Resultados de investigación

Supplementary material for "Complex architecture of mud volcano systems: new insights on flow pathways unravel intricate fluid circulation" https://doi.org/10.1130/B37954.1, Shuhui Xu is supported by the China Scholarship Council (CSC), and Walter Menapace is supported by the H2020 MSCA-IF-TURBOMUD project (grant 101018321). This research was funded in part by the Austrian Science Fund (FWF; grant M 3146-417 N) and projects CTM2015-70155-R (INSIGHT) and PID2020-114856RB-100 (ICEFLAME) funded by the Spanish Ministry of Science and Innovation (MCIN/ AEI/10.13039/501100011033). The European project EUMarineRobots (EUMR) is acknowledged for cofunding the M167 expedition (grant 731103), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Peer reviewed

Usage Policies The wwPDB policy states that data files contained in the PDB archive are available under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedicatio, Ministerio de Ciencia e Innovación (MCIN), 8OZU.pdb, Peer reviewed

[EN] The compressed file contains the different tomo3d subroutines and different folders. This version is updated with the possibility to run 2D data + script originally prepared for tomo2D. To compile this version, inside the build/ folder: 1. Modify the install_new.sh file. There are two paths that you have to modify, depending on where you put this code and depending on where you have the "boost" library, necessary for tomo3d to work. 2. Run this file in terminal (bash install_new.sh). 3. Compile in terminal with make. 4. The new tt_inverse3d executable will appear in this build/ folder. Just remember to change in your .bashrc, the path to this executable. 5. To run 2D data, add the -2 flag to the execution line in the script. It is not necessary to change anything else in the script originally prepared for tomo2D, nor to modify the 2D input data (just change the executable to tt_inverse3d and add the "-2" flag). The outputs will also be in 2D format. 6. To see an example of what Tomo3D does, watch file "video_tomo3d.gif", [ES] El archivo comprimido contiene las diferentes subrutinas que conforman el tomo3d y distintas carpetas. Esta versión está actualizada con la posibilidad de poder correr datos 2D directamente con los datos de input y scripts originalmente preparados para tomo2D. Para compilar esta versión, dentro de la carpeta build/: 1. Modificar el archivo install_new.sh. Hay dos paths que tenéis que modificar, según donde pongáis este código y según dónde tengáis la librería "boost", necesaria para el funcionamiento del tomo3d. 2. Ejecutar este archivo en terminal (bash install_new.sh). 3. Compilar en terminal con make. 4. El nuevo ejecutable tt_inverse3d aparecerá en esta carpeta build/. Simplemente acordaros de cambiar en vuestro .bashrc, el path a este ejecutable. 5. Para correr datos 2D, añadir el flag -2 a la linea de ejecución en el script. No es necesario cambiar nada más en el script preparado originalmente para el tomo2D, ni tampoco modificar los datos de input 2D (solamente cambiar el ejecutable a tt_inverse3d y añadir el flag "-2"). Los outputs también saldrán en formato 2D. 6. Para visualizar un ejemplo de lo que hace Tomo3D, ver archivo de video "video_tomo3d.gif", ICM-CSIC has funding support of the–Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI), Peer reviewed

Supplementary Materials I, II, and III - Integrating Spatial Analyses and Microbotanical Remains: A Methodological Approach for Investigating Plant Processing Activities and Domestic Spaces at Neolithic Çatalhöyük. Supplementary I contains the raw data for the microbotanical analyses on Buildings 80 and 131. It consists of laboratory track sheets and the raw counts of phytoliths and starch grains from each building. Supplementary II contains: a) A detailed description of all the starch grain typologies encountered in this research along with references from modern reference collections; b) A visual example of each of the phytolith morphotypes identified and c) The variogram and the Kriging error variances. Supplementary III refers to the R code, building shape files (Mask), and spatial data utilized to produce the Kriging and IDW stipital objects., Peer reviewed

-- ESI_ROBERT.pdf -- Electronic supporting information of the ROBERT manuscript. -- ROBERT_data.zip -- These folders contain the raw inputs and outputs from the workflows presented in the ROBERT manuscript, including: - Examples A-F from the benchmarking study (run in CESGA, 8 processors Intel Xeon Ice Lake 8352Y) - Examples A-B from the SMILES workflows (run in DRAGO, 8-16 processors Intel Xeon Gold 6248R) - Example of the discovery of Pd complexes (run in DRAGO, 8 processors Intel Xeon Gold 6248R) In all cases, an SH script is provided with the script submitted to the CESGA or DRAGO HPCs., Peer reviewed

YEAR: calendar year TREE: number of the sampled tree PLOT: number of sample plot (1,3,4,5,6,7). There is no plot nr 2. TYPE: type of the stand composition (MIXED, PURE). CENTER: number of the center of the sample plot, in cases, when the plot was subdivided into subplots. SP: species to which TREE belongs (Jt - Juniperus thurifera; Pp - Pinus pinea; Pt - Pinus pinaster; Qi - Quercus ilex) DBH: diameter of the tree measured at breast height (1.3m) [cm]. For the years before 2021, the DBH were reconstructed, as described in the Article. BA.cm2: Basal Area of the given tree, calculated as (pi * DBH^2)/4 [cm^2]. BAI.t: increment of the basal area of a given tree in a given year [cm^2 / year]. HEIGHT_2021: height of a given tree measured at the end of the year 2021 [m]. CORED: if increment cores were extracted from a tree (T, NA). DENDROM: if a band dendrometer (T) and continous (automated) dendrometer (T*) were installed on a tree. X.SW: coordinate on x-axis on a carthesian plane; the x = 0 lies on the SW edge of the sample plot [m]. Y.SW: coordinate on y-axis on a carthesian plane; the y = 0 lies on the SW edge of the sample plot [m]. R.infl: radius of influence of a given tree, calculated as DBH/100 * 30 [m]. ZAi: Zone Area; area of influence of a given tree, calculated as pi * R.infl^2 [m^2]. HGCI: sum of competition suffered by a given tree from all its identified neighbours; the competititon between the subject tree and every neighbour was calculated using the Hegyi Competition Index. Jt: competition suffered by a given tree from all Jt neighbours. Qi: competition suffered by a given tree from all Qi neighbours. Pp: competition suffered by a given tree from all Pp neighbours. Pt: competition suffered by a given tree from all Pt neighbours. CIinter: competition suffered by a given tree from all heterospecific neighbours. CIintra: competition suffered by a given tree from all conspecific neighbours. Pre.yr.mm: sum of precipitation during given year [mm]. Pre.gs.mm: sum of precipitation during the growing season of a given year (months with Tavg_month >= 8gr.C) [mm]. Pre.yr.mm: sum of precipitation during the hydrological season of a given year (October previous year - September current year) [mm]. CWB.pm.mm: climatic water balance, calculated as Pre.yr.mm - PET(Penman-Monteith) [mm]. CWB.hr.mm: climatic water balance, calculated as Pre.yr.mm - PET(Hargreaves) [mm]. CWB.th.mm: climatic water balance, calculated as Pre.yr.mm - PET(Thornthwaite) [mm]. DMI: De Martonne Index. resist: resistance to drought, calculated over ring width indices (reference period = 3 years). Formula as described in Lloret et al. 2010. recov: recovery from drought, calculated over ring width indices (reference period = 3 years). Formula as described in Lloret et al. 2010. resil: resilience to drought, calculated over ring width indices (reference period = 3 years). Formula as described in Lloret et al. 2010. rel.resil: relative resilience to drought, calculated over ring width indices (reference period = 3 years). Formula as described in Lloret et al. 2010. rec.period: growth recovery time, as in Thurm et al. 2016., European Commission, Skill-For.Action - Skill-For.Action:956355, Peer reviewed

Dataset corresponding to the figures of the article: Pucher, Thomas, et al. "Biodegradable albumen dielectrics for high-mobility MoS2 phototransistors." npj 2D Materials and Applications 7.1 (2023): 73. https://doi.org/10.1038/s41699-023-00436-7, Peer reviewed

Forest microclimatic variation can result in substantial temperature differences at local scales with concomitant impacts on plant defences and herbivory. Such microclimatic effects, however, may differ across abiotically contrasting sites depending on background environmental differences. To test these cross-scale effects shaping species' ecological and evolutionary responses, we experimentally tested the effects of aboveground microhabitat warming on insect leaf herbivory and leaf defences (toughness, phenolic compounds) for saplings of sessile oak (Quercus petraea) across two abiotically contrasting sites spanning 9° latitude. We found higher levels of herbivory at the low-latitude site, but leaf traits showed mixed patterns across sites. Toughness and condensed tannins were higher at the high-latitude site, whereas hydrolysable tannins and hydroxycinnamic acids were higher at the low-latitude site. At the microhabitat scale, experimental warming increased herbivory but did not affect any of the measured leaf traits. Condensed tannins were negatively correlated with herbivory, suggesting that they drive variation in leaf damage at both scales. Moreover, the effects of microhabitat warming on herbivory and leaf traits were consistent across sites, i.e., effects at the microhabitat scale play out similarly despite variation in factors acting at broader scales. These findings together suggest that herbivory responds to both microhabitat (warming) and broad-scale environmental factors, whereas leaf traits appear to respond more to environmental factors operating at broad scales (e.g., macroclimatic factors) than to warming at the microhabitat scale. In turn, leaf secondary chemistry (tannins) appears to drive both broad-scale and microhabitat-scale variation in herbivory. Further studies are needed using reciprocal transplants with more populations across a greater number of sites to tease apart plant plasticity from genetic differences contributing to leaf trait and associated herbivory responses across scales and, in doing so, better understand the potential for dynamics such as local adaptation and range expansion or contraction under shifting climatic regimes., European Research Council: ERC Starting Grant FORMICA 757833 Spanish National Research Council: 2021AEP082 Xunta de Galicia: IN607A 2021/03, Peer reviewed

Growth parameters: Body weight (BW), length (BL), and body mass index (BMI) after overfeeding in zebrafish Total lipid levels after zebrafish overfeeding Brain Monoamine quantification after overfeeding in zebrafish Anxiety-like behavior quantification using Novel Tank Test (NTDT) Short (STM)- and long-term memory (LTM) quantification using aversive learning tests, Ministerio de Ciencia, Innovación y Universidades PID2022-136288OB-C33 Ministerio de Ciencia, Innovación y Universidades (PID2019-103969RB-C33 Swedish Research Council VR-NT11 2017-03779, Peer reviewed