cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/76gmpt3jfn.1
title: Menstrual variations of sleep-wake rhythms in healthy women

description: The ovarian steroid hormones estrogen and progesterone, which fluctuate dynamically with the estrous cycle, alter the circadian behavioral rhythms in mammals. However, it remains unclear whether the sleep-wake rhythm fluctuates with the menstrual cycle in humans. To determine the relationship between the menstrual cycle and sleep-wake rhythms, we evaluated the objective and long-term sleep-wake rhythms of ten healthy women using a recently developed wearable device. The results showed a strong negative correlation between the sleep midpoint and the Quasi Peak (QP) value (an indicator of rhythm robustness) and a positive correlation between the menstrual cycle (days) and social jet lag (hours). These results suggest that healthy women with late sleeping habits have a disturbed sleep-wake rhythm and that irregular habits prolong the menstrual cycle. The sleep midpoint and QP values showed variations during the menstrual cycle. The QP value in the follicular phase was significantly higher than those in the menstrual and luteal phases. In rodents, the phase of locomotor activity rhythm advances, and activity increases at night during proestrus. The increase in QP values during the follicular phase, when estrogen is relatively high, may be due to the increased activity caused by estrogen. These results suggest that ovarian steroid hormones influence sleep-wake rhythms in women. Although it is necessary to verify the results of this study under various conditions, it will be possible to accurately predict the day of ovulation using only the acquisition of sleep-wake rhythms with wearable devices.
DOI: 10.17632/pcggh2rzm3.1
title: In-Shoe Plantar Shear Stress Sensor Design, Calibration and Evaluation for the Diabetic Foot.

description: This is the data repository for the raw, anonymised dataset of the study regarding in-shoe plantar shear stress sensor design, calibration and evaluation for the diabetic foot. This work was partially funded by Engineering and Physical Sciences Research Council (EPSRC) grant number EP/W00366X/1. This study was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The study received approval from the NHS Health Research Authority and Health and Care Research Wales (HCRW) Ethics Committee (REC reference: 22/NW/0216), and all participants provided written consent. Trial Registration number: NCT05865353.
DOI: 10.17632/bn8pss2g3z.3
title: An energy consumption rectification method based on Bayesian linear regression and heating degree-days

description: Matlab program and data for the paper “An energy consumption rectification method based on Bayesian linear regression and heating degree-days". "simulation model.zip" is the heating house model in Trnsys simulation software. "Example1" and "Example2" is the Matlab program and data in this paper.
DOI: 10.5281/zenodo.14670150
title: Honest Health OOC Dataset

description: The rapid proliferation of health-related misinformation, particularly in multimodal formats combining text and images, poses significant risks to public health and trust in medical systems. Existing datasets and evaluation frameworks inadequately address the unique challenges of assessing honesty in multimodal large language models (MLLMs) within the health domain. In this paper, we introduce the Honest OOC Dataset, a specialized dataset designed to evaluate the honesty of MLLMs in out-of-context (OOC) scenarios. The dataset includes 8,016 real health-related image-caption pairs, with both similarity-based and LLM-generated falsified captions that closely mimic real-world misinformation patterns. To complement the dataset, we propose a comprehensive benchmark that assesses model honesty across three dimensions: (1) Truthful Representation, evaluating faithfulness to input information; (2) Honest Uncertainty, examining the model's ability to express knowledge limitations; and (3) Evidence Honesty, assessing the accuracy of judgments based on external evidence. We evaluate five different MLLMs using this benchmark, revealing the varying levels of honesty exhibited by the models from multiple perspectives. Our findings highlight the importance of accurately interpreting external evidence and adhering to reliable information, which are crucial for effective OOC detection in the health domain.
DOI: 10.5281/zenodo.14670151
title: Honest Health OOC Dataset

description: The rapid proliferation of health-related misinformation, particularly in multimodal formats combining text and images, poses significant risks to public health and trust in medical systems. Existing datasets and evaluation frameworks inadequately address the unique challenges of assessing honesty in multimodal large language models (MLLMs) within the health domain. In this paper, we introduce the Honest OOC Dataset, a specialized dataset designed to evaluate the honesty of MLLMs in out-of-context (OOC) scenarios. The dataset includes 8,016 real health-related image-caption pairs, with both similarity-based and LLM-generated falsified captions that closely mimic real-world misinformation patterns. To complement the dataset, we propose a comprehensive benchmark that assesses model honesty across three dimensions: (1) Truthful Representation, evaluating faithfulness to input information; (2) Honest Uncertainty, examining the model's ability to express knowledge limitations; and (3) Evidence Honesty, assessing the accuracy of judgments based on external evidence. We evaluate five different MLLMs using this benchmark, revealing the varying levels of honesty exhibited by the models from multiple perspectives. Our findings highlight the importance of accurately interpreting external evidence and adhering to reliable information, which are crucial for effective OOC detection in the health domain.
DOI: 10.5281/zenodo.14671795
title: Honest Health OOC Dataset

description: The rapid proliferation of health-related misinformation, particularly in multimodal formats combining text and images, poses significant risks to public health and trust in medical systems. Existing datasets and evaluation frameworks inadequately address the unique challenges of assessing honesty in multimodal large language models (MLLMs) within the health domain. In this paper, we introduce the Honest OOC Dataset, a specialized dataset designed to evaluate the honesty of MLLMs in out-of-context (OOC) scenarios. The dataset includes 8,016 real health-related image-caption pairs, with both similarity-based and LLM-generated falsified captions that closely mimic real-world misinformation patterns. To complement the dataset, we propose a comprehensive benchmark that assesses model honesty across three dimensions: (1) Truthful Representation, evaluating faithfulness to input information; (2) Honest Uncertainty, examining the model's ability to express knowledge limitations; and (3) Evidence Honesty, assessing the accuracy of judgments based on external evidence. We evaluate five different MLLMs using this benchmark, revealing the varying levels of honesty exhibited by the models from multiple perspectives. Our findings highlight the importance of accurately interpreting external evidence and adhering to reliable information, which are crucial for effective OOC detection in the health domain.
DOI: 10.17632/4fh6txnmct.1
title: LINF_360034600

description: Armadillo repeat-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/8vfvfmnn8n.1
title: LINF_350059400

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/wb5p7hk35z.1
title: LINF_350059300

description: Diacylglycerol kinase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/hvzxbjvtgk.2
title: Raw_Data_Crayfish_Anoxia

description: Raw data used in the paper ”Neculae et al (2024) Living on the edge: Crayfish as drivers to anoxification of their own shelter microenvironment. PLoS ONE”
DOI: 10.17632/hw2n22g9f5.2
title: Accumulation of metals (REEs) in Sediments of the St. Lawrence River (2018-2022)

description: Characteristics (Grain-size, MO, C, N), major cations and trace metals concentrations in bulk sediments (2018-2022) and suspended sediments (2012) collected in the St. Lawrence River.

Suspended sediments were collected by a sediment trap downstream Montreal effluent by Environment and Climate Change Canada. Other data were collected aboard the Lampsilis Research Vessel from UQTR (2018-2021) or by motorboat sampling (2022).
DOI: 10.17632/mpbj3tw2n5.2
title: Bioaccumulation of metals (REEs) in the St. Lawrence River (2017-2021)

description: The bioaccumulation of metals in benthic invertebrates, zooplankton and fish liver from the St. Lawrence River from 2017 to 2021.

Samples were collected aboard the Lampsilis Research Vessel from UQTR, except in 2022 where a motorboat was used to sample shallower environments and some amphipods were collected along the banks of the river with a kicknet.
Fish were collected with a bottom trawler.
Most invertebrate were collected through the sediment collector.
Invertebrates were depurated 24h.
DOI: 10.17632/55xfcgg2vj.1
title: LINF_210006500

description: cysteine peptidase - Clan CA - family C2; Leishmania infantum (strain JPCM5)
DOI: 10.17632/w9h7s4wxcn.1
title: LINF_210005700

description: Qb-SNARE protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/mdr6mgmvz3.1
title: RectalCancer_spatial

description: In this study, the scRNA-seq data were generated from two cases of colorectal cancer tissue samples collected at the Seventh Affiliated Hospital of Sun Yat-sen University (Shenzhen, China). The patients were diagnosed histologically. The RC1 sample had a tumor that invaded the muscular layer without any lymph node metastasis, and was classified as stage I (T2N0M0). The RC2 sample had a tumor that invaded the extramural parietal fat and fibrous tissues of the rectum with no distant lymph node metastasis, and was classified as stage III (T4N1cM0).
DOI: 10.15468/dl.ang7gg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "ScientificName" : [
 "is Barbastella barbastellus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004230-250117142028555/datasets/export for details.
DOI: 10.17632/w4dpnr2tp5.1
title: LINF_200021600

description: tRNA (Uracil-5-)-methyltransferase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/4d9k4f6ywc.1
title: LINF_200021500

description: protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/rr24t69rfr.1
title: LDHU3_16.0110

description: Hypothetical protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/yzjmc89pdf.1
title: LDHU3_16.0090

description: Kelch motif-containing protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/5gppfkcbbs.1
title: LDHU3_16.0070

description: AAA+ ATPase; Leishmania donovani (HU3 strain)
DOI: 10.17632/hrzsmhjfn9.1
title: LINF_210006600

description: DNA topoisomerase 1A; Leishmania infantum (strain JPCM5)
DOI: 10.17632/fs2j9gz8sv.1
title: CA-passive-active-QS: Code for paper “A Cellular Automata Model of a Laser reproducing laser passive and active Q-switching”

description: Code for paper “A Cellular Automata Model of a Laser reproducing laser passive
and active Q-switching”.
DOI: 10.17632/6bppb2ggth.1
title: LDHU3_16.0170

description: Eukaryotic translation initiation factor 1A | eIF1A; Leishmania donovani (HU3 strain)
DOI: 10.17632/gn8rb3z846.1
title: Supplemental Materials to the Manuscript "Three-Dimensional Numerical Modeling of Coseismic Atmospheric Dynamics and Ionospheric Responses in Slant Total Electron Content Observations"

description: This collection hosts the datasets associated with the journal article, Three-Dimensional Numerical Modeling of Coseismic Atmospheric Dynamics and Ionospheric Responses in Slant Total Electron Content Observations.

Authors:
P.A. Inchin
Center for Space and Atmospheric Research, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA
Computational Physics, Inc., Springfield, Virginia, USA
Y. Kaneko
Department of Geophysics, Kyoto University, Kyoto, Japan
 A.-A. Gabriel
Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
Department of Earth and Environmental Sciences, Ludwig-Maximilians-University, Munich, Germany
T. Ulrich
Department of Earth and Environmental Sciences, Ludwig-Maximilians-University, Munich, Germany
L. Martire
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
 A. Komjathy
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
J. Aguilar Guerrero
Center for Space and Atmospheric Research, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA
M.D. Zettergren
Center for Space and Atmospheric Research, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA
J.B. Snively
Center for Space and Atmospheric Research, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA

Correspondence: P.A. Inchin, pinchin@cpi.com

The collection includes next datasets:
Dataset 1
Title: Sim #1. Electron density 3D fields
Description: 3D outputs of electron densities of GEMINI simulation #1 in HDF5 format, geographic coordinates and scripts for reading and plotting of the data.

Dataset 2
Title: Sim #1. Vertical fluid velocity 3D fields
Description: 3D outputs of vertical fluid velocities of MAGIC simulation #1 in mat format, geographic coordinates and scripts for reading and plotting of the data.

Dataset 3
Title: Sim #3. Vertical fluid velocity 3D fields
Description: 3D outputs of vertical fluid velocities of MAGIC simulation #3 in mat format, geographic coordinates and scripts for reading and plotting of the data.

Dataset 4
Title: DynamicVSKinematic model sTEC comparison
Description: The figures illustrating the comparison of sTEC signals from Simulation #1 and Simulation #3 and observations.
DOI: 10.17632/5f6mwy9ntc
title: Response of vegetation covers to PolSAR decomposition variables in L - band

description: The dataset includes the response of vegetation covers to polarimetric decomposition variables (Van Zyl, Yamaguchi, Cameron, Cloud-Pottier, GRVI, Cloude, generalized Freeman Durden). They are separated into summer and winter seasons 2021.
DOI: 10.17632/5f6mwy9ntc.1
title: Response of vegetation covers to PolSAR decomposition variables in L - band

description: The dataset includes the response of vegetation covers to polarimetric decomposition variables (Van Zyl, Yamaguchi, Cameron, Cloud-Pottier, GRVI, Cloude, generalized Freeman Durden). They are separated into summer and winter seasons 2021.
DOI: 10.17632/xbdjm87c2s.2
title: Salidroside directly activates HSC70, revealing a new role for HSC70 in BDNF signalling and neurogenesis after cerebral ischemia

description: Salidroside is a key bioactive component of Rhodiola species that are widely used as traditional medicines. Among them, Rhodiola crenulata is cited as a traditional Chinese medicine to treat stroke in the Chinese Pharmacopoeia. This therapeutic action of Rhodiola crenulata may involve neurogenesis, as it is known that Rhodiola crenulate enhances hippocampal neurogenesis against streptozotocin-induced neural injury in rats, probably through protecting neural stem cells by salidroside. Salidroside has attracted considerable attentions as a potential agent for the clinic, as it exhibits neuroprotective properties across a remarkably wide time window in a variety of experimental stroke models. However, whether salidroside induces neurogenesis after cerebral ischemia and its primary molecular targets remain unknown.To explore whether salidroside induces neurogenesis after cerebral ischemia, and whether the neurogenic and neuroprotective effects of salidroside are through interaction with heat shock cognate 71-kDa protein (HSC70) as its primary molecular target.
DOI: 10.17632/3ncbhdd4nw.3
title: Mobility, Kinematic, and Dynamic Analysis of a 4R1H Mechanism. Julia Files

description: This dataset contains Julia files that perform mobility, kinematic, and dynamic analysis of a 1-DOF single-loop 4R1H mechanism, which is similar to the mechanism presented in paper https://doi.org/10.1007/978-3-031-45709-8_39. The corresponding paper describing the mechanism design and applied algorithms is going to be published in the Robotica journal. Please check the list of works at https://orcid.org/0000-0002-3928-5440.

The dataset includes the following files:
1. File "main.jl" is the main file that proceeds with the mobility, kinematic, and dynamic analysis of the mechanism step by step.
2. File "init.jl" is used to define geometrical and inertial parameters of the mechanism links.
3. File "mobility.jl" computes a twist system of the output link.
4. File "kinematics.jl" computes kinematic parameters (positions, velocities, accelerations, etc.) of the links.
5. File "dynamics.jl" computes the motor torque required to realize the desired motion.
6. File "plots.jl" includes functions that visualize the results of the kinematic and dynamic analysis.

The third version of the dataset has the following changes compared to the second version:
1. Files "torque_friction.xlsx" and "torque_no_friction.xlsx" have been replaced with "torque_friction_5.xlsx," "torque_friction_10.xlsx," "torque_friction_20.xlsx," "torque_no_friction_5.xlsx," "torque_no_friction_10.xlsx," and "torque_no_friction_20.xlsx," which contain the torque data obtained with CAD simulations in the Autodesk Inventor software for the crank angular speed equal to 5, 10, and 20 rpm.
2. There is a new section in "main.jl" file titled "Visualization for three various constant speeds of 5, 10, and 20 rpm" where the CAD data is compared with the analytical solution for various crank speeds.
3. The "plots.jl" file includes new functions "plot_kinematics_3" and "plot_torques_3," which plot the results of kinematic and dynamic analysis for three different speeds of the crank.
4. Optional files "Project.toml" and "Manifest.toml," which contain the information about the used packages, have been included in this dataset.
DOI: 10.17632/22xwh6ptk2.1
title: Data for:Improving gridded population map for mainland China using 3D building, nighttime light, points-of-interest, and land use/cover data in a multiscale geographically weighted regression model

description: Auxiliary Data.gdb:
Land_use: original land use data
POI_name: interests-point-data from the Amap platform (name indicates category)

New_gridded_population_dataset(.gdb): experimental result data, i.e., a gridded population map of mainland China with a resolution of 100 meters

New_minus_WorldPop_PopulationResidual(.gdb): pixel-level residuals of the new gridded population dataset with the Worldpop dataset

PopulationData_AdministrativeUnitLevel.gdb:
Population_data_mainlandChina_level3: population data at the district and county level in mainland China
Population_data_Name_level4_Table: township and street-level population data for provinces and municipalities

POI_Correlation_Coefficient:
Python script: programming implementation for selecting the optimal bandwidth for POI
Zonal statistical output of POI kernel density values: summary of various POI kernel densities in residential areas of administrative units
Summary of POI Pearson correlation coefficients: sum of Pearson's correlation coefficients for 13 types of POIs at a certain bandwidth

Note: 
Due to the storage space limitation, 3D building, nighttime light, and WorldPop datasets have not been uploaded. To access these publicly available data, please visit the official website via the "Related links" at the bottom. In addition, we are not authorized to share data for the fourth level of administrative boundaries, so we only share the corresponding population data in tabular form.
DOI: 10.15468/dl.ngapca
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "ScientificName" : [
 "is Barbastella barbastellus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004232-250117142028555/datasets/export for details.
DOI: 10.17632/bb7tvwfss6.1
title: How social movements use religious creativity to address environmental crises in Indonesian local communities (1990-2022)

description: This dataset contains raw data and methodological explanations for a modified framework synthesis of 244 empirical studies (in English and Indonesian) on 208 environmental social movements operating in local communities in Indonesia from 1990 through 2022. 

The study resulted in a conceptual model showing how grassroots movements used lived religion to create new environmental practices and motivate environmental behavioural changes in diverse local communities. The study inventoried 571 examples of lived religious concepts, practices, rituals and systems that movements used to create environmental concepts and practices. 

This dataset includes four files:
 
Appendix A: Methods and data classification
This document provides further details about the methods and data classification used to conduct a modified synthesis framework.

Appendix B. Methods data
This Excel spreadsheet contains raw data for conducting the study with search logs, screening, and the classification of sources. Included sheets are:
• Search Logs: log of searches, count of summary data and chart
• Screening – Bibliographic Records: worksheet to screen 648 bibliographic sources
• Screening – Full-text sources: worksheet to screen 469 full-text sources
• Classification – Sources: classification sheet for 244 sources used in the study with descriptive characteristics
• Type of Sources: summary data and charts
• Language of Sources: summary data and charts

Appendix C. Results data 
This excel spreadsheet contains raw data on descriptive characteristics of the movements and the inventory of items used by movements. Included sheets are: 
• Inventory Content: Inventory of items used by movements to create new environmental concepts and practices.
• Classification – Movements: classification sheet for 208 movements by descriptive characteristics
• Date: summary data and charts
• Region: summary data and charts
• Province: summary data and charts
• District: summary data and charts
• Aims: summary data and charts
• Environmental Issues: summary data and charts
• Lived Religion: summary data and charts
• Religion and Other: summary data and charts

Appendix D. Movements and sources list 
This PDF file includes full bibliographic details of all 244 sources used in the study with a chart displaying which sources were used for each movement. 

Results of data analysis can be explored using interactive ArcGIS maps. 

Map of Environmental Social Movements in Indonesia 1990-2022 (ArcGIS): 
https://bit.ly/CRCS-map-movements

Map of Eco-religious Creativity (ArcGIS):
https://bit.ly/CRCS-map-content