Speckle statistics in adaptive optics images at visible wavelengths

Residual speckles in adaptive optics (AO) images represent a well-known limitation on the achievement of the contrast needed for faint source detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations, not corrected by the AO, or slowly evolving aberrations induced by the optical system. We take advantage of the high temporal cadence (1 ms) of the data acquired by the System for Coronagraphy with High-order Adaptive Optics from R to K bands-VIS forerunner experiment at the Large Binocular Telescope to characterize the AO residual speckles at visible wavelengths. An accurate knowledge of the speckle pattern and its dynamics is of paramount importance for the application of methods aimed at their mitigation. By means of both an automatic identification software and information theory, we study the main statistical properties of AO residuals and their dynamics. We therefore provide a speckle characterization that can be incorporated into numerical simulations to increase their realism and to optimize the performances of both real-time and postprocessing techniques aimed at the reduction of the speckle noise

Comparativo entre PVFS2 e GlusterFS em um Ambiente de Computação em Nuvem

Este trabalho apresenta um estudo comparativo sobre o desempenho de dois sistemas de arquivos distribuídos, o Parallel Virtual File System 2 (PVFS2) e o GlusterFS, em um ambiente de computação em nuvem. O estudo comparativo baseia-se no teste de medição de vazão relacionada às operações de leitura e escrita realizadas a partir de um cliente para um conjunto de servidores de dados virtualizados. Os resultados tabulados indicam que PVFS2 mantém vazão constante, e próxima a largura de banda disponível, para todos os tamanhos de arquivos e que GlusterFS mantém alta vazão para arquivos de 1MB com queda significativa para arquivos maiores, e nestes casos tem desempenho inferior ao PVFS2

SHARK-NIR: from K-band to a key instrument, a status update

SHARK-NIR channel is one of the two coronagraphic instruments proposed for the Large Binocular Telescope, in the framework of the call for second generation instruments, issued in 2014. Together with the SHARK-VIS channel, it will offer a few observing modes (direct imaging, coronagraphic imaging and coronagraphic low resolution spectroscopy) covering a wide wavelength domain, going from 0.5μm to 1.7μm. Initially proposed as an instrument covering also the K-band, the current design foresees a camera working from Y to H bands, exploiting in this way the synergy with other LBT instruments such as LBTI, which is actually covering wavelengths greater than L' band, and it will be soon upgraded to work also in K band. SHARK-NIR has been undergoing the conceptual design review at the end of 2015 and it has been approved to proceed to the final design phase, receiving the green light for successive construction and installation at LBT. The current design is significantly more flexible than the previous one, having an additional intermediate pupil plane that will allow the usage of coronagraphic techniques very efficient in term of contrast and vicinity to the star, increasing the instrument coronagraphic performance. The latter is necessary to properly exploit the search of giant exo-planets, which is the main science case and the driver for the technical choices of SHARK-NIR. We also emphasize that the LBT AO SOUL upgrade will further improve the AO performance, making possible to extend the exo-planet search to target fainter than normally achieved by other 8-m class telescopes, and opening in this way to other very interesting scientific scenarios, such as the characterization of AGN and Quasars (normally too faint to be observed) and increasing considerably the sample of disks and jets to be studied. Finally, we emphasize that SHARK-NIR will offer XAO direct imaging capability on a FoV of about 15"x15", and a simple coronagraphic spectroscopic mode offering spectral resolution ranging from few hundreds to few thousands. This article presents the current instrument design, together with the milestones for its installation at LBT. <P /

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

A História da Alimentação: balizas historiográficas

Os M. pretenderam traçar um quadro da História da Alimentação, não como um novo ramo epistemológico da disciplina, mas como um campo em desenvolvimento de práticas e atividades especializadas, incluindo pesquisa, formação, publicações, associações, encontros acadêmicos, etc. Um breve relato das condições em que tal campo se assentou faz-se preceder de um panorama dos estudos de alimentação e temas correia tos, em geral, segundo cinco abardagens Ia biológica, a econômica, a social, a cultural e a filosófica!, assim como da identificação das contribuições mais relevantes da Antropologia, Arqueologia, Sociologia e Geografia. A fim de comentar a multiforme e volumosa bibliografia histórica, foi ela organizada segundo critérios morfológicos. A seguir, alguns tópicos importantes mereceram tratamento à parte: a fome, o alimento e o domínio religioso, as descobertas européias e a difusão mundial de alimentos, gosto e gastronomia. O artigo se encerra com um rápido balanço crítico da historiografia brasileira sobre o tema

Virtual power: a cost model based on the processor energy consumption per virtual machine in IaaS clouds

The outsourcing of computing services has been through constant evolutions in the past years, due to the increase of demand for computing resources. Accordingly, data centers are the main suppliers of computing service and cloud-based computing services provide a new paradigm for the offer and consumption of these computing resources. A substantial motivator for using cloud computing is its pricing model, which enables to charge the customer only for the resources he used, thus adopting a pay-as-you-use cost model. Among cloud-based computing services, the service type Infrastructure-as-a-Service (IaaS) is the one mostly used by companies that would like to outsource their computing infrastructure. The IaaS service, in most cases, is offered through virtual machines. This paper revisits the cost models used by data centers and analyses the costs of supply of virtual machines based on IaaS. This analysis identifies that electricity represents a considerable portion of this cost and that much of the consumption comes from the use of processors in virtual machines, and that this aspect is not considered in the identified cost models. This paper describes the Virtual Power Model, a cost model based on energy consumption of the processor in cloud-based, virtual machines in IaaS. The model is based on the assumptions of energy consumption vs. processing load, among others, which are proven through experiments in a test environment of a small data center. As a result, the Virtual Power Model proves itself as a fairer pricing model for the consumed resources than the identified models. Finally, a case study is performed to compare the costs charged to a client using the cost model of Amazon for the AWS EC2 service and the same service charged using the Virtual Power Model.A terceirização dos serviços de computação tem passado por evoluções constantes nos últimos anos em função do contínuo aumento na demanda por recursos computacionais. Neste sentido, os data centers são os principais fornecedores de serviço de computação e os serviços de computação em nuvem proporcionam um novo paradigma na oferta e consumo desses recursos computacionais. Um considerável motivador do uso das nuvens computacionais é o seu modelo de tarifação que possibilita a cobrança do cliente somente dos recursos que ele utilizou, adotando um modelo de custo do tipo pay-as-you-use. Dentre os serviços de computação em nuvem, o serviço do tipo IaaS (Infrastructure-as-a-Service) é um dos mais utilizados por empresas que desejam terceirizar a sua infraestrutura computacional. O serviço de IaaS, na grande maioria dos casos, é ofertado através de instâncias de máquinas virtuais. O presente trabalho revisita os modelos de custos empregados em data centers analisando a formação dos custos no fornecimento de máquina virtuais em nuvens baseadas em IaaS. Com base nesta análise identificasse que a energia elétrica possui uma parcela considerável deste custo e que boa parte deste consumo é proveniente do uso de processadores pelas máquinas virtuais, e que esse aspecto não é considerado nos modelos de custos identificados. Este trabalho descreve o Modelo Virtual Power, um modelo de custo baseado no consumo de energia do processador por máquina virtual em nuvens IaaS. A constituição do modelo está baseada nas premissas de consumo de energia vs. carga de processamento, entre outros, que são comprovados através de experimentação em um ambiente de testes em um data center de pequeno porte. Como resultado o Modelo Virtual Power mostra-se mais justo na precificação dos recursos consumidos do que os modelos identificados. Por fim, é realizado um estudo de caso comparando os custos tarifado a um cliente empregando o modelo de custo da Amazon no serviço AWS EC2 e o mesmo serviço tarifado utilizando o Modelo Virtual Power.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Speckle statistics in adaptive optics images at visible wavelengths

Residual speckles in adaptive optics (AO) images represent a well-known limitation on the achievement of the contrast needed for faint source detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations, not corrected by the AO, or slowly evolving aberrations induced by the optical system. We take advantage of the high temporal cadence (1 ms) of the data acquired by the System for Coronagraphy with High-order Adaptive Optics from R to K bands-VIS forerunner experiment at the Large Binocular Telescope to characterize the AO residual speckles at visible wavelengths. An accurate knowledge of the speckle pattern and its dynamics is of paramount importance for the application of methods aimed at their mitigation. By means of both an automatic identification software and information theory, we study the main statistical properties of AO residuals and their dynamics. We therefore provide a speckle characterization that can be incorporated into numerical simulations to increase their realism and to optimize the performances of both real-time and postprocessing techniques aimed at the reduction of the speckle noise. (C) 2017 Society of PhotoOptical Instrumentation Engineers (SPIE).Adaptive Optics National Laboratory of Italy; European Commission [653982]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]