cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25442/hku.30009019
title: <i>Supporting data for </i><b>Reconstructing Event Durations: The Transformation of Retrospective Time Judgments</b>

description: Human time perception is essential for cognitive function. Specifically, our ability to make retrospective duration judgments helps us assess the significance of experiences and plan appropriate time allocations for future activities. However, the underlying mechanisms driving these temporal evaluations remain contested. Competing theories propose either reconstructive processes based on recalled memory or independent temporal processing systems. This thesis investigates how memory influences retrospective duration judgments, examining which memory components drive temporal perception and the neural mechanisms that enable selective temporal modification while preserving event content.<br>Directory of Files:A. Filename: Chapter 2 Data Short description: Fifty-five individuals (Female = 39, Preferred not to say = 1; M<sub>age</sub> = 22.589; SD<sub>age</sub> = 3.109) were recruited from the University of Hong Kong for this experiment. This file contains data that support the study in Chapter 2, including behavior data, coding report for drawing analysis. All information that can be used to identify human participants have been removed. B. Filename: Chapter 3 Data Short description: Fifty-seven individuals (Female = 45; M<sub>age</sub> = 24.1 years; SD<sub>age</sub> = 2.588 years) were recruited from the University of Hong Kong for this experiment. Some participants were excluded according to ensure data quality and manipulation validity.This file contains data that support the study in Chapter 3, including behavior data, preprocessed event-related spectral power (ERSP) data and ChatGPT codedverbal report results (Gist and Details). All information that can be used to identify human participants have been removed. C. Filename: Chapter 4 Data Short description: EEG analysis for the study in Chapter 3. This file contains data that support the study in Chapter 4, including behavior, Power spectral data and RSA data for the verbal report results. All information that can be used to identify human participants have been removed. <br>
DOI: 10.25442/hku.30009019.v1
title: <i>Supporting data for </i><b>Reconstructing Event Durations: The Transformation of Retrospective Time Judgments</b>

description: Human time perception is essential for cognitive function. Specifically, our ability to make retrospective duration judgments helps us assess the significance of experiences and plan appropriate time allocations for future activities. However, the underlying mechanisms driving these temporal evaluations remain contested. Competing theories propose either reconstructive processes based on recalled memory or independent temporal processing systems. This thesis investigates how memory influences retrospective duration judgments, examining which memory components drive temporal perception and the neural mechanisms that enable selective temporal modification while preserving event content.<br>Directory of Files:A. Filename: Chapter 2 Data Short description: Fifty-five individuals (Female = 39, Preferred not to say = 1; M<sub>age</sub> = 22.589; SD<sub>age</sub> = 3.109) were recruited from the University of Hong Kong for this experiment. This file contains data that support the study in Chapter 2, including behavior data, coding report for drawing analysis. All information that can be used to identify human participants have been removed. B. Filename: Chapter 3 Data Short description: Fifty-seven individuals (Female = 45; M<sub>age</sub> = 24.1 years; SD<sub>age</sub> = 2.588 years) were recruited from the University of Hong Kong for this experiment. Some participants were excluded according to ensure data quality and manipulation validity.This file contains data that support the study in Chapter 3, including behavior data, preprocessed event-related spectral power (ERSP) data and ChatGPT codedverbal report results (Gist and Details). All information that can be used to identify human participants have been removed. C. Filename: Chapter 4 Data Short description: EEG analysis for the study in Chapter 3. This file contains data that support the study in Chapter 4, including behavior, Power spectral data and RSA data for the verbal report results. All information that can be used to identify human participants have been removed. <br>
DOI: 10.5281/zenodo.17082287
title: CLINICAL SIGNS OF ANEMIA IN THE ORAL CAVITY AND PREVENTIVE MEASURES.
DOI: 10.5281/zenodo.17082288
title: CLINICAL SIGNS OF ANEMIA IN THE ORAL CAVITY AND PREVENTIVE MEASURES.
DOI: 10.15468/dl.mbu63w
title: Occurrence Download

description: A dataset containing 5267 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plantago argentea"
 ]
}

 The dataset includes 5267 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044109-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.us9648
title: Occurrence Download

description: A dataset containing 1171 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thymus odoratissimus"
 ]
}

 The dataset includes 1171 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044111-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88smy6
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is Côte d’Ivoire",
 "HasCoordinate is true"
 ]
}

 The dataset includes 41 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044112-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3v9hqs
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is Cuba",
 "HasCoordinate is true"
 ]
}

 The dataset includes 106 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044113-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17082140
title: Facial Micro-Movements as a Proxy of Increasingly Erratic Heart Rate Variability While Experiencing Pressure Pain

description: Data sets from neurotypical participants acquired during resting (control) state and during pain state induced by a sustained pressure on the arm using a blood pressure cuff.

Abstract

The sensation of pain varies from person to person. These patterns of individual variations are difficult to capture using coarse subjective self-reports. However, they are important when prescribing therapies and tailoring them to the person’s own sensations. Pain can be experienced differently by the same person, and fluctuate differently depending on the context, yet most analyses treat the problem under a one-size-fits-all model. In this work, we introduce a series of assays to objectively assess pressure pain across tasks with different motoric and cognitive demands, in relation to resting state. In a cohort of healthy individuals, we examine pain-free vs. pain states at rest, during drawing with heavy cognitive demands, during pointing to a visual target, and during a grooved peg task like inserting a grooved key in a matching grooved keyhole. We recorded Face videos, electrocardiographic signals and adopt a standardized data type called the micro-movement spikes (MMS) to characterize the biorhythmic activities of the Face micro-expressions and of the micro-fluctuations in the heart’s inter beat interval timings. Using the MMS peaks, we find that the continuous Gamma family of probability distribution functions best fit the frequency histograms of both the Face and the heart data. Further, we find that the Gamma shape and scale parameters in both signals span a scaling power law whereby as the noise-to-signal ratio (Gamma scale parameter) increases, so does the randomness of the stochastic process (the Gamma shape decreases towards the memoryless exponential range). We find that as the heart IBI turns more erratic (noisier and more random) the facial ophthalmic region increases the noise and randomness too, with higher linear correlation for tasks requiring haptic feedback (R2 0.84) than for tasks requiring higher cognitive and memory loads (R2 0.77). Increases in transfer entropy shows that recent past activity (~167ms back) of the heart IBI and Face combined lower the uncertainty in the prediction of the present ophthalmic-Face activity, suggesting that this Face region may serve as a proxy of an increasingly dysregulated heart. These results bear implications for the detection and monitoring of pressure pain and heart dysregulated states.
DOI: 10.5281/zenodo.17082141
title: Facial Micro-Movements as a Proxy of Increasingly Erratic Heart Rate Variability While Experiencing Pressure Pain

description: Data sets from neurotypical participants acquired during resting (control) state and during pain state induced by a sustained pressure on the arm using a blood pressure cuff.

Abstract

The sensation of pain varies from person to person. These patterns of individual variations are difficult to capture using coarse subjective self-reports. However, they are important when prescribing therapies and tailoring them to the person’s own sensations. Pain can be experienced differently by the same person, and fluctuate differently depending on the context, yet most analyses treat the problem under a one-size-fits-all model. In this work, we introduce a series of assays to objectively assess pressure pain across tasks with different motoric and cognitive demands, in relation to resting state. In a cohort of healthy individuals, we examine pain-free vs. pain states at rest, during drawing with heavy cognitive demands, during pointing to a visual target, and during a grooved peg task like inserting a grooved key in a matching grooved keyhole. We recorded Face videos, electrocardiographic signals and adopt a standardized data type called the micro-movement spikes (MMS) to characterize the biorhythmic activities of the Face micro-expressions and of the micro-fluctuations in the heart’s inter beat interval timings. Using the MMS peaks, we find that the continuous Gamma family of probability distribution functions best fit the frequency histograms of both the Face and the heart data. Further, we find that the Gamma shape and scale parameters in both signals span a scaling power law whereby as the noise-to-signal ratio (Gamma scale parameter) increases, so does the randomness of the stochastic process (the Gamma shape decreases towards the memoryless exponential range). We find that as the heart IBI turns more erratic (noisier and more random) the facial ophthalmic region increases the noise and randomness too, with higher linear correlation for tasks requiring haptic feedback (R2 0.84) than for tasks requiring higher cognitive and memory loads (R2 0.77). Increases in transfer entropy shows that recent past activity (~167ms back) of the heart IBI and Face combined lower the uncertainty in the prediction of the present ophthalmic-Face activity, suggesting that this Face region may serve as a proxy of an increasingly dysregulated heart. These results bear implications for the detection and monitoring of pressure pain and heart dysregulated states.
DOI: 10.5281/zenodo.17075240
title: Borehole Portable Active Seismic Source (B-PASS) Dataset: Raw and Stacked Source Functions with Vertical and Horizontal Seismometer Recordings

description: This dataset contains raw and stacked Borehole Portable Active Seismic Source (B-PASS) source functions, along with formatted and pre-processed vertical seismometer datasets (including metadata) from both vertical and horizontal B-PASS experiments.

The archive is organized into two main directories: Vertical/ and Horizontal/. Each includes three subfolders:





Stacked_Source_Functions/ – Stacked B-PASS source functions.




Raw_Source_Functions/ – Raw source function recordings.




Receiver_Data/ – Seismometer recordings:





Raw data: Not openly shared, the ownership by Tsuji Lab and JX Nippon Oil & Gas Exploration. Available upon request with approval (contact: tsuji@sys.t.u-tokyo.ac.jp). Requests must include a brief analysis plan; a non-disclosure agreement may be required.




Formatted and pre-processed data: Only partial datasets are openly included due to size limitations: 25 m depth for the horizontal experiment, and 0.5 m, 25 m, and 50 m depths for the vertical experiment. The full datasets are available upon request (contact: tsuji@sys.t.u-tokyo.ac.jp).





All processing scripts used in this study to generate Figures 5–16—including ObsPy/RF-Python pipelines for filtering, cross-correlation, weighted stacking, and deconvolution, as well as parameter and model files for the elastic-wave simulations—are openly available on GitHub (https://github.com/AhmadBahaa1995/B-PASS) and archived on Zenodo under [DOI: 10.5281/zenodo.17075959].
DOI: 10.5281/zenodo.17075241
title: Borehole Portable Active Seismic Source (B-PASS) Dataset: Raw and Stacked Source Functions with Vertical and Horizontal Seismometer Recordings

description: This dataset contains raw and stacked Borehole Portable Active Seismic Source (B-PASS) source functions, along with formatted and pre-processed vertical seismometer datasets (including metadata) from both vertical and horizontal B-PASS experiments.

The archive is organized into two main directories: Vertical/ and Horizontal/. Each includes three subfolders:





Stacked_Source_Functions/ – Stacked B-PASS source functions.




Raw_Source_Functions/ – Raw source function recordings.




Receiver_Data/ – Seismometer recordings:





Raw data: Not openly shared, the ownership by Tsuji Lab and JX Nippon Oil & Gas Exploration. Available upon request with approval (contact: tsuji@sys.t.u-tokyo.ac.jp). Requests must include a brief analysis plan; a non-disclosure agreement may be required.




Formatted and pre-processed data: Only partial datasets are openly included due to size limitations: 25 m depth for the horizontal experiment, and 0.5 m, 25 m, and 50 m depths for the vertical experiment. The full datasets are available upon request (contact: tsuji@sys.t.u-tokyo.ac.jp).





All processing scripts used in this study to generate Figures 5–16—including ObsPy/RF-Python pipelines for filtering, cross-correlation, weighted stacking, and deconvolution, as well as parameter and model files for the elastic-wave simulations—are openly available on GitHub (https://github.com/AhmadBahaa1995/B-PASS) and archived on Zenodo under [DOI: 10.5281/zenodo.17075959].
DOI: 10.57783/mhg6-wp57
title: LibreChat-DEV
DOI: 10.6084/m9.figshare.30082117
title: The role of shame and spontaneous self-affirmation among people with concealable stigmatized identities

description: Many Americans report having a concealable stigmatized identity (CSI) – when one belongs to a group that is devalued by society, but membership can be hidden – which is linked with poor health outcomes. One factor consistently linked with poor health among people with CSIs is anticipated stigma. The current study uses structural equation modeling to examine how responses to anticipated stigma (shame, spontaneous self-affirmation) explain the relationship between anticipated stigma and poor health. Using students from a large Midwestern University (<i>N</i> = 314), our model demonstrated that anticipated stigma was indirectly associated with poor health (i.e. psychological and physical quality of life, emotional eating) through shame. Spontaneous self-affirmation was associated with positive health outcomes but was not a significant mediator. This model illustrates the importance of shame and spontaneous self-affirmation as mechanisms of stigma to health relationship among individuals with CSIs, and provides potential targets (shame, spontaneous self-affirmation) for future work.
DOI: 10.6084/m9.figshare.30082117.v1
title: The role of shame and spontaneous self-affirmation among people with concealable stigmatized identities

description: Many Americans report having a concealable stigmatized identity (CSI) – when one belongs to a group that is devalued by society, but membership can be hidden – which is linked with poor health outcomes. One factor consistently linked with poor health among people with CSIs is anticipated stigma. The current study uses structural equation modeling to examine how responses to anticipated stigma (shame, spontaneous self-affirmation) explain the relationship between anticipated stigma and poor health. Using students from a large Midwestern University (<i>N</i> = 314), our model demonstrated that anticipated stigma was indirectly associated with poor health (i.e. psychological and physical quality of life, emotional eating) through shame. Spontaneous self-affirmation was associated with positive health outcomes but was not a significant mediator. This model illustrates the importance of shame and spontaneous self-affirmation as mechanisms of stigma to health relationship among individuals with CSIs, and provides potential targets (shame, spontaneous self-affirmation) for future work.
DOI: 10.15468/dl.ez36tv
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is Dominican Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 104 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044118-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r2pbg5
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is Cyprus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044115-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rdv6ms
title: Occurrence Download

description: A dataset containing 14627 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plantago asiatica"
 ]
}

 The dataset includes 14627 records from 248 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044116-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vf3wtn
title: Occurrence Download

description: A dataset containing 71230 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aythya nyroca (Güldenstädt, 1770)",
 "BasisOfRecord is one of (Human Observation, Observation)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "Country is one of (Finland, Ireland, Sweden, Cyprus, Portugal, Netherlands, France, Bulgaria, Romania, Spain, Poland, Czechia, Malta, United Kingdom of Great Britain and Northern Ireland, Austria, Croatia, Slovenia, Slovakia, Germany, Denmark, Italy, Belgium, Gibraltar, Lithuania, Greece, Luxembourg, Latvia, Estonia, Hungary)"
 ]
}

 The dataset includes 71230 records from 326 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034544-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kzn2xh
title: Occurrence Download

description: A dataset containing 3317 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trichopoda pennipes (Fabricius, 1781))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3317 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034564-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xc447z
title: Occurrence Download

description: A dataset containing 225 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Portulaca smallii P.Wilson, Portulaca socotrana Domina & Raimondo, Portulaca somalica N.E.Br.)"
 ]
}

 The dataset includes 225 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034567-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.anz4px
title: Occurrence Download

description: A dataset containing 1117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Erinaceus amurensis Schrenk, 1859)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1117 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034569-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sevxw5
title: Occurrence Download

description: A dataset containing 436 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sturmia bella (Meigen, 1824))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 436 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034570-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fn72hj
title: Occurrence Download

description: A dataset containing 95 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Potentilla johanniniana Goiran, Potentilla johnstonii Soják, Potentilla junatovii Rudaya & A.L.Ebel)"
 ]
}

 The dataset includes 95 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034571-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rtafc8
title: Occurrence Download

description: A dataset containing 444 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepus saxatilis F.Cuvier, 1823",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "Country is South Africa",
 "GadmGid is ETH"
 ]
 },
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 444 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034572-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.