The correlation matrix of Higgs rates at the LHC

The imperfect knowledge of the Higgs boson decay rates and cross sections at the LHC constitutes a critical systematic uncertainty in the study of the Higgs boson properties. We show that the full covariance matrix between the Higgs rates can be determined from the most elementary sources of uncertainty by a direct application of probability theory. We evaluate the error magnitudes and full correlation matrix on the set of Higgs cross sections and branching ratios at $\sqrt{s}=7$, $8$, $13$ and $14$ TeV, which are provided in ancillary files. The impact of this correlation matrix on the global fits is illustrated with the latest $7$+$8$ TeV Higgs dataset.Comment: 25 pages, 1 figure. Complete covariance matrix is available in C, Fortran, Mathematica, PDF, TeX and text formats in ancillary file

Artificial Tongue-Placed Tactile Biofeedback for perceptual supplementation: application to human disability and biomedical engineering

The present paper aims at introducing the innovative technologies, based on the concept of "sensory substitution" or "perceptual supplementation", we are developing in the fields of human disability and biomedical engineering. Precisely, our goal is to design, develop and validate practical assistive biomedical and/technical devices and/or rehabilitating procedures for persons with disabilities, using artificial tongue-placed tactile biofeedback systems. Proposed applications are dealing with: (1) pressure sores prevention in case of spinal cord injuries (persons with paraplegia, or tetraplegia); (2) ankle proprioceptive acuity improvement for driving assistance in older and/or disabled adults; and (3) balance control improvement to prevent fall in older and/or disabled adults. This paper presents results of three feasibility studies performed on young healthy adults

Les limites d’une mesure de dispersion des revenus comme seule variable explicative des dysfonctionnements sociaux dans le contexte d’une politique publique

Plusieurs institutions internationales et certaines recherches universitaires recommandent des politiques fiscales pour diminuer le niveau de dispersion des revenus afin de réduire les dysfonctionnements sociaux comme la criminalité, les problèmes de santé, le faible bien-être subjectif ou le manque de cohésion sociale. Le présent mémoire vise à faire une évaluation théorique d’une politique publique utilisant une mesure de dispersion des revenus pour réduire les dysfonctionnements sociaux. D’une part, l’approche empirique adoptée dans ce mémoire a confirmé qu’il existe en amont une multitude de facteurs sous-jacents comme la composition des ménages (a) qui entrent en interaction et qui affectent considérablement, de façon directe ou indirecte, une mesure de dispersion des revenus (b). D’autre part, les études portant sur la relation entre une mesure de dispersion des revenus et différents dysfonctionnements sociaux (c) varient considérablement dans leurs résultats. Certaines n’indiquent aucun lien significatif entre les deux variables alors que d’autres confirment la relation causale, mais cette dernière peut être positive ou négative. En ce sens, la complexité de l’interaction entre (a) et (b) peut faire en sorte que l’usage de (b) affecte la compréhension des politiques publiques visant la réduction de (c). En effet, on ne peut pas interpréter la relation entre (b) et (c) en faisant abstraction des phénomènes qui sous-tendent (a) et qui ont nécessairement une incidence sur (c). Par conséquent, une baisse du niveau de dispersion des revenus n’entraîne pas ou, du moins, ne favorise pas nécessairement, une diminution des dysfonctionnements sociaux initialement visés. Cette simulation permet d’approfondir les connaissances théoriques sur l’utilisation d’une mesure de dispersion des revenus afin d’assurer une meilleure adéquation entre les moyens proposés et les effets recherchés dans le cadre d’une politique publique visant la réduction des dysfonctionnements sociaux

On learning discontinuous dependencies from positive data

International audienceThis paper is concerned with learning in the model of Gold the Categorial Dependency Grammars (CDG), which express discontin- uous (non-projective) dependencies. We show that rigid and k-valued CDG (without optional and iterative types) are learnable from strings. In fact, we prove that the languages of dependency nets coding rigid CDGs have finite elasticity, and we show a learning algorithm. As a standard corollary, this result leads to the learnability of rigid or k- valued CDGs (without optional and iterative types) from strings

Tonal noise of a controlled-diffusion airfoil at low angle of attack and Reynolds number

International audienceThe acoustic signature of a controlled-diffusion airfoil immersed in a flow is experimentally characterized. Acoustic measurements have been carried out in an anechoic open-jet-wind-tunnel for low Reynolds numbers (from 5 Â 10 4 to 4.3 Â 10 5) and several angles of attack. As with the NACA0012, the acoustic spectrum is dominated by discrete tones. These tonal behaviors are divided into three different regimes. The first one is characterized by a dominant primary tone which is steady over time, surrounded by secondary peaks. The second consists of two unsteady primary tones associated with secondary peaks and the third consists of a hump dominated by several small peaks. A wavelet study allows one to identify an amplitude modulation of the acoustic signal mainly for the unsteady tonal regime. This amplitude modulation is equal to the frequency interval between two successive tones. Finally, a bispectral analysis explains the presence of tones at higher frequencies

FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels

Temporal point processes (TPP) are a natural tool for modeling event-based data. Among all TPP models, Hawkes processes have proven to be the most widely used, mainly due to their simplicity and computational ease when considering exponential or non-parametric kernels. Although non-parametric kernels are an option, such models require large datasets. While exponential kernels are more data efficient and relevant for certain applications where events immediately trigger more events, they are ill-suited for applications where latencies need to be estimated, such as in neuroscience. This work aims to offer an efficient solution to TPP inference using general parametric kernels with finite support. The developed solution consists of a fast L2 gradient-based solver leveraging a discretized version of the events. After supporting the use of discretization theoretically, the statistical and computational efficiency of the novel approach is demonstrated through various numerical experiments. Finally, the effectiveness of the method is evaluated by modeling the occurrence of stimuli-induced patterns from brain signals recorded with magnetoencephalography (MEG). Given the use of general parametric kernels, results show that the proposed approach leads to a more plausible estimation of pattern latency compared to the state-of-the-art

Prostate biopsies guided by three-dimensional real-time (4-D) transrectal ultrasonography on a phantom: comparative study versus two-dimensional transrectal ultrasound-guided biopsies

OBJECTIVE: This study evaluated the accuracy in localisation and distribution of real-time three-dimensional (4-D) ultrasound-guided biopsies on a prostate phantom. METHODS: A prostate phantom was created. A three-dimensional real-time ultrasound system with a 5.9MHz probe was used, making it possible to see several reconstructed orthogonal viewing planes in real time. Fourteen operators performed biopsies first under 2-D then 4-D transurethral ultrasound (TRUS) guidance (336 biopsies). The biopsy path was modelled using segmentation in a 3-D ultrasonographic volume. Special software was used to visualise the biopsy paths in a reference prostate and assess the sampled area. A comparative study was performed to examine the accuracy of the entry points and target of the needle. Distribution was assessed by measuring the volume sampled and a redundancy ratio of the sampled prostate. RESULTS: A significant increase in accuracy in hitting the target zone was identified using 4-D ultrasonography as compared to 2-D. There was no increase in the sampled volume or improvement in the biopsy distribution with 4-D ultrasonography as compared to 2-D. CONCLUSION: The 4-D TRUS guidance appears to show, on a synthetic model, an improvement in location accuracy and in the ability to reproduce a protocol. The biopsy distribution does not seem improved