Quasinormal modes of a black hole with a cloud of strings in Einstein-Gauss-Bonnet gravity

The quasinormal modes for a scalar field in the background spacetime corresponding to a black hole, with a cloud of strings, in Einstein-Gauss-Bonnet gravity, and the tensor quasinormal modes corresponding to perturbations in such spacetime, were both calculated using the WKB approximation. In the obtained results we emphasize the role played by the parameter associated with the string cloud, comparing them with the results already obtained for the Boulware-Deser metric. We also study how the Gauss-Bonnet correction to general relativity affects the results for the quasinormal modes, comparing them with the same background in general relativity.Comment: 15 pages, 7 figures; To appear in IJMP

Preditores de fibrilação atrial de novo em unidade de cuidados intensivos não cardíaca

OBJECTIVE: To assess the predictors of de novo atrial fibrillation in patients in a non-cardiac intensive care unit. METHODS: A total of 418 hospitalized patients were analyzed between January and September 2016 in a non-cardiac intensive care unit. Clinical characteristics, interventions, and biochemical markers were recorded during hospitalization. In-hospital mortality and length of hospital stay in the intensive care unit were also evaluated. RESULTS: A total of 310 patients were included. The mean age of the patients was 61.0 ± 18.3 years, 49.4% were male, and 23.5% presented de novo atrial fibrillation. The multivariate model identified previous stroke (OR = 10.09; p = 0.016) and elevated levels of pro-B type natriuretic peptide (proBNP, OR = 1.28 for each 1,000pg/mL increment; p = 0.004) as independent predictors of de novo atrial fibrillation. Analysis of the proBNP receiver operating characteristic curve for prediction of de novo atrial fibrillation revealed an area under the curve of 0.816 (p 5,666pg/mL. There were no differences in mortality (p = 0.370), but the lengths of hospital stay (p = 0.002) and stay in the intensive care unit (p = 0.031) were higher in patients with de novo atrial fibrillation. CONCLUSIONS: A history of previous stroke and elevated proBNP during hospitalization were independent predictors of de novo atrial fibrillation in the polyvalent intensive care unit. The proBNP is a useful and easy- and quick-access tool in the stratification of atrial fibrillation risk.Objetivo: Avaliar quais os preditores de fibrilação atrial de novo em doentes de uma unidade de cuidados intensivos não cardíaca. Métodos: Foram analisados 418 doentes internados entre janeiro e setembro de 2016 em uma unidade de cuidados intensivos não cardíaca. Registaram-se as características clínicas, as intervenções efetuadas e os marcadores bioquímicos durante a internação. Avaliaram-se ainda a mortalidade hospitalar e o tempo de internação hospitalar e na unidade de cuidados intensivos. Resultados: Foram incluídos 310 doentes, com média de idades de 61,0 ± 18,3 anos, 49,4% do sexo masculino, 23,5% com fibrilação atrial de novo. O modelo multivariável identificou acidente vascular cerebral prévio (OR de 10,09; p = 0,016) e valores aumentados de proBNP (OR de 1,28 por cada aumento em 1.000pg/mL; p = 0,004) como preditores independentes de fibrilação atrial de novo. A análise por curva Característica de Operação do Receptor do proBNP para predição de fibrilação atrial de novo revelou área sob a curva de 0,816 (p 5.666pg/mL. Não se verificaram diferenças na mortalidade (p = 0,370), porém a duração da internação hospitalar (p = 0,002) e na unidade de cuidados intensivos (p = 0,031) foi superior nos doentes com fibrilação atrial de novo. Conclusões: História de acidente vascular cerebral prévio e proBNP elevado em internação constituíram preditores independentes de fibrilação atrial de novo na unidade de cuidados intensivos polivalente. O proBNP pode constituir ferramenta útil, de fácil e rápido acesso na estratificação do risco de fibrilação atrial.info:eu-repo/semantics/publishedVersio

Tuning edge state localization in graphene nanoribbons by in-plane bending

The electronic properties of graphene are influenced by both geometric confinement and strain. We study the electronic structure of in-plane bent graphene nanoribbons, systems where confinement and strain are combined. To understand its electronic properties, we develop a tight-binding model that has a small computational cost and is based on exponentially decaying hopping and overlap parameters. Using this model, we show that the edge states in zigzag graphene nanoribbons are sensitive to bending and develop an effective dispersion that can be described by a one-dimensional atomic chain model. Because the velocity of the electrons at the edge is proportional to the slope of the dispersion, the edge states become gradually delocalized upon increasing the strength of bending.Comment: 11 pages, 8 figure