Analysis of the mitochondrial DNA of Schizophrenia patients by next generation sequencing

Mitochondrial DNA (mtDNA), a maternally inherited 16.6-Kb molecule crucial for energy production, is implicated in numerous human traits and disorders. It has been hypothesized that the presence of mutations in the mtDNA may contribute to the complex genetic basis of schizophreniadisease, due to the evidence of maternal inheritance and the presence of schizophrenia symptoms in patients affected of a mitochondrial disorder related to a mtDNA mutation. The present project aims to study the association of variants of mitochondrial DNA (mtDNA), and an increased risk of schizophrenia in a cohort of patients and controls from the same population. The entire mtDNA of 55 schizophrenia patients with an apparent maternal transmission of the disease and 38 controls was sequenced by Next Generation Sequencing (Ion Torrent PGM, Life Technologies) and compared to the reference sequence. The current method for establishing mtDNA haplotypes is Sanger sequencing, which is laborious, timeconsuming, and expensive. With the emergence of Next Generation Sequencing technologies, this sequencing process can be much more quickly and cost-efficiently. We have identified 14 variants that have not been previously reported. Two of them were missense variants: MTATP6 p.V113M and MTND5 p.F334L ,and also three variants encoding rRNA and one variant encoding tRNA. Not significant differences have been found in the number of variants between the two groups. We found that the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of the bioinformatics analysis and annotation step would be desirable to facilitate the application of NGS in mtDNA analysis.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Can the administration be trusted? An analysis of the concept of trust, applied to the public sector

In the first part of this paper, we present the various academic debates and, where applicable, questions that remain open in the literature, particularly regarding the nature of trust, the distinction between trust and trustworthiness, its role in specific relationships and its relationship to control. We then propose a way of demarcating and operationalizing the concepts of trust and trustworthiness. In the second part, on the basis of the conceptual clarifications we present, we put forward a number of "anchor points" regarding how trust is apprehended in the public sector with regard to the various relations hips that can be studied. Schematically, we distinguish between two types of relations hips in the conceptual approach to trust: on one hand, the trust that citizens, or third parties, place in the State or in various public sector authorities or entities, and on the other hand, trust within the State or the public sector, between its various authorities, entities, and actors. While studies have traditionally focused on citizens' trust in their institutions, the findings, limitations and problems observed in public - sector coordination following the reforms associated with New Public Management have also elicited growing interest in the study of trust in the relationships between the various actors within the public sector. Both the theoretical debates we present and our propositions have been extracted and adapted from an empirical comparative study of coordination between various Swiss public - service organizations and their politico - administrative authority. Using the analysis model developed for this specific relationship, between various actors within the public service, and in the light of theoretical elements on which development of this model was based, we propose some avenues for further study - questions that remain open - regarding the consideration and understanding of citizens' trust in the public sector.

The long run impact of mergers and acquisitions on performance – empirical study in the pulp and paper industry

Mergers and acquisitions (M&A) have played very important role in restructuring the pulp and paper industry (PPI). The poor performance and fragmented nature of the industry, overcapacity problems, and globalisation have driven companies to consolidate. The objective of this thesis was to examine how PPI acquirers’ have performed subsequent M&As and whether the deal characteristics have had any impact on performance. Based on the results it seems that PPI companies have not been able to enhance their performance in the long run after M&As although the per-formance of acquiring firms has remained above the industry median, and deal characteristics or the amount of premiums paid do not seem to have had any effect. The statistical significance of the results was tested with change model and regression analysis. Performance was assessed with accrual, cash flow, and market based indicators. Results are congruent with behavioural theory: managers and investors seem to be overoptimistic in determining the synergies from M&As.

Effects of unit - based pricing on the waste collection demand : a meta - regression analysis

We perform a meta - analysis of 21 studies that estimate the elasticity of the price of waste collection demand upon waste quantities, a prior literature review having revealed that the price elasticity differs markedly. Based on a meta - regression with a total of 65 observations, we find no indication that municipal data give higher estimates for price elasticities than those associated with household data. Furthermore, there is no evidence that treating prices as exogenous underestimates the price elasticity. We find that much of the variation can be explained by sample size, the use of a weight - based as opposed to a volume - based pricing system, and the pricing of compostable waste. We also show that price elasticities determined in the USA and point estimations of elasticities are more elastic, but these effects are not robust to the changing of model specifications. Finally, our tests show that there is no evidence of publication bias while there is some evidence of the existence of genuine empirical effect.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

The impact of inbound demand on price levels in tourism municipalities : Empirical evidence from Catalonia

It is usually argued that tourism exerts negative economic impacts in host jurisdictions through the increase in prices linked to increasing demand for basic services and goods from tourists. This paper surveys 149 products in 45 tourism and non-tourism jurisdictions in Catalonia (which represent a total of 18,500 prices) in order to test empirically several hypotheses related to differences in price levels in tourism and non-tourism jurisdictions. The main results show that prices in tourism jurisdictions are not significantly higher than those in non-tourism ones. The analysis suggests that tourists are likely to pay higher prices than natives for some products

Analysis of Earnings, Stock Prices and Bond Yields: The Fed Model Approach

Prediction of the stock market valuation is a common interest to all market participants. Theoretically sound market valuation can be achieved by discounting future earnings of equities to present. Competing valuation models seek to find variables that affect the equity market valuation in a way that the market valuation can be explained and also variables that could be used to predict market valuation. In this paper we test the contemporaneous relationship between stock prices, forward looking earnings and long-term government bond yields. We test this so-called Fed model in a long- and short-term time series analysis. In order to test the dynamics of the relationship, we use the cointegration framework. The data used in this study spans over four decades of various market conditions between 1964-2007, using data from United States. The empirical results of our analysis do not give support for the Fed model. We are able to show that the long-term government bonds do not play statistically significant role in this relationship. The effect of forward earnings yield on the stock market prices is significant and thus we suggest the use of standard valuation ratios when trying to predict the future paths of equity prices. Also, changes in the long-term government bond yields do not have significant short-term impact on stock prices.

Investigation and data adaptive analysis of CARS spectra

In this diploma work advantages of coherent anti-Stokes Raman scattering spectrometry (CARS) and various methods of the quantitative analysis of substance structure with its help are considered. The basic methods and concepts of the adaptive analysis are adduced. On the basis of these methods the algorithm of automatic measurement of a scattering strip size of a target component in CARS spectrum is developed. The algorithm uses known full spectrum of target substance and compares it with a CARS spectrum. The form of a differential spectrum is used as a feedback to control the accuracy of matching. To exclude the influence of a background in CARS spectra the differential spectrum is analysed by means of its second derivative. The algorithm is checked up on the simulated simple spectra and on the spectra of organic compounds received experimentally.

Vertical relations and local competition : an empirical approach

The analysis of vertical industry relations forms an essential element in the field of industrial organization. This paper tests hypotheses derived from transaction cost theory and the principal-agent problem in Chile’s petrol market. It shows that local competition plays an important role in the choice of a disintegrated vertical structure, and that low levels of service investment have the same effect. Conversely, the number of own-brand outlets and a high level of investment in services reduce the probability of disintegration. The paper demonstrates that vertical disintegration has a null effect on wholesale petrol prices and a positive effect on retail petrol prices of between 1.6 and 7 per cent, depending on fuel type.

Self-deception as affective coping. An empirical perspective on philosophical issues.

In the philosophical literature, self-deception is mainly approached through the analysis of paradoxes. Yet, it is agreed that self-deception is motivated by protection from distress. In this paper, we argue, with the help of findings from cognitive neuroscience and psychology, that self-deception is a type of affective coping. First, we criticize the main solutions to the paradoxes of self-deception. We then present a new approach to self-deception. Self-deception, we argue, involves three appraisals of the distressing evidence: (a) appraisal of the strength of evidence as uncertain, (b) low coping potential and (c) negative anticipation along the lines of Damasio's somatic marker hypothesis. At the same time, desire impacts the treatment of flattering evidence via dopamine. Our main proposal is that self-deception involves emotional mechanisms provoking a preference for immediate reward despite possible long-term negative repercussions. In the last part, we use this emotional model to revisit the philosophical paradoxes.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Time-varying Risk Premiums and Conditional Market Risk: Empirical Evidence from European Stock Markets

This study investigates the relationship between the time-varying risk premiums and conditional market risk in the stock markets of the ten member countries of Economy and Monetary Union. Second, it examines whether the conditional second moments change over time and are there asymmetric effects in the conditional covariance matrix. Third, it analyzes the possible effects of the chosen testing framework. Empirical analysis is conducted using asymmetric univariate and multivariate GARCH-in-mean models and assuming three different degrees of market integration. For a daily sample period from 1999 to 2007, the study shows that the time-varying market risk alone is not enough to explain the dynamics of risk premiums and indications are found that the market risk is detected only when its price is allowed to change over time. Also asymmetric effects in the conditional covariance matrix, which is found to be time-varying, are clearly present and should be recognized in empirical asset pricing analyses.