cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18164865
title: Data for "How cloud geometry and solar zenith angle control 3D radiative effects"

description: Supporting data for figures in "How cloud geometry and solar zenith angle control 3D radiative effects."

 Includes:



Cloud properties 



Aspect ratio (aspect_ratio_summary.csv)

Transmissivity (etas.csv)



Fields of 3D and 1D downwelling surface shortwave fluxes of diffuse and direct radiation calculated with the ray tracer of https://github.com/microhh/rte-rrtmgp-cpp



Shallow cumulus, subset due to memory requirements (cb_data_gas_false_results.tar.gz)

Deep convection (trmm_data_gas_false_results.tar.gz)

Stratocumulus (pinacles_data_gas_false_results.tar.gz)



Summary fluxes



Shallow cumulus (cloud_bot_surface_flux_summaries.tar)

Deep convection (trmm_surface_flux_summaries.tar)

Stratocumulus (pinacles_surface_flux_summaries.tar)




 

Scripts for using this data to produce manuscript figures are available via https://github.com/magpowell/3D_radiative_effects
DOI: 10.5061/dryad.tht76hf5d
title: Implementation of guidelines on prevention of coercion and violence (PreVCo) in psychiatry

description: Fifty-four psychiatric wards in Germany treating voluntary and involuntary
 patients were randomly allocated to either an intervention or to a waiting
 list condition. The intervention consisted of the implementation of three
 out of 12 suggested recommendations as selected by the ward teams,
 supported by external study workers. As the primary outcome measure, the
 number of coercive measures used per bed and month in the final 3 months
 of the intervention period was determined. Secondary outcomes were the
 cumulative duration of coercive measures used per bed and months and
 assaults per bed and month. Achieved guideline adherence was measured by a
 fidelity scale developed for this purpose during a pilot study for the
 PreVCo Rating Tool. After a 3-month baseline collection period under
 routine conditions, randomisation was done after matching wards pairwise
 according to frequency of coercive measures used and scores on the PreVCo
 Rating Tool at baseline. 
description: # Title of Dataset 
 Minimal_dataset_Implementation_of_guidelines_on_prevention_of_coercion_and_violence_PreVCo_in_Psychiatry_a_multicentre_randomised_controlled_trial ## Description of the data and file structure The file "Minimal_dataset_Implementation_of_guidelines_on_prevention_of_coercion_and_violence_PreVCo_in_Psychiatry_a_multicentre_randomised_controlled_trial" contains the necessary information on the primary and secondary outcomes, necessary for replication of the main findings. The table "Minimal_dataset_PreVCo" contains the data for calculations. 'NULL' denotes missing values. The table "Codebook" contains the vcontains the variable labels, the variable values and the variable descriptions. ## Code/Software
DOI: 10.6084/m9.figshare.31171437.v1
title: Evaluation of supervised machine learning models in predicting temporomandibular joint disc displacement on 3T magnetic resonance imaging

description: To evaluate supervised machine learning (ML) models for classifying temporomandibular joint (TMJ) disc displacement on MRI using morphometric and signal intensity features. This retrospective study analyzed 324 TMJs from 162 individuals who underwent 3T MRI. Extracted features included condylar anteroposterior and mediolateral diameters, disc and condyle morphology, and lateral pterygoid muscle signal intensity ratios. Six ML algorithms (Random Forest, Gaussian Naïve Bayes, Logistic Regression, AdaBoost, Gradient Boost, and k-Nearest Neighbor) were evaluated using stratified 5-fold cross-validation. Performance was assessed with accuracy, macro-averaged recall, precision, F1-score, and ROC-AUC. All models demonstrated good classification performance (ROC-AUC &gt;0.80). AdaBoost achieved the highest ROC-AUC (0.88), while Gaussian Naïve Bayes showed the most balanced overall metrics. Mediolateral condylar diameter and disc morphology were key features associated with disc displacement categories. ML models can identify MRI-based morphometric patterns related to TMJ disc displacement and may support radiologic assessment, while clinical diagnosis should continue to rely on established standards of care.
DOI: 10.6084/m9.figshare.31171437
title: Evaluation of supervised machine learning models in predicting temporomandibular joint disc displacement on 3T magnetic resonance imaging

description: To evaluate supervised machine learning (ML) models for classifying temporomandibular joint (TMJ) disc displacement on MRI using morphometric and signal intensity features. This retrospective study analyzed 324 TMJs from 162 individuals who underwent 3T MRI. Extracted features included condylar anteroposterior and mediolateral diameters, disc and condyle morphology, and lateral pterygoid muscle signal intensity ratios. Six ML algorithms (Random Forest, Gaussian Naïve Bayes, Logistic Regression, AdaBoost, Gradient Boost, and k-Nearest Neighbor) were evaluated using stratified 5-fold cross-validation. Performance was assessed with accuracy, macro-averaged recall, precision, F1-score, and ROC-AUC. All models demonstrated good classification performance (ROC-AUC &gt;0.80). AdaBoost achieved the highest ROC-AUC (0.88), while Gaussian Naïve Bayes showed the most balanced overall metrics. Mediolateral condylar diameter and disc morphology were key features associated with disc displacement categories. ML models can identify MRI-based morphometric patterns related to TMJ disc displacement and may support radiologic assessment, while clinical diagnosis should continue to rely on established standards of care.
DOI: 10.5061/dryad.73n5tb33m
title: Particulate organic carbon sedimentation triggers lagged methane emissions in a eutrophic reservoir

description: Reservoirs act as carbon sinks when sedimentation of particulate organic
 carbon (POC) exceeds CO2 and CH4 emissions. Here, we study the poorly
 explored process where phytoplankton-derived acidic polysaccharides (APs)
 aggregate into particulate organic matter, promoting carbon export to
 sediments. This source of particulate organic carbon (POC) in sediments
 can mineralize to CO2 and CH4 over various timescales. Our research,
 centered on a Mediterranean reservoir, elucidates phenological trends of
 APs and POC sedimentation and identifies their predominant drivers. Our
 findings present synchronic sedimentation patterns of POC and APs but
 identify a two-week delay between POC sedimentation and CH4 emissions.
 Despite its eutrophic status, our data demonstrate that this reservoir
 acts as a carbon sink by sequestering 4.33 g C m-2 y-1, which accentuates
 the importance of temporal integration at multiple scales when analyzing
 carbon budget within reservoirs.
description: # Particulate organic carbon sedimentation triggers lagged methane
 emissions in reservoirs 
 **AUTHORS:** Andrés Martínez-García, Ignacio Peralta-Maraver, Eva
 Rodríguez-Velasco, Gema L. Batanero, Miriam García-Alguacil, Félix Picazo,
 Juan Calvo, Rafael Morales-Baquero, Francisco J. Rueda, Isabel Reche
 **FILES:** Contains 2 files: **1. Script.r** - R script to replicates
 analyses and the figures including: Figure 2: Seasonal variation in
 sedimentation rates of acidic polysaccharides (APs) and particulate
 organic carbon (POC). Figure 3: Seasonal variations in the primary
 predictors influencing the sedimentation rates of acidic polysaccharides
 (APs) and particulate organic carbon (POC). Figure 3: Regression analysis
 showing the primary predictors of sedimentation rates for acidic
 polysaccharides (APs) and particulate organic carbon (POC). Figure 4:
 Seasonal dynamics of POC sedimentation rate and
 CO<sub>2</sub> emissions. **2. Dataset** with three sheets
 2.1. Sheet 1 - time_series: Contains information of the sampled variables
 during the study period. **Columns**: date: date of sampling zone: sampled
 depth state: mixing vs. stratifying period aps_c: concentration of acid
 polysaccharides aps_f: flux of acid polysaccharides pom_c: concentration
 of particulate organic carbon pom_f: flux of particulate organic carbon
 chla: concentration of chlorophyll-a cations: disolved divalent cations
 pa: prokaryotic abundance cya: cyanobacteria abundance 2.2. Sheet 2 - GHGs
 emission: Data on greenhouse gas emissions within the studied system.
 **Columns**: date: date of sampling. \**IMPORTANT NOTE: **empty cells in
 dataset represent missing values
DOI: 10.5061/dryad.fqz612jzs
title: Characterizing ambient air quality and oil and gas air pollution emissions in Broomfield County, CO

description: Unconventional oil and natural gas development (UOGD) has expanded rapidly
 across the United States in recent decades and raised concerns about
 associated air quality impacts. While significant effort has been made to
 quantify methane emissions, relatively few observations have been made of
 Volatile Organic Compounds (VOCs), especially during drilling and
 completion of new wells. Extensive air monitoring during development of
 several large, multi-well pads in Broomfield, Colorado, in the
 Denver-Julesburg Basin, provides a novel opportunity to examine changes in
 local air toxics and other VOC concentrations during well drilling and
 completions and production.
description: This data set includes VOC measurements collected in
 weekly-integrated and event-triggered canisters in Broomfield County,
 Colorado. Field measurements were conducted from October 2018 through
 December 2022 at as many as 19 sites near well pads, in adjacent
 neighborhoods, and at a more distant reference location, we identify
 impacts from each phase of well development and production.
description: **Title:** Characterizing ambient air quality and oil and gas air
 pollution emissions in Broomfield County, CO **Abstract:** Unconventional
 oil and natural gas development (UOGD) has expanded rapidly across the
 United States in recent decades and raised concerns about associated air
 quality impacts. While significant effort has been made to quantify
 methane emissions, relatively few observations have been made of Volatile
 Organic Compounds (VOCs), especially during drilling and completion of new
 wells. Extensive air monitoring during development of several large,
 multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin,
 provides a novel opportunity to examine changes in local air toxics and
 other VOC concentrations during well drilling and completions and
 production. This data set includes VOCs measurement collected in
 weekly-integrated and event-triggered canisters in Broomfield County,
 Colorado. Field measurements were conducted from October 2018 through
 Decemember 2022 at as many as 19 sites near well pads, in adjacent
 neighborhoods, and at a more distant reference location, we identify
 impacts from each phase of well development and production. **Contact:**
 **Jeffrey L. Collett, Jr.** Project PI
 [Jeffrey.collett@colostate.edu](mailto:Jeffrey.collett@colostate.edu)  
 **Recommended data citation** – Ku, I-T., Zhou, Y., Hecobian, A.,
 Benedict, K. B., Buck, B., Lachenmayer, E., Terry, B., Frazier, M., Zhang,
 J., Pan, D., Low, L., Sullivan, A. P., & Collett, J. (2023).
 Characterizing ambient air quality and oil and gas air pollution emissions
 in Broomfield County, CO [dataset]. Colorado State University. Libraries.
 **Format of data files** – .csv **Location where data were collected** –
 Broomfield County, Colorado. **Time period during which data were
 collected** – 2018-10-04 - 2022-12-29. **File Information** This data set
 includes 2 Excel (.csv) files and 2 ReadMe (.txt) files.
DOI: 10.5061/dryad.7pvmcvf11
title: Predicted genome-wide chromatin contact differences among 71 bonobos and chimpanzees

description: This file contains predicted chromatin contact differences in HFF cells
 using Akita among pairs of 71 bonobos and chimpanzees at 4,420 ~ 1 Mb
 genomic windows in the panTro6 genome. Each entry corresponds to a
 pairwise comparison at a given window. Data per comparison includes the
 individual IDs in the pairwise comparison, lineages represented,
 chromosome, position, window ID, mean squared error, Spearman correlation,
 divergence (1 - Spearman correlation), and the number of nucleotide
 differences for the pair at the given window.
description: All data in this file were generated using publicly available
 datasets (see below). Variants were filtered using bcftools to retain
 high-quality sites and high-quality genotypes. The dataframe was created
 using Pandas in a Python Jupyter notebook. Data used to
 generate these predictions: chimpanzee
 reference sequence (https://hgdownload.soe.ucsc.edu/goldenPath/panTro6/bigZips/) Illumina short reads for 71 bonobos and chimpanzees (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA189439, https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB15086)
description: This file contains descriptions of the column headers for
 "HFF\_comparisons.txt". * ind1 = individual 1 in comparison *
 ind2 = individual 2 in comparison * lineages = lineages represented in
 comparison (ppn = bonobo, pte = Nigeria-Cameroon chimpanzee, pts = eastern
 chimpanzee, ptt = central chimpanzee, ptv = western chimpanzee) * chr =
 chromosome * window\_start = 0-based position in panTro6 coordinates *
 window = window ID * mse = mean squared error between contact maps for
 individual 1 and individual 2 * spearman = Spearman correlation between
 contact maps for individual 1 and individual 2 * divergence = 1 - Spearman
 correlation between contact maps for individual 1 and individual 2 *
 seq\_diff = the number of nucleotide differences between individual 1 and
 individual 2 for the window
DOI: 10.5061/dryad.x95x69prc
title: Below-ground pitfall traps for standardised monitoring of soil mesofauna: Design and comparison to Berlese/Tullgren funnels

description: The attached CSV file supports the article Below-ground pitfall traps for
 standardised monitoring of soil mesofauna: Design and comparison to
 Berlese/Tullgren funnels (Pedobiologia, Volume 101, 2023, 150911,
 ISSN 0031-4056, https://doi.org/10.1016/j.pedobi.2023.150911)
 relative to its comparison part. It presents the specimen count of the
 deployed pitfall traps and Berlese/Tullgren extractions across five
 environments at different positions along transects. The attached stl file
 is the blueprint for the 3d printable trap connector described and
 referenced in the same article. 
description: The dataset was generated by identifying and counting the
 specimens collected in pitfall traps or Berlese extractions across five
 different environments along 5 paired positions across a transect. The
 traps were deployed and the cores were collected in Norfolk, UK, in June
 2021.
description: # Below-ground pitfall traps for standardised monitoring of soil
 mesofauna: Design and comparison to Berlese/Tullgren funnels
 [https://doi.org/10.5061/dryad.x95x69prc](https://doi.org/10.5061/dryad.x95x69prc) The database contains an abundance matrix of soil invertebrates collected with two different methods and across five environments. ## Description of the data and file structure The dataset contains a column "Sampling" indicating whether the specimens were collected with pitfall traps or Berlese/Tullgren extractions; a column "Environment" indicating the environment where the samples were collected; a column ("Transect position") indicating the paired position across the transect the two sets of samples (pitfall traps and Berlese/Tullgren extractions) were collected. The other columns represent species (for springtails) or clades (for other taxa) and the cells contain individual counts. ## Sharing/Access information The dataset supports the comparison section of the Journal article linked here: [https://doi.org/10.1016/j.pedobi.2023.150911](https://doi.org/10.1016/j.pedobi.2023.150911 "Persistent link using digital object identifier")
DOI: 10.5281/zenodo.18405006
title: Table 1 in Iheringichthys syi (Siluriformes: Pimelodidae), a new pimelodid species from upper Paraná basin, Brazil

description: Table 1. Morphometric data of holotype and 26 paratypes of Iheringichthys syi. Min = minimum; Max = maximum; SD = Standard Deviation; SOC = Supraoccipital Process.
HolotypeMin.Max.MeanSDSL (mm)149.1091.22185.00--Percents of Standard LengthPredorsal length40.3738.1942.1139.910.0096Preventral length50.1046.4451.9549.290.0120Preanal length76.7670.8277.1274.690.0160Origin of pectoral fin/origin of pelvic fin24.9321.9225.4823.990.0096Origin of pelvic fin/origin of anal fin27.2224.3228.5426.150.0100Dorsal-spine length22.4517.3523.8421.070.0140Dorsal-fin base14.8014.1618.1215.190.0083Adipose-fin base25.5123.4627.0325.110.0100Adipose-fin height5.584.897.816.300.0059Pectoral-spine length16.8616.3920.1318.350.0111Ventral-fin length17.4617.4620.3618.590.0079Anal-fin base10.458.4211.609.680.0076Body depth20.8318.8624.4321.230.0146Caudal peduncle depth8.307.669.008.200.0030Caudal peduncle length19.5014.8119.5217.360.0101Head length30.6327.9031.9329.930.0102Posterior SOC length8.506.488.877.860.0057Posterior SOC width5.424.066.655.610.0053Percents of Head LengthHead depth56.8552.4164.6159.040.0340Head width61.5653.2965.0159.200.0258Head width at nares28.4028.4038.5032.510.0198Snout length46.3542.0652.6546.830.0254Horizontal orbital diameter25.8123.3032.2427.230.0239Interorbital length20.8516.2224.8821.370.0192Postorbital length31.0930.6135.3732.090.0114Snout to anterior nare14.8010.5416.1413.610.0148Distance between nares10.779.6213.7612.090.0104Posterior nare/anterior margin of eye22.5616.4423.9819.520.0191
description: Published as part of Azpelicueta, María de las Mercedes & Britski, Heraldo A., 2012, Iheringichthys syi (Siluriformes: Pimelodidae), a new pimelodid species from upper Paraná basin, Brazil, pp. 47 in Neotropical Ichthyology 10 (1) on page 47, DOI: 10.1590/S1679-62252012000100004, http://zenodo.org/record/10476606
DOI: 10.5281/zenodo.18405007
title: Table 1 in Iheringichthys syi (Siluriformes: Pimelodidae), a new pimelodid species from upper Paraná basin, Brazil

description: Table 1. Morphometric data of holotype and 26 paratypes of Iheringichthys syi. Min = minimum; Max = maximum; SD = Standard Deviation; SOC = Supraoccipital Process.
HolotypeMin.Max.MeanSDSL (mm)149.1091.22185.00--Percents of Standard LengthPredorsal length40.3738.1942.1139.910.0096Preventral length50.1046.4451.9549.290.0120Preanal length76.7670.8277.1274.690.0160Origin of pectoral fin/origin of pelvic fin24.9321.9225.4823.990.0096Origin of pelvic fin/origin of anal fin27.2224.3228.5426.150.0100Dorsal-spine length22.4517.3523.8421.070.0140Dorsal-fin base14.8014.1618.1215.190.0083Adipose-fin base25.5123.4627.0325.110.0100Adipose-fin height5.584.897.816.300.0059Pectoral-spine length16.8616.3920.1318.350.0111Ventral-fin length17.4617.4620.3618.590.0079Anal-fin base10.458.4211.609.680.0076Body depth20.8318.8624.4321.230.0146Caudal peduncle depth8.307.669.008.200.0030Caudal peduncle length19.5014.8119.5217.360.0101Head length30.6327.9031.9329.930.0102Posterior SOC length8.506.488.877.860.0057Posterior SOC width5.424.066.655.610.0053Percents of Head LengthHead depth56.8552.4164.6159.040.0340Head width61.5653.2965.0159.200.0258Head width at nares28.4028.4038.5032.510.0198Snout length46.3542.0652.6546.830.0254Horizontal orbital diameter25.8123.3032.2427.230.0239Interorbital length20.8516.2224.8821.370.0192Postorbital length31.0930.6135.3732.090.0114Snout to anterior nare14.8010.5416.1413.610.0148Distance between nares10.779.6213.7612.090.0104Posterior nare/anterior margin of eye22.5616.4423.9819.520.0191
description: Published as part of Azpelicueta, María de las Mercedes & Britski, Heraldo A., 2012, Iheringichthys syi (Siluriformes: Pimelodidae), a new pimelodid species from upper Paraná basin, Brazil, pp. 47 in Neotropical Ichthyology 10 (1) on page 47, DOI: 10.1590/S1679-62252012000100004, http://zenodo.org/record/10476606
DOI: 10.5061/dryad.mpg4f4r67
title: Data from: Plastid phylogenomics and cytonuclear discordance in Rubioideae, Rubiaceae

description: In this study of evolutionary relationships in the subfamily Rubioideae
 (Rubiaceae), we take advantage of the off-target proportion of reads
 generated via previous target capture sequencing projects based on nuclear
 genomic data to build a plastome phylogeny and investigate cytonuclear
 discordance. The assembly of off-target reads resulted in a comprehensive
 plastome dataset and robust inference of phylogenetic relationships, where
 most intratribal and intertribal relationships are resolved with strong
 support. While the phylogenetic results were mostly in agreement with
 previous studies based on plastome data, novel relationships in the
 plastid perspective were also detected. For example, our analyses of
 plastome data provide strong support for the SCOUT clade and its sister
 relationship to the remaining members of the subfamily, which differs from
 previous results based on plastid data but agrees with recent results
 based on nuclear genomic data. However, several instances of highly
 supported cytonuclear discordance were identified across the Rubioideae
 phylogeny. Coalescent simulation analysis indicates that, while ILS could
 by itself explain the majority of the discordant relationships, plastome
 introgression may be the better explanation in some cases. Our study
 further indicates that plastomes across the Rubioideae are with few
 exceptions highly conserved and mainly conform to the structure, gene
 content, and gene order present in the majority of the flowering plants.
description: # Data from: Plastid phylogenomics and cytonuclear discordance in
 Rubioideae, Rubiaceae
 [https://doi.org/10.5061/dryad.mpg4f4r67](https://doi.org/10.5061/dryad.mpg4f4r67) This dataset contains 120 plastome sequences. The sequences were assembled using publically available paired-end Illumina sequencing data. ## Description of the data and file structure plastomes\_dryad.zip: a zipped folder containing the assembled plastome sequences as .gff annotation files with fasta sequences included.
DOI: 10.15468/dl.hkpt8e
title: Occurrence Download

description: A dataset containing 690 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Auchenoceros punctatus",
 "HasCoordinate is true",
 "DecimalLatitude is greater than -90",
 "DecimalLatitude is less than 90",
 "DecimalLongitude is greater than -180",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950",
 "Year is less than or equal to 2014"
 ]
}

 The dataset includes 690 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003776-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.