pinecone/core-2020-05-10-deduplication huggingface dataset:
Yang-Baxter deformations and string dualities

We further study integrable deformations of the AdS_5×S^5 superstring by following the Yang-Baxter sigma model approach with classical r-matrices satisfying the classical Yang-Baxter equation (CYBE). Deformed string backgrounds specified by r-matrices are considered as solutions of type IIB supergravity, and therefore the relation between gravitational solutions and r-matrices may be called the gravity/CYBE correspondence. In this paper, we present a family of string backgrounds associated with a classical r-matrices carrying two parameters and its three-parameter generalization. The two-parameter case leads to the metric and NS-NS two-form of a solution found by Hubeny-Rangamani-Ross [hep-th/0504034] and another solution in [arXiv:1402.6147]. For all of the backgrounds associated with the three-parameter case, the metric and NS-NS two-form are reproduced by performing TsT transformations and S-dualities for the undeformed AdS_5 × S^5 background. As a result, one can anticipate the R-R sector that should be reproduced via a supercoset construction
Relevant gluonic energy scale of spontaneous chiral symmetry breaking from lattice QCD

We analyze which momentum component of the gluon field induces spontaneous chiral symmetry breaking in lattice QCD. After removing the high-momentum or low-momentum component of the gluon field, we calculate the chiral condensate and observe the roles of these momentum components. The chiral condensate is found to be drastically reduced by removing the zero-momentum gluon. The reduction is about 40% of the total in our calculation condition. The nonzero-momentum infrared gluon also has a sizable contribution to the chiral condensate. From the Banks-Casher relation, this result reflects the nontrivial relation between the infrared gluon and the zero-mode quark
Exact and efficient top-K inference for multi-target prediction by
  querying separable linear relational models

Many complex multi-target prediction problems that concern large target
spaces are characterised by a need for efficient prediction strategies that
avoid the computation of predictions for all targets explicitly. Examples of
such problems emerge in several subfields of machine learning, such as
collaborative filtering, multi-label classification, dyadic prediction and
biological network inference. In this article we analyse efficient and exact
algorithms for computing the top-$K$ predictions in the above problem settings,
using a general class of models that we refer to as separable linear relational
models. We show how to use those inference algorithms, which are modifications
of well-known information retrieval methods, in a variety of machine learning
settings. Furthermore, we study the possibility of scoring items incompletely,
while still retaining an exact top-K retrieval. Experimental results in several
application domains reveal that the so-called threshold algorithm is very
scalable, performing often many orders of magnitude more efficiently than the
naive approach
Investigation and comparative analysis of plastic instability criteria: Application to forming limit diagrams

The prediction of forming limit diagrams (FLDs) is of significant interest to the sheet metal forming industry. Although a large variety of plastic instability criteria have been developed during the previous decades, there is still a lack of comparison of their respective theoretical bases. The aim of this paper is to present the theoretical formulations of a representative selection of diffuse necking and strain localization criteria based on the maximum force principle, the Marciniak-Kuczyński method and the bifurcation approach. The theoretical foundations and underlying assumptions for each criterion are specified prior to their application to several materials to determine the associated FLDs. The capability of the criteria to predict the formability of thin metal sheets is discussed and a classification of some of the criteria is attempted according to their order of occurrence in terms of the localization prediction.CNRS et Région Lorrain
A non-uniform semantic analysis of the Italian temporal connectives Prima and Dopo

In this paper, I argue that the temporal connective prima ('before') is a comparative adverb. The argument is based on a number of grammatical facts from Italian, showing that there is an asymmetry between prima and dopo ('after'). On the ground of their divergent behaviour, I suggest that dopo has a different grammatical status from prima. I propose a semantic treatment for prima that is based on an independently motivated analysis of comparatives which can be traced back to Seuren (1973). Dopo is analyzed instead as an atomic two-place predicate which contributes a binary relation over events to the sentence meaning. The different semantic treatments of the two connectives provide an explanation for the grammatical asymmetries considered at the outset; interestingly, it also sheds some light on other asymmetries between prima and dopo which are known to hold for the English temporal connectives before and after as well: these asymmetries are related to the veridicality properties, the distribution of NPIs, and the logical properties of these connectives first described in Anscombe (1964)
Recirculation cells in a wide channel

International audienceSecondary flow cells are commonly observed in straight laboratory channels, where they are often associated with duct corners. Here, we present velocity measurements acquired with an acoustic Doppler current profiler in a straight reach of the Seine river (France). We show that a remarkably regular series of stationary flow cells spans across the entire channel. They are arranged in pairs of counter-rotating vortices aligned with the primary flow. Their existence away from the river banks contradicts the usual interpretation of these secondary flow structures, which invokes the influence of boundaries. Based on these measurements, we use a depth-averaged model to evaluate the momentum transfer by these structures, and find that it is comparable with the classical turbulent transfer
Predicting the Location of Glioma Recurrence After a Resection Surgery

International audienceWe propose a method for estimating the location of glioma recurrence after surgical resection. This method consists of a pipeline including the registration of images at different time points, the estimation of the tumor infiltration map, and the prediction of tumor regrowth using a reaction-diffusion model. A data set acquired on a patient with a low-grade glioma and post surgery MRIs is considered to evaluate the accuracy of the estimated recurrence locations found using our method. We observed good agreement in tumor volume prediction and qualitative matching in regrowth locations. Therefore, the proposed method seems adequate for modeling low-grade glioma recurrence. This tool could help clinicians anticipate tumor regrowth and better characterize the radiologically non-visible infiltrative extent of the tumor. Such information could pave the way for model-based personalization of treatment planning in a near future
Bayesian modelling of an absolute chronology for Egypt's 18th Dynasty by astrophysical and radiocarbon methods

Only a few astrophysical points and synchronisms listed in texts provide anchor points for the absolute chronology of Ancient Egypt. At first we will show how we can re-calculate some of these anchor points by using Sothic dating based on the arcus visionis method, and modelling lunar dates using a Bayesian approach. Then, we will discuss two radiocarbon studies carried out on short-lived Egyptian materials held at the Louvre Museum that could be attributed to particular reigns or other precise periods. Using a Bayesian approach, these dates were combined with the known order of succession and the lengths of reigns. Sothic and lunar dates were integrated as priors in the model. This approach has led to a new proposal for the absolute chronology of Egypt's 18th Dynasty
Mother-to-child HIV transmission despite antiretroviral therapy in the ANRS French Perinatal Cohort.

International audienceOBJECTIVE: To identify factors associated with mother-to-child HIV-1 transmission (MTCT) from mothers receiving antenatal antiretroviral therapy. DESIGN: The French Perinatal Cohort (EPF), a multicenter prospective cohort of HIV-infected pregnant women and their children. METHODS: Univariate analysis and logistic regression, with child HIV status as dependent variable, were conducted among 5271 mothers who received antiretroviral therapy during pregnancy, delivered between 1997 and 2004 and did not breastfeed. RESULTS: The MTCT rate was 1.3% [67/5271; 95% confidence interval (CI), 1.0-1.6]. It was as low as 0.4% (5/1338; 95% CI, 0.1-0.9) in term births with maternal HIV-1 RNA level at delivery below 50 copies/ml. MTCT increased with viral load, short duration of antiretroviral therapy, female gender and severe premature delivery: 6.6% before 33 weeks versus 1.2% at 37 weeks or more (P < 0.001). The type of antiretroviral therapy was not associated with transmission. Intrapartum therapy was associated with four-fold lower MTCT (P = 0.04) in case of virological failure (> 10 000 copies/ml). Elective cesarean section tended to be inversely associated with MTCT in the overall population, but not in mothers who delivered at term with viral load < 400 copies/ml [odds ratio (OR), 0.83; 95% CI, 0.29-2.39; P = 0.37]. Among them, only duration of antenatal therapy was associated with transmission (OR by week, 0.94; 95% CI, 0.90-0.99; P = 0.03). CONCLUSIONS: Low maternal plasma viral load is the key factor for preventing MTCT. Benefits in terms of MTCT reduction may be expected from early antiretroviral prophylaxis. The potential toxicity of prolonged antiretroviral use in pregnancy should be evaluated
A regulation mechanism based on work activity to improve Lean approach

Part 1: Knowledge-Based Performance ImprovementInternational audienceCompanies adopting Lean increase their productivity, quality of product and delivery in the short term. But in the medium term, these performance criteria are mitigated by events such as absenteeism, sickness leaves, turnover, etc. To explain this, Occupational Health scientists identify contradictions between the components of Lean and human functioning. One of these contradictions relates to the regulation mechanism of human work activity, specific to human functioning, which would be inhibited in a Lean working environment. In this article, we focus on the integration of this mechanism in the Lean performance approach and, to illustrate our approach, we choose the example of semi-finished stock lying between each workstation: the ‘work in progress’ inventory. We propose to use a performance indicator that measures the need of ‘work in progress’ inventory taking into account the regulation mechanism of the work activity. We call this indicator “number of regulating ‘work in progress’ inventory”
Incentive Effects on Risk Attitude in Small Probability Prospects

International audienceMost studies on the role of incentives on risk attitude report data obtained from within-subject experimental investigations. This may however raise an issue of sequentiality of effects as later choices may be influenced by earlier ones. This paper reports instead between-subject results on the effect of monetary stakes on risk attitudes for small probability prospects in a laboratory experiment. Under low stakes, we find the typical risk seeking behavior for small probabilities predicted by the prospect theory. But under high stakes, we provide some evidence that risk seeking behavior is dramatically reduced. This could suggest that utility is not consistently concave over the outcome space, but rather contains a convex section for very small amounts
Automated Measurement of Models of Requirements

update for BASE on Sep 08 2018 22:43:36International audienceOn way to formalize system requirements is to express them using the object-oriented paradigm. In this case, the class model representing the structure of requirements is called a requirements metamodel, and requirements themselves are object-based models of natural-language requirements. In this paper, we show that such object-oriented requirements are well-suited to support a large class of requirements metrics. We define a requirements metamodel and use an automated measurement approach proposed in our previous work to specify requirements metrics. We show that it is possible to integrate 78 metrics from 11 different papers in the proposed framework. The software that computes the requirements metric values is fully generated from the specification of metrics
Neo4EMF, a Scalable Persistence Layer for EMF Models

International audienceSeveral industrial contexts require software engineering methods and tools able to handle large -size artifacts. The central idea of abstraction makes model-driven engineering (MDE) a promising approach in such contexts, but current tools do not scale to very large models (VLMs): already the task of storing and accessing VLMs from a persisting support is currently ine cient. In this paper we propose a scalable persistence layer for the de-facto standard MDE framework EMF. The layer exploits the e ciency of graph databases in storing and accessing graph structures, as EMF models are. A preliminary experimentation shows that typical queries in reverse-engineering EMF models have good performance on such persistence layer, compared to le-based backends
Measurement of the neutrino velocity with the OPERA detector in the CNGS beam

see paper for full list authorsThe OPERA neutrino experiment at the underground Gran Sasso Laboratory has measured the velocity of neutrinos from the CERN CNGS beam over a baseline of about 730 km with much higher accuracy than previous studies conducted with accelerator neutrinos. The measurement is based on high-statistics data taken by OPERA in the years 2009, 2010 and 2011. Dedicated upgrades of the CNGS timing system and of the OPERA detector, as well as a high precision geodesy campaign for the measurement of the neutrino baseline, allowed reaching comparable systematic and statistical accuracies. An early arrival time of CNGS muon neutrinos with respect to the one computed assuming the speed of light in vacuum of (60.7 \pm 6.9 (stat.) \pm 7.4 (sys.)) ns was measured. This anomaly corresponds to a relative difference of the muon neutrino velocity with respect to the speed of light (v-c)/c = (2.48 \pm 0.28 (stat.) \pm 0.30 (sys.)) \times 10-5
An Investigation of the Plasma Composition in Plasma-enhanced Hot Filament Catalytic Chemical Vapor Deposition of Carbon Nanotubes

International audienceA mixture of acetylene, hydrogen and ammonia (C2H2/H2/NH3) is used to produce carbon nanotubes (CNTs) by a plasma-enhanced catalytic chemical vapor depo- sition process either without (PE CCVD) or with hot filaments-assistance (PE HF CCVD). A mathematical model based on Chemkin computer package is used for analyzing specific conditions of nanotube synthesis. Simulations are compared with optical emission spectroscopy (OES) measurements. Morphological and structural investigations on the grown carbon nanostructures are also performed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It was shown that the significant change in the density and the morphology of the CNTs grown in the presence of NH3 could be mainly explained by the gas phase formation of CN and HCN. Both species display a high etching activity, whereas the species C, CH, CH2, CH2(S), C2 and C2H are expected to be the most probable carbon nanotube precursors
Autism multiplex family with 16p11.2p12.2 microduplication syndrome in monozygotic twins and distal 16p11.2 deletion in their brother.
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Duplication 16p11.2p12.2 in twins with autism

International audienceThe pericentromeric region of chromosome 16p is rich in segmental duplications that predispose to rearrangements through non-allelic homologous recombination. Several recurrent copy number variations have been described recently in chromosome 16p. 16p11.2 rearrangements (29.5-30.1 Mb) are associated with autism, intellectual disability (ID) and other neurodevelopmental disorders. Another recognizable but less common microdeletion syndrome in 16p11.2p12.2 (21.4 to 28.5-30.1 Mb) has been described in six individuals with ID, whereas apparently reciprocal duplications, studied by standard cytogenetic and fluorescence in situ hybridization techniques, have been reported in three patients with autism spectrum disorders. Here, we report a multiplex family with three boys affected with autism, including two monozygotic twins carrying a de novo 16p11.2p12.2 duplication of 8.95 Mb (21.28-30.23 Mb) characterized by single-nucleotide polymorphism array, encompassing both the 16p11.2 and 16p11.2p12.2 regions. The twins exhibited autism, severe ID, and dysmorphic features, including a triangular face, deep-set eyes, large and prominent nasal bridge, and tall, slender build. The eldest brother presented with autism, mild ID, early-onset obesity and normal craniofacial features, and carried a smaller, overlapping 16p11.2 microdeletion of 847 kb (28.40-29.25 Mb), inherited from his apparently healthy father. Recurrent deletions in this region encompassing the SH2B1 gene were recently reported in early-onset obesity and in individuals with neurodevelopmental disorders associated with phenotypic variability. We discuss the clinical and genetic implications of two different 16p chromosomal rearrangements in this family, and suggest that the 16p11.2 deletion in the father predisposed to the formation of the duplication in his twin children
Online Extraction and Single Trial Analysis of Regions Contributing to Erroneous Feedback Detection

International audienceUnderstanding how the brain processes errors is an essential and active field of neuroscience. Real time extraction and analysis of error signals provide an innovative method of assessing how individuals perceive ongoing interactions without recourse to overt behaviour. This area of research is critical in modern Brain–Computer Interface (BCI) design, but may also open fruitful perspectives in cognitive neuroscience research. In this context, we sought to determine whether we can extract discriminatory error-related activity in the source space, online, and on a trial by trial basis from electroencephalography data recorded during motor imagery. Using a data driven approach, based on interpretable inverse solution algorithms, we assessed the extent to which automatically extracted error-related activity was physiologically and functionally interpretable according to performance monitoring literature. The applicability of inverse solution based methods for automatically extracting error signals, in the presence of noise generated by motor imagery, was validated by simulation. Representative regions of interest, outlining the primary generators contributing to classification, were found to correspond closely to networks involved in error detection and performance monitoring. We observed discriminative activity in non-frontal areas, demonstrating that areas outside of the medial frontal cortex can contribute to the classification of error feedback activity
PAutomaC: a probabilistic automata and hidden Markov models learning competition

International audienceApproximating distributions over strings is a hard learning problem. Typical techniques involve using finite state machines as models and attempting to learn these; these machines can either be hand built and then have their weights estimated, or built by grammatical inference techniques: the structure and the weights are then learned simultaneously. The Probabilistic Automata learning Competition (PAutomaC), run in 2012, was the first grammatical inference challenge that allowed the comparison between these methods and algorithms. Its main goal was to provide an overview of the state-of-the-art techniques for this hard learning problem. Both artificial data and real data were presented and contestants were to try to estimate the probabilities of strings. The purpose of this paper is to describe some of the technical and intrinsic challenges such a competition has to face, to give a broad state of the art concerning both the problems dealing with learning grammars and finite state machines and the relevant literature. This paper also provides the results of the competition and a brief description and analysis of the different approaches the main participants used
Finding a Vector Orthogonal to Roughly Half a Collection of Vectors

International audienceDimitri Grigoriev has shown that for any family of $N$ vectors in the $d$-dimensional linear space $E=(\ff{2})^d$, there exists a vector in $E$ which is orthogonal to at least $N/3$ and at most $2N/3$ vectors of the family. We show that the range $[N/3,2N/3]$ can be replaced by the much smaller range $[N/2-\sqrt{N}/2,N/2+\sqrt{N}/2]$ and we give an efficient, deterministic parallel algorithm which finds a vector achieving this bound. The optimality of the bound is also investigated
Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust

Le comportement du signal radar TerraSAR-X en fonction des paramètres du sol (rugosité, humidité, structure) a été analysé sur des données 2009 et 2010. Les résultats montrent que la sensibilité du signal radar à l'humidité est plus importante pour des faibles incidences (25° en comparaison à 50°). Pour des fortes valeurs d'humidité, le signal TerraSAR-X est plus sensible à la rugosité du sol à forte incidence (50°). La forte résolution spatiale des données TerraSAR-X (1 m) permet de détecter la croûte de battance à l'échelle intra parcellaire. / Soils play a key role in shaping the environment and in risk assessment. We characterized the soils of bare agricultural plots using TerraSAR-X (9.5 GHz) data acquired in 2009 and 2010. We analyzed the behavior of the TerraSAR-X signal for two configurations, HH-25° and HH-50°, with regard to several soil conditions: moisture content, surface roughness, soil composition and soil-surface structure (slaking crust).The TerraSAR-X signal was more sensitive to soil moisture at a low (25°) incidence angle than at a high incidence angle (50°). For high soil moisture (N25%), the TerraSAR-X signal was more sensitive to soil roughness at a high incidence angle (50°) than at a low incidence angle (25°). The high spatial resolution of the TerraSAR-X data (1 m) enabled the soil composition and slaking crust to be analyzed at the within-plot scale based on the radar signal. The two loamy-soil categories that composed our training plots did not differ sufficiently in their percentages of sand and clay to be discriminated by the X-band radar signal.However, the spatial distribution of slaking crust could be detected when soil moisture variation is observed between soil crusted and soil without crust. Indeed, areas covered by slaking crust could have greater soil moisture and consequently a greater backscattering signal than soils without crust
Enhancing the area of a Raman atom interferometer using a versatile double-diffraction technique

International audienceIIn this paper we demonstrate a new scheme for Raman transitions which realize a symmetric momentum-space splitting of $4 \hbar k$, deflecting the atomic wave-packets into the same internal state. Combining the advantages of Raman and Bragg diffraction, we achieve a three pulse state labelled interferometer, intrinsically insensitive to the main systematics and applicable to all kind of atomic sources. This splitting scheme can be extended to $4N \hbar k$ momentum transfer by a multipulse sequence and is implemented on a $8 \hbar k$ interferometer. We demonstrate the area enhancement by measuring inertial forces