cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48567/69y1-zw19
title: Racer Rock Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/jw9a-yz57
title: Relay Station Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/ejrp-dp59
title: Schwerdtfeger Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/9wc5-cc44
title: Siple Dome Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/0d2g-5r29
title: Sky Blu Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/q179-fq54
title: Swithinbank Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/acb2-y921
title: Theresa Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/8s30-jf25
title: Uranus Glacier Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/wr78-rj50
title: Whitlock Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/kdq0-rt02
title: Willie Field Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.48567/c9pf-xy63
title: Windless Bight Automatic Weather Station, 2001 quality-controlled observational data.
DOI: 10.5281/zenodo.13619701
title: ToPoRg-18k: dataset of single-chain radii of gyration distribution for 18,450 architecturally diverse and chemically patterned coarse-grained polymers

description: This distribution provides access to 18,450 configurations of coarse-grained polymers. The data is provided as a serialized object using the `pickle' Python module and in csv format. The data was compiled using Python version 3.8. 

ReferencesThe specific applications and analyses of the data are described in 1.  Jiang, S.; Webb, M.A. "Physics-Guided Neural Networks for Transferable Prediction of Polymer Properties"

DataThere are seven .pickle files that contain serialized Python objects.



pattern_graph_data_*_*_rg_new.pickle: squared radii of gyration distribution from MD simulation. The number indicates the molecular weight range.

rg2_baseline_*_new.pickle: squared radii of gyration distribution from Gaussian chain theoretical prediction.

delta_data_v0314.pickle: torch_geometric training data.


UsageTo access the data in the .pickle file, users can execute the following:



# LOAD SIMULATION DATADATA_DIR = "your/custom/dir/"mw = 40 # or 90, 190 MWs

filename = os.path.join(DATA_DIR, f"pattern_graph_data_{mw}_{mw+20}_rg_new.pickle")with open(filename, "rb") as handle:    graph = pickle.load(handle)    label = pickle.load(handle)    desc  = pickle.load(handle)    meta  = pickle.load(handle)    mode  = pickle.load(handle)    rg2_mean   = pickle.load(handle)    rg2_std    = pickle.load(handle) ** 0.5 # var

# combine asymmetric and symmetric star polymerslabel[label == 'stara'] = 'star'# combine bottlebrush and other comb polymerslabel[label == 'bottlebrush'] = 'comb' 

# LOAD GAUSSIAN CHAIN THEORETICAL DATAwith open(os.path.join(DATA_DIR, f"rg2_baseline_{mw}_new.pickle"), "rb") as handle:    rg2_mean_theo = pickle.load(handle)[:, 0]    rg2_std_theo = pickle.load(handle)[:, 0]




graph: NetworkX graph representations of polymers.

label: Architectural classes of polymers (e.g., linear, cyclic, star, branch, comb, dendrimer).

desc: Topological descriptors (optional).

meta: Identifiers for unique architectures (optional).

mode: Identifiers for unique chemical patterns (optional).

rg2_mean: Mean squared radii of gyration from simulations.

rg2_std: Corresponding standard deviation from simulations.

rg2_mean_theo: Mean squared radii of gyration from theoretical models.

rg2_std_theo: Corresponding standard deviation from theoretical models.


Help, Suggestions, Corrections?If you need help, have suggestions, identify issues, or have corrections, please send your comments to Shengli Jiang at sj0161@princeton.edu

GitHubAdditional data and code relevant for this study is additionally accessible at https://github.com/webbtheosim/gcgnn
DOI: 10.15468/dl.4cy9bz
title: Occurrence Download

description: A dataset containing 59578 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-79.03906 -6.0559,-78.44033 -6.0559,-78.44033 -5.49595,-79.03906 -5.49595,-79.03906 -6.0559))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 59578 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010218-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57778/979a-nf32
title:  Annual Wetland Maps (2019-2024) of Mobile-Tensaw-Apalachee (MTA) river delta 

description: This dataset provides annual 10‑meter wetland maps for the Mobile‑Tensaw‑Apalachee (MTA) River Delta from 2019 to 2024, generated by integrating Sentinel‑2 optical imagery and Sentinel‑1 time‑series SAR data. A 1D‑CNN deep learning model was used to classify four wetland types: Forested Wetland, Marsh, Unconsolidated Shore, and Open Water, along with three non‑wetland classes. Classification accuracy ranged from 93% to 96%, supported by field verification and comparison with existing regional products. The dataset captures year-to-year changes in wetland extent and transitions, enabling the detection of subtle hydrological and ecological shifts within one of the largest freshwater wetland complexes in the United States.
DOI: 10.5281/zenodo.15277110
title: ToPoRg-18k: dataset of single-chain radii of gyration distribution for 18,450 architecturally diverse and chemically patterned coarse-grained polymers

description: Revision: This revision includes four independent trajectory values of the ensemble averages of the mean squared radii of gyration and their standard deviations, which can be used to compute statistical measures such as the standard error.


This distribution provides access to 18,450 configurations of coarse-grained polymers. The data is provided as a serialized object using the `pickle' Python module and in csv format. The data was compiled using Python version 3.8. 

ReferencesThe specific applications and analyses of the data are described in 1.  Jiang, S.; Webb, M.A. "Physics-Guided Neural Networks for Transferable Prediction of Polymer Properties"

DataThere are seven .pickle files that contain serialized Python objects.



pattern_graph_data_*_*_rg_new.pickle: squared radii of gyration distribution from MD simulation. The number indicates the molecular weight range.

rg2_baseline_*_new.pickle: squared radii of gyration distribution from Gaussian chain theoretical prediction.

delta_data_v0314.pickle: torch_geometric training data.


UsageTo access the data in the .pickle file, users can execute the following:



# LOAD SIMULATION DATADATA_DIR = "your/custom/dir/"mw = 40 # or 90, 190 MWs

filename = os.path.join(DATA_DIR, f"pattern_graph_data_{mw}_{mw+20}_rg_new.pickle")with open(filename, "rb") as handle:    graph = pickle.load(handle)    label = pickle.load(handle)    desc  = pickle.load(handle)    meta  = pickle.load(handle)    mode  = pickle.load(handle)    rg2_mean   = pickle.load(handle)    rg2_std    = pickle.load(handle) ** 0.5 # var

# combine asymmetric and symmetric star polymerslabel[label == 'stara'] = 'star'# combine bottlebrush and other comb polymerslabel[label == 'bottlebrush'] = 'comb' 

# LOAD GAUSSIAN CHAIN THEORETICAL DATAwith open(os.path.join(DATA_DIR, f"rg2_baseline_{mw}_new.pickle"), "rb") as handle:    rg2_mean_theo = pickle.load(handle)[:, 0]    rg2_std_theo = pickle.load(handle)[:, 0]




graph: NetworkX graph representations of polymers.

label: Architectural classes of polymers (e.g., linear, cyclic, star, branch, comb, dendrimer).

desc: Topological descriptors (optional).

meta: Identifiers for unique architectures (optional).

mode: Identifiers for unique chemical patterns (optional).

rg2_mean: Mean squared radii of gyration from simulations.

rg2_std: Corresponding standard deviation from simulations.

rg2_mean_theo: Mean squared radii of gyration from theoretical models.

rg2_std_theo: Corresponding standard deviation from theoretical models.


Help, Suggestions, Corrections?If you need help, have suggestions, identify issues, or have corrections, please send your comments to Shengli Jiang at sj0161@princeton.edu

GitHubAdditional data and code relevant for this study is additionally accessible at https://github.com/webbtheosim/gcgnn
DOI: 10.5281/zenodo.13619700
title: ToPoRg-18k: dataset of single-chain radii of gyration distribution for 18,450 architecturally diverse and chemically patterned coarse-grained polymers

description: Revision: This revision includes four independent trajectory values of the ensemble averages of the mean squared radii of gyration and their standard deviations, which can be used to compute statistical measures such as the standard error.


This distribution provides access to 18,450 configurations of coarse-grained polymers. The data is provided as a serialized object using the `pickle' Python module and in csv format. The data was compiled using Python version 3.8. 

ReferencesThe specific applications and analyses of the data are described in 1.  Jiang, S.; Webb, M.A. "Physics-Guided Neural Networks for Transferable Prediction of Polymer Properties"

DataThere are seven .pickle files that contain serialized Python objects.



pattern_graph_data_*_*_rg_new.pickle: squared radii of gyration distribution from MD simulation. The number indicates the molecular weight range.

rg2_baseline_*_new.pickle: squared radii of gyration distribution from Gaussian chain theoretical prediction.

delta_data_v0314.pickle: torch_geometric training data.


UsageTo access the data in the .pickle file, users can execute the following:



# LOAD SIMULATION DATADATA_DIR = "your/custom/dir/"mw = 40 # or 90, 190 MWs

filename = os.path.join(DATA_DIR, f"pattern_graph_data_{mw}_{mw+20}_rg_new.pickle")with open(filename, "rb") as handle:    graph = pickle.load(handle)    label = pickle.load(handle)    desc  = pickle.load(handle)    meta  = pickle.load(handle)    mode  = pickle.load(handle)    rg2_mean   = pickle.load(handle)    rg2_std    = pickle.load(handle) ** 0.5 # var

# combine asymmetric and symmetric star polymerslabel[label == 'stara'] = 'star'# combine bottlebrush and other comb polymerslabel[label == 'bottlebrush'] = 'comb' 

# LOAD GAUSSIAN CHAIN THEORETICAL DATAwith open(os.path.join(DATA_DIR, f"rg2_baseline_{mw}_new.pickle"), "rb") as handle:    rg2_mean_theo = pickle.load(handle)[:, 0]    rg2_std_theo = pickle.load(handle)[:, 0]




graph: NetworkX graph representations of polymers.

label: Architectural classes of polymers (e.g., linear, cyclic, star, branch, comb, dendrimer).

desc: Topological descriptors (optional).

meta: Identifiers for unique architectures (optional).

mode: Identifiers for unique chemical patterns (optional).

rg2_mean: Mean squared radii of gyration from simulations.

rg2_std: Corresponding standard deviation from simulations.

rg2_mean_theo: Mean squared radii of gyration from theoretical models.

rg2_std_theo: Corresponding standard deviation from theoretical models.


Help, Suggestions, Corrections?If you need help, have suggestions, identify issues, or have corrections, please send your comments to Shengli Jiang at sj0161@princeton.edu

GitHubAdditional data and code relevant for this study is additionally accessible at https://github.com/webbtheosim/gcgnn
DOI: 10.15468/dl.4c7kse
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Andrena montrosensis"
 ]
}

 The dataset includes 44 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010271-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14722568
title: Booru.org Top Leaderboard
DOI: 10.6084/m9.figshare.30022558
title: <b>Differentiation of bird taxa at the level of transition-transversion bias in the cytb gene sequencies</b>

description: The study of DNA marker variability provides robust insights into historical relationships, evolutionary rates, and the magnitude of genetic differentiation among taxa. This is particularly relevant for the youngest and most diverse group of vertebrates, traditionally classified as the class Aves. One of the core principles of molecular evolution theory is the transition–transversion bias, i.e., the paradoxical predominance of homotypic nucleotide substitutions (transitions) over heterotypic substitutions (transversions) during spontaneous mutational processes and speciation, a pattern that becomes progressively attenuated with increasing genetic divergence. This phenomenon exhibits group-specific features at higher taxonomic levels, allowing the identification of evolutionary characteristics unique to each lineage.The present study investigates patterns of evolutionary transition–transversion bias in birds using the mitochondrial CYTB gene as a model. The results demonstrate that the magnitude of the bias varies both along the evolutionary hierarchy depending on taxonomic level and among avian families. A predominance of transitions over transversions is observed at the population, species, genus, and family levels, whereas a slight predominance of transversions is detected at the order level. Temporal variation in transition–transversion ratios is driven by saltatory accumulation of transitions at the population, species, and genus levels against a background of relatively stable transversion frequencies. This pattern may be explained by genetic saturation effects or by divergence-level–specific features of the mutational process.Within Aves, nucleotide substitution patterns are characterized by an increase in transversion frequency and a decrease in transition frequency, accompanied by a reduction in the overall transition–transversion bias in small-bodied species from evolutionarily young families, compared with more ancient, large-bodied lineages with lower metabolic rates. The increase in transversion frequency in small-bodied, evolutionarily progressive bird groups is associated with elevated metabolic rates, leading to increased cellular oxygen availability and, consequently, higher levels of oxidative DNA damage. Metabolic intensification in birds thus represents not only a driver of enhanced genetic diversity and evolutionary advancement, but also evidently results in an increased mutational load, which may ultimately contribute to the evolutionary extinction of historically young, small-bodied taxonomic groups.
DOI: 10.15468/dl.92nt4b
title: Occurrence Download

description: A dataset containing 350 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Antilocapra americana"
 ]
}

 The dataset includes 350 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010274-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ys44y
title: Occurrence Download

description: A dataset containing 7649 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tigridia"
 ]
}

 The dataset includes 7649 records from 229 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010273-260129131611470/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.30022558.v1
title: Features of evolutionary-genetic differentiation of bird taxa at the level of transitions and transversions of the CytB gene

description: Nucleotide substitution analysis was performed for nucleotide substitutions during evolutionary divergence across major taxonomic levels within the class Aves. The frequencies of transitions (homotypic A↔G, T↔C substitutions) and transversions (heterotypic A↔T, A↔C, G↔T, G↔C substitutions) of the cytochrome b (Cytb) gene, as well as their numerical ratio (transition-transversion shift) vary widely. A pronounced predominance of transitions over transversions is observed at intraspecific and generic levels, while a slight predominance of transversions characterizes the formation of orders. This variability in transition-transversion bias is driven by an accelerated accumulation of transition at the genus level and lower levels of divergence against the background of relative stability of transversion frequencies within the evolutionary row of the class of birds. This means that at the late stages of phylogenesis (the formation of taxa of the order level and higher), the taxon formation is driven by a spontaneous mutation process, whereas at the early stages, evolutionary changes are realized through gene regulations. The variability in the nature of nucleotide substitutions is also evident across the same taxonomic levels within different avian orders. It manifests itself as an increase of the transversions frequency and a decrease in the magnitude of the transition-transversion bias within families of small-sized evolutionarily young groups. The reason for the increase in transversion frequencies is an increase in mutation rate within small-sized evolutionarily progressive groups of birds with intensive metabolism compared to families of more ancient large-sized order groups. Intensification of metabolism within birds is not only a factor of diversification and evolutionary progress, but also leads to an increase in the mutational load. There are two possible explanations for this phenomenon. First, point mutations may represent neutral events, the accumulation of which does not necessarily increase the genetic load. Second, the progressive intensification of metabolism inevitably becomes the "gravedigger" of the most evolutionarily progressive groups of birds.
DOI: 10.6084/m9.figshare.30022558.v2
title: <b>Differentiation of bird taxa at the level of transition-transversion bias in the cytb gene sequencies</b>

description: The study of DNA marker variability provides robust insights into historical relationships, evolutionary rates, and the magnitude of genetic differentiation among taxa. This is particularly relevant for the youngest and most diverse group of vertebrates, traditionally classified as the class Aves. One of the core principles of molecular evolution theory is the transition–transversion bias, i.e., the paradoxical predominance of homotypic nucleotide substitutions (transitions) over heterotypic substitutions (transversions) during spontaneous mutational processes and speciation, a pattern that becomes progressively attenuated with increasing genetic divergence. This phenomenon exhibits group-specific features at higher taxonomic levels, allowing the identification of evolutionary characteristics unique to each lineage.The present study investigates patterns of evolutionary transition–transversion bias in birds using the mitochondrial CYTB gene as a model. The results demonstrate that the magnitude of the bias varies both along the evolutionary hierarchy depending on taxonomic level and among avian families. A predominance of transitions over transversions is observed at the population, species, genus, and family levels, whereas a slight predominance of transversions is detected at the order level. Temporal variation in transition–transversion ratios is driven by saltatory accumulation of transitions at the population, species, and genus levels against a background of relatively stable transversion frequencies. This pattern may be explained by genetic saturation effects or by divergence-level–specific features of the mutational process.Within Aves, nucleotide substitution patterns are characterized by an increase in transversion frequency and a decrease in transition frequency, accompanied by a reduction in the overall transition–transversion bias in small-bodied species from evolutionarily young families, compared with more ancient, large-bodied lineages with lower metabolic rates. The increase in transversion frequency in small-bodied, evolutionarily progressive bird groups is associated with elevated metabolic rates, leading to increased cellular oxygen availability and, consequently, higher levels of oxidative DNA damage. Metabolic intensification in birds thus represents not only a driver of enhanced genetic diversity and evolutionary advancement, but also evidently results in an increased mutational load, which may ultimately contribute to the evolutionary extinction of historically young, small-bodied taxonomic groups.
DOI: 10.15468/dl.9ns6hw
title: Occurrence Download

description: A dataset containing 160 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mischocyttarus cerberus"
 ]
}

 The dataset includes 160 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010277-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cnwnqy
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CatalogNumber is one of (MVZ:Mamm:224698, MVZ:Mamm:228899, MVZ:Mamm:51447, MVZ:Mamm:241039, MVZ:Mamm:51448, MVZ:Mamm:224697)",
 "InstitutionCode is MVZ"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010276-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xuv7vu
title: Occurrence Download

description: A dataset listing the 59 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen)",
 "Geometry POLYGON((-70 -55.4,-66.4 -55.4,-66.4 -54.8,-70 -54.8,-70 -55.4))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Polychaeta"
 ]
}

 The dataset's 59 records were derived from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010253-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.