cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17863/cam.6290
title: Research data supporting “A &gt; 3 T portable magnetic field by flux jump assisted pulsed field magnetisation of superconducting bulks”

description: These are experimental data of magnetic field measured during and after the pulsed field magnetisation of high temperature superconductors.
description: EPSRC [EP/K02910X/1], The Boeing Company
DOI: 10.17863/cam.6296
title: Research data supporting “Rapid asymmetric disubstituted allene synthesis via coupling of flow-generated diazo compounds and propargylated amines”

description: This data contains a .zip file of the NMR spectra for the compounds (in .mnova format, to be opened in MestReNova) described in the Supporting Information. It also contains a .pdf copy of the Supporting Information, which contains the experimental details and full characterisation data (NMR, IR, HRMS) of all compounds produced in this publication.
description: EPSRC [EP/K009494/1, EP/K039520/1 and EP/M004120/1], Cambridge Home and European Scholarship Scheme, Erasmus Scholarship Scheme, Swiss National Science Foundation, UCB Biopharma SPRL
DOI: 10.5441/001/1.j900f88t/1
title: Kruger African Buffalo, GPS tracking, South Africa

description: Getz WM, Fortmann-Roe S, Cross PC, Lyons AJ, Ryan SJ, Wilmers CC (2007) LoCoH: Nonparameteric kernel methods for constructing home ranges and utilization distributions. PLoS ONE 2(2): e207. doi:10.1371/journal.pone.0000207
description: Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: “fixed sphere-of-influence,” or r-LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an “adaptive sphere-of-influence,” or a-LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a), and compare them to the original “fixed-number-of-points,” or k-LoCoH (all kernels constructed from k-1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a-LoCoH is generally superior to k- and r-LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu).
DOI: 10.5441/001/1.j900f88t/2
title: Kruger African Buffalo, GPS tracking, South Africa-reference-data

description: Getz WM, Fortmann-Roe S, Cross PC, Lyons AJ, Ryan SJ, Wilmers CC (2007) LoCoH: Nonparameteric kernel methods for constructing home ranges and utilization distributions. PLoS ONE 2(2): e207. doi:10.1371/journal.pone.0000207
description: Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: “fixed sphere-of-influence,” or r-LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an “adaptive sphere-of-influence,” or a-LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a), and compare them to the original “fixed-number-of-points,” or k-LoCoH (all kernels constructed from k-1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a-LoCoH is generally superior to k- and r-LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu).
DOI: 10.17863/cam.6343
title: Research data supporting “Wild jackdaws’ reproductive success and their offspring’s stress hormones are connected to provisioning rate and brood size, not to parental neophobia”

description: This data consists of one text file that explains the data labels, and two csv files. One csv file was used to compute the consistency of neophobia, control, and feeding rate measures and their impact on jackdaw fitness, the other was used to analyse the factors influencing blood CORT hormone levels. Neophobia scores, measures of reproductive success, and offspring stress hormone levels were collected from a wild population of breeding jackdaws (Corvus monedula) in Madingley, Cambridgshire, UK in 2013. Neophobia was assessed at nest boxes based on birds’ latencies to return to their nest when a novel object was present. Reproductive success was determined by counting the number and body condition of chicks per nest. A measure of baseline and stress-induced corticosterone (CORT) was taken for each chick within a subset of nests. The csv files contain data used for the analyses supporting the related research article (Wild jackdaws’ reproductive success and their offspring’s stress hormones are connected to provisioning rate and brood size, not to parental neophobia). Please see the main article for further discussion relating to the results generated from this data.
description: BBSRC [BB/L002264/1 and BB/H021817/1]
DOI: 10.17863/cam.6364
title: Research data supporting “The effect of the 'Bee Gym'(TM) Grooming Device on Varroa destructor Mite Fall from Honey Bee (Apis mellifera) Colonies”

description: Varroa destructor mite fall over 14 counts from honey bee colonies before (7 counts) and after (7 counts) insertion of a test device (The Bee Gym) or control object. The number of damaged mites is included for the 'counts after'. Data were collected between 30 June and 30 July 2014. The time the drop boards were in place for, for each count, and the time of count are also given.
description: BBSRC [BB/J014540/1], Stuart Roweth (private funder)
DOI: 10.17863/cam.6367
title: Research data supporting "Aedes aegypti exome-sequencing and Aedes bromeliae whole-genome sequencing" (VCF files containing variants)

description: This repository contains two VCF files that were generated from the called genotyped obtained from ANGSD. One VCF file contains variants obtained from whole-genome sequencing data from one individual sample of Aedes bromeliae (aedesBromeliae__1sample__Brom.mdp8.vcf.gz ) The other VCF file contains variants obtained from whole-exome sequencing data from 71 individual samples belonging to different populations in Africa and outside of Africa (aedesAegypti__71samples__AEGY.allpop.J18.AllSites.REFpol.CALLED.vcf_.gz). The data is accompanied by the raw sequencing data available in SRA with the accession number SRP092518 and with the BioProject number PRJNA349448 More information about the project is available in the manuscript that is under preparation.
description: ERC [Drosophila Infection (281668) to Francis M. Jiggins], MRC Centenary Award to William J Palmer, National Institutes of Health Ruth L. Kirschstein National Research Service Award to Jacob Crawford, KAUST AEA award to Francis M. Jiggins and Arnab Pain
DOI: 10.25612/837.8koe0a2ka4qb
title: American Community Survey (ACS) 2010 data for Harris County, Texas, USA

description: Demographic data on education, employment, families, households, housing units, tenure, poverty level, and income. From the ACS 5-year 2006-2010 estimates. Harris County (TX).
DOI: 10.15454/j4zs76
title: Verifi instal api doi prodt
title: AlternativeTitle Verifi instal api doi prod
title: Subtitle Verifi instal api doi prod

description: Test Description métadonnées Description Dataverse
description: Test Description métadonnées NOTE Dataverse
description: Test series informations
DOI: 10.15454/n9qrnv
title: Verifi instal api doi prodt
title: AlternativeTitle Verifi instal api doi prod
title: Subtitle Verifi instal api doi prod

description: Test Description métadonnées Description Dataverse
description: Test Description métadonnées NOTE Dataverse
description: Test series informations
DOI: 10.5441/001/1.356nb5mf/1
title: Movement strategies of Galapagos tortoises (data from Bastille-Rousseau et al. 2016)

description: Bastille-Rousseau G, Potts JR, Yackulic CB, Frair JL, Ellington EH, Blake S (2016) Flexible characterization of animal movement pattern using net squared displacement and a latent state model. Movement Ecology 4:15. doi:10.1186/s40462-016-0080-y
description: Background: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results: With respect to patterns of time spent and the number of transitions between modes, our approach out- performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.
DOI: 10.5441/001/1.356nb5mf/2
title: Movement strategies of Galapagos tortoises (data from Bastille-Rousseau et al. 2016)-reference-data

description: Bastille-Rousseau G, Potts JR, Yackulic CB, Frair JL, Ellington EH, Blake S (2016) Flexible characterization of animal movement pattern using net squared displacement and a latent state model. Movement Ecology 4:15. doi:10.1186/s40462-016-0080-y
description: Background: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results: With respect to patterns of time spent and the number of transitions between modes, our approach out- performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.
DOI: 10.5441/001/1.356nb5mf/3
title: GPS_map_clustering

description: Bastille-Rousseau G, Potts JR, Yackulic CB, Frair JL, Ellington EH, Blake S (2016) Flexible characterization of animal movement pattern using net squared displacement and a latent state model. Movement Ecology 4:15. doi:10.1186/s40462-016-0080-y
description: Background: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results: With respect to patterns of time spent and the number of transitions between modes, our approach out- performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.
DOI: 10.21963/12664
title: Land cover map along the Inuvik-Tuktoyaktuk Highway corridor

description: This land cover map was developed using isodata unsupervised classification method based on two SPOT 4 scenes (both acquired on 4 September 2006) and one SPOT 5 scene (acquired on 27 August 2007). The ITH corridor was classified into 14 land cover types at 20 m spatial resolution. CODE DESCRIPTIONS: 0-Water bodies or outside the map area; 1-Forest dominated by coniferous trees, mainly spruce; 2-Forest dominated by deciduous trees; 3-Shrub with sparse trees; 4-High and dense shrubs (&gt;1.0m); 5-Medium to high shrubs (0.5-1.0m); 6-Medium height shrubs (about 0.5m); 7-Sparse shrubs in slopes; 8-Sedge/shrub low lands; 9-Shrub/sedge polygons; 10-Wetland with small water bodies, usually wide trenches; 11-Seasonally flooded wetland, usually near lake shores; 12-Mixture of water and land, usually along lake shores; 13-Barren land (non-vegetated area, streets, roads, airports). The image is in 8 bits (or 1 byte) binary format (0-13) containing 7863 lines and 5182 pixels. The projection is in UTM 8W D122 at 20 m spatial resolution (Upper left: 513660 E,7734000 N; Lower right: 617300 E, 7576740 N).
description: Purpose: This land cover map was developed mainly for permafrost mapping along the Inuvik-Tuktoyaktuk Highway (ITH) corridor. Along the ITH corridor, vegetation changes from forest in the south to typical arctic tundra in the north. Vegetation conditions play important roles affecting permafrost, and they also are indicators of snow and subsurface conditions, which are critical for permafrost as well.
description: Summary: This land cover map in ITH corridor was developed using SPOT 4 and 5 satellite images at 20 m spatial resolution. The area was classified into 14 types, including water bodies, forest types (coniferous and deciduous), shrub with sparse trees, upland tundra types, lowland tundra types, and barren land.
DOI: 10.17863/cam.6607
title: Research data supporting "Observation of Weak Collapse in a Bose-Einstein Condensate"

description: The repository contains figure data as well as additional raw data sets that were used to extract the figure data points.
DOI: 10.17863/cam.6653
title: Research data supporting "Decreasing amyloid toxicity through an increased rate of aggregation"

description: Raw data supporting the publication in PCCP. Within the main folder there are more folders each containing data for a specific experimental technique. The data are a collection of experimental data for Circular Dichroism, Thioflavin T fluorescence emission, Dynamic Light Scattering, Isothermal Titration Calorimetry, Transmission Electron Microscopy, Atomic Force Microscopy. In addition, fluorescence microscopy and cell assays data are reported as well.
description: ERC [Starting Investigator grant ASPiRe 240629], EPSRC [EP/G060649/1]
DOI: 10.5441/001/1.s9s86319/1
title: Foraging behaviour and fuel accumulation of pink-footed geese (data from Chudzinska et al. 2016)-gps

description: Chudzińska ME, Nabe-Nielsen J, Nolet BA, Madsen J (2016) Foraging behaviour and fuel accumulation of capital breeders during spring migration as derived from a combination of satellite- and ground-based observations. Journal of Avian Biology 47: 1–12. doi:10.1111/jav.00899
description: The migration strategy of many capital breeders is to garner body stores along the flyway at distinct stopover sites. The rate at which they can fuel is likely to be strongly influenced by a range of factors, such as physiology, food availability, time available for foraging and perceived predation. We analysed the foraging behaviour and fuel accumulation of pink-footed geese, an Arctic capital breeder, at their mid-flyway spring stopover site and evaluated to what extent their behaviour and fuelling were related to physiological and external factors and how it differed from other stopovers along the flyway. We found that fuel accumulation rates of geese at the mid-flyway site were limited by habitat availability rather than by digestive constraints. However, as the time available for foraging increased over the stopover season, geese were able to keep constant fuelling rate. Putting this in perspective, geese increased their daily net energy intake along the flyway corresponding to the increase in time available for foraging. The net energy intake per hour of foraging remained the same. Geese showed differences in their reaction to predators/disturbance between the sites, taking higher risks particularly at the final stopover site. Hence, perceived predation along the flyway may force birds to postpone the final fuel accumulation to the last stopover along the flyway. Flexibility in behaviour appears to be an important trait to ensure fitness in this capital breeder. Our findings are based on a new, improved method for estimating fuel accumulation of animals foraging in heterogeneous landscapes based on data obtained from satellite telemetry and habitat specific intake rates.