cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7b6rvrmcy6
title: GNNs Python script for TCM fingerprints

description: We employed deep residual networks, specifically ResNet-18, ResNet-34, and ResNet-50 architectures, to analyze and categorize chromatographic fingerprints of traditional Chinese medicines (TCM).
1. Model Architecture:
 ResNet Variants: Implemented ResNet-18, ResNet-34, and ResNet-50 to manage different complexities in image data.
 Pre-trained Weights: Initialized with weights from the ImageNet dataset to improve generalization across medical images.
 Custom Top Layer: Included a 50% dropout rate and a fully connected output layer tailored for classifying chromatographic fingerprints.
2. Data Preprocessing and Augmentation:
 Standardization: Resized all images to 384x384 pixels and normalized using standard values.
 Augmentation: Applied random flips, rotations, color jittering, and affine transformations to increase model robustness.
3. Training Setup:
 Loss Function: Utilized cross-entropy loss for effective training.
 Optimizer: Used Adam optimizer with initial learning rate of 0.0001 and weight decay.
 Early Stopping: Implemented to halt training when no improvement in validation loss is observed, preventing overfitting.
4. Validation and Performance Metrics:
 Dataset Split: Data divided into training (70%), validation (15%), and testing (15%) sets.
 Metrics: Monitored accuracy, recall, F1 score, and precision to evaluate model performance.
5. Practical Application:
 Image Prediction Workflow: Developed a workflow for loading trained models, preprocessing input images, and classifying new images, facilitating practical use in diagnostics.
DOI: 10.17632/7w9n5wxs4d
title: Increasing the survival benefit from repair of intact abdominal aortic aneurysm

description: AAA.csv is the distribution of aortic sizes in a screened population of 700,000 65 year-old men. It is two columns of numbers: 1 aortic diameter (mm); 2 number of men. MSD, MSD1993 and MSD2017 are the changes in median life expectancy for combinations of age from 40 to 90 years old (rows 1-51) and aortic diameters from 1-160 mm . These are for: the generated longitudinal cohort born 1945 to age 90 years in 2035 (MSD); a population in 1993 (MSD1993); a population in 2018 (MSD2017). AAAsizes is a .rds file to be read in R. It lists around 27 million aortic diameters for the total population, generated through R code "Lancet, Threshold for AAA repair, John Carlisle".
DOI: 10.6084/m9.figshare.17039813.v2
title: A 3D deep learning approach to epicardial fat segmentation in non-contrast and post-contrast cardiac CT images

description: Raw CT data of epicardial fat in NRRD format.<br>Training and Testing data<br>Non-contrast and post-contrast datasetGround-truth segmentation
DOI: 10.6084/m9.figshare.25361176.v1
title: Taylor Swift TikTok and Reddit Posts

description: Taylor Swift is arguably one of the most popular and influential celebrities. Of particular interest, is her power as a role model for millions of fans across the world. Swift has spoken openly about different cultural issues, including her struggles with disordered eating and diet culture. Thus, the purpose of this paper was to explore whether Swift’s disclosures of her own eating and body image struggles impacted her fans. Over 200 TikTok and Reddit posts related to Swift and eating disorders or body image, as well as their associated comments were qualitatively coded to examine relevant themes. Key themes included: Swift as a role model for disordered eating recovery, use of or identification with specific Swift songs to illustrate struggles with eating or body image, continued objectification of Swift’s body, and conflicted reaction to a scene in Swift’s video for “Anti-Hero” that depicted the word “fat” on a scale. Overall, Swift’s disclosures of her own eating/body image struggles positively impacted her fans’ relationships with their eating behaviors and body image. This analysis illustrates the positive influence celebrities can have while also highlighting the limitations of personal disclosures to impact understanding of systemic issues like anti-fat bias.
DOI: 10.6084/m9.figshare.25513846.v1
title: Fig cultivar names in US circulation 2020-2024

description: Data to accompany "Landrace <i>Ficus carica</i> cultivar names in U.S. circulation, 2020-2024".<br>
DOI: 10.6084/m9.figshare.12768539.v1
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.28238771.v1
title: <b>A dataset of fruit chunks</b>

description: <b>fruit chunks detection algorithm</b>
DOI: 10.7294/28966283.v1
title: Dataset associated with: Disease Signatures in Whole Plants and Callus Culture of <i>Arabidopsis thaliana</i> Infected with the Fungal Plant Pathogen <i>Fusarium graminearum</i>

description: This dataset accompanies the manuscript titled <i>"Disease Signatures in Whole Plants and Callus Culture of Arabidopsis thaliana Infected with the Fungal Plant Pathogen Fusarium graminearum"</i> by McMullan et al. (to be submitted to <i>Plant Cell, Tissue and Organ Culture</i>). It includes quantitative measurements related to fungal infection severity and mycotoxin production in both whole plants and callus cultures of <i>Arabidopsis thaliana</i>. Three <i>A. thaliana</i> accessions with documented differences in susceptibility were assessed at 7, 14, and 21 days post-inoculation. Each file includes metadata for accession identity, timepoint, biological replicate, and the specific metric of interest. These datasets support analysis of host response dynamics and enable comparisons between whole-plant and callus-based systems for modeling plant-pathogen interactions. The data may also inform future work on phytosensor development and fungal secondary metabolite detection in simplified in vitro systems.
DOI: 10.17632/ctv68wsyv4
title: X-ray Teeth dataset of three most common disease

description: This dataset comprises cut images of raw X-ray teeth images, segmented into three common diseases. The work was conducted in collaboration with an experienced doctor.
DOI: 10.25442/hku.24954784.v2
title: Greenspace data cube for 2022_Part2

description: Greenspace data cube for 2022
DOI: 10.6084/m9.figshare.12763154.v1
title: SAMT_South_Australian_Macrobenthic_database.xlsx

description: The South Australian Macrobenthic Traits database - SAMT<br>The South Australian Macrobenthic Traits (SAMT) database contains trait information of 277 macrobenthic taxa and cover 13 traits and 54 trait-modalities. SAMT database is accompanying the manuscript "Establishing the South Australian Macrobenthic Traits (SAMT) database: a trait classification for functional assessments" submitted to <i>Ecology and Evolution.</i>
DOI: 10.6084/m9.figshare.21545784.v1
title: CKM-Physicians-Innovation_Multiplex_Social

description: This README file accompanies the dataset representing the multiplex social network of a sample of physicians in US. If you use this dataset in your work either for analysis or for visualization, you should acknowledge/cite the following paper: <br> "The Diffusion of an Innovation Among Physicians" J. Coleman, E. Katz, and H. Menzel. Sociometry (1957) 20:253-270. <br> ### Description of the dataset <br> Data collected by Coleman, Katz and Menzel on medical innovation, considering physicians in four towns in Illinois, Peoria, Bloomington, Quincy and Galesburg. <br> They were concerned with the impact of network ties on the physicians' adoption of a new drug, tetracycline. Three sociometric matrices (layers) were generated, based on the following questions: <br> 1. When you need information or advice about questions of therapy where do you usually turn? 2. And who are the three or four physicians with whom you most often find yourself discussing cases or therapy in the course of an ordinary week -- last week for instance? 3. Would you tell me the first names of your three friends whom you see most often socially? <br> There are 246 nodes in total, labelled with integer ID between 1 and 246, with 1551 connections. The multiplex is directed and unweighted, stored as edges list in the file CKM-Physicians-Innovation_multiplex.edges <br> with format <br> layerID nodeID nodeID weight <br> (Note: all weights are set to 1) <br> The IDs of all layers are stored in <br> CKM-Physicians-Innovation_layers.txt <br> The IDs of nodes can be found in the file <br> CKM-Physicians-Innovation_nodes.txt <br> The values for the 14 columns (attributes) are: <br> 1. node id 2. city 3. adoption date 4. med_sch_yr 5. meetings 6. jours 7. free_time 8. discuss 9. clubs 10. friends 11. community 12. patients 13. proximity 14. specialty <br> For the values assigned to each attribute see the original paper. <br> <br> ### License <br> The CKM-PHYSICIANS-INNOVATION MULTIPLEX DATASET is provided "as is" and without warranties as to performance or quality or any other warranties whether expressed or implied. <br> <br>
DOI: 10.6084/m9.figshare.3793104.v1
title: Supplementary Material for: A Systematic Review and Meta-Analysis of Kidney and Pregnancy Outcomes in IgA Nephropathy

description: <i>Background:</i> The outcomes of pregnancy in immunoglobulin A nephropathy (IgAN) remain controversial. We sought to evaluate the effect of pregnancy on the progression of IgAN as well as the impact of IgAN on pregnancy outcomes. <i>Methods:</i>We systematically searched MEDLINE, Embase for cohort or case-control studies. OR reductions were calculated with a random-effects model, and kidney outcomes and adverse pregnancy events were analyzed. <i>Results:</i> Our literature search returned 652 relevant articles; 4 studies were included, providing data of 376 pregnancies in 273 patients with IgAN and that of 241 IgAN who did not become pregnant. Four hundred sixty seven patients with chronic kidney disease stages 1-2 were included. Pregnancy in patients with IgAN did not increase the risk of adverse renal events including doubling of serum creatinine, 50% decline in glomerular filtration rate (GFR) and end-stage kidney disease (OR 0.97, 95% CI 0.55-1.70; p = 0.90; I2 = 0.0%, p = 0.79). There was no significant difference in the change in estimated GFR at the end of follow-up in the pregnant and non-pregnant groups (weighted mean difference 0.1 ml/min/1.73 m2 (95% CI -4.85 to 5.04 ml/min/1.73 m2), p = 0.97; I2 = 0%, p = 0.95). Women with IgAN had high rates of infant loss (12.2, 7.4-19.4%), preterm delivery (8.5, 5.9-12.1%), low birth weight (9.5, 6.7-13.3%), and preeclampsia/severe preeclampsia (7.3, 4.9-10.6%). <i>Conclusions:</i> Pregnancy in IgAN patients with preserved kidney function did not accelerate deterioration of renal function. But pregnant women with IgAN are at higher risk of pregnancy complications.
DOI: 10.17632/3dd96zny84
title: Increase in yield with the minus and addition of N, P, and K fertilizer

description: At Grobogan, N fertilization increased harvested dry grain weight by 111.96 to 180.45%, milled dry grain weight by 135.04 to 160.16% and straw dry weight by 159.14 to 182.93%. P fertilization increased the weight of harvested dry grain by 0.00 to 13.61%, the weight of milled dry grain by 0.66 to 12.63%, and the dry weight of straw by 13.50 to 39.34%. K fertilization increased the weight of harvested dry grain by 9.11 to 27.94%, milled dry grain by 11.92 to 23.25%, and dry straw by 8.63 to 22.33%.
In Pandeglang, N fertilization significantly increased the weight of harvested dry grain by 46.67 to 81.71%, milled dry grain by 43.80 to 78.83%, and dry straw by 49.35 to 88.01%. P fertilization increased rice production very little, between 0.00 and 27.91%. K fertilization increased the weight of harvested dry grain by 0.00 to 31.34%, the weight of milled dry grain by 1.50 to 34.60%, and the weight of dry straw by 4.28 to 46.14%.
The addition of N fertilizer in Sukadana significantly increased the weight of harvested dry grain by 80.00 to 136.36%, milled dry grain by 64.29 to 262.50%, and dry straw by 10.42 to 169.29%. The increase in rice production with the addition of P fertilizer is very small, ranging from 0.00 to 4.16%. The application of K fertilizer significantly increased the weight of harvested dry grain by 25.38 to 94.59%, the weight of milled dry grain by 37.39 to 160.27%, and the weight of dry straw by 18.89 to 49.64%.
DOI: 10.17632/hwntrn78vc
title: Changes in forest landscape patterns resulting from recent afforestation in Europe (1990-2012): Defragmentation of pre-existing forest versus new patch proliferation.

description: The present dataset was construct with the aim of addressing the association between forests cover increase and spatial pattern change in the European landscapes, while considering the landscape land cover composition and the altitudinal and geographical gradients. We hypothesized that forest increase is determining (i) a decrease in the overall landscape diversity, (ii) a forest defragmentation and (iii) an increase in forest connectivity across Europe. We used the recent set of medium- to high-resolution land use and cover (LC) maps worldwide available: those of the Climate Change Initiative (CCI) by the European Spatial Agency (ESA 2017), and the forest cover change maps of the Global Land Cover Facility (GLCF) from the University of Maryland(Hansen et al. 2013; Kim et al. 2014). Using LC maps we randomly selected 752 landscapes 5-km radius across Europe with recent (1990-2012) forest increase and we calculate for each landscape for the years 1990 and 2012 the following landscape metrics: forest patch number (n), mean and largest forest patch size (ha), total forest edge (m), forest effective mesh size (ha), percentage of forest like adjacencies (%), Euclidean nearest neighbour distance and Shannon diversity index. In order to assess the modulating role of environmental context on the association between forest increase and landscape change, we included a set of variables regarding geographical position, topography, and initial composition of the study landscapes: Percentage of each land cover in 1990 (%), longitude (º), latitude (º), average of slope in the plot (º), average of elevation in the plot (m), mean annual temperature between 1970-2000 (ºC), standard deviation of annual temperature between 1970-2000 (ºC), Annual precipitation between 1970-2000 (ºC) and Annual precipitation standard deviation between 1970-2000 (ºC). Finally we performed a set of GLM on randomly selected 752 landscapes with recent (1990-2012) forest increase to assess the modulating role of environmental context on the association between forest increase and landscape change. Results showed that the decrease in landscape diversity in the last decades was not associated to forest increase but to high cropland and low scrub-grassland cover. Forest increase promoted the defragmentation of already existing forests and new patch proliferation in forest-dominated and non-dominated landscapes, respectively. These processes also depend on elevation and geographical position, with forest defragmentation concentrated in Northern and Eastern Europe and new patch proliferation in southern and western regions, and in mid-elevation areas.
DOI: 10.17632/r7pnxpr2bb
title: URDD: An open dataset for urban roadway disease detection and classification

description: We present two urban road disease datasets: DURDD for road disease detection and CURDD for road disease classification. DURDD includes four main types of underground road diseases: cavity, detachment, water-rich, and looseness. It also contains disease detection datasets in three base formats: COCO, Pascal VOC, and YOLO. In CURDD, the dataset is divided into two levels: level 0 and level 1, corresponding to the "Cls0" and "Cls1" catalogs, respectively. Level 1 includes cavity, detachment, water-rich, looseness, and background. Level 0 categories combine the four main disease types mentioned earlier into a single "diseases" category, with the other category being "background." This dataset was jointly published by Hebei University and the 519 Team of North China Geological Exploration Bureau. We support individuals or teams using the data for research purposes. We also welcome collaboration for commercial use. For commercial inquiries, please contact us for authorization.
DOI: 10.6084/m9.figshare.25288810.v2
title: Annual river ice phenologies determined by IDLRM from 2000 to 2021

description: <b>*Title:</b>Annual river ice phenologies determined by IDLRM from 2000 to 2021.<br><b>*Description:</b>These tables document the annual freeze-up date, break-up date, and ice duration for 7,970 examined river segments determined by IDLRM from 2000 to 2021 in the study.The first column "river_id" is associated with unique identifiers for rivers in the Global River Widths from Landsat (GRWL) dataset. For example, "NH44_109" indicates a river in the latitude range of 28-32°N and the longitude range of 78-84°E, with an ID of "109". Further details are available at: https://zenodo.org/records/1297434#.W8JkshNKh24.The remaining columns represent the corresponding river ice phenologies for each year. For freeze-up and break-up dates, the values in the table indicate the day of the year when freezing/breaking occurred, starting from August 1st of the previous year. For ice duration, the values in the table represent the number of days the river was frozen during the respective year. Blank entries indicate either no ice formation in the river during the year or inability of the model to determine the ice conditions.
DOI: 10.6084/m9.figshare.28302725.v1
title: Dataset for "<i>Turn-taking in grooming interactions of chimpanzees (</i><i>Pan troglodytes schweinfurthii</i><i>) in the wild: The role of demographic and social factors</i>"

description: This dataset includes the relevent variables used to investigate the impact of demographic and social factors on turn-taking interactions in the grooming context. The "switch_yn" is whether the interaction (int_id) involved a turn transition, "switch_freq" is when a turn transition occured within an interaction and "switch_type" is which turn transition type occured.
DOI: 10.17632/94d9g5hx3v
title: EFFECT OF EXERCISE TRAINING ON ENDOTHELIAL FUNCTION IN INDIVIDUALS WITH EXCESS WEIGHT: A SYSTEMATIC REVIEW WITH META-ANALYSIS OF RANDOMIZED CLINICAL TRIALS 

description: Individuals with excess weight have impaired endothelial function and increased risk of atherosclerosis. Exercise training is essential for the management of excess weight, but little is known about its effects on endothelial function in this population. The objective of this systematic review was to examine the effects of exercise training on endothelial function in individuals with excess weight. Methods: Our review study included only randomized controlled trials (RCTs) involving adults (≥18 years of age) with body mass index (BMI) ≥25.0 kg/m2. Our search was conducted in the electronic bases MEDLINE (PubMed), Cochrane, LILACS and EMBASE and in the gray literature. We performed random-effects analyses for effect estimates and used 95% prediction intervals (95% PI) for estimating the uncertainty of the study results. We also assessed the risk of bias using RoB 2 tool and the strength of the body of evidence (GRADE) of the studies. RStudio software was used for statistical analyses.
DOI: 10.6084/m9.figshare.11627193.v2
title: Staphylococcus aureus core genome coordinates on the ST22 strain HO 5096 0412

description: This file contains the genomic coordinates of the <i>Staphylococcus aureus</i> species core-genome, derived from a collection of 800 <i>S. aureus</i> strains from multiple host species<sup>1</sup> using Roary<sup>2</sup>, on the clonal complex 22 S. aureus reference genome (Genbank accession number HE681097).<br><sup>1</sup> Richardson EJ, Bacigalupe R, Harrison EM, Weinert LA, Lycett S, Vrieling M, Robb K, Hoskisson PA, Holden MTG, Feil EJ, et al. 2018. Gene exchange drives the ecological success of a multi-host bacterial pathogen. <i>Nature Ecology & Evolution</i>.<br><sup>2</sup> Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MTG, Fookes M, Falush D, Keane JA, Parkhill J. 2015. Roary: rapid large-scale prokaryote pan genome analysis. <i>Bioinformatics</i> <b>31</b>: 3691–3693.
DOI: 10.6084/m9.figshare.20059259.v1
title: Base de datos Gratitud. Scurtu et al. .sav

description: La base de datos incluye: 1. Información sociodemográfica de los participantes; y puntuación total y por ítem de las escalas 2. MCGM; 3. CQ-6; 4. SWLS; 5. SHS; 6. GHQ-12; y 7. PANAS
DOI: 10.6084/m9.figshare.25747074.v1
title: Exosomal RNA counts - SLE and control biofluids

description: Count matrix of genes detected per sample from exosomal RNA sequencing.
DOI: 10.6084/m9.figshare.28844078.v2
title: Datasets for "Directed Swarm Assembly due to Mixed Misaligned Perception-Dependent Motility"

description: Each dataset is named after its corresponding figure in the manuscript.Column headers in the csv files contain the corresponding variable name and are self-explanatory.See the manuscript for more details.
DOI: 10.6084/m9.figshare.3557334.v1
title: Appendix A. A list of studies containing data sets used to assess local–regional richness relationships.

description: A list of studies containing data sets used to assess local–regional richness relationships.