cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3958314
title: Gradients1-KOK1606-DiazotrophAbundance_2020-03-04_v1.2

description: Cruise Name: Gradients 1.0 / KOK1606 Project Name: SIMONS Foundation NPSG Gradient At select stations and depths (ranging from 5 to 45m), the entire volume of a Niskin bottle was drained directly into clean ~10L carboys fitted with spigots. Carboys were covered in dark cloth and the volume was gravity filtered through a 47-mm diameter, 3 micron pore size and 10 micron pore size, black polycarbonate filter with a polyester drain disk as a backing filter. If the volume was not filtered after 2 hours, filtration was terminated and the remaining volume of the carboy was measured in order to calculate volume filtered. Following filtration, filter holders were fit with a short section of tubing and a syringe luer fitting on once side and a 2-way valve on the outflow side. For each filter, 5-ml of 2% glutaraldehyde was slowly injected onto the filter and samples were allowed to fix for 30 minutes. Fixative was drained after this time and 60ml of air was used to flush all filters. Polycarbonate filters were then mounted onto 3x2” glass slides with immersion oil, cover slides were added and the edges of each cover slip was sealed with quick dry nail polish. All slides were stored at -20°C and counted within 30 days. Enumeration of diazotrophic taxa was performed using epifluorescence microscopy.The entire slide was counted for DDAs and Trichodesimum abundance. Endosymbiont bearing diatoms of the following genus were enumerated: Rhizosolenia, Hemiaulus, Climacodium and Chaetoceras. Free Richelia intracellularis were also counted. Trichodesmium filaments were counted and the length of each filament was recorded. Trichodesmium cell number was then calculated by dividing the filament length by the mean cell length (9.9 micron ±2.5 micron).
DOI: 10.5281/zenodo.3697329
title: Gradients1-KOK1606-DiazotrophAbundance_2020-03-04_v1.2

description: Cruise Name: Gradients 1.0 / KOK1606 Project Name: SIMONS Foundation NPSG Gradient At select stations and depths (ranging from 5 to 45m), the entire volume of a Niskin bottle was drained directly into clean ~10L carboys fitted with spigots. Carboys were covered in dark cloth and the volume was gravity filtered through a 47-mm diameter, 3 micron pore size and 10 micron pore size, black polycarbonate filter with a polyester drain disk as a backing filter. If the volume was not filtered after 2 hours, filtration was terminated and the remaining volume of the carboy was measured in order to calculate volume filtered. Following filtration, filter holders were fit with a short section of tubing and a syringe luer fitting on once side and a 2-way valve on the outflow side. For each filter, 5-ml of 2% glutaraldehyde was slowly injected onto the filter and samples were allowed to fix for 30 minutes. Fixative was drained after this time and 60ml of air was used to flush all filters. Polycarbonate filters were then mounted onto 3x2” glass slides with immersion oil, cover slides were added and the edges of each cover slip was sealed with quick dry nail polish. All slides were stored at -20°C and counted within 30 days. Enumeration of diazotrophic taxa was performed using epifluorescence microscopy.The entire slide was counted for DDAs and Trichodesimum abundance. Endosymbiont bearing diatoms of the following genus were enumerated: Rhizosolenia, Hemiaulus, Climacodium and Chaetoceras. Free Richelia intracellularis were also counted. Trichodesmium filaments were counted and the length of each filament was recorded. Trichodesmium cell number was then calculated by dividing the filament length by the mean cell length (9.9 micron ±2.5 micron).
DOI: 10.5281/zenodo.3697257
title: Gradients1-KOK1606_14C-NPP_2020-03-04_V1.3

description: Cruise Name: KOK1606, Gradients 1.0. Project: Simons Foundation - Gradients NPSG Standard HOT protocols were used to measure in vitro primary productivity (PP) via the 14C radiotracer method [Karl et al., 1996]. Water samples were collected from 15m before dawn and incubated on deck in incubators screened to ~50% of surface irradiance and plumbed with flow through surface seawater for temperature regulation. Duplicate 500-ml bottles were incubated in the incubator for ~12hr and 24hr, light bottles were paired with dark bottles. Parallel samples were taken in duplicate to examine the influence of reduced light on PP for all stations. Duplicate 500-ml bottles were incubated inside mesh bags that reduced the light availability to ~25%. A time zero sample was taken at each station to ensure acidification was complete. Following dawn to dusk or dawn to dawn incubations, each sample was filtered onto a 25mm glass fiber filter. Filters were acidified with 1 ml of 2N hydrochloric acid in a fume hood for 12 hr to remove inorganic 14C after which 10 ml of Ultima Gold scintillation fluid was added to each sample. Radioactivity was determined using a Perkins Elmer 2600 liquid scintillation counter. The rate of PP was calculated by multiplying the percent of carbon labeled by the total carbon available for photosynthesis (e.g. dissolved inorganic carbon, DIC, calculated from SST and salinity measured at each station as per Lee et al. [2006]) and dividing by incubation time (t = 1 day). Rate measurements in light bottles were corrected to remove the rate measured in parallel dark bottles. Abbreviations for rate measurements are in the variable metadata. All rates are in units mg C m-3; ‘stdev’ refers to the standard deviation of duplicates for each incubation type, whereas ‘stdev-p’ refers to the propagated standard deviation. NaN’s represent stations or samples where rate measurements were not conducted.
DOI: 10.5281/zenodo.3958318
title: jellyfish data

description: DATA FOR JELLYFISH
DOI: 10.5281/zenodo.3958319
title: jellyfish data

description: DATA FOR JELLYFISH
DOI: 10.21227/rt01-w125
title: Badminton Activity Recognition (BAR)

description: The Badminton Activity Recognition (BAR) Dataset was collected for the sport of Badminton for 12 commonly played strokes. Besides the strokes, the objective of the dataset is to capture the associated leg movements.
DOI: 10.7303/syn22271040.1
title: Alertness Checker - Psychomotor Vigilance Task
DOI: 10.21227/j1z4-3a23
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2018.Composed of 13,823,630 records of flight data, each containing 50 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.21227/vpyp-2d17
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2018.Composed of 13,823,630 records of flight data, each containing 50 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.21227/kt6n-vm28
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2019.Composed of 15,948,676 records of flight data, each containing 45 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.21227/4qcv-bs89
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2019.Composed of 15,948,676 records of flight data, each containing 45 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.5281/zenodo.3958329
title: A study of Mobile Technology Capabilities and Challenges in Library Service Delivery

description: Mobile Technology has provided faster access to and delivery of information and other related services; it is also challenging the libraries and information centers to change round, modify and upgrade their services approach by implementing the new technological changes. Nowadays all mobile devices are gradually becoming an integral part of all and sundry thereby redirecting connectivity and interactions globally with dynamic feature compare to the static state of the computer technology. From the study, Mobile Technology capabilities will greatly support all forms of information access, storage, transmission etc. and provide help to researchers and users of research content to the strengthening of their relationship and providing enhanced user oriented services to existing users. The challenges facing mobile technology were also identified with a view of recommending to developers needed areas in satisfying local users. The study discusses on the capabilities and challenges of mobile technology in general services delivery
DOI: 10.5281/zenodo.3958328
title: A study of Mobile Technology Capabilities and Challenges in Library Service Delivery

description: Mobile Technology has provided faster access to and delivery of information and other related services; it is also challenging the libraries and information centers to change round, modify and upgrade their services approach by implementing the new technological changes. Nowadays all mobile devices are gradually becoming an integral part of all and sundry thereby redirecting connectivity and interactions globally with dynamic feature compare to the static state of the computer technology. From the study, Mobile Technology capabilities will greatly support all forms of information access, storage, transmission etc. and provide help to researchers and users of research content to the strengthening of their relationship and providing enhanced user oriented services to existing users. The challenges facing mobile technology were also identified with a view of recommending to developers needed areas in satisfying local users. The study discusses on the capabilities and challenges of mobile technology in general services delivery
DOI: 10.21227/44sp-ve52
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2019.Composed of 15,948,676 records of flight data, each containing 45 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.5281/zenodo.3958351
title: Climatological characteristics of thunderstorm clouds over the Tibetan Plateau indicated by TRMM/RPFs with lightning

description: The uploaded are the data associated with the figures in the paper titled "Climatological characteristics of thunderstorm clouds over the Tibetan Plateau indicated by TRMM/RPFs with lightning" which is submitted to the Journal of Climate.
DOI: 10.5519/qd.5yxekcko
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.21227/8b90-jy71
title: Trailer Mass Estimation Using System Model-Based and Machine Learning Approaches

description: A high-fidelity CarSim model is used to collect the data for almost 50 maneuvers for two different tractors with different trailer attached to them. For instance, 10 Single Lane Change (SLC) maneuvers are considered in CarSim including 5 tests with E-class SUV and 5 tests with a pick-up truck. Moreover, at each test, the trailer payload and geometry, CG location, and track width, have been changed to collect sufficient data.
DOI: 10.21227/8m8n-t819
title: Trailer Mass Estimation Using System Model-Based and Machine Learning Approaches

description: A high-fidelity CarSim model is used to collect the data for almost 50 maneuvers for two different tractors with different trailer attached to them. For instance, 10 Single Lane Change (SLC) maneuvers are considered in CarSim including 5 tests with E-class SUV and 5 tests with a pick-up truck. Moreover, at each test, the trailer payload and geometry, CG location, and track width, have been changed to collect sufficient data.
DOI: 10.5281/zenodo.3951890
title: Regionally aggregated, stitched and de-drifted CMIP-climate data, processed with netCDF-SCM v2.0.0

description: The world’s most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model<br> Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the<br> total data volume will be in the order of 20PB. Here we present a dataset of annual, monthly, global-, hemispheric- and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing simple climate models against the behaviour of physically complete models. In addition to its use for simple climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global-, hemispheric- and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialised ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, i.e. identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way.
DOI: 10.7910/dvn/hnjgqw/j85xrw
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title: Bz_uc0-1.mat

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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/umkuni
title: EAL_RogerSpherules-IRM1T-AF500G-S2-100k_Tesla-1.mat

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title: EAL_RogerSpherules-IRM1T-AF200G-S2-100k_Tesla-1.png

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DOI: 10.7910/dvn/hnjgqw/nsxaxj
title: ALH84001_1-1.mat

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DOI: 10.7910/dvn/hnjgqw/jsw19m
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title: B111-1.mat

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DOI: 10.7910/dvn/hnjgqw/mbi30p
title: ALH84001_2-1.mat

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DOI: 10.7910/dvn/hnjgqw/hsp2vn
title: EAL_RogerSpherules-IRM1T-AF700G-S2-100k_Tesla-1.mat

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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/t3l10s
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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/r1rmgc
title: B111-1.mat

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title: QDM2-1

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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/8t68lw
title: B111-1.mat

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DOI: 10.7910/dvn/hnjgqw/lkl6ku
title: B111-1.mat

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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/zeuvgv
title: map_24-1.mat

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DOI: 10.7910/dvn/hnjgqw/opmprd
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DOI: 10.7910/dvn/hnjgqw/o30x1n
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DOI: 10.7910/dvn/hnjgqw/vyos5j
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title: Bz_uc0-1.mat

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DOI: 10.7910/dvn/hnjgqw/5syc0k
title: EAL_RogerSpherules-IRM1T-AF600G-S2-100k_Tesla-1.mat

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DOI: 10.7910/dvn/hnjgqw/efpmat
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