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201 results for “portuguese”
Marine magnetic anomaly data from high resolution surveys off the SW Portuguese coast
<p>This dataset contains <strong>magnetic anomaly grids</strong> that result from the full processing of marine magnetic data collected off the SW Portuguese coast between 2014 and 2019. A total area of ~4400 km<sup>2</sup> was surveyed with average line spacing of 1 nautic mile. Surveys covered the continental shelf and in some regions reaching up to 2500 m bathymetric levels. Total magnetic field data were acquired with a G882 Cesium vapor marine magnetometer towed, towed at sea surface.</p> <p><strong>Full processing</strong> of magnetic data included: layback correction; noise removal; IGRF subtraction; base station correction; line leveling; minimum curvature gridding. The resulting sea level magnetic anomaly grid was further processed for upward continuation and reduction to the pole, providing additional outputs. </p> <p>The following grids are provided in <strong>georeferenced geotiff format</strong>:</p> <ul> <li>Magnetic anomaly (sealevel)</li> <li>Magnetic anomaly reduced to the pole (sealevel)</li> <li>Magnetic anomaly upward continued to 200 m height </li> <li>Magnetic anomaly upward continued to 200 m height, reduced to the pole</li> <li>Magnetic anomaly upward continued to 3000 m height </li> <li>Magnetic anomaly upward continued to 3000 m height, reduced to the pole</li> </ul> <p><strong>Published in</strong>: Neres, M., P. Terrinha, J. Noiva, P. Brito, M. Rosa, L. Batista, C. Ribeiro (2023). <em>New Late Cretaceous and CAMP magmatic sources off West Iberia, from high-resolution magnetic surveys on the continental shelf.</em> <strong>Tectonics</strong>. doi: 10.1029/2022TC007637</p> <p> </p>
Portuguese Live Fuel Moisture Content product
<p>This product contains a 2500m LFMC 8-day LFMC between 2017 and 2024 over the continental Portugal.<br><br>Metadata:</p> <p>Number of rows: 180<br>Number of columns: 240<br>Cell size: 0.025<br>File Format: netCDF4<br>Coordinate Reference System: GCS_WGS_1984 - EPSG 4326</p> <p>Files:</p> <ul> <li>LFMC_count - number of valid images for the entire period.</li> <li>LFMC_value - LFMC values product </li> </ul> <p>Fundings:</p> <p>Filippe Santos was supported by the Portuguese Foundation for Science and Technology, I.P (Grant 2022.11960.BD).<br>This research was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Refs. PCIF/MPG/0175/2019), ICT project (Refs. UIDB/04683/2020 and UIDP/04683/2020). This research was co-funded by the European Union through the European Regional Development Fund (FEDER) in the framework of the Interreg VI-A España-Portugal (POCTEP) 2021-2027, FIREPOCTEP+ (0139_FIREPOCTEP_MAS_6_E).</p> <p> </p>
Censored Books during the Portuguese Estado Novo: Transcription Dataset of the Censorship Commission's Card Files (1934-74)
<p>This spreadsheet contributes to a new bibliography of censored books under the Portuguese Estado Novo dictatorial regime.</p> <p>It contains the transcription of the data fields of 1,015 card files of censored books, which are indexed by author surname in letters A and B. These files are available at the Arquivo Nacional da Torre do Tombo, in Lisbon, Portugal (PT/TT/SNI-DSC/7, "Fichas de Autores de Obras Proibidas e Autorizadas", <a href="https://digitarq.arquivos.pt/details?id=4326912">https://digitarq.arquivos.pt/details?id=4326912</a>).</p> <p>The card files document data about the books censored by the Estado Novo Censorship Commission (1934-74). Data fields include file number, book report number, decision, date, author, title, origin, destination, observations, notices, and author or book process number.</p> <p>All card files have been photographed from very poor-quality photocopies and manually transcribed by Álvaro Seiça during 2020/21. Letters C-Z are ongoing work and will be added to this dataset.</p> <p>This project received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 793147, ARTDEL.</p> <p>More info at https://artdel.net</p>
OneNet Portuguese demonstration - Open Data sets
<p>File containing the open data sets from the Portuguese demonstration of the OneNet project. The file includes the flexibility assets data used for the demonstration, as well as: 1) the data series for the estimation of the accumulated flexibility potential of MV customers (supermarkets) connected at the two substations considered; 2) the consumption and generation forecasts, with generation disaggregated by source; 3) short-circuit current values calculated at the EHV/HV interface level, including the TSO contribution, the DSO contribution and the joint TSO-DSO contribution. </p><p>Scope/objective of the demonstration: Test an optimized procedure for data exchange between the Portuguese DSO and TSO for flexibility and operational planning purposes.</p>
Photonics4All Bookmark LED (Portuguese)
<p>The purpose of the bookmarks for the project Photonics4All is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).<br> <br> How can Light Emitting Diodes (LEDs) transform local food production?<br> <br> Because LEDs emit pure and specific colours they can be used to make plants grow faster and larger. LEDs can replace sunlight or costly greenhouse lamps to grow crops in cold climates or during off-season periods. Growing food locally reduces the need for long-distance transport and lessens the environmental impact used to produce the food. All thanks to Photonics!</p> <p> </p>
Photonics4All Bookmark Chip (Portuguese)
<p>The purpose of the bookmarks for the project Photonics4All is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).<br> <br> How light makes computers and phones smaller and faster?</p> <p>Did you know that we use light to fabricate the electronic chips in computers and mobile phones? Recent developments in photolithography where light is used to control where conductive metal is placed on the chips - have enabled us to put more transistors than there are people on earth! Transistors are responsible for controlling the path of electricity/information through a chip. These technological developments have led to improving the speed, size and energy consumption of our chips, making them smaller and more efficient.</p> <p> </p>
Photonics4All Bookmark Needle (Portuguese)
<p>The purpose of the bookmarks for the project Photonics4All is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).<br> <br> How can light replace a needle?</p> <p><br> We no longer need to use a needle to monitor the level of oxygen in your blood! We can use light emitting diodes (LEDs) attached to the top of your finger - and a light detector underneath to measure the amount of light passing through your finger. As Hemoglobin - the proteins in red blood cells which carry oxygen - absorbs light we can determine whether you have enough oxygen in your blood. More advanced devices can also monitor your heart-rate and blood pressure. We'll even be using light to measure your blood-sugar level in the future. All thanks to Photonics!</p> <p> </p>
Photonics4All Bookmark Bubble (Portuguese)
<p>The purpose of the bookmarks for the project Photonics4All is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).<br> <br> Why do soap bubbles have colour?<br> <br> Light reflects off both the inner and outer surfaces of a soap bubble. As the bubble dries out it changes thickness and the light waves reflecting off both surfaces have to travel different distances. White light is made up of all different colours – or waves of different lengths and - when light waves meet – or overlap - they create different colours. Because reflected light travels different distances due to the different film thicknesses we see iridescence in soap bubbles. This phenomenon is used in photonics to provide anti-reflection coating on your glasses for example.</p> <p> </p>
Dataset from: A quiet public? Procedural justice in Portuguese wind energy governance
<p>This dataset accompanies a journal article related with public participation in wind and solar energy in Portugal. It contains a database of web scraped public consultation processes related with wind power plants and decentralized solar power plants until 2023. It also contains the R Markdown files that were used to analyze the scraped data. The results of this analyzes, and their discussion, can be found in the associated article.</p>
PPORTAL_ner: An Annotated Corpus of Portuguese Literary Entities
<h2><a href="https://marianaossilva.github.io/pportal_ner/" target="_blank" rel="noopener">PPORTAL_ner</a></h2> <h3>An Annotated Dataset of Portuguese Literary Entities</h3> <p>The corpus is tailored to Brazilian and Portuguese literary texts, containing annotations for five entity categories, including PER, LOC, GPE, ORG, and DATE. Within a diverse collection of 25 literary works, it offers a total of 125,059 tokens and 5,266 annotated entities. This dataset contributes to the development of potentially more accurate and context-aware NER models, as well as to encourage further exploration within Portuguese literature.<br><br></p> <h2>Corpus Statistics</h2> <p>Our corpus is sourced from <a href="https://doi.org/10.5281/zenodo.5178063">PPORTAL</a>, an extensive repository of metadata containing over 80,000 public domain literary works in the Portuguese language, predominantly derived from Brazil and Portugal. <a href="https://doi.org/10.5281/zenodo.5178063">PPORTAL</a> aggregates data from three digital libraries: <a href="https://www.dominiopublico.gov.br/">Domínio Público</a>, <a href="https://projectoadamastor.org/">Projecto Adamastor</a>, and <a href="https://www.literaturabrasileira.ufsc.br/">Biblioteca Digital de Literatura dos Países Lusófonos (BLPL)</a>.</p> <p>To simplify referencing, this new dataset is called PPORTAL_ner. PPORTAL_ner selection process contains a diverse range of 25 individual literary works, spanning different authors and literary styles. All of these texts were published prior to 1953, adhering to the current criteria for public domain status in Brazil, with the majority falling within the timeframe spanning from 1554 to 1938.</p>
StopWords dataset: Integration of a set of stopwords in English and Portuguese - rev. 1
<p><br>StopWords dataset: Integration of a set of stopwords in English and Portuguese - rev. 1</p> <p>================================</p> <p>StopWords dataset - rev. 1 (two MS-Excel files)</p> <p>-------------<br><strong>StopWords Integrated</strong><br>Basic integration of a set of stopwords (English and Portuguese) for use in Text Mining tasks.</p> <p>File name 1: StopWords_Integrated_Favaretto.xlsx</p> <p>Tab 1 of MS-Excel: pt_accent (215 words)<br>Column Label: stopwords_pt</p> <p>Tab 2 of MS-Excel: pt_noaccent (208 words)<br>Column Label: stopwords_pt_na</p> <p>Tab 3 of MS-Excel: en (213 words)<br>Column Label: stopwords_en</p> <p><br>-------------<br><strong>StopWords Extended</strong><br>Extension of a set of stopwords (English and Portuguese) for use in Text Mining tasks.</p> <p>File name 2: StopWords_Extended_Favaretto.xlsx</p> <p>Tab 1 of MS-Excel: pt_extend (614 words)<br>Column Label: stopwords_pt_extend</p> <p>Tab 2 of MS-Excel: en_extended (483 words)<br>Column Label: stopwords_en_extend</p> <p><br>================================</p> <p><br><strong>Warning</strong>: Some words in this set of stopwords may even be misspelled intentionally, as they may occur in practice in texts that are not written correctly.</p> <p><strong>Aviso</strong>: Algumas palavras deste conjunto de stopwords podem até mesmo ter grafia errada de forma intencional, pois podem ocorrer na prática em textos não escritos corretamente.</p> <p><br>================================</p> <p>Source: elaborated by Prof. Dr. José Eduardo Ricciardi Favaretto based on a mix of several different sources</p> <p>https://orcid.org/0000-0002-0143-0809<br>https://lattes.cnpq.br/3790103269421610<br>https://linkedin.com/in/favaretto</p> <p><br>================================</p>
A Brazilian Portuguese Dataset for Offline Handwritten Text Recognition (BRESSAY)
<p>The BRESSAY dataset comprises images of handwritten essays in Brazilian Portuguese, which present a series of challenges to optical recognition models. These images were sourced from multiple online platforms, limiting our ability to standardize the capture process. Due to these varied sources and the lack of a uniform collection method, the dataset provides a realistic reflection of real-world conditions. Each essay is unique, contributed by different writers, and addresses a specific content topic. Furthermore, the constraints placed on the writers often lead to various handwriting scenarios, including hard-to-read words, connected words, noise, overwriting, and struck-through texts.</p> <h3><strong>Technical Details</strong></h3> <p>The BRESSAY dataset represents a comprehensive collection of handwritten essays in Brazilian Portuguese, offering detailed insights into various handwriting scenarios. It covers a total of 1,000 pages, each contributed by a unique writer, resulting in 1,000 distinct handwriting styles. This aspect of the dataset adds a layer of diversity, which is further emphasized by the total of 4,214 paragraphs, 30,090 lines, and 416,826 words. Regarding unique tokens, we have 41,318 unique words, and 107 unique characters.</p> <h3><strong>Data Structure</strong></h3> <p>The dataset is organized as follows:</p> <ul> <li>data/: Main folder containing segmented essay images <ul> <li>lines/: Images of individual lines <ul> <li> PNG files: Line images</li> <li> TXT files: Transcriptions of lines</li> </ul> </li> <li>pages/: Full page essay images <ul> <li> PNG files: Page images</li> <li> TXT files: Transcriptions of pages</li> </ul> </li> <li>paragraphs/: Images of paragraphs <ul> <li> PNG files: Paragraph images</li> <li> TXT files: Transcriptions of paragraphs</li> </ul> </li> <li>words/: Images of individual words <ul> <li> PNG files: Word images</li> <li> TXT files: Transcriptions of words</li> </ul> </li> </ul> </li> <li>sets/: Contains partition files <ul> <li>test.txt: Names of images in the test set</li> <li>validation.txt: Names of images in the validation set</li> <li>training.txt: Names of images in the training set</li> </ul> </li> </ul> <h3><strong>Dataset Usage and Annotations</strong></h3> <p>Each name in test.txt, validation.txt and training.txt represents the name of the page and all its content (words, lines, paragraphs) must be in the respective partition.</p> <p>Annotations used in the dataset:</p> <ul> <li> <code>##@@???@@##</code>: Superscript text that has become unidentifiable and unreadable.</li> <li> <code>$$@@???@@$$</code>: Subscript text that has become unidentifiable and unreadable.</li> <li> <code>@@???@@</code>: Text that cannot be read or identified due to its illegibility.</li> <li> <code>##--xxx--##</code>: Text that has been added as a superscript and subsequently crossed out, rendering it illegible.</li> <li> <code>$$--xxx--$$</code>: Text that has been added as a subscript and subsequently crossed out, rendering it illegible.</li> <li> <code>--xxx--</code>: Text that has been crossed out in a way that makes it unreadable.</li> <li> <code>##--text--##</code>: Text that has been added as a superscript and subsequently crossed out, but remains legible.</li> <li> <code>$$--text--$$</code>: Text that has been added as a subscript and subsequently crossed out, but remains legible.</li> <li> <code>##text##</code>: Text added as a superscript in the line, typically as a correction or additional note.</li> <li> <code>$$text$$</code>: Text added as a subscript in the line, typically as a correction or additional note.</li> <li> <code>--text--</code>: Text that has been crossed out but remains readable.</li> </ul>
Portuguese Handwriting 16th-19th c.
<p>All data were imported from the platform <a href="transkribus.org" target="_blank" rel="noopener">Transkribus</a> on which the AI model for automatic transcription “Portuguese Handwriting 16<sup>th</sup>-19<sup>th</sup> c.” was last trained in July 2023 with the recognition engine Pylaia, and can now be used.</p> <p>The data are divided into ten folders, according to the total number of the trainings, from the initial to the definitive one, plus one set for final validation. The eight previous trainings were realized between June 2022 and May 2023. The history of all trainings can be read on <a href="https://traprinq.hypotheses.org/" target="_blank" rel="noopener">e-Inquisition</a>. Each of these folders corresponds to one collection in the platform; every collection has a number of documents; every document has a number of images, or pages, as indicated below.</p> <p>The ten uploaded folders (zip) are distributed as follows:</p> <p>—nine Training Sets (TS) (ca 92% of the whole data; status of the transcriptions from the TS: Ground Truth);</p> <p>—the final Validation Set (VS) (ca 8% of the whole data; status of the transcriptions from the VS: Ground Truth).</p> <p>All TS folders contain only the new data added to the following training (thus added to the previous data).</p> <p>Only the last VS, which is complete (505 p.), is provided.</p> <p>One document = images / transcribed pages (Ground Truth: transcription made by the members of TraPrInq project (Transcrever os processos da Inquisição portuguesa, 1536-1821 | Transcribing the court records of the Portuguese Inquisition, 1536-1821), which lasted from January 2023 to July 2024.</p> <p>The majority of the documents are titled as follows: IL_number = document extracted from a trial record (<em>processo</em>) by the Inquisition of Lisbon_number of the <em>processo</em>; other titles: IC_ = Inquisition of Coimbra; IE_ = Inquisition of Évora.</p> <p>Total of transcribed pages: 6,417.</p> <p>The quality of the images in the data (jpg) is equal to that of the images used for automatic transcription.</p> <p>All digitized images can be found on the <a href="https://digitarq.arquivos.pt/" target="_blank" rel="noopener">catalog of the Portuguese National Archives</a> (Arquivo Nacional da Torre do Tombo, ANTT).</p> <p>Available data (10 zip files, total size 6.7 GB):</p> <p>Training Set1: 698 pages/images</p> <p>Training Set2: 984 pages/images</p> <p>Training Set3: 869 pages/images</p> <p>Training Set4: 926 pages/images</p> <p>Training Set5: 631 pages/images</p> <p>Training Set6: 665 pages/images</p> <p>Training Set7: 564 pages/images</p> <p>Training Set8: 549 pages/images</p> <p>Training Set9: 531 pages/images</p> <p>Validation Set_Final: 505 pages/images</p> <p>2-one pdf file:</p> <p>Paleographical criteria used by the team for the transcription of the documents; list of characters (in Portuguese).</p>
Wikipedia: wikipedia-pt (Portuguese)
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p>A Wikipédia é um projeto de enciclopédia colaborativa, universal e multilíngue estabelecido na internet sob o princípio wiki. Tem como propósito fornecer um conteúdo livre, objetivo e verificável, que todos possam editar e melhorar. O projeto é definido pelos princípios fundadores. O conteúdo é disponibilizado sob a licença Creative Commons BY-SA e pode ser copiado e reutilizado sob a mesma licença — mesmo para fins comerciais — desde que respeitando os termos e condições de uso. Todos os editores da Wikipédia são voluntários. Eles integram uma comunidade colaborativa, sem um líder, na qual os membros coordenam os seus esforços no âmbito dos projetos temáticos e diversos espaços de discussão. Dentre as várias páginas de ajuda à disposição dos interessados em contribuir, estão as que explicam como criar um artigo ou editar um artigo. Em caso de dúvidas, não hesite em perguntar. Todos podem publicar conteúdo on-line desde que sigam as regras básicas estabelecidas pela comunidade, como por exemplo a verificabilidade da informação ou notoriedade do tema. Debates e comentários sobre os artigos são bem-vindos. As páginas de discussão servem para centralizar reflexões e avaliações sobre como melhorar o conteúdo da Wikipédia. <p></p>https://pt.wikipedia.org
QuintaReiFMD - ROS1 bag dataset acquired with AgRob V16 in a portuguese forest
<p><strong>QuintaRei Forest Multimodal Dataset (QuintaReiFMD)</strong><br> <br> These ROS bags were acquired using AgRob V16 (from <a href="https://www.inesctec.pt/en/laboratories/laboratory-of-robotics-and-iot-for-smart-precision-agriculture-and-forestry">Laboratory of Robotics and IoT for Smart Precision Agriculture and Forestry</a>, from <a href="https://www.inesctec.pt">INESC TEC</a>) in a Portuguese Forest. The data that they hold are from:</p> <ul> <li>Velodyne LiDAR</li> <li>OAK-D camera</li> <li>ZED stereo camera</li> <li>FLIR M232 thermal camera</li> </ul> <p>The data are stored in the following main topics:</p> <pre><code>### Velodyne /agrobv18/velodyne_packets [velodyne_msgs/VelodyneScan] /agrobv18/velodyne_points [sensor_msgs/PointCloud2] ### OAK-D /rgb_left_depth_publisher/color/camera_info [sensor_msgs/CameraInfo] /rgb_left_depth_publisher/color/image/compressed [sensor_msgs/CompressedImage] /rgb_left_depth_publisher/left/camera_info [sensor_msgs/CameraInfo] /rgb_left_depth_publisher/right/camera_info [sensor_msgs/CameraInfo] /rgb_left_depth_publisher/stereo/camera_info [sensor_msgs/CameraInfo] /rgb_left_depth_publisher/stereo/depth [sensor_msgs/Image] ### FLIR /rtsp2/camera_info [sensor_msgs/CameraInfo] /rtsp2/image_raw/compressed [sensor_msgs/CompressedImage] ### ZED /zed_nano/zed_node/depth/camera_info [sensor_msgs/CameraInfo] /zed_nano/zed_node/depth/depth_registered/compressedDepth [sensor_msgs/CompressedImage] /zed_nano/zed_node/left/camera_info [sensor_msgs/CameraInfo] /zed_nano/zed_node/left/image_rect_color/compressed [sensor_msgs/CompressedImage] /zed_nano/zed_node/right/camera_info [sensor_msgs/CameraInfo] /zed_nano/zed_node/right/image_rect_color/compressed [sensor_msgs/CompressedImage]</code></pre> <p> </p>
Brazilian Portuguese COVID-19 Tweets
<p><strong>Brazilian Portuguese symptoms about COVID-19:</strong></p> <ul> <li><strong>Source</strong>: Twitter</li> <li><strong>Start</strong>: 2019-01-01 (January 1st)</li> <li><strong>End</strong>: 2021-09-30 (September 30th)</li> <li><strong>Tweets</strong>: 13,859,059 <ul> <li>Year 2019 [full year]: 4,043,958 obs. of 26 variables (Brazil_Portuguese_COVID19_Tweets2019.csv)</li> <li>Year 2020 [full year]: 6,155,844 obs. of 26 variables (Brazil_Portuguese_COVID19_Tweets2020.csv)</li> <li>Year 2021 [Q1 - Q3]: 3,659,257 obs. of 26 variables (Brazil_Portuguese_COVID19_Tweets2021.csv)</li> </ul> </li> </ul> <p><strong>Search terms (56 symptoms keywords about COVID-19):</strong></p> <p><strong>(1)</strong> adinamia, <strong>(2)</strong> ageusia, <strong>(3)</strong> anosmia, <strong>(4)</strong> boca azulada, <strong>(5)</strong> calafrio, <strong>(6)</strong> cansaço, <strong>(7) </strong>cefaleia, <strong>(8)</strong> cianose, <strong>(9)</strong> coloração azulada no rosto, <strong>(10)</strong> congestão nasal, <strong>(11)</strong> conjuntivite, <strong>(12) </strong>coriza, <strong>(13)</strong> desconforto respiratório, <strong>(14)</strong> diarreia, <strong>(15)</strong> dificuldade para respirar, <strong>(16)</strong> diminuição do apetite, <strong>(17)</strong> dispneia, <strong>(18)</strong> distúrbio gustativo, <strong>(19)</strong> distúrbio olfativo, <strong>(20)</strong> dor abdominal, <strong>(21)</strong> dor de cabeça, <strong>(22)</strong> dor de garganta, <strong>(23)</strong> dor no corpo, <strong>(24)</strong> dor no peito, <strong>(25) </strong>dor persistente no tórax, <strong>(26) </strong>erupção cutânea na pele, <strong>(27)</strong> fadiga, <strong>(28)</strong> falta de ar, <strong>(29)</strong> febre, <strong>(30)</strong> gripe, <strong>(31)</strong> hiporexia, <strong>(32)</strong> inapetência, <strong>(33)</strong> infecção respiratória, <strong>(34)</strong> lábio azulado, <strong>(35)</strong> mialgia, <strong>(36)</strong> nariz entupido, <strong>(37) </strong>náusea, <strong>(38)</strong> obstrução nasal, <strong>(39)</strong> perda de apetite, <strong>(40)</strong> perda do olfato, <strong>(41)</strong> perda do paladar, <strong>(42)</strong> pneumonia, <strong>(43)</strong> pressão no peito, <strong>(44)</strong> pressão no tórax, <strong>(45)</strong> prostração, <strong>(46)</strong> quadro gripal, <strong>(47)</strong> quadro respiratório, <strong>(48)</strong> queda da saturação, <strong>(49)</strong> resfriado, <strong>(50)</strong> rosto azulado, <strong>(51)</strong> saturação baixa, <strong>(52)</strong> saturação de o2 menor que 95%, <strong>(53)</strong> síndrome respiratória aguda grave, <strong>(54) </strong>srag, <strong>(55)</strong> tosse, <strong>(56)</strong> vômito.</p> <p><strong>Variables:</strong></p> <pre><code>Variable str Description ---------------------------------------------------------------------------------- id (integer64) - Tweet identifier conversation_id (integer64) - Tweet conversation identifier date (POSIXct) - Tweet created date (format: YYYY-MM-DD hh:mm:ss) tweet (chr) - Symptoms mention about COVID-19 language (chr) - Tweet language: Portuguese hashtags (chr) - Sign (#) used to identify specific topic user_id (integer64) - User identifier username (chr) - Twitter user name link (chr) - Tweet url urls (chr) - External urls from tweet photos (chr) - Photos posted in message (link) video (int) - Video posted in message (1=True;0=False) thumbnail (chr) - Thumbnail posted in message retweet (logi) - Message reposted by another user nlikes (int) - Number of tweet likes nreplies (in) - Number of tweet replies nretweets (int) - Number of tweet retweets Near (logi) - Near a certain City (Example: London) geo (logi) - Geo coordinates (lat,lon,km/mi.) user_rt_id (logi) - User retweet identifier user_rt (logi) - Retweet user retweet_id (logi) - Retweet identifier reply_to (chr) - Answer to someone retweet_date (logi) - Retweet created date (format: YYYY-MM-DD hh:mm:ss) symptoms (chr) - Symptoms mentioned nsymptoms (int) - Number of symptons mentioned </code></pre> <p><em>str: Compactly Display the Structure of an Arbitrary R Object</em></p>
Simulation and Observation of GICs in the Portuguese power network SPI substation
<p>We developed an instrumental setup to measure Geomagnetic Induced Currents (GICs), consisting of a Hall effect current sensor LEM HOP 1000-SB with a manufacturer's sensitivity 4 mV/A, and a Raspberry Pi 4 Model B platform with a high resolution 24-bit digitizer board (Waveshare AD/DA). The sensor was installed at the Portuguese power network Paraimo (SPI) substation, about 35 km north of Coimbra, in the TRF6 transformer neutral to Earth connection cable.</p> <p>Here, we present measurements of GICs at SPI, during the 17th September 2021 geomagnetic event. Measurements were compared with estimations, which are also provided in this dataset.</p>
Official-Websites-of-the-Portuguese-Municipalities: v1.0.0
<p>This repository contains a list of all 308 Portuguese municipalities, with their respective district and website. The information presented here was based on the update of January 19, 2023, and comes from the website of the General Directorate of Local Authorities (DGAL), which is the central service of the direct administration of the State integrated into the Ministry of Territorial Cohesion of Portugal [1]. Data collection took place on January 26, 2023. We also carried out a manual review of all the website addresses on the list, where we identified and corrected some incorrect email addresses through a Google search of the corresponding municipality.</p>
CPLP:tuítes – The pluricentric corpus of tweets in Portuguese language
<p>CPLP:tuítes is a corpus composed of 125,827 tweets and a total of 2,633,507 tokens. The tweets come from 53 newspaper accounts or news providers in Angola, Brazil, Cape Verde, Guinea-Bissau, Mozambique, Portugal, and São Tomé and Príncipe.</p>
Fig. 1 in Updated checklist of marine fishes (Chordata: Craniata) from Portugal and the proposed extension of the Portuguese continental shelf
Fig. 1. Map of the study area, the Portuguese EEZ, that includes the territorial waters and the area proposed for the extension of the Portuguese continental shelf (source: EMEPC–Mission Structure for the Extension of the Continental Shelf).
ScienceDex guides
Understand access before you commit
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.