cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3903753
title: Tropical Cyclone Along-track Potential Intensity (and Derived Quantities) for Six Ocean Basins from Three Reanalyses, 1980-2016

description: Supporting derived data for Shields et al. (2020, GRL) Derived tropical cyclone potential intensities and associated variables across the North Atlantic (NA), Eastern North Pacific (EP), North Indian (NI), South Indian (SI), South Pacific (SP), and Western North Pacific (WP) ocean basins, from MERRA2, ERA-I, and MERRA2 with SSTs replaced by HadISSTs. All files are netcdf format, organized by basin, with suffixes "m", "h", and "e" on data variables for MERRA2, MERRA2-HadISSTs, and ERA-I, respectively. When using this data, please include the citation:<br> <em>Shannon Shields, Allison Wing, and Daniel M. Gilford, 2020: A Global Analysis of Interannual Variability of Potential and Actual Tropical Cyclone Intensities. Geophys. Res. Lett.</em> Potential intensities calculated with the Bister and Emanuel (2002) algorithm (<strong>pcmin.m</strong>) by Kerry Emanuel (revised by Daniel Gilford), available freely at: ftp://texmex.mit.edu/pub/emanuel/TCMAX With any questions, please contact daniel[dot]gilford[at]rutgers[dot]edu.
DOI: 10.15468/wxempd
title: Dinidoridae, Megarididae e Tessaratomidae

description: This dataset contains the digitized treatments in Plazi based on the original book chapter Schwertner, Cristiano F., Grazia, Jocelia (2014): Dinidoridae, Megarididae e Tessaratomidae. In: Biodiversidad de Artrópodos Argentinos, vol. 3. Insue-Unt: 403-408, ISBN: 978-950-554-904-7, DOI: http://doi.org/10.5281/zenodo.3903685
DOI: 10.5281/zenodo.3673974
title: Comparing Transit Agency Peer Groups using Cluster Analysis-Data

description: This data is from a 2019 analysis of transit ridership in the United States. The purpose of the analysis was to codify US transit agencies into comparable groups using publicly available data. The data is split into dedicated right of way modes, and mixed right of way modes.
DOI: 10.5281/zenodo.3673965
title: Comparing Transit Agency Peer Groups using Cluster Analysis-Data

description: This data is from a 2019 analysis of transit ridership in the United States. The purpose of the analysis was to codify US transit agencies into comparable groups using publicly available data. The data is split into dedicated right of way modes, and mixed right of way modes.
DOI: 10.5281/zenodo.3774560
title: Test sets for jet anomaly detection at the LHC

description: <strong>Data Description</strong> These datasets are generated as a series of test sets for anomalous jet tagging at the LHC. They include boosted W jets, Top jets and Higgs jets. Jet transverse momentum is focused around 600 GeV. Each file includes 100k original events from MadGraph, but might have slightly less events in the final h5 files due to fatjet pre-selection. Production processes include: pp -&gt; W' -&gt; W (jj) Z(\(\nu \nu\)); \(m_{W} = 59, 80, 120, 174 ~GeV\) pp -&gt; Z' -&gt; t t~; \(m_t=80, 174 ~GeV\) pp -&gt; HH -&gt; (hh) (hh), (h -&gt; bb); \(m_H=174~GeV\), \(m_h = 20, 80 ~GeV\) <strong>Data Generation</strong> Jet samples in this dataset are generated with MadGraph, Pythia8 and Delphes (no pile-up effects simulated). Particle flow objects are used to cluster jets. FastJet was used for jet clustering. Jets are clustered using anti-kt algorithm with cone size R=1.0. Leading jet: \(p_T&gt;450 \textrm{GeV}\); sub-leading jet: \(p_T&gt;200 \textrm{GeV}\) <strong>Data Structure</strong> To get jets: f['objects/jets'] For jets, there are two datasets: ['constituents', 'obs']. (jets information is stored with higher-pt jet first) `obs[:, n_j - 1]`: jet four vectors and n-subjettiness for (n_j -1) th jet (pt, eta, phi, m, tau1, tau2, tau3, tau4, tau5) pt-sorted (highest first) jet constituents information are stored in variable length arrays for (n_j -1) th jet `constituents[:, n_j - 1]`: \(\{ E_i, P_{xi}, P_{yi}, P_{zi}, \textrm{PID}_i\}\) (PID: PDG for tracks; [22] for photon; [0] for neutral hadron) <strong>Extra Notes</strong> Since the dataset is structured as events, for W jet samples, only leading jet is available; while for Top and Higgs jets, leading and sub-leading jets are both valid. One might need to restrict jet \(p_T\) range at use. e.g. to get leading jet constituents: `f["objects/jets/constituents"][:,0]` The file names are self-explanatory on the corresponding generation process.
DOI: 10.5281/zenodo.3901833
title: Test Sets for Jet Anomaly Detection at the LHC

description: <strong>Data Description</strong> These datasets are generated as a series of test sets for anomalous jet tagging at the LHC. They include boosted W jets, Top jets, and Higgs jets. Jet transverse momentum is focused around 600 GeV and 1200 GeV (with prefix "pt1200_" in file names). Each file includes 100k original events from MadGraph, but might have slightly less events in the final h5 files due to fatjet pre-selection. Production processes include: pp -&gt; W' -&gt; W (jj) Z(\(\nu \nu\)); \(m_{W} = 59, 80, 120, 174 ~GeV\) pp -&gt; Z' -&gt; t t~; \(m_t=80, 174 ~GeV\) pp -&gt; HH -&gt; (hh) (hh), (h -&gt; bb); \(m_H=174~GeV\), \(m_h = 20, 80 ~GeV\) <strong>Data Generation</strong> Jet samples in this dataset are generated with MadGraph, Pythia8 and Delphes (no pile-up effects simulated). Particle flow objects are used to cluster jets. FastJet was used for jet clustering. Jets are clustered using anti-kt algorithm with cone size R=1.0. Leading jet: \(p_T&gt;450 \textrm{GeV}\); sub-leading jet: \(p_T&gt;200 \textrm{GeV}\) <strong>Data Structure</strong> To get jets: f['objects/jets'] For jets, there are two datasets: ['constituents', 'obs']. (jets information is stored with higher-pt jet first) `obs[:, n_j - 1]`: jet four vectors and n-subjettiness for \(n_j\)-th jet (pt, eta, phi, m, tau1, tau2, tau3, tau4, tau5) pt-sorted (highest first) jet constituents information are stored in variable length arrays for \(n_j\)-th jet `constituents[:, n_j - 1]`: \(\{ E_i, P_{xi}, P_{yi}, P_{zi}, \textrm{PID}_i\}\) (PID: PDG for tracks; [22] for photon; [0] for neutral hadron) <strong>Extra Notes</strong> Since the dataset is structured as events, for W jet samples, only leading jet is available; while for Top and Higgs jets, leading and sub-leading jets are both valid. One might need to restrict jet \(p_T\) range at use. e.g. to get leading jet constituents: `f["objects/jets/constituents"][:,0]` The file names are self-explanatory on the corresponding generation process.
DOI: 10.7910/dvn/dbw86t/gqgswo
title: HAM10000_metadata.tab

description: :unav
DOI: 10.6084/m9.figshare.21857112
title: Data - "EFFECTS OF BIRTH ORDER ON HUMAN SEXUALITY: THE SEX OF SIBLINGS MATTERS

description: Data - paper "EFFECTS OF BIRTH ORDER ON HUMAN SEXUALITY: THE SEX OF SIBLINGS MATTERS"
DOI: 10.6084/m9.figshare.21857112.v1
title: Data - "EFFECTS OF BIRTH ORDER ON HUMAN SEXUALITY: THE SEX OF SIBLINGS MATTERS

description: Data - paper "EFFECTS OF BIRTH ORDER ON HUMAN SEXUALITY: THE SEX OF SIBLINGS MATTERS"
DOI: 10.34808/en7g-m714
title: The luminescence study of Ca14Zn6Ga10−xMnxO35  coumpounds.

description: Manganese in the pentavalent state (Mn 5+) is both rare and central in materials exhibiting narrow-band near-infrared (NIR) emission and is highly sought after for phosphor-converted light-emitting diodes as promising candidates for future miniature solid-state NIR light source. We develop the Ca 14 Zn 6 Ga 10−x Mn x O 35 (x = 0.3, 0.5, 1.0, 1.25, 1.5, and 3.0) series that exhibit simultaneous Mn 4+ (650−750 nm) and Mn 5+ (1100−1250 nm) luminescence. 
In that dataset, the scientific article with Supporting Information, raw data of excitation and emission spectra, temperature-dependent, and high-pressure dependent photoluminescence and decay profiles are provided
DOI: 10.34740/kaggle/dsv/4833734
title: Computer Motherboard Production Defects
DOI: 10.34808/mshe-2r94
title: The luminescence study of  Ga2–x(Al0.68In0.32)xO3:Cr3+ coumpounds.

description: Near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) are a highly efficient perspective NIR light source, with application hindered by a narrow emission band. In this work, we broaden the emission of a new series of NIR phosphors by controlling crystal structure disorder through cation cosubstitution. By substituting Ga3+ with (Al0.68In0.32)3+, we create a Ga2–x(Al0.68In0.32)xO3:Cr3+ phosphor series in which the average crystal size is maintained, while cation disorder varies. The increased deviation of the cation radii in the substitution leads to increased electron–phonon coupling, with a resulting emission spectrum covering the 650–1000 nm range with a 30% increase in the emission full width at half-maximum (FWHM) and a relatively high internal quantum efficiency of ∼80%. A transition from the β phase to the α phase, which differs in structure from the undoped parent, is created by the application of high pressure and possesses ultra-broad-band emission and an FWHM of ∼190 nm. This work shows that the emission bandwidth can be controlled through disorder and its influence on the Stokes shift, as captured by the effective Huang–Rhys factor.
DOI: 10.6084/m9.figshare.21857331
title: Supplementary Material for: Urinary Biomarkers of Tubular Health and Risk for Kidney Function Decline or Mortality in Diabetes

description: Introduction: Diabetes is a leading cause of end-stage kidney disease (ESKD). Biomarkers of tubular health may prognosticate chronic kidney disease (CKD) progression beyond estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). Methods: We examined associations of five urinary biomarkers of tubular injury and repair (NGAL, KIM-1, IL-18, MCP-1, YKL-40) with kidney function decline (first occurrence of a decrease in eGFR≥30 ml/min/1.73 m2 if randomization eGFR≥60 or ≥50% if randomization eGFR&lt;60; ESKD) and all-cause mortality among 1,135 VA NEPHRON-D trial participants with baseline UACR ≥300 mg/g and available urine samples. Covariates included age, sex, race, BMI, systolic BP, HbA1c, treatment arm, eGFR, and UACR. In a subset of participants with 12-month samples (n=712), we evaluated associations of KIM-1, MCP-1, and YKL-40 change (from baseline to 12 months) with eGFR decline (from 12 months onwards). Results: At baseline, mean age was 65 years, mean eGFR was 56 ml/min/1.73 m2, and median UACR was 840 mg/g. Over a median of 2.2 years, 13% experienced kidney function decline and 9% died. In fully-adjusted models, the highest vs. lowest quartiles of MCP-1 and YKL-40 were associated with 2.18- and 1.76-fold higher risks of kidney function decline, respectively. One-year changes in KIM-1, MCP-1, and YKL-40 were not associated with subsequent eGFR decline. Higher baseline levels of NGAL, IL-18, MCP-1, and YKL-40 levels (per 2-fold higher) were independently associated with 10-40% higher risk of mortality. Discussion/Conclusion: Among Veterans with diabetes and CKD, urinary biomarkers of tubular health were associated with kidney function decline and mortality.
DOI: 10.6084/m9.figshare.21857331.v1
title: Supplementary Material for: Urinary Biomarkers of Tubular Health and Risk for Kidney Function Decline or Mortality in Diabetes

description: Introduction: Diabetes is a leading cause of end-stage kidney disease (ESKD). Biomarkers of tubular health may prognosticate chronic kidney disease (CKD) progression beyond estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). Methods: We examined associations of five urinary biomarkers of tubular injury and repair (NGAL, KIM-1, IL-18, MCP-1, YKL-40) with kidney function decline (first occurrence of a decrease in eGFR≥30 ml/min/1.73 m2 if randomization eGFR≥60 or ≥50% if randomization eGFR&lt;60; ESKD) and all-cause mortality among 1,135 VA NEPHRON-D trial participants with baseline UACR ≥300 mg/g and available urine samples. Covariates included age, sex, race, BMI, systolic BP, HbA1c, treatment arm, eGFR, and UACR. In a subset of participants with 12-month samples (n=712), we evaluated associations of KIM-1, MCP-1, and YKL-40 change (from baseline to 12 months) with eGFR decline (from 12 months onwards). Results: At baseline, mean age was 65 years, mean eGFR was 56 ml/min/1.73 m2, and median UACR was 840 mg/g. Over a median of 2.2 years, 13% experienced kidney function decline and 9% died. In fully-adjusted models, the highest vs. lowest quartiles of MCP-1 and YKL-40 were associated with 2.18- and 1.76-fold higher risks of kidney function decline, respectively. One-year changes in KIM-1, MCP-1, and YKL-40 were not associated with subsequent eGFR decline. Higher baseline levels of NGAL, IL-18, MCP-1, and YKL-40 levels (per 2-fold higher) were independently associated with 10-40% higher risk of mortality. Discussion/Conclusion: Among Veterans with diabetes and CKD, urinary biomarkers of tubular health were associated with kidney function decline and mortality.
DOI: 10.34808/0phs-yb59
title: SEM pictures - biomass

description: The dataset contains SEM pictures catching the changes occurring in biomass structures when the biomass undergoes pre-treatment processes.
DOI: 10.6084/m9.figshare.21437232
title: Supplementary Material for: On the variability in cell and nucleus shape

description: Cell morphology is an important regulator of cell function. Many abnormalities in cellular behavior can be discerned from changes in the shape of the cell and its organelles, typically the nucleus. Two major challenges for developing such phenotypic assays are reconstructing 3D surfaces of individual cells and nuclei from confocal images and developing characterizations of these surfaces for comparisons. We demonstrate two algorithms - 3D Active Contours and 3D Condensed-Attention UNet to segment cells and nuclei from confocal images. The cell and nuclear surfaces are then converted into vectors using a reversible, spherical transform - i.e. shapes can be recovered from the vectors. Typical methods for characterizing shapes using size, shape, and image parameters such as area, volume, shape factor, solidity, and pixel intensities are not amenable to such reverse transformation. Our vector representation's Principal Component Analysis (PCA) shows that the significant modes of variability among cell and nucleus shapes are scaling and flattening. We benchmark these modes using a known mechanical model for nucleus morphology. Subsequent modes alter the eccentricity of the nucleus and translate and rotate it with respect to the cell. Our vector-space representation of cell and nucleus shape helps physically interpret the variability sources. It may further help to guide mechanical models and identify molecular mechanisms driving cell and nuclear shape changes. The source code and the data used in this article are available at: https://github.com/iitgoa-ml/3d-cells-nuclei-segmentation
DOI: 10.6084/m9.figshare.21437232.v1
title: Supplementary Material for: On the variability in cell and nucleus shape

description: Cell morphology is an important regulator of cell function. Many abnormalities in cellular behavior can be discerned from changes in the shape of the cell and its organelles, typically the nucleus. Two major challenges for developing such phenotypic assays are reconstructing 3D surfaces of individual cells and nuclei from confocal images and developing characterizations of these surfaces for comparisons. We demonstrate two algorithms - 3D Active Contours and 3D Condensed-Attention UNet to segment cells and nuclei from confocal images. The cell and nuclear surfaces are then converted into vectors using a reversible, spherical transform - i.e. shapes can be recovered from the vectors. Typical methods for characterizing shapes using size, shape, and image parameters such as area, volume, shape factor, solidity, and pixel intensities are not amenable to such reverse transformation. Our vector representation's Principal Component Analysis (PCA) shows that the significant modes of variability among cell and nucleus shapes are scaling and flattening. We benchmark these modes using a known mechanical model for nucleus morphology. Subsequent modes alter the eccentricity of the nucleus and translate and rotate it with respect to the cell. Our vector-space representation of cell and nucleus shape helps physically interpret the variability sources. It may further help to guide mechanical models and identify molecular mechanisms driving cell and nuclear shape changes. The source code and the data used in this article are available at: https://github.com/iitgoa-ml/3d-cells-nuclei-segmentation
DOI: 10.34740/kaggle/dsv/4833766
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.6088227
title: Gelatinous macrozooplankton diversity and distribution data in the North Sea and Skagerrak/Kattegat during winter 2021

description: Original dataset, which was updated . Please see 10.5281/zenodo.6796597 instead.
description: Funding: This work was supported by the Villum und Velux Foundations [grant number 25512] to Cornelia Jaspers.
DOI: 10.5281/zenodo.6796597
title: Data on 'Gelatinous macrozooplankton diversity and distribution in the North Sea and Skagerrak/Kattegat during January-February 2021'

description: Dataset 1.2 with quality issues in the Swedish dataset for Pleurobrachia at station 102.
description: Funding: This work was supported by the Villum und Velux Foundations [grant number 25512] to Cornelia Jaspers.
DOI: 10.5281/zenodo.7519858
title: Data Set on the Literature Screening for a Scoping Review of Evacuation Training Methods in Buildings

description: This data set contains all retrieved literature records of a scoping review on fire evacuation training methods in buildings together with the reasoning for their in- or exclusion in the review.
DOI: 10.5281/zenodo.7519859
title: Data Set on the Literature Screening for a Scoping Review of Evacuation Training Methods in Buildings

description: This data set contains all retrieved literature records of a scoping review on fire evacuation training methods in buildings together with the reasoning for their in- or exclusion in the review.
DOI: 10.6084/m9.figshare.21630185
title: Supplementary Material for: Tumor radiomic features on pretreatment MRI to predict response to lenvatinib plus an anti–PD-1 antibody in advanced hepatocellular carcinoma: a multicenter study

description: Introduction: Lenvatinib plus an anti–PD-1 antibody has shown promising anti-tumor effects in patients with advanced hepatocellular carcinoma (HCC), but with clinical benefit limited to a subset of patients. We developed and validated a radiomic-based model to predict objective response to this combination therapy in advanced HCC patients. Methods: Patients (N = 170) who received first-line combination therapy with lenvatinib plus an anti–PD-1 antibody were retrospectively enrolled from 9 Chinese centers; 124 and 46 into the training and validation cohorts, respectively. Radiomic features were extracted from pretreatment contrast-enhanced MRI. After feature selection, clinicopathologic, radiomic, and clinicopathologic-radiomic models were built using a neural network. The performance of models, incremental predictive value of radiomic features compared with clinicopathologic features and relationship between radiomic features and survivals were assessed. Results: The clinicopathologic model modestly predicted objective response with an AUC of 0.748 (95% CI: 0.656–0.840) and 0.702 (95% CI: 0.547–0.884) in the training and validation cohorts, respectively. The radiomic model predicted response with an AUC of 0.886 (95% CI: 0.815–0.957) and 0.820 (95% CI: 0.648–0.984), respectively, with good calibration and clinical utility. The incremental predictive value of radiomic features to clinicopathologic features was confirmed with a net reclassification index of 47.9% (P &lt; 0.001) and 41.5% (P = 0.025) in the training and validation cohorts, respectively. Furthermore, radiomic features were associated with overall survival and progression-free survival both in the training and validation cohorts, but modified albumin-bilirubin grade and neutrophil-to-lymphocyte ratio were not. Conclusion: Radiomic features extracted from pretreatment MRI can predict individualized objective response to combination therapy with lenvatinib plus an anti–PD-1 antibody in patients with unresectable or advanced HCC, and provide incremental predictive value over clinicopathologic features, and are associated with overall survival and progression-free survival after initiation of this combination regimen.
DOI: 10.6084/m9.figshare.21673271
title: Supplementary Material for: Trends and Disparities in Stage-specific Incidence of Hepatocellular Carcinoma among US Adults, 2004-2019

description: Introduction: To determine the stage-specific incidence trend of hepatocellular carcinoma (HCC) among US adults. Methods: The age-adjusted incidence rate was extracted from Surveillance, Epidemiology, and End Results database for localized, regional and distant HCC. Trend analyses were conducted in the overall population and stratified by demographic and sociodemographic variables. The annual percentage change (APC) in 2014-2019 was estimated to determine the stage-specific incidence trend. Results: Although the incidence in localized HCC significantly declined, the incidence for regional and distant HCC plateaued in 2014-2019 (APCs, 4.4% [95% CI, -0.2% to 9.3%] and -0.7% [95% CI, -1.8% to 0.5%], respectively) with age and race/ethnicity disparities. More pronounced increases for regional and distant HCC were observed among the elderly (APCs, 8.4% [95% CI, 4.8% to 12.2%] and 2.2% [95% CI, 1.7% to 2.7%] for regional and distant HCC, respectively), non-Hispanic White individuals (APCs, 4.0% [95% CI, 2.9% to 5.1%] and 1.5% [95% CI, 0.7% to 2.4%] for regional and distant HCC, respectively). Conclusions: Disparities in incidence trends may reflect the inequalities in access to primary health care. More efforts are still in great demand for the vulnerable population.
DOI: 10.25747/4rcb-8k59
title: User evaluation of the DigitArq and DigitArq+ interfaces
DOI: 10.5258/soton/d2143
title: Dataset for: An improved numerical method for hyperbolic Lagrangian Coherent Structures using Differential Algebra

description: This dataset is available on request only https://library.soton.ac.uk/datarequest Contains data used to generate results for 'An improved numerical method for hyperbolic Lagrangian Coherent Structures using Differential Algebra'. The data also covers results presented in Chapter 5 and Section 6.4 of the Thesis 'Exploitation of Three-body Dynamics in Space Mission Design'. Publication details: Article: Jack Tyler, Alexander Wittig (2022) "An improved numerical method for hyperbolic Lagrangian Coherent Structures using Differential Algebra". Journal of Computational Science, Volume 65, https://doi.org/10.1016/j.jocs.2022.101883. Thesis: Jack Tyler (2023) "Exploitation of Three-body Dynamics in Space Mission Design", University of Southampton, Faculty of Engineering and Physical Sciences, PhD Thesis.