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37,310 results for “6”
Above- and below-ground non-structural carbohydrates (NSC) in Spartina alterniflora from 6 permanant plots near the Georgia Coastal Ecosysterms LTER flux tower, on Sapelo Island in Georgia, USA
We studied the dynamics of four non-structural carbohydrates (glucose, fructose, sucrose, and starch) and biomass in 8 different above- and below-ground tissues in Spartina alterniflora over the course of a year in a salt marsh on Sapelo Island, Georgia, USA. Tissue parts sampled included green leaves, green stems, yellow leaves, yellow stems, brown leaves and stem, flowers, belowground biomass from 0-10cm depth and belowground biomass from 10-30cm depth. Samples were collected from tall form S. alterniflora plots near the Georgia Coastal Ecosystems LTER flux tower site monthly between September 2013 and August 2014. This study was conducted to support the development of predictive, mechanistic models of Spartina by providing information on below-ground biomass and its dynamics, and in particular the storage of resources that can be used for spring re-growth.
Plant biomass dynamics following logging, burning, and thinning in Watersheds 6 and 7, Andrews Experimental Forest, 1979 to 2021
Watersheds 6 (WS06) and 7 (WS07) at the HJ Andrews are part of a three-watershed study initiated in the 1970’s to examine the response of hydrology and forest vegetation to logging. In 1974, Watershed 6 was clearcut logged; Watershed 7 was shelterwood cut, leaving 75-100 overstory trees per hectare (comprising about 40% of the original basal area). A nearby watershed (WS08) serves as an unlogged control. In 1975, all of Watershed 6 and the portion of WS07 below the road were broadcast-burned. In 1976, both watersheds were planted with Douglas-fir seedlings. Natural regeneration of Douglas-fir and western hemlock also established. In 1984, the remnant overstory trees in WS07 were harvested, and in 2001 the young stand in WS07 was thinned to about 550 trees per hectare. The thinning was not planned but provides an interesting twist to the study. The watersheds are located along the northern boundary of the HJA off the 327 and 328 roads, at elevations ranging from 850 to 1,160 m. Initial vegetation measurements were taken in the summer of 2002 in watersheds 6 and 7 for the purpose of characterizing plant succession after thinning in a small, high-elevation watershed. Understory vegetation plots are remeasured at approximately 6 year intervals.
Database of measurements for damage detection of steel beam splice connection by Coaxial Correlation Method in 6-D space
<p>This database includes series of measurements of the structure's response taken in six-dimensional space using two 6D sensors, coaxially positioned on either side of the investigated splice connection between two steel beams. The data set consists of two parts. The first part of the data set is measurements for six different specimens with wave type impact – short sweep signal with duration 0.05 s. The second part is the measurements during splice connection degradation of one of the specimens with short impulse. The degradation of a connection is presented by four different states of joints. In the "<strong>Read_me_first.pdf</strong>" is described the experiment, the format of .csv files names and files' structure.</p><p>Used materials, methods and results for the second part of the data set is described in Buka-Vaivade, K.; Kurtenoks, V.; Serdjuks, D. Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space. <i>Buildings</i> <strong>2023</strong>, <i>13</i>, 1151. https://doi.org/10.3390/buildings13051151</p>
Database of measurements for damage detection of steel beam splice connections by Coaxial Correlation Method in 6-D space
<p>This database includes series of measurements of the structure's response taken in six-dimensional space using two 6D sensors, coaxially positioned on either side of the investigated splice connection between two steel beams. The data set consists of measurements for six different specimens with two types of impact – sweep signal with duration 0.5 s and short impulse, during degradation of the splice connections realised by unbolting the bolts in the connections. In the "<strong>Read_me_first.pdf</strong>" is described the experiment, the format of .csv files names and files' structure.</p><p>This database is a continuation of the database Kurtenoks, V., Buka-Vaivade, K., Serdjuks, D., Lapkovskis, V., Mironovs, V., & Podkoritovs, A. (2023). Database of measurements for damage detection of steel beam splice connection by Coaxial Correlation Method in 6-D space (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10077332<br>Suggested by authors data post-processing is described in Buka-Vaivade, K.; Kurtenoks, V.; Serdjuks, D. Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space. <i>Buildings</i> <strong>2023</strong>, <i>13</i>, 1151. https://doi.org/10.3390/buildings13051151</p>
Hubbard Brook Experimental Forest: Chemistry of Precipitation – Monthly Fluxes, Watershed 6, 1964 - ongoing
These data are monthly fluxes of solutes in precipitation collected at the Hubbard Brook Experimental Forest and are a part of the Hubbard Brook Watershed Ecosystem Record (HBWatER), which is a long-term record of stream and precipitation chemistry and volume. The solute fluxes in precipitation are calculated as the product of precipitation volume and solute concentrations. There are nine gaged watersheds at the Hubbard Brook Experimental Forest, some of which have been subjected to experimental manipulations. The calculation of fluxes is currently supervised by John Campbell (US Forest Service). The long-term stream water record is collected and maintained by the US Forest Service. The collection and management of the long-term stream and precipitation chemistry record was initiated in 1963 by Gene E. Likens, F. Herbert Bormann, Robert S. Pierce, and Noye M. Johnson. HBWatER is currently sustained by Tammy Wooster (Cary IES) and Jeff Merriam (USFS) and the dataset is curated and maintained by a team of researchers: Chris Solomon (Cary IES), Emma Rosi (Cary IES), Emily Bernhardt (Duke), Lindsey Rustad (USFS), John Campbell (USFS), Bill McDowell (UNH), Charley Driscoll (Syracuse U.), Mark Green (Case Western), and Scott Bailey (USFS). Current Financial Support for HBWatER is provided by NSF LTREB # 1907683 and the USDA Forest Service Northern Research Station. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the US Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Chemistry of Streamwater – Monthly Fluxes, Watershed 6, 1963 - ongoing
These data are monthly fluxes of solutes in stream water measured in watersheds of the Hubbard Brook Experimental Forest and are a part of the Hubbard Brook Watershed Ecosystem Record (HBWatER), which is a long-term record of stream and precipitation chemistry and volume. The solute fluxes in stream water are calculated as the product of the volume of stream water and solute concentrations. There are nine gaged watersheds at the Hubbard Brook Experimental Forest, some of which have been subjected to experimental manipulations. The calculation of fluxes is currently supervised by John Campbell (US Forest Service). The long-term stream water record is collected and maintained by the US Forest Service. The collection and management of the long-term stream and precipitation chemistry record was initiated in 1963 by Gene E. Likens, F. Herbert Bormann, Robert S. Pierce, and Noye M. Johnson. HBWatER is currently sustained by Tammy Wooster (Cary IES) and Jeff Merriam (USFS) and the dataset is curated and maintained by a team of researchers: Chris Solomon (Cary IES), Emma Rosi (Cary IES), Emily Bernhardt (Duke), Lindsey Rustad (USFS), John Campbell (USFS), Bill McDowell (UNH), Charley Driscoll (Syracuse U.), Mark Green (Case Western), and Scott Bailey (USFS). Current Financial Support for HBWatER is provided by NSF LTREB # 1907683 and the USDA Forest Service Northern Research Station. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the US Forest Service, Northern Research Station.
Global Extra-tropical Circulation Database based on the Jenkinson-Collison Classification calculated with 6-hourly mean sea-level pressure fields from various reanalysis datasets
<h1>Dataset Description</h1> <p>Global Extra-tropical Circulation Database based on the Jenkinson-Collison Classification calculated with 6-hourly mean sea-level pressure fields from several reanalysis datasets. This dataset is the result of an extension of the Jenkinson-Collison circulation type classification to the entire globe, including a modification of its original formulation for the southern hemisphere.</p> <p>A modified version of the IPCC-AR6 Reference Regions that excludes the intertropical range where the method is not applicable is also included, as used in the reference paper for global assessment.</p> <p>Further details in <a href="https://doi.org/10.1007/s00382-022-06658-7" target="_blank" rel="noopener">https://doi.org/10.1007/s00382-022-06658-7 </a></p> <h2>Note for version 1.1.0</h2> <p>This version corrects an issue in the previous release, which was incorrectly labeled as <em>version 0.1</em>. That version was incomplete due to the omission of previously existing files, and should be considered <strong>incomplete</strong>. Version 1.1.0 restores all original files alongside the newly added one, ensuring the dataset is now complete and consistent. We apologize for any inconvenience this may have caused and appreciate your understanding.</p>
Database of measurements for damage detection of T-type timber structural joint by Coaxial Correlation Method in 6-D space
<p>This database includes series of measurements of the structure's response taken in six-dimensional space using two 6D sensors, coaxially positioned on either side of the investigated joint between two timber beams connected at an angle of 90⁰. Presented data related to seven different states of joints, five load levels, and two type of input signal (short impulse and sweep signal with duration 0.5 seconds). In the "<strong>Read_me_first.pdf</strong>" is described the experiment, the format of .csv files names and files' structure.</p>
CMS 2011A Simulation | Pythia 6 QCD1800-inf | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.CX2X.J3KW">Simulated QCD 1800-<span class="math-tex">\(\infty\)</span> Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 1400-1800 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.RC9V.B5KX">Simulated QCD 1400-1800 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 1000-1400 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.96U2.3YAH">Simulated QCD 1000-1400 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 800-1000 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.S3D5.KF2C">Simulated QCD 800-1000 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 470-600 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.BKTD.SGJX">Simulated QCD 470-600 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 300-470 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.X3XQ.USQR">Simulated QCD 300-470 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 170-300 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.WKRR.DCJP">Simulated QCD 170-300 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul>
CMS 2011A Simulation | Pythia 6 QCD 600-800 | pT > 375 GeV | MOD HDF5 Format
<p>Simulated QCD jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.EJT7.KSAY">Simulated QCD 600-800 Dataset of the CMS 2011 Open Data</a> reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}>375\)</span> GeV, where <span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have <span class="math-tex">\(|\eta^\text{jet}|<1.9\)</span> to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding datasets of simulated jets available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets 170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span> GeV</a></li> </ul> <p>There is an associated dataset of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets, pT > 375 GeV</a></li> </ul> <p>Changes:</p> <ul> <li>v1 - Uploaded missing file.</li> </ul>
Market Power / Import demand elasticity faced by an exporter at 6-digit HS level from Solleder (2020)
<p><strong>Description</strong></p> <p>This dataset contains the market power of exporters at the country level for more than 4000 6-digit HS codes (HS 1992 / H0) from Solleder (2020). Market power is proxied by the inverse of the import demand elasticity faced by the exporting country. Elasticities are estimated following the method developed by Kee et al. (2008). For more information, please refer to Solleder (2020).</p> <p>The <em>dta </em>file can be opened with STATA 14 or above. The <em>csv</em> file is a comma-separated value file. The separator is ',', and the first row is variable names. The content is the same in both files. Variables are:</p> <ul> <li><em>exporter</em>: ISO 3166 3-character country codes, string; </li> <li><em>commoditycode</em>: product 6-digit HS codes in HS revision 1992 (H0), string;</li> <li><em>epsilon</em>: import demand elasticity faced by the exporter, numeric;</li> <li><em>epsilon_se</em>: standard error of <em>epsilon</em>, numeric;</li> <li><em>marketpower</em>: market power, inverse of the absolute value of the import demand elasticity faced by the exporter, numeric.</li> </ul> <p> </p> <p><strong>Reference</strong></p> <div> <div>Kee H.L., A. Nicita, M. Olarreaga 2008 'Import demand elasticities and trade distortions' Rev. Econ. Stat., 90 (4), pp. 666-682</div> <div> </div> <div>Solleder J.M. 2020 'Market power and export taxes' European Economic Review, Volume 125, 103425, ISSN 0014-2921, <a href="https://doi.org/10.1016/j.euroecorev.2020.103425">https://doi.org/10.1016/j.euroecorev.2020.103425</a>.</div> </div> <p> </p>
Ecosystem metabolism and associated modeling parameters for 6 oligotrophic lakes and ponds in a single watershed
This dataset was collected as part of a watershed-scale study to assess impacts of smoke cover on water temperature and rates of ecosystem metabolism in small lakes and ponds. We measured thermal and metabolic responses to smoke in six waterbodies within a high-elevation watershed (watershed area 1908 ha; elevation range 2800-3229 m.a.s.l) located in Sequoia-Kings Canyon National Park in the Sierra Nevada Mountains of California. All lakes and ponds are oligotrophic, and range in maximum depth from 1.5m to 10m. The dataset includes: time series data of dissolved oxygen, water temperature, and environmental parameters relevant to modeling ecosystem metabolism; estimated rates of ecosystem metabolism using the Kalman filter method; descriptive site information including location, size, and depth.
Site Location and Environmental Characteristics for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Accoss Interior Alaska. Sampled in 2008-2010 and 2013-2015.
This dataset contains the GPS location, slope, orientation, elevation, forest type based on dominant tree biomass, Age, sampling year, total vascular cover, total lchen cover, deciduous index (Alexander et al. 2012, Ecosphere), basal area of black spruce, Alaska paper birch, trembling aspen, large deciduous shrubs and trembling aspen, organic layer depth, pH, heatload, approximated moisture class for all sites (Johnstone et al. 2008), gravimetric moisture content, and volumetric moisture content. This dataset was part of the site-level covariates used in a study of bryophyte post-fire succession in deciduous and coniferous successional trajectories. NOTE: there is some overlap between the >20 years old sites that were sampled by Heather Alexander with some of the data she submitted in relation to her 2012 Ecosphere paper.
Vegetation Data Collected with Point Frame for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Across Interior Alaska. Sampled in 2008-2010 and 2013-2015.
This dataset contains point frame data for vegetation less than 1.3 m, including vascular plants, bryophytes, lichens, leaf litter and bare ground, as well as species codes used, as described in Jean et al. 2017 Canadian Journal of Forest Research. Samples of all encountered unknown species were collected for identification in the lab. Bryophyte nomenclature followed Anderson et al. (1990).
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.