Modélisation incrémentale par méthode bayésienne

Les modèles incrémentaux sont des modèles statistiques qui ont été développés initialement dans le domaine du marketing. Ils sont composés de deux groupes, un groupe contrôle et un groupe traitement, tous deux comparés par rapport à une variable réponse binaire (le choix de réponses est « oui » ou « non »). Ces modèles ont pour but de détecter l’effet du traitement sur les individus à l’étude. Ces individus n’étant pas tous des clients, nous les appellerons : « prospects ». Cet effet peut être négatif, nul ou positif selon les caractéristiques des individus composants les différents groupes. Ce mémoire a pour objectif de comparer des modèles incrémentaux d’un point de vue bayésien et d’un point de vue fréquentiste. Les modèles incrémentaux utilisés en pratique sont ceux de Lo (2002) et de Lai (2004). Ils sont initialement réalisés d’un point de vue fréquentiste. Ainsi, dans ce mémoire, l’approche bayésienne est utilisée et comparée à l’approche fréquentiste. Les simulations sont e ectuées sur des données générées avec des régressions logistiques. Puis, les paramètres de ces régressions sont estimés avec des simulations Monte-Carlo dans l’approche bayésienne et comparés à ceux obtenus dans l’approche fréquentiste. L’estimation des paramètres a une influence directe sur la capacité du modèle à bien prédire l’effet du traitement sur les individus. Nous considérons l’utilisation de trois lois a priori pour l’estimation des paramètres de façon bayésienne. Elles sont choisies de manière à ce que les lois a priori soient non informatives. Les trois lois utilisées sont les suivantes : la loi bêta transformée, la loi Cauchy et la loi normale. Au cours de l’étude, nous remarquerons que les méthodes bayésiennes ont un réel impact positif sur le ciblage des individus composant les échantillons de petite taille.

Optimisation de l’extraction de lumière de scintillation dans les matrices de détecteurs pixellisés pour des applications en tomographie d’émission par positrons (TEP) et en tomodensitométrie (TDM)

Résumé : Les performances de détecteurs à scintillation, composés d’un cristal scintillateur couplé à un photodétecteur, dépendent de façon critique de l’efficacité de la collecte et de l’extraction des photons de scintillation du cristal vers le capteur. Dans les systèmes d’imagerie hautement pixellisés (e.g. TEP, TDM), les scintillateurs doivent être arrangés en matrices compactes avec des facteurs de forme défavorables pour le transport des photons, au détriment des performances du détecteur. Le but du projet est d’optimiser les performances de ces détecteurs pixels par l'identification des sources de pertes de lumière liées aux caractéristiques spectrales, spatiales et angulaires des photons de scintillation incidents sur les faces des scintillateurs. De telles informations acquises par simulation Monte Carlo permettent une pondération adéquate pour l'évaluation de gains atteignables par des méthodes de structuration du scintillateur visant à une extraction de lumière améliorée vers le photodétecteur. Un plan factoriel a permis d'évaluer la magnitude de paramètres affectant la collecte de lumière, notamment l'absorption des matériaux adhésifs assurant l'intégrité matricielle des cristaux ainsi que la performance optique de réflecteurs, tous deux ayant un impact considérable sur le rendement lumineux. D'ailleurs, un réflecteur abondamment utilisé en raison de ses performances optiques exceptionnelles a été caractérisé dans des conditions davantage réalistes par rapport à une immersion dans l'air, où sa réflectivité est toujours rapportée. Une importante perte de réflectivité lorsqu'il est inséré au sein de matrices de scintillateurs a été mise en évidence par simulations puis confirmée expérimentalement. Ceci explique donc les hauts taux de diaphonie observés en plus d'ouvrir la voie à des méthodes d'assemblage en matrices limitant ou tirant profit, selon les applications, de cette transparence insoupçonnée.

Commissioning of a Geant4 based treatment plan simulation tool : linac model and dicom-rt interface

A Geant4 based simulation tool has been developed to perform Monte Carlo modelling of a 6 MV VarianTM iX clinac. The computer aided design interface of Geant4 was used to accurately model the LINAC components, including the Millenium multi-leaf collimators (MLCs). The simulation tool was verified via simulation of standard commissioning dosimetry data acquired with an ionisation chamber in a water phantom. Verification of the MLC model was achieved by simulation of leaf leakage measurements performed using GafchromicTM film in a solid water phantom. An absolute dose calibration capability was added by including a virtual monitor chamber into the simulation. Furthermore, a DICOM-RT interface was integrated with the application to allow the simulation of treatment plans in radiotherapy. The ability of the simulation tool to accurately model leaf movements and doses at each control point was verified by simulation of a widely used intensity-modulated radiation therapy (IMRT) quality assurance (QA) technique, the chair test.

Stochastic simulation of chemical reactions in spatially complex media

Discrete stochastic simulations, via techniques such as the Stochastic Simulation Algorithm (SSA) are a powerful tool for understanding the dynamics of chemical kinetics when there are low numbers of certain molecular species. However, an important constraint is the assumption of well-mixedness and homogeneity. In this paper, we show how to use Monte Carlo simulations to estimate an anomalous diffusion parameter that encapsulates the crowdedness of the spatial environment. We then use this parameter to replace the rate constants of bimolecular reactions by a time-dependent power law to produce an SSA valid in cases where anomalous diffusion occurs or the system is not well-mixed (ASSA). Simulations then show that ASSA can successfully predict the temporal dynamics of chemical kinetics in a spatially constrained environment.

Stochastic simulation for spatial modelling of dynamic process in a living cell

One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.

Three dimensional simulation of a parabolic trough concentrator thermal collector

Parabolic Trough Concentrators (PTC) are the most proven solar collectors for solar thermal power plants, and are suitable for concentrating photovoltaic (CPV) applications. PV cells are sensitive to spatial uniformity of incident light and the cell operating temperature. This requires the design of CPV-PTCs to be optimised both optically and thermally. Optical modelling can be performed using Monte Carlo Ray Tracing (MCRT), with conjugate heat transfer (CHT) modelling using the computational fluid dynamics (CFD) to analyse the overall designs. This paper develops and evaluates a CHT simulation for a concentrating solar thermal PTC collector. It uses the ray tracing work by Cheng et al. (2010) and thermal performance data for LS-2 parabolic trough used in the SEGS III-VII plants from Dudley et al. (1994). This is a preliminary step to developing models to compare heat transfer performances of faceted absorbers for concentrating photovoltaic (CPV) applications. Reasonable agreement between the simulation results and the experimental data confirms the reliability of the numerical model. The model explores different physical issues as well as computational issues for this particular kind of system modeling. The physical issues include the resultant non-uniformity of the boundary heat flux profile and the temperature profile around the tube, and uneven heating of the HTF. The numerical issues include, most importantly, the design of the computational domain/s, and the solution techniques of the turbulence quantities and the near-wall physics. This simulation confirmed that optical simulation and the computational CHT simulation of the collector can be accomplished independently.

Computer simulation of scaffold degradation

Scaffolds are porous biocompatible materials with suitable microarchitectures that are designed to allow for cell adhesion, growth and proliferation. They are used in combination with cells in regenerative medicine to promote tissue regeneration by means of a controlled deposition of natural extracellular matrix by the hosted cells therein. This healing process is in many cases accompanied by scaffold degradation up to its total disappearance when the scaffold is made of a biodegradable material. This work presents a computational model that simulates the degradation of scaffolds. The model works with three-dimensional microstructures, which have been previously discretised into small cubic homogeneous elements, called voxels. The model simulates the evolution of the degradation of the scaffold using a Monte Carlo algorithm, which takes into account the curvature of the surface of the fibres. The simulation results obtained in this study are in good agreement with empirical degradation measurements performed by mass loss on scaffolds after exposure to an etching alkaline solution.

Simulation and visualization of self-assembled nanodevice networks synthesized via plasma–surface interaction

Using advanced visualization techniques, a comprehensive visualization of all the stages of the self-organized growth of internetworked nanostructures on plasma-exposed surface has been made. Atomistic kinetic Monte Carlo simulation for the initial stage of deposition, with 3-D visualization of the whole system and half-tone visualization of the density field of the adsorbed atoms, makes it possible to implement a multiscale predictive modeling of the development of the nanoscale system.

Simulation of ion flux distribution in conductive and nonconductive nanotip patterns

The distribution of flux of carbon-bearing cations over nanopatterned surfaces with conductive nanotips and nonconductive nanoislands is simulated using the Monte-Carlo technique. It is shown that the ion current is focused to nanotip surfaces when the negative substrate bias is low and only slightly perturbed at higher substrate biases. In the low-bias case, the mean horizontal ion displacement caused by the nanotip electric field exceeds 10 nm. However, at higher substrate biases, this value reduces down to 2 nm. In the nonconductive nanopattern case, the ion current distribution is highly nonuniform, with distinctive zones of depleted current density around the nanoislands. The simulation results suggest the efficient means to control ion fluxes in plasma-aided nanofabrication of ordered nanopatterns, such as nanotip microemitter structures and quantum dot or nanoparticle arrays. © World Scientific Publishing Company.

Exposure risk assessment and evaluation of the best management practice for controlling pesticide runoff from paddy fields. Part 2: Model simulation for the herbicide pretilachlor

BACKGROUND: Monitoring studies revealed high concentrations of pesticides in the drainage canal of paddy fields. It is important to have a way to predict these concentrations in different management scenarios as an assessment tool. A simulation model for predicting the pesticide concentration in a paddy block (PCPF-B) was evaluated and then used to assess the effect of water management practices for controlling pesticide runoff from paddy fields. RESULTS: The PCPF-B model achieved an acceptable performance. The model was applied to a constrained probabilistic approach using the Monte Carlo technique to evaluate the best management practices for reducing runoff of pretilachlor into the canal. The probabilistic model predictions using actual data of pesticide use and hydrological data in the canal showed that the water holding period (WHP) and the excess water storage depth (EWSD) effectively reduced the loss and concentration of pretilachlor from paddy fields to the drainage canal. The WHP also reduced the timespan of pesticide exposure in the drainage canal. CONCLUSIONS: It is recommended that: (1) the WHP be applied for as long as possible, but for at least 7 days, depending on the pesticide and field conditions; (2) an EWSD greater than 2 cm be maintained to store substantial rainfall in order to prevent paddy runoff, especially during the WHP.

Elastic property estimation using Ultrasound Assisted Optical Elastography through Remote Palpation - A simulation study - art. no. 61640Q

We propose an effective elastography technique in which an acoustic radiation force is used for remote palpation to generate localized tissue displacements, which are directly correlated to localized variations of tissue stiffness and are measured using a light probe in the same direction of ultrasound propagation. The experimental geometry has provision to input light beam along the ultrasound propagation direction, and hence it can be prealigned to ensure proper interception of the focal region by the light beam. Tissue-mimicking phantoms with homogeneous and isotropic mechanical properties of normal and malignant breast tissue are considered for the study. Each phantom is insonified by a focusing ultrasound transducer (1 MHz). The focal volume of the transducer and the ultrasound radiation force in the region are estimated through solving acoustic wave propagation through medium assuming average acoustic properties. The forward elastography problem is solved for the region of insonification assuming the Lame's parameters and Poisson's ratio, under Dirichlet boundary conditions which gives a distribution of displacement vectors. The direction of displacement, though presented spatial variation, is predominantly towards the ultrasound propagation direction. Using Monte Carlo (MC) simulation we have traced the photons through the phantom and collected the photons arriving at the detector on the boundary of the object in the direction of ultrasound. The intensity correlations are then computed from detected photons. The intensity correlation function computed through MC simulation showed a modulation whose strength is found to be proportional to the amplitude of displacement and inversely related to the storage (elastic) modulus. It is observed that when the storage modulus in the focal region is increased the computed displacement magnitude, as indicated by the depth of modulation in the intensity autocorrelation, decreased and the trend is approximately exponential.

Simulation of precipitation reactions in reverse micelles

Precipitation involving mixing of two sets of reverse micellar solutions-containing a reactant and precipitant respectively-has been analyzed. Particle formation in such systems has been simulated by a Monte Carlo (MC) scheme (Li, Y.; Park, C. W. Langmuir 1999, 15, 952), which however is very restrictive in its approach. We have simulated particle formation by developing a general Monte Carlo scheme, using the interval of quiescence technique (IQ). It uses Poisson distribution with realistic, low micellar occupancies of reactants, Brownian collision of micelles with coalescence efficiency, fission of dimers with binomial redispersion of solutes, finite nucleation rate of particles with critical number of molecules, and instantaneous particle growth. With the incorporation of these features, the previous work becomes a special case of our simulation. The present scheme was then used to predict experimental data on two systems. The first is the experimental results of Lianos and Thomas (Chem. Phys. Lett. 1986, 125, 299, J. Colloid Interface Sci. 1987, 117, 505) on formation of CdS nanoparticles. They reported the number of molecules in a particle as a function of micellar size and reactant concentrations, which have been predicted very well. The second is on the formation of Fe(OH)(3) nanoparticles, reported by Li and Park. Our simulation in this case provides a better prediction of the experimental particle size range than the prediction of the authors. The present simulation scheme is general and can be applied to explain nanoparticle formation in other systems.

Simulation of magnetovolume effects in Fe65Ni35 nanoparticles

We compare magnetovolume effects in bulk and nanoparticles by performing Monte Carlo simulations of a spin-analogous model with coupled spatial and magnetic degrees of freedom and chemical disorder. We find that correlations between surface and bulk atoms lead with decreasing particle size to a substantial modification of the magnetic and elastic behavior at low temperatures.

Cell-dynamical simulation of magnetic hysteresis in the two-dimensional Ising system

We present results from numerical simulations using a ‘‘cell-dynamical system’’ to obtain solutions to the time-dependent Ginzburg-Landau equation for a scalar, two-dimensional (2D), (Φ2)2 model in the presence of a sinusoidal external magnetic field. Our results confirm a recent scaling law proposed by Rao, Krishnamurthy, and Pandit [Phys. Rev. B 42, 856 (1990)], and are also in excellent agreement with recent Monte Carlo simulations of hysteretic behavior of 2D Ising spins by Lo and Pelcovits [Phys. Rev. A 42, 7471 (1990)].

Simulation and experimental study on compositional evolution of Li-Co in LiCoO(2) thin films during sputter deposition

The compositional evolution in sputter deposited LiCoO(2) thin films is influenced by process parameters involved during deposition. The electrochemical performance of these films strongly depends on their microstructure, preferential orientation and stoichiometry. The transport process of sputtered Li and Co atoms from the LiCoO(2) target to the substrate, through Ar plasma in a planar magnetron configuration, was investigated based on the Monte Carlo technique. The effect of sputtering gas pressure and the substrate-target distance (d(st)) on Li/Co ratio, as well as, energy and angular distribution of sputtered atoms on the substrate were examined. Stable Li/Co ratios have been obtained at 5 Pa pressure and d(st) in the range 5 11 cm. The kinetic energy and incident angular distribution of Li and Co atoms reaching the substrate have been found to be dependent on sputtering pressure. Simulations were extended to predict compositional variations in films prepared at various process conditions. These results were compared with the composition of films determined experimentally using x-ray photoelectron spectroscopy (XPS). Li/Co ratio calculated using XPS was in moderate agreement with that of the simulated value. The measured film thickness followed the same trend as predicted by simulation. These studies are shown to be useful in understanding the complexities in multicomponent sputtering. (C) 2011 American Institute of Physics. doi:10.1063/1.3597829]