Analyse et modélisation de la réponse des détecteurs du projet PICASSO pour la recherche de la matière sombre

Les mesures cosmologiques les plus récentes ont montré la présence d’un type de matière exotique constituant 85% de la masse de l’univers. Ce type de matière non baryonique serait formé de particules neutres, non relativistes, massives et interagissant faiblement avec la matière baryonique. L’ensemble des candidats est regroupé sous le nom générique WIMP (Weakly Interactive Massive Particles). L’expérience PICASSO (Projet d’Identification des CAndidats Supersymétriques de la matière SOmbre) est une expérience utilisant des détecteurs à seuil d’énergie contenant des gouttelettes surchauffées constituées de C4F10. Cette technique de détection est basée sur le principe de la chambre à bulles. Le projet PICASSO a pour but de détecter directement une particule de matière sombre. Le principe de détection est qu’une particule de matière sombre interagissant avec le liquide actif engendre un recul nucléaire du 19F. L’énergie de recul serait suffisante pour engendrer une transition de phase accompagnée d’un signal acoustique enregistrée par des senseurs piézoélectriques. Dans le cadre de ce mémoire, une simulation du taux de comptage de l’étalonnage des détecteurs PICASSO soumis à des neutrons monoénergétiques a été effectuée en utilisant la théorie de Seitz qui décrit les critères pour qu’une transition de phase ait lieu pour un liquide en état de surchauffe. De plus, un modèle calculant le signal acoustique émis lors d’une transition de phase engendré par différents types de radiations a été créé permettant de caractériser la discrimination entre différents bruits de fond en fonction de l’énergie de seuil. Finalement, un outil d’analyse, la localisation des évènements, a été utilisé pour appliquer des coupures sur le volume dans le but d’améliorer la discrimination alpha-neutron.

Les effets de la stimulation électrique transcrânienne à courant direct appliquée au cortex somatosensoriel primaire sur la perception vibrotactile

La stimulation électrique transcrânienne à courant direct (tDCS) est une technique non invasive de neuromodulation qui modifie l’excitabilité corticale via deux grosses électrodes de surface. Les effets dépendent de la polarité du courant, anodique = augmentation de l’excitabilité corticale et cathodique = diminution. Chez l’humain, il n’existe pas de consensus sur des effets de la tDCS appliquée au cortex somatosensoriel primaire (S1) sur la perception somesthésique. Nous avons étudié la perception vibrotactile (20 Hz, amplitudes variées) sur le majeur avant, pendant et après la tDCS appliquée au S1 controlatéral (anodale, a; cathodale, c; sham, s). Notre hypothèse « shift-gain » a prédit une diminution des seuils de détection et de discrimination pour la tDCS-a (déplacement vers la gauche de la courbe stimulus-réponse et une augmentation de sa pente). On attendait les effets opposés avec la tDCS-c, soit une augmentation des seuils (déplacement à droite et diminution de la pente). Chez la majorité des participants, des diminutions des seuils ont été observées pendant et immédiatement suivant la tDCS-a (1 mA, 20 min) en comparaison à la stimulation sham. Les effets n’étaient plus présents 30 min plus tard. Une diminution du seuil de discrimination a également été observée pendant, mais non après la tDCS-c (aucun effet pour détection). Nos résultats supportent notre hypothèse, uniquement pour la tDCS-a. Une suite logique serait d’étudier si des séances répétées de tDCS-a mènent à des améliorations durables sur la perception tactile. Ceci serait bénéfique pour la réadaptation sensorielle (ex. suite à un accident vasculaire cérébral).

En direct de l'EBSI, no 27

En direct de l'EBSI, la revue des diplômés de l'EBSI, est publiée annuellement par l'École de bibliothéconomie et des sciences de l'information (EBSI) de l'Université de Montréal. Une version imprimée a aussi été produite de 1988 à 2010.

Optimization of pH and Direct Imaging Conditions of Complexed Methylene Blue Sensitized Poly(vinyl chloride) Films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4×5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

Optimization of pH and Direct Imaging Conditions of Complexed Methylene Blue Sensitized Poly(vinyl chloride) Films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4×5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

Optimization of pH and direct imaging conditions of complexed methylene blue sensitized poly(vinyl chloride) films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4 . 5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

PVC Supported Liquid Membrane and Carbon Paste Potentiometric Sensors Incorporating a Mn(III)-Porphyrin for the Direct Determination of Undissociated Paracetamol

PVC supported liquid membrane and carbon paste potentiometric sensors incorporating an Mn(III)-porphyrin complex as a neutral host molecule were developed for the determination of paracetamol. The measurements were carried out in solution at pH 5.5. Under such conditions paracetamol exists as a neutral molecule. The mechanism of molecular recognition between the Mn(III)-porphyrin and paracetamol, leading to potentiometric signal generation, is discussed.The sensitivity and selectivity toward paracetamol of carbon paste and polymeric liquid membrane electrodes incorporating an Mn(III)-porphyrin host were compared. The applicability of these sensors to the direct determination of paracetamol was checked by performing a recovery test in human plasma.

Physicochemical and Biochemical Characterization of Enzymes Immobilized on lnorganic Matrices

Biotechnology is currently considered as a useful altemative to conventional process technology in industrial and catalytic fields. The increasing awareness of the need to create green and sustainable production processes in all fields of chemistry has stimulated materials scientists to search for innovative catalysts supports. lmmobilization of enzymes in inorganic matrices is very useful in practical applications due to the preserved stability and catalytic activity of the immobilized enzymes under extreme conditions. Nanostructured inorganic, organic or hybrid organic-inorganic nanocomposites present paramount advantages to facilitate integration and miniaturization of the devices (nanotechnologies), thus affording a direct connection between the inorganic, organic and biological worlds. These properties, combined with good chemical stability, make them competent candidates for designed biocatalysts, protein-separation devices, drug delivery systems, and biosensors Aluininosilicate clays and layered double hydroxides, displaying, respectively, cation and anion exchange properties, were found to be attractive materials for immobilization because of their hydrophilic, swelling and porosity properties, as well as their mechanical and thermal stability.The aim of this study is the replacement of inorganic catalysts by immobilized lipases to obtain purer and healthier products.Mesocellular silica foams were synthesized by oil-in-water microemulsion templating route and were functionalized with silane and glutaraldehyde. " The experimental results from IR spectroscopy and elemental analysis demonstrated the presence of immobilized lipase and also functionalisation with silane and glutaraldehyde on the supports.The present work is a comprehensive study on enzymatic synthesis of butyl isobutyrate through esterification reaction using lipase immobilized onto mesocellular siliceous foams and montmorillonite K-10 via adsorption and covalent binding. Moreover, the irnrnobil-ization does not modify the nature of the kinetic mechanism proposed which is of the Bi-Bi Ping—Pong type with inhibition by n-butanol. The immobilized biocatalyst can be commercially exploited for the synthesis of other short chain flavor esters. Mesocellular silica foams (MCF) were synthesized by microemusion templating method via two different routes (hydrothermal and room temperature). and were functionalized with silane and glutaraldehyde. Candida rugosa lipase was adsorbed onto MCF silica and clay using heptane as the coupling medium for reactions in non-aqueous media. I From XRD results, a slight broadening and lowering of d spacing values after immobilization and modification was observed in the case of MCF 160 and MCF35 but there was no change in the d-spacing in the case of K-10 which showed that the enzymes are adsorbed only on the external surface. This was further confirmed from the nitrogen adsorption measurements

Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

State-selective study of the direct double photoionization of the Ne valence shell

Cross sections for double photoionization of the Ne L shell into the 2s2p{^5 3}P^0} and ^1P^0 and the 2s^02p^6 ^1S^e states were measured for energies from threshold up to 150 eV, using photon induced fluorescence spectroscopy. Both 2s2p^5 channels were observed with comparable magnitude in contradiction to a propensity rule based on the Wannier-Peterkop-Rau theory. A comparison of the summed ^3P^0 and ^1P^0 cross sections with MBPT calculations results in a deviation of 50%.

Reinforcement Learning by Policy Search

One objective of artificial intelligence is to model the behavior of an intelligent agent interacting with its environment. The environment's transformations can be modeled as a Markov chain, whose state is partially observable to the agent and affected by its actions; such processes are known as partially observable Markov decision processes (POMDPs). While the environment's dynamics are assumed to obey certain rules, the agent does not know them and must learn. In this dissertation we focus on the agent's adaptation as captured by the reinforcement learning framework. This means learning a policy---a mapping of observations into actions---based on feedback from the environment. The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment. The set of policies is constrained by the architecture of the agent's controller. POMDPs require a controller to have a memory. We investigate controllers with memory, including controllers with external memory, finite state controllers and distributed controllers for multi-agent systems. For these various controllers we work out the details of the algorithms which learn by ascending the gradient of expected cumulative reinforcement. Building on statistical learning theory and experiment design theory, a policy evaluation algorithm is developed for the case of experience re-use. We address the question of sufficient experience for uniform convergence of policy evaluation and obtain sample complexity bounds for various estimators. Finally, we demonstrate the performance of the proposed algorithms on several domains, the most complex of which is simulated adaptive packet routing in a telecommunication network.