Thesis (Ed.D.)--University of West Florida, 2005. / Title from title page of source document. Document formatted into pages; contains 131 pages. Includes bibliographical references.

Atmosphere-Ocean General Circulation Models (AOGCMs) are the primary tool for modelling global climate change in the future. However, their coarse spatial resolution does not permit direct application for local scale impact studies. Therefore, either dynamical or statistical downscaling techniques are used for translating AOGCM outputs to local scale climatic variables. The main goal of this study was to improve our understanding of the historical and future climate change at local-scale in the Canadian Prairie Provinces (CPPs) of Alberta, Saskatchewan and Manitoba, comprising 47 diverse watersheds. Given the vast nature of the study area and paucity of recorded data, a novel approach for identifying homogeneous regions for regionalization of precipitation characteristics for the CPPs was proposed. This approach incorporated information about predictors ― large-scale atmospheric covariates from the National Center for Environmental Prediction (NCEP) Reanalysis-I, teleconnection indices and geographical site attributes that impact spatial patterns of precipitation in order to delineate homogeneous precipitation regions using a combination of multivariate approaches. This resulted in the delimitation of five homogeneous climatic regions which were validated independently for homogeneity using statistics computed from observations recorded at 120 stations across the CPPs. For multisite multivariate statistical downscaling, an approach based on the Generalized Linear Model (GLM) framework was developed to downscale daily observations of precipitation and minimum and maximum temperatures from 120 sites located across the CPPs. First, the aforementioned predictors and observed daily precipitation and temperature records were used to calibrate GLMs for the 1971–2000 period. Then the calibrated GLMs were used to generate daily sequences of precipitation and temperatures for the 1962–2005 historical (conditioned on NCEP predictors), and future period (2006–2100) using outputs from six CMIP5 (Coupled Model Intercomparison Project Phase-5) AOGCMs corresponding to Representative Concentration Pathway (RCP): RCP2.6, RCP4.5, and RCP8.5 scenarios. The results indicated that the fitted GLMs were able to capture spatiotemporal characteristics of observed climatic fields. According to the downscaled future climate, mean precipitation is projected to increase in summer and decrease in winter while minimum temperature is expected to warm faster than the maximum temperature. Climate extremes are projected to intensify with increased radiative forcing.

Until recent times, weather forecasts were deterministic in nature. For example, a forecast might state ``The temperature tomorrow will be $20^\circ$C.'' More recently, however, increasing interest has been paid to the uncertainty associated with such predictions. By quantifying the uncertainty of a forecast, for example with a probability distribution, users can make risk-based decisions. The uncertainty in weather forecasts is typically based upon `ensemble forecasts'. Rather than issuing a single forecast from a numerical weather prediction (NWP) model, ensemble forecasts comprise multiple model runs that differ in either the model physics or initial conditions. Ideally, ensemble forecasts would provide a representative sample of the possible outcomes of the verifying observations. However, due to model biases and inadequate specification of initial conditions, ensemble forecasts are often biased and underdispersed. As a result, estimates of the most likely values of the verifying observations, and the associated forecast uncertainty, are often inaccurate. It is therefore necessary to correct, or post-process ensemble forecasts, using statistical models known as `ensemble post-processing methods'. To this end, this thesis is concerned with the application of statistical methodology in the field of probabilistic weather forecasting, and in particular ensemble post-processing. Using various datasets, we extend existing work and propose the novel use of statistical methodology to tackle several aspects of ensemble post-processing. Our novel contributions to the field are the following. In chapter~3 we present a comparison study for several post-processing methods, with a focus on probabilistic forecasts for extreme events. We find that the benefits of ensemble post-processing are larger for forecasts of extreme events, compared with forecasts of common events. We show that allowing flexible corrections to the biases in ensemble location is important for the forecasting of extreme events. In chapter~4 we tackle the complicated problem of post-processing ensemble forecasts without making distributional assumptions, to produce recalibrated ensemble forecasts without the intermediate step of specifying a probability forecast distribution. We propose a latent variable model, and make a novel application of measurement error models. We show in three case studies that our distribution-free method is competitive with a popular alternative that makes distributional assumptions. We suggest that our distribution-free method could serve as a useful baseline on which forecasters should seek to improve. In chapter~5 we address the subject of parameter uncertainty in ensemble post-processing. As in all parametric statistical models, the parameter estimates are subject to uncertainty. We approximate the distribution of model parameters by bootstrap resampling, and demonstrate improvements in forecast skill by incorporating this additional source of uncertainty in to out-of-sample probability forecasts. In chapter~6 we use model diagnostic tools to determine how specific post-processing models may be improved. We subsequently introduce bias correction schemes that move beyond the standard linear schemes employed in the literature and in practice, particularly in the case of correcting ensemble underdispersion. Finally, we illustrate the complicated problem of assessing the skill of ensemble forecasts whose members are dependent, or correlated. We show that dependent ensemble members can result in surprising conclusions when employing standard measures of forecast skill.

A volatilidade implícita é um importante tema no campo das Finanças. Do ponto de vista acadêmico, é crescente o número de pesquisas sobre o conteúdo informacional embutido no preço dos ativos. Na visão do mercado, a volatilidade implícita pode ser negociada diretamente no mercado de derivativos como um ativo, permitindo o seu emprego para diversificação de riscos em carteiras de investimentos. No entanto, o mercado brasileiro carece de um índice de volatilidade oficial e os estudos sobre o tema no Brasil são bastante limitados, sendo urgente a proposta de métodos de obtenção deste índice coerentes com o cenário de liquidez. Assim, essa pesquisa tem como objetivo analisar o conteúdo informacional da volatilidade implícita no Brasil. Para isso foi necessário estimar um índice de volatilidade implícita para o mercado brasileiro (“VIX Brasil”), investigar o impacto da liquidez na volatilidade implícita, analisar a capacidade preditiva da volatilidade implícita em relação à volatilidade realizada futura e verificar a sua eficiência na emissão de sinais de proximidade de eventos de stress. Foram utilizados dados diários sobre o mercado de opções sobre índice de 2002 a 2013. Os principais resultados sugerem que a liquidez das opções afeta a variabilidade da volatilidade implícita ao longo do tempo. Em relação ao conteúdo informacional da volatilidade implícita no Brasil, obteve-se indícios de que (i) há significativa relação com o retorno da bolsa, sendo esta uma relação assimétrica e concentrada nos extremos da distribuição; (ii) a volatilidade implícita brasileira possui informações sobre volatilidade futura realizada além daquela contida na volatilidade histórica, porém é um estimador viesado e ineficiente; (iii) o “VIX Brasil” possui capacidade sinalizadora da proximidade de eventos de stress, em especial quando utiliza-se o limiar de 10% sobre a sua média móvel de 90 dias como abordagem de emissão de sinal. / The Implied volatility is an important topic of research in Finance. From the academics point of view, there is a growing interest in the information embedded in asset prices. From the practitioners view, the implied volatility can be directly traded in the derivatives market as an asset, being a tool for risk diversification in investment portfolios. However, the Brazilian capital market lacks an official volatility index and studies on the subject in Brazil are very limited. Hence, models for volatilities indexes consistent with the liquidity scenario of the Brazilian market are an urgent issue. Thus, this research aims to analyse the information content of implied volatility in Brazil. For achieving this goal, it was necessary to estimate an implied volatility index for the Brazilian market ("VIX Brazil"), to investigate the impact of liquidity in implied volatility, to analyse the predictive power of implied volatility for the future realized volatility and to check its efficiency for issuing early warning signals (EWS) of stress events. Daily data on the options market index over 2002 to 2013 were used. The main results suggest that the liquidity of options affects the variability of implied volatility over time. Regarding the information content of implied volatility in Brazil, evidence was obtained that (i) there is significant relationship with the market return, which is an asymmetric relationship and concentrated at the tails of the probability distribution; (ii) the Brazilian implied volatility has information about the future realized volatility than that contained in the historical volatility, but it´s a biased and inefficient estimator; (iii) the "VIX Brazil" has signalling power concerning the proximity of stress events, especially when it is used the 10% threshold on its moving average 90 days as signal emission approach.

Esse trabalho apresenta um estudo sobre os efeitos de radiação em circuitos analógicos de baixa e ultra baixa potência e tensão, identificando as fragilidades destes circuitos (e das respectivas técnicas de projeto) quando aplicados em ambientes radioativos, como, por exemplo, os circuitos em satélites, e em equipamentos de instalações nucleares. Foram realizados estudos de caso, via simulação elétrica utilizando o software HSPICE, considerando os efeitos de degradação elétrica correspondentes a doses de radiação acumulada de até 500krad(Si), além de eventos singulares considerando circuitos de baixa tensão e potência projetados para a tecnologia IBM (GF) de 130nm. Pôde-se observar que o uso de transistores de óxido mais fino, apesar de afetar negativamente o consumo estático, é recomendado para as aplicações estudadas, devido a menor sensibilidade à radiação. Ainda, foi discutido o aumento dos caminhos de fuga de corrente devido ao uso de layout distribuído. Possibilidades e estratégias de mitigação foram discutidas. Por fim, obteve-se um conjunto de sugestões e informações para auxiliar o projetista de circuitos de baixo consumo a obter soluções robustas à radiação. / This work studies the radiation effects in low-power and ultra-low power analog circuits, identifying the fragility of such circuits (and associated design techniques) when employed in radioactive environments, as for example, in satellites and nuclear facilities. Case studies were carried out using HSPICE software for electrical simulation of cumulative radiation effects, corresponding to doses up to 500krad(Si), as well as for single events simulation. We showed that, the use of thin oxide (core) MOSFETS, though increasing the static consumption, is recommended for the studied applications, because they are less sensitive to radiation. Then, we discussed the increase of current leakage paths by the distributed layout style. Mitigation strategies were also discussed. Finally, we obtained a set of suggestions and information to guide the designers of low power analog circuits towards obtaining radiation robust solutions.

We study the effectiveness of intra-household insurance among married couples when the husband loses his job due to a mass layoff or plant closure. Empirical results based on Austrian administrative data show that husbands suffer persistent employment and earnings losses, while wives' labor supply increases moderately due to extensive margin responses. Wives' earnings gains recover only a tiny fraction of the household income loss and, in the short-term, public transfers and taxes are a more important form of insurance. We show that the presence of children in the household is a crucial determinant of the wives' labor supply response.

Introduction: There are high demands on ambulance staff in relation to emergency assessments and treatment measures. In addition to this, staff are constantly exposed to potentially traumatic events. The experience of traumatic events is varied and depends on individual conditions. Aim: The aim of this literature study is to describe the ambulance staff's experiences of traumatic events in their profession. The purpose is also to review how the included articles have been selected. Method: A compilation has been made of ten scientific articles with qualitative, quantitative and mixed method. Systematic searches for articles were made in two different databases as well as manual searches. Result: Ambulance personnel’s experiences of traumatic events are based on mental and practical preparations. Feelings are described depending on the patient's condition, there are emotional differences in caring for children and adults regardless of whether the actions succeed or fail. The relatives' presence can be experienced both as suitable and unsuitable. Internal and external factors affect the experience of caring for the patient depending on circumstances. The need for processing occurs after traumatic events and is practiced in different ways. Care and guilt after an emergency situation is described in terms of different reactions. The need for necessary support is found to manifest itself after a traumatic event. Conclusion: The result shows that there is uncertainty regarding copingstrategies before, during and after traumatic events. Therefore, there is a need to improve working conditions for ambulance staff through future research.

Title: Analysis of dijet events in diffractive ep interactions with tagged leading proton at the H1 experiment Author: Richard Polifka Department: Institute of Particle and Nuclear Physics Supervisor: RNDr. Alice Valkárová, DrSc. Supervisor's e-mail address: avalkar@mail.desy.de Abstract: An inclusive dijet production in diffractive deep-inelastic scattering is measured. The diffractive selection is based on tagging of the leading proton in the Forward Proton Spectrometer. The statistics of events obtained during the HERA II running period (integrated luminosity of 156.7 pb−1 ) enables the measurement of jet final states with leading proton for the first time. The data cover the phase space of xIP < 0.1, |t| <= 1.0 GeV2 and 4 <= Q2 <= 110 GeV2 . The dijet data are compared with the next to leading order predictions of the quantum chromodynamics (QCD). The phase space of diffractive dijets is in this analysis by factor of 3 in xIP larger than in previous measurements. The QCD predictions based on the DGLAP parton evolution describe the measured data well even in a non-DGLAP enriched phase space where one on the jets goes into the region close to the direction of the outgoing proton. The measured single-differential cross sections are compared to several Monte Carlo models with different treatment of...

PURPOSE: The purpose of this study was to compare the rate of grade 3-4 immune related adverse events (irAEs) in patients with advanced metastatic melanoma treated with the combined anti-CTLA-4 and anti-PD-immune-therapy at the Dana Farber Cancer Institute(DFCI), to that of the published rate of grade 3-4 irAEs among patients treated with the same combination of check-point therapy in the pivotal phase II and phase III trials that led to the FDA approval of the combination regimen. This study also measures the tumor response with the Ipi-Nivo combination therapy and overall-survival of patients in the study cohort at DFCI. METHODS/PROCEDURES: This is a retrospective cohort study conducted at DFCI during 2014 to 2016 among stage III/IV melanoma patients treated outside of the clinical trials with the Ipi-Nivo combination therapy. Chart review of the electronic medical record(EMR) was conducted to abstract the data for this study. irAEs were graded and classified as per the NCI-CTCAE v.4.0 guidelines. The comparison of the rate of grade 3 4 toxicity in the clinical settings at DFCI and the clinical trials was performed using a one sample proportion hypothesis test. For efficacy assessment of tumor response, RECIST1.1 criterion was used to ascertain the best clinical response. RESULTS: During an overall follow-up period of 600 days, 52 patients were treated on expanded access protocol (EAP) and commercial Ipi-Nivo combination therapy at DFCI. The rate of grade 3-4 immune mediated toxicity for this cohort of patients treated outside of clinical trials was 32.6%. The average rate of grade 3-4 irAEs reported in phase II/III clinical trials was approximately 55%. The results from the one-proportion hypothesis test [(P-value: 0.002) (95% C.I: 19.14-46.23)], prove that patients in the “real world” clinical settings have a different safety profile than patients treated in the clinical trials. The rate of grade 3-4 irAEs was found to be lower (19.14% to 46.23%) in the population treated with Ipi/Nivo combination therapy at the DFCI, compared to the check-mate clinical trials (approximately 55%) CONCLUSION: The results from the study indicate a lower rate of grade 3-4 irAEs in patients treated at DFCI, in comparison with the patients treated in the clinical trials for the Ipi-Nivo combination group. The results support the need for preemptive safety signal detection of symptoms of irAEs to improve patient’s safety. However, larger database studies are required for the generalizability of this results to a wider patient population treated outside of DFCI.

Purpose: The purpose of this study is going to visualize the public sentiment on expected and unexpected social events. Exploring the relationship between tweets forwarding and sentiment. Design/methodology/approach: This research related to sentiment analysis of social events applied a lexicon-based method. The social events come from Facebook data breach and Ireland vote on abortion event. The study conducted This study focused on how the public sentiment changes over time and the relationship between sentiment and tweet forwarding. Bing lexicon and NRC lexicon are adopted in the analysis. Result: The result of this study is the dominant sentiment trend is consistent with the trend of the number of tweets over time in the Facebook data breach and Ireland vote on abortion. Besides, the sentiment has affected people forward tweets in this research.