Elementary Derivative Tasks and Neural Net Multiscale Analysis of Tasks

Neural nets are known to be universal approximators. In particular, formal neurons implementing wavelets have been shown to build nets able to approximate any multidimensional task. Such very specialized formal neurons may be, however, difficult to obtain biologically and/or industrially. In this paper we relax the constraint of a strict ``Fourier analysis'' of tasks. Rather, we use a finite number of more realistic formal neurons implementing elementary tasks such as ``window'' or ``Mexican hat'' responses, with adjustable widths. This is shown to provide a reasonably efficient, practical and robust, multifrequency analysis. A training algorithm, optimizing the task with respect to the widths of the responses, reveals two distinct training modes. The first mode induces some of the formal neurons to become identical, hence promotes ``derivative tasks''. The other mode keeps the formal neurons distinct.Comment: latex neurondlt.tex, 7 files, 6 figures, 9 pages [SPhT-T01/064], submitted to Phys. Rev.

A comparative study of two formal semantics of the SIGNAL language

International audienceSIGNAL is a part of the synchronous languages family, which are broadly used in the design of safety-critical real-time systems such as avionics, space systems, and nuclear power plants. There exist several semantics for SIGNAL, such as denotational semantics based on traces (called trace semantics), denotational semantics based on tags (called tagged model semantics), operational semantics presented by structural style through an inductive definition of the set of possible transitions, operational semantics defined by synchronous transition systems (STS), etc. However, there is little research about the equivalence between these semantics.In this work, we would like to prove the equivalence between the trace semantics and the tagged model semantics, to get a determined and precise semantics of the SIGNAL language. These two semantics have several different definitions respectively, we select appropriate ones and mechanize them in the Coq platform, the Coq expressions of the abstract syntax of SIGNAL and the two semantics domains, i.e., the trace model and the tagged model, are also given. The distance between these two semantics discourages a direct proof of equivalence. Instead, we transformthem to an intermediate model, which mixes the features of both the trace semantics and the tagged model semantics. Finally, we get a determined and precise semantics of SIGNAL

The scattering of muons in low Z materials

This paper presents the measurement of the scattering of 172 MeV/c muons in assorted materials, including liquid hydrogen, motivated by the need to understand ionisation cooling for muon acceleration. Data are compared with predictions from the Geant 4 simulation code and this simulation is used to deconvolute detector effects. The scattering distributions obtained are compared with the Moliere theory of multiple scattering and, in the case of liquid hydrogen, with ELMS. With the exception of ELMS, none of the models are found to provide a good description of the data. The results suggest that ionisation cooling will work better than would be predicted by Geant 4.7.0p01.Comment: pdfeTeX V 3.141592-1.21a-2.2, 30 pages with 22 figure

Unfolding-based Diagnosis of Systems with an Evolving Topology

We propose a framework for model-based diagnosis of systems with mobility and variable topologies, modelled as graph transformation systems. Generally speaking, model-based diagnosis is aimed at constructing explanations of observed faulty behaviours on the basis of a given model of the system. Since the number of possible explanations may be huge, we exploit the unfolding as a compact data structure to store them, along the lines of previous work dealing with Petri net models. Given a model of a system and an observation, the explanations can be constructed by unfolding the model constrained by the observation, and then removing incomplete explanations in a pruning phase. The theory is formalised in a general categorical setting: constraining the system by the observation corresponds to taking a product in the chosen category of graph grammars, so that the correctness of the procedure can be proved by using the fact that the unfolding is a right adjoint and thus it preserves products. The theory should hence be easily applicable to a wide class of system models, including graph grammars and Petri nets

A Retrospective Look at the Monitoring and Checking (MaC) Framework

The Monitoring and Checking (MaC) project gave rise to a framework for runtime monitoring with respect to formally specified properties, which later came to be known as runtime verification. The project also built a pioneering runtime verification tool, Java-MaC, that was an instantiation of the approach to check properties of Java programs. In this retrospective, we discuss decisions made in the design of the framework and summarize lessons learned in the course of the project

Paraphrastic Reformulations in Spoken Corpora

International audienceOur work addresses the automatic detection of paraphrastic reformulation in French spoken corpora. The proposed approach is syn-tagmatic. It is based on specific markers and the specificities of the spoken language. Manual multi-dimensional annotation performed by two annotators provides fine-grained reference data. An automatic method is proposed in order to decide whether sentences contain or not paraphras-tic relations. The obtained results show up to 66.4% precision. Analysis of the manual annotations indicates that few paraphrastic segments show morphological modifications (inflection, derivation or compounding) and that the syntactic equivalence between the segments is seldom respected, as these usually belong to different syntactic categories

Triterpenoid modulation of IL-17 and Nrf-2 expression ameliorates neuroinflammation and promotes remyelination in autoimmune encephalomyelitis

Inflammatory cytokines and endogenous anti-oxidants are variables affecting disease progression in multiple sclerosis (MS). Here we demonstrate the dual capacity of triterpenoids to simultaneously repress production of IL-17 and other pro-inflammatory mediators while exerting neuroprotective effects directly through Nrf2-dependent induction of anti-oxidant genes. Derivatives of the natural triterpene oleanolic acid, namely CDDO-trifluoroethyl-amide (CDDO-TFEA), completely suppressed disease in a murine model of MS, experimental autoimmune encephalomyelitis (EAE), by inhibiting Th1 and Th17 mRNA and cytokine production. Encephalitogenic T cells recovered from treated mice were hypo-responsive to myelin antigen and failed to adoptively transfer the disease. Microarray analyses showed significant suppression of pro-inflammatory transcripts with concomitant induction of anti-inflammatory genes including Ptgds and Hsd11b1. Finally, triterpenoids induced oligodendrocyte maturation in vitro and enhanced myelin repair in an LPC-induced non-inflammatory model of demyelination in vivo. These results demonstrate the unique potential of triterpenoid derivatives for the treatment of neuroinflammatory disorders such as MS