cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7632123
title: Unpaired fast- and slow-acquisition microCT scans of carbon-fibre-reinforced composites

description: data.zip contains tomographic images of carbon-fibre-reinforced composites with Toray T700S fibres in a Sicomin SR8500 KTA313 epoxy matrix.

The datasets accompany the paper Deep-learning image enhancement and fibre segmentation from time-resolved computed tomography of fibre-reinforced composites.

They are used in a two-step process:1) to train a 3DCycleGAN enhancement algorithm available on https://github.com/pvilla/3DCycleGaN.2) to train a UNetID segmentation algorithm available on https://github.com/CMG-KULeuven/UnetID-FibreSeg.

The tomograms were acquired at the TOMCAT Beamline at the Swiss Light Source in October 2021.

Acquisition specifications:

T700_GF_0p8um_1ms:



detector: GigaFRoST

effective voxel size: 800x800x800 nm³

# projections: 500

exposure time: 1 ms

total acquisition time: 500 x 1 ms = 0.5 s

beam: polychromatic

datasets: (same sample, different regions)T700-T-21_GF_0p8um_1ms_1.h5T700-T-21_GF_0p8um_1ms_2.h5T700-T-21_GF_0p8um_1ms_3.h5


T700_GF_1p6um_0p5ms:



detector: GigaFRoST

effective voxel size: 1600x1600x1600 nm³

# projections: 500

exposure time: 0.5 ms

total acquisition time: 500 x 0.5 ms = 0.25 s

beam: polychromatic

files: (same sample, different regions)T700-T-21_GF_1p6um_0p5ms_1.h5T700-T-21_GF_1p6um_0p5ms_2.h5


T700_GF_1p6um_3ms:



detector: GigaFRoST

effective voxel size: 1600x1600x1600 nm³

# projections: 500

exposure time: 3 ms

total acquisition time: 500 x 3 ms = 1.5 s

beam: polychromatic

files: (same sample, different regions)T700-T-21_GF_1p6um_3ms_1.h5T700-T-21_GF_1p6um_3ms_2.h5T700-T-21_GF_1p6um_3ms_3.h5T700-T-21_GF_1p6um_3ms_4.h5T700-T-21_GF_1p6um_3ms_5.h5


T700_pco_0p4um:



detector: pco.edge 5.5

effective voxel size: 400x400x400 nm³ (scaled from 325x325x325 nm³)

# projections: 2000

exposure time: 250 ms

total acquisition time: 2000 x 250 ms = 500 s

beam: 15 keV

files: (different samples)T700-T-02_pco_0p4um.h5T700-T-08_pco_0p4um.h5T700-T-21_pco_0p4um_reference.h5T700-T-26_pco_0p4um.h5


3DCycleGAN_trained_models.zip contains pre-trained models for the 3DCycleGAN enhancement algorithm.

UnetID_trained_models.zip contains pre-trained models for the UNetID segmentation algorithm.
DOI: 10.5281/zenodo.7632124
title: Unpaired fast- and slow-acquisition microCT scans of carbon-fibre-reinforced composites

description: data.zip contains tomographic images of carbon-fibre-reinforced composites with Toray T700S fibres in a Sicomin SR8500 KTA313 epoxy matrix.

The datasets accompany the paper Deep-learning image enhancement and fibre segmentation from time-resolved computed tomography of fibre-reinforced composites.

They are used in a two-step process:1) to train a 3DCycleGAN enhancement algorithm available on https://github.com/pvilla/3DCycleGaN.2) to train a UNetID segmentation algorithm available on https://github.com/CMG-KULeuven/UnetID-FibreSeg.

The tomograms were acquired at the TOMCAT Beamline at the Swiss Light Source in October 2021.

Acquisition specifications:

T700_GF_0p8um_1ms:



detector: GigaFRoST

effective voxel size: 800x800x800 nm³

# projections: 500

exposure time: 1 ms

total acquisition time: 500 x 1 ms = 0.5 s

beam: polychromatic

datasets: (same sample, different regions)T700-T-21_GF_0p8um_1ms_1.h5T700-T-21_GF_0p8um_1ms_2.h5T700-T-21_GF_0p8um_1ms_3.h5


T700_GF_1p6um_0p5ms:



detector: GigaFRoST

effective voxel size: 1600x1600x1600 nm³

# projections: 500

exposure time: 0.5 ms

total acquisition time: 500 x 0.5 ms = 0.25 s

beam: polychromatic

files: (same sample, different regions)T700-T-21_GF_1p6um_0p5ms_1.h5T700-T-21_GF_1p6um_0p5ms_2.h5


T700_GF_1p6um_3ms:



detector: GigaFRoST

effective voxel size: 1600x1600x1600 nm³

# projections: 500

exposure time: 3 ms

total acquisition time: 500 x 3 ms = 1.5 s

beam: polychromatic

files: (same sample, different regions)T700-T-21_GF_1p6um_3ms_1.h5T700-T-21_GF_1p6um_3ms_2.h5T700-T-21_GF_1p6um_3ms_3.h5T700-T-21_GF_1p6um_3ms_4.h5T700-T-21_GF_1p6um_3ms_5.h5


T700_pco_0p4um:



detector: pco.edge 5.5

effective voxel size: 400x400x400 nm³ (scaled from 325x325x325 nm³)

# projections: 2000

exposure time: 250 ms

total acquisition time: 2000 x 250 ms = 500 s

beam: 15 keV

files: (different samples)T700-T-02_pco_0p4um.h5T700-T-08_pco_0p4um.h5T700-T-21_pco_0p4um_reference.h5T700-T-26_pco_0p4um.h5


3DCycleGAN_trained_models.zip contains pre-trained models for the 3DCycleGAN enhancement algorithm.

UnetID_trained_models.zip contains pre-trained models for the UNetID segmentation algorithm.
DOI: 10.6084/m9.figshare.26719164.v1
title: Additional file 6 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.26719155.v1
title: Additional file 3 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.26719158
title: Additional file 4 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 4.
DOI: 10.6084/m9.figshare.26719158.v1
title: Additional file 4 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 4.
DOI: 10.15468/u75js2
title: Two new species of Trichodrilus (Annelida, Clitellata, Lumbriculidae) from Pacific drainages, western USA

description: This dataset contains the digitized treatments in Plazi based on the original journal article Fend, Steven, Rodriguez, Pilar (2024): Two new species of Trichodrilus (Annelida, Clitellata, Lumbriculidae) from Pacific drainages, western USA. Zootaxa 5551 (1): 141-156, DOI: 10.11646/zootaxa.5551.1.6, URL: https://doi.org/10.11646/zootaxa.5551.1.6AbstractTwo new species of Lumbriculidae attributed to the mostly-Palearctic genus Trichodrilus Claparède, 1862 are described from Pacific drainages in western North America. Trichodrilus baylesi sp. nov., from Fall Creek (Willamette River drainage, Oregon) has petiolate atria and one pair of spermathecae, in segment XI; it is distinguished from congeners by the spherical atrial ampullae and large, pendant penes in deep sacs. Trichodrilus humptulips, from the Humptulips River (Washington) has paired spermathecae in XI and XII and club-shaped atria, basally joined by thin vasa deferentia which open to the atrial lumen subapically, and without complex penes. The new descriptions increase the confirmed North American Trichodrilus fauna to 4 species, but limited collections from other regions suggest that the North American Trichodrilus fauna is more diverse.
DOI: 10.6084/m9.figshare.26719170.v1
title: Additional file 8 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 8.
DOI: 10.6084/m9.figshare.26719173
title: Additional file 9 of The MYB family and their response to abiotic stress in ginger (Zingiber officinale Roscoe)

description: Supplementary Material 9.
DOI: 10.6084/m9.figshare.26720982.v1
title: Additional file 1 of Association between urinary phthalate metabolites and renal function in late pregnant women

description: Additional file 1: Figure S1. Flowchart. Table S1. Varimax-rotated factor loadings of phthalate metabolites in PCA. Table S2. Retention time, ion pair, collision energy, determination coefficient, recovery rate, and detection limit of each metabolite. Table S3. Stratified regression analysis of the association of MEHP and MEHHP with eGFR (n = 851). Table S4. Association of urinary phthalate metabolites with SUA in pregnant women without hyperuricemia and abnormal blood creatinine levels (N=770). Table S5. Association of urinary phthalate metabolites with eGFR in pregnant women without hyperuricemia and abnormal blood creatinine levels (N=770). Table S6. Association of urinary phthalate metabolites with SUA in pregnant women(N=851). Table S7. Association of urinary phthalate metabolites with eGFR in the pregnant women(N=851). Table S8. Association of urinary phthalate metabolites with SUA in pregnant women (N=851). Table S9. Association of urinary phthalate metabolites with SUA in pregnant women (N=851). Table S10. Association of urinary phthalate metabolites with UA in pregnant women (N=851). Table S11. Association of urinary phthalate metabolites with eGFR in pregnant women (N=851). Table S12. Association of urinary phthalate metabolites with eGFR in pregnant women (N=851). Excluded MIBP. Table S13. Association of urinary phthalate metabolites with UA in pregnant women (N=851). Excluded MBP.
DOI: 10.15468/dl.ztmrjj
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.09776 -34.397189, 148.09776 -34.399435, 148.093269 -34.399435, 148.093269 -34.406173, 148.095514 -34.406173, 148.095514 -34.401681, 148.100006 -34.401681, 148.100006 -34.397189, 148.09776 -34.397189))"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071119-240626123714530/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.26719335
title: Additional file 2 of Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

description: Additional file 2: S1. Known Marker. S2. GWAS genes for each cancer from DisGeNET database.
DOI: 10.6084/m9.figshare.26723130.v1
title: Additional file 1 of Study on the causes of changes in colour during Hibiscus syriacus flowering based on transcriptome and metabolome analyses

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26719335.v1
title: Additional file 2 of Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

description: Additional file 2: S1. Known Marker. S2. GWAS genes for each cancer from DisGeNET database.
DOI: 10.6084/m9.figshare.26721042
title: Additional file 2 of Online dissemination of Cochrane reviews on digital health technologies: a cross-sectional study

description: Additional file 2. Search strategy.
DOI: 10.5281/zenodo.13324661
title: Implementation and Results of a "Frequency Fitness Assignment: Optimization without Bias for Good Solution outperforms Randomized Local Search on the Quadratic Assignment Problem"

description: 1. Introduction

In this archive, we provide the implementation and experimental results of a Randomized Local Search (RLS) with and without FFA applied to the Quadratic Assignment Problem. These are the data used in the paper below, which contains the exact specification of all algorithms, objective functions, and the encoding we applied.

Jiayang Chen, Zhize Wu, Sarah L. Thomson, and Thomas Weise. Frequency Fitness Assignment: Optimization without Bias for Good Solution outperforms Randomized Local Search on the Quadratic Assignment Problem. In 16th International Conference on Evolutionary Computation Theory and Applications (ECTA'24), part of the 16th International Joint Conference on Computational Intelligence (IJCCI'24). November 20-24, 2024. Porto, Portugal. Setúbal, Portugal: SciTePress.

To run the experiments, you need moptipyapps and moptipy, which contain the actual algorithm implementations. Both packages are available on GitHub and on PyPI. However, we include several versions of them in the folder source/packages, just in case.

2. Directory Structure

This archive contains the following directories:



source contains the Python source codes needed to run the experiment.

source/packages contains the source codes of the Python packages with the actual algorithm implementations.

source/experiment_execution_scripts contains the scripts to run the experiments.

results is the directory with the results, i.e., with the log files generated by the experiment.

evaluator is the folder containing Python scripts that were used to evaluate these results.

evaluation was generated using the evaluation scripts and contains tables and figures and a result summary in CSV format.


3. License

The files in this repository are under the Creative Commons Attribution 4.0 International, with the exception of the benchmark datasets included, which are under copyright of their respective owner (we believe that they are in the public domain, as they are provided by many sources, included in many software packages under various open source licenses, and on many websites). The license is contained as file LICENSE.txt in this archive.

4. Contact

If you have any questions or suggestions, please contact

Mr. Jiayang CHEN (陈嘉阳) of the Institute of Applied Optimization (应用优化研究所, IAO) of the School of Artificial Intelligence and Big Data (人工智能与大数据学院) at Hefei University (合肥大学) in Hefei, Anhui, China (中国安徽省合肥市) via email to cjy65820607@163.com.
DOI: 10.5281/zenodo.13324662
title: Implementation and Results of a "Frequency Fitness Assignment: Optimization without Bias for Good Solution outperforms Randomized Local Search on the Quadratic Assignment Problem"

description: 1. Introduction

In this archive, we provide the implementation and experimental results of a Randomized Local Search (RLS) with and without FFA applied to the Quadratic Assignment Problem. These are the data used in the paper below, which contains the exact specification of all algorithms, objective functions, and the encoding we applied.

Jiayang Chen, Zhize Wu, Sarah L. Thomson, and Thomas Weise. Frequency Fitness Assignment: Optimization without Bias for Good Solution outperforms Randomized Local Search on the Quadratic Assignment Problem. In 16th International Conference on Evolutionary Computation Theory and Applications (ECTA'24), part of the 16th International Joint Conference on Computational Intelligence (IJCCI'24). November 20-24, 2024. Porto, Portugal. Setúbal, Portugal: SciTePress.

To run the experiments, you need moptipyapps and moptipy, which contain the actual algorithm implementations. Both packages are available on GitHub and on PyPI. However, we include several versions of them in the folder source/packages, just in case.

2. Directory Structure

This archive contains the following directories:



source contains the Python source codes needed to run the experiment.

source/packages contains the source codes of the Python packages with the actual algorithm implementations.

source/experiment_execution_scripts contains the scripts to run the experiments.

results is the directory with the results, i.e., with the log files generated by the experiment.

evaluator is the folder containing Python scripts that were used to evaluate these results.

evaluation was generated using the evaluation scripts and contains tables and figures and a result summary in CSV format.


3. License

The files in this repository are under the Creative Commons Attribution 4.0 International, with the exception of the benchmark datasets included, which are under copyright of their respective owner (we believe that they are in the public domain, as they are provided by many sources, included in many software packages under various open source licenses, and on many websites). The license is contained as file LICENSE.txt in this archive.

4. Contact

If you have any questions or suggestions, please contact

Mr. Jiayang CHEN (陈嘉阳) of the Institute of Applied Optimization (应用优化研究所, IAO) of the School of Artificial Intelligence and Big Data (人工智能与大数据学院) at Hefei University (合肥大学) in Hefei, Anhui, China (中国安徽省合肥市) via email to cjy65820607@163.com.
DOI: 10.15468/dl.x7s3ae
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.257212 -34.399435, 148.257212 -34.401681, 148.259458 -34.401681, 148.259458 -34.399435, 148.257212 -34.399435))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071120-240626123714530/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.26722734
title: Additional file 3 of Adipose stem cells-derived small extracellular vesicles transport Thrombospondin 1 cargo to promote insulin resistance in gestational diabetes mellitus

description: Additional file 3. Supplementary Table 1. Primer sequences for RT-PCR.
DOI: 10.6084/m9.figshare.26722374
title: Additional file 7 of Ethylene promotes fruit ripening initiation by downregulating photosynthesis, enhancing abscisic acid and suppressing jasmonic acid in blueberry (Vaccinium ashei)

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.26722362.v1
title: Additional file 3 of Ethylene promotes fruit ripening initiation by downregulating photosynthesis, enhancing abscisic acid and suppressing jasmonic acid in blueberry (Vaccinium ashei)

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26722371
title: Additional file 6 of Ethylene promotes fruit ripening initiation by downregulating photosynthesis, enhancing abscisic acid and suppressing jasmonic acid in blueberry (Vaccinium ashei)

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26721966
title: Additional file 2 of Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.26721963
title: Additional file 1 of Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.26719008
title: Additional file 1 of Optimal trade-off between boosted tolerance and growth fitness during adaptive evolution of yeast to ethanol shocks

description: Supplementary Material 1: Table S1. List of Saccharomyces cerevisiae strains. Table listing all S. cerevisiae strains used in this study, including parental strains, evolved clones, and genetically-modified yeasts. Table S2. Flow cytometry measurements in competitions with 24% v/v ethanol treatments. The proportion of each competitor is shown before (initial) and after the 24% ethanol treatment and outgrowth (final). Selection coefficients were calculated (S) and normalized with the data obtained for the progenitor. Two datasets were generated: one for the Progenitor, P1c, P2c, P3c without acclimation, and other with the same strains subjected to prior acclimation with ethanol shocks (see text). The data was used to generate the graphics of Fig. 1C and D. Table S3. Results from WGS and variant calling of P1c, P2c, P3c, and P4c. Mutations found in the evolved clones are shown. Coordinates are related to the PE-2_H4 parental strain (GenBank accession number GCA_905220315.1). Table S4. PCR oligonucleotides used in this study. Table S5. Flow cytometry measurements for competition assays 1–3. Data from competitions 1 (green), 2 (red), and 3 (blue) display the proportions of tester-GFP and the indicated competitor at the initial and final points of the assay. Selection coefficients (S) were calculated and normalized with the S obtained for the respective parental strain. For competitions 2 and 3 the S was expressed per cell doubling. Table S6. Microplate growth assay. OD600 was recorded every 15 min. on the Tecan Sunrise™ microplate reader. Each Strain was assayed in 3–4 replicates in YPS with 8% (v/v) ethanol, or in YPS without ethanol. Table S7. Fitness estimations for cyr1A1474T/usv1Δ. The PE-2_H4 (parental) and cyr1A1474T/usv1Δ were competed against the PE-2_H4-GFP through five passages in YPS with 8% (v/v) ethanol or without ethanol. Flow cytometry records of the competitors’ proportions and cell counting were taken at the initial and final points of each transfer, allowing the calculation of selection coefficients (S) during each passage and a cumulative S during serial transfers 2–5. By plotting the cumulative S per number of calculated generations at the end of each passage, selective coefficients per cell doublings (S/d) were calculated from the trendline fitted into the data points. Thereby an S per doubling was calculated for PE-2_H4 as -0.0079 for the competition with the PE-2_H4-GFP at 8% (v/v) ethanol and as 0.0049 for the competition in YPS without ethanol. Based on these numbers, a “S correction factor for PE-2_H4” was calculated accounting for cumulative cell doublings at each passage and used to normalize the cumulative S obtained for cyr1A1474T/usv1Δ in a competition with PE-2_H4_GFP. This normalization allows to express the cyr1A1474T/usv1Δ fitness (S) in comparison to PE-2_H4 and to discount any fitness effect of GFP expression in the PE-2_H4-GFP strain. The normalized cumulative S for cyr1A1474T/usv1Δ was plotted in Fig. 6C.
DOI: 10.6084/m9.figshare.26721084
title: Additional file 1 of Combining germline, tissue and liquid biopsy analysis by comprehensive genomic profiling to improve the yield of actionable variants in a real-world cancer cohort

description: Additional file 1. Genes and their alterations types covered by next-generation sequencing panels used in the study. The genes and their alterations covered by TruSight Oncology 500 tumor/ctDNA panel and TruSight Hereditary Cancer Panel are shown. The private genes and the common genes included in each next-generation sequencing panels used are also indicated.
DOI: 10.6084/m9.figshare.26721084.v1
title: Additional file 1 of Combining germline, tissue and liquid biopsy analysis by comprehensive genomic profiling to improve the yield of actionable variants in a real-world cancer cohort

description: Additional file 1. Genes and their alterations types covered by next-generation sequencing panels used in the study. The genes and their alterations covered by TruSight Oncology 500 tumor/ctDNA panel and TruSight Hereditary Cancer Panel are shown. The private genes and the common genes included in each next-generation sequencing panels used are also indicated.
DOI: 10.6084/m9.figshare.26721393.v1
title: Additional file 2 of Ethical considerations and concerns in the implementation of AI in pharmacy practice: a cross-sectional study

description: Supplementary Material 2
DOI: 10.5281/zenodo.13329011
title: Lithospheric structure and strength variations in Antarctica from joint modeling of elevation, geoid and seismic data

description: These models include Moho depth, LAB depth and integrated lithospheric strength based on a 1D approach involving thermal analysis under local isostasy and a rheological method.
DOI: 10.5281/zenodo.13329012
title: Lithospheric structure and strength variations in Antarctica from joint modeling of elevation, geoid and seismic data

description: These models include Moho depth, LAB depth and integrated lithospheric strength based on a 1D approach involving thermal analysis under local isostasy and a rheological method.
DOI: 10.15468/dl.vc5aq5
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.621031 -34.399435, 148.621031 -34.401681, 148.625523 -34.401681, 148.625523 -34.399435, 148.621031 -34.399435)), ((148.625523 -34.401681, 148.625523 -34.406173, 148.630014 -34.406173, 148.630014 -34.401681, 148.625523 -34.401681)), ((148.630014 -34.401681, 148.636752 -34.401681, 148.636752 -34.399435, 148.630014 -34.399435, 148.630014 -34.401681)), ((148.636752 -34.401681, 148.636752 -34.406173, 148.641243 -34.406173, 148.641243 -34.408418, 148.643489 -34.408418, 148.643489 -34.401681, 148.636752 -34.401681)))"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071121-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.