Resultados totales (Incluyendo duplicados): 113
Encontrada(s) 12 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
Dataset. 2022

BRAINGUT_WINEUP DAILY LIFELIKE IMAGES [DATASET]

  • Bartolomé, Begoña
  • Moreno-Arribas, M. Victoria
  • Lloret Iglesias, Lara
  • Aguilar, Fernando
  • Cobo Cano, Miriam
  • García Díaz, Daniel
  • Heredia, Ignacio
  • Yuste, Silvia
  • Pérez-Matute, Patricia
  • Motilva, María-José
The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters. Each file name is unique and contains information of the parameters under which the photograph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Rea_Rio_C_Bor_175_nd_nd_fr10_nd_nd_ar2 corresponds to an almost real image (Rea), taken in La Rioja (Rio), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at none defined time (nd) and undefined lighting (nd), with a real back-ground (fr10) and without reference (nd) nor distance (nd) considerations, and upper angle (ar2)., Peer reviewed

DOI: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
HANDLE: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
PMID: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776
Ver en: http://hdl.handle.net/10261/284776, https://doi.org/10.20350/digitalCSIC/14816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284776

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
Dataset. 2022

BRAINGUT_WINEUP REAL IMAGES [DATASET]

  • Relaño de la Guía, Edgard
  • Lloret Iglesias, Lara
  • Aguilar, Fernando
  • Cobo Cano, Miriam
  • García Díaz, Daniel
  • Heredia, Ignacio
  • Yuste, Silvia
  • Pérez-Matute, Patricia
  • Motilva, María-José
  • Bartolomé, Begoña
  • Moreno-Arribas, M. Victoria
The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Each file name is unique and contains information of the parameters under which the photo-graph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Vol_Mad_C_Bor_175_Cena_nd_nd_nd_nd_nd corresponds to a real image taken by a consumer(#Vol), taken in Madrid (Mad), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at dinner (Cena) with undefined lighting (nd) and a random real background (nd), and without reference (nd) nor distance (nd), nor angle (nd) considerations., Peer reviewed

DOI: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
HANDLE: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
PMID: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780
Ver en: http://hdl.handle.net/10261/284780, https://doi.org/10.20350/digitalCSIC/14817
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284780

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/305242
Dataset. 2022

GLOBALSHARKMOVEMENT / GLOBALCOLLISIONRISK

  • Womersley, Freya C.
  • Humphries, Nicolas E.
  • Queiroz, Nuno
  • Vedor, Marisa
  • Costa, Ivo da
  • Furtado, Miguel
  • Tyminski, John P.
  • Abrantes, Katya
  • Araujo, Gonzalo
  • Bach, Steffen S.
  • Barnett, Adam
  • Berumen, Michael L.
  • Bessudo Lion, Sandra
  • Braun, Camrin D.
  • Clingham, Elizabeth
  • Cochran, Jesse E. M.
  • Parra, Rafael de la
  • Diamant, Stella
  • Dove, Alistair D. M.
  • Dudgeon, Christine L.
  • Erdmann, Mark V.
  • Espinoza, Eduardo
  • Fitzpatrick, Richard
  • González Cano , Jaime
  • Green, Jonathan R.
  • Guzman, Hector M.
  • Hardenstine, Royale
  • Hasan, Abdi
  • Hazin, Fábio H. V.
  • Hearn, Alex R.
  • Hueter, Robert E.
  • Jaidah, Mohammed Y.
  • Labaja, Jessica
  • Ladino, Felipe
  • Macena, Bruno C. L.
  • Morris, John J.
  • Norman, Bradley M.
  • Peñaherrera-Palma, Cesar
  • Pierce, Simon J.
  • Quintero, Lina M.
  • Ramírez-Macías, Dení
  • Reynolds, Samantha D.
  • Richardson, Anthony J.
  • Robinson, David P.
  • Rohner, Christoph A.
  • Rowat, David R. L.
  • Sheaves, Marcus
  • Shivji, Mahmood S.
  • Sianipar, Abraham B.
  • Skomal, Gregory B.
  • Soler, German
  • Syakurachman, Ismail
  • Thorrold, Simon R.
  • Webb, D. Harry
  • Wetherbee, Bradley M.
  • White, Timothy D.
  • Clavelle, Tyler
  • Kroodsma, David A.
  • Thums, Michele
  • Ferreira, Luciana C.
  • Meekan, Mark G.
  • Arrowsmith, Lucy M.
  • Lester, Emily K.
  • Meyers, Megan M.
  • Peel, Lauren R.
  • Sequeira, Ana M. M.
  • Eguíluz, Víctor M.
  • Duarte, Carlos M.
  • Sims, David W.
Repository containing derived data for the manuscript 'Global collision-risk hotspots of marine traffic and the world's largest fish, the whale shark'., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/305242, https://github.com/GlobalSharkMovement/GlobalCollisionRisk
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/305242
HANDLE: http://hdl.handle.net/10261/305242, https://github.com/GlobalSharkMovement/GlobalCollisionRisk
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/305242
PMID: http://hdl.handle.net/10261/305242, https://github.com/GlobalSharkMovement/GlobalCollisionRisk
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/305242
Ver en: http://hdl.handle.net/10261/305242, https://github.com/GlobalSharkMovement/GlobalCollisionRisk
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/305242

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310828
Dataset. 2019

COMMON PHOTOSINTHETIC ENZYMES FROM 174 METAGENOMES FROM THE MALASPINA EXPEDITION 2010 (ORTEGA ET AL. 2019)

  • Sánchez, Pablo
  • Sebastián, Marta
  • Salazar, Guillem
  • Cornejo-Castillo, Francisco M.
  • Massana, Ramon
  • Duarte, Carlos M.
  • Acinas, Silvia G.
  • Gasol, Josep M.
Predicted genes corresponding to the four most common enzymes present in photosynthetic organisms: NADH:ubiquinone reductase (H+-translocating), N-acetyl-gamma-glutamyl-phosphate reductase, DNA-directed RNA polymerase and non-specific serine/threonine protein kinase of 174 metagenomes sequenced during the Malaspina 2010 global expedition., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/310828
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310828
HANDLE: http://hdl.handle.net/10261/310828
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310828
PMID: http://hdl.handle.net/10261/310828
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310828
Ver en: http://hdl.handle.net/10261/310828
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/310828

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328251
Dataset. 2022

MALASPINA 2010 OPTICAL DATA: ACDOM_APARTICLES_KD_Z10%

  • Overmans, S.
  • Duarte, Carlos M.
  • Sobrino, Cristina
  • Iuculano, Francesca
  • Álvarez-Salgado, Xosé Anton
  • Agustí, Susana
The dataset is comprised of: downwelling diffuse attenuation coefficients, Z10%, aCDOM and ap., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/328251
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328251
HANDLE: http://hdl.handle.net/10261/328251
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328251
PMID: http://hdl.handle.net/10261/328251
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328251
Ver en: http://hdl.handle.net/10261/328251
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328251

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328261
Dataset. 2022

MALASPINA 2010 OPTICAL DATA: ACDOM_APARTICLES_KD_Z10%

  • Overmans, S.
  • Duarte, Carlos M.
  • Sobrino, Cristina
  • Iuculano, Francesca
  • Álvarez-Salgado, Xosé Anton
  • Agustí, Susana
The dataset is comprised of: downwelling diffuse attenuation coefficients, Z10%, aCDOM and ap, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/328261
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328261
HANDLE: http://hdl.handle.net/10261/328261
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328261
PMID: http://hdl.handle.net/10261/328261
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328261
Ver en: http://hdl.handle.net/10261/328261
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/328261

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329403
Dataset. 2022

SUPPORTING INFORMATION FOR PENETRATION OF ULTRAVIOLET-B RADIATION IN OLIGOTROPHIC REGIONS OF THE OCEANS DURING THE MALASPINA 2010 EXPEDITION

  • Overmans, S.
  • Duarte, Carlos M.
  • Sobrino, Cristina
  • Iuculano, Francesca
  • Álvarez-Salgado, Xosé Anton
  • Agustí, Susana
Contents of this file: Figures S1 to S8 and Table S1. -- Figure S1. CDOM absorption coefficients (aCDOM, in m-1) at UV-B wavelengths 305 nm (top panel), 313 nm (middle panel), and 320 nm (bottom panel) measured during the Malaspina 2010 Expedition. Reported values are depth-weighted averages from surface waters (3 m depth) down to the 20% PAR depth. -- Figure S2. Results of the Dunn’s tests, that were performed after Kruskal-Wallis tests to identify if aCDOM (top row), ap (middle row) and ap as % of anw (bottom row) at 305 nm (left column), 313 nm (middle column) and 320 nm (right column) varied significantly (p<0.05) between Longhurst provinces during the Malaspina 2010 Expedition. For a description of the Longhurst province codes, see Fig. 1. -- Figure S3. Particulate absorption coefficients (ap, in m-1) at UV-B wavelengths 305 nm (top panel), 313 nm (middle panel), and 320 nm (bottom panel) measured during the Malaspina Expedition. Reported values are depth-weighted averages from surface waters (3 m depth) down to the 20% PAR depth. -- Figure S4. Downwelling diffuse attenuation coefficients (Kd, in m-1) for the UV-B wavelengths 305 nm (top panel), 313 nm (middle panel), and 320 nm (bottom panel) measured during the Malaspina 2010 Circumnavigation. -- Figure S5. Downwelling diffuse attenuation coefficients (Kd, in m-1) for the UV-A wavelengths 340 nm (top panel), 380 nm (middle panel), and 395 nm (bottom panel) measured during the Malaspina 2010 Expedition. -- Figure S6. Downwelling diffuse attenuation coefficients (Kd, in m-1) for the integrated PAR spectrum (400–700 nm) measured during the Malaspina 2010 Expedition. -- Figure S7. Results of the Dunn’s tests, that were performed after Kruskal-Wallis tests to identify if the downwelling diffuse attenuation coefficient (Kd) at 305, 313, 320, 340 nm varied significantly (p <0.05) between Longhurst provinces during the Malaspina 2010 Expedition. For a description of the Longhurst provinces code, see Fig. 1. -- Figure S8. Seasonal comparison between cloud fractions in the northern and southern tropics (15.5N to 15.5S) in year 2010. Bars represent monthly averages (mean  SD) of 1 x 1 sector squares between 179.5W and 179.5E (n=5760 per bar). Data were obtained from the publicly available Aqua/MODIS satellite data set curated by NASA’s Earth Observatory (https://earthobservatory.nasa.gov/global-maps/MODAL2_M_CLD_FR). WIN, SPR, SUM and AUT refer to winter, spring, summer and autumn, respectively. WIN1 represents December for the northern latitudes and June for the southern latitudes. Asterisks indicate instances where the non-paired t-test identified significantly different means at level p <0.01. -- Table S1. Slope, correlation, 95% confidence intervals and p-values determined as part of the pairwise correlation analysis with the variables sea surface temperature, Chl-a and Kd(PAR), as well as aCDOM, ap and Kd(λ) at wavelengths 305, 313 and 320 nm. For Chl-a, aCDOM and ap, depth-weighted (3 m to 20% PAR depth) average values were used for the analysis., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/329403
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329403
HANDLE: http://hdl.handle.net/10261/329403
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329403
PMID: http://hdl.handle.net/10261/329403
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329403
Ver en: http://hdl.handle.net/10261/329403
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329403

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329547
Dataset. 2022

SUPPORTING INFORMATION FOR PREPARATION, SUPRAMOLECULAR ORGANIZATION, AND ON-SURFACE REACTIVITY OF ENANTIOPURE SUBPHTHALOCYANINES: FROM BULK TO 2D-POLYMERIZATION

  • Labella, Jorge
  • Lavarda, Giulia
  • Hernández-López, Leyre
  • Aguilar, Fernando
  • Díaz-Tendero, Sergio
  • Lobo-Checa, Jorge
  • Torres, Tomás
General information, experimental procedures, new compound characterization, crystallographic data, HPLC chromatograms, NMR spectra, DFT calculations, and STM data., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/329547
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329547
HANDLE: http://hdl.handle.net/10261/329547
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329547
PMID: http://hdl.handle.net/10261/329547
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329547
Ver en: http://hdl.handle.net/10261/329547
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329547

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329827
Dataset. 2022

DATASHEET_1_SEAGRASS THERMAL LIMITS AND VULNERABILITY TO FUTURE WARMING.PDF

  • Marbà, Núria
  • Jordá, Gabriel
  • Bennett, Scott
  • Duarte, Carlos M.
6 pages. -- Supplementary Figure 1. Current mean maximum summer temperature (average 𝑇!"# """""" for the period 1980-2005) across potential seagrass distribution. -- Supplementary Figure 2. Difference between current mean maximum summer temperature ( 𝑇!"# """""" ) and the Tlimit as a function of latitude. Negative and positive latitude values for southern and northern hemispheres, respectively. -- Supplementary Figure 3. Uncertainty associated to the time (in years) for mean maximum summer temperature to reach seagrass upper thermal limit (Tlim) at the warming rates projected under the RCP8.5 scenario around potential seagrass sites. -- Supplementary Figure 4. Time (in years) for mean maximum summer temperature to reach the upper thermal limits (Tlim) of temperate and tropical affinity seagrass flora at the warming rates projected under the RCP8.5 scenario around potential seagrass sites in the Mediterranean Sea and Queensland (Australia) coastal areas. -- Supplementary Figure 5. The time (in years) to reach Tlimit at the warming rates predicted under the RCP4.5 scenario around potential seagrass sites. -- Supplementary Figure 6. Time (in years) for mean maximum summer temperature to reach the upper thermal limits (Tlim) of temperate and tropical affinity seagrass flora at the warming rates projected under the RCP4.5 scenario around potential seagrass sites in the Mediterranean Sea and Queensland (Australia) coastal areas., Seagrasses have experienced major losses globally mostly attributed to human impacts. Recently they are also associated with marine heat waves. The paucity of information on seagrass mortality thermal thresholds prevents the assessment of the risk of seagrass loss under marine heat waves. We conducted a synthesis of reported empirically- or experimentally-determined seagrass upper thermal limits (Tlimit) and tested the hypothesis that they increase with increasing local annual temperature. We found that Tlimit increases 0.42± 0.07°C per°C increase in in situ annual temperature (R2 = 0.52). By combining modelled seagrass Tlimit across global coastal areas with current and projected thermal regimes derived from an ocean reanalysis and global climate models (GCMs), we assessed the proximity of extant seagrass meadows to their Tlimit and the time required for Tlimit to be met under high (RCP8.5) and moderate (RCP4.5) emission scenarios of greenhouse gases. Seagrass meadows worldwide showed a modal difference of 5°C between present Tmax and seagrass Tlimit. This difference was lower than 3°C at the southern Red Sea, the Arabian Gulf, the Gulf of Mexico, revealing these are the areas most in risk of warming-derived seagrass die-off, and up to 24°C at high latitude regions. Seagrasses could meet their Tlimit regularly in summer within 50-60 years or 100 years under, respectively, RCP8.5 or RCP4.5 scenarios for the areas most at risk, to more than 200 years for the Arctic under both scenarios. This study shows that implementation of the goals under the Paris Agreement would safeguard much of global seagrass from heat-derived mass mortality and identifies regions where actions to remove local anthropogenic stresses would be particularly relevant to meet the Target 10 of the Aichi Targets of the Convention of the Biological Diversity., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/329827
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329827
HANDLE: http://hdl.handle.net/10261/329827
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329827
PMID: http://hdl.handle.net/10261/329827
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329827
Ver en: http://hdl.handle.net/10261/329827
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/329827

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/338829
Dataset. 2023

SUPPORTING INFORMATION FOR SELF-ORGANIZED SULFIDE-DRIVEN TRAVELING PULSES SHAPE SEAGRASS MEADOWS

  • Ruiz-Reynés, Daniel
  • Mayol, Elvira
  • Sintes, Tomàs
  • Hendriks, Iris E.
  • Hernández-García, Emilio
  • Duarte, Carlos M.
  • Marbà, Núria
  • Gomila, Damià
13 pages. -- The PDF file includes: Supporting text. -- Figs. S1 to S1. -- Legends for Movies S1 to S4., Self_organized_appendix.pdf, pnas.2216024120.sm01.mp4, pnas.2216024120.sm02.mp4, pnas.2216024120.sm03.mp4, pnas.2216024120.sm04.mp4, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/338829
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/338829
HANDLE: http://hdl.handle.net/10261/338829
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/338829
PMID: http://hdl.handle.net/10261/338829
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/338829
Ver en: http://hdl.handle.net/10261/338829
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/338829

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