University of Amsterdam

About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.

Treatment of input uncertainty in hydrologic modeling: doing hydrology backward with Markov chain Monte Carlo simulation.

Abstract: [1] There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

Geographic Distribution of the 20210 G to A Prothrombin Variant

Abstract: A variant in prothrombin (clotting factor II), a G to A transition at nucleotide position 20210, has recently been shown to be associated with the prothrombin plasma levels and the risk of both venous and arterial thrombosis. The purpose of this study was to investigate the prevalence of carriership of this mutation in various populations. We combined data from 11 centres in nine countries, where tests for this mutation had been performed in groups representing the general population. We calculated an overall prevalence estimate, by a precision-weighted method, and, since the distribution of the prevalences did not appear homogeneous, by an unweighted average of the prevalences. We examined differences in the prevalences by geographical location and ethnic background as a possible explanation for the heterogeneity. Among a total of 5527 individuals who had been tested, 111 heterozygous carriers of the 20210A mutation were found. The prevalence estimates varied from 0.7 to 4.0 between the centres. The overall prevalence estimate was 2.0 percent (CI95 1.4-2.6%). The variation around the summary estimate appeared more than was expected by chance alone, and this heterogeneity could be explained by geographic differences. In southern Europe, the prevalence was 3.0 percent (CI95 2.3 to 3.7%), nearly twice as high as the prevalence in northern Europe (1.7%, CI95 1.3 to 2.2%). The prothrombin variant appeared very rare in individuals from Asian and African descent. The 20210A prothrombin variant is a common abnormality, with a prevalence of carriership between one and four percent. It is more common in southern than in northern Europe. Since this distribution within Europe is very different to that of another prothrombotic mutation (factor V Leiden or factor V R506Q), founder effects are the most likely explanation for the geographical distribution of both mutations.

Poor-prognosis colon cancer is defined by a molecularly distinct subtype and develops from serrated precursor lesions

Abstract: Colon cancer is a clinically diverse disease. This heterogeneity makes it difficult to determine which patients will benefit most from adjuvant therapy and impedes the development of new targeted agents. More insight into the biological diversity of colon cancers, especially in relation to clinical features, is therefore needed. We demonstrate, using an unsupervised classification strategy involving over 1,100 individuals with colon cancer, that three main molecularly distinct subtypes can be recognized. Two subtypes have been previously identified and are well characterized (chromosomal-instable and microsatellite-instable cancers). The third subtype is largely microsatellite stable and contains relatively more CpG island methylator phenotype-positive carcinomas but cannot be identified on the basis of characteristic mutations. We provide evidence that this subtype relates to sessile-serrated adenomas, which show highly similar gene expression profiles, including upregulation of genes involved in matrix remodeling and epithelial-mesenchymal transition. The identification of this subtype is crucial, as it has a very unfavorable prognosis and, moreover, is refractory to epidermal growth factor receptor-targeted therapy.

Job Destruction and Propagation of Shocks

Abstract: We develop and quantitatively implement a dynamic general equilibrium model with labor" market matching and endogenous job destruction. The model produces a close match with data on" job creation and destruction. Cyclical fluctuations in the job destruction rate serve to magnify the" effects of productivity shock on output, as well as making the effects much more persistent. " Interactions between household savings decisions and separation decisions in employment" relationships play a key role in propagating shocks.