, closely linked to amgydala function. Methods. We therefore investigated via fMRI the implicit discrimination of six emotional facial expressions in 19 adult Tourette's patients. Results. In comparison to healthy control group, Tourette's patients showed significantly higher amygdala activation, especially pronounced for fearful, angry and neutral expressions. The BOLD-activity of the left amygdala correlated negatively with the personality trait extraversion. Conclusions. We will discuss these findings as a result of either deficient frontal inhibition due to structural changes or a desynchronization in the interaction of the cortico-striato-thalamo-cortical network within structures of the limbic system. Our data show an altered pattern of implicit emotion discrimination and emphasize the need to consider motor and non-motor symptoms in Tourette's syndrome in the choice of both behavioural and pharmacological treatment.
Série Scientifique Scientific Series Predicting Systematic Risk: Implications from Growth Options Predicting Systematic Risk: Implications from Growth Options

CIRANO Le CIRANO est un organisme sans but lucratif constitué en vertu de la Loi des compagnies du Québec. Le financement de son infrastructure et de ses activités de recherche provient des cotisations de ses organisations-membres, d'une subvention d'infrastructure du Ministère du Développement économique et régional et de la Recherche, de même que des subventions et mandats obtenus par ses équipes de recherche. CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the Ministère du Développement économique et régional et de la Recherche, and grants and research mandates obtained by its research teams. Le CIRANO collabore avec de nombreux centres et chaires de recherche universitaires dont on peut consulter la liste sur son site web. Les cahiers de la série scientifique (CS) visent à rendre accessibles des résultats de recherche effectuée au CIRANO afin de susciter échanges et commentaires. Ces cahiers sont écrits dans le style des publications scientifiques. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents research carried out at CIRANO and aims at encouraging discussion and comment. The observations and viewpoints expressed are the sole responsibility of the authors. They do not necessarily represent positions of CIRANO or its partners. Résumé En vertu de l'effet de levier financier bien connu, les baisses du cours des actions produisent une hausse du bêta des capitaux propres avec facteur d'endettement par rapport à un bêta donné des capitaux propres sans facteur d'endettement. Toutefois, étant donné que les options de croissance sont plus volatiles et présentent un risque plus élevé que les actifs en place, une baisse de leur prix peut contribuer à diminuer le bêta des capitaux propres sans facteur d'endettement à cause de l'effet de « levier d'exploitation ». Ce phénomène s'explique par le fait que les baisses de prix peuvent être associées à une perte proportionnellement plus élevée dans le cas des options de croissance par rapport aux actifs en place. La plupart des études existantes mettent l'accent sur l'effet de levier financier. Le document actuel se penche sur les deux effets. Nos résultats empiriques démontrent que, contrairement à la croyance répandue, l'effet de levier d'exploitation domine largement l'effet de levier financier, même dans le cas des firmes dont …
Extracting Conditional Formulas for Cross-Platform Bug Search

With the recent increase in security breaches in embedded systems and IoT devices, it becomes increasingly important to search for vulnerabilities directly in binary executables in a cross-platform setting. However, very little has been explored in this domain. The existing efforts are prone to producing considerable false positives, and their results cannot provide explainable evidence for human analysts to eliminate these false positives. In this paper, we propose to extract conditional formulas as higher-level semantic features from the raw binary code to conduct the code search. A conditional formula explicitly captures two cardinal factors of a bug: 1) erroneous data dependencies and 2) missing or invalid condition checks. As a result, binary code search on conditional formulas produces significantly higher accuracy and provide meaningful evidence for human analysts to further examine the search results. We have implemented a prototype, XMATCH, and evaluated it using well-known software, including OpenSSL and BusyBox. Experimental results have shown that XMATCH outperforms the existing bug search techniques in terms of accuracy. Moreover, by evaluating 5 recent vulnerabilities, XMATCH provides clear evidence for human analysts to determine if a matched candidate is indeed vulnerable or has been patched.
Towards continuous speech recognition using surface electromyography

We present our research on continuous speech recognition of the surface electromyographic signals that are generated by the human articulatory muscles. Previous research on electromyographic speech recognition was limited to isolated word recognition because it was very difficult to train phoneme-based acoustic models for the electromyographic speech recognizer. In this paper, we demonstrate how to train the phoneme-based acoustic models with carefully designed electromyographic feature extraction methods. By decomposing the signal into different feature space, we successfully keep the useful information while reducing the noise. Additionally, we also model the anticipatory effect of the electromyographic signals compared to the speech signal. With a 108-word decoding vocabulary, the experimental results show that the word error rate improves from 86.8% to 32.0% by using our novel feature extraction methods. Index Terms: speech recognition, electromyography, articulatory muscles, feature extraction.
Impedance based battery diagnosis for automotive applications

In this paper, a procedure is presented, which determines and predicts the pulse power capability of a battery by means of an impedance-based model. This is achieved by a passive impedance measurement technique, which allows using current ripple and fluctuations as a signal source. The advantage of the procedure is its direct determination of the pulse power capability while no indirect and difficult to determine state variables such as state of charge and state of health are needed.
Simulation of propagation along a cylindrical bundle of cardiac tissue. II. Results of simulation

For pt.I see ibid., vol.37, no.9, p.850-60 (1990). Nonlinear membrane kinetics are introduced into the bidomain membrane and equal anisotropy ratios are assumed, permitting the transmembrane potential to be computed and its behavior examined at different depths in the bundle and for different values of conductivity and bundle diameters. In contrast with single-fiber models, the bundle model reveals that the shape of the action potential is influenced by tissue resistivities. In addition, the steady-state activation wavefront through the cross section perpendicular to the long axis of the bundle is not planar and propagates with a velocity that lies between that of a single fiber in an unbounded volume and a single-fiber in a restricted extracellular space. In general, the bundle model is shown to be significantly better than the classical single fiber model in describing the behavior of real cardiac tissue. <<ETX>>
Semi-supervised contextual classification and unmixing of hyperspectral data based on mixture distributions

This paper considers image unmixing of hyperspectral data with a small training data set. We propose a semi-supervised contextual unmixing method for hyperspectral data. Gaussian mixture models and a novel MRF (Markov random field) are assumed for distributions of feature vectors and category fraction vectors, respectively. Then, we derive a semi-supervised unmixing method through EM algorithm and ICM method. The proposed method is examined through artificial and real data sets, and shows a excellent performance.