cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15536438
title: Dataset for "keeping track of evaporating solutions to maintain traceability"

description: Dateset related to the manuscript "Keeping track of evaporating solutions to maintain traceability" which describes the effect of evaporation on solutions, providing data through (i) a simulation, (ii) the report of an experimental observation and (iii) a measurement test performed with INAA.

This dataset is thus composed:



experimental_data.xlsx: Excel file containing reports of the mass (and mass fraction) values of a real solution monitored throughout almost 70 weeks

measurement_uncertaintybudget.xlsx: Excel file containing uncertainty budgets of the INAA measurements performed on solution samples at different evaporation times

OR50_A05_d200_15052025B.Spc: gamma spectrum of measured sample A05

OR50_AS_d200_07052025.Spc: gamma spectrum of measured sample AS

OR50_B1_d200_08052025.Spc: gamma spectrum of measured sample B1

OR50_BS_d200_08052025.Spc: gamma spectrum of measured sample BS

OR50_C2_d200_14052025.Spc: gamma spectrum of measured sample C2

OR50_CS_d200_09052025.Spc: gamma spectrum of measured sample CS

simulation_script.py: python script containing the code to run the simulation aiming to evaluate value and uncertainty of the mass fraction of an element in solution after n storage steps
DOI: 10.5281/zenodo.15536439
title: Dataset for "keeping track of evaporating solutions to maintain traceability"

description: Dateset related to the manuscript "Keeping track of evaporating solutions to maintain traceability" which describes the effect of evaporation on solutions, providing data through (i) a simulation, (ii) the report of an experimental observation and (iii) a measurement test performed with INAA.

This dataset is thus composed:



experimental_data.xlsx: Excel file containing reports of the mass (and mass fraction) values of a real solution monitored throughout almost 70 weeks

measurement_uncertaintybudget.xlsx: Excel file containing uncertainty budgets of the INAA measurements performed on solution samples at different evaporation times

OR50_A05_d200_15052025B.Spc: gamma spectrum of measured sample A05

OR50_AS_d200_07052025.Spc: gamma spectrum of measured sample AS

OR50_B1_d200_08052025.Spc: gamma spectrum of measured sample B1

OR50_BS_d200_08052025.Spc: gamma spectrum of measured sample BS

OR50_C2_d200_14052025.Spc: gamma spectrum of measured sample C2

OR50_CS_d200_09052025.Spc: gamma spectrum of measured sample CS

simulation_script.py: python script containing the code to run the simulation aiming to evaluate value and uncertainty of the mass fraction of an element in solution after n storage steps
DOI: 10.15468/dl.s8pas6
title: Occurrence Download

description: A dataset containing 15218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Isoetes echinospora"
 ]
}

 The dataset includes 15218 records from 304 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0083335-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ubzyqx
title: Occurrence Download

description: A dataset containing 3334 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leonotis nepetifolia",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3334 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0083337-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.6385197
title: Accompanying simulated data for "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity"

description: The multilevel hidden Markov model (MHMM) is a promising vehicle to investigate latent dynamics over time in social and behavioral processes. By including continuous individual random effects, the model accommodates variability between individuals, providing individual-specific trajectories and facilitating the study of individual differences. However, the performance of the MHMM has not been sufficiently explored. Currently, there are no practical guidelines on the sample size needed to obtain reliable estimates related to categorical data characteristics We performed an extensive simulation to assess the effect of the number of dependent variables (1-4), the number of individuals (5-90), and the number of observations per individual (100-1600) on the estimation performance of group-level parameters and between-individual variability on a Bayesian MHMM with categorical data of various levels of complexity. We found that using multivariate data generally alleviates the sample size needed and improves the stability of the results. Regarding the estimation of group-level parameters, the number of individuals and observations largely compensate for each other. Meanwhile, only the former drives the estimation of between-individual variability. We conclude with guidelines on the sample size necessary based on the complexity of the data and the study objectives of the practitioners. This repository contains data generated for the manuscript: "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity". It comprehends: (1) model outputs (maximum a posteriori estimates) for each repetition (n=100) of each scenario (n=324) of the main simulation, (2) complete model outputs (including estimates for 4000 MCMC iterations) for two chains of each repetition (n=3) of each scenario (n=324). Please note that the empirical data used in the manuscript is not available as part of this repository. A subsample of the data used in the empirical example are openly available as an example data set in the R package mHMMbayes on CRAN. The full data set is available on request from the authors.
DOI: 10.5281/zenodo.15433591
title: Accompanying simulated data for "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity"

description: The multilevel hidden Markov model (MHMM) is a promising vehicle to investigate latent dynamics over time in social and behavioral processes. By including continuous individual random effects, the model accommodates variability between individuals, providing individual-specific trajectories and facilitating the study of individual differences. However, the performance of the MHMM has not been sufficiently explored. Currently, there are no practical guidelines on the sample size needed to obtain reliable estimates related to categorical data characteristics We performed an extensive simulation to assess the effect of the number of dependent variables (1-4), the number of individuals (5-90), and the number of observations per individual (100-1600) on the estimation performance of group-level parameters and between-individual variability on a Bayesian MHMM with categorical data of various levels of complexity. We found that using multivariate data generally alleviates the sample size needed and improves the stability of the results. Regarding the estimation of group-level parameters, the number of individuals and observations largely compensate for each other. Meanwhile, only the former drives the estimation of between-individual variability. We conclude with guidelines on the sample size necessary based on the complexity of the data and the study objectives of the practitioners.


This repository contains data generated for the manuscript: "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity". It comprehends: (1) model outputs (maximum a posteriori estimates) for each repetition (n=100) of each scenario (n=324) of the main simulation, (2) complete model outputs (including estimates for 4000 MCMC iterations) for two chains of each repetition (n=3) of each scenario (n=324). Please note that the empirical data used in the manuscript is not available as part of this repository. A subsample of the data used in the empirical example are openly available as an example data set in the R package mHMMbayes on CRAN. The full data set is available on request from the authors.
DOI: 10.5281/zenodo.6385196
title: Accompanying simulated data for "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity"

description: The multilevel hidden Markov model (MHMM) is a promising vehicle to investigate latent dynamics over time in social and behavioral processes. By including continuous individual random effects, the model accommodates variability between individuals, providing individual-specific trajectories and facilitating the study of individual differences. However, the performance of the MHMM has not been sufficiently explored. Currently, there are no practical guidelines on the sample size needed to obtain reliable estimates related to categorical data characteristics We performed an extensive simulation to assess the effect of the number of dependent variables (1-4), the number of individuals (5-90), and the number of observations per individual (100-1600) on the estimation performance of group-level parameters and between-individual variability on a Bayesian MHMM with categorical data of various levels of complexity. We found that using multivariate data generally alleviates the sample size needed and improves the stability of the results. Regarding the estimation of group-level parameters, the number of individuals and observations largely compensate for each other. Meanwhile, only the former drives the estimation of between-individual variability. We conclude with guidelines on the sample size necessary based on the complexity of the data and the study objectives of the practitioners.


This repository contains data generated for the manuscript: "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity". It comprehends: (1) model outputs (maximum a posteriori estimates) for each repetition (n=100) of each scenario (n=324) of the main simulation, (2) complete model outputs (including estimates for 4000 MCMC iterations) for two chains of each repetition (n=3) of each scenario (n=324). Please note that the empirical data used in the manuscript is not available as part of this repository. A subsample of the data used in the empirical example are openly available as an example data set in the R package mHMMbayes on CRAN. The full data set is available on request from the authors.
DOI: 10.15468/dl.b3425t
title: Occurrence Download

description: A dataset containing 4787 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Linaria triornithophora (L.) Willd."
 ]
}

 The dataset includes 4787 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010116-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cn8zzs
title: Occurrence Download

description: A dataset containing 1113 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Penelope albipennis Taczanowski, 1878"
 ]
}

 The dataset includes 1113 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053603-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vuckk4
title: Occurrence Download

description: A dataset containing 138 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is 3773272"
 ]
}

 The dataset includes 138 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0264017-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ef5rw8
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Cebus aequatorialis J.A.Allen, 1914"
 ]
}

 The dataset includes 129 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053602-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uw5z7k
title: Occurrence Download

description: A dataset containing 1210 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Jena Microbial Resource Collection (JMRC) at Leibniz Institute for Natural Product Research and Infection Biology e.V. Hans-Knöll-Institute (HKI) and Friedrich Schiller University Jena",
 "TaxonKey is Fusarium Link, 1809"
 ]
}

 The dataset includes 1210 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010132-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2fx8ws
title: Occurrence Download

description: A dataset containing 1504 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Knipolegus hudsoni P.L.Sclater, 1872"
 ]
}

 The dataset includes 1504 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053605-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aguio0
title: Occurrence Download

description: A dataset containing 1448684605 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1448684605 records from 17347 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000850-170822121629195/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.26788734
title: Content and effects of balance training in people with diabetic peripheral neuropathy – a systematic review and meta-analysis

description: Diabetic Peripheral Neuropathy (DPN) impairs balance due to sensory loss, proprioceptive deficits, muscle weakness, altered gait, and delayed reflexes. Targeted aerobic and balance training seem promising to mitigate these issues. However, the exact content of a recommended training regime is yet to be determined. To delineate and synthesise balance training content and efficacy for people with DPN. The literature search was conducted on PubMed and Embase in accordance with the PRISMA-checklist. Last search was performed on April 29, 2024. Inclusion criteria were established using the PICO-framework. Methodological quality was assessed using the TESTEX Scale. Meta-analyses were exclusively applied to studies featuring a passive control group. A total of 2007 articles were identified. Twelve studies were included in the qualitative synthesis. Seven studies were included in the meta-analyses. Two studies were of high quality. Most studies reported the frequency, session time, duration, and setting of balance training, while none reported the intensity. The meta-analyses showed a standardized mean difference in favor of balance training compared to passive control for One-Legged Stance (openeyes) (0.89[0.5,1.28]), One-Legged Stance (closed eyes) (1.48[0.36, 2.60]), Postural sway (−0.71[−1.04, −0,37]), Timed Up and Go(−0.94[−1.78, −0.10]), and Berg Balance Scale (2.26[0.48, 4.05]), respectively. Studies are few and generally of low methodological quality. The content of balance training interventions is minimally described, especially concerning the applied intensity. However, balance training does seem to improve balance outcomes in people with DPN, but given the methodological limitations, interpretation must be cautious.
DOI: 10.6084/m9.figshare.26788734.v1
title: Content and effects of balance training in people with diabetic peripheral neuropathy – a systematic review and meta-analysis

description: Diabetic Peripheral Neuropathy (DPN) impairs balance due to sensory loss, proprioceptive deficits, muscle weakness, altered gait, and delayed reflexes. Targeted aerobic and balance training seem promising to mitigate these issues. However, the exact content of a recommended training regime is yet to be determined. To delineate and synthesise balance training content and efficacy for people with DPN. The literature search was conducted on PubMed and Embase in accordance with the PRISMA-checklist. Last search was performed on April 29, 2024. Inclusion criteria were established using the PICO-framework. Methodological quality was assessed using the TESTEX Scale. Meta-analyses were exclusively applied to studies featuring a passive control group. A total of 2007 articles were identified. Twelve studies were included in the qualitative synthesis. Seven studies were included in the meta-analyses. Two studies were of high quality. Most studies reported the frequency, session time, duration, and setting of balance training, while none reported the intensity. The meta-analyses showed a standardized mean difference in favor of balance training compared to passive control for One-Legged Stance (openeyes) (0.89[0.5,1.28]), One-Legged Stance (closed eyes) (1.48[0.36, 2.60]), Postural sway (−0.71[−1.04, −0,37]), Timed Up and Go(−0.94[−1.78, −0.10]), and Berg Balance Scale (2.26[0.48, 4.05]), respectively. Studies are few and generally of low methodological quality. The content of balance training interventions is minimally described, especially concerning the applied intensity. However, balance training does seem to improve balance outcomes in people with DPN, but given the methodological limitations, interpretation must be cautious.
DOI: 10.6084/m9.figshare.26345607
title: “A feeling of being part of the future”: a qualitative study on physical therapists’ experiences of delivering digital first-line treatment for hip and knee osteoarthritis

description: Digital options for osteoarthritis (OA) treatment are increasingly available with high patient satisfaction and acceptability. Little is, however, known about physical therapists’ (PT) perception of this treatment modality. To investigate PT’s experience of delivering digital treatment for hip and knee OA using a smart-phone application. Nine PTs (mean age 36 years, women <i>n</i> = 5) with 3–24 months experience of delivering digital OA treatment were interviewed using a semi-structured interview guide. The interviews were transcribed verbatim and analyzed using content analysis. Four main categories arose; 1) A feeling of being part of the future, 2) Making an osteoarthritis diagnosis in a digital setting, 3) Facilitators and barriers of digital OA management and 4) Where to go from here? PTs were in general positive for digital treatment delivery but felt that a lack of visual assessments and physical examinations to enhance exercise evaluations and diagnosis accuracy was sometimes a disadvantage. Digital treatment delivery was in general perceived as a time-efficient way of providing high-quality care that may increase patient motivation and adherence without violating the therapeutic alliance. Future implementations of digital OA treatment programs should consider the possibility of including real-time video calls for visual assessment.
DOI: 10.6084/m9.figshare.26391118
title: Developing work readiness in university graduates: a case study in mapping a university curriculum to work readiness domains in an Australian physiotherapy degree

description: Recent research has identified six domains of work readiness: <i>Practical Wisdom</i>, <i>Interpersonal Capabilities</i>, <i>Personal Attributes</i>, <i>Organisational Acumen</i>, <i>Profession Specific Knowledge and Skills</i>, and <i>Professionally Relevant Experiences</i>. Using a case study, the aim of this study was to demonstrate the process of curriculum mapping to evaluate the alignment of a university program to the work readiness framework. A retrospective audit of curriculum material for one cohort of Macquarie University’s Doctor of Physiotherapy (DPT) was undertaken. Curriculum was categorized as declared, delivered, or assessed, mapped to the six work readiness domains through qualitative content analysis, and then quantitatively scored and expressed as percentages of maximum possible scores per unit, and average units scores per semester. Mapping curriculum to a six domain work readiness framework revealed declared, delivered, and assessed curriculum within all six work readiness domains, with varying contributions across the degree. Mapping revealed that the <i>Profession Specific Knowledge and Skills</i> domain had the highest coverage of declared (<i>M</i> = 63%, <i>SD</i> = 12), delivered (<i>M</i> = 88%, <i>SD</i> = 11) and assessed (<i>M</i> = 80%, <i>SD</i> = 7) curriculum, highlighting a strength of the program. The <i>Personal Attributes</i> domain had the lowest coverage of declared (<i>M</i> = 5%, <i>SD =</i> 5), delivered (<i>M</i> = 48%, <i>SD</i> = 24) and assessed (<i>M</i> = 29%, <i>SD</i> = 20) curriculum, highlighting opportunities for development. Mapping curriculum to a work readiness framework allows universities to consider alignment, and the strength and opportunities for the improvement of work readiness within its curriculum.
DOI: 10.6084/m9.figshare.26391118.v1
title: Developing work readiness in university graduates: a case study in mapping a university curriculum to work readiness domains in an Australian physiotherapy degree

description: Recent research has identified six domains of work readiness: <i>Practical Wisdom</i>, <i>Interpersonal Capabilities</i>, <i>Personal Attributes</i>, <i>Organisational Acumen</i>, <i>Profession Specific Knowledge and Skills</i>, and <i>Professionally Relevant Experiences</i>. Using a case study, the aim of this study was to demonstrate the process of curriculum mapping to evaluate the alignment of a university program to the work readiness framework. A retrospective audit of curriculum material for one cohort of Macquarie University’s Doctor of Physiotherapy (DPT) was undertaken. Curriculum was categorized as declared, delivered, or assessed, mapped to the six work readiness domains through qualitative content analysis, and then quantitatively scored and expressed as percentages of maximum possible scores per unit, and average units scores per semester. Mapping curriculum to a six domain work readiness framework revealed declared, delivered, and assessed curriculum within all six work readiness domains, with varying contributions across the degree. Mapping revealed that the <i>Profession Specific Knowledge and Skills</i> domain had the highest coverage of declared (<i>M</i> = 63%, <i>SD</i> = 12), delivered (<i>M</i> = 88%, <i>SD</i> = 11) and assessed (<i>M</i> = 80%, <i>SD</i> = 7) curriculum, highlighting a strength of the program. The <i>Personal Attributes</i> domain had the lowest coverage of declared (<i>M</i> = 5%, <i>SD =</i> 5), delivered (<i>M</i> = 48%, <i>SD</i> = 24) and assessed (<i>M</i> = 29%, <i>SD</i> = 20) curriculum, highlighting opportunities for development. Mapping curriculum to a work readiness framework allows universities to consider alignment, and the strength and opportunities for the improvement of work readiness within its curriculum.