Find research datasets worth reusing

opencc-by-4.0Jul 2016View details →

The Barton dataset for 23Na37Cl

The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/NaCl/23Na-37Cl/Barton. Please check the reference details according to the following description or directly from the website. NB: The html description skips data which are not included in the current version for the purpose of simplicity. Please check NaCl_23Na37Cl_Barton.md for detailed information. Definitions file <blockquote> 23Na-37Cl__Barton.def[4.65 KB] References: 1. Tennyson, J., Yurchenko, S. N., Al-Refaie, A. F., Clark, V. H. J., Chubb, K. L., Conway, E. K., Dewan, A., Gorman, M. N., Hill, C., Lynas-Gray, A. E., Mellor, T., McKemmish, L. K., Owens, A., Polyansky, O. L., Semenov, M., Somogyi, W., Tinetti, G., Upadhyay, A., Waldmann, I., Wang, Y., Wright, S., Yurchenko, O. P., "The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres", J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020). [<a href="https://doi.org/10.1016/j.jqsrt.2020.107228">https://doi.org/10.1016/j.jqsrt.2020.107228</a>] </blockquote> Spectroscopic Model <blockquote> <a href="https://exomol.com/models/NaCl/23Na-37Cl/Barton/">https://exomol.com/models/NaCl/23Na-37Cl/Barton/</a> </blockquote> Barton: line list Calculated line lists for NaCl and KCl <blockquote> NaCl_README__Barton.txt[1.8 KB] Documentation for the line list and partition function of the Barton NaCl data set. 23Na-37Cl__Barton.states.bz2[514.92 KB] States file for the Barton (23Na)(37Cl) calculated line list 23Na-37Cl__Barton.trans.bz2[8.03 MB] Transitions file for the Barton (23Na)(37Cl) calculated line list References: 1. Barton, E. J., Chui, C., Golpayegani, S., Yurchenko, S. N., Tennyson, J., Frohman, D. J., Bernath, P. F., "ExoMol molecular line lists V: The ro-vibrational spectra of NaCl and KCl", Monthly Notices of the Royal Astronomical Society 442, 1821-1829 (2014). <a href="[http://dx,doi,org/10.1093/mnras/stu944]">[http://dx,doi,org/10.1093/mnras/stu944]</a>[14BaChGo.NaCl] </blockquote> Barton: partition function Calculated line lists for NaCl and KCl <blockquote> NaCl_README__Barton.txt[1.8 KB] Documentation for the line list and partition function of the Barton NaCl data set. 23Na-37Cl__Barton.pf[73.24 KB] Partition function for (23Na)(37Cl) calculated from the energy levels of the Barton line list. References: 1. Barton, E. J., Chui, C., Golpayegani, S., Yurchenko, S. N., Tennyson, J., Frohman, D. J., Bernath, P. F., "ExoMol molecular line lists V: The ro-vibrational spectra of NaCl and KCl", Monthly Notices of the Royal Astronomical Society 442, 1821-1829 (2014). <a href="[http://dx,doi,org/10.1093/mnras/stu944]">[http://dx,doi,org/10.1093/mnras/stu944]</a>[14BaChGo.NaCl] </blockquote>

opencc-by-4.0Apr 2018View details →

The POKAZATEL dataset for 1H216O

The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/H2O/1H2-16O/POKAZATEL. Please check the reference details according to the following description or directly from the website. NB: The html description skips data which are not included in the current version for the purpose of simplicity. Please check H2O_1H216O_POKAZATEL.md for detailed information. Definitions file <blockquote> 1H2-16O__POKAZATEL.def[12.69 KB] References: 1. Tennyson, J., Yurchenko, S. N., Al-Refaie, A. F., Clark, V. H. J., Chubb, K. L., Conway, E. K., Dewan, A., Gorman, M. N., Hill, C., Lynas-Gray, A. E., Mellor, T., McKemmish, L. K., Owens, A., Polyansky, O. L., Semenov, M., Somogyi, W., Tinetti, G., Upadhyay, A., Waldmann, I., Wang, Y., Wright, S., Yurchenko, O. P., "The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres", J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020). [<a href="https://doi.org/10.1016/j.jqsrt.2020.107228">https://doi.org/10.1016/j.jqsrt.2020.107228</a>] </blockquote> Spectroscopic Model <blockquote> <a href="https://exomol.com/models/H2O/1H2-16O/POKAZATEL/">https://exomol.com/models/H2O/1H2-16O/POKAZATEL/</a> </blockquote> POKAZATEL: line list NB: These data are not included in the current version on Zenodo because the data are over Zenodo upload cap, 50GB Data can be accessed via: https://exomol.com/data/molecules/H2O/1H2-16O/POKAZATEL <blockquote> References: 1. Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., Tennyson, J., Yurchenko, S. N., Lodi, L., "ExoMol molecular line lists XXX: a complete high-accuracy line list for water", Monthly Notices of the Royal Astronomical Society 480, 2597-2608 (2018). <a href="[https://doi.org/10.1093/mnras/sty1877]">[https://doi.org/10.1093/mnras/sty1877]</a>[18PoKyZo.H2O] </blockquote> POKAZATEL: partition function The POKAZATEL calculated high-temperature water line list <blockquote> 1H2-16O__POKAZATEL.pf[253.91 KB] POKAZATEL (1H)2(16O) parition function References: 1. Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., Tennyson, J., Yurchenko, S. N., Lodi, L., "ExoMol molecular line lists XXX: a complete high-accuracy line list for water", Monthly Notices of the Royal Astronomical Society 480, 2597-2608 (2018). <a href="[https://doi.org/10.1093/mnras/sty1877]">[https://doi.org/10.1093/mnras/sty1877]</a>[18PoKyZo.H2O] </blockquote> POKAZATEL: super-line NB: These data are not included in current version on Zenodo Data can be accessed via: https://exomol.com/data/molecules/H2O/1H2-16O/POKAZATEL POKAZATEL: opacity The POKAZATEL calculated high-temperature water line list <blockquote> 1H2-16O__POKAZATEL__R1000_0.3-50mu.ktable.petitRADTRANS.h5[370.98 MB] petitRADTRANS k-tables at R= 1000 (0.3-50mu) in the HDF5 format: POKAZATEL (1H)2(16O) line list. 1H2-16O__POKAZATEL__R1000_0.3-50mu.ktable.ARCiS.fits.gz[443.73 MB] ARCiS k-tables at R= 1000 (0.3-50mu) in the fits format (gzipped): POKAZATEL (1H)2(16O) line list. 1H2-16O__POKAZATEL__R1000_0.3-50mu.ktable.NEMESIS.kta[232.01 MB] NEMESIS k-tables at R= 1000 (0.3-50mu) in the NEMESIS-kta format: POKAZATEL (1H)2(16O) line list. 1H2-16O__POKAZATEL__R15000_0.3-50mu.xsec.TauREx.h5[348.39 MB] TauREx cross sections at R= 15000 (0.3-50mu) in the HDF5 format: POKAZATEL (1H)2(16O) line list. References: 1. Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., Tennyson, J., Yurchenko, S. N., Lodi, L., "ExoMol molecular line lists XXX: a complete high-accuracy line list for water", Monthly Notices of the Royal Astronomical Society 480, 2597-2608 (2018). <a href="[https://doi.org/10.1093/mnras/sty1877]">[https://doi.org/10.1093/mnras/sty1877]</a>[18PoKyZo.H2O] 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). <a href="[http://dx.doi.org/10.1051/0004-6361/202038350]">[http://dx.doi.org/10.1051/0004-6361/202038350]</a>[20ChRoYu.] </blockquote>

opencc-by-4.0Feb 2022View details →

Data for Table S10 of the article "Source-to-sink aeolian fluxes from arid landscape dynamics in the Lut Desert"

Exhaustive list of the 227 individual denudation rates in arid areas compiled to estimate median denudation rate and sediment discharge for the internal river system of the Lut watershed.

Orbital- and Millennial-Scale Variability in Northwest African Dust Emissions Over the Past 67,000 years — Datasets

Title: Orbital- and Millennial-Scale Variability in Northwest African Dust Emissions Over the Past 67,000 years — Datasets Version: 1.0 Date of Release: December 06, 2021 Last Update: December 06, 2021 Identifier: 10.5281/zenodo.5652189 Permalink: <a href="https://doi.org/10.5281/zenodo.5652188">https://doi.org/10.5281/zenodo.5652188</a> Associated publication: Kinsley, C.W.; Bradtmiller, L.I.; McGee, D.; Galgay, M.; Stuut, J.-B.; Tjallingii, R.; Winckler, G.; deMenocal, P.B. 2021. Orbital- and Millennial-Scale Variability in Northwest African Dust Emissions Over the Past 67,000 years. Paleoceanography and Paleoclimatology. doi: <a href="https://doi.org/10.1002/essoar.10506290.1">10.1002/essoar.10506290.1</a> Link to publication preprint: <a href="https://doi.org/10.1002/essoar.10506290.1">https://doi.org/10.1002/essoar.10506290.1</a> Suggested citation: Please reference the associated publication above when using any datasets or materials in this repository. Contact information: Christopher W. Kinsley, ckinsley@mit.edu OR cwkinsley@gmail.com Dates of data collection and generation: August 2013 to February 2016 --------------- DESCRIPTION OF DATA This data repository contains the following datasets. We refer the user to the original manuscript (see above) and the text of the Supporting Information published alongside this manuscript for additional general information regarding the collection and generation of these data. DATA TABLES FOR ALL CORE SITES <ul> <li>Kinsley et al. (2021) P&P - Data Tables for OC437-7-GC-37 core - v1: This Excel workbook contains all data used in the study for the OC437-7-GC-37 core site, taken by the R/V Oceanus during the 2007 Changing Holocene Environments of the Eastern Tropical Atlantic (CHEETA) cruise. This includes the age control and age model, biogenic %s, U-Th isotopic measurements, grain size distributions and endmember modeling, and 230Th-normalized flux data. All previously published data is noted as such and referenced.</li> <li> Kinsley et al. (2021) P&P - Data Tables for OC437-7-GC-49 core - v1: This Excel workbook contains all data used in the study for the OC437-7-GC-49 core site, taken by the R/V Oceanus during the 2007 Changing Holocene Environments of the Eastern Tropical Atlantic (CHEETA) cruise. This includes the age control and age model, biogenic %s, U-Th isotopic measurements, grain size distributions and endmember modeling, and 230Th-normalized flux data. All previously published data is noted as such and referenced. </li> <li> Kinsley et al. (2021) P&P - Data Tables for OC437-7-GC-68 core - v1: This Excel workbook contains all data used in the study for the OC437-7-GC-68 core site, taken by the R/V Oceanus during the 2007 Changing Holocene Environments of the Eastern Tropical Atlantic (CHEETA) cruise. This includes the age control and age model, biogenic %s, U-Th isotopic measurements, grain size distributions and endmember modeling, and 230Th-normalized flux data. All previously published data is noted as such and referenced. </li> <li> Kinsley et al. (2021) P&P - Data Tables for ODP 108-658C core - v1: This Excel workbook contains all data used in the study for the ODP 108-658C core site, taken by the R/V JOIDES Resolution off Cap Blanc, Mauritania during Ocean Drilling Program Leg 108. This includes the age control and age model, biogenic %s, U-Th isotopic measurements, grain size distributions and endmember modeling, and 230Th-normalized flux data. All previously published data is noted as such and referenced. </li> </ul>

opencc-by-4.0Dec 2020View details →

Microbial narrow-escape is facilitated by wall interactions: Simulation Supplementary material

Simulation codes and simulation results for the paper "Microbial narrow-escape is facilitated by wall interactions".

opencc-by-4.0Feb 2021View details →

Quality-checked horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).

Dataset abstract Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present the finalised, quality-checked, horizontal particle flux data where counts have been averaged over a one-minute period. Dataset contents <ul> <li>SPC_HPF_windtrue_1min.csv, data file, comma-separated values</li> <li>SPC_HPF_windtrue_1min.png, metadata, portable network graphics</li> <li>SPC_HPF_windtrue_saveplot.py, script, Python code</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> Dataset license This quality-checked horizontal particle flux dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/

opencc-by-4.0Feb 2021View details →

Intermediate processing stage of horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).

Dataset abstract Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present an intermediate step in data processing, with relative horizontal particle flux of particles with a size between 36 – 2000 μm averaged over one-minute periods. Data are presented in daily files. Dataset contents <ul> <li>SPC_HPF_1min_YYYY_MM_DD.csv, data files, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> Dataset license This one-minute averaged horizontal particle flux dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/

Gamma dose rate monitoring using a Silicon Photomultiplier-based plastic scintillation detector

Data set in support of the publication "Gamma dose rate monitoring using a Silicon Photomultiplier-based plastic scintillation detector". It contains measurement campaign data, radionuclide sources data, measurement count rate per radionuclide.

opencc-by-4.0Dec 2019View details →

Antarctic Circumnavigation Expedition event log: recording data and sample collection in the Southern Ocean during the austral summer of 2016/17.

Dataset abstract The Antarctic Circumnavigation Expedition (ACE) spent 90 days circumnavigating Antarctica on the R/V Akademik Tryoshnikov during the austral summer of 2016/17. This dataset provides a record of the instrument deployments as well as dataset and sample collection events that took place during the expedition. Dataset contents <ul> <li>ace_events.csv, data file, comma-separated values</li> <li>sampling_method_descriptions.csv, metadata, comma-separated values</li> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> </ul> Dataset license This event log is made available under a Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/

Biomass Domestic Material Consumption by Country and over Time

Biomass domestic material consumption in thousand tons, and tons per capita for European countries. Our dataset has a 10.4% larger congruent dataset (to be used in various supervised or unsupervised learning models, such as machine learning) than the original Eurostat dataset after imputation, backcasting, forecasting.  It has overall 18% more observations after processing than the dataset at source.

Biomass Exports in Europe by Country

Biomass exports in thousand tons, and tons per capita for European countries. Our dataset has a 10.4% larger congruent dataset (to be used in various supervised or unsupervised learning models, such as machine learning) than the original Eurostat dataset after imputation, backcasting, forecasting.  It has overall 18% more observations after processing than the dataset at source.

Environmental Subsidies and Similar Transfers from Europe to the Rest of the World

Environmental subsidies and similar transfers (current, capital, tax abatement, subsidy) for all environmental protection and resource management activities from EU countries to the rest of the world. The original dataset is of Eurostat is plagued with missing data. Our version on the <a href="https://zenodo.org/communities/greendeal_observatory/">Green Deal Data Observatory</a>, though could be further improved, offers a 167% larger congruent data matrix for supervised or unsupervised learning (machine learning, regression analysis) than the <a href="https://ec.europa.eu/eurostat/databrowser/view/ENV_ESST_GG/default/table?lang=en">original dataset</a>: Environmental subsidies and similar transfers from general government, by environmental activity, sector of recipient and ESA category of transfer.

Hydrogeological data of groundwater and precipitation monitored in the Vögelsberg landslide catchment

Data contains hydrogeological data of precipitation and groundwater within the catchment of the Vögelsberg landslide (Tyrol, Austria) monitored between 2017-11-22 and 2021-07-05. The dataset provides time series of discharge, temperature, electrical conductivity and stable isotope ratios in groundwater and precipitation. Dataset is associated to following preprint: “Pfeiffer, J.; Zieher, T.; Schmieder, J.; Bogaard, T.; Rutzinger, M. and Spötl, C. (2021) Spatial assessment of probable recharge areas - Investigating the hydrogeological controls of an active deep-seated gravitational slope deformation, Natural Hazards and Earth System Sciences Discussions, Vol. 2021, p. 1-29, <a href="https://doi.org/10.5194/nhess-2021-388">https://doi.org/10.5194/nhess-2021-388</a>”. Accompanying readme file gives a detailed description of data fields contained in the published data.

Example Microscopy Metadata JSON files produced using Micro-Meta App to document example microscopy experiments performed at individual core facilities

Example Microscopy Metadata (Microscope.JSON and Settings.JSON) files produced using <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">Micro-Meta App</a> to document the Hardware Specifications of example Microscopes and the Image Acquisition Settings utilized to acquire example images as listed in the table below. <blockquote> For each facility, the dataset contains two JSON files: <ol> <li>Microscope.JSON file (e.g., 01_marcello_uliverpool_cci_zeiss_axioobserz1_lsm710.json)</li> <li>Settings.JSON file (indicated with the name of the image and with the _AS suffix)</li> </ol> </blockquote> Micro-Meta App was developed as part of a global community initiative including the <a href="http://www.4dnucleome.org/">4D Nucleome (4DN) </a>Imaging Working Group, BioImaging North America (BINA) <a href="https://www.bioimagingna.org/qc-dm-wg">Quality Control and Data Management Working Group</a>, and QUAlity and REProducibility for Instrument and Images in Light Microscopy (<a href="https://quarep.org/">QUAREP-LiMi</a>), to extend the Open Microscopy Environment (OME) <a href="https://www.openmicroscopy.org/Schemas/Documentation/Generated/OME-2016-06/ome.html">data model</a>. <blockquote> The works of this global community effort resulted in multiple publications featured on a recent Nature Methods FOCUS ISSUE dedicated to <a href="https://www.nature.com/collections/djiciihhjh">Reporting and reproducibility in microscopy</a>. </blockquote> <blockquote> Learn More! For a thorough description of Micro-Meta App consult our recent <a href="https://doi.org/10.1038/s41592-021-01315-z">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.05.31.446382">BioRxiv.org</a> publications! </blockquote>   <table> <tbody> <tr> <td>Nr.</td> <td>Manufacturer</td> <td>Model</td> <td>Tier</td> <td>Εxperiment Type</td> <td>Facility Name</td> <td>Department and Institution</td> <td>URL</td> <td>References</td> </tr> <tr> <td>1</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1 (with LSM 710 scan head)</td> <td>1</td> <td>3D visualization of superhydrophobic polymer-nanoparticles</td> <td>Centre for Cell Imaging (CCI)</td> <td>University of Liverpool</td> <td>https://cci.liv.ac.uk/equipment_710.html</td> <td>Upton et al., 2020</td> </tr> <tr> <td>2</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer (Axiovert 200M)</td> <td>2</td> <td>Μeasurement of illumination stability on Chinese Hamster Ovary cells expressing Paxillin-EGFP</td> <td>Advanced BioImaging Facility (ABIF).</td> <td>McGill University</td> <td>https://www.mcgill.ca/abif/equipment/axiovert-1</td> <td>Kiepas et al., 2020</td> </tr> <tr> <td>3</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1 (with Spinning Disk)</td> <td>2</td> <td>Immunofluorescence imaging of cryosection of Mouse kidney</td> <td>Imagerie Cellulaire; Quality Control managed by Miacellavie (https://miacellavie.com/)</td> <td>Centre de recherche du Centre Hospitalier Université de Montréal (CR CHUM), University of Montreal</td> <td>https://www.chumontreal.qc.ca/crchum/plateformes-et-services  (the web site is for all core facilities, not specifically for the core facility hosting this microscope)</td> <td>Pilliod et al., 2020</td> </tr> <tr> <td>4</td> <td>Carl Zeiss Microscopy</td> <td>Axio Imager Z2 (with Apotome)</td> <td>2</td> <td>Immunofluorescence imaging of mitotic division in Hela cells using  </td> <td>Bioimaging Unit</td> <td>Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/</td> <td>Watson et al., 2020</td> </tr> <tr> <td>5</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1</td> <td>2</td> <td>Fluorescence microscopy of human skin fibroblasts from Glycogen Storage Disease patients.</td> <td>Life Imaging Center (LIC)</td> <td>Centre for Integrative Signalling Analysis (CISA), University of Freiburg</td> <td>https://miap.eu/equipments/sd-i-abl/</td> <td>Hannibal et al., 2020</td> </tr> <tr> <td>6</td> <td>Leica Microsystems</td> <td>DMI6000B</td> <td>2</td> <td>3D immunofluorescence imaging  rhinovirus infected macrophages </td> <td>IMAG'IC Confocal Microscopy Facility</td> <td>Institut Cochin, CNRS, INSERM, Université de Paris</td> <td>https://www.institutcochin.fr/core_facilities/confocal-microscopy/cochin-imaging-photonic-microscopy/organigram_team/10054/view</td> <td>Jubrail et al., 2020</td> </tr> <tr> <td>7</td> <td>Leica Microsystems</td> <td>DM5500B</td> <td>2</td> <td>Immunofluorescence analysis of the colocalization of PML bodies with DNA double-strand breaks</td> <td>Bioimaging Unit</td> <td>Edwardson Building on the Campus for Ageing and Vitality, Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/equipment/leica-dm5500/#overview</td> <td>da Silva et al., 2019; Nelson et al., 2012   </td> </tr> <tr> <td>8</td> <td>Leica Microsystems</td> <td>DMI8-CS (with TCS SP8 STED 3X)</td> <td>2</td> <td>Live-cell imaging of N. benthamiana leaves cells-derived protoplasts</td> <td>Center for Advanced Imaging (CAi)</td> <td>School of Mathematics/Natural Sciences, Heinrich-Heine-Universität Düsseldorf</td> <td>https://www.cai.hhu.de/en/equipment/super-resolution-microscopy/leica-tcs-sp8-sted-3x</td> <td>Singer et al., 2017; Hänsch et al., 2020</td> </tr> <tr> <td>9</td> <td>Nikon Instruments</td> <td>Eclipse Ti</td> <td>2</td> <td>Immunofluorescence analysis of the cytoskeleton structure in COS cells</td> <td>Advanced Imaging Center (AIC)</td> <td>Janelia Research Campus, Howard Hughes Medical Institute</td> <td>https://www.janelia.org/support-team/light-microscopy/equipment</td> <td>Abdelfattah et al., 2019; Qian et al., 2019; Grimm et al., 2020</td> </tr> <tr> <td>10</td> <td>Nikon Instruments</td> <td>Eclipse Ti-E (HCA)</td> <td>2</td> <td>Τime-lapse analysis of the bursting behavior of amine-functionalized vesicular assemblies</td> <td>Light Microscopy Facility (IALS-LIF)</td> <td>Institute for Applied Life Sciences, University of Massachusetts at Amherst</td> <td>https://www.umass.edu/ials/light-microscopy</td> <td>Fernandez et al., 2020</td> </tr> <tr> <td>11</td> <td>Nikon Instruments/Coleman laboratory (customized)</td> <td>TIRF HILO Epifluorescence light Microscope (THEM)/ Eclipse Ti</td> <td>2</td> <td>Single-particle tracking of Halo-tagged PCNA in Lox cells</td> <td>Coleman laboratory</td> <td>Anatomy and Structural Biology Department, The Albert Einstein College of Medicine</td> <td>https://einsteinmed.org/faculty/12252/robert-coleman/</td> <td>Drosopoulos et al., 2020</td> </tr> <tr> <td>12</td> <td>Nikon Instruments</td> <td>Eclipse Ti (with Andor Dragon Fly Spinning Disk)</td> <td>2</td> <td>Investigation of the 3D structure of cerebral organoids</td> <td>Montpellier Resources Imagerie</td> <td>Centre de Recherche de Biologie cellulaire de Montpellier (MRI-CRBM), CNRS, Univerity of Montpellier</td> <td>https://www.mri.cnrs.fr/en/optical-imaging/our-facilities/mri-crbm.html</td> <td>Ayala-Nunez et al., 2019</td> </tr> <tr> <td>13</td> <td>Nikon Instruments</td> <td>Eclipse Ti2</td> <td>2</td> <td>Ιmmunofluorescence imaging of cryosections of mouse hearth myocardium </td> <td>Neuroscience Center Microscopy Core</td> <td>Neuroscience Center, University of North Carolina</td> <td>https://www.med.unc.edu/neuroscience/core-facilities/neuro-microscopy/</td> <td>Aghajanian et al., 2021</td> </tr> <tr> <td>14</td> <td>Nikon Instruments</td> <td>Eclipse Ti2</td> <td>2</td> <td>Live-cell imaging of bacterial cells expressing GFP-PopZ</td> <td>Microscopy Resources on the North Quad (MicRoN)</td> <td>Harvard Medical School </td> <td>https://micron.hms.harvard.edu/</td> <td>Lim and Bernhardt 2019; Lim et al., 2019</td> </tr> <tr> <td>15</td> <td>Olympus/Biomedical Imaging Group (customized)</td> <td>TIRF Epifluorescence Structured light Microscope (TESM)/IX71</td> <td>3</td> <td>3D distribution of HIV-1 in the nucleus of human cells</td> <td>Biomedical Imaging Group</td> <td>Program in Molecular Medicine, University of Massachusetts Medical School</td> <td>https://trello.com/b/BQ8zCcQC/tirf-epi-fluorescence-structured-light-microscope</td> <td>Navaroli et al., 2012</td> </tr> <tr> <td>16</td> <td>Olympus/Computer Vision Laboratory (customized)</td> <td>3D BrightField Scanner/IX71</td> <td>3</td> <td>Transmitted light brightfield visualization of swimming spermatocytes</td> <td>Laboratorio Nacional de Microscopia Avanzada (LNMA) and Computer Vision Laboratory of the Institute of Biotechnology</td> <td>Universidad Nacional Autonoma de Mexico (UNAM)</td> <td>https://lnma.unam.mx/wp/</td> <td>Pimentel et al., 2012; Silva-Villalobos et al., 2014</td> </tr> </tbody> </table> Getting started Use these videos to get started with using Micro-Meta App after installation into OMERO and downloading the example data files: <ol> <li><a href="https://vimeo.com/562022222">Video 1</a></li> <li><a href="https://vimeo.com/562022281">Video 2</a></li> </ol> More information <blockquote> For full information on how to use Micro-Meta App please utilize the following resources: <ol> <li>Micro-Meta App <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">website</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/index.html">Full documentation</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/intro/installation.html">Installation</a> instructions</li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/index.html#step-by-step-instructions">Step-by-Step Instructions</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/VideoTutorials.html#micro-meta-app-video-tutorials">Tutorial Videos</a></li> </ol> </blockquote> Background If you want to learn more about the importance of metadata and quality control to ensure full reproducibility, quality and scientific value in light microscopy, please take a look at our recent publications describing the development of community-driven light 4DN-BINA-OME Microscopy Metadata specifications <a href="https://doi.org/10.1038/s41592-021-01327-9">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.04.25.441198">BioRxiv.org</a> and our <a href="https://arxiv.org/abs/1910.11370">overview manuscript</a> entitled A perspective on Microscopy Metadata: data provenance and quality control.

opencc-by-4.0May 2021View details →

Example Microscopy Metadata JSON files produced using Micro-Meta App to document the acquisition of example images using a custom-built TIRF Epifluorescence Structured Illumination Microscope

Example Microscopy Metadata JSON files produced using the <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">Micro-Meta App</a> documenting an example raw-image file acquired using the custom-built TIRF Epifluorescence Structured Illumination Microscope. For this use case, which is presented in Figure 5 of <a href="http://doi: https://doi.org/10.1101/2021.05.31.446382">Rigano et al., 2021</a>, Micro-Meta App was utilized to document: 1) The Hardware Specifications of the custom build TIRF Epifluorescence Structured light Microscope (TESM; <a href="https://www.pnas.org/content/109/8/E471.long">Navaroli et al., 2010</a>) developed, built on the basis of the based on Olympus IX71 microscope stand, and owned by the Biomedical Imaging Group (http://big.umassmed.edu/) at the Program in Molecular Medicine of the University of Massachusetts Medical School. Because TESM was custom-built the most appropriate documentation level is Tier 3 (Manufacturing/Technical Development/Full Documentation) as specified by the <a href="https://doi.org/10.5281/zenodo.4710731">4DN-BINA-OME</a> Microscopy Metadata model (<a href="https://doi.org/10.1101/2021.04.25.441198">Hammer et al., 2021</a>). The TESM Hardware Specifications are stored in: Rigano et al._Figure 5_UseCase_Biomedical Imaging Group_TESM.JSON 2) The Image Acquisition Settings that were applied to the TESM microscope for the acquisition of an example image (FSWT-6hVirus-10minFIX-stk_4-EPI.tif.ome.tif) obtained by Nicholas Vecchietti and Caterina Strambio-De-Castillia. For this image, TZM-bl human cells were infected with HIV-1 retroviral three-part vector (FSWT+PAX2+pMD2.G). Six hours post-infection cells were fixed for 10 min with 1% formaldehyde in PBS, and permeabilized. Cells were stained with mouse anti-p24 primary antibody followed by DyLight488-anti-Mouse secondary antibody, to detect HIV-1 viral Capsid. In addition, cells were counterstained using rabbit anti-Lamin B1 primary antibody followed by DyLight649-anti-Rabbit secondary antibody, to visualize the nuclear envelope and with DAPI to visualize the nuclear chromosomal DNA. The Image Acquisition Settings used to acquire the FSWT-6hVirus-10minFIX-stk_4-EPI.tif.ome.tif image are stored in: Rigano et al._Figure 5_UseCase_AS_fswt-6hvirus-10minfix-stk_4-epi.tif.JSON Instructional video tutorials on how to use these example data files: Use these videos to get started with using Micro-Meta App after downloading the example data files available here. <ul> <li><a href="https://vimeo.com/562022222">Part 1/2</a></li> <li><a href="https://vimeo.com/562022281">Part 2/2</a></li> </ul>

Dataset of the article "Bayesian phylogenetics illuminate shallower relationships in Trans-Himalayan languages in Tibet-Arunachal area"

This repository archives the dataset of the article "Bayesian phylogenetics illuminate shallower relationships in Trans-Himalayan languages in Tibet-Arunachal area". The cognate annotation of Tshangla, Kho-Bwa, Hrusish, Mishmic, and Tani languages were done by us. The cognate decision on the other languages was annotated by Sagart et al. (2019).  Please use the following information to cite our work:  Wu, M.-S, Bodt, T. A, Tresoldi, T. (2022).  Bayesian phylogenetics illuminate shallower relationships Trans-Himalayan languages in the Tibet-Arunachal area. Linguistics of the Tibeto-Burman Area. [forthcoming]

Resilience estimates of Amazon and Congo rainforests based on mean annual precipitation and root zone storage capacity

Resilience refers to the capacity of the ecosystem to absorb perturbations and remain in its native stable state. Here, we quantified forest resilience of South American and African ecosystems using mean annual precipitation and root zone storage capacity (2000-2019). We adopted Hirota et al. (2011) methodology for calculating resilience using logistic regression.  This logistic regression predicts the probability of forest (tree cover > 50%) as a function of the independent variable. The predicted resilience estimates range between 0 to 1, where 1 represents the highest probability of finding forest – interpreted as highly resilient forest ecosystems. For more information, check: <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115">https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115</a>

opencc-by-4.0Jan 2021View details →

Safe Country Policies Dataset (SACOP)

The Safe Country Policies Dataset (SACOP) (Version 1.1) provides original information on the adoption and characteristics of Safe Country Policies and National Asylum Frameworks in 195 countries from 1951 until 2021. An interactive visualization by Andreas Perret (nccr – on the move) can be accessed <a href="https://tabsoft.co/3AUKrRu">here</a>.

Accounting for local temperature effect substantially alters afforestation patterns - data

Output data produced in "Accounting for local temperature effect substantially alters afforestation patterns" Contact: michael.gregory.windisch@alumni.ethz.ch Content: Output of the partial equilibrium model MAgPIE (https://github.com/magpiemodel/magpie) version v4.3.1-BGP (https://github.com/magpiemodel/magpie/tree/v4.3.1-BGP) documentation (<a href="https://rse.pik-potsdam.de/doc/magpie/4.3.1/">https://rse.pik-potsdam.de/doc/magpie/4.3.1/</a>). Archived are all runs performed to obtain data and figures for the main assessment (main_output.zip) and the two sensitivity experiments (sensitivity_output_globalTCRE.zip; sensitivity_output_plantation.zip).   Naming key: main_output control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS main_output experiment runs: BPHfillexp_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS sensitivity analysis for global TCRE control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS sensitivity analysis for global TCRE experiment runs: BPHfillexp_ann_bph_{SSP}_global_{TCRE uncertainty}_noBECCS sensitivity analysis for plantation A/R control runs: BPH_plant_nobgp_{SSP}_noBECCS sensitivity analysis for plantation A/R experiment runs: BPH_plant_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS

Tropical multi-datasource and multi-frequency temperature anomalies (TROPTEMP)

Multi-frequency temperature anomalies in the tropical region computed from the datasets: CPC, ECCO2_JPL cube92, J-OFURO, MODIS-Aqua, University of Delaware and Windsat.