cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7732547
title: Zinc Carbazole Diphosphonate

description: <em><strong>CAU-57</strong></em> The following submission contains the data collection and processing for the sample CAU-57 in the framework of the publication: <strong>Synthesis and Structure Evolution in Metal Carbazole Diphosphonates Followed by Electron Diffraction</strong>. Felix Steinke, Laura Gemmrich Hernandéz, Stephen J. I. Shearan, Maxi Pohlmann, Marco Taddei, Ute Kolb, and Norbert Stock. Inorganic Chemistry 2023 62 (1), 35-42. Precession Electron Diffraction (PED) was used to collect the dataset on the target crystal. The dataset was processed with PETS2 and eADT software. The table below summarizes the data collection parameters for the dataset. <strong>General information:</strong> Project NanED (www.naned.eu) ESR Project ESR8 Project Label CAU-57 Sample Label CAU-57 Data set Label ZnDPC_Cry7 <strong>Instrumental:</strong> Instrument FEI TECNAI F30 STWIN Radiation source FEG Accelerating voltage 300 kV Wavelength 0.0197 Å Probe Type Nanodiffraction Beam Diameter 200nm Beam Convergence Semi-parallel beam Detector US4000 - CCD camera GATAN (16-bit) (bottom mounted) Number of pixels in the image 2048 x 2048 Pixel size 15 µm x 15 µm Camera Length / Effective Camera Length 1500 mm / 1500 mm Calibration constant (not corrected for Effective Camera length) 0.00074 Å<sup>-1</sup>/pixel Hardware Binning 2 <strong>Sample description:</strong> Name CAU-57 Chemical composition [Zn<sub>6.75</sub>(H<sub>2</sub>O)<sub>1.5</sub>(HL)<sub>2.5</sub>(L)<sub>1.5</sub>]∙8H<sub>2</sub>O 3,6-diphosphono-9H-carbazole (H<sub>4</sub>L) Sample source Synthesized Sample preparation Grinded in an Agatha mortar and suspended in 1ml of EtOH. 4 µL of the suspension were dropped with a pipette on the carbon side of a carbon-coated copper grid (300 mesh). <strong>Experimental:</strong> Data Type Electron diffraction data - 3D ED Data collection method Precession Temperature (K) used during data collection 293 K Number of crystals contributing to the data set 1 Number of experimental frames 106 tilt range, tilt step, tilt per frame -45° to +60°, 1°, 0° Precession angle 1° Exposure time per frame 4 s <strong>Software:</strong> Software used for the data collection Gatan Digital Micrograph software Software used for processing PETS2 and eADT <strong>Authorship and bibliography</strong> Author(s) of the data Laura Gemmrich Hernández (ESR8) Related data CAU-37-as & CAU-37-act Publication(s) https://doi.org/10.1021/acs.inorgchem.2c02599 <strong>Files and data formats</strong> Image folder img: Folder containing images of the diffraction pattern from each frame. Image format tiff_16bit_unsigned
DOI: 10.5281/zenodo.7732545
title: Copper Carbazole Diphosphonate - 2

description: <em><strong>CAU-37-act</strong></em> The following submission contains the data collection and processing for the sample CAU-37-act in the framework of the publication: <strong>Synthesis and Structure Evolution in Metal Carbazole Diphosphonates Followed by Electron Diffraction</strong>. Felix Steinke, Laura Gemmrich Hernandéz, Stephen J. I. Shearan, Maxi Pohlmann, Marco Taddei, Ute Kolb, and Norbert Stock. Inorganic Chemistry 2023 62 (1), 35-42. Precession Electron Diffraction (PED) was used to collect the dataset on the target crystal. The dataset was processed with PETS2 and eADT software. The table below summarizes the data collection parameters for the dataset. <strong>General information:</strong> Project NanED (www.naned.eu) ESR Project ESR8 Project Label CAU-37 Sample Label CAU-37-act Data set Label CuDPC_Cry6 <strong>Instrumental:</strong> Instrument FEI TECNAI F30 STWIN Radiation source FEG Accelerating voltage 300 kV Wavelength 0.0197 Å Probe Type Nanodiffraction Beam Diameter 200nm Beam Convergence Semi-parallel beam Detector US4000 - CCD camera GATAN (16-bit) (bottom mounted) Number of pixels in the image 2048 x 2048 Pixel size 15 µm x 15 µm Camera Length / Effective Camera Length 1500 mm / 1500 mm Calibration constant (not corrected for Effective Camera length) 0.00074 Å<sup>-1</sup>/pixel Hardware Binning 2 <strong>Sample description:</strong> Name CAU-37-act Chemical composition [Cu<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>(L)]∙2H<sub>2</sub>O] 3,6-diphosphono-9H-carbazole (H<sub>4</sub>L) Sample source Synthesized Sample preparation Grinded in an Agatha mortar and suspended in 1ml of EtOH. 4 µL of the suspension were dropped with a pipette on the carbon side of a carbon-coated copper grid (300 mesh). <strong>Experimental:</strong> Data Type Electron diffraction data - 3D ED Data collection method Precession Temperature (K) used during data collection 293 K Number of crystals contributing to the data set 1 Number of experimental frames 121 tilt range, tilt step, tilt per frame -60° to +60°, 1°, 0° Precession angle 1° Exposure time per frame 4 s <strong>Software:</strong> Software used for the data collection Gatan Digital Micrograph software Software used for processing PETS2 and eADT <strong>Authorship and bibliography</strong> Author(s) of the data Laura Gemmrich Hernández (ESR8) Related data CAU-37-as & CAU-57 Publication(s) https://doi.org/10.1021/acs.inorgchem.2c02599 <strong>Files and data formats</strong> Image folder img: Folder containing images of the diffraction pattern from each frame. Image format tiff_16bit_unsigned
DOI: 10.5281/zenodo.7732544
title: Copper Carbazole Diphosphonate - 2

description: <em><strong>CAU-37-act</strong></em> The following submission contains the data collection and processing for the sample CAU-37-act in the framework of the publication: <strong>Synthesis and Structure Evolution in Metal Carbazole Diphosphonates Followed by Electron Diffraction</strong>. Felix Steinke, Laura Gemmrich Hernandéz, Stephen J. I. Shearan, Maxi Pohlmann, Marco Taddei, Ute Kolb, and Norbert Stock. Inorganic Chemistry 2023 62 (1), 35-42. Precession Electron Diffraction (PED) was used to collect the dataset on the target crystal. The dataset was processed with PETS2 and eADT software. The table below summarizes the data collection parameters for the dataset. <strong>General information:</strong> Project NanED (www.naned.eu) ESR Project ESR8 Project Label CAU-37 Sample Label CAU-37-act Data set Label CuDPC_Cry6 <strong>Instrumental:</strong> Instrument FEI TECNAI F30 STWIN Radiation source FEG Accelerating voltage 300 kV Wavelength 0.0197 Å Probe Type Nanodiffraction Beam Diameter 200nm Beam Convergence Semi-parallel beam Detector US4000 - CCD camera GATAN (16-bit) (bottom mounted) Number of pixels in the image 2048 x 2048 Pixel size 15 µm x 15 µm Camera Length / Effective Camera Length 1500 mm / 1500 mm Calibration constant (not corrected for Effective Camera length) 0.00074 Å<sup>-1</sup>/pixel Hardware Binning 2 <strong>Sample description:</strong> Name CAU-37-act Chemical composition [Cu<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>(L)]∙2H<sub>2</sub>O] 3,6-diphosphono-9H-carbazole (H<sub>4</sub>L) Sample source Synthesized Sample preparation Grinded in an Agatha mortar and suspended in 1ml of EtOH. 4 µL of the suspension were dropped with a pipette on the carbon side of a carbon-coated copper grid (300 mesh). <strong>Experimental:</strong> Data Type Electron diffraction data - 3D ED Data collection method Precession Temperature (K) used during data collection 293 K Number of crystals contributing to the data set 1 Number of experimental frames 121 tilt range, tilt step, tilt per frame -60° to +60°, 1°, 0° Precession angle 1° Exposure time per frame 4 s <strong>Software:</strong> Software used for the data collection Gatan Digital Micrograph software Software used for processing PETS2 and eADT <strong>Authorship and bibliography</strong> Author(s) of the data Laura Gemmrich Hernández (ESR8) Related data CAU-37-as & CAU-57 Publication(s) https://doi.org/10.1021/acs.inorgchem.2c02599 <strong>Files and data formats</strong> Image folder img: Folder containing images of the diffraction pattern from each frame. Image format tiff_16bit_unsigned
DOI: 10.5519/qd.y8rz80nf
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2037 records)
DOI: 10.34740/kaggle/dsv/5165398
title: AdultoMayor_17_fc
DOI: 10.6084/m9.figshare.22241077.v1
title: supplement.docx

description: <strong>Screening for primary aldosteronism on and off interfering medications</strong> <strong>Appendix </strong>
DOI: 10.5519/qd.7xz1z7kj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3001 records)
DOI: 10.6084/m9.figshare.22262476
title: Data for study

description: Responses to three scales, demographic and professional details, questionnaire
DOI: 10.6084/m9.figshare.22262476.v1
title: Questionnaire

description: Responses to three scales
DOI: 10.34740/kaggle/dsv/5165522
title: AdultoMayor_18_fc
DOI: 10.18712/nsd-nsd0472-v3
title: Leadership Survey 2000

description: In 1997, the Norwegian parliament decided to conduct a national democratic audit in Norway. The "Leadership survey", from which this dataset is derived from, constitutes a central part of this audit. The survey is conducted by Statistics Norway (SSB), and the Institute of Social Research (ISF) helped to coordinate.
The purpose of the Leadership survey has been to get insight in background and carreer pattern, contacts, the relationship between leaders in different societal areas, as well as the attitudes towards central social issues. 

The survey is divided into 6 parts:
1. Background and carreer
2. Perceptions and attituted
3. Gender equality
4. Contacts (generally and case-oriented)
5. Attitudes towards the political system and international cooperation
6. Media

The datamaterial is based on interviews of leaders within the following ten sectors:
1.  Research and higher education
2.  Defense
3.  Central administration
4.  Church
5.  Culture
6.  Media
7.  Business
8.  Organisations
9.  Politics
10. Police and judicial organs
DOI: 10.6084/m9.figshare.22269700
title: DF20_DF19_cumulated_Echo_Intentensities.xlsx

description: Here the cumulated echo intensities for each range gate of DF19 & DF20 can be found.
DOI: 10.6084/m9.figshare.22263505
title: Orthophorto.tif.ovr

description: Here you can find the spatial data of the field site in Gadria creek (IT)
DOI: 10.6084/m9.figshare.22269694
title: DF20_DF19_RG5_spectra.xlsx

description: Here the Doppler spectra of DF19 & DF20 from range gate 5 can be found.
DOI: 10.6084/m9.figshare.22269694.v1
title: DF20_DF19_RG5_spectra.xlsx

description: Here the Doppler spectra of DF19 & DF20 from range gate 5 can be found.
DOI: 10.6084/m9.figshare.22269703
title: DF20_DF19_velocities.xlsx

description: Here all binned velocity data from each range gate for DF19 & DF20 can be found.
DOI: 10.6084/m9.figshare.22269703.v1
title: DF20_DF19_velocities.xlsx

description: Here all binned velocity data from each range gate for DF19 & DF20 can be found.
DOI: 10.34740/kaggle/dsv/5165560
title: AdultoMayor_18_fc
DOI: 10.5281/zenodo.7699609
title: New York City Equitable Zoning

description: This dataset gives <strong>NYC Equitable Zoning (NYCEZ)</strong>, which is a zoning system of NYC derived from census tracts and ACS data with <strong>574 zones</strong>. The zoning system considers data reliability of 3 minority population groups: <strong>population below poverty level</strong>, <strong>seniors above 67</strong>, and <strong>long commuters (&gt;1 hour)</strong>. Underserved groups of interest include the population above 67 years old (seniors), the population under the poverty level, the population with a commute time above one hour, and the population with one or more disabilities. Only the former three groups are considered in zoning, since populations disabilities are already highly correlated with the others. The 2168 census tracts in NYC are aggregated to improve the data reliability of the 3 minority groups. Average margin of error (MOE) percentages at census tract level of population above 67, population below poverty level, and population with a commute time above 1 hour are <strong>15.22%</strong>, <strong>50.07%</strong>, and <strong>18.23%</strong>, respectively. After aggregation to the NYC Equitable Zones, MOE percentages become <strong>8.02%</strong>, <strong>12.33%</strong>, and <strong>9.88%</strong>, respectively. Equitable Zones shown in Figure 5 simultaneously reduces the average MOE percentage of demographic data by <strong>48% for seniors</strong>, <strong>75% for low-income population</strong>, and <strong>46% for long commuters</strong>. Files include: <strong>NYC census tracts shapefile with mapping to NYCEZ </strong>(“zoning” column) equitable_zoning_new_dissol.cpg equitable_zoning_new_dissol.dbf equitable_zoning_new_dissol.prj equitable_zoning_new_dissol.sbn equitable_zoning_new_dissol.sbx equitable_zoning_new_dissol.shp equitable_zoning_new_dissol.shx <strong>NYCEZ shapefile</strong> equitable_zoning_new.cpg equitable_zoning_new.dbf equitable_zoning_new.prj equitable_zoning_new.shp equitable_zoning_new.shx <strong>Data used for NYCEZ generation </strong>(from American Community Survey (ACS)) Number of seniors in each census tract (with 80 variance replicate estimates) data_elderly.csv Number of disabled in each census tract (with 80 variance replicate estimates) data_disabled.csv Number of long commuters in each census tract (with 80 variance replicate estimates) data_commute&gt;1h.csv Number of low incomers in each census tract (with 80 variance replicate estimates) data_below_poverty.csv Variance replicate estimates from ACS are used to MOE aggregation. Information can be found here: https://www.census.gov/programs-surveys/acs/data/variance-tables.html
DOI: 10.5281/zenodo.7733629
title: New York City Equitable Zoning

description: This dataset gives <strong>NYC Equitable Zoning (NYCEZ)</strong>, which is a zoning system of NYC derived from census tracts and ACS data with <strong>574 zones</strong>. The zoning system considers data reliability of 3 minority population groups: <strong>population below poverty level</strong>, <strong>seniors above 67</strong>, and <strong>long commuters (&gt;1 hour)</strong>. Underserved groups of interest include the population above 67 years old (seniors), the population under the poverty level, the population with a commute time above one hour, and the population with one or more disabilities. Only the former three groups are considered in zoning, since populations disabilities are already highly correlated with the others. The 2168 census tracts in NYC are aggregated to improve the data reliability of the 3 minority groups. Average margin of error (MOE) percentages at census tract level of population above 67, population below poverty level, and population with a commute time above 1 hour are <strong>15.22%</strong>, <strong>50.07%</strong>, and <strong>18.23%</strong>, respectively. After aggregation to the NYC Equitable Zones, MOE percentages become <strong>8.02%</strong>, <strong>12.33%</strong>, and <strong>9.88%</strong>, respectively. Equitable Zones shown in Figure 5 simultaneously reduces the average MOE percentage of demographic data by <strong>48% for seniors</strong>, <strong>75% for low-income population</strong>, and <strong>46% for long commuters</strong>. Files include: <strong>NYC census tracts shapefile with mapping to NYCEZ </strong>(“zoning” column) equitable_zoning_new_dissol.cpg equitable_zoning_new_dissol.dbf equitable_zoning_new_dissol.prj equitable_zoning_new_dissol.sbn equitable_zoning_new_dissol.sbx equitable_zoning_new_dissol.shp equitable_zoning_new_dissol.shx <strong>NYCEZ shapefile</strong> equitable_zoning_new.cpg equitable_zoning_new.dbf equitable_zoning_new.prj equitable_zoning_new.shp equitable_zoning_new.shx <strong>Data used for NYCEZ generation </strong>(from American Community Survey (ACS)) Number of seniors in each census tract (with 80 variance replicate estimates) data_elderly.csv Number of disabled in each census tract (with 80 variance replicate estimates) data_disabled.csv Number of long commuters in each census tract (with 80 variance replicate estimates) data_commute&gt;1h.csv Number of low incomers in each census tract (with 80 variance replicate estimates) data_below_poverty.csv Variance replicate estimates from ACS are used to MOE aggregation. Information can be found here: https://www.census.gov/programs-surveys/acs/data/variance-tables.html
DOI: 10.5281/zenodo.7733651
title: New York City Equitable Zoning

description: This dataset gives <strong>NYC Equitable Zoning (NYCEZ)</strong>, which is a zoning system of NYC derived from census tracts and ACS data with <strong>574 zones</strong>. The zoning system considers data reliability of 3 minority population groups: <strong>population below poverty level</strong>, <strong>seniors above 67</strong>, and <strong>long commuters (&gt;1 hour)</strong>. Underserved groups of interest include the population above 67 years old (seniors), the population under the poverty level, the population with a commute time above one hour, and the population with one or more disabilities. Only the former three groups are considered in zoning, since populations disabilities are already highly correlated with the others. The 2168 census tracts in NYC are aggregated to improve the data reliability of the 3 minority groups. Average margin of error (MOE) percentages at census tract level of population above 67, population below poverty level, and population with a commute time above 1 hour are <strong>15.22%</strong>, <strong>50.07%</strong>, and <strong>18.23%</strong>, respectively. After aggregation to the NYC Equitable Zones, MOE percentages become <strong>8.02%</strong>, <strong>12.33%</strong>, and <strong>9.88%</strong>, respectively. Equitable Zones shown in Figure 5 simultaneously reduces the average MOE percentage of demographic data by <strong>48% for seniors</strong>, <strong>75% for low-income population</strong>, and <strong>46% for long commuters</strong>. Files include: <strong>NYC census tracts shapefile with mapping to NYCEZ </strong>(“zoning” column) equitable_zoning_new_dissol.cpg equitable_zoning_new_dissol.dbf equitable_zoning_new_dissol.prj equitable_zoning_new_dissol.sbn equitable_zoning_new_dissol.sbx equitable_zoning_new_dissol.shp equitable_zoning_new_dissol.shx <strong>NYCEZ shapefile</strong> equitable_zoning_new.cpg equitable_zoning_new.dbf equitable_zoning_new.prj equitable_zoning_new.shp equitable_zoning_new.shx <strong>Data used for NYCEZ generation </strong>(from American Community Survey (ACS)) Number of seniors in each census tract (with 80 variance replicate estimates) data_elderly.csv Number of disabled in each census tract (with 80 variance replicate estimates) data_disabled.csv Number of long commuters in each census tract (with 80 variance replicate estimates) data_commute&gt;1h.csv Number of low incomers in each census tract (with 80 variance replicate estimates) data_below_poverty.csv Variance replicate estimates from ACS are used to MOE aggregation. Information can be found here: https://www.census.gov/programs-surveys/acs/data/variance-tables.html
DOI: 10.5281/zenodo.7699608
title: New York City Equitable Zoning

description: This dataset gives <strong>NYC Equitable Zoning (NYCEZ)</strong>, which is a zoning system of NYC derived from census tracts and ACS data with <strong>574 zones</strong>. The zoning system considers data reliability of 3 minority population groups: <strong>population below poverty level</strong>, <strong>seniors above 67</strong>, and <strong>long commuters (&gt;1 hour)</strong>. Underserved groups of interest include the population above 67 years old (seniors), the population under the poverty level, the population with a commute time above one hour, and the population with one or more disabilities. Only the former three groups are considered in zoning, since populations disabilities are already highly correlated with the others. The 2168 census tracts in NYC are aggregated to improve the data reliability of the 3 minority groups. Average margin of error (MOE) percentages at census tract level of population above 67, population below poverty level, and population with a commute time above 1 hour are <strong>15.22%</strong>, <strong>50.07%</strong>, and <strong>18.23%</strong>, respectively. After aggregation to the NYC Equitable Zones, MOE percentages become <strong>8.02%</strong>, <strong>12.33%</strong>, and <strong>9.88%</strong>, respectively. Equitable Zones shown in Figure 5 simultaneously reduces the average MOE percentage of demographic data by <strong>48% for seniors</strong>, <strong>75% for low-income population</strong>, and <strong>46% for long commuters</strong>. Files include: <strong>NYC census tracts shapefile with mapping to NYCEZ </strong>(“zoning” column) equitable_zoning_new_dissol.cpg equitable_zoning_new_dissol.dbf equitable_zoning_new_dissol.prj equitable_zoning_new_dissol.sbn equitable_zoning_new_dissol.sbx equitable_zoning_new_dissol.shp equitable_zoning_new_dissol.shx <strong>NYCEZ shapefile</strong> equitable_zoning_new.cpg equitable_zoning_new.dbf equitable_zoning_new.prj equitable_zoning_new.shp equitable_zoning_new.shx <strong>Data used for NYCEZ generation </strong>(from American Community Survey (ACS)) Number of seniors in each census tract (with 80 variance replicate estimates) data_elderly.csv Number of disabled in each census tract (with 80 variance replicate estimates) data_disabled.csv Number of long commuters in each census tract (with 80 variance replicate estimates) data_commute&gt;1h.csv Number of low incomers in each census tract (with 80 variance replicate estimates) data_below_poverty.csv Variance replicate estimates from ACS are used to MOE aggregation. Information can be found here: https://www.census.gov/programs-surveys/acs/data/variance-tables.html