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Dataset

DRIFT AND MIGRATION

  • Sergio, Fabrizio
  • Barbosa, Jomar M.
  • Tanferna, Alessandro
  • Silva, Rafa
  • Blas, Julio
  • Hiraldo, F.
The data are organized into seven Excel files on how black kites negotiate wind conditions when they: depart for migration (depart for migration.xlsx), travel and compensate for lateral drift (drift.xlsx), travel and negotiate axial winds (forward.xlsx), stop for a staging stop over (stop for stopover.xlsx), retake their migratory journey after a stopover (start from stopover). Two further Excel files examine how wind negotiation improves within the individual (improvements.xlsx) and is subject to mortality selection (survival & slope.xlsx)., This dataset incorporates data on wind negotiation and response to drift by migratory black kites., Part of the study was funded by Natural Research Ltd and research projects CGL2008-01781 (F.S.), CGL2011-28103 (F.S.), CGL2012-32544 (J.B.) and PGC2018-095860-B-I00 (F.S.) of the Spanish Ministry of Science and Innovation/Economy and Competitiveness and FEDER funds, 511/2012 (J.B.) of the Spanish Ministry of Agriculture, Food and the Environment (Autonomous Organism of National Parks), JA-58 (F.S.) of the Consejería de Medio Ambiente de la Junta de Andalucía and by the Excellence Projects RNM 1790 (F.S.), RNM 3822 (F.S.), RNM 7307 (F.S.) and P18-FR-4239 (F.S.) of the Junta de Andalucía. J.M.B was supported by Generalitat Valenciana (CIDEGENT/2020/030)., File List: Depart for migration.xls, Depart for stopover.xls, Drift.xls Forward.xls, Improvements.xls, Stop at stopover.xls, Survival & slope.xls., Peer reviewed


Dataset

GUÍA DE BUENAS PRÁCTICAS DE IDENTIFICACIÓN Y CONTROL DE ALGUNAS ENFERMEDADES COMUNES DE LOS BOSQUES MEDITERRÁNEOS

  • Barberini, Sara
  • Benito, Álvaro
  • Danti, Roberto
  • Rocca, Gianni Della
  • Devasirvatham, Priya
  • Díez, Sergio
  • Díez, Julio
  • Emiliani, Giovanni
  • Franco, Iván
  • Frascella, Angela
  • García Palacios, Zuleica
  • Igual, José Mariano
  • Kallen, Sven
  • López, Sofía
  • Mediavilla, Olaya
  • Mello, Antonietta
  • Múgica, Marta
  • Olaizola, Jaime
  • Peix, Álvaro
  • Rodríguez, María
  • Santa Regina, Ignacio
  • Secci, Stefano
  • Vaca Igualador, Laura
  • Venice, Francesco
55 páginas, 54 figuras, En la situación de cambio climático que vivimos desde hace algunos años, los bosques mediterráneos se encuentran amenazados por una gran variedad de factores estresantes de origen biótico y abiótico. Los periodos de sequías prolongadas, las altas temperaturas y los incendios forestales son cada vez más frecuentes en nuestros bosques. Estos factores abióticos de riesgo se han acentuado debido al abandono rural, ya que la despoblación conlleva una disminución de la práctica de la silvicultura tradicional que históricamente ayudaba a mitigar el riesgo de incendios y otras amenazas para el bosque. Nuestros bosques también se ven perjudicados por agentes de origen biótico: las plagas y los patógenos que son capaces de debilitar e incluso destruir las masas forestales, que cuando se ven afectadas por la acción de insectos y/o microorganismos patógenos son más susceptibles a incurrir en diversos factores estresantes. Al combinar estos elementos nocivos, se pone en peligro la salud y la existencia de todo el ecosistema forestal. El proyecto LIFE MycoRestore surge con la finalidad de implementar distintas estrategias para lograr una gestión sostenible de los bosques mediterráneos y sus recursos. Para ello, se están utilizando diversos recursos micológicos innovadores y prácticas de manejo forestal que permitan un mejor aprovechamiento económico, ayudando al mismo tiempo a aumentar la resistencia y adaptación al cambio climático de los bosques mediterráneos en España, Italia y Portugal., LIFE MYCORESTORE. Innovative use of mycological resources for resilient and productive Mediterranean forests threatened by climate change (LIFE18 CCA/ES/1110), Peer reviewed

Proyecto: //

Dataset

MEDICAL LEXICON FOR SPANISH (MEDLEXSP)

  • Campillos-Llanos, Leonardo
- MedLexSp.dsv: a delimiter-separated value file, with the following data fields: Field 1 is the UMLS CUI of the entity; field 2, the lemma; field 3, the variant forms; field 4, the part-of-speech; field 5, the semantic types(s); and field 6, the semantic group. - MedLexSp.xml: an XML-encoded version using the Lexical Markup Framework (LMF), which includes the morphological data (number, gender, verb tense and person, and information about affix/abbreviation data). The Document Type Definition file is also provided (lmf.dtd). - Lexical Record files: in subfolder "LR/": · LR_abr.dsv: list of equivalences between acronyms/abbreviations and full forms. · LR_affix.dsv: provides the equivalence between affixes/roots and their meanings. · LR_n_v.dsv: list of deverbal nouns. · LR_adj_n.dsv: list of adjectives derived from nouns. - Spacy lemmatizer (in subfolder "spacy_lemmatizer/"): lemmatizer.py - Stanza lemmatizer (in subfolder "stanza_lemmatizer/"): ancora-medlexsp.pt, File List: 1) MedLexSp.dsv; 2) MedLexSp.xml and lmf.dtd (Document Type Definition); 3) Lexical Record files: in subfolder "LR/": 3.1) LR_abr.dsv; 3.2) LR_affix.dsv; 3.3) LR_n_v.dsv; 3.4) LR_adj_n.dsv; 4) Spacy lemmatizer (in subfolder "spacy_lemmatizer/"): lemmatizer.py 5) Stanza lemmatizer (in subfolder "stanza_lemmatizer/"): ancora-medlexsp.pt See more information about the format below. Companion code and files can be found in the github repository: https://github.com/lcampillos/MedLexSp, MedLexSp is an unified medical lexicon for Medical Natural Language Processing in Spanish. It includes terms and inflected word forms with part-of-speech information and Unified Medical Language System (UMLS) semantic types, groups and Concept Unique Identifiers (CUIs). To create it, we used Natural Language Processing techniques and domain corpora (e.g. MedlinePlus). We also collected terms from the Dictionary of Medical Terms from the Spanish Royal Academy of Medicine, the Medical Subject Headings (MeSH), the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED-CT), the Medical Dictionary for Regulatory Activities Terminology (MedDRA), the International Classification of Diseases vs 10, the Anatomical Therapeutical Classification, the National Cancer Institute (NCI) Dictionary, the Online Mendelian Inheritance in Man (OMIM) and OrphaData. Terms related to COVID-19 were assembled by applying a similarity-based approach with word embeddings trained on a large corpus. This dataset was collected during the NLPMedTerm project and the CLARA-MeD project, with the goal of creating a lexical resource for medical text processing in the Spanish language., MedLexSp is an unified medical lexicon for Medical Natural Language Processing in Spanish. It includes 100 887 lemmas, 302 543 inflected forms (conjugated verbs, and number/gender variants), and 42 958 Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs)., Spain, Latin America and United States of America (data from MedlinePlus Spanish and the Spanish version of the National Cancer Institute Dictionary of Medical Terms)., This dataset was collected in the NLPMedTerm project, funded by the European Union’s Horizon 2020 research programme under the Marie Skodowska-Curie grant agreement nº. 713366 (InterTalentum UAM), and the CLARA-MeD project (PID2020-116001RA-C33), funded by MCIN/AEI/10.13039/501100011033/, in project call: "Proyectos I+D+i Retos Investigación"., Peer reviewed


Dataset

RAIN AND HAIL INTENSITY. APRIL 2013

  • Aguilar, Fernando
Rain and Hail intensity. Cuerda del Pozo. April 2013, Peer reviewed

Proyecto: //

Dataset

RAIN AND HAIL INTENSITY. APRIL 2013

  • Aguilar, Fernando
Rain and Hail intensity. Cuerda del Pozo. April 2013, Peer reviewed

Proyecto: //

Dataset

WIND JANUARY 2013

  • Aguilar, Fernando
Wind Direction and speed in CDP, Peer reviewed

Proyecto: //

Dataset

RAIN AND HAIL INTENSITY. JANUARY 2013

  • Aguilar, Fernando
Rain and Hail intensity. Cuerda del Pozo. January 2013, Peer reviewed

Proyecto: //

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