cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25196030
title: Supplementary Material for: Exploring the methodological approaches of studies on radiographic databases used in cariology to feed AI: A Systematic Review

description: Introduction: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to certified dentists. This methodological systematic review aims to evaluate the different methodological approaches used by studies focusing on machine learning and deep learning and that have used radiographic databases to classify, detect, and segment dental caries.
Methods: The protocol was registered in PROSPERO before data collection (CRD42022348097). Literature research was performed in MEDLINE, Embase, IEEE Xplore, and Web of Science until December 2022, without language restrictions. Studies and surveys using a dental radiographic database for the classification, detection, or segmentation of carious lesions were sought. Records deemed eligible were retrieved and further assessed for inclusion by two reviewers who resolved any discrepancies through consensus. A third reviewer was consulted when any disagreements or discrepancies persist between the two reviewers.
After data extraction, the same reviewers assessed the methodological quality using the CLAIM and QUADAS-AI checklists. 
Results: After screening 325 articles, 35 studies were eligible and included. The bitewing was the most commonly used radiograph (n=17) at the time when detection (n=15) was the most explored computer vision task. The sample sizes used ranged from 95 to 38437, while the augmented training set ranged from 300 to 315786. Convolutional neural network (CNN) was the most commonly used model. The mean completeness of CLAIM items was 49 % (SD ± 34%). The applicability of the CLAIM checklist items revealed several weaknesses in the methodology of the selected studies: most of the studies were monocentric, and only 9% of them used an external test set when evaluating the model’s performance. The QUADAS-AI tool revealed that only 43% of the studies included in this systematic review were at low risk of bias concerning the standard reference domain. 
Conclusion: This review demonstrates that the overall scientific quality of studies conducted to feed AI algorithms is low. Some improvement in the design and validation of studies can be made with the development of a standardized guideline for the reproducibility and generalizability of results and, thus, their clinical applications.
DOI: 10.6084/m9.figshare.25943893
title: <b>An interpretable deep learning framework for genome-informed precision oncology</b>

description: Cancers result from aberrations in cellular signaling systems, typically resulting from driver somatic genome alterations (SGAs) in individual tumors. Precision oncology requires understanding the cellular state and selecting medications that induce vulnerability in cancer cells under such conditions. To this end, we developed a computational framework consisting of two components: 1) A representation-learning component, which learns a representation of the cellular signaling systems when perturbed by SGAs, using a biologically motivated and interpretable deep learning model. 2) A drug-response-prediction component, which predicts drug response by leveraging the information of the cellular state of the cancer cells derived by the first component. Our cell-state-oriented framework significantly improves drug response prediction accuracy compared to models using SGAs directly in cell lines. Moreover, our model performs well with real patient data. Importantly, our framework enables the prediction of response to chemotherapy agents based on SGAs, thus expanding genome-informed precision oncology beyond molecularly targeted drugs.
DOI: 10.6084/m9.figshare.4630375
title: Hymenoptera: UCE and Exon bait sets from Branstetter et al. 2017.

description: This file provides a brief description of each of the bait set files.<br>(1) 'hymenoptera-v2-PRINCIPAL-bait-set.fasta': This file includes 27,495 uce baits designed from 7 Hymenoptera genomes. This is the 'principal hym-v2 bait bait set' described in the paper.<br>(2) 'hymenoptera-v2-ANT-SPECIFIC-uce-baits.fasta': This file includes 9,446 uce baits designed from two ant genomes. It includes baits targeting uce loci only. The exon baits are included in separate files (described below).<br>(3) 'hymenoptera-v2-ANT-SPECIFIC-exon-baits-by-exon.fasta': This file includes 452 baits targeting legacy markers (exons) in ants. The baits target 16 exons from 12 genes and include sequences from 4 different ant taxa. The baits are organized by exon.<br>(4) 'hymenoptera-v2-ANT-SPECIFIC-exon-baits-by-gene.fasta': Same as (3), except that the baits are organized by gene.<br>(5) 'ANT-exon-sequences-40-taxa.fasta': Exon sequences from 12 legacy markers for 40 ant species (Ward, unpublished data). We used these sequences as 'baits' to extract exon data from enriched samples. The sequences are grouped by gene.<br>(6) 'ANT-exon-sequences-40-taxa-reduced.fasta': Same as (5), except that several exons were excluded so that each gene would only be represented by a single exon. This file worked the best for extracting exon data from enriched samples using PHYLUCE.
DOI: 10.18739/a2mp4vq0x
title: Snow–ice interface temperatures from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition in the Central Arctic (2019-2020)

description: The dataset contains snow–ice interface temperature measurements made during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition in the Central Arctic from October 2019 – September 2020 (MOSAiC ID: PS122/2). The data are time series measurements of snow–ice interface temperature from eight fixed first year ice locations. Each temperature sensor was installed next to an ice mass balance measurement station, and is identified by the associated ablation stake ID. These data are ancillary to an archived ice mass balance dataset, where detailed site and sampling descriptions can be found: doi:10.18739/A2NK36626.
DOI: 10.5281/zenodo.10088109
title: Imputed multiplexed DNA FISH data from mouse cells

description: Imputed multiplexed DNA FISH data from the following studies:

Huang et al 2021 (DOI: 10.1038/s41588-021-00863-6): 5kb resolution chromatin tracing data of mouse embryonic stem cells
Takei et al 2021 (DOI: 10.1038/s41586-020-03126-2): 5kb and 1Mb resolution DNA seqFISH+ data of mouse embryonic stem cells
Takei et al 2021 (DOI: 10.1126/science.abj1966): 1Mb resolution DNA seqFISH+ data of mouse brain cells (excitatory neurons not included)
DOI: 10.5281/zenodo.10477516
title: Seismic data from the HiSEIZE survey

description: Seismic data from the HiSEIZE acquisition. The data available:

Line 1 raw seismic data (.sgy)

Line 2 raw seismic data (.sgy)

Line 3 raw seismic data (.sgy)

Data is unprocessed and fully geometrized.

More details about the geometry can me found inside "Data_Description.txt"
DOI: 10.5281/zenodo.7729585
title: Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions

description: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1]. The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions. We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration. Database Details: - Covers all elements (Z: 1-108) and all edges - Large energy range: 0.01 - 4000 eV - Large momentum range: 0.05 -50 Å-1 - Fine log sampling: 128 points for energy and 256 points for momentum - Data format: GOSH [3] Calculation Details: - Single atoms only; solid-state effects are not considered - Unoccupied states before continuum states of ionization are not considered; no fine structure - Plane Wave Born Approximation - Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when - core-shell electron is excited - Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances - Both large and small component contributions of Dirac solutions are included in GOS - Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference. [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.
description: The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through Project No.G.0502.18N. This project has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 770887 PICOMETRICS and No. 823717 ESTEEM3).
DOI: 10.5281/zenodo.7876186
title: Extended X-ray absorption spectroscopy using an ultrashort pulse laboratory-scale laser-plasma accelerator

description: The data contained in this repository was used in the production of the publication "Extended X-ray absorption spectroscopy using an ultrashort pulse laboratory-scale laser-plasma accelerator"
description: We wish to acknowledge the support of the staff at the Central Laser Facility. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no 682399), as well as support from the John Adams Institute for Accelerator Science (STFC: ST/P002021/1, ST/V001639/1), the EPSRC (EP/S001379/1, EP/V044397/1, EP/N027175/1), the US DOE grant No. DE-SC0022109, the Knut and Alice Wallenberg Foundation (KAW 2019.0318), the Swedish Research Council (2019-04784), and the Helmholtz Association (VH-NG-1338).
DOI: 10.6084/m9.figshare.26132035.v1
title: TrapaJoE2024_WCVPTrapaDistributionMapping

description: This item complements the International Biological Flora: <i>Trapa natans</i><i> </i>(Journal of Ecology, in press) manuscript. It comprises two files, including:R Skript for Figure 1: "dist_Trapa_WCVP.r"Distribution Data used for creating Figure 1: "dist_Trapa_WCVP.geojson", based on data extracted for the <i>Trapa </i>genus from Govaerts, R., Nic Lughadha, E., Black, N., Turner, R. & Paton, A. (2021). The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. <i>Scientific Data</i>, <i>8</i>, 215.
DOI: 10.15468/dl.5fetzg
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prociphilus fraxinifolii (Riley, 1879)"
 ]
}

 The dataset includes 75 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0317815-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.20372/aau_rdm/eaogka
title: Rural Household Resilience to Food Insecurity in Majang Zone, Southwestern Ethiopia

description: The data is collected at the household level to measure resilience status and its determinants
DOI: 10.21410/dshs_2016/1hi8ms
title: La gouvernance territoriale en Europe entre convergence et capacité [2012-2014] = Territorial governance between convergence and capacity = La gobernanza territorial en Europa entre convergencia y capacidad

description: L'objet de l'enquête est la comparaison des processus de décentralisation de quatre régions européennes : le Pays de Galles (RU), la Bretagne (F), l’Andalousie (ES) et la Wallonie (B). Financé par la fondation Leverhulme (IN-2012-109) une équipe de chercheurs coordonnée par Alistair Cole de l’Université de Cardiff (puis Sciences Po Lyon) a réalisé une campagne d’entretiens à destination des élites régionales de ces quatre régions en 2012-2014. Ont été conduits (en français, en anglais ou en espagnol, selon les lieux) une centaine d'entretiens semi-directifs avec des panels (similaires dans les quatre pays) composés d’élus des groupes politiques représentés à l’Assemblée ; des agents des administrations publiques régionales (étatiques et/ou autonomes); et des représentants des réseaux d’action publique (notamment les syndicats et les organisations d’employeurs). Trois dimensions principales sont mises en avant dans les entretiens: l’expérience de la rigueur budgétaire liée à la crise (sur la qualité des services publics notamment); l’impact de l’Européisation normatif (notamment les effets de la nouvelle architecture budgétaire de l’UE sur la gestion territoriale); et la restructuration de l’État (sous ses diverses formes). Les entretiens o Ont aussi fait l'objet d'analyse de contenu sous le logiciel NVIVO selon les "nodes" : crise économique , Union européenne (et les régions) , dévolution, éducation, style , partis politiques , défis , finances publiques , Relations inter-gouvernementales, convergence, capacité , divergence Les résultats de l'enquête ont par ailleurs fait l'objet d'une quinzaine de publications (ouvrages, contributions, rapports), sur les cas "Pays de Galles", "Bretagne", "Andalousie" ou "Wallonie", ou sur la comparaison de leur mode de fonctionnement.
DOI: 10.24432/c5x60b
title: Metro Interstate Traffic Volume
DOI: 10.5281/zenodo.10080436
title: Decomposition of the horizontal wind divergence using MODES

description: Data used for plots and analyses in "Decomposition of the horizontal wind divergence associated with the Rossby, inertia-gravity, mixed Rossby-gravity, and Kelvin waves on the sphere" article. 
Data consists of Hough expansion coefficients for daily ERA5 data and Fourier coefficients of divergence of Kelvin (K), EIG, WIG, Rossby (R), and mixed Rossby-gravity (MRG) waves.
DOI: 10.5281/zenodo.10577812
title: Supplemental Information - Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling

description: This folder contains

1) maps of plasmids

2) files of phylogenetic analysis 

3) Replication information

4) Image cropping information

5) Gene IDs and protein sequences

that are part of the manuscript "Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling"
DOI: 10.5281/zenodo.11061716
title: Planetary Boundary Layer Height Retrievals from Micropulse-lidar at four Multiple ARM Sites Around the World

description: Planetary Boundary Layer Height Retrievals from Micropulse-lidar at the following ARM campaigns: GOAMAZON (MAO), COPS (FKB), CACTI (COR), and BAECC (TMP). These retrievals were computed using the Different Thermo-Dynamic Stabilities (DTDS) algorithm  (Su et al., 2020; Su et al., 2022).  The quality-control flag is provided in the dataset file, where zero (0) indicates a high-quality flag. 

Su, T., Zheng, Y. and Li, Z., 2022. Methodology to determine the coupling of continental clouds with surface and boundary layer height under cloudy conditions from lidar and meteorological data. Atmospheric Chemistry and Physics, 22(2), pp.1453-1466.

Su, T., Li, Z. and Kahn, R., 2020. A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. Remote Sensing of Environment, 237, p.111519.

Roldán-Henao, N., Su, T., and Li, Z. (2024, under review). Refining Planetary Boundary Layer Height Retrievals from Micropulse-lidar at Multiple ARM Sites Around the World. Submitted to Journal of Geophysical Research: Atmospheres.
DOI: 10.5281/zenodo.11063218
title: Data for "Global ocean pCO2 variation regimes: spatial patterns and the emergence of a hybrid regime"

description: Model data for article "Global ocean pCO2 variation regimes: spatial patterns and the emergence of a hybrid regime".
DOI: 10.5281/zenodo.11506583
title: Supplementary dataset for manuscript "Generation of Archaean oxidizing and wet magmas from mafic crustal overthickening"

description: Supplementary Tables 1 and 2
DOI: 10.6084/m9.figshare.14923089
title: Si and CdTe detector models from JMI 043501 (2020)

description: Si and CdTe detector models from Mats Persson, Adam Wang, and Norbert J. Pelc "Detective quantum efficiency of photon-counting CdTe and Si detectors for computed tomography: a simulation study," Journal of Medical Imaging 7(4), 043501 (17 July 2020). <br>Change log:2021-09-14: added a script generateFullPsf.m for generating the full psf from the intermediate.<br>
DOI: 10.15468/dl.ky988a
title: Occurrence Download

description: A dataset containing 154119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Potamopyrgus antipodarum (J.E.Gray, 1843)"
 ]
}

 The dataset includes 154119 records from 349 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0262771-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x3tga3
title: Occurrence Download

description: A dataset containing 142297 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Potamopyrgus antipodarum (J.E.Gray, 1843)"
 ]
}

 The dataset includes 142297 records from 261 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0215706-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/gmk6hg
title: The Freshwater Biodiversity Information System (FBIS) Fish Data

description: Freshwater fishes are regarded as South Africa’s most threatened species group. Long-term distributional data for freshwater fish species can be vital for detecting critical ecosystem changes, such as species range shifts, new records of non-native invasions and loss of ecosystem services or unique biodiversity. Understanding exactly how the abundance and distribution of freshwater fishes (both native and non-native) are changing is pivotal to effectively manage and conserve unique and threatened freshwater biodiversity and ecosystems. In light of this, a comprehensive freshwater fish dataset (freshwaterbiodiversity.org) was built, comprising all available records of formally described freshwater fish species occurring in South Africa. The comprehensive search for data resulted in the accrual of a total of 60 837 records of freshwater fish from South Africa, which includes 35 955 records new records to the Global Biodiversity Information Facility (GBIF). Of the 101 native species occurring in the country, almost half of all assessed species were found to be threatened, with the number of occurrences decreasing in recent years. Conversely, the number of occurrences and distribution ranges of many non-native species were found to be increasing, especially within the past three decades. These data have provided a much-needed update to the known status and distribution of freshwater fishes in the country.
DOI: 10.15468/ikshke
title: Données d'occurrences Espèces issues de l'inventaire des ZNIEFF

description: Les données correspondent à des données de synthèse des espèces présentes dans les ZNIEFF. Les données sont bancarisées à la zone.
DOI: 10.17632/94gmt9c7fj.1
title: Impact of climate change on drought in the Canary Islands

description: This data set corresponds to the referenced work (https://doi.org/10.1038/s41612-023-00358-7), related to climate projections, for the Canary Islands, of some aridity and drought indices. The meteorological variables used to calculate these indices are also provided, as they may be useful for other studies. 
 
Regional climate simulations, at 3 km resolution,  were computed using the WRF model driven by three CMIP5 global climate models (GFDL-ESM2M, IPSL-CM5A-MR and MIROC-ESM). The simulations were performed for three 30-year periods, recent past (1980–2009), mid-century (2030–2059), and end-century (2070–2099) and two future greenhouse gas emission scenarios (RCP4.5 and RCP8.5). 

Each file name has the following nomenclature:

canary_VAR_PERIOD_FREQ_mean_WRF_driven_by_GCM.nc

where:
* VAR is the variable (aridity, evspsblpot, pr, spi3, spi12, spei3, spei12, tasmin, tasmax, sfcWind)
* PERIOD is the simulation period, and also indicates, for future periods, the corresponding emission scenario (1980_2009, 2030_2059_rcp45, …)
*FREQ is the frequency for data: year (mean value of  annual values for the whole period) or monthly (mean value for each month, that is, the average for all the januaries, …)
* GCM is the global climate model (GCM) whose results have been used to drive the WRF simulations (GFDL_ESM2M, IPSL_CM5A_MR, MIROC_ESM)

The variables provided are:
* aridity: Aridity index (UNEP, 1992), defined as P/PET where PET is the mean annual potential evapotranspiration and P is the average annual precipitation for the same period.
* evspsblpo: mean (over the period)  of the monthly potential evapotranspiration (PET). The Penman–Monteith (PM) method was used to calculate PET. Units are kg m-2 s-1. To convert, for example, the january value to the total mean evapotranspiration for that month, in mm, the original value must be multiplied by 60*60*24*31 = 2678400 (seconds in that month).
* pr: precipitation. Units are kg m-2 s-1. Therefore, the unit conversion factor is the same as for evapotranspiration. 
* spi3: Standardized Precipitation Index computed from precipitation amounts for an accumulation period of 3 months. SPI values below ‒1 indicate rainfall deficits (drier than normal), while SPI values above 1 indicate excess rainfall (wetter than normal). The lower the SPI, the more intense the drought. Values are provided only for future periods, since, being a standardized index, the average over the same period in which the cumulative probability function is calculated (1980-2009) is zero. 
* spi12: same as spi3 but for an accumulation period of 12 months.
* spei3: Standardized Precipitation-Evapotranspiration Index, computed from “precipitation minus PET” amounts for an accumulation period of 3 months.
* spei12: same as spei3 but for an accumulation period of 12 months.
* tasmin: monthly mean of daily minimum temperature, in K.
* tasmax: monthly mean of daily maximum temperature, in K.
* sfcWind: monthly mean 10 m wind speed, m s-1
DOI: 10.18112/openneuro.ds004636.v1.0.4
title: fmri_data