Colorado State University

About: Colorado State University is a education organization based out in Fort Collins, Colorado, United States. It is known for research contribution in the topics: Population & Laser. The organization has 31430 authors who have published 69040 publications receiving 2724463 citations. The organization is also known as: CSU & Colorado Agricultural College.

Interpretation of recent Southern Hemisphere climate change

Abstract: Climate variability in the high-latitude Southern Hemisphere (SH) is dominated by the SH annular mode, a large-scale pattern of variability characterized by fluctuations in the strength of the circumpolar vortex. We present evidence that recent trends in the SH tropospheric circulation can be interpreted as a bias toward the high-index polarity of this pattern, with stronger westerly flow encircling the polar cap. It is argued that the largest and most significant tropospheric trends can be traced to recent trends in the lower stratospheric polar vortex, which are due largely to photochemical ozone losses. During the summer-fall season, the trend toward stronger circumpolar flow has contributed substantially to the observed warming over the Antarctic Peninsula and Patagonia and to the cooling over eastern Antarctica and the Antarctic plateau.

A comprehensive meteorological modeling system?RAMS

Abstract: This paper presents a range of applications of the Regional Atmospheric Modeling System (RAMS), a comprehensive mesoscale meterological modeling system. Applications discussed in this paper include large eddy simulations (LES) and simulations of thunderstorms, cumulus fields, mesoscale convective systems, mid-latitude cirrus clouds, winter storms, mechanically- and thermally-forced mesoscale systems, and mesoscale atmospheric disperision. A summary of current RAMS options is also presented. Improvements to RAMS currently underway include refinements to the cloud radiation, cloud microphysics, cumulus, and surface soil/vegetative parameterization schemes, the parallelization of the code, development of a more versatile visualization capability, and research into meso-α-scale cumulus parameterization.

Host defense mechanisms triggered by microbial lipoproteins through toll-like receptors.

Abstract: The generation of cell-mediated immunity against many infectious pathogens involves the production of interleukin-12 (IL-12), a key signal of the innate immune system. Yet, for many pathogens, the molecules that induce IL-12 production by macrophages and the mechanisms by which they do so remain undefined. Here it is shown that microbial lipoproteins are potent stimulators of IL-12 production by human macrophages, and that induction is mediated by Toll-like receptors (TLRs). Several lipoproteins stimulated TLR-dependent transcription of inducible nitric oxide synthase and the production of nitric oxide, a powerful microbicidal pathway. Activation of TLRs by microbial lipoproteins may initiate innate defense mechanisms against infectious pathogens.

Are women more risk averse

Abstract: We find that single women exhibit relatively more risk aversion in financial decision making than single men. Using U.S. sample data, we examine household holdings of risky assets to determine whether there are gender differences in financial risk taking. As wealth increases, the proportion of wealth held as risky assets is estimated to increase by a smaller amount for single women than for single men. Gender differences in financial risk taking are also influenced by age, race, and number of children. Greater financial risk aversion may provide an explanation for women's lower levels of wealth compared with men's. (JEL J16, D81, G11)

A gentle introduction to quantile regression for ecologists

Abstract: Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogen...