cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11186455
title: Morphological/WB/ELISA/cell counting data of the paper 'Serotonergic and dopaminergic neurons in the dorsal raphe are differentially altered in a mouse model for parkinsonism'
title: Morphology Data/Suppl.Fig.4-5

description: The files contain the data included in Figure 2B, Figure 2C, Figure 4B, Figure 4C, Figure 6B, Figure 6C, Suppl.Fig.4, Suppl. Figure 5, Suppl. Figure 6I, Suppl. Figure 6J.
DOI: 10.5281/zenodo.11371818
title: Electrophysiological data of the paper 'Serotonergic and dopaminergic neurons in the dorsal raphe are differentially altered in a mouse model for parkinsonism'

description: This excel data set contains the electrophysiological data presented in the paper including figure 1I, 1J, figure 3, figure 5, suppl. figure 2A, suppl. figure 3, suppl. figure 6E, 6G, 6L & 6N.

 

More information about how the data was extracted can be found in the materials and methods section of the paper.
DOI: 10.5281/zenodo.1185579
title: Microclimate In Cocoa Production Systems Data

description: This dataset contains the canopy openness and light, throughfall, temperature and relative humidity of cocoa monocultures and agroforestry systems within a long-term trial in Alto Beni, Bolivia. The dataset has be described in the Article "Shade trees and tree pruning alter throughfall and microclimate in cocoa (<em>Theobroma cacao</em> L.) production systems" published in Annals of Forest Science. Please cite both, the article and the DOI of the dataset when making use of the data.
DOI: 10.5281/zenodo.7786276
title: CoastSeg: Shoreline data at 30-m spatial resolution for 5x5 degree regions of the world, in geoJSON format.

description: <em><strong>CoastSeg: global 30-m shoreline in 5x5 degree chunks</strong></em> Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 Metadata file (each file listed alongside the bounds in WGS84 latitude/longitude): global_5x5grid.geojson
DOI: 10.5281/zenodo.8307371
title: H2020 ENODISE: TUD Experimental database configuration B1

description: This dataset contains experimental data for aerodynamics and acoustics of configuration B1, which was defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise). The measurements were taken in the Low-Speed, Low-Turbulence Tunnel (LTT) at Delft University of Technology, using a Distributed Electric Propulsion (DEP) configuration model that consists of three propellers installed side-by-side on the leading edge of a wing.
DOI: 10.5286/isis.e.rb1810304
title: Can we use the H-H stretch of adsorbed dihydrogen to characterise materials?

description: The use of the J 0-to-1 rotational transition of dihydrogen has been extensively used to characterise the state if hydrogen in and on materials. The disadvantage of studying the rotational transition is that it is very difficult to model. These difficulties could be reduced by studying the fundamental stretch vibration at 4161 cm-1, because the calculation is now a conventional ab initio lattice dynamics problem, which are tractable with CASTEP. It is proposed to study the metal organic framework materials Cu-BTC and Fe-BTC using both the HH stretch at ~4100 cm-1 and the J 0-to-1 rotational line at 120 cm-1. Parahydrogen will be used to both simplify the spectra and increase the signal.
DOI: 10.6084/m9.figshare.24916536
title: Supplementary Material for: Pattern of expression of microRNA in patients with radiation induced bladder injury

description: Introduction: Bladder cancer (BC) is sensitive to radiation treatment and a subset of patient experiences radiation induced injuries including shrinkage of bladder due to bladder fibrosis. 
Methods: Using a micro-RNA (miRNA) array comparing patient’s samples with, or without radiation induced injuries, we have checked the clustering of miRNA expression. 
Results: Hsa-miR-130a, hsa-miR-200c, hsa-miR-141, and hsa-miR-96 were found to be highly expressed (&gt;50 times) in patients with fibrotic bladder shrinkage (FBS) compared to those with intact bladder (IB) function. In patients with FBS, hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 were detected to have lesser than half expression to IB patients. We have analyzed the significance of these genes in relation to overall survival of 409 BC patients retrieved from TCGA data set. We have run combined survival analysis of mean expression of these four miRNAs highly expressed in FBS patients. 175 patients with high expression had longer median survival of 98.47 months than 23.73 months in 233 patients with low expression (HR: 0.53; 0.39 – 0.72, logrank P value: 7.3e-0.5). Combination analysis of all 8 genes including hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 showed the same HR for OS. Target scanning for these miRNAs matched specific cytokines known as an early biomarker to develop radiation induced fibrosis.
Conclusions: BC patients with fibrotic radiation injury have specific miRNA expression profile targeting pro-fibrotic cytokines and these miRNAs possibly renders to favorable survival.
DOI: 10.6084/m9.figshare.25232234
title: Supplementary Material for: Urothelial cell carcinoma of the bladder and urinary bladder rupture: a rare cause of acute peritonitis

description: Introduction: Urothelial carcinoma of the bladder causing spontaneous rupture of the bladder is an extremely rare condition with poor outcomes due to it being highly suggestive of advanced malignancy. 
Case Presentation: We present the case of a 74-year-old man who presented with non-specific signs and symptoms of abdominal pain and haematuria. Abdominal imaging were suggestive of a small bowel obstruction and a bowel perforation. At time of laparotomy however, the patient was found to have metastatic urothelial carcinoma with peritoneal metastases. The patient unfortunately passed away two months following their initial presentation. 
Conclusion: Bladder perforation secondary to urothelial cancer is a rare pathology associated with poor prognosis. There are fewer than thirty cases reported in the literature and it is often not considered during initial diagnostic workup of patients with abdominal sepsis in the context of bladder cancer. A high degree of suspicion for bladder rupture is recommended in patients with peritonism and urinary symptoms. Awareness of this condition will help facilitate prompt diagnosis and appropriate management.
DOI: 10.6084/m9.figshare.25593138
title: Supplementary Material.pdf

description: supplementary material
DOI: 10.6084/m9.figshare.26013145
title: <b>The high-quality chromosome-level genome assembly of </b><b>Guide Black-Fur sheep (</b><b><i>Ovis aries</i></b><b>)</b>

description: Files of chromosome assembly, genome annotation for the manuscript entitled "The high-quality chromosome-level genome assembly of Guide Black-Fur sheep (Ovis aries)".
DOI: 10.1594/pangaea.955777
title: Water colour spectro-radiometry platform raw data (cau_boeoetle_1) from pack ice during legs 4 and 5 of the MOSAiC expedition with POLARSTERN to the Arctic Ocean

description: This raw dataset contains in-situ hyperspectral and co-located water depth measurments from melt ponds on Legs 4 & 5 of the MOSAiC Expedition, collected by Böötle. The dataset allows to calculate remote sensing reflectance (R_rs) over melt ponds with associated melt pond water depth measurements.The small Böötle remote controlled water colour spectro-radiometry platform allows for the simultaneous collection of hyperspectral, bathymetric and temperature data in waters as shallow as 15cm. It is equipped with three OceanOptics STS-VIS spectro-radiometers (downwelling above-water and below-water irradiance, upwelling below-water radiance), a Tritech PA500 point sonar (water depth), and a DS18B20 temperature probe (subsurface water temperature). Propulsion is achieved by two air screws, thereby limiting the impact on the water column and the bottom substrate. The platform is remotely controlled by the operator with a maximum range of 100m. A web interface is provided via a wireless network, which allows for configuration and control of the sensor array. With a GPS receiver and two camera based systems, three independent localization systems are available. Data of each deployment is collected into a zip/tar file, holding a folder of plain text raw data (spectra, depth, GPS position) and image-based raw data (on-board all-sky camera; on-board and on-shore action cams (AC folders)). Digital copies of field notes (if any) are also included.
description: The Development of a hyperspectral measurement platform was supported by Prof. Dr. Werner Petersen-Stiftung (funding number 610).
DOI: 10.18419/darus-1666/27
title: 00004184.JPG

description: :unav
DOI: 10.18419/darus-1666/29
title: 00004212.JPG

description: :unav
DOI: 10.18419/darus-1666/30
title: 00004224.JPG

description: :unav
DOI: 10.18419/darus-1666/31
title: 00004174.JPG

description: :unav
DOI: 10.25326/449
title: DARDAR CLOUD - Heymfield's composite mass-size relationship

description: DARDAR CLOUD products (raDAR/liDAR cloud parameter retrievals)
CALIPSO/CALIOP-CloudSat/CPR Radar-Lidar Cloud  Level 2 Product

This synergetic ice cloud retrieval product is derived from the combination of the CloudSat radar, the CALIPSO lidar and MODIS measurements. The algorithm used to retrieve ice cloud properties, within a variational framework, is referred to as Varcloud. It was developed at the University of Reading by Julien Delanoë and Robin Hogan, Delanoë and Hogan (2008, 2010). Ice cloud retrievals are available at CloudSat horizontal resolution (1.4km) and CALIPSO vertical resolution (60m). This algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content and effective radius in ice clouds using the combination of radar reflectivity, lidar attenuated backscatter. The forward model includes effects such as non-Rayleigh scattering by the radar and molecular and multiple scattering by the lidar. By rigorous treatment of errors, and a careful choice of state variables and associated a priori estimates, a seamless retrieval is possible between regions of the cloud detected by both radar and lidar, and regions detected by just one of these two instruments. Thus, when the lidar signal is unavailable (such as due to strong attenuation), the retrieval tends towards an empirical relationship using radar reflectivity factor and temperature, and when the radar signal is unavailable (such as in optically thin cirrus), the a priori information is used to support lidar measurement.

<b>Important note: this declination uses the Heymfield's composite mass/size relationship</b> (Delanoë et al. 2013, https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013JD020700). An another declination based on the Brown and Francis modified one  is also available. As shown in Cazenave et al. 2019 (https://amt.copernicus.org/articles/12/2819/2019/) one of the major hypotheses in the retrieval is the mass-size relationship. Therefore you might use both products in order to assess the impact of this choice on your study.

You could refer to Listowski et al. 2020 for a comparison between the two products (https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL088785)
DOI: 10.25326/450
title: DARDAR CLOUD - Brown and Francis mass-size relationship

description: DARDAR CLOUD products (raDAR/liDAR cloud parameter retrievals)
CALIPSO/CALIOP-CloudSat/CPR Radar-Lidar Cloud  Level 2 Product

This synergetic ice cloud retrieval product is derived from the combination of the CloudSat radar, the CALIPSO lidar and MODIS measurements. The algorithm used to retrieve ice cloud properties, within a variational framework, is referred to as Varcloud. It was developed at the University of Reading by Julien Delanoë and Robin Hogan, Delanoë and Hogan (2008, 2010). Ice cloud retrievals are available at CloudSat horizontal resolution (1.4km) and CALIPSO vertical resolution (60m). This algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content and effective radius in ice clouds using the combination of radar reflectivity, lidar attenuated backscatter. The forward model includes effects such as non-Rayleigh scattering by the radar and molecular and multiple scattering by the lidar. By rigorous treatment of errors, and a careful choice of state variables and associated a priori estimates, a seamless retrieval is possible between regions of the cloud detected by both radar and lidar, and regions detected by just one of these two instruments. Thus, when the lidar signal is unavailable (such as due to strong attenuation), the retrieval tends towards an empirical relationship using radar reflectivity factor and temperature, and when the radar signal is unavailable (such as in optically thin cirrus), the a priori information is used to support lidar measurement.

<b>Important note: this declination uses the Brown and Francis modified mass/size relationship.</b> This is the one used in previous versions of the product. An another declination based on the Heymsfield's composite one (Delanoë et al. 2013, https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013JD020700) is also available.
As shown in Cazenave et al. 2019 (https://amt.copernicus.org/articles/12/2819/2019/) one of the major hypotheses in the retrieval is the mass-size relationship. Therefore you might use both products in order to assess the impact of this choice on your study.

You could refer to Listowski et al. 2020 for a comparison between the two products (https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL088785).
DOI: 10.4121/0c6f100c-cf16-4fe1-81fe-afcafabdc7ca.v1
title: Replication data for: Reducing hardware requirements for entanglement distribution via joint hardware-protocol optimization

description: This is the data corresponding to the publication "Reducing hardware requirements for entanglement distribution via joint hardware-protocol optimization". It contains the raw data resulting from all the optimization runs performed (see publication for details).
DOI: 10.5281/zenodo.11066607
title: Dataset of paper "Neural Network Modeling of Black Box Controls for Internal Combustion Engine Calibration"

description: These are the two training datasets for the Exhaust Temperature Model (ETM) and the Three-Way Catalyst Control Lambda Set Point (TWCC) Model, used in Black-Box Modeling, such as through Neural Networks.

The datasets for each black box model are stored in XLSX files. Each dataset file contains ECU channel inputs, related Map parameters, and output. The ECU channel inputs and Map parameters are collected with Sobol methods. The output is generated by Hardware-in-the-Loop (HiL) corresponding to the related ECU channel inputs and Map parameters.

The ETM model has four effective Maps, hence there are 32 corresponding shape-based algorithm parameters. Its output is the exhaust temperature. Its ECU channel inputs are as follows:

CH_1:       Intake valve cut-off condition

CH_2:       Thrust cut-off condition

CH_3:       Cylinder equalization control work cycle injection enabled

CH_4:       Ignition angle efficiency

CH_5:       Relative level of reduction

CH_6:       Lean engine lambda for cylinders on exhaust bank with lambda split

CH_7:       Rich engine lambda for cylinders on exhaust bank with lambda split

CH_8:       Exhaust gas mass flow

CH_9:       Engine speed

CH_10:     Relative air filling

CH_11:     Material temperature

CH_12:     Engine temperature

 

The TWCC model has one Map, hence there are 8 corresponding shape-based algorithm parameters. Its output is lambda set point. Its ECU channel inputs are as follows:

CH_1:       Exhaust mass flow

CH_2:       Trigger bit for inhibiting the purge

CH_3:       Trigger bit for a rich mixture

CH_4:       Trigger bit for empty catalyst

CH_5:       Trigger bit for catalyst reset

CH_6:       Oxygen storage level

CH_7:       Desired air-fuel ratio
DOI: 10.5281/zenodo.11165668
title: Model configuration and input files for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"

description: This collection hosts the configuration and input files to reproduce the regional CESM/MOM6 simulation in: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". The initial, open boundary conditions and monthly means for the sponge layers were generated from the GLORYS12V1 reanalysis: https://doi.org/10.3389/feart.2021.698876

The tidal amplitudes and phases were generated from the TPXO model: https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2 

The monthly Chlorophyll-a climatology was generated from the SeaWifs mission dataset: 10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018

The river runoff to ocean was generated from the GloFAS dataset: https://doi.org/10.24381/cds.a4fdd6b9 

The topography was generated from the Shuttle Radar Topography Mission: https://doi.org/10.1029/2019EA000658 and smoothed with a Cressman weighted interpolation scheme.

This collection does not include the JRA55-do atmospheric forcing dataset: https://doi.org/10.1016/j.ocemod.2018.07.002 

Steps to setup a regional configuration of CESM/MOM6 can be found here: https://github.com/NCAR/regional_cesm_mom6.git
DOI: 10.5281/zenodo.11264009
title: Model output for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"

description: This collection hosts the model output fields used in : "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". daily_surface_fields.tar: contains daily output of sea surface salinity, surface u and v velocity components, sea-surface height and mixed layer depths. Files are split in two: 2000-01-01:2009-12-31 and 2010-01-01:2019-12-31 as specified by each filename.

monthly_3D_tracers.tar: contains monthly mean output of temperature and salinity for the full 3D field (lat,lon,depth). Files are split in two: 2000-01-01:2009-12-31 and 2010-01-01:2019-12-31 as specified by each filename.
DOI: 10.5281/zenodo.11267615
title: Trajectories of backtracked passive particles for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"

description: This collection hosts the trajectories of bactracked passive particles using Ocean Parcels v2.0 (The Parcels v2.0 Lagrangian framework: new field interpolation schemes. Delandmeter, P and E van Sebille (2019), Geoscientific Model Development, 12, 3571–3584) and ocean surface velocity fields from the output of: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". 

trajectories_2009.tar: trajectories for particles released between 2009-01-01 and 2009-12-31

trajectories_2010.tar: trajectories for particles released between 2010-01-01 and 2010-12-31 (as shown in "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea")

trajectories_2011.tar: trajectories for particles released between 2011-01-01 and 2011-12-31

release_sites.csv: release sites for each release date.

ocean_parcels_backtrack_VIB_carib12.py : python script to run ocean parcels to generate the trajectories published here.
DOI: 10.5281/zenodo.12188016
title: ICESat-2 Sea Ice Surface Topography from the University of Maryland-Ridge Detection Algorithm: Coastal Alaska

description: This dataset is derived from the ICESat-2 Global Geolocated Photon Height Product (ATL03, Neumann et al., 2023), release 006, using the University of Maryland-Ridge Detection Algorithm (UMD-RDA, Duncan & Farrell, 2022). The UMD-RDA is applied to ATL03 granules on a per-shot basis, nominally resulting in elevation measurements at ICESat-2's along-track sampling of ~0.7 m.

Data Bounds: 

LL corner: (-169.71, 68.32), UR corner: (-137.1, 72.18)

 

File Format

Coastal Alaska data are provided in .xz compressed format and decompress to ascii text. The columns are as follows:



Longitude (degrees)

Latitude (degrees)

Time (seconds since 2018-01-01)

Elevation (meters, relative to DTU18 Mean Sea Surface)


Data are provided monthly for the period December 2021 (202112) to May 2022 (202205).

 

Users of this dataset are asked to cite the following publication:

Duncan, K. and Farrell, S. L. (2022). Determining Variability in Arctic Sea Ice Pressure Ridge Topography with ICESat-2. Geophys. Res. Lett., 49, e2022GL100272. https://doi.org/10.1029/2022GL100272

 

For any questions regarding this dataset you can contact Kyle Duncan by email: kduncan at umd . edu
DOI: 10.5281/zenodo.4600706
title: Transient global warming levels for CMIP5 and CMIP6

description: year when a certain global warming level was reached in cmip5 and cmip6 data
DOI: 10.5281/zenodo.6601980
title: FaIR v1.6.2 calibrated and constrained parameter set

description: These .json files provides the 2237 ensemble members that are used to run the FaIR simple climate model in the IPCC's Sixth Assessment Report contributions to Working Group 1 and Working Group 3. v1.1 of this dataset includes two versions of the files: the original full parameter set `fair-1.6.2-wg3-params.json` as in v1.0 reduced file size versions `fair-1.6.2-wg3-params-slim.json` and `fair-1.6.2-wg3-params-common.json` where only the parameters that vary between ensemble members are included in the former and everything else is in the latter. This is optimised for running the Working Group 3 climate assessment. Drawn from an initial prior ensemble of 1 million, the following constraints are placed upon the results: representation of observed warming from 1850-2019, within observational uncertainty representation of observed ocean heat content change 1971-2018, within observational uncertainty reproduction of near-present day atmospheric concentrations of CO2 from the carbon cycle airborne fraction of CO2 with a distribution similar to the assessed range of Chapter 5, IPCC Working Group 1 AR6 equilibrium climate sensitivity with a similar distribution to Chapter 7, IPCC Working Group 1, AR6 transient climate response with a similar distribution to Chapter 7, IPCC Working Group 1, AR6 projected future warming that is of a similar distribution to the SSP scenarios of Chapter 4, IPCC Working Group 1, AR6, when run with prescribed concentrations <strong>Changelog</strong> v1.1: inclusion of lightweight parameter sets. v1.0: original upload full parameter sets.