15 Works

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...

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...

Data from: State-aware detection of sensory stimuli in the cortex of the awake mouse

Audrey J. Sederberg, Aurelie Pala, He J. V. Zheng, Biyu J. He & Garrett B. Stanley
Cortical responses to sensory inputs vary across repeated presentations of identical stimuli, but how this trial-to-trial variability impacts detection of sensory inputs is not fully understood. Using multi-channel local field potential (LFP) recordings in primary somatosensory cortex (S1) of the awake mouse, we optimized a data-driven cortical state classifier to predict single-trial sensory-evoked responses, based on features of the spontaneous, ongoing LFP recorded across cortical layers. Our findings show that, by utilizing an ongoing prediction...

Data from: The complex geography of domestication of the African rice Oryza glaberrima

Jae Young Choi, Maricris Zaidem, Rafal Gutaker, Katherine Dorph, Rakesh Kumar Singh & Michael D. Purugganan
While the domestication history of Asian rice has been extensively studied, details of the evolution of African rice remain elusive. The inner Niger delta has been suggested as the center of origin but molecular data to support this hypothesis is lacking. Here, we present a comprehensive analysis of the evolutionary and domestication history of African rice. By analyzing whole genome re-sequencing data from 282 individuals of domesticated African rice Oryza glaberrima and its progenitor O....

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: Human sound localization depends on sound intensity: implications for sensory coding

Antje Ihlefeld, Nima Alamatsaz & Robert M. Shapley
Human sound localization is an important computation performed by the brain. Models of sound localization commonly assume that sound lateralization from interaural time differences is level invariant. Here we observe that two prevalent theories of sound localization make opposing predictions. The labelled-line model encodes location through tuned representations of spatial location and predicts that perceived direction is level invariant. In contrast, the hemispheric-difference model encodes location through spike-rate and predicts that perceived direction becomes medially...

Data from: Evolutionary rate covariation analysis of E-cadherin identifies Raskol as a regulator of cell adhesion and actin dynamics in Drosophila

Qanber Raza, Jae Young Choi, Yang Li, Roisin M. O'Dowd, Simon C. Watkins, Yang Hong, Maria Chikina, Nathan L. Clark & Adam V. Kwiatkowski
The adherens junction couples the actin cytoskeletons of neighboring cells to provide the foundation for multicellular organization. The core of the adherens junction is the cadherin-catenin complex that arose early in the evolution of multicellularity to link actin to intercellular adhesions. Over time, evolutionary pressures have shaped the signaling and mechanical functions of the adherens junction to meet specific developmental and physiological demands. Evolutionary rate covariation (ERC) identifies proteins with correlated fluctuations in evolutionary rate...

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: 7 Tesla MRI of the ex vivo human brain at 100 micron resolution

Brian L. Edlow, Azma Mareyam, Andreas Horn, Jonathan R. Polimeni, Thomas Witzel, M. Dylan Tisdall, Jean Augustinack, Jason P. Stockmann, Bram R. Diamond, Allison Stevens, Lee S. Tirrell, Rebecca D. Folkerth, Lawrence L. Wald, Bruce Fischl & Andre Van Der Kouwe
We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 ┬Ám isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of...

Data from: The African ape-like foot of Ardipithecus ramidus and its implications for the origin of bipedalism

Thomas Cody Prang
The ancestral condition from which humans evolved is critical for understanding the adaptive origin of bipedal locomotion. The 4.4 million-year-old hominin partial skeleton attributed to Ardipithecus ramidus preserves a foot that purportedly shares morphometric affinities with monkeys, but this interpretation remains controversial. Here I show that the foot of Ar. ramidus is most similar to living chimpanzee and gorilla species among a large sample of anthropoid primates. The foot morphology of Ar. ramidus suggests that...

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...

Registration Year

  • 2019
    15

Resource Types

  • Dataset
    15

Affiliations

  • 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
  • University of Oxford, Department of Earth Sciences
    9