Identificação dos parâmetros de um modelo de interceptação utilizando um algoritmo de calibração automática

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Sanitária e Ambiental.Os modelos hidrológicos possuem parâmetros que devem ser estimados adequadamente para que os resultados das simulações sejam confiáveis. Uma forma de obter seus valores é por meio da calibração do modelo. O presente trabalho tem por objetivo avaliar o desempenho da calibração de um modelo de interceptação utilizando um algoritmo de calibração automática. O estudo foi realizado a partir de dados coletados em uma bacia coberta por Floresta Ombrófila Mista localizada no norte do estado de Santa Catarina. As séries de dados meteorológicos, de precipitação total, de precipitação interna e de escoamento pelos troncos consideradas neste trabalho correspondem ao período de 26 de fevereiro de 2014 a 06 de outubro de 2014, totalizando 223 dias de monitoramento. O algoritmo de calibração automática Differential Evolution Adaptive Metropolis (DREAM) foi utilizado na identificação dos parâmetros do modelo de Rutter para o caso esparso a partir de dados observados de precipitação interna e precipitação líquida de 60 eventos contidos no período monitorado. Foi verificada uma grande variação nos valores dos parâmetros conforme o evento utilizado na calibração. Não foi identificada nenhuma relação evidente entre as características dos eventos e os valores dos parâmetros e nenhum padrão de variação sazonal dos mesmos. Foi verificado que eventos com precipitação total inferior a 2 mm não apresentaram informação suficiente para identificação dos parâmetros do modelo. Eventos com precipitação total superior a 15 mm possibilitaram a identificação de faixas para os parâmetros com as quais foram obtidos valores de Nash para as simulações de precipitação interna variando de 0,71 a 0,88. Estes resultados ficaram próximos ao encontrado com o emprego de parâmetros determinados a partir de métodos de regressão, com os quais foi obtido um valor de Nash de 0,85. Além da identificação dos valores dos parâmetros, o método de calibração utilizado permitiu o estabelecimento de uma faixa de incerteza associada às simulações do modelo

Avanços e desafios da ciência de recursos hídricos no Brasil: uma síntese comunitária do XXIII Simpósio Brasileiro de Recursos Hídricos

In this paper we synthesize the special sessions of the XXIII Brazilian Water Resources Symposium 2019 in order to understand the major advances and challenges in the water sciences in Brazil. We analyzed more than 250 papers and presentations of 16 special sessions covering topics of Climate Variability and Change, Disasters, Modeling, Large Scale Hydrology, Remote Sensing, Education, and Water Resources Management. This exercise highlighted the unique diversity of natural and human water features in Brazil, that offers a great opportunity for understanding coupled hydrological and societal systems. Most contributions were related to methods and the quantification of water phenomena, therefore, there is a clear necessity for fostering more research on phenomena comprehension. There is a vast network of co-authorship among institutions but mostly from academia and with some degree of regional fragmentation. The ABRhidro community now has the challenge to enhance its collaboration network, the culture of synthesis analysis, and to build a common agenda for water resources research. It is also time for us to be aligned with the international water science community and to use our experiences to actively contribute to the tackling of global water issues.Este artigo apresenta uma síntese das sessões especiais do XXIII Simpósio Brasileiro de Recursos Hídricos 2019, com o objetivo de compreender os principais avanços e desafios em recursos hídricos no Brasil. Foram analisados mais de 250 trabalhos e apresentações em 16 sessões especiais abrangendo temas como Variabilidade e Mudanças Climáticas, Desastres, Modelagem, Hidrologia de Grande Escala, Sensoriamento Remoto, Educação e Gestão de Recursos Hídricos. Esta avaliação destacou a diversidade única de atributos naturais e antrópicos dos recursos hídricos brasileiros, que oferece uma grande oportunidade para aprendizado sobre sistemas hidrológico e humano acoplados. A maioria das contribuições é relacionada a métodos e quantificação de fenômenos hídricos, existindo uma necessidade clara de incentivo a mais pesquisas em compreensão de fenômenos. Existe uma vasta rede de coautores, mas principalmente da academia e com certo grau de fragmentação regional. A comunidade da ABRhidro tem o desafio de aumentar a sua rede de colaboração, a cultura de análises de síntese, e construir uma agenda comum para a pesquisa em recursos hídricos. Também é o momento de alinhar esforços com a comunidade de recursos hídricos internacional, usando nossas experiências para contribuir ativamente na solução de questões relacionadas à água em nível global

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

Statistical Underpinning of Process-Based Diagnostics of Hydrologic Models

Modern search and optimization methods rely on classical measures of the quality of fit to support model-data synthesis. The limited guidance classical measures of quality of fit provide on model misspecification has led Gupta et al. (2008) to propose steps toward a more robust and powerful method of model evaluation. This so-called diagnostic approach quantifies model performance in ways that correspond to major behavioral functions of the watershed. These functions and/or patterns of watershed behavior, or hydrologic signatures, represent unique, recurring and measurable aspects of the streamflow hydrograph and may require the definition of multiple summary metrics to be meaningfully characterized. Diagnostic evaluation then proceeds with an analysis of the similarities and differences between the observed and simulated signatures. Ideally, these signatures are related to individual process descriptions and therefore help guide model improvements in a more meaningful way. The diagnostic approach to model evaluation lacks a rigorous statistical underpinning. The aim of this dissertation is to improve the statistical foundation of model diagnostics to help reduce type I errors (failure to reject “bad” models) and type II errors (falsely rejecting a “good” model). In the first part of this dissertation, we are concerned with the characterization of the uncertainty of hydrologic signatures and the selection of robust signature formulations for diagnostic analysis. As the signatures are numeral descriptors of the discharge time series, their uncertainty stems from streamflow uncertainty. Thus, we first introduce a relatively simple data-driven method for the representation of the uncertainty in daily discharge records (Chapter 2). The proposed method relies only on hourly discharge data and takes advantage of a nonparametric difference-based estimator in the characterization of random errors in discharge time series. This procedure produces replicates of the discharge record that portray accurately the assigned streamflow uncertainty, preserve key statistical properties of the discharge record and are hydrologically realistic. Next, we address signature selection and investigate the sensitivity of hydrologic signatures to aleatory errors and to the length and period used in their computation (Chapter 3). Our results identify robustness problems in the investigated signatures and reveal that signature uncertainty stemming from aleatory errors is rather small. Chapter 4 consequently presents a more complete treatment of the uncertainty in discharge records by considering rating curve uncertainty. This allows us to provide a rigorous description of the uncertainty in hydrologic signatures, which are subsequently used in the evaluation of a previously calibrated hydrologic model. This approach, however, does not explore the full potential of a given model structure in reproducing a set of signatures. In the second part of this dissertation, we investigate the use of hydrologic signatures within a Bayesian framework for the calibration and evaluation of hydrologic models with the aim of shedding light on model structural errors and improving model fidelity. Its successful application relies on robust estimates of signature uncertainty and the use of an adequate likelihood function. Thus, we start by formulating distribution-adaptive likelihood functions and evaluating their use in uncertainty quantification of hydrologic models (Chapter 5). Next, we present a hydrologic modeling toolbox that allows many hydrologic models to be built through the combination of alternative model structures and process representations (Chapter 6). The toolbox supports our analysis of model structural errors by enabling any deficient part of a model to be easily switched. Finally, in Chapter 7, we evaluate the use of a method that couples traditional Bayesian inference with summary metrics, coined diagnostic Bayes, and illustrate the potential of this approach to improve model consistency

Análise bayesiana aplicada à modelagem dos processos de interceptação e chuva-vazão em duas bacias florestais

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Ambiental, Florianópolis, 2018.Modelos são representações simplificadas da realidade. Devido a simplificações dos modelos de sistemas ambientais, assim como a existência de diversos erros envolvidos no processo de modelagem, todo estudo de modelagem está necessariamente sujeito a incertezas. A inferência Bayesiana permite a estimativa conjunta dos valores dos parâmetros do modelo e da incerteza associada às simulações. A principal dificuldade na utilização da inferência Bayesiana nesse processo reside na formulação de uma função de verossimilhança que represente os resíduos de maneira adequada. Nesta dissertação buscou-se identificar funções de verossimilhança que se adequem à representação dos resíduos de modelos de interceptação e chuva-vazão. Os modelos foram aplicados a duas bacias florestais: a bacia do rio Saci, coberta majoritariamente por reflorestamento de pinus; e a bacia do rio Araponga, com vegetação nativa. A partir da escolha de uma função de verossimilhança adequada, foram investigados (1) o uso de diferentes formulações para representar o processo de interceptação e chuva-vazão e (2) a influência do processo de interceptação na simulação do processo chuva-vazão. A seleção entre os diferentes modelos testados foi realizada com base na qualidade da faixa de incerteza associada aos resultados das simulações e nos valores dos critérios de informação de Akaike e de Bayes. A escolha da função de verossimilhança impactou a qualidade da faixa de incerteza, os valores dos parâmetros obtidos na inferência e os valores de critério de informação. Este resultado indica que a escolha da função de verossimilhança é uma etapa fundamental do processo de modelagem. O processo de interceptação foi melhor descrito por formulações que separam o armazenamento e transferência da água na vegetação da parte da água da chuva que atinge o solo diretamente passando pelos vazios da copa. A geração de escoamento nas duas bacias foi melhor representada por modelos que incluem um reservatório da zona não saturada seguido por dois reservatórios conectados em paralelo, um representando o movimento rápido da água por meio de caminhos preferenciais, e outro representando a resposta mais lenta da bacia. A consideração explícita do processo de interceptação na modelagem chuva-vazão resultou em maiores valores para o valor máximo da função de verossimilhança; porém, sem afetar de maneira significativa a qualidade da faixa de incerteza.Abstract : Models are simplifications of the system being modeled. Therefore, they are not intended to represent exactly all the processes that occur in nature and their interactions. Due to this intrinsic simplification, as well as many sources of errors in the modeling process, every modeling exercise is subject to uncertainty. Bayesian inference allows the joint inference of model parameters and the uncertainty in model predictions. The main difficulty associated with the use of Bayesian inference for that purpose is the formulation of a likelihood function that correctly represents model residuals. In this study, different likelihood functions were tested in terms of their ability to represent the residuals from interception and rainfall-runoff models. These models were applied to two forested catchments: the Saci river catchment, mainly covered by pine plantation; and the Araponga river catchment, covered by native forest. Once the likelihood function was identified, the following investigations were conducted: (1) the comparison of different formulations used to represent the interception and the rainfall-runoff processes; and (2) the influence of explicitly considering the interception process in rainfall-runoff modeling. The selection between competing models with different complexity levels was carried out by analyzing the quality of the predictive uncertainty and by using the Akaike and the Bayes information criteria. The choice of the likelihood function impacted the quality of the predictive uncertainty, the posterior parameter distribution and the values of the information criteria. This result indicates that the choice of the likelihood function is an extremely important step of the modeling process. The interception process was better described by formulations that separate the routing of water through the vegetation from the portion of rainfall that reaches directly the forest floor by passing through the gaps in the canopy. The runoff generation in the two basins were better represented by formulations that include an unsatured soil reservoir followed by two reservoirs connected in parallel, one representing the fast movement of water through preferential flowpaths and the other representing a slower response of the watersheds. The explicit consideration of the interception process in rainfall-runoff modeling always resulted in higher maximum likelihood values; however, without a signiticant impact in the quality of the predictive uncertainty

Consistent improvement with eculizumab across muscle groups in myasthenia gravis

Objective: To assess whether eculizumab, a terminal complement inhibitor, improves patient- and physician-reported outcomes (evaluated using the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale, respectively) in patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis across four domains, representing ocular, bulbar, respiratory, and limb/gross motor muscle groups. Methods: Patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis were randomized 1:1 to receive either placebo or eculizumab during the REGAIN study (NCT01997229). Patients who completed REGAIN were eligible to continue into the open-label extension trial (NCT02301624) for up to 4 years. The four domain scores of each of the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale recorded throughout REGAIN and through 130 weeks of the open-label extension were analyzed. Results: Of the 125 patients who participated in REGAIN, 117 enrolled in the open-label extension; 61 had received placebo and 56 had received eculizumab during REGAIN. Patients experienced rapid improvements in total scores and all four domain scores of both the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale with eculizumab treatment. These improvements were sustained through 130 weeks of the open-label extension. Interpretation: Eculizumab treatment elicits rapid and sustained improvements in muscle strength across ocular, bulbar, respiratory, and limb/gross motor muscle groups and in associated daily activities in patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis

Safety and efficacy of eculizumab in anti-acetylcholine receptor antibody-positive refractory generalised myasthenia gravis (REGAIN): a phase 3, randomised, double-blind, placebo-controlled, multicentre study

Background Complement is likely to have a role in refractory generalised myasthenia gravis, but no approved therapies specifically target this system. Results from a phase 2 study suggested that eculizumab, a terminal complement inhibitor, produced clinically meaningful improvements in patients with anti-acetylcholine receptor antibody-positive refractory generalised myasthenia gravis. We further assessed the efficacy and safety of eculizumab in this patient population in a phase 3 trial. Methods We did a phase 3, randomised, double-blind, placebo-controlled, multicentre study (REGAIN) in 76 hospitals and specialised clinics in 17 countries across North America, Latin America, Europe, and Asia. Eligible patients were aged at least 18 years, with a Myasthenia Gravis-Activities of Daily Living (MG-ADL) score of 6 or more, Myasthenia Gravis Foundation of America (MGFA) class II\ue2\u80\u93IV disease, vaccination against Neisseria meningitides, and previous treatment with at least two immunosuppressive therapies or one immunosuppressive therapy and chronic intravenous immunoglobulin or plasma exchange for 12 months without symptom control. Patients with a history of thymoma or thymic neoplasms, thymectomy within 12 months before screening, or use of intravenous immunoglobulin or plasma exchange within 4 weeks before randomisation, or rituximab within 6 months before screening, were excluded. We randomly assigned participants (1:1) to either intravenous eculizumab or intravenous matched placebo for 26 weeks. Dosing for eculizumab was 900 mg on day 1 and at weeks 1, 2, and 3; 1200 mg at week 4; and 1200 mg given every second week thereafter as maintenance dosing. Randomisation was done centrally with an interactive voice or web-response system with patients stratified to one of four groups based on MGFA disease classification. Where possible, patients were maintained on existing myasthenia gravis therapies and rescue medication was allowed at the study physician's discretion. Patients, investigators, staff, and outcome assessors were masked to treatment assignment. The primary efficacy endpoint was the change from baseline to week 26 in MG-ADL total score measured by worst-rank ANCOVA. The efficacy population set was defined as all patients randomly assigned to treatment groups who received at least one dose of study drug, had a valid baseline MG-ADL assessment, and at least one post-baseline MG-ADL assessment. The safety analyses included all randomly assigned patients who received eculizumab or placebo. This trial is registered with ClinicalTrials.gov, number NCT01997229. Findings Between April 30, 2014, and Feb 19, 2016, we randomly assigned and treated 125 patients, 62 with eculizumab and 63 with placebo. The primary analysis showed no significant difference between eculizumab and placebo (least-squares mean rank 56\uc2\ub76 [SEM 4\uc2\ub75] vs 68\uc2\ub73 [4\uc2\ub75]; rank-based treatment difference \ue2\u88\u9211\uc2\ub77, 95% CI \ue2\u88\u9224\uc2\ub73 to 0\uc2\ub796; p=0\uc2\ub70698). No deaths or cases of meningococcal infection occurred during the study. The most common adverse events in both groups were headache and upper respiratory tract infection (ten [16%] for both events in the eculizumab group and 12 [19%] for both in the placebo group). Myasthenia gravis exacerbations were reported by six (10%) patients in the eculizumab group and 15 (24%) in the placebo group. Six (10%) patients in the eculizumab group and 12 (19%) in the placebo group required rescue therapy. Interpretation The change in the MG-ADL score was not statistically significant between eculizumab and placebo, as measured by the worst-rank analysis. Eculizumab was well tolerated. The use of a worst-rank analytical approach proved to be an important limitation of this study since the secondary and sensitivity analyses results were inconsistent with the primary endpoint result; further research into the role of complement is needed. Funding Alexion Pharmaceuticals

Long-term efficacy and safety of eculizumab in Japanese patients with generalized myasthenia gravis: A subgroup analysis of the REGAIN open-label extension study

The terminal complement inhibitor eculizumab was shown to improve myasthenia gravis-related symptoms in the 26-week, phase 3, randomized, double-blind, placebo-controlled REGAIN study (NCT01997229). In this 52-week sub-analysis of the open-label extension of REGAIN (NCT02301624), eculizumab's efficacy and safety were assessed in 11 Japanese and 88 Caucasian patients with anti-acetylcholine receptor antibody-positive refractory generalized myasthenia gravis. For patients who had received placebo during REGAIN, treatment with open-label eculizumab resulted in generally similar outcomes in the Japanese and Caucasian populations. Rapid improvements were maintained for 52 weeks, assessed by change in score from open-label extension baseline to week 52 (mean [standard error]) using the following scales (in Japanese and Caucasian patients, respectively): Myasthenia Gravis Activities of Daily Living (−2.4 [1.34] and − 3.3 [0.65]); Quantitative Myasthenia Gravis (−2.9 [1.98] and − 4.3 [0.79]); Myasthenia Gravis Composite (−4.5 [2.63] and − 4.9 [1.19]); and Myasthenia Gravis Quality of Life 15-item questionnaire (−8.6 [5.68] and − 6.5 [1.93]). Overall, the safety of eculizumab was consistent with its known safety profile. In this interim sub-analysis, the efficacy and safety of eculizumab in Japanese and Caucasian patients were generally similar, and consistent with the overall REGAIN population

Long-term safety and efficacy of eculizumab in generalized myasthenia gravis

Introduction: Eculizumab is effective and well tolerated in patients with antiacetylcholine receptor antibody-positive refractory generalized myasthenia gravis (gMG; REGAIN; NCT01997229). We report an interim analysis of an open-label extension of REGAIN, evaluating eculizumab's long-term safety and efficacy. Methods: Eculizumab (1,200 mg every 2 weeks for 22.7 months [median]) was administered to 117 patients. Results: The safety profile of eculizumab was consistent with REGAIN; no cases of meningococcal infection were reported during the interim analysis period. Myasthenia gravis exacerbation rate was reduced by 75% from the year before REGAIN (P < 0.0001). Improvements with eculizumab in activities of daily living, muscle strength, functional ability, and quality of life in REGAIN were maintained through 3 years; 56% of patients achieved minimal manifestations or pharmacological remission. Patients who had received placebo during REGAIN experienced rapid and sustained improvements during open-label eculizumab (P < 0.0001). Discussion: These findings provide evidence for the long-term safety and sustained efficacy of eculizumab for refractory gMG. Muscle Nerve 2019