22 Works

2010 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2015 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2016 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Data from: Cross-boundary human impacts compromise the Serengeti-Mara ecosystem

Michiel P. Veldhuis, Mark E. Ritchie, Joseph O. Ogutu, Thomas A. Morrison, Colin M. Beale, Anna B. Estes, William Mwakilema, Gordon O. Ojwang, Catherine L. Parr, James Probert, Patrick W. Wargute, J. Grant C. Hopcraft & Han Olff
Protected areas provide major benefits for humans in the form of ecosystem services, but landscape degradation by human activity at their edges may compromise their ecological functioning. Using multiple lines of evidence from 40 years of research in the Serengeti-Mara ecosystem, we find that such edge degradation has effectively “squeezed” wildlife into the core protected area and has altered the ecosystem’s dynamics even within this 40,000-square-kilometer ecosystem. This spatial cascade reduced resilience in the core...

Artificial light at night, in interaction with spring temperature, modulates timing of reproduction in a passerine bird

Davide M. Dominoni, Johan Kjellberg Jensen, Maaike De Jong, Marcel E. Visser & Kamiel Spoelstra
The ecological impact of artificial light at night (ALAN) on phenological events such as reproductive timing is increasingly recognized. In birds, previous experiments under controlled conditions showed that ALAN strongly advances gonadal growth, but effects on egg-laying date are less clear. In particular, effects of ALAN on timing of egg-laying are found to be year-dependent, suggesting an interaction with climatic conditions such as spring temperature, which is known have strong effects on the phenology of...

2013 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2012 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2017 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2018 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Towards a comparative approach to the structure of animal personality variation

Stephen White, David Pascall & Alastair Wilson
Latent personality traits underpinning observed behavioral variation have been studied in a great many species. However, a lack of standardized behavioral assays, coupled to a common reliance on inferring personality from a single, observed, behavioral trait makes it difficult to determine if, when, and how conclusions can be directly compared across taxa. Here, we estimate the among-individual (co)variance structure (ID) for a set of four behaviors expressed in an open field trial, putatively indicative of...

Data from: The sensitivity of seabird populations to density-dependence, environmental stochasticity and anthropogenic mortality

Julie A. O. Miller, Robert W. Furness, Mark Trinder & Jason Matthiopoulos
1.The balance between economic growth and wildlife conservation is a priority for many governments. Enhancing realism in assessment of population‐level impacts of anthropogenic mortality can help achieve this balance. Population Viability Analysis (PVA) is commonly applied to investigate population vulnerability, but outcomes of PVA are sensitive to formulations of density‐dependence, environmental stochasticity and life‐history. Current practice in marine assessments is to use precautionary models that assume no compensation from density‐dependence or rescue‐effects via “re‐seeding” from...

Data from: Knock-on community impacts of a novel vector: spillover of emerging DWV-B from Varroa-infested honeybees to wild bumblebees

Robyn Manley, Ben Temperton, Toby Doyle, Daisy Gates, Sophie Hedges, Michael Boots & Lena Wilfert
Novel transmission routes can directly impact the evolutionary ecology of infectious diseases, with potentially dramatic effect on host populations and knock-on effects on the wider host community. The invasion of Varroa destructor, an ectoparasitic viral vector in Western honeybees, provides a unique opportunity to examine how a novel vector affects disease epidemiology in a host community. This specialist honeybee mite vectors deformed wing virus (DWV), an important re-emerging honeybee pathogen that also infects wild bumblebees....

Fluorescent biomarkers demonstrate prospects for spreadable vaccines to control disease transmission in wild bats

Kevin Bakker, Tonie Rocke, Rachel Abbott, Carlos Tello, Jorge Carrera, William Valderrama, Carlos Shiva, Nestor Falcon, Jorge Osorio & Daniel Streicker
Vaccines that autonomously transfer among individuals have been proposed as a strategy to control infectious diseases within wildlife populations. However, understanding rates of spread and epidemiological efficacy in real world systems remain elusive. Here, we investigated whether topical vaccines that transfer among bats through social contacts can control vampire bat rabies, a medically and economically important zoonosis in Latin America. Field experiments in 3 Peruvian bat colonies which used fluorescent biomarkers as a proxy for...

2014 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Data from: Assessing for interaction between APOE ε4, sex, and lifestyle on cognitive abilities

Donald M. Lyall, Carlos Celis-Morales, Laura M. Lyall, Christopher Graham, Nicholas Graham, Daniel F. Mackay, Rona J. Strawbridge, Joey Ward, Jason M.R. Gill, Naveed Sattar, Jonathan Cavanagh, Daniel J. Smith & Jill P. Pell
Objective: To test for statistically significant interactions between apolipoprotein (APOE) e4 genotype, and lifestyle factors on worse cognitive abilities in UK Biobank. Methods: Using UK Biobank cohort data, we tested for statistically significant interactions between APOE e4 allele presence, lifestyle factors of alcohol intake, smoking, total physical activity and obesity, and sex, on cognitive tests of reasoning, information processing speed and executive function (n range=70,988-324,725 depending on the test). We statistically adjusted for potential confounders...

Data from: Diastolic pressure ratio: new approach and validation vs. the instantaneous wave-free ratio

Nils P Johnson
Aims The instantaneous wave-free ratio (iFR) and whole-cycle Pd/Pa investigate coronary physiology during non-hyperaemic conditions. To test for unique physiologic properties of the wave-free period when making resting coronary pressure measurements, we compared post hoc a diastolic pressure ratio (dPR) and Pd/Pa against iFR for numerical similarity and test/retest repeatability. Methods and results Eight hundred and ninety-three lesions from 833 subjects were included from the VERIFY 2 and CONTRAST studies. Diastolic pressure ratio and a...

Intracranial haemodynamic relationships in patients with cerebral small vessel disease

Gordon Blair, Michael Thrippleton, Yulu Shi, Iona Hamilton, Michael Stringer, Francesca Chappell, David Alexander Dickie, Peter Andrews, Ian Marshall, Fergus Doubal & Joanna Wardlaw
Objective To investigate cerebrovascular reactivity (CVR), blood flow, vascular and cerebrospinal fluid (CSF) pulsatility, and their independent relationship to cerebral small vessel disease (SVD) features, in patients with minor ischaemic stroke and MRI evidence of SVD. Methods We recruited patients with minor ischaemic stroke and assessed CVR using Blood Oxygen Level Dependent (BOLD) MRI during a hypercapnic challenge, cerebral blood flow, vascular and CSF pulsatility using phase contrast MRI, and structural MR brain imaging to...

Data from: Everything is not everywhere: marine compartments shape phytoplankton assemblages

Sofie Spatharis, Vasiliki Lamprinou, Alexandra Meziti, Konstantinos Kormas, Daniel Danielidis, Evangelia Smeti, Daniel Roelke, Rebecca Mancy & George Tsirtsis
The idea that “everything is everywhere, but the environment selects” has been seminal in microbial biogeography, and marine phytoplankton is one of the prototypical groups used to illustrate this. The typical argument has been that phytoplankton is ubiquitous, but that distinct assemblages form under environmental selection. It is well established that phytoplankton assemblages vary considerably between coastal ecosystems. However, the relative roles of compartmentalisation of regional seas and site-specific environmental conditions in shaping assemblage structures,...

Changing environments and genetic variation: natural variation in inbreeding does not compromise short-term physiological responses

James Buckley, Rónán Daly, Christina Cobbold, Karl Burgess & Barbara Mable
Selfing plant lineages are surprisingly widespread and successful in a broad range of environments, despite showing reduced genetic diversity, which is predicted to reduce long-term evolutionary potential. However, appropriate short-term plastic responses to new environmental conditions might not require high levels of standing genetic variation. In this study, we tested whether mating system variation among populations, and associated changes in genetic variability, affected short-term responses to environmental challenges. We compared relative fitness and metabolome profiles...

Data from: Simulating nutrient release from parental carcasses increases the growth, biomass and genetic diversity of juvenile Atlantic salmon

Darryl McLennan, Sonya K. Auer, Graeme J. Anderson, Thomas C. Reid, Ronald D. Bassar, David C. Stewart, Eef Cauwelier, James Sampayo, Simon McKelvey, Keith H. Nislow, John D. Armstrong & Neil B. Metcalfe
1. The net transport of nutrients by migratory fish from oceans to inland spawning areas has decreased due to population declines and migration barriers. Restoration of nutrients to increasingly oligotrophic upland streams (that were historically salmon spawning areas) have shown short-term benefits for juvenile salmon, but the longer-term consequences are little known. 2. Here we simulated the deposition of a small number of adult Atlantic salmon Salmo salar carcasses at the end of the spawning...

2011 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Stakeholder surveys to local farmers and officials in Chinese villages to understand knowledge management dynamics

Y. Zheng, L. Naylor, S. Waldron & D. Oliver
Data comprise results of social surveys carried out in China during 2016 – 2018 to the local stakeholders (farmers and village to county level officials) to understand their knowledge learning dynamics and preference. Surveys were conducted in the rural villages in Puding County, Guizhou Province and in Yujiang County, Jiangxi Province. The study was funded by the grant NE/N007425/1 which was awarded by the UK Natural Environment Research Council (NERC), and through cooperation with grant...

Registration Year

  • 2019
    22

Resource Types

  • Dataset
    22

Affiliations

  • University of Glasgow
    12
  • Hansen Experimental Physics Laboratory, Stanford University
    9
  • Electrical Engineering and Computer Science Department, University of Michigan
    9
  • SUPA School of Physics and Astronomy, University of Glasgow
    9
  • NASA Goddard Space Flight Center
    9
  • Center for Data Science, New York University
    9
  • Lockheed Martin Solar & Astrophysics Laboratory
    9
  • SETI Institute
    9
  • Southwest Research Institute
    9
  • Department of Psychiatry, University of Amsterdam
    9