Intermédialité et déconstruction de la fiction chez Alain Robbe-Gillet : analyse comparative de "La maison de rendez-vous" et de "L'homme qui ment"

Alain Robbe-Grillet, d’abord connu en tant que romancier, a dès le début des années 1960 partagé son temps entre le cinéma et la littérature. Après avoir fourni le scénario de L’année dernière à Marienbad, il est passé derrière la caméra et a réalisé une dizaine de films qui, tant par leur forme que leur propos, poursuivent les recherches esthétiques entreprises dans sa pratique littéraire. Plus encore, il nous semble que le début de cette aventure cinématographique marque un tournant dans son œuvre. Alors que le point de vue qui portait les premiers romans — point de vue que les critiques ont rapproché de celui d’une caméra —, marquait déjà la dimension intermédiale de son œuvre, il apparaît que son passage dans la chaise du réalisateur a été le germe d’une radicalisation de sa pratique. Ainsi, les romans et les films qui ont suivi possèdent une portée intermédiale beaucoup plus large. De fait, c’est l’ensemble de la narration qui s’y trouve remise en question par la mise en évidence des spécificités de chacun des médias et par la transposition de procédés propres à la littérature dans le film, et vice versa. C’est par une étude comparative de La maison de rendez-vous (1965) et de L’homme qui ment (1968) que nous montrons en quoi consiste la relation intermédiale que Robbe-Grillet établit entre les disciplines, en plus de mettre en évidence les mécaniques qui, ancrées dans la matérialité des médias, fondent le roman et le film

Caractérisation de la position 48 du récepteur phoQ de Salmonella enterica serovar typhimurium

La première partie de cette étude décrit la mise au point d'un test in vivo . Ce test utilise la luciférase comme gène rapporteur et permet de quantifier l'activité du récepteur PhoQ. Ce test est idéal pour la mesure de l'activité globale et de la régulation par le magnésium des différents mutants du récepteur PhoQ de Salmonella enterica serovar typhymurium obtenus par mutagenèse dirigée. De plus, cette étude démontre que l'ajout d'extension dépassant 8 acides aminés en C-terminal du récepteur PhoQ peut amener une plus grande phosphorylation de PhoP. La seconde partie de cette étude traite de la caractérisation de la position 48. Des études in vivo et in vitro démontrent que la mutation de la thréonine 48 du récepteur PhoQ conduit à la modification de l'équilibre kinase/phosphatase, et affecte le degré de phosphorylation de PhoP. Finalement, la cartographie par formation de ponts disulfures de la région environnant le résidu 48 suggère que ce dernier est positionné vers l'intérieur de l'interface de dimérisation."--Résumé abrégé par UM

Improving the numerical accuracy of programs by automatic transformation

The dangers of programs performing floatingpoint computations are well known. This is due to the sensitivity of the results to the way formulæ are written. These last years, several techniques have been proposed concerning the transformation of arithmetic expressions in order to improve their numerical accuracy and, in this article, we go one step further by automatically transforming larger pieces of code containing assignments and control structures. We define a set of transformation rules allowing the generation, under certain conditions and in polynomial time, of larger expressions by performing limited formal computations, possibly among several iterations of a loop. These larger expressions are better suited to improve, by reparsing, the numerical accuracy of the program results. We use abstract interpretation-based static analysis techniques to over-approximate the round-off errors in programs and during the transformation of expressions. A tool has been implemented and experimental results are presented concerning classical numerical algorithms and algorithms for embedded systems

Numerical Accuracy Improvement of Programs: Principles and Experiments

In general, the correctness of numerical computations of programs based on floating-point arithmetic is not intuitive and developers hope to compute an accurate result without guaranty. To solve this problem, we procceed by automatic source to source transformation of programs to improve their numerical accuracy

Numerical Accuracy Improvement by Interprocedural Program Transformation

Floating-point numbers are used to approximate the exact real numbers in a wide range of domains like numerical simulations, embedded software, etc. However, floating-point numbers are a finite approximation of real numbers. In practice, this approximation may introduce round-off errors and this can lead to catastrophic results. To cope with this issue, we have developed a tool which corrects partly these round-off errors and which consequently improves the numerical accuracy of computations by automatically transforming programs in a source to source manner. Our transformation, relies on static analysis by abstract interpretation and operates on pieces of code with assignments, conditionals and loops. In former work, we have focused on the intraprocedural transformation of programs and, in this article, we introduce the interprocedural transformation to improve accuracy

Numerical program optimisation by automatic improvement of the accuracy of computations

Over the last decade, guaranteeing the accuracy of computations relying on the IEEE754 floating-point arithmetic has become increasingly complex. Failures, caused by small or large perturbations due to round-off errors, have been registered. To cope with this issue, we have developed a tool which corrects these errors by automatically transforming programs in a source to source manner. Our transformation, relying on static analysis by abstract abstraction, operates on pieces of code with assignments, conditionals and loops. By transforming programs, we can significantly optimize the numerical accuracy of computations by minimizing the error relatively to the exact result. In this article, we present two important desirable side-effects of our transformation. Firstly, we show that our transformed programs, executed in single precision, may compete with not transformed codes executed in double precision. Secondly, we show that optimizing the numerical accuracy of programs accelerates the convergence of numerical iterative methods. Both of these properties of our transformation are of great interest for numerical software

Data-types optimization for floating-point formats by program transformation

In floating-point arithmetic, a desirable property of computations is to be accurate, since in many industrial context small or large perturbations due to round-off errors may cause considerable damages. To cope with this matter of fact, we have developed a tool which corrects these errors by automatically transforming programs in a source to source manner. Our transformation, relying on static analysis by abstract abstraction, concerns pieces of code with assignments, conditionals and loops. By transforming programs, we can significantly optimize the numerical accuracy of computations by minimizing the error relatively to the exact result. An interesting side-effect of our technique is that more accurate computations may make it possible to use smaller data-types. In this article, we show that our transformed programs, executed in single precision, may compete with not transformed codes executed in double precision

Transformation of a PID Controller for Numerical Accuracy

Numerical programs performing floating-point computations are very sensitive to the way formulas are written. Several techniques have been proposed concerning the transformation of expressions in order to improve their accuracy and now we aim at going a step further by automatically transforming larger pieces of code containing several assignments and control structures. This article presents a case study in this direction. We consider a PID controller and we transform its code in order to improve its accuracy. The experimental data obtained when we compare the different versions of the code (which are mathematically equivalent) show that those transformations have a significant impact on the accuracy of the computation

Impact of Accuracy Optimization on the Convergence of Numerical Iterative Methods

Among other objectives, rewriting programs serves as a useful technique to improve numerical accuracy. However, this optimization is not intuitive and this is why we switch to automatic transformation techniques. We are interested in the optimization of numerical programs relying on the IEEE754 oating-point arithmetic. In this article, our main contribution is to study the impact of optimizing the numerical accuracy of programs on the time required by numerical iterative methods to converge. To emphasize the usefulness of our tool, we make it optimize several examples of numerical methods such as Jacobi's method, Newton-Raphson's method, etc. We show that significant speedups are obtained in terms of number of iterations, time and ops

Transformation of a PID Controller for Numerical Accuracy

Numerical programs performing floating-point computations are very sensitive to the way formulas are written. Several techniques have been proposed concerning the transformation of expressions in order to improve their accuracy and now we aim at going a step further by automatically transforming larger pieces of code containing several assignments and control structures. This article presents a case study in this direction. We consider a PID controller and we transform its code in order to improve its accuracy. The experimental data obtained when we compare the different versions of the code (which are mathematically equivalent) show that those transformations have a significant impact on the accuracy of the computation