cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.r2280gbpw
title: Effect of verbal interference and response hand on hemisphere asymmetries in sad facial expression processing

description: A growing amount of evidence highlights a role for the left hemisphere in
 negative facial expression processing. The present study investigated the
 extent to which language contributes to this left hemisphere involvement
 by comparing performance during an emotion detection task presented to the
 left and right hemispheres using divided visual field under conditions of
 verbal interference (covertly rehearsing a 6-digit string for a subsequent
 memory) and no interference. Participants were college undergraduates with
 no known neurological or psychiatric conditions. Half used their right
 hand to respond and half used their left. In line with the hypothesis that
 language contributes to left hemisphere involvement in negative expression
 processing, participants who used their right hand to respond were more
 accurate with sad facial expressions when they were presented to the left
 hemisphere than the right during the no interference condition, but this
 left-hemisphere advantage disappeared during the verbal interference
 condition. Contrary to the hypothesis, participants who used their left
 hand to respond were more accurate with sad facial expressions when they
 were presented to the right hemisphere than when they were presented to
 the left, and this right-hemisphere advantage did not differ significantly
 between interference groups. Results highlight the influence of language
 as well as response hand on hemisphere asymmetries in facial expression
 processing and point towards areas for future research.
description: # Effect of verbal interference and response hand on hemisphere
 asymmetries in sad facial expression processing Dataset DOI:
 [10.5061/dryad.r2280gbpw](10.5061/dryad.r2280gbpw) ## Description of the
 data and file structure We provide the hit/false alarm rate, d-prime
 score, and response time (ms) for each participant in each
 expression-by-visual-field condition. ### Files and variables ####
 Description of the data and file structure A label describing the data
 contained in each column is provided in row 1 of the .csv file. **Column
 Descriptions:** * participant: Unique identifier assigned to each
 individual participant * gender: Participant’s gender identity *
 interference: Indicates whether the participant was in the verbal
 interference condition (verbal) or not (none) * response_hand: Hand used
 by the participant to respond (right or left) **Abbreviations used in
 variable names:** **Facial expressions** * an = angry * di = disgusted *
 fe = fearful * ha = happy * sa = sad * su = surprised * ne = neutral
 **Visual field** * l = left visual field * r = right visual field
 **Measurement type** * hit = hit rate * fa = false alarm rate * d =
 d-prime * rt_empty = response time (ms) with empty cells for conditions in
 which a participant did not get any items correct * rt_replaced = response
 time (ms) with empty cells replaced with the grand mean (592 ms)
DOI: 10.5281/zenodo.18407869
title: Quarterly Census of Employment and Wages (QCEW) 2024: 409 BEA sectors, all U.S. counties

description: County-level QCEW data for 2024, aggregated to 409 BEA sectors. Derived from Tapestry (University of Idaho) and redistributed under CC BY-SA 4.0.
DOI: 10.5281/zenodo.18407868
title: Quarterly Census of Employment and Wages (QCEW) 2024: 409 BEA sectors, all U.S. counties

description: County-level QCEW data for 2024, aggregated to 409 BEA sectors. Derived from Tapestry (University of Idaho) and redistributed under CC BY-SA 4.0.
DOI: 10.5061/dryad.mgqnk999c
title: Data from: What’s on the menu? Examining native apex- and invasive meso-predator diets to understand impacts on ecosystems

description: In Australia, populations of a native, terrestrial apex predator, the
 dingo Canis dingo/C. familiaris, introduced invasive subordinate
 mesopredators, the European red fox Vulpes vulpes and feral cat Felis
 catus, which co-occur, but there is limited understanding of their
 relative impacts on native and invasive prey in different ecosystems. We
 collected scats from each predator across a ~10,000 km2 semi-arid
 mallee environment, and used macroscopic scat analysis to identify prey
 species making up the diet of the three predator species. The archived
 dataset is the raw diet results of all scats collected as part of this
 study.
description: # What’s on the menu? Examining native apex- and invasive meso-predator
 diets to understand impacts on ecosystems Dataset DOI:
 [10.5061/dryad.mgqnk999c](10.5061/dryad.mgqnk999c) ## Description of the
 data and file structure **Prey Items tab:** The archived dataset contains
 the raw diet results of all predator scats collected as part of this
 study. In the spreadsheet, each scat has been assigned a unique ID, listed
 in the "ID" column (column A), and identified as a specific
 predator (feral cat *Felis catus*, European fox *Vulpes vulpes*, or dingo
 *Canis dingo*) in the "Predator" column (B). Column headings for
 columns C – AL list all prey species/categories identified across all
 scats. Cells in columns C – AL contain the estimated percent each prey
 species/category contributed to the total volume of each scat (i.e. cells
 containing a value of 100 indicate 100% of the scat volume was made up of
 that specific prey species/category).  **Metadata tab:**  Column A =
 unique scat ID correlating to data in the Prey Items tab Column B = Y
 coordinates where scat was located Column C = X coordinates where scat was
 located Column D = Predator species **Note**: Due to cultural and
 conservation sensitives, GPS coordiinates of dingo scat locations will
 only be available on reasonable request to the corresponding author.
 **Corresponding author details:**  Rachel T Mason -
 [rachel.mason@research.deakin.edu.au](mailto:rachel.mason@research.deakin.edu.au)
DOI: 10.15468/dl.89kudx
title: Occurrence Download

description: A dataset containing 294 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Malapterurus electricus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 294 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004288-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.96akte
title: Occurrence Download

description: A dataset containing 389 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-180 -60,-70 -60,-70 70,-180 70,-180 -60))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Balaenoptera acutorostrata",
 "Year 2000-2026"
 ]
}

 The dataset includes 389 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004287-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.dr7sqvb8q
title: Script from: The marginal majority effect: when social influence produces lock-in

description: People are influenced by the choices of others, a phenomenon observed
 across contexts in the social and behavioral sciences. Social influence
 can lock in an initial popularity advantage of an option over a higher
 quality alternative. Yet, several experiments designed to enable social
 influence have found that social systems self-correct rather than lock in.
 Here, we identify a behavioral phenomenon that makes inferior lock-in
 possible, which we call the 'marginal majority effect': A
 discontinuous increase in the choice probability of an option as its
 popularity exceeds that of a competing option. We demonstrate the
 existence of a marginal majority effect in several recent experiments and
 show that lock-in always occurs when the effect is large enough to offset
 the quality effect on choice, but rarely otherwise. Our results reconcile
 conflicting past empirical evidence and connect a behavioral phenomenon to
 the possibility of social lock-in.
description: # Script from: The marginal majority effect: when social influence
 produces lock-in Dataset DOI:
 [10.5061/dryad.dr7sqvb8q](10.5061/dryad.dr7sqvb8q) ## Description of the
 data and file structure #### File: main.py **Description:** This is the
 code used to generate figures 4 and 6-9 in the paper "The marginal
 majority effect: when social influence produces lock-in", as well as
 supplementary figures S2-S13. It also performs the statistical analyses
 reported in both the main paper an the supplementary material. It has been
 tested in Python 3.13 with the following package versions: matplotlib
 3.10.7 pandas 2.3.3 scipy 1.16.2 seaborn 0.13.2 statsmodels 0.14.5 
 
 ### How to run the code To reproduce the figures and statistical
 analyses, first download the data from the experiments analyzed: \- V2019:
 [https://doi.org/10.17605/osf.io/p4y37](https://doi.org/10.17605/osf.io/p4y37), specifically the file vanderijt2019.csv \- MDRT2019: [https://doi.org/10.5281/zenodo.17455649](https://doi.org/10.5281/zenodo.17455649), specifically the file experiment_analysis_1/answer_data.csv (original repository [https://github.com/AlexMRuch/PartyLab](https://github.com/AlexMRuch/PartyLab), accessed November 3rd 2025) \- FV2021: [https://doi.org/10.17605/osf.io/5f2cm](https://doi.org/10.17605/osf.io/5f2cm), specifically the file Frey_vdRijt_WoC/data/WoC_web.dta Save the above files in the same folder as the main.py script and run the script. The output will be saved in the same folder. If you are interested only in certain parts of the analysis/figures, comment out any lines near the end of the script that are not needed (the output name in each line corresponds to the figure/statistical analysis that line performs). NOTE: The statistical analyses for sections 5.2-5.4 of the supplementary material that are performed at the end are somewhat slow, in the order of minutes on a personal computer. To speed them up, adjust the num_reps parameter.
DOI: 10.5061/dryad.5x69p8dg4
title: Supplementary data from: Inherent single-cell heterogeneity of the transcriptional response to hypoxia in cancer cells

description: Hypoxia-inducible factor (HIF) is a master regulator of cancer cell
 adaptation to tumor hypoxia and is involved in cancer progression.
 Single-cell (sc) differences in the HIF response allow for tumor evolution
 and cause therapy resistance. These sc-differences are usually ascribed to
 tumor microenvironmental differences and/or clonal (epi)genetic
 variability. However, the sc-heterogeneity of the HIF response in
 otherwise identical cells cultured under defined in vitro conditions has
 not yet been addressed. Therefore, we analyzed the sc-response to hypoxia
 in nonclonal cell lines and multiple clonal derivatives, including HIF-1a
 or HIF-2a knockouts. While HIF-1a and HIF-1 target mRNA sc-heterogeneity
 was slightly higher than global transcription or specific housekeeping
 mRNAs, HIF-2a and especially HIF-2 target mRNA sc-heterogeneity was
 extraordinary, and remained in independent clones and following HIFa
 knockouts. Unexpectedly, neither HIF-2a mRNA nor nuclear protein levels
 correlated with target mRNA levels. Unsupervised but not supervised HIF
 target gene dimensionality reduction revealed the initial sample
 composition after scRNAseq, demonstrating that, owing to sc-heterogeneity,
 individual HIF target genes are not sufficient to unequivocally identify
 hypoxic cancer cells. In conclusion, the pronounced intrinsic
 sc-heterogeneity of the HIF response represents a hitherto unrecognized
 feature of cancer cells that impairs clinical HIF pathway-dependent cancer
 cell identification and targeting.
description: # Supplementary data from: Inherent single-cell heterogeneity of the
 transcriptional response to hypoxia in cancer cells Dataset DOI:
 [10.5061/dryad.5x69p8dg4](10.5061/dryad.5x69p8dg4) ## Description of the
 data and file structure Underlying primary data for the supplement of the
 publication Wilk et al., "Inherent single-cell heterogeneity of the
 transcriptional response to hypoxia in cancer cells" in NAR Cancer,
 2025, 7, zcaf021. All information about data content and file structure
 can be found therein. **Files and variables** **File:
 Wilk_SupplementaryFigures.zip, PythonScript_DensityPlots.ipynb, and
 PythonScript_HeterogeneityPlots.ipynb** **Description:** Underlying
 supplementary data of Figures S1 to S12 of the publication Wilk et al.,
 "Inherent single-cell heterogeneity of the transcriptional response
 to hypoxia in cancer cells". **Code/software** Image viewer, Excel,
 cell profiler, Adobe acrobat, Python script (ipynb).
DOI: 10.15468/dl.wrwwmk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euzetacanthus simplex",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004290-260126135527185/datasets/export for details.
DOI: 10.15468/dl.g72dep
title: Occurrence Download

description: A dataset containing 364597 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "TaxonKey is one of (Aponogeton distachyos, Arthurdendyus triangulatus, Cabomba caroliniana, Callosciurus finlaysonii, Cherax destructor, Corvus splendens, Crassula helmsii, Elodea densa, Eriocheir sinensis, Erythranthe guttata, Faxonius immunis, Faxonius juvenilis, Faxonius rusticus, Faxonius virilis, Gambusia affinis, Heracleum mantegazzianum, Heracleum persicum, Heracleum pubescens, Houttuynia cordata, , Impatiens glandulifera, Koenigia polystachya, Lagarosiphon major, Lepomis gibbosus, Limnoperna fortunei, Ludwigia grandiflora, Ludwigia peploides, Lysichiton americanus, Morone americana, Muntiacus reevesi, Myriophyllum aquaticum, Myriophyllum heterophyllum, Pacifastacus leniusculus, Petasites japonicus, Pontederia cordata, Procambarus acutus, Procambarus clarkii, Procambarus virginalis, Pseudorasbora parva, Pycnonotus cafer, Saururus cernuus, Sciurus carolinensis, Sciurus niger, Solenopsis invicta, Solenopsis richteri, Threskiornis aethiopicus, Vespa velutina, Zizania latifolia)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 364597 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004261-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.x0k6djhwn
title: Database for spring, summer and fall-planted cover crop performance across the state of Nebraska

description: This repository contains raw datasets from multi-year cover crop variety
 trials conducted across Nebraska to evaluate biomass production, plant
 height, nutrient content, and soil health parameters. Trials were
 established in multiple ecoregions, including UNL research stations and
 private farms, to assess cover crop performance under diverse conditions.
 The data includes cover crop biomass, soil properties, root measurements,
 and vegetative indices, along with metadata on trial locations and
 management practices. This repository supports researchers, agronomists,
 and stakeholders in optimizing cover crop management and soil health. The
 structured datasets facilitate reproducibility and contribute to
 developing Nebraska-specific cover crop growth models and management
 recommendations.
description: # Database for spring, summer and fall-planted cover crop performance
 across the state of Nebraska Dataset DOI:
 [10.5061/dryad.x0k6djhwn](10.5061/dryad.x0k6djhwn) This database contains
 data on cover crop aboveground biomass measurements taken during different
 seasons: Spring, Summer, and Fall. The datasets include details on cover
 crop species, biomass production, plant height, nutrient content, and
 other agronomic parameters, obtained from multiple cover crop variety
 trials performed in different locations in the state of Nebraska from 2022
 - 2024. ## Description of the data and file structure Data files are
 numbered and described in the 1_data_dictionary.csv file.
 1_data_dictionary.csv provides a definition of variables for the following
 files. 2_proyect_metadata.csv provides detailed site location, cover crop
 growing season, and study design information.
 3_spring_cc_aboveground_data.csv contains all the cover crop-related data
 associated with the spring-planted cover crop variety trials.
 4_summer_cc_aboveground_data.csv contains all the cover crop aboveground
 data associated with the summer-planted cover crop variety trials.
 5_summer_cc_vegetative_index.csv contains the vegetative index (NDVI and
 NDRE) data associated with summer cover crop variety trials.
 6_fall_cc_aboveground_data.csv contains all the cover crop aboveground
 data associated with the fall-planted cover crop variety trials.
 7_fall_cc_soil_data.csv provides all the soil sample data obtained from
 fall-planted cover crop variety trials. 8_fall_cc_root_data.csv provides
 root biomass data obtained from fall-planted cover crop variety trials.
 9_agronomic_data.csv provides agronomic management data general to each
 study. Empty cells or cells containing NA indicate that no data were
 available.
DOI: 10.5061/dryad.f1vhhmh6z
title: Data from: A pulsar-helium star compact binary system formed by common envelope evolution

description: A stellar common envelope occurs in a binary system when the atmosphere of
 an evolving star expands to encompass an orbiting companion object. Such
 systems are predicted to evolve rapidly, ejecting the stellar envelope and
 leaving the companion in a tighter orbit around a stripped star. We use
 radio timing to identify a pulsar, PSR J1928+1815, with a spin period of
 10.55 ms in a compact binary system with an orbital period of 3.60 hours.
 The companion star has 1.0 to 1.6 solar masses and eclipses the pulsar for
 about 17% of the orbit, so is most likely a stripped helium star but is
 undetected at other wavelengths. We interpret this system as having
 recently undergone a common envelope phase, producing a compact binary.
description: # Data from: A pulsar-helium star compact binary system formed by common
 envelope evolution Dataset DOI:
 [10.5061/dryad.f1vhhmh6z](10.5061/dryad.f1vhhmh6z) ## Description of the
 data and file structure Processed FAST data of PSR J1928+1815, a binary
 pulsar discovered in FAST GPPS survey. ### Files and variables #### File:
 yhz25dat.tar.gz **Description:** Processed FAST data of PSR J1928+1815, a
 binary pulsar discovered in FAST GPPS survey. 1\) Folded pulsar profiles
 of PSR J1928+1815. These profiles have a bin number of 128 a sub-bint
 integration time is 300 s and 4 frequency channels. The radio frequency
 range is 1.0 to 1.5 GHz. 2\) We link three observations during which the
 pulsar was eclipsed to the 'nodect' folder . 3\) The sum
 polarization profile is in 'sum_profile' folder. 4\) The
 ephemeris and TOAs of PSR J1928+1815 is in 'timing' folder. ##
 Code/software The code used for view the data is PSRCHIVE package
 ([https://psrchive.sourceforge.net/](https://psrchive.sourceforge.net/)),
 the package version is 2022 January 14. ## Access information Other
 publicly accessible locations of the data: *
 [http://zmtt.bao.ac.cn/GPPS/gpps0121/](http://zmtt.bao.ac.cn/GPPS/gpps0121/)
DOI: 10.5061/dryad.1ns1rn952
title: Floristic characteristics and regionalisation of karst woody plants in China

description: Information on 111 sampling sites of karst woody plant communities in
 China. This includes location, GPS coordinates, number of specimens, and
 identification results of all specimens (some are only identified to genus
 level or not identified). At the same time, we summarised the
 characteristic genera of karst woody plants in China and speculated their
 possible floristic origins.
description: # Floristic characteristics and regionalisation of karst woody plants in
 China Dataset DOI: [10.5061/dryad.1ns1rn952](10.5061/dryad.1ns1rn952) ##
 Description of the data and file structure This datasets include
 geographic information and species identification lists of all sampling
 sites. ### Files and variables #### File:
 1\_Sampling\_sites\_information.xlsx **Description:** Geographic
 information of all 111 sampling sites, including county, province, GPS
 coordinates and total specimens number of the site. ##### Variables * Site
 code: The unique number of each sampling site, starting with K, plus a 2
 to 3-digit number, and some sites have been removed due to non-standard
 sampling, so the numbers are not completely sequential. * Site name: The
 name of the county in China where the sampling sites are located. *
 Province: The name of the province in China where the sampling sites are
 located. * Latitude: The latitude coordinates of the sampling sites, saved
 in decimal format. * Longitude:  The longitude coordinates of the sampling
 sites, saved in decimal format. * Number of specimens: Number of dicot
 woody plant samples contained at each sampling site. #### File:
 2\_Species\_list\_of\_sampling\_sites.xlsx **Description:** Taxa
 identification lists of all 111 sampling sites, including specimens no.
 and taxa. These specimens are preserved in the Herbarium of Xishuangbanna
 Tropical Botanical Garden, Chinese Academy of Sciences (HITBC). #####
 Variables * Specimen No.: The unique number of each specimen is composed
 of the sampling site number plus a 2~3-digit numeric number, separated by
 "_" in the middle. * Taxa:  The preliminary identification
 results of the specimen were identified at the species, genus or family
 level. #### File:
 3\_Karst\_genera\_and\_their\_possible\_floristic\_origin.xlsx
 **Description:** 169 characteristic genera of karst woody plants of China
 and their possible floristic origins. Alphabetical order by genus name.
 ##### Variables * Genus: The genus name of the representative genera of
 karst woody plants of China. * Family:  The family to which the genus
 belongs, according to the latest taxonomy. * Possible floristic
 origin: The estimated paleofloristic origins of these genera are as
 follows: Arctic Tertiary, Palaeotropic Tertiary, Tethys Tertiary,
 Gondwana, and uncertain.
DOI: 10.5281/zenodo.18407888
title: Topographic barriers and lowland corridors structure gene flow in the Chagas vector Rhodnius pallescens across the Isthmian Forests
DOI: 10.5281/zenodo.18407889
title: Topographic barriers and lowland corridors structure gene flow in the Chagas vector Rhodnius pallescens across the Isthmian Forests
DOI: 10.15468/dl.8jpf2s
title: Occurrence Download

description: A dataset containing 389 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-180 -60,-70 -60,-70 70,-180 70,-180 -60))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Balaenoptera acutorostrata",
 "Year 2000-2026"
 ]
}

 The dataset includes 389 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004291-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.