cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12765986.v1
title: Aged_Lunar_Crater_Database_DeepCraters_2020(1).csv

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.v1
title: Data --- Energy and Pitch-Angle Change (Gaussian Pulse Ei)

description: dEdt and dMUdt, under Gaussian Pulse Ei<br>
DOI: 10.6084/m9.figshare.12765971
title: Data --- Energy and Pitch-Angle Change (MLT Dependent Ei)

description: dEdt and dMUdt, under MLT Dependent Ei<br>
DOI: 10.6084/m9.figshare.12765971.v1
title: Data --- Energy and Pitch-Angle Change (MLT Dependent Ei)

description: dEdt and dMUdt, under MLT Dependent Ei<br>
DOI: 10.6084/m9.figshare.12765911
title: Data --- Inductive Drift (MLT Dependent Ei)

description: Data --- Inductive Drift (MLT Dependent Ei)
DOI: 10.6084/m9.figshare.12765914
title: Data --- Inductive Drift (Gaussian Pulse Ei)

description: Data --- Inductive Drift (Gaussian Pulse Ei)<br>
DOI: 10.6084/m9.figshare.12765905
title: Data --- Electrostatic Potential Drift

description: Data --- Electrostatic Potential Drift
DOI: 10.6084/m9.figshare.12765902
title: Data --- Magnetic Gradient-Curvature Drift

description: Data --- Magnetic Gradient-Curvature Drift
DOI: 10.6084/m9.figshare.12765911.v1
title: Data --- Inductive Drift (MLT Dependent Ei)

description: Data --- Inductive Drift (MLT Dependent Ei)
DOI: 10.6084/m9.figshare.12765914.v1
title: Data --- Inductive Drift (Gaussian Pulse Ei)

description: Data --- Inductive Drift (Gaussian Pulse Ei)<br>
DOI: 10.6084/m9.figshare.12765848
title: Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird

description: This .zip file contains the dataset and R code used in <i>Valdebenito et al. 2020 Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird. 10.1371/journal.pone.0237369</i>
DOI: 10.6084/m9.figshare.12765839
title: Data --- Self-Consistent Ei Convergence Test

description: Data --- Self-Consistent Ei Convergence Test
DOI: 10.6084/m9.figshare.12765815
title: Data --- Equatorial Magnetic Field Change

description: Data --- Equatorial dBdt
DOI: 10.6084/m9.figshare.12765839.v1
title: Data --- Self-Consistent Ei Convergence Test

description: Data --- Self-Consistent Ei Convergence Test
DOI: 10.6084/m9.figshare.12765806
title: Data --- Equatorial Magnetic Field

description: Data --- Equatorial Magnetic Field
DOI: 10.6084/m9.figshare.12765815.v1
title: Data --- Equatorial Magnetic Field Change

description: Data --- Equatorial dBdt
DOI: 10.6084/m9.figshare.12765848.v2
title: Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird

description: This .zip file contains the dataset and R code used in <i>Valdebenito et al. 2020 Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird. 10.1371/journal.pone.0237369</i>
DOI: 10.6084/m9.figshare.12765788
title: Historical Word Association Norms

description: Long format csv's with word association norms from several historical sources: Kent GH and Rosanoff AJ (1910), Russell WA and Jenkins JJ (1954), Palermo DS and Jenkins JJ (1964).
DOI: 10.6084/m9.figshare.12765746
title: Data --- Propagating Gaussian Pulse Inductive Electric Field

description: Equatorial Propagating Gaussian Pulse<br>
DOI: 10.6084/m9.figshare.12765767
title: Data --- MLT Dependent Inductive Electric Field

description: Data --- MLT Dependent Inductive Electric Field
DOI: 10.6084/m9.figshare.12765788.v1
title: Historical Word Association Norms

description: Long format csv's with word association norms from several historical sources: Kent GH and Rosanoff AJ (1910), Russell WA and Jenkins JJ (1954), Palermo DS and Jenkins JJ (1964).
DOI: 10.6084/m9.figshare.12765848.v1
title: dataset&Rcode.zip

description: This .zip file contains the dataset and R code used in <i>Valdebenito et al. 2020 Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird. 10.1371/journal.pone.0237369</i>
DOI: 10.6084/m9.figshare.12765656
title: all_breed_data_3_1.map

description: A total of 397 individual pigs from seven indigenous breeds (Laiwu, Dapulian, Licha Black, Yantai Black, Yimeng Black, Wulian Black, and Zaozhuang Heigai) and five Western commercial breeds (Yorkshire, Landrace, Duroc, Berkshire, and Pietrain) were used in the study. All animals were genotyped using Porcine SNP55K BeadChips according to the manufacturer’s protocol. The BeadChip was designed and promoted by Compass Biotechnology Corporation, Beijing, China (http://www.kangpusen.com/), and manufactured by Illumina (San Diego, CA, USA). Using PLINK v1.90 [12], SNPs were filtered with call rate ≧95% and MAF ≧0.05. A total of 39,300 informative SNPs , out of 43,832 SNPs contained in the BeadChip, were obtained. The SNP positions within a chromosome were based on the current pig genome assembly (Sscrofa11.1).
DOI: 10.6084/m9.figshare.12765713.v1
title: Velocity model and Catalogue

description: This folder contains the 3-D velocity model in the 1969 earthquake doublet area offshore Hainan Island and the catalogue of earthquakes in and around Hainan from 2000 to 2012.
DOI: 10.6084/m9.figshare.12765746.v1
title: The effects of inductive electric field on the spatial and temporal evolution of inner magnetospheric ring current

description: Propagating Gaussian Pulse<br>
DOI: 10.6084/m9.figshare.12765656.v1
title: all_breed_data_3_1.map

description: A total of 397 individual pigs from seven indigenous breeds (Laiwu, Dapulian, Licha Black, Yantai Black, Yimeng Black, Wulian Black, and Zaozhuang Heigai) and five Western commercial breeds (Yorkshire, Landrace, Duroc, Berkshire, and Pietrain) were used in the study. All animals were genotyped using Porcine SNP55K BeadChips according to the manufacturer’s protocol. The BeadChip was designed and promoted by Compass Biotechnology Corporation, Beijing, China (http://www.kangpusen.com/), and manufactured by Illumina (San Diego, CA, USA). Using PLINK v1.90 [12], SNPs were filtered with call rate ≧95% and MAF ≧0.05. A total of 39,300 informative SNPs , out of 43,832 SNPs contained in the BeadChip, were obtained. The SNP positions within a chromosome were based on the current pig genome assembly (Sscrofa11.1).
DOI: 10.6084/m9.figshare.12765746.v3
title: Data --- Propagating Gaussian Pulse Inductive Electric Field

description: Equatorial Propagating Gaussian Pulse<br>
DOI: 10.6084/m9.figshare.12765746.v2
title: Data --- Propagating Gaussian Pulse

description: Propagating Gaussian Pulse<br>
DOI: 10.6084/m9.figshare.12765494
title: Labels for wave-scarp interaction images

description: Beach and surf cameras offer a way to visualize interactions between waves and scarps (both dune and beach scarps). This dataset is a single csv file that lists 1) publicly available frames of video from Buxton, North Carolina, USA; 2) a human coded label describing whether ocean waves are interacting with a beach or dune scarp. A total of 984 frames have been labeled<br><br>The data table has 6 columns: 1) the name of the catalog (Buxton Coastal Camera); 2) the archive name, which corresponds to the specific video that supplies the frames used for coding. The videos are demarcated using year, month, day, time format, and correspond to 10 minute increments (which is the time interval provided during data retrieval); 3) the frame number from that video segment; Columns 4 through 6 indicate the coding of the image based on wave-scarp interaction seen in the frame. There are three options: ‘NoInteraction’ (waves are not impacting the scarp), Interaction (waves are impacting the scarp), or ‘Close’ (the waves are close to the scarp, and judged by the human labeler to have a high likelihood of interacting with the scarp in subsequent frames). <br><br>The publicly available video from Buxton, North Carolina, USA is from the NOAA NOS (National Ocean Service) and SECOORA (The Southeast Coastal Ocean Observing Regional Association) camera monitoring system — WebCAT (Web Camera Applications Testbed). The link to the WebCAT site is found below, as well as a link to a programmatic tool (PyWebCAT) for retrieving video and slicing video into frames. We encourage users of this dataset to use PyWebCAT to download video, extract frames, and then merge with this dataset. Hand labeling was done using the Coastal Image Labeler (link below).<br><br><br>We thank NOAA NOS, SECOORA and the WebCAT project for making camera footage publicly available and supporting open science and data.
DOI: 10.6084/m9.figshare.12765494.v1
title: Labels for wave-scarp interaction images

description: Beach and surf cameras offer a way to visualize interactions between waves and scarps (both dune and beach scarps). This dataset is a single csv file that lists 1) publicly available frames of video from Buxton, North Carolina, USA; 2) a human coded label describing whether ocean waves are interacting with a beach or dune scarp. A total of 984 frames have been labeled<br><br>The data table has 6 columns: 1) the name of the catalog (Buxton Coastal Camera); 2) the archive name, which corresponds to the specific video that supplies the frames used for coding. The videos are demarcated using year, month, day, time format, and correspond to 10 minute increments (which is the time interval provided during data retrieval); 3) the frame number from that video segment; Columns 4 through 6 indicate the coding of the image based on wave-scarp interaction seen in the frame. There are three options: ‘NoInteraction’ (waves are not impacting the scarp), Interaction (waves are impacting the scarp), or ‘Close’ (the waves are close to the scarp, and judged by the human labeler to have a high likelihood of interacting with the scarp in subsequent frames). <br><br>The publicly available video from Buxton, North Carolina, USA is from the NOAA NOS (National Ocean Service) and SECOORA (The Southeast Coastal Ocean Observing Regional Association) camera monitoring system — WebCAT (Web Camera Applications Testbed). The link to the WebCAT site is found below, as well as a link to a programmatic tool (PyWebCAT) for retrieving video and slicing video into frames. We encourage users of this dataset to use PyWebCAT to download video, extract frames, and then merge with this dataset. Hand labeling was done using the Coastal Image Labeler (link below).<br><br><br>We thank NOAA NOS, SECOORA and the WebCAT project for making camera footage publicly available and supporting open science and data.
DOI: 10.6084/m9.figshare.12765383
title: Supplementary Material for: Development of Predictive Risk Models of Postpartum Stress Urinary Incontinence for Primiparous and Multiparous Women

description: <b><i>Objectives:</i></b> To develop risk predictive models of postpartum stress urinary incontinence (SUI) for both primiparous and multiparous women. <b><i>Materials and Methods:</i></b> From July 2016 to July 2017, 815 singleton pregnant women without incontinence before pregnancy who were 18 years or older and admitted to 2 hospitals in Shenzhen, China, were enrolled. Pregnancy-related data were collected at enrollment. Delivery information was obtained from electronic medical records. Telephone follow-up was conducted to investigate SUI at 6 weeks postpartum. Multivariable logistic regression analyses using stepwise selection were used to establish predictive models for postpartum SUI for all women, and separately for primiparous and multiparous. Internal validation of the models was performed with discrimination and calibration using a bootstrapping (1,000 resampling) method. <b><i>Results:</i></b> The analysis included 727 participants. The prevalence of postpartum SUI was 15.96% (116/727), 12.5% (49/393) for primiparous women and 20.1% (67/334) for multiparous women, with a significant difference between them (<i>p</i> = 0.008). For primiparous women, the predictive postpartum SUI model included age, abortion/miscarriage history, SUI during pregnancy, and mode of delivery. For multiparous women, pre-pregnancy BMI, abortion/miscarriage history, SUI during pregnancy, and mode of delivery were included in the model. There was satisfactory calibration between the models’ predicted probability of postpartum SUI and the observed probability for both primiparous and multiparous women (Hosmer-Lemeshow test, <i>p</i> = 0.390 for primiparous and 0.364 for multiparous women). The optimism-corrected C-statistic of the models by bootstrapping stepwise was 0.763 (95% confidence interval [CI]: 0.693–0.833) for primiparous women and 0.783 (95% CI: 0.726–0.841) for multiparous women. <b><i>Conclusion:</i></b> We developed predictive models of postpartum SUI for both primiparous and multiparous women. This approach may provide a useful tool for high-risk prediction of postpartum SUI before and after delivery.
DOI: 10.6084/m9.figshare.12765404
title: appendix: weight changes and lipids

description: appendix to systematic review
DOI: 10.6084/m9.figshare.12765359
title: Supplemental data thyroid and lipids

description: supplemental data
DOI: 10.6084/m9.figshare.12765383.v1
title: Supplementary Material for: Development of Predictive Risk Models of Postpartum Stress Urinary Incontinence for Primiparous and Multiparous Women

description: <b><i>Objectives:</i></b> To develop risk predictive models of postpartum stress urinary incontinence (SUI) for both primiparous and multiparous women. <b><i>Materials and Methods:</i></b> From July 2016 to July 2017, 815 singleton pregnant women without incontinence before pregnancy who were 18 years or older and admitted to 2 hospitals in Shenzhen, China, were enrolled. Pregnancy-related data were collected at enrollment. Delivery information was obtained from electronic medical records. Telephone follow-up was conducted to investigate SUI at 6 weeks postpartum. Multivariable logistic regression analyses using stepwise selection were used to establish predictive models for postpartum SUI for all women, and separately for primiparous and multiparous. Internal validation of the models was performed with discrimination and calibration using a bootstrapping (1,000 resampling) method. <b><i>Results:</i></b> The analysis included 727 participants. The prevalence of postpartum SUI was 15.96% (116/727), 12.5% (49/393) for primiparous women and 20.1% (67/334) for multiparous women, with a significant difference between them (<i>p</i> = 0.008). For primiparous women, the predictive postpartum SUI model included age, abortion/miscarriage history, SUI during pregnancy, and mode of delivery. For multiparous women, pre-pregnancy BMI, abortion/miscarriage history, SUI during pregnancy, and mode of delivery were included in the model. There was satisfactory calibration between the models’ predicted probability of postpartum SUI and the observed probability for both primiparous and multiparous women (Hosmer-Lemeshow test, <i>p</i> = 0.390 for primiparous and 0.364 for multiparous women). The optimism-corrected C-statistic of the models by bootstrapping stepwise was 0.763 (95% confidence interval [CI]: 0.693–0.833) for primiparous women and 0.783 (95% CI: 0.726–0.841) for multiparous women. <b><i>Conclusion:</i></b> We developed predictive models of postpartum SUI for both primiparous and multiparous women. This approach may provide a useful tool for high-risk prediction of postpartum SUI before and after delivery.
DOI: 10.6084/m9.figshare.12765272
title: Supplementary Material for: CD49d Is Upregulated in Circulating T Lymphocytes from HTLV-1-Infected Patients

description: <b><i>Introduction:</i></b> HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a chronic progressive myelopathy associated with an inflammation of the central nervous system (CNS), being characterized by perivascular infiltration of inflammatory cells. HTLV-1-infected cells have the capacity to migrate through endothelial layers by enhancing adhesion receptor expression and corresponding ligands. T cells interact with the extracellular matrix via integrin receptors and these interactions affect both cell migration and proliferation. The importance of these interactions in retrovirus-induced diseases, however, remains less clear. <b><i>Methods:</i></b> Herein we studied the expression of 3 integrin alpha chains (CD49d, CD49e, and CD49f) on the membrane of T-cell subsets in patients infected by HTLV-1, both HAM/TSP patients and oligo/asymptomatic subjects who were asymptomatic or presented slight manifestations related to the virus infection. <b><i>Results:</i></b> We observed higher peripheral blood frequency of CD49d<sup>hi</sup>CD4<sup>+</sup> and CD49d<sup>hi</sup>CD8<sup>+</sup> T cells in HTLV-1-infected patients. <b><i>Conclusion:</i></b> Our findings suggest that the increased expression of adhesion molecules, such as CD49d on T lymphocytes from HTLV-1-infected patients may contribute to the pathogenesis of the disease, in both oligo/asymptomatic and HAM/TSP-infected subjects. Accordingly, it is conceivable that there is a potential use of CD49d as target for a therapeutic approach aiming at blocking migration of activated T cells from HTLV-1-infected patients into the CNS, thus avoiding the progression to HAM/TSP.
DOI: 10.6084/m9.figshare.12765260
title: Supplementary Material for: Treatment of Pemphigus Vulgaris and Foliaceus with Adjuvant Rituximab Compared to Immunosuppression Alone: Real-Life Experience

description: <b><i>Introduction:</i></b> In a randomized prospective trial, adjuvant rituximab was more efficacious than corticosteroids alone in the treatment of pemphigus; however, real-life data are limited. Rituximab treatment for pemphigus has only recently been introduced to the Israeli health basket. Previously, patients received rituximab if they paid out of pocket or through private insurance, separating patients into 2 treatment groups, mostly based on economic capability. <b><i>Methods:</i></b> A retrospective cohort study of the 12-month clinical response of pemphigus vulgaris/foliaceus patients. We compared patients after a single cycle (1,000 mg on days 0 and 15 or weekly 375 mg/m<sup>2</sup> for 4 weeks) of adjuvant rituximab with systemic corticosteroids ± steroid-sparing agents, to patients who were prescribed rituximab, could not obtain it, and received systemic corticosteroids ± steroid-sparing agents. <b><i>Results:</i></b> Forty-five patients were included (adjuvant rituximab, <i>n</i> = 29; immunosuppression alone, <i>n</i> = 16). At baseline, rituximab patients had a higher mean pemphigus disease area index (PDAI) (<i>p</i> = 0.07) and higher mean daily dosages of prednisone (1.51 vs. 1.16 mg/kg, <i>p</i> = 0.39). All patients but 1 in the rituximab group continued systemic steroids, and 31% in the rituximab group versus 50% in the immunosuppression-alone group received systemic adjuvants. At 12 months, partial or complete remission rates (on or off maximum 40 mg/day prednisone equivalent) were nonsignificantly higher in the rituximab group (62 vs. 50%, <i>p</i> = 0.53); however, patients on rituximab showed faster remissions (3.4 ± 1.9 vs. 5.9 ± 3.6 months; <i>p</i> = 0.03) with a trend for a greater PDAI reduction (<i>p</i> = 0.051). Adverse events were comparable. <b><i>Conclusions:</i></b> In this real-life study, a single cycle of rituximab achieved more remissions and sooner compared to conventional immunosuppression, but the differences were not significant, probably due to a small sample size and severe baseline disease in the rituximab group. Future real-life studies on larger groups are needed.