On blocking rules for the bootstrap with dependent data

We address the issue of optimal block choice in applicationsof the block bootstrap to dependent data. It is shown that optimalblock size depends significantly on context, being equal ton^1/3, n^1/4 and n^1/5 in the cases of variance or bias estimation,estimation of a onesided distribution function, and estimationof a two-sided distribution function, respectively. A clearintuitive explanation of this phenomenon is given, togetherwith outlines of theoretical arguments in specific cases. Itis shown that these orders of magnitude of block sizes can beused to produce a simple, practical rule for selecting blocksize empirically. That technique is explored numerically.     

Co‐occurrence patterns of trees along macro‐climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

Aim During recent and future climate change, shifts in large‐scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress‐gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad‐scale environmental data. We evaluated the variation of species co‐occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates. Location Europe. Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co‐occurrence patterns. Results Correlation analyses supported the stress‐gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co‐occurrence patterns may play a major role. Main conclusions Our results demonstrate the importance of species co‐occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate‐induced spatial segregation of the major tree species could have ecological and economic consequences.     

Robust Selection of the Most Discriminative Variables in the Dichotomous Problem with Application to Some Respiratory Disease Data

A robust method for selection of variables with the greatest discriminatory power is presented in the paper. The method deals with the two groups of data problem. An application of the method to some respiratory disease data and comparisons with classical procedures are given, also.     

Field studies on the population dynamics of Biomphalaria glabrata, intermediate host of Schistosoma mansoni on the West Indian Island of St. Lucia

Growth curves, calculated for field populations of B. glabrata, were not materially affected by habitat, altitude or season. A mean growth curve was therefore used to estimate the age-frequency distribution of snails in successive field samples. These data permitted the construction of ecological life tables and the estimation of r, the intrinsic rate of natural increase (or decrease) of the different populations. The calculated values of r were inserted in a simple model of unlimited population growth but the resultant curves poorly represented the observed data. A model for unlimited growth was more satisfactory for pond and marsh populations but, apparently, immigration made it less satisfactory for stream and banana drain populations. Nevertheless, r may still be of value in predicting repopulation rates in certain habitats after a mollusciciding which does not kill the entire snail population.     

Transitions: Homo erectus and the Acheulian: the Ethiopian sites of Gadeb and the Middle Awash

Significant differences in activity-site patterning and artifact composition at Middle Pleistocene localities in Ethiopia's high plains and Afar Rift are indications of both single-episode, small-site residues from small groups and multi-purpose, multiple occupation sites from which larger, temporary groupings might be inferred. Reconstructions of palaeo-environments and geography show that large assemblages relate to relatively stable topography, such as stream channels or lake margins, while small assemblages are more common in deltaic situations of rapid sedimentation and burial in the Rift that preclude possibility of reoccupation. A model for Acheulian socio-economic behaviour within the drier African savanna, based (in part) on chimpanzee behaviour in open savanna habitats, is proposed. This takes the form of organization into relatively extensive territories, each with several more closed-vegetation core areas, of limited extent close to permanent water, surrounded by more extensive areas of drier, open savanna, regularly exploited and patrolled by small groups. Movement from one core area to another was rapid and made together as a group, to minimize danger from large predators and competition from other hominid groups.     

An overview of mechanistic modeling of liquid chromatography

Abstract

Liquid chromatography is considered to be the bottleneck for purification of therapeutic proteins. Development and optimization of chromatography process is a cumbersome activity due to the increasing complexities in the types and content of impurities present in the high product titer cell culture harvest obtained from the upstream processing. Further, regulatory expectations are continuously rising with the recent initiatives of quality by design and process analytical technology expecting the manufacturer to have a deeper understanding of the process and the product. Mechanistic modeling is one approach to gain this deeper understanding of a process step. It involves modeling of the underlying physicochemical processes. A well calibrated model with acceptable predictability can be very effective in both process optimization and process characterization activities. In this paper we provide an overview of mechanistic modeling of liquid chromatography. We discuss the various components that such a model entails and also presents the status quo of this area.