cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7d0ob3
title: Occurrence Download

description: A dataset containing 147 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leiopathes glaberrima (Esper, 1792)"
 ]
}

 The dataset includes 147 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058576-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bzs47b
title: Occurrence Download

description: A dataset containing 2150 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ozimops petersi (Leche, 1884)"
 ]
}

 The dataset includes 2150 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075142-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.umh5u5
title: Occurrence Download

description: A dataset containing 112214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Fraxinus excelsior L."
 ]
}

 The dataset includes 112214 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120234-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4tuuee
title: Occurrence Download

description: A dataset containing 2829 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dicamptodon tenebrosus (Baird & Girard, 1852)"
 ]
}

 The dataset includes 2829 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064382-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tgdwe4
title: Occurrence Download

description: A dataset containing 2311 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carex laxa Wahlenb.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2311 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076224-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.duwysc
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Onychocamptus mohammed (Blanchard & Richard, 1891))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 41 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043439-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ht6uy
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is one of (Litoria longicrus (Boulenger, 1911))"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043441-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7xcgd
title: Occurrence Download

description: A dataset containing 5834 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Podarcis erhardii (Bedriaga, 1882)"
 ]
}

 The dataset includes 5834 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0145219-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfeyzk
title: Occurrence Download

description: A dataset containing 2410140 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euphorbiaceae"
 ]
}

 The dataset includes 2410140 records from 1845 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001913-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/h96nnk9byn
title: Benmelstobart plus anlotinib versus pembrolizumab as first-line treatment for PD-L1-positive advanced non–small cell lung cancer (CAMPASS)

description: The multicentre, blinded, randomised controlled phase 3 CAMPASS trial compared benmelstobart plus anlotinib with pembrolizumab as the first-line treatment for patients with driver-negative advanced NSCLC and a PD-L1 TPS of 1% or greater.
The primary endpoint was PFS as assessed by a blinded IRC per Response Evaluation Criteria in Solid Tumours version 1.1 (RECIST v1.1), which was defined as the time from randomisation until disease progression or all-cause death. The key secondary endpoint was OS (time from randomisation to death from any cause) and other prespecified secondary endpoints included investigator-assessed PFS, objective response rate (ORR, percentage of patients with complete or partial responses according to RECIST v1.1), disease control rate (DCR, percentage of patients with objective response and stable disease according to RECIST v1.1), duration of response (DoR, time from the first documented objective response to disease progression or all-cause death), 6-/12-month PFS rates (percentage of patients who were alive without disease progression at 6 and 12 months), and 12-month OS rate (percentage of patients who were alive at 12 months), safety, patient-reported health-related quality of life (published separately later), and immunogenicity (published separately later).
Between August 2021 and December 2022, 531 of 1420 patients assessed for eligibility were enrolled and randomly assigned to benmelstobart plus anlotinib (n=354) or pembrolizumab (n=177), composing the intention-to-treat population.
The CAMPASS trial demonstrated that benmelstobart plus anlotinib resulted in a significantly improved PFS and a better objective response compared to pembrolizumab in previously untreated, driver-negative, PD-L1-positive, advanced NSCLC, supporting benmelstobart plus anlotinib as a potential first-line treatment option in this population, especially with TPS of 50% or greater. The safety profiles were manageable and no new safety signals were observed.
DOI: 10.17632/h96nnk9byn.1
title: Benmelstobart plus anlotinib versus pembrolizumab as first-line treatment for PD-L1-positive advanced non–small cell lung cancer (CAMPASS)

description: The multicentre, blinded, randomised controlled phase 3 CAMPASS trial compared benmelstobart plus anlotinib with pembrolizumab as the first-line treatment for patients with driver-negative advanced NSCLC and a PD-L1 TPS of 1% or greater.
The primary endpoint was PFS as assessed by a blinded IRC per Response Evaluation Criteria in Solid Tumours version 1.1 (RECIST v1.1), which was defined as the time from randomisation until disease progression or all-cause death. The key secondary endpoint was OS (time from randomisation to death from any cause) and other prespecified secondary endpoints included investigator-assessed PFS, objective response rate (ORR, percentage of patients with complete or partial responses according to RECIST v1.1), disease control rate (DCR, percentage of patients with objective response and stable disease according to RECIST v1.1), duration of response (DoR, time from the first documented objective response to disease progression or all-cause death), 6-/12-month PFS rates (percentage of patients who were alive without disease progression at 6 and 12 months), and 12-month OS rate (percentage of patients who were alive at 12 months), safety, patient-reported health-related quality of life (published separately later), and immunogenicity (published separately later).
Between August 2021 and December 2022, 531 of 1420 patients assessed for eligibility were enrolled and randomly assigned to benmelstobart plus anlotinib (n=354) or pembrolizumab (n=177), composing the intention-to-treat population.
The CAMPASS trial demonstrated that benmelstobart plus anlotinib resulted in a significantly improved PFS and a better objective response compared to pembrolizumab in previously untreated, driver-negative, PD-L1-positive, advanced NSCLC, supporting benmelstobart plus anlotinib as a potential first-line treatment option in this population, especially with TPS of 50% or greater. The safety profiles were manageable and no new safety signals were observed.
DOI: 10.17632/bp7pmxdf68
title: Soil organic carbon in Betula wetlands

description: Soil organic carbon in Betula wetlands
DOI: 10.17632/bp7pmxdf68.1
title: Soil organic carbon in Betula wetlands

description: Soil organic carbon in Betula wetlands
DOI: 10.17632/y86rwg29j9
title: EFFECT OF PHOTOBIOMODULATION ON TRAPEZIUS MYOFASCIAL PAIN: a randomized, sham-controlled, double-blind clinical trial
DOI: 10.17632/y86rwg29j9.1
title: EFFECT OF PHOTOBIOMODULATION ON TRAPEZIUS MYOFASCIAL PAIN: a randomized, sham-controlled, double-blind clinical trial
DOI: 10.17632/fc5rgbj3b4
title: The Notched Ball Test (NBT): Effective Volumes and Effective Surfaces for Weibull Strength Scaling

description: In order to compare strength testing results of ceramic specimens obtained through different testing methods, the knowledge of the effective surface or effective volume is essential. 

In this repository, data to determine the maximum tensile stress, the effective surface and effective volume for the "Notched Ball Test", described in [https://doi.org/10.1016/j.jeurceramsoc.2009.02.018], is given. The relevant geometrical and material parameters to determine the effective surface or effective volume are:

-Ball diameter D
-Notch length l
-Notch width w
-Notch root radius rn
-Poisson's ratio v
-Weibull modulus m

The data is available within:

0.74 &lt;= l/D &lt;= 0.92
0.05 &lt;= w/D &lt;= 0.2
0 &lt;= rn/w &lt;= 0.5
0.2 &lt;= v &lt;= 0.35
1 &lt;= m &lt;=50

Based on the data for stress interpolation, the maximum tensile stress can be determined from an interpolation of "finter" and the relevant geometrical properties (see equation 2 in the paper cited above). The normalized effective surface or effective volume can be determined through interpolation of the Seff and Veff data of this repository in the same way. 
The normalization volume Vnorm and normalization surface Snorm are given through the volume (= Pi*4/3*(D/2)^3) and surface (= 4*Pi*(D/2)^2) of the ball, respectively.
To aid evaluation, interpolation files in Python, Excel and Mathematica are also provided in this repository. 

Additional information:

-Data-files (.csv,.tsv,.xlsx)
 
The structure of the data in each file for stress evaluation is as follows:
 
 l/D || w/D || rn/w || v || finter

All files provided follow this convention, and the permutation follows v -&gt; rn/w -&gt; w/D -&gt; l/D

 
The structure of the data in each file for the evaluation of Veff and Seff is as follows:
 
 l/D || w/D || rn/w || v || m || Veff/Vnorm || Seff/Snorm

All files provided follow this convention, and the permutation follows m -&gt; v -&gt; rn/w -&gt; w/D -&gt; l/D


-Interpolation files (.xlsx,.py,.nb)
 
The Interpolation implemented in the Excel-file is linear, while the others are cubic. The results from Python- and Mathematica-files vary slightly.
 
 Excel-file:

Entering the specimen geometry and material parameters will automatically adjust the values for the maximum tensile stress and all effective quantities. 
 
 Python-file:

The .csv-files have to be in the same directory as the script. Running the script opens prompts in the command line
to enter the specimen geometry and material parameters. Afterwards, results for the maximum tensile stress and all effective quantities are given.

 Mathematica-file:

The .csv-files have to be in the same directory as the script. The rows marked in red represent the input-lines
for the specimen geometry and material parameters. Results for the maximum tensile stress and all effective quantities are given in lines highlighted in green.
DOI: 10.17632/fc5rgbj3b4.1
title: The Notched Ball Test (NBT): Effective Volumes and Effective Surfaces for Weibull Strength Scaling

description: In order to compare strength testing results of ceramic specimens obtained through different testing methods, the knowledge of the effective surface or effective volume is essential. 

In this repository, data to determine the maximum tensile stress, the effective surface and effective volume for the "Notched Ball Test", described in [https://doi.org/10.1016/j.jeurceramsoc.2009.02.018], is given. The relevant geometrical and material parameters to determine the effective surface or effective volume are:

-Ball diameter D
-Notch length l
-Notch width w
-Notch root radius rn
-Poisson's ratio v
-Weibull modulus m

The data is available within:

0.74 &lt;= l/D &lt;= 0.92
0.05 &lt;= w/D &lt;= 0.2
0 &lt;= rn/w &lt;= 0.5
0.2 &lt;= v &lt;= 0.35
1 &lt;= m &lt;=50

Based on the data for stress interpolation, the maximum tensile stress can be determined from an interpolation of "finter" and the relevant geometrical properties (see equation 2 in the paper cited above). The normalized effective surface or effective volume can be determined through interpolation of the Seff and Veff data of this repository in the same way. 
The normalization volume Vnorm and normalization surface Snorm are given through the volume (= Pi*4/3*(D/2)^3) and surface (= 4*Pi*(D/2)^2) of the ball, respectively.
To aid evaluation, interpolation files in Python, Excel and Mathematica are also provided in this repository. 

Additional information:

-Data-files (.csv,.tsv,.xlsx)
 
The structure of the data in each file for stress evaluation is as follows:
 
 l/D || w/D || rn/w || v || finter

All files provided follow this convention, and the permutation follows v -&gt; rn/w -&gt; w/D -&gt; l/D

 
The structure of the data in each file for the evaluation of Veff and Seff is as follows:
 
 l/D || w/D || rn/w || v || m || Veff/Vnorm || Seff/Snorm

All files provided follow this convention, and the permutation follows m -&gt; v -&gt; rn/w -&gt; w/D -&gt; l/D


-Interpolation files (.xlsx,.py,.nb)
 
The Interpolation implemented in the Excel-file is linear, while the others are cubic. The results from Python- and Mathematica-files vary slightly.
 
 Excel-file:

Entering the specimen geometry and material parameters will automatically adjust the values for the maximum tensile stress and all effective quantities. 
 
 Python-file:

The .csv-files have to be in the same directory as the script. Running the script opens prompts in the command line
to enter the specimen geometry and material parameters. Afterwards, results for the maximum tensile stress and all effective quantities are given.

 Mathematica-file:

The .csv-files have to be in the same directory as the script. The rows marked in red represent the input-lines
for the specimen geometry and material parameters. Results for the maximum tensile stress and all effective quantities are given in lines highlighted in green.
DOI: 10.17632/8bvb37fhw4
title: GLP-1RA code file

description: Python code used for data analysis of GLP-1RA case listings extracted from the Food and Drug Administration Adverse Event Reporting System (FAERS). 'drug' was altered for each GLP1RA of interest and control to extract relevant data. .csv files include the extracted data from FAERS used in the data analysis.
DOI: 10.17632/8bvb37fhw4.1
title: GLP-1RA code file

description: Python code used for data analysis of GLP-1RA case listings extracted from the Food and Drug Administration Adverse Event Reporting System (FAERS). 'drug' was altered for each GLP1RA of interest and control to extract relevant data. .csv files include the extracted data from FAERS used in the data analysis.
DOI: 10.17632/d3dn44ykj6
title: SEG-Y and CSV data extracted from reflection seismic profiles and exploration well of the ViDEPI project in the Taranto Valley area (Ionian Sea, Southern Italy)

description: The outer slope of the Taranto Trench (Ionian Sea, Southern Italy) is characterised by gravitational instability features that present an hazard for the Apulian coastal zone. One of the most evident feature has been identified in the offshore Taranto (MaGIC project), with witness of a landslide that can be found in the vintage unmigrated staked seismic reflection profiles of the ViDEPI project database (www.videpi.com/videpi/videpi.asp). These represents the only freely available subsurface data in this zone, provided as low-quality raster images in PDF format, making interpretation challenging. To enable detailed investigation of this area through higher quality visual data, reflection seismic profiles F75-42, F75-44, F75-83, F75-85, D-482 and MT-457-85 were converted to SEG-Y format using the procedure reported by Cicala et al. (2024). In order to obtain these files, we first combined the raster images as PDF files and transformed them into TIFF format. Subsequently, these images, along with their related TXT files (containing rows of code with information such as trace length in pixels, seismic line number, marine or land position, SEG-Y revision format, SEG-Y numeric format, UTM zone, geographic coordinates, pixel position, delay or time over the datum, time interval of the seismic profile in milliseconds), were converted using the MATLAB© program IMAGE2SEGY (Farran, 2012). To further enhance the seismic image in SEG-Y format the final step involved removing the low frequency noise through the data processing in DELPH Seismic® software ambient. Specifically, a high-pass filter was applied to all the seismic reflection profiles with cutoff values ranging from 8 Hz and 18 Hz, while the low-pass filter was applied only to seismic reflection profile D-482, with a cutoff set to 113 Hz; the automatic gain control function was also enabled to enhance the signal quality. After conversion, the following image files were obtained and included in the database: F75_85.jpg, F75_83.jpg, F75_44.jpg, F75_42.jpg, MT_457_85.jpg, D_482.jpg.
Moreover, to allow the correlation between the seismic signal and the stratigraphy, for future interpretation, the database includes also the digitalized sonic log of the exploration well Sansone-1 (geographic coordinates 40°24’02.55’’ N, 16°49’16.95’’ E), obtained from the raster image in PDF format (available in the ViDEPI project database) and converted in CSV file format. Following the procedure described by Cicala et al. (2023), the resulted file consists of 1033 pairs of data organised in two columns, A and B, representing interval transit time Δt [µs/ft] and depth [m], respectively. This digitalization, useful to define the seismic P-wave average velocity of the lithostratigraphic succession characterising the exploration well, is aimed to correlate the lithostratigraphic units with the seismic facies in the converted reflection seismic profiles.
DOI: 10.15468/dl.ae4r73
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum arevaloi (Schltr.) Hágsater"
 ]
}

 The dataset includes 81 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007479-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nxsgnw
title: Occurrence Download

description: A dataset containing 7945 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bradypus variegatus Schinz, 1825"
 ]
}

 The dataset includes 7945 records from 152 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007480-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3gvtg7
title: Occurrence Download

description: A dataset containing 848 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Perdita turgiceps Timberlake, 1954",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is United States of America"
 ]
}

 The dataset includes 848 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007482-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wkhdcf
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Daucus carota L.",
 "Year 1600-1758"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007481-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r2bmz2
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-0.8 50.9,-0.7 50.9,-0.7 51,-0.8 51,-0.8 50.9))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Meles meles (Linnaeus, 1758)",
 "Year 2013-2015"
 ]
}

 The dataset's 1 records were derived from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007472-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ky8z65
title: Occurrence Download

description: A dataset containing 34716 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Geometry POLYGON((-123.08 35.54,-111.1 35.54,-111.1 37.53,-123.08 37.53,-123.08 35.54))",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Ochrophyta"
 ]
}

 The dataset includes 34716 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007483-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rcf4g8
title: Occurrence Download

description: A dataset containing 219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Placusa complanata Erichson, 1839",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 219 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007484-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n826u7
title: Occurrence Download

description: A dataset containing 164 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Demodex folliculorum (Simon, 1842)"
 ]
}

 The dataset includes 164 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007485-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.