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448 results for “Rio Grande do Sul”
Mapa de Localização da Escola Municipal de Ensino Fundamental Santo Antônio, Linha dos Pomeranos, Agudo, Rio Grande do Sul
<p>Mapa de Localização da Escola Municipal de Ensino Fundamental Santo Antônio, Linha dos Pomeranos, Agudo, Rio Grande do Sul, realizado com o software QGIS, versão 3.12.3, com técnica de sombreamento utilizando o relevo sombreado do TOPODATA do Instituto Nacional de Pesquisas Espaciais (INPE).</p>
Consórcios Públicos Intermunicipais no Rio Grande do Sul (2023-2024)
<p>Mapeamento dos municípios consorciados e municípios-sede dos 46 Consórcios Públicos Intermunicipais identificados no Rio Grande do Sul, no período de 2023-2024.</p> <p>Esse levantamento foi realizado na pesquisa de tese "Cidades pequenas e cooperação interfederativa: Estratégias dos Consórcios Públicos em relação ao planejamento e gestão das políticas públicas no Rio Grande do Sul", 2020-2024. (Doutorado em Planejamento Urbano e Regional) – Programa de Pós-Graduação em Planejamento Urbano e Regional, UFRGS, Porto Alegre. </p>
Figure 2 in Taxonomic study and population variation of scale insects (Hemiptera: Coccidae and Diaspididae) and associated parasitoids (Hymenoptera: Chalcidoidea) in an olive grove at Rio Grande do Sul, Brazil
Figure 2. Population variation of Hemiberlesia lataniae (Hemiptera: Diaspididae) on different varieties of Olea europaea (Arbequina, Arbosana and Koroneiki), at different times of sampling, in Barra do Ribeiro (30°30′54.95″S, 51°30′20.84″W), Rio Grande do Sul, Brazil.
Figure 1 in Taxonomic study and population variation of scale insects (Hemiptera: Coccidae and Diaspididae) and associated parasitoids (Hymenoptera: Chalcidoidea) in an olive grove at Rio Grande do Sul, Brazil
Figure 1. Population variation of Hemiberlesia lataniae (Hemiptera: Diaspididae) in an Olea europaea multivarietal olive grove (Arbequina, Arbosana and Koroneiki), at different sampling times, considering different phases and stage of development in Barra do Ribeiro (30°30′54.95″S, 51°30′20.84″W), Rio Grande do Sul, Brazil.
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at July 11, 2017, Rio Grande do Sul, Brazil
<p>Title:</p> <p>Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at July 11, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170711</p> <p>Time of day (BRT = -3)</p> <p>10h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0</p> <p>Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8</p> <p> </p> <p>Acknowledgments:</p> <p>This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.</p> <p> </p> <p>References associated:</p> <p>Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943</p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil
<p>Title:Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170707</p> <p>Time of day (BRT = -3)</p> <p>14h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High-speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0</p> <p>Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8</p> <p> </p> <p>Acknowledgments:</p> <p>This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.</p> <p> </p> <p>References associated:</p> <p> </p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p> <p>Title:</p> <p> </p> <p>Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170707</p> <p>Time of day (BRT = -3)</p> <p>14h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0</p> <p>Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8</p> <p> </p> <p>Acknowledgments:</p> <p>This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.</p> <p> </p> <p>References associated:</p> <p> </p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p>
FIGURES 1 – 3. Tupiperla sepeensis n in A New species and records of Gripopterygidae (Plecoptera) from Rio Grande do Sul State, Southern Brazil
FIGURES 1 – 3. Tupiperla sepeensis n. sp. Male holotype, terminalia. 1. Dorsal view; 2. Ventral view; 3. Lateral view. Scale bar for all figures, 1.0 mm.
Figura 2 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 2. Espécies de Leguminosae, subfamília Caesalpinioideae. Tribo Cassieae: A. Senna corymbosa; B. Chamaecrista repens; C. C. flexuosa; D. C. nictitans. (Fotos A: Elaine Biondo; B-D: Daiane Vahl).
Figura 3 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 3. Espécies de Leguminosae, subfamília Caesalpinioideae. Tribo Mimoseae: A. Desmanthus tatuhyensis; B. Mimosa dolens; C. M. sanguinolenta; D. M. bimucronata; Tribo Ingeae: E. Calliandra tweedii; F. Enterolobium contortisiliquum. (Fotos A-C, E-F: Daiane Vahl, D: Gustavo Heiden).
Figura 1 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 1. Paisagem natural de butiazal (Butia odorata), na Fazenda São Miguel, Tapes, Rio Grande do Sul, Brasil.
Figura 5 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 5. Espécies de Leguminosae, subfamília Papilionoideae. Tribo Desmodieae: A. Desmodium incanum; B. D. cuneatum; C. D. affine; D. D. adscendens; E. D. barbatum. (Fotos A-C: Daiane Vahl; D: Rosângela Rolim, Flora Digital do RS; E: Sérgio Bordignon, Flora Digital do RS).
Figura 8 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 8. Espécies e tribos de Leguminosae. A. Lupinus lanatus – Tribo Genisteae; B. Macroptilium prostratum – Tribo Phaseoleae; C. Calliandra tweediei – Tribo Ingeae; D-E. Chamaecrista nictitans – Tribo Cassieae; F-G. Mimosa sanguinolenta – Tribo Mimoseae; H-J. Crotalaria tweediana – Tribo Crotalarieae; K. Stylosanthes montevidensis – Tribo Dalbergieae; M. Desmodium incanum – Tribo Desmodieae. Barras: A-D, F-H, K, M = 2 cm; E, G, I, J, L = 0,2 cm. Ilustrações: Ingrid Lessa.
Figura 4 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 4. Espécies de Leguminosae, subfamília Papilionoideae. Tribo Crotalarieae: A. Crotalaria tweediana; Tribo Dalbergieae: B. Ctenodon falcatus var. falcatus; C. Poiretia tetraphylla; D. Stylosanthes scabra; E. S. montevidensis; F. Zornia reticulata; G. Z. pardina. (Fotos A-B, D-G: Daiane Vahl; C: Gustavo Heiden).
Figura 7 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 7. Espécies de Leguminosae, subfamília Papilionoideae. Tribo Phaseoleae: A. Ancistrotropis peduncularis; B. Clitoria nana; C. Eriosema tacuaremboense; D. Macroptilium prostratum; E. M. psammodes; F. Rhynchosia lineata; G. R. corylifolia. (Fotos A, D-G: Daiane Vahl; B-C: Gustavo Heiden).
Figura 6 in Leguminosae na área de conservação in situ do butiazal da Fazenda São Miguel, Tapes, Rio Grande do Sul
Figura 6. Espécies de Leguminosae, subfamília Papilionoideae. Tribo Genisteae: A. Lupinus albescens; B. L. lanatus. (Fotos A-B: Gustavo Heiden).
Data supporting research on journalistic production on science by press offices of universities and university centers in Rio Grande do Sul (2016)
<p>These data are part of a final paper called Scientific Journalism in Community Higher Education Institutions in Rio Grande do Sul. The work was developed at the University of Vale do Taquari - Univates, between 2016 and 2017. The data is in Portuguese. The abstract of the paper is available below. Science occupies an important place in today's society. It is what has allowed us to reach our current stages of intellectual development and also to achieve memorable feats as a species. Science is produced, to a large extent, in the academic environment. This monograph focuses its efforts on trying to understand how 15 universities and university centers in the state of Rio Grande do Sul, partners in the Consortium of Community Universities of Rio Grande do Sul (Comung), carry out the dissemination of their academic production. It is understood that it is important to disseminate scientific information to the population so that individuals can critically evaluate the actions developed in the field of science. The general objective of this study is to investigate the production of scientific news in higher education institutions linked to Comung, as well as to characterize the relationships between the actors and processes related to the journalistic dissemination of science produced in these same institutions. The qualitative and quantitative analysis of the scientific dissemination texts was directed to the news published by the organizations, through an exploratory study that mapped all the production of the press offices between January and August 2016. Subsequently, a qualitative analysis of the discourse of press officers was carried out, after applying a questionnaire. Throughout the investigation, the hypothesis that the institutions disseminate their scientific production was confirmed, but they do so in markedly different ways. The study is available at this link: https://www.univates.br/bdu/items/4cdf0835-1fbe-425a-a216-2a511e9aabf8. </p>
Figs 15–20 in Four decades after Belton: a review of records and evidences on the avifauna of Rio Grande do Sul, Brazil*
Figs 15–20. Photographic documentation for five species added to the main list of birds of Rio Grande do Sul, Brazil: 15, Donacobius atricapilla, São Borja, 18 June 2015 (D. Freitas); 16, Catharus cf. swainsoni, Marques de Souza, 18 January 2016 (M. Sand); 17, Tangara ornata, Três Cachoeiras, 30 January 2010 (A. Cardoso); 18, 19, Thlypopsis sordida, Uruguaiana, 12 June 2016 (E. Mandarino); 20, Sturnus vulgaris, male in breeding season, Lavras do Sul, 29 October 2014 (V. Souza).
Figs 30, 31 in Four decades after Belton: a review of records and evidences on the avifauna of Rio Grande do Sul, Brazil*
Figs 30, 31. Photographic records of two species added as hypothetical to the list of birds of Rio Grande do Sul, Brazil: 30, Progne cf. sinaloae, Coxilha, 24 September 2016 (C. E. Agne); 31, Cyanerpes cyaneus, female, Santo Antônio da Patrulha, 27 July 2015 (R. Kurz).
Figs 7–10 in Four decades after Belton: a review of records and evidences on the avifauna of Rio Grande do Sul, Brazil*
Figs 7–10. Photographic documentation for three species added to the main list of birds of Rio Grande do Sul, Brazil: 7, Todirostrum cinereum, Palmeira das Missões, 7 November 2015 (C. E. Agne); 8, Pseudocolopteryx acutipennis, Mostardas, 28 December 2015 (P. Fenalti); 9, 10, Tyrannus tyrannus, Mostardas, 7 February 2017 (G. R. Peres).
Figs 1–6 in Four decades after Belton: a review of records and evidences on the avifauna of Rio Grande do Sul, Brazil*
Figs 1–6. Photographic documentation for six species added to the main list of birds of Rio Grande do Sul, Brazil: 1, Phoebetria palpebrata, Arroio do Sal, 5 October 2016 (M. Tavares); 2, Ictinia mississippiensis, juvenile, Ijuí, 6 November 2016 (C. E. Agne); 3, Heliornis fulica, presumed male, Marau, 17 October 2015 (C. Longo); 4, Tringa inornata, adult nonbreeding, São José do Norte, 17 April 2014 (C. D. Timm); 5, Thinocorus rumicivorus, male (left) and female (right), Tavares, 5 August 2016 (F. Ronaldo); 6, Leucophaeus atricilla, adult nonbreeding, Cidreira, 7 January 2016 (P. Fenalti).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.