University of Virginia

About: University of Virginia is a education organization based out in Charlottesville, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 52543 authors who have published 113268 publications receiving 5220506 citations. The organization is also known as: U of V & UVa.

SPEED: a stateless protocol for real-time communication in sensor networks

Abstract: In this paper, we present a real-time communication protocol for sensor networks, called SPEED. The protocol provides three types of real-time communication services, namely, real-time unicast, real-time area-multicast and real-time area-anycast. SPEED is specifically tailored to be a stateless, localized algorithm with minimal control overhead End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and non-deterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments and a real implementation on Berkeley motes are provided to validate our claims.

Seagrass ecosystems as a globally significant carbon stock

Abstract: Seagrass meadows are some of the most productive ecosystems on Earth. An analysis of organic carbon data from just under one thousand seagrass meadows indicates that, globally, these systems could store between 4.2 and 8.4 Pg carbon.

Evaluating Clinical Accuracy of Systems for Self-Monitoring of Blood Glucose

Abstract: Although the scientific literature contains numerous reports of the statistical accuracy of systems for self-monitoring of blood glucose (SMBG), most of these studies determine accuracy in ways that may not be clinically useful. We have developed an error grid analysis (EGA), which describes the clinical accuracy of SMBG systems over the entire range of blood glucose values, taking into account 1) the absolute value of the system-generated glucose value, 2) the absolute value of the reference blood glucose value, 3) the relative difference between these two values, and 4) the clinical significance of this difference. The EGA of accuracy of five different reflectance meters (Eyetone, Dextrometer, Glucometer I, Glucometer II, Memory Glucometer II), a visually interpretable glucose reagent strip (Glucostix), and filter-paper spot glucose determinations is presented. In addition, reanalyses of a laboratory comparison of three reflectance meters (Accucheck II, Glucometer II, Glucoscan 9000) and of two previously published studies comparing the accuracy of five different reflectance meters with EGA is described. EGA provides the practitioner and the researcher with a clinically meaningful method for evaluating the accuracy of blood glucose values generated with various monitoring systems and for analyzing the clinical implications of previously published data.

Genome-wide analysis of estrogen receptor binding sites

Abstract: The estrogen receptor is the master transcriptional regulator of breast cancer phenotype and the archetype of a molecular therapeutic target. We mapped all estrogen receptor and RNA polymerase II binding sites on a genome-wide scale, identifying the authentic cis binding sites and target genes, in breast cancer cells. Combining this unique resource with gene expression data demonstrates distinct temporal mechanisms of estrogen-mediated gene regulation, particularly in the case of estrogen-suppressed genes. Furthermore, this resource has allowed the identification of cis-regulatory sites in previously unexplored regions of the genome and the cooperating transcription factors underlying estrogen signaling in breast cancer.