cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12768539
title: CE_DeepCraters

description: # DeepCraters Lunar Craters Database 2020-07<br>This is a database of 117240 lunar impact craters larger than about 1 km in diameter. Craters were identified on 120m CE-1, 50m CE-2 DOM and DEM images captured by Chang’E-1 (CE-1) and Chang’E-2 (CE-2) orbiters. And that the formation Systems of new detected craters, 18,996 larger than 8km, are estimated.<br><br>## Method review<br>The database of 117240 lunar impact craters are identified by the trained R-FCN model and the age of craters is estimated by a dual-channel classification model with the semisupervised method. (the details of method can be found in our paper[1]).<br><br><br>## Briefly Description<br>The database contains two comma-delimited table files: `Lunar_Crater_Database_DeepCraters_2020.csv` and `Aged_Lunar_Crater_Database_DeepCraters_2020.csv`. <br><br>&gt; The first table is the detected craters larger than about 1 km in diameter, which contains 117240 craters with 5 common fields in each crater. What needs illustration is that the first 7009 craters contains additional 2 fields `Lat_new` and `Lon_new` because of the inaccuracy of the CE1 dataset. the details of each field are listed below:<br>&gt; - `Flags_data`: 'CE1' or 'CE2' indicats the crater detected from CE-1 or CE-2 data;<br>&gt; - `ID`: the index of craters;<br>&gt; - `Lat`: the latitude of crater center in degree;<br>&gt; - `Lon`: the longitude of crater center in degree;<br>&gt; - `Diam_km`: the diameter of crater in kilometer;<br>&gt; - `Lat_new`: the latitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree;<br>&gt; - `Lon_new`: the longitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree.<br>&gt;<br><br>&gt; The second table is the aged craters larger than 8 km in diameter, which contains 18996 craters with 6 fields in each craetr. And the first 5 fields are the same as in the first table, the last field `Age` indicates the system that the crater belongs to.<br>&gt;<br>&gt; - `Age`=1: pre-Nectarian System<br>&gt; - `Age`=2: Nectarian System<br>&gt; - `Age`=3: Imbrian System<br>&gt; - `Age`=4: Eratosthenian System <br>&gt; - `Age`=5: Copernican System<br><br><br><br>--------<br><br>## Note<br><br>The diameter of craters detected by DeepCraters is slightly larger than the real size of the craters. <br><br><br><br><br>## Reference<br>[1] Yang C , Zhao H , Bruzzone L , et al. Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning. [Online]. https://nature-research-under-consideration.nature.com/posts/57165-lunar-impact-craters-identification-and-age-estimation-with-chang-e-data-by-deep-and-transfer-learning.<br><br>[2] Robbins, S. J. A new global database of lunar impact craters &gt;1–2 km: 1. crater locations and sizes, comparisons with published databases, and global analysis. Journal of Geophysical Research (Planets),124(4), 871-892(2019).<br>
DOI: 10.6084/m9.figshare.12768479
title: A novel outlier-adapted multi-stage ensemble model with feature transformation for credit scoring

description: The raw data are divided into three parts: the Australian credit dataset (Australian.csv), the Japanese credit dataset (JapanData.csv), and the Polish credit dataset (Polish.csv). These raw data were downloaded from the UCI machine learning library.
DOI: 10.6084/m9.figshare.12768476
title: Probing co-evolution of ribosomal proteins through structural phylogeny

description: Ribosomes are highly conserved macromolecular machines at the domain level. This necessitates that ribosomal proteins also exhibit conservation in structure and function across genus and species. Specifically, ribosomal proteins are in contact with each other and ribosomal RNA (rRNA) in either the small or large ribosomal subunit. These contact points thus provide constraints in evolution and natural selection, and may have resulted in co-evolution. Given that coevolution between different ribosomal proteins could manifest as similarity in protein structure, the structures of the different ribosomal proteins could be obtained through a homology search server, Phyre<sup>2</sup> to provide the foundational data for a cross-comparison of ribosomal protein structure for understanding the selection pressure exerted on the ribosomal proteins. Specifically, multiple ribosomal proteins and rRNA interact with each other within the ribosome and the contact sites at which ribosomal protein and rRNA interact could serve as points at which selection pressure could tune the evolutionary trajectories of the ribosomal protein and rRNA. Thus, co-evolution between ribosomal proteins and between ribosomal proteins and rRNA would manifest as structural motifs tuned for binding with each other or where protein-protein and protein-rRNA interactions result in conserved structural motifs for interaction.
DOI: 10.6084/m9.figshare.12768449
title: air quality monitoring protocol amendment

description: Air quality reported under standard and actual conditions
DOI: 10.6084/m9.figshare.12768413
title: The catalytic dwell in ATPases is not crucial for movement against applied torque

description: Supporting pdb files and calculation input files for the paper. Check README for details.
DOI: 10.6084/m9.figshare.12768449.v1
title: air quality monitoring protocol amendment

description: Air quality reported under standard and actual conditions
DOI: 10.6084/m9.figshare.12768413.v2
title: The catalytic dwell in ATPases is not crucial for movement against applied torque

description: Supporting pdb files and calculation input files for the paper. Check README for details.
DOI: 10.6084/m9.figshare.12768347
title: Data set for Muslim study

description: Proportion of Muslim population, country IQ, three climatic variables, and six control aiables.<br>
DOI: 10.6084/m9.figshare.12768413.v1
title: The catalytic dwell in ATPases is not crucial for movement against applied torque

description: Supporting data files for the paper.
DOI: 10.6084/m9.figshare.12768347.v1
title: Data set for Muslim study

description: Proportion of Muslim population, country IQ, three climatic variables, and six control aiables.<br>
DOI: 10.6084/m9.figshare.12768332
title: Exercise influences the impact of polychlorinated biphenyl exposure on immune function

description: This study explores whether exercise can reverse or mitigate some of the adverse effects of PCBs by measuring wound healing times and analyzing cytokines.
DOI: 10.6084/m9.figshare.12768146
title: Extended data table 2

description: Known INSR binders detected by mass spectrometry.
DOI: 10.6084/m9.figshare.12768332.v1
title: Exercise influences the impact of polychlorinated biphenyl exposure on immune function

description: This study explores whether exercise can reverse or mitigate some of the adverse effects of PCBs by measuring wound healing times and analyzing cytokines.
DOI: 10.6084/m9.figshare.12768140
title: Extended data table 1

description: A table showing proteins association levels with the INSR during the experiment time course.
DOI: 10.6084/m9.figshare.12768140.v1
title: Extended data table 1

description: A table showing proteins association levels with the INSR during the experiment time course.
DOI: 10.6084/m9.figshare.12768146.v1
title: Extended data table 2

description: Known INSR binders detected by mass spectrometry.
DOI: 10.6084/m9.figshare.12768071
title: Supplementary Materials 1 from Biases in bulk: DNA metabarcoding of marine communities and the methodology involved

description: Dataset belonging to "Biases in bulk: DNA metabarcoding of marine communities and the methodology involved" Molecular Ecology (2020). LM van der Loos & R Nijland.<br>In order to synthesise and do a ‘stock take’ of recent approaches and methods used for DNA metabarcoding of bulk samples, we conducted a systematic literature survey. We searched the database Web of Science in April 2019 using the key words “DNA metabarcoding”, “marine”, “benthos”, “fauna”, “biodiversity”, “meiofauna”, “macrofauna”, “sediment”, “diet” and “hard substrate” in various combinations of 2-3 keywords, resulting in 518 returned records. Duplicate papers were removed as well as those that were not primary research articles, not published in peer-reviewed journals and not written in English. Following initial filtering, a total of 133 studies were considered for future reading, with data extracted only from papers that concerned (a) eukaryotic organisms; (b) organisms sampled in a marine environment, and (c) DNA metabarcoding of bulk samples. After excluding all studies that did not meet these criteria, 64 studies published between 2010 and 2019 were analysed. For each study, we extracted information about the sample type (plankton, soft sediment, hard substrate, or stomach content/faeces), the target species groups, sample pre-processing, the preservation method, the DNA extraction method, the selected markers (target DNA region and primers), the PCR thermal profile, the number of technical PCR replicates, and the sequencing platform used. This data is presented in the current table (Supplementary Materials 1).
DOI: 10.6084/m9.figshare.12768059
title: Larvicidal, but not ovicidal, activity of chlorantraniliprole on the potato tuber moth Tecia solanivora (Lepidoptera: Gelechiidae)

description: In this study, we evaluated the toxic effect of chlorantraniliprole against early immature stages of T. solanivora<br>
DOI: 10.6084/m9.figshare.12768023
title: Moral Vignettes, Iran

description: This dataset contains responses of 25 Iranian subjects to everyday moral dilemmas. The scenarios have been selected from Knutson et al.
DOI: 10.6084/m9.figshare.12768071.v1
title: Supplementary Materials 1 from Biases in bulk: DNA metabarcoding of marine communities and the methodology involved

description: Dataset belonging to "Biases in bulk: DNA metabarcoding of marine communities and the methodology involved" Molecular Ecology (2020). LM van der Loos & R Nijland.<br>In order to synthesise and do a ‘stock take’ of recent approaches and methods used for DNA metabarcoding of bulk samples, we conducted a systematic literature survey. We searched the database Web of Science in April 2019 using the key words “DNA metabarcoding”, “marine”, “benthos”, “fauna”, “biodiversity”, “meiofauna”, “macrofauna”, “sediment”, “diet” and “hard substrate” in various combinations of 2-3 keywords, resulting in 518 returned records. Duplicate papers were removed as well as those that were not primary research articles, not published in peer-reviewed journals and not written in English. Following initial filtering, a total of 133 studies were considered for future reading, with data extracted only from papers that concerned (a) eukaryotic organisms; (b) organisms sampled in a marine environment, and (c) DNA metabarcoding of bulk samples. After excluding all studies that did not meet these criteria, 64 studies published between 2010 and 2019 were analysed. For each study, we extracted information about the sample type (plankton, soft sediment, hard substrate, or stomach content/faeces), the target species groups, sample pre-processing, the preservation method, the DNA extraction method, the selected markers (target DNA region and primers), the PCR thermal profile, the number of technical PCR replicates, and the sequencing platform used. This data is presented in the current table (Supplementary Materials 1).
DOI: 10.6084/m9.figshare.12768023.v1
title: Moral Vignettes, Iran

description: This dataset contains responses of 25 Iranian subjects to everyday moral dilemmas. The scenarios have been selected from Knutson et al.
DOI: 10.6084/m9.figshare.12767447
title: Data Availability_Gerolamo et al. - American Journal of Botany 2020- Appendix S8.xlsx

description: <b>INTERSPECIFIC ANATOMICAL DIFFERENCES RESULT IN SIMILAR HIGHLY FLEXIBLE STEMS IN BIGNONIACEAE LIANAS</b>Gerolamo et al. - <i>American Journal of Botany</i> 2020 -Appendix S8. <b><br></b>Measurements of anatomical architecture and bending stiffness (structural Young's modulus) included light microscopy observations and three-point bending tests, which were performed on basal stems of eight individuals from four Bignonieae species.The dataset was collected in the field of the Ducke Reserve (Manaus, Brazil) and the anatomical procedures and analyses in Institute of Biosciences, Department of Botany, University of São Paulo (São Paulo, Brazil).More details are available in the associated paper in the American Journal of Botany.
DOI: 10.6084/m9.figshare.12766382
title: Growth Rate_ATCC 17978.xlsx

description: OD600 readings at varying timepoints in response to AZM exposure
DOI: 10.6084/m9.figshare.12766871
title: OD600 readings_ATCC 17978

description: OD600 readings of ATCC 17978 at harvested timepoint
DOI: 10.6084/m9.figshare.12766313
title: Exctrated Data - Literature Study.xlsx

description: A spreadsheet containing all the raw data extracted from the primary studies
DOI: 10.6084/m9.figshare.12766382.v1
title: Growth Rate_ATCC 17978.xlsx

description: OD600 readings at varying timepoints in response to AZM exposure
DOI: 10.6084/m9.figshare.12766871.v1
title: OD600 readings_ATCC 17978

description: OD600 readings of ATCC 17978 at harvested timepoint
DOI: 10.6084/m9.figshare.12767447.v2
title: Data Availability_Gerolamo et al. - American Journal of Botany 2020- Appendix S8.xlsx

description: <b>INTERSPECIFIC ANATOMICAL DIFFERENCES RESULT IN SIMILAR HIGHLY FLEXIBLE STEMS IN BIGNONIACEAE LIANAS</b>Gerolamo et al. - <i>American Journal of Botany</i> 2020 -Appendix S8. <b><br></b>Measurements of anatomical architecture and bending stiffness (structural Young's modulus) included light microscopy observations and three-point bending tests, which were performed on basal stems of eight individuals from four Bignonieae species.The dataset was collected in the field of the Ducke Reserve (Manaus, Brazil) and the anatomical procedures and analyses in Institute of Biosciences, Department of Botany, University of São Paulo (São Paulo, Brazil).More details are available in the associated paper in the American Journal of Botany.
DOI: 10.6084/m9.figshare.12766313.v1
title: Exctrated Data - Literature Study.xlsx

description: A spreadsheet containing all the raw data extracted from the primary studies
DOI: 10.6084/m9.figshare.12767447.v1
title: Data Availability_Gerolamo et al. - American Journal of Botany 2020- Appendix S8.xlsx

description: <b>INTERSPECIFIC ANATOMICAL DIFFERENCES RESULT IN SIMILAR HIGHLY FLEXIBLE STEMS IN BIGNONIACEAE LIANAS</b>Gerolamo et al. - <i>American Journal of Botany</i> 2020 -Appendix S8. <b><br></b>Measurements of anatomical architecture and bending stiffness (structural Young's modulus) included light microscopy observations and three-point bending tests, which were performed on basal stems of eight individuals from four Bignonieae species.The dataset was collected in the field of the Ducke Reserve (Manaus, Brazil) and the anatomical procedures and analyses in Institute of Biosciences, Department of Botany, University of São Paulo (São Paulo, Brazil).More details are available in the associated paper in the American Journal of Botany.
DOI: 10.6084/m9.figshare.12765989
title: Data --- Ion Pressure Evolution (Dynamic Magnetic, 0 Ei)

description: Ion Pressure Evolution (Dynamic Magnetic, 0 Ei)
DOI: 10.6084/m9.figshare.12765986
title: CE_DeepCraters

description: # DeepCraters Lunar Craters Database 2020-07<br>This is a database of 117240 lunar impact craters larger than about 1 km in diameter. Craters were identified on 120m CE-1, 50m CE-2 DOM and DEM images captured by Chang’E-1 (CE-1) and Chang’E-2 (CE-2) orbiters. And that the formation Systems of new detected craters, 18,996 larger than 8km, are estimated.<br><br>## Method review<br>The database of 117240 lunar impact craters are identified by the trained R-FCN model and the age of craters is estimated by a dual-channel classification model with the semisupervised method. (the details of method can be found in our paper[1]).<br><br><br>## Briefly Description<br>The database contains two comma-delimited table files: `Lunar_Crater_Database_DeepCraters_2020.csv` and `Aged_Lunar_Crater_Database_DeepCraters_2020.csv`. <br><br>&gt; The first table is the detected craters larger than about 1 km in diameter, which contains 117240 craters with 5 common fields in each crater. What needs illustration is that the first 7009 craters contains additional 2 fields `Lat_new` and `Lon_new` because of the inaccuracy of the CE1 dataset. the details of each field are listed below:<br>&gt; - `Flags_data`: 'CE1' or 'CE2' indicats the crater detected from CE-1 or CE-2 data;<br>&gt; - `ID`: the index of craters;<br>&gt; - `Lat`: the latitude of crater center in degree;<br>&gt; - `Lon`: the longitude of crater center in degree;<br>&gt; - `Diam_km`: the diameter of crater in kilometer;<br>&gt; - `Lat_new`: the latitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree;<br>&gt; - `Lon_new`: the longitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree.<br>&gt;<br><br>&gt; The second table is the aged craters larger than 8 km in diameter, which contains 18996 craters with 6 fields in each craetr. And the first 5 fields are the same as in the first table, the last field `Age` indicates the system that the crater belongs to.<br>&gt;<br>&gt; - `Age`=1: pre-Nectarian System<br>&gt; - `Age`=2: Nectarian System<br>&gt; - `Age`=3: Imbrian System<br>&gt; - `Age`=4: Eratosthenian System <br>&gt; - `Age`=5: Copernican System<br><br><br><br>--------<br><br>## Note<br><br>The diameter of craters detected by DeepCraters is slightly larger than the real size of the craters. <br><br><br><br><br>## Reference<br>[1] Yang C , Zhao H , Bruzzone L , et al. Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning. [Online]. https://nature-research-under-consideration.nature.com/posts/57165-lunar-impact-craters-identification-and-age-estimation-with-chang-e-data-by-deep-and-transfer-learning.<br><br>[2] Robbins, S. J. A new global database of lunar impact craters &gt;1–2 km: 1. crater locations and sizes, comparisons with published databases, and global analysis. Journal of Geophysical Research (Planets),124(4), 871-892(2019).<br><br><br>
DOI: 10.6084/m9.figshare.12765989.v1
title: Data --- Ion Pressure Evolution (Dynamic Magnetic, 0 Ei)

description: Ion Pressure Evolution (Dynamic Magnetic, 0 Ei)
DOI: 10.6084/m9.figshare.12765983
title: Table S1. Number of days with subzero air temperatures during the growing season at Utqiaġvik, AK.

description: Number of days with subzero air temperatures during the growing season at Utqiaġvik, AK.
DOI: 10.6084/m9.figshare.12765977
title: GilesData Figshare.csv

description: Landmark Data
DOI: 10.6084/m9.figshare.12765980
title: Data --- Ion Pressure Evolution (Static Magnetic, 0 Ei)

description: Ion Pressure Evolution (Static Magnetic, 0 Ei)
DOI: 10.6084/m9.figshare.12765983.v1
title: Table S1. Number of days with subzero air temperatures during the growing season at Utqiaġvik, AK.

description: Number of days with subzero air temperatures during the growing season at Utqiaġvik, AK.
DOI: 10.6084/m9.figshare.12765980.v1
title: Data --- Ion Pressure Evolution (Static Magnetic, 0 Ei)

description: Ion Pressure Evolution (Static Magnetic, 0 Ei)
DOI: 10.6084/m9.figshare.12765986.v2
title: CE_DeepCraters

description: # DeepCraters Lunar Craters Database 2020-07<br>This is a database of 117240 lunar impact craters larger than about 1 km in diameter. Craters were identified on 120m CE-1, 50m CE-2 DOM and DEM images captured by Chang’E-1 (CE-1) and Chang’E-2 (CE-2) orbiters. And that the formation Systems of new detected craters, 18,996 larger than 8km, are estimated.<br><br>## Method review<br>The database of 117240 lunar impact craters are identified by the trained R-FCN model and the age of craters is estimated by a dual-channel classification model with the semisupervised method. (the details of method can be found in our paper[1]).<br><br><br>## Briefly Description<br>The database contains two comma-delimited table files: `Lunar_Crater_Database_DeepCraters_2020.csv` and `Aged_Lunar_Crater_Database_DeepCraters_2020.csv`. <br><br>&gt; The first table is the detected craters larger than about 1 km in diameter, which contains 117240 craters with 5 common fields in each crater. What needs illustration is that the first 7009 craters contains additional 2 fields `Lat_new` and `Lon_new` because of the inaccuracy of the CE1 dataset. the details of each field are listed below:<br>&gt; - `Flags_data`: 'CE1' or 'CE2' indicats the crater detected from CE-1 or CE-2 data;<br>&gt; - `ID`: the index of craters;<br>&gt; - `Lat`: the latitude of crater center in degree;<br>&gt; - `Lon`: the longitude of crater center in degree;<br>&gt; - `Diam_km`: the diameter of crater in kilometer;<br>&gt; - `Lat_new`: the latitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree;<br>&gt; - `Lon_new`: the longitude of the corresponding crater in Robbins Lunar Crater Database[2] in degree.<br>&gt;<br><br>&gt; The second table is the aged craters larger than 8 km in diameter, which contains 18996 craters with 6 fields in each craetr. And the first 5 fields are the same as in the first table, the last field `Age` indicates the system that the crater belongs to.<br>&gt;<br>&gt; - `Age`=1: pre-Nectarian System<br>&gt; - `Age`=2: Nectarian System<br>&gt; - `Age`=3: Imbrian System<br>&gt; - `Age`=4: Eratosthenian System <br>&gt; - `Age`=5: Copernican System<br><br><br><br>--------<br><br>## Note<br><br>The diameter of craters detected by DeepCraters is slightly larger than the real size of the craters. <br><br><br><br><br>## Reference<br>[1] Yang C , Zhao H , Bruzzone L , et al. Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning. [Online]. https://nature-research-under-consideration.nature.com/posts/57165-lunar-impact-craters-identification-and-age-estimation-with-chang-e-data-by-deep-and-transfer-learning.<br><br>[2] Robbins, S. J. A new global database of lunar impact craters &gt;1–2 km: 1. crater locations and sizes, comparisons with published databases, and global analysis. Journal of Geophysical Research (Planets),124(4), 871-892(2019).<br><br><br>
DOI: 10.6084/m9.figshare.12765962
title: Data --- Energy and Pitch-Angle Change (Gaussian Pulse Ei)

description: dEdt and dMUdt, under Gaussian Pulse Ei<br>