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2,516 results for “Seri”
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 11
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 11 contains a stitched image montage of a thin section (selected area) through the lung of patient C05 which was acquired by scanning electron microscopy. The image shows a lung area with a dissolved alveolar architecture and a massive type-2-cell hyperplasia.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 10
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 10 contains stitched image montages of thin sections (selected areas) through the lung of patient C08 which were acquired by transmission electron microscopy. Cells, infected with SARS-CoV-2 particles, are shown in overview (A, C) and detail (B, C).</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 14
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 14 contains stitched image montages of a thin section through the lung of patient C04 which were acquired by scanning electron microscopy. The file “Data_set_14.tif” contains a montage of the entire thin section while the other files contain selected areas of the section recorded at higher resolution.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 09
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 09 contains stitched image montages of thin sections (selected areas) through the lung of patient C03 which were acquired by scanning electron microscopy (C03_A & C) or transmission electron microscopy (C03_B). The images show accumulation of cells and debris in the alveolar cavity.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 08
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 08 contains stitched image montages of thin sections (selected areas) through the lung of patients C04 and C08 which were acquired by scanning electron microscopy (C04) or transmission electron microscopy (C08_A & B). The images show the pathological changes of the alveolar epithelium: Type-1-cells detachment from the basal membrane (C08_A & B) and type-2-cell hyperplasia (C04).</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 07
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 07 contains stitched image montages of thin sections (selected areas) through the lung of patients C04 to C06 which were acquired by scanning electron microscopy. The images show alveolae with different degree of structural modification: Intact alveolar septum (C06); alveolar septum with detached alveolar epithelium (C04); dissolved alveolar organization (C05).</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 06
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 06 contains a stitched image montage of the first and of the last semithin section from the analysis of patient C08, which was acquired by bright-field light microscopy.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 05
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 05 contains a stitched image montage of the first and of the last semithin section from the analysis of patient C07, which was acquired by bright-field light microscopy.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 15
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 15 contains stitched image montages of a thin section through the lung of patient C05 which were acquired by scanning electron microscopy. The file “Data_set_15.tif” contains a montage of the entire thin section while the other files contain selected areas of the section recorded at higher resolution.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 13
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 13 contains stitched image montages of a thin section through the lung of patient C03 which were acquired by scanning electron microscopy. The file “Data_set_13.tif” contains a montage of the entire thin section while the other files contain selected areas of the section recorded at higher resolution.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 01
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 01 contains a stitched image montage of the first and of the last semithin section from the analysis of patient C03, which was acquired by bright-field light microscopy.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 02
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 02 contains a stitched image montage of the first and of the last semithin section from the analysis of patient C04, which was acquired by bright-field light microscopy.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 03
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 03 contains a stitched image montage of the first and of the last semithin section from the analysis of patient C05, which was acquired by bright-field light microscopy.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 18
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 18 contains stitched image montages of a thin section through the lung of patient C08 which were acquired by scanning electron microscopy. The file “Data_set_18.tif” contains a montage of the entire thin section while the other files contain selected areas of the section recorded at higher resolution.</p>
A detailed ultrastructural examination of lung cryobiopsy samples from a COVID-19 patient case series – Data set 17
<p>We investigated six cryobiopsy samples from six deceased patients (patients C03 to C08 from Barisione et al. 2020 <a href="https://doi.org/10.1007/s00428-020-02934-1">doi.org/10.1007/s00428-020-02934-1</a>) by using thin section electron microscopy (Cortese et al. 2022 <a href="http://doi.org/10.1007/s00428-022-03308-5">doi.org/10.1007/s00428-022-03308-5</a>). A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 17 contains stitched image montages of a thin section through the lung of patient C07 which were acquired by scanning electron microscopy. The file “Data_set_17.tif” contains a montage of the entire thin section while the other files contain selected areas of the section recorded at higher resolution.</p> <p> </p>
Research Space and DMPTool - Streamlining the research lifecycle and enhancing FAIR principles with a series of interoperable tools
<p>A video demonstration of the integration between the Electronic Lab Notebook, RSpace, and the DMPTool. Presented at the FORCE11 annual conference on December 7, 2021.</p>
Replication Package for the Paper: Transfer Learning with Time Series Data: A Systematic Mapping Study
<p>This is a replication package for the paper "Transfer Learning with Time Series Data: A Systematic Mapping Study".</p> <p>It provides</p> <ul> <li>a documentation of the conducted electronic literature search,</li> <li>exports of the search results from each literature database,</li> <li>and an excel file on the included literature and extracted data.</li> </ul>
GPS Time Series Kamchatka 2013
<p>GPS time series presented in the article: "Transient slab plunge prior to the Mw 8.3 2013 Okhotsk deep-focus earthquake"</p> <p>The columns of the files correspond to </p> <p>Year ; Month ; Day ; Hour ; Minute ; Second ; East position (mm) ; North position (mm) ; Up position (mm) ; East uncertainty (mm) ; North uncertainty (mm) ; Up uncertainty (mm) ;</p>
Analysis of the root diameter distribution from time series images of real and simulated Cassava root systems
<p>The data was collected, simulated and analyzed in the framework of the CassavaStore project (a collaboration between IBG-2, Forschungszentrum Jülich, Germany and different institution from Thailand; for details see <a href="https://www.international-bioeconomy.org/cassavastore_eng">https://www.international-bioeconomy.org/cassavastore_eng</a>). Aim of this project is to get a better understanding of storage root development in cassava (<em>Manihot esculenta</em> Crantz) in order to optimize cassava growth with respect to variety breeding and growth management. The storage root is one of the main providers of starch in Thailand and therefore of high economic importance. Monitoring the formation of storage roots over time via quantification of the root diameter distribution of excavated root systems was one of the key aspects addressed in this project. To measure the diameters a software was developed that identifies roots in RGB images and analyzes the diameters along each identified root automatically. The published data contains 1) analyzed images from cassava roots that were acquired in a video box; 2) simulated virtual root model images with known root diameter distributions that were used to validate the analysis approach; 3) a description of the data and the folder structure.</p>
1 km Monthly Precipitation Dataset for China from 1952 to 2019 (ChinaClim_time-series)
<p>ChinaClim_time-series is a monthly temperatures and precipitation dataset in China for the period of 1952-2019 of 1km spatial resolution, the data was generated by superimposing monthly anomaly surface and baseline climatology surface (ChinaClim_baseline) based on climatologically aided interpolation (CAI). The scale factor of the data is 0.1.</p>
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