Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

Inoculation methods under greenhouse conditions for evaluating soybean resistance to sudden death syndrome

The objectives of this work were to evaluate two greenhouse screening methods for sudden death syndrome (SDS) and to determine which one is best correlated with field resistance of soybean genotypes. The evaluations were done with three sets of genotypes that were classified as partially resistant, intermediate, and susceptible to SDS based on previous field evaluations. These three sets were independently evaluated for greenhouse SDS reactions using cone and tray inoculation methods. Plants were infected using grains of white sorghum [Sorghum bicolor (L.) Moench] infested with Fusarium solani f. sp. glycines. Foliar symptom severity was rated 21 days after emergence. The cone and field SDS ratings were significantly correlated and ranged from 0.69 for set 1 to 0.51 for set 3. Correlations of SDS ratings of genotypes between field and greenhouse tray ratings were significant for set 1 and not significant for set 2. The cone method showed the highest correlation with field results and is recommended to screen soybean genotypes for SDS resistance.

Todennäköisyyspohjaisen paloanalyysimenetelmän kehittäminen ydinvoimalaitoksella

Diplomityössä on tutustuttu ydinvoimalaitosten paloriskejä käsittelevään todennäköisyyspohjaiseen turvallisuusanalyysiin. Tavoitteena on ollut Olkiluoto 1 ja 2 laitosyksiköiden paloanalyysimenetelmän kehittäminen. Työssä esitetään paloanalyysin pääpiirteet, kaksi erilaista palotaajuuksien estimointimenetelmää sekä palojen leviämisen arviointimenetelmiä. Palotaajuuksien estimointimenetelmistä keskitytään Berryn menetelmän sekä NUREG/CR-6850-palotaajuuslaskentamenetelmän tarkasteluun. Palon leviämisen arvioinnissa on esitetty kolmen erilaisen virtausteknisen laskentatyökalun perusteet sekä palon leviämistodennäköisyyksiä arvioivan Probabilistic Fire Simulator (PFS) -ohjelman käyttöä. Työn aikana on laskettu molemmilla palotaajuuden estimointimenetelmillä palotaajuuksia eri tyyppisille huonetiloille. Berryn menetelmän palotaajuudet olivat pääosin alhaisempia kuin NUREG/CR-6850-menetelmällä lasketut palotaajuudet. Palon leviämistarkastelussa on tutkittu ydinvoimalaitoksen relehuoneen tulipaloa. PFS:n avulla laskettujen leviämistodennäköisyyksien arvoja on vertailtu TVO:n paloanalyysissa käytettyihin kvalitatiivisiin peittokertoimiin. Palon leviämistodennäköisyys eri osajärjestelmien välillä todettiin suuresti riippuvan analyysissaoletetuista vaurioitumislämpötiloista. Tutkittuja menetelmiä hyödyntäen diplomityössä kehitettiin paloanalyysimenetelmäkuvaus. Menetelmäkuvauksessa huonetilojen paloriskit kartoitetaan aluksi Berryn menetelmällä. Näin kaikille laitoksen huonetiloille saadaan arvioitua palotaajuus sekä paloalkutapahtumaluokkien sydänvauriotaajuus. Seuraavaksi suoritetaan valintamenettely, jossa valitut kriteerit täyttäville huonetiloille tehdään tarkentava palotaajuuslaskenta. Tarkentava palotaajuuslaskenta perustuu NUREG/CR-6850-menetelmän mukaisesti huonetilojen realistisiin syttymislähteisiin. Kriittisimpien huonetilojen osalta palon leviämisen arviointiin on tarkoitus hyödyntää numeerista simulointia.

Mass transfer and particleinteractions in granular systems and suspension flows

The purpose of this study was to investigate some important features of granular flows and suspension flows by computational simulation methods. Granular materials have been considered as an independent state ofmatter because of their complex behaviors. They sometimes behave like a solid, sometimes like a fluid, and sometimes can contain both phases in equilibrium. The computer simulation of dense shear granular flows of monodisperse, spherical particles shows that the collisional model of contacts yields the coexistence of solid and fluid phases while the frictional model represents a uniform flow of fluid phase. However, a comparison between the stress signals from the simulations and experiments revealed that the collisional model would result a proper match with the experimental evidences. Although the effect of gravity is found to beimportant in sedimentation of solid part, the stick-slip behavior associated with the collisional model looks more similar to that of experiments. The mathematical formulations based on the kinetic theory have been derived for the moderatesolid volume fractions with the assumption of the homogeneity of flow. In orderto make some simulations which can provide such an ideal flow, the simulation of unbounded granular shear flows was performed. Therefore, the homogeneous flow properties could be achieved in the moderate solid volume fractions. A new algorithm, namely the nonequilibrium approach was introduced to show the features of self-diffusion in the granular flows. Using this algorithm a one way flow can beextracted from the entire flow, which not only provides a straightforward calculation of self-diffusion coefficient but also can qualitatively determine the deviation of self-diffusion from the linear law at some regions nearby the wall inbounded flows. Anyhow, the average lateral self-diffusion coefficient, which was calculated by the aforementioned method, showed a desirable agreement with thepredictions of kinetic theory formulation. In the continuation of computer simulation of shear granular flows, some numerical and theoretical investigations were carried out on mass transfer and particle interactions in particulate flows. In this context, the boundary element method and its combination with the spectral method using the special capabilities of wavelets have been introduced as theefficient numerical methods to solve the governing equations of mass transfer in particulate flows. A theoretical formulation of fluid dispersivity in suspension flows revealed that the fluid dispersivity depends upon the fluid properties and particle parameters as well as the fluid-particle and particle-particle interactions.

Numerical evaluation of the modulus of longitudinal elasticity in structural round timber elements of the Eucalyptus genus

Currently, the standards that deal with the determination of the properties of rigidity and strength for structural round timber elements do not take in consideration in their calculations and mathematical models the influence of the existing irregularities in the geometry of these elements. This study has as objective to determine the effective value of the modulus of longitudinal elasticity for structural round timber pieces of the Eucalyptus citriodora genus by a technique of optimization allied to the Inverse Analysis Method, to the Finite Element Method and the Least Square Method.

Modelling of potentiometric ion sensors

Potentiometric ion sensors are a very important subgroup of electrochemical sensors, very attractive for practical applications due to their small size, portability, low-energy consumption, relatively low cost and not changing the sample composition. They are investigated by the researchers from many fields of science. The continuous development of this field creates the necessity for a detailed description of sensor response and the electrochemical processes important in the practical applications of ion sensors. The aim of this thesis is to present the existing models available for the description of potentiometric ion sensors as well as their applicability and limitations. This includes the description of the diffusion potential occurring at the reference electrodes. The wide range of existing models, from most idealised phase boundary models to most general models, including migration, is discussed. This work concentrates on the advanced modelling of ion sensors, namely the Nernst-Planck-Poisson (NPP) model, which is the most general of the presented models, therefore the most widely applicable. It allows the modelling of the transport processes occurring in ion sensors and generating the potentiometric response. Details of the solution of the NPP model (including the numerical methods used) are shown. The comparisons between NPP and the more idealized models are presented. The applicability of the model to describe the formation of diffusion potential in reference electrode, the lower detection limit of both ion-exchanger and neutral carrier electrodes and the effect of the complexation in the membrane are discussed. The model was applied for the description of both types of electrodes, i.e. with the inner filling solution and solidcontact electrodes. The NPP model allows the electrochemical methods other than potentiometry to be described. Application of this model in Electrochemical Impedance Spectroscopy is discussed and a possible use in chrono-potentiometry is indicated. By combining the NPP model with evolutionary algorithms, namely Hierarchical Genetic Strategy (HGS), a novel method allowing the facilitation of the design of ion sensors was created. It is described in detail in this thesis and its possible applications in the field of ion sensors are indicated. Finally, some interesting effects occurring in the ion sensors (i.e. overshot response and influence of anionic sites) as well as the possible applications of NPP in biochemistry are described.

Numerical Simulation of the Cavitation in the Hydrodynamic Lubrication of Journal Bearings: a Parallel Algorithm

In this paper we present an algorithm for the numerical simulation of the cavitation in the hydrodynamic lubrication of journal bearings. Despite the fact that this physical process is usually modelled as a free boundary problem, we adopted the equivalent variational inequality formulation. We propose a two-level iterative algorithm, where the outer iteration is associated to the penalty method, used to transform the variational inequality into a variational equation, and the inner iteration is associated to the conjugate gradient method, used to solve the linear system generated by applying the finite element method to the variational equation. This inner part was implemented using the element by element strategy, which is easily parallelized. We analyse the behavior of two physical parameters and discuss some numerical results. Also, we analyse some results related to the performance of a parallel implementation of the algorithm.

FE-analyysin soveltaminen S960 QC teräksisen I-profiilin äärikestävyyden määrittämisessä

Tässä työssä tutkittiin FE-analyysin soveltamista S960 QC teräksisen I-profiilin kestävyyden määrittämisessä. Työn tavoitteena oli tarkastella nykyisten suunnitteluohjeiden soveltuvuutta ultralujille teräksille ja koota ohjemateriaali I-profiilin optimoimisesta sekä FE-analyysin hyö-dyntämisestä I-profiilin staattisen ja dynaamisen kestävyyden määrittämisessä. I-profiili mitoitettiin ja optimoitiin Eurokoodi 3:ssa esitettyjen PL3 mukaisten mitoitusohjeiden avulla. Rakenteelle suoritettiin Eurokoodi 3:n ja IIW:n mukaiset lommahdus-, kiepahdus- ja vä-symiskestävyystarkastelut. Väsymistarkastelussa sovellettiin nimellisen jännityksen, rakenteelli-sen jännityksen ja tehollisen lovijännityksen menetelmiä sekä murtumismekaniikkaa. Rakenteel-lisen jännityksen menetelmässä sovellettiin lisäksi lineaarista ja parabolista pintaa pitkin ekstra-polointia, paksuuden yli linearisointia sekä Dong:in menetelmää. Lommahdus-, kiepahdus- ja väsymistarkasteluissa hyödynnettiin analyyttistä laskentaa, FE-analyysiä sekä Frank2d sovellusta. Tarkastelujen perusteella voidaan todeta, että analyyttisillä menetelmillä saadaan numeerisia me-netelmiä varmemmalla puolella olevia tuloksia. Lommahdustarkastelussa ero tulosten välillä on suurimmillaan 8 % ja kiepahdustarkastelussa suurimmillaan 20 % mutta väsymistarkastelussa saadut tulokset eroavat keskenään huomattavasti. Väsymistarkastelussa tehollisen lovijännityksen menetelmällä sekä rakenteellisen jännityksen menetelmän Dong:in menetelmällä saadaan huo-mattavasti muita menetelmiä pidempiä kestoikiä, kun taas yksinkertaisemmilla menetelmillä saa-dut kestoiät ovat lyhyempiä. Rakenteen kestävyyden määrittäminen analyyttisillä menetelmillä on melko helppoa, mutta tu-lokset ovat monesti liian konservatiivisia. FE-analyysillä saadaan puolestaan hyvin tarkkoja tu-loksia mallin ollessa yksityiskohtainen. Mallintaminen on kuitenkin aikaa ja resursseja vievää ja vaatii käyttökokemusta. FE-analyysin mahdolliset hyödyt on aina arvioitava tapauskohtaisesti tarkasteltavan geometrian, kuormitusten ja reunaehtojen perusteella.

Linear prediction in optical spectroscopy

A linear prediction procedure is one of the approved numerical methods of signal processing. In the field of optical spectroscopy it is used mainly for extrapolation known parts of an optical signal in order to obtain a longer one or deduce missing signal samples. The first is needed particularly when narrowing spectral lines for the purpose of spectral information extraction. In the present paper the coherent anti-Stokes Raman scattering (CARS) spectra were under investigation. The spectra were significantly distorted by the presence of nonlinear nonresonant background. In addition, line shapes were far from Gaussian/Lorentz profiles. To overcome these disadvantages the maximum entropy method (MEM) for phase spectrum retrieval was used. The obtained broad MEM spectra were further underwent the linear prediction analysis in order to be narrowed.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Consumer neuroscience: usability of brain imaging methods in marketing research

Consumer neuroscience (neuromarketing) is an emerging field of marketing research which uses brain imaging techniques to study neural conditions and processes that underlie consumption. The purpose of this study was to map this fairly new and growing field in Finland by studying the opinions of both Finnish consumers and marketing professionals towards it and comparing the opinions to the current consumer neuroscience literature, and based on that evaluate the usability of brain imaging techniques as a marketing research method. Mixed methods research design was chosen for this study. Quantitative data was collected from 232 consumers and 28 marketing professionals by means of online surveys. Both respondent groups had either neutral opinions or lacked knowledge about the four themes chosen for this study: benefits, limitations and challenges, ethical issues and future prospects of consumer neuroscience. Qualitative interview data was collected from 2 individuals from Finnish neuromarketing companies to deepen insights gained from quantitative research. The four interview themes were the same as in the surveys and the interviewees’ answers were mostly in line with the current literature, although more optimistic about the future of the field. The interviews also exposed a gap between academic consumer neuroscience research and practical level applications. The results of this study suggest that there are still many unresolved challenges and relevant populations either have neutral opinions or lack information about consumer neuroscience. The practical level applications are, however, already being successfully used and this new field of marketing research is growing both globally and in Finland.

Consumer neuroscience: usability of brain imaging methods in marketing research

Consumer neuroscience (neuromarketing) is an emerging field of marketing research which uses brain imaging techniques to study neural conditions and processes that underlie consumption. The purpose of this study was to map this fairly new and growing field in Finland by studying the opinions of both Finnish consumers and marketing professionals towards it and comparing the opinions to the current consumer neuroscience literature, and based on that evaluate the usability of brain imaging techniques as a marketing research method. Mixed methods research design was chosen for this study. Quantitative data was collected from 232 consumers and 28 marketing professionals by means of online surveys. Both respondent groups had either neutral opinions or lacked knowledge about the four themes chosen for this study: benefits, limitations and challenges, ethical issues and future prospects of consumer neuroscience. Qualitative interview data was collected from 2 individuals from Finnish neuromarketing companies to deepen insights gained from quantitative research. The four interview themes were the same as in the surveys and the interviewees’ answers were mostly in line with the current literature, although more optimistic about the future of the field. The interviews also exposed a gap between academic consumer neuroscience research and practical level applications. The results of this study suggest that there are still many unresolved challenges and relevant populations either have neutral opinions or lack information about consumer neuroscience. The practical level applications are, however, already being successfully used and this new field of marketing research is growing both globally and in Finland.

La méthode IIM pour une membrane immergée dans un fluide incompressible

La méthode IIM (Immersed Interface Method) permet d'étendre certaines méthodes numériques à des problèmes présentant des discontinuités. Elle est utilisée ici pour étudier un fluide incompressible régi par les équations de Navier-Stokes, dans lequel est immergée une membrane exerçant une force singulière. Nous utilisons une méthode de projection dans une grille de différences finies de type MAC. Une dérivation très complète des conditions de saut dans le cas où la viscosité est continue est présentée en annexe. Deux exemples numériques sont présentés : l'un sans membrane, et l'un où la membrane est immobile. Le cas général d'une membrane mobile est aussi étudié en profondeur.

Étude numérique des origines hémodynamiques des oscillations dans des réseaux de capillaires

En simulant l’écoulement du sang dans un réseau de capillaires (en l’absence de contrôle biologique), il est possible d’observer la présence d’oscillations de certains paramètres comme le débit volumique, la pression et l’hématocrite (volume des globules rouges par rapport au volume du sang total). Ce comportement semble être en concordance avec certaines expériences in vivo. Malgré cet accord, il faut se demander si les fluctuations observées lors des simulations de l’écoulement sont physiques, numériques ou un artefact de modèles irréalistes puisqu’il existe toujours des différences entre des modélisations et des expériences in vivo. Pour répondre à cette question de façon satisfaisante, nous étudierons et analyserons l’écoulement du sang ainsi que la nature des oscillations observées dans quelques réseaux de capillaires utilisant un modèle convectif et un modèle moyenné pour décrire les équations de conservation de masse des globules rouges. Ces modèles tiennent compte de deux effets rhéologiques importants : l’effet Fåhraeus-Lindqvist décrivant la viscosité apparente dans un vaisseau et l’effet de séparation de phase schématisant la distribution des globules rouges aux points de bifurcation. Pour décrire ce dernier effet, deux lois de séparation de phase (les lois de Pries et al. et de Fenton et al.) seront étudiées et comparées. Dans ce mémoire, nous présenterons une description du problème physiologique (rhéologie du sang). Nous montrerons les modèles mathématiques employés (moyenné et convectif) ainsi que les lois de séparation de phase (Pries et al. et Fenton et al.) accompagnés d’une analyse des schémas numériques implémentés. Pour le modèle moyenné, nous employons le schéma numérique explicite traditionnel d’Euler ainsi qu’un nouveau schéma implicite qui permet de résoudre ce problème d’une manière efficace. Ceci est fait en utilisant une méthode de Newton- Krylov avec gradient conjugué préconditionné et la méthode de GMRES pour les itérations intérieures ainsi qu’une méthode quasi-Newton (la méthode de Broyden). Cette méthode inclura le schéma implicite d’Euler et la méthode des trapèzes. Pour le schéma convectif, la méthode explicite de Kiani et al. sera implémentée ainsi qu’une nouvelle approche implicite. La stabilité des deux modèles sera également explorée. À l’aide de trois différentes topologies, nous comparerons les résultats de ces deux modèles mathématiques ainsi que les lois de séparation de phase afin de déterminer dans quelle mesure les oscillations observées peuvent être attribuables au choix des modèles mathématiques ou au choix des méthodes numériques.

Méthodes numériques pour la capture et la résolution des discontinuités dans les solutions des systèmes hyperboliques

Réalisé en majeure partie sous la tutelle de feu le Professeur Paul Arminjon. Après sa disparition, le Docteur Aziz Madrane a pris la relève de la direction de mes travaux.