cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j2c62mbp6f.1
title: Seasonal water and fuel collection Halaba, Ethiopia

description: This data is a subset of a larger data set which was collected from 112 households across 4 kebeles of Halaba Special Woreda in 2017. It relates to the use of organic resources such as crop residues and cow dung as well as fuel use and water collection times between wet season and dry season. A key to the column headings is provided in the second worksheet. It is other wise formatted to be readable in R. The information was collected in view of establishing the feasibility of small-scale biogas digesters in the areas. However, it can be useful for many other purposes. Small differences may occur to figures in the linked manuscript due to the number of decimal places used.
DOI: 10.17632/vrg995gjzh.3
title: Community Level Child Mortality Data, Nigeria

description: The study was conducted in 2018 on the factors determining child mortality at the community level in Nigeria were this kind of data is rarely available. The data collection was done by employing multi-stage cross-sectional survey technique conducted at the Local Government Area (LGA), Primary Health Care (PHC) facilities, and at he individual levels.The unit of analysis is pregnant women attending ante-natal care who had given birth to at least a child three years before the time of the study. The total sample was 1350 pregnant women collected at 20 Primary Health Care facilities in Ifo Local Government Area of Ogun State Nigeria. Key data collected included socio-demographic characteristics, environmental factors, child mortality, immunization, breastfeeding practices, preventable diseases, accessibility to health facilities among others.
DOI: 10.5281/zenodo.3713530
title: Canadian Fire Weather System - WRF/NOA

description: The <strong>Canadian FWI System </strong>(Van Wagner, 1987) is a sub-system of the Canadian Fire Danger Rating System (Stocks et al., 1989), comprised of <strong>five components</strong> that consider the effects of fuel moisture and wind on fire behavior. The first three components, called <strong>fuel moisture codes</strong>, are numeric ratings of <strong>(1) </strong>the moisture content of surface litter and other fine fuels (fine fuel moisture code; <strong>FFMC</strong>), <strong>(2)</strong> the average moisture content of loosely compacted organic material (duff moisture code; <strong>DMC</strong>), and <strong>(3)</strong> the average moisture content of deep layers of organic material (drought code; <strong>DC</strong>). The remaining two components are related to <strong>fire behavior and spread</strong>: <strong>(1)</strong> the initial spread index (<strong>ISI</strong>), which represents the rate of spread, and <strong>(2) </strong>the build-up index (<strong>BUI</strong>), which represents the potential fuel availability. The above five parameters are finally combined for computing the <strong>fire weather index</strong> (hereafter referred to as the <strong>FWI</strong>), which represents the intensity of a spreading fire per unit length of fire front and is used as an indicator of fire danger. Computation of the Canadian Fire Weather System components was carried out using <strong>12 UTC meteorological data</strong> extracted from <strong>high-resolution (~12 km) WRF simulations</strong>, focussing on the <strong>Euro-Mediterranean region</strong>. These data include the 24 h accumulated precipitation (mm), 2 m air temperature (<sup>o</sup>C) and relative humidity (%), and 10 m wind speed (km h<sup>-1</sup>). It should be noted that normally, FWI is computed using meteorological data at 12 local time. The use of the 12 UTC data in our study is dictated by the fact that the Euro-Mediterranean encompasses different time zones (e.g. Bedia et al., 2012, 2018; Herrera et al., 2013). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326) Longitude range: [-9.91, +36.4] Latitude range: [+32.1, +48.93] Temporal resolution: 1 day (at 12 UTC) Spatial resolution: 0.12 degrees (~12 Km) Spatial coverage: Euro-Mediterranean Time span: May 1 to September 30, for the years 1987-2016 Stream: Regional climate simulations (driven by the WRF model)
DOI: 10.5281/zenodo.3713531
title: Canadian Fire Weather System - WRF/NOA

description: The <strong>Canadian FWI System </strong>(Van Wagner, 1987) is a sub-system of the Canadian Fire Danger Rating System (Stocks et al., 1989), comprised of <strong>five components</strong> that consider the effects of fuel moisture and wind on fire behavior. The first three components, called <strong>fuel moisture codes</strong>, are numeric ratings of <strong>(1) </strong>the moisture content of surface litter and other fine fuels (fine fuel moisture code; <strong>FFMC</strong>), <strong>(2)</strong> the average moisture content of loosely compacted organic material (duff moisture code; <strong>DMC</strong>), and <strong>(3)</strong> the average moisture content of deep layers of organic material (drought code; <strong>DC</strong>). The remaining two components are related to <strong>fire behavior and spread</strong>: <strong>(1)</strong> the initial spread index (<strong>ISI</strong>), which represents the rate of spread, and <strong>(2) </strong>the build-up index (<strong>BUI</strong>), which represents the potential fuel availability. The above five parameters are finally combined for computing the <strong>fire weather index</strong> (hereafter referred to as the <strong>FWI</strong>), which represents the intensity of a spreading fire per unit length of fire front and is used as an indicator of fire danger. Computation of the Canadian Fire Weather System components was carried out using <strong>12 UTC meteorological data</strong> extracted from <strong>high-resolution (~12 km) WRF simulations</strong>, focussing on the <strong>Euro-Mediterranean region</strong>. These data include the 24 h accumulated precipitation (mm), 2 m air temperature (<sup>o</sup>C) and relative humidity (%), and 10 m wind speed (km h<sup>-1</sup>). It should be noted that normally, FWI is computed using meteorological data at 12 local time. The use of the 12 UTC data in our study is dictated by the fact that the Euro-Mediterranean encompasses different time zones (e.g. Bedia et al., 2012, 2018; Herrera et al., 2013). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326) Longitude range: [-9.91, +36.4] Latitude range: [+32.1, +48.93] Temporal resolution: 1 day (at 12 UTC) Spatial resolution: 0.12 degrees (~12 Km) Spatial coverage: Euro-Mediterranean Time span: May 1 to September 30, for the years 1987-2016 Stream: Regional climate simulations (driven by the WRF model)
DOI: 10.5281/zenodo.3733255
title: Adjoint-based Data Assimilation of an Epidemiology Model for the Covid-19 Pandemic in 2020 --- Data Files

description: New data on github: https://github.com/sesterhenn/Corona-DataAssimilation doi://10.5281/zenodo.3732292 https://zenodo.org/record/3733244
description: See: https://zenodo.org/record/3733244
DOI: 10.5281/zenodo.3733256
title: Adjoint-based Data Assimilation of an Epidemiology Model for the Covid-19 Pandemic in 2020 --- Data Files

description: New data on github: https://github.com/sesterhenn/Corona-DataAssimilation doi://10.5281/zenodo.3732292 https://zenodo.org/record/3733244
description: See: https://zenodo.org/record/3733244
DOI: 10.15129/d4055a23-f2f7-482d-9cb2-4e15960b17f6
title: Code for: "Probabilistic Access Forecasting for Improved Offshore Operations"

description: Code used to generate the results from the research paper: "Probabilistic Access Forecasting for Improved Offshore Operations" Also includes beta version of the R package ProbCast by Jethro Browell (author, creator), and Ciaran Gilbert (author) which is not currently widely available and used extensively in the model fitting process. License: CC BY 4.0
DOI: 10.17632/gg3v3sstgs.1
title: Control of sugar and amino acid feeding via pharyngeal taste neurons

description: Raw data for 2-choice food preference assays, FLIC assays, immunofluorescence staining, pharyngeal calcium imaging, and optogenetics.
DOI: 10.17632/vmwrtj29kr.1
title: Cardiopulmonary excercise breath-by-breath data during locomotion in 6 healthy young subjects

description: Ergospyrometric evaluations are useful in physio-mechanics of locomotion. This dataset includes the raw ergospyrometric data of 6 young subjects during locomotion on a treadmill at different speeds and gaits. Characteristics of the experimental group: - gender: 5 males and 1 female - age: 26.5 (2.3 SD) - height: 171.5 cm (5.5 SD) - weight: 72.2 kg (7.5 SD) Equipments: - Cosmed K5 wearable metabolic analyzer - Software Cosmed Omnia v.1.6.5 Experimental design: Subjects were first asked to stand in orthostasis for 5' in order to assess their oxygen consumption in resting conditions. Then they were asked to walk, run and gallop (skipping) on the treadmill. Trial lasted 5' each, in order to reach a stable oxygen consumption during the last 2' of each one. Walk: the walking trials were performed one after the other at 2.0, 3.0, 4.0, 5.0, 6.0 km/h, as the effort was light and there were no signs of fatigue. A stable O2 consumption was reached shortly after the beginning of each step. Run: five trials (7.0, 8.5, 10.0, 11.5, 13.0 km/h) were performed in aleatory order. After each trial the subject rested 4 to 6', until his/her parameters returned to the rest conditions. Skipping: four trials (4.0, 5.5, 7.0, 8.5 km/h)* were performed in aleatory order. After each trial the subject rested 4 to 6', until his/her parameters returned to the rest conditions. (* One subject skip at 3.0, 5.0, 7.0, 9.0 km/h). Note: not all the subject performed the entire protocol. In particular some data are lacking in walking and skipping. Cost of Transport Analysis: - The resting O2 (RO2) consumption was computed as the averaged VO2 (ml/min/kg) of the 5' in orthostasis. - The trial O2 (TO2) consumption was computed as the averaged VO2 (ml/min/kg) of the last 2' of each speed trial - The exercise O2 (EO2) consumption was computed as TO2 - RO2 - The trial respiratory quotient (RQ) was computed as the averaged RQ (VCO2/VO2) of the last 2' of each speed trial - The RQ based Energetic Equivalent (EE) to transform mlO2 in Joules was derived from Di Prampero (2015). - The metabolic power (W/kg) was computed as (EO2 * EE) / 60 (remember that W = J/s) - The Cost of transport (J/kg/m) was computed by dividing the metabolic power for the speed (m/s) (Saibene and Minetti, 2003) All the participants signed an informed consent. The protocol was approved by the Ethical Committee of the University (#003065-000653-16). References: Di Prampero, P. E. (2015). La locomozione umana su terra, in acqua, in aria. Edi-Ermes, Milano. Saibene, F., & Minetti, A. E. (2003). Biomechanical and physiological aspects of legged locomotion in humans. European journal of applied physiology, 88(4-5), 297-316.
DOI: 10.25919/5e82989a39f81
title: Parkes observations for project P595 semester 2019OCTS_15

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the FERMI Gamma ray mission, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.
DOI: 10.5525/gla.researchdata.882
title: Two-photon Quantum Interference and Entanglement at 2.1 μm

description: This data set contains the data related to the manuscript titled "Two-photon Quantum Interference and Entanglement at 2.1 μm"
DOI: 10.17632/n8w9n7rgz3.1
title: Convalescent plasma：Possible therapy for COVID-19

description: The recent Corona Virus Disease 2019(COVID-19) epidemic is spreading all over the world. So far, no specific effective treatment has been developed for COVID-19 except for meticulous supportive care including critical care and organ support when necessary. Evidence shows that convalescent plasma from patients who have recovered from viral infections could be used as a treatment without the occurrence of severe adverse events when a specific treatment is not available. Hence, we provides an overview of convalescent plasma as a possible therapy for COVID-19.
DOI: 10.21227/dzkc-mr06
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 13,419,667This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the LSTM model deployed here at sentiment.live. The model monitors the real-time Twitter feed for corona virus-related tweets. As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).Schema of the CSV files: First column: tweet ID, Second column: Sentiment score for the particular tweet.Files details (time: GMT+5:45):corona_tweets_01.csv: 831,327 tweets (March 20, 2020 01:37 AM - March 20, 2020 10:28 AM)corona_tweets_02.csv: 870,924 tweets (March 20, 2020 10:31 AM - March 20, 2020 09:43 PM)corona_tweets_03.csv: 773,729 tweets (March 20, 2020 09:49 PM - March 21, 2020 09:25 AM)corona_tweets_04.csv: 1,233,340 tweets (March 21, 2020 09:27 AM - March 22, 2020 07:46 AM)corona_tweets_05.csv: 1,782,157 tweets (March 22, 2020 07:50 AM - March 23, 2020 09:08 AM)corona_tweets_06.csv: 1,771,295 tweets (March 23, 2020 09:11 AM - March 24, 2020 11:35 AM)corona_tweets_07.csv: 1,479,651 tweets (March 24, 2020 11:42 AM - March 25, 2020 11:43 AM)corona_tweets_08.csv: 1,272,592 tweets (March 25, 2020 11:47 AM - March 26, 2020 12:46 PM)corona_tweets_09.csv: 1,091,429 tweets (March 26, 2020 12:51 PM - March 27, 2020 11:53 AM)corona_tweets_10.csv: 1,172,013 tweets (March 27, 2020 11:56 AM - March 28, 2020 01:59 PM)corona_tweets_11.csv: 1,141,210 tweets (March 28, 2020 02:03 PM - March 29, 2020 04:01 PM)----- March 29, 2020 04:05 PM - March 30, 2020 12:30 PM -- Some folk(s) messed around with the server. DoS attack most probably. Tweets for this period won't be available. However, I'll be continuing adding the new Tweet IDs. Some preventive measures have been taken. Sorry for the inconvenience. -----To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [1] has been appended as the second column. New databases will be added to this dataset every day. Bookmark this page for further updates. [1] https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/xt2p-fg98
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 13,419,667This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the LSTM model deployed here at sentiment.live. The model monitors the real-time Twitter feed for corona virus-related tweets. As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).Schema of the CSV files: First column: tweet ID, Second column: Sentiment score for the particular tweet.Files details (time: GMT+5:45):corona_tweets_01.csv: 831,327 tweets (March 20, 2020 01:37 AM - March 20, 2020 10:28 AM)corona_tweets_02.csv: 870,924 tweets (March 20, 2020 10:31 AM - March 20, 2020 09:43 PM)corona_tweets_03.csv: 773,729 tweets (March 20, 2020 09:49 PM - March 21, 2020 09:25 AM)corona_tweets_04.csv: 1,233,340 tweets (March 21, 2020 09:27 AM - March 22, 2020 07:46 AM)corona_tweets_05.csv: 1,782,157 tweets (March 22, 2020 07:50 AM - March 23, 2020 09:08 AM)corona_tweets_06.csv: 1,771,295 tweets (March 23, 2020 09:11 AM - March 24, 2020 11:35 AM)corona_tweets_07.csv: 1,479,651 tweets (March 24, 2020 11:42 AM - March 25, 2020 11:43 AM)corona_tweets_08.csv: 1,272,592 tweets (March 25, 2020 11:47 AM - March 26, 2020 12:46 PM)corona_tweets_09.csv: 1,091,429 tweets (March 26, 2020 12:51 PM - March 27, 2020 11:53 AM)corona_tweets_10.csv: 1,172,013 tweets (March 27, 2020 11:56 AM - March 28, 2020 01:59 PM)corona_tweets_11.csv: 1,141,210 tweets (March 28, 2020 02:03 PM - March 29, 2020 04:01 PM)----- March 29, 2020 04:05 PM - March 30, 2020 12:30 PM -- Some folk(s) messed around with the server. DoS most probably. Tweets for this period won't be available. However, I'll be continuing adding the new Tweet IDs. Some preventive measures have been taken. Sorry for the inconvenience. -----To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [1] has been appended as the second column. New databases will be added to this dataset every day. Bookmark this page for further updates. [1] https://textblob.readthedocs.io/en/dev/
DOI: 10.25919/5e829eb202b39
title: Parkes observations for project P595 semester 2019OCTS_16

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the FERMI Gamma ray mission, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.
DOI: 10.25345/c5xd69
title: MassIVE MSV000085196 - AP-MS analysis using Flp-In-293 cells stably expressing SUDS3 with N-terminal HaloTag
title: AP-MS analysis using Flp-In-293 cells stably expressing SUDS3 with N-terminal HaloTag
DOI: 10.5281/zenodo.3724443
title: Reproduction package for paper "Forecasts for detecting the gravitational-wave memory effect with Advanced LIGO and Virgo"

description: This is a basic reproduction package for the paper "Forecasts for detecting the gravitational-wave memory effect with Advanced LIGO and Virgo".
description: O. M. B. acknowledges funding from Vici research program "ARGO" with Project No. 639.043.815, financed by the Dutch Research Council (NWO). D. A. N. acknowledges the support of the Netherlands Organization for Scientific Research through the NWO VIDI Grant No. 639.042.612-Nissanke. P. S. acknowledges NWO Veni Grant No. 680-47-460.
DOI: 10.5281/zenodo.3733884
title: Gradients1-KOK1606-Hyperpro-Profiles_2020-03-25_v1.0

description: Cruise: KOK1606, Gradients 1 Project Name: Simons Foundation, Gradients NPSG Description: The Satlantic (now Seabird) HyperPro is an in-situ free-fall profiling unit designed to measure the apparent optical properties of the ocean with concurrent measurements of temperature, salinity, chlorophyll and dissolved matter fluorescence, and optical backscattering (a proxy for total particle load). The unit is equipped with one up-looking and one down-looking hyperspectral (350-800nm) radiometer with 10 ± 0.3 nm resolution, a WET Labs ECO-Puck Triplet, and temperature, pressure, and conductivity sensors. It also incorporates a ship-mounted surface (air) hyperspectral radiometer. These data are collated from the vertical profiles conducted during the Gradients I cruise.
DOI: 10.17632/h7gtk8s2p6.1
title: Data for: Origin of dissolved gas (CO2, O2, N2, alkanes) in pore waters of a clay formation in the critical zone (Tégulines Clay, France)

description: The supplementary data file includes the gas measurements obtained by core degassing in all the samples from this study and calculated concentrations of dissolved gas.
DOI: 10.25345/c5m40g
title: MassIVE MSV000085183 - Metabolomics dataset for manuscript "The omega-3 fatty acid 7(S)-HDHA is a physiological ligand for PPARalpha"
title: A pull-down assay by incubating the His-tagged PPARalpha-LBD with various brain tissue (cortex, cerebellum, and hippocampus) extracts.
DOI: 10.17632/42dgdr7dmw.2
title: Data for: Radiolarian assemblage as an indicator of environmental conditions in the marginal seas of the Western North Pacific

description: Supplementary material Supplementary material Table 1, Taxonomic information of total radiolarian taxa encountered in study. Supplementary material Table 2, Basic environmental informations with annual, summer, and winter timescales of the 45 surface sediment samples. Supplementary material Table 3, Raw counting data of the total radiolarian assemblages in the 45 surface sediment samples.
DOI: 10.25919/5e82a79f5aeef
title: Parkes observations for project P895 semester 2019OCTS_02

description: Since the year 2005, the Parkes Pulsar Timing Array (PPTA) project has been placing ever more stringent constraints on the amplitude of a gravitational wave background signal. Such upper bounds on the amplitude of the gravitational wave signal are currently dominated by a single pulsar: PSR J1909-3744. The upper bound with this pulsar alone already cuts into the range of tenable theoretical models. Further reducing the amplitude bound (by continued regular observations of this pulsar) will significantly narrow that range. The first evidence of gravitational waves in the pulsar data are likely to be observed in the timing for PSR J1909-3744, but with only a single pulsar we will not be able to make an unambiguous detection. However, knowledge of the likely signal strength (derived from this pulsar) will help to optimise the observing strategy for the detection of the gravitational wave signals with existing or future pulsar timing arrays.
DOI: 10.25919/5e82a79f72bf0
title: Parkes observations for project P595 semester 2019OCTS_17

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the FERMI Gamma ray mission, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.