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Data from: Carotenoid metabolic profiling and transcriptome-genome mining reveal functional equivalence among blue-pigmented copepods and appendicularia
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Data from: Disentangling ecologically equivalent from neutral species: the mechanisms of population regulation matter
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Data from: Assessing risks of invasion through gamete performance: farm Atlantic salmon sperm and eggs show equivalence in function, fertility, compatibility and competitiveness to wild Atlantic salmon
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U.S.-EPA-BELD4-Equivalent Landuse Database for Canada – Version 2
<p>Air Quality Research Division, Environment and Climate Change Canada,</p> <p>4905 Dufferin Street, Toronto, Ontario, M3H 5T4, Canada</p> <p>Email: Junhua.zhang@canada.ca</p> <p> </p> <p>The first version of a U.S.-EPA-BELD4-equivalent landuse database for Canada was compiled in 2018 by Environment and Climate Change Canada (ECCC) based on: (1) the first version of Canada-wide tree species composition maps based on the 2001 Canadian National Forest Inventory (NFI; Beaudoin et al., 2014); (2) the 2016 Canadian Annual Crop Inventory (ACI); and (3) the Land Cover Classification System surface hydrology (LCCS3) data set contained in the Collection 6 MODIS Land Cover product MCD12Q1 (Zhang and Moran, 2018). Recently, an improved mapping approach for estimating forest attributes from MODIS imagery was applied to reprocess the 2001 NFI-based species composition maps and to create a new set of species composition maps for 2011 using 2011 MODIS imagery (Beaudoin et al., 2017a,b). The new mapping approach resulted in an improved set of 2001 species composition maps as indicated by increased correlation coefficients and decreased mean deviations (MD) and root-mean-square deviations (RMSD) between 35,305 MODIS reference pixels for 2001 and the 2001 NFI photo-plot product (Beaudoin et al., 2017b). In addition, for the new 2011 species composition maps, expected reductions in forest coverage were seen for areas of Canada that had experienced rapid development between 2001 and 2011, such as the Athabasca Oil Sands (AOS) area in northeastern Alberta and areas near major urban centres such as Toronto and Vancouver. Given the improved mapping approach and the greater recentness of the 2011 tree species composition maps, the Canadian BELD4 landuse database was updated using these new 2011 maps and the same methodology described in Zhang and Moran (2018). Note that no change was made to the ACI and MODIS Land Cover product data sets that were used to develop this new database version.</p> <p>Because the number of tree species considered in the 2001 NFI-based forest composition maps was reduced from 109 in the first version to 75 in the second version due to the least abundant tree species being lumped with other related species (Beaudoin et al., 2017b), gridded fractional-coverage fields for the U.S.-EPA-BELD4-equivalent landuse categories compiled for Canada have also been reduced, from 92 in the first version of the Canadian BELD4 database to 80 in this second version. The mapping from the 75 NFI tree species to the U.S. Environmental Protection Agency (EPA) BELD4 landuse categories is shown in the attached spreadsheet “ACI_NFI_BELD4_species_match_V2.xlsx”, along with the unchanged mapping of 62 ACI species and other landuse categories. The mapping used to link the LCCS3 categories to the BELD4 categories also remains unchanged and is described in the attached Excel file “MODIS_LCCS3_BELD4_mapping.xlsx”. </p> <p>The updated version 2 of the Canadian BELD4 landuse database is provided here in GeoTIFF format at 1-km resolution for a Lambert conformal conic projection (+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs) in the compressed file “CAN-BELD4_tif_V2.7z”. Note that to use this dataset in conjunction with the U.S. EPA BELD4 database (<a href="https://www.epa.gov/air-emissions-modeling/biogenic-emission-sources">https://www.epa.gov/air-emissions-modeling/biogenic-emission-sources</a>), all MODIS landuse categories in the original EPA BELD4 database must be removed for Canada to avoid double-counting. Plots of the 80 matched Canadian and U.S. BELD4 vegetation species and other landuse categories in the new Canadian BELD4 database are shown in the attached file “CAN_US_Matched_BELD4_Species_Plots_V2.pdf”. Lastly, an overview and description of the updated Canadian BELD4 landuse database was presented at a recent conference (Zhang et al., 2019, <a href="https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf">https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf</a>); this presentation is also provided in this package as file “2019EI_Updated_BELD4_Impact_on_VOC_emissions.pptx”. </p> <p> </p> <p><strong>REFERENCES</strong></p> <p>Beaudoin, A., Bernier, P.Y., Guindon, L., Villemaire, P., Guo, X.J., Stinson, G., Bergeron, T., Magnussen, S., and Hall, R.J.: Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery. <em>Canadian Journal of Forest Research</em>, <strong>44</strong>, 521–532, <a href="https://doi.org/10.1139/cjfr-2013-0401">https://doi.org/10.1139/cjfr-2013-0401</a>, 2014.</p> <p>Beaudoin A., Bernier P.Y., Villemaire P., Guindon L., Guo X.-J., Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada, <a href="https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990">https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990</a>, 2017a.</p> <p>Beaudoin, A., Bernier, P.Y., Villemaire, P., Guindon, L., Guo, X.-J., Tracking forest attributes across Canada between 2001 and 2011 using a kNN mapping approach applied to MODIS imagery, <em>Canadian Journal of Forest Research</em>, 48: 85–93, <a href="https://doi.org/10.1139/cjfr-2017-0184">https://doi.org/10.1139/cjfr-2017-0184</a>, 2017b.</p> <p>Zhang, J. and Moran, M. D., U.S.-EPA-BELD4-Equivalent Landuse Database for Canada [Data set]. Zenodo. <a href="http://doi.org/10.5281/zenodo.2231047">http://doi.org/10.5281/zenodo.2231047</a>, 2018.</p> <p>Zhang, J., Moran, M.D., and He, Z.: Updates to Version 4 of the Biogenic Emissions Landuse Database (BELD4) for Canada and Impacts on Biogenic VOC Emissions, <em>2019 International Emissions Inventory Conference, </em>July 29th – Aug. 2nd, Dallas, Texas, USA, <a href="https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf">https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf</a>, 2019.</p> <p> </p> <p><strong>AcknowledgementS</strong></p> <p>We are very grateful for the dedicated assistance of Dr. Zhuanshi He of SOLANA Networks Inc. in preparing this updated version of the database. </p> <p> </p> <p><strong>RELATED DATA SETS AND MATERIALS</strong></p> <ol> <li>“CAN-BELD4_tif_V2.7z” – Version 2 of the extended BELD4 GeoTIFF file for Canada</li> <li>“ACI_NFI_BELD4_species_match_V2.xlsx” – Version 2 of the NFI/ACI-BELD4 landuse-category crosswalk file</li> <li>“MODIS_LCCS3_BELD4_mapping.xlsx” – MODIS-BELD4 landuse-category crosswalk file (same as in Version 1)</li> <li>“CAN_US_Matched_BELD4_Species_Plots_V2.pdf” – Plots of 80 updated BELD4 landuse category fields over Canada.</li> <li>“2019EI_Updated_BELD4_Impact_on_VOC_emissions.pptx” – 2019 conference presentation on this new version of the Canadian BELD4 landuse database</li> </ol>
Synthetic model parameters for the comparison between an equivalent source and a minimum curvature interpolator of aeromagnetic data
<p>Parameters of the synthetic case used in Gavazzi et al. (submitted)[1]</p> <p>FILES (ASCII FORMAT)</p> <p>param.txt<br> General parameters of the geomagnetic field<br> Incl. inclination of the geomagnetic field<br> decl. declination of the geomagnetic field</p> <p>sources.txt<br> Localization and magnetization of the simulated sources<br> xs x-position of the sources (in m)<br> ys y-position of the sources (in m)<br> zs z-position of the sources (in m)<br> Ms magnetization of the sources (in A/m)</p> <p>profiles.txt<br> Localization of the simulated acquisition profiles<br> xx x-position of the data<br> yy y-position of the data<br> zz z-position of the data</p> <p>eqsources.txt<br> Localization and magnetization of the equivalent sources<br> xdeq x-position of the sources (in m)<br> ydeq y-position of the sources (in m)<br> zdeq z-position of the sources (in m)<br> JJ magnetization of the sources (in A/m)</p> <p>[1] Gavazzi, B., Bertrand, L., Munschy, M., Mercier de Lépinay, J., Diraison, M. & Géraud, Y. (submitted). On the use of aeromagnetism for geological interpretation part I: comparison of scalar and vector magnetometers for aeromagnetic surveys and an equivalent source interpolator for combining, gridding and transform fixed altitude and draping datasets, Journal of Geophysical Research: Solid Earth.</p>
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia. in Bite-force estimation for Tyrannosaurus rex from tooth-marked bones
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia.
Raw Data for Article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents"
<p>NMR, IR and MS raw data for the article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents" published in Angewandte Chemie in 2020, DOI: 10.1002/anie.202006707 and 10.1002/ange.202006707</p> <p>The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.</p>
A Lightweight Technique to Identify Equivalent Mutants
<p>Mutation analysis is a popular but costly approach to assess the quality of test suites. Equivalent mutants are useless and contribute to increase costs. We propose a lightweight technique to identify equivalent mutants by proving equivalences with Z3 in the context of weak mutation testing. To evaluate our approach, we apply our technique for 40 mutation targets (mutations of an expression or statement) and automatically identify 13 equivalent mutations for seven mutation targets. We manually confirm that the equivalent mutants detected by our technique are indeed equivalent. Moreover, we evaluate our approach in the context of strong mutation testing against mutants generated by MuJava for 5 projects. Our technique detects all equivalent mutants detected by TCE. The results of our technique can be useful to improve mutation testing tools by avoiding the application of 13 mutations for 7 mutation targets.</p>
Age-related change of axial length, spherical equivalent, prevalence of myopia and high myopia in school-age children in Shanghai: 2014 to 2018
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective </b> To investigate the age-related changefor axial length (AL), Spherical equivalent (SE), prevalence of myopia and high myopiain children at 7 to 18 year-olds in Shanghai in 2014 and 2018, respectively, to compare these parameters between 2014 and 2018, and to evaluated the potential factors associated with AL.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Design</b> An observational study.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Setting</b> Jinshan Hospital of Fudan University in Shanghai.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Methods</b> One primary school, one junior high school, and one senior high school were randomly selected in 2014 and 2018, respectively. AL, SE, prevalence of myopia and high myopia, height and weight were measured. A questionnaire regarding the lifestyles was completed.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results</b> Mean AL were shorter in 2018 than in 2014 (P = 0.003), whereas mean SE was greater in 2018 than in 2014 (P < 0.001). The prevalence of myopia and high myopia was lower in 2018 than in 2014 (P < 0.001 and P = 0.013, respectively). Mean AL increased with age from 7 year-oldsto18 year-oldsin 2014and 2018 (both P < 0.001), respectively. Mean SE decreased with age in 2014 and 2018 (both P < 0.001), respectively. The prevalence of myopia and high myopia increased with age in 2014 and 2018 (all P < 0.001), respectively. Multivariate regression analysis revealed that longer AL was mainly associated male gender and body height.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusion </b>This study shows normative growth values for AL and SE in Shanghai children at the age of 7 to 18 year-olds, as well as the age-specific prevalence of myopia and high myopia.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: BAMM at the court of false equivalency: a response to Meyer and Wiens
The software program BAMM has been widely used to study rates of speciation, extinction, and phenotypic evolution on phylogenetic trees. The program implements a model-based clustering algorithm to identify clades that share common macroevolutionary rate dynamics and to estimate parameters. A recent simulation study by Meyer and Wiens (M&W) claimed that (i) a simple inference framework ("MS") performs much better than BAMM, and (ii) evolutionary rates inferred with BAMM are poorly correlated with true rates. I address two statistical concerns with their assessment that affect the generality of their conclusions. These considerations are not specific to BAMM and apply to other methods for estimating parameters from empirical data where the true grouping structure of the data is unknown. M&W constrain roughly half of the parameters in their MS analyses to their true values, but BAMM is given no such information and must estimate all parameters from the data. This information disparity results in a substantial degrees-of-freedom advantage for the MS estimators. When both methods are given equivalent information, BAMM outperforms the MS estimators.
Data from: Equivalence analysis to support environmental safety assessment: using nontarget organism count data from field trials with cisgenically modified potato
This paper considers the statistical analysis of entomological count data from field experiments with genetically modified (GM) plants. Such trials are carried out to assess environmental safety. Potential effects on nontarget organisms (NTOs), as indicators of biodiversity, are investigated. The European Food Safety Authority (EFSA) gives broad guidance on the environmental risk assessment (ERA) of GM plants. Field experiments must contain suitable comparator crops as a benchmark for the assessment of designated endpoints. In this paper, a detailed protocol is proposed to perform data analysis for the purpose of assessing environmental safety. The protocol includes the specification of a list of endpoints and their hierarchical relations, the specification of intended levels of data analysis, and the specification of provisional limits of concern to decide on the need for further investigation. The protocol emphasizes a graphical representation of estimates and confidence intervals for the ratio of mean abundances for the GM plant and its comparator crop. Interpretation relies mainly on equivalence testing in which confidence intervals are compared with the limits of concern. The proposed methodology is illustrated with entomological count data resulting from multiyear, multilocation field trials. A cisgenically modified potato line (with enhanced resistance to late blight disease) was compared to the original conventional potato variety in the Netherlands and Ireland in two successive years (2013, 2014). It is shown that the protocol encompasses alternative schemes for safety assessment resulting from different research questions and/or expert choices. Graphical displays of equivalence testing at several hierarchical levels and their interpretation are presented for one of these schemes. The proposed approaches should be of help in the ERA of GM or other novel plants.
Data from: Calculating maximum morphine equivalent daily dose from prescription directions for use in the electronic health record: a case report
Objective To demonstrate a process of calculating the maximum potential morphine milligram equivalent daily dose (MEDD) based on the prescription Sig for use in quality improvement initiatives. Methods To calculate an opioid prescription's maximum potential Sig-MEDD, we developed SQL code to determine a prescription's maximum units/day using discrete field data and text-parsing in the prescription instructions. We validated the derived units/day calculation using 3,000 Sigs, then compared the Sig-MEDD calculation against the Epic MEDD calculator. Results Of the 101,782 outpatient opioid prescriptions ordered over one year, 80% used discrete-field Sigs, 7% used free-text Sigs, and 3% used both types. We determined units/day and calculated a Sig-MEDD for 98.3% of all prescriptions, 99.99% of discrete-Sig prescriptions, and 81.5% of free-text-Sig prescriptions. Conclusion Analyzing opioid prescription Sigs to determine a maximum potential Sig-MEDD provides greater insight into a patient's risk for opioid exposure.
Data from: State-space reduction and equivalence class sampling for a molecular self-assembly model
Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.
PLCspecif permissive equivalence checking example model
<p>Example models for the permissive equivalence checking relations of PLCspecif.</p>
Nordic44 - 2015 Powerflow Data: An Open Data Repository of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data for 2015
<p>This repository is used to provide documentation related to the model and data development process, provide source (raw) data for the model in different forms (i.e. Modelica, CIM 14, and PSS/E) for an equivalent Nordic grid model that has been matched to historical power flow data.</p> <p>The repository is documented in the paper below, see [Ref00].</p> <p><strong>Using this model, data or related software = cite our publications!</strong></p> <p>We are happy to contribute with this dataset, however, if you use any of the data or software provided, we will appreciate if you cite the following publications, as follows:</p> <p>A) Cite that "the raw and processed data files corresponding to the model are available as an open data set and documented in [Ref00]."</p> <p>B) Cite that the first appearance of the model, i.e. "the model is first presented in [Ref01]"</p> <p>[Ref00] L. Vanfretti, S.H. Olsen, V. S. Narasimham Arava, G. Laera, A. Bibadafar, T. Rabuzin, H. Jackobsen, J. Lavenius, and M. Baudette, "An Open Data Repository and a Data Processing Software Toolset of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data," submitted for publication, Data in Brief, 2016.</p> <p>[Ref01] L. Vanfretti, T. Rabuzin, M. Baudette, M. Murad, iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations, SoftwareX, Available online 18 May 2016, ISSN 2352-7110, http://dx.doi.org/10.1016/j.softx.2016.05.001.</p> <p><strong>Acknowledgment:</strong></p> <p>This model was originally developed in the context of the FP7 iTesla project, and further extended within the ITEA3 openCPSproject.</p> <p>Structure of the repository:</p> <p><strong>01_PSSE_Resources</strong>:</p> <ol> <li> <p><strong>Models</strong> :</p> <ul> <li> <p>A folder with PSS/E files of the base case</p> </li> <li> <p>A folder with a 7zip archive containing files of the original N44 system that has been modified to have the PSS/E base case</p> </li> </ul> </li> <li> <p><strong>Snapshots</strong> :</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (for example <em>N44_20150401</em> refers to the 1st of April 2015). In each folder there are Excel files (<em>Consumption_xx.xlsx</em>, <em>Exchange_xx.xlsx</em>, <em>Production_xx.xlsx</em>) with data downloaded from Nord Pool website, an Excel file (<em>PSSE_in_out.xlsx</em>) summarizing the results from the Python script <em>Nordic44.py</em> in the folder <strong>04_Python_Resources</strong>, PSS/E snapshots for each hour before solving the power flow (<em>hx_before_PF.raw</em>) and after solving the power flow (<em>hx_after_PF.raw</em>)</p> </li> <li> <p><em>N44_BC.sav</em> is the PSS/E solved base case that Python script <em>Nordic44.py</em> (put the reference)</p> </li> </ul> </li> </ol> <p><strong>02_CIM14_Snapshots</strong>:</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (e.g. <strong>N44_20150401</strong> refers to the 1st of April 2015). In each folder there are CIM files for each hour (<em>N44_hx_EQ.xml</em>, <em>N44_hx_SV.xml_, _N44_hx_TP.xml</em>)</p> </li> <li> <p><strong>N44_noOL_RDFIDMAP.xml</strong> is the file with IDs mapping of those cases (<em>N44_hx_noOL_EQ.xml</em>, <em>N44_hx_noOL_SV.xml</em>, <em>N44_hx_noOL_TP.xml</em>) with fixed overloading problems.</p> </li> <li> <p><strong>N44_RDFIDMAP_2015-1.xml</strong> and <strong>N44_RDFIDMAP_2015-2.xml</strong> are the files with IDs mapping of the remaining snapshots from 2015</p> </li> </ul> <p><strong>03_Modelica</strong>:</p> <ol> <li> <p><strong>iTesla_Platform</strong></p> <ul> <li> <p><strong>iPSL</strong> folder contains the version of the library which can be used to simulate snapshots generated from the iTesla Platform</p> </li> <li> <p><strong>Modelica_snapshots</strong> Modelica models generated from the snapshots by iTesla Platform</p> </li> </ul> </li> <li> <p><strong>SmarTSLab</strong></p> <ul> <li> <p><strong>OpenIPSL</strong> folder contains the version of the forked iPSL library which can be used to simulate the manually generated Modelica model of N44 with the record structures corresponding to the snapshots</p> </li> <li> <p><strong>Snapshots</strong> folder contains Modelica records automatically generated from the PSS/E records</p> </li> <li> <p><em>N44_Base_Case.mo</em> is the handmade N44 model with the loaded record of the power flow results from the PSS/E base case. It can be used to load other PF results from the folder <strong>03_Modelica/Snapshots</strong></p> </li> </ul> </li> </ol>
LACUNAES AND NON-EQUIVALENT VOCABULARY AS A REFLECTION OF LINGUISTIC CULTURE
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Silicone induces pro-inflammatory response in 3D skin equivalent
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SWECA: High-resolution daily Snow Water Equivalent estimates for Mountainous Central Asia (1979–2016)
<p>The dataset provides daily estimates of snow water equivalent (SWE) for Central Asia, at a spatial resolution of 1km, covering the period from 1979 to 2016. The dataset were generated within the <a href="https://www.iamo.de/en/research/research-projects/details/sweca/">SWECA</a> project, supported by GEO Mountains under the Adaptation at Altitude Programme (Swiss Agency for Development and Cooperation Project Number: 7F-10208.01.02).</p> <p><strong>Spatial Domain:</strong><br>The dataset encompasses the Central Asian region within the bounding coordinates 61W, 81E, 44N, 34S, which covers the Tian-Shan and Pamir mountains, a larger extent of the Hindukush mountains, and the northern part of the Karakoram mountains.</p> <p><strong>Data Generation and Validation:</strong><br>The SWE data was generated using the <a href="../records/10161423">GEMS snow mode</a>l (Umirbekov, Essery, and Müller, 2024), forced by CHELSA-W5E5 daily climate data (Karger et al., 2023). Simulated SWE was validated using historical records of SWE from 1980 to 1992 from Central Asian Snow Survey database (Bedford and Tsarev, 2001), and by comparing extent of the modelled SWE with MODIS derived snowcover for two consecutive hydrological years (2015-2016). Data generation procedures and validation results will be provided in upcoming data description paper (TBD).</p> <p><strong>File Descriptions:</strong><br>The daily SWE estimates (in millimeters) are compiled into 37 GeoTIFF files, each corresponding to a hydrological year from 1979 to 2016. The hydrological year begins on October 1st and concludes on September 30th of next year. To avoid the need for auxiliary files, the corresponding date of each layer in the GeoTIFF file is incorporated as a layer`s name. </p> <p>References: </p> <ul> <li>Bedford, D. and Tsarev, B. (2001) ‘Central Asian Snow Cover from Hydrometeorological Surveys, Version 1 [Dataset]’. Boulder, Colorado USA.: National Snow and Ice Data Center. doi: <a href="https://doi.org/10.7265/N51Z4291">10.7265/N51Z4291</a>.</li> <li>Karger, D. N. et al. (2023) ‘CHELSA-W5E5: daily 1km meteorological forcing data for climate impact studies’, Earth System Science Data, 15(6), pp. 2445–2464. doi: <a href="https://doi.org/10.5194/essd-15-2445-2023">10.5194/essd-15-2445-2023</a>.</li> <li>Riggs, G., Hall, D. and Salomonson, V. (2019) ‘MODIS snow products user guide to collection 6.1: MODIS-derived snow cover retrievals using the cloud-gap-filled MOD10A1F product’.</li> <li>Umirbekov, A., Essery, R. and Müller, D. (2024) ‘GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers’, Geoscientific Model Development, 17(2), pp. 911–929. doi: <a href="https://doi.org/10.5194/gmd-17-911-2024">10.5194/gmd-17-911-2024</a>. </li> </ul>
Static electric equivalent circuit of commercial lithium-ion battery cells using genetic algorithms
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EQUIVALENT WORDS AND THEIR REFLECTION IN A WORK OF ART
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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.