cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/p9t8mz749v.2
title: The effect of relational mobility on pursuit of beauty in appearance: Evidence from Chinese and the US samples

description: Data from Study 1 were collected using an experience sampling method, where participants reported their daily beauty-related behaviors. The dataset includes several variables: relational mobility (measured using a Likert scale), beauty-related behaviors (selfie editing, makeup application, weight control), and behavioral intentions (willingness to undergo cosmetic surgery). The data were gathered from participants in both China and the US, and all data were anonymized to ensure participant privacy. The mediation analysis conducted in Study 1 confirmed that relational mobility mediates the cultural differences in beauty-seeking behaviors between the two groups.
Study 2 involved manipulating relational mobility levels (high vs. low) for both Chinese and US participants to examine the causal effect on beauty-related behaviors. The dataset from Study 2 includes experimental manipulations of relational mobility and measures of beauty-related behaviors such as clothing preferences, willingness to undergo cosmetic surgery, and photo-editing choices. Responses were collected via surveys and choice tasks, allowing for a comparison of the effect of relational mobility on beauty behaviors across cultures.
The findings from Study 2 provide evidence of a causal relationship between relational mobility and beauty-related behaviors, further supporting the hypothesis that relational mobility influences the pursuit of appearance enhancement in both cultural contexts.
DOI: 10.15468/dl.awcvdq
title: Occurrence Download

description: A dataset containing 191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pyrus bourgaeana Decne.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 191 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004328-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/b7mr-8v67
title: Vehicle CG and Head Accelerations from TB32 Impacts Against Various Barriers

description: Organized into separate folders, cable, concrete, and w_beam,each subdirectory provides a single CSV file (vrz_ax_ay_az.csv) detailing the translational accelerations along the X, Y, and Z axes and the rotational velocity around the Z axis of the vehicle’s center of gravity during an EN1317 TB32 impact test. Additionally, a resultant_head_accelerations.csv file in the main directory compiles occupant head acceleration data from all three barrier configurations, facilitating comparisons of occupant kinematics and potential injury metrics across different roadside barrier designs.
DOI: 10.6084/m9.figshare.27187530
title: Structural insights into transmembrane helix S0 facilitated RyR1 channel gating by Ca2+/ATP

description: The data reported in this manuscript is deposit to pdb and emdb for reviewing.File names are specified as sample buffer conditions.
DOI: 10.6084/m9.figshare.27187530.v1
title: Structural insights into transmembrane helix S0 facilitated RyR1 channel gating by Ca2+/ATP

description: The data reported in this manuscript is deposit to pdb and emdb for reviewing.File names are specified as sample buffer conditions.
DOI: 10.5281/zenodo.14921711
title: Combined Retracted Paper IDs from Retraction Watch Data and OpenAlex (December 31, 2024 Version)

description: What is this data?

This dataset was constructed for the analysis of retracted papers by combining "Retraction Watch Data" with OpenAlex data.

What is the format of this data?

It adopts a simple schema with two fields: OpenAlex’s works_id and DOI. Other necessary information—such as the paper’s title, authors, and retraction reasons—can be obtained using these IDs from sources like OpenAlex, Crossref, and "Retraction Watch Data."

What is the source data?

"Retraction Watch Data" is the December 31, 2024 version that was acquired on January 1, 2025 via Crossref’s GitLab repository (https://gitlab.com/crossref/retraction-watch-data). Similarly, OpenAlex was obtained as a snapshot from the official S3 repository, also dated December 31, 2024.

Why is this necessary?

As is well known, OpenAlex incorporates "Retraction Watch Data", so one might assume that analyzing the retraction flags in the works object would suffice. However, as pointed out in the following literature (https://doi.org/10.48550/arXiv.2403.13339), there are many errors. Moreover, the retraction reasons are available only in the "Retraction Watch Data." Therefore, by independently merging both datasets, the accuracy and scope of the analysis can be enhanced.

How were they combined?

In merging "Retraction Watch Data" with OpenAlex, the paper’s DOI (Digital Object Identifier) is used as the primary key.

Note that "Retraction Watch Data"contains two types of DOIs:



RetractionDOI: The DOI of the retraction notice (i.e., the article announcing the retraction).

OriginalPaperDOI: The DOI of the retracted paper (i.e., the regular paper that is being retracted).


There are cases where the two DOIs are identical or where only one is available. For the merging process described above, the OriginalPaperDOI is used. The number of unique OriginalPaperDOIs is 50,831, representing the maximum number of mergeable candidates. In comparison, the simple unique count of RetractionDOIs is 51,050; excluding those identical to the OriginalPaperDOIs leaves 38,314, and further limiting to records that do not have an OriginalPaperDOI yields 2,605 unique RetractionDOIs.

Even among papers with DOIs, some are not included in OpenAlex, resulting in 50,073 records being linked. Among these linked retracted papers, several were published in the 1960s. Therefore, the analysis was limited to a 10-year period from 2013 to 2022, resulting in 32,368 papers being included in the study.
DOI: 10.5281/zenodo.14921712
title: Combined Retracted Paper IDs from Retraction Watch Data and OpenAlex (December 31, 2024 Version)

description: What is this data?

This dataset was constructed for the analysis of retracted papers by combining "Retraction Watch Data" with OpenAlex data.

What is the format of this data?

It adopts a simple schema with two fields: OpenAlex’s works_id and DOI. Other necessary information—such as the paper’s title, authors, and retraction reasons—can be obtained using these IDs from sources like OpenAlex, Crossref, and "Retraction Watch Data."

What is the source data?

"Retraction Watch Data" is the December 31, 2024 version that was acquired on January 1, 2025 via Crossref’s GitLab repository (https://gitlab.com/crossref/retraction-watch-data). Similarly, OpenAlex was obtained as a snapshot from the official S3 repository, also dated December 31, 2024.

Why is this necessary?

As is well known, OpenAlex incorporates "Retraction Watch Data", so one might assume that analyzing the retraction flags in the works object would suffice. However, as pointed out in the following literature (https://doi.org/10.48550/arXiv.2403.13339), there are many errors. Moreover, the retraction reasons are available only in the "Retraction Watch Data." Therefore, by independently merging both datasets, the accuracy and scope of the analysis can be enhanced.

How were they combined?

In merging "Retraction Watch Data" with OpenAlex, the paper’s DOI (Digital Object Identifier) is used as the primary key.

Note that "Retraction Watch Data"contains two types of DOIs:



RetractionDOI: The DOI of the retraction notice (i.e., the article announcing the retraction).

OriginalPaperDOI: The DOI of the retracted paper (i.e., the regular paper that is being retracted).


There are cases where the two DOIs are identical or where only one is available. For the merging process described above, the OriginalPaperDOI is used. The number of unique OriginalPaperDOIs is 50,831, representing the maximum number of mergeable candidates. In comparison, the simple unique count of RetractionDOIs is 51,050; excluding those identical to the OriginalPaperDOIs leaves 38,314, and further limiting to records that do not have an OriginalPaperDOI yields 2,605 unique RetractionDOIs.

Even among papers with DOIs, some are not included in OpenAlex, resulting in 50,073 records being linked. Among these linked retracted papers, several were published in the 1960s. Therefore, the analysis was limited to a 10-year period from 2013 to 2022, resulting in 32,368 papers being included in the study.
DOI: 10.15468/dl.pygztu
title: Occurrence Download

description: A dataset containing 2316 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Melochia nodiflora Sw."
 ]
}

 The dataset includes 2316 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004327-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hpd49kv6cf.1
title: Higher education management in times of crisis: A qualitative approach

description: The article seeks to answer the question: How did private higher education institutions survive during the pandemic? What strategies were developed to ensure the sustainability of the institution?
What practical measures were taken? Research shows that in times of crisis, HEIs tend to adopt a centralized management approach, partially delegating their actions in an environment of intense collaboration.
DOI: 10.5281/zenodo.14921709
title: 4DHydro_Results_Tetis_Po_15sec_daily_exp31_20070101_20221231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 15 sec, and temporal resolution daily. Experiment 31. Forcing "mergedera5gpmsm2a". Calibrating methodology MOSCEM, calibrated variable SM

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2
DOI: 10.5281/zenodo.14921710
title: 4DHydro_Results_Tetis_Po_15sec_daily_exp31_20070101_20221231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 15 sec, and temporal resolution daily. Experiment 31. Forcing "mergedera5gpmsm2a". Calibrating methodology MOSCEM, calibrated variable SM

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2
DOI: 10.17632/c4wpbkwwx4.1
title: Factores asociados a la lactancia materna exclusiva en un hospital de referencia nacional

description: Es una base de datos filtrada que estudia los factores asociados con la práctica de lactancia materna exclusiva al momento del egreso hospitalario.
DOI: 10.6084/m9.figshare.28448441
title: A dataset of near-surface NO₂ concentrations with a 1km² resolution over mainland China (2014 to 2020).

description: This dataset is based on the fusion of multiple satellite NO₂ column concentration data, combined with meteorological reanalysis data, human activity data and other geographically related variables, and uses machine learning models to generate the surface NO₂ concentration and its distribution in mainland China from 2014 to 2020. Among them, the "2014.7z, 2015.7z, 2016.7z, 2017.7z, 2018.7z, 2019.7z, 2020.7z" compressed packages save the monthly average values ​​of surface NO2 in mainland China in the corresponding years; the "Monthly_average.7z" compressed package saves the monthly average values ​​of surface NO2 in mainland China from 2014 to 2020; the "Annual_average.7z" compressed package saves the annual average values ​​of surface NO2 in mainland China from 2014 to 2020.By integrating two satellite products and multi-source geographic data, combined with machine learning algorithms, this dataset fully utilizes the advantages of satellite data in long-term spatiotemporal scales, and provides important support for revealing the spatiotemporal evolution of NO₂ concentrations in mainland China. The spatial resolution of 1km² ensures its high accuracy in pollutant distribution studies at the city level or even smaller scales, and is particularly suitable for fine-grained environmental pollution analysis. This dataset not only provides a scientific basis for environmental monitoring and policy making, but also can deeply explore the complex relationship between air quality and human activities through spatiotemporal change analysis, providing data support for pollution control and air quality improvement.
DOI: 10.6084/m9.figshare.28448441.v4
title: A dataset of near-surface NO₂ concentrations with a 1km² resolution over mainland China (2014 to 2020).

description: This dataset is based on the fusion of multiple satellite NO₂ column concentration data, combined with meteorological reanalysis data, human activity data and other geographically related variables, and uses machine learning models to generate the surface NO₂ concentration and its distribution in mainland China from 2014 to 2020. Among them, the "2014.7z, 2015.7z, 2016.7z, 2017.7z, 2018.7z, 2019.7z, 2020.7z" compressed packages save the monthly average values ​​of surface NO2 in mainland China in the corresponding years; the "Monthly_average.7z" compressed package saves the monthly average values ​​of surface NO2 in mainland China from 2014 to 2020; the "Annual_average.7z" compressed package saves the annual average values ​​of surface NO2 in mainland China from 2014 to 2020.By integrating two satellite products and multi-source geographic data, combined with machine learning algorithms, this dataset fully utilizes the advantages of satellite data in long-term spatiotemporal scales, and provides important support for revealing the spatiotemporal evolution of NO₂ concentrations in mainland China. The spatial resolution of 1km² ensures its high accuracy in pollutant distribution studies at the city level or even smaller scales, and is particularly suitable for fine-grained environmental pollution analysis. This dataset not only provides a scientific basis for environmental monitoring and policy making, but also can deeply explore the complex relationship between air quality and human activities through spatiotemporal change analysis, providing data support for pollution control and air quality improvement.
DOI: 10.17632/hptm86n5k4.1
title: Dataset for Myosin II regulatory light chain phosphorylation and formin availability modulate cytokinesis upon changes in carbohydrate metabolism. Elife (2023) Feb 24;12:e83285. doi: 10.7554/eLife.83285

description: Full data for Figures and Supplementary Figures published in Elife (2023) Feb 24;12:e83285. doi: 10.7554/eLife.83285
DOI: 10.17632/n4f79j4hhz.1
title: Inequality and Optimal Monetary Policy in the Open Economy

description: CODES FOR "INEQUALITY AND OPTIMAL MONETARY POLICY IN THE OPEN ECONOMY" BY SUSHANT ACHARYA AND EDOUARD CHALLE FOR PUBLICATION IN THE JOURNAL OF INTERNATIONAL ECONOMICS
************************************************************************
The codes are written in MATLAB and run in MATLAB 4.2.0.2806996. MATLAB is not freeware and can be obtained from https://www.mathworks.com/products/matlab.html
The code also requires the MATLAB Symbolic Math Toolbox Version 24.2 

Instructions:
1. Run pics_for_paper.m to generate Figures 1,2,3 and 4. 

Other functions called by the above scripts:
a) makesteady.m : this function computes the steady state of the Ramsey plan in the HANK economy.
b) make_steady_RANK.m : this function computes steady states of the Ramsey plan for the RANK benchmark.
c) optdynamics.m : this function computes the optimal dynamics in response to an aggregate shock shock in the HANK economy.
d) opt_dynamics_RANK.m : this function computes the optimal dynamics in response to an aggregate shock shock in the RANK economy.
e) pricestab.m : this function coputes the dyamics in response to shocks in HANK when monetary policy inefficiently implements price stability.
F) colors.m : this function assigns names to returns RGB tuples adapted from % http://en.wikipedia.org/wiki/List_of_colors, and is used in plotting curves in all figures.
DOI: 10.17632/n4f79j4hhz.2
title: Inequality and Optimal Monetary Policy in the Open Economy

description: CODES FOR "INEQUALITY AND OPTIMAL MONETARY POLICY IN THE OPEN ECONOMY" BY SUSHANT ACHARYA AND EDOUARD CHALLE FOR PUBLICATION IN THE JOURNAL OF INTERNATIONAL ECONOMICS
************************************************************************
The codes are written in MATLAB and run in MATLAB 4.2.0.2806996. MATLAB is not freeware and can be obtained from https://www.mathworks.com/products/matlab.html
The code also requires the MATLAB Symbolic Math Toolbox Version 24.2 

Instructions:
1. Run pics_for_paper.m to generate Figures 1,2,3 and 4. 

Other functions called by the above scripts:
a) makesteady.m : this function computes the steady state of the Ramsey plan in the HANK economy.
b) make_steady_RANK.m : this function computes steady states of the Ramsey plan for the RANK benchmark.
c) optdynamics.m : this function computes the optimal dynamics in response to an aggregate shock shock in the HANK economy.
d) opt_dynamics_RANK.m : this function computes the optimal dynamics in response to an aggregate shock shock in the RANK economy.
e) pricestab.m : this function coputes the dyamics in response to shocks in HANK when monetary policy inefficiently implements price stability.
F) colors.m : this function assigns names to returns RGB tuples adapted from % http://en.wikipedia.org/wiki/List_of_colors, and is used in plotting curves in all figures.
DOI: 10.17632/j28xwntfms.1
title: Dataset for Evolutionary divergence of cytokinesis and dimorphism control by myosin II and regulatory light chain phosphorylation in the fission yeast clade. iScience (2023) Aug 12; 26(9):107611. doi: 10.1016/j.isci.2023.107611

description: Full raw data corresponding to Figures in iScience (2023) Aug 12; 26(9):107611.
DOI: 10.15468/dl.avtmg3
title: Occurrence Download

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bonia Balansa"
 ]
}

 The dataset includes 108 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004331-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9x96vxp2cs.1
title: Skin Pain Characteristics in Psoriasis and Psoriatic Arthritis: A Cross-Sectional Study

description: Supplementary materials for manuscript entitled "Skin Pain Characteristics in Psoriasis and Psoriatic Arthritis: A Cross-Sectional Study".
DOI: 10.5281/zenodo.14910005
title: FESOM2 meshes: SO3

description: FESOM2 mesh with a focus on the Southern Ocean. The resolution in the Southern Ocean is around 3 km, while in the rest of the globe, it is around 25 km. The resolution in major straits is also increased.

Vertices: 11087062, Triangles: 22138985

Mesh is generated with JIGSAW-GEO

To reproduce the plot, you need pyfesom2 installed. The resolution is shown according to Danilov (2022).
DOI: 10.15468/dl.r6tafz
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cirsium arvense var. alpestre Nägeli"
 ]
}

 The dataset includes 173 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004332-250221090833381/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.28481012
title: Long non-coding RNA and mRNA expression profiling of porcine satellite cells using strand-specific RNA-seq

description: Transcriptome analysis
DOI: 10.24427/2022/45/b/hs4/01414_pb_7
title: Dane z badań miasto Łomża / Research data from Łomża City
DOI: 10.17632/2hf4kn49fn.1
title: Replication file for: "The Fiscal Multiplier in Presence of Unconventional Monetary Policy: Evidence for 17 OECD countries"

description: Data, code, figures and tables for article: "The Fiscal Multiplier in Presence of Unconventional Monetary Policy: Evidence for 17 OECD countries"
DOI: 10.17632/cjbczy723b.1
title: UV-Vis spectrophotometric determination of rare earth elements (REE) speciation at near-neutral to alkaline pH. Part II: hydrolysis of Er from 25 to 75 °C

description: Here, UV-Vis spectrophotometry experiments were conducted as a function of temperature between 35 and 75 ℃ to determine the hydrolysis of Er in near-neutral to alkaline solutions using mCP as an in situ pH color indicator. The experiments were conducted with Er concentrations from 0 to ~0.253 mmol/kg in low ionic strength solutions (≤ 0.001 mol/kg). The average OH− ligand number coordinated to Er3+ increases from 1.0 to 2.7 at 35 ℃ and from 1.5 to 3.2 at 75 ℃ over a pH range from 6.3 to 9.0. The measured speciation shows an increased predominance of Er(OH)30 over the Er(OH)2+ and Er(OH)2+ species with increased temperature. The logarithmic values of Er hydrolysis constants (log*βn◦, n =1 to 3) were derived for the reaction Er3+ + nH2O = Er(OH)n3-n + nH+ at each temperature of 35, 50, and 75 ℃: log*β1◦ of −7.02 ± 0.09, −6.19 ± 0.06, −5.43 ± 0.16; log*β2◦ of −14.39 ± 0.15, −13.98 ± 0.01, and −13.45 ± 0.24; log*β3◦ of −22.85 ± 0.15, −21.79 ± 0.14, and −20.32 ± 0.09. These equilibrium constants were fitted to a function to predict the hydrolysis constants of Er between 25 and 75 ℃, and show a systematic increase in the stability of REE hydroxyl complexes with higher ligand numbers with increased temperature.
DOI: 10.15468/dl.5dy3gh
title: Occurrence Download

description: A dataset containing 94 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((4.80873 43.9457,4.76277 43.92153,4.92363 43.93053,4.80873 43.9457))",
 "Geometry POLYGON((4.75203 43.84861,4.93257 43.84861,4.93257 43.98082,4.75203 43.98082,4.75203 43.84861))"
 ]
 },
 "PublishingCountry is France",
 "TaxonKey is Chiroptera",
 "Year 2019-2025"
 ]
}

 The dataset includes 94 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004333-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pnhw5czzcz
title: In situ Raman investigation of Dy complexation in Cl-bearing aqueous solutions at 20–300 °C

description: In this study, the speciation of Dy in acidic chloride-bearing hydrothermal solutions was investigated using confocal Raman spectroscopy with a new capillary Raman heating stage at
20–300 °C. Background solutions (pure water, NaCl-solutions) and solutions with 0.14–1.8 mol kg−1 dissolved DyCl3 were sealed in quartz capillary cells. Comparison of the spectra for Dy chloride solutions
with those for background solutions and the spectra for reference Dy-bearing solids was used to identify Raman bands specific to Dy–O and Dy–Cl bonds. The Raman band for the Dy–O stretching mode of
hydrated Dy3+ aqua ions was measured at 365–384 cm−1 and a Raman band for the Dy–Cl stretching modes of Dy chloride complexes was measured near 240 cm−1 . The Dy–O band decreases systematically
with temperature, whereas the Dy–Cl band systematically increases, indicating a systematic increase in the stability of Dy chloride complexes with temperature. This study provides the framework for expanding
the use of in situ Raman spectroscopy to investigate the speciation of REE in aqueous solutions to hydrothermal conditions.