Main task of the thesis, as it is clear from its name, is the application of operations research methods, which could be used for selecting suppliers of electricity for the home. In the first part of thesis the functioning of the electricity market in the Czech Republic is explained and the theoretical assumptions, which are necessary for understanding the issue is described. In the practical part of the thesis some methods of multicriteria decision making and of data envelopment analysis models are presented. The results of each method are explained in detail and they are compared with results of other methods.

For two decades, researchers and clinicians have been using the diagnostic criteria for FTD to generally diagnose a patient as suffering from PPA and the criteria of Neary et al. (1998) to further specify the diagnosis as progressive nonfluent aphasia or semantic dementia. However, there were a number of PPA cases that could not be classified according to the criteria of Neary and colleagues, which led to a revision of the diagnostic clinical and research criteria for PPA by Gorno-Tempini et al. (2011). The revised criteria encompass three PPA variants (svPPA, nfvPPA, and lvPPA) with three stages characterized by increasing evidence: clinical diagnosis, imaging-supported diagnosis, and diagnosis with definite pathology. As compared to the previous diagnostic criteria, more emphasis is placed on imaging markers as supportive features. These imaging criteria were however proposed based on a purely qualitative evaluation of the literature and have not been validated so far. The aim of this thesis was to quantitatively evaluate the validity of the new diagnostic imaging criteria for PPA variants using anatomical likelihood meta-analyses (study 1) and to investigate the usefulness of these imaging criteria for the individual diagnosis of PPA patients in clinical routine using support vector machine classification (study 2).

ISO 26262 is an international standard about functional safety published on 2011, aiming to avoid failure in safety related electrical and electronic systems in passenger cars. A corresponding standard for heavy vehicles is expected to be published in a few years’ time. In order to be well-prepared, the heavy vehicle manufacturer Scania decides to start investigating what impact ISO26262 can bring. At Scania, modularization is one of the most important features of the product, which means several modules can be combined together into a vehicle in a variety of ways, so that highly configurable products can be provided for the customer. Huge number of unique module combinations bring big challenges to systems integration testing department REST/I in Scania because of limited time and resource availability for testing. Nowadays, people in REST/I deal with the variant mainly based on human experience, which is quite difficult to obtain the exact complete variant information and concrete testing coverage. In order to fulfill the requirement related with variant handling in ISO26262, better variant handling methods are proposed in this thesis, which can mainly be divided into two parts: method for variant generating and method for configuration selecting. To simplify the implementation work of this thesis, only the ECU components are focused on (other components such as sensors are ignored), and the risk-based feature is not added to the configuration selecting. Variant generating is to generate variant information from Allocation Element Diagram in Sesamm database systematically. According to the generated variant information, the configuration can be selected automatically by using Greedy best-first-search algorithm based on the proposed testing coverage metrics. Since all these work can be done automatically by computer, REST/I not only can work more efficiently by saving a lot of labor resource, but also can avoid mistakes caused by anthropogenic factors. However, not all the data needed for the automation are existed today, so the suggestions for consummation of the data to be ready for implementing the proposed methods are also mentioned in this thesis.

The unicellular eukaryote Trypanosoma brucei causes African Sleeping sickness and multiplies extracellularly in the bloodstream of the infected host. The parasite evades antibody-mediated lysis by switching its Variant Surface Glycoprotein (VSG) coat. Blocking VSG synthesis results in an abrupt growth inhibition and a precise pre-cytokinesis cell cycle arrest, with an accumulation of cells with two nuclei and two kinetoplasts. Additionally, induction of VSG RNAi triggers a global block in translation, which is not due to a general decrease in transcript levels. The mechanism behind this translation arrest was investigated. It was observed that it correlated with a decrease in polysomes, indicating that translation was blocked at the level of initiation. It was also shown that the VSG RNAi-triggered growth inhibition was reversible, which suggests that this is not a lethal phenotype. The VSG221 RNAi-induced growth arrest could be alleviated if a second different VSG (VSG117), which was not recognised by the VSG221 RNAi, was expressed immediately downstream of the promoter of the active VSG221 Expression site. Further, it was possible to delete the telomeric VSG221 in these VSG double-expressors, leaving the cells completely reliant on the second complementing VSG117 gene. VSG117 expressed from a promoter-adjacent position in the active Expression site was shown to form a functional surface coat that protected the parasites from complement-mediated lysis in vitro. Transiently transfecting cells with anti-VSG221 morpholino oligonucleotides allowed us to specifically block translation of VSG221 mRNA without degrading it. This resulted in a pre-cytokinesis cell cycle arrest similar to that induced by VSG221 RNAi. This indicates that the VSG RNAi-triggered growth inhibition was due to a lack of VSG protein or its synthesis rather than the ablation of the abundant VSG mRNA. In addition, it was shown that blocking VSG synthesis reduced the rate of surface VSG internalisation in cells that were stalled precytokinesis, but had no effect on other endocytic markers. These experiments give us further insight into the importance of the protective VSG coat for pathogenicity in T. brucei.

Diet and lifestyle have changed dramatically in the last few decades, leading to an increase in prevalence of obesity, defined as a body mass index >30Kg/m2, dyslipidaemias (defined as abnormal lipid profiles) and type 2 diabetes (T2D). Together, these cardiometabolic traits and diseases, have contributed to the increased burden of cardiovascular disease, the leading cause of death in Western societies. Complex traits and diseases, such as cardiometabolic traits, arise as a result of the interaction between an individual's predisposing genetic makeup and a permissive environment. Since 2007, genome-wide association studies (GWAS) have been successfully applied to complex traits leading to the discovery of thousands of trait-associated variants. Nonetheless, much is still to be understood regarding the genetic architecture of these traits, as well as their underlying biology. This thesis aims to further explore the genetic architecture of cardiometabolic traits by using complementary approaches with greater genetic and phenotype resolution, ranging from studying clinically ascertained extreme phenotypes, deep molecular profiling, or sequence level data. In chapter 2, I investigated the genetic architecture of healthy human thinness (N=1,471) and contrasted it to that of severe early onset childhood obesity (N=1,456). I demonstrated that healthy human thinness, like severe obesity, is a heritable trait, with a polygenic component. I identified a novel BMI-associated locus at PKHD1, and found evidence of association at several loci that had only been discovered using large cohorts with >40,000 individuals demonstrating the power gains in studying clinical extreme phenotypes. In chapter 3, I coupled high-resolution nuclear magnetic resonance (NMR) measurements in healthy blood donors, with next-generation sequencing to establish the role of rare coding variation in circulating metabolic biomarker biology. In gene-based analysis, I identified ACSL1, MYCN, FBXO36 and B4GALNT3 as novel gene-trait associations (P < 2.5x10-6). I also found a novel link between loss-of-function mutations in the "regulation of the pyruvate dehydrogenase (PDH) complex" pathway and intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and circulating cholesterol measurements. In addition, I demonstrated that rare "protective" variation in lipoprotein metabolism genes was present in the lower tails of four measurements which are CVD risk factors in this healthy population, demonstrating a role for rare coding variation and the extremes of healthy phenotypes. In chapter 4, I performed a genome-wide association study of fructosamine, a measurement of total serum protein glycation which is useful to monitor rapid changes in glycaemic levels after treatment, as it reflects average glycaemia over 2-3 weeks. In contrast to HbA1c, which reflects average glucose concentration over the life-span of the erythrocyte (~3 months), fructosamine levels are not predicted to be influenced by factors affecting the erythrocyte. Surprisingly, I found that in this dataset fructosamine had low heritability (2% vs 20% for HbA1c), and was poorly correlated with HbA1c and other glycaemic traits. Despite this, I found two loci previously associated with glycaemic or albumin traits, G6PC2 and FCGRT respectively (P < 5x10-8), associated with fructosamine suggesting shared genetic influence. Altogether my results demonstrate the utility of higher resolution genotype and phenotype data in further elucidating the genetic architecture of a range of cardiometabolic traits, and the power advantages of study designs that focus on individuals at the extremes of phenotype distribution. As large cohorts and national biobanks with sequencing and deep multi-dimensional phenotyping become more prevalent, we will be moving closer to understanding the multiple aetiological mechanisms leading to CVD, and subsequently improve diagnosis and treatment of these conditions.

Práce pojednává o budoucnosti lodní nákladní dopravy v ČR. Některé varianty provozu a možnosti získání přepravního prostředku - plavidla, jsou řešeny pomocí metod manažerského rozhodování a finanční analýzy. Varianty analyzují situaci a možnosti podnikání v lodní nákladní přepravě v roce 2006 a možnou provozní situaci firem po výstavbě jednoho anebo obou zbývajících plavebních stupňů na Dolním Labi u města Děčína.

Diplomová práce se zabývá srovnáním systémů terciárního vzdělávání v zemích Evropské unie s využitím metod vícekriteriálního hodnocení variant. Teorie vícekriteriálního rozhodování slouží k usnadnění a objektivizaci rozhodovacích procesů. Použití rozhodovacích metod sice významným způsobem snižuje vliv hodnotícího subjektu, stále ale v těchto úlohách přetrvávají subjektivní faktory, které nelze nikdy zcela vyloučit. Takovými faktory, které jsou závislé na uživateli postupu a ovlivňují výsledky hodnocení, jsou například: použitá metoda hodnocení variant; relevance použitých kritérií; množina kritérií, podle kterých se varianty budou vyhodnocovat a množina hodnocených variant.

Cílem diplomové práce je použití různých metod vícekriteriálního rozhodování v realitě konkrétně zhodnocení postavení firmy SAMSUNG na českém trhu, jak si zde stojí v porovnání s ostatními konkurenčními společnostmi. Dalším cílem, bylo posloužit subjektům, kteří zamýšlí pořídit si tento druh spotřební elektroniky. Úkolem bylo uspořádat výrobky podle výsledků jednotlivých metod. Zaměřila jsem se hlavně na výrobky společnosti SAMSUNG. Při výběru elektroniky musíme vzít v potaz velké množství kritérií, a to jak kritéria ekonomická, jako je cena, tak také kritéria technická. K výpočtům jsem využila MS Excel a program SANNA.

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Cancer is a complex and deadly disease that is caused by genetic lesions in somatic cells. Further research in computational methodology for detecting and characterizing somatic mutations is necessary in order to understand the comprehensive systems level model of the roles of those lesions in cancer development. In the first project, I trained a list of supervised machine learning classifiers that classify false positive versus true positive somatic single nucleotide variants (SNVs). I was able to show an improvement of somatic SNV detection on the data set over the reported classifier. In the second project, we developed PhyloSub model that uses a nonparametric Bayesian prior over a set of trees to cluster SNVs, and infer the subclonal phylogenetic structure of tumors with uncertainty from SNV sequencing data. Experiments showed that PhyloSub model could infer the subclonal phylogenetic structure from both single and multiple tumor samples.