cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.820868
title: Landslides From Space - Big Sur Landslide, Usa (20Th May 2017)

description: One of the biggest, recent landslides in California burried the famous Pacific Coast Highway and added approx. 5 hectar of new land<br>
<br>
The pre-event acquisition is from 17th May 2017 (Sentinel-2) and the post-event acquisition is from 27th May 2017 (Sentinel-2). A false colour composite with near-infrared, red and green band is visualised as RGB image.<br>
<br>
<em>Contains modified Copernicus Sentinel data (2017)</em>
description: {"references": ["http://edition.cnn.com/2017/06/01/us/big-sur-landslide/index.html"]}
DOI: 10.5281/zenodo.820869
title: Landslides From Space - Big Sur Landslide, Usa (20Th May 2017)

description: One of the biggest, recent landslides in California burried the famous Pacific Coast Highway and added approx. 5 hectar of new land<br>
<br>
The pre-event acquisition is from 17th May 2017 (Sentinel-2) and the post-event acquisition is from 27th May 2017 (Sentinel-2). A false colour composite with near-infrared, red and green band is visualised as RGB image.<br>
<br>
<em>Contains modified Copernicus Sentinel data (2017)</em>
description: {"references": ["http://edition.cnn.com/2017/06/01/us/big-sur-landslide/index.html"]}
DOI: 10.5255/ukda-sn-7650-6
title: Annual Population Survey, July 2013 - June 2014
DOI: 10.5255/ukda-sn-7684-6
title: Annual Population Survey, January - December, 2014
DOI: 10.5255/ukda-sn-7847-5
title: Annual Population Survey, July 2014 - June 2015
DOI: 10.5255/ukda-sn-7858-5
title: Annual Population Survey, October 2014 - September 2015
DOI: 10.5255/ukda-sn-7928-6
title: Annual Population Survey, January - December, 2015
DOI: 10.5255/ukda-sn-8003-3
title: Annual Population Survey, April 2015 - March 2016
DOI: 10.5255/ukda-sn-8054-3
title: Annual Population Survey, July 2015 - June 2016
DOI: 10.5281/zenodo.820918
title: Landslides From Space - Nuugaatsiaq: Landslide-Induced Tsunami, Greenland (17Th June 2017)

description: On 17th June 2017 the village of Nuugaatsiaq was struck by a large, isolated tsunami. This Tsunami was caused by a landslide on a nearby cliff.<br>
<br>
The pre-event acquisition is from 2nd June 2017 (Sentinel-2) and the post-event acquisition is from 19th June 2017 (Sentinel-2). A false colour composite with near-infrared, red and green band is visualised as RGB image.<br>
<br>
<em>Contains modified Copernicus Sentinel data (2017)</em>
description: {"references": ["http://blogs.agu.org/landslideblog/2017/06/19/nuugaatsiaq/"]}
DOI: 10.5281/zenodo.820919
title: Landslides From Space - Nuugaatsiaq: Landslide-Induced Tsunami, Greenland (17Th June 2017)

description: On 17th June 2017 the village of Nuugaatsiaq was struck by a large, isolated tsunami. This Tsunami was caused by a landslide on a nearby cliff.<br>
<br>
The pre-event acquisition is from 2nd June 2017 (Sentinel-2) and the post-event acquisition is from 19th June 2017 (Sentinel-2). A false colour composite with near-infrared, red and green band is visualised as RGB image.<br>
<br>
<em>Contains modified Copernicus Sentinel data (2017)</em>
description: {"references": ["http://blogs.agu.org/landslideblog/2017/06/19/nuugaatsiaq/"]}
DOI: 10.5255/ukda-sn-8118-3
title: Annual Population Survey, October 2015 - September 2016
DOI: 10.5255/ukda-sn-8160-2
title: Annual Population Survey, January - December, 2016
DOI: 10.4225/08/5955b8434a239
title: BioAssess database

description: Microsoft Access 2013 database containing all field data pertaining to the 2003 BioAssess project
DOI: 10.11577/1365656
title: Experimental phase determination with selenomethionine or mercury-derivatization in serial femtosecond crystallography

description: Please check the README file for more information about the dataset.
DOI: 10.4225/08/5955b9411953c
title: Sustainable Firewood Supply in the Murray Darling Basin

description: CSIRO Sustainable Ecosystems was engaged by the Commonwealth Department of Environment and Heritage (then Environment Australia) to: 1.) Develop regional exploitation criteria for sustainable harvesting of firewood from woodland and forest communities in the Murray-Darling Basin, based on three scenarios for future harvesting of firewood; 2) Identify the location and sustainable yield of firewood from those woodland and forest communities in the Murray-Darling Basin that meet the exploitation criteria of each scenario; and 3) Analyse the possible ecological impacts of the harvesting scenarios, particularly the greenwood scenario. This collection contains the project field survery database (MS Access 2013) and zipped report with all appendices.
DOI: 10.5281/zenodo.569453
title: Self-Assembly Of Ordered Graphene Nanodot Arrays

description: Raw data associated with the publication "Self-assembly of ordered graphene nanodot arrays" published in Nature Communications under the DOI: 10.1038/s41467-017-00042-4

Abstract: The ability to fabricate nanoscale domains of uniform size in two-dimensional (2D) materials could potentially enable new applications in nanoelectronics and the development of innovative metamaterials. However, achieving even minimal control over the growth of 2D lateral heterostructures at such extreme dimensions has proven exceptionally challenging. Here we show the spontaneous formation of ordered arrays of graphene nano-domains (dots), epitaxially embedded in a 2D boron-carbon-nitrogen alloy. These dots exhibit a strikingly uniform size of 1.6nm ± 0.2nm and strong ordering, and the array periodicity can be tuned by adjusting the growth conditions. We explain this behaviour with a model incorporating dot-boundary energy, a moiré-modulated substrate interaction, and long-range repulsion between dots. This new 2D material, which theory predicts to be an ordered composite of uniform-size semiconducting graphene quantum dots laterally integrated within a larger-bandgap matrix, holds promise for novel electronic and optoelectronic properties, with a variety of potential device applications.
DOI: 10.5281/zenodo.603935
title: Self-Assembly Of Ordered Graphene Nanodot Arrays

description: Raw data associated with the publication "Self-assembly of ordered graphene nanodot arrays" published in Nature Communications under the DOI: 10.1038/s41467-017-00042-4

Abstract: The ability to fabricate nanoscale domains of uniform size in two-dimensional (2D) materials could potentially enable new applications in nanoelectronics and the development of innovative metamaterials. However, achieving even minimal control over the growth of 2D lateral heterostructures at such extreme dimensions has proven exceptionally challenging. Here we show the spontaneous formation of ordered arrays of graphene nano-domains (dots), epitaxially embedded in a 2D boron-carbon-nitrogen alloy. These dots exhibit a strikingly uniform size of 1.6nm ± 0.2nm and strong ordering, and the array periodicity can be tuned by adjusting the growth conditions. We explain this behaviour with a model incorporating dot-boundary energy, a moiré-modulated substrate interaction, and long-range repulsion between dots. This new 2D material, which theory predicts to be an ordered composite of uniform-size semiconducting graphene quantum dots laterally integrated within a larger-bandgap matrix, holds promise for novel electronic and optoelectronic properties, with a variety of potential device applications.
DOI: 10.5281/zenodo.819580
title: Relazione Per Il Corso Di Idrologia

description: Relazione corso idrologia parte 2.
DOI: 10.5281/zenodo.819581
title: Relazione Per Il Corso Di Idrologia

description: Relazione corso idrologia parte 2.
DOI: 10.6073/pasta/325f2cd2e4dd5569e700556b00e44604
title: Comparisons among five canopy-cover estimating methods in five Douglas-fir/western hemlock structure types in the western Oregon Cascades
DOI: 10.4225/08/595516226b9ca
title: WAMSI Kimberley Science Node: Project 2.2.2 Pathways to production: Biogeochemical processes in the Kimberley region

description: KSN Project 2.2.2 provides key information on the oceanographic and biological forcing associated with nutrient supply that determines the near-shore productivity of the Kimberley region, and links these with higher trophic levels. Key objectives of the research were - To make new estimates of pelagic primary productivity, identifying the key physical and community processes driving production in the region. - To better describe the phytoplankton and zooplankton communities in coastal waters of the Kimberley, to determine the trophic linkages within these communities and to identify the key factors controlling pelagic secondary productivity. - To integrate these parameters into an extensible biogeochemical modelling framework, allowing predictive linkages between physical and biological processes in the region. This metadata records specifically relates to modelling aspects of the project completed by CSIRO. The data originates from a number of model simulations conducted between 3/1/2010 to 21/12/2010. All field data is held by AIMS.
DOI: 10.4225/08/5955c9b915e76
title: RV Investigator Voyage IN2016_E02 End of Voyage (EOV) Archive

description: This record describes the End of Voyage (EOV) archive from the Marine National Facility (MNF) RV Investigator research voyage in2016_e02, titled "MNF Equipment Sea Trials." The voyage took place from Sydney (NSW) to Hobart (TAS) between December 15 and 19, 2016.

For further information refer to the Voyage documentation links below.

Data collected include:
Acoustic Doppler Current Profiler (ADCP; 75, 150 KHz ),  Fisheries echosounder (EK60, ME70), Multibeam Echosounder (EM710, EM122),  Sub-bottom Profiler (SBP120), GPS Positioning System,  Doppler Velocity Log,  Ultra Short BaseLine Underwater Positioning System (USBL),  Starboard and Portside Radiometers, Pyranometers, Radon, Ozone and Oxygen sensors,  Weather Radar, Greenhouse Gas Analysers (Aerodyne, Picarro), Air Pressure, Wind Speed and Direction sensors, Photosynthetically Active Radiation (PAR) sensor, Thermosalinographs.

Voyage Specific data:
Nephelometer, Cloud Condensation Nuclei counter (CCN), pCO2, Ultra-Short Base Line (USBL), DECAF (Deep Water Calibration Facility), Video.

The archive for the in2016_e02 raw data is curated by the CSIRO Oceans and Atmosphere (O&A) Information and Data Centre (IDC) in Hobart, with a permanent archive at the CSIRO Data Access Portal (DAP, https://data.csiro.au/dap/), providing access to participants and processors of the data collected in the voyage.

All voyage documentation is available electronically to MNF support via the local network. Access to voyage documentation for non-CSIRO participants can be made via DataLibrariansOAMNF@csiro.au.
DOI: 10.5281/zenodo.821245
title: Naist Contribution To Zerospeech 2017 (Track 1)

description: This is the official submission of NAIST for track 1 of the zero resource speech challenge 2017 (ZeroSpeech2017).

Our system uses feature vector optimized DPGMM based clustering for unsupervised subword modeling. The general idea is to unsupervisedly learn frame-level class labels in a first run of DPGMM based clustering. These labels are then used to automatically learn speech feature transformations (LDA, MLLT, (basis) fMLLR) to improve discriminability and to reduce speaker variance. The optimized feature vectors are re-clustered and frame-wise posteriorgrams are extracted to serve as new speech representation.

The system also applies posteriorgram based model combination.

This pipeline is entirely unsupervised and only needs the raw audio recordings as input. No pre-defined segmentation, speaker IDs or other meta data is required.

The only parameter subject to tuning is the LDA output dimensionality, which in this case has been optimized on the development data sets (english, french, mandarin) and tested on the surprise language data sets (LANG1, LANG2).

Since the output is posteriorgrams, the ABX scoring needs to be done with the Kullback-Leibler (KL) divergence.
DOI: 10.5281/zenodo.821246
title: Naist Contribution To Zerospeech 2017 (Track 1)

description: This is the official submission of NAIST for track 1 of the zero resource speech challenge 2017 (ZeroSpeech2017).

Our system uses feature vector optimized DPGMM based clustering for unsupervised subword modeling. The general idea is to unsupervisedly learn frame-level class labels in a first run of DPGMM based clustering. These labels are then used to automatically learn speech feature transformations (LDA, MLLT, (basis) fMLLR) to improve discriminability and to reduce speaker variance. The optimized feature vectors are re-clustered and frame-wise posteriorgrams are extracted to serve as new speech representation.

The system also applies posteriorgram based model combination.

This pipeline is entirely unsupervised and only needs the raw audio recordings as input. No pre-defined segmentation, speaker IDs or other meta data is required.

The only parameter subject to tuning is the LDA output dimensionality, which in this case has been optimized on the development data sets (english, french, mandarin) and tested on the surprise language data sets (LANG1, LANG2).

Since the output is posteriorgrams, the ABX scoring needs to be done with the Kullback-Leibler (KL) divergence.
DOI: 10.5255/ukda-sn-3454-3
title: Demography of Sri Lanka, 1900-1954
DOI: 10.3886/e100785v1
title: The Financial Burden of Cancer on Families in the United States

description: This study examined the
relationship between a diagnosis of cancer and the likelihood of having any out
of pocket costs (OOPC) and medical debt, and the amounts of OOPC and medical
debt, at the household level. We used the 2011 Panel Study of Income
Dynamics, an ongoing nationally representative
panel survey that collects detailed socioeconomic and demographic data in the United States. The
analytic sample included households where heads and their spouse (if
married) were between 18 and 64 years old. Adjusted logistic
regression models and generalized linear models with logarithmic link and a gamma distribution were
used. Two models were used. Model 1 controlled for the gender, age, race,
marital status, and education of the head of household, and household variables
of the number of children in the household, the number of chronic health
conditions for the
head of household and spouse if married, and households where
both the head and the spouse (if married) reported a diagnosis of cancer. Model 2 additionally controlled
for home equity. Related to OOPC, both models showed that
having a diagnosis of cancer increased a households likelihood of having any OOPC
by 119% (p &lt; .01) compared to
those that did not have a diagnosis of cancer. Additionally, for households
with positive amounts of OOPC, it was found that a diagnosis of cancer increased
the amount of OOPC by 24% (p &lt; .01)
compared to households without a diagnosis of cancer. Related to medical debt, Model 1
showed that having a diagnosis of cancer increased a households likelihood of
having any medical debt by 67% (p =
.052) compared to those without a diagnosis of cancer. However, when including
home equity in Model 2, having a
diagnosis of cancer increased a households likelihood of having any medical
debt by 78% (p &lt; .05) compared to
those without a diagnosis of cancer. Further, a diagnosis of cancer increased the amount of medical
debt similarly for Model 1 (101%) and
Model 2 (102%) for households with positive amounts of
medical debt compared to those without a diagnosis of cancer (p &lt; .05). All tests of significance were two-sided. This study shows that a diagnosis of cancer
imposes a significant financial burden on families in the United States even
after controlling for systematic differences between households with a
diagnosis of cancer compared to those without a diagnosis of cancer.

<br><br><br><br>
DOI: 10.5281/zenodo.804240
title: Data Used In "Fast Metabolite Identification With Input Output Kernel Regression"

description: This repository contains the data used in [1] to evaluate the performance for metabolite identification from tandem mass spectra. These data have been extracted and processed in [2]. We used a subset of 4138 MS/MS spectra extracted from the GNPS public spectral library (https://gnps.ucsd.edu/ProteoSAFe/libraries.jsp) for training and evaluation. For searching, we used molecular structures from PubChem as candidate sets.

Please mention and cite GNPS when using these data.

The implementation of the method proposed in [1] is available on: https://version.aalto.fi/gitlab/kepaco/Fast-metabolite-identification-with-IOKR

<strong>Files description:</strong>


	<em>spectra.txt</em>: informations about the MS/MS spectra (GNPS identifier, compound name and INCHI identifier)
	<em>data_GNPS.mat</em>: contains the molecular fingerprints, molecular formula and InCHI corresponding to the MS/MS spectra
	<em>cv_ind.txt</em>: indices of the cross-validation folds
	<em>ind_eval.txt</em>: indices of the examples used for evaluation
	<em>candidates</em>: fingerprints and INCHI for the different candidate sets
	<em>input_kernels</em>: contains 24 input kernel matrices


<strong>References:</strong>

[1] Brouard, C., Shen, H., Dührkop, K., d'Alché-Buc, F., Böcker, S. and Rousu, J.: Fast metabolite identification with Input Output Kernel Regression. In the proceedings of ISMB 2016, Bioinformatics 32(12): i28-i36, 2016. DOI: https://doi.org/10.1093/bioinformatics/btw246

[2] Dührkop, K., Shen, H., Meusel, M., Rousu, J. and Böcker, S.: Searching molecular structure databases with tandem mass spectra using CSI:FingerID. PNAS, 112(41), 12580-12585, 2015. doi:10.1073/pnas.1509788112
DOI: 10.5281/zenodo.804241
title: Data Used In "Fast Metabolite Identification With Input Output Kernel Regression"

description: This repository contains the data used in [1] to evaluate the performance for metabolite identification from tandem mass spectra. These data have been extracted and processed in [2]. We used a subset of 4138 MS/MS spectra extracted from the GNPS public spectral library (https://gnps.ucsd.edu/ProteoSAFe/libraries.jsp) for training and evaluation. For searching, we used molecular structures from PubChem as candidate sets.

Please mention and cite GNPS when using these data.

The implementation of the method proposed in [1] is available on: https://version.aalto.fi/gitlab/kepaco/Fast-metabolite-identification-with-IOKR

<strong>Files description:</strong>


	<em>spectra.txt</em>: informations about the MS/MS spectra (GNPS identifier, compound name and INCHI identifier)
	<em>data_GNPS.mat</em>: contains the molecular fingerprints, molecular formula and InCHI corresponding to the MS/MS spectra
	<em>cv_ind.txt</em>: indices of the cross-validation folds
	<em>ind_eval.txt</em>: indices of the examples used for evaluation
	<em>candidates</em>: fingerprints and INCHI for the different candidate sets
	<em>input_kernels</em>: contains 24 input kernel matrices


<strong>References:</strong>

[1] Brouard, C., Shen, H., Dührkop, K., d'Alché-Buc, F., Böcker, S. and Rousu, J.: Fast metabolite identification with Input Output Kernel Regression. In the proceedings of ISMB 2016, Bioinformatics 32(12): i28-i36, 2016. DOI: https://doi.org/10.1093/bioinformatics/btw246

[2] Dührkop, K., Shen, H., Meusel, M., Rousu, J. and Böcker, S.: Searching molecular structure databases with tandem mass spectra using CSI:FingerID. PNAS, 112(41), 12580-12585, 2015. doi:10.1073/pnas.1509788112
DOI: 10.6084/m9.figshare.12977942.v1
title: Xinyang study.sav

description: 1207 participants
DOI: 10.7487/2017.180.1.1063
title: 2015 US Navy data

description: all taxa for all N atl, raw, 2015
DOI: 10.6084/m9.figshare.12977942
title: Xinyang study.sav

description: 1207 participants
DOI: 10.4225/08/5955d58e8cab6
title: Savernake and Native Dog Farmscapes Project database

description: Microsoft Access 2013 database holding data from a biodiversity benchmarking survey of plants and animals within 35 remnant sites and 35 extra sites surveyed for birds only, in the Savernake and Native Dog Landcare Group area.
DOI: 10.17197/u16003
title: U16003 Voluntary association and fertility practices in the Skellefteå region 1880-1950

description: Under våtterminen 2017 har utredare och systemutvecklare vid CEDAR, avdelningen för Demografiska databasen, arbetat med en beställning från Johan Junkka. Uppdraget har syftat till att länka information från medlemsregister från arbetarrörelseföreningar och nykterhetsföreningar i Skellefteå till ett tidigare datauttag från samma region. Genom att länka information från medlemsregister från arbetar- och nykterhetsrörelsen med information som finns i den digitaliserade kyrkoboksdatabasen POPLINK är det möjligt att studera relationen mellan sociala nätverk och fertilitet ur ett longitudinellt perspektiv på en individnivå under en avgörande tid i den europeiska demografiska historien.
DOI: 10.17632/9pc5pyrp7c.1
title: 1H and 19F NMR in drug stress testing: the case of voriconazole

description: NMR data
DOI: 10.5281/zenodo.815538
title: Phenological Time Lapse Images From Crown Camera Mc122 In Lammi Birch Stand (2015-2016)

description: This dataset contains phenological time lapse images from camera Lammi Birch stand. Camera was mounted at crown view level at location 61.05211; 25.04180(N;E, WGS84). Images were taken between 08.05.2015--31.12.2016.<br>
Cameras were set to fix white balance, brightness automatically adjusted by camera.Image have equal resolution throughout the time series, time indicated in UTC+2. Images are taken half-hourly during fixed day-time period over the year. Gaps in time series and dark images possibly exist.<br>
More details on the camera installations and operation history can be found at 10.5281/zenodo.777952<br>
The cameras were set up and images collected under EU Life+ (LIFE ENV/FI/000409) Monimet project, http://monimet.fmi.fi.<br>
For further information contact john.loehr@helsinki.fi
DOI: 10.5061/dryad.bh6k6/2
title: DNA alignments and phylogenetic trees