University of Paris

About: University of Paris is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Medicine. The organization has 102426 authors who have published 174180 publications receiving 5041753 citations. The organization is also known as: Sorbonne.

Improved Cosmological Constraints from New, Old, and Combined Supernova Data Sets

Abstract: We present a new compilation of Type Ia supernovae (SNe Ia), a new data set of low-redshift nearby-Hubble-flow SNe, and new analysis procedures to work with these heterogeneous compilations This "Union" compilation of 414 SNe Ia, which reduces to 307 SNe after selection cuts, includes the recent large samples of SNe Ia from the Supernova Legacy Survey and ESSENCE Survey, the older data sets, as well as the recently extended data set of distant supernovae observed with the Hubble Space Telescope (HST) A single, consistent, and blind analysis procedure is used for all the various SN Ia subsamples, and a new procedure is implemented that consistently weights the heterogeneous data sets and rejects outliers We present the latest results from this Union compilation and discuss the cosmological constraints from this new compilation and its combination with other cosmological measurements (CMB and BAO) The constraint we obtain from supernovae on the dark energy density is ΩΛ = 0713+ 0027−0029(stat)+ 0036−0039(sys) , for a flat, ΛCDM universe Assuming a constant equation of state parameter, w, the combined constraints from SNe, BAO, and CMB give w = − 0969+ 0059−0063(stat)+ 0063−0066(sys) While our results are consistent with a cosmological constant, we obtain only relatively weak constraints on a w that varies with redshift In particular, the current SN data do not yet significantly constrain w at z > 1 With the addition of our new nearby Hubble-flow SNe Ia, these resulting cosmological constraints are currently the tightest available

Mutations in the gene encoding the synaptic scaffolding protein SHANK3 are associated with autism spectrum disorders.

Abstract: SHANK3 (also known as ProSAP2) regulates the structural organization of dendritic spines and is a binding partner of neuroligins; genes encoding neuroligins are mutated in autism and Asperger syndrome. Here, we report that a mutation of a single copy of SHANK3 on chromosome 22q13 can result in language and/or social communication disorders. These mutations concern only a small number of individuals, but they shed light on one gene dosage-sensitive synaptic pathway that is involved in autism spectrum disorders.

Time reversal of ultrasonic fields. I. Basic principles

Abstract: Time reversal of ultrasonic fields represents a way to focus through an inhomogeneous medium. This may be accomplished by a time-reversal mirror (TRM) made from an array of transmit-receive transducers that respond linearly and allow the incident acoustic pressure to be sampled. The pressure field is then time-reversed and re-emitted. This process can be used to focus through inhomogeneous media on a reflective target that behaves as an acoustic source after being insonified. The time-reversal approach is introduced in a discussion of the classical techniques used for focusing pulsed waves through inhomogeneous media (adaptive time-delay techniques). Pulsed wave time-reversal focusing is shown using reciprocity valid in inhomogeneous medium to be optimal in the sense that it realizes the spatial-temporal matched filter to the inhomogeneous propagation transfer function between the array and the target. The research on time-reversed wave fields has also led to the development of new concepts that are described: time-reversal cavity that extends the concept of the TRM, and iterative time-reversal processing for automatic sorting of targets according to their reflectivity and resonating of extended targets. >

The Variational Approach to Fracture

Abstract: 1 Introduction 2 Going variational 2.1 Griffith's theory 2.2 The 1-homogeneous case - A variational equivalence 2.3 Smoothness - The soft belly of Griffith's formulation 2.4 The non 1-homogeneous case - A discrete variational evolution 2.5 Functional framework - A weak variational evolution 2.6 Cohesiveness and the variational evolution 3 Stationarity versus local or global minimality - A comparison 3.1 1d traction 3.1.1 The Griffith case - Soft device 3.1.2 The Griffith case - Hard device 3.1.3 Cohesive case - Soft device 3.1.4 Cohesive case - Hard device 3.2 A tearing experiment 4 Initiation 4.1 Initiation - The Griffith case 4.1.1 Initiation - The Griffith case - Global minimality 4.1.2 Initiation - The Griffith case - Local minimality 4.2 Initiation - The cohesive case 4.2.1 Initiation - The cohesive 1d case - Stationarity 4.2.2 Initiation - The cohesive 3d case - Stationarity 4.2.3 Initiation - The cohesive case - Global minimality 5 Irreversibility 5.1 Irreversibility - The Griffith case - Well-posedness of the variational evolution 5.1.1 Irreversibility - The Griffith case - Discrete evolution 5.1.2 Irreversibility - The Griffith case - Global minimality in the limit 5.1.3 Irreversibility - The Griffith case - Energy balance in the limit 5.1.4 Irreversibility - The Griffith case - The time-continuous evolution 5.2 Irreversibility - The cohesive case 6 Path 7 Griffith vs. Barenblatt 8 Numerics and Griffith 8.1 Numerical approximation of the energy 8.1.1 The first time step 8.1.2 Quasi-static evolution 8.2 Minimization algorithm 8.2.1 The alternate minimization algorithm 8.2.2 The backtracking algorithm 8.3 Numerical experiments 8.3.1 The 1D traction (hard device) 8.3.2 The Tearing experiment 8.3.3 Revisiting the 2D traction experiment on a fiber reinforced matrix 9 Fatigue 9.1 Peeling Evolution 9.2 The limitfatigue law when d tends to 0 9.3 A variational formulation for fatigue 9.3.1 Peeling revisited 9.3.2 Generalization Appendix Glossary References.