Michigan State University

About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.

Output feedback stabilization of fully linearizable systems

Abstract: An observer-based controller is designed to stabilize a fully linearizable nonlinear system. The system is assumed to be left-invertible and minimum-phase. The controller is robust to uncertainties in modelling the nonlinearities of the system. The design of the controller and the stability analysis employs the techniques of singular perturbations. A new ‘Tikhonov-like’ theorem is presented and used to analyse the system when the control is globally bounded.

Big houses, big cars, superfleas and the costs of reproduction

Abstract: The assumption of costs of reproduction were a logical necessity for much of the early development of life history theory. An unfortunate property of 'logical necessities' is that it is easy to also assume that they must be true. What if this does not turn out to be the case? The existence and universality of costs of reproduction were initially challenged with empirical data of questionable value, but later with increasingly strong theoretical and empirical results. Here, we discuss Ken Spitze's 'superfleas', which represent what we consider to be the strongest empirical challenge to the universality of costs, then offer a possible explanation for their existence.

Plot-scale evidence of tundra vegetation change and links to recent summer warming.

Abstract: Temperature is increasing at unprecedented rates across most of the tundra biome(1). Remote-sensing data indicate that contemporary climate warming has already resulted in increased productivity ov ...

Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine.

Abstract: Background: Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. Highthroughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. Methods and Findings: Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400–1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. Conclusions: The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genuslevel with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate well with pyrosequencing-based compositions, especially for lower-order ranks, indicating high robustness of both approaches. However, incompatible grouping schemes make exact comparison difficult.