cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10933334
title: Data from: The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

description: Included are raw neuroimaging and preprocessed neural recording data from "The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation" (see Related Works section; citation will be updated after publication). Please cite this paper if you use any of these data. Refer to the linked github repository for associated code.

Neuroimaging data is organized in BIDS format and saved as NIfTI files. We used MION (monocrystalline iron oxide nanoparticle) as a contrast agent. Functional resting state files can be found in the 'func' folder for each imaging session. The final six runs are resting state data (the first two/three are short EPI sequences used to test that MION is present in the brain; all resting state data used in our analyses consist of 300 volumes). The first three of these six runs consist of baseline data with no drug treatment. Four through six are resting state data recorded after I.M. injection of vehicle (2% DMSO in saline), dechloroclozapine (DCZ) or clozapine-N-oxide (CNO). 

Neural recording data is separated into LFP data, organized by folder, and putative single units, organized the 'Sorted neurons' folder. LFP data folders are named by subject's intial and date of recording. Single units are labeled according to this same system. All data are stored in .mat format and can be opened in MATLAB. KB2.mat files store timing information: the first event in the KBD2 file indicates the start of baseline, pre-injection data acquisition, and the second event indicates the start of post-injection treatment data. The KB3.mat files contains the timing information of the drug injection. As with the fMRI data, we treated animals with I.M. injection of vehicle, DCZ, or CNO. 

Treatment information for both modalities is as follows. Neuroimaging: 2020/03/16 Animal L DCZ 1; 2020/05/27 Animal H vehicle 1; 2020/06/01 Animal L vehicle 1; 2020/06/08 Animal H DCZ 1; 2020/06/22 Animal L DCZ 2; 2020/06/24 Animal H vehicle 2; 2020/07/06 Animal L vehicle 2; 2020/07/08 Animal H DCZ 2; 2021/10/25 Animal L CNO; 2022/01/13 Animal H CNO. Neural recordings: 2022/04/14 Animal H DCZ 1; 2022/04/21 Animal H vehicle 1; 2022/05/12 Animal H DCZ 2; 2022/05/24 Animal H vehicle 2; 2022/06/03 Animal H CNO; 2022/08/18 Animal L vehicle 1; 2022/08/25 Animal L DCZ 1; 2022/09/01 Animal L DCZ 2; 2022/09/08 Animal L vehicle 2; 2022/09/22 Animal L CNO.
DOI: 10.5281/zenodo.10933335
title: Data from: The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

description: Included are raw neuroimaging and preprocessed neural recording data from "The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation" (see Related Works section; citation will be updated after publication). Please cite this paper if you use any of these data. Refer to the linked github repository for associated code.

Neuroimaging data is organized in BIDS format and saved as NIfTI files. We used MION (monocrystalline iron oxide nanoparticle) as a contrast agent. Functional resting state files can be found in the 'func' folder for each imaging session. The final six runs are resting state data (the first two/three are short EPI sequences used to test that MION is present in the brain; all resting state data used in our analyses consist of 300 volumes). The first three of these six runs consist of baseline data with no drug treatment. Four through six are resting state data recorded after I.M. injection of vehicle (2% DMSO in saline), dechloroclozapine (DCZ) or clozapine-N-oxide (CNO). 

Neural recording data is separated into LFP data, organized by folder, and putative single units, organized the 'Sorted neurons' folder. LFP data folders are named by subject's intial and date of recording. Single units are labeled according to this same system. All data are stored in .mat format and can be opened in MATLAB. KB2.mat files store timing information: the first event in the KBD2 file indicates the start of baseline, pre-injection data acquisition, and the second event indicates the start of post-injection treatment data. The KB3.mat files contains the timing information of the drug injection. As with the fMRI data, we treated animals with I.M. injection of vehicle, DCZ, or CNO. 

Treatment information for both modalities is as follows. Neuroimaging: 2020/03/16 Animal L DCZ 1; 2020/05/27 Animal H vehicle 1; 2020/06/01 Animal L vehicle 1; 2020/06/08 Animal H DCZ 1; 2020/06/22 Animal L DCZ 2; 2020/06/24 Animal H vehicle 2; 2020/07/06 Animal L vehicle 2; 2020/07/08 Animal H DCZ 2; 2021/10/25 Animal L CNO; 2022/01/13 Animal H CNO. Neural recordings: 2022/04/14 Animal H DCZ 1; 2022/04/21 Animal H vehicle 1; 2022/05/12 Animal H DCZ 2; 2022/05/24 Animal H vehicle 2; 2022/06/03 Animal H CNO; 2022/08/18 Animal L vehicle 1; 2022/08/25 Animal L DCZ 1; 2022/09/01 Animal L DCZ 2; 2022/09/08 Animal L vehicle 2; 2022/09/22 Animal L CNO.
DOI: 10.5281/zenodo.10975361
title: Experimental data associated with publication "Small-scale roughness entraps water and controls underwater adhesion"

description: This folder contains:



Experimental adhesion data and the JKR Fit parameters.

Raw SFG data used to create Figure 2.

Power spectral densities of the 4 rough diamond surfaces. 

Summary sheets containing results for dry and underwater adhesion measurements.
DOI: 10.5281/zenodo.10975362
title: Experimental data associated with publication "Small-scale roughness entraps water and controls underwater adhesion"

description: This folder contains:



Experimental adhesion data and the JKR Fit parameters.

Raw SFG data used to create Figure 2.

Power spectral densities of the 4 rough diamond surfaces. 

Summary sheets containing results for dry and underwater adhesion measurements.
DOI: 10.5281/zenodo.10975438
title: A collection of datasets for software vulnerability detection

description: This is a collection of datasets that are used for AI-based software vulnerability detection. All the datasets are in the .csv format and each row represents a sample. Each dataset includes a set of functions written in C and the target of each function is either 0 (non-vulnerable) or 1 (vulnerable).



data_C_Lin2017_test.csv:



Reference paper: Vulnerability Discovery with Function Representation Learning from Unlabeled Projects, 2017.

Data source on GitHub: https://github.com/DanielLin1986/function_representation_learning

This dataset includes 44 vulnerable and 577 non-vulnerable functions from the LibPNG project.



data_C_LineVul_test.csv:



Reference paper: LineVul: A Transformer-based Line-Level Vulnerability Prediction, 2022.

Data source on Hugging Face: https://huggingface.co/datasets/Partha117/LineVul_Test_Dataset

This dataset includes 1055 vulnerable and 17809 non-vulnerable functions.



data_C_PrimeVul_test.csv:



Reference paper: Vulnerability Detection with Code LanguageModels: How Far Are We? 2024.

Data source on GitHub: https://github.com/DLVulDet/PrimeVul

From the data source, the primevul_test.jsonl was used to created this dataset.

This dataset includes 695 vulnerable and 25213 non-vulnerable functions.



data_C_Choi2017_test.csv:



Reference paper: End-to-End Prediction of Buffer Overruns from Raw Source Codevia Neural Memory Networks, 2017.

Data source on GitHub: https://github.com/mjc92/buffer_overrun_memory_networks

From GitHub, all the data in trainnig_100.txt, test_1_100.txt, test_2_100.txt,test_3_100.txt,test_4_100.txt, and corresponding _labels.txt files are combined to create this dataset.

This dataset includes 7054 vulnerable and 6946 non-vulnerable functions.



data_C_Devign_test.csv:



Reference paper: Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks, 2019

Data source on Hugging Face: https://huggingface.co/datasets/claudios/code_x_glue_devign

From Hugging Face, all the data in train, validation, and test are combined to create this dataset.

This dataset includes 12460 vulnerable and 14858 non-vulnerable functions.



data_C_Ours_{train,test}.csv:



This dataset is manually collected from projects on GitHub that have registered CVEs into NVD from 2002 to 2023. The 6,766 non-vulnerable code functions are extracted from the DiverseVul dataset to increase the code diversity. 

This training set includes 5413 vulnerable and 5413 non-vulnerable functions.

The test set includes 1353 vulnerable and 1353 non-vulnerable functions.
DOI: 10.5281/zenodo.10975439
title: A collection of datasets for software vulnerability detection

description: This is a collection of datasets that are used for AI-based software vulnerability detection. All the datasets are in the .csv format and each row represents a sample. Each dataset includes a set of functions written in C and the target of each function is either 0 (non-vulnerable) or 1 (vulnerable).



data_C_Lin2017_test.csv:



Reference paper: Vulnerability Discovery with Function Representation Learning from Unlabeled Projects, 2017.

Data source on GitHub: https://github.com/DanielLin1986/function_representation_learning

This dataset includes 44 vulnerable and 577 non-vulnerable functions from the LibPNG project.



data_C_LineVul_test.csv:



Reference paper: LineVul: A Transformer-based Line-Level Vulnerability Prediction, 2022.

Data source on Hugging Face: https://huggingface.co/datasets/Partha117/LineVul_Test_Dataset

This dataset includes 1055 vulnerable and 17809 non-vulnerable functions.



data_C_PrimeVul_test.csv:



Reference paper: Vulnerability Detection with Code LanguageModels: How Far Are We? 2024.

Data source on GitHub: https://github.com/DLVulDet/PrimeVul

From the data source, the primevul_test.jsonl was used to created this dataset.

This dataset includes 695 vulnerable and 25213 non-vulnerable functions.



data_C_Choi2017_test.csv:



Reference paper: End-to-End Prediction of Buffer Overruns from Raw Source Codevia Neural Memory Networks, 2017.

Data source on GitHub: https://github.com/mjc92/buffer_overrun_memory_networks

From GitHub, all the data in trainnig_100.txt, test_1_100.txt, test_2_100.txt,test_3_100.txt,test_4_100.txt, and corresponding _labels.txt files are combined to create this dataset.

This dataset includes 7054 vulnerable and 6946 non-vulnerable functions.



data_C_Devign_test.csv:



Reference paper: Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks, 2019

Data source on Hugging Face: https://huggingface.co/datasets/claudios/code_x_glue_devign

From Hugging Face, all the data in train, validation, and test are combined to create this dataset.

This dataset includes 12460 vulnerable and 14858 non-vulnerable functions.



data_C_Ours_{train,test}.csv:



This dataset is manually collected from projects on GitHub that have registered CVEs into NVD from 2002 to 2023. The 6,766 non-vulnerable code functions are extracted from the DiverseVul dataset to increase the code diversity. 

This training set includes 5413 vulnerable and 5413 non-vulnerable functions.

The test set includes 1353 vulnerable and 1353 non-vulnerable functions.
DOI: 10.15468/dl.xw6kc8
title: Occurrence Download

description: A dataset containing 1895 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cichorium pumilum Jacq."
 ]
}

 The dataset includes 1895 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137866-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10975232
title: 3DED data of lanthanum hexaboride

description: 3DED data of commerically obtained lanthanum hexaboride were collected using continuous rotation in selected area mode. The table below summarizes data collection parameters.

 




General information
 


Project
 


Project label
 


Sample label
LaB6


Collection site
University of Southampton, NCS


 
 


Instrumental
 


Instrument
Rigaku XtaLAB Synergy-ED, electron diffractometer


Radiation source
LaB6


Accelerating voltage [kV]
200


Wavelength [Å]
0.02510


Probe type
Parallel beam


Beam diameter
 


Beam convergence
Parallel beam


Detector
Rigaku HyPix-ED, hybrid pixel array detector


Number of pixels in the image
775 x 385


Pixel size [µm]
100


Hardware binning
1


 
 


Sample description
 


Name
lanthanum hexaboride


Chemical composition
La B6


Sample source
commercial (Sigma Aldrich 241857)


Grid
Agar Scientific holey carbon coated copper grid 200 mesh


Sample preparation
solid sample gently ground and dispersed between microscopy glass slides, grid tapped on solid


Sample holder
JEOL standard TEM holder with high tilt retainer


 
 


Experimental
 


Data type
Electron diffraction data - 3DED


Data collection method
continuous rotation  - cRED


Collection temperature [K]
rt


 
 


Software
 


Software used for the data collection
CrysAlisPro 1.171.43.111a


Software used for processing
CrysAlisPro 1.171.43.119a


 
 


Files and data formats
 


Image folders
./frames/xxx.rodhypix./frames/PETS_exp_701/frames/xxx.tiff


Image format
.rodhypix (Rigaku proprietary image format).tiff (16bit, converted with CrysAlisPro 1.171.43.119a)


Additional files


CrysAlisPro input files:./expinfo/./CrysalisExpSettings.ini./exp_701.par./exp_701.run./new.ccd

PETS2 (http://pets.fzu.cz/) input file:./frames/PETS_exp_701/exp_701.pts2

Crystal Image:./exp_701_microed_grain_snapshot.jpg
DOI: 10.5281/zenodo.10975233
title: 3DED data of lanthanum hexaboride

description: 3DED data of commerically obtained lanthanum hexaboride were collected using continuous rotation in selected area mode. The table below summarizes data collection parameters.

 




General information
 


Project
 


Project label
 


Sample label
LaB6


Collection site
University of Southampton, NCS


 
 


Instrumental
 


Instrument
Rigaku XtaLAB Synergy-ED, electron diffractometer


Radiation source
LaB6


Accelerating voltage [kV]
200


Wavelength [Å]
0.02510


Probe type
Parallel beam


Beam diameter
 


Beam convergence
Parallel beam


Detector
Rigaku HyPix-ED, hybrid pixel array detector


Number of pixels in the image
775 x 385


Pixel size [µm]
100


Hardware binning
1


 
 


Sample description
 


Name
lanthanum hexaboride


Chemical composition
La B6


Sample source
commercial (Sigma Aldrich 241857)


Grid
Agar Scientific holey carbon coated copper grid 200 mesh


Sample preparation
solid sample gently ground and dispersed between microscopy glass slides, grid tapped on solid


Sample holder
JEOL standard TEM holder with high tilt retainer


 
 


Experimental
 


Data type
Electron diffraction data - 3DED


Data collection method
continuous rotation  - cRED


Collection temperature [K]
rt


 
 


Software
 


Software used for the data collection
CrysAlisPro 1.171.43.111a


Software used for processing
CrysAlisPro 1.171.43.119a


 
 


Files and data formats
 


Image folders
./frames/xxx.rodhypix./frames/PETS_exp_701/frames/xxx.tiff


Image format
.rodhypix (Rigaku proprietary image format).tiff (16bit, converted with CrysAlisPro 1.171.43.119a)


Additional files


CrysAlisPro input files:./expinfo/./CrysalisExpSettings.ini./exp_701.par./exp_701.run./new.ccd

PETS2 (http://pets.fzu.cz/) input file:./frames/PETS_exp_701/exp_701.pts2

Crystal Image:./exp_701_microed_grain_snapshot.jpg
DOI: 10.15468/dl.slabvc
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tetrastigma rafflesiae (Miq.) Planch."
 ]
}

 The dataset includes 11 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004439-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10975491
title: Evaluation of comparative Efficacy of two routes of administration of Carathmus Tinctorius (Medicated Enema and Nasal Administration) as an Adjuvant Therapy with Standard Care With Physiotherapy in the Rehabilitation of Thrombolytic Stroke (Pakshaghat): A Randomized Controlled Trial Protocol
DOI: 10.5281/zenodo.10975492
title: Evaluation of comparative Efficacy of two routes of administration of Carathmus Tinctorius (Medicated Enema and Nasal Administration) as an Adjuvant Therapy with Standard Care With Physiotherapy in the Rehabilitation of Thrombolytic Stroke (Pakshaghat): A Randomized Controlled Trial Protocol
DOI: 10.5281/zenodo.10975575
title: BOLD release 5 April 2024, curated with pipeline commit d7f034f1e14f15daed708bb3e0e8ddf1b50e0249
DOI: 10.15468/dl.e6m3zz
title: Occurrence Download

description: A dataset containing 375 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Brunei Darussalam",
 "Country is Indonesia",
 "Country is Malaysia",
 "Country is Philippines",
 "Country is Timor-Leste",
 "Country is Papua New Guinea",
 "Country is Singapore"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Saccolomataceae",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 375 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004439-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n7dqff
title: Occurrence Download

description: A dataset containing 381 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cichorium spinosum L."
 ]
}

 The dataset includes 381 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137867-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10975737
title: test
DOI: 10.15468/dl.9z4qg2
title: Occurrence Download

description: A dataset containing 307 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-118.92018 14.49432,-85.77235 14.49432,-85.77235 32.95869,-118.92018 32.95869,-118.92018 14.49432))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Isthmura Dubois & Raffaelli, 2012",
 "Year 2000-2023"
 ]
}

 The dataset includes 307 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137950-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6lguzx
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Changnienia amoena S.S.Chien",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 10 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035108-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10975576
title: BOLD release 5 April 2024, curated with pipeline commit d7f034f1e14f15daed708bb3e0e8ddf1b50e0249
DOI: 10.5281/zenodo.10975736
title: test
DOI: 10.15468/dl.mnujnn
title: Occurrence Download

description: A dataset containing 27988 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Inventaire National du Patrimoine Naturel : Loup en France"
 ]
}

 The dataset includes 27988 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004439-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10959700
title: Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer

description: Colorectal Cancer (CRC) is a highly heterogeneous group of diseases, with distinctive genetic and epigenetic alterations. CRC tumors bearing KRAS or BRAF mutations still remain resistant to new therapies. Thus, this augments the necessity to reveal new therapeutic targets in mutKRAS/BRAF, which may account for up to 50% of the total CRC patients. To this end, we investigated primary untreated CRC tumors (WES & RNA-Seq) from 28 Greek patients for their systematic molecular characterization and stratification into diverse groups based on their microsatellite instability (MSI) status and KRAS/BRAF genetic variations, in order to unravel novel targets and putative personalized treatment interventions. The raw data of this project (WES & RNA-Seq) have been uploaded in the EGA European Genome-Phenome Archive (EGAD00001011262 and EGAD00001011263).
DOI: 10.15468/dl.n8jae3
title: Occurrence Download

description: A dataset containing 488 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cionosicys excisus (Griseb.) C.Jeffrey"
 ]
}

 The dataset includes 488 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137968-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10975590
title: Research data for "Predicting Dynamics from Structure in a Sodium Silicate Glass"

description: This dataset supports the paper "Predicting Dynamics from Structure in a Sodium Silicate Glass".

The following files are provided.

File: dataset_800.zip

- Pickle files for:



400 Sodium silicate glass structures of 3000 atoms

30 Trajectories sampled eight times at various timescales up to 1 ns for each if the 400 glass structures


File: in.comb

- Lammps inputfile used to generate simulation from with the data in dataset was sampled
DOI: 10.15468/dl.wg7k9z
title: Occurrence Download

description: A dataset containing 60332 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Month is April",
 "Month is May"
 ]
 },
 "TaxonKey is Phainopepla nitens (Swainson, 1838)"
 ]
}

 The dataset includes 60332 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035638-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10959699
title: Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer

description: Colorectal Cancer (CRC) is a highly heterogeneous group of diseases, with distinctive genetic and epigenetic alterations. CRC tumors bearing KRAS or BRAF mutations still remain resistant to new therapies. Thus, this augments the necessity to reveal new therapeutic targets in mutKRAS/BRAF, which may account for up to 50% of the total CRC patients. To this end, we investigated primary untreated CRC tumors (WES & RNA-Seq) from 28 Greek patients for their systematic molecular characterization and stratification into diverse groups based on their microsatellite instability (MSI) status and KRAS/BRAF genetic variations, in order to unravel novel targets and putative personalized treatment interventions. The raw data of this project (WES & RNA-Seq) have been uploaded in the EGA European Genome-Phenome Archive (EGAD00001011262 and EGAD00001011263).
DOI: 10.5281/zenodo.10975591
title: Research data for "Predicting Dynamics from Structure in a Sodium Silicate Glass"

description: This dataset supports the paper "Predicting Dynamics from Structure in a Sodium Silicate Glass".

The following files are provided.

File: dataset_800.zip

- Pickle files for:



400 Sodium silicate glass structures of 3000 atoms

30 Trajectories sampled eight times at various timescales up to 1 ns for each if the 400 glass structures


File: in.comb

- Lammps inputfile used to generate simulation from with the data in dataset was sampled