cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0978547.10fu
title: SH0978547.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.ynatmh
title: Occurrence Download

description: A dataset containing 5285 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gardenia jasminoides J.Ellis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5285 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0109526-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25901/d3mg-4h18
title: Samford Peri-Urban Site, South East Queensland, Litterfall Data From Dry Sclerophyll Forest, 2011-2013
DOI: 10.6084/m9.figshare.23273272
title: Additional file 1 of Modelling of Hepatitis B Virus vertical transmission dynamics in Ethiopia: a compartmental modelling approach

description: Additional file 1.
DOI: 10.6084/m9.figshare.23273272.v1
title: Additional file 1 of Modelling of Hepatitis B Virus vertical transmission dynamics in Ethiopia: a compartmental modelling approach

description: Additional file 1.
DOI: 10.6084/m9.figshare.23273280
title: Additional file 1 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 1: Table S1. Overview of variables used in RF models.
DOI: 10.6084/m9.figshare.23273280.v1
title: Additional file 1 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 1: Table S1. Overview of variables used in RF models.
DOI: 10.6084/m9.figshare.23273283
title: Additional file 2 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 2: Table S2. Descriptives of continuous variables in the 2012 dataset (n = 199,840)
DOI: 10.6084/m9.figshare.23273283.v1
title: Additional file 2 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 2: Table S2. Descriptives of continuous variables in the 2012 dataset (n = 199,840)
DOI: 10.6084/m9.figshare.23273286
title: Additional file 3 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 3: Table S3. Descriptives of categorical exposures of 2012 dataset (n = 199,840).
DOI: 10.6084/m9.figshare.23273286.v1
title: Additional file 3 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 3: Table S3. Descriptives of categorical exposures of 2012 dataset (n = 199,840).
DOI: 10.6084/m9.figshare.23273289
title: Additional file 4 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 4: Table S4. Descriptives of continuous variables of 2016 dataset (n = 244,557).
DOI: 10.6084/m9.figshare.23273289.v1
title: Additional file 4 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 4: Table S4. Descriptives of continuous variables of 2016 dataset (n = 244,557).
DOI: 10.6084/m9.figshare.23273292
title: Additional file 5 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 5: Table S5. Descriptives of categorical exposures of 2016 dataset (n = 244,557).
DOI: 10.6084/m9.figshare.23273292.v1
title: Additional file 5 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 5: Table S5. Descriptives of categorical exposures of 2016 dataset (n = 244,557).
DOI: 10.6084/m9.figshare.23273295
title: Additional file 6 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 6: Table S6. Pearson r2 correlation matrix of numerical exposures of the 2016 dataset (n = 244,557)
DOI: 10.6084/m9.figshare.23273295.v1
title: Additional file 6 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 6: Table S6. Pearson r2 correlation matrix of numerical exposures of the 2016 dataset (n = 244,557)
DOI: 10.6084/m9.figshare.23273298
title: Additional file 7 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 7: Table S7. VI rankings of RF models based on the 2012 and 2016 datasets.
DOI: 10.6084/m9.figshare.23273298.v1
title: Additional file 7 of Predicting self-perceived general health status using machine learning: an external exposome study

description: Additional file 7: Table S7. VI rankings of RF models based on the 2012 and 2016 datasets.
DOI: 10.6084/m9.figshare.23273365
title: Additional file 2 of Development of an international core outcome set for treatment trials in necrotizing enterocolitis—a study protocol

description: Additional file 2. Outcomes from SR.
DOI: 10.6084/m9.figshare.23273365.v1
title: Additional file 2 of Development of an international core outcome set for treatment trials in necrotizing enterocolitis—a study protocol

description: Additional file 2. Outcomes from SR.
DOI: 10.6084/m9.figshare.23273379
title: Additional file 2 of Assessing needs-based supply of physicians: a criteria-led methodological review of international studies in high-resource settings

description: Additional file 2: Overview of the criteria for operationalizing population need for healthcare for physician planning
DOI: 10.6084/m9.figshare.23273379.v1
title: Additional file 2 of Assessing needs-based supply of physicians: a criteria-led methodological review of international studies in high-resource settings

description: Additional file 2: Overview of the criteria for operationalizing population need for healthcare for physician planning
DOI: 10.6084/m9.figshare.23273398
title: Additional file 8 of Metagenome-mining indicates an association between bacteriocin presence and strain diversity in the infant gut

description: Additional file 8: Metagenome accession numbers.
DOI: 10.6084/m9.figshare.23273398.v1
title: Additional file 8 of Metagenome-mining indicates an association between bacteriocin presence and strain diversity in the infant gut

description: Additional file 8: Metagenome accession numbers.
DOI: 10.6084/m9.figshare.23273407
title: Additional file 1 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 1: Supplementary Table S1. Sequence relatedness of PlDIRs.
DOI: 10.6084/m9.figshare.23273407.v1
title: Additional file 1 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 1: Supplementary Table S1. Sequence relatedness of PlDIRs.
DOI: 10.6084/m9.figshare.23273413
title: Additional file 2 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 2: Supplementary Table S2. Identified motifs of PlDIR genes.
DOI: 10.6084/m9.figshare.23273413.v1
title: Additional file 2 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 2: Supplementary Table S2. Identified motifs of PlDIR genes.
DOI: 10.6084/m9.figshare.23273419
title: Additional file 4 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 4: Supplementary Table S3. Selected co-expression genes list.
DOI: 10.6084/m9.figshare.23273419.v1
title: Additional file 4 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 4: Supplementary Table S3. Selected co-expression genes list.
DOI: 10.6084/m9.figshare.23273425
title: Additional file 6 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 6: Supplementary Table S4. Primers used in this study.
DOI: 10.6084/m9.figshare.23273425.v1
title: Additional file 6 of Identification and functional characterization of the dirigent gene family in Phryma leptostachya and the contribution of PlDIR1 in lignan biosynthesis

description: Additional file 6: Supplementary Table S4. Primers used in this study.
DOI: 10.18112/openneuro.ds004395.v2.0.0
title: Penn Electrophysiology of Encoding and Retrieval Study (PEERS)
DOI: 10.5281/zenodo.7992797
title: Raw data of Chemical composition of single-particle muscovite from loess, deserts and Yellow River

description: Raw data of Chemical composition of single-particle muscovite from loess, deserts and Yellow River
DOI: 10.5281/zenodo.7992796
title: Raw data of Chemical composition of single-particle muscovite from loess, deserts and Yellow River

description: Raw data of Chemical composition of single-particle muscovite from loess, deserts and Yellow River
DOI: 10.5281/zenodo.8047365
title: Dataset for: Faculty Publication Trends in a Japanese National University: A Diachronic Document Analysis

description: Dataset for paper titled: Faculty Publication Trends in a Japanese National University: A Diachronic Document Analysis
description: Funding: This work was supported by JSPS KAKENHI Grant Number 22K13177.
DOI: 10.5281/zenodo.8047364
title: Dataset for: Faculty Publication Trends in a Japanese National University: A Diachronic Document Analysis

description: Dataset for paper titled: Faculty Publication Trends in a Japanese National University: A Diachronic Document Analysis
description: Funding: This work was supported by JSPS KAKENHI Grant Number 22K13177.
DOI: 10.48324/dandi.000458/0.230317.0039
title: Simultaneous electroencephalography, extracellular electrophysiology, and cortical electrical stimulation in head-fixed mice

description: In this set of experiments, we recorded neural signals using an electroencephalography (EEG) array and Neuropixels probes while directly electrically stimulating the cortex in awake and anesthetized head-fixed mice. Details of the experiments can be found in the associated manuscript (Claar, Rembado et al., 2023). Briefly, the recordings and stimulation commenced while the mouse was awake, free to rest or move on a rotating disc. After delivering a series of stimuli, anesthesia was induced with isoflurane (5% via inhalation). Once a surgical level of anesthesia was reached, the mouse was maintained unconscious (1-1.5% isoflurane) during the delivery of another series of stimuli. In some subjects another series of stimuli was delivered after the isoflurane was turned off, this epoch/state is referred to as “recovery” in the dataset.

Each session file includes the following data: raw EEG signals from all 30 surface electrodes and the associated electrode information; raw LFP signals from all electrodes on all Neuropixels probes (if used) and the associated electrode information; spike times for all units (spike sorted with Kilosort 2.0) that passed our quality threshold with associated information (brain region, spike waveform duration, etc.); subject’s speed computed from the rotation of the disc for the entire session; epochs marking when isoflurane was induced and when it was maintained; and a trial table containing information about every stimulus delivered throughout the session.

All sessions included an awake and an isoflurane epoch, but not all sessions included a recovery epoch. Some subjects received visual stimulation trials (visual stimuli presented on a screen in the subject’s right field of view) interleaved with the electrical stimulation trials.
DOI: 10.6084/m9.figshare.23506005.v1
title: Supplementary Material for: Primary Breast Sarcoma: A Two-Centre Analysis and Review of Literature

description: <b><i>Introduction:</i></b> Primary breast sarcoma is a very rare malignant type of breast tumours with an incidence of 0.1% of all primary breast malignancies. <b><i>Methods:</i></b> We present a retrospective analysis of the case series from two hospitals in the Czech Republic with a review of the diagnostic and treatment approach to primary breast sarcomas with an analysis of published prognostic factors. <b><i>Results:</i></b> Eleven patients were included in the study, 9 women and 2 men. Statistical evaluation revealed that tumour size (<i>p</i> = 0.1964), grade (<i>p</i> = 0.1667), margin distance (<i>p</i> = 0.5403), mitotic activity (<i>p</i> = 0.8577), or age (<i>p</i> = 0.7822) were not prognostic factors in our cohort. <b><i>Conclusion:</i></b> The analysis did not prove any of the factors, such as age, tumour size, grade, or mitotic activity, to be statistically significant prognostic factors. Based on the literature review, the most common published prognostic factors are tumour size, margin status, and grade, but the results are ambiguous.
DOI: 10.6084/m9.figshare.22773769.v1
title: Tie-break Bootstrap for Nonparametric Rank Statistics

description: In this paper, we propose a new bootstrap procedure for the empirical copula process. The procedure involves taking pseudo samples of normalized ranks in the same fashion as the classical bootstrap and applying small perturbations to break ties in the normalized ranks. Our procedure is a simple modification of the usual bootstrap based on sampling with replacement, yet it provides noticeable improvement in the finite sample performance. We also discuss how to incorporate our procedure into the time series framework. Since nonparametric rank statistics can be treated as functionals of the empirical copula, our proposal is useful in approximating the distribution of rank statistics in general. As an empirical illustration, we apply our bootstrap procedure to test the null hypotheses of positive quadrant dependence, tail monotonicity, and stochastic monotonicity, using U.S. Census data on spousal incomes in the past fifteen years.
DOI: 10.5281/zenodo.6926522
title: High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas

description: We present the design of a digital phantom that tries to overcome the problems of the current PET digital brain phantoms, particularly for the simulation of simultaneous PET-MRI data sets. We propose a new brain digital brain phantom based on the BigBrain atlas, a free, publicly available tool that provides considerable neuroanatomical insight into the human brain with an ultrahigh-resolution 3D model of a human brain at nearly cellular resolution of 20 micrometers. We used the histology maps, the classified tissue maps and the MRI image of the BigBrain atlas, as well as the Hammersmith atlas and a PET [18F]FDG template as inputs to create an instance of this ultra high-resolution heterogeneous PET-MRI phantom. Full details of this phantom in Medical Physics: "Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas", 10.1002/mp.14218. You can find codes examples for reading the data at https://github.com/mabelzunce/PETBrainPhantoms Please cite this paper if you use this phantom in your work: Belzunce, M.A. and Reader, A.J. (2020), Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas. Med. Phys., 47: 3356-3362. doi:10.1002/mp.14218
DOI: 10.5281/zenodo.1190597
title: High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas

description: We present the design of a digital phantom that tries to overcome the problems of the current PET digital brain phantoms, particularly for the simulation of simultaneous PET-MRI data sets. We propose a new brain digital brain phantom based on the BigBrain atlas, a free, publicly available tool that provides considerable neuroanatomical insight into the human brain with an ultrahigh-resolution 3D model of a human brain at nearly cellular resolution of 20 micrometers. We used the histology maps, the classified tissue maps and the MRI image of the BigBrain atlas, as well as the Hammersmith atlas and a PET [18F]FDG template as inputs to create an instance of this ultra high-resolution heterogeneous PET-MRI phantom. Full details of this phantom in Medical Physics: "Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas", 10.1002/mp.14218. You can find codes examples for reading the data at https://github.com/mabelzunce/PETBrainPhantoms Please cite this paper if you use this phantom in your work: Belzunce, M.A. and Reader, A.J. (2020), Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas. Med. Phys., 47: 3356-3362. doi:10.1002/mp.14218
description: This version fixes a bug where ct images and umap are interchanged.
DOI: 10.5281/zenodo.8045458
title: High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas

description: We present the design of a digital phantom that tries to overcome the problems of the current PET digital brain phantoms, particularly for the simulation of simultaneous PET-MRI data sets. We propose a new brain digital brain phantom based on the BigBrain atlas, a free, publicly available tool that provides considerable neuroanatomical insight into the human brain with an ultrahigh-resolution 3D model of a human brain at nearly cellular resolution of 20 micrometers. We used the histology maps, the classified tissue maps and the MRI image of the BigBrain atlas, as well as the Hammersmith atlas and a PET [18F]FDG template as inputs to create an instance of this ultra high-resolution heterogeneous PET-MRI phantom. Full details of this phantom in Medical Physics: "Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas", 10.1002/mp.14218. You can find codes examples for reading the data at https://github.com/mabelzunce/PETBrainPhantoms Please cite this paper if you use this phantom in your work: Belzunce, M.A. and Reader, A.J. (2020), Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas. Med. Phys., 47: 3356-3362. doi:10.1002/mp.14218
description: This version fixes a bug where ct images and umap are interchanged.
DOI: 10.34740/kaggle/dsv/5948220
title: COVID Vaccination in World (updated daily)
DOI: 10.25345/c5k931h1n
title: MassIVE MSV000092189 - WNT2B is required for development and function of human intestine
title: The experiment goal was to identify differentially expressed proteins associated with WNT2B mutation p.R69* in human intestinal epithelia. Skin fibroblasts from a patient with the mutation were used to establish human intestinal organoids (HIOs). The hESC H1 cell line was used to generate wild-type WNT2B HIOs for comparison. The HIOs were transplanted into mice to promote maturation for 8 weeks, followed by dissection and crypt isolation to seed ex vivo epithelial (enteroid) cultures. The enteroid cultures were harvested for analysis by tandem mass tag spectrometry.
DOI: 10.6084/m9.figshare.23531664
title: Occurrence of co-production

description: The occurrence of co-production is a category of the ESSENZ method determining supply risks. The occurrence of co-production poses a supply risk due to the dependencies between the primary product and the by-products. Co-production arises when multiple products are generated simultaneously from a single production process. Co-production yields from specific processes often have fixed ratios. As a result, if the demand for one product changes, it becomes challenging to adjust production so that it accommodates the varying demands while maintaining the optimal ratio. This inflexibility can lead to either shortages or excess inventory for co-produced products, thus increasing the supply risk of co-products. The data is based on M. Angerer, G. Erdmann, L. Marscheider-Weidemann, F. Scharp, M. Lüllmann, A. Handke, V. Marwerde (2009): Rohstoffe für Zukunftstechnologien, Stuttgart.
DOI: 10.6084/m9.figshare.23531664.v1
title: Occurrence of co-production

description: The occurrence of co-production is a category of the ESSENZ method determining supply risks. The occurrence of co-production poses a supply risk due to the dependencies between the primary product and the by-products. Co-production arises when multiple products are generated simultaneously from a single production process. Co-production yields from specific processes often have fixed ratios. As a result, if the demand for one product changes, it becomes challenging to adjust production so that it accommodates the varying demands while maintaining the optimal ratio. This inflexibility can lead to either shortages or excess inventory for co-produced products, thus increasing the supply risk of co-products. The data is based on M. Angerer, G. Erdmann, L. Marscheider-Weidemann, F. Scharp, M. Lüllmann, A. Handke, V. Marwerde (2009): Rohstoffe für Zukunftstechnologien, Stuttgart.
DOI: 10.15468/dl.8ggt6t
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron albertsenianum Forrest ex Balf.fil."
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097259-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfaev5
title: Occurrence Download

description: A dataset containing 711 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ranunculus ashibetsuensis Wiegleb"
 ]
}

 The dataset includes 711 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097258-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ajffh
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Renanthera matutina Lindl."
 ]
}

 The dataset includes 73 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097260-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.