cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vvtxuz
title: Occurrence Download

description: A dataset containing 1739 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 {
 "or" : [
 "Continent is North America",
 "Continent is South America"
 ]
 },
 "TaxonKey is Baiomys True, 1894",
 "Year 1980-2021"
 ]
}

 The dataset includes 1739 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0281128-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.37rwh7
title: Occurrence Download

description: A dataset containing 1510 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Royal Museum of Central Africa - Metafro-Infosys - Prelude"
 ]
}

 The dataset includes 1510 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007626-150615163101818/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ekme2f
title: Occurrence Download

description: A dataset containing 562803 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is one of (Acer platanoides L., Adelges tsugae Annand, 1924, Agrilus planipennis Fairmaire, 1888, Alliaria petiolata (M.Bieb.) Cavara & Grande, Channa argus (Cantor, 1842), Crocodylus niloticus Laurenti, 1768, Dreissena polymorpha (Pallas, 1771), Faxonius rusticus (Girard, 1852), Frangula alnus Mill., Heracleum mantegazzianum Sommier & Levier, Heracleum sphondylium L., Hydrocharis morsus-ranae L., Impatiens glandulifera Royle, Kali tragus (L.) Scop., Lissachatina fulica (Bowdich, 1822), Lycorma delicatula (White, 1845), Myriophyllum spicatum L., Phragmites australis subsp. australis, Potamogeton crispus L., Pterois volitans (Linnaeus, 1758), Pueraria lobata (Willd.) Ohwi, Python bivittatus Kuhl, 1820, Reynoutria japonica Houtt., Reynoutria sachalinensis (F.Schmidt) Nakai, Reynoutria ×bohemica Chrtek & Chrtková, Rhamnus cathartica L., Rhinella marina (Linnaeus, 1758), Stratiotes aloides L., Trapa natans L., Vincetoxicum nigrum (L.) Moench, Vincetoxicum rossicum (Kleopow) Barbar.)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 562803 records from 559 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001492-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jhkauc
title: Occurrence Download

description: A dataset containing 529 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Korea, Republic of",
 "TaxonKey is Abies koreana E.H.Wilson"
 ]
}

 The dataset includes 529 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081724-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wdmo7i
title: Occurrence Download

description: A dataset containing 7558499 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7558499 records from 1254 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007626-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/p8hw5rt8k4.1
title: Salidroside project

description: The project tested primarily the influence of salidroside on cytochrome P450 metabolic activities and a possible mechanism of induced changes. The rats were treated with salidroside at the doses from 5 to 45 mg/kg/day for 7 consecutive days. The liver microsomes were isolated and tested for P450 metabolic activities with specific substrates. In vitro inhibition studies with human liver microsomes and naive rat liver microsomes were also performed.
DOI: 10.17632/vjpmw8gwbg
title: my dta for bibliometric study

description: this data set is used in my Bibliometric study
DOI: 10.17632/vjpmw8gwbg.1
title: my dta for bibliometric study

description: this data set is used in my Bibliometric study
DOI: 10.17632/tkdzp2xm5t
title: DEM_DOI:10.20944/preprints202508.0467.v1

description: DEM data DOI:10.20944/preprints202508.0467.v1
DOI: 10.17632/tkdzp2xm5t.1
title: DEM_DOI:10.20944/preprints202508.0467.v1

description: DEM data DOI:10.20944/preprints202508.0467.v1
DOI: 10.17632/ptschm67th
title: Pancreatic Islet Oscillation Rhythmicity Arises from δ and α Cell Interactions

description: This is source data for figures in &lt;&gt; study. 
1. We developed a microfluidic chip enabling high-throughput observation of islets Ca2+ activities and their 3D composition. Our findings demonstrated that δ-α cell-to-cell interactions are the primary source of variability in glucose-induced Ca2+ oscillation patterns.
2. Through experimental investigations, we identified a phase diagram in the oscillation modes, covering the transition from fast-to-mixed and mixed-to-slow oscillations, with increasing somatostatin or decreasing α cell mass.
3. We proposed a mathematical model focusing on the paracrine interactions between α and δ cells. Our model depicts that fast-mixed-slow oscillation transitions as a Hopf bifurcation.
4. Finally, we found that in vivo hypoglycemia/euglycemia induces fast Ca2+ oscillations, while hyperglycemia induces slow Ca2+ oscillations.
DOI: 10.17632/ptschm67th.1
title: Pancreatic Islet Oscillation Rhythmicity Arises from δ and α Cell Interactions

description: This is source data for figures in &lt;&gt; study. 
1. We developed a microfluidic chip enabling high-throughput observation of islets Ca2+ activities and their 3D composition. Our findings demonstrated that δ-α cell-to-cell interactions are the primary source of variability in glucose-induced Ca2+ oscillation patterns.
2. Through experimental investigations, we identified a phase diagram in the oscillation modes, covering the transition from fast-to-mixed and mixed-to-slow oscillations, with increasing somatostatin or decreasing α cell mass.
3. We proposed a mathematical model focusing on the paracrine interactions between α and δ cells. Our model depicts that fast-mixed-slow oscillation transitions as a Hopf bifurcation.
4. Finally, we found that in vivo hypoglycemia/euglycemia induces fast Ca2+ oscillations, while hyperglycemia induces slow Ca2+ oscillations.
DOI: 10.17632/5y5cwdp2h8
title: wildfire_borders_DOI:10.20944/preprints202508.0467.v1

description: limits of area burnt in big wildfires in Castellon province 1990-2024. Used in DOI:10.20944/preprints202508.0467.v1
DOI: 10.17632/5y5cwdp2h8.1
title: wildfire_borders_DOI:10.20944/preprints202508.0467.v1

description: limits of area burnt in big wildfires in Castellon province 1990-2024. Used in DOI:10.20944/preprints202508.0467.v1
DOI: 10.17632/tcs89ytmp7
title: sınav stresi altındaki tıp fakültesi öğrencilerinin yürüme analizleri ve renkli gözlük takmanın yürümelerine etkisi

description: stresten etkilenmiş yürüyüşe sahip deneklerin renkli gözlük takarak yürümesi, yürüyüşlerini olumlu etkileyebilir. renkli gözlüklerin seçilme sırası gönüllülerin tercihlerine bırakıldı.
DOI: 10.17632/tcs89ytmp7.1
title: sınav stresi altındaki tıp fakültesi öğrencilerinin yürüme analizleri ve renkli gözlük takmanın yürümelerine etkisi

description: stresten etkilenmiş yürüyüşe sahip deneklerin renkli gözlük takarak yürümesi, yürüyüşlerini olumlu etkileyebilir. renkli gözlüklerin seçilme sırası gönüllülerin tercihlerine bırakıldı.
DOI: 10.17632/mh6wb9k9f3
title: Single-cell dataset of renal cell carcinoma

description: We collected the single-cell transcriptome data of patients receiving ICB treatments, including ICB treatment-naïve tumor samples, ICB-resistant samples (post treatments) and ICB-sensitive samples for the investigation of ICB-resistant mechanisms. Besides, we also included adjacent normal tissues and PBMC samples for comparison. Taken together, we obtained a total of 6 adjacent normal, 9 ICB treatment-naïve tumor, 5 ICB-sensitive tumor, 4 ICB-resistant tumor and 2 PBMC samples.
We used the Cell Ranger software (Version 7.0.0) with default settings to align and quantify single-cell transcriptome data in FASTQ format published by 10x Genomics against the GRCh38 human reference genome[67]. The Cell Ranger software's quantified count matrix was loaded into the Seurat tool (Version 4.1.1) for further analyses.The cells were then subjected to quality control. Basically, cells with fewer than 500 identified genes and those with greater than 10% mitochondrial content were eliminated. To further exclude probable doublets, cells containing more than 8000 identified genes were discarded. Possible doublets predicted by the DoubletFinder software were eliminated so as not to impede the analyses. After filtering, samples containing fewer than 500 cells were deemed of poor quality and eliminated. More than 1000 thousand cells of good quality were preserved for further analysis. All individual high-quality single-cell samples were then curated into a single object and to eliminate batch effects. The dimensionality of this dataset was reduced through principal component analysis (PCA) with highly variable features, and the first 15 PCs were selected for investigation. Then, unsupervised clustering was approximated using the shared nearest-neighbor network produced by the Louvain algorithm and the edge weights between any two cells. Using the t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) methods, the identified clusters were displayed. We identified the differentially expressed markers of the resultant clusters and used the default nonparametric test, the Wilcoxon rank sum test with Bonferroni correction, to label the cell clusters.
DOI: 10.17632/mh6wb9k9f3.1
title: Single-cell dataset of renal cell carcinoma

description: We collected the single-cell transcriptome data of patients receiving ICB treatments, including ICB treatment-naïve tumor samples, ICB-resistant samples (post treatments) and ICB-sensitive samples for the investigation of ICB-resistant mechanisms. Besides, we also included adjacent normal tissues and PBMC samples for comparison. Taken together, we obtained a total of 6 adjacent normal, 9 ICB treatment-naïve tumor, 5 ICB-sensitive tumor, 4 ICB-resistant tumor and 2 PBMC samples.
We used the Cell Ranger software (Version 7.0.0) with default settings to align and quantify single-cell transcriptome data in FASTQ format published by 10x Genomics against the GRCh38 human reference genome[67]. The Cell Ranger software's quantified count matrix was loaded into the Seurat tool (Version 4.1.1) for further analyses.The cells were then subjected to quality control. Basically, cells with fewer than 500 identified genes and those with greater than 10% mitochondrial content were eliminated. To further exclude probable doublets, cells containing more than 8000 identified genes were discarded. Possible doublets predicted by the DoubletFinder software were eliminated so as not to impede the analyses. After filtering, samples containing fewer than 500 cells were deemed of poor quality and eliminated. More than 1000 thousand cells of good quality were preserved for further analysis. All individual high-quality single-cell samples were then curated into a single object and to eliminate batch effects. The dimensionality of this dataset was reduced through principal component analysis (PCA) with highly variable features, and the first 15 PCs were selected for investigation. Then, unsupervised clustering was approximated using the shared nearest-neighbor network produced by the Louvain algorithm and the edge weights between any two cells. Using the t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) methods, the identified clusters were displayed. We identified the differentially expressed markers of the resultant clusters and used the default nonparametric test, the Wilcoxon rank sum test with Bonferroni correction, to label the cell clusters.
DOI: 10.17632/59mjw8hfd3
title: Shared Muscle Synergies between Physical Performance Tests and Running: Implications for Return to Running

description: The dataset includes analog surface EMG signals recorded at 2000 Hz from 16 lower-limb and trunk muscles during overground running and nine physical performance test (PPT)–related tasks.

Participants. Ten healthy young males.
Trials. Each PPT-related task and running were performed in five repetitions per participant (total: 10 conditions × 5 trials).
Tasks.
The dataset includes ten tasks: task1 was walking at a comfortable speed; task2 was running at a jogging pace; task3 was a single-leg hop at 30% of each participant’s maximal forward hop distance (SLH30); task4 was a single-leg hop at 60% of maximal distance (SLH60); task5 was a single-leg hop at 100% of maximal distance (SLH100); task6 was a single-leg squat performed at approximately 45° of knee flexion; task7 was the Y-Balance test, including anterior, posteromedial, and posterolateral reaches; task8 was a single-leg heel-raise; task9 was a step-up-down task involving a forward step onto a 10-cm box followed by a return to the floor; and task10 was the diver balance task, in which participants stood on one leg while flexing the trunk forward and extending the contralateral hip.

Data format. EMG data are stored in matrix form; rows represent time points (sampled at 2000 Hz) and columns correspond to muscle channels in the following fixed order:

RA – Rectus Abdominis

OE – Oblique Externus

ESL1 – Erector Spinae (L1 level)

GM – Gluteus Maximus

Gmed – Gluteus Medius

BF – Biceps Femoris (long head)

ST – Semitendinosus

TFL – Tensor Fasciae Latae

ADD – Adductor Longus

RF – Rectus Femoris

VM – Vastus Medialis

VL – Vastus Lateralis

TA – Tibialis Anterior

MG – Gastrocnemius Medialis

SOL – Soleus

POL – Peroneus Longus

Pre-processing.
Raw EMG signals were high-pass filtered at 30 Hz to remove motion artifacts, full-wave rectified, and low-pass filtered at 10 Hz to obtain smoothed envelopes. For each task, the processed EMG data were time-normalized to 200 samples per trial, with five repetitions per task (5 × 200 = 1000 points) across the 16 recorded muscle channels.
DOI: 10.17632/59mjw8hfd3.1
title: Shared Muscle Synergies between Physical Performance Tests and Running: Implications for Return to Running

description: The dataset includes analog surface EMG signals recorded at 2000 Hz from 16 lower-limb and trunk muscles during overground running and nine physical performance test (PPT)–related tasks.

Participants. Ten healthy young males.
Trials. Each PPT-related task and running were performed in five repetitions per participant (total: 10 conditions × 5 trials).
Tasks.
The dataset includes ten tasks: task1 was walking at a comfortable speed; task2 was running at a jogging pace; task3 was a single-leg hop at 30% of each participant’s maximal forward hop distance (SLH30); task4 was a single-leg hop at 60% of maximal distance (SLH60); task5 was a single-leg hop at 100% of maximal distance (SLH100); task6 was a single-leg squat performed at approximately 45° of knee flexion; task7 was the Y-Balance test, including anterior, posteromedial, and posterolateral reaches; task8 was a single-leg heel-raise; task9 was a step-up-down task involving a forward step onto a 10-cm box followed by a return to the floor; and task10 was the diver balance task, in which participants stood on one leg while flexing the trunk forward and extending the contralateral hip.

Data format. EMG data are stored in matrix form; rows represent time points (sampled at 2000 Hz) and columns correspond to muscle channels in the following fixed order:

RA – Rectus Abdominis

OE – Oblique Externus

ESL1 – Erector Spinae (L1 level)

GM – Gluteus Maximus

Gmed – Gluteus Medius

BF – Biceps Femoris (long head)

ST – Semitendinosus

TFL – Tensor Fasciae Latae

ADD – Adductor Longus

RF – Rectus Femoris

VM – Vastus Medialis

VL – Vastus Lateralis

TA – Tibialis Anterior

MG – Gastrocnemius Medialis

SOL – Soleus

POL – Peroneus Longus

Pre-processing.
Raw EMG signals were high-pass filtered at 30 Hz to remove motion artifacts, full-wave rectified, and low-pass filtered at 10 Hz to obtain smoothed envelopes. For each task, the processed EMG data were time-normalized to 200 samples per trial, with five repetitions per task (5 × 200 = 1000 points) across the 16 recorded muscle channels.
DOI: 10.17632/r76v8jzt4z
title: Industry Metal Commodities

description: Industry Metals Price
DOI: 10.5281/zenodo.16985872
title: Golden UML Modelset

description: The Golden UML modelset is a community-currated, high-quality set of UML class diagrams with a textual description. The dataset, its purpose and construction are described in the paper "Toward a Community-Curated Golden Dataset of UML Models", accepted at the Educators Symposium at MODELS2025.
DOI: 10.5281/zenodo.16985873
title: Golden UML Modelset

description: The Golden UML modelset is a community-currated, high-quality set of UML class diagrams with a textual description. The dataset, its purpose and construction are described in the paper "Toward a Community-Curated Golden Dataset of UML Models", accepted at the Educators Symposium at MODELS2025.
DOI: 10.17632/r76v8jzt4z.1
title: Industry Metal Commodities

description: Industry Metals Price
DOI: 10.6084/m9.figshare.30024757
title: <b>High-Density Lipoprotein Cholesterol and Cognitive Impairment: A U-Shaped Relationship in China’s Aging Population</b>

description: This study investigated the association between high-density lipoprotein cholesterol (HDL-C) levels and the risk of cognitive disorders in older adults. Data were obtained from the 2011 Chinese Health and Retirement Longitudinal Study and included 7,509 participants. Cognitive function was assessed using a scale that measured episodic memory and mental status. Statistical analyses included multiple linear regression, restricted cubic splines, and threshold effect analysis to explore the relationship between HDL-C levels and cognitive scores. Compared with Q1 (&lt;35 mg/dL), very high HDL-C was associated with lower cognitive scores (Q4: β = −0.622 [95% CI, −0.908 to −0.337]; Q5: β = −0.322 [−0.627 to −0.017]). A U-shaped association was observed, with a turning point at 67.43 mg/dL. Below the threshold, a 1-SD higher HDL-C was associated with a 0.08-SD higher cognitive score (β = +0.08; 95% CI, 0.06–0.11; p&lt;0.001), whereas above the threshold a 1-SD higher HDL-C was associated with a 0.07-SD lower score (β = −0.07; 95% CI, −0.14 to −0.01; p=0.019).Therefore, the relationship between lipid profiles and cognitive health is nuanced and nonlinear. Understanding these complexities is crucial for developing strategies to maintain cognitive function in older adults.
DOI: 10.6084/m9.figshare.30024757.v1
title: <b>High-Density Lipoprotein Cholesterol and Cognitive Impairment: A U-Shaped Relationship in China’s Aging Population</b>

description: This study investigated the association between high-density lipoprotein cholesterol (HDL-C) levels and the risk of cognitive disorders in older adults. Data were obtained from the 2011 Chinese Health and Retirement Longitudinal Study and included 7,509 participants. Cognitive function was assessed using a scale that measured episodic memory and mental status. Statistical analyses included multiple linear regression, restricted cubic splines, and threshold effect analysis to explore the relationship between HDL-C levels and cognitive scores. Compared with Q1 (&lt;35 mg/dL), very high HDL-C was associated with lower cognitive scores (Q4: β = −0.622 [95% CI, −0.908 to −0.337]; Q5: β = −0.322 [−0.627 to −0.017]). A U-shaped association was observed, with a turning point at 67.43 mg/dL. Below the threshold, a 1-SD higher HDL-C was associated with a 0.08-SD higher cognitive score (β = +0.08; 95% CI, 0.06–0.11; p&lt;0.001), whereas above the threshold a 1-SD higher HDL-C was associated with a 0.07-SD lower score (β = −0.07; 95% CI, −0.14 to −0.01; p=0.019).Therefore, the relationship between lipid profiles and cognitive health is nuanced and nonlinear. Understanding these complexities is crucial for developing strategies to maintain cognitive function in older adults.
DOI: 10.17632/k7w8bxmznp
title: Microbial Community Profiles of Biofilms from Hot Springs: 16S and 18S rRNA Amplicon Sequencing Data

description: This dataset contains the fasta sequences and related information from 16S and 18S rRNA amplicon sequencing of biofilm samples from six hot springs located in the states of Selangor, Federal Territory Kuala Lumpur, and Negeri Sembilan in Malaysia. The ‘Readme’ file contains the methods of the study.
DOI: 10.17632/k7w8bxmznp.2
title: Microbial Community Profiles of Biofilms from Hot Springs: 16S and 18S rRNA Amplicon Sequencing Data

description: This dataset contains the fasta sequences and related information from 16S and 18S rRNA amplicon sequencing of biofilm samples from six hot springs located in the states of Selangor, Federal Territory Kuala Lumpur, and Negeri Sembilan in Malaysia. The ‘Readme’ file contains the methods of the study.
DOI: 10.17632/x2yxdt4ppc
title: Liquid Chromatography–Tandem Mass Spectrometry

description: Liquid Chromatography–Tandem Mass Spectrometry
DOI: 10.17632/x2yxdt4ppc.1
title: Liquid Chromatography–Tandem Mass Spectrometry

description: Liquid Chromatography–Tandem Mass Spectrometry
DOI: 10.17632/yhyk89n944
title: N1-methylpseudouridine mRNA modification enhances efficiency and specificity of gene overexpression by preventing Prkra-mediated global translation repression

description: In vitro transcribed messenger RNA (IVT mRNA) has emerged as a pivotal tool in mRNA-based therapies and has been extensively employed in gene function studies and genetic tool applications. However, the IVT process generates double-stranded RNA (dsRNA) by-products that are recognized by dsRNA sensors, triggering innate immune responses. In this study, we comprehensively analyzed the detrimental effects of dsRNA by-products on early zebrafish embryos, revealing that these by-products induce cell necrosis and delay maternal-zygotic transition by reducing global translation efficiency via Prkra, a recently identified dsRNA sensor in pluripotent cells. Importantly, we demonstrate that N1-methylpseudouridine (m1Ψ) modification of IVT mRNAs effectively mitigates these adverse effects, as m1Ψ-modified dsRNAs exhibit significantly lower binding affinity to the Prkra dimer. Our findings underscore a previously overlooked challenge in the use of IVT mRNA in early embryos and offer a robust solution to enhance the fidelity of mRNA applications. Furthermore, we elucidate that m1Ψ modification minimizes the dsRNA-induced stress response in pluripotent cells through a distinct mechanism.