cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48420/21916617.v1
title: Appendix D. Mineral compositions in silica-rich igneous rims and chondrules from CR chondrites

description: Mineral compositions in chondrules and associated silica-rich igneous rims (SIRs) from CR chondrites. Electron microprobe data obtained by wavelength-dispersive spectroscopy (WDS) X-ray mapping.
DOI: 10.48420/21916617
title: Appendix D. Mineral compositions in silica-rich igneous rims and chondrules from CR chondrites

description: Mineral compositions in chondrules and associated silica-rich igneous rims (SIRs) from CR chondrites. Electron microprobe data obtained by wavelength-dispersive spectroscopy (WDS) X-ray mapping.
DOI: 10.5281/zenodo.7565985
title: Mapeo del ecosistema de emprendimiento e innovación social de Bogotá

description: Esta base de datos contiene 338 elementos identificados del ecosistema de emprendimiento e innovación social de Bogotá.
DOI: 10.5281/zenodo.7565984
title: Mapeo del ecosistema de emprendimiento e innovación social de Bogotá

description: Esta base de datos contiene 338 elementos identificados del ecosistema de emprendimiento e innovación social de Bogotá.
DOI: 10.48366/r282511
title: X-ray observations from cosmic objects 4: stars

description: X-rays are a central ingredient moderating the gas chemistry of cosmic bodies in the universe. In this comparison a set of publications are presented from the field of X-ray Astronomy. This field has seen an increased interest since the launch of space observatories like Chandra X-ray Observatory and XMM - Newton. This is the fourth comparison of a set that covers X-ray observations on various cosmic body types: comets, https://orkg.org/comparison/R274032/ planets, https://orkg.org/comparison/R275000/, the sun, https://orkg.org/comparison/R282510/ ,the stars and warm-hot intergalactic medium. This set is also a direct evolution from published comparisons about the complementary topic of laboratory X-ray measurements in Highly Charged Ions (HCIs).
DOI: 10.7294/21818604
title: InSAR-based Line-of-sight Displacement at Los Angeles Area

description: Line-of-sight Displacement across Los Angeles as shown in Fig 14b of Lee and Shirzaei (2023) Remote Sensing of Environment. Volume 286, 113447 The SAR data sets spanning from 26 February 2016 to 29 August 2022 include 247 images in descending orbits of the Sentinel-1 C-band satellite. The data set is processed using WabInSAR algorithm. See citations below for details. Associated Resource Citation: Lee, Jui-Chi, and Shirzaei. Manoochehr (2023), Novel Algorithms for Pair and Pixel Selection and Atmospheric Error Correction in Multitemporal InSAR, Remote Sensing of Environment. Volume 286, 113447, doi:10.1126/j.rse.2022.113447 References: [1] M. Shirzaei, J. Freymueller, T. E. Törnqvist, D. L. Galloway, T. Dura, and P. S. J. Minderhoud, "Measuring, modelling and projecting coastal land subsidence," Nature Reviews Earth & Environment, 2020/12/10 2021, doi: 10.1038/s43017-020-00115-x. [2] M. M. Miller and M. Shirzaei, "Assessment of future flood hazards for southeastern Texas: Synthesizing subsidence, sea‐level rise, and storm surge scenarios," Geophysical Research Letters, vol. 48, no. 8, p. e2021GL092544, 2021. [3] E. Blackwell, M. Shirzaei, C. Ojha, and S. Werth, "Tracking California’s sinking coast from space: Implications for relative sea-level rise," Science Advances, vol. 6, no. 31, p. eaba4551, 2020, doi: 10.1126/sciadv.aba4551. [4] C. Ojha, M. Shirzaei, S. Werth, D. F. Argus, and T. G. Farr, "Sustained Groundwater loss in California's Central Valley exacerbated by intense drought periods," Water resources research, vol. 54, no. 7, pp. 4449-4460, 2018. [5] M. Shirzaei and R. Bürgmann, "Time-dependent model of creep on Hayward fault inferred from joint inversion of 18 years InSAR time series and surface creep data," J. Geophys. Res. Solid Earth, vol. 118, no. 1733–1746, p. doi:10.1002/jgrb.50149, 2013. [6] M. Shirzaei, "A Wavelet-Based Multitemporal DInSAR Algorithm for Monitoring Ground Surface Motion," (in English), Ieee Geoscience and Remote Sensing Letters, vol. 10, no. 3, pp. 456-460, May 2013, doi: Doi 10.1109/Lgrs.2012.2208935. [7] M. Shirzaei and R. Bürgmann, "Topography correlated atmospheric delay correction in radar interferometry using wavelet transforms," Geophysical Research Letters, vol. 39, no. 1, p. doi: 10.1029/2011GL049971, Jan 6 2012. [Online]. Available: ://WOS:000298930900002 [8] M. Shirzaei, R. Bürgmann, and E. J. Fielding, "Applicability of Sentinel‐1 Terrain Observation by Progressive Scans multitemporal interferometry for monitoring slow ground motions in the San Francisco Bay Area," Geophysical Research Letters, vol. 44, no. 6, pp. 2733-2742, 2017, doi: 10.1002/2017GL072663. <br>
DOI: 10.7294/21818604.v2
title: InSAR-based Line-of-sight Displacement at Los Angeles Area

description: Line-of-sight Displacement across Los Angeles as shown in Fig 14b of Lee and Shirzaei (2023) Remote Sensing of Environment. Volume 286, 113447 The SAR data sets spanning from 26 February 2016 to 29 August 2022 include 247 images in descending orbits of the Sentinel-1 C-band satellite. The data set is processed using WabInSAR algorithm. See citations below for details. Associated Resource Citation: Lee, Jui-Chi, and Shirzaei. Manoochehr (2023), Novel Algorithms for Pair and Pixel Selection and Atmospheric Error Correction in Multitemporal InSAR, Remote Sensing of Environment. Volume 286, 113447, doi:10.1126/j.rse.2022.113447 References: [1] M. Shirzaei, J. Freymueller, T. E. Törnqvist, D. L. Galloway, T. Dura, and P. S. J. Minderhoud, "Measuring, modelling and projecting coastal land subsidence," Nature Reviews Earth & Environment, 2020/12/10 2021, doi: 10.1038/s43017-020-00115-x. [2] M. M. Miller and M. Shirzaei, "Assessment of future flood hazards for southeastern Texas: Synthesizing subsidence, sea‐level rise, and storm surge scenarios," Geophysical Research Letters, vol. 48, no. 8, p. e2021GL092544, 2021. [3] E. Blackwell, M. Shirzaei, C. Ojha, and S. Werth, "Tracking California’s sinking coast from space: Implications for relative sea-level rise," Science Advances, vol. 6, no. 31, p. eaba4551, 2020, doi: 10.1126/sciadv.aba4551. [4] C. Ojha, M. Shirzaei, S. Werth, D. F. Argus, and T. G. Farr, "Sustained Groundwater loss in California's Central Valley exacerbated by intense drought periods," Water resources research, vol. 54, no. 7, pp. 4449-4460, 2018. [5] M. Shirzaei and R. Bürgmann, "Time-dependent model of creep on Hayward fault inferred from joint inversion of 18 years InSAR time series and surface creep data," J. Geophys. Res. Solid Earth, vol. 118, no. 1733–1746, p. doi:10.1002/jgrb.50149, 2013. [6] M. Shirzaei, "A Wavelet-Based Multitemporal DInSAR Algorithm for Monitoring Ground Surface Motion," (in English), Ieee Geoscience and Remote Sensing Letters, vol. 10, no. 3, pp. 456-460, May 2013, doi: Doi 10.1109/Lgrs.2012.2208935. [7] M. Shirzaei and R. Bürgmann, "Topography correlated atmospheric delay correction in radar interferometry using wavelet transforms," Geophysical Research Letters, vol. 39, no. 1, p. doi: 10.1029/2011GL049971, Jan 6 2012. [Online]. Available: ://WOS:000298930900002 [8] M. Shirzaei, R. Bürgmann, and E. J. Fielding, "Applicability of Sentinel‐1 Terrain Observation by Progressive Scans multitemporal interferometry for monitoring slow ground motions in the San Francisco Bay Area," Geophysical Research Letters, vol. 44, no. 6, pp. 2733-2742, 2017, doi: 10.1002/2017GL072663. <br>
DOI: 10.5281/zenodo.7565882
title: Reference dataset of multi-objective and multi-fidelity optimization in laser-plasma acceleration

description: This repository contains a dataset used for the article "<em>Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration</em>" (arXiv:2210.03484). The dataset consists of 2443 FBPIC particle-in-cell simulations of a laser wakefield accelerator that were selected using a Bayesian optimizer. The goal of the optimization was to perform multi-objective multi-fidelity optimization of electron beam parameters. The dataset contains simulations of different resolutions, accordingly with differing fidelities. The typical runtime at lowest (highest) resolution is approximately 1 (90) minutes. In the dataset we have <em>train_x </em>and <em>train_obj </em>numpy arrays with dimensions <em>(n,5)</em> and<em> (n,3)</em>, respectively. Here <em>n</em> is the number of FBPIC simulations. The five columns in <em>train_x </em>are [plasma density, upramp length, laser focus, downramp length, fidelity]. The fidelity parameter controls the resolution and hence the runtime of the simulation. The three columns in the <em>train_obj </em>are the [total charge, distance of median to target energy, bandwidth of electron beams]. For the distance, the target energy is fixed to 300 MeV and for the bandwidth is defined by the median absolute deviation around the median. The two columns have negative values since the optimizer assumes a maximization of all objectives while the distance and bandwidth in this study were being minimized. The different folders contain data of different kind of single and multi-objectives that were used to produce figures 2, 3, 5 in the associated paper. For more details please see the referred article. The folder "combined" contains the data of all simulations together and is most suitable for (5D x 3D) surrogate model generation.
description: {"references": ["Irshad F, Karsch S, D\u00f6pp A. Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration. arXiv preprint arXiv:2210.03484. 2022 Oct 7."]}
DOI: 10.5281/zenodo.7565881
title: Reference dataset of multi-objective and multi-fidelity optimization in laser-plasma acceleration

description: This repository contains a dataset used for the article "<em>Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration</em>" (arXiv:2210.03484). The dataset consists of 2443 FBPIC particle-in-cell simulations of a laser wakefield accelerator that were selected using a Bayesian optimizer. The goal of the optimization was to perform multi-objective multi-fidelity optimization of electron beam parameters. The dataset contains simulations of different resolutions, accordingly with differing fidelities. The typical runtime at lowest (highest) resolution is approximately 1 (90) minutes. In the dataset we have <em>train_x </em>and <em>train_obj </em>numpy arrays with dimensions <em>(n,5)</em> and<em> (n,3)</em>, respectively. Here <em>n</em> is the number of FBPIC simulations. The five columns in <em>train_x </em>are [plasma density, upramp length, laser focus, downramp length, fidelity]. The fidelity parameter controls the resolution and hence the runtime of the simulation. The three columns in the <em>train_obj </em>are the [total charge, distance of median to target energy, bandwidth of electron beams]. For the distance, the target energy is fixed to 300 MeV and for the bandwidth is defined by the median absolute deviation around the median. The two columns have negative values since the optimizer assumes a maximization of all objectives while the distance and bandwidth in this study were being minimized. The different folders contain data of different kind of single and multi-objectives that were used to produce figures 2, 3, 5 in the associated paper. For more details please see the referred article. The folder "combined" contains the data of all simulations together and is most suitable for (5D x 3D) surrogate model generation.
description: {"references": ["Irshad F, Karsch S, D\u00f6pp A. Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration. arXiv preprint arXiv:2210.03484. 2022 Oct 7."]}
DOI: 10.5281/zenodo.7565983
title: CO2 electroreduction experiments - supplementary data

description: Set of raw data supporting our work on CO2 electroreduction.
DOI: 10.5281/zenodo.7565982
title: CO2 electroreduction experiments - supplementary data

description: Set of raw data supporting our work on CO2 electroreduction.
DOI: 10.48366/r282512
title: X-ray observations from cosmic objects 5: intergalactic medium (IGM,WHIM)

description: X-rays are a central ingredient moderating the gas chemistry of cosmic bodies in the universe. In this comparison a set of publications are presented from the field of X-ray Astronomy. This field has seen an increased interest since the launch of space observatories like Chandra X-ray Observatory and XMM - Newton. This is the fifth comparison of a set that covers X-ray observations on various cosmic body types: comets, https://orkg.org/comparison/R274032/ planets, https://orkg.org/comparison/R275000/, the sun, https://orkg.org/comparison/R282510/ the stars https://orkg.org/comparison/R282511/ and warm-hot intergalactic medium. This set of comparisons is also a direct evolution from published comparisons about the complementary topic of laboratory X-ray measurements in Highly Charged Ions (HCIs).
DOI: 10.5281/zenodo.7566019
title: 5D-NP-FABTECH_SALV - Open Dataset for "3D Micropatterned Functional Surface Inspired by Salvinia Molesta via Direct Laser Lithography for Air Retention and Drag Reduction"

description: This is the open dataset for the paper: "Omar Tricinci*, Francesca Pignatelli, Virgilio Mattoli*, 3D Micropatterned Functional Surface Inspired by Salvinia Molesta via Direct Laser Lithography for Air Retention and Drag Reduction, On line (2023) [DOI: 10.1002/adfm.202206946] " This include the Supplementary Information file ("SI-PaperSalvinia3_PostRevOKV2.pdf.pdf"), all the source material used for the paper preparation and more. For each folder (sub-dataset) there is a corresponding readme file describing the content and including metadata
DOI: 10.5281/zenodo.7566018
title: 5D-NP-FABTECH_SALV - Open Dataset for "3D Micropatterned Functional Surface Inspired by Salvinia Molesta via Direct Laser Lithography for Air Retention and Drag Reduction"

description: This is the open dataset for the paper: "Omar Tricinci*, Francesca Pignatelli, Virgilio Mattoli*, 3D Micropatterned Functional Surface Inspired by Salvinia Molesta via Direct Laser Lithography for Air Retention and Drag Reduction, On line (2023) [DOI: 10.1002/adfm.202206946] " This include the Supplementary Information file ("SI-PaperSalvinia3_PostRevOKV2.pdf.pdf"), all the source material used for the paper preparation and more. For each folder (sub-dataset) there is a corresponding readme file describing the content and including metadata
DOI: 10.35078/isjmlt
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Montes Claros| Município: Montes Claros

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.15156/bio/sh0844098.10fu
title: SH0844098.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844099.10fu
title: SH0844099.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844100.10fu
title: SH0844100.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844101.10fu
title: SH0844101.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844102.10fu
title: SH0844102.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844103.10fu
title: SH0844103.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0844104.10fu
title: SH0844104.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.