cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-1095/646
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DOI: 10.18419/darus-1095/668
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DOI: 10.15468/dl.x99e6d
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Observation, Machine Observation, Human Observation, Material sample, Material citation, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cladodonta lyallii (J.D.Hooker & Harvey) Skottsberg, 1923",
 "Year 1950-2024"
 ]
}

 The dataset includes 24 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037507-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-1095/669
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DOI: 10.18419/darus-1095/677
title: KK06-09.mtl

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DOI: 10.18419/darus-1095/678
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DOI: 10.18419/darus-1095/679
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DOI: 10.18419/darus-1095/681
title: KK06-09.las

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DOI: 10.18419/darus-1666/1
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DOI: 10.18419/darus-1666/2
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DOI: 10.18419/darus-1666/4
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DOI: 10.18419/darus-1666/5
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DOI: 10.18419/darus-1666/9
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title: KK10-09.mtl

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DOI: 10.18419/darus-1666/17
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DOI: 10.18419/darus-1666/18
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DOI: 10.18419/darus-1666/19
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DOI: 10.18419/darus-1666/20
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DOI: 10.18419/darus-1666/21
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DOI: 10.5281/zenodo.10520198
title: NOAA GML and CIRES/Uni. of Colorado-Boulder Ceilometer Cloud Data Products at Kettle Ponds (CKP) for SPLASH

description: Cloud base height / vertical visibility and attenuated backscatter coefficient profiles from NOAA GML's Vaisala CL51 ceilometer deployed at Kettle Ponds (CKP). Data have been sampled to nearest 1-min. See Readme document for details.
DOI: 10.15468/dd.qww46f
title: Data downloaded for the study Sydenham et al (2024). Climatic conditions and landscape diversity predict plant-bee interactions and pollen deposition in bee-pollinated plants. Ecography, doi: 10.1111/ecog.07138

description: Wild bee occurrence data downloaded 22.02.2022 and used to estimate the regional commonness of bee species within our study region.
DOI: 10.18419/darus-1666/22
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DOI: 10.18419/darus-1666/23
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description: :unav
DOI: 10.4121/a6333b17-bab2-476f-a636-61244b5c6f9e.v1
title: Code and data underlying the thesis "Evidence based expert judgment in flood risk"

description: This repository contains and describes the data and code base used to generate and support the results of the dissertation "Evidence based expert judgment in flood risk" by Guus Rongen (2024). This thesis investigates the use of structured expert judgment in flood risk assessments through four studies. An overview of the studies, the supporting software, and the license is shown in the README file. Furthermore, separate README files are added to the subdirectories, to describe details on the code and data related to each of the topics.
DOI: 10.5066/p9nod5es
title: Hydrogen and oxygen stable isotope mass balance evaluation of the National Water Model (v2.1) streamflow, runoff and groundwater flows

description: This data release contains the results of an isotopic mass balance approach to provide an estimate of the long-term average isotope ratios of NWM streamflow for the summer season (JJA) between 2000 and 2019 in the Western United States. The NWM-estimated long-term average isotope ratios are compared directly to 6426 stream stable isotope observations in 995 unique catchments. Quantified similarities and differences, in the form of p-values, provide useful information about important hydrologic processes. Significant p-values mean that the observed isotope ratio differs from the long-term average mass balance calculated isotope ratios and indicates that flows may be influenced by processes that are not accounted for by the NWM. For δ18O, 1821 observations were significantly different from the NWM estimate, whereas for δ2H, 4281 observations were significantly different from the NWM estimate.
DOI: 10.5281/zenodo.10695570
title: Raw data to "(Almost) Everything is a Dicke model – Mapping correlated light-matter systems to the exactly solvable Dicke model"

description: This collection of data is complementary to the linked publication "(Almost) Everything is a Dicke model – Mapping correlated light-matter systems to the exactly solvable Dicke model", Andreas Schellenberger, Kai Phillip Schmidt, 2024, in preparation.


It contains all data used for all figures in the publication. The files are structured according to the figures as







Fig. 1: `visualization_model.blend`



Fig. 2: `spectrum_effective_Dicke_model.yaml`

Fig. 3: `phase_diagram_Dicke_Ising.yaml`

Fig. 4: `spectrum_Dicke_Ising_PNP.yaml`

Fig. 5: `spectrum_Dicke_Ising_ANP.yaml`

Fig. 6: `comparison_ED.yaml`

Fig. 7: `comparison_pcstpp.yaml`


For the pcst++ calculations, done in Sec. 3.4, we provide a separate file `coefficients_expectation_values_pcstpp.yaml` including the coefficients and expectation values for the investigated systems. For the coefficient calculation, the program openly available under GitHub was used (https://github.com/FAU-kpslab/pcstpp_CoefficientGenerator).


More information about the data is given as comments within the individual files.





For the file `visualization_model.blend` of the 3D model you need blender (https://www.blender.org) or another program that can handle `.blend` files.




For further information about the data we refer to the linked publication (in preparation).


If any question may arise, you are highly welcome to contact us (see, e.g., contact information on the publication).
DOI: 10.5281/zenodo.11092106
title: Sulfate anomaly during CAFE-EU/BLUESKY 10 days LAGRANTO back trajectories

description: Short description

The dataset contains trajectories along one segment of the flight path during research flight 01 (RF01) during the CAFE-EU/BLUESKY mission. In this segment we observed a particulate sulfate anomaly and are interested in the air mass origin. Therefore, we built a cross structure to sample in total 231 trajectories for each release point. The detailed method and analysis is published in the corresponding and related work.

 

Funding

This project has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR 301 – Project-ID 428312742, TPChange:  The Tropopause Region in a Changing Atmosphere (https://tpchange.de/).
DOI: 10.5281/zenodo.11294495
title: Archive of the microtremor data used in Cho and Nakazawa 2024

description: This archive includes microtremor data and the analysis results used in "Shallow microtremor survey using miniature and small arrays: Strategy for efficient and feasible dense survey" by Ikuo Cho and Tsutomu Nakazawa (2024, Earth and Space Science).
DOI: 10.5281/zenodo.5775266
title: Aspergillus fumigatus pangenome dataset

description: <em>Aspergillus fumigatus </em>is a deadly agent of human fungal disease, where virulence heterogeneity is thought to be at least partially structured by genetic variation between strains. While population genomic analyses based on reference genome alignments offer valuable insights into how gene variants are distributed across populations, these approaches fail to capture intraspecific variation in genes absent from the reference genome. Pan-genomic analyses based on <em>de novo</em> assemblies offer a promising alternative to reference-based genomics, with the potential to address the full genetic repertoire of a species. Here, we use a combination of population genomics, phylogenomics, and pan-genomics to assess population structure and recombination frequency, phylogenetically structured gene presence-absence variation, evidence for metabolic specificity, and the distribution of putative antifungal resistance genes in <em>A. fumigatus</em>. We provide evidence for three distinct populations of <em>A. fumigatus</em>, structured by both gene variation (SNPs and indels) and distinct gene presence-absence variation with unique suites of accessory genes present exclusively in each clade. Accessory genes displayed functional enrichment for nitrogen and carbohydrate metabolism, hinting that populations may be stratified by environmental niche specialization. Similarly, the distribution of antifungal resistance genes and resistance alleles were often structured by phylogeny. Despite low levels of outcrossing, <em>A. fumigatus</em> demonstrated a large pan-genome including many genes unrepresented in the Af293 reference genome. These results highlight the inadequacy of relying on a single-reference based approach for evaluating intraspecific variation, and the power of combined genomic approaches to elucidate population structure, genetic diversity, and the putative ecological drivers of clinically relevant fungi.
DOI: 10.5281/zenodo.8432741
title: NOAA GML Kettle Ponds Broadband Solar Radiation Data for SPLASH

description: These files contain Surface Energy Balance data at the Kettle Ponds (CKP) site as part of NOAA’s Global Monitoring Laboratory’s deployment in the Sail-SPLASH Campaign between October 2021 through August 2023.
DOI: 10.5525/gla.researchdata.1371
title: CYRI-B mediated macropinocytosis drives metastasis via lysophosphatidic acid receptor uptake

description: This dataset contains primary data in the form of images, spreadsheets for analysis and videos that support the above paper. Please see details in the readme file and use the 'Request Data' button to be sent a link to download the dataset.
DOI: 10.6084/m9.figshare.24829959
title: Supplementary Material for: Diversity in Renal Mass Data Cohorts: Implications for Urology AI Researchers

description: Objective 
We examine the heterogeneity and distribution of the cohort populations in two publicly used radiological image cohorts, Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCIA TCGA KIRC) collection and 2019 MICCAI Kidney Tumor Segmentation Challenge (KiTS19), and deviations in real world population renal cancer data from National Cancer Database (NCDB) Participant User Data File (PUF) and tertiary center data. PUF data is used as an anchor for prevalence rate bias assessment. 
Specific gene expression and therefore biology of RCC differ by self-reported race especially between the African American and Caucasian population. AI algorithms learn from datasets, but if the dataset misrepresents the population, reinforcing bias may occur. Ignoring these demographic features may lead to inaccurate downstream effects, thereby limiting the translation of these analyses to clinical practice. Consciousness of model training biases is vital to patient care decisions when using models in clinical settings. 
Method 
Data evaluated included the gender, demographic and reported pathologic grading and cancer staging. American Urological Association risk levels were used. Poisson regression was used to estimate the population-based and sample specific estimation for prevalence rate and corresponding 95% confidence interval. SAS 9.4 was used for data analysis. 
Result 
Compared to PUF, KiTS19 and TCGA KIRC over sampled Caucasian by 9.5% (95% CI, -3.7% to 22.7%) and 15.1% (95% CI, 1.5% to 28.8%), under sampled African American by -6.7% (95% CI, -10% to -3.3%), -5.5% (95% CI, -9.3% to -1.8%). Tertiary also under sampled African American by -6.6% (95% CI, -8.7% to -4.6%). The tertiary cohort largely under sampled aggressive cancers by -14.7% (95% CI, -20.9% to -8.4%). No statistically significant difference was found among PUF, TCGA, and KiTS19 in aggressive rate, however heterogeneities in risk are notable. 
Conclusion 
Heterogeneities between cohorts need to be considered in future AI training and cross-validation for renal masses.
DOI: 10.6084/m9.figshare.24919590.v1
title: Processed data for analysis and visualization of results described in Gillespie et al, eLife 2024, "Neurofeedback training can modulate task-relevant replay rate in rats"

description: These processed data files are provided to enable the re-analysis and visualization of results published by Gillespie et al in the eLife reviewed preprint, "Neurofeedback training can modulate task-relevant memory replay rate in rats". The github codebase used to run these analyses is linked below. Please refer to this codebase and the manuscript for further details, and contact Anna Gillespie at the University of Washington with any questions.
DOI: 10.6084/m9.figshare.25200974
title: Supplementary Material for: Evaluating Hymenoptera Venom Allergy Severity: A Data-Centric Comparison of Grading Instruments

description: Introduction: While a consensus seems to have been reached with regards to the definition of anaphylaxis, there is no universal instrument for scoring allergic reaction severity despite more than 30 having been proposed by the time of writing. This severely hampers comparison of data between studies. While scales have been compared with regards to their utility in grading food-related reactions, no such comparisons have been made for Hymenoptera venom-associated reactions.
Methods: The study conducted a retrospective analysis to compare the severity of Hymenoptera venom allergy reactions in104 participants with suspected Hymenoptera venom allergy. The study applied six grading instruments to each reaction, also evaluating them against the NIAID/FAAN anaphylaxis criteria. Sensitivity, specificity, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) for identifying anaphylaxis were calculated. Severity scales were simplified into "mild," "moderate," and "severe" categories. The most common severity grade across the five scales was determined using a custom function to establish a consensus severity grade. 
Results: The most common culprit insects were honeybees (49.0%). Among the 88 participants with generalized reactions, the highest proportion had involvement of four organ systems. The scales showed high specificity for detecting anaphylaxis, especially when using higher grades of the Mueller, WAO, and Dribin scales. The diagnostic yields (AUC) varied, with the WAO scale having the highest AUC (0.94) for grades 3, 4, and 5. Spearman correlation analysis showed the strongest correlations seen between the Brown and Dribin, Ring & Messmer and Dribin, and Ring & Messmer and Reisman scales. The lowest correlations were observed with the Mueller scale when paired with the WAO, Reisman, and Dribin scales. An inter-rater reliability analysis showed substantial agreement between scales with the same number of grading levels. The agreement was highest for the Brown and Dribin scales, indicating a strong consistency in reaction severity classification across different instruments. 
Conclusion: While all instruments were effective in stratifying reactions, they showed limitations in differentiating milder phenotypes. The Brown and Dribin scales stood out for their high agreement with the consensus score and sensitivity in identifying anaphylaxis. Our findings suggest that adopting either of these scales could significantly unify the reporting of allergic reactions. We believe, the format of an instrument should be tailored to its intended purpose, with clinical decision aids being simpler and research tools being more detailed.
DOI: 10.6084/m9.figshare.25218521
title: Supplementary Material for: Shared and distinct renal transcriptome signatures in three standard mouse models of chronic kidney disease

description: Introduction: Several mouse models with diverse disease etiologies are used in preclinical research for chronic kidney disease (CKD). Here, we performed a head-to-head comparison of renal transcriptome signatures in standard mouse models of CKD to assess shared and distinct molecular changes in three mouse models commonly employed in preclinical CKD research and drug discovery. 
Methods: All experiments were conducted on male C57BL/6J mice. Mice underwent sham, unilateral ureter obstruction (UUO) or unilateral ischemic reperfusion injury (uIRI) surgery and were terminated two- and six-weeks post-surgery, respectively. The adenine-supplemented diet-induced (ADI) model of CKD was established by feeding with adenine diet for six weeks and compared to control diet feeding. For all models, endpoints included plasma biochemistry, kidney histology and RNA sequencing. 
Results: All models displayed increased macrophage infiltration (F4/80 IHC) and fibrosis (Col1a1 IHC). Compared to corresponding controls, all models were characterized by an extensive number of renal differentially expressed genes (≥11,000) , with a notable overlap in transcriptomic signatures across models. Gene expression markers of fibrosis, inflammation and kidney injury supported histological findings. Interestingly, model-specific transcriptome signatures included several genes representing current drug targets for CKD, emphasizing advantages and limitations of the three CKD models in preclinical target and drug discovery.
Conclusion: The UUO, uIRI and ADI mouse models of CKD have significant commonalities in their renal global transcriptome profile. Model-specific renal transcriptional signatures should be considered when selecting the specific model in preclinical target and drug discovery.
DOI: 10.7267/zc77sz60m
title: Data and Scripts describing dissolved organic carbon concentrations across a stream network in Oregon following the 2020 Holiday Farm Wildfire

description: In 2020, the Holiday Farm Wildfire burned ~18 % of the McKenzie sub-basin in Oregon, USA. To investigate the impact of the wildfire on in-stream dissolved organic carbon (DOC) concentrations, we collected water samples from 129 stream sites within the McKenzie sub-basin stream network over four distinct seasonal wetness conditions (wetting, wet, drying, dry) between November 2022 and September 2023. This data was used to create spatial network models to model DOC concentrations across the stream network. This data package consists of (1) a spreadsheet spreadsheet containing DOC concentrations, landscape characteristics, and site information for the stream sites within the McKenzie sub-basin, OR, USA. (2) A spatial stream network (SSN) object developed for the McKenzie sub-basin from the proceeding DOC and landscape data. (3) Scripts written in R used to process, analyze, and report our findings from this data. This data package is associated with the publication "The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions post-fire" submitted to Biogeosciences (Wampler et al. 2024).
DOI: 10.18419/darus-1666/24
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DOI: 10.18419/darus-1666/25
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DOI: 10.18419/darus-1666/26
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DOI: 10.4225/08/5a7280a3a0d2a
title: CSIRO Australia Coastal Sealevel Simulation Hindcast

description: Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally, however, there is significant uncertainty around short-term coastal sea level variability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability (including extremes) around Australia by means of historical conditions as well as future changes under a high greenhouse gas emissions scenario (RCP 8.5). To do this, a multi-decade hindcast simulation is validated against tide gauge data. The role of tide-surge interaction is assessed and found to have negligible effects on storm surge characteristic heights over most of the coastline. For future projections, a couple of twenty-year long simulations are carried out over the time periods 1981-1999 and 2081-2099 using atmospheric forcing from four CMIP5 climate models. Results provide insights into how future atmospheric circulation changes may impact Australia’s coastal zone and highlight regions of potential sensitivity to atmospheric circulation changes. Areas of note are the Gulf of Carpentaria in the north where changes to the northwest monsoon could lead to relatively large increases in extreme sea levels during Austral summer. For the southern mainland coast the simulated scenarios suggest that a southward movement of the subtropical ridge leads to a small reduction in sea level extremes. This collections provides sea surface height data from the model forced with CFSR hindcast data.