Quantum confined electronic states in atomically well-defined graphene nanostructures

Despite the enormous interest in the properties of graphene and the potential of graphene nanostructures in electronic applications, the study of quantum confined states in atomically well-defined graphene nanostructures remains an experimental challenge. Here, we study graphene quantum dots (GQDs) with well-defined edges in the zigzag direction, grown by chemical vapor deposition (CVD) on an iridium(111) substrate, by low-temperature scanning tunneling microscopy (STM) and spectroscopy (STS). We measure the atomic structure and local density of states (LDOS) of individual GQDs as a function of their size and shape in the range from a couple of nanometers up to ca. 20 nm. The results can be quantitatively modeled by a relativistic wave equation and atomistic tight-binding calculations. The observed states are analogous to the solutions of the text book "particle-in-a-box" problem applied to relativistic massless fermions.Comment: accepted for publication in Phys. Rev. Let

Assessment of the systemic effects of budesonide inhaled from Easyhaler®and from Turbuhaler®in healthy male volunteers

AbstractThe main objective of this study was to show dose-dependent equivalence in the systemic activity of budesonide 800 μ g day−1and 1600 μ g day−1delivered from either Easyhaler®or Turbuhaler®in healthy male subjects.This single-centre study was carried out according to a randomized, double-blind, double-dummy, five-way cross-over design over a 9-week period. All subjects received 1 week of treatment with the following, in randomized order, with a washout week between each treatment: budesonide Easyhaler®800 μ g day−1plus placebo Turbuhaler®; budesonide Easyhaler®1600 μ g day−1plus placebo Turbuhaler®; placebo Easyhaler®plus Pulmicort®Turbuhaler®800 μ g day−1; placebo Easyhaler®plus Pulmicort®Turbuhaler®1600 μ g day−1; placebo Easyhaler®plus placebo Turbuhaler®. The final inhalation of study drug was performed at the study centre, where blood and urine samples were collected.Fifteen subjects were recruited and all completed the study. Mean serum cortisol AUC0–20values (the primary outcome variable) were comparable for each device at the two dose levels, and met the defined criteria for equivalence (90% CI 0·8–1·25 for between-treatment difference). Budesonide 800 μ g day−1caused minimal suppression of serum cortisol AUC0-20values. Budesonide 1600 μ g day−1statistically significantly suppressed serum cortisol AUC0–20values compared with placebo. Mean morning serum cortisol values were within the reference range in all treatment groups. At a budesonide dose of 800 μ g day−1mean urine cortisol/creatinine ratio was statistically significantly higher with Easyhaler®than with Turbuhaler®, but there was no significant difference between the devices at the 1600 μ g day−1dose. Serum budesonide concentrations were equivalent for each device at both dose levels. Adverse drug reactions were infrequent and mild in nature and there were no clinically significant changes in laboratory safety variables.In conclusion, in healthy male volunteers, budesonide 800μ g day−1and 1600 μ g day−1inhaled from Easyhaler®had comparable systemic effects to the same doses inhaled via Turbuhaler®

Behavioural issues in environmental modelling -the missing perspective

Abstract The paper aims to demonstrate the importance of behavioural issues in environmental modelling. These issues can relate both to the modeler and to the modelling process including the social interaction in the modelling team. The origins of behavioural effects can be in the cognitive and motivational biases or in the social systems created as well as in the visual and verbal communication strategies used. The possible occurrence of these phenomena in the context of environmental modelling is discussed and suggestions for research topics are provided

A Bayesian test for the appropriateness of a model in the biomagnetic inverse problem

This paper extends the work of Clarke [1] on the Bayesian foundations of the biomagnetic inverse problem. It derives expressions for the expectation and variance of the a posteriori source current probability distribution given a prior source current probability distribution, a source space weight function and a data set. The calculation of the variance enables the construction of a Bayesian test for the appropriateness of any source model that is chosen as the a priori infomation. The test is illustrated using both simulated (multi-dipole) data and the results of a study of early latency processing of images of human faces. [1] C.J.S. Clarke. Error estimates in the biomagnetic inverse problem. Inverse Problems, 10:77--86, 1994.Comment: 13 pages, 16 figures. Submitted to Inverse Problem