cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25625/o5txte
title: Data_Hartmann_Metz_2025_Productivity_moisture_competition_affecting_viability_of_Dactylorhiza_majalis_under_conservation

description: We studied 95 wet grassland sites across the Federal State of Brandenburg in NE-Germany . All sites harbored extant populations of D. majalis in our study years (86 sites) or at least until 5 years ago (9 sites). In order to characterize the vegetation and derive abiotic parameters, we conducted vegetation relevés in 3 – 6 plots of 2m × 2m in all sites during the main flowering period of D. majalis (mid-May – June). Across all 95 sites, we sampled in total 355 plots (3.7 plots per site on average), spread over three years for feasibility (2020 – 2022). In each 2m × 2m plot, all vascular plant species were identified to species level and their abundance was estimated using the scale of Braun-Blanquet (1964). As indicators of vegetation structure, we measured the average height of the vegetation (hereafter vegetation height), estimated the percent of ground covered by bryophytes (hereafter moss cover) and summed up the percent of all Poaceae species per 2m × 2m plot (hereafter grass cover). Moreover, we derived abiotic parameters from the vegetation relevés by calculating mean Ellenberg indicator values (EIV; weighted by the log-transformed cover per species) for moisture (F), nitrogen (N), and soil reaction (R) for each 2m × 2m plot (Ellenberg et al., 1992). Four proxies for population viability (hereafter viability proxy) were measured within the above described 2m × 2m plots: As abundance-based viability proxies, we counted the total number of i) juvenile and ii) flowering individuals of D. majalis per plot. As individual-based proxies of flowering individuals, we iii) counted their total number of flowers and iv) quantified their plant size. For the latter, we counted the leaves, measured the width and length of the first (subscript 1) and second (subscript 2) leaf closest to the ground, and quantified plant size as: leaf number × [(0.5 × leaf width1 × leaf length1) + (0.5 × leaf width2 × leaf length2)] (similar to Kindlmann and Balounová, 1999). Both individual-based proxies were quantified for and subsequently averaged across 5 (2021, 2022) or 10 (2020) randomly chosen flowering individuals per 2m x 2m plot, if available. If fewer flowering individuals occurred, all were measured. This resulted in a total of 1715 measured flowering individuals across 214 plots in 74 sites. As a fifth viability proxy, describing the long-term performance of D. majalis at the population level, we categorized whether population trends were positive, negative or had no trend (stable). For 60 sites, trend categories were calculated from long-term monitoring data of practitioners (1993 – 2020) with yearly counts of flowering D. majalis: (details in Hartmann and Metz, 2023). For 35 sites, the population trends (positive, negative, no trend) were based on expert judgements of practitioners that are familiar with the respective site for several years.
DOI: 10.5066/p9pdo2ng
title: Deep-learning-derived alluvium, shallow-to-exposed bedrock, and surficial sediment thickness map for the upper Neversink River watershed, New York

description: This dataset consists of a raster and surficial shapefiles for the Neversink River watershed, NY, that were generated using ArcGIS Pro's deep learning functionality. The shapefiles contain polygons that show the locations of shallow-to-exposed bedrock and alluvium-filled valleys, while the raster provides estimated minimum sediment thicknesses in the areas between the shallow/exposed bedrock and alluvium-filled valleys. The deep learning model that generated shallow/exposed bedrock and alluvium polygons was trained on existing geologic maps of New York and Pennsylvania. Minimum sediment thicknesses were estimated by applying an inverse distance weighting interpolation to measurements of stream incision depth and edges of shallow/exposed [...]
DOI: 10.5066/p9v75f9q
title: Laboratory results for anthropogenic bioactive chemicals in the Illinois Waterway upstream and downstream of the bigheaded carp population front (2015; ver. 2.0, March 2020)

description: Two non-native bigheaded carp species have invaded the Illinois River system and are a potential threat to the Great Lakes ecosystem. Discharges from industry, wastewater treatment plants, and urban and agricultural runoff, may be a factor contributing to the stalling of the upstream movement of the bigheaded carp population front near Illinois Waterway mile 278. In 2015, the U.S. Geological Survey collected 4 sets of water samples under a range of seasonal and hydrologic conditions from 3 locations upstream and 4 locations downstream from river mile 278 using a Lagrangian-style sampling strategy. Water samples were analyzed for over 639 constituents of which 280 were detected at least once, including many anthropogenic bioactive chemicals (ABCs) such as pesticides, pharmaceuticals, hormones, and volatile organic compounds (VOCs). Many ABCs were detected upstream of river mile 278, and some persisted or were introduced downstream. For example, in June 2015, at river mile 286, sampling detected 43 of 105 pharmaceuticals (total concentration and total load of 9,251 nanograms per liter (ng/L) and 66.2 kilograms per day (kg/d), respectively); 46 of 251 pesticides (total concentration and load of 5,956 ng/L and 84.5 kg/d); 9 of 55 wastewater indicator chemicals (total concentration and load of 4,092 ng/L and 58.0 kg/d); and 10 of 116 VOCs (total concentration and load of 9,626 ng/L and 137 kg/d). By the time that water moved downstream to river mile 243, sampling detected 13 pharmaceuticals (total concentration and load of 417 ng/L and 27.8 kg/d); 51 pesticides (total concentration and load of 11,207 ng/L and 1,687 kg/d); 5 wastewater indicator chemicals (total concentration and load of 309 ng/L and 46.5 kg/d); and 2 VOCs (total concentration and load of 340 ng/L and 51 kg/d). This set of tables is a revised version of the original tables. There are 11 data tables provided in this data release: Carboxylic_Acids_Data_Revised.csv, Discharge_Field_Ions_Data_Revised.csv, Disinfection_By_Products_Data_Revised.csv, Hormones_Data_Revised.csv, Metals_Data_Revised.csv, Nutrients_Data_Revised.csv, Other_Wastewater_Indicators_Data_Revised.csv, Pesticides_Data_Revised.csv, Pharmaceuticals_Data_Revised.csv, Site_Information_Revised.csv, and Volatile_Organic_Compounds_Data_Revised.csv.
DOI: 10.5067/0506kqls6512
title: MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities, Version 2
DOI: 10.5067/0djchzky1nvo
title: SMAPVEX16 Iowa PALS Brightness Temperature and Soil Moisture Data, Version 1
DOI: 10.5067/aqua/modis/l3m/chl/2022
title: Aqua MODIS Level 3 Mapped Chlorophyll Data, Version R2022.0
DOI: 10.5281/zenodo.13828550
title: Global Cluster Test Results: Pathogenic Fungi in Decayed Norway Spruce Stands

description: Accessing the Results: Users can retrieve the test results by opening the dataset Global_cluster_test_results.RData in an R session and using the functions inside the script of the same name.

Description: This dataset provides global cluster test results analyzing the spatial distribution of pathogenic fungi in 273 Norway spruce stands in Norway (Lara et al., 2024). The stands, composed mainly of Norway spruce (27% to 100%), also include Scots pine and birch. It focuses on spatial patterns of decayed spruce trees, offering p-values, clustering metrics, and other parameters from statistical analyses.

Analysis: The dataset includes results from three global cluster tests (Tango, 2010):



Tango's Nearest Neighbors (TNN)

Tango's Double Exponential Clinal (TCN)

Diggle and Chetwynd’s (DC)


Methodology: Cluster testing employed 1,000 Monte Carlo simulations for each test across all stands to establish null distributions and adjusted p-values, ensuring robust statistical assessments under the random labeling hypothesis: H0: the observed n0 decayed trees are a random sample from the entire sample of size n = n0 + n1 (decayed trees + healthy trees) (Tango, 2010).
DOI: 10.5281/zenodo.14803630
title: Dataset for Lee Wave Identification Using U-Net

description: This dataset consists of three main components:



Model Training Code: U-Net model and training code based on transfer learning.

Training Dataset: Includes manually segmented data and synthetic wave perturbation data.

Detection Results: Final model outputs after processing a large number of images.
DOI: 10.5281/zenodo.14905088
title: Data for publication "Magnetically quiet-time traveling ionospheric disturbances over mid-latitude Eastern Europe observed by the Kharkiv incoherent scatter radar during the 24th solar cycle"

description: This dataset are used to plot figures in the article "Magnetically quiet-time traveling ionospheric disturbances over mid-latitude Eastern Europe observed by the Kharkiv incoherent scatter radar during the 24th solar cycle".
DOI: 10.5281/zenodo.15003863
title: Assessing Artificial Intelligence Knowledge Among Al-Zahraa University Students: A Cross-Sectional Study
DOI: 10.5281/zenodo.2789117
title: Ceratocystis fagacearum ̶ Pest Report and Datasheet to support ranking of EU candidate priority pests

description: These two files are part of the outputs produced under the mandate M-2017-0056 of the European Commission requesting EFSA for technical assistance in the field of quarantine pests qualifying as priority pests as by Article 6(2) of the Regulation (EU) 2016/2031 <em>on protective measures against pests of plants</em>. Under the mandate EFSA produced: i) 1 methodology report (DOI available at the field "Related/alternate identifiers"), ii) 28 datasheets, one for each of the 28 candidate pests, and iii) 28 pest reports supporting the information provided in the datasheets. EFSA wishes to acknowledge the contribution of Anna Maria Vettraino to the EKE and the review conducted by Christer Magnusson.
description: EU; XLS; alpha@efsa.europa.eu
DOI: 10.5281/zenodo.4739739
title: A single-cell and spatially resolved atlas of human breast cancers | spatial transcriptomics data

description: This repository contains spatial transcriptomics data related to the Wu et al. 2021 study "<strong>A single-cell and spatially resolved atlas of human breast cancers</strong>". Processed count matrices, brightfield HE-images (plain and annotated) and meta-data (containing clinical information and spot pathological details) for 6 primary breast cancers profiled using the Visium assay (10X Genomics). If you use this dataset in your research, please consider citing the above study. The content of the files are:<br> raw_count_matrices.tar.gz - spaceranger processed raw count matrices. spatial.tar.gz - spaceranger processed spatial files (images, scalefactors, aligned fiducials, position lists) filtered_count_matrices.tar.gz - filtered count matrices. metadata.tar.gz - metadata for tissues and spots of filtered count matrices, including clinical subtype and pathological annotation of each spot. images.pdf - pdf detailing the H&E and annotation images.
DOI: 10.5281/zenodo.5526318
title: dictionaria/guarayu: Guarayu. A revised dictionary by Alfred Hoeller

description: Danielsen, Swintha and Sell, Lena and Terhart, Lena. 2019. Guarayu. A revised dictionary by Alfred Hoeller. Dictionaria 7. 1-3590 (Available online at https://dictionaria.clld.org/contributions/guarayu)
DOI: 10.5281/zenodo.6802613
title: Dataset with segmentations of 117 important anatomical structures in 1228 CT images

description: Info: This is version 2 of the TotalSegmentator dataset.In 1228 CT images we segmented 117 anatomical structures covering a majority of relevant classes for most use cases. The CT images were randomly sampled from clinical routine, thus representing a real world dataset which generalizes to clinical application. The dataset contains a wide range of different pathologies, scanners, sequences and institutions.
Link to a copy of this dataset on Dropbox for much quicker download: Dropbox Link
Overview of differences to v1 of this dataset: here
A small subset of this dataset with only 102 subjects for quick download+exploration can be found here: here
You can find a segmentation model trained on this dataset here.More details about the dataset can be found in the corresponding paper (the paper describes v1 of the dataset). Please cite this paper if you use the dataset.
This dataset was created by the department of Research and Analysis at University Hospital Basel.
UPDATE: On 2023-10-27 we uploaded version 2.0.1 which fixes broken files.
DOI: 10.5439/1095316
title: interpolatedsonde

description: ARM Instrument: Interpolated Sonde
DOI: 10.57760/sciencedb.01119
title: Cold-induced Arabidopsis FRIGIDA nuclear condensates for FLC repression
title: Cold-induced Arabidopsis FRIGIDA nuclear condensates for FLC repression

description: This contains all the raw images supporting the findings in the Article "Cold-induced Arabidopsis FRIGIDA nuclear condensates for FLC repression".
description: This contains all the raw images supporting the findings in the Article "Cold-induced Arabidopsis FRIGIDA nuclear condensates for FLC repression".
DOI: 10.6073/pasta/daad81be7f12173e3aefbf3df5d6d2fe
title: North Temperate Lakes LTER: High Frequency Data: Meteorological, Dissolved Oxygen, Chlorophyll, Phycocyanin - Lake Mendota Buoy 2006 - current

description: The instrumented buoy on Lake Mendota is equipped with limnological and meteorological sensors that provide fundamental information on lake thermal structure, weather conditions, and lake metabolism. Data are collected every minute. Hourly and daily averages are derived from the high resolution (1 minute) data. Hourly and daily values may not be current with high resolution data as they are calculated at the end of the season.
 Meteorological sensors measure wind speed, wind direction, relative humidity, air temperature, and photosynthetically active radiation (PAR). Not all sensors are deployed each season. A list of sensors used since the first deployment in 2006 is provided as a downloadable CSV file. The buoy is removed during the winter when the lake is ice-covered (typically Dec-Apr). Lake temperature data collected at the same buoy site can be found in an ancillary dataset.
 Number of sites: 1. Location lat/long: 43.0995, -89.4045
 Notable events:
 2017 - A boating mishap caused the loss of air temperature, relative humidity, and wind sensors between May 28 and July 11. The dissolved oxygen sensor had significant biofouling from algae and zebra mussels.
 2019 - A YSI EXO2 sonde was added to the buoy and includes DO, chlorophyll, phycocyanin, specific conductance, pH, fDOM, and turbidity sensors. The chlorophyll and phycocyanin sensors replace Turner Cyclops 7 fluorometers that had been in use in prior years. Both sets of sensors output RFU, but have significant magnitude differences. The YSI pH, DO, and specific conductance sensors were cleaned and recalibrated every two weeks. 
 2020 - Cleaning and calibration of the YSI sensors occurred nearly every week. The dissolved CO2 sensor was not operating between July 2 and September 17.
 2021 - Due to power and communications issues, the buoy was not operating August 22-31, and data is intermittent between November 8 and December 3. An effective method to keep the underwater PAR sensor mostly free of biofouling algae has been employed.
 2022 - Buoy was not operating June 6-9 and July 2-5 due to power issues. Underwater PAR sensor unusable after October 1.
 2023 - Conductivity sensor was not operational Apr 27 - May 24. The sensor was replaced. The wiper for the YSI sonde had failed Nov 4 - 14, which significantly affected four sensors: chlorophyll, phycocyanin, conductivity, and turbidity.
DOI: 10.6084/m9.figshare.12887213
title: County-level CO2 emissions in China

description: A dataset of county-level CO2 emissions in China, downscalled from provincial emissions from fossil fuel consumption.
DOI: 10.6084/m9.figshare.26085487
title: <b>County-level Cooking Emission inventory in China from 1990 to 2021</b>

description: This dataset provides county-level cooking emission inventory in China from 1990 to 2021 by counties, subsectors, and pollutants in the xlsx file.- The years include every year from 1990 to 2021.- The provinces cover all 2848 counties of mainland China based on 2020 administrative divisions.- The subsectors include commercial cooking, residential cooking, and canteen cooking.-The pollutants include organics in the full volatility range (VOCs, SVOCs, IVOCs, and xLVOCs), PM2.5, ultrafine particles (UFPs), and polycyclic aromatic hydrocarbons (PAHs, encompassing gaseous PAHs, particulate PAHs, and benzo[a]pyrene equivalents (BaPeq))- The emissions of UFPs are in particles/yr and emissions of other pollutants are in kt/year.
DOI: 10.6084/m9.figshare.28078370
title: Diversity, Diversity and Tolerance profile of Wild Yeasts from Natural Forests

description: In a natural forest in southwest Ethiopia, the study investigates the diversity and distribution of wild yeast species in the rhizosphere soil and plant surfaces. With high rates of yeast isolation from tree bark, it exposes a variety of yeast genera. Seasonal differences in yeast abundance were also discovered by the study; spring and summer demonstrated significant positive relationships. The discovery of stress-tolerant yeast species showed how adaptable they are to harsh environments. The study emphasizes the potential of stress-tolerant yeasts for biotechnological applications as well as the significance of natural forests as repositories of microbial diversity.
DOI: 10.6084/m9.figshare.28123442
title: <b>Exploring the Relationship between Macroeconomic Indicators on sectoral Indices of Indian Stock Market</b>

description: The influence of macroeconomic indicators makes it important to study the relationship between macroeconomic indicators and stock market return.
DOI: 10.6084/m9.figshare.28558205
title: Supplementary Material for: Coexisting Collagenous Sprue and Celiac Disease: A Case Report

description: Introduction: Collagenous sprue (CS) is an extremely rare enteropathy of unknown etiology and if untreated, can lead to substantial morbidity and mortality. CS often co-presents with celiac disease. The presence of a subepithelial collagen band on histology differentiates CS from celiac disease, as both have villous blunting. The management of the two diseases is different, and thus it is critical that the proper diagnosis of CS is made promptly to prevent complications. 

Case Presentation: We present a case report of collagenous sprue in an elderly male who was initially diagnosed with celiac disease alone before returning to care years later with unresolved gastrointestinal symptoms. 

Conclusion: Clinicians must verify that CS has been ruled out following a celiac disease diagnosis. In regard to CS’s mechanism, CS’s high frequency of comorbid autoimmune conditions and its robust response to corticosteroids support an immune-mediated process. Future research should continue to aim to elucidate the mechanism as it would allow for a more targeted approach to treatment, such as anti-fibrotic or specific immunomodulator therapy.
DOI: 10.6084/m9.figshare.28722095
title: Supplementary Material for: Dynamic Prediction of Cardiovascular Death among Old People with Mildly Reduced Kidney Function Using Deep Learning Models Based on a Prospective Cohort Study

description: ABSTRACT
Aim: Cardiovascular disease (CVD) is more likely to occur in old people with mildly reduced kidney function. We aimed to identify target features in this cohort to reduce cardiovascular death using deep learning models.
Methods: A total of 12,650 order people (age ≥ 60) with mildly reduced kidney function from Tianjin Community Health Promotion Prospective Study were recruited from 2014 to 2020. Cardiovascular death was verified by the death certificates from the provincial vital statistics offices. Mildly reduced kidney function was defined when estimated glomerular filtration rate (eGFR) between 45 mL/min/1.73m2 ≤and 90 mL/min/1.73m2. Data were analyzed using Cox regression, Random Survival Forest (RSF), DeepHit (DH), and Dynamic DH (DDH). Concordance Index (C-index) and Brier Score(B-S) were used to compare the models' performances.
Results: During the follow-up of 7 years, 838 people died of CVD (6.62%). Age, gender, hypertension, diabetes, and eGFR were closely related to cardiovascular death. Both accuracy and precision of models, predictive performance gets better as the number of follow-up visits increases. In predicting cardiovascular death, the C-index and B-S value of COX were only 0.711 and 0.001 at the first follow-up, and values were 0.767 and 0.073 at last time, respectively. This trend is similar in the other three models, with the DDH model standing, which showed the individual survival prediction with more accuracy at different time points (for the 6-year survival prediction, the C-index = 0.797 and B-S = 0.022 for the average of all time points) than the Cox, RSF, and DH.
Conclusion: A novel deep learning algorithm used in our study has shown its superior performance in the prediction of individual dynamics in longitudinal studies, which improves predictive power with increasing data input over time.
DOI: 10.6084/m9.figshare.28723145
title: Supplementary Material for: Trauma-induced psoriatic arthritis: A deep Köbner phenomenon

description: Introduction: Psoriasis is a chronic systemic inflammatory disorder resulting from complex interactions between genetic and environmental factors. In addition to cutaneous manifestations, psoriasis is associated with psoriatic arthritis (PsA). Among the recognized mechanisms of disease exacerbation, the Köbner phenomenon (KP) plays a crucial role. KP refers to the appearance of new psoriatic lesions on previously healthy skin following trauma. A deeper variant of this phenomenon, the deep Köbner phenomenon (DKP), involves severe trauma triggering systemic inflammation, including the onset of PsA. Trauma-induced DKP represents unique disease mechanisms, linking external mechanical stress to immune-mediated joint pathology.
Case Presentation: We present a case of a 60-year-old male with psoriasis, who initially responded well to ixekizumab, an IL-17A inhibitor, but subsequently developed PsA following a wrist injury. The PsA exacerbation was attributed to increased mechanical stress from daily activities and rehabilitation efforts. Adjustments were made to rehabilitation intensity and joint movement restrictions, leading to gradual symptom improvement over three months without intensifying biological therapy.
Conclusion: This case highlights the pathophysiological relationship between trauma, DKP, and PsA. The rapid onset of PsA following trauma suggests that inflammatory mediators and neuropeptides triggered by DKP play significant roles. Given that rehabilitation plays crucial roles in recovery but may also exacerbate symptoms if improperly managed, tailored rehabilitation strategies are essential in managing trauma-induced PsA. This case also underscores the importance of comprehensive management, including biological therapy and personalized rehabilitation approaches. Further studies are needed to optimize inflammation control and joint function in patients experiencing post-trauma PsA.