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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246369
Dataset. 2021

DATA SUPPORTING THE RESULTS PUBLISHED IN THE PAPER ENTITLED EXPRESSION OF A TRUNCATED YEAST CCC1 VACUOLAR TRANSPORTER INCREASES THE ACCUMULATION OF ENDOGENOUS IRON

  • Sorribes Dauden, Raquel
  • Martínez Pastor, María Teresa
  • Puig, Sergi
The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL, This research was funded by a predoctoral contract ACIF/2018/077 (to R.S.-D.) and grant PROMETEO/2020/014 from the Regional Government of Valencia (Generalitat Valencia-na), grant BIO2017-87828-C2-1-P and PID2020-116940RB-I00 from the Spanish Ministry of Science, Innovation and Universities, and FEDER funds (ESF, European Social Fund)., List of experimental data: Figure 2: Figure 2.xlsx Figure 2A.SC-Ura 20mM FAS.jpg Figure 2A.SC-Ura 2mM FAS.jpg Figure 2A.SC-Ura 40mM FAS.jpg Figure 2A.SC-Ura 500Fz.jpg Figure 2A.SC.jpg Figure 2C.jpg Figure 2D.jpg Figure 3: Figure 3A.SC-Ura Galactose.jpg Figure 3A.SC-Ura Galactose_1.jpg Figure 3A.SC-Ura Galactose_2.jpg Figure 3A.SC-Ura Glucose_1.jpg Figure 3A.SC-Ura Glucose_2.jpg Figure 3B.SC-Ura-Met 20mM FAS.jpg Figure 3B.SC-Ura-Met 3mM FAS.jpg Figure 3B.SC-Ura-Met 40mM FAS.jpg Figure 3B.SC-Ura-Met 5mM FAS.jpg Figure 3B.SC-Ura-Met.jpg SC-Ura glucosa.jpg Figure 4 & S1 Figure 4 & S1.xlsx Figure 5 & S2 Figure 5 & S2. Xlsx Figure 5.SC-Ura-Met 3mM FAS.Replicate 1. aGFP 10sec.jpg Figure 5.SC-Ura-Met 3mM FAS.Replicate 1. Ponceau.jpg Figure 5.SC-Ura-Met 3mM FAS.Replicate 2. aGFP 10sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 2. aGFP 20sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 2. aGFP 30sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 2. aPgk1.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 2. Ponceau.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 3. aGFP 10sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 3. aGFP 20sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 3. aGFP 30sec.tif Figure 5.SC-Ura-Met 3mM FAS.Replicate 3. Ponceau.jpg Figure 5.SC-Ura-Met.Replicate 1. aGFP 10sec.tif Figure 5.SC-Ura-Met.Replicate 1. aGFP 20sec.tif Figure 5.SC-Ura-Met.Replicate 1. aGFP 30sec.tif Figure 5.SC-Ura-Met.Replicate 1. Ponceau.jpg Figure 5.SC-Ura-Met.Replicate 2. aGFP 10sec.tif Figure 5.SC-Ura-Met.Replicate 2. aGFP 20sec.tif Figure 5.SC-Ura-Met.Replicate 2. aGFP 30sec.tif Figure 5.SC-Ura-Met.Replicate 2. aPgk1.tif Figure 5.SC-Ura-Met.Replicate 2. Ponceau.jpg Figure 5.SC-Ura-Met.Replicate 3. aGFP 10sec.tif Figure 5.SC-Ura-Met.Replicate 3. aGFP 20sec.tif Figure 5.SC-Ura-Met.Replicate 3. aGFP 30sec.tif Figure 5.SC-Ura-Met.Replicate 3. Ponceau.jpg Figure 6: Figure 6.PTEF2CCC1 SC-Ura-Met-3mMFAS-DIC.tif Figure 6.PTEF2CCC1 SC-Ura-Met-3mMFAS-FM4-64.tif Figure 6.PTEF2CCC1 SC-Ura-Met-3mMFAS-GFP.tif Figure 6.PTEF2CCC1 SC-Ura-Met-3mMFAS-Merge.tif Figure 6.PTEF2CCC1 SC-Ura-Met-DIC.tif Figure 6.PTEF2CCC1 SC-Ura-Met-FM4-64.tif Figure 6.PTEF2CCC1 SC-Ura-Met-GFP.tif Figure 6.PTEF2CCC1 SC-Ura-Met-Merge.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-3mMFAS-DIC.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-3mMFAS-FM4-64.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-3mMFAS-GFP.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-3mMFAS-Merge.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-DIC.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-FM4-64.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-GFP.tif Figure 6.PTEF2NtCCC1 SC-Ura-Met-Merge.tif, Peer reviewed

DOI: http://hdl.handle.net/10261/246369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246369
HANDLE: http://hdl.handle.net/10261/246369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246369
PMID: http://hdl.handle.net/10261/246369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246369
Ver en: http://hdl.handle.net/10261/246369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246369

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246544
Dataset. 2021

LAYING DATE IN A MEDITERRANEAN POPULATION OF PIED FLYCATCHERS (FICEDULA HYPOLEUCA)

  • Le Vaillant, Justine
  • Potti, Jaime
  • Camacho, Carlos
  • Canal, David
  • Martínez-Padilla, Jesús
Nombre de la variable y descripción: Year (Año de toma de datos / Year), LayingDate (Fecha de puesta / laying date), Habitat (Habitat (Robledal:1 / Pinar: 2) / Habitat (Oak:1 / Pine: 2)), Mate (Pareja única, con hembra primaria (Mon) o hembra secundaria con ayuda (SecA) o secundaria sin ayuda (SecNoA)/ female mating as primary (Mon), secondary with male help (SecA) or secondary without help (SecNopA)), Age (Edad / Age), MaxPApril (Precipitación máxima de abril / Maximum precipitation in April), MaxPMay (Precipitación máxima de May / Maximum precipitation in May), NAOw (Índice de NAO en invierno / NAO index in winter), PrecipMinLD (Precipitación mínima durante la fecha de puesta / Minimum precipitation during laying), MaxTApril (Temperatura máxima de abril / Maximum temperature in April), TempMaxPreLD (Temperatura máxima durante el período prepuesta / Maximum temperature during prelaying period), PrecipMinPreLD (Precipitación mínima durante el período prepuesta / Minimum precipitation during prelaying period), TempMinLD (Temperatura mínima durante la fecha de puesta / Minimum temperature during laying), MinTMay (Temperatura mínima de Mayo / Maximum temperature in May), MinTApril (Temperatura mínima de Abril / Minimum temperature in April), Female (Identidad de la hembra / Female identity)., The origin of natural selection is found in the environmental heterogeneity that determines a variation in relative fitness among phenotypes. However, individuals in wild populations are exposed not a single but to a plethora of biotic and abiotic environmental factors. Surprisingly, the relative influence of multiple environmental conditions on relative fitness of phenotypes has rarely been tested in wild populations. Identifying the main selection agent(s) is crucial when the target phenotype is tightly linked to reproduction and when temporal variation in selection is expected to affect evolutionary response. By using individual-based information from a short-lived migratory passerine, the pied flycatcher (Ficedula hypoleuca), we studied the relative influence of 28 temperature- and precipitation-based factors at local and global scales on selection on breeding time (egg laying) at the phenotypic level over 29 breeding seasons. Selection penalised late breeders using number of recruits as proxy of fitness. Minimum temperatures in April and May were the environmental drivers that best explained selection on laying date. In particular, there was negative directional selection on laying date mediated by minimum temperature in April being strongest in colder years. In addition, non-linear selection on laying date was shaped by minimum temperatures in May, with selection on laying date changing from null to negative as the breeding season advances. The intensity of selection on late breeders increased when minimum temperatures in May were highest. Our results illustrate the complex influence of environmental factors on selection on laying date in wild bird populations. Despite minimum temperature in April being the only variable that changed overtime, its increase did not induce a shift in laying date in the population. In this songbird population stabilizing selection has led to a three-decade stasis in breeding time. We suggest that the influence of local climatic variables on selection in addition to global climatic trends, may constrain phenotypic change., Financiación: PID2019-104835GB-I00; CGL2015-70639-P/BOS; CGL2014-55969-P; CGL2015-70639-P; ARAID., Peer reviewed

DOI: http://hdl.handle.net/10261/246544
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246544
HANDLE: http://hdl.handle.net/10261/246544
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246544
PMID: http://hdl.handle.net/10261/246544
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246544
Ver en: http://hdl.handle.net/10261/246544
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246544

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246731
Dataset. 2021

OLEUM PROJECT. DATA OF A HARMONIZED SPME-GC-MS METHOD FOR THE ANALYSIS OF SELECTED VOLATILE COMPOUNDS IN VIRGIN OLIVE OILS [DATASET]

  • Aparicio-Ruiz, R.
  • Ortiz-Romero, Clemente
  • Casadei, Enrico
  • García-González, Diego L.
  • Servili, Maurizio
  • Selvaggini, Roberto
  • Lacoste, Florence
  • Escobessa, Julien
  • Vichi, Stefania
  • Quintanilla-Casas, Beatriz
  • Golay, Pierre Alain
  • Lucci, Paolo
  • Moret, Erica
  • Valli, Enrico
  • Bendini, Alessandra
  • Gallina Toschi, Tullia
The data set consists of: - a numerical quantitative file saved both in .xlsx and .ods formats: “OLEUM_Dataset_SPME-GC-MS_xlsx.xlsx”, “OLEUM_Dataset_SPME-GC-MS_ods.ods”. - a README file: “OLEUM_Dataset SPME-GC-MS_README_rtf.rtf”.-- Content of the file OLEUM_Dataset_SPME-GC-MS_xlsx/ods: SPME-GC-MS: This sheet presents the repeatability and reproducibility values, expressed as relative standard deviation (RSD%), for three quantification methods (QM1, QM2 and QM3). The three quantification methods are described in Casadei et al., 2021 (Food Control, Vol. 123, 2021, 107823, p. 107823. doi: 10.1016/j.foodcont.2020.107823). Additionally, the concentrations (min and max) determined by the 5 labs for each of 15 samples are shown., This data corresponds to an inter-laboratory study (5 labs) applying a harmonized SPME-GC-MS method to analyze volatile compounds on 15 samples. The data shows the min-max concentration and the repeatability and reproducibility results. This work is relevant to know the performance of this method to be applied as a supporting tool for sensory assessment of virgin olive oil. The data are presented for 18 volatile compound that were selected for their contribution to positive attributes (fruitiness) and sensory defect. This work was developed in the context of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale”, funded by the European Commission within the Horizon 2020 Programme (2014–2020, GA no. 635690)., OLEUM (Advanced solutions for assuring the overall authenticity and quality of olive oil), funded by European Union, Horizon 2020 Programme. Grant Agreement num. 635690; http://www.oleumproject.eu/., Peer reviewed

Proyecto: EC/H2020/635690
DOI: http://hdl.handle.net/10261/246731
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246731
HANDLE: http://hdl.handle.net/10261/246731
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246731
PMID: http://hdl.handle.net/10261/246731
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246731
Ver en: http://hdl.handle.net/10261/246731
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/246731

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247612
Dataset. 2021

SUPPLEMENTARY TABLE 1 - NITROGEN AND PHOSPHORUS FLUX RATES THROUGH MARINE SPONGES

  • Maldonado, Manuel
  • Bayer, Kristina
  • López-Acosta, María
Supplementary material.-- 1 file, This Excel file is the Supplementary Table 1 of the book chapter entitled "Nitrogen And Phosphorus Cycling Through Marine Sponges: Physiology, cytology, genomics, and ecological implications". It includes the 33 studies published before early 2021 in which ammonium, nitrite, nitrate, and/or phosphate net fluxes have been measured in marine sponges, which have been used in the overall calculations made in the chapter, This study has been partially supported by grant MICIU-PID2019-108627RB-I00 to Manuel Maldonado, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/247612
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247612
HANDLE: http://hdl.handle.net/10261/247612
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247612
PMID: http://hdl.handle.net/10261/247612
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247612
Ver en: http://hdl.handle.net/10261/247612
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247612

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247639
Dataset. 2021

[DATASET] FOR “ACCURATE FLUID FLOW MODELING OF FRACTURED MEDIA USING A CONTINUUM APPROACH “

  • Vilarrasa, Víctor
  • Vaezi, Iman
  • Parisio, Francesco
  • Yoshioka, Keita
This dataset includes the input files of the numerical models used in this manuscript for simulating fractures as well as the executable file of the numerical code (CODE_BRIGHT). There are two main folders pertinent to equivalency of fracture thickness and sensitivity analysis to rock matrix permeability. Each folder contains the input files of the numerical models in subfolders whose names represent a short description of the corresponding model. “Equivalency” folder contains the benchmark model (with real fracture aperture, i.e., 10 μm) and three models with upscaled apertures (1 cm, 10 cm, and 1 m) using equivalent properties to obtain the same result. “Sensitivity analysis” folder includes models with 1 cm upscaled aperture for rock matrix permeability ranging from 10-18 to 10-24 m2. In each folder, there is a file with the name of the folder ended as “_gen.dat” which contains the input data of the model, including material properties, initial and boundary conditions and the time intervals. There is also a file ended as “_gri.dat” that includes the information on the mesh. The file “root.dat” includes the name of the model. To run the simulation, copy and paste Code_Bright executable file, i.e., “Cb_v9_3.exe”, in a folder that contains the input files and execute it., This dataset includes the input files of the numerical models used in this manuscript for simulating fractures as well as the executable file of the numerical code (CODE_BRIGHT)., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/247639
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247639
HANDLE: http://hdl.handle.net/10261/247639
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247639
PMID: http://hdl.handle.net/10261/247639
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247639
Ver en: http://hdl.handle.net/10261/247639
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247639

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247742
Dataset. 2021

THE EURO-MEDITERRANEAN SUBMARINE LANDSLIDE DATABASE (EMSS21), EURO-MEDITERRANEAN SUBMARINE LANDSLIDE DATABASE (EMSS21): ONLINE DATA

  • Urgeles, Roger
  • Camerlenghi, Angelo
  • Rüther, Denise C.
  • Fantoni, L.
  • Brückner, Nils W.
  • de Pro Díaz, Yolanda
The Euro-Mediterranean Submarine landSlide database (EMSS21) displays information collected from both the literature and geophysical records. Data from the literature is collected from georeferenced map figures, from which the outline of the landslide deposit and the landslide scar have been digitized. Most information such as age, volume, typology, inferred trigger mechanism and relationship to fluid flow features and metadata is extracted from the relevant article. Area of the deposit and landslide runout is determined from the digitized polygons and polylines, volume (if not available) is determined from area and mean thickness. If the latter is not available, the volume is determined from the Area-Volume relationship for landslides where volume has already been determined. When the data originates directly from geophysical records the outline and scars have been determined from geomorphological interpretation of swath bathymetric maps and interpretation of submarine landslides on a variety of seismic records. In such instances, age information originates from a variety of methods presenting a wide range of accuracies, from radiometric dating to well-seismic correlation as well as ages inferred from mean sedimentation rates. In many instances, landslides identified in the literature are dated with an age epoch only., Disclaimer: The EMSS21 is open to later additions and improvements. For these reasons and due to its intrinsic nature, the EMSS21 cannot be guaranteed to be complete, accurate and updated in any part, and will be subjected to successive revisions. Although the Institut de Ciències del Mar of CSIC makes every effort to supply the best available information, no warranty, expressed or implied, is provided as to the accuracy and reliability of all the data supplied in the EMSS21. Users are cautioned to consider carefully the nature of the data and information before using it for decisions that concern personal or public safety. Conclusions drawn from the EMSS21, or actions undertaken on the basis of its contents, are the sole responsibility of the user., The Euro-Mediterranean Submarine landSlide database (EMSS21) is a catalogue of submarine landslides of the Mediterranean Sea and the European continental margins of the Atlantic and Arctic Oceans. The catalogue is compiled from data available in the literature as well as information collected from geophysical data and not published in the scientific literature. The data set includes polygons and polylines for the landslide deposits and landslide scars as well as information relative to age, volume, area, runout, thickness, typology, scar elevation, geological setting, depth, slope, inferred trigger mechanism, relationship to fluid flow features as well as the relevant metadata. The catalogue includes submarine landslides that span the Miocene to Present day. Nevertheless a clear bias exist towards submarine landslides of younger age, particularly for the smaller events, as these events are difficult to map/identify on lower resolution geophysical data sets typically collected in deep-water and large sub-surface depths. The catalogue aims to offer improved understanding of mass-wasting processes, the potentially resulting tsunamis and derived geohazard. The EMSS21 displays information collected from both the literature and geophysical records. Data from the literature is collected from georeferenced map figures, from which the outline of the landslide deposit and the landslide scar have been digitized. Most information such as age, volume, typology, inferred trigger mechanism and relationship to fluid flow features and metadata is extracted from the relevant article. Area of the deposit and landslide runout is determined from the digitized polygons and polylines, volume (if not available) is determined from area and mean thickness. If the latter is not available, the volume is determined from the Area-Volume relationship for landslides where volume has already been determined. When the data originates directly from geophysical records the outline and scars have been determined from geomorphological interpretation of swath bathymetric maps and interpretation of submarine landslides on a variety of seismic records. In such instances, age information originates from a variety of methods presenting a wide range of accuracies, from radiometric dating to well-seismic correlation as well as ages inferred from mean sedimentation rates. In many instances, landslides identified in the literature are dated with an age epoch only., Data compilation has been possible thanks to projects: Submarine landslides and Their impact on European continental margins (SLATE) - H2020-MSCA-ITN-2016-721403. ImagiNg large SeismogenIc and tsunamiGenic structures of the Gulf of Cadiz with ultra-High resolution Technologies (INSIGHT). - CTM2015-70155-R., The Euro-Mediterranean Submarine landSlide database (EMSS21) is a catalogue of submarine landslides of the Mediterranean Sea and the European continental margins of the Atlantic and Arctic Oceans. The catalogue is compiled from data available in the literature as well as information collected from geophysical data and not published in the scientific literature. The data set includes polygons and polylines for the landslide deposits and landslide scars as well as information relative to age, volume, area, runout, thickness, typology, scar elevation, geological setting, depth, slope, inferred trigger mechanism, relationship to fluid flow features as well as the relevant metadata. The catalogue includes submarine landslides that span the Miocene to Present day. Nevertheless a clear bias exist towards submarine landslides of younger age, particularly for the smaller events, as theseevents are difficult to map/identify on lower resolution geophysical data sets typically collected in deep-water and large sub-surface depths. The catalogue aims to offer improved understanding of mass-wasting processes, the potentially resulting tsunamis and derived geohazard., Peer reviewed

DOI: http://hdl.handle.net/10261/247742
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247742
HANDLE: http://hdl.handle.net/10261/247742
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247742
PMID: http://hdl.handle.net/10261/247742
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247742
Ver en: http://hdl.handle.net/10261/247742
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247742

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247857
Dataset. 2021

APPRAISING SCREENING, MAKING RISK IN/VISIBLE. THE MEDICAL DEBATE OVER NON-RARE THROMBOPHILIA (NRT) TESTING BEFORE PRESCRIBING THE PILL [DATASET]

  • Turrini, Mauro
  • Bourgain, Catherine
The dataset includes: - a detailed description of the search procedure, the queries adopted, and selection criteria of selection exclusion (section #1); - the two original bibliographic searches (section #2 & #3); - the final 21 articles selected coming from these searches and 7 additional articles coming from manual searches of literature reviews (section #4)., Non-rare thrombophilias (NRT) are hereditary predispositions to thromboembolism, the most severe side-effect of hormonal contraception. In the mid-1990s, the identification of NRT stirred up a controversy over the possibility of investigating these genetic variants in women wishing to use contraception. Appraising how to handle this test led the medical profession to reconfigure the risk visibility on hormonal contraception. Through a review of scientific literature, this paper reconstructs the debate over whether and how NRT genetic tests should enter the distribution system of pharmacological contraception. The main arguments concern their epidemiological, social, economic, and clinical consequences of these risk factors. We analyze this debate as a process consisting in shaping the risk visibility. To those who opt for selective thrombophilia screening, this test should become a part of the medical decision-making process, and its visibility should be kept under medical control to protect contraception safety. To advocates of universal or “extended” screening, NRT visibility becomes a moral/legal obligation, and the test a valuable, if not mandatory, means to assure contraception safety. Risk visibility reveals assumptions about medical power, women’s responsibility, and drug safety, and points to an appraisal process as an ideal field to explore political and epistemological implications of screening., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/247857
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247857
HANDLE: http://hdl.handle.net/10261/247857
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247857
PMID: http://hdl.handle.net/10261/247857
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247857
Ver en: http://hdl.handle.net/10261/247857
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/247857

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248177
Dataset. 2022

DATA FROM: USING FLOWER STRIPS TO PROMOTE GREEN LACEWINGS TO CONTROL CABBAGE INSECT PESTS [DATASET]

  • Alcalá Herrera, Rafael
  • Cotes, Belén
  • Agustí, Nuria
  • Tasin, Marco
  • Porcel, M.
The dataset reports: 1) Pest and predator presence in cabbage crops (section 2.2), 2) Arthropod collected in flower strips (section 2.3) and 3) Pollen-foraging preference assay and gut content analysis from Chrysopidae collected in the field (section 2.4)., The dataset contains six objects: 1) Visual sampling data (section 2.2), 2) Suction sampling data (section 2.3), 3) Pollen-foraging preference assay number and volume of pollen grains data (section 2.4) and 4) Number and volume of pollen grains data (section 2.4) from Chrysopidae collected in the field. In columns (=variables) and lines (=samples). Results were published in Journal of Pest Science 95: 669-683 (2022)., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The study was financed by SLU Ekoforsk at the Swedish University of Agricultural Sciences (Project number 2016.4.1-742-4)., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/248177
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248177
HANDLE: http://hdl.handle.net/10261/248177
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248177
PMID: http://hdl.handle.net/10261/248177
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248177
Ver en: http://hdl.handle.net/10261/248177
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248177

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248554
Dataset. 2021

DATA FOR THE PAPER “OPTICAL AND VISUAL QUALITY OF REAL INTRAOCULAR LENSES PHYSICALLY PROJECTED ON THE PATIENT’S EYE”

  • Benedi, Clara
  • Viñas, María
  • Lago, Carmen M.
  • Aissati, Sara
  • Castro, Alberto de
  • Dorronsoro, Carlos
  • Marcos, Susana
The provided Data Set contains an Excel file with the results obtained in the study entitled “Optical and visual quality of the real intraocular lenses physically projected on the patient’s eye”, by C. Benedi-Garcia, M. Vinas, C. M. Lago, S. Aissati, A. de Castro, C. Dorronsoro, S. Marcos, to be published in Biomedical Optics Express (2021)., Visual simulators aim at evaluating vision with ophthalmic corrections prior to prescription or implantation of intraocular lenses (IOLs) in the patient’s eye. In the present study, we present the design, implementation, and validation of a new IOL-in-cuvette channel in an Adaptive Optics visual simulator, which provides an alternative channel for pre-operative simulation of vision with IOLs. IOL-in-cuvette is projected to the pupil’s plane of the subject by using a Rassow system. A second lens, the Rassow lens, compensates for an IOL of 20 D while other powers can be corrected with a Badal system in a 5 D range. The new channel was evaluated by through-focus (TF) optical quality on an artificial eye on bench, and by TF visual acuity in patients, with various IOL designs (monofocal, diffractive trifocal, and refractive extended depth of focus)., Spanish Government FIS2017-84753R. Spanish Government Predoctoral Grant FPU16/01944 to SA. ERC AdG-2018-833106 SILKEYE to SM., Peer reviewed

DOI: http://hdl.handle.net/10261/248554
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248554
HANDLE: http://hdl.handle.net/10261/248554
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248554
PMID: http://hdl.handle.net/10261/248554
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248554
Ver en: http://hdl.handle.net/10261/248554
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/248554

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/249281
Dataset. 2018

ROAGA CRUISE

  • Xunta de Galicia
  • CSIC - Unidad de Tecnología Marina (UTM)
ROAGA Cruise (29MY20181009), Environmental Observation Network of Galicia (ROAGA) Xunta de Galicia, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/249281
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/249281
HANDLE: http://hdl.handle.net/10261/249281
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/249281
PMID: http://hdl.handle.net/10261/249281
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/249281
Ver en: http://hdl.handle.net/10261/249281
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/249281

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