Find research datasets worth reusing

opencc-by-4.0Apr 2023View details →

A dataset of aerial images taken by UAV that we collected for "LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images"

Our private dataset of UAV aerial imagery for paper "<a href="https://doi.org/10.7717/peerj-cs.1467">LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images</a>".

opencc-by-4.0Apr 2023View details →

Pre-trained Model and Relation Extraction Dataset

NIPA

opencc-by-4.0Dec 2022View details →

Datasets of issue-commit and issue-method links extracted from GitHub repositories

Contains issue-commit and issue-method links extracted from GitHub repositories. Available on GitHub: https://github.com/pragma-once/utilizing-bert-for-traceability/releases

Extracted Data from Reviewed Studies for Platform Ecosystems Analytics SLR

Aggregation of data extraction results as part of a systematic literature review on platform ecosystems analytics.

Annotated sequences extracted from bacterial genomes

Three files containing sequences extracted from 1,049,210 bacterial genomes available from GenBank (release 252). Protein coding sequences were annotated with IDTAXA (PMID: 34541527) using taxon-specific KEGG groups (Bacteria_Protein_subset.fas.gz). These annotations were transferred to their corresponding (nucleotide) coding sequences (Bacteria_Nucleotide_subset.fas.gz). Intergenic regions were extracted from each genome and annotated by FindNonCoding (PMID: 34636849) for their overlap with any of 25 common bacterial non-coding RNAs in Rfam (v14). Intergenic regions were required to be at least 100 nucleotides long and contain no ambiguities (Bacteria_Intergenic_subset.fas.gz). Each subset contains only distinct sequences randomly ordered. Headers Sequence headers contain the assembly accession followed by the annotation and separated by a "|" character. For example: Bacteria_Intergenic_subset.fas.gz >GCA_022121725.1|RF00000 ATGTTACCTTCTTGAGTGATACGGGATGAA[...] Bacteria_Protein_subset.fas.gz >GCA_014764685.1|K02049 MPRDLIRISGLEKTYADGSVHALSNIDLSIKD[...] Bacteria_Nucleotide_subset.fas.gz >GCA_015948525.1|K02197 GTGAACCTGCGACGTAAAAACCGGCTAYG[...] Annotations Protein and protein coding sequences are labeled with their KEGG group, starting with "K". Intergenic sequences are named by any overlapping Rfam families, starting with a "RF", and separated by commas when multiple are predicted. "RF00000" is a placeholder for the absence of any predicted RF families.

Automated patent extraction powers generative modeling in focused chemical spaces: Training data and model checkpoints release

Training data and model checkpoints accompanying paper on "Automated patent extraction powers generative modeling in focused chemical spaces". If you use this data, please cite the following manuscript: <pre>@article{subramanian2023automated, title={Automated patent extraction powers generative modeling in focused chemical spaces}, author={Subramanian, Akshay and Greenman, Kevin P and Gervaix, Alexis and Yang, Tzuhsiung and G{\'o}mez-Bombarelli, Rafael}, journal={Digital Discovery}, year={2023}, publisher={Royal Society of Chemistry} }</pre>

opencc-by-4.0Jun 2023View details →

APPENDIX H: Evidence Synthesis Form and APPENDIX I: Extracted Associators

APPENDIX H: Evidence Synthesis Form and APPENDIX I: Extracted Associators for Memoryscapes in Recto-spection: Visualizing Avenida, Recto, and Carriedo, Manila as Virtual Memoryscapes  through immersive mobile technologies and digital heritage interpretation. Thesis Adviser: Dr. Cathe Desiree S. Nadal, Ph. D.

opencc-by-4.0Jul 2023View details →

Dataset for "Extraction of stratigraphic exposures on visible images using a supervised machine learning technique"

This is the dataset used in a research paper "Extraction of stratigraphic exposures on visible images using a supervised machine learning technique". The content is <ul> <li>Augmented images used in the U-Net training (aug_images.zip) <ul> <li>train/*.png: augmented original images (14,219 files)</li> <li>train_masks/*.png: augmented hand-masked images (14,219 files).</li> </ul> </li> </ul> Note that original images include images obtained using google-image-download, a Python script published on GitHub (<a href="https://github.com/Joeclinton1/google-images-download/tree/patch-1">https://github.com/Joeclinton1/google-images-download/tree/patch-1</a>, Copyright © 2015-2019 Hardik Vasa). The whole images we obtained by google-image-download were labeled as noncommercial reuse with modification. For more details, please refer to a research paper "Extraction of stratigraphic exposures on visible images using a supervised machine learning technique". Correspondence: Rina Noguchi (r-noguchi@env.sc.niigata-u.ac.jp)

opennotspecifiedFeb 2022View details →

Fig. 2. A in Psilostachyins as trypanocidal compounds: Bioguided fractionation of Ambrosia tenuifolia chemically modified extract

Fig. 2. A) Schematic representation of bioguided separation of CH2Cl2-m-CPBA modified extract of Ambrosia tenuifolia to isolate and identify the main SLs responsible for the trypanocidal activity. B) Percentage of parasite inhibition after treatment with the pools (I-VI) and benznidazole at 5 μg/mL. Asterisks indicate significant differences between the indicated groups and the control, benznidazole (****, p <0.001), and ns indicates no significant differences. C) Percentage of parasite inhibition after treatment at different concentrations (1, 5 and 10 μg/mL) with the pure compounds obtained after chemical extract derivatization. At 1 and 5 μg/mL, only the indicated groups did not exhibit significant differences compared to the respective concentration of benznidazole (ns). At 10 μg/mL, the indicated group showed significant differences compared to benznidazole at the same concentration (****, p <0.001). The molar concentrations equivalent to 1 μg/mL of each compound are 3.8 μM (Psi C and benznidazol) and 3.6 μM (Psi A, paulitin, isopaulitin, 2 and 3), for more details see figure S8.

Fig. 4 in An extensive study on the chemical diversity of lipophilic extractives from Eucalyptus globulus wood

Fig. 4. Radial profile of different chemical families (proportion of chemical families) in the lipophilic DCM along the tree height levels (0%, 35% and 60%) in E. globulus mature wood trees.

Fig. 3 in An extensive study on the chemical diversity of lipophilic extractives from Eucalyptus globulus wood

Fig. 3. Proportion of chemical families in the lipophilic DCM extracts of E. globulus mature wood trees. Average of 36 runs (3 trees × 3 height levels x 2 extractions x 2 injections).

Fig. 2 in An extensive study on the chemical diversity of lipophilic extractives from Eucalyptus globulus wood

Fig. 2. Example of one GC-MS chromatogram of dichloromethane extracts (as TMS derivatives) of Eucalyptus globulus mature wood trees and range of the principal chemical family distribution. Main peaks: 3 - Decanoic acid (C10:0); 5 - Vanillin; 11 - Dodecanoic acid (C12:0); 12 - 4-hydroxy-3,5- dimethoxybenzaldehyde; 13 - homovanillic alcohol; 14 - Vanillic acid; 25 - Syringic acid; 36 - Propiovanillone; 39 - Hexadecanoic acid (C16:0); 52 - Octadeca-9,12-dienoic acid (C18:2); 55 - Octadecanoic acid (C18:0); 66 - ω-hydroxy fatty acid (C18:2); 67 - Icosanoic acid (C20:0) 74 - 1-palmitoylglycerol (G- C16:0); 79 - 2-hydroxy-decane-1,10-dioic acid (C10:0); 86 - Octacosane (C28); 90 -Tetracosanoic acid; 94 - Hexacosan-1-ol (C26); 102 - a-tocopherol; 109 - campesterol; 115 - tritriacontane (C33); 118 - β-Sitosterol; 123 - 2-tetracosanoylglycerol (G-C24:0); 140 - Betulinic acid isomer; 146 - 1-hexacosanoylglycerol (G-C26:0); 147 - Ursolic acid; 161 - Arjunolic acid; 162 - Asiatic acid; 168 - sitosteryl 3-β-D-glucopyranoside. All the identified peaks are listed in Tables 1–6

Fig. 1 in An extensive study on the chemical diversity of lipophilic extractives from Eucalyptus globulus wood

Fig. 1. Schematic drawing of sapwood heartwood outer and inner in the stems of E. globulus trees harvested for these study. Heartwood area and extractives content (average of three trees ± STDEV) (Adapted from Gominho et al., 2015).

Effect of Herbal Extracts on the Survival of Staphylococcus aureus in Goats' Raw Milk Cheese

Presented as e-Poster Flash Presentation; and in Book of Abstracts of the International Seminar ArtiSaneFood - Biopreservation and Risk Modelling Approaches. Bragança, Portugal (24-25 May 2023) (Page 54).

opennotspecifiedFeb 2023View details →

Fig. 11 in Biological activities of organic extracts and specialized metabolites from different parts of Cryptomeria japonica (Cupressaceae) - A critical review

Fig. 11. Lignans (27–33, 35 and 36), norlignans (34, 37 and 38) and anthraquinone (58) from Cryptomeria japonica biomass residues.

opennotspecifiedFeb 2023View details →

Fig. 7 in Biological activities of organic extracts and specialized metabolites from different parts of Cryptomeria japonica (Cupressaceae) - A critical review

Fig. 7. Sesquiterpenes from Cryptomeria japonica biomass residues, including eudesmanes (17 and 48), bisabolanes (18, 47, 49, 50, 56 and 59) and cadinanes (39, 43–46, 52, 57 and 60) types.

opennotspecifiedFeb 2023View details →

Fig. 4 in Biological activities of organic extracts and specialized metabolites from different parts of Cryptomeria japonica (Cupressaceae) - A critical review

Fig. 4. Pimarane (10, 14 and 61) and isopimarane-type diterpenes from Cryptomeria japonica biomass residues.

opennotspecifiedJun 2022View details →

Fig. 3 in Derrisrobustones A-D, isoflavones from the twig extract of Derris robusta (DC.) Benth. and their α-glucosidase inhibitory activity

Fig. 3. ECD spectra of compounds 1–3. (A) Experimental and TDDFT calculated ECD spectra of (+)-(2′′S)-derrisrobustone A and ()-(2′′R)-derrisrobustone A at B3LYP/6311++G(d,p) level in MeOH (CPCM). (B) Experimental ECD spectra of (+)-(1′′R,2′′R)-derrisrobustone B and ()-(1′′S,2′′S)-derrisrobustone B at B3LYP/ 6311++G(d,p) level in MeOH (CPCM). (C) Experimental and TDDFT calculated ECD spectra of (+)-(1′′S,2′′R)-derrisrobustone C and ()-(1′′R,2′′S)-derrisrobustone C.

opennotspecifiedFeb 2022View details →

Fig. 5 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis

Fig. 5. Multivariate statistical analysis results of 9 different types of Panax notoginseng samples. (a) Score scatter plot of 2D PCA model, (b) Score scatter plot of 3D PCA model, (c) Score scatter plot of OPLS-DA model, (d) Bar plot with OPLS-DA model of VIP.