Úkolem této práce je vytvoření adaptivního filtru pro vizualizaci CME v obrazech z kosmického koronografu, jejich implementování a výsledné testování na datech z kosmické sondy SOHO. V práci je zahrnuta potřebná teorie z oblasti astronomie a matematiky, popis NRGF, navrhnuté úpravy tohoto filtru a je přiložen program, který sloužil k jejich otestování.

Spectral indices and flatness scaling exponents corresponding to solar wind plasma measurements before, during and after a coronal mass ejection (CME) detected by NASA's Wind spacecraft on September 2014 have been obtained. The Politano-Pouquet (PP) law for isotropic and incompressible magnetohydrodynamic (MHD) turbulence has been validated over a series of selected time intervals. The performed analysis showed that turbulence was well established within most of such intervals and several mean energy transfer rates were computed. Furthermore, the results detailed in this essay suggest possible correlations between the aforementioned energy transfer rates and the spectral indices and flatness scaling exponents, and also between enhanced intermittencies and large values of the mean energy transfer rates.

For the first time, germania-based hybrid organic-inorganic sol-gel materials were developed for analytical sample preparation and chromatographic separation. Being an isostructural analog of silica (SiO2), germania (GeO2) is compatible with silica network. This structural similarity, which is reflected by the relative positions of germanium and silicon in the periodic table, stimulated our investigation on the development of germania-based sol-gel hybrid organic-inorganic coatings for analytical applications. Sol-gel sorbents and stationary phases reported to date are predominantly silica-based. Poor pH stability of silica-based materials is a major drawback. In this work, this problem was addressed through development of germania-based organic-inorganic hybrid sol-gel materials. For this, tetramethoxygermane (TMOG) and tetraethyoxygermane (TEOG) were used as precursors to create a sol-gel network via hydrolytic polycondensation reactions to provide the inorganic component (germania) of the organic-inorganic hybrid coating. The growing sol-gel germania network was simultaneously reacted with an organic ligand that contained sol-gel-active sites in its chemical structure. Hydroxy-terminated polydimethylsiloxane (PDMS) and 3-cyanopropyltriethoxysilane (CPTES) served as sources of nonpolar and polar organic components, respectively. The sol-gel reactions were performed within fused silica capillaries. The prepared sol-gel germania coatings were found to provide excellent pH and thermal stability. Their extraction characteristics remained practically unchanged after continuous rinsing of the sol-gel germania-PDMS capillary for 24 hours with highly basic (pH=13) and/or acidic (pH = 1.3) solution. They were very efficient in extracting non-polar and moderately polar analytes such as polycyclic aromatic hydrocarbons, aldehydes, ketones. Possessing the polar cyanopropyl moiety, sol-gel germania cyanopropyl-PDMS capillaries were found to effectively extract polar analytes such as alcohols, fatty acids, and phenols. Besides, they also showed superior thermal stability compared with commercial cyano-PDMS coatings thanks to the covalent attachment of the coating to capillary surface achieved through sol-gel technology. Their extraction characteristics remained unchanged up to 330°C which is significantly higher than the maximum operation temperature ( < 280 ºC) for commercial cyano-PDMS coatings. Low ng/L detection limits were achieved for both non-polar and polar test solutes. Our preliminary results also indicated that sol-gel hybrid germania coatings have the potential to offer great analytical performance as GC stationary phases.

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Yes / In this work, machine learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CMEs catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flares and CMEs data, which are later arranged in numerical training vectors and fed to machine learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Different properties are extracted from all the associated (A) and not-associated (NA) flares representing the intensity, flare duration, duration of decline and duration of growth. Cascade Correlation Neural Networks (CCNN) are used in our work. The flare properties are converted to numerical formats that are suitable for CCNN. The CCNN will predict if a certain flare is likely to initiate a CME after input of its properties. Intensive experiments using the Jack-knife techniques are carried out and it is concluded that our system provides an accurate prediction rate of 65.3%. The prediction performance is analysed and recommendation for enhancing the performance are provided.

Acinetobacter baumannii is an increasingly multidrug-resistant pathogen contributing to hospital-acquired infections necessitating the discovery of novel treatments. A bacterial second messenger, cyclic diguanosine monophosphate (cyclic di-GMP), can regulate various persistence factors that are potentially advantageous for survival in hospital environments. Cyclic di-GMP–modulating enzymes and cyclic di-GMP–binding effectors predictively are encoded in the Acinetobacter baumannii genome. I hypothesized that cyclic di-GMP controls motility, biofilm formation, and desiccation tolerance in Acinetobacter baumannii. Disrupting cyclic di-GMP–modulating enzymes or cyclic di-GMP–binding effectors should alter the regulatory effectiveness of these phenotypes. I tested the multidrug-resistant isolate Acinetobacter baumannii strain AB5075 and identified several transposon mutants that altered twitching motility, biofilm formation, and desiccation tolerance; these results suggest that cyclic di-GMP plays a role during these three responses in Acinetobacter baumannii AB5075. Inhibiting these cyclic di-GMP signaling pathways could produce novel mechanisms to combat this pathogen in the hospital environment.

配對交易策略為一被廣為使用的交易策略，其特性為使用數個關聯性高的資產同時建立多空部位，藉此消除大部分的市場風險，賺取與市場趨勢無關聯性的報酬；本研究欲探討共整合法配對交易策略應用於兩類標的資產上之可行性及其功效:台灣證券交易所掛牌的6檔陸股ETF、以及COMEX黃金期貨與CME日幣期貨之組合。本研究使用之配對交易策略應用於6檔陸股ETF大部分參數設定下可獲得正報酬，獲利性卻不如預期，且共整合性質較佳之配對無法保證其交易績效亦較佳；COMEX黃金期貨及CME日幣期貨雖相對共整合性質不佳，仍以原策略測試可獲得較優秀的績效，此結果顯示共整合法配對交易策略於兩類資產上可行性皆不高，而配對交易策略於黃金、日幣組合上可能仍有其功效，尚須以不同方法進行驗證。 / Pairs trading strategy is one kind of market neutral strategy which take both long and short positions in two or more highly correlated assets. By doing this pairs trading strategy can eliminate market risk and make profits which are not correlated with market trends. This paper aims to figure out if pairs trading strategy work well on China ETFs listed in TWSE and the COMEX gold-CME yen future pair. We use the cointegration approach to test and simulate trading performance on the securities mentioned. The result shows that pairs trading strategy profit on China ETFs under most of the parameters, but the returns are insufficient. Furthermore, good cointegration property in the input periods can’t guarantee better performances in the outputs periods. For COMEX gold future and CME yen future, cointegration property in the input periods are worse than China ETFs, but using the same strategy we find a more profitable outcome. The empirical result indicate that pairs trading strategy might still work on gold and yen, but the cointegration approach is not suitable for these two groups of assets.

Dabartinė Lietuvos saugos ir sveikatos būklė kelia nerimą, nes nelaimingų atsitikimų darbe ir profesinių ligų skaičius mažėja ne visose ūkinės veiklos srityse. Statyba išlieka viena iš pavojingiausių ekonominės veiklos sektorių, ypač mažose ir vidutinėse statybos įmonėse. Todėl šiame darbe yra atliktas saugos ir sveikatos mažose ir vidutinėse statybos įmonėse ergonominis tyrimas. Anketinės apklausos tyrime dalyvavo šių statybos įmonių vadovai. Buvo tirta darbuotojų darbo aplinka, jos įtaka sveikatos būklei, įmonės socialinė ir ūkinė veikla. Šiame darbe yra pateikta tyrimo metodika bei pagrindiniai tyrimų rezultatai, su jais susijusios išvados ir pasi��lymai. Pasiūlytos rekomendacijos apie techninių ir organizacinių priemonių taikymą, kurios didintų darbuotojų saugą ir galėtų pratęsti darbingumą, sukurtų produktyvesnę darbo aplinką ir darbuotojų darbinio gyvenimo kokybę. / Current state of safety and health in Lithuania is a matter of great concern, because the amount of accidents and professional illnesses decreases not in all spheres of economic activity. Construction still remains the most dangerous sector of economic activity, especially in small and medium building companies. This is why an ergonomic research in small and medium building companies is made in this work. The directors of these building companies took part in a questionnaire survey. Employees’ working environment, its influence on the state of health, and social and economic activity were analyzed. Research method and the main results of the research are represented in this work; conclusions and suggestions are related with them. There are recommendations about the application of technical and organizational measures suggested, that would improve employees’ safety and efficiency and create a more productive working atmosphere and quality of employees’ working life.

This work serves to present the background, approach, and selected results for the initial master thesis and prototyping phase of Open Space, a joint visualization software development project by National Aeronautics and Space Administration (NASA), Linköping University (LiU) and the American Museum of Natural History (AMNH). The thesis report provides a theoretical introduction to heliophysics, modeling of space weather events, volumetric rendering, and an understanding of how these relate in the bigger scope of Open Space. A set of visualization tools that are currently used at NASA and AMNH are presented and discussed. These tools are used to visualize global heliosphere models, both for scientific studies and for public presentations, and are mainly making use of geometric rendering techniques. The paper will, in detail, describe a new approach to visualize the science models with volumetric rendering to better represent the volumetric structure of the data. Custom processors have been developed for the open source volumetric rendering engine Voreen, to load and visualize science models provided by the Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center (GSFC). Selected parts of the code are presented by C++ code examples. To best represent models that are defined in non-Cartesian space, a new approach to volumetric rendering is presented and discussed. Compared to the traditional approach of transforming such models to Cartesian space, this new approach performs no such model transformations, and thus minimizes the amount of empty voxels and introduces less interpolation artifacts. Final results are presented as rendered images and are discussed from a scientific visualization perspective, taking into account the physics representation, potential rendering artifacts, and the rendering performance.

High-performance liquid chromatography (HPLC) is the most widely used analysis technique. However, its sensitivity is limited. Sample preconcentration methods, such as fiber-based solid-phase microextraction (SPME) and in-tube SPME (capillary microextraction) offer improved detection limits. It is, however, difficult to couple fiber SPME on-line with HPLC due to the need for complicated desorption devices. Such coupling is further complicated due to the limited solvent stability of the extracting phase both in the fiber and in-tube formats of SPME. In this research, surface-bonded sol-gel sorbents were developed to provide the solvent stability required for effective on-line hyphenation of capillary microextraction (CME) with HPLC. These sol-gel sorbents were prepared using (1) silica-based, (2) titania-based, and (3) germania-based sol-gel precursors. Sol-gel reactions were performed within fused silica capillaries to create a number of organic-inorganic hybrid sorbents in the form of surface-bonded coatings: (1) alkyl (methyl, octyl, octadecyl), (2) polydimethyldiphenylsiloxane, (3) titania poly(tetrahydrofuran), and (4) germania tri-block polymer. The sol-gel coated microextraction capillaries were capable of efficiently extracting a wide variety of analytes, including polycyclic aromatic hydrocarbons, ketones, aldehydes, aromatic compounds, amines, alcohols, and phenols with ng/L to pg/L detection limits. The sol-gel methyl coating demonstrated a counterintuitive ability to extract polar analytes. Sol-gel polydimethyldiphenylsiloxane coatings were found to be resistant to high temperature solvent exposure (150°C and 200°C), making them suitable for use in high-temperature liquid phase separations. To better understand how extraction takes place, effects of alkyl chain length and sol-gel precursor concentration were evaluated in the study on sol-gel alkyl coatings. The sol-gel titania poly(tetrahydrofuran) coating was also capable of extracting underivatized aromatic acids and polypeptides at pHs near their respective isolectric points. The sol-gel titania poly(tetrahydrofuran) coatings and the sol-gel germania tri-block polymer coatings demonstrated impressive resistance to extreme pH conditions, surviving prolonged exposure to 1.0 M HCl (pH approx. 0.0) and 1.0 M NaOH (pH approx. 14.0) with virtually no change in extraction behavior. Sol-gel germania tri-block polymer coatings were also stable under high temperature solvent conditions (200°C). In addition, for the first time, the analyte distribution constants between a sol-gel germania coating and the aqueous samples (Kcs) were determined.