Fluctuating velocity measurements in the turbulent wake of a wind turbine model

An experimental study of the turbulent wake of a wind turbine model was realized at the “Joaquim Blessmann” wind tunnel of the UFRGS. The turbine model was developed at the Universidade de Caxias do Sul and it represents a three blade turbine characterized by a NACA 4412 aerodynamic profile. Measurements of the velocity fluctuations were realized by hot wire anemometry. Complexity of the turbulent flow is evaluated by mean and fluctuating velocity profiles. The influence of the incident flow turbulence and the flow reconstructing process are analysed by the measurement results

Características da esteira turbulenta do modelo de um aerogerador

An experimental study of the turbulent wake of a wind turbine model was realized at the “Joaquim Blessmann” wind tunnel of the UFRGS. The turbine model was developed at the Universidade de Caxias do Sul and it represents a three blade turbine characterized by a NACA 4412 aerodynamic profile. Measurements of the velocity fluctuations were realized by hot wire anemometry. Complexity of the turbulent flow is evaluated by mean and fluctuating velocity profiles. The influence of the incident flow turbulence and the flow reconstructing process are analyzed by the measurement results.Um estudo experimental das características da esteira turbulenta a sotavento do rotor de uma turbina eólica foi realizado no túnel de vento “Joaquim Blessmann” da UFRGS. O modelo da turbina foi desenvolvido na Universidade de Caxias do Sul e representa um aerogerador de três pás caracterizadas por um perfil aerodinâmico NACA 4412. Medições das flutuações de velocidade foram realizadas com um anemômetro de fio quente. A complexidade do escoamento turbulento é avaliada a partir dos perfis de velocidade média e flutuantes. A influência da turbulência do escoamento incidente e o processo de recomposição do escoamento são avaliados através das medições realizadas

Phase locked neural activity in the human brainstem predicts preference for musical consonance.

When musical notes are combined to make a chord, the closeness of fit of the combined spectrum to a single harmonic series (the 'harmonicity' of the chord) predicts the perceived consonance (how pleasant and stable the chord sounds; McDermott, Lehr, & Oxenham, 2010). The distinction between consonance and dissonance is central to Western musical form. Harmonicity is represented in the temporal firing patterns of populations of brainstem neurons. The current study investigates the role of brainstem temporal coding of harmonicity in the perception of consonance. Individual preference for consonant over dissonant chords was measured using a rating scale for pairs of simultaneous notes. In order to investigate the effects of cochlear interactions, notes were presented in two ways: both notes to both ears or each note to different ears. The electrophysiological frequency following response (FFR), reflecting sustained neural activity in the brainstem synchronised to the stimulus, was also measured. When both notes were presented to both ears the perceptual distinction between consonant and dissonant chords was stronger than when the notes were presented to different ears. In the condition in which both notes were presented to the both ears additional low-frequency components, corresponding to difference tones resulting from nonlinear cochlear processing, were observable in the FFR effectively enhancing the neural harmonicity of consonant chords but not dissonant chords. Suppressing the cochlear envelope component of the FFR also suppressed the additional frequency components. This suggests that, in the case of consonant chords, difference tones generated by interactions between notes in the cochlea enhance the perception of consonance. Furthermore, individuals with a greater distinction between consonant and dissonant chords in the FFR to individual harmonics had a stronger preference for consonant over dissonant chords. Overall, the results provide compelling evidence for the role of neural temporal coding in the perception of consonance, and suggest that the representation of harmonicity in phase locked neural firing drives the perception of consonance

Plant Trait Dataset for Tree-Like Growth Forms Species of the Subtropical Atlantic Rain Forest in Brazil

Plant functional traits have been incorporated in studies of vegetation ecology to better understand the mechanisms of ecological processes. For this reason, a global effort has been made to collect functional traits data for as many species as possible. In light of this, we identified the most common species of an area of 15,335 km2 inserted in the subtropical Atlantic Rain Forest in Southern Brazil. Then, we compiled functional trait information mostly from field samples, but also from herbarium and literature. The dataset presents traits of leaf, branch, maximum potential height, seed mass, and dispersion syndrome of 117 species, including trees, tree ferns, and palms. We also share images of anatomical features of branches used to measure wood traits. Data tables present mean trait values at individual and species level. Images of wood and stomatal features may be useful to assess other anatomical traits that were not covered in the data tables for the anatomical determination of species and/or for educational purposes

Fluctuating velocity measurements in the turbulent wake of a wind turbine model

An experimental study of the turbulent wake of a wind turbine model was realized at the “Joaquim Blessmann” wind tunnel of the UFRGS. The turbine model was developed at the Universidade de Caxias do Sul and it represents a three blade turbine characterized by a NACA 4412 aerodynamic profile. Measurements of the velocity fluctuations were realized by hot wire anemometry. Complexity of the turbulent flow is evaluated by mean and fluctuating velocity profiles. The influence of the incident flow turbulence and the flow reconstructing process are analysed by the measurement results

Molecular epidemiology of Mycobacterium tuberculosis in Brazil before the whole genome sequencing era: a literature review

Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Programa de Pós-Graduação em Pesquisa Clínica e Doenças Infecciosas. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Bacteriologia e Bioensaios em Micobactérias. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular Aplicada a Micobactérias. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio Grande do Sul. Programa de Pós-Graduação em Biologia Celular e Molecular. Porto Alegre, RS, Brasil / Secretaria Estadual de Saúde do Rio Grande do Sul. Centro Estadual de Vigilância em Saúde. Centro de Desenvolvimento Científico e Tecnológico. Porto Alegre, RS, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Centro de Referência Professor Hélio Fraga. Laboratório de Referência Nacional para Tuberculose e outras Micobacterioses. Rio de Janeiro, RJ, Brasil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Pós-Graduação Biologia Parasitária na Amazônia. Belém, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Pós-Graduação Biologia Parasitária na Amazônia. Belém, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Laboratório de Geoprocessamento. Ananindeua, PA, Brasil.International Institute of Information Technology. Department of Data Science. Bangalore, India.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Secretaria Estadual de Saúde do Rio Grande do Sul. Centro Estadual de Vigilância em Saúde. Centro de Desenvolvimento Científico e Tecnológico. Porto Alegre, RS, Brasil.Universidade de São Paulo. Faculdade de Medicina. Departamento de Clínica Médica. Ribeirão Preto, SP, Brasil.Universidade de São Paulo. Faculdade de Medicina. Departamento de Clínica Médica. Ribeirão Preto, SP, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular Aplicada a Micobactérias. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Microbiologia Paulo de Góes. Laboratório de Micobactérias. Rio de Janeiro, RJ, Brasil.Universidade Federal de São Paulo. Departamento de Microbiologia, Imunologia e Parasitologia. São Paulo, SP, Brasil.Instituto Adolfo Lutz. Centro de Bacteriologia. Núcleo de Tuberculose e Micobacterioses. São Paulo, SP, Brasil.Universit e Paris-Saclay. Ecologie Systematique Evolution. Centre National de la Recherche Scientifique. AgroParisTech, Orsay, France.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Bacteriologia e Bioensaios em Micobactérias. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular Aplicada a Micobactérias. Rio de Janeiro, RJ, Brasil.Coordenação Geral de Vigilância das Doenças de Transmissão Respiratória de Condições Crônicas. Brasília, DF, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genética Molecular de Microrganismos. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Microbiologia Paulo de Góes. Laboratório de Micobactérias. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Molecular Aplicada a Micobactérias. Rio de Janeiro, RJ, Brasil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Pós-Graduação Biologia Parasitária na Amazônia. Belém, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Molecular-typing can help in unraveling epidemiological scenarios and improvement for disease control strategies. A literature review of Mycobacterium tuberculosis transmission in Brazil through genotyping on 56 studies published from 1996-2019 was performed. The clustering rate for mycobacterial interspersed repetitive units - variable tandem repeats (MIRUVNTR) of 1,613 isolates were: 73%, 33% and 28% based on 12, 15 and 24-loci, respectively; while for RFLP-IS6110 were: 84% among prison population in Rio de Janeiro, 69% among multidrug-resistant isolates in Rio Grande do Sul, and 56.2% in general population in São Paulo. These findings could improve tuberculosis (TB) surveillance and set up a solid basis to build a database of Mycobacterium genome