Vrije Universiteit Brussel

About: Vrije Universiteit Brussel is a education organization based out in Brussels, Belgium. It is known for research contribution in the topics: Population & Context (language use). The organization has 14295 authors who have published 38258 publications receiving 1203970 citations. The organization is also known as: VUB.

Anthropogenic perturbation of the carbon fluxes from land to ocean

Abstract: A substantial amount of the atmospheric carbon taken up on land through photosynthesis and chemical weathering is transported laterally along the aquatic continuum from upland terrestrial ecosystems to the ocean. So far, global carbon budget estimates have implicitly assumed that the transformation and lateral transport of carbon along this aquatic continuum has remained unchanged since pre-industrial times. A synthesis of published work reveals the magnitude of present-day lateral carbon fluxes from land to ocean, and the extent to which human activities have altered these fluxes. We show that anthropogenic perturbation may have increased the flux of carbon to inland waters by as much as 1.0 Pg C yr−1 since pre-industrial times, mainly owing to enhanced carbon export from soils. Most of this additional carbon input to upstream rivers is either emitted back to the atmosphere as carbon dioxide (~0.4 Pg C yr−1) or sequestered in sediments (~0.5 Pg C yr−1) along the continuum of freshwater bodies, estuaries and coastal waters, leaving only a perturbation carbon input of ~0.1 Pg C yr−1 to the open ocean. According to our analysis, terrestrial ecosystems store ~0.9 Pg C yr−1 at present, which is in agreement with results from forest inventories but significantly differs from the figure of 1.5 Pg C yr−1 previously estimated when ignoring changes in lateral carbon fluxes. We suggest that carbon fluxes along the land–ocean aquatic continuum need to be included in global carbon dioxide budgets.

How informative is the mouse for human gut microbiota research

Abstract: The microbiota of the human gut is gaining broad attention owing to its association with a wide range of diseases, ranging from metabolic disorders (e.g. obesity and type 2 diabetes) to autoimmune diseases (such as inflammatory bowel disease and type 1 diabetes), cancer and even neurodevelopmental disorders (e.g. autism). Having been increasingly used in biomedical research, mice have become the model of choice for most studies in this emerging field. Mouse models allow perturbations in gut microbiota to be studied in a controlled experimental setup, and thus help in assessing causality of the complex host-microbiota interactions and in developing mechanistic hypotheses. However, pitfalls should be considered when translating gut microbiome research results from mouse models to humans. In this Special Article, we discuss the intrinsic similarities and differences that exist between the two systems, and compare the human and murine core gut microbiota based on a meta-analysis of currently available datasets. Finally, we discuss the external factors that influence the capability of mouse models to recapitulate the gut microbiota shifts associated with human diseases, and investigate which alternative model systems exist for gut microbiota research.

Handbook of Chemometrics and Qualimetrics

Abstract: Introduction. Statistical Description of the Quality of Processes and Measurements. The Normal Distribution. An Introduction to Hypothesis Testing. Some Important Hypothesis Tests. Analysis of Variance. Control Charts. Straight Line Regression and Calibration. Vectors and Matrices. Multiple and Polynomial Regression. Non-linear Regression. Robust Statistics. Internal Method Validation. Method Validation by Interlaboratory Studies. Other Distributions. The 2 2 Contingency Table. Principal Components. Information Theory. Fuzzy Methods. Process Modelling and Sampling. An Introduction to Experimental Design. Two-level Factorial Designs. Fractional Factorial Designs. Multi-level Designs. Mixture Designs. Other Optimization Methods. Genetic Algorithms and Other Global Search Strategies. Index.

Robust regression by means of s-estimators

Abstract: There are at least two reasons why robust regression techniques are useful tools in robust time series analysis. First of all, one often wants to estimate autoregressive parameters in a robust way, and secondly, one sometimes has to fit a linear or nonlinear trend to a time series. In this paper we shall develop a class of methods for robust regression, and briefly comment on their use in time series. These new estimators are introduced because of their invulnerability to large fractions of contaminated data. We propose to call them “S-estimators” because they are based on estimators of scale.