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534 results for “saturation”
PIE LTER transects of the Parker River Plum Island Sound Estuary, Massachusetts conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 data.
Multi-year transects, beginning in 1995, of the Parker River Plum Island Sound Estuary conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, salinity, DIC and pCO2 measurements. Differences between dawn and dusk measurements can be used to determine the water metabolism and corresponding estimates of gross primary production, total system respiration and net ecosystem production.
Transects of the Rowley River, Plum Island Sound Estuary, Massachusetts conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 data, PIE LTER.
Multi-year transects, beginning in 2016, of the Rowley River Plum Island Sound Estuary, MA conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 measurements. Differences between dawn and dusk measurements can be used to determine the water column metabolism and corresponding estimates of gross primary production, total system respiration and net ecosystem production.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra recovery after a thermal erosion event: saturating nutrients.
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery under saturating nutrient conditions. Data is presented for day 250 of each year.
Light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration from the 1980-82 Eriophorum vaginatum reciprocal transplant plots from Eagle Creek to Prudhoe Bay, Alaska, 2010
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK, in the south to Prudhoe Bay, AK, in the north (Shaver et al. 1986) .Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. Data were collected in July 2010 for tussocks transplanted in 1980-82 in a reciprocal transplant experiment and then harvested in 2011. Important variables are garden name, source population, light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration.
Hubbard Brook Experimental Forest: Watershed 3 – One year of resin-extracted solutes from variably saturated soils
Hbr363: WS3 One year of resin-extracted solutes from variably saturated soils The Lateral Weathering Study looks at spatial patterns of mineral weathering processes at Hubbard Brook Experimental Forest. This project is characterizing mineral and elemental depletion/enrichment, soil morphology and chemistry, solute transport, and groundwater chemistry along hydropedological gradients. This dataset provides the total elemental mass of inorganic solutes (Ca, Na, Mg, Al, Fe, Mn, P, and S) as well as dissolved organic carbon (DOC) that were extracted off resins installed into shallow groundwater wells (~30-100cm) in Watershed 3. Resin packs were deployed for a total of one year (August 2019-2020) with four consecutive deployment periods, to avoid overloading resin ion capacity. Total mass for each solute was accounted for an entire resin pack, which was 5cm in height and 5cm in diameter, containing approximately 90 g of resin. Resin packs were installed in three different topographic positions along three transects (sites = 9), to characterize solute mass fluxes through different hydropedological units.
Data for "Saturation of destratifying and restratifying instabilities during down front wind events: a case study in the Irminger Sea"
<p>This archive contains processed data used in the study "Saturation of destratifying and restratifying instabilities during down front wind events: a case study in the Irminger Sea".</p> <p>We are grateful for the financial support of the Natural Environment Research Council (grants NE/L002612/1 and NE/T013494/1).</p> <p>This work used the ARCHER2 UK National Supercomputing Service (https://www.archer2.ac.uk).</p> <p>We would also like to thank Andrew Coward for providing computational support.</p> <p>The results contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p> <p>The results contain modified GEBCO data produced by the GEBCO Compilation Group (2023) GEBCO 2023 Grid (doi:10.5285/f98b053b-0cbc-6c23-e053-6c86abc0af7b)</p>
Data of "Towards a More Reliable Forecast of Ice Supersaturation: Concept of a One-Moment Ice Cloud Scheme that Avoids Saturation Adjustment"
<p>These are the data used for generating the figures in the ACP article "Towards a More Reliable Forecast of Ice Supersaturation: Concept of a One-Moment Ice Cloud Scheme that Avoids Saturation Adjustment" by Sperber and Gierens.</p> <p>The data sets labeled "Box" have been generated by the stochastic box model, "adj" refers to the parameterisation using saturation adjustment and data labeled "par" originate from the newly developed parameterisation.</p> <p>The label "const" followed by a number refers to simulations with a constant updraught of the speed specified by the number in cm/s. The label "cos" refers to the simulations in which the updraught velocity follows a cosine function in time.</p> <p>"a10" labels simulations with less initial clear sky humidity fluctuations of plus/minus 10% instead of plus/minus 25%. "al0028" labels simulations with a higher deposition rate of 0.0028 1/s instead of 0.0003 1/s. "step10" labels simulations with a longer time step of 10 minutes instead of 1 minute.</p> <p>"Box_const2_rh1.txt" contains data from a simulation similar to "Box_const2.txt" but with an initial mean relative humidity of 100% instead of 110%. "Box_het.txt" contains data from a simulation including heterogeneous nucleation. "Box_slow_nuc.txt" contains data from a simulation where the deposition rate increases over time from zero after nucleation in every air parcel. "Box_upvar.txt" contains data from a simulation, where the updraught velocity in every air parcel varies randomly between 1 cm/s and 3 cm/s and the deposition rate inside the air parcel depends on the updraught velocity at the time of nucleation.</p> <p> </p> <p>The columns in the "Box" files represent from left to right:</p> <p>1. Time since the simulation start in s</p> <p>2. Cloud fraction</p> <p>3. Mean relative humidity across all air parcels</p> <p>4. Mean specific humidity across all air parcels</p> <p>5. Mean specific ice content across all air parcels</p> <p>6. Mean relative humidity across all cloudy air parcels</p> <p>7. Mean relative humidity across all clear air parcels</p> <p>8. Mean equilibrium supersaturation</p> <p>9. Mean threshold relative humidity for homogeneous nucleation</p> <p>10. Mean deposition rate across all cloudy air parcels</p> <p>11. Mean updraught velocity</p> <p> </p> <p>The columns in the "adj" files represent from left to right:</p> <p>1. Time since the simulation start in s</p> <p>2. Cloud fraction</p> <p>3. Mean relative humidity</p> <p>4. Mean specific humidity</p> <p>5. Mean specific ice content</p> <p>6. In-cloud Humidity</p> <p>7. Clear sky humidity</p> <p> </p> <p>The columns in the "par" files represent from left to right:</p> <p>1. Time since the simulation start in s</p> <p>2. Cloud fraction</p> <p>3. Mean relative humidity</p> <p>4. Mean specific humidity</p> <p>5. Mean specific ice content</p> <p>6. In-cloud Humidity</p> <p>7. Clear sky humidity</p> <p>8. Obsolete</p> <p>9. Equilibrium supersaturation</p>
MCR LTER: Coral Reef: Biodiversity has a positive but saturating effect on imperiled coral reefs; data for Clements and Hay 2021, Science Advances
Species loss threatens ecosystems worldwide, but the ecological processes and thresholds that underpin positive biodiversity effects among critically important foundation species, such as corals on tropical reefs, remain inadequately understood. In field experiments, we manipulated coral species richness and intraspecific density to test whether, and how, biodiversity affects coral productivity and survival. Corals performed better in mixed species assemblages. Improved performance was unexplained by competition theory alone, suggesting that positive effects exceeded agonistic interactions during our experiments. Peak coral performance occurred at intermediate species richness and declined thereafter. Positive effects of coral diversity suggest that species’ losses on degraded reefs make recovery more difficult and further decline more likely. Harnessing these positive interactions may improve ecosystem conservation and restoration in a changing ocean. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2022). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site. Datasets used in this study are available online from the BCO-DMO data system. Data for this paper can be found at (https://www.bco-dmo.org/project/837802).
A saturation-mutagenesis analysis of the interplay between stability and activation in Ras
<p>Dataset for the Hidalgo et al. eLife paper DOI: <a href="https://doi.org/10.7554/eLife.76595">https://doi.org/10.7554/eLife.76595</a></p>
Pathogen-sugar interactions revealed by universal saturation transfer analysis
<p>Supporting data for the "Pathogen-sugar interactions revealed by universal saturation transfer analysis" manuscript.</p>
Dataset: Infrared-radiofluorescence: dose saturation and long-term signal stability of a K-feldspar sample
<p>Original measurement and processed data of the study <em>Infrared-radiofluorescence: dose saturation and long-term signal stability of a K-feldspar sample </em>submitted for review to Radiation Measurements. The data are structured as follows:</p> <ol> <li><strong>Measurement data </strong></li> <li><strong>Processed data</strong></li> </ol> <p>Experiments were carried out at the Archéosciences Bordeaux (UMR 6034, CNRS - Université Bordeaux Montaigne; former IRAMAT-CRP2A) in Bordeaux (France) and at the Département des sciences de la Terre of the Université du Québec à Montréal (Canada). The subfolders are organised by the laboratory where the experiments were carried out: spectrometer measurements in Montréal (00_Montreal_Spectrometer) and spatially resolved measurements (camera) in Bordeaux (10_Bordeaux_Camera). </p> <p><strong>Measurement data </strong>contains sequence files used to run the experiments (so-called *.lseq files) as well as the raw, unaltered measurement output in the form of files with the ending *.xsyg and *.tiff. For the camera measurements in Bordeaux, the system returned a couple of single TIFF files. We merged those files in two files, one for <em>RF<sub>nat</sub></em> and <em>RF<sub>reg</sub></em>, for convenience reasons. The data are, however, unprocessed. </p> <p><strong>Processed data</strong> is organized like the measurement data folder containing all kinds of semi-automated processed data (PDF files, images). All data were processed with the R (R Core Team, 2021) package 'Luminescence' (Kreutzer et al., 2012; 2021) and an <em>ImageJ </em>macro detailed in Mittelstraß and Kreutzer (2021)</p> <p> </p> <p><strong>References</strong></p> <p>Kreutzer, S., Schmidt, C., Fuchs, M.C., Dietze, M., Fischer, M., Fuchs, M., 2012. Introducing an R package for luminescence dating analysis. Ancient TL 30, 1–8.</p> <p>Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Smedley, R.K., Christophe, C., Zink, A., Durcan, J., King, G.E., Philippe, A., Guérin, G., Riedesel, S., Autzen, M., Guibert, P., Mittelstrass, D., Gray, H.J., 2021. Luminescence: Comprehensive luminescence dating data analysis. CRAN. https://doi.org/10.5281/zenodo.4729933</p> <p>Mittelstraß, D., Kreutzer, S., 2021. Spatially resolved infrared radiofluorescence: single-grain K-feldspar dating using CCD imaging. Geochronology 3, 299–319. https://doi.org/10.5194/gchron-3-299-2021</p> <p>R Core Team, 2021. R: A language and environment for statistical computing. https://www.r-project.org</p> <p> </p> <p> </p>
Evaluation of the saturator efficiency of the low frost-point generator INRIM 03 Mark 1
<p>These datasets refers to the evaluation of the saturator efficiency of the low frost-point generator INRIM 03 developed at the Istituto Nazionale di Ricerca Metrologica. Alternating the inlet gas between a dry source and a moist gas source is it possible to test the capability of the generator to saturate the carrier gas (or condensate the excess water) at the corresponding saturation<br>temperature.</p> <p>This work has been carried out within the European Metrology Programme for Innovation and Research (EMPIR) Project ‘PROMETH2O—Metrology for trace water in ultra-pure process gases’.<br>This project (Grant No. 20IND06 PROMETH2O) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme.</p>
Data underpinning "Pulse sequence considerations for interleaved chemical exchange saturation transfer acquisition sequences."
<p>=================================================<br> Robert Casper Brand, PhD Candidate<br> Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.<br> =================================================</p> <p>This folder contains the images and datasets used to generate the figures of the paper named: "Pulse sequence considerations for interleaved chemical exchange saturation transfer acquisition sequences." </p> <p>Each figure of the paper, with its corresponding data, is contained in an opensource TikZ format file. The TikZ files include both information on the axis as well as the supporting data and can be opened with any generic text editor. For more information on TikZ, see:<br> https://www.sharelatex.com/learn/TikZ_package). </p> <p>Where datasets were too large to be run by standard TeX distributions, the data was attached in an alternative format, and a TikZ wrapper included.</p> <p>The figures can be generated through any of the opensource TeX distributions. For more information on LaTeX and TeX, please see: <br> https://www.latex-project.org/get/ and<br> https://www.sharelatex.com/learn/Pgfplots_package.</p> <p>A compilation example of all figures, which also lists any additional packages, is included in the "wrapper. Tex" file. The output of this process was added to this folder as well (wrapper.pdf).</p> <p>The included files were created using directly from Matlab using the matlab2tikz code:<br> https://www.mathworks.com/matlabcentral/fileexchange/22022-matlab2tikz-matlab2tikz</p>
Experimental data for fracture toughness analysis of sandstone and granite samples under fluid saturation conditions
<p>This database includes experimental results from mode I fracture toughness (KIC) tests conducted on saturated rock specimens. Three lithologies were studied: a porous siliceous sandstone (Corvio, C) and two high-strength, low-porosity granites (Blanco Mera, BM and Blanco Alba, BA). Tests were conducted at room pressure and temperature using the pseudo-compact tension (pCT) methodology. Seven different fluids were used: deionized water, methanol, NaCl-saturated water, mineral oil, diesel fuel, an acidic HCl solution, and a caustic NaOH solution.</p>
APARENT2 Genome-wide In-silico Saturation Mutagenesis
<p>In-silico saturation mutagenesis predictions for all polyadenylation signals found in PolyADB V3 using the APARENT2 model (transcript-wide). The file 'aparent2_ism_scores_polyadb_v3.csv.gz' contains all data. The file 'aparent2_ism_scores_polyadb_v3_cutoff.csv.gz' contains only variants with more than 1.25-fold increase or decrease in isoform odds. The data columns 'delta_logodds' and 'delta_usage' contain variant isoform log odds ratios and isoform proportion differences (wrt. PolyADB measurements) for polyadenylation occurring anywhere +/- 100bp of the canonical cleavage site. The columns 'delta_logodds_narrow' and 'delta_usage_narrow' contains log odds ratios and proportion differences for cleaveage that occurs +0bp to +50bp immediately downstream of the canonical core hexamer motif. The data columns 'pas_position_hg19' and 'pas_position_hg38' indicate the start coordinate of the core hexamer.</p>
Dataset for "A capillary bundle model for the electrical conductivity of saturated frozen porous media"
<p>This dataset supports the research study 'A capillary bundle model for the electrical conductivity of saturated frozen porous media' by H. L. Luo, D. Jougnot, A. Jost, J. D. Teng and L. D Thanh.</p> <p>We provide the experimental data from this study and the published data from Coperey et al. (2019a,b) and Duvillard et al. (2018, 2021) for verifing the proposed model with different PSDs (lognormal and fractal distribution).</p> <p>Matlab code Description:</p> <p>Untitled 1- the code for determining the electrical conductivity as a function of temperature and the sensitive analysis;</p> <p>Untitled 2- the code for comparison between the experimental data and the proposed model;</p> <p>Untitled 3- the code for comparison of the contribution between the bulk conduction and surface conduction to the total electrical conductivity;</p> <p>Untiled 4- the code for evolution of the effective formation factor as a function of the temperature.</p>
Dataset and stimuli: Perception of saturation in natural objects
<p><strong>This dataset contains observer data and stimulus information for the below publication. Refer to this manuscript for more details.</strong></p> <p>Laysa Hedjar, Matteo Toscani, and Karl R. Gegenfurtner, "Perception of saturation in natural objects," Journal of the Optical Society of American A <strong>40</strong>(3), A190-A198 (2023), doi:10.1364/JOSAA.476874.</p> <p> </p> <p>Participant data is available in two files: <em>fruit_pt_data.csv </em>and <em>blob_pt_data.csv</em></p> <ul> <li><em>fruit_pt_data.csv</em>: <ul> <li>fruit name: name of fruit pair</li> <li>object or swatch: whether the stimulus pair were whole objects or 8x8 swatches</li> <li>participant ID: given participant identification number</li> <li>proportion positive: proportion of trials in which participant chose the positive stimulus as more saturated (out of 10 total trials per stimulus pair)</li> </ul> </li> <li><em>blob_pt_data.csv</em>: <ul> <li>blob hue (radians - LAB): hue in radians of the blob pair, as defined in LAB-LCH color space</li> <li>object or swatch: whether the stimulus pair were whole objects or 8x8 swatches</li> <li>matched or unmatched: whether the stimulus pair were matched in terms of blob ID (refers to spatial configuration)</li> <li>positive stimulus ID: identification number of the positive LC-slope stimulus (refers to spatial configuration)</li> <li>negative stimulus ID: identification number of the negative LC-slope stimulus (refers to spatial configuration) <ul> <li>note that the above two IDs should be identical if the stimulus is a 'matched' pair</li> </ul> </li> <li>participant ID: given participant identification number</li> <li>proportion positive: proportion of trials in which participant chose the positive stimulus as more saturated (out of 5 total trials per stimulus pair)</li> </ul> </li> </ul> <p> </p> <p>Stimuli pngs are in the zip file s<em>timuli.zip</em>. Pngs are not gamma-corrected. Blob and fruit stimulus sets are separated by folder; object and swatch stimulus sets are also separated by folder.</p> <p>Fruit pngs are labeled:</p> <p> fruit_[object/swatch]_[fruitName]-[negative/positive].png</p> <p>For blob pngs, six possible spatial configurations for each hue were used. An ID was given for each configuration. Blob pngs are labeled:</p> <p> blob_[object/swatch]_hue[hueInRadians]_ID[1-6]-[negative/positive].png</p> <p> </p> <p>Statistics of the stimulus images are presented in the files <em>fruit_stats_objects.csv</em>, <em>fruit_stats_swatches.csv</em>, <em>blob_stats_objects.csv</em>, and <em>blob_stats_swatches.csv</em>. Each column represents a different stimulus image. Each row represents a different statistic taken across the distribution of pixels. Calculations were made in CIELAB-LCH color space ('white point' defined as white of monitor: CIE1931 xyY 0.3328, 0.3343, 142.35).</p>
Dataset for "Predicting the electrical conductivity of partially saturated frozen porous media, a fractal model for wide ranges of temperatures and salinities"
<p>This dataset supports the research study "Predicting the electrical conductivity of partially saturated frozen porous media, a fractal model for wide ranges of temperatures and salinities" by H. L. Luo, D. Jougnot, A. Jost, J. D. Teng, A. Mendieta, G. Lin, and L. D. Thanh.<br> We provide the experimental data of electrical condutivity and unfrozen water saturation with different initial water saturations and salinities. Meanwhile, we also offer the matlab code for calculating the predicted values of electrical conductivity and apparent formation factor.</p> <p>Each file has its header, describing each column.</p> <p> </p>
Supplementary Files for "Extinction debt and functional traits mediate community saturation over large spatiotemporal scales"
<p><strong>Supplementary Files for "Extinction debt and functional traits mediate community saturation over large spatiotemporal scales"</strong></p> <p><strong>Supplementary Tables:</strong></p> <p><strong>Supplementary Table S1.</strong> Species composition data of the 67 sites included herein from members of the Dipsadidae.</p> <p><strong>Supplementary Table S2.</strong> Scores for the Principal Component (PC) Axes corresponding to the PC analyses performed with the climatic variables of the sites included in this work.</p> <p><strong>Supplementary Table S3.</strong> Species composition data of the 67 sites included herein from species from families different from Dipsadidae.</p> <p><strong>Supplementary Table S4.</strong> Functional data corresponding to each of the species found in the 67 sites included in this work.</p> <p><strong>Supplementary Table S5.</strong> Functional data corresponding to each of the species from families different from Dipsadidae found in the 67 sites included in this work.</p> <p><strong>Supplementary Table S6.</strong> GenBank accession numbers of each of the sequences used for constructing the timetree used for this work.</p> <p><strong>Supplementary Table S7.</strong> Table indicating the areas inhabited by each of the species of the Dipsadidae included in the Bayesian timetree used for the ancestral area estimation performed herein.</p> <p><strong>References used for constructing Supplementary Tables S4 and S5</strong></p> <p> </p> <p><strong>Supplementary Figures:</strong></p> <p><strong>Supplementary Figure S1.</strong> Results of the ancestral estimations as recovered by ‘BioGeoBEARS’</p>
Hubbard Brook Experimental Forest: Watershed 3 Saturated Hydraulic Conductivity
This is a dataset of soil saturated hydraulic conductivity (Ksat) collected from augered boreholes or installed groundwater wells in Watershed 3 of the Hubbard Brook Experimental Forest. Hydraulic conductivity describes the ability of a porous medium such as soil to transmit fluid. It is dependent on both fluid (e.g., viscosity) and porous medium properties, and is a key property for estimating subsurface flow rates. Measurements were collected from near the soil surface (10-15 cm depth) to several meters below the surface. Locations are provided for sites where the confidence in coordinates established by GPS was high. Soil horizons without subordinate designators are approximate since the characterization skill of observers varied. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES) and several other NSF grants over the period from approximately 2007 to 2019. The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
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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.
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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
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