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opennotspecifiedFeb 2020View details →

FIG. 4 in A Target Enrichment Bait Set for Studying Relationships among Ostariophysan Fishes

FIG. 4. Maximum likelihood phylogenetic hypothesis of relationships among taxa comprising the loricarioid dataset with family names in color. Ictalurus punctatus is the outgroup taxon, and bootstrap support is indicated at each node. An asterisk by any taxon name indicates that these data were harvested, in silico, from existing genome assemblies, and the numbers in parentheses to the right of each taxon denote the count of loci enriched/harvested from that organism. See Data Accessibility for tree file.

Consistent set of atmospheric and oceanic angular momentum, 1994 - 2022

Data supplement for manuscript Kiani Shahvandi, M., Schindelegger, M., Börger, L., Mishra, S., & Soja, B. (2024). Revisiting the excitation of free core nutation. Journal of Geophysical Research: Solid Earth, 129, e2024JB029583. <a href="https://doi.org/10.1029/2024JB029583">https://doi.org/10.1029/2024JB029583</a>   Specifications for AAM: <ul> <li>Data source: Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2)</li> <li>Temporal resolution & coverage: 3 hourly, 1994--2022</li> <li>Units for mass and motion terms: kg*m^2*s^(-1)</li> <li>Processing: Stationary signals due to atmospheric tides have been removed</li> <li>Other processing steps: Mass terms include angular momentum changes associated with the ocean's inverted barometer (IB) response</li> </ul>   Specifications for OAM: <ul> <li>Derived from a barotropic ocean model simulation (the DEBOT model w/o data assimilation) using MERRA-2 atmospheric forcing</li> <li>Temporal resolution & coverage: 3 hourly, 1994--2022</li> <li>Units for mass and motion terms: kg*m^2*s^(-1)</li> <li>Processing: Stationary signals due to atmospheric tides have been removed</li> <li>Other processing steps: Angular momentum changes associated with the ocean's IB response are not part of OAM, but AAM (see above)</li> </ul>   For further information see ReadMe.txt.   Terms of usage: If you use the AAM time series, please cite:  Kiani Shahvandi, M., Schindelegger, M., Börger, L., Mishra, S., & Soja, B. (2024). Revisiting the excitation of free core nutation. Journal of Geophysical Research: Solid Earth, 129, e2024JB029583. <a href="https://doi.org/10.1029/2024JB029583">https://doi.org/10.1029/2024JB029583</a>   If you use the OAM time series, please cite:  Harker, A.A., Schindelegger, M., Ponte, R.M., Salstein, D.A., 2021. Modeling ocean-induced rapid Earth rotation variations: an update. J Geod 95, 110. https://doi.org/10.1007/s00190-021-01555-z   Please cite both papers if you use the AAM and OAM time series.   Contact: L. Börger (lboerger@igg.uni-bonn.de)

"Field integration of shoot gas exchange and leaf chlorophyll fluorescence measurements to study the long-term regulation of photosynthesis in situ" data set

The main data used in the "Field integration of shoot gas exchange and leaf chlorophyll fluorescence measurements to study the long-term regulation of photosynthesis in situ" publication, as well as the readme-file for the dataset. Supplementary figures are available at the Tree Physiology website.

opencc-by-4.0Jun 2024View details →

Virtual screening data sets for fragmented interaction fingerprint

Data sets containing docking poses, structure-activity relationship matrix (SARM) train-test splitting, and 2048 bits extended connectivity fingerprint (ECFP) descriptors for six biological targets. Poses were generated by employing molecular docking using Molecular Operating Environment (MOE) software. Details will be described in the original publication.

Fig. 5 in Setting the records straight: the ventral receptacle and the spermathecae of Piophila casei (Diptera: Piophilidae)

Fig. 5 Ventral receptacle of other Piophilidae. a Arctopiophila vulgaris. b Prochyliza nigriceps. c Prochyliza xanthostoma. d Protopiophila latipes (Meigen, 1838). The same magnification as Fig. 4a. Bars 200 μm

Fig. 4 in Setting the records straight: the ventral receptacle and the spermathecae of Piophila casei (Diptera: Piophilidae)

Fig. 4 Piophila casei female reproductive tract, specimen with surrounding tissues decomposed, micrograph with DIC. a Overview. b Ventral receptacle and adjacent structures. ag accessory gland, co common oviduct, sp spermatheca, spd spermathecal duct, sz likely spermatozoa within ventral receptacle, us unsclerotized spot, va vagina, vp vagina pouch, vr ventral receptacle, vrs ventral receptacle stalk; 1–3, three spiny spots near the orifice of the ventral receptacle. Bar: a 200 μm; b 50 μm

Fig. 1 in Setting the records straight: the ventral receptacle and the spermathecae of Piophila casei (Diptera: Piophilidae)

Fig. 1 Piophila casei female reproductive tract, illustration by Dufour (1844) retouched to enhance outlines, with revised terminology. a ovaries with ovarioles, b suspension ligaments of accessory glands, c lateral oviducts, d accessory glands, e spermathecae, f ventral receptacle, g anteroventral vagina pouch, h posterior part of vagina, i last preabdominal segment, j ovipositor, and k rectal ampulla containing four rectal papillae. Inserts: bottom left, spermatheca with its duct and surrounding tissues; bottom right, accessory gland with its duct. Dufour, L. (1844). Histoire des métamorphoses et de l'anatomie du Piophila petasionis. Annales des Sciences Naturelles, 1, Planche 16, Figs. 16, 19, and 20

Fig. 2 in Setting the records straight: the ventral receptacle and the spermathecae of Piophila casei (Diptera: Piophilidae)

Fig. 2 Piophila casei, ventral receptacle, poorly preserved specimen, stereoscope. a Female with ventral receptacle visible as a dark sphere within the last preabdominal segment. b Posterior abdomen enlarged. c, d Two aspects of the cleared ventral receptacle after dissection. Solid arrow, ventral receptacle; dotted arrow, unsclerotized spot on ventral receptacle. Bar: a 2 mm; b 400 μm; c, d 100 μm

opencc-by-4.0Jun 2024View details →

Data set for the manuscript 'Leveraging pleiotropy identifies common-variant associations with selective IgA deficiency'

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Weak Exchange Interactions in Multispin Systems: EPR Studies of Metalloporphyrins Decorated with {Cr7Ni} Rings. Open data set

Data supporting the original figures 2, 3, 4b, 5, and 6 of the related publication.

Land surface phenology derived from 3 sets of vegetation indices

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opencc-by-nc-nd-4.0Aug 2024View details →

Key SOILL actions to consider for proposals when setting up Soil Health Living Labs (SHLLs) & Lighthouses (LHs)

The infographic "Key SOILL Actions to Consider for Proposals When Setting Up Soil Health Living Labs (SHLLs) & Lighthouses (LHs)" provides a strategic overview for potential applicants to the Horizon Europe topics funding the establishement of the Soil Health Living Labs on the essential activities and commitments required for effective participation in the SOILL, the EU-funded Support Structure for the Soil Health Living Labs and Lighthouses. Designed in response to a need highlighted by the key stakeholders, this visual guide ensures that applicants consider the necessary time and budget for involvement in SOILL events, training, and collaborative efforts. The infographic categorises actions into in-person, in-person/online, and online-only engagements, offering a clear understanding for integrating these elements into the proposals. This tool has been realised with aim to fulfil the SOILL and NATI00NS project's missions, aiding in the preparation and alignment of SHLL/LH proposals with SOILL's overarching goals.

Data from: Lupus and inflammatory bowel disease share a common set of microbiome features distinct from other autoimmune disorders

Supplemental data for "Lupus and inflammatory bowel disease share a common set of microbiome features distinct from other autoimmune disorders"

Verus: A Practical Foundation for Systems Verification -- Artifact -- Set 2 Screen Capture

A screen capture of the experiment in Set 2 of the artifact for the SOSP24 conditionally accepted paper "Verus: A Practical Foundation for Systems Verification": the experiment was performed on an Amazon AWS c5.4xlarge machine running Windows.

Regional-scale hydrologic settings buffer black spruce regeneration in the presence of post-fire droughts dataset

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opencc-by-4.0Feb 2023View details →

ITC data set of DNA binding by YdaT repressor from Escherichia coli O157:H7

Raw isothermal titration calorimetry data set from the published article Prolic-Kalinsek, M., Volkov, A. N., Hadzi, S., Van Dyck, J., Bervoets, I., Charlier, D. & Loris, R. Structural basis of DNA binding by YdaT, a functional equivalent of the CII repressor in the cryptic prophage CP-933P from Escherichia coli O157:H7. (2023). Acta Cryst. D79, 245-258. DOI: 10.1107/S2059798323001249. Concentrations in the files are expressed as monomer protein and duplex DNA. Titrations were measured at 25 °C. Buffer is 10 mM NaH2PO4, 10 mM Na2HPO4, 100 mM NaCl, 50 mM glutamic acid, 50 mM arginine pH 7.5.

Data sets and code for Sullivan and Koski "The role of photosynthetic response to environmental variation in shaping an elevational cline in leaf variegation"

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opencc-by-4.0Sep 2021View details →

ITC data set of nanobody (Nb33) binding to PaaR2 repressor truncates from Escherichia coli O157:H7

Raw isothermal titration calorimetry data set from the published article De Bruyn, P., Prolič-Kalin&scaron;ek, M., Vandervelde, A., Malfait, M., Sterckx, Y. G. J., Sobott, F., Hadži, S., Pardon, E., Steyaert, J., & Loris, R. (2021). Nanobody-aided crystallization of the transcription regulator PaaR2 from Escherichia coli O157:H7. Acta crystallographica. Section F, Structural biology communications, 77(Pt 10), 374–384. https://doi.org/10.1107/S2053230X21009006. Titrations were measured at different temperatures (5-37 °C, indicated in the file name). Concentrations are listed in each itc data file. Buffer is 10 mM NaH2PO4, 10 mM Na2HPO4, 150 mM NaCl, 0.01% Triton X-100, pH 7.5.

Source data sets_Figure 1, 2, 6_Salmonella cancer therapy metabolically disrupts tumours at the collateral cost of T cell immunity

Flow cytometry data files associated with Copland et al., Salmonella cancer therapy metabolically disrupts tumours at the collateral cost of T cell immunity. Data associated to Figures 1, 2 and 6.

Data Set for Probabilistic Indoor Temperature Forecasting

<h1>1. Dataset Manifest</h1> This text provides a description of the dataset used for model training and evaluation in our study "A Tutorial on Deep Learning for Probabilistic Indoor Temperature Forecasting". The dataset consists of various simulated thermal and environmental parameters for different room configurations. Below, you will find a table detailing each column in the dataset along with its description and unit of measurement.  <h2>1.1. Columns Description</h2> <table> <tbody> <tr> <th>Column Name</th> <th>Description</th> <th>Unit</th> </tr> <tr> <td><code>time</code></td> <td>Time stamp of the measurement</td> <td>-</td> </tr> <tr> <td><code>ZweiPersonenBuero.TAir</code></td> <td>Air temperature inside a two-person office</td> <td>°C</td> </tr> <tr> <td><code>heatStat.Heat.Q_flow</code></td> <td>Heating rate in the room</td> <td>W</td> </tr> <tr> <td><code>weaDat.AirPressure</code></td> <td>Atmospheric pressure</td> <td>Pa</td> </tr> <tr> <td><code>weaDat.AirTemp</code></td> <td>Outside air temperature</td> <td>°C</td> </tr> <tr> <td><code>weaDat.SkyRadiation</code></td> <td>Longwave sky radiation</td> <td>W/m²</td> </tr> <tr> <td><code>weaDat.TerrestrialRadiation</code></td> <td>Terrestrial radiation</td> <td>W/m²</td> </tr> <tr> <td><code>weaDat.WaterInAir</code></td> <td>Absolute humidity</td> <td>g/kg</td> </tr> <tr> <td><code>VAir</code></td> <td>Air volume in the room</td> <td>m³</td> </tr> <tr> <td><code>AExt0</code></td> <td>Exterior wall area facing the south</td> <td>m²</td> </tr> <tr> <td><code>AExt1</code></td> <td>Exterior wall area facing the north</td> <td>m²</td> </tr> <tr> <td><code>AInt</code></td> <td>Total interior wall area</td> <td>m²</td> </tr> <tr> <td><code>AFloor</code></td> <td>Floor area of the room</td> <td>m²</td> </tr> <tr> <td><code>AWin0</code></td> <td>Window area facing the south</td> <td>m²</td> </tr> <tr> <td><code>AWin1</code></td> <td>Window area facing the north</td> <td>m²</td> </tr> <tr> <td><code>azi0</code></td> <td>Azimuth (direction) of the first exterior wall</td> <td>rad</td> </tr> <tr> <td><code>azi1</code></td> <td>Azimuth (direction) of the second exterior wall</td> <td>rad</td> </tr> <tr> <td><code>id</code></td> <td>Unique identifier for the room configuration</td> <td>-</td> </tr> <tr> <td><code>is_holiday</code></td> <td>Indicator whether the day is a holiday (1 for yes, 0 for no)</td> <td>-</td> </tr> </tbody> </table> <h2>1.2. Note on Multi-Value Columns</h2> <div> For rooms with multiple exterior walls (rooms 15-30): <ul> <li>AExt: {Exterior wall 1 area, Exterior wall 2 area}</li> <li>AWin: {Window area on exterior wall 1, Window area on exterior wall 2}</li> <li>azi: {Azimuth of exterior wall 1, Azimuth of exterior wall 2}</li> </ul> Example: <ul> <li>AExt = {10, 15}</li> <li>AWin = {2, 0}</li> <li>azi = {0, 3.1415}</li> </ul> This indicates two exterior walls with areas of 10 m² and 15 m² facing south (0 rad) and north (3.1415 rad), respectively. The south-facing wall has a window of 2 m², while the north-facing wall has no window. <h2>1.3. Data Sources</h2> <div> <ul> <li>Room Model: Simulated using the reduced-order package of the Modelica Buildings Library.</li> <li>Weather Data: Provided by the German Meteorological Service (DWD) in Test Reference Year (TRY) format.</li> </ul> This comprehensive dataset provides crucial parameters required to train and evaluate thermal models for different room configurations. The simulation data ensures a diverse range of environmental and occupancy conditions, enhancing the robustness of the models. <h2>1.4. Data scaling</h2> The data set contains the raw data as well as the scaled data used for training and testing the model. The scaling was carried out using the <a href="https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html" target="_blank" rel="noopener">StandardScaler</a> package. <h2>1.5. Weather data license</h2> This data set contains weather data recorded by the DWD under license &bdquo;Datenlizenz Deutschland – Namensnennung – Version 2.0" (<a href="https://www.govdata.de/dl-de/by-2-0" target="_blank" rel="noopener">URL</a>). The data is provided by "<a href="https://www.bbsr.bund.de" target="_blank" rel="noopener">Bundesinstitut für Bau-, Stadt- und Raumforschung</a>". The data can be downloaded from <a href="https://www.bbsr.bund.de/BBSR/DE/forschung/programme/zb/Auftragsforschung/5EnergieKlimaBauen/2013/testreferenzjahre/01-start.html?pos=2" target="_blank" rel="noopener">here</a>. We use data from the year 2015 from Heilbronn. We have added the weather data to the data set unchanged. </div> </div>