Gene finding in eukaryotic genomes is an essential part of a comprehensive approach to modern systems biology. Most methods developed in the past rely on a combination of computational prediction and external information about gene structures from transcript sequences and comparative genomics. In the past, external sequence information consisted of a combination of full-length cDNA and expressed sequence tag (EST) sequences. Much improvement in prediction of genes and gene isoforms is promised by availability of RNA-seq data. However, productive use of RNA-seq for gene prediction has been difficult due to challenges associated with mapping RNA-seq reads which span splice junctions to prevalent splicing noise in the cell. This work addresses this difficulty with the development of methods and implementation of two new pipelines: 1/ a novel pipeline for accurate mapping of RNA-seq reads to compact genomes and 2/ a pipeline for prediction of genes using the RNA-seq spliced alignments in eukaryotic genomes. Machine learning methods are employed in order to overcome errors associated with the process of mapping short RNA-seq reads across introns and using them for determining sequence model parameters for gene prediction. In addition to the development of these new methods, genome annotation work was performed on several plant genome projects.

Receptor occupancy assessed by Positron Emission Tomography (PET) can provide important translational information to help bridge information from one drug to another or from animal to man. The aim of this thesis was to develop nonlinear mixed effects methods for estimation of the relationship between drug exposure and receptor occupancy for the two mGluR5 antagonists AZD9272 and AZD2066 and for the 5HT1B receptor antagonist AZD3783. Also the optimal design for improved estimation of the relationship between drug exposure and receptor occupancy as well as for improved dose finding in neuropathic pain treatment, was investigated. Different modeling approaches were applied. For AZD9272, the radioligand kinetics and receptor occupancy was simultaneously estimated using arterial concentrations as input function and including two brain regions of interest. For AZD2066, a model was developed where brain/plasma partition coefficients from ten different brain regions were included simultaneously as observations. For AZD3783, the simplified reference tissue model was extended to allow different non-specific binding in the reference region and brain regions of interest and the possibility of using white matter as reference was also evaluated. The optimal dose-selection for improved precision of receptor occupancy as well as for improved precision of the minimum effective dose of a neuropathic pain treatment was assessed, using the D-optimal as well as the Ds-optimal criteria. Simultaneous modelling of radioligand and occupancy provided a means to avoid simplifications or approximations and provided the possibility to tests or to relax assumptions. Inclusion of several brain regions of different receptor density simultaneously in the analysis, markedly improved the precision of the affinity parameter. Higher precision was achieved in relevant parameters with designs based on the Ds compared to the D-optimal criterion. The optimal design for improved precision of the relationship between dose and receptor occupancy depended on the number of brain regions and the receptor density of these regions. In conclusion, this thesis presents novel non-linear mixed effects models estimating the relationship between drug exposure and receptor occupancy, providing useful translational information, allowing for a better informed drug-development.

Effektivare offentliga upphandlingar kan enligt tidigare forskning innebära stora möjligheter till besparingar för det svenska samhället. Upphandling av läkemedel till slutenvården är ett område som många aktörer identifierat som problematiskt. Syftet med studien är därför att identifiera problem och potentiella lösningar med upphandling av läkemedel. Tillvägagångssättet var att analysera allmänt påtalade problem och lösningar med upphandling samt empiriska resultat från intervjuer och en enkät utifrån problem finding and problem solving metoden. De empiriska resultaten var fyra huvudsakliga problem: (1) olikformighet i kravspecifikationer, (2) bristande dialog mellan aktörer, (3) för kort tid mellan tilldelningsbeslut och avtalsstart samt (4) omfattande dokumenthantering. Alternativa lösningar ställdes upp för varje problem där sedan slutsatser drogs kring vilka potentiella lösningar som var bäst lämpade för läkemedelsupphandlingar.

Form-finding in Architecture looks at processes in nature to discover a more correct way in which to organize building. It is a study into the capability of discovering optimum form, dynamic adaptability, and exposes a set of unique relationships not relevant to Architecture previously. The beauty of these objects does not have to be designed. It is an emergent property of natural form. However, the wonder lies not in aesthetics, but in the manner in which natural forms come into being seemingly without a plan, at a multitude of scales, and in a vast array of materials. Alone, pattern in nature opens a vast array of potentialities for the study into new methods of architectural design. It is important to note that this inquiry will not be into the aesthetics of self-organized pattern, but the mathematical and procedural processes of formation itself. This study forms a set of principles, methodologies and tools for structuring a full-scale form-finding inquiry through the self-organization of pattern in nature. Following this inquiry one should be able to apply the organizational principles of patterning in nature, specifically breakdown patterns, to inform the programmatic design and layout of shopping malls. The rules set forth outline the formation of breakdown patterns, and the ordering of shopping malls. Through the use of parametric modeling software and computer programming language, sets of digital models efficiently explore of the vast number of potential pattern organizations by mimicking their formation in digital space. Through computational scripting, digital models also reveal formation changes due to the adaptation to site, circulatory loads, and spatial distribution, while still maintaining the laws of pattern formation.

No description available.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 187-190). Also available via the Internet.

abstract: In rehabilitation settings, activity limitation can be a significant barrier to recovery. This study sought to examine the effects of state and trait level benefit finding, positive affect, and catastrophizing on activity limitation among individuals with a physician-confirmed diagnosis of either Osteoarthritis (OA), Fibromyalgia (FM), or a dual diagnosis of OA/FM. Participants (106 OA, 53 FM, and 101 OA/FM) who had no diagnosed autoimmune disorder, a pain rating above 20 on a 0-100 scale, and no involvement in litigation regarding their condition were recruited in the Phoenix metropolitan area for inclusion in the current study. After initial questionnaires were completed, participants were trained to complete daily diaries on a laptop computer and instructed to do so a half an hour before bed each night for 30 days. In each diary, participants rated their average daily pain, benefit finding, positive affect, catastrophizing, and activity limitation. A single item, "I thought about some of the good things that have come from living with my pain" was used to examine the broader construct of benefit finding. It was hypothesized that state and trait level benefit finding would have a direct relation with activity limitation and a partially mediated relationship, through positive affect. Multilevel modeling with SAS PROC MIXED revealed that benefit finding was not directly related to activity limitation. Increases in benefit finding were associated, however, with decreases in activity limitation through a significant mediated relationship with positive affect. Individuals who benefit find had a higher level of positive affect which was associated with decreased activity limitation. A suppression effect involving pain and benefit finding at the trait level was also found. Pain appeared to increase the predictive validity of the relation of benefit finding to activity limitation. These findings have important implications for rehabilitation psychologists and should embolden clinicians to encourage patients to increase positive affect by employing active approach-oriented coping strategies like benefit finding to reduce activity limitation. / Dissertation/Thesis / Ph.D. Psychology 2012

Esta dissertação apresenta uma revisão histórica dos trabalhos acerca de superfícies minimais, ressaltando a pertinência da analogia entre a busca de superfícies de mínima área e a busca de formas de membranas estruturais sujeitas a um estado de tensões superficiais, homogêneo e isótropo. São colocados alguns conceitos geométricos das superfícies parametrizáveis, com base na geometria diferencial, a fim de realizar o equilíbrio diferencial de membranas e determinar as suas equações de equilíbrio. Além disso, é apresentada uma metodologia puramente geométrica para a determinação de superfícies minimais, baseada na minimização do funcional da área, dado pela soma das áreas das facetas triangulares nas quais a superfície é discretizada. O trabalho discute a formulação matemática do problema e apresenta resultados obtidos tanto por meio das rotinas implementadas no software MATLAB quanto por meio daquelas da biblioteca de otimização deste mesmo software. Finalmente, são realizados alguns exemplos e um teste de convergência, comparando as superfícies resultantes dos métodos numéricos com suas respectivas respostas analíticas. A geometria final de um dos exemplos é verificada por meio da analogia dos filmes de sabão, realizando-se uma análise não-linear de equilíbrio através do software Ansys. As soluções foram bastante satisfatórias, resultando em formas muito próximas das analíticas e com pequenos erros relativos das áreas. O teste de convergência também comprovou que o refinamento da discretização leva a uma solução mais próxima da desejada. Portanto, os procedimentos apresentados podem ser empregados no processo de busca da forma de membranas estruturais. / This dissertation presents a historical review on the theoretical developments on minimal surfaces, highlighting the important analogy between the problems of finding minimal area surfaces and finding membrane surfaces with homogeneous and isotropic stress fields. Some geometric concepts of the parametric surfaces are placed, on the basis of differential geometry, in order to do the differential equilibrium of membranes and to achieve its equilibrium equations. Moreover, a purely geometric methodology for the determination of minimal surfaces is presented, based on the minimization of the area functional, which is computed by the simple addition of a finite number of triangular facet areas in which the surface is divided. It discusses the mathematical formulation of the problem as well as some results obtained with the algorithms implemented in MATLAB and others obtained with the aid of MATLAB optimization routines. Finally, some examples and a convergence test are produced, comparing their analytical and numerical results. The final geometry of one of examples is verified by means of the soap film analogy, with a nonlinear equilibrium analysis through Ansys. The solutions have been sufficiently satisfactory, resulting forms very close to the analytical ones and with small areas relative errors. Convergence test also confirm that the method lead to numerical solutions as close to the analytical one as required, as long as the triangular facets mesh is refined. Therefore, the presented procedures can be used in structural membranes form finding.

Nowadays people use mobile phones and other mobile devices. Most of us have a small computing device that is always with us. People use it example for calling, as calendar and organizer. Mobile devices with GPS receiver are also used to find paths in navigation. The main disadvantage of those systems is that we have to know places which we want to visit and they usually do not store any usable, valuable information about points of interest except phone numbers and addresses. The main idea of this thesis was to design a system that will run on most of phones and palms and will be helpful when visiting some new places and cities. This system should be able to find a route using user criteria. Those criteria should be simple and natural, like for example: a list of museums, the most famous historical objects, restaurants to visit, constraints to travel by bus and by walking. The system should find a path that fulfils those criteria, show it on screen, show names of objects, some short descriptions and photos of them and possible entrance costs. It should also be able to estimate time needed to travel from one object to the next and if it is possible, advise which bus line or other public means of transport may be used. It should be helpful for people that want to visit a city without having much information about it. Paths that are output of this system are only a proposition for trip. They will not be optimal but can not be counterintuitive and must be acceptable by the user.

Large scale datasets collected using non-expert labelers are prone to labeling errors. Errors in the given labels or label noise affect the classifier performance, classifier complexity, class proportions, etc. It may be that a relatively small, but important class needs to have all its examples identified. Typical solutions to the label noise problem involve creating classifiers that are robust or tolerant to errors in the labels, or removing the suspected examples using machine learning algorithms. Finding the label noise examples through a manual review process is largely unexplored due to the cost and time factors involved. Nevertheless, we believe it is the only way to create a label noise free dataset. This dissertation proposes a solution exploiting the characteristics of the Support Vector Machine (SVM) classifier and the sparsity of its solution representation to identify uniform random label noise examples in a dataset. Application of this method is illustrated with problems involving two real-world large scale datasets. This dissertation also presents results for datasets that contain adversarial label noise. A simple extension of this method to a semi-supervised learning approach is also presented. The results show that most mislabels are quickly and effectively identified by the approaches developed in this dissertation.