cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ffdnwe
title: Occurrence Download

description: A dataset containing 47007 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Geometry POLYGON((-115.1647 37.65684,-115.378 37.67373,-115.4271 37.50599,-115.4504 37.61634,-115.6779 37.54731,-115.5296 37.24377,-115.7473 37.02409,-116.0185 37.27166,-115.928 36.99763,-115.9906 36.93546,-116.6995 36.9972,-116.8065 37.28315,-116.9092 37.19524,-117.0246 37.43963,-117.1808 37.52838,-117.879 37.40723,-117.9617 37.28309,-117.8731 37.28723,-117.7944 37.07732,-117.9544 37.00084,-117.9515 36.88746,-117.8227 36.66252,-117.5905 36.53221,-117.702 36.54888,-117.7001 36.33985,-117.8002 36.52408,-117.9937 36.60588,-118.0845 36.84138,-118.2462 36.70385,-118.0401 36.46577,-117.8747 35.6612,-118.1077 35.52994,-118.0064 35.30001,-118.067 35.21965,-118.7917 34.78093,-118.4387 34.71956,-117.4643 34.26589,-117.1769 34.41801,-116.4889 34.32896,-116.5167 34.16457,-116.3997 34.13626,-116.4803 34.10575,-116.3148 34.09686,-115.9023 33.67817,-115.4918 33.71225,-115.3721 33.95609,-115.2841 33.87187,-115.5649 34.39096,-115.3579 34.50802,-115.2336 34.50913,-115.1734 34.281,-115.0287 34.49015,-114.9045 34.48742,-114.8483 34.31828,-114.0637 34.52534,-113.7549 34.46349,-113.6928 34.6298,-113.9285 34.76649,-114.0439 35.11463,-113.8177 35.22367,-113.8187 35.40141,-113.7145 35.4153,-113.8815 35.71407,-114.0844 35.81357,-113.816 36.22755,-113.7161 36.52703,-113.7669 36.72443,-113.3502 36.84576,-113.2794 37.29557,-113.8386 37.20913,-113.9632 37.38364,-114.3332 37.26329,-114.575 37.38097,-114.8029 37.22457,-114.8184 37.32927,-114.9423 37.28012,-115.1626 37.47778,-115.1647 37.65684))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Melospiza melodia"
 ]
}

 The dataset includes 47007 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015366-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12681906
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.e3uas5
title: Occurrence Download

description: A dataset containing 930 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epinephelus coeruleopunctatus"
 ]
}

 The dataset includes 930 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015368-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u6qxbd
title: Occurrence Download

description: A dataset containing 596 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is GBR.1.38_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Lissotriton vulgaris"
 ]
}

 The dataset includes 596 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015369-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hxvbdk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Herpestes javanicus",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015372-250802193616735/datasets/export for details.
DOI: 10.15468/dl.ew4rcd
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is Africa",
 "Country is one of (Cameroon, Senegal, Burkina Faso, Congo, Democratic Republic of the, Nigeria, Tanzania, United Republic of, Ghana, Gabon)",
 "OccurrenceStatus is Present",
 "TaxonKey is Schoenefeldia gracilis"
 ]
}

 The dataset includes 289 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015371-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nah3pz
title: Occurrence Download

description: A dataset containing 4346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hypseleotris klunzingeri)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 4346 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015370-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tpy29y
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Herpestes javanicus",
 "Country is Comoros",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015373-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xrz7wh
title: Occurrence Download

description: A dataset containing 122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Astur atricapillus"
 ]
}

 The dataset includes 122 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015375-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3tqq7
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epinephelus caeruleeopunctatus"
 ]
}

 The dataset includes 173 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015376-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h6pac3
title: Occurrence Download

description: A dataset containing 4362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Vipera ursinii"
 ]
}

 The dataset includes 4362 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015377-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.my6cr7
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((60.97355 0.87082,158.05290 0.87082,158.05290 39.65274,60.97355 39.65274,60.97355 0.87082))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Holigarna arnottiana"
 ]
}

 The dataset includes 71 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015374-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16746357
title: Absorption cross sections for air- and H2O-broadened CO2 in the 1.6 µm and 2 µm regions (including continuum) and air- and self-broadened H2O in the 1.6 µm region

description: Remote sensing of CO2 requires high accuracy spectroscopic reference data. This requirement can only be fulfilled with many line parameters per line in combination with highly sophisticated line models. When using these line parameters the user is faced with the problem of implementation and validation, which can be rather time consuming and error prone. The way out is that the originator of the line parameters makes the data available in form of absorption cross sections, as it is done for the OCO missions defining and utilizing the ABSCO database [1]. The present absorption cross sections were obtained from line parameters and continua published under the five ZENODO links below, measurements and analysis were carried out in the frame of the ESA-funded ISOGG project. 

The CO2 absorption cross sections are given in the ranges 4750-5175 cm-1 and 5970-6575 cm-1 for 12CO2 (and other isotopologues except for 13CO2), 13CO2, and the CO2/air continuum with a wavenumber spacing of 0.0025 cm-1. The pressure, temperature, and humidity grids were adopted from the ABSCO database. The intensity depletion (for pure CO2 see [2]) was also taken into account. In case of H2O only the range 5970-6575 cm-1 is covered. The format of the database is HDF5 (Hierarchical Data Format), which is a binary to be accessed with corresponding software libraries. 

 

ZENODO entries of line parameter databases (also including measurement databases)

Measurement database and line parameter database for air- and H2O-broadened CO2 in the 5970-6575 cm-1 region including continuum

Measurement and line parameter database CO2 5975-6575 cm-1 including intensity depletion and continua

Measurement database and line parameter database for air- and H2O-broadened CO2 in the 4750-5175 cm-1 region including continuum

Self broadening measurement and line parameter database CO2 4750-5175 cm-1

Measurement database and line parameter database for air- and self-broadened H2O in the 5970-6575 cm-1 region

 

[1] Vivienne H. Payne et al., Absorption coefficient (ABSCO) tables for the Orbiting Carbon Observatories: Version 5.1, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 255, 2020, 107217, https://doi.org/10.1016/j.jqsrt.2020.107217.

[2] M. Birk, C. Röske, G. Wagner, The pressure dependence of the experimentally-determined line intensity and continuum absorption of pure CO2 in the 1.6µm region, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 324, 2024, 109055,   https://doi.org/10.1016/j.jqsrt.2024.109055.
DOI: 10.5281/zenodo.16746358
title: Absorption cross sections for air- and H2O-broadened CO2 in the 1.6 µm and 2 µm regions (including continuum) and air- and self-broadened H2O in the 1.6 µm region

description: Remote sensing of CO2 requires high accuracy spectroscopic reference data. This requirement can only be fulfilled with many line parameters per line in combination with highly sophisticated line models. When using these line parameters the user is faced with the problem of implementation and validation, which can be rather time consuming and error prone. The way out is that the originator of the line parameters makes the data available in form of absorption cross sections, as it is done for the OCO missions defining and utilizing the ABSCO database [1]. The present absorption cross sections were obtained from line parameters and continua published under the five ZENODO links below, measurements and analysis were carried out in the frame of the ESA-funded ISOGG project. 

The CO2 absorption cross sections are given in the ranges 4750-5175 cm-1 and 5970-6575 cm-1 for 12CO2 (and other isotopologues except for 13CO2), 13CO2, and the CO2/air continuum with a wavenumber spacing of 0.0025 cm-1. The pressure, temperature, and humidity grids were adopted from the ABSCO database. The intensity depletion (for pure CO2 see [2]) was also taken into account. In case of H2O only the range 5970-6575 cm-1 is covered. The format of the database is HDF5 (Hierarchical Data Format), which is a binary to be accessed with corresponding software libraries. 

 

ZENODO entries of line parameter databases (also including measurement databases)

Measurement database and line parameter database for air- and H2O-broadened CO2 in the 5970-6575 cm-1 region including continuum

Measurement and line parameter database CO2 5975-6575 cm-1 including intensity depletion and continua

Measurement database and line parameter database for air- and H2O-broadened CO2 in the 4750-5175 cm-1 region including continuum

Self broadening measurement and line parameter database CO2 4750-5175 cm-1

Measurement database and line parameter database for air- and self-broadened H2O in the 5970-6575 cm-1 region

 

[1] Vivienne H. Payne et al., Absorption coefficient (ABSCO) tables for the Orbiting Carbon Observatories: Version 5.1, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 255, 2020, 107217, https://doi.org/10.1016/j.jqsrt.2020.107217.

[2] M. Birk, C. Röske, G. Wagner, The pressure dependence of the experimentally-determined line intensity and continuum absorption of pure CO2 in the 1.6µm region, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 324, 2024, 109055,   https://doi.org/10.1016/j.jqsrt.2024.109055.
DOI: 10.15468/dl.wrvfjv
title: Occurrence Download

description: A dataset containing 549 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Schoenefeldia gracilis"
 ]
}

 The dataset includes 549 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015378-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5bc3t93z
title: MassIVE MSV000098726 - Spc2 modulates substrate- and cleavage site-selection in the yeast signal peptidase complex
title: LC-MS/MS data associated with: "Yeonji Chung, Chewon Yim, Gilberto P. Pereira, Sungjoon Son, Lisbeth R. Kjoelbye, Lauren E. Mazurkiewicz, Amy M. Weeks, Friedrich Foerster, Gunnar von Heijne, Paulo C.T. Souza, Hyun Kim; Spc2 modulates substrate- and cleavage site-selection in the yeast signal peptidase complex. J Cell Biol 2 December 2024; 223 (12): e202211035. doi: https://doi.org/10.1083/jcb.202211035"
DOI: 10.15468/dl.74s24r
title: Occurrence Download

description: A dataset containing 293 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((63.02496 2.60953,141.56865 2.60953,141.56865 33.98669,63.02496 33.98669,63.02496 2.60953))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Holigarna"
 ]
}

 The dataset includes 293 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015379-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29356879
title: A Practical Interval Estimation Method for Spectral Density Function

description: The spectral density function can play a key role in time series analysis, where nonparametric interval estimation of the spectral density is a fundamental issue. However, the prevailing pointwise interval methods for spectral densities, including Chi-square approximation and frequency domain bootstrap (FDB), can be misleading in practice, perhaps more so than appreciated, as confidence intervals often exhibit low coverage accuracy as well as high sensitivity to tuning parameters. To provide a practical alternative, we propose a new hybrid method that combines the strengths of empirical likelihood (EL) and FDB. The method involves developing an EL statistic for spectral density inference along with a corresponding bootstrap approximation under time dependence, where we allow for general time processes as well as for two different types of kernel smoothing found in application (so-called A- or K-windows). Such windows require differing theories and implementations in practice. As an advantage, the FDB-EL procedure is formally valid under mild conditions for application to a broad range of processes, including both linear and nonlinear time series. Simulation studies demonstrate that FDB-EL-based confidence intervals are effective compared to other methods, as intervals maintain good coverage accuracy while being less sensitive to bandwidth parameters. The confidence interval procedure is illustrated with an application to studying the wind spectrum. Extension to simultaneous confidence intervals has also been discussed. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29829136.v1
title: Integrative Analysis of Microbial 16S Gene and Shotgun Metagenomic Sequencing Data Improves Statistical Efficiency in Testing Differential Abundance

description: The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Surprisingly, many microbiome studies have performed both experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, suggesting that an integrative analysis of both datasets could enhance the testing power for these signatures. However, differential experimental biases, partially overlapping samples, and uneven library sizes pose tremendous challenges when combining the two datasets. In this article, we introduce the first method of this kind, named Com-2seq, that combines the two datasets for testing differential abundance at the genus level as well as the community level while overcoming these difficulties. Our simulation studies demonstrate that Com-2seq substantially enhances statistical efficiency over analysis of a single dataset and outperforms two <i>ad hoc</i> approaches to integrative analysis. In analysis of real microbiome data, Com-2seq uncovered scientifically plausible findings, namely, the association of <i>Butyrivibrio</i>, <i>Gemella</i> and <i>Ignavigranum</i> with prediabetes status, which would have been missed by analyzing a single dataset. <i>Butyrivibrio</i> failed to reach the significance level in the analysis of each dataset despite showing a consistent trend; <i>Gemella</i> and <i>Ignavigranum</i> failed to produce adequate data in the 16S experiment. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29356879.v2
title: A Practical Interval Estimation Method for Spectral Density Function

description: The spectral density function can play a key role in time series analysis, where nonparametric interval estimation of the spectral density is a fundamental issue. However, the prevailing pointwise interval methods for spectral densities, including Chi-square approximation and frequency domain bootstrap (FDB), can be misleading in practice, perhaps more so than appreciated, as confidence intervals often exhibit low coverage accuracy as well as high sensitivity to tuning parameters. To provide a practical alternative, we propose a new hybrid method that combines the strengths of empirical likelihood (EL) and FDB. The method involves developing an EL statistic for spectral density inference along with a corresponding bootstrap approximation under time dependence, where we allow for general time processes as well as for two different types of kernel smoothing found in application (so-called A- or K-windows). Such windows require differing theories and implementations in practice. As an advantage, the FDB-EL procedure is formally valid under mild conditions for application to a broad range of processes, including both linear and nonlinear time series. Simulation studies demonstrate that FDB-EL-based confidence intervals are effective compared to other methods, as intervals maintain good coverage accuracy while being less sensitive to bandwidth parameters. The confidence interval procedure is illustrated with an application to studying the wind spectrum. Extension to simultaneous confidence intervals has also been discussed. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29829136
title: Integrative Analysis of Microbial 16S Gene and Shotgun Metagenomic Sequencing Data Improves Statistical Efficiency in Testing Differential Abundance

description: The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Surprisingly, many microbiome studies have performed both experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, suggesting that an integrative analysis of both datasets could enhance the testing power for these signatures. However, differential experimental biases, partially overlapping samples, and uneven library sizes pose tremendous challenges when combining the two datasets. In this article, we introduce the first method of this kind, named Com-2seq, that combines the two datasets for testing differential abundance at the genus level as well as the community level while overcoming these difficulties. Our simulation studies demonstrate that Com-2seq substantially enhances statistical efficiency over analysis of a single dataset and outperforms two <i>ad hoc</i> approaches to integrative analysis. In analysis of real microbiome data, Com-2seq uncovered scientifically plausible findings, namely, the association of <i>Butyrivibrio</i>, <i>Gemella</i> and <i>Ignavigranum</i> with prediabetes status, which would have been missed by analyzing a single dataset. <i>Butyrivibrio</i> failed to reach the significance level in the analysis of each dataset despite showing a consistent trend; <i>Gemella</i> and <i>Ignavigranum</i> failed to produce adequate data in the 16S experiment. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29356879.v1
title: A practical interval estimation method for spectral density function

description: The spectral density function can play a key role in time series analysis, where nonparametric interval estimation of the spectral density is a fundamental issue. However, the prevailing pointwise interval methods for spectral densities, including chi-square approximation and frequency domain bootstrap (FDB), can be misleading in practice, perhaps more so than appreciated, as confidence intervals often exhibit low coverage accuracy as well as high sensitivity to tuning parameters. To provide a practical alternative, we propose a new hybrid method that combines the strengths of empirical likelihood (EL) and FDB. The method involves developing an EL statistic for spectral density inference along with a corresponding bootstrap approximation under time dependence, where we allow for general time processes as well as for two different types of kernel smoothing found in application (so-called A- or K-windows). Such windows require differing theories and implementations in practice. As an advantage, the FDB-EL procedure is formally valid under mild conditions for application to a broad range of processes, including both linear and nonlinear time series. Simulation studies demonstrate that FDB-EL-based confidence intervals are effective compared to other methods, as intervals maintain good coverage accuracy while being less sensitive to bandwidth parameters. The confidence interval procedure is illustrated with an application to studying the wind spectrum. Extension to simultaneous confidence intervals has also been discussed.