cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14039327.v1
title: Metadata record for: An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

description: This dataset contains key characteristics about the data described in the Data Descriptor An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.14910147
title: Efficient light-harvesting of mesophotic corals is facilitated by coral optical traits

description: Sustained light-dependent coral reef communities can be found at a wide range of light environments extending from the sea level to as deep as 150 m (i.e., mesophotic). How mesophotic corals thrive despite extremely limited light conditions still requires further investigation. Here, we undertook a comprehensive ecophysiological and bio-optical study on four depth-generalist coral species aiming to delineate the functional role that optical trait-properties have in light-harvesting, at contrasting light regimes. We show that the optical traits of coral skeletons are adjusted to their ambient light conditions and complement the microalgal demands for sufficient light, thus exhibiting a spatially efficient photosymbiotic system. In contrast to shallow corals, mesophotic corals absorbed up to three-fold more light, resulting in excellent photosynthetic response under light conditions of only ~3% of the incident surface irradiance. The enhanced light-harvesting capacity of mesophotic corals was achieved by redistributing light in the coral skeleton through optical scattering, thereby facilitating light transport and absorption by densely pigmented host tissue. Our findings provide fundamental insight into the light-harvesting mechanisms underlying the productivity of mesophotic coral reef ecosystems, yet also raise concerns regarding their ability to withstand prolonged environmental disturbances.
DOI: 10.5281/zenodo.5070193
title: Pyrrhura cruentata SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.14910147.v1
title: Efficient light-harvesting of mesophotic corals is facilitated by coral optical traits

description: Sustained light-dependent coral reef communities can be found at a wide range of light environments extending from the sea level to as deep as 150 m (i.e., mesophotic). How mesophotic corals thrive despite extremely limited light conditions still requires further investigation. Here, we undertook a comprehensive ecophysiological and bio-optical study on four depth-generalist coral species aiming to delineate the functional role that optical trait-properties have in light-harvesting, at contrasting light regimes. We show that the optical traits of coral skeletons are adjusted to their ambient light conditions and complement the microalgal demands for sufficient light, thus exhibiting a spatially efficient photosymbiotic system. In contrast to shallow corals, mesophotic corals absorbed up to three-fold more light, resulting in excellent photosynthetic response under light conditions of only ~3% of the incident surface irradiance. The enhanced light-harvesting capacity of mesophotic corals was achieved by redistributing light in the coral skeleton through optical scattering, thereby facilitating light transport and absorption by densely pigmented host tissue. Our findings provide fundamental insight into the light-harvesting mechanisms underlying the productivity of mesophotic coral reef ecosystems, yet also raise concerns regarding their ability to withstand prolonged environmental disturbances.
DOI: 10.5281/zenodo.5070192
title: Pyrrhura cruentata SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.14357123
title: Metadata record for: Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users

description: This dataset contains key characteristics about the data described in the Data Descriptor Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.14357123.v1
title: Metadata record for: Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users

description: This dataset contains key characteristics about the data described in the Data Descriptor Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.5281/zenodo.5069683
title: fastPET-LD

description: In this challenge, we provide 2 training datasets of 68 cases each: the first one was acquired at Sheba medical center (Israel) nuclear medicine department with a very-short exposure of 30s pbp, while the second is the same data followed by a denoising step implemented by a fully convolutional Dnn architecture trained under perceptual loss [1,2]. The purpose of this challenge is the detection of “hot spots”, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by Dr. Liran Domachevsky, chair of nuclear medicine at Sheba medical center. It consists of a 3-D segmentation map of the hot spots as well as an Excel file containing the position and size of a 3D cuboid bounding box for each hot spot. Out of 68 cases, 55 with ground truth, for training, while 13 cases, the test set, are provided without ground truth.
DOI: 10.5281/zenodo.4756187
title: fastPET-LD

description: In this challenge, we provide 2 training datasets of 68 cases each: the first one was acquired at Sheba medical center (Israel) nuclear medicine department with a very-short exposure of 30s pbp, while the second is the same data followed by a denoising step implemented by a fully convolutional Dnn architecture trained under perceptual loss [1,2]. The purpose of this challenge is the detection of “hot spots”, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by Dr. Liran Domachevsky, chair of nuclear medicine at Sheba medical center. It consists of a 3-D segmentation map of the hot spots as well as an Excel file containing the position and size of a 3D cuboid bounding box for each hot spot. Out of 68 cases, 55 with ground truth, for training, while 13 cases, the test set, are provided without ground truth.
DOI: 10.48366/r109041
title: Comparison of methods for the quantification of VUV emission among various low pressure plasmas.

description: Low pressure plasmas, and in particular with low temperature, are intensively used in industrial applications. The presence of Vacuum Ultraviolet (high energy) photons is pervasive in these plasmas. The quantification of these photons is very relevant for the present and future applications. Comparison among various plasma discharges is endemically difficult due to the proliferation of methods in producing these plasmas.
DOI: 10.25646/8752
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.5036643
title: Dataset for: Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning

description: Dataset for: Importance of satellite observations for high-resolution mapping of near-surface NO<sub>2 </sub>by machine learning This dataset is uploaded as a part of the article by Kim et al. (2021). The dataset is the hourly maps of near-surface nitrogen dioxide (NO<sub>2</sub>) concentrations at 100 m resolution for an Alpine domain (Switzerland and northern Italy, 6-12 °E, 42-48 °N). The dataset is provided per day (24 hours) in a netcdf (*.nc ~550MB). In this work, we have generated NO<sub>2 </sub>hourly maps for Feb. 2019 to May 2020 and, here, we upload for March 2019 only (~16 GB). If you need data for another period of time, please contact Gerrit Kuhlmann (gerrit.kuhlmann@empa.ch) or Minsu Kim (minsu.kim@empa.ch).
description: {"references": ["Minsu Kim, Dominik Brunner, Gerrit Kuhlmann (2021) Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning, Remote sensing of Environment DOI: https://doi.org/10.1016/j.rse.2021.112573"]}
DOI: 10.5281/zenodo.5036642
title: Dataset for: Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning

description: Dataset for: Importance of satellite observations for high-resolution mapping of near-surface NO<sub>2 </sub>by machine learning This dataset is uploaded as a part of the article by Kim et al. (2021). The dataset is the hourly maps of near-surface nitrogen dioxide (NO<sub>2</sub>) concentrations at 100 m resolution for an Alpine domain (Switzerland and northern Italy, 6-12 °E, 42-48 °N). The dataset is provided per day (24 hours) in a netcdf (*.nc ~550MB). In this work, we have generated NO<sub>2 </sub>hourly maps for Feb. 2019 to May 2020 and, here, we upload for March 2019 only (~16 GB). If you need data for another period of time, please contact Gerrit Kuhlmann (gerrit.kuhlmann@empa.ch) or Minsu Kim (minsu.kim@empa.ch).
description: {"references": ["Minsu Kim, Dominik Brunner, Gerrit Kuhlmann (2021) Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning, Remote sensing of Environment DOI: https://doi.org/10.1016/j.rse.2021.112573"]}
DOI: 10.5281/zenodo.5070215
title: Race against time? Interrelationships between children, time, work-life balance and technology

description: Research proposal of a recently finished mixed methods project on parents and adolescents Hungarian National Research Development and Innovation Office, Grant K120086 Principal investigator: Beáta Nagy
DOI: 10.5281/zenodo.5070214
title: Race against time? Interrelationships between children, time, work-life balance and technology

description: Research proposal of a recently finished mixed methods project on parents and adolescents Hungarian National Research Development and Innovation Office, Grant K120086 Principal investigator: Beáta Nagy
DOI: 10.15468/b55y9x
title: Isbrueckerichthys epakmos, a new species of loricariid catfish from the rio Ribeira de Iguape basin, Brazil (Teleostei: Siluriformes)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Pereira, Edson H. L., Oyakawa, Osvaldo T. (2003): Isbrueckerichthys epakmos, a new species of loricariid catfish from the rio Ribeira de Iguape basin, Brazil (Teleostei: Siluriformes). Neotropical Ichthyology 1 (1): 3-9, DOI: 10.1590/S1679-62252003000100001, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252003000100001&lng=en&tlng=en
DOI: 10.5281/zenodo.5070151
title: Supplementary material for "Learning Boolean controls in regulated metabolic networks: a case-study"

description: This record contains notebooks and Docker image for reproducing the learning of Boolean controls in regulated metabolic networks, and the case study presented in the CMSB 2021 conference proceeding article "Learning Boolean controls in regulated metabolic networks: a case-study". Visualize notebooks online: CaseStudy-Simulations.ipynb CaseStudy-SearchSpace.ipynb CaseStudy-Inference.ipynb Notebooks can be executed interactively within the Docker image <code>bioasp/boolean-caspo-flux:cmsb2021 </code>which extends the CoLoMoTo Docker version <code>2021-02-01.</code> Alternatively, they can be executed without any installation at https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/. The Docker image can be executed as follows: <pre><code class="language-bash">docker pull bioasp/boolean-caspo-flux:cmsb2021 docker run -it --rm -p 8888:8888 bioasp/boolean-caspo-flux:cmsb2021 </code></pre> then point your browser to http://127.0.0.1:8888. The image can be imported using the command <code>docker load</code> with the image file provided in this record: <pre><code>docker load -i image.tar.gz</code></pre> or with the <code>donodo</code> command available at https://github.com/pauleve/donodo: <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.5070151</code></pre>
DOI: 10.5281/zenodo.5060984
title: Supplementary material for "Learning Boolean controls in regulated metabolic networks: a case-study"

description: This record contains notebooks and Docker image for reproducing the learning of Boolean controls in regulated metabolic networks, and the case study presented in the CMSB 2021 conference proceeding article "Learning Boolean controls in regulated metabolic networks: a case-study". Visualize notebooks online: CaseStudy-Simulations.ipynb CaseStudy-SearchSpace.ipynb CaseStudy-Inference.ipynb Notebooks can be executed interactively within the Docker image <code>bioasp/boolean-caspo-flux:cmsb2021 </code>which extends the CoLoMoTo Docker version <code>2021-02-01.</code> Alternatively, they can be executed without any installation at https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/. The Docker image can be executed as follows: <pre><code class="language-bash">docker pull bioasp/boolean-caspo-flux:cmsb2021 docker run -it --rm -p 8888:8888 bioasp/boolean-caspo-flux:cmsb2021 </code></pre> then point your browser to http://127.0.0.1:8888. The image can be imported using the command <code>docker load</code> with the image file provided in this record: <pre><code>docker load -i image.tar.gz</code></pre> or with the <code>donodo</code> command available at https://github.com/pauleve/donodo: <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.5070151</code></pre>
DOI: 10.5281/zenodo.5070235
title: Practitioners Interpretation of conditional Requirements

description: This dataset contains (1) the survey protocol and (2) the survey responses of the study on how practitioners interpret conditional requirements. A readme provides guidance on how to comprehend the data.
DOI: 10.5281/zenodo.5040640
title: Practitioners Interpretation of conditional Requirements

description: This dataset contains (1) the survey protocol and (2) the survey responses of the study on how practitioners interpret conditional requirements. A readme provides guidance on how to comprehend the data.
DOI: 10.5281/zenodo.4417458
title: SGD-SM: Generating Seamless Global Daily AMSR2 Soil Moisture Long-term Products (2013-2019)

description: <strong>If you used our dataset, please cite our reference:</strong> <strong>Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., and Zhang, L.: Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019, Earth Syst. Sci. Data, 13, 1385–1401, https://doi.org/10.5194/essd-13-1385-2021, 2021.</strong> <strong>Description:</strong> A <strong>seamless global daily</strong> (<strong>SGD</strong>) AMSR2 soil moisture long-term (2013-2019) dataset is generated through the proposed model. This daily products include <strong>2553</strong> global soil moisture NetCDF4 files, starting from Jan 01, 2013 to Dec 31, 2019 (about <strong>20GB</strong> memory after uncompressing this zip file). To further validate the effectiveness of these products, three verification ways are employed as follow: 1) In-situ validation; 2) Time-series validation; And 3) simulated missing regions validation. More validation results can be viewed at <strong>SGD-SM</strong>. An example Python code of extracting this dataset is also available at <strong>https://github.com/qzhang95/SGD-SM</strong>. Official LPRM AMSR2 Descending L3 soil moisture products indeed only have 28 daily files in May 2013 (missing data files in date May 11, May 12, and May 13). This soil moisture dataset is comprised of netCDF4 (*.nc) files. Therefore, users need to install <strong>netCDF4</strong> toolkit before reading the data: <pre><code class="language-python">pip install netCDF4 pip install numpy</code></pre> It should be noted that the original and reconstructed soil moisture data are both recorded in one NC file. User can read the original data, reconstructed data, and mask data as follows: <pre><code class="language-python">Data = nc.Dataset(NC_file_position) Ori_data = Data.variables['original_sm_c1'] Rec_data = Data.variables['reconstructed_sm_c1'] Ori = Ori_data[0:720, 0:1440] Rec = Rec_data[0:720, 0:1440] Mask_ori = np.ma.getmask(Ori)</code></pre>
description: {"references": ["Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., and Zhang, L.: Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013\u20132019, Earth Syst. Sci. Data, 13, 1385\u20131401, https://doi.org/10.5194/essd-13-1385-2021, 2021."]}
DOI: 10.5281/zenodo.3960424
title: SGD-SM: Generating Seamless Global Daily AMSR2 Soil Moisture Long-term Products (2013-2019)

description: <strong>If you used our dataset, please cite our reference:</strong> <strong>Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., and Zhang, L.: Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019, Earth Syst. Sci. Data, 13, 1385–1401, https://doi.org/10.5194/essd-13-1385-2021, 2021.</strong> <strong>Description:</strong> A <strong>seamless global daily</strong> (<strong>SGD</strong>) AMSR2 soil moisture long-term (2013-2019) dataset is generated through the proposed model. This daily products include <strong>2553</strong> global soil moisture NetCDF4 files, starting from Jan 01, 2013 to Dec 31, 2019 (about <strong>20GB</strong> memory after uncompressing this zip file). To further validate the effectiveness of these products, three verification ways are employed as follow: 1) In-situ validation; 2) Time-series validation; And 3) simulated missing regions validation. More validation results can be viewed at <strong>SGD-SM</strong>. An example Python code of extracting this dataset is also available at <strong>https://github.com/qzhang95/SGD-SM</strong>. Official LPRM AMSR2 Descending L3 soil moisture products indeed only have 28 daily files in May 2013 (missing data files in date May 11, May 12, and May 13). This soil moisture dataset is comprised of netCDF4 (*.nc) files. Therefore, users need to install <strong>netCDF4</strong> toolkit before reading the data: <pre><code class="language-python">pip install netCDF4 pip install numpy</code></pre> It should be noted that the original and reconstructed soil moisture data are both recorded in one NC file. User can read the original data, reconstructed data, and mask data as follows: <pre><code class="language-python">Data = nc.Dataset(NC_file_position) Ori_data = Data.variables['original_sm_c1'] Rec_data = Data.variables['reconstructed_sm_c1'] Ori = Ori_data[0:720, 0:1440] Rec = Rec_data[0:720, 0:1440] Mask_ori = np.ma.getmask(Ori)</code></pre>
description: {"references": ["Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., and Zhang, L.: Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013\u20132019, Earth Syst. Sci. Data, 13, 1385\u20131401, https://doi.org/10.5194/essd-13-1385-2021, 2021."]}
DOI: 10.15468/qcu6b9
title: Three new species of Hyphessobrycon (Characiformes: Characidae) from the upper rio Araguaia basin in Brazil

description: This dataset contains the digitized treatments in Plazi based on the original journal article Lima, Flávio C. T., Moreira, Cristiano R. (2003): Three new species of Hyphessobrycon (Characiformes: Characidae) from the upper rio Araguaia basin in Brazil. Neotropical Ichthyology 1 (1): 21-33, DOI: 10.1590/S1679-62252003000100003, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252003000100003&lng=en&tlng=en
DOI: 10.15468/yzu9as
title: New characid fish, Hyphessobrycon scutulatus, from the rio Teles Pires drainage, upper rio Tapajós system (Ostariophysi: Characiformes: Characidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Lucena, Carlos Alberto Santos de (2003): New characid fish, Hyphessobrycon scutulatus, from the rio Teles Pires drainage, upper rio Tapajós system (Ostariophysi: Characiformes: Characidae). Neotropical Ichthyology 1 (2): 93-96, DOI: 10.1590/S1679-62252003000200003, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252003000200003&lng=en&tlng=en
DOI: 10.15468/wfp3gh
title: Austrolebias varzeae, a new annual fish from the upper rio Uruguay basin, southern Brazil (Cyprinodontiformes: Rivulidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Costa, Wilson J. E. M., Reis, Roberto E., Behr, Everton R. (2004): Austrolebias varzeae, a new annual fish from the upper rio Uruguay basin, southern Brazil (Cyprinodontiformes: Rivulidae). Neotropical Ichthyology 2 (1): 13-17, DOI: 10.1590/S1679-62252004000100003, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252004000100003&lng=en&tlng=en
DOI: 10.5281/zenodo.4696059
title: Synthetic building performance data

description: A dataset of uncertainty-infused synthetic building performance profiles as hallucinated by a generative adversarial network (GAN). This dataset includes both the original building performance data, as well as 50 synthetic performance scenarios that are generated by a GAN. Further details on the method and codes can be found here: https://github.com/Khayatian/seer
DOI: 10.15468/km5nxy
title: Two new species of Bryconamericus Eigenmann (Characiformes: Characidae) from southern Brazil

description: This dataset contains the digitized treatments in Plazi based on the original journal article Silva, José Francisco Pezzi da (2004): Two new species of Bryconamericus Eigenmann (Characiformes: Characidae) from southern Brazil. Neotropical Ichthyology 2 (2): 55-60, DOI: 10.1590/S1679-62252004000200002, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252004000200002&lng=en&tlng=en
DOI: 10.15468/wa6c6u
title: Acyrtus pauciradiatus, a new species of clingfish (Teleostei: Gobiesocidae) from Fernando de Noronha Archipelago, Pernambuco state, Northeastern Brazil

description: This dataset contains the digitized treatments in Plazi based on the original journal article Sampaio, Cláudio L. S., Nunes, José de Anchieta C. C., Mendes, Liana F. (2004): Acyrtus pauciradiatus, a new species of clingfish (Teleostei: Gobiesocidae) from Fernando de Noronha Archipelago, Pernambuco state, Northeastern Brazil. Neotropical Ichthyology 2 (4): 205-208, DOI: 10.1590/S1679-62252004000400002, URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-62252004000400002&lng=en&tlng=en
DOI: 10.6084/m9.figshare.13139351.v3
title: Contested Science: Individuals with higher metacognitive insight into interpretation of evidence are less likely to polarize

description: DataSet Metacognition and Belief Polarization<br>