cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6366024
title: dataset related to article "Clinical, molecular and glycophenotype insights in SLC39A8-CDG"

description: NGS data (.vcf; .bam; .bam.bai; .csv; .fastq) of patient analysed and sanger sequencing (.abi) for confirm the mutation and segregation in the family (mather, father and sibling)
DOI: 10.5281/zenodo.6366023
title: dataset related to article "Clinical, molecular and glycophenotype insights in SLC39A8-CDG"

description: NGS data (.vcf; .bam; .bam.bai; .csv; .fastq) of patient analysed and sanger sequencing (.abi) for confirm the mutation and segregation in the family (mather, father and sibling)
DOI: 10.6084/m9.figshare.19376471
title: Raw resfinder output from Abricate

description: Raw abricate output
DOI: 10.6084/m9.figshare.19376474
title: Raw Kleborate output

description: Raw Kleborate output
DOI: 10.6084/m9.figshare.19376474.v1
title: Raw Kleborate output

description: Raw Kleborate output
DOI: 10.6073/pasta/ccbaf9c6c38a1c63561ce1a59960f17b
title: Years 2019-2021, 15 minute measurements of stage in a small headwater stream draining a highly suburban catchment (72% residential), Saw Mill Brook, Burlington, MA.

description: Year 2019, 2020, and 2021 continuous measurements, every 15 minutes, were made of depth and stream temperature in a small headwater stream, Saw Mill Brook, Burlington, MA, draining a highly suburban catchment (72% residential) in the Ipswich River watershed. Discharge is determined from stage using discharge vs stage regressions.
DOI: 10.5519/qd.l8i3selb
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5079232 records)
DOI: 10.5281/zenodo.6366045
title: Dataset Related to article "NEURODEVELOPMENTAL DISORDER AND LATE-ONSET DEGENERATIVE PARKINSONISM IN A PATIENT WITH A WDR45 DEFECT"

description: NGS data (.vcf; .bam; .bam.bai; .csv; .fastq) of patient analysed and sanger sequencing (.abi) for confirm the mutation.
DOI: 10.5281/zenodo.6366044
title: Dataset Related to article "NEURODEVELOPMENTAL DISORDER AND LATE-ONSET DEGENERATIVE PARKINSONISM IN A PATIENT WITH A WDR45 DEFECT"

description: NGS data (.vcf; .bam; .bam.bai; .csv; .fastq) of patient analysed and sanger sequencing (.abi) for confirm the mutation.
DOI: 10.5519/qd.2zdo6vtt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (13218 records)
DOI: 10.14459/2022mp1651629
title: Temporal data of the turbulent swirl EM2C burner at different combustor back plate temperatures for the estimation of Flame Impulse Response

description: The dataset contains the statistically-steady state data (.h5) generated from fully compressible LES simulations carried out in AVBP 7.0.1 at the base combustor back plate temperature of 823 K. The dataset also contains temporal data (.h5) of the simulations carried out at different combustor back plate temperatures as described in the work of Kulkarni et al., Confidence in Flame Impulse Response Estimation From Large Eddy Simulation With Uncertain Thermal Boundary Conditions, JEGTP, GTP-21-1276
DOI: 10.5281/zenodo.6366047
title: Cyphoma gibbosum SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6366046
title: Cyphoma gibbosum SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6345532
title: Treasury Yield Database

description: Please use the updated data in version 2. This reference data set is based on the method in our paper "<strong>Stripping the Discount Curve - Robust Machine Learning Approach</strong>". We introduce a robust, flexible and easy-to-implement method for estimating the yield curve from Treasury securities. This method is non-parametric and optimally learns basis functions with an economically motivated smoothness reward. We show in an extensive empirical study on daily U.S. Treasury securities, that our method strongly dominates all parametric and non-parametric benchmarks. Our method achieves substantially smaller out-of-sample yield and pricing errors, while being robust to outliers and data selection choices. We attribute the superior performance to the optimal trade-off between flexibility and smoothness, which positions our method as the new standard for yield curve estimation. We provide the "<strong>GitHub code</strong>" with examples and a documentation of how to use our method. Our data provide estimates of annualized continuously compounded zero-coupon yields. Datasets come in four combinations of two frequencies (daily and monthly) and two granularity levels (daily and monthly). Datasets at monthly frequency report the yields for the last day of every month. The sampling period starts on June 14, 1961. The data set is updated regularly. In summary, we have the following four data sets: Yields at daily frequency for daily maturities Yields at monthly frequency for daily maturities Yields at daily frequency for monthly maturities Yields at monthly frequency for monthly maturities The first column in each dataset is observation date in format MM/DD/YY. The second column is maximum maturity of securities on the observation date, which sets the boundary for the extrapolation region. Titles of the remaining columns are time-to-maturity in unit of the corresponding granularity of the dataset. 10-Year, 20-year, and 30-year yield estimates are provided starting from June 14, 1961, January 5, 1973, and November 25, 1985 respectively.
description: {"references": ["Stripping the Discount Curve\u2014a Robust Machine Learning Approach: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4058150"]}
DOI: 10.6084/m9.figshare.19376528
title: Quast assembly statistics

description: Quast assembly statistics
DOI: 10.6084/m9.figshare.19376528.v1
title: Quast assembly statistics

description: Quast assembly statistics
DOI: 10.6084/m9.figshare.19102907
title: Optimal Estimation of the Number of Network Communities

description: In network analysis, how to estimate the number of communities <i>K</i> is a fundamental problem. We consider a broad setting where we allow severe degree heterogeneity and a wide range of sparsity levels, and propose Stepwise Goodness of Fit (StGoF) as a new approach. This is a stepwise algorithm, where for m=1,2,…, we alternately use a community detection step and a goodness of fit (GoF) step. We adapt SCORE Jin for community detection, and propose a new GoF metric. We show that at step <i>m</i>, the GoF metric diverges to ∞ in probability for all <i>m</i> &lt; <i>K</i> and converges to <i>N</i>(0, 1) if <i>m</i> = <i>K</i>. This gives rise to a consistent estimate for <i>K</i>. Also, we discover the right way to define the signal-to-noise ratio (SNR) for our problem and show that consistent estimates for <i>K</i> do not exist if SNR→0, and StGoF is uniformly consistent for <i>K</i> if SNR→∞. Therefore, StGoF achieves the optimal phase transition. Similar stepwise methods are known to face analytical challenges. We overcome the challenges by using a different stepwise scheme in StGoF and by deriving sharp results that are not available before. The key to our analysis is to show that SCORE has the <i>Nonsplitting Property (NSP)</i>. Primarily due to a nontractable rotation of eigenvectors dictated by the Davis–Kahan sin (θ) theorem, the NSP is nontrivial to prove and requires new techniques we develop. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.19102907.v2
title: Optimal Estimation of the Number of Network Communities

description: In network analysis, how to estimate the number of communities <i>K</i> is a fundamental problem. We consider a broad setting where we allow severe degree heterogeneity and a wide range of sparsity levels, and propose Stepwise Goodness of Fit (StGoF) as a new approach. This is a stepwise algorithm, where for m=1,2,…, we alternately use a community detection step and a goodness of fit (GoF) step. We adapt SCORE Jin for community detection, and propose a new GoF metric. We show that at step <i>m</i>, the GoF metric diverges to ∞ in probability for all <i>m</i> &lt; <i>K</i> and converges to <i>N</i>(0, 1) if <i>m</i> = <i>K</i>. This gives rise to a consistent estimate for <i>K</i>. Also, we discover the right way to define the signal-to-noise ratio (SNR) for our problem and show that consistent estimates for <i>K</i> do not exist if SNR→0, and StGoF is uniformly consistent for <i>K</i> if SNR→∞. Therefore, StGoF achieves the optimal phase transition. Similar stepwise methods are known to face analytical challenges. We overcome the challenges by using a different stepwise scheme in StGoF and by deriving sharp results that are not available before. The key to our analysis is to show that SCORE has the <i>Nonsplitting Property (NSP)</i>. Primarily due to a nontractable rotation of eigenvectors dictated by the Davis–Kahan sin (θ) theorem, the NSP is nontrivial to prove and requires new techniques we develop. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.19102907.v1
title: Optimal Estimation of the Number of Communities

description: In network analysis, how to estimate the number of communities <i>K</i> is a fundamental problem. We consider a broad setting where we allow severe degree heterogeneity and a wide range of sparsity levels, and propose Stepwise Goodness-of-Fit (StGoF) as a new approach. This is a stepwise algorithm, where for m=1,2,…, we alternately use a community detection step and a goodness-of-fit (GoF) step. We adapt SCORE [19] for community detection, and propose a new GoF metric. We show that at step <i>m</i>, the GoF metric diverges to ∞ in probability for all <i>m</i> &lt; <i>K</i> and converges to <i>N</i>(0, 1) if <i>m</i> = <i>K</i>. This gives rise to a consistent estimate for <i>K</i>. Also, we discover the right way to define the signal-to-noise ratio (SNR) for our problem and show that consistent estimates for <i>K</i> do not exist if SNR→0, and StGoF is uniformly consistent for <i>K</i> if SNR→∞. Therefore, StGoF achieves the optimal phase transition. Similar stepwise methods (e.g., [38, 34]) are known to face analytical challenges. We overcome the challenges by using a different stepwise scheme in StGoF and by deriving sharp results that are not available before. The key to our analysis is to show that SCORE has the <i>Non-Splitting Property (NSP)</i>. Primarily due to a non-tractable rotation of eigenvectors dictated by the Davis-Kahan sin (θ) theorem, the NSP is non-trivial to prove and requires new techniques we develop.
DOI: 10.5517/ccdc.csd.cc2929zp
title: CCDC 2117392: Experimental Crystal Structure Determination

description: Related Article: Yuan Gao, Jun-Su Zhou, Hong-Chun Liu, Yan Zhang, Wei-Hang Yin, Qun-Fang Liu, Guan-Wu Wang, Jin-Xin Zhao, Jian-Min Yue|2022|Phytochemistry|198|113142|doi:10.1016/j.phytochem.2022.113142
DOI: 10.5517/ccdc.csd.cc292t4c
title: CCDC 2117862: Experimental Crystal Structure Determination

description: Related Article: Zi-Juan Yi, Jian-Ting Sun, Tian-Yu Yang, Xian-Yong Yu, Xiao-Li Han, Bang-Guo Wei|2022|Org.Biomol.Chem.|20|2261|doi:10.1039/D1OB02383G
DOI: 10.5281/zenodo.6365664
title: CaptuRING and scanned wood core samples

description: Wood samples in digitized cores with CaptuRING (CR_ in files) and scanned with Epson 750VPRO (scan_) for sample digitization comparison. Species: <em>Fagus sylvatica </em>(FS) <em>Quercus faginea </em>(QF) <em>Quercus ilex </em>(QI) <em>Quercus pyrenaica </em>(QY) <em>Juniperus cedrus </em>(JC) <em>Juniperus thurifera </em>(JT) <em>Pinus nigra </em>(PN) <em>Pinus pinaster </em>(PP) Graphical scale was fitted with empirical values for CR samples, and theoretical resolution value in scanning software for scanned ones. SupplementaryMaterials2.csv file includes summary table from image comparison data.
description: Funded by Spanish Ministry of Science (CGL2017-87309-P and PROWARM PID2020-118444GA-I00, Junta de Castilla y León (OUTBREAK VA171P20 and IR2020-1-UVA08) and UPM (RP200060107). Catedra de Conocimiento e Innovación Caja Rural de Soria - Universidad de Valladolid
DOI: 10.5281/zenodo.5734100
title: CaptuRING and scanned wood core samples

description: Wood samples in digitized cores with CaptuRING (CR_ in files) and scanned with Epson 750VPRO (scan_) for sample digitization comparison. Species: <em>Fagus sylvatica </em>(FS) <em>Quercus faginea </em>(QF) <em>Quercus ilex </em>(QI) <em>Quercus pyrenaica </em>(QY) <em>Juniperus cedrus </em>(JC) <em>Juniperus thurifera </em>(JT) <em>Pinus nigra </em>(PN) <em>Pinus pinaster </em>(PP) Graphical scale was fitted with empirical values for CR samples, and theoretical resolution value in scanning software for scanned ones. SupplementaryMaterials2.csv file includes summary table from image comparison data.
description: Funded by Spanish Ministry of Science (CGL2017-87309-P and PROWARM PID2020-118444GA-I00, Junta de Castilla y León (OUTBREAK VA171P20 and IR2020-1-UVA08) and UPM (RP200060107). Catedra de Conocimiento e Innovación Caja Rural de Soria - Universidad de Valladolid
DOI: 10.5285/763eb87e0682446cafa8c74488dd5fb8
title: ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1982 - 2018), version 2.0

description: This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 1982-2018. The product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. The retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.630 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. The following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water; permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology. The Remote Sensing Research Group of the University of Bern is responsible for the SCFV product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. The SCFV AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years.
DOI: 10.15468/dl.ski79n
title: Occurrence Download

description: A dataset containing 4317 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((42.25342 -26.63086,51.17432 -26.63086,51.17432 -11.55762,42.25342 -11.55762,42.25342 -26.63086))",
 "TaxonKey is Ephemeroptera"
 ]
}

 The dataset includes 4317 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016863-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ppqyq
title: Occurrence Download

description: A dataset containing 1109 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Macaca cyclopis (Swinhoe, 1863)"
 ]
}

 The dataset includes 1109 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067067-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tcepuf
title: Occurrence Download

description: A dataset containing 3204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "DatasetKey is Faunal Inventory of Morysin Nature Reserve"
 ]
}

 The dataset includes 3204 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007275-150922153815467/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwse22
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prunus eremophila Prigge"
 ]
}

 The dataset includes 67 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018455-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fy1v90
title: Occurrence Download

description: A dataset containing 18063 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myrtus L."
 ]
}

 The dataset includes 18063 records from 249 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016874-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6h6bpk
title: Occurrence Download

description: A dataset containing 15580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-144.8191 1.6191,-52.35075 1.6191,-52.35075 62.96482,-144.8191 62.96482,-144.8191 1.6191))",
 "TaxonKey is Elaeagnus umbellata Thunb."
 ]
}

 The dataset includes 15580 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035859-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2nukqe
title: Occurrence Download

description: A dataset containing 26841337 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium)",
 "BasisOfRecord is one of (Observation, Human Observation, Material sample, Literature Occurrence, Specimen, Unknown evidence, Machine Observation)",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2021",
 "HasCoordinate is true"
 ]
}

 The dataset includes 26841337 records from 193 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071060-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ccxtzg
title: Occurrence Download

description: A dataset containing 24767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "Country is Uganda"
 ]
}

 The dataset includes 24767 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007275-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pg9fjz
title: Occurrence Download

description: A dataset containing 310546 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "GadmGid is CAN.2_1",
 "Geometry POLYGON((-126.07257 48.90476,-115.83337 48.90476,-115.83337 53.78676,-126.07257 53.78676,-126.07257 48.90476))",
 "HasGeospatialIssue is false",
 "TaxonKey is Haliaeetus leucocephalus (Linnaeus, 1766)"
 ]
}

 The dataset includes 310546 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037685-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2u6nb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Zygophyllum mongolicum (Maxim.) Christenh. & Byng"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037703-231002084531237/datasets/export for details.
DOI: 10.15468/dl.uryhsk
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Leopardus tigrinus (Schreber, 1775)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 153 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007275-171002173027117/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.op2zny
title: Occurrence Download

description: A dataset containing 267 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ligustrum robustum (Roxb.) Blume"
 ]
}

 The dataset includes 267 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007275-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.venscg
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Photinia impressivena Hayata"
 ]
}

 The dataset includes 207 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018414-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w9s6xd
title: Occurrence Download

description: A dataset containing 19153 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herbario Universidad de Caldas - FAUC"
 ]
}

 The dataset includes 19153 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0118021-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.