cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5063/28061r
title: Compiled statewide Alaskan daily salmon escapement counts, 1922-2017

description: As salmon migrate from the marine environment to freshwater streams to spawn, a certain number are allowed to pass through, or 'escape' the salmon fishery (frequently located near the mouth of the freshwater stream) as a management strategy to preserve the species. Escapement data are the enumeration of these migrating fish as they pass upstream, and represent an index of the total abundance of spawning salmon in that particular stream. These data are important for fisheries management, since most salmon harvest occurs in freshwater rivers during this migration. Escapement data are collected in a variety of ways. Stationary projects utilize observers stationed along freshwater corridors who count salmon as they pass upriver through weirs or past elevated towers. Sonar equipment placed in the river can also give a stationary escapement count. These counts usually represent a sample, and are expanded to represent a 24h period. Escapement data can also be collected using aerial surveys, where observers in an aircraft provide an index to estimate escapement. In general, escapement counts do not represent total abundance, but instead an index of abundance. Surveys are usually timed to coincide with peak spawning activity, generally in the summer, but in the case of Coho salmon in the fall as well. Some data about non-salmon species are also included. This dataset contains compiled data from a number of sources. The .Rmd merges all datasets, identifies and flags duplicate records, and performs quality assurance checks by filtering and graphing results. These escapement data are merged with a location dataset ('Escapement_locations.csv') to connect escapement counts with detailed information about the sampling locations.This merged dataset is stored as 'Escapement_locations_linked.csv
DOI: 10.5281/zenodo.5192130
title: Parametric 3D CAD model of human foot

description: The parametric 3D CAD model of human foot was developed from CT data. A CT (Toshiba® Aquilion 4 equipment) scan was performed on a 29 years old male (65 Kg). 345 slices were captured with a slice distance of 1.0 mm (see Figure 2.a). Scans were made for both feet in their neutral posture in which there is the least tension or pressure on tendons, muscles and bones. Medical images were, then, exported into standard .DICOM format (image resolution 512x512 pixels) and processed by using ScanIP® and SolidWorks. Bone structure was composed of 19 bones: tibia, fibula, talus, calcaneus, cuboid, navicular, 3 cuneiforms (bones of the metatarsus), 5 metatarsals (bones of the metatarsus) and 5 components of the phalanges (bones of the toes). Phalange bones (a proximal and a distal phalanx for the great toe; proximal, middle and distal phalanges for the second to fifth toes) were fused together since their relative motion do not affect plantar pressures. More details can be found in the publications below: <strong>Franciosa, P.</strong>, Gerbino S., From CT Scan to Plantar Pressure Map Distribution of a 3D Anatomic Human Foot, in Proc. of COMSOL Conference’10, Paris (France), November 17-19, 2010. <strong>Franciosa, P.</strong>, Gerbino, S., Lanzotti A., Silvestri L., Improving Comfort of Shoe Sole through Experiments based on CAD-FEM Modeling, Medical Engineering and Physics, doi:10.1016/j.medengphy.2012.03.007, 2013.
DOI: 10.5281/zenodo.5192129
title: Parametric 3D CAD model of human foot

description: The parametric 3D CAD model of human foot was developed from CT data. A CT (Toshiba® Aquilion 4 equipment) scan was performed on a 29 years old male (65 Kg). 345 slices were captured with a slice distance of 1.0 mm (see Figure 2.a). Scans were made for both feet in their neutral posture in which there is the least tension or pressure on tendons, muscles and bones. Medical images were, then, exported into standard .DICOM format (image resolution 512x512 pixels) and processed by using ScanIP® and SolidWorks. Bone structure was composed of 19 bones: tibia, fibula, talus, calcaneus, cuboid, navicular, 3 cuneiforms (bones of the metatarsus), 5 metatarsals (bones of the metatarsus) and 5 components of the phalanges (bones of the toes). Phalange bones (a proximal and a distal phalanx for the great toe; proximal, middle and distal phalanges for the second to fifth toes) were fused together since their relative motion do not affect plantar pressures. More details can be found in the publications below: <strong>Franciosa, P.</strong>, Gerbino S., From CT Scan to Plantar Pressure Map Distribution of a 3D Anatomic Human Foot, in Proc. of COMSOL Conference’10, Paris (France), November 17-19, 2010. <strong>Franciosa, P.</strong>, Gerbino, S., Lanzotti A., Silvestri L., Improving Comfort of Shoe Sole through Experiments based on CAD-FEM Modeling, Medical Engineering and Physics, doi:10.1016/j.medengphy.2012.03.007, 2013.
DOI: 10.5281/zenodo.5185901
title: Himawari-8 Cloud-top phase products

description: This product is derived from a decision tree algorithm for advanced Himawari imager (AHI) observations, and it provides cloud-top phase (temperature) on each AHI pixel. The cloud-top is distinguished as liquid water, ice, and mixed phases, and further classed into clear (or probably clear, probably cloudy), water, supercooled, mixed, thick ice, cirrus, overlap and overshooting in conjunction with the cloud-top height and optical thickness. The original product is a full-disk data with highest resolution of 2 km at the sub-satellite point (140.7 °E), then it is projected to equal-longitude-latitude grids (110-150°E, 10-50°N) and with resolution of 0.1°×0.1°, while the temporal resolution is 30 minutes. In the dataset, CldHeight means Cloud-top height from ACHA algorithm; CldTemperature means Cloud-top temperature from ACHA algorithm; CldType means Cloud types (clear=0, probably_clear=1, probably_cloudy=2, water=3, supercooled=4, mixed=5, Thick Ice=6, cirrus=7, overlap=8, overshooting=9) Data is stored as a binary matrix (401*401) corresponding to the domain of (110-150°E, 10-50°N),with a Header(128 byte).
description: {"references": ["Zhuge, X., Zou, X. & Wang, Y. (2021). Determining AHI Cloud-top Phase and Intercomparisons with Modis Products over North Pacific. IEEE Transactions on Geoscience and Remote Sensing, 59(1), 436-448. doi: https://doi.org/10.1109/TGRS.2020.2990955"]}
DOI: 10.5281/zenodo.5185900
title: Himawari-8 Cloud-top phase products

description: This product is derived from a decision tree algorithm for advanced Himawari imager (AHI) observations, and it provides cloud-top phase (temperature) on each AHI pixel. The cloud-top is distinguished as liquid water, ice, and mixed phases, and further classed into clear (or probably clear, probably cloudy), water, supercooled, mixed, thick ice, cirrus, overlap and overshooting in conjunction with the cloud-top height and optical thickness. The original product is a full-disk data with highest resolution of 2 km at the sub-satellite point (140.7 °E), then it is projected to equal-longitude-latitude grids (110-150°E, 10-50°N) and with resolution of 0.1°×0.1°, while the temporal resolution is 30 minutes. In the dataset, CldHeight means Cloud-top height from ACHA algorithm; CldTemperature means Cloud-top temperature from ACHA algorithm; CldType means Cloud types (clear=0, probably_clear=1, probably_cloudy=2, water=3, supercooled=4, mixed=5, Thick Ice=6, cirrus=7, overlap=8, overshooting=9) Data is stored as a binary matrix (401*401) corresponding to the domain of (110-150°E, 10-50°N),with a Header(128 byte).
description: {"references": ["Zhuge, X., Zou, X. & Wang, Y. (2021). Determining AHI Cloud-top Phase and Intercomparisons with Modis Products over North Pacific. IEEE Transactions on Geoscience and Remote Sensing, 59(1), 436-448. doi: https://doi.org/10.1109/TGRS.2020.2990955"]}
DOI: 10.5281/zenodo.5192368
title: Semeval2020_sampled_pairs

description: 20000 and 300 pairs for word. SemEval 2020
DOI: 10.5281/zenodo.5177286
title: Semeval2020_sampled_pairs

description: 20000 and 300 pairs for word. SemEval 2020
DOI: 10.5281/zenodo.5192278
title: Data and analysis for the paper Qubits made by advanced semiconductor manufacturing

description: Data and analysis scripts for the paper: Qubits made by advanced semiconductor manufacturing by A.M.J. Zwerver,<em> et al.</em>
DOI: 10.5281/zenodo.5192277
title: Data and analysis for the paper Qubits made by advanced semiconductor manufacturing

description: Data and analysis scripts for the paper: Qubits made by advanced semiconductor manufacturing by A.M.J. Zwerver,<em> et al.</em>
DOI: 10.5281/zenodo.5191798
title: Central de Fatos

description: In recent times, the interest for research dissecting the dissemination and prevention of misinformation in the online environment has spiked dramatically. Given that scenario, a recurring obstacle is the unavailability of public datasets containing fact-checked instances. In this work, we performed an extensive data collection of such instances from the better part of all major internationally recognized Brazilian fact-checking agencies. Particularly, this paper offers the research community a novel dataset containing fact-checks from various trustworthy sources regarding a wide range of topics. In total, the resulting collection encompasses 11647 fact-check instances collected across 6 different agencies that can be used for several studies in the contexts of identifying and combating misinformation on digital platforms in Brazil.
DOI: 10.5281/zenodo.5191797
title: Central de Fatos

description: In recent times, the interest for research dissecting the dissemination and prevention of misinformation in the online environment has spiked dramatically. Given that scenario, a recurring obstacle is the unavailability of public datasets containing fact-checked instances. In this work, we performed an extensive data collection of such instances from the better part of all major internationally recognized Brazilian fact-checking agencies. Particularly, this paper offers the research community a novel dataset containing fact-checks from various trustworthy sources regarding a wide range of topics. In total, the resulting collection encompasses 11647 fact-check instances collected across 6 different agencies that can be used for several studies in the contexts of identifying and combating misinformation on digital platforms in Brazil.
DOI: 10.5517/ccdc.csd.cc27s4ry
title: CCDC 2078790: Experimental Crystal Structure Determination

description: Related Article: Ruifang Cui, Rui Li, Zheng Li, Mingming Wei, Xiong Wang, Xia Li|2021|Dyes Pigm.|195|109669|doi:10.1016/j.dyepig.2021.109669
DOI: 10.5517/ccdc.csd.cc27stkf
title: CCDC 2079435: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stlg
title: CCDC 2079436: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stmh
title: CCDC 2079437: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stnj
title: CCDC 2079438: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stpk
title: CCDC 2079439: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stql
title: CCDC 2079440: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27strm
title: CCDC 2079441: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stsn
title: CCDC 2079442: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27sttp
title: CCDC 2079443: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stvq
title: CCDC 2079444: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc27stwr
title: CCDC 2079445: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf,  Udo Radius,  Maik Finze|2021|Angew.Chem.,Int.Ed.|60|17974|doi:10.1002/anie.202105529
DOI: 10.5517/ccdc.csd.cc25v6x5
title: CCDC 2021197: Experimental Crystal Structure Determination

description: Related Article: Nels T. Anderson, Joseph C. Wright, Gregory S. Girolami|2021|Inorg.Chem.|60|11164|doi:10.1021/acs.inorgchem.1c01139
DOI: 10.5517/ccdc.csd.cc27vjh4
title: CCDC 2081076: Experimental Crystal Structure Determination

description: Related Article: Jaruwan Amtawong, Bastian Bjerkem Skjelstad, Rex C. Handford, Benjamin A. Suslick, David Balcells, T. Don Tilley|2021|J.Am.Chem.Soc.|143|12108|doi:10.1021/jacs.1c04069
DOI: 10.5517/ccdc.csd.cc27vjj5
title: CCDC 2081077: Experimental Crystal Structure Determination

description: Related Article: Jaruwan Amtawong, Bastian Bjerkem Skjelstad, Rex C. Handford, Benjamin A. Suslick, David Balcells, T. Don Tilley|2021|J.Am.Chem.Soc.|143|12108|doi:10.1021/jacs.1c04069
DOI: 10.5517/ccdc.csd.cc27vrwr
title: CCDC 2081305: Experimental Crystal Structure Determination

description: Related Article: Jin Choi, Gabriele Laudadio, Edouard Godineau, Phil S. Baran|2021|J.Am.Chem.Soc.|143|11927|doi:10.1021/jacs.1c05278
DOI: 10.5517/ccdc.csd.cc27yljb
title: CCDC 2084022: Experimental Crystal Structure Determination

description: Related Article: Tiago F. C. Cruz, Cláudia A. Figueira, Luís F. Veiros, Pedro T. Gomes|2021|Organometallics|40|2594|doi:10.1021/acs.organomet.1c00297
DOI: 10.5517/ccdc.csd.cc27ylkc
title: CCDC 2084023: Experimental Crystal Structure Determination

description: Related Article: Tiago F. C. Cruz, Cláudia A. Figueira, Luís F. Veiros, Pedro T. Gomes|2021|Organometallics|40|2594|doi:10.1021/acs.organomet.1c00297
DOI: 10.5517/ccdc.csd.cc27ylld
title: CCDC 2084024: Experimental Crystal Structure Determination

description: Related Article: Tiago F. C. Cruz, Cláudia A. Figueira, Luís F. Veiros, Pedro T. Gomes|2021|Organometallics|40|2594|doi:10.1021/acs.organomet.1c00297
DOI: 10.5517/ccdc.csd.cc27ylmf
title: CCDC 2084025: Experimental Crystal Structure Determination

description: Related Article: Tiago F. C. Cruz, Cláudia A. Figueira, Luís F. Veiros, Pedro T. Gomes|2021|Organometallics|40|2594|doi:10.1021/acs.organomet.1c00297
DOI: 10.5517/ccdc.csd.cc280jsm
title: CCDC 2085890: Experimental Crystal Structure Determination

description: Related Article: Daniel N. Huh, Asim Maity, Gerard P. Van Trieste, Nathan D. Schley, David C. Powers, Ian A. Tonks|2021|Polyhedron|207|115368|doi:10.1016/j.poly.2021.115368
DOI: 10.5517/ccdc.csd.cc280jtn
title: CCDC 2085891: Experimental Crystal Structure Determination

description: Related Article: Daniel N. Huh, Asim Maity, Gerard P. Van Trieste, Nathan D. Schley, David C. Powers, Ian A. Tonks|2021|Polyhedron|207|115368|doi:10.1016/j.poly.2021.115368
DOI: 10.5517/ccdc.csd.cc280jvp
title: CCDC 2085892: Experimental Crystal Structure Determination

description: Related Article: Daniel N. Huh, Asim Maity, Gerard P. Van Trieste, Nathan D. Schley, David C. Powers, Ian A. Tonks|2021|Polyhedron|207|115368|doi:10.1016/j.poly.2021.115368
DOI: 10.5517/ccdc.csd.cc26f9cb
title: CCDC 2038571: Experimental Crystal Structure Determination

description: Related Article: Biplab Keshari Pandia, Chidambaram Gunanathan|2021|J.Org.Chem.|86|9994|doi:10.1021/acs.joc.1c00685
DOI: 10.5517/ccdc.csd.cc280smq
title: CCDC 2086133: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5517/ccdc.csd.cc280snr
title: CCDC 2086134: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5517/ccdc.csd.cc280sps
title: CCDC 2086135: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5517/ccdc.csd.cc280sqt
title: CCDC 2086136: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5517/ccdc.csd.cc280srv
title: CCDC 2086137: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5517/ccdc.csd.cc280ssw
title: CCDC 2086138: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, Zheng Yin, Xiao-Ting Hu, Zhi-Yue Dong, Ming-Hua Zeng|2021|Inorg.Chem.Commun.|131|108758|doi:10.1016/j.inoche.2021.108758
DOI: 10.5281/zenodo.5192849
title: Neurally Relevant BOLD Response Delay: Intermediary Dataset

description: BOLD fMRI timeseries from V1 voxels, extracted from preprocessed BOLD volume timeseries. Accompanying a scientific article to be submitted to Neuroimage. Code will follow.
DOI: 10.5281/zenodo.5183027
title: Neurally Relevant BOLD Response Delay: Intermediary Dataset

description: BOLD fMRI timeseries from V1 voxels, extracted from preprocessed BOLD volume timeseries. Accompanying a scientific article to be submitted to Neuroimage. Code will follow.
DOI: 10.17632/r6vh2rfnts.1
title: Immunoglobulin heavy constant gamma gene evolution is modulated by both the divergent and birth-and-death evolutionary models

description: Immunoglobulin heavy constant gamma (Igγ) gene, CDS and amino acid sequences alignment from 38 primates species
DOI: 10.17632/p65tkrr89v.1
title: Empirical analysis of eukaryotic ER signal peptides

description: Content: - An excel file containing sequences from all experimentally verified eukaryotic signal peptides available on UniProtKB in May 2021, (as well as all human signal peptide sequences &gt;60 amino acids and selected cases from the literature), and probabilities for their respective n-, h-, and c-regions. - Signal peptide sequences were automatically extracted, and subjected to region probability prediction by the Hidden Markov models algorithm in SignalP 3.0. Additionally, all human entries were subjected to manual curation, whereby adjacent hydrophobic stretches were added to the h-region. - The data contains the following information content for 1,492 entries: UniProtKb identifier, review status, protein name, organism, taxonomic lineage, full protein sequence, experimental signal peptide sequence, experimental signal peptide length, predicted n-region sequence and length, predicted h-region sequence and length, predicted c-region sequence and length, experimental cleavage site, predicted cleavage site, difference between predicted and experimental cleavage site, prediction probability, author comment. Also contains the raw data pulled from UniProtKb and the raw output from SignalP 3.0. - The data has been separated into subsets with different cleavage site predictions and probabilities as well as different evolutionary lineages (found in different tabs of the excel file). The following tabs can be found: Summary; Cleavage site identical to experimental; Cleavage site different from experimental; Low probability; Humans (identical cleavage site); Humans (manually curated); Very long SPs; Vertebrates (identical cleavage site); Protostomes (identical cleavage site); Plants (identical cleavage site); Fungi(identical cleavage site). For each subset, the average and median length, standard deviation, and minimal/maximal length for each region are reported. Implications of the data: - The data shows that the length of eukaryotic h-regions is, by average and mean, 11 amino acids, with a maximum length of 14 amino acids for high-probability predictions (&gt;0.5). This is considerably shorter than the hydrophobic segments of non-cleaved transmembrane helices. - Further, the data show that the bulk of length variation in eukaryotic signal peptides stems from the h-region. - A substantial subset (19%) of the data show a different predicted and reported experimental cleavage site, for unclear reasons.
DOI: 10.17632/vfd7m2x38k.1
title: Dog behaviour activity day/night

description: Tallied observations of nocturnal and diurnal behaviour dogs.
DOI: 10.17632/yxxcxsm2d2.1
title: Data for: Zircon surface ages for the Millennium Eruption Products of Changbaishan Volcano and Extremely Reducing Magmatic Conditions

description: Table 1. U-Th isotope and concentration data for Millennium Eruption of Changbaishan volcano Table 2. Magnetite and ilmenite compositions and calculated temperature, oxygen fugacity, and TiO2 activity Table A1. Clinopyroxene-liquid equilibrium temperature Table A2. Calculation of temperature from Ti-in-zircon geothermometer
DOI: 10.17632/4nccgtcpgn.1
title: Genome mock to predict single-crosses

description: Genomic prediction, based on molecular markers, enables speed breeding schemes and increases the response to selection. Even though there are several genotyping platforms for obtaining single nucleotide polymorphism (SNP) markers, lacking comparative information on how these platforms affect hybrid prediction or the inclusion of non-additive effects. Moreover, SNP discovery techniques are commonly based on a unique reference genome, which can introduce an ascertainment bias when tested germplasms are distant from reference. We employed a tropical maize single-crosses panel and genomic data from two genotyping platforms: array and genotyping-by-sequencing, both based on the B73 genome (temperate). Also, we used a pipeline to build a mock reference genome for SNP discovery aiming to capture unique SNP markers within the tropical maize population, independent from an external reference genome. Our results indicate that mock reference genomes deliver reliable estimates for genetic diversity and population structure assessment. Furthermore, genomic prediction estimates were comparable to standard approaches, especially when considering additive effects or simple traits. However, mock genomes were slightly worse to predict complex traits and estimate dominance effects, but still with similar GBS performance using B73 as the reference genome. Nevertheless, the SNP-array methods achieved the best predictive ability and reliability to estimate variance components. Finally, the mock genomes can be a worthy alternative to perform genetic diversity and genomic selection studies, especially for those species where the reference genome is not available.
DOI: 10.17632/hgyyrb248v.1
title: Rewarding good political behavior: US aid, democracy, and human rights

description: Data and code to reproduce the results reported in the article “Rewarding Good Political Behavior: US Aid, Democracy, and Human Rights” by Zohid Askarov, Hristos Doucouliagos, Martin Paldam, and T.D. Stanley, European Journal of Political Economy.