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Barragens são estruturas geralmente construídas transversalmente a um rio, tendo como objetivos, a geração de energia elétrica, a captação de água para abastecimento público, o controle de cheias e a navegação. Para atender a estes objetivos, as barragens elevam o nível dágua à montante de seu eixo e, em algumas obras, acumulam um significativo volume hídrico para garantir a regularização do corpo dágua afetado. Devido às grandes dimensões envolvidas, dos impactos provocados e dos investimentos necessários, as barragens devem ser sempre seguras, pois acidentes a ela relacionados, geralmente ligados a liberação dos volumes de água acumulados, afetam fortemente o meio ambiente e a sociedade em geral, incluindo vidas humanas. Desta forma, ferramentas que permitam a previsão destes impactos, e a subseqüente organização de planos de ações preventivas e emergenciais, fazem parte das rotinas de projeto, construção e operação destes empreendimentos. Neste trabalho apresenta-se um estudo metodológico, aplicado à Barragem Guarapiranga, voltado para a gestão de emergências ocasionadas por rupturas de barragens, visando o estabelecimento de rotinas para a avaliação dos impactos, através de ferramentas capazes de simular o efluente de um acidente hidrológico ou estrutural, seu desenvolvimento na forma de uma onda de cheia que se propaga pelo vale a jusante e finalmente, a proposição de uma seqüência de atividades relacionadas a interpretação dos resultados das simulações, que permitam a formação dos planos de ações preventivas e emergenciais. / Dams are structures usually built across a river with goals of, generation of electricity, public water supply, flood control and navigation. In order to achieve these goals, dams promote the raise of water level upstream of its axis and, in some cases, it accumulates a significant volume of water to ensure the regularization of the affected water mass. Due to their large dimensions, in associated impacts and the necessary investments, dams must be safe because accidents usually release big amount reserved water and strongly affect the environment and the society, including human lives. Thus, tools that are able to predict such impacts and then, construct plans for the preventive and emergency actions, must be part of the routine of design, built and operation of those dams. This work presents a methodological study, applied in Guarapiranga Dam, for management of emergencies caused by dam-breaks, with the purpose of establishing routines to evaluate the impacts, by using tools that are able to simulate the discharges related to a hydrologic or structural failure, and its wave propagation through the downstream. Finally this work proposes a sequence of activities related to the interpretation of the simulation results that allow the construction of plans for preventive and emergency plans.

Wong, Wing Shuet. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (p. 86-88). / Abstract also in Chinese. / Table Of Contents --- p.i / Tables of Figures and Tables --- p.vi / Chapter Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Distribution Strategies --- p.1 / Chapter 1.2 --- Motivation --- p.7 / Chapter 1.3 --- Problem Description --- p.9 / Chapter 1.4 --- Contributions --- p.11 / Chapter 1.5 --- Conclusion --- p.12 / Chapter Chapter 2. --- Literature Review --- p.13 / Chapter 2.1 --- Crossdocking in the supply chain --- p.13 / Chapter 2.2 --- Simulation of crossdocking --- p.16 / Chapter 2.3 --- Mathematic programming in crossdocking --- p.17 / Chapter 2.4 --- Conclusion --- p.29 / Chapter Chapter 3. --- Model Approach and Assumptions --- p.30 / Chapter 3.1 --- Simulation Modeling --- p.30 / Chapter 3.2 --- Model Assumptions --- p.31 / Chapter 3.3 --- Crossdocking in Arena® -Modules --- p.36 / Chapter 3.4 --- Conclusion --- p.43 / Chapter Chapter 4. --- Simulation Design --- p.44 / Chapter 4.1 --- Factors in Simulation --- p.44 / Chapter 4.2 --- Experimental Design --- p.53 / Chapter 4.3 --- Performance Measures --- p.56 / Chapter 4.4 --- Conclusion --- p.57 / Chapter Chapter 5. --- Results and Analysis --- p.58 / Chapter 5.1 --- Mean Hourly Throughput per Forklift (MTF) --- p.58 / Chapter 5.2 --- Mean Handling Time per Pallet (MHP) --- p.63 / Chapter 5.3 --- Comparison with original results --- p.65 / Chapter 5.4 --- Conclusion --- p.68 / Chapter Chapter 6. --- Conclusion and Recommendations For Future Work --- p.82 / Chapter 6.1 --- Conclusion --- p.82 / Chapter 6.2 --- Future research directions --- p.84 / References --- p.86

Law, Shu Kei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 39-40). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Basic concept of clustering --- p.1 / Chapter 1.2 --- Main problems --- p.2 / Chapter 1.3 --- Review --- p.3 / Chapter 1.4 --- Newly proposed method --- p.7 / Chapter 1.5 --- Summary --- p.7 / Chapter 2 --- k-means clustering --- p.9 / Chapter 2.1 --- Algorithm of k-means clustering --- p.9 / Chapter 2.2 --- Selecting k in k-mcans clustering --- p.11 / Chapter 2.3 --- Disadvantages of k-means clustering --- p.12 / Chapter 3 --- Methodology and Algorithm --- p.14 / Chapter 3.1 --- Methodology and Algorithm --- p.14 / Chapter 3.2 --- Illustrative Example --- p.20 / Chapter 4 --- Simulation Study --- p.25 / Chapter 4.1 --- Simulation Plan --- p.25 / Chapter 4.2 --- Simulation Details --- p.27 / Chapter 4.3 --- Simulation Result --- p.30 / Chapter 4.4 --- Summary --- p.34 / Chapter 5 --- Conclusion and Further research --- p.36 / Bibliography --- p.38

The aim of this study is to propose managerial rules for recovering from a disruption event in liner shipping. A critical realism philosophy is adopted in the design of the research. Optimisation and an experimental methodology which follows the critical realism paradigm is used as a framework. Particle swarm optimisation (PSO) is an optimisation model in which various rules are implemented to search for the optimal option to recover from a disruption problem. Solution representations for two options, speeding up and skipping, have been designed. A case study of a trans- Pacific route is used to generate novelty in the model under various configurations of degrees of disruption, maximum speeds, fuel prices, time windows and skipping penalties. The results show that the skipping option performs better than the speeding up option when there is a large amount of delay. The port skipping option is more valuable when the maximum speed limit of a vessel is low. The option of port skipping saves more total cost than the option of speeding up when fuel prices increase. Particularly, a vessel which applies the skipping option can save more total cost than one which applies the speeding option when there are high fuel prices and high degrees of disruption. In other words, speeding up is recommended in the case of low fuel prices and low degrees of disruption. The speeding option is recommended when a vessel faces a short delay and has a long time window. In contrast, the skipping option is more valuable when there is a long delay and a short time window. The higher the skipping delay penalties, the more valuable the speeding option is.

Cardiovascular disease remains the leading cause of mortality in the United States, and a primary educational objective is to develop professional competency among nurses to ensure the provision of safe and effective care to the cardiac patient. Benner's theory of novice-to-expert led to the development of an evidence-based scenario for the care of the patient with chest pain using risk-free high-fidelity simulation environments that focused on assessment, history taking, and communication, while evaluating improvements in the competency of nurses providing care to chest pain patients. Thirty-six nurses volunteered in the study. Feedback from nurse educators, which led to modifications to the scenario, preceptor evaluation of participants during simulation, and post simulation feedback of participants, were analyzed using an inductive and exploratory theme analysis. Participants reported they learned meaningful information but felt somewhat confused regarding the correct course of action when multiple events occurred simultaneously. Preceptors' feedback identified participant failure to meet stated scenario expectations. Quantitative analysis of data, using one sample t test, compared the pre- and post-test scores measuring participant knowledge on assessment, history taking, and communication. Although knowledge scores increased, the difference was not clinically significant based on the negative feedback from both preceptor and participants. Accurate appraisal of nurses' competency in assessment, history-taking, and communication skills is needed prior to exposure to simulation. Simulation scenarios may be more clinically significant when tailored to an individual participant's competency levels.

1 / Bin Meng

acase@tulane.edu / Since the mid-20th century supramolecular chemistry has become a thriving field in synthetic chemistry. Supramolecular assemblies are assemblies of molecules formed and stabilized by non-covalent interactions. Deep-cavity cavitands, bowl-shaped molecules, are one such class of molecules that form assemblies using the hydrophobic effect when in the presence of suitable hydrophobic guests in an aqueous environment. Computer simulations allow us to study these assemblies at the molecular level and provide valuable insight into both the thermodynamics of assembly as well as provide information relevant to the design of the next generation of deep-cavity cavitands. This research begins by investigating dimeric capsules of a deep-cavity cavitand known as Octa-acid (OA). We use Molecular Dynamics to study a homologous series of n-alkane guests in order to learn some of the "rules" of guest packing. Additionally we use a machine learning technique to harvest a dominant conformation from each simulation and compare computed chemical shifts of that structure with experimental chemical shifts. The second part of this dissertation looks into multimeric systems formed by one of OA's derivatives known as Tetra-endomethyl Octa-acid (TEMOA). The entrance to the binding pocket of TEMOA is narrower than OA due to four methyls being added to its rim. TEMOA forms not only dimers, but also tetramers and hexamers, depending on the guest size. We use free energy techniques to show that guest packing primarily drives the transitions between each assembly state. Additionally we obtain the interior volumes of each multimer and demonstrate that they now approach that of structures formed by other means. We give insight into why TEMOA forms multimeric systems and OA does not. The last section of this dissertation compares the interior hydration characteristics of OA and TEMOA. We show that the small structural changes from OA to TEMOA promote a large change in wetting/dewetting behavior inside the binding pocket. Normally OA is full of water in its interior, but TEMOA exhibits a two-phase behavior. Here we also demonstrate a simple bridge between simulation and experiment to validate our findings by using partial molar volume calculations. / 1 / James Wesley Barnett

acase@tulane.edu / Background The prediction of diabetes-related comorbidities and mortality over lifetime has significant clinical and policy implications. A prediction model can be used for economic evaluation on diabetes medications, comparative effectiveness review (CER) over different therapeutic plans, and estimation of the expected long-tern outcomes for different treatment goals (e.g., HbA1c). Most of the current diabetes prediction models heavily relied on the UKPDS risk engine and Framingham equation, which used data from 1970s on European populations. These populations were significantly different from current US population in various ways including race, different health related concept, treatment algorithm, screening method of comorbidities and even definition of diabetes. In addition, UKPDS risk engine does not include impact of hypoglycemia, which emerged as an important issue in the management of diabetes due to its impact on quality of life, cardiovascular events and mortality. Furthermore, with the advancement of the medical technology and innovation in redefining treatment guideline during the last decades, the rates of cardiovascular events, all-cause mortality and event related mortality have fundamentally changed, especially the survival rates from CVD events has substantially increased. There is an urgent needs to develop a new risk engine that more adaptable to the current US population. Objective The objective of this study was to update risk engine using a cohort of patients with type 2 diabetes in the United States. Methods A total of 21 equations for forecasting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using data on 10,251 patients from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Left truncated proportional hazard model was applied to fit each event equation using diabetes duration as time index, and a variety of distributions including Weibull and Gompertz distribution were tested. 10-folds cross-validation or bootstrapped validation was applied to account for overfitting issue. Predicted cumulative incidence rates was plotted against the observed cumulative incidence to serve as internal validation to evaluate the prediction accuracy of the BRAVO risk engine on ACCORD data. External validation was performed through applying the BRAVO risk engine onto population from other clinical trials. Results The BRAVO risk engine’s forecast felled within the 95% confidence interval for the occurrence of observed events at each time point through 40 years after diabetes onset. The model prediction provides accurate prediction according to the internal validation and external validation process, and good face validity on risk factors were established by endocrinologists. Severe hypoglycemia was found to be an important risk factor for congestive heart failure (CHF), myocardial infarction (MI), angina, blindness, and associated with increased mortality. Racial factor was included in more than half of the events equations (e.g. MI, revascularization surgery, blindness, SPSL, hypoglycemia). Therefore, the BRAVO risk engine can capture racial difference on diabetes outcomes among US population, as a significant improvement over UKPDS risk engine. Conclusion The BRAVO risk engine for the US diabetes cohort has a good internal validity to simulate events that closely match observed outcomes in the ACCORD trial. And it is also capable of accurately predict diabetes comorbidities in other US and non-US based clinical trials. The risk engine can be extrapolated over lifetime and provide long-term effect evaluation. The BRAVO risk engine can potentially provide more accurate prediction over a range of long-term outcomes than other current models, thus assist making clinical and policy decisions. / 1 / Hui Shao

It is not always possible to provide students and new users of complex instrumentation with sufficient hands-on use to fully develop the required knowledge of the instrument. Access may also be limited when there is a need to develop data collection and processing procedures. One solution to this problem is to develop a simulation of the instrument in readily accessible computer software. Modern computer-based technology allows traditional instrumentation to be replaced with Virtual Instruments consisting of digital control/acquisition hardware and software that graphically represents the functions of the physical instrument.In this thesis, operating and analysis software to simulate the operation of complex analytical instrumentation was successfully developed using a numerical model of the instrument. The approach will reduce the need for machine time for operator training and the development of data collection processing procedures. In particular the thesis developed software to emulate the behaviour of a VG-354 Thermal Ionisation Mass Spectrometer. Graphical programming tools were employed to create a modular set of Virtual Instruments that formed the basis of the model. The Simulated Mass Spectrometer produced results that compared well with real data obtained from the physical instrument.Virtual Instrument peak centring and measurement modules were then developed to operate the Simulated Mass Spectrometer in peak jumping mode. Uncertainties were reduced with improved analysis techniques employing polynomial least-squares fits for peak centring and single-collector isotope ratio measurements. The techniques also have the potential to accommodate hysteresis effects in the magnetic sector analyser, further reducing uncertainty.