Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Jatkuvavaletun teräksen leikkaussuunnitelman optimointi

Teollisuuden tuotannon eri prosessien optimointi on hyvin ajankohtainen aihe. Monet ohjausjärjestelmät ovat ajalta, jolloin tietokoneiden laskentateho oli hyvin vaatimaton nykyisiin verrattuna. Työssä esitetään tuotantoprosessi, joka sisältää teräksen leikkaussuunnitelman muodostamisongelman. Valuprosessi on yksi teräksen valmistuksen välivaiheita. Siinä sopivaan laatuun saatettu sula teräs valetaan linjastoon, jossa se jähmettyy ja leikataan aihioiksi. Myöhemmissä vaiheissa teräsaihioista muokataan pienempiä kokonaisuuksia, tehtaan lopputuotteita. Jatkuvavaletut aihiot voidaan leikata tilauskannasta riippuen monella eri tavalla. Tätä varten tarvitaan leikkaussuunnitelma, jonka muodostamiseksi on ratkaistava sekalukuoptimointiongelma. Sekalukuoptimointiongelmat ovat optimoinnin haastavin muoto. Niitä on tutkittu yksinkertaisempiin optimointiongelmiin nähden vähän. Nykyisten tietokoneiden laskentateho on kuitenkin mahdollistanut raskaampien ja monimutkaisempien optimointialgoritmien käytön ja kehittämisen. Työssä on käytetty ja esitetty eräs stokastisen optimoinnin menetelmä, differentiaalievoluutioalgoritmi. Tässä työssä esitetään teräksen leikkausoptimointialgoritmi. Kehitetty optimointimenetelmä toimii dynaamisesti tehdasympäristössä käyttäjien määrittelemien parametrien mukaisesti. Työ on osa Syncron Tech Oy:n Ovako Bar Oy Ab:lle toimittamaa ohjausjärjestelmää.

Brain surface non-rigid registration in auditory processing

Résumé: Le développement rapide de nouvelles technologies comme l'imagerie médicale a permis l'expansion des études sur les fonctions cérébrales. Le rôle principal des études fonctionnelles cérébrales est de comparer l'activation neuronale entre différents individus. Dans ce contexte, la variabilité anatomique de la taille et de la forme du cerveau pose un problème majeur. Les méthodes actuelles permettent les comparaisons interindividuelles par la normalisation des cerveaux en utilisant un cerveau standard. Les cerveaux standards les plus utilisés actuellement sont le cerveau de Talairach et le cerveau de l'Institut Neurologique de Montréal (MNI) (SPM99). Les méthodes de recalage qui utilisent le cerveau de Talairach, ou celui de MNI, ne sont pas suffisamment précises pour superposer les parties plus variables d'un cortex cérébral (p.ex., le néocortex ou la zone perisylvienne), ainsi que les régions qui ont une asymétrie très importante entre les deux hémisphères. Le but de ce projet est d'évaluer une nouvelle technique de traitement d'images basée sur le recalage non-rigide et utilisant les repères anatomiques. Tout d'abord, nous devons identifier et extraire les structures anatomiques (les repères anatomiques) dans le cerveau à déformer et celui de référence. La correspondance entre ces deux jeux de repères nous permet de déterminer en 3D la déformation appropriée. Pour les repères anatomiques, nous utilisons six points de contrôle qui sont situés : un sur le gyrus de Heschl, un sur la zone motrice de la main et le dernier sur la fissure sylvienne, bilatéralement. Evaluation de notre programme de recalage est accomplie sur les images d'IRM et d'IRMf de neuf sujets parmi dix-huit qui ont participés dans une étude précédente de Maeder et al. Le résultat sur les images anatomiques, IRM, montre le déplacement des repères anatomiques du cerveau à déformer à la position des repères anatomiques de cerveau de référence. La distance du cerveau à déformer par rapport au cerveau de référence diminue après le recalage. Le recalage des images fonctionnelles, IRMf, ne montre pas de variation significative. Le petit nombre de repères, six points de contrôle, n'est pas suffisant pour produire les modifications des cartes statistiques. Cette thèse ouvre la voie à une nouvelle technique de recalage du cortex cérébral dont la direction principale est le recalage de plusieurs points représentant un sillon cérébral. Abstract : The fast development of new technologies such as digital medical imaging brought to the expansion of brain functional studies. One of the methodolgical key issue in brain functional studies is to compare neuronal activation between individuals. In this context, the great variability of brain size and shape is a major problem. Current methods allow inter-individual comparisions by means of normalisation of subjects' brains in relation to a standard brain. A largerly used standard brains are the proportional grid of Talairach and Tournoux and the Montreal Neurological Insititute standard brain (SPM99). However, there is a lack of more precise methods for the superposition of more variable portions of the cerebral cortex (e.g, neocrotex and perisyvlian zone) and in brain regions highly asymmetric between the two cerebral hemipsheres (e.g. planum termporale). The aim of this thesis is to evaluate a new image processing technique based on non-linear model-based registration. Contrary to the intensity-based, model-based registration uses spatial and not intensitiy information to fit one image to another. We extract identifiable anatomical features (point landmarks) in both deforming and target images and by their correspondence we determine the appropriate deformation in 3D. As landmarks, we use six control points that are situated: one on the Heschl'y Gyrus, one on the motor hand area, and one on the sylvian fissure, bilaterally. The evaluation of this model-based approach is performed on MRI and fMRI images of nine of eighteen subjects participating in the Maeder et al. study. Results on anatomical, i.e. MRI, images, show the mouvement of the deforming brain control points to the location of the reference brain control points. The distance of the deforming brain to the reference brain is smallest after the registration compared to the distance before the registration. Registration of functional images, i.e fMRI, doesn't show a significant variation. The small number of registration landmarks, i.e. six, is obvious not sufficient to produce significant modification on the fMRI statistical maps. This thesis opens the way to a new computation technique for cortex registration in which the main directions will be improvement of the registation algorithm, using not only one point as landmark, but many points, representing one particular sulcus.

Imatinib plasma concentrations variability in hemato-oncologic patients

Abstract Imatinib (Glivec~ has transformed the treatment and prognosis of chronic myeloid leukaemia (CML) and of gastrointestinal stromal tumor (GIST). However, the treatment must be taken indefinitely and is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs. Considering the large interindividual differences in the function of the enzymatic and transport systems involved in imatinib disposition, exposure to this drug can be expected to vary widely among patients. Among those known systems is a cytochrome P450 (CYI'3A4) that metabolizes imatinib, the multidrug transporter P-glycoprotein (P-gp; product of the MDR1 gene) that expels imatinib out of cells, and al-acid glycoprotein (AGP), a circulating protein binding imatinib in the plasma. The aim of this observational study was to explore the influence of these covariates on imatinib pharmacokinetics (PK), to assess the interindividual variability of the PK parameters of the drug, and to evaluate whether imatinib use would benefit from a therapeutic drug monitoring (TDM) program. A total of 321 plasma concentrations were measured in 59 patients receiving imatinib, using a validated chromatographic method developed for this study (HPLC-LTV). The results were analyzed by non-linear mixed effect modeling (NONMEM). A one-compartment pharmacokinetic model with first-order absorption appropriately described the data, and a large interindividual variability was observed. The MDK> polymorphism 3435C>T and the CYP3A4 activity appeared to modulate the disposition of imatinib, albeit not significantly. A hyperbolic relationship between plasma AGP levels and oral clearance, as well as volume of distribution, was observed. A mechanistic approach was built up, postulating that only the unbound imatinib concentration was able to undergo first-order elimination. This approach allowed determining an average free clearance (CL,~ of 13101/h and a volume of distribution (Vd) of 301 1. By comparison, the total clearance determined was 141/h (i.e. 233 ml/min). Free clearance was affected by body weight and pathology diagnosis. The estimated variability of imatinib disposition (17% for CLu and 66% for Vd) decreased globally about one half with the model incorporating the AGP impact. Moreover, some associations were observed between PK parameters of the free imatinib concentration and its efficacy and toxicity. Finally, the functional influence of P-gp activity has been demonstrated in vitro in cell cultures. These elements are arguments to further investigate the possible usefulness of a TDM program for imatinib. It may help in individualizing the dosing regimen before overt disease progression or development of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug. Résumé L'imatinib (Glivec ®) a révolutionné le traitement et le pronostic de la leucémie myéloïde chronique (LMC) et des tumeurs stromales d'origine digestive (GIST). Il s'agit toutefois d'un traitement non dénué d'inconvénients et de toxicité, et qui doit être pris indéfiniment. Par ailleurs, une résistance, ou des échappements au traitement, sont également rencontrés. Le devenir de ce médicament dans l'organisme dépend de systèmes enzymatiques et de transport connus pour présenter de grandes différences interindividuelles, et l'on peut s'attendre à ce que l'exposition à ce médicament varie largement d'un patient à l'autre. Parmi ces systèmes, on note un cytochrome P450 (le CYP3A4) métabolisant l'imatinib, la P-glycoprotéine (P-gp ;codée par le gène MDR1), un transporteur d'efflux expulsant le médicament hors des cellules, et l'atglycoprotéine acide (AAG), une protéine circulante sur laquelle se fixe l'imatinib dans le plasma. L'objectif de la présente étude clinique a été de déterminer l'influence de ces covariats sur la pharmacocinétique (PK) de l'imatinib, d'établir la variabilité interindividuelle des paramètres PK du médicament, et d'évaluer dans quelle mesure l'imatinib pouvait bénéficier d'un programme de suivi thérapeutique (TDM). En utilisant une méthode chromatographique développée et validée à cet effet (HPLC-UV), un total de 321 concentrations plasmatiques a été dosé chez 59 patients recevant de l'imatinib. Les résultats ont été analysés par modélisation non linéaire à effets mixtes (NONMEM). Un modèle pharmacocinétique à un compartiment avec absorption de premier ordre a permis de décrire les données, et une grande variabilité interindividuelle a été observée. Le polymorphisme du gène MDK1 3435C>T et l'activité du CYP3A4 ont montré une influence, toutefois non significative, sur le devenir de l'imatinib. Une relation hyperbolique entre les taux plasmatiques d'AAG et la clairance, comme le volume de distribution, a été observée. Une approche mécanistique a donc été élaborée, postulant que seule la concentration libre subissait une élimination du premier ordre. Cette approche a permis de déterminer une clairance libre moyenne (CLlibre) de 13101/h et un volume de distribution (Vd) de 301 l. Par comparaison, la clairance totale était de 141/h (c.à.d. 233 ml/min). La CLlibre est affectée par le poids corporel et le type de pathologie. La variabilité interindividuelle estimée pour le devenir de l'imatinib (17% sur CLlibre et 66% sur Vd) diminuait globalement de moitié avec le modèle incorporant l'impact de l'AAG. De plus, une certaine association entre les paramètres PK de la concentration d'imatinib libre et l'efficacité et la toxicité a été observée. Finalement, l'influence fonctionnelle de l'activité de la P-gp a été démontrée in nitro dans des cultures cellulaires. Ces divers éléments constituent des arguments pour étudier davantage l'utilité potentielle d'un programme de TDM appliqué à l'imatinib. Un tel suivi pourrait aider à l'individualisation des régimes posologiques avant la progression manifeste de la maladie ou l'apparition de toxicité, améliorant tant l'efficacité que la tolérabilité de ce médicament. Résumé large public L'imatinib (un médicament commercialisé sous le nom de Glivec ®) a révolutionné le traitement et le pronostic de deux types de cancers, l'un d'origine sanguine (leucémie) et l'autre d'origine digestive. Il s'agit toutefois d'un traitement non dénué d'inconvénients et de toxicité, et qui doit être pris indéfiniment. De plus, des résistances ou des échappements au traitement sont également rencontrés. Le devenir de ce médicament dans le corps humain (dont l'étude relève de la discipline appelée pharmacocinétique) dépend de systèmes connus pour présenter de grandes différences entre les individus, et l'on peut s'attendre à ce que l'exposition à ce médicament varie largement d'un patient à l'autre. Parmi ces systèmes, l'un est responsable de la dégradation du médicament dans le foie (métabolisme), l'autre de l'expulsion du médicament hors des cellules cibles, alors que le dernier consiste en une protéine (dénommée AAG) qui transporte l'imatinib dans le sang. L'objectif de notre étude a été de déterminer l'influence de ces différents systèmes sur le comportement pharmacocinétique de l'imatinib chez les patients, et d'étudier dans quelle mesure le devenir de ce médicament dans l'organisme variait d'un patient à l'autre. Enfin, cette étude avait pour but d'évaluer à quel point la surveillance des concentrations d'imatinib présentes dans le sang pourrait améliorer le traitement des patients cancéreux. Une telle surveillance permet en fait de connaître l'exposition effective de l'organisme au médicament (concept abrégé par le terme anglais TDM, pour Therapeutic Drag Monitoring. Ce projet de recherche a d'abord nécessité la mise au point d'une méthode d'analyse pour la mesure des quantités (ou concentrations) d'imatinib présentes dans le sang. Cela nous a permis d'effectuer régulièrement des mesures chez 59 patients. Il nous a ainsi été possible de décrire le devenir du médicament dans le corps à l'aide de modèles mathématiques. Nous avons notamment pu déterminer chez ces patients la vitesse à laquelle l'imatinib est éliminé du sang et l'étendue de sa distribution dans l'organisme. Nous avons également observé chez les patients que les concentrations sanguines d'imatinib étaient très variables d'un individu à l'autre pour une même dose de médicament ingérée. Nous avons pu aussi mettre en évidence que les concentrations de la protéine AAG, sur laquelle l'imatinib se lie dans le sang, avait une grande influence sur la vitesse à laquelle le médicament est éliminé de l'organisme. Ensuite, en tenant compte des concentrations sanguines d'imatinib et de cette protéine, nous avons également pu calculer les quantités de médicament non liées à cette protéine (= libres), qui sont seules susceptibles d'avoir une activité anticancéreuse. Enfin, il a été possible d'établir qu'il existait une certaine relation entre ces concentrations, l'effet thérapeutique et la toxicité du traitement. Tous ces éléments constituent des arguments pour approfondir encore l'étude de l'utilité d'un programme de TDM appliqué à l'imatinib. Comme chaque patient est différent, un tel suivi pourrait aider à l'ajustement des doses du médicament avant la progression manifeste de la maladie ou l'apparition de toxicité, améliorant ainsi tant son efficacité que son innocuité.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Meta-analysis of the influence of bonding parameters on the clinical outcome of tooth-colored cervical restorations

PURPOSE: To meta-analyze the literature on the clinical performance of Class V restorations to assess the factors that influence retention, marginal integrity, and marginal discoloration of cervical lesions restored with composite resins, glass-ionomer-cement-based materials [glass-ionomer cement (GIC) and resin-modified glass ionomers (RMGICs)], and polyacid-modified resin composites (PMRC). MATERIALS AND METHODS: The English literature was searched (MEDLINE and SCOPUS) for prospective clinical trials on cervical restorations with an observation period of at least 18 months. The studies had to report about retention, marginal discoloration, marginal integrity, and marginal caries and include a description of the operative technique (beveling of enamel, roughening of dentin, type of isolation). Eighty-one studies involving 185 experiments for 47 adhesives matched the inclusion criteria. The statistical analysis was carried out by using the following linear mixed model: log (-log (Y /100)) = β + α log(T ) + error with β = log(λ), where β is a summary measure of the non-linear deterioration occurring in each experiment, including a random study effect. RESULTS: On average, 12.3% of the cervical restorations were lost, 27.9% exhibited marginal discoloration, and 34.6% exhibited deterioration of marginal integrity after 5 years. The calculation of the clinical index was 17.4% of failures after 5 years and 32.3% after 8 years. A higher variability was found for retention loss and marginal discoloration. Hardly any secondary caries lesions were detected, even in the experiments with a follow-up time longer than 8 years. Restorations placed using rubber-dam in teeth whose dentin was roughened showed a statistically significantly higher retention rate than those placed in teeth with unprepared dentin or without rubber-dam (p < 0.05). However, enamel beveling had no influence on any of the examined variables. Significant differences were found between pairs of adhesive systems and also between pairs of classes of adhesive systems. One-step self-etching had a significantly worse clinically index than two-step self-etching and three-step etch-and-rinse (p = 0.026 and p = 0.002, respectively). CONCLUSION: The clinical performance is significantly influenced by the type of adhesive system and/or the adhesive class to which the system belongs. Whether the dentin/enamel is roughened or not and whether rubberdam isolation is used or not also significantly influenced the clinical performance. Composite resin restorations placed with two-step self-etching and three-step etch-and-rinse adhesive systems should be preferred over onestep self-etching adhesive systems, GIC-based materials, and PMRCs.

Solution thermodynamics of methocarbamol in some ethanol + water mixtures

Apparent thermodynamic functions, Gibbs energy, enthalpy and entropy of solution and mixing, for methocarbamol in ethanol + water mixtures, were evaluated from solubility data determined at temperatures from 293.15 K to 313.15 K and from calorimetric values of drug fusion. The drug solubility was greatest in the mixtures with 0.70 or 0.80 mass fraction of ethanol and lowest in neat water across all temperatures studied. Non-linear enthalpy-entropy compensation was found for the dissolution processes. Accordingly, solution enthalpy drives the respective processes in almost all the solvent systems analyzed.

Local Web Buckling in Tapered Composite Beams: A Parametric Study

Composite flooring systems supported by tapered (varying web depth) beams are very attractive from an economic point of view. However, the tapered beam sections are fabricated from plate by welding, and are susceptible to imperfection effects. These may interact with the localised compressive stress field that is generated in the web at a slope change in the lower flange to cause local web buckling. A substantial parametric study using a non-linear elasto-plastic finite element program and covering practical ranges of the important parameters including the area of the tension flange, taper slope and web thickness is reported. Moment-rotation relations, peak moments and failure mechanisms have been predicted. The validity of the work is supported by the good correlation obtained between the results of the parametric study and experimental data.

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.

Investigation of the composition of linear alkylbenzenes with emphasis on the identification and quantitation of some trace compounds using GS/MS system in both electron impact and chemical ionization modes

Linear alkylbenzenes, LAB, formed by the Alel3 or HF catalyzed alkylation of benzene are common raw materials for surfactant manufacture. Normally they are sulphonated using S03 or oleum to give the corresponding linear alkylbenzene sulphonates In >95 % yield. As concern has grown about the environmental impact of surfactants,' questions have been raised about the trace levels of unreacted raw materials, linear alkylbenzenes and minor impurities present in them. With the advent of modem analytical instruments and techniques, namely GCIMS, the opportunity has arisen to identify the exact nature of these impurities and to determine the actual levels of them present in the commercial linear ,alkylbenzenes. The object of the proposed study was to separate, identify and quantify major and minor components (1-10%) in commercial linear alkylbenzenes. The focus of this study was on the structure elucidation and determination of impurities and on the qualitative determination of them in all analyzed linear alkylbenzene samples. A gas chromatography/mass spectrometry, (GCIMS) study was performed o~ five samples from the same manufacturer (different production dates) and then it was followed by the analyses of ten commercial linear alkylbenzenes from four different suppliers. All the major components, namely linear alkylbenzene isomers, followed the same elution pattern with the 2-phenyl isomer eluting last. The individual isomers were identified by interpretation of their electron impact and chemical ionization mass spectra. The percent isomer distribution was found to be different from sample to sample. Average molecular weights were calculated using two methods, GC and GCIMS, and compared with the results reported on the Certificate of Analyses (C.O.A.) provided by the manufacturers of commercial linear alkylbenzenes. The GC results in most cases agreed with the reported values, whereas GC/MS results were significantly lower, between 0.41 and 3.29 amu. The minor components, impurities such as branched alkylbenzenes and dialkyltetralins eluted according to their molecular weights. Their fragmentation patterns were studied using electron impact ionization mode and their molecular weight ions confirmed by a 'soft ionization technique', chemical ionization. The level of impurities present i~ the analyzed commercial linear alkylbenzenes was expressed as the percent of the total sample weight, as well as, in mg/g. The percent of impurities was observed to vary between 4.5 % and 16.8 % with the highest being in sample "I". Quantitation (mg/g) of impurities such as branched alkylbenzenes and dialkyltetralins was done using cis/trans-l,4,6,7-tetramethyltetralin as an internal standard. Samples were analyzed using .GC/MS system operating under full scan and single ion monitoring data acquisition modes. The latter data acquisition mode, which offers higher sensitivity, was used to analyze all samples under investigation for presence of linear dialkyltetralins. Dialkyltetralins were reported quantitatively, whereas branched alkylbenzenes were reported semi-qualitatively. The GC/MS method that was developed during the course of this study allowed identification of some other trace impurities present in commercial LABs. Compounds such as non-linear dialkyltetralins, dialkylindanes, diphenylalkanes and alkylnaphthalenes were identified but their detailed structure elucidation and the quantitation was beyond the scope of this study. However, further investigation of these compounds will be the subject of a future study.

Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions

In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.