University of Minnesota

About: University of Minnesota is a education organization based out in Minneapolis, Minnesota, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 117432 authors who have published 257986 publications receiving 11944239 citations. The organization is also known as: University of Minnesota, Twin Cities & University of Minnesota-Twin Cities.

Guidelines on management (diagnosis and treatment) of syncope

Abstract: Table of contents Preamble Scope of the document 1256 Method 1257 Part 1. Classification, epidemiology and prognosis Definition 1258 Brief overview of pathophysiology of syncope 1258 Classification 1259 Epidemiological considerations 1259 Prognostic stratification: identification of factors predictive of adverse outcome 1260 Part 2. Diagnosis Strategy of evaluation (flow chart) 1262 Initial evaluation (history, physical examination, baseline electrocardiogram) 1264 Echocardiogram 1266 Carotid sinus massage 1266 Tilt testing 1268 Electrocardiographic monitoring (non-invasive and invasive) 1271 Electrophysiological testing 1273 ATP test 1277 Ventricular signal-averaged electrocardiogram 1278 Exercise testing 1278 Cardiac catheterization and angiography 1279 Neurological and psychiatric evaluation 1279 Diagnostic yield and prevalence of causes of syncope 1282

Energy-efficient target coverage in wireless sensor networks

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

QM/MM: what have we learned, where are we, and where do we go from here?

Abstract: This paper briefly reviews the current status of the most popular methods for combined quantum mechanical/molecular mechanical (QM/MM) calculations, including their advantages and disadvantages There is a special emphasis on very general link-atom methods and various ways to treat the charge near the boundary Mechanical and electric embedding are contrasted We consider methods applicable to gas-phase organic chemistry, liquid-phase organic and organometallic chemistry, biochemistry, and solid-state chemistry Then we review some recent tests of QM/MM methods and summarize what we learn about QM/MM from these studies We also discuss some available software Finally, we present a few comments about future directions of research in this exciting area, where we focus on more intimate blends of QM with MM