A conodont fauna of the Dinantian from the Kuznetsk Basin (Southern Siberia)

Lower to middle Tournaisian conodonts are recorded for the first time from southern Siberia. An exact correlation with Belgian and West-German Tournaisian stratotypes seems impossible. The conodont assemblage is characteristic of shallow marine costal areas

Recherches biostratigraphiques dans quelques coupes du Famennien de l'Avesnois (Nord de la France)

Conodonts and Goniatites from four "old" famennian sections in the Avesnois (France) have been carefully studies. For the first time, the biostratigraphic position of these sections is determined

Stratigraphic interpretation of the Tohogne borehole (province de Luxembourg). Devonian - Carbinoferous transition

The Tohogne borehole section, from the Lower Tournaisian into the Upper Famennian, has a remarkable micropalaeontological content (conodonts, foraminifers, spores) which enabled a detailed subdivision of these strata. New data in biostratigraphy and systematic palaeontology and palaeogeographic implications are presented, as well as correlations with reference sections

Efficient estimation of AUC in a sliding window

In many applications, monitoring area under the ROC curve (AUC) in a sliding window over a data stream is a natural way of detecting changes in the system. The drawback is that computing AUC in a sliding window is expensive, especially if the window size is large and the data flow is significant. In this paper we propose a scheme for maintaining an approximate AUC in a sliding window of length $k$. More specifically, we propose an algorithm that, given $\epsilon$, estimates AUC within $\epsilon / 2$, and can maintain this estimate in $O((\log k) / \epsilon)$ time, per update, as the window slides. This provides a speed-up over the exact computation of AUC, which requires $O(k)$ time, per update. The speed-up becomes more significant as the size of the window increases. Our estimate is based on grouping the data points together, and using these groups to calculate AUC. The grouping is designed carefully such that ($i$) the groups are small enough, so that the error stays small, ($ii$) the number of groups is small, so that enumerating them is not expensive, and ($iii$) the definition is flexible enough so that we can maintain the groups efficiently. Our experimental evaluation demonstrates that the average approximation error in practice is much smaller than the approximation guarantee $\epsilon / 2$, and that we can achieve significant speed-ups with only a modest sacrifice in accuracy

StarBEAST2 Brings Faster Species Tree Inference and Accurate Estimates of Substitution Rates

Fully Bayesian multispecies coalescent (MSC) methods like *BEAST estimate species trees from multiple sequence alignments. Today thousands of genes can be sequenced for a given study, but using that many genes with *BEAST is intractably slow. An alternative is to use heuristic methods which compromise accuracy or completeness in return for speed. A common heuristic is concatenation, which assumes that the evolutionary history of each gene tree is identical to the species tree. This is an inconsistent estimator of species tree topology, a worse estimator of divergence times, and induces spurious substitution rate variation when incomplete lineage sorting is present. Another class of heuristics directly motivated by the MSC avoids many of the pitfalls of concatenation but cannot be used to estimate divergence times. To enable fuller use of available data and more accurate inference of species tree topologies, divergence times, and substitution rates, we have developed a new version of *BEAST called StarBEAST2. To improve convergence rates we add analytical integration of population sizes, novel MCMC operators and other optimizations. Computational performance improved by 13.5× and 13.8× respectively when analyzing two empirical data sets, and an average of 33.1× across 30 simulated data sets. To enable accurate estimates of per-species substitution rates, we introduce species tree relaxed clocks, and show that StarBEAST2 is a more powerful and robust estimator of rate variation than concatenation. StarBEAST2 is available through the BEAUTi package manager in BEAST 2.4 and above.This work was supported by a Rutherford Discovery Fellowship awarded to A.J.D. by the Royal Society of New Zealand. H.A.O. was supported by an Australian Laureate Fellowship awarded to Craig Moritz by the Australian Research Council (FL110100104)

Korte historiek van het aandeel van de diergeneeskunde in het experimenteel onderzoek in de humane geneeskunde = A short description of veterinary contributions to experimental research in human medicine

A short description is given of the life and work of scientists active in veterinary research, who contributed substantially to the knowledge of human disease and health. Microbiology and immunology were their main fields of interest. Important microbiologists include Edmond Nocard, Karl F. Meyer, Daniel Salmon, Victor Babes and Arnold Theiler. Still others were mainly active as immunologists. Gaston Ramon's works on bacterial toxins resulted in effective vaccines against tetanos as well as diphteritis, until then an important cause of child mortality. Early findings of Auguste Chauveau established a basis for understanding immunity to microbial diseases. Nobel prize-winning Peter C. Doherty helped to elucidate the complex mechanisms of cellular immunity

Gebruikersbevragingen bij de overheid

Klantentevredenheidsmetingen hebben ook hun intrede gedaan bij overheden. Belangrijke verschilpunten met tevredenheidsmetingen in de private sector zijn dat een groot aantal factoren die niet met de kwaliteit van de dienstverlening te maken hebben tevredenheid beïnvloeden, en dat dergelijke bevragingen ook belangrijk zijn als instrument om gebruikers en burgers daadwerkelijk te betrekken bij het beleid

Gebruikersbevragingen bij de overheid

Klantentevredenheidsmetingen hebben ook hun intrede gedaan bij overheden. Belangrijke verschilpunten met tevredenheidsmetingen in de private sector zijn dat een groot aantal factoren die niet met de kwaliteit van de dienstverlening te maken hebben tevredenheid beïnvloeden, en dat dergelijke bevragingen ook belangrijk zijn als instrument om gebruikers en burgers daadwerkelijk te betrekken bij het beleid