Raman analysis of multilayer automotive paints in forensic science: measurement variability and depth profile?

The aim of this work is to study the influence of several analytical parameters on the variability of Raman spectra of paint samples. In the present study, microtome thin section and direct (no preparation) analysis are considered as sample preparation. In order to evaluate their influence on the measures, an experimental design such as 'fractional full factorial' with seven factors (including the sampling process) is applied, for a total of 32 experiments representing 160 measures. Once the influence of sample preparation highlighted, a depth profile of a paint sample is carried out by changing the focusing plane in order to measure the colored layer under a clearcoat. This is undertaken in order to avoid sample preparation such a microtome sectioning. Finally, chemometric treatments such as principal component analysis are applied to the resulting spectra. The findings of this study indicate the importance of sample preparation, or more specifically, the surface roughness, on the variability of the measurements on a same sample. Moreover, the depth profile experiment highlights the influence of the refractive index of the upper layer (clearcoat) when measuring through a transparent layer.

Consolidation with Radioimmunotherapy May Prolong Survival in First Remission of Mantle Cell Lymphoma Patients Uneligible for Stem Cell Transplantation, An Analysis of the International RIT-Network

Background: Mantle cell lymphoma (MCL) is a rare subtype (3-9%) of Non Hodgkin Lymphoma (NHL) with a relatively poor prognosis (5-year survival < 40%). Although consolidation of first remission with autologous stem cell transplantation (ASCT) is regarded as "golden standard", less than half of the patients may be subjected to this intensive treatment due to advanced age and co-morbidities. Standard-dose non-myeloablative radioimmunotherapy (RIT) seems to be a very efficient approach for treatment of certain NHL. However, there are almost no data available on the efficacy and safety of RIT in MCL. Methods and Patients: In the RIT-Network, a web-based international registry collecting real observational data from RIT-treated patients, 115 MCL patients treated with ibritumomab tiuxetan were recorded. Most of the patients were elderly males with advanced stage of the disease: median age - 63 (range 31-78); males - 70.4%, stage III/IV - 92%. RIT (i.e. application of ibritumomab tiuxetan) was a part of the first line therapy in 48 pts. (43%). Further 38 pts. (33%) received ibritumomab tiuxetan after two previous chemotherapy regimens, and 33 pts. (24%) after completing 3-8 lines. In 75 cases RIT was applied as a consolidation of chemotherapy induced response; the rest of the patients received ibritumomab tiuxetan because of relapse/refractory disease. At the moment follow up data are available for 74 MCL patients. Results: After RIT the patients achieved high response rate: CR 60.8%, PR 25.7%, and SD 2.7%. Only 10.8% of the patients progressed. For survival analysis many data had to be censored since the documentation had not been completed yet. The projected 3-year overall survival (OAS, fig.1 - image 001.gif) after radioimmunotherapy was 72% for pts. subjected to RIT consolidation versus 29% for those treated in relapse/refractory disease (p=0.03). RIT was feasible for almost all patients; only 3 procedure-related deaths were reported in the whole group. The main adverse event was hematological toxicity (grade III/IV cytopenias) showing a median time of recovery of Hb, WBC and Plt of 45, 40 and 38 days respectively. Conclusion: Standard-dose non-myeloablative RIT is a feasible and safe treatment modality, even for elderly MCL pts. Consolidation radioimmunotherapy with ibritumomab tiuxetan may prolong survival of patients who achieved clinical response after chemotherapy. Therefore, this consolidation approach should be considered as a treatment strategy for those, who are not eligible for ASCT. RIT also has a potential role as a palliation therapy in relapsing/resistant cases.

On-line desorption of dried blood spots coupled to hydrophilic interaction/reversed-phase LC/MS/MS system for the simultaneous analysis of drugs and their polar metabolites.

An assay for the simultaneous analysis of pharmaceutical compounds and their metabolites from micro-whole blood samples (i.e. 5 microL) was developed using an on-line dried blood spot (on-line DBS) device coupled with hydrophilic interaction/reversed-phase (HILIC/RP) LC/MS/MS. Filter paper is directly integrated to the LC device using a homemade inox desorption cell. Without any sample pretreatment, analytes are desorbed from the paper towards an automated system of valves linking a zwitterionic-HILIC column to an RP C18 column. In the same run, the polar fraction is separated by the zwitterionic-HILIC column while the non-polar fraction is eluted on the RP C18. Both fractions are detected by IT-MS operating in full scan mode for the survey scan and in product ion mode for the dependant scan using an ESI source. The procedure was evaluated by the simultaneous qualitative analysis of four probes and their relative phase I and II metabolites spiked in whole blood. In addition, the method was successfully applied to the in vivo monitoring of buprenorphine metabolism after the administration of an intraperitoneal injection of 30 mg/kg on adult female Wistar rat.

Weber's law in decision making: integrating behavioral data in humans with a neurophysiological model

Recent single-cell studies in monkeys (Romo et al., 2004) show that the activity of neurons in the ventral premotor cortex covaries with the animal's decisions in a perceptual comparison task regarding the frequency of vibrotactile events. The firing rate response of these neurons was dependent only on the frequency differences between the two applied vibrations, the sign of that difference being the determining factor for correct task performance. We present a biophysically realistic neurodynamical model that can account for the most relevant characteristics of this decision-making-related neural activity. One of the nontrivial predictions of this model is that Weber's law will underlie the perceptual discrimination behavior. We confirmed this prediction in behavioral tests of vibrotactile discrimination in humans and propose a computational explanation of perceptual discrimination that accounts naturally for the emergence of Weber's law. We conclude that the neurodynamical mechanisms and computational principles underlying the decision-making processes in this perceptual discrimination task are consistent with a fluctuation-driven scenario in a multistable regime.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Determinants of the effect of existential behavioral therapy for bereaved partners: a qualitative study.

BACKGROUND: Informal caregivers of palliative patients took part in existential behavioral therapy (EBT), a group intervention comprising mindfulness exercises to reduce psychological distress and improve quality of life. OBJECTIVES: This study examined what the participants perceived as helpful to cope with their loss during the first year of bereavement, particularly with regard to the EBT intervention. DESIGN: Sixteen problem-centered, semi-structured interviews were evaluated with content analysis. RESULTS: Two main categories were found: social support and self-regulation. Social support includes sense of belonging as well as emotional, cognitive, and practical help experienced from others. Mindfulness and acceptance, a clear focus on the positive, and orientation toward the future were helpful strategies of self-regulation; these were also part of the EBT intervention. Mindfulness was understood as permitting emotions and acceptance of one's inner processes, even if they were not pleasant, and was found to be helpful to stop ruminative thinking. CONCLUSIONS: The categories considered as being helpful parallel core elements of EBT and recent grief theories. The intervention was found to be supportive and met the needs of the participants. The interviewees appreciated the continuity of EBT support from palliative care into bereavement.

Effects of bisoprolol fumarate on left ventricular size, function, and exercise capacity in patients with heart failure: analysis with magnetic resonance myocardial tagging.

BACKGROUND: Recent data suggest that beta-blockers can be beneficial in subgroups of patients with chronic heart failure (CHF). For metoprolol and carvedilol, an increase in ejection fraction has been shown and favorable effects on the myocardial remodeling process have been reported in some studies. We examined the effects of bisoprolol fumarate on exercise capacity and left ventricular volume with magnetic resonance imaging (MRI) and applied a novel high-resolution MRI tagging technique to determine myocardial rotation and relaxation velocity. METHODS: Twenty-eight patients (mean age, 57 +/- 11 years; mean ejection fraction, 26 +/- 6%) were randomized to bisoprolol fumarate (n = 13) or to placebo therapy (n = 15). The dosage of the drugs was titrated to match that of the the Cardiac Insufficiency Bisoprolol Study protocol. Hemodynamic and gas exchange responses to exercise, MRI measurements of left ventricular end-systolic and end-diastolic volumes and ejection fraction, and left ventricular rotation and relaxation velocities were measured before the administration of the drug and 6 and 12 months later. RESULTS: After 1 year, heart rate was reduced in the bisoprolol fumarate group both at rest (81 +/- 12 before therapy versus 61 +/- 11 after therapy; P <.01) and peak exercise (144 +/- 20 before therapy versus 127 +/- 17 after therapy; P <.01), which indicated a reduction in sympathetic drive. No differences were observed in heart rate responses in the placebo group. No differences were observed within or between groups in peak oxygen uptake, although work rate achieved was higher (117.9 +/- 36 watts versus 146.1 +/- 33 watts; P <.05) and exercise time tended to be higher (9.1 +/- 1.7 minutes versus 11.4 +/- 2.8 minutes; P =.06) in the bisoprolol fumarate group. A trend for a reduction in left ventricular end-diastolic volume (-54 mL) and left ventricular end-systolic volume (-62 mL) in the bisoprolol fumarate group occurred after 1 year. Ejection fraction was higher in the bisoprolol fumarate group (25.0 +/- 7 versus 36.2 +/- 9%; P <.05), and the placebo group remained unchanged. Most changes in volume and ejection fraction occurred during the latter 6 months of treatment. With myocardial tagging, insignificant reductions in left ventricular rotation velocity were observed in both groups, whereas relaxation velocity was reduced only after bisoprolol fumarate therapy (by 39%; P <.05). CONCLUSION: One year of bisoprolol fumarate therapy resulted in an improvement in exercise capacity, showed trends for reductions in end-diastolic and end-systolic volumes, increased ejection fraction, and significantly reduced relaxation velocity. Although these results generally confirm the beneficial effects of beta-blockade in patients with chronic heart failure, they show differential effects on systolic and diastolic function.

High-growth firms and innovation: an empirical analysis for Spanish firms

This paper analyses the effect of R&D investment on firm growth. We use an extensive sample of Spanish manufacturing and service firms. The database comprises diverse waves of Spanish Community Innovation Survey and covers the period 2004–2008. First, a probit model corrected for sample selection analyses the role of innovation on the probability of being a high-growth firm (HGF). Second, a quantile regression technique is applied to explore the determinants of firm growth. Our database shows that a small number of firms experience fast growth rates in terms of sales or employees. Our results reveal that R&D investments positively affect the probability of becoming a HGF. However, differences appear between manufacturing and service firms. Finally, when we study the impact of R&D investment on firm growth, quantile estimations show that internal R&D presents a significant positive impact for the upper quantiles, while external R&D shows a significant positive impact up to the median. Keywords : High-growth firms, Firm growth, Innovation activity. JEL Classifications : L11, L25, L26, O30

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

From geriatric service to primary care: a retrospective pharmaceutical analysis of the medical prescription

Introduction The population of elderly persons is increasing andnegative outcomes due to polymedication are frequent. Discrepanciesin information about medication are frequent when older persons aretransitioning from hospital to home, increasing the risk of hospitalreadmission. The aims of this study were a) to determine discrepanciesin medical regimen indicated in two official discharge documents(DS = discharge summary, DP=discharge prescription); b) to characterizethe pharmacotherapy prescribed in older patients dischargedfrom a geriatric service.Materials & Methods Elderly patients (N=230) discharged from thegeriatric service (CHUV, Lausanne) over a 6-month period (January toJune 2009) were selected. Community pharmacists compared DS andDP to identify discrepancies including (a) drugs' name; (b) schedule ofadministration, dosage, frequency, prn prescription, treatment durationand galenic formulation. Beers' criteria were applied to identifypotentially inappropriate drugs and a descriptive analysis of drug costs,prescription profiles and generics were also performed.Results On average, patients were 82 ± 7 years old and stayed23.0 ± 11.6 days in the geriatric service. The delay between the datesof patient's discharge with the DP and the sending of the DS to hisgeneral physician averaged 14.0 ± 7.5 days (range 1-55). The DPhad an average of 10.0 ± 3.3 drugs (range 2-19). 77% of patients hadat least one discrepancy. A drug was missing on the DS in 57.8% ofpatients and 19.6% had a missing prn prescription. Among the 2312drugs prescribed, 3% belonged to Beers' list. They were prescribed to61 patients (26.5%), with 6 patients cumulating two Beers' potentiallyinappropriate drugs in their treatment. Analgesics (85% of thepatients), anticoagulants (80%), mineral supplements (77%), laxatives(52%) and antihypertensives (46%) were the drug classes most frequentlyprescribed. Mean costs of treatment as per DP was160.4 ± 179.4 Euros. Generic prescription represented more than 5%of the costs for 3 therapeutic classes (cholesterol-lowering agents(64%), antihypertensives (50%) and antidepressants (47%)).Discussion & Conclusion The high discrepancy rate between medicationlisted in the DP and the DS highlights a need for safetyimprovement. Potential benefits are expected from reinforced pharmacist-physician collaboration in transition from hospital to primarycare. In addition, even though Beers' criteria are questionable, thedrugs prescribed in this already fragile population, and the potentialopportunities of economical optimizations, are advocating thedevelopment and the scientific evaluation of a structured advancedcollaborative pharmacy practice service. This foresees improvedeffectiveness, safety and efficiency in the medication management ofelderly persons.

Multi-scale systems analysis of plant development : beyond cellular signaling and tissue morphodynamics

Les plantes sont essentielles pour les sociétés humaines. Notre alimentation quotidienne, les matériaux de constructions et les sources énergétiques dérivent de la biomasse végétale. En revanche, la compréhension des multiples aspects développementaux des plantes est encore peu exploitée et représente un sujet de recherche majeur pour la science. L'émergence des technologies à haut débit pour le séquençage de génome à grande échelle ou l'imagerie de haute résolution permet à présent de produire des quantités énormes d'information. L'analyse informatique est une façon d'intégrer ces données et de réduire la complexité apparente vers une échelle d'abstraction appropriée, dont la finalité est de fournir des perspectives de recherches ciblées. Ceci représente la raison première de cette thèse. En d'autres termes, nous appliquons des méthodes descriptives et prédictives combinées à des simulations numériques afin d'apporter des solutions originales à des problèmes relatifs à la morphogénèse à l'échelle de la cellule et de l'organe. Nous nous sommes fixés parmi les objectifs principaux de cette thèse d'élucider de quelle manière l'interaction croisée des phytohormones auxine et brassinosteroïdes (BRs) détermine la croissance de la cellule dans la racine du méristème apical d'Arabidopsis thaliana, l'organisme modèle de référence pour les études moléculaires en plantes. Pour reconstruire le réseau de signalement cellulaire, nous avons extrait de la littérature les informations pertinentes concernant les relations entre les protéines impliquées dans la transduction des signaux hormonaux. Le réseau a ensuite été modélisé en utilisant un formalisme logique et qualitatif pour pallier l'absence de données quantitatives. Tout d'abord, Les résultats ont permis de confirmer que l'auxine et les BRs agissent en synergie pour contrôler la croissance de la cellule, puis, d'expliquer des observations phénotypiques paradoxales et au final, de mettre à jour une interaction clef entre deux protéines dans la maintenance du méristème de la racine. Une étude ultérieure chez la plante modèle Brachypodium dystachion (Brachypo- dium) a révélé l'ajustement du réseau d'interaction croisée entre auxine et éthylène par rapport à Arabidopsis. Chez ce dernier, interférer avec la biosynthèse de l'auxine mène à la formation d'une racine courte. Néanmoins, nous avons isolé chez Brachypodium un mutant hypomorphique dans la biosynthèse de l'auxine qui affiche une racine plus longue. Nous avons alors conduit une analyse morphométrique qui a confirmé que des cellules plus anisotropique (plus fines et longues) sont à l'origine de ce phénotype racinaire. Des analyses plus approfondies ont démontré que la différence phénotypique entre Brachypodium et Arabidopsis s'explique par une inversion de la fonction régulatrice dans la relation entre le réseau de signalisation par l'éthylène et la biosynthèse de l'auxine. L'analyse morphométrique utilisée dans l'étude précédente exploite le pipeline de traitement d'image de notre méthode d'histologie quantitative. Pendant la croissance secondaire, la symétrie bilatérale de l'hypocotyle est remplacée par une symétrie radiale et une organisation concentrique des tissus constitutifs. Ces tissus sont initialement composés d'une douzaine de cellules mais peuvent aisément atteindre des dizaines de milliers dans les derniers stades du développement. Cette échelle dépasse largement le seuil d'investigation par les moyens dits 'traditionnels' comme l'imagerie directe de tissus en profondeur. L'étude de ce système pendant cette phase de développement ne peut se faire qu'en réalisant des coupes fines de l'organe, ce qui empêche une compréhension des phénomènes cellulaires dynamiques sous-jacents. Nous y avons remédié en proposant une stratégie originale nommée, histologie quantitative. De fait, nous avons extrait l'information contenue dans des images de très haute résolution de sections transverses d'hypocotyles en utilisant un pipeline d'analyse et de segmentation d'image à grande échelle. Nous l'avons ensuite combiné avec un algorithme de reconnaissance automatique des cellules. Cet outil nous a permis de réaliser une description quantitative de la progression de la croissance secondaire révélant des schémas développementales non-apparents avec une inspection visuelle classique. La formation de pôle de phloèmes en structure répétée et espacée entre eux d'une longueur constante illustre les bénéfices de notre approche. Par ailleurs, l'exploitation approfondie de ces résultats a montré un changement de croissance anisotropique des cellules du cambium et du phloème qui semble en phase avec l'expansion du xylème. Combinant des outils génétiques et de la modélisation biomécanique, nous avons démontré que seule la croissance plus rapide des tissus internes peut produire une réorientation de l'axe de croissance anisotropique des tissus périphériques. Cette prédiction a été confirmée par le calcul du ratio des taux de croissance du xylème et du phloème au cours de développement secondaire ; des ratios élevés sont effectivement observés et concomitant à l'établissement progressif et tangentiel du cambium. Ces résultats suggèrent un mécanisme d'auto-organisation établi par un gradient de division méristématique qui génèrent une distribution de contraintes mécaniques. Ceci réoriente la croissance anisotropique des tissus périphériques pour supporter la croissance secondaire. - Plants are essential for human society, because our daily food, construction materials and sustainable energy are derived from plant biomass. Yet, despite this importance, the multiple developmental aspects of plants are still poorly understood and represent a major challenge for science. With the emergence of high throughput devices for genome sequencing and high-resolution imaging, data has never been so easy to collect, generating huge amounts of information. Computational analysis is one way to integrate those data and to decrease the apparent complexity towards an appropriate scale of abstraction with the aim to eventually provide new answers and direct further research perspectives. This is the motivation behind this thesis work, i.e. the application of descriptive and predictive analytics combined with computational modeling to answer problems that revolve around morphogenesis at the subcellular and organ scale. One of the goals of this thesis is to elucidate how the auxin-brassinosteroid phytohormone interaction determines the cell growth in the root apical meristem of Arabidopsis thaliana (Arabidopsis), the plant model of reference for molecular studies. The pertinent information about signaling protein relationships was obtained through the literature to reconstruct the entire hormonal crosstalk. Due to a lack of quantitative information, we employed a qualitative modeling formalism. This work permitted to confirm the synergistic effect of the hormonal crosstalk on cell elongation, to explain some of our paradoxical mutant phenotypes and to predict a novel interaction between the BREVIS RADIX (BRX) protein and the transcription factor MONOPTEROS (MP),which turned out to be critical for the maintenance of the root meristem. On the same subcellular scale, another study in the monocot model Brachypodium dystachion (Brachypodium) revealed an alternative wiring of auxin-ethylene crosstalk as compared to Arabidopsis. In the latter, increasing interference with auxin biosynthesis results in progressively shorter roots. By contrast, a hypomorphic Brachypodium mutant isolated in this study in an enzyme of the auxin biosynthesis pathway displayed a dramatically longer seminal root. Our morphometric analysis confirmed that more anisotropic cells (thinner and longer) are principally responsible for the mutant root phenotype. Further characterization pointed towards an inverted regulatory logic in the relation between ethylene signaling and auxin biosynthesis in Brachypodium as compared to Arabidopsis, which explains the phenotypic discrepancy. Finally, the morphometric analysis of hypocotyl secondary growth that we applied in this study was performed with the image-processing pipeline of our quantitative histology method. During its secondary growth, the hypocotyl reorganizes its primary bilateral symmetry to a radial symmetry of highly specialized tissues comprising several thousand cells, starting with a few dozens. However, such a scale only permits observations in thin cross-sections, severely hampering a comprehensive analysis of the morphodynamics involved. Our quantitative histology strategy overcomes this limitation. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with an automated cell type recognition algorithm, it allows precise quantitative characterization of vascular development and reveals developmental patterns that were not evident from visual inspection, for example the steady interspace distance of the phloem poles. Further analyses indicated a change in growth anisotropy of cambial and phloem cells, which appeared in phase with the expansion of xylem. Combining genetic tools and computational modeling, we showed that the reorientation of growth anisotropy axis of peripheral tissue layers only occurs when the growth rate of central tissue is higher than the peripheral one. This was confirmed by the calculation of the ratio of the growth rate xylem to phloem throughout secondary growth. High ratios are indeed observed and concomitant with the homogenization of cambium anisotropy. These results suggest a self-organization mechanism, promoted by a gradient of division in the cambium that generates a pattern of mechanical constraints. This, in turn, reorients the growth anisotropy of peripheral tissues to sustain the secondary growth.

New directions in Stochastic Multicriteria Acceptability Analysis

Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

Meta-analysis and imputation refines the association of 15q25 with smoking quantity.

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.