cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6891244
title: Two multi-temporal datasets to track debris flow after the 2008 Wenchuan earthquake

description: We provide two datasets for tracking the debris flow induced by the 2008 Wenchuan Mw 7.9 earthquake on a section of the Longmen mountains on the eastern side of the Tibetan plateau (Sichuan, China). The database was obtained through a literature review and field survey reports in the epicenter area, combined with high-resolution remote sensing imagery and extensive data collection and processing. The first dataset covers an area of 892 km<sup>2</sup>, including debris flows from 2008 to 2020. 186 debris flows affecting 79 watersheds were identified. 89 rainfall stations were collected to determine the rainfall events for the post-earthquake debris flow outbreak. The second database is a list of mitigation measures for post-earthquake debris flows, including catchment name, check dam number, coordinates, construction time, and successful debris flow mitigation date. This two datasets can aid different applications, including the early warning monitoring and engineering prevention of post-earthquake debris flow, as well as provide valuable data support for research in related disciplines.
DOI: 10.6084/m9.figshare.20549409
title: Supplementary Material for: Communicating Precision Medicine Research: Multidisciplinary Teams and Diverse Communities

description: <b><i>Introduction:</i></b> Precision medicine research investigates the differences in individuals’ genetics, environment, and lifestyle to tailor health prevention and treatment options as part of an emerging model of health care delivery. Advancing precision medicine research will require effective communication across a wide range of scientific and health care disciplines and with research participants who represent diverse segments of the population. <b><i>Methods:</i></b> A multidisciplinary group convened over the course of a year and developed precision medicine research case examples to facilitate precision medicine research discussions with communities. <b><i>Results:</i></b> A shared definition of precision medicine research as well as six case examples of precision medicine research involving genetic risk, pharmacogenetics, epigenetics, the microbiome, mobile health, and electronic health records were developed. <b><i>Discussion/Conclusion:</i></b> The precision medicine research definition and case examples can be used as planning tools to establish a shared understanding of the scope of precision medicine research across multidisciplinary teams and with the diverse communities in which precision medicine research will take place. This shared understanding is vital for successful and equitable progress in precision medicine.
DOI: 10.6084/m9.figshare.20707963
title: Supplementary Material for: Single-Use or Disposable Flexible Bronchoscopy in Advanced Bronchoscopy Procedures: Experience in a Quaternary Referral Centre

description: <b><i>Background:</i></b> The development of single-use flexible or disposable bronchoscopes (SUFBs) has accelerated in recent years, with the reduced risk of infectious transmission and reduced need for endoscopy staffing particularly advantageous in the COVID-19 pandemic era. <b><i>Objective:</i></b> The objective of this study was to assess the performance of a novel single-use bronchoscope in an academic quaternary referral centre with on-site interventional pulmonology programme. <b><i>Methods:</i></b> With ethical approval in a quaternary referral centre, we prospectively collected data on sequential bronchoscopy procedures using The Surgical Company Broncoflex© range of SUFBs. Data collected included demographic, procedural, scope performance, user satisfaction, and complication parameters in a tertiary bronchoscopy service. <b><i>Results:</i></b> 139 procedures were performed by five pulmonology faculty from January to July 2021. The majority were carried out for infection (45%) and malignancy (32%). Most were performed in the endoscopy suite and 8% were COVID positive or suspected. Most procedures reported the highest score in satisfaction (85%) with technical limitations reported in 15% (predominately related to scope suction or inadequate image quality) reverting to a reusable scope in 2.8 %. <b><i>Conclusion:</i></b> In our subset of patients in a bronchoscopy unit, SUFBs are safe, and both routine and advanced bronchoscopy procedures can be performed with high satisfaction reported.
DOI: 10.5281/zenodo.6547800
title: Effects of convective mergers on the evolution of microphysical and electrical activity in a severe squall line simulated by WRF coupled with explicit electrification scheme

description: These are important data supporting the conclusion of the paper are available in the main text.The STORM973 dataset including BLNET data and radar data are provided here.Some of the E-WRF outputs are also provided here. The corresponding scripts are based on NCL (version 6.6.2.).
DOI: 10.7303/syn27202355
title: Brighten Studies - Longitudinal PHQ-9 data table
DOI: 10.15151/esrf-es-883953841
title: Towards the understanding of the Interaction between the Spike Fusion Region and the cell Plasma Membrane

description: SARS-CoV-2 is an encapsulated virus responsible for a lethal respiratory illness since its outbreak at the end of 2019. Interestingly, the fusion domain of the spike protein triggers the fusion between viral and host membranes, initializing the infection. However, the molecular mechanism regulating this process has not been deeply understood. Our approach to date has been to study the interaction of several putative fusion peptides at or near the N-terminus of S2 subunit with model membranes in the form of monolayers, composed of cholesterol and natural lipids extracted from yeast cells. A combination of different X-ray surface scattering methods available at ID10 beamline (XRR, GISAXS, and GIXD) will help to answer questions still not answered such as how does the fusion region induces the reorganization of the lipid packing, as well as, how is the fusion process modulated by lipid composition and environmental factors such as the presence of divalent cations.
DOI: 10.5281/zenodo.4919132
title: Dataset: A multi-scale probabilistic atlas of the human connectome

description: This repository complements the paper submitted to <strong>Scientific Data</strong> named <em>A multi-scale probabilistic atlas of the human connectome</em>. <strong>Introduction</strong> The assessment of the networks underlying brain processes is key to understand brain-related disorders. However, groundbreaking connectomics research is highly demanding in terms of equipment and expertise. The aim of this work is to create a multiscale probabilistic atlas of the human white matter (WM) to carry out network analyses in the context of clinical research, particularly when diffusion data is not directly available. <strong>Methods</strong> Sixty six subjects from the Human Connectome Project (HCP) database (29 males, age: 22-36 years old) were used to build the WM probabilistic atlas. MRI acquisition protocols are described in (Van Essen et al, 2012). Besides T1-, T2- and diffusion-weighted (DW) images, the HCP database provides the FreeSurfer outputs (Glasser et al, 2016) namely cortical surfaces (pial and white), subcortical segmentation and a cortical surface parcellation containing 34 structures for each hemisphere (Desikan et al, 2006). For each subject, the DWIs were employed to segment each thalamus in seven nuclei (Battistella et al, 2016) and to estimate the WM streamlines distribution. The constrained spherical deconvolution (Tournier et al, 2007) algorithm was used to compute the intravoxel fiber distribution functions for the anatomically-constrained particle-filter tractography approach (Descoteaux et al, 2009) to compute the WM streamlines. Subcortical, thalamic and multiscale cortical (Cammoun et al, 2012) parcellations were gathered to obtain four individual gray matter (GM) parcellations. Finally, for each scale, individual fiber bundles, were created by selecting the streamlines connecting each pair of GM regions (Figure 1a). <em>Atlas construction</em> The T1 and T2 images were non-linearly warped to their corresponding MNI templates (Evans et al, 2012, mni_icbm152_tal_nlin_asym_09c version) using ANTs (Avants et al, 2010). The resulting spatial transformations were applied to warp the individual fiber bundles to stereotactic space and the normalized tract density images (TDIs) were created. In these images, each voxel contains the number of streamlines passing through it. Finally, the spatial probability map for each bundle was obtained by binarizing and averaging the bundle TDIs across the subjects (Figure. 1b). Different views of the developed probabilistic multi-scale connectome atlas are shown in Figure 2.
DOI: 10.6084/m9.figshare.20547933
title: Supplementary Material for: Expansion of Phenotypically Altered Dendritic Cell Populations in the Small Airways and Alveolar Parenchyma in Patients with Chronic Obstructive Pulmonary Disease

description: Contrasting the antigen-presenting dendritic cells (DCs) in the conducting airways, the alveolar DC populations in human lungs have remained poorly investigated. Consequently, little is known about how alveolar DCs are altered in diseases such as chronic obstructive pulmonary disease (COPD). This study maps multiple tissue DC categories in the distal lung across COPD severities. Specifically, single-multiplex immunohistochemistry was applied to quantify langerin/CD207<sup>+</sup>, CD1a<sup>+</sup>, BDCA2<sup>+</sup>, and CD11c<sup>+</sup> subsets in distal lung compartments from patients with COPD (GOLD stage I–IV) and never-smoking and smoking controls. In the alveolar parenchyma, increased numbers of CD1a<sup>+</sup>langerin<sup>−</sup> (<i>p</i> &lt; 0.05) and BDCA-2<sup>+</sup> DCs (<i>p</i> &lt; 0.001) were observed in advanced COPD compared with controls. Alveolar CD11c<sup>+</sup> DCs also increased in advanced COPD (<i>p</i> &lt; 0.01). In small airways, langerin<sup>+</sup> and BDCA-2<sup>+</sup> DCs were also significantly increased. Contrasting the small airway DCs, most alveolar DC subsets frequently extended luminal protrusions. Importantly, alveolar and small airway langerin<sup>+</sup> DCs in COPD lungs displayed site-specific marker profiles. Further, multiplex immunohistochemistry with single-cell quantification was used to specifically profile langerin DCs and reveal site-specific expression patterns of the maturation and activation markers S100, fascin, MHC2, and B7. Taken together, our results show that clinically advanced COPD is associated with increased levels of multiple alveolar DC populations exhibiting features of both adaptive and innate immunity phenotypes. This expansion is likely to contribute to the distal lung immunopathology in COPD patients.
DOI: 10.17632/r3v7236kkz.1
title: CooRecorder Tutorial Videos

description: We present a brief overview of how to measure tree-ring widths in the software application CooRecorder (Cybis Elektronik & Data AB) for tree-ring analysis complementing two video tutorials. The first tutorial covers the basics of opening files, measuring ring widths, preliminary crossdating with a reference chronology, and setting dates. The second tutorial covers setting earlywood-latewood boundaries, measuring across cracks, inserting locally absent or missing rings, manual adjustments, and metadata. The video tutorials can be found here https://www.youtube.com/watch?v=c-GNKHVUj9I and here https://www.youtube.com/watch?v=xO7Phc93xyM&t=3s. Videos have been closed-captioned in English. Article published in Dendrochronologia- Measuring tree-ring widths using the CooRecorder software application By R. Stockton Maxwell & Lars-Ake Larsson 10.1016/j.dendro.2021.125841 https://www.sciencedirect.com/science/article/pii/S1125786521000370
DOI: 10.17864/1947.244
title: A new multi-variable benchmark for Last Glacial Maximum climate simulations

description: Reconstruction of climate anomalies for the Last Glacial Maximum (LGM, ca 21,000 years ago), made by combining pollen based reconstructions (from Bartlein et al. 2011) and averaged outputs of LGM simulations from the 3rd round of the Palaeoclimate Model Intercomparison Project (PMIP, Braconnot et al. 2011), under a variational data assimilation technique. This reconstruction is designed to be used for data-model comparison, specifically against the results of PMIP4. The dataset consists of 6 variables: moisture index (the ratio precipitation and equilibrium evapotranspiration), mean annual precipitation (mm), mean annual temperature (degrees C), mean temperature of the coldest month (degrees C), mean temperature of the warmest month (degrees C), growing degree days above 5 degrees C (day degrees C). The standard deviation of these variables is also given. This dataset supersedes the version published at http://dx.doi.org/10.17864/1947.229, where an incorrect value for MI SD was used in Australia, a non-linear MAP non-dimensionalisation was used (instead of the linear one here), the background error covariance matrix was square rooted improperly and incorrect values for MI were used in central Asia.
description: This dataset is made by combining site-based pollen reconstructions with aggregated outputs of PMIP3. The possible climates are varied and the most likely climate is found under a 3D-Variational data assimilation scheme. The uncertainty from this process is then used to screen out areas where the pollen reconstructions have had a minimal effect. By using a vegetation model, the effect of changing CO_2 concentrations on pollen reconstructions is also accounted for. The error of the resulting reconstruction is also calculated and given as 1 standard deviation from the variables. The individual fields are: grid cell centre latitude grid cell centre longitude moisture index mean annual precipitation (mm) mean annual temperature (degrees C) mean temperature of the coldest month (degrees C) mean temperature of the warmest month (degrees C) growing degree days above 5 degrees C (days degrees C) moisture index standard deviation mean annual precipitation standard deviation (mm) mean annual temperature standard deviation (degrees C) mean temperature of the coldest month standard deviation (degrees C) mean temperature of the warmest month standard deviation (degrees C) growing degree days above 5 degrees C standard deviation (days degrees C).
DOI: 10.5281/zenodo.5799648
title: Dataset for "First Observations of Large Scale Traveling Ionospheric Disturbances Using Automated Amateur Radio Receiving Networks"

description: # 20171103.rbn_pskreporter_wspr_data.csv<br> #<br> # This data file contains the amateur radio spot data used in the manuscript:<br> # "First Observations of Large Scale Traveling Ionospheric Disturbances Using Automated Amateur Radio Receiving Networks"<br> # by Nathaniel A. Frissell W2NAF, Stephen R. Kaeppler AD0AE, Diego F. Sanchez KD2RLM, Gareth W. Perry KD2SAK,<br> # William D. Engelke AB4EJ, Philip J. Erickson W1PJE, Anthea J. Coster, J. Michael Ruohoniemi, and Joseph B. H. Baker<br> #<br> # Observations are provided courtesy of:<br> # 1. The Weak Signal Propagation Reporting Network (WSPRNet, https://www.wsprnet.org/)<br> # Operated by Bruce Walker W1BW<br> #<br> # 2. The Reverse Beacon Network (RBN, http://www.reversebeacon.net/)<br> # Operated by Nick Sinanis F5VIH/SV3SJ, David Pascoe KM3T, Mark Glenn K7MJG, Peter Smith N4ZR, Felipe Ceglia PY1NB/CT7ANO, and Dick Williams W3OA<br> #<br> # 3. PSKReporter (https://pskreporter.info/)<br> # Operated by Philip Gladstone N1DQ<br> #<br> # Explanation of Data Columns:<br> # freq: Frequency [kHz]<br> # ut: Time of Observation in Universal Time (UT)<br> # source: Observation Network (WSPRNet, RBN, or PSKReporter)<br> # tx_grid: Transmitter Maidenhead Gridsquare<br> # rx_grid: Receiver Maindenhead Gridsquare<br> # tx_lat: Transmitter Latitude (deg)<br> # tx_long: Transmitter Longitude (deg)<br> # rx_lat: Receiver Latitude (deg)<br> # rx_long: Receiver Longitude (deg)<br> # dist_Km: Ground-Level Great Circle Distance between Transmitter and Receiver (km)<br> # md_lat: Midpoint between Transmitter and Receiver Latitude (deg)<br> # md_long: Midpoint between Transmitter and Receiver Longitude (deg)<br> # slt_mid: Solar Local Time of Midpoint (hr)<br> #<br> # This datafile is a subset of the full WSPRNet/RBN/PSKReporter data, filtered with the following parameters:<br> # ut min: 2017-11-03 00:00:00<br> # ut max: 2017-11-03 23:59:59<br> # freq min: 14000.382<br> # freq max: 14280.0<br> # md_lat min: 20.004737453151876<br> # md_lat max: 54.99977112001497<br> # md_long min: -129.99845895196913<br> # md_long max: -60.008771378901315<br> # dist_Km min: 0.0<br> # dist_Km max: 19861.14355003741
DOI: 10.5281/zenodo.6478730
title: On the application of an observations-based machine learning parameterization of surface layer fluxes within an atmospheric large-eddy simulation model: Trained Models

description: Trained machine learning models and scaling values used in the paper "On the application of an observations-based machine learning parameterization of surface layer fluxes within an atmospheric large-eddy simulation model."
DOI: 10.5281/zenodo.6568212
title: Dataset for "An approach for the pore-centred description of adsorption in hierarchical porous materials"

description: Supporting dataset for: “An approach for the pore-centred description of adsorption in hierarchical porous materials”, J. D. Evans, <strong>2022</strong> <strong>Contains:</strong> structures: Structural models used in YAFF .chk format. code: All the code used to generate the pore distributions, adsorption simulations and analysis. geometricporosity: Output from zeo++ used in this analysis. porestructure: Pore size distribution probes labeled by Pr, Nd, Pm. clustering: Metadata produced from the clustering analysis. porecenters: Locations of the pore centres combined with the structure in CIF format, where each pore is labeled by Pr, Nd, Pm. adsorption: Results of Ar simulation at 87K.
DOI: 10.6084/m9.figshare.17826404.v2
title: Monthly-Averaged XCO2 in Global

description: F:\GOSATMc\Hdf\NHDFObtaining highly accurate and high-resolution spatiotemporal maps of <em>carbon dioxide</em> concentration (XCO<sub>2</sub>) distributions is crucial for promoting the study of the carbon cycle, carbon sources, carbon sinks, carbon neutralization, and carbon emissions assessed by top-down theory. However, the official discrete satellite data provided by Gosat-2, OCO-2, and OCO-3 have low efficiency due to clouds and aerosols. Here, we present carbon dioxide cover, an innovative methodology to obtain XCO<sub>2</sub> maps of high spatiotemporal resolution by using satellite data. The method is developed to support the producers and end users of the global-scale study of the carbon cycle by providing a transparent, version-based framework. This mapping technique can fill the spatiotemporal gaps in satellite measurements, and its accuracy and resolution are sufficiently high for scientific application. It enables the development of strategies to reduce XCO<sub>2</sub> at the global scale.
DOI: 10.5255/ukda-sn-852031
title: Key factors in the international market driving process: The role of internal competencies and external network actors
DOI: 10.5281/zenodo.6771834
title: A dataset of anonymised hospitalised COVID-19 patient data: outcomes, demographics and biomarker measurements for two New York hospitals

description: These datasets are for a cohort of n=1540 anonymised hospitalised COVID-19 patients, and the data provide information on outcomes (i.e. patient death or discharge), demographics and biomarker measurements for two New York hospitals: State<br> University of New York (SUNY) Downstate Health Sciences University and Maimonides<br> Medical Center. The file "demographics_both_hospitals.csv" contains the ultimate outcomes of hospitalisation (whether a patient was discharged or died), demographic information and known comorbidities for each of the patients. The file "dynamics_clean_both_hospitals.csv" contains cleaned dynamic biomarker measurements for the n=1233 patients where this information was available and the data passed our various checks (see https://doi.org/10.1101/2021.11.12.21266248 for information of these checks and the cleaning process). Patients can be matched to demographic data via the "id" column. <strong>Study approval and data collection</strong> Study approval was obtained from the State University of New York (SUNY) Downstate Health Sciences University Institutional Review Board (IRB\#1595271-1) and Maimonides Medical Center Institutional Review Board/Research Committee (IRB\#2020-05-07). A retrospective query was performed among the patients who were admitted to SUNY Downstate Medical Center and Maimonides Medical Center with COVID-19-related symptoms, which was subsequently confirmed by RT PCR, from the beginning of February 2020 until the end of May 2020. Stratified randomization was used to select at least 500 patients who were discharged and 500 patients who died due to the complications of COVID-19. Patient outcome was recorded as a binary choice of “discharged” versus “COVID-19 related mortality”. Patients whose outcome was unknown were excluded. Demographic, clinical history and laboratory data was extracted from the hospital’s electronic health records.
DOI: 10.6084/m9.figshare.20553984
title: Supplementary Material for: Mortality, Causes of Death, and Predictors of Death among Patients On and Off Opioid Agonist Treatment: Results from a 19-Year Cohort Study

description: <b><i>Background:</i></b> Mortality is increased among people with opioid use disorder but reduced while on opioid agonist treatment (OAT). However, the impact of patient and treatment characteristics on mortality and causes of death is insufficiently studied. <b><i>Objectives:</i></b> The objective of this study was to explore mortality and causes of death and examine the impact of patient and treatment characteristics on mortality in an OAT cohort with high retention in treatment. <b><i>Methods:</i></b> <i>Design</i>: longitudinal cohort study. <i>Setting</i>: Norway. <i>Observation period</i>: time from OAT start as of 1998 until death or end of 2016, 2,508 person-years (PY) in total. <i>Sample</i>: 200 persons starting OAT 1998–2007. <i>Data sources</i>: hospital records, interviews, the Norwegian Cause of Death Registry, Statistics Norway. <b><i>Results:</i></b> Retention: 86.4% of the observation period was on OAT, 9.0% off, 4.6% unknown OAT status. All-cause crude mortality rate per 100 PY during the whole observation period was 1.64 (95% CI: 1.19–2.20), for deaths of somatic cause 0.88 (0.56–1.31), for drug-induced deaths 0.44 (0.23–0.76), and traumatic deaths 0.24 (0.10–0.50). Off-versus-on-OAT all-cause mortality ratio was 2.31 (1.00–4.85). On OAT, 58% of the deaths were of somatic cause and 21% drug-induced; off OAT, 38% of somatic cause and 50% drug-induced. Increasing baseline age and rate of somatic hospital treatment episodes were independently associated with <i>increased</i> all-cause mortality risk, while increasing rate of in-patient psychiatric treatment episodes was associated with <i>reduced</i> risk. Increasing duration of nicotine and cannabis use and alcohol dependence as well as increasing severity of polydrug use were associated with increased all-cause and somatic mortality adjusted for age and sex. <b><i>Conclusion:</i></b> The long observation period made it possible to demonstrate the importance of long-term retention in OAT to reduce mortality. Further, the preponderance of somatic and reduction of drug-induced causes of death during OAT underlines the need for follow-up of chronic diseases and health-promoting lifestyle changes. These findings add to the knowledge about long-term OAT effects, not least in ageing OAT populations.