Human mitochondrial disease: from pathogenesis to therapeutic intervention.

The spectrum of diseases caused by mitochondrial dysfunction is very broad and encompasses the archetypal mtDNA mutation diseases, mutations of nuclear genesencoding mitochondrial proteins (including those of the oxidative phosphorylation system), and a variety predominantly neurodegenerative diseases in which the primary cause of mitochondrial dysfunction remains undefined. The last two decades have seen an explosion in our understanding of the archetypal i mitochondrial disorders. Attention has now focused on the nuclear encoded mitochondrial disorders. Furthermore, nuclear factors may be of significance in the pathogenesis of the archetypal disorders associated with mitochondrial DNA mutations. These conditions are typified by their clinical diversity and poor phenotype-genotype correlation. One of several potential explanations for this is that nuclear genes determine the fate of mtDNA mutations, or that secondary mtDNA mutations have a modulating effect upon the expression of the primary mutation. In this thesis I have sought to address several aspects of the biochemical and clinical features of mitochondrial diseases. In chapter 3 cell cybrids have been used to study the role of the nuclear genome on the biochemical expression of mtDNA mutations in an attempt to understand potential influences on phenotypic expression. An extension of this was the use of xenomitochondrial cybrids to analyse nuclear-mitochondrial interactions and the function of the respiratory chain. At the biochemical/clinical interface, skeletal muscle from patients with focal dystonia has been used as a model to investigate the role that mitochondrial dysfunction might play in this movement disorder. Finally, the clinical role of therapy for mitochondrial disorders has been investigated in the context of Friedreich's ataxia (FRDA). Existing rating scales have been assessed and new ones developed to lay a firm foundation for evaluating disease-modifying therapies. These have been piloted in a long term intervention trial for FRDA

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Testing Autonomous Robot Control Software Using Procedural Content Generation

We present a novel approach for reducing manual effort when testing autonomous robot control algorithms. We use procedural content generation, as developed for the film and video game industries, to create a diverse range of test situations. We execute these in the Player/Stage robot simulator and automatically rate them for their safety significance using an event-based scoring system. Situations exhibiting dangerous behaviour will score highly, and are thus flagged for the attention of a safety engineer. This process removes the time-consuming tasks of hand-crafting and monitoring situations while testing an autonomous robot control algorithm. We present a case study of the proposed approach – we generated 500 randomised situations, and our prototype tool simulated and rated them. We have analysed the three highest rated situations in depth, and this analysis revealed weaknesses in the smoothed nearness-diagram control algorithm

Endovascular exclusion of iliac artery to iliac vein fistula after lumbar disk surgery

AbstractIliac arteriovenous (AV) fistula is rare after lumbar disk surgery. Traditionally, open repair through the arterial lumen was performed. We report endovascular exclusion of an iliac AV fistula in a 41-year-old woman 8 years after lumbar diskectomy. An angiogram showed an AV fistula connecting the right common iliac artery and vein. This was repaired with placement of two covered wall stents in the right common artery and external iliac artery, and embolization of the right internal iliac artery. Contrast medium-enhanced computed tomography scan at 5 months confirmed elimination of the AV fistula and right iliac artery patency. This technique should be considered in management of iliac AV fistulas. (J Vasc Surg 2003;37:1091-3.

Обзор детекторов гамма-излучения для контроля положения ствола горизонтальной скважины

Представлен обзор детекторов гамма-излучения и принципы их работы. Приведены основные характеристики счетчиков гамма-излучения. Отмечены основные достоинства и недостатки данных устройств. Выбран детектор для регистрации гамма-излучения в процессе горизонтального бурения нефтяных и газовых скважин

Preceding rule induction with instance reduction methods

A new prepruning technique for rule induction is presented which applies instance reduction before rule induction. An empirical evaluation records the predictive accuracy and size of rule-sets generated from 24 datasets from the UCI Machine Learning Repository. Three instance reduction algorithms (Edited Nearest Neighbour, AllKnn and DROP5) are compared. Each one is used to reduce the size of the training set, prior to inducing a set of rules using Clark and Boswell's modification of CN2. A hybrid instance reduction algorithm (comprised of AllKnn and DROP5) is also tested. For most of the datasets, pruning the training set using ENN, AllKnn or the hybrid significantly reduces the number of rules generated by CN2, without adversely affecting the predictive performance. The hybrid achieves the highest average predictive accuracy

On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes

This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for example, predict the target class of the tested sample. Recently, an implementation of the k-NN, named as the Locally Linear Reconstruction (LLR) [11], has been proposed. The salient feature of the latter is that by invoking a quadratic optimization process, it is capable of systematically setting model parameters, such as the number of neighbors (specified by the parameter, k) and the weights. However, the LLR takes more time than other conventional methods when it has to be applied to classification tasks. To overcome this problem, we propose a strategy of using a PRS to efficiently compute the optimization problem. In this paper, we demonstrate, first of all, that by completely discarding the points not included by the PRS, we can obtain a reduced set of sample points, using which, in turn, the quadratic optimization problem can be computed far more expediently. The values of the corresponding indices are comparable to those obtained with the original training set (i.e., the one which considers all the data points) even though the computations required to obtain the prototypes and the corresponding classification accuracies are noticeably less. The proposed method has been tested on artificial and real-life data sets, and the results obtained are very promising, and has potential in PR applications

Comparisons of Supergranule Characteristics During the Solar Minima of Cycles 22/23 and 23/24

Supergranulation is a component of solar convection that manifests itself on the photosphere as a cellular network of around 35 Mm across, with a turnover lifetime of 1-2 days. It is strongly linked to the structure of the magnetic field. The horizontal, divergent flows within supergranule cells carry local field lines to the cell boundaries, while the rotational properties of supergranule upflows may contribute to the restoration of the poloidal field as part of the dynamo mechanism that controls the solar cycle. The solar minimum at the transition from cycle 23 to 24 was notable for its low level of activity and its extended length. It is of interest to study whether the convective phenomena that influences the solar magnetic field during this time differed in character to periods of previous minima. This study investigates three characteristics (velocity components, sizes and lifetimes) of solar supergranulation. Comparisons of these characteristics are made between the minima of cycles 22/23 and 23/24 using MDI Doppler data from 1996 and 2008, respectively. It is found that whereas the lifetimes are equal during both epochs (around 18 h), the sizes are larger in 1996 (35.9 +/- 0.3 Mm) than in 2008 (35.0 +/- 0.3 Mm), while the dominant horizontal velocity flows are weaker (139 +/- 1 m/s in 1996; 141 +/- 1 m/s in 2008). Although numerical differences are seen, they are not conclusive proof of the most recent minimum being inherently unusual.Comment: 22 pages, 5 figures. Solar Physics, in pres

Improving Risk Predictions by Preprocessing Imbalanced Credit Data

Imbalanced credit data sets refer to databases in which the class of defaulters is heavily under-represented in comparison to the class of non-defaulters. This is a very common situation in real-life credit scoring applications, but it has still received little attention. This paper investigates whether data resampling can be used to improve the performance of learners built from imbalanced credit data sets, and whether the effectiveness of resampling is related to the type of classifier. Experimental results demonstrate that learning with the resampled sets consistently outperforms the use of the original imbalanced credit data, independently of the classifier used