次級房貸風暴造成全球金融海嘯，投資人對金融衍生性商品一度避之唯恐不及。在各方韃伐之下，卻忽略衍生性商品作為風險管理的工具及促進市場效率及完整性的重要性，未來在金融市場著重風險控管的趨勢下，衍生性商品仍會扮演不可或缺的角色。 本論文針對市場上交易量較大的利率衍生性金融商品及匯率衍生性金融商品，進行個案的評價與分析，提供投資人或發行者一個明確易懂的評價分析方式，能使市場上衍生性商品的交易更具效率性。 本論文以瑞士銀行所發行的「上下限固定期限交換利率利差連動債券」及「數據百慕達式匯率連動債券」為例，分別以LIBOR Market Model和最小平方蒙地卡羅法做為評價方式。依據評價結果分析發行商的避險策略與投資人所面對的投資風險。

Radiotherapy is the most widely used treatment for cancer, with 4 out of 10 cancer patients receiving radiotherapy as part of their treatment. The delineation of gross tumour volume (GTV) is crucial in the treatment of radiotherapy. An automatic contouring system would be beneficial in radiotherapy planning in order to generate objective, accurate and reproducible GTV contours. Image guided radiotherapy (IGRT) acquires patient images just before treatment delivery to allow any necessary positional correction. Consequently, real-time contouring system provides an opportunity to adopt radiotherapy on the treatment day. In this thesis, freely deformable models (FDM) and shape constrained deformable models (SCDMs) were used to automatically delineate the GTV for brain cancer and prostate cancer. Level set method (LSM) is a typical FDM which was used to contour glioma on brain MRI. A series of low level image segmentation methodologies are cascaded to form a case-wise fully automatic initialisation pipeline for the level set function. Dice similarity coefficients (DSCs) were used to evaluate the contours. Results shown a good agreement between clinical contours and LSM contours, in 93% of cases the DSCs was found to be between 60% and 80%. The second significant contribution is a novel development to the active shape model (ASM), a profile feature was selected from pre-computed texture features by minimising the Mahalanobis distance (MD) to obtain the most distinct feature for each landmark, instead of conventional image intensity. A new group-wise registration scheme was applied to solve the correspondence definition within the training data. This ASM model was used to delineated prostate GTV on CT. DSCs for this case was found between 0.75 and 0.91 with the mean DSC 0.81. The last contribution is a fully automatic active appearance model (AAM) which captures image appearance near the GTV boundary. The image appearance of inner GTV was discarded to spare the potential disruption caused by brachytherapy seeds or gold markers. This model outperforms conventional AAM at the prostate base and apex region by involving surround organs. The overall mean DSC for this case is 0.85.

Large-scale circulation patterns have a significant modulating influence on local hydro-meteorological variables, and consequently on water availability. An understanding of the influence of these patterns on the hydrological cycle, and the ability to timely predict their impacts, is crucial for water resources planning and management. This dissertation focusses on the influence of two major large-scale circulation patterns, the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), on the Rio Grande basin and the state of Texas, US. Both study areas are subject to a varying climate, and are extremely vulnerable to droughts, which can have devastating socio-economic impacts. The strength and spatial correlation structure of the climate indices on gauged precipitation was first established. Precipitation is not linearly related to water availability; therefore a land surface model (LSM), with land use land cover constant, was used to create naturalized flow, as it incorporates all necessary hydro-meteorological factors. As not all ENSO events are created equal, the influence of individual El Niño and La Niña events, classified using four different metrics, on water availability was examined. A general increase (decrease) in runoff during El Niños (La Niñas) was noted, but some individual events actually caused a decrease (increase) in water availability. Long duration El Niños have more influence on water availability than short duration high intensity events. Positive PDO enhances the effect of El Niño, and dampens the negative effect of La Niña, but when it is in its neutral or transition phase, La Niña tends to dominate climatic conditions and reduce water availability. LSM derived runoffs were converted into 3-month Standardized Runoff Indices (SRI 3) from which water deficit durations and severities were extracted. Conditional probability models of duration and severity were developed and compared with that based on observed precipitations. It was found that model derived information can be used in regions having limited ground observation data, or can be used in tandem with observation driven conditional probabilities for more efficient water resources planning and management. Finally a multidimensional model was developed, using copulas, to predict precipitation based on the phase of ENSO and PDO. A bivariate model, with ENSO and precipitation, was compared to a trivariate model, which incorporates PDO, and it was found that information on the state of PDO is important for efficient precipitation predictions.

Solid oxide fuel cells (SOFCs) are electrochemical devices that can convert a variety of fuels directly into electricity. Their commercialization requires efficient operation of its components. The sluggish kinetics for the oxygen reduction reaction (ORR) at the SOFC cathode contributes to the loss in the fuel cell efficiency. In this work, the ORR was investigated for the strontium-doped lanthanum manganite cathode (LSM) and yttria-stabilized zirconia electrolyte (YSZ) system. A combined mathematical modelling and experimental framework was developed to estimate, for the first time, the kinetics of the elementary processes of the ORR for porous LSM cathodes. The kinetics of each process was then analyzed to identify the contribution to the cathode resistance. The steady state and impedance response for polarized and unpolarized LSM cathodes was collected over a temperature range between 750C and 850C and two different oxygen partial pressure (pO2) ranges: (i) between 0.0001atm and 0.001atm, where LSM is considered to be stoichiometric with respect to oxygen and (ii) between 0.01atm and 0.21atm, where LSM is considered to be superstoichiometric with respect to oxygen. A mathematical model was developed to analyze both the steady state and impedance data. Two pathways for the ORR were considered: one where oxygen is transported in the gas phase and one where oxygen is transported along the surface of the LSM cathode. Rate constants, transport coefficients and their respective activation energies were obtained for the adsorption/desorption, surface diffusion and charge transfer processes. The experimental results indicated different polarization behavior between low and high pO2. It is hypothesized that the concentration of cation vacancies on the LSM surface changes with both pO2 and extent of polarization and that cation vacancies on the LSM surface can promote the ORR. Modelling results at low pO2 suggested that the adsorption reaction was slow and that thermodynamic limitations resulting in low equilibrium oxygen surface coverage can play an important role at both low and high polarizations. Modelling in high pO2 was complicated by the nature of the LSM surface in these conditions and suggests an electrochemical reaction at the gas/LSM interface and the transport of charged adsorbed oxygen atoms. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2009-12-31 11:53:23.535

<p>Abstract</p><p> Hfq is a pleiotropic posttranscriptional regulator and RNA chaperone that facilitates annealing of trans-encoded sRNA/mRNA pairs. It regulates many different cellular pathways including environmental stress responses, quorum sensing, virulence and maintenance of membrane integrity. Hfq is a member of the Sm/LSm family and forms a homohexamer that has two faces, termed proximal and distal. Hfq preferentially binds A/U rich regions that are near stem loop structures. Crystal structures have shown that poly-A sequences tend to bind the distal face while poly-U sequences bind the proximal face. Currently crystal structures reveal the binding mechanisms for short RNA sequences however; physiologically relevant RNA sequences are typically longer and more structured. To study how these more complex RNA sequences interact with Hfq, a tryptophan fluorescence quenching (TFQ) assay has been developed. Here it is presented that TFQ can correctly identify the binding face for two control sequences, A15 and U6, using the E. coli, S. aureus and L. monocytogenes Hfq homologues. Using fluorescence anisotropy and crystallography it is observed that Trp mutants necessary for TFQ may affect binding to some degree but do not affect the overall structure or RNA binding function of Hfq. TFQ is then used to examine the distal face binding motifs for both Gram-negative (E. coli) and Gram-positive (S. aureus/L. monocytogenes) Hfq, (A-R-N)n and (R-L)n respectively. Using sequences that either fulfilled just (A-R-N)n or both (A-R-N)n and (A-A-N)n motifs it is shown that the distal face motif for Gram-negative Hfq is the more specific (A-A-N)n motif. Using sequences that either fulfilled just (R-L)n or both (R-L)n and (A-L)n motifs it is shown that the Gram-positive distal face motif can be redefined to the (A-L)n motif. Finally TFQ is used to explore autoregulation of E. coli hfq. Two identified binding sites located in the 5'UTR of hfq mRNA, site A and site B, were used for TFQ, along with a longer RNA sequence that contains both sites and their native linker, 5' UTR. TFQ illustrates that the individual sites and the 5' UTR are capable of binding both faces. Each site appears to prefer binding to one face over the other, suggesting a model for hfq 5' UTR mRNA binding to Hfq where either one or two hfq mRNA bind a single Hfq hexamer. In conclusion, TFQ is a straightforward method for analyzing how RNA sequences interact with Hfq that can be utilized to study how longer, physiologically relevant RNA sequences bind Hfq.</p> / Dissertation

主催：JST/CREST，Vrije University, ALTERRA, IBPC

Swing options had been part of natural gas market before its embedded option feature was appreciated. The flexibility of delivery is valuable because of characteristic features of energy commodities as non-storability, high frequency of events and seasonality. Swing options enable this flexibility. Holder of the option is allowed to react to market situation in flexible way and change the amount of delivery up or down in some known intervals. Total deviation from negotiated amount can't exceed some boundaries in case of "take-or-pay" condition. It is not unique general valuation form of such flexible contracts as swing options. General definition of Longstaff Schwartz Least Square approximation method (LSM) is provided at first. Then it is shown other standard valuation concept as finite difference method. It is also mentioned tree method and more complex dynamic stochastic programming method. Analysis of energy commodities time series of central Europe is done and it is shown example of LSM approach use in valuing swing option with underlying asset of base load electricity in Czech Republic.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / In this study, simulated to net radiation and energy flux in a region with rotation of crops, for two distinct periods: Period 1 (01 / Feb / 2009 to 31 / Jan / 2010) and period 2 (14 / Dec / 2009 to 28 / Apr / 2010). In these simulations we used the NOAH LSM surface model. For the period 1 initially, without any calibration simulations were performed only with the input of the local weather conditions, an adjustment of an experiment controlfile file and spin up for the stabilization of the initial conditions. In these simulations, the results were very poor, indicating a need to test the sensitivity of the model especially because of the launch conditions of temperature and soil moisture. After these tests it was found that the initial predictions of impact can be considerable conditions for the two cases. It is noticed that the soil moisture changes generate greater impact in the model that temperature variations boot. As a result, proposed a calibration for the model. The calibration method was to make some simulations manually varying the parameters of soil and vegetation, or both, according to the deficiencies of the NOAH LSM. The tests were carried out until they could get a more optimized forecast for the period studied. The initial analysis of the local conditions of the experimental site was very important for calibration, as it allowed establishing previous parameters corresponding to values close to those parameters when calibrated. Simulation results after calibration applied satisfactorily exhibited liquid radiation and heat flows. So it can be said that the calibration is proposed representing characteristics of vegetation and soil correctly. Nevertheless, the corrections that the model still needs, especially in sensible and latent heat fluxes, may be associated with representation in heat distribution processes and water, or by the fact that the colder months had considerable regime rains. So when there is cloud cover, the model still has problems in representation. Results for long periods of data, as in this work, may lose some of representativeness due to the seasonality of the vegetation parameters, for which varied the parameters for periods culture and fallow. The most important contribution made in this work was a model fit for an agricultural ecosystem area and validate it for the future, it may be used as an initial boundary condition in numerical weather prediction models. The implementation variations in LAI and albedo parameter applied in the simulations of period 2 (soybean) improved the description of the heat flux and net radiation. / Neste estudo simulou-se a radiação líquida e os fluxos de energia para uma região com rotações de cultivos agrícolas, para dois períodos distintos: Período 1 (01/Fev/2009 até 31/Jan/2010) e período 2 (14/Dez/2009 até 28/Abr/2010). Nestas simulações utilizou-se o modelo de superfície NOAH LSM. Inicialmente, para o período 1, foram feitas simulações sem nenhuma calibração, apenas com a entrada das condições meteorológicas locais, um ajuste do arquivo controlfile e um experimento spin up para a estabilização das condições iniciais. Nestas simulações, os resultados foram muito insatisfatórios, indicando uma necessidade de testar a sensibilidade do modelo principalmente frente às condições de inicialização da temperatura e da umidade do solo. Após estes testes verificou-se que impactos das previsões às condições iniciais podem ser consideráveis para os dois casos. Percebe-se que as variações de umidade do solo geram maior impacto no modelo devido à temperatura do solo que é simulada. Na sequência, propôs-se uma calibração para o modelo. O método de calibração consistiu em fazer algumas simulações variando-se manualmente os parâmetros de solo e vegetação, ou ambos, de acordo com as deficiências do NOAH LSM. Assim, os testes foram realizados até que se conseguisse uma previsão mais otimizada para o período estudado. A análise inicial das condições locais do sítio experimental foi de suma importância para a calibração, pois ela possibilitou estabelecer parâmetros prévios que correspondem a valores próximos dos parâmetros quando calibrados. Os resultados das simulações, após a calibração aplicada, representaram satisfatoriamente a radiação líquida e os fluxos de calor. Portanto, pode-se dizer que a calibração proposta está representando as características de vegetação e de solo de forma correta. Apesar disso, as correções que o modelo ainda necessita, principalmente nos fluxos de calor sensível e latente, podem estar associadas a representação nos processos de distribuição do calor e da água, ou ainda pelo fato de que os meses mais frios tiveram um considerável regime de chuvas. Assim, quando há nebulosidade, o modelo ainda apresenta problemas na representação. Os resultados para períodos longos de dados, os quais foram considerados neste trabalho podem perder um pouco da representatividade em função da sazonalidade dos parâmetros de vegetação, motivo pelo qual variou-se os parâmetros para períodos com cultura e com pousios. A contribuição mais importante realizada neste trabalho foi um ajuste do modelo para uma região de ecossistema agrícola e a sua validação para que futuramente, possa ser utilizado como condição de contorno inicial em modelos de previsão numérica do Tempo. A implementação das variações diárias no parâmetro IAF e no albedo, aplicada nas simulações do período 2 na cultura de soja, melhorou a descrição dos fluxos de calor e da radiação líquida.

The successful verification of the behaviour of an Autonomous driving (AD) vehicle is fundamental for the commercialization of this new technology. Formal verification can be used to exhaustively verify the correctness of a system, but it requires a formal model to do so. An exact mathematical definition of the model description of the system is required. Manually defining a model is daunting, error-prone, and intractable for large systems. Automata learning is a branch of Machine learning (ML) that automatically creates a formal model by dynamically interacting with the system. In prior research, automata learning algorithms have been shown to learn a formal model from AD software implemented in MATLAB. However, practical challenges were highlighted in addressing the state-space explosion problem and in obtaining suitable abstractions to deal with large systems. To obtain valuable insights to scale up automata learning for industrial use, this thesis investigates the topic of automatically learning an extended finite automata formalism, called register automata. The SL* algorithm, an extension of the L* algorithm, is used to learn a register automata model of AD software from MATLAB code. The new algorithm creates a register automaton that manages to deal with the data dependencies intrinsically created from the case study between the input variables. Some approximations to the original model were made to obtain the desired solution. The obtained results are presented, from establishing the learning interface, validation of the interface, and from learning the case study. Evidence has been shown that similar problems to those highlighted for DFA learning are encountered. Future works have been discussed to address the same topic and to improve the proposed methodology. / Den framgångsrika verifieringen av beteendet hos ett autonomt körande fordon är grundläggande för kommersialiseringen av denna innovativa teknik. Formella metoder kan förutses som den sista tekniken för att uppnå detta mål. Den exakta matematiska definitionen av modellbeskrivningen för systemet behövs. Tidigare verk kunde inte skapa en metod för att automatiskt beskriva beteendemodellen för SUL. Nuvarande Lateral State Manager varierar komplexiteten som förhindrade användningen av ramverk som LearnLib eller den normala L * -algoritmen. Den stora mängden ingångar och den exponentiella tillväxten av den observerbara tabellen är några av orsakerna som gör att standardalgoritmerna misslyckas. Tidigare löstes problemet delvis och introducerade viss abstraktion till SUL. I denna avhandling föreslår vi en metod baserad på en innovativ algoritm: SL *. Den är utvecklad tack vare förlängningen av LearnLib-ramverket RALib. Den nya algoritmen skapar en registerautomat som klarar av att hantera databeroendet som skapats ur studiens fall. För att få en lösning inom acceptabel tid gjorde vi en ungefärlig tillnärmning till den ursprungliga modellen som vi tror inte påverkar det slutliga resultatet och skapar en modell som kan användas för de ändamål den var tänkt för. / La corretta verifica del comportamento di un veicolo a guida autonoma è fondamentale per la commercializzazione di questa tecnologia. Diversi metodi formali possono essere previsti come una possibile tecnica al fine di raggiungere parte di questo vasto obiettivo. Al fine di utilizzare tali metodi è necessaria l’esatta descrizione matematica del modello comportamentale del sistema. Precedenti studi non sono stati in grado di creare automaticamente un metodo per descrivere il comportamento del sistema sotto esame. Il Lateral State Manager presenta varie complessità che hanno impedito l’uso di framework come LearnLib o dell’algoritmo L_. La grande quantità di input e la crescita esponenziale della tabella delle osservazioni sono alcune delle principali cause che portano i comuni algoritmi al fallimento. In precedenza il problema è stato parzialmente risolto introducendo alcune astrazioni al caso di studio. In questa dissertazione proponiamo un metodo basato su un algoritmo innovativo: SL *. Lo stesso è sviluppato grazie all’estensione del framework LearnLib, chiamato RALib. Il nuovo algoritmo crea degli automi basati sui registri che riescono a gestire la dipendenza tra i dati intrinsecamente creati dal caso di studio. Per ottenere una soluzione in tempi accettabili si sono rese necessarie alcune approssimazioni del modello originale che riteniamo non influiscano sul risultato finale, creando un modello che possa essere utilizzato per gli scopi per cui è stato pensato.

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