86 research outputs found
The ionized methylene transfer from the distonic radical cation +CH2-O-CH2 to heterocyclic compounds. A pentaquadrupole mass spectrometric study
No full textIon-molecule reactions of the mass-selected distonic radical cation +CH2-O-CH2 (1) with several heterocyclic compounds have been investigated by multiple stage mass spectro- metric experiments performed in a pentaquadrupole mass spectrometer. Reactions with pyridine, 2-, 3-, and 4-ethyl, 2-methoxy, and 2-n-propyl pyridine occur mainly by transfer of CH2+ to the nitrogen, which yields distonic N-methylene-pyridinium radical cations. The MS3 spectra of these products display very characteristic collision-induced dissociation chemistry, which is greatly affected by the position of the substituent in the pyridine ring. Ortho isomers undergo a δ-cleavage cyclization process induced by the free-radical character of the N-methylene group that yields bicyclic pyridinium cations. On the other hand, extensive CH2+ transfer followed by rapid hydrogen atom loss, that is, a net CH+ transfer, occurs not to the heteroatoms, but to the aromatic ring of furan, thiophene, pyrrole, and N-methyl pyrrole. The reaction proceeds through five- to six-membered ring expansion, which yields the pyrilium, thiapyrilium, N-protonated, and N-methylated pyridine cations, respectively, as indicated by MS3 scans. Ion 1 fails to transfer CH2+ to tetrahydrofuran, whereas a new α-distonic sulfur ion is formed in reactions with tetrahydrothiophene. Unstable N-methylene distonic ions, likely formed by transfer of CH2+ to the nitrogen of piperidine and pyrrolidine, undergo rapid fragmentation by loss of the α-NH hydrogen to yield closed-shell immonium cations. The most thermodynamically favorable products are formed in these reactions, as estimated by ab initio calculations at the MP2/6-31G(d,p)//6- 31G(d,p) + ZPE level of theory
TopoLink: A software to validate structural models using chemical crosslinking constraints
No full textAlgoritmo para identificação de peptídeos covalentemente ligados e analisados por espectrometria de massas
No full textO estudo de estruturas e interações proteicas é uma importante área de pesquisa para se entender as funções das proteínas. No entanto, essa é também uma das áreas de grandes desafios experimentais, devido à inerente complexidade atômica de proteínas e peptídeos. Os métodos de elucidação estrutural de alta resolução (e.g. difração de raios-X e RMN) são hoje os considerados “padrões-ouro” para esses tipos
de estudos. No entanto, uma grande parte das proteínas e seus respectivos complexos não são passíveis de serem resolvidos por esses métodos, motivando o desenvolvimento de novas técnicas para a caracterização estrutural de proteínas e seus complexos. Neste sentido, a espectrometria de massas acoplada à técnica de crosslinking (XL-MS) é uma grande promessa, devido às suas características intrínsecas, tais como alta sensibilidade e ampla aplicabilidade. Neste trabalho, desenvolveu-se um software com aplicações pioneiras, denominado SIM-XL, capaz de identificar peptídeos covalentemente ligados e analisados por espectrometria de massas, a fim de caracterizar estruturas de proteínas, bem como de complexos proteínas-proteínas e proteína-peptídeo. Esse software faz uso de técnicas de reconhecimento de padrões para resolver um gargalo na modelagem proteica e interação proteína-proteína. Portanto, o algoritmo aqui apresentado, traz benefícios imediatos nas áreas de biologia e biotecnologia e indiretamente, em diversas outras áreas, como por exemplo, no desenvolvimento de novos fármacos.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Conselho Nacional de
Desenvolvimento Científico e Tecnológico (CNPq), Programa de Apoio à Pesquisa Estratégica em Saúde (Papes) da Fiocruz, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Microsoft Research.The study of protein structures and interactions is an important area of development for understanding the function of proteins. However, this is also an area of great experimental challenge, due to the inherent atomic complexity of proteins and peptides. The methods of structural elucidation of high-resolution (e.g. X-ray
diffraction and NMR) are currently considered the “gold standard” for these types of studies. However, many proteins are not amendable to being solved by these methods; thus motivating the development of new techniques for structural characterization of proteins and their complexes. In this regard, mass spectrometry coupled by crosslinking technique (XL-MS) poses as a promise to overcome these limitations as it
provides a high sensitivity and wide applicability. Here we present SIM-XL, a software pioneer in many ways, capable of identifying cross-linked peptides analyzed by mass spectrometry and thus ultimately aiding in structural characterization and in determining protein-protein interactions. Our software uses pattern recognition strategies to address a bottleneck in protein modeling and protein-protein interaction.
As such, various fields related to biology and biotechnology suffer an immediate benefit from this work, and other areas, say, the development of new drugs, are indirectly benefited as well
Algoritmo para identificação de peptídeos covalentemente ligados e analisados por espectrometria de massas
No full textCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Conselho Nacional de
Desenvolvimento Científico e Tecnológico (CNPq), Programa de Apoio à Pesquisa Estratégica em Saúde (Papes) da Fiocruz, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Microsoft Research.Instituto Carlos Chagas, Fiocruz-PR, Curitiba, PR, BrasilO estudo de estruturas e interações proteicas é uma importante área de pesquisa para se entender as funções das proteínas. No entanto, essa é também uma das áreas de grandes desafios experimentais, devido à inerente complexidade atômica de proteínas e peptídeos. Os métodos de elucidação estrutural de alta resolução (e.g. difração de raios-X e RMN) são hoje os considerados “padrões-ouro” para esses tipos
de estudos. No entanto, uma grande parte das proteínas e seus respectivos complexos não são passíveis de serem resolvidos por esses métodos, motivando o desenvolvimento de novas técnicas para a caracterização estrutural de proteínas e seus complexos. Neste sentido, a espectrometria de massas acoplada à técnica de crosslinking (XL-MS) é uma grande promessa, devido às suas características intrínsecas, tais como alta sensibilidade e ampla aplicabilidade. Neste trabalho, desenvolveu-se um software com aplicações pioneiras, denominado SIM-XL, capaz de identificar peptídeos covalentemente ligados e analisados por espectrometria de massas, a fim de caracterizar estruturas de proteínas, bem como de complexos proteínas-proteínas e proteína-peptídeo. Esse software faz uso de técnicas de reconhecimento de padrões para resolver um gargalo na modelagem proteica e interação proteína-proteína. Portanto, o algoritmo aqui apresentado, traz benefícios imediatos nas áreas de biologia e biotecnologia e indiretamente, em diversas outras áreas, como por exemplo, no desenvolvimento de novos fármacos.The study of protein structures and interactions is an important area of development for understanding the function of proteins. However, this is also an area of great experimental challenge, due to the inherent atomic complexity of proteins and peptides. The methods of structural elucidation of high-resolution (e.g. X-ray
diffraction and NMR) are currently considered the “gold standard” for these types of studies. However, many proteins are not amendable to being solved by these methods; thus motivating the development of new techniques for structural characterization of proteins and their complexes. In this regard, mass spectrometry coupled by crosslinking technique (XL-MS) poses as a promise to overcome these limitations as it
provides a high sensitivity and wide applicability. Here we present SIM-XL, a software pioneer in many ways, capable of identifying cross-linked peptides analyzed by mass spectrometry and thus ultimately aiding in structural characterization and in determining protein-protein interactions. Our software uses pattern recognition strategies to address a bottleneck in protein modeling and protein-protein interaction.
As such, various fields related to biology and biotechnology suffer an immediate benefit from this work, and other areas, say, the development of new drugs, are indirectly benefited as well
Unmanned Aerial Vehicle (UAV) data acquired over a secondary subtropical forest area of the UFSM campus Frederico Westphalen, on June 14, 2021, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a secondary subtropical forest area of the UFSM campus Frederico Westphalen, at June 14, 2021, Rio Grande do Sul, Brazil
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a 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 (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Figure 1. Location of the site of data acquisition.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20210614
Time of day (BRT = -3)
14:40 h a.m.
UAV – Drone - Camera
Matrice 100 (X3)
Fly high (meters above ground)
80 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High speed wind
Approximate data acquisition duration
12 minutes
Total of photographs acquired
X3 - 252
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture (₢)
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic and DEM are showed below (Figure 2 and Figrue 3, respectively), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
Figure 2. The capture of an orthomosaic of X3 camera.
Figure 3. The capture of an DEM
References to the main project/publications:
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
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
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
Acknowledgments:
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).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
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.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Breunig, Fábio Marcelo (2021): Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen on December 13, 2017 in Rio Grande do Sul, Brazil. PANGAEA, PDF. https://doi.pangaea.de/10.1594/PANGAEA.930004
Eduardo Rieder, Geovani Sestari, & Fabio Marcelo Breunig. (2021, February 27). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 29, 2019, in the Rio Grande do Sul State, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4565584
Eduardo Rieder, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4564677
Eduardo Rieder, Renato Souza Santos, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 2, 2019, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4560622
Fabio Marcelo Breunig, Eduardo Rieder, & Renato Souza Santos. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4559718
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 5, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4558265
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4558044
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. PDF. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in the Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in the Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo(2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
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, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.91011
Correction to: International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy (Military Medical Research, (2024), 11, 1, (70), 10.1186/s40779-024-00562-3)
No full textAfter publication of the article, it was brought to our attention that the author name Otas Durutovic was duplicated in the author list and the second one should be replaced by the author Chu Ann Chai, and the affiliations of Ji-Wen Cheng and Chu Ann Chai are incorrect, the correct author list with correct affiliations is shown below: Guo-Hua Zeng, Wen Zhong, Giorgio Mazzon, Wei Zhu, Sven Lahme, Sanjay Khadgi, Janak Desai, Madhu Agrawal, David Schulsinger, Mantu Gupta, Emanuele Montanari, Juan Manuel Lopez Martinez, Shabir Almousawi, Vincent Emanuel F. Malonzo, Seshadri Sriprasad, Otas Durutovic, Vimoshan Arumuham, Stefania Ferretti, Wissam Kamal, Ke-Wei Xu, Fan Cheng, Xiao-Feng Gao, Ji-Wen Cheng, Bhaskar Somani, Mordechai Duvdevani, Kah Ann Git, Christian Seitz, Norberto Bernardo, Tarek Ahmed Amin Ibrahim, Albert Aquino, Takahiro Yasui, Cristian Fiori, Thomas Knoll, Athanasios Papatsoris, Nariman Gadzhiev, Ulanbek Zhanbyrbekuly, Oriol Angerri, Hugo Lopez Ramos, Iliya Saltirov, Mohamad Moussa, Guido Giusti, Fabio Vicentini, Edgar Beltran Suarez, Margaret Pearle, Glenn M. Preminger, Qing-Hui Wu, Chu Ann Chai, Khurshid Ghani, Marcus Maroccolo, Marianne Brehmer, Palle J. Osther, Marek Zawadzki, Azimdjon Tursunkulov, Monolov Nurbek Kytaibekovich, Abdusamad Abdukakhorovich Abuvohidov, Cesar Antonio Recalde Lara, Zamari Noori, Stefano Paolo Zanetti, Sunil Shrestha, Jean de la Rosette, John Denstedt, Zhang-Qun Ye, Kemal Sarica & Simon Choong. The original publication has been updated. © The Author(s) 2024
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
No full textTitle: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
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) 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 (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20170707
Time of day (BRT = -3)
14h a.m.
UAV – Drone - Camera
Phantom 4.
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High-speed wind
Approximate data acquisition duration
16 minutes
Total of photographs acquired
143
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture
For more information contact: Fábio Marcelo Breunig, [email protected]
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.
Figure 2. The capture of an orthomosaic and processing workflow
References to the main project/publications:
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
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
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
Acknowledgments:
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).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
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.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
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, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
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. PANGAEA, https://doi.org/10.1594/PANGAEA.910114
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
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) 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 (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20170707
Time of day (BRT = -3)
14h a.m.
UAV – Drone - Camera
Phantom 4.
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High speed wind
Approximate data acquisition duration
16 minutes
Total of photographs acquired
143
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture
For more information contact: Fábio Marcelo Breunig, [email protected]
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.
Figure 2. The capture of an orthomosaic and processing workflow
References to the main project/publications:
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
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
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
Acknowledgments:
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).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
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.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
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, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
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. PANGAEA, https://doi.org/10.1594/PANGAEA.910114A General description PDF file presents more details
Correction: International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy
No full textAfter publication of the article, it was brought to our attention that the author name Otas Durutovic was duplicated in the author list and the second one should be replaced by the author Chu Ann Chai, and the affiliations of Ji-Wen Cheng and Chu Ann Chai are incorrect, the correct author list with correct affiliations is shown below: Guo-Hua Zeng, Wen Zhong, Giorgio Mazzon, Wei Zhu, Sven Lahme, Sanjay Khadgi, Janak Desai, Madhu Agrawal, David Schulsinger, Mantu Gupta, Emanuele Montanari, Juan Manuel Lopez Martinez, Shabir Almousawi, Vincent Emanuel F. Malonzo, Seshadri Sriprasad, Otas Durutovic, Vimoshan Arumuham, Stefania Ferretti, Wissam Kamal, Ke-Wei Xu, Fan Cheng, Xiao-Feng Gao, Ji-Wen Cheng, Bhaskar Somani, Mordechai Duvdevani, Kah Ann Git, Christian Seitz, Norberto Bernardo, Tarek Ahmed Amin Ibrahim, Albert Aquino, Takahiro Yasui, Cristian Fiori, Thomas Knoll, Athanasios Papatsoris, Nariman Gadzhiev, Ulanbek Zhanbyrbekuly, Oriol Angerri, Hugo Lopez Ramos, Iliya Saltirov, Mohamad Moussa, Guido Giusti, Fabio Vicentini, Edgar Beltran Suarez, Margaret Pearle, Glenn M. Preminger, Qing-Hui Wu, Chu Ann Chai, Khurshid Ghani, Marcus Maroccolo, Marianne Brehmer, Palle J. Osther, Marek Zawadzki, Azimdjon Tursunkulov, Monolov Nurbek Kytaibekovich, Abdusamad Abdukakhorovich Abuvohidov, Cesar Antonio Recalde Lara, Zamari Noori, Stefano Paolo Zanetti, Sunil Shrestha, Jean de la Rosette, John Denstedt, Zhang-Qun Ye, Kemal Sarica & Simon Choong. The original publication has been updated.</p
Mismatch and conciliation: the relation between the narrator and the narrated subject in Jubiabá, by Jorge Amado
No full textO presente trabalho propõe uma leitura do romance Jubiabá (1935), de Jorge Amado, com base na ideia de \"descompasso conciliador\". Trata-se de uma dinâmica caracterizada pela relação ora convergente, ora divergente do narrador em relação à matéria narrada, organizada em torno do herói negro Antônio Balduíno. A pesquisa visa analisar como essa dinâmica reverbera na estrutura da narrativa como um todo, e produz impasses criticamente significativos. Dessa maneira, é possível identificar, por meio das angulações narrativas, o tratamento dispensado pelo autor a temas como candomblé, malandragem, trabalho, escravidão, favor e dependênciaThis paper propounds an interpretation of the novel Jubiabá (1935), by Jorge Amado, based on the idea of a \"conciliatory mismatch\". The concept is a dynamic which is characterized by the relation at times convergent, at times divergent of the narrator in regards to the narrated subject, organized around the Afro-Brazilian hero Antônio Balduíno. The research aims to analyze how this dynamic reverberates in the narrative structure as a whole, producing critically significant impasses. Thus, it is possible to identify through the narrative angles the treatment given by the author to themes such as the Candomblé, trickery, work, slavery, favor and dependenc
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil
Keywords
Images, Drone, UAV, Forest, UFSM, Remote Sensing, GIS.
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a 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 (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Please, see the PDF file.
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20191101
Time of day (BRT = -3)
13:00 h
UAV – Drone - Camera
Phantom 4
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High-speed wind
Approximate data acquisition duration
30 minutes
Total of photographs acquired
Sensor 1/2.3” CMOS
Effective pixels:12.4 M
Lens FOV 94° 20 mm (35 mm format equivalent) f/2.8 focus at ∞
301 photos
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Drone Deploy
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic and DEM is showed below (Figure 2 e Figura 3), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
Please, see the PDF file.
Figure 2. The capture of an orthomosaic in the processing workflow of X3 camera. The lowest quality was applied.
Please, see the PDF file.
Figure 3. The capture of a DEM in the processing workflow of X3 camera. The lowest quality was applied.
References to the main project/publications:
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat, and Sentinel-2 images to precision silviculture and agriculture in a subtropical region. Project. National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
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
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
Acknowledgments:
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).
Other considerations
PS. A pdf file is also attached with this description.
Declaration of Competing Interest
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.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Fabio Marcelo Breunig, Eduardo Rieder, & Renato Souza Santos. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4559718
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558044
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 5, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558265
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
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, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Breunig, Fábio Marcelo, Rafaelo Balbinot, Rafael Vendruscolo, and Renato Beppler Spohr, ‘Situação Ambiental Do Campus Da UFSM de Frederico Westphalen, RS’, in Anais XVI Simpósio Brasileiro de Sensoriamento Remoto - SBSR, ed. by Instituto Nacional De Pesquisas Espaciais - INPE (Foz do Iguaçu - PR, Brazil: INPE, 2013), pp. 7241–48
Bertani, Gabriel, Fabio Marcelo Breunig, and Renato Beppler Sphor, ‘Análise de crescimento da mancha urbana do município de Frederico Westphalen, RS-Brasil através de imagens Landsat 5 TM’, Revista Geografar, 7 (2012), 68–83
Rex, Franciel Eduardo, Pâmela Suélen Käfer, Fábio Marcelo Breunig, and Renato Beppler Spohr Renato Souza Santos, ‘CLASSIFICAÇÃO SUPERVISIONADA DE COPAS DE ÁRVORES EM IMAGEM DE ALTA RESOLUÇÃO ESPACIAL’, BIOFIX Scientific Journal, 3 (2018), 216–23
Eduardo Rieder, Renato Souza Santos, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 2, 2019, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4560622
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.910114
ORCID
Eduardo Rieder: https://orcid.org/0000-0003-3572-4941
Fábio Marcelo Breunig: https://orcid.org/0000-0002-0405-960
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