cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24138670.v2
title: FNETS: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

description: We propose FNETS, a methodology for network estimation and forecasting of high-dimensional time series exhibiting strong serial- and cross-sectional correlations. We operate under a factor-adjusted vector autoregressive (VAR) model which, after accounting for pervasive co-movements of the variables by <i>common</i> factors, models the remaining <i>idiosyncratic</i> dynamic dependence between the variables as a sparse VAR process. Network estimation of FNETS consists of three steps: (i) factor-adjustment via dynamic principal component analysis, (ii) estimation of the latent VAR process via l1-regularized Yule-Walker estimator, and (iii) estimation of partial correlation and long-run partial correlation matrices. In doing so, we learn three networks underpinning the VAR process, namely a directed network representing the Granger causal linkages between the variables, an undirected one embedding their contemporaneous relationships and finally, an undirected network that summarizes both lead-lag and contemporaneous linkages. In addition, FNETS provides a suite of methods for forecasting the factor-driven and the idiosyncratic VAR processes. Under general conditions permitting tails heavier than the Gaussian one, we derive uniform consistency rates for the estimators in both network estimation and forecasting, which hold as the dimension of the panel and the sample size diverge. Simulation studies and real data application confirm the good performance of FNETS.
DOI: 10.6084/m9.figshare.24138670.v1
title: FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series

description: Abstract–<b>We propose FNETS, a methodology for network estimation and forecasting of high-dimensional time series exhibiting strong serial- and cross-sectional correlations. We operate under a factor-adjusted vector autoregressive (VAR) model which, after accounting for pervasive co-movements of the variables by <i>common</i> factors, models the remaining <i>idiosyncratic</i> dynamic dependence between the variables as a sparse VAR process. Network estimation of FNETS consists of three steps: (i) factor-adjustment via dynamic principal component analysis, (ii) estimation of the latent VAR process via</b><b>-regularised Yule-Walker estimator, and (iii) estimation of partial correlation and long-run partial correlation matrices. In doing so, we learn three networks underpinning the VAR process, namely a directed network representing the Granger causal linkages between the variables, an undirected one embedding their contemporaneous relationships and finally, an undirected network that summarises both lead-lag and contemporaneous linkages. In addition, FNETS provides a suite of methods for forecasting the factor-driven and the idiosyncratic VAR processes. Under general conditions permitting tails heavier than the Gaussian one, we derive uniform consistency rates for the estimators in both network estimation and forecasting, which hold as the dimension of the panel and the sample size diverge. Simulation studies and real data application confirm the good performance of FNETS.</b>
DOI: 10.6073/pasta/10d6e47ddf2c3c558f6a55b798032e91
title: Hubbard Brook Experimental Forest: Soil-atmosphere fluxes of carbon dioxide, nitrous oxide and methane on Watershed 1 and Bear Brook

description: Soil atmosphere fluxes of the trace gases; carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) have been measured at several locations at the Hubbard Brook Experimental Forest (HBEF) including 1) the “freeze” study reference plots that provide contrast between stands dominated (80%) by sugar maple versus yellow birch and low and high elevation areas, 2) the Bear Brook Watershed where trace gas sampling is coordinated with long-term monitoring of microbial biomass and activity and 3) watershed 1 where trace gas sampling locations were co-located with long-term microbial biomass and activity monitoring sites that are located near a subset of the lysimeter sites established for the calcium addition study on this watershed. This dataset contains the Watershed 1 and Bear Brook data. Freeze plot trace gas can be found in: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=251. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
DOI: 10.18434/mds2-2905
title: Database Infrastructure for Mass Spectrometry - Per- and Polyfluoroalkyl Substances
DOI: 10.5281/zenodo.8105535
title: A Harmonised Dataset for Modelling Select Underutilised Crops Across EU

description: Datasets are a compilation of information that are collected from various sources including books, research articles, databases, website articles, experts and local communities growing underutilised crops, etc. The focus was on extracting data from literature sources that were mainly peer reviewed, credible, and are primarily published in English language. Taxonomy data: crop, variety or landrace Publication information: author, journal, year Geographic data: continent, country, site, latitude, longitude Soil data: Lower Depth, Clay (%), Sand (%), Silt (%), Texture, S.O., Bulk Density, Total carbon (%) Experimental data: Experiment duration (years), Seeding rate, Sowing depth, dates of each treatment /intervention. Production: yield, yield date, Above Ground Biomass (Agb), Agb date Phenology data: Growing Degree Days (sowing-to-harvest), emergence date, flowering date, maturity date Metadata: Study number, DOI, link Credible sources containing experimental data, either from agronomy trials or meta-analysis containing experimental data were selected through literature search. As the focus of the work was to collate as much information as possible about agronomy trials of select underutilised crops, all data were collected and inserted into a shareable template on Google Docs. Units were harmonised to ensure their usability in crop modelling. List of crops:<br> <br> <em>Ceratonia siliqua</em>, Carob, Underutilised legume tree<br> <em>Cichorium endivia</em>, Endive, Underutilised vegetable<br> <em>Eragrostis tef</em>, Teff, Underutilised cereal<br> <em>Ficus carica</em>, Fig, Underutilised fruit tree<br> <em>Helianthus tuberosus</em>, Jerusalem artichoke, Underutilised starchy roots/tubers<br> <em>Lentil Culinaris</em>, Lentil, Pulse<br> <em>Lupinus albus</em>, White lupin, Underutilised legume<br> <em>Malus domestica</em>, Apple, Fruit<br> <em>Malus pumila</em>, Apple, Fruit<br> <em>Medicago sativa</em>, Alfaalfa, Underutilised legume<br> <em>Panicum miliaceum</em> , Proso millet, Underutilised minor millet<br> <em>Pisum sativum</em>, Pea, Legume<br> <em>Prunus avium</em>, Cherry, Fruit<br> <em>Prunus domestica</em>, Plum, Fruit<br> <em>Pyrus communis,</em> Pear, Fruit<br> <em>Rheum rhaponticum</em>, Rhubarb, Underutilised vegetable<br> <em>Setaria italic</em>, Foxtail millet, Underutilised minor millet<br> <em>Trifolium repens</em> , Clover, Underutilised legume<br> <em>Vicia faba</em>, Faba bean, Underutilised legume<br> <em>Vigna unguiculata</em>, Cowpea, Underutilised legume
DOI: 10.25824/redu/vyedbs
title: Slug_W_A.rar
DOI: 10.5281/zenodo.8406389
title: Supplementary Data for "Enhanced interfacial water dissociation on a hydrated iron porphyrin single-atom catalyst defect in graphene"

description: Supplementary Data for the article:<br> "Enhanced interfacial water dissociation on a hydrated iron porphyrin single-atom catalyst defect in graphene"<br> Laura Scalfi, Maximilian R. Becker, Roland R. Netz and Marie-Laure Bocquet, Communications Chemistry (2023)<br> [preprint: 10.26434/chemrxiv-2023-31hbx]
DOI: 10.5281/zenodo.8406388
title: Supplementary Data for "Enhanced interfacial water dissociation on a hydrated iron porphyrin single-atom catalyst defect in graphene"

description: Supplementary Data for the article:<br> "Enhanced interfacial water dissociation on a hydrated iron porphyrin single-atom catalyst defect in graphene"<br> Laura Scalfi, Maximilian R. Becker, Roland R. Netz and Marie-Laure Bocquet, Communications Chemistry (2023)<br> [preprint: 10.26434/chemrxiv-2023-31hbx]
DOI: 10.5517/ccdc.csd.cc296dnl
title: CCDC 2121319: Experimental Crystal Structure Determination

description: Related Article: Sarah J. Pike, Richard Telford, Louise Male|2023|Org.Biomol.Chem.|21|7717|doi:10.1039/D3OB01137B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hswh
title: CCDC 2130347: Experimental Crystal Structure Determination

description: Related Article: Sarah J. Pike, Richard Telford, Louise Male|2023|Org.Biomol.Chem.|21|7717|doi:10.1039/D3OB01137B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d0q5b
title: CCDC 2205221: Experimental Crystal Structure Determination

description: Related Article: Yuxiao Duan, Meng Chen, Hironobu Hayashi, Hiroko Yamada, Xinyue Liu, Lei Zhang|2023|Chemical Science|14|10420|doi:10.1039/D3SC00658A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hxb2
title: CCDC 2130454: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hxh7
title: CCDC 2130459: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hy1t
title: CCDC 2130476: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hy4x
title: CCDC 2130479: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dps2z
title: CCDC 2225461: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dps74
title: CCDC 2225466: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dps85
title: CCDC 2225467: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dps96
title: CCDC 2225468: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsb7
title: CCDC 2225469: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsd9
title: CCDC 2225471: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsfb
title: CCDC 2225472: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsgc
title: CCDC 2225473: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpshd
title: CCDC 2225474: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpslh
title: CCDC 2225477: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsmj
title: CCDC 2225478: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dpsrn
title: CCDC 2225482: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Chengbo Li, Hui Ma, Fanda Feng, Yuan Zhang, Wei Huang|2023|Chemical Science|14|10446|doi:10.1039/D3SC03201A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.8123676
title: Dataset: Simulation-based parameter optimization for fetal brain MRI super-resolution reconstruction

description: This dataset contains the data used in the paper de Dumast, P., Sanchez, T., Lajous, H., Bach Cuadra, M. (2023). Simulation-Based Parameter Optimization for Fetal Brain MRI Super-Resolution Reconstruction. MICCAI 2023. LNCS, vol 14226. Springer, Cham. https://doi.org/10.1007/978-3-031-43990-2_32 A preprint can also be found on arXiv. If you found this dataset useful or used it in your research, please cite this reference. This paper studied the impact of the regularization parameter \(\alpha \) on the super-resolution reconstruction of fetal brain magnetic resonance (MR) images. It used simulated T2-weighted data MR images generated using FaBiAN v2.0, a Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates fast spin echo (FSE) sequences of the developing fetal brain throughout gestation. The dataset contains the raw simulated data, the corresponding ground truths as well as corresponding super-resolution (SR) reconstructions using MIALSRTK and NiftyMIC with varying regularization parameters \(\alpha \). Copyright (c) - All rights reserved. Medical Image Analysis Laboratory - Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland & CIBM Center for Biomedical Imaging. 2023.
description: This work is supported by the Swiss National Science Foundation through grants 182602 and 141283, and by the Eranet Neuron MULTIFACT project (SNSF 31NE30 203977). We acknowledge access to the facilities and expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by CHUV, UNIL, EPFL, UNIGE and HUG.
description: {"references": ["Lajous, H., et al. (2021). Medical-Image-Analysis-Laboratory/FaBiAN: FaBiAN. Zenodo. https://doi.org/10.5281/zenodo.5471094", "Lajous, H., et al. (2022). A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN). Sci Rep 12, 8682. https://doi.org/10.1038/s41598-022-10335-4", "Tourbier, S., et al. (2015). An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization. NeuroImage, 118, 584-597. https://doi.org/10.1016/j.neuroimage.2015.06.018", "Tourbier, S., et al. (2023). Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit: MIAL Super-Resolution Toolkit v2.1.0 (v2.1.0). Zenodo. https://doi.org/10.5281/zenodo.7612119", "Ebner, M., et al. (2020). An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. NeuroImage, 206, 116324. https://doi.org/10.1016/j.neuroimage.2019.116324"]}