cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7315055
title: A framework for exposure characterization and gamma dosimetry at the NMBU FIGARO irradiation facility

description: <b>Purpose</b>: The FIGARO low dose <sup>60</sup>Co gamma irradiation facility at the Norwegian University of Life Sciences, Ås, Norway, is dedicated to the study of effects on living organisms from acute or chronic ionizing radiation exposures, either alone or in combination with other stressors such as UV radiation, metals or radionuclides. Here, we present a framework of working guidelines and computer software for characterization of absorbed dose rates and accumulated doses to organisms exposed within the continuous gamma field at FIGARO. The aims of the framework are to ensure gamma exposures are well characterized, that results from exposures are correctly interpreted in terms of absorbed dose rates and accumulated doses, and that sufficient information is available so that exposures can be reproduced later or at other facilities. <b>Methods</b>: The software of the framework includes a Geant4 application for Monte Carlo radiation transport simulations and tools for dose planning, recording and reporting. The working guidelines are prepared for expert users who provide simulated, calculated or estimated absorbed dose rates and for regular users who conduct exposure experiments and are responsible for record keeping. To demonstrate the developed framework, we use a case study where 14 freshwater microcosms are exposed to four levels of gamma dose rates at FIGARO. <b>Conclusion</b>: The framework guides users towards good dosimetry practices. Lessons learned could be transferable to other gamma irradiation facilities.
DOI: 10.7284/126035
title: Multibeam Echosounder data collected during research cruise RR1607 using a Kongsberg EM122 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7315040
title: Data

description: Data used for the systematic review
DOI: 10.6084/m9.figshare.7315049.v1
title: Cross_Mappability_hg19_gencode19

description: This dataset contains cross-mappability resources computed on human genome hg19 using gene annotations from GENCODE v19. 75-mers from exon and 36-mers from UTRs were used to compute gene mappability and cross-mappability.
DOI: 10.7284/126038
title: Winch data collected during research cruise RR1607 using a Markey DUTW-9-11 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7315049.v2
title: Cross-mappability for hg19 using Gencode v19 annotation (75-mers from exon, 36-mers from UTR)

description: This dataset contains cross-mappability resources computed on human genome hg19 using gene annotations from GENCODE v19. 75-mers from exon and 36-mers from UTRs were used to compute gene mappability and cross-mappability.
DOI: 10.7284/126042
title: Winch data collected during research cruise RR1607 using a Markey DUSH-5 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7315049.v3
title: Mappability resources for hg19 using Gencode v19 annotation

description: This dataset contains cross-mappability resources computed on human genome hg19 using gene annotations from GENCODE v19. 75-mers from exon and 36-mers from UTRs were used to compute gene mappability and cross-mappability.
DOI: 10.6084/m9.figshare.7315049.v5
title: Mappability resources for hg19 using Gencode v19 annotation

description: This dataset contains mappability resources computed on human genome hg19 using gene annotations from GENCODE v19.
DOI: 10.7284/126048
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise RR1608 using a Hawaii UHDAS instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314875
title: Living inside and outside Nostoc sp. colonies: a comparison of bacterial community composition

description: Otu table with its fasta file
DOI: 10.6084/m9.figshare.7314896
title: A supervised machine learning method to classify Dutch-language news items

description: <b>Please contact s.a.m.vermeer@uva.nl for questions or further information. </b><br><br><i>Background</i>Based on a supervised machine learning method, we developed a classifier in Python (version 3.5.2) that returns the news topic of Dutch-language news items (as a string). To train the classifier, we collected more than 1 million news items from approximately 150 different Dutch-language news websites, as well as search engines and social media, collected over 8 months in 2017/18.This tool can be used for mapping Dutch-news items into different news categories, namely: (1) Politics, which covers items about <i>internal politics, international politics, </i>and<i> military </i>and <i>defense; </i>(2) Business, includes <i>economy, education, and health, welfare and social services; </i>(3) Entertainment, covers <i>sports, culture, fashion </i>and <i>human interest; </i>and (4) Other, includes <i>science and technology, environment, communication, weather </i>and<i> religion and beliefs. </i><i><br></i><i>Performance</i>We used three different pre-processing steps, resulting in three different <b>.pkl </b>modules: (1) All text: '<i>...text_Dutch_news.pkl</i>', (2) Stop word removal: '...<i>stopword_Dutch_news.pkl</i>', and (3) Lead: '...<i>lead_Dutch_news.pkl</i>'.For every text category, the classifier reached an accuracy, precision and recall of at least .<b>81</b>. <br><i>Usage</i>The classifiers have been developed in Python 3.5.2, and scikit-learn 0.19.2, and can be used as follows:-- clf=joblib.load('PassiveAggressive_text_Dutch_news.pkl')-- topic=clf.predict([text]) #text is a news item<br>Susan VermeerDamian TrillingSanne KruikemeierClaes de Vreese
DOI: 10.6084/m9.figshare.7315049.v4
title: Mappability resources for hg19 using Gencode v19 annotation

description: This dataset contains mappability resources computed on human genome hg19 using gene annotations from GENCODE v19. 75-mers from exon and 36-mers from UTRs were used to compute gene mappability and cross-mappability.
DOI: 10.7284/126049
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1608 using a Furuno GP-150 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314875.v1
title: Living inside and outside Nostoc sp. colonies: a comparison of bacterial community composition

description: Otu table with its fasta file
DOI: 10.6084/m9.figshare.7314875.v2
title: Living inside and outside Nostoc sp. colonies: a comparison of bacterial community composition

description: Otu table with its fasta file
DOI: 10.7284/126051
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1608 using a Ashtech ADU2 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314821
title: Investigation of the Slinky Whistler Effect

description: Investigation of the Slinky Whistler Effect<br>This project is a part of coursework for CY1308 Physics in Semester 1 of the Academic Year 2018/2019.<br>
DOI: 10.6084/m9.figshare.7314821.v1
title: Investigation of the Slinky Whistler Effect

description: Investigation of the Slinky Whistler Effect<br>This project is a part of coursework for CY1308 Physics in Semester 1 of the Academic Year 2018/2019.<br>
DOI: 10.7284/126057
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1608 using a Trimble SPS351 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126054
title: Gyrocompass data collected during research cruise RR1608 using a iXSea Phins instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314734
title: Complete Mitochondrial Genomes

description: Complete Mitochondrial Genomes
DOI: 10.6084/m9.figshare.7314728
title: All mtDNA raw contigs

description: All mtDNA raw contigs
DOI: 10.7284/126058
title: INS (Inertial Navigation System) data collected during research cruise RR1608 using a Kongsberg Seapath 320+ instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126047
title: Meteorological Station data collected during research cruise RR1608 using a SIO MET-System instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314731.v1
title: Kellenberger_etal_overdominance_small_datasets.xlsx

description: Study:Emergence of a floral colour polymorphism by pollinator-mediated overdominance<br>Authors:Roman T. Kellenberger, Kelsey J.R.P. Byers, Rita M. De Brito Francisco, Yannick M. Städler, Amy M. LaFountain, Jürg Schönenberger, Florian P. Schiestl, Philipp M. Schlüter<br>Content: Table containing estimated absolute and relative frequencies of G. rhellicani colour morphs at Puflatsch 1997-2016 Table containing morphological and fitness data for the G. rhellicani colour morphs in the 14 plots at Puflatsch 2015-2016 Table containing morphological, metabolomic, and genetic data for the focal G. rhellicani plants at Puflatsch Table containing results of the pollinator exclusion experiment conducted at Ofenpass in 2016 Table containing time-lapse camera recordings of insect landings on G. rhellicani inflorescences at Puflatsch 2016-2017 Table containing genetic information of the G. rhellicani plants used for time-lapse recordings of insect landings in 2017 Table containing temperature measurements of G. rhellicani inflorescences at Puflatsch in 2016 Table containing floral scent profiles from 3 time points, morphological, and genetic information of G. rhellicani plants Table containing morphological, metabolomic, and genetic data for G. rhellicani plants at Bondone Table containing genetic information of G. rhellicani plants from 13 other Alpine populations Table containing qRT-PCR quantifications of GrMYB1 and GrANS1 in G. rhellicani plants from Ofenpass treated with GrMYB1 dsRNA
DOI: 10.7284/126050
title: Multibeam Echosounder data collected during research cruise RR1608 using a Kongsberg EM122 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126053
title: Winch data collected during research cruise RR1608 using a Markey DUTW-9-11 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126056
title: Winch data collected during research cruise RR1608 using a Markey DUSH-5 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126061
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise RR1609 using a Hawaii UHDAS instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126069
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise RR1609 using a Sea-Bird SBE-911+ instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126062
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1609 using a Furuno GP-150 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314692
title: MAST nuclear NAD contigs

description: MAST nuclear NAD contigs
DOI: 10.7284/126064
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1609 using a Ashtech ADU2 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126071
title: GNSS (Global Navigation Satellite System) data collected during research cruise RR1609 using a Trimble SPS351 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314674
title: Choanoflagellate intron ORFs

description: Choanoflagellate intron ORFs
DOI: 10.7284/126067
title: INS (Inertial Navigation System) data collected during research cruise RR1609 using a iXSea Phins instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126072
title: INS (Inertial Navigation System) data collected during research cruise RR1609 using a Kongsberg Seapath 320+ instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126060
title: Meteorological Station data collected during research cruise RR1609 using a SIO MET-System instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126063
title: Multibeam Echosounder data collected during research cruise RR1609 using a Kongsberg EM122 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126066
title: Winch data collected during research cruise RR1609 using a Markey DUTW-9-11 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/126070
title: Winch data collected during research cruise RR1609 using a Markey DUSH-5 instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314572
title: Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

description: Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R<sup>2</sup> 0.21–0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R<sup>2</sup> 0.33–0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.
DOI: 10.7284/126076
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise RR1610 using a Hawaii UHDAS instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7314572.v1
title: Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

description: Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R<sup>2</sup> 0.21–0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R<sup>2</sup> 0.33–0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.
DOI: 10.6084/m9.figshare.7314566
title: Characterizing multi-decadal, annual land cover change dynamics in Houston, TX based on automated classification of Landsat imagery

description: In 2017, Hurricane Harvey caused substantial loss of life and property in the swiftly urbanizing region of Houston, TX. Now in its wake, researchers are tasked with investigating how to plan for and mitigate the impact of similar events in the future, despite expectations of increased storm intensity and frequency as well as accelerating urbanization trends. Critical to this task is the development of automated workflows for producing accurate and consistent land cover maps of sufficiently fine spatio-temporal resolution over large areas and long timespans. In this study, we developed an innovative automated classification algorithm that overcomes some of the traditional trade-offs between fine spatio-temporal resolution and extent – to produce a multi-scene, 30m annual land cover time series characterizing 21 years of land cover dynamics in the 35,000 km2 Greater Houston area. The ensemble algorithm takes advantage of the synergistic value of employing all acceptable Landsat imagery in a given year, using aggregate votes from the posterior predictive distributions of multiple image composites to mitigate against misclassifications in any one image, and fill gaps due to missing and contaminated data, such as those from clouds and cloud shadows. The procedure is fully automated, combining adaptive signature generalization and spatio-temporal stabilization for consistency across sensors and scenes. The land cover time series is validated using independent, multi-temporal fine-resolution imagery, achieving crisp overall accuracies between 78–86% and fuzzy overall accuracies between 91–94%. Validated maps and corresponding areal cover estimates corroborate what census and economic data from the Greater Houston area likewise indicate: rapid growth from 1997–2017, demonstrated by the conversion of 2,040 km<sup>2</sup> (± 400 km<sup>2</sup>) to developed land cover, 14% of which resulted from the conversion of wetlands. Beyond its implications for urbanization trends in Greater Houston, this study demonstrates the potential for automated approaches to quantifying large extent, fine resolution land cover change, as well as the added value of temporally-dense time series for characterizing higher-order spatio-temporal dynamics of land cover, including periodicity, abrupt transitions, and time lags from underlying demographic and socio-economic trends.
DOI: 10.6084/m9.figshare.7314566.v1
title: Characterizing multi-decadal, annual land cover change dynamics in Houston, TX based on automated classification of Landsat imagery

description: In 2017, Hurricane Harvey caused substantial loss of life and property in the swiftly urbanizing region of Houston, TX. Now in its wake, researchers are tasked with investigating how to plan for and mitigate the impact of similar events in the future, despite expectations of increased storm intensity and frequency as well as accelerating urbanization trends. Critical to this task is the development of automated workflows for producing accurate and consistent land cover maps of sufficiently fine spatio-temporal resolution over large areas and long timespans. In this study, we developed an innovative automated classification algorithm that overcomes some of the traditional trade-offs between fine spatio-temporal resolution and extent – to produce a multi-scene, 30m annual land cover time series characterizing 21 years of land cover dynamics in the 35,000 km2 Greater Houston area. The ensemble algorithm takes advantage of the synergistic value of employing all acceptable Landsat imagery in a given year, using aggregate votes from the posterior predictive distributions of multiple image composites to mitigate against misclassifications in any one image, and fill gaps due to missing and contaminated data, such as those from clouds and cloud shadows. The procedure is fully automated, combining adaptive signature generalization and spatio-temporal stabilization for consistency across sensors and scenes. The land cover time series is validated using independent, multi-temporal fine-resolution imagery, achieving crisp overall accuracies between 78–86% and fuzzy overall accuracies between 91–94%. Validated maps and corresponding areal cover estimates corroborate what census and economic data from the Greater Houston area likewise indicate: rapid growth from 1997–2017, demonstrated by the conversion of 2,040 km<sup>2</sup> (± 400 km<sup>2</sup>) to developed land cover, 14% of which resulted from the conversion of wetlands. Beyond its implications for urbanization trends in Greater Houston, this study demonstrates the potential for automated approaches to quantifying large extent, fine resolution land cover change, as well as the added value of temporally-dense time series for characterizing higher-order spatio-temporal dynamics of land cover, including periodicity, abrupt transitions, and time lags from underlying demographic and socio-economic trends.
DOI: 10.7284/126088
title: Expendable Probe data collected during research cruise RR1610 using a Turo Quoll instrument system onboard the platform RV Roger Revelle

description: Original (unprocessed) data collected during a Field_expedition