Three-Algebras in N = 5, 6 Superconformal Chern-Simons Theories: Representations and Relations

In this work we present 3-algebraic constructions and representations for three-dimensional N = 5 supersymmetric Chern-Simons theories, and show how they relate to theories with additional supersymmetries. The N = 5 structure constants give theories with Sp(2N) \times SO(M) gauge symmetry, as well as more exotic symmetries known from gauged supergravity. We find explicit lifts from N = 6 to 8, and N = 5 to 6 and 8, for appropriate gauge groups.Comment: 23 pages. Published version. References correcte

Claw-free t-perfect graphs can be recognised in polynomial time

A graph is called t-perfect if its stable set polytope is defined by non-negativity, edge and odd-cycle inequalities. We show that it can be decided in polynomial time whether a given claw-free graph is t-perfect

Wirkortäquilibration, Anschlagzeit, "time to peak effect": Bedeutung pharmakokinetisch-dynamischer Prinzipien für die tägliche klinische Praxis

Zusammenfassung: In der anästhesiologischen Pharmakologie spielen im Gegensatz zur internistischen Pharmakologie "Non-steady-state-Phänomene" eine herausragende Rolle. Ihr Verständnis ist eine Conditio sine qua non für die sichere und effiziente Applikation von anästhesierelevanten Medikamenten. Insbesondere die Verfügbarkeit der "optimierten target controlled infusion" ("optimized TCI"), von TCI-Systemen mit Ansteuerung des Effektkompartiments und dem relativ geringen Dosierungsspielraum bei "conscious sedation" unter erhaltener Spontanatmung verlangen von Anästhesisten, sich mit dem Konzept des Konzentrationsverlaufes am Wirkort auseinander zu setzen. Der Leser wird in die grundlegende Problematik eingeführt. Anwendungen der Prinzipien bei der Applikation von Muskelrelaxanzien, Propofol mit TCI-Systemen, volatilen Anästhetika und Opiaten werden erläuter

Protocol for the United Kingdom Rotator Cuff Study (UKUFF) : a randomised controlled trial of open and arthroscopic rotator cuff repair

This project was funded by the NIHR Health Technology Assessment programme (project number 05/47/02). J. L. Rees has received a grant from Oxford University which is related to this paper. J. Dawson reports that Oxford University has received a grant from HTA which is related to this paper, as well as a study grant.Peer reviewedPublisher PD

Challenges to estimating vaccine impact using hospitalization data.

Because the real-world impact of new vaccines cannot be known before they are implemented in national programs, post-implementation studies at the population level are critical. Studies based on analysis of hospitalization rates of vaccine-preventable outcomes are typically used for this purpose. However, estimates of vaccine impact based on hospitalization data are particularly prone to confounding, as hospitalization rates are tightly linked to changes in the quality, access and use of the healthcare system, which often occur simultaneously with introduction of new vaccines. Here we illustrate how changes in healthcare delivery coincident with vaccine introduction can influence estimates of vaccine impact, using as an example reductions in infant pneumonia hospitalizations after introduction of the 10-valent pneumococcal conjugate vaccine (PCV10) in Brazil. To this end, we explore the effect of changes in several metrics of quality and access to public healthcare on trends in hospitalization rates before (2008-09) and after (2011-12) PCV10 introduction in 2010. Changes in infant pneumonia hospitalization rates following vaccine introduction were significantly associated with concomitant changes in hospital capacity and the fraction of the population using public hospitals. Importantly, reduction of pneumonia hospitalization rates after PCV10 were also associated with the expansion of outpatient services in several Brazilian states, falling more sharply where primary care coverage and the number of health units offering basic and emergency care increased more. We show that adjustments for unrelated (non-vaccine) trends commonly employed by impact studies, such as use of single control outcomes, are not always sufficient for accurate impact assessment. We discuss several ways to identify and overcome such biases, including sensitivity analyses using different denominators to calculate hospitalizations rates and methods that track changes in the outpatient setting. Employing these practices can improve the accuracy of vaccine impact estimates, particularly in evolving healthcare settings typical of low- and middle-income countries