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1,018 results for “paste”
Dataset for "X-ray near-field ptychographic nanoimaging of cement pastes" paper
<p>Dataset for paper (doi:) with the abstract: "The hydration processes of Portland cements (PC) and blends are complicated as there are many components with great heterogeneity at different length scales. Thus, 3D nanoimaging techniques with high spatial resolution and scanning large fields of view are needed. Here, synchrotron X-ray near-field ptychographic tomography is used to investigate four pastes within 0.2 mm thick capillaries: PC with CaCl2, PC hydration enhanced by C-S-H nucleation seeding, PC partly substituted with metakaolin, and PC partly substituted with metakaolin and limestone. Data analysis emphasis has been placed on the characterisation of amorphous components: (i) C-S-H and C-A-S-H gels; (ii) iron aluminium siliceous hydrogarnets; (iii) metakaolin; and (iv) aluminium carboaluminate, AFm-like. Synchrotron ptychotomography yields electron density and absorption coefficient tomograms and the resulting bivariate plots are instrumental for characterising these amorphous components. The attained spatial resolution, ~220 nm, with very good contrast allowed us to determine nanofeatures including mass densities and spatial distributions of amorphous components. For instance, the C-S-H gel mass density differences between the two type of accelerated pastes are detailed."</p>
Dataset for the paper "VANETs' research over the past decade: overview, credibility, and trends"
<p>These two files contain a form and a dataset, both related to the paper "VANETs' research over the past decade: overview, credibility, and trends", which was submitted for publication in the Computer Communication Review (CCR) by Elmano Ramalho Cavalcanti et al., 2018.</p>
Ptychographic X-ray computed tomography data for three Portland cement pastes
<p>Mortars and concretes are ubiquitous materials with very complex hierarchical microstructures. To fully understand their main properties and to decrease their CO<sub>2</sub> footprints, a sound description of their (spatially-resolved) mineralogy is compulsory. Developing this knowledge is very challenging as about half of the volume of hydrated cement is a nanocrystalline component, calcium-silicate-hydrate (C-S-H gel). Furthermore, other poorly crystalline phases (e.g. iron-siliceous hydrogarnet or silica oxide) may coexist which are even more difficult to characterise. Traditional spatially-resolved techniques like electron microscopies involve complex sample preparation steps that often lead to artefacts (e.g. dehydration and microstructural changes). Here, we have used synchrotron ptychographic tomography for obtaining spatially-resolved information on three unaltered representative samples: neat Portland paste, Portland-calcite and Portland-fly ash blend pastes with spatial resolution below 100 nm in samples of up to 5×10<sup>4</sup> mm<sup>3</sup> of volume. For the neat Portland paste, the ptychotomographic study gave densities of 2.11 and 2.52 gcm<sup>-3</sup> and contents of 41.1 and 6.4 vol% for nanocrystalline C-S-H gel and poorly crystalline iron-siliceous hydrogarnet, respectively. Furthermore, the spatially-resolved volumetric mass density information has allowed to characterise inner product and outer product C-S-H gels. The average density of inner product C-S-H is smaller than that of outer product and its variability larger. Full characterisation of the pastes, including segmentation of the different components, is reported and the contents are compared with the results obtained by thermodynamical modelling.</p> <p> </p> <p> </p> <p> </p> <p>Ptychographic X-ray computed tomography provides 3D electron mass density and attenuation coefficient distributions of unaltered cement pastes with an isotropic resolution below 100 nm. This imaging technique allows quantitatively distinguishing between different components with very similar absorption contrast.</p> <p>Samples were measured at the cSAXS beamline: i) a neat Portland Cement (PC); ii) a PC-CC blend: 80 wt% of PC and 20 wt% of CaCO<sub>3</sub>, and iii) a PC-FA blend: 70 wt% of PC and 30 wt% of fly ash. The main aim of this study is to have a better insight of the microstructure of the amorphous/nanocrystalline gels with submicrometer spatial resolution. It is worth noting that it is possible to determine the gel mass density and water content within the attained 3D resolution (about 100 nm).</p> <p>Here, we focused on the spatial distribution of the different components and in the variation of the electron density values which are very related to the mass density values. Special attention is paid to the density values of the amorphous (or nanocrystalline) components. The electron and mass density values of the C-S-H gel for three pastes are thoroughly analyzed. The density values range from 2.05-2.10 g·cm<sup>-3</sup> for high density C-S-H gel for neat PC and PC-CC pastes to 1.80 g<sup>.</sup>cm<sup>-3</sup> for low density C-S-H gel in PC-FA paste. The density value of poorly crystalline iron-siliceous hydrogarnet component, r=2.52 g·cm<sup>-3</sup>, has also been determined.</p> <p>A summary of our ongoing research focused on the analyses of cement pastes by synchrotron PXCT is reported and discussed.</p> <p> </p> <p> </p> <p> </p> <p><strong>PC sample:</strong></p> <p>tomo_beta_S02536_to_S03341_Hann_freqscl_0.35_0xxx</p> <p>tomo_delta_S02536_to_S03341_Hann_freqscl_1.00_0xxx</p> <p> </p> <p><strong>PC-CC sample:</strong></p> <p>tomo_beta_S04692_to_S06001_Hann_freqscl_0.35_0xxx</p> <p>tomo_delta_S04692_to_S06001_Hann_freqscl_1.00_0xxx</p> <p> </p> <p><strong>PC-FA sample:</strong></p> <p>tomo_beta_S03351_to_S04661_Hann_freqscl_0.35_0xxx</p> <p>tomo_delta_S03351_to_S04661_Hann_freqscl_1.00_0xxx</p> <p> </p> <p> </p>
Fig. 2 in Out of the Past: A new species of Tantilla of the calamarina group (Squamata: Colubridae) from southeastern coastal Guerrero, Mexico, with comments on relationships among members of the group
Fig. 2. Dorsal view of the holotype of Tantilla carolina sp. nov. (BMNH 1906.6.1.241).
Building pseudo latewood tree ring records for De Soto National Forest using MPI-ESM synthetic storms for the past millennium
<p>This release contains the past millennium synthetic storm dataset (MPI-ESM) passing De Soto National Forest (31.08<span>°</span>,-89.08<span>°</span>) and scripts needed to develop pseudo tree ring and sediment records used in Wallace et al. (2024).</p>
Fig. 1 in The dawn of phylogenetic research on Neotropical fishes: a commentary and introduction to Baskin (1973), with an overview of past progress on trichomycterid phylogenetics
Fig. 1. Title page and examiners' page of Baskin (1973).
The past and future changes of river sediment in the U.S. Mid-Atlantic
<p><a href="../api/records/12597593/draft/files/E3SM-tanzeli-lnd-elm-erosion-v3.zip/content" target="_blank" rel="noopener noreferrer">E3SM-tanzeli-lnd-elm-erosion-v3.zip</a>: Model code</p> <p><a href="../api/records/12597593/draft/files/domain_lnd_Mid-Atlantic_MPAS_c220107.nc/content" target="_blank" rel="noopener noreferrer">domain_lnd_Mid-Atlantic_MPAS_c220107.nc</a>: Mid-Atlantic mesh grid</p> <p><a href="../api/records/12597593/draft/files/ancillary.pk/content" target="_blank" rel="noopener noreferrer">ancillary.pk</a>: ancillary variables including "area" (grid cell area: m^2), "areaTotal" (upstream drainage area: m^2), "DSIG" (downstream index), "GINDEX" (grid cell index), "outletG" (river basin index), and "rlen" (river channel length: m).</p> <p><a href="../api/records/12597593/draft/files/Baseline.pk/content" target="_blank" rel="noopener noreferrer">Baseline.pk</a>: Baseline simulation: "Q": discharge (m^3/s), "Qs": sediment discharge (kg/s)</p> <p><a href="../api/records/12597593/draft/files/CLIM_noLU_noDAM.pk/content" target="_blank" rel="noopener noreferrer">CLIM_noLU_noDAM.pk</a>: CLIM_noLU_noDAM simulation</p> <p><a href="../api/records/12597593/draft/files/noCLIM_LU_noDAM.pk/content" target="_blank" rel="noopener noreferrer">noCLIM_LU_noDAM.pk</a>: noCLIM_LU_noDAM simulation</p> <p><a href="../api/records/12597593/draft/files/noCLIM_noLU_DAM.pk/content" target="_blank" rel="noopener noreferrer">noCLIM_noLU_DAM.pk</a>: noCLIM_noLU_DAM simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_UKESM1-0-LL.pk/content" target="_blank" rel="noopener noreferrer">SSP585_UKESM1-0-LL.pk</a>: SSP585_UKESM1-0-LL simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_MPI-ESM1-2-HR.pk/content" target="_blank" rel="noopener noreferrer">SSP585_MPI-ESM1-2-HR.pk</a>: SSP585_MPI-ESM1-2-HR simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_GFDL-ESM4.pk/content" target="_blank" rel="noopener noreferrer">SSP585_GFDL-ESM4.pk</a>: SSP585_GFDL-ESM4 simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_IPSL-CM6A-LR.pk/content" target="_blank" rel="noopener noreferrer">SSP585_IPSL-CM6A-LR.pk</a>: SSP585_IPSL-CM6A-LR simulation</p> <p><a href="../api/records/12597593/draft/files/draw_ssc_channel_vari4pub.py/content" target="_blank" rel="noopener noreferrer">draw_ssc_channel_vari4pub.py</a>: Python script to plot longitudinal SSC variations</p> <p><a href="../api/records/12597593/draft/files/cmp_qs_icom_future4pub.py/content" target="_blank" rel="noopener noreferrer">cmp_qs_icom_future4pub.py</a>: Python script to plot future sediment discharge change</p>
Streptococcus pyogenes pharyngitis elicits diverse antibody responses to key vaccine antigens influenced by the imprint of past infections.
<p>Here you will find the raw data (RawData.RData) and code (CHIVAS_SEROLOGY_Code.Rmd, an R Markdown file) for generating the analysis and figures for the following publication:</p> <p><strong><em>Streptococcus pyogenes</em> pharyngitis elicits diverse antibody responses to key vaccine antigens influenced by the imprint of past infections.</strong></p> <p>Joshua Osowicki1,2,3 #, Hannah R Frost1 #, Kristy I Azzopardi1, Alana L Whitcombe4, Reuben McGregor4, Lauren H. Carlton4, Ciara Baker1, Loraine Fabri1,5,6, Manisha Pandey7, Michael F Good7, Jonathan R. Carapetis8,9,10, Mark J Walker11,12,13, Pierre R Smeesters1,2,5,6, Paul V Licciardi2,14, Nicole J Moreland4 *, Danika L Hill15 *, Andrew C Steer1,2,3 *</p> <p>Provided in the RData file are the following items: </p> <p><strong>Dataframes: </strong></p> <p>"outcome" : clinical variables associated with human challenge for each participant</p> <p>"data" : ELISA and functional antibody responses for human challenge participants. Each timepoint and isotype for each antigen as seperate column)</p> <p>"data_long": Data equivalent to "data" file but in long format, i.e. One column for each antigen, timepoint and isotype as factors. </p> <p>"data.melt" : Data equivalent to "data" file but in longer format , i.e. timepoint, isotype and antigen as factors, 'value' as ELISA AU. </p> <p>"luminex" : IgG responses to 6 antigens analysed by luminex bead-based assay in human challenge participants.</p> <p>"luminex.children" : IgG responses to 6 antigen analysed by luminex bead-based assay in children</p> <p><strong>Vectors:</strong></p> <p>"pharyngitis" : participant "id" for the 19 individuals that developed pharyngitis. </p> <p>"Antigen.Order" : relates to "Main" antigen classification used in Figure 2</p> <p>'additional" : relates to "Additional </p> <p><strong>Function: </strong></p> <p>"custom_theme" : used as a theme when using ggplot to graph. </p> <p>Adobe Illustrator or Inkscape were used to generate the final image files for publication, with some graph editing to axes labels, font size, adding p-values etc. </p> <p> </p> <p><em><strong>Additional files: </strong></em></p> <p> 3 .csv files have been included for download</p> <p>"ELISA_data_wide_format.csv", a wide format data table of 25 human challenge individuals and 219 variables. Equivalent to the 'data' dataframe in the RData file</p> <p>"CHIVAS_luminex.csv", a long format data table of 25 human challenge participants at 1 week, 1 month, and 3 months. Equivalent to the 'luminex' dataframe in the RData file. </p> <p>"Luminex.children.csv", a datatable of 6 luminex variables for 39 children (healthy and post pharyngitis). Equivalent to the 'luminex.children' dataframe in the RData file. </p> <p> </p>
Compressive strength measurements on binary and ternary blended cementitious paste specimens produced with seawater-mixing
<p>The following file consists of data from the published article Rathnarajan et al., (2024) Comprehensive evaluation of early-age hydration and compressive strength development in seawater-mixed binary and ternary cementitious systems published in Archives of Civil and Mechanical Engineering. </p> <p>The excel file contains of compressive strength data of cement paste specimens of size 2 cm. </p> <p>1. From column B to Column N: Mix proportion details including the type of binders, total binder content, and clinker substitution level with SCMs are provided</p> <p>2. From Column O to Column AM: Compressive strength data of the paste specimens were listed out for FW-mixed and SW-mixed cementitious systems for the testing ages, 2, 7, 14, 28 and 90 days. </p> <p>3. Also the % change in compressive strength is calculated by calculating the difference in strength between SW-mixed and FW-mixed specimen divided by strength of FW-mixed specimens</p> <p>SYMBOLS AND NOTATIONS</p> <p>PC - CEM I <br>PF - CEM I + Fly ash <br>PS - CEM I + Slag<br>PM - CEM I + Metakaolin<br>PL - CEM I + Limestone<br>FW - Fresh water mixed <br>SW - Seawater mixed<br>SCM - Supplementary cementitious materials like Fly ash, slag, metakaolin and Limestone<br>SD - Standard deviation<br>%change - Percentage change in compressive strength with respect to strength of FW-mixed paste cubes. </p>
Isothermal calorimetry data of seawater-mixed cement pastes produced with binary and ternary blended binder composition with fly ash, slag, metakaolin, and limestone
<p>The following file consists of data and its metadata from the published article Rathnarajan et al., (2024) Comprehensive evaluation of early-age hydration and compressive strength development in seawater-mixed binary and ternary cementitious systems published in Archives of Civil and Mechanical Engineering. </p> <p>Metadata file: metadata_calorimetry.xlsx consists of the details of file name, operator of equipment, test starting to completion time, number of hours, and notation of the mix-IDs according to the paper. </p> <p>In 11 data files in xlsx format, the heat flow and cumulative heat generated up to 7 days for the various binder combinations produced with CEM I, fly ash, metakaolin, slag, and limestone are presented. Along with that normalized heat flow and normalized cumulative heat with respec to time up to 7 days were included. The following are the data file names in .xlsx format included along with this zip file. </p> <p>P1-P8.xlsx<br>P9-P14.xlsx<br>P15-P18.xlsx<br>P19-P24.xlsx<br>P25-28.xlsx<br>P29-30-43-46.xlsx<br>P33_34-P39-41.xlsx<br>P47-P52.xlsx<br>P53-P58.xlsx<br>P59-P64.xlsx<br>P65-P70.xlsx</p> <p>The following files can be accessed with the pacakge Microsoft excel and data can be used for further analysis. </p>
Dwelling conversion and energy retrofit modify building anthropogenic heat emission under past and future climates: a case study of London terraced houses
<p>This archive includes the data used (e.g. Time use survey (UK-TUS) data), model files (idf files for running EnergyPlus) and codes for analysis in the paper (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.enbuild.2024.114668" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.enbuild.2024.114668</a>).</p> <p>Files in this archive should include:</p> <ul> <li>Time use survey data analysis</li> </ul> <p>o Main dataset: TUS_activity.zip</p> <p>o Code: TUS_clustering_code.zip</p> <p>o Output: InternalHeatProfile.zip</p> <ul> <li>Building energy modeling </li> </ul> <p>o Main dataset (run in EnergPlus 9.4): IDFfiles.zip</p> <p>o Output: Eplus_output.zip</p> <ul> <li>PostProcess analysis</li> </ul> <p>o Code: QF_analysis_code.zip</p> <p>o Output: QF_output.zip</p> <p> </p> <p>Note: this version currently only includes the outputs of all processes, the main dataset and code will be updated later.</p>
Data from: Tropical forest soundscapes as testimonies of past land use
<p><span>Habitat loss is considered one of the factors that causes a decrease in biodiversity in the tropics. Many efforts have been made to protect and restore tropical forests, but it is difficult to quantify biodiversity and assess restoration areas. Studies have used soundscape analyses to gain information about the landscape, using acoustic indices as indicators of the health of faunal communities. We aimed to assess the changes in acoustic indices in habitats with different types of human exploitation and to evaluate the variation in acoustic indices during the hours of the day among these different habitats. The recordings were performed using passive acoustic monitoring (PAM), deriving 15 acoustic indices to assess the characteristics of each environment. The results suggest that in rubber plantations (RP) there was less acoustic activity, followed by rubber-forest plantations (RFP) and light selectively logged areas (LSL), while in habitats of young secondary forests (YSF), mature secondary forests (MSF) and intensive selectively logged forests (ISL) there was more acoustic activity, which indicates greater faunal activity.<span> </span>This study demonstrates that across the various indices tested, the plantation areas (RP and RFP) presented lower values, which indicate reduced acoustic activity compared to forested areas, with the exception of the area lightly selective logged (LSL) which showed lower values of the indices that measure the activity of sonoriferous specie. Therefore, assessing landscape use by monitoring the soundscape can be useful to timely evaluate the ecological dynamics of areas with high species richness, such as the Atlantic Forest.<span> </span></span></p>
APECOSM configuration files used in the Earth's Future "Past and Future of Marine Ecosystems" special issue
<p>This dataset contains the configuration files to run the <em>piControl-spinup</em> and <em>piControl</em> experiment in the ToE paper.</p> <p>In the <em>piControl</em> experiment, light is provided by the <em>rsdo </em>variable, which is is converted into PAR by using a constant conversion factor (0.43). However, this variable is not available for the <em>piControl-spinup</em> experiment, in which PAR has been reconstructed from chlorophyll and solar radiation using the <a href="https://github.com/apecosm/par-calculation" target="_blank" rel="noopener">par-calculation</a> tool (version <code>58ab94c</code>)</p> <p>All the other simulations use the same parameters as in the <em>piControl</em> , except for the forcing and restart paths.</p> <p>The APECOSM version used is <code>c0a910b8</code>.</p> <p> </p>
Table 3 in First insights into past biodiversity of giraffes based on mitochondrial sequences from museum specimens
<p><b>Table 3.</b> Minimum and maximum pairwise distances (in %), as well as mean distance (between brackets), calculated using the mtDNA-91T dataset both within and between haplogroups (Fig. 3). <b>Boldface</b> = maximal intrapopulational variation.</p><table><tbody><tr><th>Taxa</th><th><b>I</b>.</th><th><b>II</b>.</th><th><b>III</b>.</th><th><b>IV</b>.</th><th><b>V</b>.</th><th><b>VI</b>.</th><th><b>VII</b>.</th><th><b>VIII</b>.</th><th><b>IX</b>.</th><th><b>X</b>.</th><th><b>XI</b>.</th></tr></tbody><tbody><tr><th><b>I</b>. Nubia</th><td><b>0</b>. <b>17</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>II</b>. Senegal</th><td>1.38 – 1.5 (1.44)</td><td><b>0</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>III</b>. Niger</th><td>1.09 – 1.47 (1.24)</td><td>1.74 – 1.93 (1.82)</td><td><b>0</b>. <b>26</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>IV</b>. Kordofan I</th><td>0.75 – 1.14 (0.96)</td><td>1.67 – 1.78 (1.7)</td><td>1.28 – 1.67 (1.41)</td><td><b>0</b>. <b>52</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>V</b>. Kordofan II</th><td>1.22 – 1.41 (1.32)</td><td>1.99</td><td>1.67 – 1.86 (1.75)</td><td>0.9 – 1.15 (0.98)</td><td><b>0</b></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>VI</b>. Rothschild</th><td>1.15 – 1.73 (1.35)</td><td>1.49 – 2 (1.68)</td><td>1.21 – 1.67 (1.35)</td><td>1.21 – 1.67 (1.48)</td><td>1.48 – 1.67 (1.58)</td><td><b>0</b>. <b>58</b></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th><b>VII</b>. Reticulated I</th><td>1.54 – 1.99 (1.69)</td><td>1.55 – 1.87 (1.75)</td><td>1.48 – 2.19 (1.74)</td><td>1.48 – 2.12 (1.68)</td><td>1.8 – 2.06 (1.89)</td><td>1.35 – 1.99 (1.60)</td><td><b>1</b>. <b>16</b></td><td></td><td></td><td></td><td></td></tr><tr><th><b>VIII</b>. Masai I</th><td>3.75 – 3.87 (3.82)</td><td>4.13 – 4.13 (4.13)</td><td>3.99 – 4.13 (4.05)</td><td>3.68 – 3.93 (3.80)</td><td>4.12 – 4.12 (4.12)</td><td>3.81 – 4.26 (4.01)</td><td>3.81 – 4.07 (4.00)</td><td><b>0</b></td><td></td><td></td><td></td></tr><tr><th><b>IX</b>. Masai II</th><td>3.73 – 3.99 (3.85)</td><td>4.08 – 4.26 (4.17)</td><td>3.92 – 4.25 (4.04)</td><td>3.50 – 3.91 (3.74)</td><td>4.05 – 4.24 (4.11)</td><td>3.85 – 4.37 (4.03)</td><td>3.86 – 4.31 (4.03)</td><td>0.31 – 0.94 (076)</td><td><b>0</b>. <b>98</b></td><td></td><td></td></tr><tr><th><b>X</b>. Southeast Africa</th><td>4.12 – 4.31 (4.21)</td><td>4.26 – 4.45 (4.34)</td><td>4.31 – 4.69 (4.46)</td><td>4.18 – 4.63 (4.32)</td><td>4.44 – 4.63 (4.51)</td><td>4.18 – 4.63 (4.35)</td><td>4.12 – 4.57 (4.37)</td><td>1.35 – 1.54 (1.43)</td><td>1.29 – 1.56 (1.40)</td><td><b>0</b>. <b>32</b></td><td></td></tr><tr><th><b>XI</b>. Southwestern</th><td>3.13 – 3.73 (3.52)</td><td>3.49 – 4.12 (3.95)</td><td>3.53 – 4.11 (3.80)</td><td>3.07 – 3.86 (3.58)</td><td>3.66 – 4.11 (3.91)</td><td>3.54 – 4.31 (3.94)</td><td>3.73 – 4.24 (3.95)</td><td>2.64 – 2.9 (2.78)</td><td>2.48 – 3.09 (2.80)</td><td>3.02 – 3.41 (3.16)</td><td><b>0</b>. <b>65</b></td></tr></tbody></table>
Data from: Genomic signatures of paleodrainages in a freshwater fish along the southeastern coast of Brazil: genetic structure reflects past riverine properties
Past shifts in connectivity in riverine environments (for example, sea-level changes) and the properties of current drainages can act as drivers of genetic structure and demographic processes in riverine population of fishes. However, it is unclear whether the same river properties that structure variation on recent timescales will also leave similar genomic signatures that reflect paleodrainage properties. By characterizing genetic structure in a freshwater fish species (Hollandichthys multifasciatus) from a system of basins along the Atlantic coast of Brazil we test for the effects of paleodrainages caused by sea-level changes during the Pleistocene. Given that the paleodrainage properties differ along the Brazilian coast, we also evaluate whether estimated genetic diversity within paleodrainages can be explained by past riverine properties (i.e., area and number of rivers in a paleodrainage). Our results demonstrate that genetic structure between populations is not just highly concordant with paleodrainages, but that differences in the genetic diversity among paleodrainages correspond to the joint effect of differences in the area encompassed by, and the number of rivers, within a paleodrainage. Our findings extend the influence of current riverine properties on genetic diversity to those associated with past paleodrainage properties. We discuss how these findings may explain the inconsistent support for paleodrainages in structuring divergence from different global regions and the importance of taking into account past conditions for understanding the high species diversity of freshwater fish that we currently observe in the world, and especially in the Neotropics.
Dataset: Stability of hemicarbonate under cement paste-like conditions
<p>Data, and scripts (analysis, plots) to go with the publication:</p> <p><br> Stability of hemicarbonate under cement paste-like conditions<br> Fabien Georget (a,1,∗), Barbara Lothenbach (b) , William Wilson (a,c) , Franco Zunino (a) Karen L. Scrivener (a)</p> <p>a: aboratory of Construction Materials, LMC, EPFL-STI-IMX, Station 12, CH-1015<br> Lausanne, Switzerland<br> b: Empa, Concrete & Asphalt Laboratory, Dübendorf, Switzerland<br> c: Sherbrooke University, Sherbrooke, Quebec, Canada</p> <p>1: current address: Institute of Building Materials Research, RWTH Aachen, Aachen, Germany</p> <p>* corresponding author</p> <p>To be submitted to Cement and Concrete Research</p> <p> </p>
Data from: Genomic data and multi-species demographic modelling uncover past hybridization between currently allopatric freshwater species
<p>Evidence for ancient interspecific gene flow through hybridization has been reported in many animal and plant taxa based on genetic markers. The study of genomic patterns of closely related species with allopatric distributions allows the assessment of the relative importance of vicariant isolating events and past gene flow. Here, we investigated the role of gene flow in the evolutionary history of four closely related freshwater fish species with currently allopatric distributions in western Iberian rivers - Squalius carolitertii, S. pyrenaicus, S. torgalensis and S. aradensis - using a population genomics dataset of 23 562 SNPs from 48 individuals, obtained through genotyping by sequencing (GBS). We uncovered a species tree with two well differentiated clades: (i) S. carolitertii and S. pyrenaicus; and (ii) S. torgalensis and S. aradensis. By using D-statistics and demographic modelling based on the site frequency spectrum, comparing alternative demographic scenarios of hybrid origin, secondary contact and isolation, we found that the S. pyrenaicus North lineage is likely the result of an ancient hybridization event between S. carolitertii (contributing ~84%) and S. pyrenaicus South lineage (contributing ~16%), consistent with a hybrid speciation scenario. Furthermore, in the hybrid lineage we identify outlier loci potentially affected by selection favouring genes from each parental lineage at different genomic regions. Our results suggest that ancient hybridization can affect speciation and that freshwater fish species currently in allopatry are useful to study these processes.</p>
Rapid morphological change in a small mammal species after habitat fragmentation over the past half-century
<p><span><b>Study Aim:</b> To compare the rapid shifts in body size of mainland and island populations of a native rodent and examine the mechanisms underlying these changes.</span></p> <p><span><b>Location:</b> Thousand Island Lake, China, which was created in 1959 when the Xin'anjiang Dam was constructed for generating hydroelectricity.</span></p> <p><b>Taxon:</b> The Chinese white-bellied rat, <i>Niviventer confucianus</i>.</p> <p><span><b>Methods</b>: Field surveys were conducted from 2015 to 2018 to collect data on body size of the rodents from a set of islands and nearby mainland sites. We constructed multiple linear models to examine the relationships between body size (length and mass) of rodents and biological variables (predators, interspecific and intraspecific competitors, and food availability). We also conducted structural equation modeling (SEM) by constructing models via confirmatory path analysis.</span></p> <p><span><b>Results: </b>All island populations of <i>N. confucianus</i> had significantly larger body size (both body mass and body length) than their mainland counterparts. Moreover, populations on small and more isolated islands had larger body size than their relatives on big islands. The relative absence of predators (large-bodied mammals, snakes, and raptors) on islands was most strongly associated with shifts in the body size of rodents. The documented changes occurred after only a half-century of fragmentation.</span></p> <p><span><b>Main conclusions: </b>The observed rapid body enlargement of rodents after habitat fragmentation is consistent with a release from predation pressure. SEM indicated that island area, rather than island isolation, had positive effects on the richness of predators, interspecific competitors and food resources, which then had an indirect impact on body size of the rodents. In this study, we report a remarkably rapid case of mammal morphological shifts in a small mammal in response to habitat fragmentation. Given the omnipresence of dams and other anthropogenic disturbances, our findings suggest that a wave of rapid phenotypic shifts in terrestrial vertebrates is taking place in the Anthropocene.</span></p>
Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.50) in TIFF format
<p>A detailed description of this dataset can be found in <a href="https://doi.org/10.1016/j.dib.2023.108903">https://doi.org/10.1016/j.dib.2023.108903</a><a href="https://doi.org/10.1016/j.dib.2023.108903">.</a></p> <p>This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence.</p> <p>The dataset contains two sets of images:</p> <p>- “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel)</p> <p>- smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see <a href="https://doi.org/10.1016/j.cemconcomp.2022.104798">10.1016/j.cemconcomp.2022.104798</a> for details.</p> <p>Note that the same dataset stored in *raw format is available from <a href="https://doi.org/10.5281/zenodo.7193819">https://doi.org/10.5281/zenodo.7193819</a></p>
Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.35) in TIFF format
<p>A detailed description of this dataset can be found in <a href="https://doi.org/10.1016/j.dib.2023.108903">https://doi.org/10.1016/j.dib.2023.108903</a><a href="https://doi.org/10.1016/j.dib.2023.108903">.</a></p> <p>This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence.</p> <p>The dataset contains two sets of images:</p> <p>- “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel)</p> <p>- smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see <a href="https://doi.org/10.1016/j.cemconcomp.2022.104798">10.1016/j.cemconcomp.2022.104798</a> for details.</p> <p>Note that the same dataset stored in *raw format is available from <a href="https://doi.org/10.5281/zenodo.7193808">https://doi.org/10.5281/zenodo.7193808</a></p>
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.