North Carolina State University

About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.

The genome sequence of the probiotic intestinal bacterium Lactobacillus johnsonii NCC 533

Abstract: Lactobacillus johnsonii NCC 533 is a member of the acidophilus group of intestinal lactobacilli that has been extensively studied for their "probiotic" activities that include, pathogen inhibition, epithelial cell attachment, and immunomodulation. To gain insight into its physiology and identify genes potentially involved in interactions with the host, we sequenced and analyzed the 1.99-Mb genome of L. johnsonii NCC 533. Strikingly, the organism completely lacked genes encoding biosynthetic pathways for amino acids, purine nucleotides, and most cofactors. In apparent compensation, a remarkable number of uncommon and often duplicated amino acid permeases, peptidases, and phosphotransferase-type transporters were discovered, suggesting a strong dependency of NCC 533 on the host or other intestinal microbes to provide simple monomeric nutrients. Genome analysis also predicted an abundance (>12) of large and unusual cell-surface proteins, including fimbrial subunits, which may be involved in adhesion to glycoproteins or other components of mucin, a characteristic expected to affect persistence in the gastrointestinal tract (GIT). Three bile salt hydrolases and two bile acid transporters, proteins apparently critical for GIT survival, were also detected. In silico genome comparisons with the >95% complete genome sequence of the closely related Lactobacillus gasseri revealed extensive synteny punctuated by clear-cut insertions or deletions of single genes or operons. Many of these regions of difference appear to encode metabolic or structural components that could affect the organisms competitiveness or interactions with the GIT ecosystem.

Rule-Based Control of Battery Energy Storage for Dispatching Intermittent Renewable Sources

Abstract: Integrating a battery energy storage system (BESS) with a solar photovoltaic (PV) system or a wind farm can make these intermittent renewable energy sources more dispatchable. This paper focuses on the development of a control strategy for optimal use of the BESS for this purpose. The paper considers a rule-based control scheme, which is the solution of the optimal control problem defined, to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge current limits, and lifetime. The goal of the control is to have the BESS provide as much smoothing as possible so that the renewable resource can be dispatched on an hourly basis based on the forecasted solar/wind conditions. The effectiveness of this control strategy has been tested by using an actual PV system and wind farm data and it is shown that the BESS can indeed help to cope with variability in wind's and solar's generation.

NTP‐CERHR expert panel report on the reproductive and developmental toxicity of bisphenol A

Abstract: Robert E. Chapin, Jane Adams, Kim Boekelheide, L. Earl Gray Jr, Simon W. Hayward, Peter S.J. Lees, Barry S. McIntyre, Kenneth M. Portier, Teresa M. Schnorr, Sherry G. Selevan, John G. Vandenbergh, and Susan R. Woskie Pfizer, Inc., Groton, CT University of Massachusetts, Boston, MA Brown University, Providence, RI U.S. Environmental Protection Agency, Research Triangle Park, NC Vanderbilt University Medical Center, Nashville, TN Johns Hopkins University, Baltimore, MD Schering Plough Research Institute, Summit, NJ American Cancer Society, Atlanta, GA National Institute for Occupational Safety and Health, Cincinnati, OH U.S. Public Health Service (Ret), Silver Spring, MD North Carolina State University, Raleigh, NC University of Massachusetts, Lowell, MA

Simultaneous regression shrinkage, variable selection, and supervised clustering of predictors with OSCAR.

Abstract: Variable selection can be challenging, particularly in situations with a large number of predictors with possibly high correlations, such as gene expression data. In this article, a new method called the OSCAR (octagonal shrinkage and clustering algorithm for regression) is proposed to simultaneously select variables while grouping them into predictive clusters. In addition to improving prediction accuracy and interpretation, these resulting groups can then be investigated further to discover what contributes to the group having a similar behavior. The technique is based on penalized least squares with a geometrically intuitive penalty function that shrinks some coefficients to exactly zero. Additionally, this penalty yields exact equality of some coefficients, encouraging correlated predictors that have a similar effect on the response to form predictive clusters represented by a single coefficient. The proposed procedure is shown to compare favorably to the existing shrinkage and variable selection techniques in terms of both prediction error and model complexity, while yielding the additional grouping information.