Psoroptic mange in cattle of european and indian breeds, in the state of São Paulo, Brasil. Psoroptes natalensis, hirst 1919 synonimous to P. equi var. bovis (Gerlach 1857)

1) — A sarna psoróptica dos bovinos de raças européias e indianas é referida pela primeira vez no Estado de São Paulo, nos municípios de Burí e Itapetininga. 2) — O seu tratamento póde ser eficazmente feito pelos banhos arsênico-sulfo-cálcicos, estudados no Uruguai por Heguito e colaboradores. 3) — O estudo morfológico dos machos e das fêmeas púberes encontrados em cópula mostra que P. natalensis, Hirst 1919, é sinônimo de P. equi var. bovis (Gerlach, 1857), não apenas por serem os caracteres distintivos dos machos variáveis demais para merecerem valor específico, como também por não existirem diferenças entre as fêmeas púberes de P. natalensis e P. equi var. bovis.1) — The existence of psoroptic mange in cattle from both European and Indian breeds is demonstrated for the first lime in the State of São Paulo, Brazil. 2) — When treated with baths containing sulfur, lime and sodium hydroxide, as studied by Heguito and co-workers in Uruguay, the results were satisfactory. 3) — The study of the morphology of males and pubescent females found in copulation shows that Psoroptes natalensis, Hirst 1919 is synonymous to P. equi var. bovis (Cerlach, 1857)

Relato de dois casos consecutivos de derivação biliodigestiva pela técnica de Couinaud-Soupault, no tratamento de icterícia obstrutiva por neoplasia de via biliar / Report of two consecutive cases of biliodigestive shunt by the Couinaud-Soupault technique, in the treatment of obstructive jaundice due to biliary tract neoplasia

A anastomose Biliodigestiva com técnica de Couinaud-Soupault foi realizada como tratamento paliativo de ictéricia obstrutiva em dois casos de neoplasias em via biliar intra-hepática no Hospital Municipal Lourenço Jorge (HMLJ)

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

A aventura crítica da semiótica

The critical adventure of semiotics courses through the main theses about semiotics and communication that have been discussed during the first stage of the research Critical Semiotics: Towards a theory of materialities in communication. In it, the Semiotics and Communication Cultures Research Group (GPESC) discussed the potentialities and limits of a communicational perspective not only based on the founding works of semiotic research (Saussure, Peirce) and developed in its structuralist models (Jakobson, Barthes, Hjelmslev, Lotman), but also revisited by ideas that deconstructed structuralism through the postulates of this very structuralism (Derrida, Kristeva, Deleuze, Guattari). The paper presents this suggestion by means of ten deconstructions related to concepts and theoretical problems which are key to the debate around the materialities of communication: semiotics, communication, materialities, presence, phenomenon, representamen, mediums, sign and significant, structure and system. In so doing, it suggests a move from materialities towards the immanence of a micropolitical and post- human communication.A aventura crítica da semiótica percorre as principais teses sobre a semiótica e a comunicação conforme trabalhadas na primeira etapa da pesquisa Semiótica Crítica, denominada Por uma teoria das materialidades na comunicação. Nela, o Grupo de Pesquisa Semiótica e Culturas da Comunicação procurou discutir as potencialidades e limites de uma perspectiva comunicacional não somente fundamentada nos trabalhos fundadores da semiótica (Saussure, Peirce) e desenvolvida em seus modelos estruturalistas (como em Jakobson, Barthes, Hjelmslev e Lotman), mas também revisitada pelos textos que operaram uma desconstrução do estruturalismo pelo interior dos postulados deste próprio estruturalismo (Derrida, Kristeva, Deleuze, Guattari). O artigo apresenta esta proposta pelos modos como a pesquisa trabalhou com dez desconstruções ligadas a conceitos e problemas teóricos centrais ao debate das materialidades da comunicação: semiótica, comunicação, materialidades, presença, fenômeno, representâmen, meios, signo e significante, estrutura e sistema, sugerindo uma passagem das materialidades à imanência de uma comunicação micropolítica e pós-humana

SDSS-III: Massive Spectroscopic Surveys of the Distant Universe, the Milky Way Galaxy, and Extra-Solar Planetary Systems

Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z<0.7 and at z~2.5. SEGUE-2, which is now completed, measured medium-resolution (R=1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE will obtain high-resolution (R~30,000), high signal-to-noise (S/N>100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged)Comment: Revised to version published in The Astronomical Journa

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost