HST Imaging of the Brightest z ∼ 8–9 Galaxies from UltraVISTA: The Extreme Bright End of the UV Luminosity Function

NASA Astrophysics Data System (ADS)

Stefanon, Mauro; Labbé, Ivo; Bouwens, Rychard J.; Brammer, Gabriel B.; Oesch, Pascal; Franx, Marijn; Fynbo, Johan P. U.; Milvang-Jensen, Bo; Muzzin, Adam; Illingworth, Garth D.; Le Fèvre, Olivier; Caputi, Karina I.; Holwerda, Benne W.; McCracken, Henry J.; Smit, Renske; Magee, Dan

2017-12-01

We report on the discovery of three especially bright candidate {z}{phot}≳ 8 galaxies. Five sources were targeted for follow-up with the Hubble Space Telescope (HST)/Wide Field Camera 3 (WFC3), selected from a larger sample of 16 bright (24.8≲ H≲ 25.5 mag) candidate z≳ 8 Lyman break galaxies (LBGs) identified over 1.6 degrees2 of the COSMOS/UltraVISTA field. These were selected as Y and J dropouts by leveraging the deep (Y-to-{K}{{S}}∼ 25.3{--}24.8 mag, 5σ ) NIR data from the UltraVISTA DR3 release, deep ground-based optical imaging from the CFHTLS and Suprime-Cam programs, and Spitzer/IRAC mosaics combining observations from the SMUVS and SPLASH programs. Through the refined spectral energy distributions, which now also include new HyperSuprimeCam g-, r-, i-, z-, and Y-band data, we confirm that 3/5 galaxies have robust {z}{phot}∼ 8.0{--}8.7, consistent with the initial selection. The remaining 2/5 galaxies have a nominal {z}{phot}∼ 2. However, with HST data alone, these objects have increased probability of being at z∼ 9. We measure mean UV continuum slopes β =-1.74+/- 0.35 for the three z∼ 8{--}9 galaxies, marginally bluer than similarly luminous z∼ 4{--}6 in CANDELS but consistent with previous measurements of similarly luminous galaxies at z∼ 7. The circularized effective radius for our brightest source is 0.9 ± 0.3 kpc, similar to previous measurements for a bright z∼ 11 galaxy and bright z∼ 7 galaxies. Finally, enlarging our sample to include the six brightest z∼ 8 LBGs identified over UltraVISTA (i.e., including three other sources from Labbé et al.) we estimate for the first time the volume density of galaxies at the extreme bright end ({M}{UV}∼ -22 mag) of the z∼ 8 UV luminosity function. Despite this exceptional result, the still large statistical uncertainties do not allow us to discriminate between a Schechter and a double-power-law form.

THE SLOAN DIGITAL SKY SURVEY REVERBERATION MAPPING PROJECT: TECHNICAL OVERVIEW

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Yue; Brandt, W. N.; Dawson, Kyle S.

2015-01-01

The Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project is a dedicated multi-object RM experiment that has spectroscopically monitored a sample of 849 broad-line quasars in a single 7 deg{sup 2} field with the SDSS-III Baryon Oscillation Spectroscopic Survey spectrograph. The RM quasar sample is flux-limited to i {sub psf} = 21.7 mag, and covers a redshift range of 0.1 < z < 4.5 without any other cuts on quasar properties. Optical spectroscopy was performed during 2014 January-July dark/gray time, with an average cadence of ∼4 days, totaling more than 30 epochs. Supporting photometric monitoring in the g and i bandsmore » was conducted at multiple facilities including the Canada-France-Hawaii Telescope (CFHT) and the Steward Observatory Bok telescope in 2014, with a cadence of ∼2 days and covering all lunar phases. The RM field (R.A., decl. = 14:14:49.00, +53:05:00.0) lies within the CFHT-LS W3 field, and coincides with the Pan-STARRS 1 (PS1) Medium Deep Field MD07, with three prior years of multi-band PS1 light curves. The SDSS-RM six month baseline program aims to detect time lags between the quasar continuum and broad line region (BLR) variability on timescales of up to several months (in the observed frame) for ∼10% of the sample, and to anchor the time baseline for continued monitoring in the future to detect lags on longer timescales and at higher redshift. SDSS-RM is the first major program to systematically explore the potential of RM for broad-line quasars at z > 0.3, and will investigate the prospects of RM with all major broad lines covered in optical spectroscopy. SDSS-RM will provide guidance on future multi-object RM campaigns on larger scales, and is aiming to deliver more than tens of BLR lag detections for a homogeneous sample of quasars. We describe the motivation, design, and implementation of this program, and outline the science impact expected from the resulting data for RM and general quasar science.« less

Evolution of the observed Lyα luminosity function from z = 6.5 to z = 7.7: evidence for the epoch of reionization?

NASA Astrophysics Data System (ADS)

Clément, B.; Cuby, J.-G.; Courbin, F.; Fontana, A.; Freudling, W.; Fynbo, J.; Gallego, J.; Hibon, P.; Kneib, J.-P.; Le Fèvre, O.; Lidman, C.; McMahon, R.; Milvang-Jensen, B.; Moller, P.; Moorwood, A.; Nilsson, K. K.; Pentericci, L.; Venemans, B.; Villar, V.; Willis, J.

2012-02-01

Aims: Lyα emitters (LAEs) can be detected out to very high redshifts during the epoch of reionization. The evolution of the LAE luminosity function with redshift is a direct probe of the Lyα transmission of the intergalactic medium (IGM), and therefore of the IGM neutral-hydrogen fraction. Measuring the Lyα luminosity function (LF) of Lyα emitters at redshift z = 7.7 therefore allows us to constrain the ionizing state of the Universe at this redshift. Methods: We observed three 7'.5 × 7'.5 fields with the HAWK-I instrument at the VLT with a narrow band filter centred at 1.06 μm and targeting Lyα emitters at redshift z ~ 7.7. The fields were chosen for the availability of multiwavelength data. One field is a galaxy cluster, the Bullet Cluster, which allowed us to use gravitational amplification to probe luminosities that are fainter than in the field. The two other fields are subareas of the GOODS Chandra Deep Field South and CFHTLS-D4 deep field. We selected z = 7.7 LAE candidates from a variety of colour criteria, in particular from the absence of detection in the optical bands. Results: We do not find any LAE candidates at z = 7.7 in ~2.4 × 104 Mpc3 down to a narrow band AB magnitude of ~26, which allows us to infer robust constraints on the Lyα LAE luminosity function at this redshift. Conclusions: The predicted mean number of objects at z = 6.5, derived from somewhat different luminosity functions of Hu et al. (2010, ApJ, 725, 394), Ouchi et al. (2010, ApJ, 723, 869), and Kashikawa et al. (2011, ApJ, 734, 119) are 2.5, 13.7, and 11.6, respectively. Depending on which of these luminosity functions we refer to, we exclude a scenario with no evolution from z = 6.5 to z = 7.7 at 85% confidence without requiring a strong change in the IGM Lyα transmission, or at 99% confidence with a significant quenching of the IGM Lyα transmission, possibly from a strong increase in the high neutral-hydrogen fraction between these two redshifts. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere (ESO), Chile, Prog-Id 181.A-0485, 181.A-0717, 60.A-9284, 084.A-0749. Based on observations obtained at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France (CNRS), and the University of Hawaii. This work is based in part on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA and in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Full spectroscopic data and auxiliary information release (PDR-2)

NASA Astrophysics Data System (ADS)

Scodeggio, M.; Guzzo, L.; Garilli, B.; Granett, B. R.; Bolzonella, M.; de la Torre, S.; Abbas, U.; Adami, C.; Arnouts, S.; Bottini, D.; Cappi, A.; Coupon, J.; Cucciati, O.; Davidzon, I.; Franzetti, P.; Fritz, A.; Iovino, A.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; Marchetti, A.; Marulli, F.; Polletta, M.; Pollo, A.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Bel, J.; Branchini, E.; De Lucia, G.; Ilbert, O.; McCracken, H. J.; Moutard, T.; Peacock, J. A.; Zamorani, G.; Burden, A.; Fumana, M.; Jullo, E.; Marinoni, C.; Mellier, Y.; Moscardini, L.; Percival, W. J.

2018-01-01

We present the full public data release (PDR-2) of the VIMOS Public Extragalactic Redshift Survey (VIPERS), performed at the ESO VLT. We release redshifts, spectra, CFHTLS magnitudes and ancillary information (as masks and weights) for a complete sample of 86 775 galaxies (plus 4732 other objects, including stars and serendipitous galaxies); we also include their full photometrically-selected parent catalogue. The sample is magnitude limited to iAB ≤ 22.5, with an additional colour-colour pre-selection devised as to exclude galaxies at z < 0.5. This practically doubles the effective sampling of the VIMOS spectrograph over the range 0.5 < z < 1.2 (reaching 47% on average), yielding a final median local galaxy density close to 5 × 10-3h3 Mpc-3. The total area spanned by the final data set is ≃ 23.5 deg2, corresponding to 288 VIMOS fields with marginal overlaps, split over two regions within the CFHTLS-Wide W1 and W4 equatorial fields (at RA ≃ 2 and ≃ 22 h, respectively). Spectra were observed at a resolution R = 220, covering a wavelength range 5500-9500 Å. Data reduction and redshift measurements were performed through a fully automated pipeline; all redshift determinations were then visually validated and assigned a quality flag. Measurements with a quality flag ≥ 2 are shown to have a confidence level of 96% or larger and make up 88% of all measured galaxy redshifts (76 552 out of 86 775), constituting the VIPERS prime catalogue for statistical investigations. For this sample the rms redshift error, estimated using repeated measurements of about 3000 galaxies, is found to be σz = 0.00054(1 + z). All data are available at http://vipers.inaf.it and on the ESO Archive. Based on observations collected at the European Southern Observatory, Cerro Paranal, Chile, using the Very Large Telescope under programmes 182.A-0886 and partly 070.A-9007. Also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://www.vipers.inaf.it/

K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thanjavur, Karun; Willis, Jon; Crampton, David, E-mail: karun@uvic.c

2009-11-20

We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg{sup 2} images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulationsmore » show that the false detection rate for these data, at our selected threshold, is only approx1%, and that the cluster catalogs are approx80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z approx 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg{sup 2} are detected, with 1-2 Fornax-like or richer clusters every 2 deg{sup 2}. Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.« less

VizieR Online Data Catalog: VIMOS Public Extragalactic Survey (VIPERS) DR1 (Garilli+, 2014)

NASA Astrophysics Data System (ADS)

Garilli, B.; Guzzo, L.; Scodeggio, M.; Bolzonella, M.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bottini, D.; Branchini, E.; Cappi, A.; Coupon, J.; Cucciati, O.; Davidzon, I.; de Lucia, G.; de la Torre, S.; Franzetti, P.; Fritz, A.; Fumana, M.; Granett, B. R.; Ilbert, O.; Iovino, A.; Krywult, J.; Le Brun, V.; Le Fevre, O.; Maccagni, D.; Malek, K.; Marulli, F.; McCracken, H. J.; Paioro, L.; Polletta, M.; Pollo, A.; Schlagenhaufer, H.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zamorani, G.; Zanichelli, A.; Burden, A.; di Porto, C.; Marchetti, A.; Marinoni, C.; Mellier, Y.; Moscardini, L.; Nichol, R. C.; Peacock, J. A.; Percival, W. J.; Phleps, S.; Wolk, M.

2014-09-01

We present the first Public Data Release (PDR-1) of the VIMOS Public Extragalactic Survey (VIPERS). It comprises 57204 spectroscopic measurements together with all additional information necessary for optimal scientific exploitation of the data, in particular the associated photometric measurements and quantification of the photometric and survey completeness. VIPERS is an ESO Large Programme designed to build a spectroscopic sample of =~100000 galaxies with iAB<22.5 and 0.5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daniel, Scott F.; Linder, Eric V.; Lawrence Berkeley National Laboratory, Berkeley, California

Deviations from general relativity, such as could be responsible for the cosmic acceleration, would influence the growth of large-scale structure and the deflection of light by that structure. We clarify the relations between several different model-independent approaches to deviations from general relativity appearing in the literature, devising a translation table. We examine current constraints on such deviations, using weak gravitational lensing data of the CFHTLS and COSMOS surveys, cosmic microwave background radiation data of WMAP5, and supernova distance data of Union2. A Markov chain Monte Carlo likelihood analysis of the parameters over various redshift ranges yields consistency with general relativitymore » at the 95% confidence level.« less

VizieR Online Data Catalog: Photometric Calibration of SNLS (Regnault+, 2009)

NASA Astrophysics Data System (ADS)

Regnault, N.; Conley, A.; Guy, J.; Sullivan, M.; Cuillandre, J.-C.; Astier, P.; Balland, C.; Basa, S.; Carlberg, R. G.; Fouchez, D.; Hardin, D.; Hook, I. M.; Howell, D. A.; Pain, R.; Perrett, K.; Pritchet, C. J.

2009-08-01

This is the photometric calibration of the SuperNova Legacy Survey (SNLS) three year dataset. The SNLS corresponds to the DEEP component of the larger Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). The SNLS repeatedly monitors four one square degree fields (labeled D[1-4]) with the MegaCam wide-field imager, in the g, r, i and z bands. u-band observations of the same fields are also available, although not formally part of the SNLS dataset. The non-uniformities of the MegaCam imager photometric response have been mapped as a function of the position on the focal plane. The fluxes, measured on the survey images processed with the CFHT Elixir pipeline, have been corrected for these non-uniformities in order to obtain measurements that are uniform at the ~1% level. The MegaCam passband transmissions were found to be non-uniform, the filters being 3 to 6 nanometers bluer on the edges of the camera than on the center. This result agrees with the filter scans provided by the filter manufacturer (Sagem/REOSC). This has important consequences on the definition of the MegaCam magnitudes: the natural magnitude system depends on the focal plane location where the observations were made. In order not to break the connection between calibrated magnitudes and their physical flux counterparts, we chose to report the *natural magnitudes* of each object, measured in the MegaCam passbands, at the focal plane location where the object was observed. We call this system, "Local Natural Magnitudes". The non-uniformities of the MegaCam effective passbands are small and, for main sequence stellar objects, they may be accounted for using linear color corrections. The relation between the Local Natural Magnitudes of a given star, observed at two locations x_0 and x of the focal plane are: g|x = g|x0 + dkggr(x) * ( (g-r)|x0 - (g-r)BD+17|x_0 ) ... z|x = z|x0 + dkziz(x) * ( (i-z)|x0 - (i-z)BD+17|x_0 ) where the dk(x) are (position dependant) color terms. We provide dk(x) maps for each MegaCam band (see below). The SNLS 3 year calibration relies on the (Landolt, 1992AJ....104..340) standard star catalog. Landolt fields are observed during each photometric night along with the SNLS fields. Zero-points are derived from these observations. Stable and isolated stars are detected on the SNLS fields and selected as "tertiary standards". The calibrated magnitudes of each tertiary standard obtained under photometric conditions are combined to produce a calibration catalog for each SNLS field. To interpret the tertiary standard magnitudes as physical fluxes, we need a primary standard, i.e. a star with known MegaCam magnitudes and whose spectral energy distribution has been measured absolutely. The SNLS uses BD+17 4708 whose SED has been measured in Bohlin & Gilliland, 2004, Cat. using the HST STIS and NICMOS spectrographs. BD+17 4708 has not been directly observed by SNLS, however, its MegaCam magnitudes were inferred from its known Landolt magnitudes (this paper, table 7). The tertiary star Local Natural Magnitudes are defined so that the associated physical broadband flux f|x is given by: f|x = 10{-0.4*(m|x-mref)}*{int}[Sref(l)*T(l;x)]dl where m|x is the tertiary star magnitudes at location x on the focal plane, mref is the MegaCam magnitude of BD+17 4708 (at the center of the focal plane, see table 7 of this paper), Sref(l) is the SED of BD+17 4708 measured in 2004AJ....128.3053B, and T(l;x) is the effective passband of MegaCam at location x. Attached is all the necessary information to tie MegaCam observations to this system. We provide (a) the griz magnitudes of the SNLS tertiary standards for all four SNLS fields (b) the MegaCam open transmission and the ugriz MegaCam filter scans at various position along a diagonal (c) the final uncertainty budget in the form of 3 covariance matrices. The u-band observations of the SNLS DEEP fields are not formally part of the SNLS. Nevetheless we give u-band magnitudes for a subset of the SNLS tertiary stars. (22 data files).

Investigating the Density of Isolated Field Elliptical Galaxies

NASA Astrophysics Data System (ADS)

Ulgen, E. Kaan

2016-02-01

In this thesis, 215.590 elliptical galaxies with M(r) ≤ -21 in the CFHTLS-W1 field which is covering 72 sq. deg on the sky are examined . Criterion given by Smith et al. (2004) has been used to determine isolated elliptical galaxies. 118 isolated elliptical galaxies have been determined in total. By using g, r and i photometric bands, the true-colour images of candidates are produced and visually inspected. In order to have a clean list of IfEs some candidates are excluded from the final sample after visual inspection. The final sample consists of 60 IfEs which corresponds to the 0.027 per cent of the whole sample. In other words, IfE density in the W1 is 0.8 IfE / sq.deg. Since the formation of the ellipticals in the isolated regions is not known clearly, it is crucial to determine IfEs and compare their photometric and morphological properties to the normal or cluster ellipticals. When the (g-i) distributions of three different elliptical galaxy class are compared, it is found that they have almost the same colours. When the redshift distributions of the galaxies are considered, it can be seen that IfEs formed later than the cluster and normal ellipticals. The average redshift of IfEs is determined as zphot=0.284, while for normal and cluster ellipticals, it is, respectively, 0.410 and 0.732. In addition, when the effective radii of the three elliptical systems are considered, it is found that the IfEs are bigger than the other two elliptical classes.

WFIRST: Science from Deep Field Surveys

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Foley, Ryan; WFIRST Deep Field Working Group

2018-06-01

WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

WFIRST: Science from Deep Field Surveys

NASA Astrophysics Data System (ADS)

Koekemoer, Anton; Foley, Ryan; WFIRST Deep Field Working Group

2018-01-01

WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

Dosimetric comparison of moderate deep inspiration breath-hold and free-breathing intensity-modulated radiotherapy for left-sided breast cancer.

PubMed

Chi, F; Wu, S; Zhou, J; Li, F; Sun, J; Lin, Q; Lin, H; Guan, X; He, Z

2015-05-01

This study determined the dosimetric comparison of moderate deep inspiration breath-hold using active breathing control and free-breathing intensity-modulated radiotherapy (IMRT) after breast-conserving surgery for left-sided breast cancer. Thirty-one patients were enrolled. One free breathe and two moderate deep inspiration breath-hold images were obtained. A field-in-field-IMRT free-breathing plan and two field-in-field-IMRT moderate deep inspiration breath-holding plans were compared in the dosimetry to target volume coverage of the glandular breast tissue and organs at risks for each patient. The breath-holding time under moderate deep inspiration extended significantly after breathing training (P<0.05). There was no significant difference between the free-breathing and moderate deep inspiration breath-holding in the target volume coverage. The volume of the ipsilateral lung in the free-breathing technique were significantly smaller than the moderate deep inspiration breath-holding techniques (P<0.05); however, there was no significant difference between the two moderate deep inspiration breath-holding plans. There were no significant differences in target volume coverage between the three plans for the field-in-field-IMRT (all P>0.05). The dose to ipsilateral lung, coronary artery and heart in the field-in-field-IMRT were significantly lower for the free-breathing plan than for the two moderate deep inspiration breath-holding plans (all P<0.05); however, there was no significant difference between the two moderate deep inspiration breath-holding plans. The whole-breast field-in-field-IMRT under moderate deep inspiration breath-hold with active breathing control after breast-conserving surgery in left-sided breast cancer can reduce the irradiation volume and dose to organs at risks. There are no significant differences between various moderate deep inspiration breath-holding states in the dosimetry of irradiation to the field-in-field-IMRT target volume coverage and organs at risks. Copyright © 2015 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

PubMed

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

NASA Astrophysics Data System (ADS)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-01

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

The weak lensing analysis of the CFHTLS and NGVS RedGOLD galaxy clusters

NASA Astrophysics Data System (ADS)

Parroni, C.; Mei, S.; Erben, T.; Van Waerbeke, L.; Raichoor, A.; Ford, J.; Licitra, R.; Meneghetti, M.; Hildebrandt, H.; Miller, L.; Côté, P.; Covone, G.; Cuillandre, J.-C.; Duc, P.-A.; Ferrarese, L.; Gwyn, S. D. J.; Puzia, T. H.

2017-12-01

An accurate estimation of galaxy cluster masses is essential for their use in cosmological and astrophysical studies. We studied the accuracy of the optical richness obtained by our RedGOLD cluster detection algorithm tep{licitra2016a, licitra2016b} as a mass proxy, using weak lensing and X-ray mass measurements. We measured stacked weak lensing cluster masses for a sample of 1323 galaxy clusters in the Canada-France-Hawaii Telescope Legacy Survey W1 and the Next Generation Virgo Cluster Survey at 0.2

Overview of deep learning in medical imaging.

PubMed

Suzuki, Kenji

2017-09-01

The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a lesser number of training cases than did CNNs. "Deep learning", or ML with image input, in medical imaging is an explosively growing, promising field. It is expected that ML with image input will be the mainstream area in the field of medical imaging in the next few decades.

The First Pan-Starrs Medium Deep Field Variable Star Catalog

NASA Astrophysics Data System (ADS)

Flewelling, Heather

2013-01-01

We present the first Pan-Starrs 1 Medium Deep Field Variable Star Catalog (PS1-MDF-VSC). The Pan-Starrs 1 (PS1) telescope is a 1.8 meter survey telescope with a 1.4 Gigapixel camera, and is located in Haleakala, Hawaii. The Medium Deep survey, which consists of 10 fields located uniformly across the sky, totalling 70 square degrees, is observed each night, in 2-3 filters per field, with 8 exposures per filter. We have located and classified several hundred periodic variable stars within the Medium Deep fields, and we present the first catalog listing the properties of these variable stars.

Swimming in Sculptor

NASA Image and Video Library

2016-03-07

Peering deep into the early Universe, this picturesque parallel field observation from the NASA/ESA Hubble Space Telescope reveals thousands of colourful galaxies swimming in the inky blackness of space. A few foreground stars from our own galaxy, the Milky Way, are also visible. In October 2013 Hubble’s Wide Field Camera 3 (WFC3) and Advanced Camera for Surveys (ACS) began observing this portion of sky as part of the Frontier Fields programme. This spectacular skyscape was captured during the study of the giant galaxy cluster Abell 2744, otherwise known as Pandora’s Box. While one of Hubble’s cameras concentrated on Abell 2744, the other camera viewed this adjacent patch of sky near to the cluster. Containing countless galaxies of various ages, shapes and sizes, this parallel field observation is nearly as deep as the Hubble Ultra-Deep Field. In addition to showcasing the stunning beauty of the deep Universe in incredible detail, this parallel field — when compared to other deep fields — will help astronomers understand how similar the Universe looks in different directions

Three dimensional amorphous silicon/microcrystalline silicon solar cells

DOEpatents

Kaschmitter, James L.

1996-01-01

Three dimensional deep contact amorphous silicon/microcrystalline silicon (a-Si/.mu.c-Si) solar cells which use deep (high aspect ratio) p and n contacts to create high electric fields within the carrier collection volume material of the cell. The deep contacts are fabricated using repetitive pulsed laser doping so as to create the high aspect p and n contacts. By the provision of the deep contacts which penetrate the electric field deep into the material where the high strength of the field can collect many of the carriers, thereby resulting in a high efficiency solar cell.

Three dimensional amorphous silicon/microcrystalline silicon solar cells

DOEpatents

Kaschmitter, J.L.

1996-07-23

Three dimensional deep contact amorphous silicon/microcrystalline silicon (a-Si/{micro}c-Si) solar cells are disclosed which use deep (high aspect ratio) p and n contacts to create high electric fields within the carrier collection volume material of the cell. The deep contacts are fabricated using repetitive pulsed laser doping so as to create the high aspect p and n contacts. By the provision of the deep contacts which penetrate the electric field deep into the material where the high strength of the field can collect many of the carriers, thereby resulting in a high efficiency solar cell. 4 figs.

Long Range Effect of The M7.8 April 2015 Nepal Earth Quake on the Deep Groudwater Outflow in a Thousand-Mile-Away Geothermal Field in Southern China's Guangdong

NASA Astrophysics Data System (ADS)

Lu, G.; Yu, S.; Xu, F.; Wang, X.; Yan, K.; Yuen, D. A.

2015-12-01

Deep ground waters sustain high temperature and pressure and are susceptible to impact from an earthquake. How an earthquake would have been associated with long-range effect on geological environment of deep groundwater is a question of interest to the scientific community and general public. The massive Richter 8.1 Nepal Earthquake (on April 25, 2015) provided a rare opportunity to test the response of deep groundwater systems. Deep ground waters at elevated temperature would naturally flow to ground surface along preferential flow path such as a deep fault, forming geothermal water flows. Geothermal water flows are susceptible to stress variation and can reflect the physical conditions of supercritical hot water kilometers deep down inside the crust. This paper introduces the monitoring work on the outflow in Xijiang Geothermal Field of Xinyi City, Guangdong Province in southern China. The geothermal field is one of typical geothermal fields with deep faults in Guangdong. The geothermal spring has characteristic daily variation of up to 72% in flow rate, which results from being associated with a north-south run deep fault susceptible to earthquake event. We use year-long monitoring data to illustrate how the Nepal earthquake would have affected the flows at the field site over 2.5 thousand kilometers away. The irregularity of flow is judged by deviation from otherwise good correlation of geothermal spring flow with solid earth tidal waves. This work could potentially provide the basis for further study of deep groundwater systems and insight to earthquake prediction.

SEDS: The Spitzer Extended Deep Survey. Survey Design, Photometry, and Deep IRAC Source Counts

NASA Technical Reports Server (NTRS)

Ashby, M. L. N.; Willner, S. P.; Fazio, G. G.; Huang, J.-S.; Arendt, A.; Barmby, P.; Barro, G; Bell, E. F.; Bouwens, R.; Cattaneo, A.;

Deepest X-Rays Ever Reveal universe Teeming With Black Holes

NASA Astrophysics Data System (ADS)

2001-03-01

For the first time, astronomers believe they have proof black holes of all sizes once ruled the universe. NASA's Chandra X-ray Observatory provided the deepest X-ray images ever recorded, and those pictures deliver a novel look at the past 12 billion years of black holes. Two independent teams of astronomers today presented images that contain the faintest X-ray sources ever detected, which include an abundance of active super massive black holes. "The Chandra data show us that giant black holes were much more active in the past than at present," said Riccardo Giacconi, of Johns Hopkins University and Associated Universities, Inc., Washington, DC. The exposure is known as "Chandra Deep Field South" since it is located in the Southern Hemisphere constellation of Fornax. "In this million-second image, we also detect relatively faint X-ray emission from galaxies, groups, and clusters of galaxies". The images, known as Chandra Deep Fields, were obtained during many long exposures over the course of more than a year. Data from the Chandra Deep Field South will be placed in a public archive for scientists beginning today. "For the first time, we are able to use X-rays to look back to a time when normal galaxies were several billion years younger," said Ann Hornschemeier, Pennsylvania State University, University Park. The group’s 500,000-second exposure included the Hubble Deep Field North, allowing scientists the opportunity to combine the power of Chandra and the Hubble Space Telescope, two of NASA's Great Observatories. The Penn State team recently acquired an additional 500,000 seconds of data, creating another one-million-second Chandra Deep Field, located in the constellation of Ursa Major. Chandra Deep Field North/Hubble Deep Field North Press Image and Caption The images are called Chandra Deep Fields because they are comparable to the famous Hubble Deep Field in being able to see further and fainter objects than any image of the universe taken at X-ray wavelengths. Both Chandra Deep Fields are comparable in observation time to the Hubble Deep Fields, but cover a much larger area of the sky. "In essence, it is like seeing galaxies similar to our own Milky Way at much earlier times in their lives," Hornschemeier added. "These data will help scientists better understand star formation and how stellar-sized black holes evolve." Combining infrared and X-ray observations, the Penn State team also found veils of dust and gas are common around young black holes. Another discovery to emerge from the Chandra Deep Field South is the detection of an extremely distant X-ray quasar, shrouded in gas and dust. "The discovery of this object, some 12 billion light years away, is key to understanding how dense clouds of gas form galaxies, with massive black holes at their centers," said Colin Norman of Johns Hopkins University. The Chandra Deep Field South results were complemented by the extensive use of deep optical observations supplied by the Very Large Telescope of the European Southern Observatory in Garching, Germany. The Penn State team obtained optical spectroscopy and imaging using the Hobby-Eberly Telescope in Ft. Davis, TX, and the Keck Observatory atop Mauna Kea, HI. Chandra's Advanced CCD Imaging Spectrometer was developed for NASA by Penn State and Massachusetts Institute of Technology under the leadership of Penn State Professor Gordon Garmire. NASA's Marshall Space Flight Center, Huntsville, AL, manages the Chandra program for the Office of Space Science, Washington, DC. TRW, Inc., Redondo Beach, California, is the prime contractor for the spacecraft. The Smithsonian's Chandra X-ray Center controls science and flight operations from Cambridge, MA. More information is available on the Internet at: http://chandra.harvard.edu AND http://chandra.nasa.gov

[Deep learning and neuronal networks in ophthalmology : Applications in the field of optical coherence tomography].

PubMed

Treder, M; Eter, N

2018-04-19

Deep learning is increasingly becoming the focus of various imaging methods in medicine. Due to the large number of different imaging modalities, ophthalmology is particularly suitable for this field of application. This article gives a general overview on the topic of deep learning and its current applications in the field of optical coherence tomography. For the benefit of the reader it focuses on the clinical rather than the technical aspects.

Deep learning for computational chemistry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less

Deep Extragalactic VIsible Legacy Survey (DEVILS): Motivation, Design and Target Catalogue

NASA Astrophysics Data System (ADS)

Davies, L. J. M.; Robotham, A. S. G.; Driver, S. P.; Lagos, C. P.; Cortese, L.; Mannering, E.; Foster, C.; Lidman, C.; Hashemizadeh, A.; Koushan, S.; O'Toole, S.; Baldry, I. K.; Bilicki, M.; Bland-Hawthorn, J.; Bremer, M. N.; Brown, M. J. I.; Bryant, J. J.; Catinella, B.; Croom, S. M.; Grootes, M. W.; Holwerda, B. W.; Jarvis, M. J.; Maddox, N.; Meyer, M.; Moffett, A. J.; Phillipps, S.; Taylor, E. N.; Windhorst, R. A.; Wolf, C.

2018-06-01

The Deep Extragalactic VIsible Legacy Survey (DEVILS) is a large spectroscopic campaign at the Anglo-Australian Telescope (AAT) aimed at bridging the near and distant Universe by producing the highest completeness survey of galaxies and groups at intermediate redshifts (0.3 < z < 1.0). Our sample consists of ˜60,000 galaxies to Y<21.2 mag, over ˜6 deg2 in three well-studied deep extragalactic fields (Cosmic Origins Survey field, COSMOS, Extended Chandra Deep Field South, ECDFS and the X-ray Multi-Mirror Mission Large-Scale Structure region, XMM-LSS - all Large Synoptic Survey Telescope deep-drill fields). This paper presents the broad experimental design of DEVILS. Our target sample has been selected from deep Visible and Infrared Survey Telescope for Astronomy (VISTA) Y-band imaging (VISTA Deep Extragalactic Observations, VIDEO and UltraVISTA), with photometry measured by PROFOUND. Photometric star/galaxy separation is done on the basis of NIR colours, and has been validated by visual inspection. To maximise our observing efficiency for faint targets we employ a redshift feedback strategy, which continually updates our target lists, feeding back the results from the previous night's observations. We also present an overview of the initial spectroscopic observations undertaken in late 2017 and early 2018.

Development and application of deep convolutional neural network in target detection

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.

PubMed

Choi, Hongyoon

2018-04-01

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones.

PubMed

Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

2018-01-23

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

PubMed Central

Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

2018-01-01

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones. PMID:29360793

Hubble Sees a Legion of Galaxies

NASA Image and Video Library

2017-12-08

Peering deep into the early universe, this picturesque parallel field observation from the NASA/ESA Hubble Space Telescope reveals thousands of colorful galaxies swimming in the inky blackness of space. A few foreground stars from our own galaxy, the Milky Way, are also visible. In October 2013 Hubble’s Wide Field Camera 3 (WFC3) and Advanced Camera for Surveys (ACS) began observing this portion of sky as part of the Frontier Fields program. This spectacular skyscape was captured during the study of the giant galaxy cluster Abell 2744, otherwise known as Pandora’s Box. While one of Hubble’s cameras concentrated on Abell 2744, the other camera viewed this adjacent patch of sky near to the cluster. Containing countless galaxies of various ages, shapes and sizes, this parallel field observation is nearly as deep as the Hubble Ultra-Deep Field. In addition to showcasing the stunning beauty of the deep universe in incredible detail, this parallel field — when compared to other deep fields — will help astronomers understand how similar the universe looks in different directions. Image credit: NASA, ESA and the HST Frontier Fields team (STScI), NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Quantum neuromorphic hardware for quantum artificial intelligence

NASA Astrophysics Data System (ADS)

Prati, Enrico

2017-08-01

The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.

Deep Borehole Field Test Research Activities at LBNL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dobson, Patrick; Tsang, Chin-Fu; Kneafsey, Timothy

The goal of the U.S. Department of Energy Used Fuel Disposition’s (UFD) Deep Borehole Field Test is to drill two 5 km large-diameter boreholes: a characterization borehole with a bottom-hole diameter of 8.5 inches and a field test borehole with a bottom-hole diameter of 17 inches. These boreholes will be used to demonstrate the ability to drill such holes in crystalline rocks, effectively characterize the bedrock repository system using geophysical, geochemical, and hydrological techniques, and emplace and retrieve test waste packages. These studies will be used to test the deep borehole disposal concept, which requires a hydrologically isolated environment characterizedmore » by low permeability, stable fluid density, reducing fluid chemistry conditions, and an effective borehole seal. During FY16, Lawrence Berkeley National Laboratory scientists conducted a number of research studies to support the UFD Deep Borehole Field Test effort. This work included providing supporting data for the Los Alamos National Laboratory geologic framework model for the proposed deep borehole site, conducting an analog study using an extensive suite of geoscience data and samples from a deep (2.5 km) research borehole in Sweden, conducting laboratory experiments and coupled process modeling related to borehole seals, and developing a suite of potential techniques that could be applied to the characterization and monitoring of the deep borehole environment. The results of these studies are presented in this report.« less

VizieR Online Data Catalog: Spitzer-CANDELS catalog within 5 deep fields (Ashby+, 2015)

NASA Astrophysics Data System (ADS)

Ashby, M. L. N.; Willner, S. P.; Fazio, G. G.; Dunlop, J. S.; Egami, E.; Faber, S. M.; Ferguson, H. C.; Grogin, N. A.; Hora, J. L.; Huang, J.-S.; Koekemoer, A. M.; Labbe, I.; Wang, Z.

2015-08-01

We chose to locate S-CANDELS inside the wider and shallower fields already covered by Spitzer Extended Deep Survey (SEDS), in regions that enjoy deep optical and NIR imaging from HST/CANDELS. These S-CANDELS fields are thus the Extended GOODS-south (aka the GEMS field, hereafter ECDFS; Rix et al. 2004ApJS..152..163R; Castellano et al. 2010A&A...511A..20C), the Extended GOODS-north (HDFN; Giavalisco et al. 2004, II/261; Wang et al. 2010, J/ApJS/187/251; Hathi et al. 2012ApJ...757...43H; Lin et al. 2012ApJ...756...71L), the UKIDSS UDS (aka the Subaru/XMM Deep Field, Ouchi et al. 2001ApJ...558L..83O; Lawrence et al. 2007, II/319), a narrow field within the EGS (Davis et al. 2007ApJ...660L...1D; Bielby et al. 2012A&A...545A..23B), and a strip within the UltraVista deep survey of the larger COSMOS field (Scoville et al. 2007ApJS..172...38S; McCracken et al. 2012, J/A+A/544/A156). The S-CANDELS observing strategy was designed to maximize the area covered to full depth within the CANDELS area. Each field was visited twice with six months separating the two visits. Table 1 lists the epochs for each field. All of the IRAC full-depth coverage is within the SEDS area (Ashby et al. 2013, J/ApJ/769/80), and almost all is within the area covered by HST for CANDELS. (6 data files).

Low-cost, high-precision micro-lensed optical fiber providing deep-micrometer to deep-nanometer-level light focusing.

PubMed

Wen, Sy-Bor; Sundaram, Vijay M; McBride, Daniel; Yang, Yu

2016-04-15

A new type of micro-lensed optical fiber through stacking appropriate high-refractive microspheres at designed locations with respect to the cleaved end of an optical fiber is numerically and experimentally demonstrated. This new type of micro-lensed optical fiber can be precisely constructed with low cost and high speed. Deep micrometer-scale and submicrometer-scale far-field light spots can be achieved when the optical fibers are multimode and single mode, respectively. By placing an appropriate teardrop dielectric nanoscale scatterer at the far-field spot of this new type of micro-lensed optical fiber, a deep-nanometer near-field spot can also be generated with high intensity and minimum joule heating, which is valuable in high-speed, high-resolution, and high-power nanoscale detection compared with traditional near-field optical fibers containing a significant portion of metallic material.

Deep CFHT Y-band Imaging of VVDS-F22 Field. II. Quasar Selection and Quasar Luminosity Function

NASA Astrophysics Data System (ADS)

Yang, Jinyi; Wu, Xue-Bing; Liu, Dezi; Fan, Xiaohui; Yang, Qian; Wang, Feige; McGreer, Ian D.; Fan, Zuhui; Yuan, Shuo; Shan, Huanyuan

2018-03-01

We report the results of a faint quasar survey in a one-square-degree field. The aim is to test the Y-K/g-z and J-K/i-Y color selection criteria for quasars at faint magnitudes to obtain a complete sample of quasars based on deep optical and near-infrared color–color selection and to measure the faint end of the quasar luminosity function (QLF) over a wide redshift range. We carried out a quasar survey based on the Y-K/g-z and J-K/i-Y quasar selection criteria, using the deep Y-band data obtained from our CFHT/WIRCam Y-band images in a two-degree field within the F22 field of the VIMOS VLT deep survey, optical co-added data from Sloan Digital Sky Survey Stripe 82 and deep near-infrared data from the UKIDSS Deep Extragalactic Survey in the same field. We discovered 25 new quasars at 0.5< z< 4.5 and i< 22.5 mag within one-square-degree field. The survey significantly increases the number of faint quasars in this field, especially at z∼ 2{--}3. It confirms that our color selections are highly complete in a wide redshift range (z< 4.5), especially over the quasar number density peak at z∼ 2{--}3, even for faint quasars. Combining all previous known quasars and new discoveries, we construct a sample with 109 quasars and measure the binned QLF and parametric QLF. Although the sample is small, our results agree with a pure luminosity evolution at lower redshift and luminosity evolution and density evolution model at redshift z> 2.5.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling

PubMed Central

Wang, Sheng; Sun, Siqi

2017-01-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC. PMID:28884168

Microsurgical robotic system for the deep surgical field: development of a prototype and feasibility studies in animal and cadaveric models.

PubMed

Morita, Akio; Sora, Shigeo; Mitsuishi, Mamoru; Warisawa, Shinichi; Suruman, Katopo; Asai, Daisuke; Arata, Junpei; Baba, Shoichi; Takahashi, Hidechika; Mochizuki, Ryo; Kirino, Takaaki

2005-08-01

To enhance the surgeon's dexterity and maneuverability in the deep surgical field, the authors developed a master-slave microsurgical robotic system. This concept and the results of preliminary experiments are reported in this paper. The system has a master control unit, which conveys motion commands in six degrees of freedom (X, Y, and Z directions; rotation; tip flexion; and grasping) to two arms. The slave manipulator has a hanging base with an additional six degrees of freedom; it holds a motorized operating unit with two manipulators (5 mm in diameter, 18 cm in length). The accuracy of the prototype in both shallow and deep surgical fields was compared with routine freehand microsurgery. Closure of a partial arteriotomy and complete end-to-end anastomosis of the carotid artery (CA) in the deep operative field were performed in 20 Wistar rats. Three routine surgical procedures were also performed in cadavers. The accuracy of pointing with the nondominant hand in the deep surgical field was significantly improved through the use of robotics. The authors successfully closed the partial arteriotomy and completely anastomosed the rat CAs in the deep surgical field. The time needed for stitching was significantly shortened over the course of the first 10 rat experiments. The robotic instruments also moved satisfactorily in cadavers, but the manipulators still need to be smaller to fit into the narrow intracranial space. Computer-controlled surgical manipulation will be an important tool for neurosurgery, and preliminary experiments involving this robotic system demonstrate its promising maneuverability.

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

Deep Learning and Its Applications in Biomedicine.

PubMed

Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

2018-02-01

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

Estimates of deep percolation beneath native vegetation, irrigated fields, and the Amargosa-River Channel, Amargosa Desert, Nye County, Nevada

USGS Publications Warehouse

Stonestrom, David A.; Prudic, David E.; Laczniak, Randell J.; Akstin, Katherine C.; Boyd, Robert A.; Henkelman, Katherine K.

2003-01-01

The presence and approximate rates of deep percolation beneath areas of native vegetation, irrigated fields, and the Amargosa-River channel in the Amargosa Desert of southern Nevada were evaluated using the chloride mass-balance method and inferred downward velocities of chloride and nitrate peaks. Estimates of deep-percolation rates in the Amargosa Desert are needed for the analysis of regional ground-water flow and transport. An understanding of regional flow patterns is important because ground water originating on the Nevada Test Site may pass through the area before discharging from springs at lower elevations in the Amargosa Desert and in Death Valley. Nine boreholes 10 to 16 meters deep were cored nearly continuously using a hollow-stem auger designed for gravelly sediments. Two boreholes were drilled in each of three irrigated fields in the Amargosa-Farms area, two in the Amargosa-River channel, and one in an undisturbed area of native vegetation. Data from previously cored boreholes beneath undisturbed, native vegetation were compared with the new data to further assess deep percolation under current climatic conditions and provide information on spatial variability.The profiles beneath native vegetation were characterized by large amounts of accumulated chloride just below the root zone with almost no further accumulation at greater depths. This pattern is typical of profiles beneath interfluvial areas in arid alluvial basins of the southwestern United States, where salts have been accumulating since the end of the Pleistocene. The profiles beneath irrigated fields and the Amargosa-River channel contained more than twice the volume of water compared to profiles beneath native vegetation, consistent with active deep percolation beneath these sites. Chloride profiles beneath two older fields (cultivated since the 1960’s) as well as the upstream Amargosa-River site were indicative of long-term, quasi-steady deep percolation. Chloride profiles beneath the newest field (cultivated since 1993), the downstream Amargosa-River site, and the edge of an older field were indicative of recently active deep percolation moving previously accumulated salts from the upper profile to greater depths.Results clearly indicate that deep percolation and ground-water recharge occur not only beneath areas of irrigation but also beneath ephemeral stream channels, despite the arid climate and infrequency of runoff. Rates of deep percolation beneath irrigated fields ranged from 0.1 to 0.5 m/yr. Estimated rates of deep percolation beneath the Amargosa-River channel ranged from 0.02 to 0.15 m/yr. Only a few decades are needed for excess irrigation water to move through the unsaturated zone and recharge ground water. Assuming vertical, one-dimensional flow, the estimated time for irrigation-return flow to reach the water table beneath the irrigated fields ranged from about 10 to 70 years. In contrast, infiltration from present-day runoff takes centuries to move through the unsaturated zone and reach the water table. The estimated time for water to reach the water table beneath the channel ranged from 140 to 1000 years. These values represent minimum times, as they do not take lateral flow into account. The estimated fraction of irrigation water becoming deep percolation averaged 8 to 16 percent. Similar fractions of infiltration from ephemeral flow events were estimated to become deep percolation beneath the normally dry Amargosa-River channel. In areas where flood-induced channel migration occurs at sub-centennial frequencies, residence times in the unsaturated zone beneath the Amargosa channel could be longer. Estimates of deep percolation presented herein provide a basis for evaluating the importance of recharge from irrigation and channel infiltration in models of ground-water flow from the Nevada Test Site.

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

PubMed

Hu, T H; Wan, L; Liu, T A; Wang, M W; Chen, T; Wang, Y H

2017-12-01

Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences. Based on these advantages of deep learning in image recognition, we combine it with the research of bone age assessment to provide basic datum for constructing a forensic automatic system of bone age assessment. This paper reviews the basic concept and network architectures of deep learning, and describes its recent research progress on image recognition in different research fields at home and abroad, and explores its advantages and application prospects in bone age assessment. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Albedo Neutron Dosimetry in a Deep Geological Disposal Repository for High-Level Nuclear Waste.

PubMed

Pang, Bo; Becker, Frank

2017-04-28

Albedo neutron dosemeter is the German official personal neutron dosemeter in mixed radiation fields where neutrons contribute to personal dose. In deep geological repositories for high-level nuclear waste, where neutrons can dominate the radiation field, it is of interest to investigate the performance of albedo neutron dosemeter in such facilities. In this study, the deep geological repository is represented by a shielding cask loaded with spent nuclear fuel placed inside a rock salt emplacement drift. Due to the backscattering of neutrons in the drift, issues concerning calibration of the dosemeter arise. Field-specific calibration of the albedo neutron dosemeter was hence performed with Monte Carlo simulations. In order to assess the applicability of the albedo neutron dosemeter in a deep geological repository over a long time scale, spent nuclear fuel with different ages of 50, 100 and 500 years were investigated. It was found out, that the neutron radiation field in a deep geological repository can be assigned to the application area 'N1' of the albedo neutron dosemeter, which is typical in reactors and accelerators with heavy shielding. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Primary experimental study on safety of deep brain stimulation in RF electromagnetic field.

PubMed

Jun, Xu; Luming, Li; Hongwei, Hao

2009-01-01

With the rapid growth of clinical application of Deep Brain Stimulation, its safety and functional concern in the electromagnetic field, another pollution becoming much more serious, has become more and more significant. Meanwhile, the measuring standards on Electromagnetic Compatibility (EMC) for DBS are still incomplete. Particularly, the knowledge of the electromagnetic field induced signals on the implanted lead is ignorant while some informal reports some side effects. This paper briefly surmised the status of EMC standards on implantable medical devices. Based on the EMC experiments of DBS device we developed, two experiments for measuring the induced voltage of the deep brain stimulator in RF electromagnetic field were reported. The measured data showed that the induced voltage in some frequency was prominent, for example over 2V. As a primary research, we think these results would be significant to cause researcher to pay more attention to the EMC safety problem and biological effects of the induced voltage in deep brain stimulation and other implantable devices.

Information System through ANIS at CeSAM

NASA Astrophysics Data System (ADS)

Moreau, C.; Agneray, F.; Gimenez, S.

2015-09-01

ANIS (AstroNomical Information System) is a web generic tool developed at CeSAM to facilitate and standardize the implementation of astronomical data of various kinds through private and/or public dedicated Information Systems. The architecture of ANIS is composed of a database server which contains the project data, a web user interface template which provides high level services (search, extract and display imaging and spectroscopic data using a combination of criteria, an object list, a sql query module or a cone search interfaces), a framework composed of several packages, and a metadata database managed by a web administration entity. The process to implement a new ANIS instance at CeSAM is easy and fast : the scientific project has to submit data or a data secure access, the CeSAM team installs the new instance (web interface template and the metadata database), and the project administrator can configure the instance with the web ANIS-administration entity. Currently, the CeSAM offers through ANIS a web access to VO compliant Information Systems for different projects (HeDaM, HST-COSMOS, CFHTLS-ZPhots, ExoDAT,...).

Current oscillations in semi-insulating GaAs associated with field-enhanced capture of electrons by the major deep donor EL2

NASA Technical Reports Server (NTRS)

Kaminska, M.; Parsey, J. M.; Lagowski, J.; Gatos, H. C.

1982-01-01

Current oscillations thermally activated by the release of electrons from deep levels in undoped semiinsulating GaAs were observed for the first time. They were attributed to electric field-enhanced capture of electrons by the dominant deep donor EL2 (antisite AsGa defect). This enhanced capture is due to the configurational energy barrier of EL2, which is readily penetrated by hot electrons.

Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice

PubMed Central

Zhang, Qian; Castellanos Rubio, Idoia; del Pino, Pablo

2017-01-01

Establishing how neurocircuit activation causes particular behaviors requires modulating the activity of specific neurons. Here, we demonstrate that magnetothermal genetic stimulation provides tetherless deep brain activation sufficient to evoke motor behavior in awake mice. The approach uses alternating magnetic fields to heat superparamagnetic nanoparticles on the neuronal membrane. Neurons, heat-sensitized by expressing TRPV1 are activated with magnetic field application. Magnetothermal genetic stimulation in the motor cortex evoked ambulation, deep brain stimulation in the striatum caused rotation around the body-axis, and stimulation near the ridge between ventral and dorsal striatum caused freezing-of-gait. The duration of the behavior correlated tightly with field application. This approach provides genetically and spatially targetable, repeatable and temporarily precise activation of deep-brain circuits without the need for surgical implantation of any device. PMID:28826470

REVIEWS OF TOPICAL PROBLEMS: Sky surveys and deep fields of ground-based and space telescopes

NASA Astrophysics Data System (ADS)

Reshetnikov, Vladimir P.

2005-11-01

Selected results obtained in major observational sky surveys (DSS, 2MASS, 2dF, SDSS) and deep field observations (HDF, GOODS, UHDF, etc.) are reviewed. Modern surveys provide information on the characteristics and space distribution of millions of galaxies. Deep fields allow one to study galaxies at the stage of formation and to trace their evolution over billions of years. The wealth of observational data is altering the face of modern astronomy: the formulation of problems and their solutions are changing and all the previous knowledge, from planetary studies in the solar system to the most distant galaxies and quasars, is being revised.

Accurate segmentation of lung fields on chest radiographs using deep convolutional networks

NASA Astrophysics Data System (ADS)

Arbabshirani, Mohammad R.; Dallal, Ahmed H.; Agarwal, Chirag; Patel, Aalpan; Moore, Gregory

2017-02-01

Accurate segmentation of lung fields on chest radiographs is the primary step for computer-aided detection of various conditions such as lung cancer and tuberculosis. The size, shape and texture of lung fields are key parameters for chest X-ray (CXR) based lung disease diagnosis in which the lung field segmentation is a significant primary step. Although many methods have been proposed for this problem, lung field segmentation remains as a challenge. In recent years, deep learning has shown state of the art performance in many visual tasks such as object detection, image classification and semantic image segmentation. In this study, we propose a deep convolutional neural network (CNN) framework for segmentation of lung fields. The algorithm was developed and tested on 167 clinical posterior-anterior (PA) CXR images collected retrospectively from picture archiving and communication system (PACS) of Geisinger Health System. The proposed multi-scale network is composed of five convolutional and two fully connected layers. The framework achieved IOU (intersection over union) of 0.96 on the testing dataset as compared to manual segmentation. The suggested framework outperforms state of the art registration-based segmentation by a significant margin. To our knowledge, this is the first deep learning based study of lung field segmentation on CXR images developed on a heterogeneous clinical dataset. The results suggest that convolutional neural networks could be employed reliably for lung field segmentation.

Deep-turbulence wavefront sensing using digital holography in the on-axis phase shifting recording geometry

NASA Astrophysics Data System (ADS)

Thornton, Douglas E.; Spencer, Mark F.; Perram, Glen P.

2017-09-01

The effects of deep turbulence in long-range imaging applications presents unique challenges to properly measure and correct for aberrations incurred along the atmospheric path. In practice, digital holography can detect the path-integrated wavefront distortions caused by deep turbulence, and di erent recording geometries offer different benefits depending on the application of interest. Previous studies have evaluated the performance of the off-axis image and pupil plane recording geometries for deep-turbulence sensing. This study models digital holography in the on-axis phase shifting recording geometry using wave optics simulations. In particular, the analysis models spherical-wave propagation through varying deep-turbulence conditions to estimate the complex optical field, and performance is evaluated by calculating the field-estimated Strehl ratio and RMS wavefront error. Altogether, the results show that digital holography in the on-axis phase shifting recording geometry is an effective wavefront-sensing method in the presence of deep turbulence.

A comparative study of approaches to compute the field distribution of deep brain stimulation in the Hemiparkinson rat model.

PubMed

Bohme, Andrea; van Rienen, Ursula

2016-08-01

Computational modeling of the stimulating field distribution during Deep Brain Stimulation provides an opportunity to advance our knowledge of this neurosurgical therapy for Parkinson's disease. There exist several approaches to model the target region for Deep Brain Stimulation in Hemi-parkinson Rats with volume conductor models. We have described and compared the normalized mapping approach as well as the modeling with three-dimensional structures, which include curvilinear coordinates to assure an anatomically realistic conductivity tensor orientation.

The Chandra Deep Wide-Field Survey: Completing the new generation of Chandra extragalactic surveys

NASA Astrophysics Data System (ADS)

Hickox, Ryan

2016-09-01

Chandra X-ray surveys have revolutionized our view of the growth of black holes across cosmic time. Recently, fundamental questions have emerged about the connection of AGN to their host large scale structures that clearly demand a wide, deep survey over a large area, comparable to the recent extensive Chandra surveys in smaller fields. We propose the Chandra Deep Wide-Field Survey (CDWFS) covering the central 6 sq. deg in the Bootes field, totaling 1.025 Ms (building on 550 ks from the HRC GTO program). CDWFS will efficiently probe a large cosmic volume, allowing us to carry out accurate new investigations of the connections between black holes and their large-scale structures, and will complete the next generation surveys that comprise a key part of Chandra's legacy.

Deep Seawater Intrusion Enhanced by Geothermal Through Deep Faults in Xinzhou Geothermal Field in Guangdong, China

NASA Astrophysics Data System (ADS)

Lu, G.; Ou, H.; Hu, B. X.; Wang, X.

2017-12-01

This study investigates abnormal sea water intrusion from deep depth, riding an inland-ward deep groundwater flow, which is enhanced by deep faults and geothermal processes. The study site Xinzhou geothermal field is 20 km from the coast line. It is in southern China's Guangdong coast, a part of China's long coastal geothermal belt. The geothermal water is salty, having fueled an speculation that it was ancient sea water retained. However, the perpetual "pumping" of the self-flowing outflow of geothermal waters might alter the deep underground flow to favor large-scale or long distant sea water intrusion. We studied geochemical characteristics of the geothermal water and found it as a mixture of the sea water with rain water or pore water, with no indication of dilution involved. And we conducted numerical studies of the buoyancy-driven geothermal flow in the deep ground and find that deep down in thousand meters there is favorable hydraulic gradient favoring inland-ward groundwater flow, allowing seawater intrude inland for an unusually long tens of kilometers in a granitic groundwater flow system. This work formed the first in understanding geo-environment for deep ground water flow.

ARC-2012-ACD12-0020-001

NASA Image and Video Library

2012-02-02

Stein_Sun: Visualization of the complex magnetic field produced as magnetic flux rises toward the Sun¹s surface from the deep convection zone. The image shows a snapshot of how the magnetic field has evolved two days from the time uniform, untwisted, horizontal magnetic field started to be advected by inflows at the bottom (20 megameters deep). Axes are in megameters, and the color scale shows the log of the magnetic field strength. Credit: Robert Stein, Michigan State University; Tim Sandstrom, NASA/Ames

Adding the missing piece: Spitzer imaging of the HSC-Deep/PFS fields

NASA Astrophysics Data System (ADS)

Sajina, Anna; Bezanson, Rachel; Capak, Peter; Egami, Eiichi; Fan, Xiaohui; Farrah, Duncan; Greene, Jenny; Goulding, Andy; Lacy, Mark; Lin, Yen-Ting; Liu, Xin; Marchesini, Danilo; Moutard, Thibaud; Ono, Yoshiaki; Ouchi, Masami; Sawicki, Marcin; Strauss, Michael; Surace, Jason; Whitaker, Katherine

2018-05-01

We propose to observe a total of 7sq.deg. to complete the Spitzer-IRAC coverage of the HSC-Deep survey fields. These fields are the sites of the PrimeFocusSpectrograph (PFS) galaxy evolution survey which will provide spectra of wide wavelength range and resolution for almost all M* galaxies at z 0.7-1.7, and extend out to z 7 for targeted samples. Our fields already have deep broadband and narrowband photometry in 12 bands spanning from u through K and a wealth of other ancillary data. We propose completing the matching depth IRAC observations in the extended COSMOS, ELAIS-N1 and Deep2-3 fields. By complementing existing Spitzer coverage, this program will lead to an unprecedended in spectro-photometric coverage dataset across a total of 15 sq.deg. This dataset will have significant legacy value as it samples a large enough cosmic volume to be representative of the full range of environments, but also doing so with sufficient information content per galaxy to confidently derive stellar population characteristics. This enables detailed studies of the growth and quenching of galaxies and their supermassive black holes in the context of a galaxy's local and large scale environment.

Deep Zonal Flow and Time Variation of Jupiter’s Magnetic Field

NASA Astrophysics Data System (ADS)

Cao, Hao; Stevenson, David J.

2017-10-01

All four giant planets in the Solar System feature zonal flows on the order of 100 m/s in the cloud deck, and large-scale intrinsic magnetic fields on the order of 1 Gauss near the surface. The vertical structure of the zonal flows remains obscure. The end-member scenarios are shallow flows confined in the radiative atmosphere and deep flows throughout the entire planet. The electrical conductivity increases rapidly yet smoothly as a function of depth inside Jupiter and Saturn. Deep zonal flows will advect the non-axisymmetric component of the magnetic field, at depth with even modest electrical conductivity, and create time variations in the magnetic field.The observed time variations of the geomagnetic field has been used to derive surface flows of the Earth’s outer core. The same principle applies to Jupiter, however, the connection between the time variation of the magnetic field (dB/dt) and deep zonal flow (Uphi) at Jupiter is not well understood due to strong radial variation of electrical conductivity. Here we perform a quantitative analysis of the connection between dB/dt and Uphi for Jupiter adopting realistic interior electrical conductivity profile, taking the likely presence of alkali metals into account. This provides a tool to translate expected measurement of the time variation of Jupiter’s magnetic field to deep zonal flows. We show that the current upper limit on the dipole drift rate of Jupiter (3 degrees per 20 years) is compatible with 10 m/s zonal flows with < 500 km vertical scale height below 0.972 Rj. We further demonstrate that fast drift of resolved magnetic features (e.g. magnetic spots) at Jupiter is a possibility.

VizieR Online Data Catalog: Galaxy samples rest-frame ultraviolet structure (Bond+, 2014)

NASA Astrophysics Data System (ADS)

Bond, N. A.; Gardner, J. P.; de Mello, D. F.; Teplitz, H. I.; Rafelski, M.; Koekemoer, A. M.; Coe, D.; Grogin, N.; Gawiser, E.; Ravindranath, S.; Scarlata, C.

2017-03-01

In this paper, we use data taken as part of a program (GO 11563, PI: Teplitz) to obtain UV imaging of the Hubble Ultra Deep Field (hereafter UVUDF) and study intermediate-redshift galaxy structure in the F336W, F275W, and F225W filters, complementing existing optical and near-IR measurements from the 2012 Hubble Ultra Deep Field (HUDF12; Ellis et al. 2013ApJ...763L...7E) survey. We use AB magnitudes throughout and assume a concordance cosmology with H0=71 km/s/Mpc, ωm=0.27, and ωλ=0.73 (Spergel et al. 2007ApJS..170..377S). The UVUDF data and the optical Hubble Ultradeep Field (UDF; Beckwith et al. 2006, J/AJ/132/1729) are both contained within a single deep field in the Great Observatories Origins Deep Survey South. The new UVUDF data include imaging in three filters (F336W, F275W, and F225W), obtained in 10 visits, for a total of 30 orbits per filter. In addition, from the UDF, we make use of deep drizzled images taken in the observed optical with the F435W, F606W, and F775W filters. (1 data file).

DC3 Data and Information Page

Atmospheric Science Data Center

2015-03-16

Deep Convective Clouds and Chemistry (DC3) Data and Information The Deep Convective Clouds and Chemistry ( DC3 ) field campaign is investigating the impact of deep, ... processes, on upper tropospheric (UT) composition and chemistry. The primary science objectives are:   To quantify and ...

Deep brain stimulation as a functional scalpel.

PubMed

Broggi, G; Franzini, A; Tringali, G; Ferroli, P; Marras, C; Romito, L; Maccagnano, E

2006-01-01

Since 1995, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan (INNCB,) 401 deep brain electrodes were implanted to treat several drug-resistant neurological syndromes (Fig. 1). More than 200 patients are still available for follow-up and therapeutical considerations. In this paper our experience is reviewed and pioneered fields are highlighted. The reported series of patients extends the use of deep brain stimulation beyond the field of Parkinson's disease to new fields such as cluster headache, disruptive behaviour, SUNCt, epilepsy and tardive dystonia. The low complication rate, the reversibility of the procedure and the available image guided surgery tools will further increase the therapeutic applications of DBS. New therapeutical applications are expected for this functional scalpel.

A warm Spitzer survey of the LSST/DES 'Deep drilling' fields

NASA Astrophysics Data System (ADS)

Lacy, Mark; Farrah, Duncan; Brandt, Niel; Sako, Masao; Richards, Gordon; Norris, Ray; Ridgway, Susan; Afonso, Jose; Brunner, Robert; Clements, Dave; Cooray, Asantha; Covone, Giovanni; D'Andrea, Chris; Dickinson, Mark; Ferguson, Harry; Frieman, Joshua; Gupta, Ravi; Hatziminaoglou, Evanthia; Jarvis, Matt; Kimball, Amy; Lubin, Lori; Mao, Minnie; Marchetti, Lucia; Mauduit, Jean-Christophe; Mei, Simona; Newman, Jeffrey; Nichol, Robert; Oliver, Seb; Perez-Fournon, Ismael; Pierre, Marguerite; Rottgering, Huub; Seymour, Nick; Smail, Ian; Surace, Jason; Thorman, Paul; Vaccari, Mattia; Verma, Aprajita; Wilson, Gillian; Wood-Vasey, Michael; Cane, Rachel; Wechsler, Risa; Martini, Paul; Evrard, August; McMahon, Richard; Borne, Kirk; Capozzi, Diego; Huang, Jiashang; Lagos, Claudia; Lidman, Chris; Maraston, Claudia; Pforr, Janine; Sajina, Anna; Somerville, Rachel; Strauss, Michael; Jones, Kristen; Barkhouse, Wayne; Cooper, Michael; Ballantyne, David; Jagannathan, Preshanth; Murphy, Eric; Pradoni, Isabella; Suntzeff, Nicholas; Covarrubias, Ricardo; Spitler, Lee

2014-12-01

We propose a warm Spitzer survey to microJy depth of the four predefined Deep Drilling Fields (DDFs) for the Large Synoptic Survey Telescope (LSST) (three of which are also deep drilling fields for the Dark Energy Survey (DES)). Imaging these fields with warm Spitzer is a key component of the overall success of these projects, that address the 'Physics of the Universe' theme of the Astro2010 decadal survey. With deep, accurate, near-infrared photometry from Spitzer in the DDFs, we will generate photometric redshift distributions to apply to the surveys as a whole. The DDFs are also the areas where the supernova searches of DES and LSST are concentrated, and deep Spitzer data is essential to obtain photometric redshifts, stellar masses and constraints on ages and metallicities for the >10000 supernova host galaxies these surveys will find. This 'DEEPDRILL' survey will also address the 'Cosmic Dawn' goal of Astro2010 through being deep enough to find all the >10^11 solar mass galaxies within the survey area out to z~6. DEEPDRILL will complete the final 24.4 square degrees of imaging in the DDFs, which, when added to the 14 square degrees already imaged to this depth, will map a volume of 1-Gpc^3 at z>2. It will find ~100 > 10^11 solar mass galaxies at z~5 and ~40 protoclusters at z>2, providing targets for JWST that can be found in no other way. The Spitzer data, in conjunction with the multiwavelength surveys in these fields, ranging from X-ray through far-infrared and cm-radio, will comprise a unique legacy dataset for studies of galaxy evolution.

FIELD TEST OF AIR SPARGING COUPLED WITH SOIL VAPOR EXTRACTION

EPA Science Inventory

A controlled field study was designed and conducted to assess the performance of air sparging for remediation of petroleum fuel and solvent contamination in a shallow (3-m deep) groundwater aquifer. Sparging was performed in an insolation test cell (5 m by 3 m by 8-m deep). A soi...

Data to Support Development of Geologic Framework Models for the Deep Borehole Field Test

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perry, Frank Vinton; Kelley, Richard E.

This report summarizes work conducted in FY2017 to identify and document publically available data for developing a Geologic Framework Model (GFM) for the Deep Borehole Field Test (DBFT). Data was collected for all four of the sites being considered in 2017 for a DBFT site.

Miniature ingestible telemeter devices to measure deep-body temperature

NASA Technical Reports Server (NTRS)

Pope, J. M.; Fryer, T. B. (Inventor)

1976-01-01

A telemetry device comprised of a pill-size ingestible transmitter developed to obtain deep body temperature measurements of a human is described. The device has particular utility in the medical field where deep body temperatures provide an indication of general health.

Making Data Mobile: The Hubble Deep Field Academy iPad app

NASA Astrophysics Data System (ADS)

Eisenhamer, Bonnie; Cordes, K.; Davis, S.; Eisenhamer, J.

2013-01-01

Many school districts are purchasing iPads for educators and students to use as learning tools in the classroom. Educators often prefer these devices to desktop and laptop computers because they offer portability and an intuitive design, while having a larger screen size when compared to smart phones. As a result, we began investigating the potential of adapting online activities for use on Apple’s iPad to enhance the dissemination and usage of these activities in instructional settings while continuing to meet educators’ needs. As a pilot effort, we are developing an iPad app for the “Hubble Deep Field Academy” - an activity that is currently available online and commonly used by middle school educators. The Hubble Deep Field Academy app features the HDF-North image while centering on the theme of how scientists use light to explore and study the universe. It also includes features such as embedded links to vocabulary, images and videos, teacher background materials, and readings about Hubble’s other deep field surveys. It is our goal is to impact students’ engagement in STEM-related activities, while enhancing educators’ usage of NASA data via new and innovative mediums. We also hope to develop and share lessons learned with the E/PO community that can be used to support similar projects. We plan to test the Hubble Deep Field Academy app during the school year to determine if this new activity format is beneficial to the education community.

Comparison of the induced fields using different coil configurations during deep transcranial magnetic stimulation.

PubMed

Lu, Mai; Ueno, Shoogo

2017-01-01

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) plays a role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disorders. However, electric field distributions induced in the brain by deep transcranial magnetic stimulation (dTMS) are still unknown. In this paper, the double cone coil, H-coil and Halo-circular assembly (HCA) coil which have been proposed for dTMS have been numerically designed. The distributions of magnetic flux density, induced electric field in an anatomically based realistic head model by applying the dTMS coils were numerically calculated by the impedance method. Results were compared with that of standard figure-of-eight (Fo8) coil. Simulation results show that double cone, H- and HCA coils have significantly deep field penetration compared to the conventional Fo8 coil, at the expense of induced higher and wider spread electrical fields in superficial cortical regions. Double cone and HCA coils have better ability to stimulate deep brain subregions compared to that of the H-coil. In the mean time, both double cone and HCA coils increase risk for optical nerve excitation. Our results suggest although the dTMS coils offer new tool with potential for both research and clinical applications for psychiatric and neurological disorders associated with dysfunctions of deep brain regions, the selection of the most suitable coil settings for a specific clinical application should be based on a balanced evaluation between stimulation depth and focality.

Unfolding the atmospheric and deep internal flows on Jupiter and Saturn using the Juno and Cassini gravity measurements

NASA Astrophysics Data System (ADS)

Galanti, Eli; Kaspi, Yohai

2016-10-01

In light of the first orbits of Juno at Jupiter, we discuss the Juno gravity experiment and possible initial results. Relating the flow on Jupiter and Saturn to perturbations in their density field is key to the analysis of the gravity measurements expected from both the Juno (Jupiter) and Cassini (Saturn) spacecraft during 2016-17. Both missions will provide latitude-dependent gravity fields, which in principle could be inverted to calculate the vertical structure of the observed cloud-level zonal flow on these planets. Current observations for the flow on these planets exists only at the cloud-level (0.1-1 bar). The observed cloud-level wind might be confined to the upper layers, or be a manifestation of deep cylindrical flows. Moreover, it is possible that in the case where the observed wind is superficial, there exists deep interior flow that is completely decoupled from the observed atmospheric flow.In this talk, we present a new adjoint based inverse model for inversion of the gravity measurements into flow fields. The model is constructed to be as general as possible, allowing for both cloud-level wind extending inward, and a decoupled deep flow that is constructed to produce cylindrical structures with variable width and magnitude, or can even be set to be completely general. The deep flow is also set to decay when approaching the upper levels so it has no manifestation there. The two sources of flow are then combined to a total flow field that is related to the density anomalies and gravity moments via a dynamical model. Given the measured gravitational moments from Jupiter and Saturn, the dynamical model, together with the adjoint inverse model are used for optimizing the control parameters and by this unfolding the deep and surface flows. Several scenarios are examined, including cases in which the surface wind and the deep flow have comparable effects on the gravity field, cases in which the deep flow is dominating over the surface wind, and an extreme case where the deep flow can have an unconstrained pattern. The method enables also the calculation of the uncertainties associated with each solution. We discuss the physical limitations to the method in view of the measurement uncertainties.

Hubble Space Telescope Deep Field Lesson Package. Teacher's Guide, Grades 6-8. Amazing Space: Education On-Line from the Hubble Space Telescope.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Washington, DC.

This lesson guide accompanies the Hubble Deep Field set of 10 lithographs and introduces 4 astronomy lesson plans for middle school students. Lessons include: (1) "How Many Objects Are There?"; (2) "Classifying and Identifying"; (3) "Estimating Distances in Space"; and (4) "Review and Assessment." Appendices…

Deep-Earth reactor: nuclear fission, helium, and the geomagnetic field.

PubMed

Hollenbach, D F; Herndon, J M

2001-09-25

Geomagnetic field reversals and changes in intensity are understandable from an energy standpoint as natural consequences of intermittent and/or variable nuclear fission chain reactions deep within the Earth. Moreover, deep-Earth production of helium, having (3)He/(4)He ratios within the range observed from deep-mantle sources, is demonstrated to be a consequence of nuclear fission. Numerical simulations of a planetary-scale geo-reactor were made by using the SCALE sequence of codes. The results clearly demonstrate that such a geo-reactor (i) would function as a fast-neutron fuel breeder reactor; (ii) could, under appropriate conditions, operate over the entire period of geologic time; and (iii) would function in such a manner as to yield variable and/or intermittent output power.

Finding the First Galaxies

NASA Technical Reports Server (NTRS)

Gardner, Jonathan P.

2009-01-01

Astronomers study distant galaxies by taking long exposures in deep survey fields. They choose fields that are empty of known sources, so that they are statistically representative of the Universe as a whole. Astronomers can compare the distribution of the detected galaxies in brightness, color, morphology and redshift to theoretical models, in order to puzzle out the processes of galaxy evolution. In 2004, the Hubble Space Telescope was pointed at a small, deep-survey field in the southern constellation Fornax for more than 500 hours of exposure time. The resulting Hubble Ultra-Deep Field could see the faintest and most distant galaxies that the telescope is capable of viewing. These galaxies emitted their light less than 1 billion years after the Big Bang. From the Ultra Deep Field and other galaxy surveys, astronomers have built up a history of star formation in the universe. the peak occurred about7 billion years ago, about half of the age of the current universe, then the number of stars that were forming was about 15 time the rate today. Going backward in time to when the very first starts and galaxies formed, the average star-formation rate should drop to zero. but when looking at the most distant galaxies in the Ultra Deep field, the star formation rate is still higher than it is today. The faintest galaxies seen by Hubble are not the first galaxies that formed in the early universe. To detect these galaxies NASA is planning the James Webb Space Telescope for launch in 2013. Webb will have a 6.5-meter diameter primary mirror, much bigger than Hubble's 2.4-meter primary, and will be optimized for infrared observations to see the highly redshifted galaxies.

The GISMO two-millimeter deep field in GOODS-N

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staguhn, Johannes G.; Kovács, Attila; Arendt, Richard G.

2014-07-20

We present deep continuum observations using the GISMO camera at a wavelength of 2 mm centered on the Hubble Deep Field in the GOODS-N field. These are the first deep field observations ever obtained at this wavelength. The 1σ sensitivity in the innermost ∼4' of the 7' diameter map is ∼135 μJy beam{sup –1}, a factor of three higher in flux/beam sensitivity than the deepest available SCUBA 850 μm observations, and almost a factor of four higher in flux/beam sensitivity than the combined MAMBO/AzTEC 1.2 mm observations of this region. Our source extraction algorithm identifies 12 sources directly, and anothermore » 3 through correlation with known sources at 1.2 mm and 850 μm. Five of the directly detected GISMO sources have counterparts in the MAMBO/AzTEC catalog, and four of those also have SCUBA counterparts. HDF850.1, one of the first blank-field detected submillimeter galaxies, is now detected at 2 mm. The median redshift of all sources with counterparts of known redshifts is z-tilde =2.91±0.94. Statistically, the detections are most likely real for five of the seven 2 mm sources without shorter wavelength counterparts, while the probability for none of them being real is negligible.« less

Development of the EM tomography system by the vertical electromagnetic profiling (VEMP) method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miura, Y.; Osato, K.; Takasugi, S.

1995-12-31

As a part of the {open_quotes}Deep-Seated Geothermal Resources Survey{close_quotes} project being undertaken by the NEDO, the Vertical ElectroMagnetic Profiling (VEMP) method is being developed to accurately obtain deep resistivity structure. The VEMP method acquires multi-frequency three-component magnetic field data in an open hole well using controlled sources (loop sources or grounded-wire sources) emitted at the surface. Numerical simulation using EM3D demonstrated that phase data of the VEMP method is very sensitive to resistivity structure and the phase data will also indicate presence of deep anomalies. Forward modelling was also used to determine required transmitter moments for various grounded-wire and loopmore » sources for a field test using the WD-1 well in the Kakkonda geothermal area. Field logging of the well was carried out in May 1994 and the processed field data matches well the simulated data.« less

Computational analysis of transcranial magnetic stimulation in the presence of deep brain stimulation probes

NASA Astrophysics Data System (ADS)

Syeda, F.; Holloway, K.; El-Gendy, A. A.; Hadimani, R. L.

2017-05-01

Transcranial Magnetic Stimulation is an emerging non-invasive treatment for depression, Parkinson's disease, and a variety of other neurological disorders. Many Parkinson's patients receive the treatment known as Deep Brain Stimulation, but often require additional therapy for speech and swallowing impairment. Transcranial Magnetic Stimulation has been explored as a possible treatment by stimulating the mouth motor area of the brain. We have calculated induced electric field, magnetic field, and temperature distributions in the brain using finite element analysis and anatomically realistic heterogeneous head models fitted with Deep Brain Stimulation leads. A Figure of 8 coil, current of 5000 A, and frequency of 2.5 kHz are used as simulation parameters. Results suggest that Deep Brain Stimulation leads cause surrounding tissues to experience slightly increased E-field (Δ Emax =30 V/m), but not exceeding the nominal values induced in brain tissue by Transcranial Magnetic Stimulation without leads (215 V/m). The maximum temperature in the brain tissues surrounding leads did not change significantly from the normal human body temperature of 37 °C. Therefore, we ascertain that Transcranial Magnetic Stimulation in the mouth motor area may stimulate brain tissue surrounding Deep Brain Stimulation leads, but will not cause tissue damage.

Deep Borehole Field Test Requirements and Controlled Assumptions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardin, Ernest

2015-07-01

This document presents design requirements and controlled assumptions intended for use in the engineering development and testing of: 1) prototype packages for radioactive waste disposal in deep boreholes; 2) a waste package surface handling system; and 3) a subsurface system for emplacing and retrieving packages in deep boreholes. Engineering development and testing is being performed as part of the Deep Borehole Field Test (DBFT; SNL 2014a). This document presents parallel sets of requirements for a waste disposal system and for the DBFT, showing the close relationship. In addition to design, it will also inform planning for drilling, construction, and scientificmore » characterization activities for the DBFT. The information presented here follows typical preparations for engineering design. It includes functional and operating requirements for handling and emplacement/retrieval equipment, waste package design and emplacement requirements, borehole construction requirements, sealing requirements, and performance criteria. Assumptions are included where they could impact engineering design. Design solutions are avoided in the requirements discussion. Deep Borehole Field Test Requirements and Controlled Assumptions July 21, 2015 iv ACKNOWLEDGEMENTS This set of requirements and assumptions has benefited greatly from reviews by Gordon Appel, Geoff Freeze, Kris Kuhlman, Bob MacKinnon, Steve Pye, David Sassani, Dave Sevougian, and Jiann Su.« less

Model United Nations and Deep Learning: Theoretical and Professional Learning

ERIC Educational Resources Information Center

Engel, Susan; Pallas, Josh; Lambert, Sarah

2017-01-01

This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…

Evaluation of Resuspension from Propeller Wash in DoD Harbors

DTIC Science & Technology

2016-05-01

RESUSPENSION CHARACTERIZATION ............................................................. 11 5.3 DEEP -DRAFT RESUSPENSION STUDY IN PEARL HARBOR...RESUSPENSION FROM A DEEP -DRAFT VESSEL .............................................. 21 6.4.1 Field Observations Using ADCP...event resulted in validation of the FANS model for prediction of sediment resuspension by a deep draft vessel. While working on the resuspension

Comment on 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study'.

PubMed

Valdes, Gilmer; Interian, Yannet

2018-03-15

The application of machine learning (ML) presents tremendous opportunities for the field of oncology, thus we read 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study' with great interest. In this article, the authors used state of the art techniques: a pre-trained convolutional neural network (VGG-16 CNN), transfer learning, data augmentation, drop out and early stopping, all of which are directly responsible for the success and the excitement that these algorithms have created in other fields. We believe that the use of these techniques can offer tremendous opportunities in the field of Medical Physics and as such we would like to praise the authors for their pioneering application to the field of Radiation Oncology. That being said, given that the field of Medical Physics has unique characteristics that differentiate us from those fields where these techniques have been applied successfully, we would like to raise some points for future discussion and follow up studies that could help the community understand the limitations and nuances of deep learning techniques.

Comparison of the induced fields using different coil configurations during deep transcranial magnetic stimulation

PubMed Central

Ueno, Shoogo

2017-01-01

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) plays a role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disorders. However, electric field distributions induced in the brain by deep transcranial magnetic stimulation (dTMS) are still unknown. In this paper, the double cone coil, H-coil and Halo-circular assembly (HCA) coil which have been proposed for dTMS have been numerically designed. The distributions of magnetic flux density, induced electric field in an anatomically based realistic head model by applying the dTMS coils were numerically calculated by the impedance method. Results were compared with that of standard figure-of-eight (Fo8) coil. Simulation results show that double cone, H- and HCA coils have significantly deep field penetration compared to the conventional Fo8 coil, at the expense of induced higher and wider spread electrical fields in superficial cortical regions. Double cone and HCA coils have better ability to stimulate deep brain subregions compared to that of the H-coil. In the mean time, both double cone and HCA coils increase risk for optical nerve excitation. Our results suggest although the dTMS coils offer new tool with potential for both research and clinical applications for psychiatric and neurological disorders associated with dysfunctions of deep brain regions, the selection of the most suitable coil settings for a specific clinical application should be based on a balanced evaluation between stimulation depth and focality. PMID:28586349

Near Infrared Imaging of the Hubble Deep Field with Keck Telescope

NASA Technical Reports Server (NTRS)

Hogg, David W.; Neugebauer, G.; Armus, Lee; Matthews, K.; Pahre, Michael A.; Soifer, B. T.; Weinberger, A. J.

1997-01-01

Two deep K-band (2.2 micrometer) images, with point-source detection limits of K=25.2 mag (one sigma), taken with the Keck Telescope in subfields of the Hubble Deep Field, are presented and analyzed. A sample of objects to K=24 mag is constructed and V(sub 606)- I(sub 814) and I(sub 814)-K colors are measured. By stacking visually selected objects, mean I(sub 814)-K colors can be measured to very faint levels, the mean I(sub 814)-K color is constant with apparent magnitude down to V(sub 606)=28 mag.

VizieR Online Data Catalog: Redshifts of 65 CANDELS supernovae (Rodney+, 2014)

NASA Astrophysics Data System (ADS)

Rodney, S. A.; Riess, A. G.; Strolger, L.-G.; Dahlen, T.; Graur, O.; Casertano, S.; Dickinson, M. E.; Ferguson, H. C.; Garnavich, P.; Hayden, B.; Jha, S. W.; Jones, D. O.; Kirshner, R. P.; Koekemoer, A. M.; McCully, C.; Mobasher, B.; Patel, B.; Weiner, B. J.; Cenko, S. B.; Clubb, K. I.; Cooper, M.; Filippenko, A. V.; Frederiksen, T. F.; Hjorth, J.; Leibundgut, B.; Matheson, T.; Nayyeri, H.; Penner, K.; Trump, J.; Silverman, J. M.; U, V.; Azalee Bostroem, K.; Challis, P.; Rajan, A.; Wolff, S.; Faber, S. M.; Grogin, N. A.; Kocevski, D.

2015-01-01

In this paper we present a measurement of the Type Ia supernova explosion rate as a function of redshift (SNR(z)) from a sample of 65 supernovae discovered in the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) supernova program. This supernova survey is a joint operation of two Hubble Space Telescope (HST) Multi-Cycle Treasury (MCT) programs: CANDELS (PIs: Faber and Ferguson; Grogin et al., 2011ApJS..197...35G; Koekemoer et al., 2011ApJS..197...36K), and the Cluster Lensing and Supernovae search with Hubble (CLASH; PI: Postman; Postman et al. 2012, cat. J/ApJS/199/25). The supernova discovery and follow-up for both programs were allocated to the HST MCT supernova program (PI: Riess). The results presented here are based on the full five fields and ~0.25deg2 of the CANDELS program, observed from 2010 to 2013. A companion paper presents the SN Ia rates from the CLASH sample (Graur et al., 2014ApJ...783...28G). A composite analysis that combines the CANDELS+CLASH supernova sample and revisits past HST surveys will be presented in a future paper. The three-year CANDELS program was designed to probe galaxy evolution out to z~8 with deep infrared and optical imaging of five well-studied extragalactic fields: GOODS-S, GOODS-N (the Great Observatories Origins Deep Survey South and North; Giavalisco et al. 2004, cat. II/261), COSMOS (the Cosmic Evolution Survey, Scoville et al., 2007ApJS..172....1S; Koekemoer et al., 2007ApJS..172..196K), UDS (the UKIDSS Ultra Deep Survey; Lawrence et al. 2007, cat. II/314; Cirasuolo et al., 2007MNRAS.380..585C), EGS (the Extended Groth Strip; Davis et al. 2007, cat. III/248). As described fully in Grogin et al. (2011ApJS..197...35G), the CANDELS program includes both "wide" and "deep" fields. The wide component of CANDELS comprises the COSMOS, UDS, and EGS fields, plus one-third of the GOODS-S field and one half of the GOODS-N field--a total survey area of 730 arcmin2. The "deep" component of CANDELS came from the central 67arcmin2 of each of the GOODS-S and GOODS-N fields. The CANDELS fields analyzed in this work are described in Table 1. (6 data files).

The effect of external magnetic field changing on the correlated quantum dot dynamics

NASA Astrophysics Data System (ADS)

Mantsevich, V. N.; Maslova, N. S.; Arseyev, P. I.

2018-06-01

The non-stationary response of local magnetic moment to abrupt switching "on" and "off" of external magnetic field was studied for a single-level quantum dot (QD) coupled to a reservoir. We found that transient processes look different for the shallow and deep localized energy level. It was demonstrated that for deep energy level the relaxation rates of the local magnetic moment strongly differ in the case of magnetic field switching "on" or "off". Obtained results can be applied in the area of dynamic memory devices stabilization in the presence of magnetic field.

Near-UV Sources in the Hubble Ultra Deep Field: The Catalog

NASA Technical Reports Server (NTRS)

Gardner, Jonathan P.; Voyrer, Elysse; de Mello, Duilia F.; Siana, Brian; Quirk, Cori; Teplitz, Harry I.

2009-01-01

The catalog from the first high resolution U-band image of the Hubble Ultra Deep Field, taken with Hubble s Wide Field Planetary Camera 2 through the F300W filter, is presented. We detect 96 U-band objects and compare and combine this catalog with a Great Observatories Origins Deep Survey (GOODS) B-selected catalog that provides B, V, i, and z photometry, spectral types, and photometric redshifts. We have also obtained Far-Ultraviolet (FUV, 1614 Angstroms) data with Hubble s Advanced Camera for Surveys Solar Blind Channel (ACS/SBC) and with Galaxy Evolution Explorer (GALEX). We detected 31 sources with ACS/SBC, 28 with GALEX/FUV, and 45 with GALEX/NUV. The methods of observations, image processing, object identification, catalog preparation, and catalog matching are presented.

Deep geothermal processes acting on faults and solid tides in coastal Xinzhou geothermal field, Guangdong, China

NASA Astrophysics Data System (ADS)

Lu, Guoping; Wang, Xiao; Li, Fusi; Xu, Fangyiming; Wang, Yanxin; Qi, Shihua; Yuen, David

2017-03-01

This paper investigated the deep fault thermal flow processes in the Xinzhou geothermal field in the Yangjiang region of Guangdong Province. Deep faults channel geothermal energy to the shallow ground, which makes it difficult to study due to the hidden nature. We conducted numerical experiments in order to investigate the physical states of the geothermal water inside the fault zone. We view the deep fault as a fast flow path for the thermal water from the deep crust driven up by the buoyancy. Temperature measurements at the springs or wells constrain the upper boundary, and the temperature inferred from the Currie temperature interface bounds the bottom. The deepened boundary allows the thermal reservoir to revolve rather than to be at a fixed temperature. The results detail the concept of a thermal reservoir in terms of its formation and heat distribution. The concept also reconciles the discrepancy in reservoir temperatures predicted from both quartz and Na-K-Mg. The downward displacement of the crust increases the pressure at the deep ground and leads to an elevated temperature and a lighter water density. Ultimately, our results are a first step in implementing numerical studies of deep faults through geothermal water flows; future works need to extend to cases of supercritical states. This approach is applicable to general deep-fault thermal flows and dissipation paths for the seismic energy from the deep crust.

SMUVS: Spitzer Matching survey of the UltraVISTA ultra-deep Stripes

NASA Astrophysics Data System (ADS)

Caputi, Karina; Ashby, Matthew; Fazio, Giovanni; Huang, Jiasheng; Dunlop, James; Franx, Marijn; Le Fevre, Olivier; Fynbo, Johan; McCracken, Henry; Milvang-Jensen, Bo; Muzzin, Adam; Ilbert, Olivier; Somerville, Rachel; Wechsler, Risa; Behroozi, Peter; Lu, Yu

2014-12-01

We request 2026.5 hours to homogenize the matching ultra-deep IRAC data of the UltraVISTA ultra-deep stripes, producing a final area of ~0.6 square degrees with the deepest near- and mid-IR coverage existing in any such large area of the sky (H, Ks, [3.6], [4.5] ~ 25.3-26.1 AB mag; 5 sigma). The UltraVISTA ultra-deep stripes are contained within the larger COSMOS field, which has a rich collection of multi-wavelength, ancillary data, making it ideal to study different aspects of galaxy evolution with high statistical significance and excellent redshift accuracy. The UltraVISTA ultra-deep stripes are the region of the COSMOS field where these studies can be pushed to the highest redshifts, but securely identifying high-z galaxies, and determining their stellar masses, will only be possible if ultra-deep mid-IR data are available. Our IRAC observations will allow us to: 1) extend the galaxy stellar mass function at redshifts z=3 to z=5 to the intermediate mass regime (M~5x10^9-10^10 Msun), which is critical to constrain galaxy formation models; 2) gain a factor of six in the area where it is possible to effectively search for z>=6 galaxies and study their properties; 3) measure, for the first time, the large-scale structure traced by an unbiased galaxy sample at z=5 to z=7, and make the link to their host dark matter haloes. This cannot be done in any other field of the sky, as the UltraVISTA ultra-deep stripes form a quasi-contiguous, regular-shape field, which has a unique combination of large area and photometric depth. 4) provide a unique resource for the selection of secure z>5 targets for JWST and ALMA follow up. Our observations will have an enormous legacy value which amply justifies this new observing-time investment in the COSMOS field. Spitzer cannot miss this unique opportunity to open up a large 0.6 square-degree window to the early Universe.

Deep-Earth reactor: Nuclear fission, helium, and the geomagnetic field

PubMed Central

Hollenbach, D. F.; Herndon, J. M.

2001-01-01

Geomagnetic field reversals and changes in intensity are understandable from an energy standpoint as natural consequences of intermittent and/or variable nuclear fission chain reactions deep within the Earth. Moreover, deep-Earth production of helium, having 3He/4He ratios within the range observed from deep-mantle sources, is demonstrated to be a consequence of nuclear fission. Numerical simulations of a planetary-scale geo-reactor were made by using the SCALE sequence of codes. The results clearly demonstrate that such a geo-reactor (i) would function as a fast-neutron fuel breeder reactor; (ii) could, under appropriate conditions, operate over the entire period of geologic time; and (iii) would function in such a manner as to yield variable and/or intermittent output power. PMID:11562483

Soil coring at multiple field environments can directly quantify variation in deep root traits to select wheat genotypes for breeding.

PubMed

Wasson, A P; Rebetzke, G J; Kirkegaard, J A; Christopher, J; Richards, R A; Watt, M

2014-11-01

We aim to incorporate deep root traits into future wheat varieties to increase access to stored soil water during grain development, which is twice as valuable for yield as water captured at younger stages. Most root phenotyping efforts have been indirect studies in the laboratory, at young plant stages, or using indirect shoot measures. Here, soil coring to 2 m depth was used across three field environments to directly phenotype deep root traits on grain development (depth, descent rate, density, length, and distribution). Shoot phenotypes at coring included canopy temperature depression, chlorophyll reflectance, and green leaf scoring, with developmental stage, biomass, and yield. Current varieties, and genotypes with breeding histories and plant architectures expected to promote deep roots, were used to maximize identification of variation due to genetics. Variation was observed for deep root traits (e.g. 111.4-178.5cm (60%) for depth; 0.09-0.22cm/°C day (144%) for descent rate) using soil coring in the field environments. There was significant variation for root traits between sites, and variation in the relative performance of genotypes between sites. However, genotypes were identified that performed consistently well or poorly at both sites. Furthermore, high-performing genotypes were statistically superior in root traits than low-performing genotypes or commercial varieties. There was a weak but significant negative correlation between green leaf score (-0.5), CTD (0.45), and rooting depth and a positive correlation for chlorophyll reflectance (0.32). Shoot phenotypes did not predict other root traits. This study suggests that field coring can directly identify variation in deep root traits to speed up selection of genotypes for breeding programmes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Large-scale fluctuations in the number density of galaxies in independent surveys of deep fields

NASA Astrophysics Data System (ADS)

Shirokov, S. I.; Lovyagin, N. Yu.; Baryshev, Yu. V.; Gorokhov, V. L.

2016-06-01

New arguments supporting the reality of large-scale fluctuations in the density of the visible matter in deep galaxy surveys are presented. A statistical analysis of the radial distributions of galaxies in the COSMOS and HDF-N deep fields is presented. Independent spectral and photometric surveys exist for each field, carried out in different wavelength ranges and using different observing methods. Catalogs of photometric redshifts in the optical (COSMOS-Zphot) and infrared (UltraVISTA) were used for the COSMOS field in the redshift interval 0.1 < z < 3.5, as well as the zCOSMOS (10kZ) spectroscopic survey and the XMM-COSMOS and ALHAMBRA-F4 photometric redshift surveys. The HDFN-Zphot and ALHAMBRA-F5 catalogs of photometric redshifts were used for the HDF-N field. The Pearson correlation coefficient for the fluctuations in the numbers of galaxies obtained for independent surveys of the same deep field reaches R = 0.70 ± 0.16. The presence of this positive correlation supports the reality of fluctuations in the density of visible matter with sizes of up to 1000 Mpc and amplitudes of up to 20% at redshifts z ~ 2. The absence of correlations between the fluctuations in different fields (the correlation coefficient between COSMOS and HDF-N is R = -0.20 ± 0.31) testifies to the independence of structures visible in different directions on the celestial sphere. This also indicates an absence of any influence from universal systematic errors (such as "spectral voids"), which could imitate the detection of correlated structures.

Scientific analogs and the development of human mission architectures for the Moon, deep space and Mars

NASA Astrophysics Data System (ADS)

Lim, D. S. S.; Abercromby, A.; Beaton, K.; Brady, A. L.; Cardman, Z.; Chappell, S.; Cockell, C. S.; Cohen, B. A.; Cohen, T.; Deans, M.; Deliz, I.; Downs, M.; Elphic, R. C.; Hamilton, J. C.; Heldmann, J.; Hillenius, S.; Hoffman, J.; Hughes, S. S.; Kobs-Nawotniak, S. E.; Lees, D. S.; Marquez, J.; Miller, M.; Milovsoroff, C.; Payler, S.; Sehlke, A.; Squyres, S. W.

2016-12-01

Analogs are destinations on Earth that allow researchers to approximate operational and/or physical conditions on other planetary bodies and within deep space. Over the past decade, our team has been conducting geobiological field science studies under simulated deep space and Mars mission conditions. Each of these missions integrate scientific and operational research with the goal to identify concepts of operations (ConOps) and capabilities that will enable and enhance scientific return during human and human-robotic missions to the Moon, into deep space and on Mars. Working under these simulated mission conditions presents a number of unique challenges that are not encountered during typical scientific field expeditions. However, there are significant benefits to this working model from the perspective of the human space flight and scientific operations research community. Specifically, by applying human (and human-robotic) mission architectures to real field science endeavors, we create a unique operational litmus test for those ConOps and capabilities that have otherwise been vetted under circumstances that did not necessarily demand scientific data return meeting the rigors of peer-review standards. The presentation will give an overview of our team's recent analog research, with a focus on the scientific operations research. The intent is to encourage collaborative dialog with a broader set of analog research community members with an eye towards future scientific field endeavors that will have a significant impact on how we design human and human-robotic missions to the Moon, into deep space and to Mars.

Galaxies in the Diffuse Baryon Field Approaching Reionization: A Joint Study with JWST, HST, and Large Telescopes

NASA Astrophysics Data System (ADS)

Simcoe, Robert

2017-08-01

Our team is conducting a dedicated survey for emission-line galaxies at 5 < z < 7 in six fields containing the best and brightest z > 6 quasars, using JWST/NIRCAM's slitless grism in a 110 hour GTO allocation. We have acquired deep near-IR spectra of the QSOs, revealing multiple heavy-element absorption systems and probing the HI optical depth within each object's survey volume. These data will provide the first systematic view of the circumgalactic medium at z > 4, allowing us to study early metal enrichment, correlations of the intergalactic HI optical depth with galaxy density, and the environment of the quasar hosts. These fields generally do not have deep multicolor photometry that would facilitate selection of broadband dropout galaxies for future observation with JWST/NIRSPEC. However during long spectroscopic integrations with NIRCAM's long channel we will obtain deep JWST photometry in F115W and F200W, together with F356W for wavelength calibration. Here we request 30 orbits with HST/ACS to acquire deep optical photometry that (together with the JWST IR bands) will constrain SED models and enable dropout selection of fainter objects. For lower redshift objects the rest-UV ACS data will improve estimates of star formation rate and stellar mass. Within a Small-GO program scope we will obtain sensitivity similar to CANDELS-Deep in all six fields, and approximately double the size of our galaxy sample appropriate for JWST/NIRSPEC followup at redshifts approaching the reionization epoch.

Static Electric Fields and Lightning Over Land and Ocean in Florida Thunderstorms

NASA Technical Reports Server (NTRS)

Wilson, J. G.; Cummins, K. L.; Simpson, A. A.; Hinckley, A.

2017-01-01

Natural cloud-to-ground (CG) lightning and the charge structure of the associated clouds behave differently over land and ocean. Existing literature has raised questions over the years on the behavior of thunderstorms and lightning over oceans, and there are still open scientific questions. We expand on the observational datasets by obtaining identical electric field observations over coastal land, near-shore, and deep ocean regions during both clear air and thunderstorm periods. Oceanic observations were obtained using two 3-meter NOAA buoys that were instrumented with Campbell Scientific electric field mills to measure the static electric fields. These data were compared to selected electric field records from the existing on-shore electric field mill suite of 31 sensors at Kennedy Space Center (KSC). CG lightning occurrence times, locations and peak current values for both on-shore and ocean were provided by the U.S. National Lightning Detection Network. The buoy instruments were first evaluated on-shore at the Florida coast, to calibrate field enhancements and to confirm proper behavior of the system in elevated-field environments. The buoys were then moored 20NM and 120NM off the coast of KSC in February (20NM) and August (120NM) 2014. Statistically larger CG peak currents were reported over the deep ocean for first strokes and for subsequent strokes with new contacts points. Storm-related static fields were significantly larger at both oceanic sites, likely due to decreased screening by nearby space charge. Time-evolution of the static field during storm development and propagation indicated weak or missing lower positive charge regions in most storms that initiated over the deep ocean, supporting one mechanism for the observed high peak currents in negative first strokes over the deep ocean. This project also demonstrated the practicality of off-shore electric field measurements for safety-related decision making at KSC.

Frontier Fields: Bringing the Distant Universe into View

NASA Astrophysics Data System (ADS)

Eisenhamer, Bonnie; Lawton, Brandon L.; Summers, Frank; Ryer, Holly

2014-06-01

The Frontier Fields is a multi-cycle program of six deep-field observations of strong-lensing galaxy clusters that will be taken in parallel with six deep “blank fields.” The three-year long collaborative program centers on observations from NASA’s Great Observatories, who will team up to look deeper into the universe than ever before, and potentially uncover galaxies that are as much as 100 times fainter than what the telescopes can typically see. Because of the unprecedented views of the universe that will be achieved, the Frontier Fields science program is ideal for informing audiences about scientific advances and topics in STEM. For example, the program provides an opportunity to look back on the history of deep field observations and how they changed (and continue to change) astronomy, while exploring the ways astronomers approach big science problems. As a result, the Space Telescope Science Institute’s Office of Public Outreach has initiated an education and public outreach (E/PO) project to follow the progress of the Frontier Fields program - providing a behind-the-scenes perspective of this observing initiative. This poster will highlight the goals of the Frontier Fields E/PO project and the cost-effective approach being used to bring the program’s results to both the public and educational audiences.

Development of deep eutectic solvents applied in extraction and separation.

PubMed

Li, Xiaoxia; Row, Kyung Ho

2016-09-01

Deep eutectic solvents, as an alternative to ionic liquids, have greener credentials than ionic liquids, and have attracted considerable attention in related chemical research. Deep eutectic solvents have attracted increasing attention in chemistry for the extraction and separation of various target compounds from natural products. This review highlights the preparation of deep eutectic solvents, unique properties of deep eutectic solvents, and synthesis of deep-eutectic-solvent-based materials. On the other hand, application in the extraction and separation of deep eutectic solvents is also included in this report. In this paper, the available data and references in this field are reviewed to summarize the applications and developments of deep eutectic solvents. Based on the development of deep eutectic solvents, an exploitation of new deep eutectic solvents and deep eutectic solvents-based materials is expected to diversify into extraction and separation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders.

PubMed

Işil, Çağatay; Yorulmaz, Mustafa; Solmaz, Berkan; Turhan, Adil Burak; Yurdakul, Celalettin; Ünlü, Selim; Ozbay, Ekmel; Koç, Aykut

2018-04-01

Wide-field interferometric microscopy is a highly sensitive, label-free, and low-cost biosensing imaging technique capable of visualizing individual biological nanoparticles such as viral pathogens and exosomes. However, further resolution enhancement is necessary to increase detection and classification accuracy of subdiffraction-limited nanoparticles. In this study, we propose a deep-learning approach, based on coupled deep autoencoders, to improve resolution of images of L-shaped nanostructures. During training, our method utilizes microscope image patches and their corresponding manual truth image patches in order to learn the transformation between them. Following training, the designed network reconstructs denoised and resolution-enhanced image patches for unseen input.

The Deep Space Network as an instrument for radio science research

NASA Technical Reports Server (NTRS)

Asmar, S. W.; Renzetti, N. A.

1993-01-01

Radio science experiments use radio links between spacecraft and sensor instrumentation that is implemented in the Deep Space Network. The deep space communication complexes along with the telecommunications subsystem on board the spacecraft constitute the major elements of the radio science instrumentation. Investigators examine small changes in the phase and/or amplitude of the radio signal propagating from a spacecraft to study the atmospheric and ionospheric structure of planets and satellites, planetary gravitational fields, shapes, masses, planetary rings, ephemerides of planets, solar corona, magnetic fields, cometary comae, and such aspects of the theory of general relativity as gravitational waves and gravitational redshift.

A Comparison of Peak Electric Fields and GICs in the Pacific Northwest Using 1-D and 3-D Conductivity

NASA Astrophysics Data System (ADS)

Gannon, J. L.; Birchfield, A. B.; Shetye, K. S.; Overbye, T. J.

2017-11-01

Geomagnetically induced currents (GICs) are a result of the changing magnetic fields during a geomagnetic disturbance interacting with the deep conductivity structures of the Earth. When assessing GIC hazard, it is a common practice to use layer-cake or one-dimensional conductivity models to approximate deep Earth conductivity. In this paper, we calculate the electric field and estimate GICs induced in the long lines of a realistic system model of the Pacific Northwest, using the traditional 1-D models, as well as 3-D models represented by Earthscope's Electromagnetic transfer functions. The results show that the peak electric field during a given event has considerable variation across the analysis region in the Pacific Northwest, but the 1-D physiographic approximations may accurately represent the average response of an area, although corrections are needed. Rotations caused by real deep Earth conductivity structures greatly affect the direction of the induced electric field. This effect may be just as, or more, important than peak intensity when estimating GICs induced in long bulk power system lines.

Deep Vadose Zone Treatability Test for the Hanford Central Plateau. Interim Post-Desiccation Monitoring Results, Fiscal Year 2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truex, Michael J.; Strickland, Christopher E.; Oostrom, Martinus

A field test of desiccation is being conducted as an element of the Deep Vadose Zone Treatability Test Program. The active desiccation portion of the test has been completed. Monitoring data have been collected at the field test site during the post-desiccation period and are reported herein. This is an interim data summary report that includes about 4 years of post-desiccation monitoring data. The DOE field test plan proscribes a total of 5 years of post-desiccation monitoring.

The scheme of LLSST based on inter-satellite link for planet gravity field measurement in deep-space mission

NASA Astrophysics Data System (ADS)

Yang, Yikang; Li, Xue; Liu, Lei

2009-12-01

Gravity field measurement for the interested planets and their moos in solar system, such as Luna and Mars, is one important task in the next step of deep-space mission. In this paper, Similar to GRACE mission, LLSST and DOWR technology of common-orbit master-slave satellites around task planet is inherited in this scheme. Furthermore, by intersatellite 2-way UQPSK-DSSS link, time synchronization and data processing are implemented autonomously by masterslave satellites instead of GPS and ground facilities supporting system. Conclusion is derived that the ISL DOWR based on 2-way incoherent time synchronization has the same precise level to GRACE DOWR based on GPS time synchronization. Moreover, because of inter-satellite link, the proposed scheme is rather autonomous for gravity field measurement of the task planet in deep-space mission.

Comment on ‘Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study’

NASA Astrophysics Data System (ADS)

Valdes, Gilmer; Interian, Yannet

2018-03-01

The application of machine learning (ML) presents tremendous opportunities for the field of oncology, thus we read ‘Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study’ with great interest. In this article, the authors used state of the art techniques: a pre-trained convolutional neural network (VGG-16 CNN), transfer learning, data augmentation, drop out and early stopping, all of which are directly responsible for the success and the excitement that these algorithms have created in other fields. We believe that the use of these techniques can offer tremendous opportunities in the field of Medical Physics and as such we would like to praise the authors for their pioneering application to the field of Radiation Oncology. That being said, given that the field of Medical Physics has unique characteristics that differentiate us from those fields where these techniques have been applied successfully, we would like to raise some points for future discussion and follow up studies that could help the community understand the limitations and nuances of deep learning techniques.

Photometric redshifts for the next generation of deep radio continuum surveys - I. Template fitting

NASA Astrophysics Data System (ADS)

Duncan, Kenneth J.; Brown, Michael J. I.; Williams, Wendy L.; Best, Philip N.; Buat, Veronique; Burgarella, Denis; Jarvis, Matt J.; Małek, Katarzyna; Oliver, S. J.; Röttgering, Huub J. A.; Smith, Daniel J. B.

2018-01-01

We present a study of photometric redshift performance for galaxies and active galactic nuclei detected in deep radio continuum surveys. Using two multiwavelength data sets, over the NOAO Deep Wide Field Survey Boötes and COSMOS fields, we assess photometric redshift (photo-z) performance for a sample of ∼4500 radio continuum sources with spectroscopic redshifts relative to those of ∼63 000 non-radio-detected sources in the same fields. We investigate the performance of three photometric redshift template sets as a function of redshift, radio luminosity and infrared/X-ray properties. We find that no single template library is able to provide the best performance across all subsets of the radio-detected population, with variation in the optimum template set both between subsets and between fields. Through a hierarchical Bayesian combination of the photo-z estimates from all three template sets, we are able to produce a consensus photo-z estimate that equals or improves upon the performance of any individual template set.

Deep rooting conferred by DEEPER ROOTING 1 enhances rice yield in paddy fields.

PubMed

Arai-Sanoh, Yumiko; Takai, Toshiyuki; Yoshinaga, Satoshi; Nakano, Hiroshi; Kojima, Mikiko; Sakakibara, Hitoshi; Kondo, Motohiko; Uga, Yusaku

2014-07-03

To clarify the effect of deep rooting on grain yield in rice (Oryza sativa L.) in an irrigated paddy field with or without fertilizer, we used the shallow-rooting IR64 and the deep-rooting Dro1-NIL (a near-isogenic line homozygous for the Kinandang Patong allele of DEEPER ROOTING 1 (DRO1) in the IR64 genetic background). Although total root length was similar in both lines, more roots were distributed within the lower soil layer of the paddy field in Dro1-NIL than in IR64, irrespective of fertilizer treatment. At maturity, Dro1-NIL showed approximately 10% higher grain yield than IR64, irrespective of fertilizer treatment. Higher grain yield of Dro1-NIL was mainly due to the increased 1000-kernel weight and increased percentage of ripened grains, which resulted in a higher harvest index. After heading, the uptake of nitrogen from soil and leaf nitrogen concentration were higher in Dro1-NIL than in IR64. At the mid-grain-filling stage, Dro1-NIL maintained higher cytokinin fluxes from roots to shoots than IR64. These results suggest that deep rooting by DRO1 enhances nitrogen uptake and cytokinin fluxes at late stages, resulting in better grain filling in Dro1-NIL in a paddy field in this study.

Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Characterization of deep level defects and thermally stimulated depolarization phenomena in La-doped TlInS{sub 2} layered semiconductor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seyidov, MirHasan Yu., E-mail: smirhasan@gyte.edu.tr; Suleymanov, Rauf A.; Mikailzade, Faik A.

2015-06-14

Lanthanum-doped high quality TlInS{sub 2} (TlInS{sub 2}:La) ferroelectric-semiconductor was characterized by photo-induced current transient spectroscopy (PICTS). Different impurity centers are resolved and identified. Analyses of the experimental data were performed in order to determine the characteristic parameters of the extrinsic and intrinsic defects. The energies and capturing cross section of deep traps were obtained by using the heating rate method. The observed changes in the Thermally Stimulated Depolarization Currents (TSDC) near the phase transition points in TlInS{sub 2}:La ferroelectric-semiconductor are interpreted as a result of self-polarization of the crystal due to the internal electric field caused by charged defects. Themore » TSDC spectra show the depolarization peaks, which are attributed to defects of dipolar origin. These peaks provide important information on the defect structure and localized energy states in TlInS{sub 2}:La. Thermal treatments of TlInS{sub 2}:La under an external electric field, which was applied at different temperatures, allowed us to identify a peak in TSDC which was originated from La-dopant. It was established that deep energy level trap BTE43, which are active at low temperature (T ≤ 156 K) and have activation energy 0.29 eV and the capture cross section 2.2 × 10{sup −14} cm{sup 2}, corresponds to the La dopant. According to the PICTS results, the deep level trap center B5 is activated in the temperature region of incommensurate (IC) phases of TlInS{sub 2}:La, having the giant static dielectric constant due to the structural disorders. From the PICTS simulation results for B5, native deep level trap having an activation energy of 0.3 eV and the capture cross section of 1.8 × 10{sup −16} cm{sup 2} were established. A substantial amount of residual space charges is trapped by the deep level localized energy states of B5 in IC-phase. While the external electric field is applied, permanent dipoles, which are originated from the charged B5 deep level defects, are aligned in the direction of the applied electric field and the equilibrium polarization can be reached in a relatively short time. When the polarization field is maintained, while cooling the temperature of sample to a sufficiently low degrees, the relaxation times of the aligned dipoles drastically increases. Practically, frozen internal electric field or electrets states remain inside the TlInS{sub 2}:La when the applied bias field is switched off. The influence of deep level defects on TSDC spectra of TlInS{sub 2}:La has been revealed for the first time.« less

Dro1, a major QTL involved in deep rooting of rice under upland field conditions.

PubMed

Uga, Yusaku; Okuno, Kazutoshi; Yano, Masahiro

2011-05-01

Developing a deep root system is an important strategy for avoiding drought stress in rice. Using the 'basket' method, the ratio of deep rooting (RDR; the proportion of total roots that elongated through the basket bottom) was calculated to evaluate deep rooting. A new major quantitative trait locus (QTL) controlling RDR was detected on chromosome 9 by using 117 recombinant inbred lines (RILs) derived from a cross between the lowland cultivar IR64, with shallow rooting, and the upland cultivar Kinandang Patong (KP), with deep rooting. This QTL explained 66.6% of the total phenotypic variance in RDR in the RILs. A BC(2)F(3) line homozygous for the KP allele of the QTL had an RDR of 40.4%, compared with 2.6% for the homozygous IR64 allele. Fine mapping of this QTL was undertaken using eight BC(2)F(3) recombinant lines. The RDR QTL Dro1 (Deeper rooting 1) was mapped between the markers RM24393 and RM7424, which delimit a 608.4 kb interval in the reference cultivar Nipponbare. To clarify the influence of Dro1 in an upland field, the root distribution in different soil layers was quantified by means of core sampling. A line homozygous for the KP allele of Dro1 (Dro1-KP) and IR64 did not differ in root dry weight in the shallow soil layers (0-25 cm), but root dry weight of Dro1-KP in deep soil layers (25-50 cm) was significantly greater than that of IR64, suggesting that Dro1 plays a crucial role in increased deep rooting under upland field conditions.

FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coe, Dan; Bradley, Larry; Zitrin, Adi, E-mail: DCoe@STScI.edu

2015-02-20

The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z >more » 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.« less

Hello World Deep Learning in Medical Imaging.

PubMed

Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

2018-05-03

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

High-resolution Topography of PACMANUS and DESMOS Hydrothermal Fields in the Manus Basin through ROV "FAXIAN"

NASA Astrophysics Data System (ADS)

Luan, Z.; Ma, X.; Yan, J.; Zhang, X.; Zheng, C.; Sun, D.

2016-12-01

High-resolution topography can help us deeply understand the seabed and related geological processes (e.g. hydrothermal/cold spring systems) in the deep sea areas. However, such studies are rare in China due to the limit of deep-sea detection technology. Here, we report the advances of the application of ROV in China and the newly measured high-resolution topographical data in PACMANUS and DESMOS hydrothermal fields. In June 2015, the ROV "FAXIAN" with a multibeam system (Kongsberg EM2040) was deployed to measure the topography of PACMANUS and DESMOS hydrothermal fields in the Manus basin. A composite positioning system on the ROV provided long baseline (LBL) navigation and positioning during measurements, giving a high positioning accuracy (better than 0.5m). The raw bathymetric data obtained were processed using CARIS HIPS (version 8.1). Based on the high-resolution data, we can describe the topographical details of the PACMANUS and DESMOS hydrothermal fields. High-resolution terrain clearly shows the detailed characters of the topography in the PACMANUS hydrothermal field, and some cones are corresponding to the pre discovered hydrothermal points and volcanic area. Most hydrothermal points in the PACMANUS hydrothermal field mainly developed on the steep slopes with a gradient exceeding 30 °. In contrast, the DESMOS field is a caldera that is approximately 250 m deep in the center with an E-W diameter of approximately1 km and a N-S diameter of approximately 2 km. The seafloor is much steeper on the inner side of the circular fracture. Two highlands occur in the northern and the southern flanks of the caldera. Video record indicated that pillow lava, sulfide talus, breccia, anhydrite, outcrops, and sediment all appeared in the DESMOS field. This is the first time for the ROV "FAXIAN" to be used in near-bottom topography measurements in the hydrothermal fields, opening a window of deep-sea researches in China.

Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter.

PubMed

Elkady, Ahmed M; Sun, Hongfu; Wilman, Alan H

2016-05-01

Quantitative Susceptibility Mapping (QSM) is an emerging area of brain research with clear application to brain iron studies in deep gray matter. However, acquisition of standard whole brain QSM can be time-consuming. One means to reduce scan time is to use a focal acquisition restricted only to the regions of interest such as deep gray matter. However, the non-local dipole field necessary for QSM reconstruction extends far beyond the structure of interest. We demonstrate the practical implications of these non-local fields on the choice of brain volume for QSM. In an illustrative numerical simulation and then in human brain experiments, we examine the effect on QSM of volume reduction in each dimension. For the globus pallidus, as an example of iron-rich deep gray matter, we demonstrate that substantial errors can arise even when the field-of-view far exceeds the physical structural boundaries. Thus, QSM reconstruction requires a non-local field-of-view prescription to ensure minimal errors. An axial QSM acquisition, centered on the globus pallidus, should encompass at least 76mm in the superior-inferior direction to conserve susceptibility values from the globus pallidus. This dimension exceeds the physical coronal extent of this structure by at least five-fold. As QSM sees wider use in the neuroscience community, its unique requirement for an extended field-of-view needs to be considered. Copyright © 2016 Elsevier Inc. All rights reserved.

The ROSAT Deep Survey. 2; Optical Identification, Photometry and Spectra of X-Ray Sources in the Lockman Field

NASA Technical Reports Server (NTRS)

Schmidt, M.; Hasinger, G.; Gunn, J.; Schneider, D.; Burg, R.; Giacconi, R.; Lehmann, I.; MacKenty, J.; Truemper, J.; Zamorani, G.

1998-01-01

The ROSAT Deep Survey includes a complete sample of 50 X-ray sources with fluxes in the 0.5 - 2 keV band larger than 5.5 x 10(exp -15)erg/sq cm/s in the Lockman field (Hasinger et al., Paper 1). We have obtained deep broad-band CCD images of the field and spectra of many optical objects near the positions of the X-ray sources. We define systematically the process leading to the optical identifications of the X-ray sources. For this purpose, we introduce five identification (ID) classes that characterize the process in each case. Among the 50 X-ray sources, we identify 39 AGNs, 3 groups of galaxies, 1 galaxy and 3 galactic stars. Four X-ray sources remain unidentified so far; two of these objects may have an unusually large ratio of X-ray to optical flux.

Hubble Team Unveils Most Colorful View of Universe Captured by Space Telescope

NASA Image and Video Library

2014-06-04

Astronomers using NASA's Hubble Space Telescope have assembled a comprehensive picture of the evolving universe – among the most colorful deep space images ever captured by the 24-year-old telescope. Researchers say the image, in new study called the Ultraviolet Coverage of the Hubble Ultra Deep Field, provides the missing link in star formation. The Hubble Ultra Deep Field 2014 image is a composite of separate exposures taken in 2003 to 2012 with Hubble's Advanced Camera for Surveys and Wide Field Camera 3. Credit: NASA/ESA Read more: 1.usa.gov/1neD0se NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Reconstruction of Horizontal Plasma Motions at the Photosphere from Intensitygrams: A Comparison Between DeepVel, LCT, FLCT, and CST

NASA Astrophysics Data System (ADS)

Tremblay, Benoit; Roudier, Thierry; Rieutord, Michel; Vincent, Alain

2018-04-01

Direct measurements of plasma motions in the photosphere are limited to the line-of-sight component of the velocity. Several algorithms have therefore been developed to reconstruct the transverse components from observed continuum images or magnetograms. We compare the space and time averages of horizontal velocity fields in the photosphere inferred from pairs of consecutive intensitygrams by the LCT, FLCT, and CST methods and the DeepVel neural network in order to identify the method that is best suited for generating synthetic observations to be used for data assimilation. The Stein and Nordlund ( Astrophys. J. Lett. 753, L13, 2012) magnetoconvection simulation is used to generate synthetic SDO/HMI intensitygrams and reference flows to train DeepVel. Inferred velocity fields show that DeepVel performs best at subgranular and granular scales and is second only to FLCT at mesogranular and supergranular scales.

The Great Easter Egg Hunt: The Void's Incredible Richness

NASA Astrophysics Data System (ADS)

2006-04-01

An image made of about 300 million pixels is being released by ESO, based on more than 64 hours of observations with the Wide-Field Camera on the 2.2m telescope at La Silla (Chile). The image covers an 'empty' region of the sky five times the size of the full moon, opening an exceptionally clear view towards the most distant part of our universe. It reveals objects that are 100 million times fainter than what the unaided eye can see. Easter is in many countries a time of great excitement for children who are on the big hunt for chocolate eggs, hidden all about the places. Astronomers, however, do not need to wait this special day to get such an excitement: it is indeed daily that they look for faraway objects concealed in deep images of the sky. And as with chocolate eggs, deep sky objects, such as galaxies, quasars or gravitational lenses, come in the wildest variety of colours and shapes. ESO PR Photo 11/06 ESO PR Photo 14a/06 The Deep 3 'Empty' Field The image presented here is one of such very deep image of the sky. It is the combination of 714 frames for a total exposure time of 64.5 hours obtained through four different filters (B, V, R, and I)! It consists of four adjacent Wide-Field Camera pointings (each 33x34 arcmin), covering a total area larger than one square degree. Yet, if you were to look at this large portion of the firmament with the unaided eye, you would just see... nothing. The area, named Deep 3, was indeed chosen to be a random but empty, high galactic latitude field, positioned in such a way that it can be observed from the La Silla observatory all over the year. Together with two other regions, Deep 1 and Deep 2, Deep 3 is part of the Deep Public Survey (DPS), based on ideas submitted by the ESO community and covering a total sky area of 3 square degrees. Deep 1 and Deep 2 were selected because they overlapped with regions of other scientific interest. For instance, Deep 1 was chosen to complement the deep ATESP radio survey carried out with the Australia Telescope Compact Array (ATCA) covering the region surveyed by the ESO Slice Project, while Deep 2 included the CDF-S field. Each region is observed in the optical, with the WFI, and in the near-infrared, with SOFI on the 3.5-m New Technology Telescope also at La Silla. Deep 3 is located in the Crater ('The Cup'), a southern constellation with very little interest (the brightest star is of fourth magnitude, i.e. only a factor six brighter than what a keen observer can see with the unaided eye), in between the Virgo, Corvus and Hydra constellations. Such comparatively empty fields provide an unusually clear view towards the distant regions in the Universe and thus open a window towards the earliest cosmic times. The deep imaging data can for example be used to pre-select objects by colour for follow-up spectroscopy with ESO's Very Large Telescope instruments. ESO PR Photo 11/06 ESO PR Photo 14b/06 Galaxy ESO 570-19 and Variable Star UW Crateris But being empty is only a relative notion. True, on the whole image, the SIMBAD Astronomical database references less than 50 objects, clearly a tiny number compared to the myriad of anonymous stars and galaxies that can be seen in the deep image obtained by the Survey! Among the objects catalogued is the galaxy visible in the top middle right (see also PR Photo 14b/06) and named ESO 570-19. Located 60 million light-years away, this spiral galaxy is the largest in the image. It is located not so far - on the image! - from the brightest star in the field, UW Crateris. This red giant is a variable star that is about 8 times fainter than what the unaided eye can see. The second and third brightest stars in this image are visible in the lower far right and in the lower middle left. The first is a star slightly more massive than the Sun, HD 98081, while the other is another red giant, HD 98507. ESO PR Photo 11/06 ESO PR Photo 14c/06 The DPS Deep 3 Field (Detail) In the image, a vast number of stars and galaxies are to be studied and compared. They come in a variety of colours and the stars form amazing asterisms (a group of stars forming a pattern), while the galaxies, which are to be counted by the tens of thousands come in different shapes and some even interact or form part of a cluster. The image and the other associated data will certainly provide a plethora of new results in the years to come. In the meantime, why don't you explore the image with the zoom-in facility, and start your own journey into infinity? Just be careful not to get lost. And remember: don't eat too many of these chocolate eggs! High resolution images and their captions are available on this page.

Water resources data of the Seward area, Alaska

USGS Publications Warehouse

Dearborn, Larry L.; Anderson, Gary S.; Zenone, Chester

1979-01-01

Seward, Alaska, obtains a water supply of about 2 million gallons per day primarily from Marathon Springs and the Fort Raymond well field. The springs have supplied up to 800 gallons per minute, and the city 's deep wells currently have a combined capacity of about 3,000 gallons per minute. Freshwater is abundant in the area; future public supplies could be derived from both shallow and deep ground water and from stream impoundment with diversion. High deep-aquifer transmissivity at the Fort Raymond well field indicates that additional wells could be developed there. Water quality is generally not a problem for public consumption. A flood potential exists along several streams having broad alluvial fans. (Woodard-USGS)

Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

PubMed

van Ginneken, Bram

2017-03-01

Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

Project DEEP STEAM

NASA Astrophysics Data System (ADS)

Aeschliman, D. P.; Clay, R. G.; Donaldson, A. B.; Eisenhawer, S. W.; Fox, R. L.; Johnson, D. R.; Mulac, A. J.

1982-01-01

The objective of Project DEEP STEAM is to develop the technology to economically produce heavy oils from deep reservoirs. The tasks included in this project are the development of thermally efficient delivery systems and downhole steam generation systems. During the period January 1-March 31, 1981, effort has continued on a low pressure combustion downhole generator (Rocketdyne), and on two high pressure designs (Foster-Miller Associates, Sandia National Laboratories). The Sandia design was prepared for deployment in the Wilmington Field at Long Beach, California. Progress continued on the Min-Stress II packer concept at L'Garde, Inc., and on the extruded metal packer at Foster-Miller. Initial bare string field data are reported on the insulated tubular test at Lloydminster, Saskatchewan, Canada.

Execution of deep dipole geoelectrical soundings in areas of geothermal interest. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patella, D.

It is suggested that deep geoelectrical problems may be resolved by carrying out dipole soundings in the field and applying a quantitative interpretation in the Schlumberger domain. The 'transformation' of original field dipole sounding curves into equivalent Schlumberger curves is outlined for the cases of layered structures and arbitrary underground structures. Theoretical apparent resistivity curves are derived for soundings over bidimensional structures. Following a summary of the geological features of the Travale-Radicondoli geothermal area of Italy, the dipole sounding method employed for this field study and the means of collecting and analyzing the data, are outlined.

Electromagnetic sounding of the moon using Apollo 16 and Lunokhod 2 surface magnetometer observations /preliminary results/

NASA Technical Reports Server (NTRS)

Vanian, L. L.; Vnutchokova, T. A.; Fainberg, E. B.; Eroschenko, E. A.; Dyal, P.; Parkin, C. W.; Daily, W. D.

1977-01-01

A technique of deep electromagnetic sounding of the moon using simultaneous magnetic-field measurements at two lunar surface sites is described. The method, used with the assumption that deep electrical conductivity is a function only of lunar radius, has the advantage of allowing calculation of the external driving field from two surface-site measurements only and therefore does not require data from a lunar orbiting satellite. A transient-response calculation is presented for the example of a magnetic-field discontinuity, measured simultaneously by Apollo 16 and Lunokhod 2 surface magnetometers.

Electromagnetic Sounding of the Moon Using Apollo 16 and Lunokhod 2 Surface Magnetometer Observations (Preliminary Results)

NASA Technical Reports Server (NTRS)

Vanyan, L. L.; Vnutchokova, T. A.; Fainberg, E. B.; Eroschenko, E. A.; Dyal, P.; Parkin, C. W.; Parkin, C. W.

1977-01-01

A new technique of deep electromagnetic sounding of the Moon using simultaneous magnetic field measurements at two lunar surface sites is described. The method, used with the assumption that deep electrical conductivity is a function only of lunar radius, has the advantage of allowing calculation of the external driving field from two surface site measurements only, and therefore does not require data from a lunar orbiting satellite. A transient response calculation is presented for the example of a magnetic field discontinuity of February 13, 1973, measured simultaneously by Apollo 16 and Lunokhod 2 surface magnetometers.

Using Jupiter's gravitational field to probe the Jovian convective dynamo.

PubMed

Kong, Dali; Zhang, Keke; Schubert, Gerald

2016-03-23

Convective motion in the deep metallic hydrogen region of Jupiter is believed to generate its magnetic field, the strongest in the solar system. The amplitude, structure and depth of the convective motion are unknown. A promising way of probing the Jovian convective dynamo is to measure its effect on the external gravitational field, a task to be soon undertaken by the Juno spacecraft. We calculate the gravitational signature of non-axisymmetric convective motion in the Jovian metallic hydrogen region and show that with sufficiently accurate measurements it can reveal the nature of the deep convection.

Using Jupiter’s gravitational field to probe the Jovian convective dynamo

PubMed Central

Kong, Dali; Zhang, Keke; Schubert, Gerald

2016-01-01

Convective motion in the deep metallic hydrogen region of Jupiter is believed to generate its magnetic field, the strongest in the solar system. The amplitude, structure and depth of the convective motion are unknown. A promising way of probing the Jovian convective dynamo is to measure its effect on the external gravitational field, a task to be soon undertaken by the Juno spacecraft. We calculate the gravitational signature of non-axisymmetric convective motion in the Jovian metallic hydrogen region and show that with sufficiently accurate measurements it can reveal the nature of the deep convection. PMID:27005472

A tribute to Peter A. Rona: A Russian Perspective

NASA Astrophysics Data System (ADS)

Sagalevich, Anatoly; Lutz, Richard A.

2015-11-01

In July 1985 Peter Rona led a cruise of the National Oceanic and Atmospheric Administration (NOAA) ship Researcher as part of the NOAA Vents Program and discovered, for the first time, black smokers, massive sulfide deposits and vent biota in the Atlantic Ocean. The site of the venting phenomena was the Trans-Atlantic Geotraverse (TAG) Hydrothermal Field on the east wall of the rift valley of the Mid-Atlantic Ridge at 26°08‧N; 44°50‧W (Rona, 1985; Rona et al., 1986). In 1986, Peter and an international research team carried out multidisciplnary investigations of both active and inactive hydrothermal zones of the TAG field using the R/V Atlantis and DSV Alvin, discovering two new species of shrimp (Rimicaris exoculata and Chorocaris chacei) (Williams and Rona, 1986) and a hexagonal-shaped form (Paleodictyon nodosum) thought to be extinct (Rona et al., 2009). In 1991 a Russian crew aboard the R/V Akademik Mstislav Keldysh, with two deep-diving, human-occupied submersibles (Mir-1 and Mir-2) (Fig. 1), had the honor of having Peter Rona and a Canadian IMAX film crew from the Stephen Low Company on board to visit the TAG hydrothermal vent field. This was the first of many deep-sea interactions between Russian deep-sea scientists and their colleagues from both the U.S. and Canada. This expedition to the TAG site was part of a major Russian undersea program aimed at exploring extreme deep-sea environments; between 1988 and 2005, the Mir submersibles visited hydrothermal vents and cold seep areas in 20 deep-sea regions throughout the world's oceans (Sagalevich, 2002). Images of several of these areas (the TAG, Snake Pit, Lost City and 9°50‧N vent fields) were obtained using an IMAX camera system emplaced for the first time within the spheres of the Mir submersibles and DSV Alvin in conjunction with the filming of science documentaries (e.g., ;Volcanoes of the Deep Sea;) produced by the Stephen Low Company in conjunction with Emory Kristof of National Geographic and Peter Rona. The initial test of this submersible-emplaced camera system was conducted during the 1991 expedition to the TAG hydrothermal vent field.

Quantification of deep percolation from two flood-irrigated alfalfa field, Roswell Basin, New Mexico

USGS Publications Warehouse

Roark, D. Michael; Healy, D.F.

1998-01-01

For many years water management in the Roswell ground-water basin (Roswell Basin) and other declared basins in New Mexico has been the responsibility of the State of New Mexico. One of the water management issues requiring better quantification is the amount of deep percolation from applied irrigation water. Two adjacent fields, planted in alfalfa, were studied to determine deep percolation by the water-budget, volumetric-moisture, and chloride mass-balance methods. Components of the water-budget method were measured, in study plots called borders, for both fields during the 1996 irrigation season. The amount of irrigation water applied in the west border was 95.8 centimeters and in the east border was 169.8 centimeters. The total amount of precipitation that fell during the irrigation season was 21.9 centimeters. The increase in soil-moisture storage from the beginning to the end of the irrigation season was 3.2 centimeters in the west border and 8.8 centimeters in the east border. Evapotranspiration, as estimated by the Bowen ratio energy balance technique, in the west border was 97.8 centimeters and in the east border was 101.0 centimeters. Deep percolation determined using the water-budget method was 16.4 centimeters in the west border and 81.6 centimeters in the east border. An average deep percolation of 22.3 centimeters in the west border and 31.6 centimeters in the east border was determined using the volumetric-moisture method. The chloride mass-balance method determined the multiyear deep percolation to be 15.0 centimeters in the west border and 38.0 centimeters in the east border. Large differences in the amount of deep percolation between the two borders calculated by the water-budget method are due to differences in the amount of water that was applied to each border. More water was required to flood the east border because of the greater permeability of the soils in that field and the smaller rate at which water could be applied.

Long-term detection of Parkinsonian tremor activity from subthalamic nucleus local field potentials.

PubMed

Houston, Brady; Blumenfeld, Zack; Quinn, Emma; Bronte-Stewart, Helen; Chizeck, Howard

2015-01-01

Current deep brain stimulation paradigms deliver continuous stimulation to deep brain structures to ameliorate the symptoms of Parkinson's disease. This continuous stimulation has undesirable side effects and decreases the lifespan of the unit's battery, necessitating earlier replacement. A closed-loop deep brain stimulator that uses brain signals to determine when to deliver stimulation based on the occurrence of symptoms could potentially address these drawbacks of current technology. Attempts to detect Parkinsonian tremor using brain signals recorded during the implantation procedure have been successful. However, the ability of these methods to accurately detect tremor over extended periods of time is unknown. Here we use local field potentials recorded during a deep brain stimulation clinical follow-up visit 1 month after initial programming to build a tremor detection algorithm and use this algorithm to detect tremor in subsequent visits up to 8 months later. Using this method, we detected the occurrence of tremor with accuracies between 68-93%. These results demonstrate the potential of tremor detection methods for efficacious closed-loop deep brain stimulation over extended periods of time.

Magnetically targeted delivery through cartilage

NASA Astrophysics Data System (ADS)

Jafari, Sahar; Mair, Lamar O.; Chowdhury, Sagar; Nacev, Alek; Hilaman, Ryan; Stepanov, Pavel; Baker-McKee, James; Ijanaten, Said; Koudelka, Christian; English, Bradley; Malik, Pulkit; Weinberg, Irving N.

2018-05-01

In this study, we have invented a method of delivering drugs deep into articular cartilage with shaped dynamic magnetic fields acting on small metallic magnetic nanoparticles with polyethylene glycol coating and average diameter of 30 nm. It was shown that transport of magnetic nanoparticles through the entire thickness of bovine articular cartilage can be controlled by a combined alternating magnetic field at 100 Hz frequency and static magnetic field of 0.8 tesla (T) generated by 1" dia. x 2" thick permanent magnet. Magnetic nanoparticles transport through bovine articular cartilage samples was investigated at various settings of magnetic field and time durations. Combined application of an alternating magnetic field and the static field gradient resulted in a nearly 50 times increase in magnetic nanoparticles transport in bovine articular cartilage tissue as compared with static field conditions. This method can be applied to locally deliver therapeutic-loaded magnetic nanoparticles deep into articular cartilage to prevent cartilage degeneration and promote cartilage repair in osteoarthritis.

The Local Group: the ultimate deep field

NASA Astrophysics Data System (ADS)

Boylan-Kolchin, Michael; Weisz, Daniel R.; Bullock, James S.; Cooper, Michael C.

2016-10-01

Near-field cosmology - using detailed observations of the Local Group and its environs to study wide-ranging questions in galaxy formation and dark matter physics - has become a mature and rich field over the past decade. There are lingering concerns, however, that the relatively small size of the present-day Local Group (˜2 Mpc diameter) imposes insurmountable sample-variance uncertainties, limiting its broader utility. We consider the region spanned by the Local Group's progenitors at earlier times and show that it reaches 3 arcmin ≈ 7 comoving Mpc in linear size (a volume of ≈350 Mpc3) at z = 7. This size at early cosmic epochs is large enough to be representative in terms of the matter density and counts of dark matter haloes with Mvir(z = 7) ≲ 2 × 109 M⊙. The Local Group's stellar fossil record traces the cosmic evolution of galaxies with 103 ≲ M⋆(z = 0)/M⊙ ≲ 109 (reaching M1500 > -9 at z ˜ 7) over a region that is comparable to or larger than the Hubble Ultra-Deep Field (HUDF) for the entire history of the Universe. In the JWST era, resolved stellar populations will probe regions larger than the HUDF and any deep JWST fields, further enhancing the value of near-field cosmology.

Assessing the temporal stability of spatial patterns of soil apparent electrical conductivity using geophysical methods

NASA Astrophysics Data System (ADS)

De Caires, Sunshine A.; Wuddivira, Mark N.; Bekele, Isaac

2014-10-01

Cocoa remains in the same field for decades, resulting in plantations dominated with aging trees growing on variable and depleted soils. We determined the spatio-temporal variability of key soil properties in a (5.81 ha) field from the International Cocoa Genebank, Trinidad using geophysical methods. Multi-year (2008-2009) measurements of apparent electrical conductivity at 0-0.75 m (shallow) and 0.75-1.5 m (deep) were conducted. Apparent electrical conductivity at deep and shallow gave the strongest linear correlation with clay-silt content (R = 0.67 and R = 0.78, respectively) and soil solution electrical conductivity (R = 0.76 and R = 0.60, respectively). Spearman rank correlation coefficients ranged between 0.89-0.97 and 0.81- 0.95 for apparent electrical conductivity at deep and shallow, respectively, signifying a strong linear dependence between measurement days. Thus, in the humid tropics, cocoa fields with thick organic litter layer and relatively dense understory cover, experience minimal fluctuations in transient properties of soil water and temperature at the topsoil resulting in similarly stable apparent electrical conductivity at shallow and deep. Therefore, apparent electrical conductivity at shallow, which covers the depth where cocoa feeder roots concentrate, can be used as a fertility indicator and to develop soil zones for efficient application of inputs and management of cocoa fields.

Smoldering Remediation of Coal-Tar-Contaminated Soil: Pilot Field Tests of STAR.

PubMed

Scholes, Grant C; Gerhard, Jason I; Grant, Gavin P; Major, David W; Vidumsky, John E; Switzer, Christine; Torero, Jose L

2015-12-15

Self-sustaining treatment for active remediation (STAR) is an emerging, smoldering-based technology for nonaqueous-phase liquid (NAPL) remediation. This work presents the first in situ field evaluation of STAR. Pilot field tests were performed at 3.0 m (shallow test) and 7.9 m (deep test) below ground surface within distinct lithological units contaminated with coal tar at a former industrial facility. Self-sustained smoldering (i.e., after the in-well ignition heater was terminated) was demonstrated below the water table for the first time. The outward propagation of a NAPL smoldering front was mapped, and the NAPL destruction rate was quantified in real time. A total of 3700 kg of coal tar over 12 days in the shallow test and 860 kg over 11 days in the deep test was destroyed; less than 2% of total mass removed was volatilized. Self-sustaining propagation was relatively uniform radially outward in the deep test, achieving a radius of influence of 3.7 m; strong permeability contrasts and installed barriers influenced the front propagation geometry in the shallow test. Reductions in soil hydrocarbon concentrations of 99.3% and 97.3% were achieved in the shallow and deep tests, respectively. Overall, this provides the first field evaluation of STAR and demonstrates that it is effective in situ and under a variety of conditions and provides the information necessary for designing the full-scale site treatment.

Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Zulia Mayari; Papuga, Shirley Anne; Swetish, Jessica Blaine; van Leeuwen, Willem Jan Dirk; Szutu, Daphne; Hartfield, Kyle

2014-05-01

As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.

The JWST North Ecliptic Pole Survey Field for Time-domain Studies

NASA Astrophysics Data System (ADS)

Jansen, Rolf A.; Alpaslan, Mehmet; Ashby, Matthew; Ashcraft, Teresa; Cohen, Seth H.; Condon, James J.; Conselice, Christopher; Ferrara, Andrea; Frye, Brenda L.; Grogin, Norman A.; Hammel, Heidi B.; Hathi, Nimish P.; Joshi, Bhavin; Kim, Duho; Koekemoer, Anton M.; Mechtley, Matt; Milam, Stefanie N.; Rodney, Steven A.; Rutkowski, Michael J.; Strolger, Louis-Gregory; Trujillo, Chadwick A.; Willmer, Christopher; Windhorst, Rogier A.; Yan, Haojing

2017-01-01

The JWST North Ecliptic Pole (NEP) Survey field is located within JWST's northern Continuous Viewing Zone, will span ˜14‧ in diameter (˜10‧ with NIRISS coverage) and will be roughly circular in shape (initially sampled during Cycle 1 at 4 distinct orientations with JWST/NIRCam's 4.4‧×2.2‧ FoV —the JWST “windmill”) and will have NIRISS slitless grism spectroscopy taken in parallel, overlapping an alternate NIRCam orientation. This is the only region in the sky where JWST can observe a clean extragalactic deep survey field (free of bright foreground stars and with low Galactic foreground extinction AV) at arbitrary cadence or at arbitrary orientation. This will crucially enable a wide range of new and exciting time-domain science, including high redshift transient searches and monitoring (e.g., SNe), variability studies from Active Galactic Nuclei to brown dwarf atmospheres, as well as proper motions of extreme scattered Kuiper Belt and Oort Cloud Objects, and of nearby Galactic brown dwarfs, low-mass stars, and ultracool white dwarfs. We therefore welcome and encourage follow-up through GO programs of the initial GTO observations to realize its potential as a JWST time-domain community field. The JWST NEP Survey field was selected from an analysis of WISE 3.4+4.6 micron, 2MASS JHKs, and SDSS ugriz source counts and of Galactic foreground extinction, and is one of very few such ˜10‧ fields that are devoid of sources brighter than mAB = 16 mag. We have secured deep (mAB ˜ 26 mag) wide-field (˜23‧×25‧) Ugrz images of this field and its surroundings with LBT/LBC. We also expect that deep MMT/MMIRS YJHK images, deep 8-12 GHz VLA radio observations (pending), and possibly HST ACS/WFC and WFC3/UVIS ultraviolet-visible images will be available before JWST launches in Oct 2018.

The JWST North Ecliptic Pole Survey Field for Time-domain Studies

NASA Astrophysics Data System (ADS)

Jansen, Rolf A.; Webb Medium Deep Fields IDS GTO Team, the NEPTDS-VLA/VLBA Team, and the NEPTDS-Chandra Team

2017-06-01

The JWST North Ecliptic Pole (NEP) Survey field is located within JWST's northern Continuous Viewing Zone, will span ~14‧ in diameter (~10‧ with NIRISS coverage) and will be roughly circular in shape (initially sampled during Cycle 1 at 4 distinct orientations with JWST/NIRCam's 4.4‧×2.2‧ FoV —the JWST "windmill") and will have NIRISS slitless grism spectroscopy taken in parallel, overlapping an alternate NIRCam orientation. This is the only region in the sky where JWST can observe a clean extragalactic deep survey field (free of bright foreground stars and with low Galactic foreground extinction AV) at arbitrary cadence or at arbitrary orientation. This will crucially enable a wide range of new and exciting time-domain science, including high redshift transient searches and monitoring (e.g., SNe), variability studies from Active Galactic Nuclei to brown dwarf atmospheres, as well as proper motions of extreme scattered Kuiper Belt and Oort Cloud Objects, and of nearby Galactic brown dwarfs, low-mass stars, and ultracool white dwarfs. We therefore welcome and encourage follow-up through GO programs of the initial GTO observations to realize its potential as a JWST time-domain community field. The JWST NEP Survey field was selected from an analysis of WISE 3.4+4.6 μm, 2MASS JHKs, and SDSS ugriz source counts and of Galactic foreground extinction, and is one of very few such ~10‧ fields that are devoid of sources brighter than mAB = 16 mag. We have secured deep (mAB ~ 26 mag) wide-field (~23‧×25‧) Ugrz images of this field and its surroundings with LBT/LBC. We also expect that deep MMT/MMIRS YJHK images, deep 3-4.5 GHz VLA and VLBA radio observations, and possibly HST ACS/WFC and WFC3/UVIS ultraviolet-visible (pending) and Chandra/ACIS X-ray (pending) images will be available before JWST launches in Oct 2018.

THE MULTIWAVELENGTH SURVEY BY YALE-CHILE (MUSYC): DEEP MEDIUM-BAND OPTICAL IMAGING AND HIGH-QUALITY 32-BAND PHOTOMETRIC REDSHIFTS IN THE ECDF-S

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cardamone, Carolin N.; Van Dokkum, Pieter G.; Urry, C. Megan

2010-08-15

We present deep optical 18-medium-band photometry from the Subaru telescope over the {approx}30' x 30' Extended Chandra Deep Field-South, as part of the Multiwavelength Survey by Yale-Chile (MUSYC). This field has a wealth of ground- and space-based ancillary data, and contains the GOODS-South field and the Hubble Ultra Deep Field. We combine the Subaru imaging with existing UBVRIzJHK and Spitzer IRAC images to create a uniform catalog. Detecting sources in the MUSYC 'BVR' image we find {approx}40,000 galaxies with R {sub AB} < 25.3, the median 5{sigma} limit of the 18 medium bands. Photometric redshifts are determined using the EAzYmore » code and compared to {approx}2000 spectroscopic redshifts in this field. The medium-band filters provide very accurate redshifts for the (bright) subset of galaxies with spectroscopic redshifts, particularly at 0.1 < z < 1.2 and at z {approx}> 3.5. For 0.1 < z < 1.2, we find a 1{sigma} scatter in {Delta}z/(1 + z) of 0.007, similar to results obtained with a similar filter set in the COSMOS field. As a demonstration of the data quality, we show that the red sequence and blue cloud can be cleanly identified in rest-frame color-magnitude diagrams at 0.1 < z < 1.2. We find that {approx}20% of the red sequence galaxies show evidence of dust emission at longer rest-frame wavelengths. The reduced images, photometric catalog, and photometric redshifts are provided through the public MUSYC Web site.« less

SELFI: an object-based, Bayesian method for faint emission line source detection in MUSE deep field data cubes

NASA Astrophysics Data System (ADS)

Meillier, Céline; Chatelain, Florent; Michel, Olivier; Bacon, Roland; Piqueras, Laure; Bacher, Raphael; Ayasso, Hacheme

2016-04-01

We present SELFI, the Source Emission Line FInder, a new Bayesian method optimized for detection of faint galaxies in Multi Unit Spectroscopic Explorer (MUSE) deep fields. MUSE is the new panoramic integral field spectrograph at the Very Large Telescope (VLT) that has unique capabilities for spectroscopic investigation of the deep sky. It has provided data cubes with 324 million voxels over a single 1 arcmin2 field of view. To address the challenge of faint-galaxy detection in these large data cubes, we developed a new method that processes 3D data either for modeling or for estimation and extraction of source configurations. This object-based approach yields a natural sparse representation of the sources in massive data fields, such as MUSE data cubes. In the Bayesian framework, the parameters that describe the observed sources are considered random variables. The Bayesian model leads to a general and robust algorithm where the parameters are estimated in a fully data-driven way. This detection algorithm was applied to the MUSE observation of Hubble Deep Field-South. With 27 h total integration time, these observations provide a catalog of 189 sources of various categories and with secured redshift. The algorithm retrieved 91% of the galaxies with only 9% false detection. This method also allowed the discovery of three new Lyα emitters and one [OII] emitter, all without any Hubble Space Telescope counterpart. We analyzed the reasons for failure for some targets, and found that the most important limitation of the method is when faint sources are located in the vicinity of bright spatially resolved galaxies that cannot be approximated by the Sérsic elliptical profile. The software and its documentation are available on the MUSE science web service (muse-vlt.eu/science).

A MULTIWAVELENGTH STUDY OF TADPOLE GALAXIES IN THE HUBBLE ULTRA DEEP FIELD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straughn, Amber N.; Eufrasio, Rafael T.; Gardner, Jonathan P.

2015-12-01

Multiwavelength data are essential in order to provide a complete picture of galaxy evolution and to inform studies of galaxies’ morphological properties across cosmic time. Here we present the results of a multiwavelength investigation of the morphologies of “tadpole” galaxies at intermediate redshift (0.314 < z < 3.175) in the Hubble Ultra Deep Field. These galaxies were previously selected from deep Hubble Space Telescope (HST) F775W data based on their distinct asymmetric knot-plus-tail morphologies. Here we use deep Wide Field Camera 3 near-infrared imaging in addition to the HST optical data in order to study the rest-frame UV/optical morphologies ofmore » these galaxies across the redshift range 0.3 < z < 3.2. This study reveals that the majority of these galaxies do retain their general asymmetric morphology in the rest-frame optical over this redshift range, if not the distinct “tadpole” shape. The average stellar mass of tadpole galaxies is lower than that of field galaxies, with the effect being slightly greater at higher redshift within the errors. Estimated from spectral energy distribution fits, the average age of tadpole galaxies is younger than that of field galaxies in the lower-redshift bin, and the average metallicity is lower (whereas the specific star formation rate for tadpoles is roughly the same as field galaxies across the redshift range probed here). These average effects combined support the conclusion that this subset of galaxies is in an active phase of assembly, either late-stage merging or cold gas accretion causing localized clumpy star formation.« less

Magnetically tunable oil droplet lens of deep-sea shrimp

NASA Astrophysics Data System (ADS)

Iwasaka, M.; Hirota, N.; Oba, Y.

2018-05-01

In this study, the tunable properties of a bio-lens from a deep-sea shrimp were investigated for the first time using magnetic fields. The skin of the shrimp exhibited a brilliantly colored reflection of incident white light. The light reflecting parts and the oil droplets in the shrimp's skin were observed in a glass slide sample cell using a digital microscope that operated in the bore of two superconducting magnets (maximum strengths of 5 and 13 T). In the ventral skin of the shrimp, which contained many oil droplets, some comparatively large oil droplets (50 to 150 μm in diameter) were present. A distinct response to magnetic fields was found in these large oil droplets. Further, the application of the magnetic fields to the sample cell caused a change in the size of the oil droplets. The phenomena observed in this work indicate that the oil droplets of deep sea shrimp can act as lenses in which the optical focusing can be modified via the application of external magnetic fields. The results of this study will make it possible to fabricate bio-inspired soft optical devices in future.

The Charging of Composites in the Space Environment

NASA Technical Reports Server (NTRS)

Czepiela, Steven A.

1997-01-01

Deep dielectric charging and subsequent electrostatic discharge in composite materials used on spacecraft have become greater concerns since composite materials are being used more extensively as main structural components. Deep dielectric charging occurs when high energy particles penetrate and deposit themselves in the insulating material of spacecraft components. These deposited particles induce an electric field in the material, which causes the particles to move and thus changes the electric field. The electric field continues to change until a steady state is reached between the incoming particles from the space environment and the particles moving away due to the electric field. An electrostatic discharge occurs when the electric field is greater than the dielectric strength of the composite material. The goal of the current investigation is to investigate deep dielectric charging in composite materials and ascertain what modifications have to be made to the composite properties to alleviate any breakdown issues. A 1-D model was created. The space environment, which is calculated using the Environmental Workbench software, the composite material properties, and the electric field and voltage boundary conditions are input into the model. The output from the model is the charge density, electric field, and voltage distributions as functions of the depth into the material and time. Analysis using the model show that there should be no deep dielectric charging problem with conductive composites such as carbon fiber/epoxy. With insulating materials such as glass fiber/epoxy, Kevlar, and polymers, there is also no concern of deep dielectric charging problems with average day-to-day particle fluxes. However, problems can arise during geomagnetic substorms and solar particle events where particle flux levels increase by several orders of magnitude, and thus increase the electric field in the material by several orders of magnitude. Therefore, the second part of this investigation was an experimental attempt to measure the continuum electrical properties of a carbon fiber/epoxy composite, and to create a composite with tailorable conductivity without affecting its mechanical properties. The measurement of the conductivity and dielectric strength of carbon fiber/epoxy composites showed that these properties are surface layer dominated and difficult to measure. In the second experimental task, the conductivity of a glass fiber/epoxy composite was increased by 3 orders of magnitude, dielectric constant was increased approximately by a factor of 16, with minimal change to the mechanical properties, by adding conductive carbon black to the epoxy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Constable, S.A.; Orange, Arnold S.; Hoversten, G. Michael

Induction in electrically conductive seawater attenuates themagnetotelluric (MT) fields and, coupled with a minimum around 1 Hz inthe natural magnetic field spectrum, leads to a dramatic loss of electricand magnetic field power on the sea floor at periods shorter than 1000 s,For this reason the marine MT method traditionally has been used only atperiods of 10(3) to 10(5) s to probe deep mantle structure; rarely does asea-floor MT response extend to a 100-s period. To be useful for mappingcontinental shelf structure at depths relevant to petroleum exploration,however, MT measurements need to be made at periods between 1 and 1000 s.Thismore » can be accomplished using ac-coupled sensors, induction coils forthe magnetic field, and an electric field amplifier developed for marinecontrolled-source applications. The electrically quiet sea floor allowsthe attenuated electric field to be amplified greatly before recording;in deep (l-km) water, motional noise in magnetic field sensors appearsnot to be a problem. In shallower water, motional noise does degrade themagnetic measurement, but sea-floor magnetic records can be replaced byland recordings, producing an effective sea-surface MT response. Fieldtrials of such equipment in l-km-deep water produced good-quality MTresponses at periods of 3 to 1000 s: in shallower water, responses to afew hertz can be obtained. Using an autonomous sea-floor data loggerdeveloped at Scripps Institution of Oceanography, marine surveys of 50 to100 sites are feasible.« less

Project DEEP STEAM: Fourth meeting of the technical advisory panel

NASA Astrophysics Data System (ADS)

Fox, R. L.; Donaldson, A. B.; Eisenhawer, S. W.; Hart, C. M.; Johnson, D. R.; Mulac, A. J.; Wayland, J. R.; Weirick, L. J.

1981-07-01

The status of project DEEP STEAM was reviewed. Proceedings, are divided into five main sections: (1) the injection string modification program; (2) the downhole steam generator program; (3) supporting activities; (4) field testing; and (5) recommendations and discussion.

The JPL roadmap for Deep Space navigation

NASA Technical Reports Server (NTRS)

Martin-Mur, Tomas J.; Abraham, Douglas S.; Berry, David; Bhaskaran, Shyam; Cesarone, Robert J.; Wood, Lincoln

2006-01-01

This paper reviews the tentative set of deep space missions that will be supported by NASA's Deep Space Mission System in the next twenty-five years, and extracts the driving set of navigation capabilities that these missions will require. There will be many challenges including the support of new mission navigation approaches such as formation flying and rendezvous in deep space, low-energy and low-thrust orbit transfers, precise landing and ascent vehicles, and autonomous navigation. Innovative strategies and approaches will be needed to develop and field advanced navigation capabilities.

MUSE deep-fields: the Ly α luminosity function in the Hubble Deep Field-South at 2.91 < z < 6.64

NASA Astrophysics Data System (ADS)

Drake, Alyssa B.; Guiderdoni, Bruno; Blaizot, Jérémy; Wisotzki, Lutz; Herenz, Edmund Christian; Garel, Thibault; Richard, Johan; Bacon, Roland; Bina, David; Cantalupo, Sebastiano; Contini, Thierry; den Brok, Mark; Hashimoto, Takuya; Marino, Raffaella Anna; Pelló, Roser; Schaye, Joop; Schmidt, Kasper B.

2017-10-01

We present the first estimate of the Ly α luminosity function using blind spectroscopy from the Multi Unit Spectroscopic Explorer, MUSE, in the Hubble Deep Field-South. Using automatic source-detection software, we assemble a homogeneously detected sample of 59 Ly α emitters covering a flux range of -18.0 < log10 (F) < -16.3 (erg s-1 cm-2), corresponding to luminosities of 41.4 < log10 (L) < 42.8 (erg s-1). As recent studies have shown, Ly α fluxes can be underestimated by a factor of 2 or more via traditional methods, and so we undertake a careful assessment of each object's Ly α flux using a curve-of-growth analysis to account for extended emission. We describe our self-consistent method for determining the completeness of the sample, and present an estimate of the global Ly α luminosity function between redshifts 2.91 < z < 6.64 using the 1/Vmax estimator. We find that the luminosity function is higher than many number densities reported in the literature by a factor of 2-3, although our result is consistent at the 1σ level with most of these studies. Our observed luminosity function is also in good agreement with predictions from semi-analytic models, and shows no evidence for strong evolution between the high- and low-redshift halves of the data. We demonstrate that one's approach to Ly α flux estimation does alter the observed luminosity function, and caution that accurate flux assessments will be crucial in measurements of the faint-end slope. This is a pilot study for the Ly α luminosity function in the MUSE deep-fields, to be built on with data from the Hubble Ultra Deep Field that will increase the size of our sample by almost a factor of 10.

Deep Flaw Detection with Giant Magnetoresistive (GMR) Based Self-Nulling Probe

NASA Technical Reports Server (NTRS)

Wincheski, Buzz; Namkung, Min

2004-01-01

In this paper a design modification to the Very-Low Frequency GMR Based Self-Nulling Probe has been presented to enable improved signal to noise ratio for deeply buried flaws. The design change consists of incorporating a feedback coil in the center of the flux focusing lens. The use of the feedback coil enables cancellation of the leakage fields in the center of the probe and biasing of the GMR sensor to a location of high magnetic field sensitivity. The effect of the feedback on the probe output was examined, and experimental results for deep flaw detection were presented. The experimental results show that the modified probe is capable of clearly identifying flaws up to 1 cm deep in aluminum alloy structures.

A Comparison between Deep and Shallow Stress Fields in Korea Using Earthquake Focal Mechanism Inversions and Hydraulic Fracturing Stress Measurements

NASA Astrophysics Data System (ADS)

Lee, Rayeon; Chang, Chandong; Hong, Tae-kyung; Lee, Junhyung; Bae, Seong-Ho; Park, Eui-Seob; Park, Chan

2016-04-01

We are characterizing stress fields in Korea using two types of stress data: earthquake focal mechanism inversions (FMF) and hydraulic fracturing stress measurements (HF). The earthquake focal mechanism inversion data represent stress conditions at 2-20 km depths, whereas the hydraulic fracturing stress measurements, mostly conducted for geotechnical purposes, have been carried out at depths shallower than 1 km. We classified individual stress data based on the World Stress Map quality ranking scheme. A total of 20 FMF data were classified into A-B quality, possibly representing tectonic stress fields. A total of 83 HF data out of compiled 226 data were classified into B-C quality, which we use for shallow stress field characterization. The tectonic stress, revealed from the FMF data, is characterized by a remarkable consistency in its maximum stress (σ1) directions in and around Korea (N79±2° E), indicating a quite uniform deep stress field throughout. On the other hand, the shallow stress field, represented by HF data, exhibits local variations in σ1 directions, possibly due to effects of topography and geologic structures such as faults. Nonetheless, there is a general similarity in σ1 directions between deep and shallow stress fields. To investigate the shallow stress field statistically, we follow 'the mean orientation and wavelength analysis' suggested by Reiter et al. (2014). After the stress pattern analysis, the resulting stress points distribute sporadically over the country, not covering the entire region evenly. In the western part of Korea, the shallow σ1directions are generally uniform with their search radius reaching 100 km, where the average stress direction agrees well with those of the deep tectonic stress. We note two noticeable differences between shallow and deep stresses in the eastern part of Korea. First, the shallow σ1 orientations are markedly non-uniform in the southeastern part of Korea with their search radius less than 25 km. In this region, the average σ1orientation based on the entire B-C quality stress data is calculated to be 77±37° ; however, the average orientation is somewhat meaningless because of the high standard deviation. The southeastern part of Korea consists mainly of Cretaceous sedimentary basin, geologically younger than the rest of the country, where regional scale faults are intensely populated. The highly scattered stress directions in this region may represent the effect of the geologic structures on shallow stress field. Second, shallow σ1 directions in the northeastern part of Korea strike consistently to 135±12° , which is deviated by as much as 56° from the deep tectonic stress direction. This region is characterized by high altitude mountainous topography (an elevation of an order of 1 km) with its major ridge axis in the NW-SE direction. We interpret, as a rule of thumb, that the ridge-perpendicular shallow horizontal stress components may be weak, leading to the ridge-parallel components to be the maximum. Overall, there are similarity and also difference between shallow and deep stress fields. Thus, it will be necessary to differentiate the strategy to tackle the stress-related problems based on their natures.

Deep circulations under simple classes of stratification

NASA Technical Reports Server (NTRS)

Salby, Murry L.

1989-01-01

Deep circulations where the motion field is vertically aligned over one or more scale heights are studied under barotropic and equivalent barotropic stratifications. The study uses two-dimensional equations reduced from the three-dimensional primitive equations in spherical geometry. A mapping is established between the full primitive equations and general shallow water behavior and the correspondence between variables describing deep atmospheric motion and those of shallow water behavior is established.

Space Science

NASA Image and Video Library

2002-04-01

This picture of the galaxy UGC 10214 was was taken by the Advanced Camera for Surveys (ACS), which was installed aboard the Hubble Space Telescope (HST) in March 2002 during HST Servicing Mission 3B (STS-109 mission). Dubbed the "Tadpole," this spiral galaxy is unlike the textbook images of stately galaxies. Its distorted shape was caused by a small interloper, a very blue, compact galaxy visible in the upper left corner of the more massive Tadpole. The Tadpole resides about 420 million light-years away in the constellation Draco. Seen shining through the Tadpole's disk, the tiny intruder is likely a hit-and-run galaxy that is now leaving the scene of the accident. Strong gravitational forces from the interaction created the long tail of debris, consisting of stars and gas that stretch our more than 280,000 light-years. The galactic carnage and torrent of star birth are playing out against a spectacular backdrop: a "wallpaper pattern" of 6,000 galaxies. These galaxies represent twice the number of those discovered in the legendary Hubble Deep Field, the orbiting observatory's "deepest" view of the heavens, taken in 1995 by the Wide Field and planetary camera 2. The ACS picture, however, was taken in one-twelfth of the time it took to observe the original HST Deep Field. In blue light, ACS sees even fainter objects than were seen in the "deep field." The galaxies in the ACS picture, like those in the deep field, stretch back to nearly the begirning of time. Credit: NASA, H. Ford (JHU), G. Illingworth (USCS/LO), M. Clampin (STScI), G. Hartig (STScI), the ACS Science Team, and ESA.

HST/ACS Observations of RR Lyrae Stars in Six Ultra-Deep Fields of M31

NASA Technical Reports Server (NTRS)

Jeffery, E. J.; Smith, E.; Brown, T. M.; Sweigart, A. V.; Kalirai, J. S.; Ferguson, H. C.; Guhathakurta, P.; Renzini, A.; Rich, R. M.

2010-01-01

We present HST/ACS observations of RR Lyrae variable stars in six ultra deep fields of the Andromeda galaxy (M31), including parts of the halo, disk, and giant stellar stream. Past work on the RR Lyrae stars in M31 has focused on various aspects of the stellar populations that make up the galaxy s halo, including their distances and metallicities. This study builds upon this previous work by increasing the spatial coverage (something that has been lacking in previous studies) and by searching for these variable stars in constituents of the galaxy not yet explored. Besides the 55 RR Lyrae stars we found in our initial field located 11kpc from the galactic nucleus, we find additional RR Lyrae stars in four of the remaining five ultra deep fields as follows: 21 in the disk, 24 in the giant stellar stream, 3 in the halo field 21kpc from the galactic nucleus, and 5 in one of the halo fields at 35kpc. No RR Lyrae were found in the second halo field at 35kpc. The RR Lyrae populations of these fields appear to mostly be of Oosterhoff I type, although the 11kpc field appears to be intermediate or mixed. We will discuss the properties of these stars including period and reddening distributions. We calculate metallicities and distances for the stars in each of these fields using different methods and compare the results, to an extent that has not yet been done. We compare these methods not just on RR Lyrae in our M31 fields, but also on a data set of Milky Way field RR Lyrae stars.

Wide Field Imaging of the Hubble Deep Field-South Region III: Catalog

NASA Technical Reports Server (NTRS)

Palunas, Povilas; Collins, Nicholas R.; Gardner, Jonathan P.; Hill, Robert S.; Malumuth, Eliot M.; Rhodes, Jason; Teplitz, Harry I.; Woodgate, Bruce E.

2002-01-01

We present 1/2 square degree uBVRI imaging around the Hubble Deep Field - South. These data have been used in earlier papers to examine the QSO population and the evolution of the correlation function in the region around the HDF-S. The images were obtained with the Big Throughput Camera at CTIO in September 1998. The images reach 5 sigma limits of u approx. 24.4, B approx. 25.6, V approx. 25.3, R approx. 24.9 and I approx. 23.9. We present a catalog of approx. 22,000 galaxies. We also present number-magnitude counts and a comparison with other observations of the same field. The data presented here are available over the world wide web.

A deep redshift survey of field galaxies. Comments on the reality of the Butcher-Oemler effect

NASA Technical Reports Server (NTRS)

Koo, David C.; Kron, Richard G.

1987-01-01

A spectroscopic survey of over 400 field galaxies has been completed in three fields for which we have deep UBVI photographic photometry. The galaxies typically range from B=20 to 22 and possess redshifts z from 0.1 to 0.5 that are often quite spiky in distribution. Little, if any, luminosity evolution is observed up to redshifts z approx 0.5. By such redshifts, however, an unexpectedly large fraction of luminous galaxies has very blue intrinsic colors that suggest extensive star formation; in contrast, the reddest galaxies still have colors that match those of present-day ellipticals.

An extended moderate-depth contiguous layer of the Chandra Bootes field - additional pointings

NASA Astrophysics Data System (ADS)

Kraft, Ralph

2016-09-01

We propose 150ks (6x25ks) ACIS-I observations to supplement existing X-ray data in XBootes. These new observations will allow the expansion of relatively large contiguous ( 2deg2) region in Bootes covered at 40ks, i.e., 5-8x deeper than the nominal Bootes field. In concert with the recently approved 1.025 Ms Chandra Deep Wide-Field Survey, this additional deep layer of Bootes will (1) provide new insights into the dark matter halos and large-scale structures that host AGN; (2) allow new measurements of the distribution of X-ray luminosities and connections to host galaxy evolution.

Searching for filaments and large-scale structure around DAFT/FADA clusters

NASA Astrophysics Data System (ADS)

Durret, F.; Márquez, I.; Acebrón, A.; Adami, C.; Cabrera-Lavers, A.; Capelato, H.; Martinet, N.; Sarron, F.; Ulmer, M. P.

2016-04-01

Context. Clusters of galaxies are located at the intersection of cosmic filaments and are still accreting galaxies and groups along these preferential directions. However, because of their relatively low contrast on the sky, filaments are difficult to detect (unless a large amount of spectroscopic data are available), and unambiguous detections have been limited until now to relatively low redshifts (z< ~ 0.3). Aims: This project is aimed at searching for extensions and filaments around clusters, traced by galaxies selected to be at the cluster redshift based on the red sequence. In the 0.4

Detection of a possible superluminous supernova in the epoch of reionization

NASA Astrophysics Data System (ADS)

Mould, Jeremy; Abbott, Tim; Cooke, Jeff; Curtin, Chris; Katsiani, Antonios; Koekemoer, Anton; Tescari, Edoardo; Uddin, Syed; Wang, Lifan; Wyithe, Stuaet

2017-04-01

An interesting transient has been detected in one of our three Dark Energy Camera deep fields. Observations of these deep fields take advantage of the high red sensitivity of DECam on the Cerro Tololo Interamerican Observatory Blanco telescope. The survey includes the Y band with rest wavelength 1430{Å} at z = 6. Survey fields (the Prime field 0555-6130, the 16hr field 1600-75 and the SUDSS New Southern Field) are deeper in Y than other infrared surveys. They are circumpolar, allowing all night to be used efficiently, exploiting the moon tolerance of 1 micron observations to minimize conflict with the Dark Energy Survey. As an i-band dropout (meaning that the flux decrement shortward of Lyman alpha is in the i bandpass), the transient we report here is a supernova candidate with z 6, with a luminosity comparable to the brightest known current epoch superluminous supernova (i.e., 2 x 10^11 solar luminosities).

Deep Defects Seen on Visual Fields Spatially Correspond Well to Loss of Retinal Nerve Fiber Layer Seen on Circumpapillary OCT Scans.

PubMed

Mavrommatis, Maria A; Wu, Zhichao; Naegele, Saskia I; Nunez, Jason; De Moraes, Carlos; Ritch, Robert; Hood, Donald C

2018-02-01

To examine the structure-function relationship in glaucoma between deep defects on visual fields (VF) and deep losses in the circumpapillary retinal nerve fiber layer (cpRNFL) on optical coherence tomography (OCT) circle scans. Thirty two glaucomatous eyes with deep VF defects, as defined by at least one test location worse than ≤ -15 dB on the 10-2 and/or 24-2 VF pattern deviation (PD) plots, were included from 87 eyes with "early" glaucoma (i.e., 24-2 mean deviation better than -6 dB). Using the location of the deep VF points and a schematic model, the location of local damage on an OCT circle scan was predicted. The thinnest location of cpRNFL (i.e., deepest loss) was also determined. In 19 of 32 eyes, a region of complete or near complete cpRNFL loss was observed. All 19 of these had deep VF defects on the 24-2 and/or 10-2. All of the 32 eyes with deep VF defects had abnormal cpRNFL regions (red, 1%) and all but 2 had a region of cpRNFL thickness <21 μm. The midpoint of the VF defect and the location of deepest cpRNFL had a 95% limit of agreement within approximately two-thirds of a clock-hour (or 30°) sector (between -22.1° to 25.2°). Individual fovea-to-disc angle (FtoDa) adjustment improved agreement in one eye with an extreme FtoDa. Although studies relating local structural (OCT) and functional (VF) measures typically show poor to moderate correlations, there is good qualitative agreement between the location of deep cpRNFL loss and deep defects on VFs.

The MUSE Hubble Ultra Deep Field Survey. II. Spectroscopic redshifts and comparisons to color selections of high-redshift galaxies

NASA Astrophysics Data System (ADS)

Inami, H.; Bacon, R.; Brinchmann, J.; Richard, J.; Contini, T.; Conseil, S.; Hamer, S.; Akhlaghi, M.; Bouché, N.; Clément, B.; Desprez, G.; Drake, A. B.; Hashimoto, T.; Leclercq, F.; Maseda, M.; Michel-Dansac, L.; Paalvast, M.; Tresse, L.; Ventou, E.; Kollatschny, W.; Boogaard, L. A.; Finley, H.; Marino, R. A.; Schaye, J.; Wisotzki, L.

2017-11-01

We have conducted a two-layered spectroscopic survey (1' × 1' ultra deep and 3' × 3' deep regions) in the Hubble Ultra Deep Field (HUDF) with the Multi Unit Spectroscopic Explorer (MUSE). The combination of a large field of view, high sensitivity, and wide wavelength coverage provides an order of magnitude improvement in spectroscopically confirmed redshifts in the HUDF; i.e., 1206 secure spectroscopic redshifts for Hubble Space Telescope (HST) continuum selected objects, which corresponds to 15% of the total (7904). The redshift distribution extends well beyond z> 3 and to HST/F775W magnitudes as faint as ≈ 30 mag (AB, 1σ). In addition, 132 secure redshifts were obtained for sources with no HST counterparts that were discovered in the MUSE data cubes by a blind search for emission-line features. In total, we present 1338 high quality redshifts, which is a factor of eight increase compared with the previously known spectroscopic redshifts in the same field. We assessed redshifts mainly with the spectral features [O II] at z< 1.5 (473 objects) and Lyα at 2.9

Field Placement Treatments: A Comparative Study

ERIC Educational Resources Information Center

Parkison, Paul T.

2008-01-01

Field placement within teacher education represents a topic of interest for all preservice teacher programs. Present research addresses a set of important questions regarding field placement: (1) What pedagogical methodologies facilitate deep learning during field experiences? (2) Is there a significant difference in treatment effect for…

WHATS-3: An improved flow-through multi-bottle fluid sampler for deep-sea geofluid research

NASA Astrophysics Data System (ADS)

Miyazaki, Junichi; Makabe, Akiko; Matsui, Yohei; Ebina, Naoya; Tsutsumi, Saki; Ishibashi, Jun-ichiro; Chen, Chong; Kaneko, Sho; Takai, Ken; Kawagucci, Shinsuke

2017-06-01

Deep-sea geofluid systems, such as hydrothermal vents and cold seeps, are key to understanding subseafloor environments of Earth. Fluid chemistry, especially, provides crucial information towards elucidating the physical, chemical and biological processes that occur in these ecosystems. To accurately assess fluid and gas properties of deep-sea geofluids, well-designed pressure-tight fluid samplers are indispensable and as such they are important assets of deep-sea geofluid research. Here, the development of a new flow-through, pressure-tight fluid sampler capable of four independent sampling events (two subsamples for liquid and gas analyses from each) is reported. This new sampler, named WHATS-3, is a new addition to the WHATS-series samplers and a major upgrade from the previous WHATS-2 sampler with improvements in sample number, valve operational time, physical robustness, and ease of maintenance. Routine laboratory-based pressure tests proved that it is suitable for operation up to 35 MPa pressure. Successful field tests of the new sampler were also carried out in five hydrothermal fields, two in Indian Ocean and three in Okinawa Trough (max. depth 3,300 m). Relations of Mg and major ion species demonstrated bimodal mixing trends between a hydrothermal fluid and seawater, confirming the high-quality of fluids sampled. The newly developed WHATS-3 sampler is well-balanced in sampling capability, field usability, and maintenance feasibility, and can serve as one of the best geofluid samplers available at present to conduct efficient research of deep-sea geofluid systems.

Opportunities and obstacles for deep learning in biology and medicine.

PubMed

Ching, Travers; Himmelstein, Daniel S; Beaulieu-Jones, Brett K; Kalinin, Alexandr A; Do, Brian T; Way, Gregory P; Ferrero, Enrico; Agapow, Paul-Michael; Zietz, Michael; Hoffman, Michael M; Xie, Wei; Rosen, Gail L; Lengerich, Benjamin J; Israeli, Johnny; Lanchantin, Jack; Woloszynek, Stephen; Carpenter, Anne E; Shrikumar, Avanti; Xu, Jinbo; Cofer, Evan M; Lavender, Christopher A; Turaga, Srinivas C; Alexandari, Amr M; Lu, Zhiyong; Harris, David J; DeCaprio, Dave; Qi, Yanjun; Kundaje, Anshul; Peng, Yifan; Wiley, Laura K; Segler, Marwin H S; Boca, Simina M; Swamidass, S Joshua; Huang, Austin; Gitter, Anthony; Greene, Casey S

2018-04-01

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. © 2018 The Authors.

Opportunities and obstacles for deep learning in biology and medicine

PubMed Central

2018-01-01

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems—patient classification, fundamental biological processes and treatment of patients—and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. PMID:29618526

Models of gravitational lens candidates from Space Warps CFHTLS

NASA Astrophysics Data System (ADS)

Küng, Rafael; Saha, Prasenjit; Ferreras, Ignacio; Baeten, Elisabeth; Coles, Jonathan; Cornen, Claude; Macmillan, Christine; Marshall, Phil; More, Anupreeta; Oswald, Lucy; Verma, Aprajita; Wilcox, Julianne K.

2018-03-01

We report modelling follow-up of recently discovered gravitational-lens candidates in the Canada France Hawaii Telescope Legacy Survey. Lens modelling was done by a small group of specially interested volunteers from the Space Warps citizen-science community who originally found the candidate lenses. Models are categorized according to seven diagnostics indicating (a) the image morphology and how clear or indistinct it is, (b) whether the mass map and synthetic lensed image appear to be plausible, and (c) how the lens-model mass compares with the stellar mass and the abundance-matched halo mass. The lensing masses range from ˜1011 to >1013 M⊙. Preliminary estimates of the stellar masses show a smaller spread in stellar mass (except for two lenses): a factor of a few below or above ˜1011 M⊙. Therefore, we expect the stellar-to-total mass fraction to decline sharply as lensing mass increases. The most massive system with a convincing model is J1434+522 (SW 05). The two low-mass outliers are J0206-095 (SW 19) and J2217+015 (SW 42); if these two are indeed lenses, they probe an interesting regime of very low star formation efficiency. Some improvements to the modelling software (SpaghettiLens), and discussion of strategies regarding scaling to future surveys with more and frequent discoveries, are included.

The Faint End of the z = 5 Quasar Luminosity Function from the CFHTLS

NASA Astrophysics Data System (ADS)

McGreer, Ian D.; Fan, Xiaohui; Jiang, Linhua; Cai, Zheng

2018-03-01

We present results from a spectroscopic survey of z ∼ 5 quasars in the CFHT Legacy Survey. Using both optical color selection and a likelihood method, we select 97 candidates over an area of 105 deg2 to a limit of i AB < 23.2, and 7 candidates in the range 23.2 < i AB < 23.7 over an area of 18.5 deg2. Spectroscopic observations for 43 candidates were obtained with Gemini, MMT, and Large Binocular Telescope, of which 37 are z > 4 quasars. This sample extends measurements of the quasar luminosity function ∼1.5 mag fainter than our previous work in Sloan Digital Sky Survey Stripe 82. The resulting luminosity function is in good agreement with our previous results, and suggests that the faint end slope is not steep. We perform a detailed examination of our survey completeness, particularly the impact of the Lyα emission assumed in our quasar spectral models, and find hints that the observed Lyα emission from faint z ∼ 5 quasars is weaker than for z ∼ 3 quasars at a similar luminosity. Our results strongly disfavor a significant contribution of faint quasars to the hydrogen-ionizing background at z = 5.

Field performance of self-siphon sediment cleansing set for sediment removal in deep CSO chamber.

PubMed

Zhou, Yongchao; Zhang, Yiping; Tang, Ping

2013-01-01

This paper presents a study of the self-siphon sediment cleansing set (SSCS), a system designed to remove sediment from the deep combined sewer overflow (CSO) chamber during dry-weather periods. In order to get a better understanding of the sediment removal effectiveness and operational conditions of the SSCS system, we carried out a full-scale field study and comparison analysis on the sediment depth changes in the deep CSO chambers under the conditions with and without the SSCS. The field investigation results demonstrated that the SSCS drains the dry-weather flow that accumulated for 50-57 min from the sewer channel to the intercepting system in about 10 min. It is estimated that the bed shear stress in the CSO chamber and sewer channel is improved almost 25 times on average. The SSCS acts to remove the near bed solids with high pollution load efficiently. Moreover, it cleans up not only the new sediment layer but also part of the previously accumulated sediment.

Field testing of stiffened deep cement mixing piles under lateral cyclic loading

NASA Astrophysics Data System (ADS)

Raongjant, Werasak; Jing, Meng

2013-06-01

Construction of seaside and underground wall bracing often uses stiffened deep cement mixed columns (SDCM). This research investigates methods used to improve the level of bearing capacity of these SDCM when subjected to cyclic lateral loading via various types of stiffer cores. Eight piles, two deep cement mixed piles and six stiffened deep cement mixing piles with three different types of cores, H shape cross section prestressed concrete, steel pipe, and H-beam steel, were embedded though soft clay into medium-hard clay on site in Thailand. Cyclic horizontal loading was gradually applied until pile failure and the hysteresis loops of lateral load vs. lateral deformation were recorded. The lateral carrying capacities of the SDCM piles with an H-beam steel core increased by 3-4 times that of the DCM piles. This field research clearly shows that using H-beam steel as a stiffer core for SDCM piles is the best method to improve its lateral carrying capacity, ductility and energy dissipation capacity.

Laminar Neural Field Model of Laterally Propagating Waves of Orientation Selectivity

PubMed Central

2015-01-01

We construct a laminar neural-field model of primary visual cortex (V1) consisting of a superficial layer of neurons that encode the spatial location and orientation of a local visual stimulus coupled to a deep layer of neurons that only encode spatial location. The spatially-structured connections in the deep layer support the propagation of a traveling front, which then drives propagating orientation-dependent activity in the superficial layer. Using a combination of mathematical analysis and numerical simulations, we establish that the existence of a coherent orientation-selective wave relies on the presence of weak, long-range connections in the superficial layer that couple cells of similar orientation preference. Moreover, the wave persists in the presence of feedback from the superficial layer to the deep layer. Our results are consistent with recent experimental studies that indicate that deep and superficial layers work in tandem to determine the patterns of cortical activity observed in vivo. PMID:26491877

Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement

USGS Publications Warehouse

Bern, Carleton R.; Breit, George N.; Healy, Richard W.; Zupancic, John W.; Hammack, Richard

2013-01-01

Water co-produced with coal-bed methane (CBM) in the semi-arid Powder River Basin of Wyoming and Montana commonly has relatively low salinity and high sodium adsorption ratios that can degrade soil permeability where used for irrigation. Nevertheless, a desire to derive beneficial use from the water and a need to dispose of large volumes of it have motivated the design of a deep subsurface drip irrigation (SDI) system capable of utilizing that water. Drip tubing is buried 92 cm deep and irrigates at a relatively constant rate year-round, while evapotranspiration by the alfalfa and grass crops grown is seasonal. We use field data from two sites and computer simulations of unsaturated flow to understand water and solute movements in the SDI fields. Combined irrigation and precipitation exceed potential evapotranspiration by 300-480 mm annually. Initially, excess water contributes to increased storage in the unsaturated zone, and then drainage causes cyclical rises in the water table beneath the fields. Native chloride and nitrate below 200 cm depth are leached by the drainage. Some CBM water moves upward from the drip tubing, drawn by drier conditions above. Chloride from CBM water accumulates there as root uptake removes the water. Year over year accumulations indicated by computer simulations illustrate that infiltration of precipitation water from the surface only partially leaches such accumulations away. Field data show that 7% and 27% of added chloride has accumulated above the drip tubing in an alfalfa and grass field, respectively, following 6 years of irrigation. Maximum chloride concentrations in the alfalfa field are around 45 cm depth but reach the surface in parts of the grass field, illustrating differences driven by crop physiology. Deep SDI offers a means of utilizing marginal quality irrigation waters and managing the accumulation of their associated solutes in the crop rooting zone.

Do Students Develop towards More Deep Approaches to Learning during Studies? A Systematic Review on the Development of Students' Deep and Surface Approaches to Learning in Higher Education

ERIC Educational Resources Information Center

Asikainen, Henna; Gijbels, David

2017-01-01

The focus of the present paper is on the contribution of the research in the student approaches to learning tradition. Several studies in this field have started from the assumption that students' approaches to learning develop towards more deep approaches to learning in higher education. This paper reports on a systematic review of longitudinal…

Deep Learning for Computer Vision: A Brief Review

PubMed Central

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

Deep-subwavelength imaging of both electric and magnetic localized optical fields by plasmonic campanile nanoantenna

DOE PAGES

Caselli, Niccolò; La China, Federico; Bao, Wei; ...

2015-06-05

Tailoring the electromagnetic field at the nanoscale has led to artificial materials exhibiting fascinating optical properties unavailable in naturally occurring substances. Besides having fundamental implications for classical and quantum optics, nanoscale metamaterials provide a platform for developing disruptive novel technologies, in which a combination of both the electric and magnetic radiation field components at optical frequencies is relevant to engineer the light-matter interaction. Thus, an experimental investigation of the spatial distribution of the photonic states at the nanoscale for both field components is of crucial importance. Here we experimentally demonstrate a concomitant deep-subwavelength near-field imaging of the electric and magneticmore » intensities of the optical modes localized in a photonic crystal nanocavity. We take advantage of the “campanile tip”, a plasmonic near-field probe that efficiently combines broadband field enhancement with strong far-field to near-field coupling. In conclusion, by exploiting the electric and magnetic polarizability components of the campanile tip along with the perturbation imaging method, we are able to map in a single measurement both the electric and magnetic localized near-field distributions.« less

Vorticity and Vertical Motions Diagnosed from Satellite Deep-Layer Temperatures. Revised

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Lapenta, William M.; Robertson, Franklin R.

1994-01-01

Spatial fields of satellite-measured deep-layer temperatures are examined in the context of quasigeostrophic theory. It is found that midtropospheric geostrophic vorticity and quasigeostrophic vertical motions can be diagnosed from microwave temperature measurements of only two deep layers. The lower- ( 1000-400 hPa) and upper- (400-50 hPa) layer temperatures are estimated from limb-corrected TIROS-N Microwave Sounding Units (MSU) channel 2 and 3 data, spatial fields of which can be used to estimate the midtropospheric thermal wind and geostrophic vorticity fields. Together with Trenberth's simplification of the quasigeostrophic omega equation, these two quantities can be then used to estimate the geostrophic vorticity advection by the thermal wind, which is related to the quasigeostrophic vertical velocity in the midtroposphere. Critical to the technique is the observation that geostrophic vorticity fields calculated from the channel 3 temperature features are very similar to those calculated from traditional, 'bottom-up' integrated height fields from radiosonde data. This suggests a lack of cyclone-scale height features near the top of the channel 3 weighting function, making the channel 3 cyclone-scale 'thickness' features approximately the same as height features near the bottom of the weighting function. Thus, the MSU data provide observational validation of the LID (level of insignificant dynamics) assumption of Hirshberg and Fritsch.

The Pan-STARRS 1 Medium Deep Field Variable Star Catalog

NASA Astrophysics Data System (ADS)

Flewelling, Heather

2016-01-01

We present the first Pan-STARRS 1 Medium Deep Field Variable Star Catalog (PS1-MDF-VSC). The Pan-STARRS 1 (PS1) telescope is a 1.8 meter survey telescope with a 1.4 Gigapixel camera, located in Haleakala, Hawaii. The Medium Deep survey, which consists of 10 fields located uniformly across the sky, totaling 70 square degrees, is observed each night, in 2-3 filters per field, with 8 exposures per filter, resulting in 3000-4000 data points per star over a time span of 3.5 years. To find the variables, we select objects with > 200 detections, and remove those flagged as saturated. No other cuts are used. There are approximately 2.4 million objects that fit this criteria, with magnitudes between 13th and 24th. These objects are then passed through a lomb-scargle fitting routine to determine periodicity. After a periodicity cut, the candidates are classified by eye into different types of variable stars. We have identified several thousand periodic variable stars, with periods ranging between a few minutes to a few days. We compare our findings to the variable star catalogs within Vizier and AAVSO. In particular, for field MD02, we recover all the variables that are faint in Vizier, and we find good agreement with the periods reported in Vizier.

The Great Observatories Origins Deep Survey

NASA Astrophysics Data System (ADS)

Dickinson, Mark

2008-05-01

Observing the formation and evolution of ordinary galaxies at early cosmic times requires data at many wavelengths in order to recognize, separate and analyze the many physical processes which shape galaxies' history, including the growth of large scale structure, gravitational interactions, star formation, and active nuclei. Extremely deep data, covering an adequately large volume, are needed to detect ordinary galaxies in sufficient numbers at such great distances. The Great Observatories Origins Deep Survey (GOODS) was designed for this purpose as an anthology of deep field observing programs that span the electromagnetic spectrum. GOODS targets two fields, one in each hemisphere. Some of the deepest and most extensive imaging and spectroscopic surveys have been carried out in the GOODS fields, using nearly every major space- and ground-based observatory. Many of these data have been taken as part of large, public surveys (including several Hubble Treasury, Spitzer Legacy, and ESO Large Programs), which have produced large data sets that are widely used by the astronomical community. I will review the history of the GOODS program, highlighting results on the formation and early growth of galaxies and their active nuclei. I will also describe new and upcoming observations, such as the GOODS Herschel Key Program, which will continue to fill out our portrait of galaxies in the young universe.

Deep nightside photoelectron observations by MAVEN SWEA: Implications for Martian northern hemispheric magnetic topology and nightside ionosphere source

NASA Astrophysics Data System (ADS)

Xu, Shaosui; Mitchell, David; Liemohn, Michael; Dong, Chuanfei; Bougher, Stephen; Fillingim, Matthew; Lillis, Robert; McFadden, James; Mazelle, Christian; Connerney, Jack; Jakosky, Bruce

2016-09-01

The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission samples the Mars ionosphere down to altitudes of ˜150 km over a wide range of local times and solar zenith angles. On 5 January 2015 (Orbit 520) when the spacecraft was in darkness at high northern latitudes (solar zenith angle, SZA >120° latitude >60°), the Solar Wind Electron Analyzer (SWEA) instrument observed photoelectrons at altitudes below 200 km. Such observations imply the presence of closed crustal magnetic field loops that cross the terminator and extend thousands of kilometers to the deep nightside. This occurs over the weak northern crustal magnetic source regions, where the magnetic field has been thought to be dominated by draped interplanetary magnetic fields (IMF). Such a day-night magnetic connectivity also provides a source of plasma and energy to the deep nightside. Simulations with the SuperThermal Electron Transport (STET) model show that photoelectron fluxes measured by SWEA precipitating onto the nightside atmosphere provide a source of ionization that can account for the O2+ density measured by the Suprathermal and Thermal Ion Composition (STATIC) instrument below 200 km. This finding indicates another channel for Martian energy redistribution to the deep nightside and consequently localized ionosphere patches and potentially aurora.

Van Allen Probes Measurements of Energetic Particle Deep Penetration Into the Low L Region (L < 4) During the Storm on 8 April 2016

NASA Astrophysics Data System (ADS)

Zhao, H.; Baker, D. N.; Califf, S.; Li, X.; Jaynes, A. N.; Leonard, T.; Kanekal, S. G.; Blake, J. B.; Fennell, J. F.; Claudepierre, S. G.; Turner, D. L.; Reeves, G. D.; Spence, H. E.

2017-12-01

Using measurements from the Van Allen Probes, a penetration event of tens to hundreds of keV electrons and tens of keV protons into the low L shells (L < 4) is studied. Timing and magnetic local time (MLT) differences of energetic particle deep penetration are unveiled and underlying physical processes are examined. During this event, both proton and electron penetrations are MLT asymmetric. The observed MLT difference of proton penetration is consistent with convection of plasma sheet protons, suggesting enhanced convection during geomagnetic active times to be the cause of energetic proton deep penetration during this event. The observed MLT difference of tens to hundreds of keV electron penetration is completely different from tens of keV protons and cannot be well explained by inward radial diffusion, convection of plasma sheet electrons, or transport of trapped electrons by enhanced convection electric field represented by the Volland-Stern model or a uniform dawn-dusk electric field model based on the electric field measurements. It suggests that the underlying physical mechanism responsible for energetic electron deep penetration, which is very important for fully understanding energetic electron dynamics in the low L shells, should be MLT localized.

Anomalously deep polarization in SrTiO3 (001) interfaced with an epitaxial ultrathin manganite film

DOE PAGES

Wang, Zhen; Tao, Jing; Yu, Liping; ...

2016-10-17

Using atomically-resolved imaging and spectroscopy, we reveal a remarkably deep polarization in non-ferroelectric SrTiO 3 near its interface with an ultrathin nonmetallic film of La 2/3Sr 1/3MnO 3. Electron holography shows an electric field near the interface in SrTiO 3, yielding a surprising spontaneous polarization density of ~ 21 μC/cm 2. Combining the experimental results with first principles calculations, we propose that the observed deep polarization is induced by the electric field originating from oxygen vacancies that extend beyond a dozen unit-cells from the interface, thus providing important evidence of the role of defects in the emergent interface properties ofmore » transition metal oxides.« less

Evolution of the cluster optical galaxy luminosity function in the CFHTLS: breaking the degeneracy between mass and redshift

NASA Astrophysics Data System (ADS)

Sarron, F.; Martinet, N.; Durret, F.; Adami, C.

2018-06-01

Obtaining large samples of galaxy clusters is important for cosmology: cluster counts as a function of redshift and mass can constrain the parameters of our Universe. They are also useful in order to understand the formation and evolution of clusters. We develop an improved version of the Adami & MAzure Cluster FInder (AMACFI), now the Adami, MAzure & Sarron Cluster FInder (AMASCFI), and apply it to the 154 deg2 of the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) to obtain a large catalogue of 1371 cluster candidates with mass M200 > 1014 M⊙ and redshift z ≤ 0.7. We derive the selection function of the algorithm from the Millennium simulation, and cluster masses from a richness-mass scaling relation built from matching our candidates with X-ray detections. We study the evolution of these clusters with mass and redshift by computing the i'-band galaxy luminosity functions (GLFs) for the early-type (ETGs) and late-type galaxies (LTGs). This sample is 90% pure and 70% complete, and therefore our results are representative of a large fraction of the cluster population in these redshift and mass ranges. We find an increase in both the ETG and LTG faint populations with decreasing redshift (with Schechter slopes αETG = -0.65 ± 0.03 and αLTG = -0.95 ± 0.04 at z = 0.6, and αETG = -0.79 ± 0.02 and αLTG = -1.26 ± 0.03 at z = 0.2) and also a decrease in the LTG (but not the ETG) bright end. Our large sample allows us to break the degeneracy between mass and redshift, finding that the redshift evolution is more pronounced in high-mass clusters, but that there is no significant dependence of the faint end on mass for a given redshift. These results show that the cluster red sequence is mainly formed at redshift z > 0.7, and that faint ETGs continue to enrich the red sequence through quenching of brighter LTGs at z ≤ 0.7. The efficiency of this quenching is higher in large-mass clusters, while the accretion rate of faint LTGs is lower as the more massive clusters have already emptied most of their environment at higher redshifts. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at Terapix available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS.The candidate cluster catalog is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/613/A67

Radio Identification of Millimeter-Bright Galaxies Detected in the AzTEC/ASTE Blank Field Survey

NASA Astrophysics Data System (ADS)

Hatsukade, Bunyo; Kohno, Kotaro; White, Glenn; Matsuura, Shuji; Hanami, Hitoshi; Shirahata, Mai; Nakanishi, Kouichiro; Hughes, David; Tamura, Yoichi; Iono, Daisuke; Wilson, Grant; Yun, Min

2008-10-01

We propose a deep 1.4-GHz imaging of millimeter-bright sources in the AzTEC/ASTE 1.1-mm blank field survey of AKARI Deep Field-South. The AzTEC/ASTE uncovered 37 sources, which are possibly at z > 2. We have obtained multi-wavelength data in this field, but the large beam size of AzTEC/ASTE (30 arcsec) prevents us from identifying counterparts. The aim of this proposal is to identify radio counterparts with higher-angular resolution. This enables us (i) To identifying optical/IR counterparts. It enables optical spectroscopy to determine precise redshifts, allowing us to derive SFRs, luminosity functions, clustering properties, mass of dark matter halos, etc. (ii) To constrain luminosity evolutions of SMGs by comparing of 1.4-GHz number counts (and luminosity functions) with luminosity evolution models. (iii) To estimate photometric redshifts from 1.4-GHz and 1.1-mm data using the radio-FIR flux correlation. In case of non-detection, we can put deep lower limits (3 sigma limit of z > 3). These information lead to the study of evolutionary history of SMGs, their relationship with other galaxy populations, contribution to the cosmic star formation history and the infrared background.

The Pan-STARRS 1 Medium Deep Field Variable Star Catalog

NASA Astrophysics Data System (ADS)

Flewelling, Heather

2015-01-01

We present the first Pan-STARRS 1 Medium Deep Field Variable Star Catalog (PS1-MDF-VSC). The Pan-STARRS 1 (PS1) telescope is a 1.8 meter survey telescope with a 1.4 Gigapixel camera, located in Haleakala, Hawaii. The Medium Deep survey, which consists of 10 fields located uniformly across the sky, totalling 70 square degrees, is observed each night, in 2-3 filters per field, with 8 exposures per filter, resulting in 3000-4000 data points per star over a time span of 3.5 years. To find the variables, we select the stars with > 200 detections, between 16th and 21st magnitude. There are approximately 500k stars that fit this criteria, they then go through a lomb-scargle fitting routine to determine periodicity. After a periodicity cut, the ~400 candidates are classified by eye into different types of variable stars. We have identified several hundred variable stars, with periods ranging between a few minutes to a few days, and about half are not previously identified in the literature. We compare our results to the stripe 82 variable catalog, which overlaps part of the sky with the PS1 catalog.

The Pan-STARRS 1 Medium Deep Field Variable Star Catalog

NASA Astrophysics Data System (ADS)

Flewelling, Heather

2015-08-01

We present the first Pan-STARRS 1 Medium Deep Field Variable Star Catalog (PS1-MDF-VSC). The Pan-STARRS 1 (PS1) telescope is a 1.8 meter survey telescope with a 1.4 Gigapixel camera, located in Haleakala, Hawaii. The Medium Deep survey, which consists of 10 fields located uniformly across the sky, totalling 70 square degrees, is observed each night, in 2-3 filters per field, with 8 exposures per filter, resulting in 3000-4000 data points per star over a time span of 3.5 years. To find the variables, we select the stars with > 200 detections, between 16th and 21st magnitude. There are approximately 500k stars that fit this criteria, they then go through a lomb-scargle fitting routine to determine periodicity. After a periodicity cut, the ~400 candidates are classified by eye into different types of variable stars. We have identified several hundred variable stars, with periods ranging between a few minutes to a few days, and about half are not previously identified in the literature. We compare our results to the stripe 82 variable catalog, which overlaps part of the sky with the PS1 catalog.

Using Gaia as an Astrometric Tool for Deep Ground-based Surveys

NASA Astrophysics Data System (ADS)

Casetti-Dinescu, Dana I.; Girard, Terrence M.; Schriefer, Michael

2018-04-01

Gaia DR1 positions are used to astrometrically calibrate three epochs' worth of Subaru SuprimeCam images in the fields of globular cluster NGC 2419 and the Sextans dwarf spheroidal galaxy. Distortion-correction ``maps'' are constructed from a combination of offset dithers and reference to Gaia DR1. These are used to derive absolute proper motions in the field of NGC 2419. Notably, we identify the photometrically-detected Monoceros structure in the foreground of NGC 2419 as a kinematically-cold population of stars, distinct from Galactic-field stars. This project demonstrates the feasibility of combining Gaia with deep, ground-based surveys, thus extending high-quality astrometry to magnitudes beyond the limits of Gaia.

24. EXTERIOR VIEW, SHOWING AIRPLANES IN VERY DEEP SNOW. Photographic ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

24. EXTERIOR VIEW, SHOWING AIRPLANES IN VERY DEEP SNOW. Photographic copy of historic photograph. July-Dec. 1948 OAMA (original print located at Ogden Air Logistics Center, Hill Air Force Base, Utah). Photographer unknown. - Hill Field, Airplane Repair Hangars No. 1-No. 4, 5875 Southgate Avenue, Layton, Davis County, UT

The Herschel Lensing Survey (HLS): HST Frontier Field Coverage

NASA Astrophysics Data System (ADS)

Egami, Eiichi

2015-08-01

The Herschel Lensing Survey (HLS; PI: Egami) is a large Far-IR/Submm imaging survey of massive galaxy clusters using the Herschel Space Observatory. Its main goal is to detect and study IR/Submm galaxies that are below the nominal confusion limit of Herschel by taking advantage of the strong gravitational lensing power of massive galaxy clusters. HLS has obtained deep PACS (100/160 um) and SPIRE (250/350/500 um) images for 54 cluster fields (HLS-deep) as well as shallower but nearly confusion-limited SPIRE-only images for 527 cluster fields (HLS-snapshot) with a total observing time of ~420 hours. Extensive multi-wavelength follow-up studies are currently on-going with a variety of observing facilities including ALMA.Here, I will focus on the analysis of the deep Herschel PACS/SPIRE images obtained for the 6 HST Frontier Fields (5 observed by HLS-deep; 1 observed by the Herschel GT programs). The Herschel/SPIRE maps are wide enough to cover the Frontier-Field parallel pointings, and we have detected a total of ~180 sources, some of which are strongly lensed. I will present the sample and discuss the properties of these Herschel-detected dusty star-forming galaxies (DSFGs) identified in the Frontier Fields. Although the majority of these Herschel sources are at moderate redshift (z<3), a small number of extremely high-redshift (z>6) candidates can be identified as "Herschel dropouts" when combined with longer-wavelength data. We have also identified ~40 sources as likely cluster members, which will allow us to study the properties of DSFGs in the dense cluster environment.A great legacy of our HLS project will be the extensive multi-wavelength database that incorporates most of the currently available data/information for the fields of the Frontier-Field, CLASH, and other HLS clusters (e.g., HST/Spitzer/Herschel images, spectroscopic/photometric redshifts, lensing models, best-fit SED models etc.). Provided with a user-friendly GUI and a flexible search engine, this database should serve as a powerful tool for a variety of projects including those with ALMA and JWST in the future. I will conclude by introducing this HLS database system.

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

PubMed

Chen, Liang-Chieh; Papandreou, George; Kokkinos, Iasonas; Murphy, Kevin; Yuille, Alan L

2018-04-01

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7 percent mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.

The Chandra Deepest Fields in the Infrared: Making the Connection between Normal Galaxies and AGN

NASA Astrophysics Data System (ADS)

Grogin, N. A.; Ferguson, H. C.; Dickinson, M. E.; Giavalisco, M.; Mobasher, B.; Padovani, P.; Williams, R. E.; Chary, R.; Gilli, R.; Heckman, T. M.; Stern, D.; Winge, C.

2001-12-01

Within each of the two Chandra Deepest Fields (CDFs), there are ~10'x15' regions targeted for non-proprietary, deep SIRTF 3.6--24μ m imaging as part of the Great Observatories Origins Deep Survey (GOODS) Legacy program. In advance of the SIRTF observations, the GOODS team has recently begun obtaining non-proprietary, deep ground-based optical and near-IR imaging and spectroscopy over these regions, which contain virtually all of the current ≈1 Msec CXO coverage in the CDF North and much of the ≈1 Msec coverage in the CDF South. In particular, the planned depth of the near-IR imaging (JAB ~ 25.3; HAB ~ 24.8; KAB ~ 24.4) combined with the deep Chandra data can allow us to trace the evolutionary connection between normal galaxies, starbursts, and AGN out to z ~ 1 and beyond. We describe our CDF Archival program, which is integrating these GOODS-supporting observations together with the CDF archival data and other publicly-available datasets in these regions to create a multi-wavelength deep imaging and spectroscpic database available to the entire community. We highlight progress toward near-term science goals of this program, including: (a) pushing constraints on the redshift distribution and spectral-energy distributions of the faintest X-ray sources to the deepest possible levels via photometric redshifts; and (b) better characterizing the heavily-obscured and the high-redshift populations via both a near-IR search for optically-undetected CDF X-ray sources and also X-ray stacking analyses on the CXO-undetected EROs in these fields.

Habitat Demonstration Unit-Deep Space Habitat (HDU-DSH) Integration and Preparation for Desert RATS 2011

NASA Technical Reports Server (NTRS)

Barbeau, Zack

2011-01-01

The Habitat Demonstration Unit, or HDU, is a multi-purpose test bed that allows NASA scientists and engineers to design, develop, and test new living quarters, laboratories, and workspaces for the next generation space mission. Previous testing and integration has occurred during 2010 at the annual Desert Research and Technology Studies (Desert RATS) field testing campaign in the Arizona desert. There the HDU team tests the configuration developed for the fiscal year, or FY configuration. For FY2011, the NASA mission calls for simulating a deep space condition. The HDU-DSH, or Deep Space Habitat, will be configured with new systems and modules that will outfit the test bed with new deep space capabilities. One such addition is the new X-HAB (eXploration Habitat) Inflatable Loft. With any deep space mission there is the need for safe, suitable living quarters. The current HDU configuration does not allow for any living space at all. In fact, Desert RATS 2010 saw the crew sleeping in the Space Exploration Vehicles (SEV) instead of the HDU. The X-HAB Challenge pitted three universities against each other: Oklahoma State University, University of Maryland, and the University of Wisconsin. The winning team will have their design implemented by NASA for field testing at DRATS 2011. This paper will highlight the primary objective of getting the X-HAB field ready which involves the implementation of an elevator/handrail system along with smaller logistical and integration tasks associated with getting the HDU-DSH ready for shipment to DRATS.

A two-dimensional ocean model for long-term climatic simulations: Stability and coupling to atmospheric and sea ice models

NASA Astrophysics Data System (ADS)

Harvey, L. D. Danny

1992-06-01

A two-dimensional (latitude-depth) deep ocean model is presented which is coupled to a sea ice model and an Energy Balance Climate Model (EBCM), the latter having land-sea and surface-air resolution. The processes which occur in the ocean model are thermohaline overturning driven by the horizontal density gradient, shallow wind-driven overturning cells, convective overturning, and vertical and horizontal diffusion of heat and salt. The density field is determined from the temperature and salinity fields using a nonlinear equation of state. Mixed layer salinity is affected by evaporation, precipitation, runoff from continents, and sea ice freezing and melting, as well as by advective, convective, and diffusive exchanges with the deep ocean. The ocean model is first tested in an uncoupled mode, in which hemispherically symmetric mixed layer temperature and salinity, or salinity flux, are specified as upper boundary conditions. An experiment performed with previous models is repeated in which a mixed layer salinity perturbation is introduced in the polar half of one hemisphere after switching from a fixed salinity to a fixed salinity flux boundary condition. For small values of the vertical diffusion coefficient KV, the model undergoes self-sustained oscillations with a period of about 1500 years. With larger values of KV, the model locks into either an asymmetric mode with a single overturning cell spanning both hemispheres, or a symmetric quiescent state with downwelling near the equator, upwelling at high latitudes, and a warm deep ocean (depending on the value of KV). When the ocean model is forced with observed mixed layer temperature and salinity, no oscillations occur. The model successfully simulates the very weak meridional overturning and strong Antarctic Circumpolar Current at the latitudes of the Drake Passage. The coupled EBCM-deep ocean model displays internal oscillations with a period of 3000 years if the ocean fraction is uniform with latitude and KV and the horizontal diffusion coefficient in the mixed layer are not too large. Globally averaged atmospheric temperature changes of 2 K are driven by oscillations in the heat flux into or out of the deep ocean, with the sudden onset of a heat flux out of the deep ocean associated with the rapid onset of thermohaline overturning after a quiescent period, and the sudden onset of a heat flux into the deep ocean associated with the collapse of thermohaline overturning. When the coupled model is run with prescribed parameters (such as land-sea fraction and precipitation) varying with latitude based on observations, the model does not oscillate and produces a reasonable deep ocean temperature field but a completely unrealistic salinity field. Resetting the mixed layer salinity to observations on each time step (equivalent to the "flux correction" method used in atmosphere-ocean general circulation models) is sufficient to give a realistic salinity field throughout the ocean depth, but dramatically alters the flow field and associated heat transport. Although the model is highly idealized, the finding that the maximum perturbation in globally averaged heat flux from the deep ocean to the surface over a 100-year period is 1.4 W m-2 suggests that effect of continuing greenhouse gas increases, which could result in a heating perturbation of 10 W m-2 by the end of the next century, will swamp possible surface heating perturbations due to changes in oceanic circulation. On the other hand, the extreme sensitivity of the oceanic flow field to variations in precipitation and evaporation suggests that it will not be possible to produce accurate projections of regional climatic change in the near term, if at all.

Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms.

PubMed

Li, Hui; Giger, Maryellen L; Huynh, Benjamin Q; Antropova, Natalia O

2017-10-01

To evaluate deep learning in the assessment of breast cancer risk in which convolutional neural networks (CNNs) with transfer learning are used to extract parenchymal characteristics directly from full-field digital mammographic (FFDM) images instead of using computerized radiographic texture analysis (RTA), 456 clinical FFDM cases were included: a "high-risk" BRCA1/2 gene-mutation carriers dataset (53 cases), a "high-risk" unilateral cancer patients dataset (75 cases), and a "low-risk dataset" (328 cases). Deep learning was compared to the use of features from RTA, as well as to a combination of both in the task of distinguishing between high- and low-risk subjects. Similar classification performances were obtained using CNN [area under the curve [Formula: see text]; standard error [Formula: see text

Kinematic solar dynamo models with a deep meridional flow

NASA Astrophysics Data System (ADS)

Guerrero, G. A.; Muñoz, J. D.

2004-05-01

We develop two different solar dynamo models to verify the hypothesis that a deep meridional flow can restrict the appearance of sunspots below 45°, proposed recently by Nandy & Choudhuri. In the first one, a single polytropic approximation for the density profile was taken, for both radiative and convective zones. In the second one, that of Pinzon & Calvo-Mozo, two polytropes were used to distinguish between both zones. The magnetic buoyancy mechanism proposed by Dikpati & Charbonneau was chosen in both models. We have in fact obtained that a deep meridional flow pushes the maxima of toroidal magnetic field towards the solar equator, but, in contrast to Nandy & Choudhuri, a second zone of maximal fields remains at the poles. The second model, although closely resembling the solar standard model of Bahcall et al., gives solar cycles three times longer than observed.

Quantitative phase microscopy using deep neural networks

NASA Astrophysics Data System (ADS)

Li, Shuai; Sinha, Ayan; Lee, Justin; Barbastathis, George

2018-02-01

Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data generated by a phase SLM. The results showed that our DNN was able to reconstruct the profile of the phase target qualitatively. In the meantime, large error still existed, which indicated that our approach still need to be improved.

Pacific deep circulation and ventilation controlled by tidal mixing away from the sea bottom.

PubMed

Oka, Akira; Niwa, Yoshihiro

2013-01-01

Vertical mixing in the ocean is a key driver of the global ocean thermohaline circulation, one of the most important factors controlling past and future climate change. Prior observational and theoretical studies have focused on intense tidal mixing near the sea bottom (near-field mixing). However, ocean general circulation models that employ a parameterization of near-field mixing significantly underestimate the strength of the Pacific thermohaline circulation. Here we demonstrate that tidally induced mixing away from the sea bottom (far-field mixing) is essential in controlling the Pacific thermohaline circulation. Via the addition of far-field mixing to a widely used tidal parameterization, we successfully simulate the Pacific thermohaline circulation. We also propose that far-field mixing is indispensable for explaining the presence of the world ocean's oldest water in the eastern North Pacific Ocean. Our findings suggest that far-field mixing controls ventilation of the deep Pacific Ocean, a process important for ocean carbon and biogeochemical cycles.

Deep level study of Mg-doped GaN using deep level transient spectroscopy and minority carrier transient spectroscopy

NASA Astrophysics Data System (ADS)

Duc, Tran Thien; Pozina, Galia; Amano, Hiroshi; Monemar, Bo; Janzén, Erik; Hemmingsson, Carl

2016-07-01

Deep levels in Mg-doped GaN grown by metal organic chemical vapor deposition (MOCVD), undoped GaN grown by MOCVD, and halide vapor phase epitaxy (HVPE)-grown GaN have been studied using deep level transient spectroscopy and minority charge carrier transient spectroscopy on Schottky diodes. One hole trap, labeled HT1, was detected in the Mg-doped sample. It is observed that the hole emission rate of the trap is enhanced by increasing electric field. By fitting four different theoretical models for field-assisted carrier emission processes, the three-dimensional Coulombic Poole-Frenkel (PF) effect, three-dimensional square well PF effect, phonon-assisted tunneling, and one-dimensional Coulombic PF effect including phonon-assisted tunneling, it is found that the one-dimensional Coulombic PF model, including phonon-assisted tunneling, is consistent with the experimental data. Since the trap exhibits the PF effect, we suggest it is acceptorlike. From the theoretical model, the zero field ionization energy of the trap and an estimate of the hole capture cross section have been determined. Depending on whether the charge state is -1 or -2 after hole emission, the zero field activation energy Ei 0 is 0.57 eV or 0.60 eV, respectively, and the hole capture cross section σp is 1.3 ×10-15c m2 or 1.6 ×10-16c m2 , respectively. Since the level was not observed in undoped GaN, it is suggested that the trap is associated with an Mg related defect.

MRI-induced heating of deep brain stimulation leads

NASA Astrophysics Data System (ADS)

Mohsin, Syed A.; Sheikh, Noor M.; Saeed, Usman

2008-10-01

The radiofrequency (RF) field used in magnetic resonance imaging is scattered by medical implants. The scattered field of a deep brain stimulation lead can be very intense near the electrodes stimulating the brain. The effect is more pronounced if the lead behaves as a resonant antenna. In this paper, we examine the resonant length effect. We also use the finite element method to compute the near field for (i) the lead immersed in inhomogeneous tissue (fat, muscle, and brain tissues) and (ii) the lead connected to an implantable pulse generator. Electric field, specific absorption rate and induced temperature rise distributions have been obtained in the brain tissue surrounding the electrodes. The worst-case scenario has been evaluated by neglecting the effect of blood perfusion. The computed values are in good agreement with in vitro measurements made in the laboratory.

Study on Seismogenesis of 2013 Ms5.1 Badong Earthquake in the Three Gorges Reservoir Region

NASA Astrophysics Data System (ADS)

Li, X.; Zeng, Z.; Xu, S.; He, C.

2015-12-01

On 16 December, 2013, an earthquake of Ms5.1 occurred in Badong County, the Three Gorges Reservoir area, China. We collected all the 150 published focal mechanism solutions (FMS) and inversed the tectonic stress field in Badong, the Three Gorges Dam and Huangling anticline area using the software SATSI (Hardebeck and Michael, 2006). Inversion results show that the orientations of maximum principle stress axis (σ1) in Badong plunge to NNE or SSW. Detailed characteristics of the stress field indicate that the σ1 axis is almost vertical in the center of Huangling anticline and turns horizontal to the west. As to deep structures, we studied the satellite gravity anomalies of 8-638 order in this area using the EIGEN-6C2 model provided by ICGRM. Combining the seismic sounding profile through the epicenter of Badong earthquake and the petrology data, we reinterpreted the deep structure in the study area. The results show that the deep crust in Badong is unstable and the deep material's upwelling leads to Huangling anticline continued uplifting, which is consistent with the result indicated from the stress filed. Both of them provide energy for the preparation of earthquake. The FMS shows that Gaoqiao Fault is the causative fault of this Ms5.1 earthquake. Field investigations indicated that the lithology and fracture characteristic in Badong is beneficial to reservoir water infiltration. Before the earthquake, reservoir water level raised to 175m, the highest storage level, which increased the loading. Based on above researches, we believe that the Ms5.1 Badong earthquake is controlled by deep tectonic environment and stress field in shallow crust. The reservoir water infiltration and uploading increase generated by water storage of the Three Gorges area reduced the strength of Gaoqiao Fault and changed its stress state. These factors jointly promoted an abrupt movement of the fault in the critical stress state, and triggered the Ms5.1 Badong earthquake.

The SCUBA-2 Cosmology Legacy Survey: the EGS deep field - I. Deep number counts and the redshift distribution of the recovered cosmic infrared background at 450 and 850 μ m

NASA Astrophysics Data System (ADS)

Zavala, J. A.; Aretxaga, I.; Geach, J. E.; Hughes, D. H.; Birkinshaw, M.; Chapin, E.; Chapman, S.; Chen, Chian-Chou; Clements, D. L.; Dunlop, J. S.; Farrah, D.; Ivison, R. J.; Jenness, T.; Michałowski, M. J.; Robson, E. I.; Scott, Douglas; Simpson, J.; Spaans, M.; van der Werf, P.

2017-01-01

We present deep observations at 450 and 850 μm in the Extended Groth Strip field taken with the SCUBA-2 camera mounted on the James Clerk Maxwell Telescope as part of the deep SCUBA-2 Cosmology Legacy Survey (S2CLS), achieving a central instrumental depth of σ450 = 1.2 mJy beam-1 and σ850 = 0.2 mJy beam-1. We detect 57 sources at 450 μm and 90 at 850 μm with signal-to-noise ratio >3.5 over ˜70 arcmin2. From these detections, we derive the number counts at flux densities S450 > 4.0 mJy and S850 > 0.9 mJy, which represent the deepest number counts at these wavelengths derived using directly extracted sources from only blank-field observations with a single-dish telescope. Our measurements smoothly connect the gap between previous shallower blank-field single-dish observations and deep interferometric ALMA results. We estimate the contribution of our SCUBA-2 detected galaxies to the cosmic infrared background (CIB), as well as the contribution of 24 μm-selected galaxies through a stacking technique, which add a total of 0.26 ± 0.03 and 0.07 ± 0.01 MJy sr-1, at 450 and 850 μm, respectively. These surface brightnesses correspond to 60 ± 20 and 50 ± 20 per cent of the total CIB measurements, where the errors are dominated by those of the total CIB. Using the photometric redshifts of the 24 μm-selected sample and the redshift distributions of the submillimetre galaxies, we find that the redshift distribution of the recovered CIB is different at each wavelength, with a peak at z ˜ 1 for 450 μm and at z ˜ 2 for 850 μm, consistent with previous observations and theoretical models.

Artificial Intelligence in planetary spectroscopy

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2017-10-01

The field of exoplanetary spectroscopy is as fast moving as it is new. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain. This is true for both: the data analysis of observations as well as the theoretical modelling of their atmospheres.Issues of low signal-to-noise data and large, non-linear parameter spaces are nothing new and commonly found in many fields of engineering and the physical sciences. Recent years have seen vast improvements in statistical data analysis and machine learning that have revolutionised fields as diverse as telecommunication, pattern recognition, medical physics and cosmology.In many aspects, data mining and non-linearity challenges encountered in other data intensive fields are directly transferable to the field of extrasolar planets. In this conference, I will discuss how deep neural networks can be designed to facilitate solving said issues both in exoplanet atmospheres as well as for atmospheres in our own solar system. I will present a deep belief network, RobERt (Robotic Exoplanet Recognition), able to learn to recognise exoplanetary spectra and provide artificial intelligences to state-of-the-art atmospheric retrieval algorithms. Furthermore, I will present a new deep convolutional network that is able to map planetary surface compositions using hyper-spectral imaging and demonstrate its uses on Cassini-VIMS data of Saturn.

What Can Be Learned from a Laboratory Model of Conceptual Change? Descriptive Findings and Methodological Issues

ERIC Educational Resources Information Center

Ohlsson, Stellan; Cosejo, David G.

2014-01-01

The problem of how people process novel and unexpected information--"deep learning" (Ohlsson in "Deep learning: how the mind overrides experience." Cambridge University Press, New York, 2011)--is central to several fields of research, including creativity, belief revision, and conceptual change. Researchers have not converged…

Perceived Deep-Level Dissimilarity: Personality Antecedents and Impact on Overall Job Attitude, Helping, Work Withdrawal, and Turnover

ERIC Educational Resources Information Center

Liao, Hui; Chuang, Aichia; Joshi, Aparna

2008-01-01

The current research extends three research areas in relational demography: considering deep-level dissimilarity in theory building, assessing dissimilarity perceptions directly in theory testing, and examining the antecedents of dissimilarity perceptions. The results, based on two field studies using diverse samples, demonstrate the effects of…

Effect of deep vs. shallow tillage on onion stunting and onion bulb yield, 2012

USDA-ARS?s Scientific Manuscript database

A field experiment was conducted at a site inoculated with R. solani AG 8 at the Oregon State University Hermiston Agricultural Research and Extension Center in Hermiston, OR to determine the effect of plowing (deep tillage) vs. rototilling (shallow tillage) on onion stunting caused by R. solani AG ...

High-speed rupture during the initiation of the 2015 Bonin Islands deep earthquake

NASA Astrophysics Data System (ADS)

Zhan, Z.; Ye, L.; Shearer, P. M.; Lay, T.; Kanamori, H.

2015-12-01

Among the long-standing questions on how deep earthquakes rupture, the nucleation phase of large deep events is one of the most puzzling parts. Resolving the rupture properties of the initiation phase is difficult to achieve with far-field data because of the need for accurate corrections for structural effects on the waveforms (e.g., attenuation, scattering, and site effects) and alignment errors. Here, taking the 2015 Mw 7.9 Bonin Islands earthquake (depth = 678 km) as an example, we jointly invert its far-field P waves at multiple stations for the average rupture speed during the first second of the event. We use waveforms from a closely located aftershock as empirical Green's functions, and correct for possible differences in focal mechanisms and waveform misalignments with an iterative approach. We find that the average initial rupture speed is over 5 km/s, significantly higher than the average rupture speed of 3 km/s later in the event. This contrast suggests that rupture speeds of deep earthquakes can be highly variable during individual events and may define different stages of rupture, potentially with different mechanisms.

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

PubMed

Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

2017-01-01

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

Temperature profiles in the earth of importance to deep electrical conductivity models

NASA Astrophysics Data System (ADS)

Čermák, Vladimír; Laštovičková, Marcela

1987-03-01

Deep in the Earth, the electrical conductivity of geological material is extremely dependent on temperature. The knowledge of temperature is thus essential for any interpretation of magnetotelluric data in projecting lithospheric structural models. The measured values of the terrestrial heat flow, radiogenic heat production and thermal conductivity of rocks allow the extrapolation of surface observations to a greater depth and the calculation of the temperature field within the lithosphere. Various methods of deep temperature calculations are presented and discussed. Characteristic geotherms are proposed for major tectonic provinces of Europe and it is shown that the existing temperatures on the crust-upper mantle boundary may vary in a broad interval of 350 1,000°C. The present work is completed with a survey of the temperature dependence of electrical conductivity for selected crustal and upper mantle rocks within the interval 200 1,000°C. It is shown how the knowledge of the temperature field can be used in the evaluation of the deep electrical conductivity pattern by converting the conductivity-versustemperature data into the conductivity-versus-depth data.

Deep Keck u-Band Imaging of the Hubble Ultra Deep Field: A Catalog of z ~ 3 Lyman Break Galaxies

NASA Astrophysics Data System (ADS)

Rafelski, Marc; Wolfe, Arthur M.; Cooke, Jeff; Chen, Hsiao-Wen; Armandroff, Taft E.; Wirth, Gregory D.

2009-10-01

We present a sample of 407 z ~ 3 Lyman break galaxies (LBGs) to a limiting isophotal u-band magnitude of 27.6 mag in the Hubble Ultra Deep Field. The LBGs are selected using a combination of photometric redshifts and the u-band drop-out technique enabled by the introduction of an extremely deep u-band image obtained with the Keck I telescope and the blue channel of the Low Resolution Imaging Spectrometer. The Keck u-band image, totaling 9 hr of integration time, has a 1σ depth of 30.7 mag arcsec-2, making it one of the most sensitive u-band images ever obtained. The u-band image also substantially improves the accuracy of photometric redshift measurements of ~50% of the z ~ 3 LBGs, significantly reducing the traditional degeneracy of colors between z ~ 3 and z ~ 0.2 galaxies. This sample provides the most sensitive, high-resolution multi-filter imaging of reliably identified z ~ 3 LBGs for morphological studies of galaxy formation and evolution and the star formation efficiency of gas at high redshift.

Observing the Birth and evolution of Galaxies - the ATCA-AKARI-ASTE/AzTEC deep South Ecliptic Pole Field

NASA Astrophysics Data System (ADS)

White, Glenn; Kohno, Kotaro; Matsuhara, Hideo; Matsuura, Shuji; Hanami, Hitoshi; Lee, Hyung Mok; Pearson, Chris; Takagi, Toshi; Serjeant, Stephen; Jeong, Woongseob; Oyabu, Shinki; Shirahata, Mai; Nakanishi, Kouichiro; Figueredo, Elysandra; Etxaluze, Mireya

2007-04-01

We propose deep 20 cm observations supporting the AKARI (3-160 micron)/ASTE/AzTEC (1.1 mm) SEP ultra deep ('Oyabu Field') survey of an extremely low cirrus region at the South Ecliptic Pole. Our combined IR/mm/Radio survey addresses the questions: How do protogalaxies and protospheroids form and evolve? How do AGN link with ULIRGs in their birth and evolution? What is the nature of the mm/submm extragalactic source population? We will address these by sampling the star formation history in the early universe to at least z~2. Compared to other Deep Surveys, a) AKARI multi-band IR measurements allow precision photo-z estimates of optically obscured objects, b) our multi-waveband contiguous area will mitigate effects of cosmic variance, c) the low cirrus noise at the SEP (< 0.08 MJy/sr) rivals that of the Lockman Hole "Astronomy's other ultra-deep 'cosmological window'", and d) our coverage of four FIR bands will characterise the far-IR dust emission hump of our starburst galaxies better than SPITZER's two MIPS bands allow. The ATCA data are crucial to galaxy identification, and determining the star formation rates and intrinsic luminosities through this unique Southern cosmological window.

Step-off, vertical electromagnetic responses of a deep resistivity layer buried in marine sediments

NASA Astrophysics Data System (ADS)

Jang, Hangilro; Jang, Hannuree; Lee, Ki Ha; Kim, Hee Joon

2013-04-01

A frequency-domain, marine controlled-source electromagnetic (CSEM) method has been applied successfully in deep water areas for detecting hydrocarbon (HC) reservoirs. However, a typical technique with horizontal transmitters and receivers requires large source-receiver separations with respect to the target depth. A time-domain EM system with vertical transmitters and receivers can be an alternative because vertical electric fields are sensitive to deep resistive layers. In this paper, a time-domain modelling code, with multiple source and receiver dipoles that are finite in length, has been written to investigate transient EM problems. With the use of this code, we calculate step-off responses for one-dimensional HC reservoir models. Although the vertical electric field has much smaller amplitude of signal than the horizontal field, vertical currents resulting from a vertical transmitter are sensitive to resistive layers. The modelling shows a significant difference between step-off responses of HC- and water-filled reservoirs, and the contrast can be recognized at late times at relatively short offsets. A maximum contrast occurs at more than 4 s, being delayed with the depth of the HC layer.

Deep geothermal resources in the Yangbajing Field, Tibet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao Ping; Jin Jian; Duo Ji

1997-12-31

Since the first well was bored in July 1997 in the Yangbajing geothermal field, more than 80 wells have been drilled. The total of installed capacity is 25.18MWe for geothermal power plant that has generated about 1.0 x 10{sup 9} kWh electricity in all. Temperatures inside shallow reservoir are in the range from 150{degrees}C to 165{degrees}C. No high-temperature field if found below the shallow reservoir in the southern part. In order to enlarge the installed capacity and solve pressure decline in current productive wells, an exploration project of deep geothermal resources has been carried out in the northern part. Themore » highest temperature of 329{degrees}C was detected in well ZK4002 at 1850m depth in 1994. Well ZK4001 drilled in 1996 flows out high-enthalpy thermal fluid at the wellhead, in which the average temperature is 248{degrees}C in the feeding zones. There is a great potential for power generation in the northern part. The exploitation of deep geothermal resources would effect the production of existing wells.« less

Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

PubMed

Ohsugi, Hideharu; Tabuchi, Hitoshi; Enno, Hiroki; Ishitobi, Naofumi

2017-08-25

Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep learning, a machine-learning technology, to detect RRD using ultra-wide-field fundus images and investigated its performance. In total, 411 images (329 for training and 82 for grading) from 407 RRD patients and 420 images (336 for training and 84 for grading) from 238 non-RRD patients were used in this study. The deep learning model demonstrated a high sensitivity of 97.6% [95% confidence interval (CI), 94.2-100%] and a high specificity of 96.5% (95% CI, 90.2-100%), and the area under the curve was 0.988 (95% CI, 0.981-0.995). This model can improve medical care in remote areas where eye clinics are not available by using ultra-wide-field fundus ophthalmoscopy for the accurate diagnosis of RRD. Early diagnosis of RRD can prevent blindness.

Dark-ages reionization and galaxy formation simulation-XI. Clustering and halo masses of high redshift galaxies

NASA Astrophysics Data System (ADS)

Park, Jaehong; Kim, Han-Seek; Liu, Chuanwu; Trenti, Michele; Duffy, Alan R.; Geil, Paul M.; Mutch, Simon J.; Poole, Gregory B.; Mesinger, Andrei; Wyithe, J. Stuart B.

2017-12-01

We investigate the clustering properties of Lyman-break galaxies (LBGs) at z ∼ 6 - 8. Using the semi-analytical model MERAXES constructed as part of the dark-ages reionization and galaxy-formation observables from numerical simulation (DRAGONS) project, we predict the angular correlation function (ACF) of LBGs at z ∼ 6 - 8. Overall, we find that the predicted ACFs are in good agreement with recent measurements at z ∼ 6 and z ∼ 7.2 from observations consisting of the Hubble eXtreme Deep Field, the Hubble Ultra Deep Field and cosmic sssembly near-infrared deep extragalactic legacy survey field. We confirm the dependence of clustering on luminosity, with more massive dark matter haloes hosting brighter galaxies, remains valid at high redshift. The predicted galaxy bias at fixed luminosity is found to increase with redshift, in agreement with observations. We find that LBGs of magnitude MAB(1600) < -19.4 at 6 ≲ z ≲ 8 reside in dark matter haloes of mean mass ∼1011.0-1011.5 M⊙, and this dark matter halo mass does not evolve significantly during reionisation.

Deep Space Gateway Science Opportunities

NASA Technical Reports Server (NTRS)

Quincy, C. D.; Charles, J. B.; Hamill, Doris; Sidney, S. C.

2018-01-01

The NASA Life Sciences Research Capabilities Team (LSRCT) has been discussing deep space research needs for the last two years. NASA's programs conducting life sciences studies - the Human Research Program, Space Biology, Astrobiology, and Planetary Protection - see the Deep Space Gateway (DSG) as affording enormous opportunities to investigate biological organisms in a unique environment that cannot be replicated in Earth-based laboratories or on Low Earth Orbit science platforms. These investigations may provide in many cases the definitive answers to risks associated with exploration and living outside Earth's protective magnetic field. Unlike Low Earth Orbit or terrestrial locations, the Gateway location will be subjected to the true deep space spectrum and influence of both galactic cosmic and solar particle radiation and thus presents an opportunity to investigate their long-term exposure effects. The question of how a community of biological organisms change over time within the harsh environment of space flight outside of the magnetic field protection can be investigated. The biological response to the absence of Earth's geomagnetic field can be studied for the first time. Will organisms change in new and unique ways under these new conditions? This may be specifically true on investigations of microbial communities. The Gateway provides a platform for microbiology experiments both inside, to improve understanding of interactions between microbes and human habitats, and outside, to improve understanding of microbe-hardware interactions exposed to the space environment.

High-throughput DNA separation in nanofilter arrays.

PubMed

Choi, Sungup; Kim, Ju Min; Ahn, Kyung Hyun; Lee, Seung Jong

2014-08-01

We numerically investigated the dynamics of short double-stranded DNA molecules moving through a deep-shallow alternating nanofilter, by utilizing Brownian dynamics simulation. We propose a novel mechanism for high-throughput DNA separation with a high electric field, which was originally predicted by Laachi et al. [Phys. Rev. Lett. 2007, 98, 098106]. In this work, we show that DNA molecules deterministically move along different electrophoretic streamlines according to their length, owing to geometric constraint at the exit of the shallow region. Consequently, it is more probable that long DNA molecules pass over a deep well region without significant lateral migration toward the bottom of the deep well, which is in contrast to the long dwelling time for short DNA molecules. We investigated the dynamics of DNA passage through a nanofilter facilitating electrophoretic field kinematics. The statistical distribution of the DNA molecules according to their size clearly corroborates our assumption. On the other hand, it was also found that the tapering angle between the shallow and deep regions significantly affects the DNA separation performance. The current results show that the nonuniform field effect combined with geometric constraint plays a key role in nanofilter-based DNA separation. We expect that our results will be helpful in designing and operating nanofluidics-based DNA separation devices and in understanding the polymer dynamics in confined geometries. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Study of laser cooling in deep optical lattice: two-level quantum model

NASA Astrophysics Data System (ADS)

Prudnikov, O. N.; Il'enkov, R. Ya.; Taichenachev, A. V.; Yudin, V. I.; Rasel, E. M.

2018-01-01

We study a possibility of laser cooling of 24Mg atoms in deep optical lattice formed by intense off-resonant laser field in a presence of cooling field resonant to narrow (3s3s) 1 S 0 → (3s3p)3 P 1 (λ = 457 nm) optical transition. For description of laser cooling with taking into account quantum recoil effects we consider two quantum models. The first one is based on direct numerical solution of quantum kinetic equation for atom density matrix and the second one is simplified model based on decomposition of atom density matrix over vibration states in the lattice wells. We search cooling field intensity and detuning for minimum cooling energy and fast laser cooling.

Deep Vadose Zone Treatability Test for the Hanford Central Plateau: Interim Post-Desiccation Monitoring Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truex, Michael J.; Oostrom, Martinus; Strickland, Christopher E.

2013-09-01

A field test of desiccation is being conducted as an element of the deep vadose zone treatability test program. Desiccation technology relies on removal of water from a portion of the subsurface such that the resultant low moisture conditions inhibit downward movement of water and dissolved contaminants. Previously, a field test report (Truex et al. 2012a) was prepared describing the active desiccation portion of the test and initial post-desiccation monitoring data. Additional monitoring data have been collected at the field test site during the post-desiccation period and is reported herein along with interpretation with respect to desiccation performance. This ismore » an interim report including about 2 years of post-desiccation monitoring data.« less

Engines for the Cosmos

NASA Technical Reports Server (NTRS)

Rodgers, Stephen L.; Reisz, Al; Wyckoff, James (Technical Monitor)

2002-01-01

Galactic forces spiral across the cosmos fueled by nuclear fission and fusion and atoms in plasmatic states with throes of constraints of gravitational forces and magnetic fields, In their wanderings these galaxies spew light, radiation, atomic and subatomic particles throughout the universe. Throughout the ages of man visions of journeying through the stars have been wondered. If humans and human devices from Earth are to go beyond the Moon and journey into deep space, it must be accomplished with like forces of the cosmos such as electrical fields, magnetic fields, ions, electrons and energies generated from the manipulation of subatomic and atomic particles. Forms of electromagnetic waves such as light, radio waves and lasers must control deep space engines. We won't get far on our Earth accustomed hydrocarbon fuels.

Deep ultraviolet scanning near-field optical microscopy for the structural analysis of organic and biological materials

NASA Astrophysics Data System (ADS)

Aoki, Hiroyuki; Hamamatsu, Toyohiro; Ito, Shinzaburo

2004-01-01

Scanning near-field optical microscopy (SNOM) using a deep ultraviolet (DUV) light source was developed for in situ imaging of a variety of chemical species without staining. Numerous kinds of chemical species have a carbon-carbon double bond or aromatic group in their chemical structure, which can be excited at the wavelength below 300 nm. In this study, the wavelength range available for SNOM imaging was extended to the DUV region. DUV-SNOM allowed the direct imaging of polymer thin films with high detection sensitivity and spatial resolution of several tens of nanometers. In addition to the polymer materials, we demonstrated the near-field imaging of a cell without using a fluorescence label.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

PubMed

Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David

2018-05-01

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

Deep learning in bioinformatics.

PubMed

Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

2017-09-01

In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analysis of Near-field of Circular Aperture Antennas with Application to Study of High Intensity Radio Frequency (HIRF) Hazards to Aviation from JPL/NASA Deep Space Network Antennas

NASA Technical Reports Server (NTRS)

Jamnejad, Vahraz; Statman, Joseph

2013-01-01

This work includes a simplified analysis of the radiated near to mid-field from JPL/NASA Deep Space Network (DSN) reflector antennas and uses an averaging technique over the main beam region and beyond for complying with FAA regulations in specific aviation environments. The work identifies areas that require special attention, including the implications of the very narrow beam of the DSN transmitters. The paper derives the maximum averaged power densities allowed and identifies zones where mitigation measures are required.

Anomalous enhancement of the lower critical field deep in the superconducting state of LaRu4As12

NASA Astrophysics Data System (ADS)

Juraszek, J.; Bochenek, Ł.; Wawryk, R.; Henkie, Z.; Konczykowski, M.; Cichorek, T.

2018-05-01

LaRu4As12 with the critical temperature Tc = 10.4 K displays several features which point at a non-singlet superconducting order parameter, although the bcc crystal structure of the filled skutterudites does not favour the emergence of multiple energy gaps. LaRu4As12 displays an unexpected enhancement of the lower critical field deep in superconducting state which can be attributed to the existence of two superconducting gaps. At T = 0.4 K, the local magnetization measurements were performed utilizing miniaturized Hall sensors.

The Chandra Deep Field South as a test case for Global Multi Conjugate Adaptive Optics

NASA Astrophysics Data System (ADS)

Portaluri, E.; Viotto, V.; Ragazzoni, R.; Gullieuszik, M.; Bergomi, M.; Greggio, D.; Biondi, F.; Dima, M.; Magrin, D.; Farinato, J.

2017-04-01

The era of the next generation of giant telescopes requires not only the advent of new technologies but also the development of novel methods, in order to exploit fully the extraordinary potential they are built for. Global Multi Conjugate Adaptive Optics (GMCAO) pursues this approach, with the goal of achieving good performance over a field of view of a few arcmin and an increase in sky coverage. In this article, we show the gain offered by this technique to an astrophysical application, such as the photometric survey strategy applied to the Chandra Deep Field South as a case study. We simulated a close-to-real observation of a 500 × 500 arcsec2 extragalactic deep field with a 40-m class telescope that implements GMCAO. We analysed mock K-band images of 6000 high-redshift (up to z = 2.75) galaxies therein as if they were real to recover the initial input parameters. We attained 94.5 per cent completeness for source detection with SEXTRACTOR. We also measured the morphological parameters of all the sources with the two-dimensional fitting tools GALFIT. The agreement we found between recovered and intrinsic parameters demonstrates GMCAO as a reliable approach to assist extremely large telescope (ELT) observations of extragalactic interest.

The Great Observatories Origins Deep Survey (GOODS): Overview and Status

NASA Astrophysics Data System (ADS)

Hook, R. N.; GOODS Team

2002-12-01

GOODS is a very large project to gather deep imaging data and spectroscopic followup of two fields, the Hubble Deep Field North (HDF-N) and the Chandra Deep Field South (CDF-S), with both space and ground-based instruments to create an extensive multiwavelength public data set for community research on the distant Universe. GOODS includes a SIRTF Legacy Program (PI: Mark Dickinson) and a Hubble Treasury Program of ACS imaging (PI: Mauro Giavalisco). The ACS imaging was also optimized for the detection of high-z supernovae which are being followed up by a further target of opportunity Hubble GO Program (PI: Adam Riess). The bulk of the CDF-S ground-based data presently available comes from an ESO Large Programme (PI: Catherine Cesarsky) which includes both deep imaging and multi-object followup spectroscopy. This is currently complemented in the South by additional CTIO imaging. Currently available HDF-N ground-based data forming part of GOODS includes NOAO imaging. Although the SIRTF part of the survey will not begin until later in the year the ACS imaging is well advanced and there is also a huge body of complementary ground-based imaging and some follow-up spectroscopy which is already publicly available. We summarize the current status of GOODS and give an overview of the data products currently available and present the timescales for the future. Many early science results from the survey are presented in other GOODS papers at this meeting. Support for the HST GOODS program presented here and in companion abstracts was provided by NASA thorugh grant number GO-9425 from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555.

Lyman-alpha fractions in the Hubble Ultra Deep Field at 4 < z < 6

NASA Astrophysics Data System (ADS)

Harish, Santosh; Malhotra, Sangeeta; Rhoads, James; Christensen, Lise; Tilvi, Vithal; Finkelstein, Steven; Pharo, John

2018-01-01

Lyman-alpha (Lya) emitting galaxies at high-redshifts serve as a good probe of neutral hydrogen in the intergalactic medium (IGM). Here we present measurements of the Lya fraction using a sample of Lyman-break galaxies (LBGs) between 4 < z < 6 with deep HST grism observations from the GRAPES/PEARS projects as well as spectroscopic observations from the MUSE integral-field spectrograph. The sample of LBGs at z~5 & 6 are spectroscopically confirmed with deep HST grism data from the GRAPES and PEARS projects. We also measure Lya fractions using a sample of photometrically-selected LBGs for the same redshift range. In addition, we study the EW distribution in relation to continuum and line luminosities, as well as the relation between photometric and spectroscopic redshift. We find that objects with higher EWs tend to have larger differences between photometric and spectroscopic redshifts.

The Key Factors Analysis of Palisades Temperature in Deep Open-pit Mine

NASA Astrophysics Data System (ADS)

Wang, Yuan; Du, Cuifeng; Jin, Wenbo; Wang, Puyu

2018-01-01

In order to study the key factors of palisades temperature field in a deep open-pit mine in the natural environment, the influence of natural factors on the palisades temperature in a deep open-pit mine were analysed based on the principle of heat transfer. Four typical places with different ways of solar radiation were selected to carry out the field test. The results show that solar radiation, atmospheric temperature, and wind speed are three main factors affecting the temperature of palisades and that the direct sunlight plays a leading role. The time period of the sun shining directly on the shady slope of the palisades is short because of blocking effect, whose temperature changes in a smaller scale. At the same time, the sun slope of the palisades suffers from the solar radiation for a long time, whose temperature changes in a larger scale, and the variation is similar to the air temperature.

Seismic anisotropy of the crystalline crust: What does it tell us?

USGS Publications Warehouse

Rabbel, Wolfgang; Mooney, Walter D.

1996-01-01

The study of the directional dependence of seismic velocities (seismic anisotropy) promises more refined insight into mineral composition and physical properties of the crystalline crust than conventional deep seismic refraction or reflection profiles providing average values of P-and S-wave velocities. The alignment of specific minerals by ductile rock deformation, for instance, causes specific types of seismic anisotropy which can be identified by appropriate field measurements.Vice versa, the determination of anisotropy can help to discriminate between different rock candidates in the deep crust. Seismic field measurements at the Continental Deep Drilling Site (KTB, S Germany) are shown as an example that anisotropy has to be considered in crustal studies. At the KTB, the dependence of seismic velocity on the direction of wave propagation in situ was found to be compatible with the texture, composition and fracture density of drilled crustal rocks.

Hydrogeochemical and stream sediment special reconnaissance report for the Deep Creek Mountains, Nevada and Utah

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qualheim, B.

1979-04-01

This report represents the results of the reconnaissance sampling of the Deep Creek Mountains of western Utah. The Deep Creek range is located in the northwest corner of the Delta NTMS 1:250,000 and the southwestern corner of the Tooele NTMS 1:250,000 sheets and covers an area of 1750 km/sup 2/. Samples collected in this study include dry and wet stream sediments and water from available streams, wells, and springs. The samples were analyzed for uranium, as well as 15 to 20 trace elements, using neutron activation techniques. In addition, field and laboratory measurements were made on the water samples. Analyticalmore » data and field measurements are presented in tabular hard copy and fiche format. Water-sample site locations, water-sample uranium concentrations, sediment-sample site locations, and sediment-sample uranium concentrations are shown on separate overlays.« less

Magnetic field fluctuations analysis for the ion trap implementation of the quantum Rabi model in the deep strong coupling regime

NASA Astrophysics Data System (ADS)

Puebla, Ricardo; Casanova, Jorge; Plenio, Martin B.

2018-03-01

The dynamics of the quantum Rabi model (QRM) in the deep strong coupling regime is theoretically analyzed in a trapped-ion set-up. Recognizably, the main hallmark of this regime is the emergence of collapses and revivals, whose faithful observation is hindered under realistic magnetic dephasing noise. Here, we discuss how to attain a faithful implementation of the QRM in the deep strong coupling regime which is robust against magnetic field fluctuations and at the same time provides a large tunability of the simulated parameters. This is achieved by combining standing wave laser configuration with continuous dynamical decoupling. In addition, we study the role that amplitude fluctuations play to correctly attain the QRM using the proposed method. In this manner, the present work further supports the suitability of continuous dynamical decoupling techniques in trapped-ion settings to faithfully realize different interacting dynamics.

Crop response to deep tillage - a meta-analysis

NASA Astrophysics Data System (ADS)

Schneider, Florian; Don, Axel; Hennings, Inga; Schmittmann, Oliver; Seidel, Sabine J.

2017-04-01

Subsoil, i.e. the soil layer below the topsoil, stores tremendous stocks of nutrients and can keep water even under drought conditions. Deep tillage may be a method to enhance the plant-availability of subsoil resources. However, in field trials, deep tillage effects on crop yields were inconsistent. Therefore, we conducted a meta-analysis of crop yield response to subsoiling, deep ploughing and deep mixing of soil profiles. Our search resulted in 1530 yield comparisons following deep and conventional control tillage on 67 experimental cropping sites. The vast majority of the data derived from temperate latitudes, from trials conducted in the USA (679 observations) and Germany (630 observations). On average, crop yield response to deep tillage was slightly positive (6% increase). However, individual deep tillage effects were highly scattered including about 40% yield depressions after deep tillage. Deep tillage on soils with root restrictive layers increased crop yields about 20%, while soils containing >70% silt increased the risk of yield depressions following deep tillage. Generally, deep tillage effects increased with drought intensity indicating deep tillage as climate adaptation measure at certain sites. Our results suggest that deep tillage can facilitate the plant-availability of subsoil nutrients, which increases crop yields if (i) nutrients in the topsoil are growth limiting, and (ii) deep tillage does not come at the cost of impairing topsoil fertility. On sites with root restrictive soil layers, deep tillage can be an effective measure to mitigate drought stress and improve the resilience of crops. However, deep tillage should only be performed on soils with a stable structure, i.e. <70% silt content. We will discuss the contribution of deep tillage options to enhance the sustainability of agricultural production by facilitating the uptake of nutrients and water from the subsoil.

Science Investigations Enabled by Magnetic Field Measurements on the Lunar Surface

NASA Astrophysics Data System (ADS)

Chi, P. J.; Russell, C. T.; Strangeway, R. J.; Farrell, W. M.; Garrick-Bethell, I.; Taylor, P.

2018-02-01

We present examples of the geophysical and heliophysics investigations that can be performed with magnetic field measurements on the lunar surface enabled by the support/servicing of lunar landers from the Deep Space Gateway.

Multi-Object Spectroscopy with MUSE

NASA Astrophysics Data System (ADS)

Kelz, A.; Kamann, S.; Urrutia, T.; Weilbacher, P.; Bacon, R.

2016-10-01

Since 2014, MUSE, the Multi-Unit Spectroscopic Explorer, is in operation at the ESO-VLT. It combines a superb spatial sampling with a large wavelength coverage. By design, MUSE is an integral-field instrument, but its field-of-view and large multiplex make it a powerful tool for multi-object spectroscopy too. Every data-cube consists of 90,000 image-sliced spectra and 3700 monochromatic images. In autumn 2014, the observing programs with MUSE have commenced, with targets ranging from distant galaxies in the Hubble Deep Field to local stellar populations, star formation regions and globular clusters. This paper provides a brief summary of the key features of the MUSE instrument and its complex data reduction software. Some selected examples are given, how multi-object spectroscopy for hundreds of continuum and emission-line objects can be obtained in wide, deep and crowded fields with MUSE, without the classical need for any target pre-selection.

The BUFFALO HST Survey

NASA Astrophysics Data System (ADS)

Steinhardt, Charles; Jauzac, Mathilde; Capak, Peter; Koekemoer, Anton; Oesch, Pascal; Richard, Johan; Sharon, Keren q.; BUFFALO

2018-01-01

Beyond Ultra-deep Frontier Fields And Legacy Observations (BUFFALO) is an astronomical survey built around the six Hubble Space Telescope (HST) Frontier Fields clusters designed to learn about early galactic assembly and clustering and prepare targets for observations with the James Webb Space Telescope. BUFFALO will place significant new constraints on how and when the most massive and luminous galaxies in the universe formed and how early galaxy formation is linked to dark matter assembly. The same data will also probe the temperature and cross section of dark matter in the massive Frontier Fields galaxy clusters, and tell us how the dark matter, cluster gas, and dynamics of the clusters influence the galaxies in and around them. These studies are possible because the Spitzer Space Telescope, Chandra X-ray Observatory, XMM-Newton, and ground based telescopes have already invested heavily in deep observations around the Frontier Fields, so that the addition of HST observations can yield significant new results.

Resources for Hope: Ideas for Alternatives from Heterodox Higher Education Institutions

ERIC Educational Resources Information Center

Butcher, Catherine Norma

2017-01-01

This report describes my field visits to Berea and Deep Springs Colleges in the U.S.A. and explores their forms of ownership/control, governance, financing and organisational structure. Berea and Deep Springs are small, liberal arts colleges, distinctive in American higher education, in which students actively participate in a spirit of democracy.…

Practical considerations and nuances in anesthesia for patients undergoing deep brain stimulation implantation surgery.

PubMed

Scharpf, Danielle Teresa; Sharma, Mayur; Deogaonkar, Milind; Rezai, Ali; Bergese, Sergio D

2015-08-01

The field of functional neurosurgery has expanded in last decade to include newer indications, new devices, and new methods. This advancement has challenged anesthesia providers to adapt to these new requirements. This review aims to discuss the nuances and practical issues that are faced while administering anesthesia for deep brain stimulation surgery.

AEGIS-X: Deep Chandra Imaging of the Central Groth Strip

NASA Astrophysics Data System (ADS)

Nandra, K.; Laird, E. S.; Aird, J. A.; Salvato, M.; Georgakakis, A.; Barro, G.; Perez-Gonzalez, P. G.; Barmby, P.; Chary, R.-R.; Coil, A.; Cooper, M. C.; Davis, M.; Dickinson, M.; Faber, S. M.; Fazio, G. G.; Guhathakurta, P.; Gwyn, S.; Hsu, L.-T.; Huang, J.-S.; Ivison, R. J.; Koo, D. C.; Newman, J. A.; Rangel, C.; Yamada, T.; Willmer, C.

2015-09-01

We present the results of deep Chandra imaging of the central region of the Extended Groth Strip, the AEGIS-X Deep (AEGIS-XD) survey. When combined with previous Chandra observations of a wider area of the strip, AEGIS-X Wide (AEGIS-XW), these provide data to a nominal exposure depth of 800 ks in the three central ACIS-I fields, a region of approximately 0.29 deg2. This is currently the third deepest X-ray survey in existence; a factor ∼ 2-3 shallower than the Chandra Deep Fields (CDFs), but over an area ∼3 times greater than each CDF. We present a catalog of 937 point sources detected in the deep Chandra observations, along with identifications of our X-ray sources from deep ground-based, Spitzer, GALEX, and Hubble Space Telescope imaging. Using a likelihood ratio analysis, we associate multiband counterparts for 929/937 of our X-ray sources, with an estimated 95% reliability, making the identification completeness approximately 94% in a statistical sense. Reliable spectroscopic redshifts for 353 of our X-ray sources are available predominantly from Keck (DEEP2/3) and MMT Hectospec, so the current spectroscopic completeness is ∼38%. For the remainder of the X-ray sources, we compute photometric redshifts based on multiband photometry in up to 35 bands from the UV to mid-IR. Particular attention is given to the fact that the vast majority the X-ray sources are active galactic nuclei and require hybrid templates. Our photometric redshifts have mean accuracy of σ =0.04 and an outlier fraction of approximately 5%, reaching σ =0.03 with less than 4% outliers in the area covered by CANDELS . The X-ray, multiwavelength photometry, and redshift catalogs are made publicly available.

Accuracy of open magnetic resonance imaging for guiding injection of the equine deep digital flexor tendon within the hoof.

PubMed

Groom, Lauren M; White, Nathaniel A; Adams, M Norris; Barrett, Jennifer G

2017-11-01

Lesions of the distal deep digital flexor tendon (DDFT) are frequently diagnosed using MRI in horses with foot pain. Intralesional injection of biologic therapeutics shows promise in tendon healing; however, accurate injection of distal deep digital flexor tendon lesions within the hoof is difficult. The aim of this experimental study was to evaluate accuracy of a technique for injection of the deep digital flexor tendon within the hoof using MRI-guidance, which could be performed in standing patients. We hypothesized that injection of the distal deep digital flexor tendon within the hoof could be accurately guided using open low-field MRI to target either the lateral or medial lobe at a specific location. Ten cadaver limbs were positioned in an open, low-field MRI unit. Each distal deep digital flexor tendon lobe was assigned to have a proximal (adjacent to the proximal aspect of the navicular bursa) or distal (adjacent to the navicular bone) injection. A titanium needle was inserted into each tendon lobe, guided by T1-weighted transverse images acquired simultaneously during injection. Colored dye was injected as a marker and postinjection MRI and gross sections were assessed. The success of injection as evaluated on gross section was 85% (70% proximal, 100% distal). The success of injection as evaluated by MRI was 65% (60% proximal, 70% distal). There was no significant difference between the success of injecting the medial versus lateral lobe. The major limitation of this study was the use of cadaver limbs with normal tendons. The authors conclude that injection of the distal deep digital flexor tendon within the hoof is possible using MRI guidance. © 2017 American College of Veterinary Radiology.

A survey on deep learning in medical image analysis.

PubMed

Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

2017-12-01

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

Research on Daily Objects Detection Based on Deep Neural Network

NASA Astrophysics Data System (ADS)

Ding, Sheng; Zhao, Kun

2018-03-01

With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Around 1500 near-Earth-asteroid orbits improved via EURONEAR

NASA Astrophysics Data System (ADS)

Vaduvescu, O.; Hudin, L.; Birlan, M.; Popescu, M.; Tudorica, A.; Toma, R.

2014-07-01

Born in 2006 in Paris, the European Near Earth Asteroids Research project (EURONEAR, euronear.imcce.fr) aims ''to study NEAs and PHAs using existing telescopes available to its network and hopefully in the future some automated dedicated 1--2 m facilities''. Although we believe the first aim is fulfilled, the second was not achieved yet, requiring serious commitment from the European NEA researchers and funding agencies. Mainly using free labor by about 30 students and amateur astronomers (from Romania, Chile, UK, France, etc), the PI backed up by his associates M. Birlan (IMCCE Paris) and J. Licandro (IAC Tenerife) and a few other astronomers of the EURONEAR network having access to a few telescopes are approaching around 1,500 observed NEAs whose orbits were improved based on our astrometric contributions. To achive this milestone, we used two main resources and a total of 15 facilities: i) Observing time obtained at 11 professional 1--4 m class telescopes (Chile, La Palma, France, Germany) plus 3 smaller 30--50 cm educational/public outreach telescopes (Romania and Germany) adding about 1,000 observed NEAs; and ii) astrometry obtained from data mining of 4 major image archives (ESO/MPG WFI, INT WFC, CFHTLS Megacam and Subaru SuprimeCam) adding about 500 NEAs recovered in archival images. Among the highlights, about 100 NEAs, PHAs and VIs were observed, recovered or precovered in archives at their second opposition (up to about 15 years away from discovery) or have their orbital arc much extended, and a few VIs and PHAs were eliminated. Incidentally, about 15,000 positions of almost 2,000 known MBAs were reported (mostly in the INT, ESO/MPG and Blanco large fields). About 40 new (one night) NEO candidates and more than 2,000 (one night) unknown MBAs were reported, including about 150 MBAs credited as EURONEAR discoveries. Based on the INT and Blanco data we derived some statistics about the MBA and NEA population observable with 2m and 4m telescopes, proposing a model to rate the NEO candidates observed close to opposition. Based on this work, 10 papers and around 100 MPC circulars were published since 2006.

Far-Ultraviolet Number Counts of Field Galaxies

NASA Technical Reports Server (NTRS)

Voyer, Elysse N.; Gardner, Jonathan P.; Teplitz, Harry I.; Siana, Brian D.; deMello, Duilia F.

2010-01-01

The Number counts of far-ultraviolet (FUV) galaxies as a function of magnitude provide a direct statistical measure of the density and evolution of star-forming galaxies. We report on the results of measurements of the rest-frame FUV number counts computed from data of several fields including the Hubble Ultra Deep Field, the Hubble Deep Field North, and the GOODS-North and -South fields. These data were obtained from the Hubble Space Telescope Solar Blind Channel of the Advance Camera for Surveys. The number counts cover an AB magnitude range from 20-29 magnitudes, covering a total area of 15.9 arcmin'. We show that the number counts are lower than those in previous studies using smaller areas. The differences in the counts are likely the result of cosmic variance; our new data cover more area and more lines of sight than the previous studies. The slope of our number counts connects well with local FUV counts and they show good agreement with recent semi-analytical models based on dark matter "merger trees".

A Parameter-Free Dynamic Alternative to Hyper-Viscosity for Coupled Transport Equations: Application to the Simulation of 3D Squall Lines Using Spectral Elements

DTIC Science & Technology

2015-06-04

that involve physics coupling with phase change in the simulation of 3D deep convection. We show that the VMS+DC approach is a robust technique that can...of 3D deep convection. We show that the VMS+DC approach is a robust technique that can damp the high order modes characterizing the spectral element...of Spectral Elements, Deep Convection, Kessler Microphysics Preprint J. Comput. Phys. 283 (2015) 360-373 June 4, 2015 1. Introduction In the field of

Deep Imaging of the HCG 95 Field. I. Ultra-diffuse Galaxies

NASA Astrophysics Data System (ADS)

Shi, Dong Dong; Zheng, Xian Zhong; Zhao, Hai Bin; Pan, Zhi Zheng; Li, Bin; Zou, Hu; Zhou, Xu; Guo, KeXin; An, Fang Xia; Li, Yu Bin

2017-09-01

We present a detection of 89 candidates of ultra-diffuse galaxies (UDGs) in a 4.9 degree2 field centered on the Hickson Compact Group 95 (HCG 95) using deep g- and r-band images taken with the Chinese Near Object Survey Telescope. This field contains one rich galaxy cluster (Abell 2588 at z = 0.199) and two poor clusters (Pegasus I at z = 0.013 and Pegasus II at z = 0.040). The 89 candidates are likely associated with the two poor clusters, giving about 50-60 true UDGs with a half-light radius {r}{{e}}> 1.5 {kpc} and a central surface brightness μ (g,0)> 24.0 mag arcsec-2. Deep z\\prime -band images are available for 84 of the 89 galaxies from the Dark Energy Camera Legacy Survey (DECaLS), confirming that these galaxies have an extremely low central surface brightness. Moreover, our UDG candidates are spread over a wide range in g - r color, and ˜26% are as blue as normal star-forming galaxies, which is suggestive of young UDGs that are still in formation. Interestingly, we find that one UDG linked with HCG 95 is a gas-rich galaxy with H I mass 1.1× {10}9 M ⊙ detected by the Very Large Array, and has a stellar mass of {M}\\star ˜ 1.8× {10}8 M ⊙. This indicates that UDGs at least partially overlap with the population of nearly dark galaxies found in deep H I surveys. Our results show that the high abundance of blue UDGs in the HCG 95 field is favored by the environment of poor galaxy clusters residing in H I-rich large-scale structures.

X-UDS: The Chandra Legacy Survey of the UKIDSS Ultra Deep Survey Field

NASA Astrophysics Data System (ADS)

Kocevski, Dale D.; Hasinger, Guenther; Brightman, Murray; Nandra, Kirpal; Georgakakis, Antonis; Cappelluti, Nico; Civano, Francesca; Li, Yuxuan; Li, Yanxia; Aird, James; Alexander, David M.; Almaini, Omar; Brusa, Marcella; Buchner, Johannes; Comastri, Andrea; Conselice, Christopher J.; Dickinson, Mark A.; Finoguenov, Alexis; Gilli, Roberto; Koekemoer, Anton M.; Miyaji, Takamitsu; Mullaney, James R.; Papovich, Casey; Rosario, David; Salvato, Mara; Silverman, John D.; Somerville, Rachel S.; Ueda, Yoshihiro

2018-06-01

We present the X-UDS survey, a set of wide and deep Chandra observations of the Subaru-XMM Deep/UKIDSS Ultra Deep Survey (SXDS/UDS) field. The survey consists of 25 observations that cover a total area of 0.33 deg2. The observations are combined to provide a nominal depth of ∼600 ks in the central 100 arcmin2 region of the field that has been imaged with Hubble/WFC3 by the CANDELS survey and ∼200 ks in the remainder of the field. In this paper, we outline the survey’s scientific goals, describe our observing strategy, and detail our data reduction and point source detection algorithms. Our analysis has resulted in a total of 868 band-merged point sources detected with a false-positive Poisson probability of <1 × 10‑4. In addition, we present the results of an X-ray spectral analysis and provide best-fitting neutral hydrogen column densities, N H, as well as a sample of 51 Compton-thick active galactic nucleus candidates. Using this sample, we find the intrinsic Compton-thick fraction to be 30%–35% over a wide range in redshift (z = 0.1–3), suggesting the obscured fraction does not evolve very strongly with epoch. However, if we assume that the Compton-thick fraction is dependent on luminosity, as is seen for Compton-thin sources, then our results are consistent with a rise in the obscured fraction out to z ∼ 3. Finally, an examination of the host morphologies of our Compton-thick candidates shows a high fraction of morphological disturbances, in agreement with our previous results. All data products described in this paper are made available via a public website.

A simple prescription for simulating and characterizing gravitational arcs

NASA Astrophysics Data System (ADS)

Furlanetto, C.; Santiago, B. X.; Makler, M.; de Bom, C.; Brandt, C. H.; Neto, A. F.; Ferreira, P. C.; da Costa, L. N.; Maia, M. A. G.

2013-01-01

Simple models of gravitational arcs are crucial for simulating large samples of these objects with full control of the input parameters. These models also provide approximate and automated estimates of the shape and structure of the arcs, which are necessary for detecting and characterizing these objects on massive wide-area imaging surveys. We here present and explore the ArcEllipse, a simple prescription for creating objects with a shape similar to gravitational arcs. We also present PaintArcs, which is a code that couples this geometrical form with a brightness distribution and adds the resulting object to images. Finally, we introduce ArcFitting, which is a tool that fits ArcEllipses to images of real gravitational arcs. We validate this fitting technique using simulated arcs and apply it to CFHTLS and HST images of tangential arcs around clusters of galaxies. Our simple ArcEllipse model for the arc, associated to a Sérsic profile for the source, recovers the total signal in real images typically within 10%-30%. The ArcEllipse+Sérsic models also automatically recover visual estimates of length-to-width ratios of real arcs. Residual maps between data and model images reveal the incidence of arc substructure. They may thus be used as a diagnostic for arcs formed by the merging of multiple images. The incidence of these substructures is the main factor that prevents ArcEllipse models from accurately describing real lensed systems.

A CONSTRAINT ON QUASAR CLUSTERING AT z = 5 FROM A BINARY QUASAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGreer, Ian D.; Fan, Xiaohui; Eftekharzadeh, Sarah

2016-03-15

We report the discovery of a quasar pair at z = 5 separated by 21″. Both objects were identified as quasar candidates using simple color selection techniques applied to photometric catalogs from the Canada–France–Hawaii Telescope (CFHT) Legacy Survey (CFHTLS). Spectra obtained with the MMT present no discernible offset in redshift between the two objects; on the other hand, there are clear differences in the emission line profiles and in the multiwavelength spectral energy distributions that strongly disfavor the hypothesis that they are gravitationally lensed images of a single quasar. Both quasars are surprisingly bright given their proximity (a projected separation of ∼135more » kpc), with i = 19.4 and i = 21.4. Previous measurements of the luminosity function demonstrate that luminous quasars are extremely rare at z = 5; the existence of this pair suggests that quasars have strong small-scale clustering at high redshift. Assuming a real-space correlation function of the form ξ(r) ∝ (r/r{sub 0}){sup −2}, this discovery implies a correlation length of r{sub 0} ≳ 20h{sup −1} Mpc, consistent with a rapid strengthening of quasar clustering at high redshift as seen in previous observations and predicted by theoretical models where feedback effects are inefficient at shutting down black hole growth at high redshift.« less

MIGHTEE: The MeerKAT International GHz Tiered Extragalactic Exploration

NASA Astrophysics Data System (ADS)

Taylor, A. Russ; Jarvis, Matt

2017-05-01

The MeerKAT telescope is the precursor of the Square Kilometre Array mid-frequency dish array to be deployed later this decade on the African continent. MIGHTEE is one of the MeerKAT large survey projects designed to pathfind SKA key science in cosmology and galaxy evolution. Through a tiered radio continuum deep imaging project including several fields totaling 20 square degrees to microJy sensitivities and an ultra-deep image of a single 1 square degree field of view, MIGHTEE will explore dark matter and large scale structure, the evolution of galaxies, including AGN activity and star formation as a function of cosmic time and environment, the emergence and evolution of magnetic fields in galaxies, and the magnetic counter part to large scale structure of the universe.

Extensive young silicic volcanism produces large deep submarine lava flows in the NE Lau Basin

NASA Astrophysics Data System (ADS)

Embley, Robert W.; Rubin, Kenneth H.

2018-04-01

New field observations reveal that extensive (up to 402 km2) aphyric, glassy dacite lavas were erupted at multiple sites in the recent past in the NE Lau basin, located about 200 km southwest of Samoa. This discovery of volumetrically significant and widespread submarine dacite lava flows extends the domain for siliceous effusive volcanism into the deep seafloor. Although several lava flow fields were discovered on the flank of a large silicic seamount, Niuatahi, two of the largest lava fields and several smaller ones ("northern lava flow fields") were found well north of the seamount. The most distal portion of the northernmost of these fields is 60 km north of the center of Niuatahi caldera. We estimate that lava flow lengths from probable eruptive vents to the distal ends of flows range from a few km to more than 10 km. Camera tows on the shallower, near-vent areas show complex lava morphology that includes anastomosing tube-like pillow flows and ropey surfaces, endogenous domes and/or ridges, some with "crease-like" extrusion ridges, and inflated lobes with extrusion structures. A 2 × 1.5 km, 30-m deep depression could be an eruption center for one of the lava flow fields. The Lau lava flow fields appear to have erupted at presumptive high effusion rates and possibly reduced viscosity induced by presumptive high magmatic water content and/or a high eruption temperature, consistent with both erupted composition ( 66% SiO2) and glassy low crystallinity groundmass textures. The large areal extent (236 km2) and relatively small range of compositional variation ( σ = 0.60 for wt% Si02%) within the northern lava flow fields imply the existence of large, eruptible batches of differentiated melt in the upper mantle or lower crust of the NE Lau basin. At this site, the volcanism could be controlled by deep crustal fractures caused by the long-term extension in this rear-arc region. Submarine dacite flows exhibiting similar morphology have been described in ancient sequences from the Archaean through the Miocene and in small batches on present-day seafloor spreading centers. This study shows that extensive siliceous lavas can erupt on the modern seafloor under the right conditions.

Shaping field for deep tissue microscopy

NASA Astrophysics Data System (ADS)

Colon, J.; Lim, H.

2015-05-01

Information capacity of a lossless image-forming system is a conserved property determined by two imaging parameters - the resolution and the field of view (FOV). Adaptive optics improves the former by manipulating the phase, or wavefront, in the pupil plane. Here we describe a homologous approach, namely adaptive field microscopy, which aims to enhance the FOV by controlling the phase, or defocus, in the focal plane. In deep tissue imaging, the useful FOV can be severely limited if the region of interest is buried in a thick sample and not perpendicular to the optic axis. One must acquire many z-scans and reconstruct by post-processing, which exposes tissue to excessive radiation and is also time consuming. We demonstrate the effective FOV can be substantially enhanced by dynamic control of the image plane. Specifically, the tilt of the image plane is continuously adjusted in situ to match the oblique orientation of the sample plane within tissue. The utility of adaptive field microscopy is tested for imaging tissue with non-planar morphology. Ocular tissue of small animals was imaged by two-photon excited fluorescence. Our results show that adaptive field microscopy can utilize the full FOV. The freedom to adjust the image plane to account for the geometrical variations of sample could be extremely useful for 3D biological imaging. Furthermore, it could facilitate rapid surveillance of cellular features within deep tissue while avoiding photo damages, making it suitable for in vivo imaging.

Implications of the Deep Minimum for Slow Solar Wind Origin

NASA Astrophysics Data System (ADS)

Antiochos, S. K.; Mikic, Z.; Lionello, R.; Titov, V. S.; Linker, J. A.

2009-12-01

The origin of the slow solar wind has long been one of the most important problems in solar/heliospheric physics. Two observational constraints make this problem especially challenging. First, the slow wind has the composition of the closed-field corona, unlike the fast wind that originates on open field lines. Second, the slow wind has substantial angular extent, of order 30 degrees, which is much larger than the widths observed for streamer stalks or the widths expected theoretically for a dynamic heliospheric current sheet. We propose that the slow wind originates from an intricate network of narrow (possibly singular) open-field corridors that emanate from the polar coronal hole regions. Using topological arguments, we show that these corridors must be ubiquitous in the solar corona. The total solar eclipse in August 2008, near the lowest point of the Deep Minimum, affords an ideal opportunity to test this theory by using the ultra-high resolution Predictive Science's (PSI) eclipse model for the corona and wind. Analysis of the PSI eclipse model demonstrates that the extent and scales of the open-field corridors can account for both the angular width of the slow wind and its closed-field composition. We discuss the implications of our slow wind theory for the structure of the corona and heliosphere at the Deep Minimum and describe further observational and theoretical tests. This work has been supported by the NASA HTP, SR&T, and LWS programs.

Deep erosions of the palmar aspect of the navicular bone diagnosed by standing magnetic resonance imaging.

PubMed

Sherlock, C; Mair, T; Blunden, T

2008-11-01

Erosion of the palmar (flexor) aspect of the navicular bone is difficult to diagnose with conventional imaging techniques. To review the clinical, magnetic resonance (MR) and pathological features of deep erosions of the palmar aspect of the navicular bone. Cases of deep erosions of the palmar aspect of the navicular bone, diagnosed by standing low field MR imaging, were selected. Clinical details, results of diagnostic procedures, MR features and pathological findings were reviewed. Deep erosions of the palmar aspect of the navicular bone were diagnosed in 16 mature horses, 6 of which were bilaterally lame. Sudden onset of lameness was recorded in 63%. Radiography prior to MR imaging showed equivocal changes in 7 horses. The MR features consisted of focal areas of intermediate or high signal intensity on T1-, T2*- and T2-weighted images and STIR images affecting the dorsal aspect of the deep digital flexor tendon, the fibrocartilage of the palmar aspect, subchondral compact bone and medulla of the navicular bone. On follow-up, 7/16 horses (44%) had been subjected to euthanasia and only one was being worked at its previous level. Erosions of the palmar aspect of the navicular bone were confirmed post mortem in 2 horses. Histologically, the lesions were characterised by localised degeneration of fibrocartilage with underlying focal osteonecrosis and fibroplasia. The adjacent deep digital flexor tendon showed fibril formation and fibrocartilaginous metaplasia. Deep erosions of the palmar aspect of the navicular bone are more easily diagnosed by standing low field MR imaging than by conventional radiography. The lesions involve degeneration of the palmar fibrocartilage with underlying osteonecrosis and fibroplasia affecting the subchondral compact bone and medulla, and carry a poor prognosis for return to performance. Diagnosis of shallow erosive lesions of the palmar fibrocartilage may allow therapeutic intervention earlier in the disease process, thereby preventing progression to deep erosive lesions.

Incorporating "Virtual" and "Real World" Field Trips into Introductory Geography Modules

ERIC Educational Resources Information Center

Friess, Daniel A.; Oliver, Grahame J. H.; Quak, Michelle S. Y.; Lau, Annie Y. A.

2016-01-01

The "field trip" is a key pedagogical tool within geographical education to encourage deep learning, though they are increasingly difficult to implement due to reduced budgets, safety concerns and increasing class sizes. We incorporated three field-learning activities into a large introductory module. A traditional staff-led trip was the…

Anomalous sea surface structures as an object of statistical topography

NASA Astrophysics Data System (ADS)

Klyatskin, V. I.; Koshel, K. V.

2015-06-01

By exploiting ideas of statistical topography, we analyze the stochastic boundary problem of emergence of anomalous high structures on the sea surface. The kinematic boundary condition on the sea surface is assumed to be a closed stochastic quasilinear equation. Applying the stochastic Liouville equation, and presuming the stochastic nature of a given hydrodynamic velocity field within the diffusion approximation, we derive an equation for a spatially single-point, simultaneous joint probability density of the surface elevation field and its gradient. An important feature of the model is that it accounts for stochastic bottom irregularities as one, but not a single, perturbation. Hence, we address the assumption of the infinitely deep ocean to obtain statistic features of the surface elevation field and the squared elevation gradient field. According to the calculations, we show that clustering in the absolute surface elevation gradient field happens with the unit probability. It results in the emergence of rare events such as anomalous high structures and deep gaps on the sea surface almost in every realization of a stochastic velocity field.

Hubble Space Telescope Medium Deep Survey. 2: Deconvolution of Wide Field Camera field galaxy images in the 13 hour + 43 deg field

NASA Technical Reports Server (NTRS)

Windhorst, R. A.; Schmidtke, P. C.; Pascarelle, S. M.; Gordon, J. M.; Griffiths, R. E.; Ratnatunga, K. U.; Neuschaefer, L. W.; Ellis, R. S.; Gilmore, G.; Glazebrook, K.

1994-01-01

We present isophotal profiles of six faint field galaxies from some of the first deep images taken for the Hubble Space Telescope (HST) Medium Deep Survey (MDS). These have redshifts in the range z = 0.126 to 0.402. The images were taken with the Wide Field Camera (WFC) in `parallel mode' and deconvolved with the Lucy method using as the point-spread function nearby stars in the image stack. The WFC deconvolutions have a dynamic range of 16 to 20 dB (4 to 5 mag) and an effective resolution approximately less than 0.2 sec (FWHM). The multiorbit HST images allow us to trace the morphology, light profiles, and color gradients of faint field galaxies down to V approximately equal to 22 to 23 mag at sub-kpc resolution, since the redshift range covered is z = 0.1 to 0.4. The goals of the MDS are to study the sub-kpc scale morphology, light profiles, and color gradients for a large samole of faint field galaxies down to V approximately equal to 23 mag, and to trace the fraction of early to late-type galaxies as function of cosmic time. In this paper we study the brighter MDS galaxies in the 13 hour + 43 deg MDS field in detail, and investigate to what extent model fits with pure exponential disks or a(exp 1/4) bulges are justified at V approximately less than 22 mag. Four of the six field galaxies have light profiles that indicate (small) inner bulges following r(exp 1/4) laws down to 0.2 sec resolution, plus a dominant surrounding exponential disk with little or no color gradients. Two occur in a group at z = 0.401, two are barred spiral galaxies at z = 0.179 and z = 0.302, and two are rather subluminous (and edge-on) disk galaxies at z = 0.126 and z = 0.179. Our deep MDS images can detect galaxies down to V, I approximately less than 25 to 26 mag, and demonstrate the impressive potential of HST--even with its pre-refurbished optics--to resolve morphological details in galaxies at cosmologically significant distances (v approximately less than 23 mag). Since the median redshift of these galaxies is approximately less than 0.4, the HST resolution allows us to study sub kpc size scales at the galaxy, which cannot be done with stable images over wide fields from the best ground-based sites.

Downscaling ocean conditions with application to the Gulf of Maine, Scotian Shelf and adjacent deep ocean

NASA Astrophysics Data System (ADS)

Katavouta, Anna; Thompson, Keith

2017-04-01

A high resolution regional model (1/36 degree) of the Gulf of Maine, Scotian Shelf and adjacent deep ocean (GoMSS) is developed to downscale ocean conditions from an existing global operational system. First, predictions from the regional GoMSS model in a one-way nesting set up are evaluated using observations from multiple sources including satellite-borne sensors of surface temperature and sea level, CTDs, Argo floats and moored current meters. It is shown that on the shelf, the regional model predicts more realistic fields than the global system because it has higher resolution and includes tides that are absent from the global system. However, in deep water the regional model misplaces deep ocean eddies and meanders associated with the Gulf Stream. This is because of unrealistic internally generated variability (associated with the one-way nesting set up) that leads to decoupling of the regional model from the global system in the deep water. To overcome this problem, the large scales (length scales > 90 km) of the regional model are spectrally nudged towards the global system fields. This leads to more realistic predictions off the shelf. Wavenumber spectra show that even though spectral nudging constrains the large scales, it does not suppress the variability on small scales; on the contrary, it favours the formation of eddies with length scales below the cut-off wavelength of the spectral nudging.

Positron deep level transient spectroscopy — a new application of positron annihilation to semiconductor physics

NASA Astrophysics Data System (ADS)

Beling, C. D.; Fung, S.; Au, H. L.; Ling, C. C.; Reddy, C. V.; Deng, A. H.; Panda, B. K.

1997-05-01

Recent positron mobility and lifetime measurements made on ac-biased metal on semi-insulating GaAs junctions, which have identified the native EL2 defect through a determination of the characteristic ionization energy of the donor level, are reviewed. It is shown that these measurements point towards a new spectroscopy, tentatively named positron-DLTS (deep level transient spectroscopy), that is the direct complement to conventional DLTS in that it monitors transients in the electric field of the depletion region rather than the inversely related depletion width, as deep levels undergo ionization. In this new spectroscopy, which may be applied to doped material by use of a suitable positron beam, electric field transients are monitored through the Doppler shift of the annihilation radiation resulting from the drift velocity of the positron in the depletion region. Two useful extensions of the new spectroscopy beyond conventional capacitance-DLTS are suggested. The first is that in some instances information on the microstructure of the defect causing the deep level may be inferred from the sensitivity of the positron to vacancy defects of negative and neutral charge states. The second is that the positron annihilation technique is intrinsically much faster than conventional DLTS with the capability of observing transients some 10 6 times faster, thus allowing deep levels (and even shallow levels) to be investigated without problems associated with carrier freeze-out.

Deep Carbon Observatory investigates Carbon from Crust to Core: An Academic Record of the History of Deep Carbon Science

NASA Astrophysics Data System (ADS)

Mitton, S. A.

2017-12-01

Carbon plays an unparalleled role in our lives: as the element of life, as the basis of most of society's energy, as the backbone of most new materials, and as the central focus in efforts to understand Earth's variable and uncertain climate. Yet in spite of carbon's importance, scientists remain largely ignorant of the physical, chemical, and biological behavior of many of Earth's carbon-bearing systems. The Deep Carbon Observatory (DCO) is a global research program to transform our understanding of carbon in Earth. At its heart, DCO is a community of scientists, from biologists to physicists, geoscientists to chemists, and many others whose work crosses these disciplinary lines, forging a new, integrative field of deep carbon science. As a historian of science, I specialise in the history of planetary science and astronomy since 1900. This is directed toward understanding of the history of the steps on the road to discovering the internal dynamics of our planet. Within a framework that describes the historical background to the new field of Earth System Science, I present the first history of deep carbon science. This project will identifies the key discoveries of deep carbon science. It will assess the impact of new knowledge on geochemistry, geodynamics, and geobiology. The project will lead to publication, in book form in 2019, of an illuminating narrative that will highlight the engaging human stories of many remarkable scientists and natural philosophers from whom we have learned about the complexity of Earth's internal world. On this journey of discovery we will encounter not just the pioneering researchers of deep carbon science, but also their institutions, their instrumental inventiveness, and their passion for exploration. The book is organised thematically around the four communities of the Deep Carbon Observatory: Deep Life, Extreme Physics and Chemistry, Reservoirs and Fluxes, and Deep Energy. The presentation has a gallery and list of Deep Carbon Pioneers. As a biographer, I am keenly searching for people who may have been overlooked in the standard accounts of the historical development of geology, geodynamics, and the study of subsurface life. Whom would you choose as pioneers? Can you nominate a colleague, or even add a selfie? Do you have a standout story or personal recollection to enrich my chronicle?

Efficient collective swimming by harnessing vortices through deep reinforcement learning.

PubMed

Verma, Siddhartha; Novati, Guido; Koumoutsakos, Petros

2018-06-05

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long-short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, "smart swimmer(s)" place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

Grass control improves early growth of black walnut more than either deep ripping or irrigation

Treesearch

J.W. Van Sambeek; F.D. McBride

1991-01-01

Chemical control of a tall fescue sod (Festuca arundinacea Schreb.) using glyphosate and simazine improved early tree growth of black walnut (Juglans nigra L.) more than either deep ripping or irrigation on an upland old field site in southern Illinois. Growth of trees with irrigation and grass control was less than with grass...

Squeeze-SegNet: a new fast deep convolutional neural network for semantic segmentation

NASA Astrophysics Data System (ADS)

Nanfack, Geraldin; Elhassouny, Azeddine; Oulad Haj Thami, Rachid

2018-04-01

The recent researches in Deep Convolutional Neural Network have focused their attention on improving accuracy that provide significant advances. However, if they were limited to classification tasks, nowadays with contributions from Scientific Communities who are embarking in this field, they have become very useful in higher level tasks such as object detection and pixel-wise semantic segmentation. Thus, brilliant ideas in the field of semantic segmentation with deep learning have completed the state of the art of accuracy, however this architectures become very difficult to apply in embedded systems as is the case for autonomous driving. We present a new Deep fully Convolutional Neural Network for pixel-wise semantic segmentation which we call Squeeze-SegNet. The architecture is based on Encoder-Decoder style. We use a SqueezeNet-like encoder and a decoder formed by our proposed squeeze-decoder module and upsample layer using downsample indices like in SegNet and we add a deconvolution layer to provide final multi-channel feature map. On datasets like Camvid or City-states, our net gets SegNet-level accuracy with less than 10 times fewer parameters than SegNet.

SOLAR WAVE-FIELD SIMULATION FOR TESTING PROSPECTS OF HELIOSEISMIC MEASUREMENTS OF DEEP MERIDIONAL FLOWS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartlep, T.; Zhao, J.; Kosovichev, A. G.

2013-01-10

The meridional flow in the Sun is an axisymmetric flow that is generally directed poleward at the surface, and is presumed to be of fundamental importance in the generation and transport of magnetic fields. Its true shape and strength, however, are debated. We present a numerical simulation of helioseismic wave propagation in the whole solar interior in the presence of a prescribed, stationary, single-cell, deep meridional circulation serving as synthetic data for helioseismic measurement techniques. A deep-focusing time-distance helioseismology technique is applied to the synthetic data, showing that it can in fact be used to measure the effects of themore » meridional flow very deep in the solar convection zone. It is shown that the ray approximation that is commonly used for interpretation of helioseismology measurements remains a reasonable approximation even for very long distances between 12 Degree-Sign and 42 Degree-Sign corresponding to depths between 52 and 195 Mm. From the measurement noise, we extrapolate that time-resolved observations on the order of a full solar cycle may be needed to probe the flow all the way to the base of the convection zone.« less

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

NASA Astrophysics Data System (ADS)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Investigating Jupiter's Deep Flow Structure using the Juno Magnetic and Gravity Measurements

NASA Astrophysics Data System (ADS)

Duer, K.; Galanti, E.; Cao, H.; Kaspi, Y.

2017-12-01

Jupiter's flow below its cloud-level is still largely unknown. The gravity measurements from Juno provide now an initial insight into the depth of the flow via the relation between the gravity field and the flow field. Furthermore, additional constraints could be put on the flow if the expected Juno magnetic measurements are also used. Specifically, the gravity and magnetic measurements can be combined to allow a more robust estimate of the deep flow structure. However, a complexity comes from the fact that both the radial profile of the flow, and it's connection to the induced magnetic field, might vary with latitude. In this study we propose a method for using the expected Juno's high-precision measurements of both the magnetic and gravity fields, together with latitude dependent models that relate the measurements to the structure of the internal flow. We simulate possible measurements by setting-up specific deep wind profiles and forward calculate the resulting anomalies in both the magnetic and gravity fields. We allow these profiles to include also latitude dependency. The relation of the flow field to the gravity field is based on thermal wind balance, and it's relation to the magnetic field is via a mean-field electrodynamics balance. The latter includes an alpha-effect, describing the mean magnetic effect of turbulent rotating convection, which might also vary with latitude. Using an adjoint based optimization process, we examine the ability of the combined magnetic-gravity model to decipher the flow structure under the different potential Juno measurements. We investigate the effect of different latitude dependencies on the derived solutions and their associated uncertainties. The novelty of this study is the combination of two independent Juno measurements for the calculation of a latitudinal dependent interior flow profile. This method might lead to a better constraint of Jupiter's flow structure.

Progress on applications of high temperature superconducting microwave filters

NASA Astrophysics Data System (ADS)

Chunguang, Li; Xu, Wang; Jia, Wang; Liang, Sun; Yusheng, He

2017-07-01

In the past two decades, various kinds of high performance high temperature superconducting (HTS) filters have been constructed and the HTS filters and their front-end subsystems have been successfully applied in many fields. The HTS filters with small insertion loss, narrow bandwidth, flat in-band group delay, deep out-of-band rejection, and steep skirt slope are reviewed. Novel HTS filter design technologies, including those in high power handling filters, multiband filters and frequency tunable filters, are reviewed, as well as the all-HTS integrated front-end receivers. The successful applications to various civilian fields, such as mobile communication, radar, deep space detection, and satellite technology, are also reviewed.

Infrared Faint Radio Sources in the Extended Chandra Deep Field South

NASA Astrophysics Data System (ADS)

Huynh, Minh T.

2009-01-01

Infrared-Faint Radio Sources (IFRSs) are a class of radio objects found in the Australia Telescope Large Area Survey (ATLAS) which have no observable counterpart in the Spitzer Wide-area Infrared Extragalactic Survey (SWIRE). The extended Chandra Deep Field South now has even deeper Spitzer imaging (3.6 to 70 micron) from a number of Legacy surveys. We report the detections of two IFRS sources in IRAC images. The non-detection of two other IFRSs allows us to constrain the source type. Detailed modeling of the SED of these objects shows that they are consistent with high redshift AGN (z > 2).

VizieR Online Data Catalog: Merging galaxies with tidal tails in COSMOS to z=1 (Wen+, 2016)

NASA Astrophysics Data System (ADS)

Wen, Z. Z.; Zheng, X. Z.

2017-02-01

Our study utilizes the public data and catalogs from multi-band deep surveys of the COSMOS field. The UltraVISTA survey (McCracken+ 2012, J/A+A/544/A156) provides ultra-deep near-IR imaging observations of this field in the Y,J,H, and Ks-band, as well as a narrow band (NB118). The HST/ACS I-band imaging data are publicly available, allowing us to measure morphologies in the rest-frame optical for galaxies at z<=1. The HST/ACS I-band images reach a 5σ depth of 27.2 magnitude for point sources. (1 data file).

Magnetoresistive flux focusing eddy current flaw detection

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor); Simpson, John W. (Inventor); Namkung, Min (Inventor)

2005-01-01

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil's longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multilayer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

Cortical depth dependent population receptive field attraction by spatial attention in human V1.

PubMed

Klein, Barrie P; Fracasso, Alessio; van Dijk, Jelle A; Paffen, Chris L E; Te Pas, Susan F; Dumoulin, Serge O

2018-04-27

Visual spatial attention concentrates neural resources at the attended location. Recently, we demonstrated that voluntary spatial attention attracts population receptive fields (pRFs) toward its location throughout the visual hierarchy. Theoretically, both a feed forward or feedback mechanism could underlie pRF attraction in a given cortical area. Here, we use sub-millimeter ultra-high field functional MRI to measure pRF attraction across cortical depth and assess the contribution of feed forward and feedback signals to pRF attraction. In line with previous findings, we find consistent attraction of pRFs with voluntary spatial attention in V1. When assessed as a function of cortical depth, we find pRF attraction in every cortical portion (deep, center and superficial), although the attraction is strongest in deep cortical portions (near the gray-white matter boundary). Following the organization of feed forward and feedback processing across V1, we speculate that a mixture of feed forward and feedback processing underlies pRF attraction in V1. Specifically, we propose that feedback processing contributes to the pRF attraction in deep cortical portions. Copyright © 2018. Published by Elsevier Inc.

Magnetoresistive Flux Focusing Eddy Current Flaw Detection

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor); Namkung, Min (Inventor); Simpson, John W. (Inventor)

2005-01-01

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil s longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multi-layer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

The VIRMOS deep imaging survey. I. Overview, survey strategy, and CFH12K observations

NASA Astrophysics Data System (ADS)

Le Fèvre, O.; Mellier, Y.; McCracken, H. J.; Foucaud, S.; Gwyn, S.; Radovich, M.; Dantel-Fort, M.; Bertin, E.; Moreau, C.; Cuillandre, J.-C.; Pierre, M.; Le Brun, V.; Mazure, A.; Tresse, L.

2004-04-01

This paper describes the CFH12K-VIRMOS survey: a deep BVRI imaging survey in four fields totalling more than 17 deg2, conducted with the 40×30 arcmin2 field CFH-12K camera. The survey is intended to be a multi-purpose survey used for a variety of science goals, including surveys of very high redshift galaxies and weak lensing studies. Four high galactic latitude fields, each 2×2 deg2, have been selected along the celestial equator: 0226-04, 1003+01, 1400+05, and 2217+00. The 16 deg2 of the ``wide'' survey are covered with exposure times of 2 hr, 1.5 hr, 1 hr, 1 hr, respectively while the 1.3×1 deg2 area of the ``deep'' survey at the center of the 0226-04 field is covered with exposure times of 7 h, 4.5 h, 3 h, 3 h, in BVRI respectively. An additional area ˜2 deg2 has been imaged in the 0226-04 field corresponding to the area surveyed by the XMM-LSS program \\citep{pierre03}. The data is pipeline processed at the Terapix facility at the Institut d'Astrophysique de Paris to produce large mosaic images. The catalogs produced contain the positions, shapes, total and aperture magnitudes for 2.175 million objects measured in the four areas. The limiting magnitudes, measured as a 5σ measurement in a 3 arcsec diameter aperture is IAB=24.8 in the ``Wide'' areas, and IAB=25.3 in the deep area. Careful quality control has been applied on the data to ensure internal consistency and assess the photometric and astrometric accuracy as described in a joint paper \\citep{mccracken03}. These catalogs are used to select targets for the VIRMOS-VLT Deep Survey, a large spectroscopic survey of the distant universe (Le Fèvre et al. 2003). First results from the CFH12K-VIRMOS survey have been published on weak lensing (e.g. van Waerbeke & Mellier 2003). Catalogs and images are available through the VIRMOS database environment under Oracle (http://www.oamp.fr/cencos). They are open for general use since July 1st, 2003. Appendix A is only available in electronic form at http://www.edpsciences.org

Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment.

PubMed

Eskofier, Bjoern M; Lee, Sunghoon I; Daneault, Jean-Francois; Golabchi, Fatemeh N; Ferreira-Carvalho, Gabriela; Vergara-Diaz, Gloria; Sapienza, Stefano; Costante, Gianluca; Klucken, Jochen; Kautz, Thomas; Bonato, Paolo

2016-08-01

The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units. Several motor tasks were expert-labeled and used for classification. We specifically focused on the detection of bradykinesia. For this, we compared standard machine learning pipelines with deep learning based on convolutional neural networks. Our results showed that deep learning outperformed other state-of-the-art machine learning algorithms by at least 4.6 % in terms of classification rate. We contribute a discussion of the advantages and disadvantages of deep learning for sensor-based movement assessment and conclude that deep learning is a promising method for this field.

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops.

PubMed

Wasson, A P; Richards, R A; Chatrath, R; Misra, S C; Prasad, S V Sai; Rebetzke, G J; Kirkegaard, J A; Christopher, J; Watt, M

2012-05-01

Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity resistances. Such a programme with field and laboratory evaluation at the outset will speed up delivery of varieties with improved root systems for higher yield.

Deep Learning in Medical Image Analysis.

PubMed

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

DOE Office of Scientific and Technical Information (OSTI.GOV)

James P. Barry; Peter G. Brewer

OAK-B135 This report summarizes activities and results of investigations of the potential environmental consequences of direct injection of carbon dioxide into the deep-sea as a carbon sequestration method. Results of field experiments using small scale in situ releases of liquid CO2 are described in detail. The major conclusions of these experiments are that mortality rates of deep sea biota will vary depending on the concentrations of CO2 in deep ocean waters that result from a carbon sequestration project. Large changes in seawater acidity and carbon dioxide content near CO2 release sites will likely cause significant harm to deep-sea marine life.more » Smaller changes in seawater chemistry at greater distances from release sites will be less harmful, but may result in significant ecosystem changes.« less

Electron emission from deep level defects EL2 and EL6 in semi-insulating GaAs observed by positron drift velocity transient measurements

NASA Astrophysics Data System (ADS)

Tsia, J. M.; Ling, C. C.; Beling, C. D.; Fung, S.

2002-09-01

A plus-or-minus100 V square wave applied to a Au/semi-insulating SI-GaAs interface was used to bring about electron emission from and capture into deep level defects in the region adjacent to the interface. The electric field transient resulting from deep level emission was studied by monitoring the positron drift velocity in the region. A deep level transient spectrum was obtained by computing the trap emission rate as a function of temperature and two peaks corresponding to EL2 (Ea=0.81plus-or-minus0.15 eV) and EL6 (Ea=0.30plus-or-minus0.12 eV) have been identified.

The dynamics of biogeographic ranges in the deep sea.

PubMed

McClain, Craig R; Hardy, Sarah Mincks

2010-12-07

Anthropogenic disturbances such as fishing, mining, oil drilling, bioprospecting, warming, and acidification in the deep sea are increasing, yet generalities about deep-sea biogeography remain elusive. Owing to the lack of perceived environmental variability and geographical barriers, ranges of deep-sea species were traditionally assumed to be exceedingly large. In contrast, seamount and chemosynthetic habitats with reported high endemicity challenge the broad applicability of a single biogeographic paradigm for the deep sea. New research benefiting from higher resolution sampling, molecular methods and public databases can now more rigorously examine dispersal distances and species ranges on the vast ocean floor. Here, we explore the major outstanding questions in deep-sea biogeography. Based on current evidence, many taxa appear broadly distributed across the deep sea, a pattern replicated in both the abyssal plains and specialized environments such as hydrothermal vents. Cold waters may slow larval metabolism and development augmenting the great intrinsic ability for dispersal among many deep-sea species. Currents, environmental shifts, and topography can prove to be dispersal barriers but are often semipermeable. Evidence of historical events such as points of faunal origin and climatic fluctuations are also evident in contemporary biogeographic ranges. Continued synthetic analysis, database construction, theoretical advancement and field sampling will be required to further refine hypotheses regarding deep-sea biogeography.

The dynamics of biogeographic ranges in the deep sea

PubMed Central

McClain, Craig R.; Hardy, Sarah Mincks

2010-01-01

Anthropogenic disturbances such as fishing, mining, oil drilling, bioprospecting, warming, and acidification in the deep sea are increasing, yet generalities about deep-sea biogeography remain elusive. Owing to the lack of perceived environmental variability and geographical barriers, ranges of deep-sea species were traditionally assumed to be exceedingly large. In contrast, seamount and chemosynthetic habitats with reported high endemicity challenge the broad applicability of a single biogeographic paradigm for the deep sea. New research benefiting from higher resolution sampling, molecular methods and public databases can now more rigorously examine dispersal distances and species ranges on the vast ocean floor. Here, we explore the major outstanding questions in deep-sea biogeography. Based on current evidence, many taxa appear broadly distributed across the deep sea, a pattern replicated in both the abyssal plains and specialized environments such as hydrothermal vents. Cold waters may slow larval metabolism and development augmenting the great intrinsic ability for dispersal among many deep-sea species. Currents, environmental shifts, and topography can prove to be dispersal barriers but are often semipermeable. Evidence of historical events such as points of faunal origin and climatic fluctuations are also evident in contemporary biogeographic ranges. Continued synthetic analysis, database construction, theoretical advancement and field sampling will be required to further refine hypotheses regarding deep-sea biogeography. PMID:20667884

Numerical Experiments on the Role of the Lower Crust in the Development of Extension-driven Gneiss Domes

NASA Astrophysics Data System (ADS)

Korchinski, M.; Rey, P. F.; Teyssier, C. P.; Mondy, L. S.; Whitney, D.

2016-12-01

Flow of orogenic crust is a critical geodynamic process in the chemical and physical evolution of continents. Deeply sourced rocks are transported to the near surface within gneiss domes, which are ubiquitous features in orogens and extensional regions. Exhumation of material within a gneiss dome can occur as the result of tectonic stresses, where material moves into space previously occupied by the shallow crust as the result of extension localized along a detachment system. Gravitationally driven flow may also contribute to exhumation. This research addresses how physical parameters (density, viscosity) of the deep crust (base of brittle crust to Moho) impact (1) the localization of extension in the shallow crust, and (2) the flow of deep crust by tectonic and non-tectonic stresses. We present 2D numerical experiments in which the density (2900-3100 kg m-3) and viscosity (1e19-1e21 Pa s) of the deep crust are systematically varied. Lateral and vertical transport of deep crustal rocks toward the gneiss dome occurs across the entire parameter space. A low viscosity deep crust yields localized extension in the upper crust and crustal-scale upward flow; this case produces the highest exhumation. A high viscosity deep crust results in distributed thinning of the upper crust, which suppresses upward mass transport. The density of the deep crust has only a second-order effect on the shallow crust extension regime. We capture the flow field generated after the cessation of extension to evaluate mass transport that is not driven by tectonic stresses. Upward transport of material within the gneiss dome is present across the entire parameter space. In the case of a low-viscosity deep crust, horizontal flow occurs adjacent to the dome above the Moho; this flow is an order of magnitude higher than that within the dome. Density variations do not drastically alter the flow field in the low viscosity lower crust. However, a high density and high viscosity deep crust results in boudinage of the whole crust, which generates significant upward flow from the buoyant asthenosphere.

How to study deep roots—and why it matters

PubMed Central

Maeght, Jean-Luc; Rewald, Boris; Pierret, Alain

2013-01-01

The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of “deep roots” is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydraulic lift (HL). Subterranean fauna and microbial communities are highly influenced by resources provided in the deep rhizosphere and deep roots can influence soil pedogenesis and carbon storage.Despite recent technological advances, the study of deep roots and their rhizosphere remains inherently time-consuming, technically demanding and costly, which explains why deep roots have yet to be given the attention they deserve. While state-of-the-art technologies are promising for laboratory studies involving relatively small soil volumes, they remain of limited use for the in situ observation of deep roots. Thus, basic techniques such as destructive sampling or observations at transparent interfaces with the soil (e.g., root windows) which have been known and used for decades to observe roots near the soil surface, must be adapted to the specific requirements of deep root observation. In this review, we successively address major physical, biogeochemical and ecological functions of deep roots to emphasize the significance of deep roots and to illustrate the yet limited knowledge. In the second part we describe the main methodological options to observe and measure deep roots, providing researchers interested in the field of deep root/rhizosphere studies with a comprehensive overview. Addressed methodologies are: excavations, trenches and soil coring approaches, minirhizotrons (MR), access shafts, caves and mines, and indirect approaches such as tracer-based techniques. PMID:23964281

The MUSE Hubble Ultra Deep Field Survey. IX. Evolution of galaxy merger fraction since z ≈ 6

NASA Astrophysics Data System (ADS)

Ventou, E.; Contini, T.; Bouché, N.; Epinat, B.; Brinchmann, J.; Bacon, R.; Inami, H.; Lam, D.; Drake, A.; Garel, T.; Michel-Dansac, L.; Pello, R.; Steinmetz, M.; Weilbacher, P. M.; Wisotzki, L.; Carollo, M.

2017-11-01

We provide, for the first time, robust observational constraints on the galaxy major merger fraction up to z ≈ 6 using spectroscopic close pair counts. Deep Multi Unit Spectroscopic Explorer (MUSE) observations in the Hubble Ultra Deep Field (HUDF) and Hubble Deep Field South (HDF-S) are used to identify 113 secure close pairs of galaxies among a parent sample of 1801 galaxies spread over a large redshift range (0.2 < z < 6) and stellar masses (107-1011 M⊙), thus probing about 12 Gyr of galaxy evolution. Stellar masses are estimated from spectral energy distribution (SED) fitting over the extensive UV-to-NIR HST photometry available in these deep Hubble fields, adding Spitzer IRAC bands to better constrain masses for high-redshift (z ⩾ 3) galaxies. These stellar masses are used to isolate a sample of 54 major close pairs with a galaxy mass ratio limit of 1:6. Among this sample, 23 pairs are identified at high redshift (z ⩾ 3) through their Lyα emission. The sample of major close pairs is divided into five redshift intervals in order to probe the evolution of the merger fraction with cosmic time. Our estimates are in very good agreement with previous close pair counts with a constant increase of the merger fraction up to z ≈ 3 where it reaches a maximum of 20%. At higher redshift, we show that the fraction slowly decreases down to about 10% at z ≈ 6. The sample is further divided into two ranges of stellar masses using either a constant separation limit of 109.5 M⊙ or the median value of stellar mass computed in each redshift bin. Overall, the major close pair fraction for low-mass and massive galaxies follows the same trend. These new, homogeneous, and robust estimates of the major merger fraction since z ≈ 6 are in good agreement with recent predictions of cosmological numerical simulations. Based on observations made with ESO telescopes at the La Silla-Paranal Observatory under programmes 094.A-0289(B), 095.A-0010(A), 096.A-0045(A) and 096.A-0045(B).

Deep neck infection after third molar extraction: A case report.

PubMed

da Silva Junior, Alberto Ferreira; de Magalhaes Rocha, Gustavo Silvestre; da Silva Neves de Araujo, Camila Fialho; Franco, Ademir; Silva, Rhonan Ferreira

2017-01-01

Deep neck infections are associated with high morbidity rates in dentistry. Early diagnosis and intervention play an essential part in decreasing morbidity rates. The present study aims to report a case of odontogenic deep neck infection after third molar extraction. A 51-year-old male patient underwent extraction of the mandibular right third molar. Seven days later, the patient developed symptoms and signs of progressive infection. Laboratorial and radiologic examinations in association with clinical investigations confirmed deep neck infection. Extraoral drainage was performed under orotracheal intubation. Postoperative laboratory tests and clinical examinations revealed signs of complete remission within a follow-up period of 10 days. Considering the invasive nature of pathogens related to deep neck infections, it is possible to infer that a combination of accurate diagnosis and early intervention plays an essential role in the field of maxillofacial surgery and pathology.

Tackling the Challenge of Deep Vadose Zone Remediation at the Hanford Site

NASA Astrophysics Data System (ADS)

Morse, J. G.; Wellman, D. M.; Gephart, R.

2010-12-01

The Central Plateau of the Hanford Site in Washington State contains some 800 waste disposal sites where 1.7 trillion liters of contaminated water was once discharged into the subsurface. Most of these sites received liquids from the chemical reprocessing of spent uranium fuel to recover plutonium. In addition, 67 single shell tanks have leaked or are suspected to have leaked 3.8 million liters of high alkali and aluminate rich cesium-contaminated liquids into the sediment. Today, this inventory of subsurface contamination contains an estimated 550,000 curies of radioactivity and 150 million kg (165,000 tons) of metals and hazardous chemicals. Radionuclides range from mobile 99Tc to more immobilized 137Cs, 241Am, uranium, and plutonium. A significant fraction of these contaminants likely remain within the deep vadose zone. Plumes of groundwater containing tritium, nitrate, 129I and other contaminants have migrated through the vadose zone and now extend outward from the Central Plateau to the Columbia River. During most of Hanford Site history, subsurface studies focused on groundwater monitoring and characterization to support waste management decisions. Deep vadose zone studies were not a priority because waste practices relied upon that zone to buffer contaminant releases into the underlying aquifer. Remediation of the deep vadose zone is now central to Hanford Site cleanup because these sediments can provide an ongoing source of contamination to the aquifer and therefore to the Columbia River. However, characterization and remediation of the deep vadose zone pose some unique challenges. These include sediment thickness; contaminant depth; coupled geohydrologic, geochemical, and microbial processes controlling contaminant spread; limited availability and effectiveness of traditional characterization tools and cleanup remedies; and predicting contaminant behavior and remediation performance over long time periods and across molecular to field scales. The U.S Department of Energy recognizes these challenges and is committed to a sustained, focused effort of continuing to apply existing technologies where feasible while investing and developing in new innovative, field-demonstrated capabilities supporting longer-term basic and applied research to establish the technical underpinning for solving intractable deep vadose zone problems and implementing final remedies. This approach will rely upon Multi-Project Teams focusing on coordinated projects across multiple DOE offices, programs, and site contractors plus the facilitation of basic and applied research investments through implementing a Deep Vadose Zone Applied Field Research Center and other scientific studies.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

DOE PAGES

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.; ...

2018-04-17

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

Machine Learning, deep learning and optimization in computer vision

NASA Astrophysics Data System (ADS)

Canu, Stéphane

2017-03-01

As quoted in the Large Scale Computer Vision Systems NIPS workshop, computer vision is a mature field with a long tradition of research, but recent advances in machine learning, deep learning, representation learning and optimization have provided models with new capabilities to better understand visual content. The presentation will go through these new developments in machine learning covering basic motivations, ideas, models and optimization in deep learning for computer vision, identifying challenges and opportunities. It will focus on issues related with large scale learning that is: high dimensional features, large variety of visual classes, and large number of examples.

Treatment of nonconvergence of Fourier modal method arising from irregular field singularities at lossless metal-dielectric right-angle edges.

PubMed

Mei, Yanpeng; Liu, Haitao; Zhong, Ying

2014-04-01

In a recent work [J. Opt. Soc. Am. A28, 738 (2011)], Lifeng Li and Gerard Granet investigate nonconvergence cases of the Fourier modal method (FMM). They demonstrate that the nonconvergence is due to the irregular field singularities at lossless metal-dielectric right-angle edges. Here we make further investigations on the problem and find that the FMM surprisingly converges for deep sub-wavelength gratings (grating period being much smaller than the illumination wavelength). To overcome the nonconvergence for gratings that are not deep sub-wavelength, we approximately replace the lossless metal-dielectric right-angle edges by a medium with a gradually varied refraction index, so as to remove the irregular field singularities. With such treatment, convergence is observed as the region of the approximate medium approaches vanishing.

Astrometry with LSST: Objectives and Challenges

NASA Astrophysics Data System (ADS)

Casetti-Dinescu, D. I.; Girard, T. M.; Méndez, R. A.; Petronchak, R. M.

2018-01-01

The forthcoming Large Synoptic Survey Telescope (LSST) is an optical telescope with an effective aperture of 6.4 m, and a field of view of 9.6 square degrees. Thus, LSST will have an étendue larger than any other optical telescope, performing wide-field, deep imaging of the sky. There are four broad categories of science objectives: 1) dark-energy and dark matter, 2) transients, 3) the Milky Way and its neighbours and, 4) the Solar System. In particular, for the Milky-Way science case, astrometry will make a critical contribution; therefore, special attention must be devoted to extract the maximum amount of astrometric information from the LSST data. Here, we outline the astrometric challenges posed by such a massive survey. We also present some current examples of ground-based, wide-field, deep imagers used for astrometry, as precursors of the LSST.

Condenser for ring-field deep-ultraviolet and extreme-ultraviolet lithography

DOEpatents

Chapman, Henry N.; Nugent, Keith A.

2001-01-01

A condenser for use with a ring-field deep ultraviolet or extreme ultraviolet lithography system. A condenser includes a ripple-plate mirror which is illuminated by a collimated beam at grazing incidence. The ripple plate comprises a plate mirror into which is formed a series of channels along an axis of the mirror to produce a series of concave surfaces in an undulating pattern. Light incident along the channels of the mirror is reflected onto a series of cones. The distribution of slopes on the ripple plate leads to a distribution of angles of reflection of the incident beam. This distribution has the form of an arc, with the extremes of the arc given by the greatest slope in the ripple plate. An imaging mirror focuses this distribution to a ring-field arc at the mask plane.

The Arctic Gakkel Vents (AGAVE) Expedition: Technology Development and the Search for Deep-Sea Hydrothermal Vent Fields Under the Arctic Ice Cap

NASA Astrophysics Data System (ADS)

Reves-Sohn, R. A.; Singh, H.; Humphris, S.; Shank, T.; Jakuba, M.; Kunz, C.; Murphy, C.; Willis, C.

2007-12-01

Deep-sea hydrothermal fields on the Gakkel Ridge beneath the Arctic ice cap provide perhaps the best terrestrial analogue for volcanically-hosted chemosynthetic biological communities that may exist beneath the ice-covered ocean of Europa. In both cases the key enabling technologies are robotic (untethered) vehicles that can swim freely under the ice and the supporting hardware and software. The development of robotic technology for deep- sea research beneath ice-covered oceans thus has relevance to both polar oceanography and future astrobiological missions to Europa. These considerations motivated a technology development effort under the auspices of NASA's ASTEP program and NSF's Office of Polar Programs that culminated in the AGAVE expedition aboard the icebreaker Oden from July 1 - August 10, 2007. The scientific objective was to study hydrothermal processes on the Gakkel Ridge, which is a key target for global studies of deep-sea vent fields. We developed two new autonomous underwater vehicles (AUVs) for the project, and deployed them to search for vent fields beneath the ice. We conducted eight AUV missions (four to completion) during the 40-day long expedition, which also included ship-based bathymetric surveys, CTD/rosette water column surveys, and wireline photographic and sampling surveys of remote sections of the Gakkel Ridge. The AUV missions, which lasted 16 hours on average and achieved operational depths of 4200 meters, returned sensor data that showed clear evidence of hydrothermal venting, but for a combination of technical reasons and time constraints, the AUVs did not ultimately return images of deep-sea vent fields. Nevertheless we used our wireline system to obtain images and samples of extensive microbial mats that covered fresh volcanic surfaces on a newly discovered set of volcanoes. The microbes appear to be living in regions where reducing and slightly warm fluids are seeping through cracks in the fresh volcanic terrain. These discoveries shed new light on the nature of volcanic and hydrothermal processes in the Arctic basin, and also demonstrate the importance of new technologies for advancing science beneath ice-covered oceans. Operationally, the AUV missions pushed the envelope of deep-sea technology. The recoveries were particularly difficult as it was necessary to have the vehicle find small pools of open water next to the ship, but in some cases the ice was in a state of regional compression such that no open water could be found or created. In these cases a well-calibrated, ship-based, short-baseline acoustic system was essential for successful vehicle recoveries. In all we were able to achieve a variety of operational and technological advances that provide stepping stones for future under-ice robotic missions, both on Earth and perhaps eventually on Europa.

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

NASA Technical Reports Server (NTRS)

Newman, Jeffrey A.; Cooper, Michael C.; Davis, Marc; Faber, S. M.; Coil, Alison L; Guhathakurta, Puraga; Koo, David C.; Phillips, Andrew C.; Conroy, Charlie; Dutton, Aaron A.;

Dynamics of Oceanic Motions

DTIC Science & Technology

1997-09-30

research is multiscale , interdisciplinary and generic. The methods are applicable to an arbitrary region of the coastal and/or deep ocean and across the...dynamics. OBJECTIVES General objectives are: (I) To determine for the coastal and/or coupled deep ocean the multiscale processes which occur: i) in...Straits and the eastern basin; iii) extension and application of our balance of terms scheme (EVA) to multiscale , interdisciplinary fields with data

An approach for in situ studies of deep-sea amphipods and their microbial gut flora

NASA Astrophysics Data System (ADS)

Jannasch, H. W.; Cuhel, R. L.; Wirsen, C. O.; Taylor, C. D.

1980-10-01

A technique has been developed and field-tested for the trapping, feeding, and timed incubation of amphipods on the deep-sea floor. Data obtained from experiments using radiolabeled foodstuffs indicate that shifts within the labeled fractions of the major biological polymers make it possible to distinguish between the metabolism of the amphipods and that of their intestinal microflora.

The Hubble Space Telescope Medium Deep Survey with the Wide Field and Planetary Camera. 1: Methodology and results on the field near 3C 273

NASA Technical Reports Server (NTRS)

Griffiths, R. E.; Ratnatunga, K. U.; Neuschaefer, L. W.; Casertano, S.; Im, M.; Wyckoff, E. W.; Ellis, R. S.; Gilmore, G. F.; Elson, R. A. W.; Glazebrook, K.

1994-01-01

We present results from the Medium Deep Survey (MDS), a Key Project using the Hubble Space Telescope (HST). Wide Field Camera (WFC) images of random fields have been taken in 'parallel mode' with an effective resolution of 0.2 sec full width at half maximum (FWHM) in the V(F555W) and I(F785LP) filters. The exposures presented here were targeted on a field away from 3C 273, and resulted in approximately 5 hr integration time in each filter. Detailed morphological structure is seen in galaxy images with total integrated magnitudes down to V approximately = 22.5 and I approximately = 21.5. Parameters are estimated that best fit the observed galaxy images, and 143 objects are identified (including 23 stars) in the field to a fainter limiting magnitude of I approximately = 23.5. We outline the extragalactic goals of the HST Medium Deep Survey, summarize our basic data reduction procedures, and present number (magnitude) counts, a color-magnitude diagram for the field, surface brightness profiles for the brighter galaxies, and best-fit half-light radii for the fainter galaxies as a function of apparent magnitude. A median galaxy half-light radius of 0.4 sec is measured, and the distribution of galaxy sizes versus magnitude is presented. We observe an apparent deficit of galaxies with half-light radii between approximately 0.6 sec and 1.5 sec, with respect to standard no-evolution or mild evolution cosmological models. An apparent excess of compact objects (half-light radii approximately 0.1 sec) is also observed with respect to those models. Finally, we find a small excess in the number of faint galaxy pairs and groups with respect to a random low-redshift field sample.

Ultra-deep K S-band Imaging of the Hubble Frontier Fields

NASA Astrophysics Data System (ADS)

Brammer, Gabriel B.; Marchesini, Danilo; Labbé, Ivo; Spitler, Lee; Lange-Vagle, Daniel; Barker, Elizbeth A.; Tanaka, Masayuki; Fontana, Adriano; Galametz, Audrey; Ferré-Mateu, Anna; Kodama, Tadayuki; Lundgren, Britt; Martis, Nicholas; Muzzin, Adam; Stefanon, Mauro; Toft, Sune; van der Wel, Arjen; Vulcani, Benedetta; Whitaker, Katherine E.

2016-09-01

We present an overview of the “KIFF” project, which provides ultra-deep K s -band imaging of all six of the Hubble Frontier Fields clusters, Abell 2744, MACS-0416, Abell S1063, Abell 370, MACS-0717, and MACS-1149. All of these fields have recently been observed with large allocations of Directors’ Discretionary Time with the Hubble and Spitzer telescopes, covering 0.4\\lt λ \\lt 1.6 μ {{m}} and 3.6-4.5 μ {{m}}, respectively. VLT/HAWK-I integrations of the first four fields reach 5σ limiting depths of {K}s˜ 26.0 (AB, point sources) and have excellent image quality (FWHM ˜ 0.″4). The MACS-0717 and MACS-1149 fields are observable from the northern hemisphere, and shorter Keck/MOSFIRE integrations on those fields reach limiting depths of K s = 25.5 and 25.1, with a seeing FWHM of ˜ 0.″4 and 0\\buildrel{\\prime\\prime}\\over{.} 5. In all cases the K s -band mosaics cover the primary cluster and parallel HST/ACS+WFC3 fields. The total area of the K s -band coverage is 490 arcmin2. The K s -band at 2.2 μ {{m}} crucially fills the gap between the reddest HST filter (1.6 μ {{m}} ˜ H band) and the IRAC 3.6 μ {{m}} passband. While reaching the full depths of the space-based imaging is not currently feasible from the ground, the deep K s -band images provide important constraints on both the redshifts and the stellar population properties of galaxies extending well below the characteristic stellar mass across most of the age of the universe, down to and including the redshifts of the targeted galaxy clusters (z≲ 0.5). Reduced, aligned mosaics of all six survey fields are provided.

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

PubMed

Kruthiventi, Srinivas S S; Ayush, Kumar; Babu, R Venkatesh

2017-09-01

Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account, by using network layers with very large receptive fields. Generally, fully convolutional nets are spatially invariant-this prevents them from modeling location-dependent patterns (e.g., centre-bias). Our network handles this by incorporating a novel location-biased convolutional layer. We evaluate our model on multiple challenging saliency data sets and show that it achieves the state-of-the-art results.

Image inpainting and super-resolution using non-local recursive deep convolutional network with skip connections

NASA Astrophysics Data System (ADS)

Liu, Miaofeng

2017-07-01

In recent years, deep convolutional neural networks come into use in image inpainting and super-resolution in many fields. Distinct to most of the former methods requiring to know beforehand the local information for corrupted pixels, we propose a 20-depth fully convolutional network to learn an end-to-end mapping a dataset of damaged/ground truth subimage pairs realizing non-local blind inpainting and super-resolution. As there often exist image with huge corruptions or inpainting on a low-resolution image that the existing approaches unable to perform well, we also share parameters in local area of layers to achieve spatial recursion and enlarge the receptive field. To avoid the difficulty of training this deep neural network, skip-connections between symmetric convolutional layers are designed. Experimental results shows that the proposed method outperforms state-of-the-art methods for diverse corrupting and low-resolution conditions, it works excellently when realizing super-resolution and image inpainting simultaneously

The thermal evolution of Mercury's Fe-Si core

NASA Astrophysics Data System (ADS)

Knibbe, Jurriën Sebastiaan; van Westrenen, Wim

2018-01-01

We have studied the thermal and magnetic field evolution of planet Mercury with a core of Fe-Si alloy to assess whether an Fe-Si core matches its present-day partially molten state, Mercury's magnetic field strength, and the observed ancient crustal magnetization. The main advantages of an Fe-Si core, opposed to a previously assumed Fe-S core, are that a Si-bearing core is consistent with the highly reduced nature of Mercury and that no compositional convection is generated upon core solidification, in agreement with magnetic field indications of a stable layer at the top of Mercury's core. This study also present the first implementation of a conductive temperature profile in the core where heat fluxes are sub-adiabatic in a global thermal evolution model. We show that heat migrates from the deep core to the outer part of the core as soon as heat fluxes at the outer core become sub-adiabatic. As a result, the deep core cools throughout Mercury's evolution independent of the temperature evolution at the core-mantle boundary, causing an early start of inner core solidification and magnetic field generation. The conductive layer at the outer core suppresses the rate of core growth after temperature differences between the deep and shallow core are relaxed, such that a magnetic field can be generated until the present. Also, the outer core and mantle operate at higher temperatures than previously thought, which prolongs mantle melting and mantle convection. The results indicate that S is not a necessary ingredient of Mercury's core, bringing bulk compositional models of Mercury more in line with reduced meteorite analogues.

Accidental deep field bias in CMB T and SNe z correlation

NASA Astrophysics Data System (ADS)

Friday, Tracey; Clowes, Roger G.; Raghunathan, Srinivasan; Williger, Gerard M.

2018-05-01

Evidence presented by Yershov, Orlov and Raikov apparently showed that the WMAP/Planck cosmic microwave background (CMB) pixel-temperatures (T) at supernovae (SNe) locations tend to increase with increasing redshift (z). They suggest this correlation could be caused by the Integrated Sachs-Wolfe effect and/or by some unrelated foreground emission. Here, we assess this correlation independently using Planck 2015 SMICA R2.01 data and, following Yershov et al., a sample of 2783 SNe from the Sternberg Astronomical Institute. Our analysis supports the prima facie existence of the correlation but attributes it to a composite selection bias (high CMB T × high SNe z) caused by the accidental alignment of seven deep survey fields with CMB hotspots. These seven fields contain 9.2 per cent of the SNe sample (256 SNe). Spearman's rank-order correlation coefficient indicates the correlation present in the whole sample (ρs = 0.5, p-value =6.7 × 10-9) is insignificant for a sub-sample of the seven fields together (ρs = 0.2, p-value =0.2) and entirely absent for the remainder of the SNe (ρs = 0.1, p-value =0.6). We demonstrate the temperature and redshift biases of these seven deep fields, and estimate the likelihood of their falling on CMB hotspots by chance is at least ˜ 6.8 per cent (approximately 1 in 15). We show that a sample of 7880 SNe from the Open Supernova Catalogue exhibits the same effect and we conclude that the correlation is an accidental but not unlikely selection bias.

Early Environmental Field Research Career Exploration: An Analysis of Impacts on Precollege Apprentices

ERIC Educational Resources Information Center

Flowers, Susan K.; Beyer, Katherine M.; Pérez, Maria; Jeffe, Donna B.

2016-01-01

Research apprenticeships offer opportunities for deep understanding of scientific practice, transparency about research careers, and possible transformational effects on precollege youth. We examined two consecutive field-based environmental biology apprenticeship programs designed to deliver realistic career exploration and connections to…

Plasmonic metasurface cavity for simultaneous enhancement of optical electric and magnetic fields in deep subwavelength volume.

PubMed

Hong, Jongwoo; Kim, Sun-Je; Kim, Inki; Yun, Hansik; Mun, Sang-Eun; Rho, Junsuk; Lee, Byoungho

2018-05-14

It has been hard to achieve simultaneous plasmonic enhancement of nanoscale light-matter interactions in terms of both electric and magnetic manners with easily reproducible fabrication method and systematic theoretical design rule. In this paper, a novel concept of a flat nanofocusing device is proposed for simultaneously squeezing both electric and magnetic fields in deep-subwavelength volume (~λ 3 /538) in a large area. Based on the funneled unit cell structures and surface plasmon-assisted coherent interactions between them, the array of rectangular nanocavity connected to a tapered nanoantenna, plasmonic metasurface cavity, is constructed by periodic arrangement of the unit cell. The average enhancement factors of electric and magnetic field intensities reach about 60 and 22 in nanocavities, respectively. The proposed outstanding performance of the device is verified numerically and experimentally. We expect that this work would expand methodologies involving optical near-field manipulations in large areas and related potential applications including nanophotonic sensors, nonlinear responses, and quantum interactions.

Field estimates of groundwater circulation depths in two mountainous watersheds in the western U.S. and the effect of deep circulation on solute concentrations in streamflow

NASA Astrophysics Data System (ADS)

Frisbee, Marty D.; Tolley, Douglas G.; Wilson, John L.

2017-04-01

Estimates of groundwater circulation depths based on field data are lacking. These data are critical to inform and refine hydrogeologic models of mountainous watersheds, and to quantify depth and time dependencies of weathering processes in watersheds. Here we test two competing hypotheses on the role of geology and geologic setting in deep groundwater circulation and the role of deep groundwater in the geochemical evolution of streams and springs. We test these hypotheses in two mountainous watersheds that have distinctly different geologic settings (one crystalline, metamorphic bedrock and the other volcanic bedrock). Estimated circulation depths for springs in both watersheds range from 0.6 to 1.6 km and may be as great as 2.5 km. These estimated groundwater circulation depths are much deeper than commonly modeled depths suggesting that we may be forcing groundwater flow paths too shallow in models. In addition, the spatial relationships of groundwater circulation depths are different between the two watersheds. Groundwater circulation depths in the crystalline bedrock watershed increase with decreasing elevation indicative of topography-driven groundwater flow. This relationship is not present in the volcanic bedrock watershed suggesting that both the source of fracturing (tectonic versus volcanic) and increased primary porosity in the volcanic bedrock play a role in deep groundwater circulation. The results from the crystalline bedrock watershed also indicate that relatively deep groundwater circulation can occur at local scales in headwater drainages less than 9.0 km2 and at larger fractions than commonly perceived. Deep groundwater is a primary control on streamflow processes and solute concentrations in both watersheds.

Reservoir compartmentalization of deep-water Intra Qua Iboe sand (Pliocene), Edop field, offshore Nigeria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hermance, W.E.; Olaifa, J.O.; Shanmugam, G.

An integration of 3-D seismic and sedimentological information provides a basis for recognizing and mapping individual flow units within the Intra Qua Iboe (IQI) reservoir (Pliocene), Edop Field, offshore Nigeria. Core examination show the following depositional facies: A-Sandy slump/mass flow, B-Muddy slump/mass flow, C. Bottom current reworking. D-Non-channelized turbidity currents, E. Channelized (coalesced) turbidity currents. F-Channelized (isolated) turbidity currents, G-Pelagic/hemipelagic, H-Levee, I-Reworked slope, J-Wave dominated, and K-Tide dominated facies. With the exception of facies J and K, all these facies are of deep-water affinity. The IQI was deposited on an upper slope environment in close proximity to the shelf edge.more » Through time, as the shelf edge migrated scaward, deposition began with a channel dominated deep-water system (IQI 1 and 2) and progressed through a slump/debris flow dominated deep-water system (IQI 3, the principle reservoir) to a tide and wave dominated shallow-water system (IQI 4). Compositional and textural similarities between the deep-water facies result in similar log motifs. Furthermore, these depositional facies are not readily apparent as distinct seismic facies. Deep-water facies A, D, E, and F are reservoir facies, whereas facies B, C, G, H, and I are non-reservoir facies. However, Facies G is useful as a seismically mappable event throughout the study area. Mapping of these non-reservoir events provides the framework for understanding gross reservoir architecture. This study has resulted in seven defined reservoir units within the IQI, which serves as the architectural framework for ongoing reservoir characterization.« less

AKARI Deep Observations of the Chandra Deep Field South

NASA Astrophysics Data System (ADS)

Burgarella, D.; Buat, V.; Takeuchi, T. T.; Wada, T.; Pearson, C.

2009-12-01

The Chandra Deep Field South is one of the deep fields that has been observed over almost all the electromagnetic spectrum. It contains a wealth of data very useful to study and better understand distant galaxies and their evolution. However, one piece of information was missing in the Mid Infrared and that is why we have obtained 15 μm observations with AKARI/IRC infrared space telescope. From these observations, we have defined a sample of mid infrared-selected galaxies at 15 μm and 15 μm flux densities for a sample of Lyman Break Galaxies at z ˜ 1 already observed at 24 μm with Spitzer/MIPS and identified in the ultraviolet with GALEX. Of the two above samples at z ˜ 1 we have tested the validity of the conversions from luminosities νfν at 8 μm to total dust luminosities by comparing with luminosities estimated from 12 μm data used as a reference. Some calibrations seem better when compared to Ldust evaluated from longer wavelength luminosities. We also have found that the rest-frame 8 μm luminosities provide good estimates of Ldust. By comparing our data to several libraries of spectral energy distributions, we have found that models can explain the diversity of the observed f24 / f15 ratio quite reasonably. Finally, we have revisited the evolution of Ldust / LUV ratio with the redshift z by re-calibrating previous Ldust at z ˜ 2 based on our results and added new data points at higher redshifts. The decreasing trend is amplified as compared to the previous estimate.

Cosmic Accretion and Galaxy Co-Evolution: Lessons from the Extended Chandra Deep Field South

NASA Astrophysics Data System (ADS)

Urry, C. Megan

2011-05-01

The Chandra deep fields reveal that most cosmic accretion onto supermassive black holes is obscured by gas and dust. The GOODS and MUSYC multiwavelength data show that many X-ray-detected AGN are faint and red (or even undetectable) in the optical but bright in the infrared, as is characteristic of obscured sources. (N.B. The ECDFS is most sensitive to the AGN that constitute the X-ray background, namely, moderate luminosity AGN, with log Lx=43-44, at moderate redshifts, 0.5

Drilling into a present-day migration pathway for hydrocarbons within a fault zone conduit in the Eugene Island 330 field, offshore Louisiana

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, R.N.

1995-11-01

Within the Global Basins Research Network, we have developed 4-D seismic analysis techniques that, when integrated with pressure and temperature mapping, production history, geochemical monitoring, and finite element modeling, allow for the imaging of active fluid migration in the subsurface. We have imaged fluid flow pathways that are actively recharging shallower hydrocarbon reservoirs in the Eugene Island 330 field, offshore Louisiana. The hydrocarbons appear to be sourcing from turbidite stacks within the salt-withdrawal mini-basin buried deep within geopressure. Fault zone conduits provide transient migration pathways out of geopressure. To accomplish this 4-D imaging, we use multiple 3-D seismic surveys donemore » several years apart over the same blocks. 3-D volume processing and attribute analysis algorithms are used to identify significant seismic amplitude interconnectivity and changes over time that result from active fluid migration. Pressures and temperatures are then mapped and modeled to pro- vide rate and timing constraints for the fluid movement. Geochemical variability observed in the shallow reservoirs is attributed to the mixing of new with old oils. The Department of Energy has funded an industry cost-sharing project to drill into one of these active conduits in Eugene Island Block 330. Active fluid flow was encountered within the fault zone in the field demonstration experiment, and hydrocarbons were recovered. The active migration events connecting shallow reservoirs to deep sourcing regions imply that large, heretofore undiscovered hydrocarbon reserves exist deep within geopressures along the deep continental shelf of the northern Gulf of Mexico.« less

VizieR Online Data Catalog: VANDELS High-Redshift Galaxy Evolution (McLure+, 2017)

NASA Astrophysics Data System (ADS)

McLure, R.; Pentericci, L.; Vandels Team

2017-11-01

This is the first data release (DR1) of the VANDELS survey, an ESO public spectroscopy survey targeting the high-redshift Universe. The VANDELS survey uses the VIMOS spectrograph on ESO's VLT to obtain ultra-deep, medium resolution, optical spectra of galaxies within the UKIDSS Ultra Deep Survey (UDS) and Chandra Deep Field South (CDFS) survey fields (0.2 sq. degree total area). Using robust photometric redshift pre-selection, VANDELS is targeting ~2100 galaxies in the redshift interval 1.0=3. In addition, VANDELS is targeting a substantial number of passive galaxies in the redshift interval 1.0

Holography as deep learning

NASA Astrophysics Data System (ADS)

Gan, Wen-Cong; Shu, Fu-Wen

Quantum many-body problem with exponentially large degrees of freedom can be reduced to a tractable computational form by neural network method [G. Carleo and M. Troyer, Science 355 (2017) 602, arXiv:1606.02318.] The power of deep neural network (DNN) based on deep learning is clarified by mapping it to renormalization group (RG), which may shed lights on holographic principle by identifying a sequence of RG transformations to the AdS geometry. In this paper, we show that any network which reflects RG process has intrinsic hyperbolic geometry, and discuss the structure of entanglement encoded in the graph of DNN. We find the entanglement structure of DNN is of Ryu-Takayanagi form. Based on these facts, we argue that the emergence of holographic gravitational theory is related to deep learning process of the quantum-field theory.

Metal-dielectric composites for beam splitting and far-field deep sub-wavelength resolution for visible wavelengths.

PubMed

Yan, Changchun; Zhang, Dao Hua; Zhang, Yuan; Li, Dongdong; Fiddy, M A

2010-07-05

We report beam splitting in a metamaterial composed of a silver-alumina composite covered by a layer of chromium containing one slit. By simulating distributions of energy flow in the metamaterial for H-polarized waves, we find that the beam splitting occurs when the width of the slit is shorter than the wavelength, which is conducive to making a beam splitter in sub-wavelength photonic devices. We also find that the metamaterial possesses deep sub-wavelength resolution capabilities in the far field when there are two slits and the central silver layer is at least 36 nm in thickness, which has potential applications in superresolution imaging.

Phylogenetic Paleoecology: Tree-Thinking and Ecology in Deep Time.

PubMed

Lamsdell, James C; Congreve, Curtis R; Hopkins, Melanie J; Krug, Andrew Z; Patzkowsky, Mark E

2017-06-01

The new and emerging field of phylogenetic paleoecology leverages the evolutionary relationships among species to explain temporal and spatial changes in species diversity, abundance, and distribution in deep time. This field is poised for rapid progress as knowledge of the evolutionary relationships among fossil species continues to expand. In particular, this approach will lend new insights to many of the longstanding questions in evolutionary biology, such as: the relationships among character change, ecology, and evolutionary rates; the processes that determine the evolutionary relationships among species within communities and along environmental gradients; and the phylogenetic signal underlying ecological selectivity in background and mass extinctions and in major evolutionary radiations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structure of the screening layer near a plane isolated body in the deep vacuum. Part 2. Monoenergetic isotropic flow

NASA Astrophysics Data System (ADS)

Gunko, Yuri F.; Gunko, Natalia A.

2018-05-01

In this paper we consider the problem of determining the structure of the electric field near the surface of a flat insulated body under conditions of a deep vacuum. It is assumed that the emitted particles are electrons leaving the body surface under the influence of ionizing radiation whose velocities distribution near the surface is isotropic. It is estimated the thickness of the screening layer under conditions of stationary emission from a flat surface. The solutio of the problem of determining a stationary self-consistent electric field near the surface is found in a simple analytical form. The thickness of the screening layer is calculated from this formula.

Quasar Host Galaxies/Neptune Rotation/Galaxy Building Blocks/Hubble Deep Field/Saturn Storm

NASA Technical Reports Server (NTRS)

2001-01-01

Computerized animations simulate a quasar erupting in the core of a normal spiral galaxy, the collision of two interacting galaxies, and the evolution of the universe. Hubble Space Telescope (HST) images show six quasars' host galaxies (including spirals, ellipticals, and colliding galaxies) and six clumps of galaxies approximately 11 billion light years away. A false color time lapse movie of Neptune displays the planet's 16-hour rotation, and the evolution of a storm on Saturn is seen though a video of the planet's rotation. A zoom sequence starts with a ground-based image of the constellation Ursa major and ends with the Hubble Deep Field through progressively narrower and deeper views.

Land-Surface Subsidence and Open Bedrock Fractures in the Tully Valley, Onondaga County, New York

USGS Publications Warehouse

Hackett, William R.; Gleason, Gayle C.; Kappel, William M.

2009-01-01

Open bedrock fractures were mapped in and near two brine field areas in Tully Valley, New York. More than 400 open fractures and closed joints were mapped for dimension, orientation, and distribution along the east and west valley walls adjacent to two former brine fields. The bedrock fractures are as much as 2 feet wide and over 50 feet deep, while linear depressions in the soil, which are 3 to 10 feet wide and 3 to 6 feet deep, indicate the presence of open bedrock fractures below the soil. The fractures are probably the result of solution mining of halite deposits about 1,200 feet below the land surface.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bishofberger, Kip A.

Within Building 19 of TA-53, a screen room has been evaluated for use as a reverb chamber (with deep gratitude to Dale Dalmas and Greg Dale for their assistance). With minimal additional sealing of the chamber, we expect the Q to increase even more, and thus field levels for the same RF source power. Future studies need to determine leakage field levels, which will define maximum achievable field levels.

Biofilm development in a hotspot of mixing between shallow and deep groundwater in a fractured aquifer: field evidence from joint flow, chemical and microbiological measurements

NASA Astrophysics Data System (ADS)

Bochet, O.; Dufresne, A.; Pédrot, M.; Chatton, E.; Labasque, T.; Ben Maamar, S.; Burté, L.; de la Bernardie, J.; Guihéneuf, N.; Lavenant, N.; Petton, C.; Bour, O.; Aquilina, L.; Le Borgne, T.

2015-12-01

Biofilms play a major role in controlling the fluxes and reactivity of chemical species transported in hydro-logical systems. Micro-organisms require both electron donors and electron acceptors for cellular growth, proliferation and maintenance of their metabolic functions. The mechanisms controlling these reactions derive from the interactions occurring at the micro-scale that depend on mineral compositions, the biota of subsurface environment, but also fluid mixing, which determines the local concentrations of nutriments, electron donors and electron acceptors. Hence, mixing zones between oxygen and nutriment rich shallow groundwater and mineralized deep groundwater are often considered as potential hotspots of microbial activity, although relatively few field data document flow distributions, transport properties, chemical gradients and micro-organisms distributions across these mixing interfaces. Here we investigate the origin of a localized biofilm development observed in the fractured granite aquifer at the Ploemeur observatory (H+ network hplus.ore.fr).This biofilm composed of ferro-oxidizing bacteria is observed in an 130m deep artesian well. Borehole video logs show an important colonization of the well by the biofilm in the shallower part (0 to 60m), while it is inexistent in the deeper part (60 to 130m). As flow is localized in a few deep and shallow fractures, we presume that the spatial distribution of biofilm is controlled by mixing between shallow and deep groundwater. To verify this hypothesis we conducted a field campaign with joint characterization of the flow and chemical composition of water flowing from the different fractures, as well as the microbiological composition of the biofilm at different depth, using pyrosequencing techniques. We will discuss in this presentation the results of this interdisciplinary dataset and their implications for the occurrence of hotspots of microbiological activity in the subsurface.

Young Galaxy Candidates in the Hubble Frontier Fields. IV. MACS J1149.5+2223

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zitrin, Adi; Infante, Leopoldo; Laporte, Nicolas; Huang, Xingxing; Moustakas, John; Ford, Holland C.; Shu, Xinwen; Wang, Junxian; Diego, Jose M.; Bauer, Franz E.; Troncoso Iribarren, Paulina; Broadhurst, Tom; Molino, Alberto

2017-02-01

We search for high-redshift dropout galaxies behind the Hubble Frontier Fields (HFF) galaxy cluster MACS J1149.5+2223, a powerful cosmic lens that has revealed a number of unique objects in its field. Using the deep images from the Hubble and Spitzer space telescopes, we find 11 galaxies at z > 7 in the MACS J1149.5+2223 cluster field, and 11 in its parallel field. The high-redshift nature of the bright z ≃ 9.6 galaxy MACS1149-JD, previously reported by Zheng et al., is further supported by non-detection in the extremely deep optical images from the HFF campaign. With the new photometry, the best photometric redshift solution for MACS1149-JD reduces slightly to z = 9.44 ± 0.12. The young galaxy has an estimated stellar mass of (7+/- 2)× {10}8 {M}⊙ , and was formed at z={13.2}-1.6+1.9 when the universe was ≈300 Myr old. Data available for the first four HFF clusters have already enabled us to find faint galaxies to an intrinsic magnitude of {M}{UV}≃ -15.5, approximately a factor of 10 deeper than the parallel fields.

The FLARE mission: deep and wide-field 1-5um imaging and spectroscopy for the early universe: a proposal for M5 cosmic vision call

NASA Astrophysics Data System (ADS)

Burgarella, D.; Levacher, P.; Vives, S.; Dohlen, K.; Pascal, S.

2016-07-01

FLARE (First Light And Reionization Explorer) is a space mission that will be submitted to ESA (M5 call). Its primary goal (~80% of lifetime) is to identify and study the universe before the end of the reionization at z > 6. A secondary objective (~20% of lifetime) is to survey star formation in the Milky Way. FLARE's strategy optimizes the science return: imaging and spectroscopic integral-field observations will be carried out simultaneously on two parallel focal planes and over very wide instantaneous fields of view. FLARE will help addressing two of ESA's Cosmic Vision themes: a) << How did the universe originate and what is it made of? » and b) « What are the conditions for planet formation and the emergence of life? >> and more specifically, << From gas and dust to stars and planets >>. FLARE will provide to the ESA community a leading position to statistically study the early universe after JWST's deep but pin-hole surveys. Moreover, the instrumental development of wide-field imaging and wide-field integral-field spectroscopy in space will be a major breakthrough after making them available on ground-based telescopes.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Estimating the Effects of Conversion of Agricultural Land to Urban Land on Deep Percolation of Irrigation Water in the Grand Valley, Western Colorado

USGS Publications Warehouse

Mayo, John W.

2008-01-01

The conversion of agricultural land to urban residential land is associated with rapid population growth in the Grand Valley of western Colorado. Information regarding the effects of this land-use conversion on deep percolation, irrigation-water application, and associated salt loading to the Colorado River is needed to support water-resource planning and conservation efforts. The Natural Resources Conservation Service (NRCS) assessed deep percolation and estimated salt loading derived from irrigated agricultural lands in the Grand Valley in a 1985 to 2002 monitoring and evaluation study (NRCS M&E). The U.S. Geological Survey (USGS), in cooperation with the Colorado River Salinity Control Forum and the Mesa Conservation District, quantified the current (2005-2006) deep percolation and irrigation-water application characteristics of 1/4-acre residential lots and 5-acre estates, urban parks, and urban orchard grass fields in the Grand Valley, and compared the results to NRCS M&E results from alfalfa-crop sites. In addition, pond seepage from three irrigation-water holding ponds was estimated. Salt loading was estimated for the urban study results and the NRCS M&E results by using standard salt-loading factors. A daily soil-moisture balance calculation technique was used at all urban study irrigated sites. Deep percolation was defined as any water infiltrating below the top 12 inches of soil. Deep percolation occurred when the soil-moisture balance in the first 12 inches of soil exceeded the field capacity for the soil type at each site. Results were reported separately for urban study bluegrass-only sites and for all-vegetation type (bluegrass, native plants, and orchard grass) sites. Deep percolation and irrigation-water application also were estimated for a complete irrigation season at three subdivisions by using mean site data from each subdivision. It was estimated that for the three subdivisions, 37 percent of the developed acreage was irrigated (the balance being impermeable surfaces).

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction

PubMed Central

Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

2014-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80% and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test data set of 198 proteins, achieving a Q3 accuracy of 80.7% and a Sov accuracy of 74.2%. PMID:25750595

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

PubMed

Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

Challenging Oil Bioremediation at Deep-Sea Hydrostatic Pressure

PubMed Central

Scoma, Alberto; Yakimov, Michail M.; Boon, Nico

2016-01-01

The Deepwater Horizon accident has brought oil contamination of deep-sea environments to worldwide attention. The risk for new deep-sea spills is not expected to decrease in the future, as political pressure mounts to access deep-water fossil reserves, and poorly tested technologies are used to access oil. This also applies to the response to oil-contamination events, with bioremediation the only (bio)technology presently available to combat deep-sea spills. Many questions about the fate of petroleum-hydrocarbons within deep-sea environments remain unanswered, as well as the main constraints limiting bioremediation under increased hydrostatic pressures and low temperatures. The microbial pathways fueling oil bioassimilation are unclear, and the mild upregulation observed for beta-oxidation-related genes in both water and sediments contrasts with the high amount of alkanes present in the spilled oil. The fate of solid alkanes (tar), hydrocarbon degradation rates and the reason why the most predominant hydrocarbonoclastic genera were not enriched at deep-sea despite being present at hydrocarbon seeps at the Gulf of Mexico have been largely overlooked. This mini-review aims at highlighting the missing information in the field, proposing a holistic approach where in situ and ex situ studies are integrated to reveal the principal mechanisms accounting for deep-sea oil bioremediation. PMID:27536290

Local vs. volume conductance activity of field potentials in the human subthalamic nucleus

PubMed Central

Marmor, Odeya; Valsky, Dan; Joshua, Mati; Bick, Atira S; Arkadir, David; Tamir, Idit; Bergman, Hagai; Israel, Zvi

2017-01-01

Subthalamic nucleus field potentials have attracted growing research and clinical interest over the last few decades. However, it is unclear whether subthalamic field potentials represent locally generated neuronal subthreshold activity or volume conductance of the organized neuronal activity generated in the cortex. This study aimed at understanding of the physiological origin of subthalamic field potentials and determining the most accurate method for recording them. We compared different methods of recordings in the human subthalamic nucleus: spikes (300–9,000 Hz) and field potentials (3–100 Hz) recorded by monopolar micro- and macroelectrodes, as well as by differential-bipolar macroelectrodes. The recordings were done outside and inside the subthalamic nucleus during electrophysiological navigation for deep brain stimulation procedures (150 electrode trajectories) in 41 Parkinson’s disease patients. We modeled the signal and estimated the contribution of nearby/independent vs. remote/common activity in each recording configuration and area. Monopolar micro- and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity. However, bipolar macroelectrode recordings inside the subthalamic nucleus can detect locally generated potentials. These results are confirmed by high correspondence between the model predictions and actual correlation of neuronal activity recorded by electrode pairs. Differential bipolar macroelectrode subthalamic field potentials can overcome volume conductance effects and reflect locally generated neuronal activity. Bipolar macroelectrode local field potential recordings might be used as a biological marker of normal and pathological brain functions for future electrophysiological studies and navigation systems as well as for closed-loop deep brain stimulation paradigms. NEW & NOTEWORTHY Our results integrate a new method for human subthalamic recordings with a development of an advanced mathematical model. We found that while monopolar microelectrode and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity, bipolar macroelectrode recordings inside the subthalamic nucleus (STN) detect locally generated potentials that are significantly different than those recorded outside the STN. Differential bipolar subthalamic field potentials can be used in navigation and closed-loop deep brain stimulation paradigms. PMID:28202569

Mechanisms of ultrafast laser-induced deep-subwavelength gratings on graphite and diamond

NASA Astrophysics Data System (ADS)

Huang, Min; Zhao, Fuli; Cheng, Ya; Xu, Ningsheg; Xu, Zhizhan

2009-03-01

Deep-subwavelength gratings with periodicities of 170, 120, and 70 nm can be observed on highly oriented pyrolytic graphite irradiated by a femtosecond (fs) laser at 800 nm. Under picosecond laser irradiation, such gratings likewise can be produced. Interestingly, the 170-nm grating is also observed on single-crystal diamond irradiated by the 800-nm fs laser. In our opinion, the optical properties of the high-excited state of material surface play a key role for the formation of the deep-subwavelength gratings. The numerical simulations of the graphite deep-subwavelength grating at normal and high-excited states confirm that in the groove the light intensity can be extraordinarily enhanced via cavity-mode excitation in the condition of transverse-magnetic wave irradiation with near-ablation-threshold fluences. This field enhancement of polarization sensitiveness in deep-subwavelength apertures acts as an important feedback mechanism for the growth and polarization dependence of the deep-subwavelength gratings. In addition, we suggest that surface plasmons are responsible for the formation of seed deep-subwavelength apertures with a particular periodicity and the initial polarization dependence. Finally, we propose that the nanoscale Coulomb explosion occurring in the groove is responsible for the ultrafast nonthermal ablation mechanism.

De novo peptide sequencing by deep learning

PubMed Central

Tran, Ngoc Hieu; Zhang, Xianglilan; Xin, Lei; Shan, Baozhen; Li, Ming

2017-01-01

De novo peptide sequencing from tandem MS data is the key technology in proteomics for the characterization of proteins, especially for new sequences, such as mAbs. In this study, we propose a deep neural network model, DeepNovo, for de novo peptide sequencing. DeepNovo architecture combines recent advances in convolutional neural networks and recurrent neural networks to learn features of tandem mass spectra, fragment ions, and sequence patterns of peptides. The networks are further integrated with local dynamic programming to solve the complex optimization task of de novo sequencing. We evaluated the method on a wide variety of species and found that DeepNovo considerably outperformed state of the art methods, achieving 7.7–22.9% higher accuracy at the amino acid level and 38.1–64.0% higher accuracy at the peptide level. We further used DeepNovo to automatically reconstruct the complete sequences of antibody light and heavy chains of mouse, achieving 97.5–100% coverage and 97.2–99.5% accuracy, without assisting databases. Moreover, DeepNovo is retrainable to adapt to any sources of data and provides a complete end-to-end training and prediction solution to the de novo sequencing problem. Not only does our study extend the deep learning revolution to a new field, but it also shows an innovative approach in solving optimization problems by using deep learning and dynamic programming. PMID:28720701

Extraordinary Teachers, Exceptional Students

ERIC Educational Resources Information Center

Arnove, Robert. F.

2010-01-01

A study of master teachers in the arts, sports, cooking, and other fields reveals characteristics and attitudes that enable them to help their students succeed. These characteristics include a deep knowledge of their field, caring, generosity, and being self critical. Exemplary public school teachers also possess these characteristics, but they…

The Capodimonte Deep Field

NASA Astrophysics Data System (ADS)

2001-04-01

A Window towards the Distant Universe Summary The Osservatorio Astronomico Capodimonte Deep Field (OACDF) is a multi-colour imaging survey project that is opening a new window towards the distant universe. It is conducted with the ESO Wide Field Imager (WFI) , a 67-million pixel advanced camera attached to the MPG/ESO 2.2-m telescope at the La Silla Observatory (Chile). As a pilot project at the Osservatorio Astronomico di Capodimonte (OAC) [1], the OACDF aims at providing a large photometric database for deep extragalactic studies, with important by-products for galactic and planetary research. Moreover, it also serves to gather experience in the proper and efficient handling of very large data sets, preparing for the arrival of the VLT Survey Telescope (VST) with the 1 x 1 degree 2 OmegaCam facility. PR Photo 15a/01 : Colour composite of the OACDF2 field . PR Photo 15b/01 : Interacting galaxies in the OACDF2 field. PR Photo 15c/01 : Spiral galaxy and nebulous object in the OACDF2 field. PR Photo 15d/01 : A galaxy cluster in the OACDF2 field. PR Photo 15e/01 : Another galaxy cluster in the OACDF2 field. PR Photo 15f/01 : An elliptical galaxy in the OACDF2 field. The Capodimonte Deep Field ESO PR Photo 15a/01 ESO PR Photo 15a/01 [Preview - JPEG: 400 x 426 pix - 73k] [Normal - JPEG: 800 x 851 pix - 736k] [Hi-Res - JPEG: 3000 x 3190 pix - 7.3M] Caption : This three-colour image of about 1/4 of the Capodimonte Deep Field (OACDF) was obtained with the Wide-Field Imager (WFI) on the MPG/ESO 2.2-m telescope at the la Silla Observatory. It covers "OACDF Subfield no. 2 (OACDF2)" with an area of about 35 x 32 arcmin 2 (about the size of the full moon), and it is one of the "deepest" wide-field images ever obtained. Technical information about this photo is available below. With the comparatively few large telescopes available in the world, it is not possible to study the Universe to its outmost limits in all directions. Instead, astronomers try to obtain the most detailed information possible in selected viewing directions, assuming that what they find there is representative for the Universe as a whole. This is the philosophy behind the so-called "deep-field" projects that subject small areas of the sky to intensive observations with different telescopes and methods. The astronomers determine the properties of the objects seen, as well as their distances and are then able to obtain a map of the space within the corresponding cone-of-view (the "pencil beam"). Recent, successful examples of this technique are the "Hubble Deep Field" (cf. ESO PR Photo 26/98 ) and the "Chandra Deep Field" ( ESO PR 05/01 ). In this context, the Capodimonte Deep Field (OACDF) is a pilot research project, now underway at the Osservatorio Astronomico di Capodimonte (OAC) in Napoli (Italy). It is a multi-colour imaging survey performed with the Wide Field Imager (WFI) , a 67-million pixel (8k x 8k) digital camera that is installed at the 2.2-m MPG/ESO Telescope at ESO's La Silla Observatory in Chile. The scientific goal of the OACDF is to provide an important database for subsequent extragalactic, galactic and planetary studies. It will allow the astronomers at OAC - who are involved in the VLT Survey Telescope (VST) project - to gain insight into the processing (and use) of the large data flow from a camera similar to, but four times smaller than the OmegaCam wide-field camera that will be installed at the VST. The field selection for the OACDF was based on the following criteria: * There must be no stars brighter than about 9th magnitude in the field, in order to avoid saturation of the CCD detector and effects from straylight in the telescope and camera. No Solar System planets should be near the field during the observations; * It must be located far from the Milky Way plane (at high galactic latitude) in order to reduce the number of galactic stars seen in this direction; * It must be located in the southern sky in order to optimize observing conditions (in particular, the altitude of the field above the horizon), as seen from the La Silla and Paranal sites; * There should be little interstellar material in this direction that may obscure the view towards the distant Universe; * Observations in this field should have been made with the Hubble Space Telescope (HST) that may serve for comparison and calibration purposes. Based on these criteria, the astronomers selected a field measuring about 1 x 1 deg 2 in the southern constellation of Corvus (The Raven). This is now known as the Capodimonte Deep Field (OACDF) . The above photo ( PR Photo 15a/01 ) covers one-quarter of the full field (Subfield No. 2 - OACDF2) - some of the objects seen in this area are shown below in more detail. More than 35,000 objects have been found in this area; the faintest are nearly 100 million fainter than what can be perceived with the unaided eye in the dark sky. Selected objects in the Capodimonte Deep Field ESO PR Photo 15b/01 ESO PR Photo 15b/01 [Preview - JPEG: 400 x 435 pix - 60k] [Normal - JPEG: 800 x 870 pix - 738k] [Hi-Res - JPEG: 3000 x 3261 pix - 5.1M] Caption : Enlargement of the interacting galaxies that are seen in the upper left corner of the OACDF2 field shown in PR Photo 15a/01 . The enlargement covers 1250 x 1130 WFI pixels (1 pixel = 0.24 arcsec), or about 5.0 x 4.5 arcmin 2 in the sky. The lower spiral is itself an interactive double. ESO PR Photo 15c/01 ESO PR Photo 15c/01 [Preview - JPEG: 557 x 400 pix - 93k] [Normal - JPEG: 1113 x 800 pix - 937k] [Hi-Res - JPEG: 3000 x 2156 pix - 4.0M] Caption : Enlargement of a spiral galaxy and a nebulous object in this area. The field shown covers 1250 x 750 pixels, or about 5 x 3 arcmin 2 in the sky. Note the very red objects next to the two bright stars in the lower-right corner. The colours of these objects are consistent with those of spheroidal galaxies at intermediate distances (redshifts). ESO PR Photo 15d/01 ESO PR Photo 15d/01 [Preview - JPEG: 400 x 530 pix - 68k] [Normal - JPEG: 800 x 1060 pix - 870k] [Hi-Res - JPEG: 2768 x 3668 pix - 6.2M] Caption : A further enlargement of a galaxy cluster of which most members are located in the north-east quadrant (upper left) and have a reddish colour. The nebulous object to the upper left is a dwarf galaxy of spheroidal shape. The red object, located near the centre of the field and resembling a double star, is very likely a gravitational lens [2]. Some of the very red, point-like objects in the field may be distant quasars, very-low mass stars or, possibly, relatively nearby brown dwarf stars. The field shown covers 1380 x 1630 pixels, or 5.5 x 6.5 arcmin 2. ESO PR Photo 15e/01 ESO PR Photo 15e/01 [Preview - JPEG: 400 x 418 pix - 56k] [Normal - JPEG: 800 x 835 pix - 700k] [Hi-Res - JPEG: 3000 x 3131 pix - 5.0M] Caption : Enlargement of a moderately distant galaxy cluster in the south-east quadrant (lower left) of the OACDF2 field. The field measures 1380 x 1260 pixels, or about 5.5 x 5.0 arcmin 2 in the sky. ESO PR Photo 15f/01 ESO PR Photo 15f/01 [Preview - JPEG: 449 x 400 pix - 68k] [Normal - JPEG: 897 x 800 pix - 799k] [Hi-Res - JPEG: 3000 x 2675 pix - 5.6M] Caption : Enlargement of the elliptical galaxy that is located to the west (right) in the OACDF2 field. The numerous tiny objects surrounding the galaxy may be globular clusters. The fuzzy object on the right edge of the field may be a dwarf spheroidal galaxy. The size of the field is about 6 x 5 arcmin 2. Technical Information about the OACDF Survey The observations for the OACDF project were performed in three different ESO periods (18-22 April 1999, 7-12 March 2000 and 26-30 April 2000). Some 100 Gbyte of raw data were collected during each of the three observing runs. The first OACDF run was done just after the commissioning of the ESO-WFI. The observational strategy was to perform a 1 x 1 deg 2 short-exposure ("shallow") survey and then a 0.5 x 1 deg 2 "deep" survey. The shallow survey was performed in the B, V, R and I broad-band filters. Four adjacent 30 x 30 arcmin 2 fields, together covering a 1 x 1 deg 2 field in the sky, were observed for the shallow survey. Two of these fields were chosen for the 0.5 x 1 deg 2 deep survey; OACDF2 shown above is one of these. The deep survey was performed in the B, V, R broad-bands and in other intermediate-band filters. The OACDF data are fully reduced and the catalogue extraction has started. A two-processor (500 Mhz each) DS20 machine with 100 Gbyte of hard disk, specifically acquired at the OAC for WFI data reduction, was used. The detailed guidelines of the data reduction, as well as the catalogue extraction, are reported in a research paper that will appear in the European research journal Astronomy & Astrophysics . Notes [1]: The team members are: Massimo Capaccioli, Juan M. Alcala', Roberto Silvotti, Magda Arnaboldi, Vincenzo Ripepi, Emanuella Puddu, Massimo Dall'Ora, Giuseppe Longo and Roberto Scaramella . [2]: This is a preliminary result by Juan Alcala', Massimo Capaccioli, Giuseppe Longo, Mikhail Sazhin, Roberto Silvotti and Vincenzo Testa , based on recent observations with the Telescopio Nazionale Galileo (TNG) which show that the spectra of the two objects are identical. Technical information about the photos PR Photo 15a/01 has been obtained by the combination of the B, V, and R stacked images of the OACDF2 field. The total exposure times in the three bands are 2 hours in B and V (12 ditherings of 10 min each were stacked to produce the B and V images) and 3 hours in R (13 ditherings of 15 min each). The mosaic images in the B and V bands were aligned relative to the R-band image and adjusted to a logarithmic intensity scale prior to the combination. The typical seeing was of the order of 1 arcsec in each of the three bands. Preliminary estimates of the three-sigma limiting magnitudes in B, V and R indicate 25.5, 25.0 and 25.0, respectively. More than 35,000 objects are detected above the three-sigma level. PR Photos 15b-f/01 display selected areas of the field shown in PR Photo 15a/01 at the original WFI scale, hereby also demonstrating the enormous amount of information contained in these wide-field images. In all photos, North is up and East is left.

Energy Levels in Quantum Wells.

NASA Astrophysics Data System (ADS)

Zang, Jan Xin

Normalized analytical equations for eigenstates of an arbitrary one-dimensional configuration of square potentials in a well have been derived. The general formulation is used to evaluate the energy levels of a particle in a very deep potential well containing seven internal barriers. The configuration can be considered as a finite superlattice sample or as a simplified model for a sample with only several atom layers. The results are shown in graphical forms as functions of the height and width of the potential barriers and as functions of the ratio of the effective mass in barrier to the mass in well. The formation of energy bands and surface eigenstates from eigenstates of a deep single well, the coming close of two energy bands and a surface state which are separate ordinarily, and mixing of the wave function of a surface state with the bulk energy bands are seen. Then the normalized derivation is extended to study the effect of a uniform electric field applied across a one-dimensional well containing an internal configuration of square potentials The general formulation is used to calculate the electric field dependence of the energy levels of a deep well with five internal barriers. Typical results are shown in graphical forms as functions of the barrier height, barrier width, barrier effective mass and the field strength. The formation of Stark ladders and surface states from the eigenstates of a single deep well in an electric field, the localization process of wave functions with changing barrier height, width, and field strength and their anticrossing behaviors are seen. The energy levels of a hydrogenic impurity in a uniform medium and in a uniform magnetic field are calculated with variational methods. The energy eigenvalues for the eigenstates with major quantum number less than or equal to 3 are obtained. The results are consistent with previous results. Furthermore, the energy levels of a hydrogenic impurity at the bottom of a one-dimensional parabolic quantum well with a magnetic field normal to the plane of the well are calculated with the finite-basis-set variational method. The limit of small radial distance and the limit of great radial distance are considered to choose a set of proper basis functions. It is found that the energy levels increase with increasing parabolic parameter alpha and increase with increasing normalized magnetic field strength gamma except those levels with magnetic quantum number m < 0 at small gamma.

Field performance of timber bridges. 17, Ciphers stress-laminated deck bridge

Treesearch

James P. Wacker; James A. Kainz; Michael A. Ritter

In September 1989, the Ciphers bridge was constructed within the Beltrami Island State Forest in Roseau County, Minnesota. The bridge superstructure is a two-span continuous stress-laminated deck that is approximately 12.19 m long, 5.49 m wide, and 305 mm deep (40 ft long, 18 ft wide, and 12 in. deep). The bridge is one of the first to utilize red pine sawn lumber for...

Field performance of timber bridges. 12, Christian Hollow stress-laminated box-beam bridge

Treesearch

J. P. Wacker; S. C. Catherman; R. G. Winnett

In January 1992, the Christian Hollow bridge was constructed in Steuben County, New York. The bridge is a single-span, stress-laminated box-beam superstructure that is 9.1 m long, 9.8 m wide, and 502 mm deep (30 ft long, 32 ft wide, and 19-3/4 in. deep). The performance of the bridge was continuously monitored for 28 months, beginning shortly after installation....

Ground-water levels and direction of ground-water flow in the central part of Bernalillo County, New Mexico, summer 1983

USGS Publications Warehouse

Kues, Georginna E.

1986-01-01

In 1980, toxic chemicals were detected in water samples from wells in and near Albuquerque 's San Jose well field. At the request of the Environmental Improvement Division of the New Mexico Health and Environment Department, the U.S. Geological Survey conducted a study to determine groundwater levels and flow direction. Water levels were measured in 44 wells in a 64 sq mi area along the Rio Grande and adjacent areas during a period of near maximum municipal pumpage. Based on the altitude of screened interval, wells were grouped into shallow (screened internal above an altitude of 4,800 ft) or deep (screened internal below an altitude of 4,800 ft) zones. Groundwater in the shallow zone generally moves from north to south parallel to flow in the Rio Grande. Groundwater in the deep zone generally moves from the northwest to the east and southeast. A poorly developed cone of depression within the deep zone was present in the northeast. Water levels in wells were as much as 18 feet higher in the shallow zone than in the deep zone in the vicinity of the San Jose well field, indicating a downward gradient. (Author 's abstract)

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

Characterization Efforts in a Deep Borehole Field Test

NASA Astrophysics Data System (ADS)

Kuhlman, K. L.; Sassani, D.; Freeze, G. A.; Hardin, E. L.; Brady, P. V.

2016-12-01

The US Department of Energy Office of Nuclear Energy is embarking on a Deep Borehole Field Test to investigate the feasibility of constructing and characterizing two boreholes in crystalline basement rock to a depth of 5 km (16,400 ft). The concept of deep borehole disposal for radioactive waste has some advantages, including incremental construction and loading and the enhanced natural barriers provided by deep continental crystalline basement. Site characterization activities will include geomechanical (i.e., hydrofracture stress measurements), geological (i.e., core and mud logging), hydrological (i.e., packer-based pulse and pumping tests), and chemical (i.e., fluids sampled in situ from packer intervals and extracted from cores) tests. Borehole-based characterization will be used to determine the variability of system state (i.e., stress, pressure, temperature, and chemistry) with depth and interpretation of material and system parameters relevant to numerical site simulation. We explore the effects fluid density and geothermal temperature gradients (i.e., thermohaline convection) have on characterization goals in light of expected downhole conditions, including a disturbed rock zone surrounding the borehole. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Dynamic Jahn-Teller effect: Calculation of fine structure spectrum, isotope shift and Zeeman behavior at deep center Ni2+ in CdS

NASA Astrophysics Data System (ADS)

Schoepp, Juergen

The internal transition of the deep center Ni2+ in II to IV semiconductor cadmium sulfide is examined with reference to crystal field theory. An algorithm was developed for calculation, in a basis fitted to trigonal symmetry, of fine structure operator matrix which is made of the sum of operators from spin trajectory coupling, trigonal field and electron phonon coupling. The dependence of energy level on the mass was calculated in order to examine the isotropy effect at Ni2+ transition. The mass dependence of phonon energy was estimated in an atomic cluster by using a valence force model from Keating for elastic energy. The Zeeman behavior of Ni2+ transition was examined for magnetic fields; the Zeeman operator was added to the fine structure operator and the resulting matrix was diagonalized. It is noticed that calculations are quantitatively and qualitatively in agreement with experiments.

Condenser for ring-field deep ultraviolet and extreme ultraviolet lithography

DOEpatents

Chapman, Henry N.; Nugent, Keith A.

2002-01-01

A condenser for use with a ring-field deep ultraviolet or extreme ultraviolet lithography system. A condenser includes a ripple-plate mirror which is illuminated by a collimated or converging beam at grazing incidence. The ripple plate comprises a flat or curved plate mirror into which is formed a series of channels along an axis of the mirror to produce a series of concave surfaces in an undulating pattern. Light incident along the channels of the mirror is reflected onto a series of cones. The distribution of slopes on the ripple plate leads to a distribution of angles of reflection of the incident beam. This distribution has the form of an arc, with the extremes of the arc given by the greatest slope in the ripple plate. An imaging mirror focuses this distribution to a ring-field arc at the mask plane.

Deep Borehole Field Test Conceptual Design Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardin, Ernest L.

This report documents conceptual design development for the Deep Borehole Field Test (DBFT), including test packages (simulated waste packages, not containing waste) and a system for demonstrating emplacement and retrieval of those packages in the planned Field Test Borehole (FTB). For the DBFT to have demonstration value, it must be based on conceptualization of a deep borehole disposal (DBD) system. This document therefore identifies key options for a DBD system, describes an updated reference DBD concept, and derives a recommended concept for the DBFT demonstration. The objective of the DBFT is to confirm the safety and feasibility of the DBDmore » concept for long-term isolation of radioactive waste. The conceptual design described in this report will demonstrate equipment and operations for safe waste handling and downhole emplacement of test packages, while contributing to an evaluation of the overall safety and practicality of the DBD concept. The DBFT also includes drilling and downhole characterization investigations that are described elsewhere (see Section 1). Importantly, no radioactive waste will be used in the DBFT, nor will the DBFT site be used for disposal of any type of waste. The foremost performance objective for conduct of the DBFT is to demonstrate safe operations in all aspects of the test.« less

2015 DOE Final UF Report. Effects of Warming the Deep Soil and Permafrost on Ecosystem Carbon Balance in Alaskan Tundra. A Coupled Measurement and Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuur, Edward

2015-06-11

The major research goal of this project was to understand and quantify the fate of carbon stored in permafrost ecosystems using a combination of field and laboratory experiments to measure isotope ratios and C fluxes in a tundra ecosystem exposed to experimental warming. Field measurements centered on the establishment of a two-factor experimental warming using a snow fence and open top chambers to increase winter and summer temperatures alone, and in combination, at a tundra field site at the Eight Mile Lake watershed near Healy, Alaska. The objective of this experimental warming was to significantly raise air and deep soilmore » temperatures and increase the depth of thaw beyond that of previous warming experiments. Detecting the loss and fate of the old permafrost C pool remains a major challenge. Because soil C has been accumulating in these ecosystems over the past 10,000 years, there is a strong difference between the radiocarbon isotopic composition of C deep in the soil profile and permafrost compared to that near the soil surface. This large range of isotopic variability is unique to radiocarbon and provides a valuable and sensitive fingerprint for detecting the loss of old soil C as permafrost thaws.« less

Benchmarking Deep Learning Models on Large Healthcare Datasets.

PubMed

Purushotham, Sanjay; Meng, Chuizheng; Che, Zhengping; Liu, Yan

2018-06-04

Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking results for several clinical prediction tasks such as mortality prediction, length of stay prediction, and ICD-9 code group prediction using Deep Learning models, ensemble of machine learning models (Super Learner algorithm), SAPS II and SOFA scores. We used the Medical Information Mart for Intensive Care III (MIMIC-III) (v1.4) publicly available dataset, which includes all patients admitted to an ICU at the Beth Israel Deaconess Medical Center from 2001 to 2012, for the benchmarking tasks. Our results show that deep learning models consistently outperform all the other approaches especially when the 'raw' clinical time series data is used as input features to the models. Copyright © 2018 Elsevier Inc. All rights reserved.

Deep learning of unsteady laminar flow over a cylinder

NASA Astrophysics Data System (ADS)

Lee, Sangseung; You, Donghyun

2017-11-01

Unsteady flow over a circular cylinder is reconstructed using deep learning with a particular emphasis on elucidating the potential of learning the solution of the Navier-Stokes equations. A deep neural network (DNN) is employed for deep learning, while numerical simulations are conducted to produce training database. Instantaneous and mean flow fields which are reconstructed by deep learning are compared with the simulation results. Fourier transform of flow variables has been conducted to validate the ability of DNN to capture both amplitudes and frequencies of flow motions. Basis decomposition of learned flow is performed to understand the underlying mechanisms of learning flow through DNN. The present study suggests that a deep learning technique can be utilized for reconstruction and, potentially, for prediction of fluid flow instead of solving the Navier-Stokes equations. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(Ministry of Science, ICT and Future Planning) (No. 2014R1A2A1A11049599, No. 2015R1A2A1A15056086, No. 2016R1E1A2A01939553).

[Effects of deep plowing and mulch in fallow period on soil water and yield of wheat in dryland].

PubMed

Deng, Yan; Gao, Zhi-Qiang; Sun, Min; Zhao, Wei-Feng; Zhao, Hong-Mei; Li, Qing

2014-01-01

A field test was carried out in Qiujialing Village, Wenxi, Shanxi from 2009 to 2011 to study the soil water movement of 0-300 cm layer, yield formation and water use efficiency (WUE) of wheat with deep plowing and mulching the whole ground immediately (no mulch as control) 15 days and 45 days after harvest. The results indicated that deep plowing and mulch in fallow period could improve soil water storage of the 100-180 cm layer before sowing, the soil water storage efficiency in fallow period, and soil water storage from pre-wintering stage to booting stage. Compared with deep plowing 15 days after wheat harvest, deep plowing 45 days after wheat harvest did better in improving soil water storage and water use efficiency, as well as ear number and yield, which was more conducive in the year with more precipitation. Generally, deep plowing and mulching after raining during fallow period could benefit the soil water storage and conservation, thus would be helpful to improve wheat yield in dryland.

Polar Cap Energy Deposition Events During the 5-6 August 2011 Magnetic Storm

NASA Astrophysics Data System (ADS)

Horvath, Ildiko; Lovell, Brian C.

2018-03-01

We study the 5-6 August 2011 storm for its energy deposition events occurring deep in the polar cap region, where the consequential localized intensifications of earthward directed Poynting flux led to the development of their related localized neutral density increases. For unraveling the underlying physical processes, we investigate the relations among Poynting flux intensifications, flow channels (FCs), and localized neutral density enhancements plus the nature of the underlying reconnection events. Observational results demonstrate Poynting flux increase deep in the polar cap in a FC-2 type FC during magnetopause reconnections and in a FC-4 type FC during lobe reconnections. During the latter stages of these different types of reconnection events, energy/momentum transfer occurred along old-open field lines and commonly led to the development of localized neutral density increases during their respective upwelling events fueled by field-aligned currents and above/within these polar FCs. The prevailing BY domination and the pulsed nature of this storm created favorable conditions for the development of these FC-2 and FC-4 types in the sunlit northern summer hemisphere and caused the observed Poynting flux intensifications deep in the polar cap. The solar wind source of these reconnections taking place along old-open field lines was situated in the high-latitude boundary layer. Thus, the high-latitude boundary layer dynamo provided a vigorous source of energy/momentum transfer during the latter-stage reconnections unfolding along old-open field lines.

The intense starburst HDF 850.1 in a galaxy overdensity at z ≈ 5.2 in the Hubble Deep Field.

PubMed

Walter, Fabian; Decarli, Roberto; Carilli, Chris; Bertoldi, Frank; Cox, Pierre; Da Cunha, Elisabete; Daddi, Emanuele; Dickinson, Mark; Downes, Dennis; Elbaz, David; Ellis, Richard; Hodge, Jacqueline; Neri, Roberto; Riechers, Dominik A; Weiss, Axel; Bell, Eric; Dannerbauer, Helmut; Krips, Melanie; Krumholz, Mark; Lentati, Lindley; Maiolino, Roberto; Menten, Karl; Rix, Hans-Walter; Robertson, Brant; Spinrad, Hyron; Stark, Dan P; Stern, Daniel

2012-06-13

The Hubble Deep Field provides one of the deepest multiwavelength views of the distant Universe and has led to the detection of thousands of galaxies seen throughout cosmic time. An early map of the Hubble Deep Field at a wavelength of 850 micrometres, which is sensitive to dust emission powered by star formation, revealed the brightest source in the field, dubbed HDF 850.1 (ref. 2). For more than a decade, and despite significant efforts, no counterpart was found at shorter wavelengths, and it was not possible to determine its redshift, size or mass. Here we report a redshift of z = 5.183 for HDF 850.1, from a millimetre-wave molecular line scan. This places HDF 850.1 in a galaxy overdensity at z ≈ 5.2, corresponding to a cosmic age of only 1.1 billion years after the Big Bang. This redshift is significantly higher than earlier estimates and higher than those of most of the hundreds of submillimetre-bright galaxies identified so far. The source has a star-formation rate of 850 solar masses per year and is spatially resolved on scales of 5 kiloparsecs, with an implied dynamical mass of about 1.3 × 10(11) solar masses, a significant fraction of which is present in the form of molecular gas. Despite our accurate determination of redshift and position, a counterpart emitting starlight remains elusive.

VizieR Online Data Catalog: Morphologies of selected AGN (Griffith+, 2010)

NASA Astrophysics Data System (ADS)

Griffith, R. L.; Stern, D.

2012-06-01

The cornerstone data set for the COSMOS survey is its wide-field HST Advanced Camera for Surveys (ACS) imaging (Scoville et al. 2007ApJS..172...38S). With 583 single-orbit HST ACS F814W (I band; hereafter I814) observations, it is the largest contiguous HST imaging survey to date. The VLA-COSMOS large project (Schinnerer et al., 2007, Cat. J/ApJS/172/46) acquired deep, uniform 1.4GHz data over the entire COSMOS field using the A-array configuration of the Very Large Array (VLA). The XMM-Newton COSMOS survey (Hasinger et al., 2007, Cat. J/ApJS/172/29; Cappelluti et al., 2009, Cat. J/A+A/497/635) acquired deep X-ray data over the entire COSMOS HST ACS field. The S-COSMOS survey (Sanders et al., 2007ApJS..172...86S) is a Spitzer Legacy program which carried out a uniformly deep survey of the full COSMOS field in seven mid-IR bands (3.6, 4.5, 5.8, 8.0, 24, 70, and 160um). The Advanced Camera for Surveys General Catalog2 (ACS-GC) data (R.L. Griffith et al., 2012ApJS..200....9G) was constructed to study the evolution of galaxy morphologies over a wide range of look-back times. The ACS-GC uniformly analyzes the largest HST ACS imaging surveys (AEGIS, GEMS, GOODS-S, GOODS-N, and COSMOS) using the GALAPAGOS code. (3 data files).

Software Graphics Processing Unit (sGPU) for Deep Space Applications

NASA Technical Reports Server (NTRS)

McCabe, Mary; Salazar, George; Steele, Glen

2015-01-01

A graphics processing capability will be required for deep space missions and must include a range of applications, from safety-critical vehicle health status to telemedicine for crew health. However, preliminary radiation testing of commercial graphics processing cards suggest they cannot operate in the deep space radiation environment. Investigation into an Software Graphics Processing Unit (sGPU)comprised of commercial-equivalent radiation hardened/tolerant single board computers, field programmable gate arrays, and safety-critical display software shows promising results. Preliminary performance of approximately 30 frames per second (FPS) has been achieved. Use of multi-core processors may provide a significant increase in performance.

Developments in deep brain stimulation using time dependent magnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crowther, L.J.; Nlebedim, I.C.; Jiles, D.C.

2012-03-07

The effect of head model complexity upon the strength of field in different brain regions for transcranial magnetic stimulation (TMS) has been investigated. Experimental measurements were used to verify the validity of magnetic field calculations and induced electric field calculations for three 3D human head models of varying complexity. Results show the inability for simplified head models to accurately determine the site of high fields that lead to neuronal stimulation and highlight the necessity for realistic head modeling for TMS applications.

Developments in deep brain stimulation using time dependent magnetic fields

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Nlebedim, I. C.; Jiles, D. C.

2012-04-01

The effect of head model complexity upon the strength of field in different brain regions for transcranial magnetic stimulation (TMS) has been investigated. Experimental measurements were used to verify the validity of magnetic field calculations and induced electric field calculations for three 3D human head models of varying complexity. Results show the inability for simplified head models to accurately determine the site of high fields that lead to neuronal stimulation and highlight the necessity for realistic head modeling for TMS applications.

THE ALLEN TELESCOPE ARRAY Pi GHz SKY SURVEY. III. THE ELAIS-N1, COMA, AND LOCKMAN HOLE FIELDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croft, Steve; Bower, Geoffrey C.; Whysong, David

2013-01-10

We present results from a total of 459 repeated 3.1 GHz radio continuum observations (of which 379 were used in a search for transient sources) of the ELAIS-N1, Coma, Lockman Hole, and NOAO Deep Wide Field Survey fields as part of the Pi GHz Sky Survey. The observations were taken approximately once per day between 2009 May and 2011 April. Each image covers 11.8 square degrees and has 100'' FWHM resolution. Deep images for each of the four fields have rms noise between 180 and 310 {mu}Jy, and the corresponding catalogs contain {approx}200 sources in each field. Typically 40-50 ofmore » these sources are detected in each single-epoch image. This represents one of the shortest cadence, largest area, multi-epoch surveys undertaken at these frequencies. We compare the catalogs generated from the combined images to those from individual epochs, and from monthly averages, as well as to legacy surveys. We undertake a search for transients, with particular emphasis on excluding false positive sources. We find no confirmed transients, defined here as sources that can be shown to have varied by at least a factor of 10. However, we find one source that brightened in a single-epoch image to at least six times the upper limit from the corresponding deep image. We also find a source associated with a z = 0.6 quasar which appears to have brightened by a factor {approx}3 in one of our deep images, when compared to catalogs from legacy surveys. We place new upper limits on the number of transients brighter than 10 mJy: fewer than 0.08 transients deg{sup -2} with characteristic timescales of months to years; fewer than 0.02 deg{sup -2} with timescales of months; and fewer than 0.009 deg{sup -2} with timescales of days. We also plot upper limits as a function of flux density for transients on the same timescales.« less

High permeability cores to optimize the stimulation of deeply located brain regions using transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Salvador, R.; Miranda, P. C.; Roth, Y.; Zangen, A.

2009-05-01

Efficient stimulation of deeply located brain regions with transcranial magnetic stimulation (TMS) poses many challenges, arising from the fact that the induced field decays rapidly and becomes less focal with depth. We propose a new method to improve the efficiency of TMS of deep brain regions that combines high permeability cores, to increase focality and field intensity, with a coil specifically designed to induce a field that decays slowly with increasing depth. The performance of the proposed design was investigated using the finite element method to determine the total electric field induced by this coil/core arrangement on a realistically shaped homogeneous head model. The calculations show that the inclusion of the cores increases the field's magnitude by as much as 25% while also decreasing the field's decay with depth along specific directions. The focality, as measured by the area where the field's norm is greater than 1/\\sqrt 2 of its maximum value, is also improved by as much as 15% with some core arrangements. The coil's inductance is not significantly increased by the cores. These results show that the presence of the cores might make this specially designed coil even more suited for the effective stimulation of deep brain regions.

Deep eutectic solvent formation: a structural view using molecular dynamics simulations with classical force fields

NASA Astrophysics Data System (ADS)

Mainberger, Sebastian; Kindlein, Moritz; Bezold, Franziska; Elts, Ekaterina; Minceva, Mirjana; Briesen, Heiko

2017-06-01

Deep eutectic solvents (DES) have gained a reputation as inexpensive and easy to handle ionic liquid analogues. This work employs molecular dynamics (MD) to simulate a variety of DES. The hydrogen bond acceptor (HBA) choline chloride was paired with the hydrogen bond donors (HBD) glycerol, 1,4-butanediol, and levulinic acid. Levulinic acid was also paired with the zwitterionic HBA betaine. In order to evaluate the reliability of data MD simulations can provide for DES, two force fields were compared: the Merck Molecular Force Field and the General Amber Force Field with two different sets of partial charges for the latter. The force fields were evaluated by comparing available experimental thermodynamic and transport properties against simulated values. Structural analysis was performed on the eutectic systems and compared to non-eutectic compositions. All force fields could be validated against certain experimental properties, but performance varied depending on the system and property in question. While extensive hydrogen bonding was found for all systems, details about the contribution of individual groups strongly varied among force fields. Interaction potentials revealed that HBA-HBA interactions weaken linearly with increasing HBD ratio, while HBD-HBD interactions grew disproportionally in magnitude, which might hint at the eutectic composition of a system.

The Wide Field X-ray Telescope Mission

NASA Astrophysics Data System (ADS)

Murray, Stephen S.; WFXT Team

2010-01-01

To explore the high-redshift Universe to the era of galaxy formation requires an X-ray survey that is both sensitive and extensive, which complements deep wide-field surveys at other wavelengths. The Wide-Field X-ray Telescope (WFXT) is designed to be two orders of magnitude more effective than previous and planned X-ray missions for surveys. WFXT consists of three co-aligned wide-field X-ray telescopes with a 1 sq. deg. field of view and <10 arc sec (goal of 5 arc sec) angular resolution over the full field. With nearly ten times Chandra's collecting area and more than ten times Chandra's field of view, WFXT will perform sensitive deep surveys that will discover and characterize extremely large populations of high redshift AGN and galaxy clusters. In five years, WFXT will perform three extragalactic surveys: 1) 20,000 sq. deg. of extragalactic sky at 100-1000 times the sensitivity, and twenty times better angular resolution than the ROSAT All Sky Survey; 2) 3000 sq.deg. to deep Chandra sensitivity; and 3) 100 sq.deg. to the deepest Chandra sensitivity. WFXT will generate a legacy dataset of >500,000 galaxy clusters to redshifts about 2, measuring redshift, gas abundance and temperature for a significant fraction of them, and a sample of more than 10 million AGN to redshifts > 6, many with X-ray spectra sufficient to distinguish obscured from unobscured quasars. These surveys will address fundamental questions of how supermassive black holes grow and influence the evolution of the host galaxy and how clusters form and evolve, as well as providing large samples of massive clusters that can be used in cosmological studies. WFXT surveys will map systems spanning many square degrees including Galactic star forming regions, the Magellanic Clouds and the Virgo Cluster. WFXT data will become public through annual Data Releases that will constitute a vast scientific legacy.

VizieR Online Data Catalog: GOODS-S CANDELS multiwavelength catalog (Guo+, 2013)

NASA Astrophysics Data System (ADS)

Guo, Y.; Ferguson, H. C.; Giavalisco, M.; Barro, G.; Willner, S. P.; Ashby, M. L. N.; Dahlen, T.; Donley, J. L.; Faber, S. M.; Fontana, A.; Galametz, A.; Grazian, A.; Huang, K.-H.; Kocevski, D. D.; Koekemoer, A. M.; Koo, D. C.; McGrath, E. J.; Peth, M.; Salvato, M.; Wuyts, S.; Castellano, M.; Cooray, A. R.; Dickinson, M. E.; Dunlop, J. S.; Fazio, G. G.; Gardner, J. P.; Gawiser, E.; Grogin, N. A.; Hathi, N. P.; Hsu, L.-T.; Lee, K.-S.; Lucas, R. A.; Mobasher, B.; Nandra, K.; Newman, J. A.; van der Wel, A.

2014-04-01

The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS; Grogin et al. 2011ApJS..197...35G; Koekemoer et al. 2011ApJS..197...36K) is designed to document galaxy formation and evolution over the redshift range of z=1.5-8. The core of CANDELS is to use the revolutionary near-infrared HST/WFC3 camera, installed on HST in 2009 May, to obtain deep imaging of faint and faraway objects. The GOODS-S field, centered at RAJ2000=03:32:30 and DEJ2000=-27:48:20 and located within the Chandra Deep Field South (CDFS; Giacconi et al. 2002, Cat. J/ApJS/139/369), is a sky region of about 170arcmin2 which has been targeted for some of the deepest observations ever taken by NASA's Great Observatories, HST, Spitzer, and Chandra as well as by other world-class telescopes. The field has been (among others) imaged in the optical wavelength with HST/ACS in F435W, F606W, F775W, and F850LP bands as part of the HST Treasury Program: the Great Observatories Origins Deep Survey (GOODS; Giavalisco et al. 2004, Cat. II/261); in the mid-IR (3.6-24um) wavelength with Spitzer as part of the GOODS Spitzer Legacy Program (PI: M. Dickinson). The CDF-S/GOODS field was observed by the MOSAIC II imager on the CTIO 4m Blanco telescope to obtain deep U-band observations in 2001 September. Another U-band survey in GOODS-S was carried out using the VIMOS instrument mounted at the Melipal Unit Telescope of the VLT at ESO's Cerro Paranal Observatory, Chile. This large program of ESO (168.A-0485; PI: C. Cesarsky) was obtained in service mode observations in UT3 between 2004 August and fall 2006. In the ground-based NIR, imaging observations of the CDFS were carried out in J, H, Ks bands using the ISAAC instrument mounted at the Antu Unit Telescope of the VLT. Data were obtained as part of the ESO Large Programme 168.A-0485 (PI: C. Cesarsky) as well as ESO Programmes 64.O-0643, 66.A-0572, and 68.A-0544 (PI: E. Giallongo) with a total allocation time of ~500 hr from 1999 October to 2007 January. The CANDELS/GOODS-S field was also observed in the NIR as part of the ongoing HAWK-I UDS and GOODS-S survey (HUGS; VLT large program ID 186.A-0898; PI: A. Fontana; A. Fontana et al., in preparation) using the High Acuity Wide field K-band Imager (HAWK-I) on VLT. (1 data file).

The Iceland Deep Drilling Project (IDDP): (I) A New Era in Geothermal Development?

NASA Astrophysics Data System (ADS)

Elders, W. A.; Fridleifsson, G. O.; Bird, D. K.; Reed, M. H.; Schiffman, P.; Zierenberg, R.

2007-12-01

The Iceland Deep Drilling Project (IDDP) announced in September 2007 that an international industrial consortium has signed a new contract to collaborate in exploratory deep drilling in Iceland. The main objective of the IDDP is to investigate whether it is economically feasible to produce energy from geothermal systems at supercritical conditions. This will require drilling to depths of 4 to 5 km in order to reach temperatures of 400 to 600°C. Today, geothermal wells in Iceland typically range up to 2.5 km in depth and produce steam at about 300°C, or less, at a rate sufficient to generate about 4 to 7 megawatts of electricity. It is estimated that producing steam from a well penetrating a reservoir with temperatures >450°C, and at a rate of 0.67 cubic meters a second, could generate 40 to 50 MWe. If IDDP's test of this concept proves successful, it could lead to major improvements in the development of high-temperature geothermal resources worldwide. The consortium collaborating to fund this investigation of supercritical geothermal energy consists of three leading Icelandic power companies, Hitaveita Sudurnesja Ltd., Landsvirkjun, Orkuveita Reykjavikur, together with Orkustofnun (the National Energy Authority) and Alcoa Inc. (an international aluminum company). The three power companies financed a feasibility study for the project that was completed in 2003. Each of the three power companies is committed to drill, at their own cost, a 3.5 to 4.0 km deep well in a geothermal field that they operate. The design of these wells will permit them to be deepened to 4.5 or 5.0 km by the IDDP, and funded by the consortium with additional funds from international scientific agencies. The first deep IDDP well will be drilled in the latter part of 2008 in the Krafla geothermal field near the northern end of the central rift zone of Iceland, within a volcanic caldera that has had recent volcanic activity. Two new wells, ~4 km deep, will then be drilled at the Hengill and the Reykjanes geothermal fields during 2009-2010, and subsequently deepened. In contrast to the fresh water systems at Krafla and Hengill, the Reykjanes geothermal system produces hydrothermally modified seawater on the Reykjanes peninsula, in southern Iceland, where the Mid-Atlantic Ridge comes on land in southern Iceland. Processes at depth at Reykjanes should be similar to those responsible for black smokers on ocean spreading centers. The IDDP has engendered considerable international scientific interest. The US National Science Foundation and the International Continental Scientific Drilling Program will jointly fund the coring and sampling for scientific studies. In preparation for studying the data and samples that will be recovered by deep drilling research is underway on samples from existing wells in the target geothermal fields, and on exposed "fossil" geothermal systems and active mid-ocean ridge systems that have conditions believed to be similar to those that will be encountered in deep drilling by the IDDP. Some of these initial scientific studies by US investigators are reported in the accompanying papers.

Ethnomathematics in Perspective of Sundanese Culture

ERIC Educational Resources Information Center

Abdullah, Atje Setiawan

2017-01-01

This study is an exploratory research aims to find and know about a phenomenon by exploration. Therefore, the approach used in this study is ethnographic approach, an empirical and theoretical approach to get description and deep analysis about a culture based on field study. From the sustainable interviews and confirmation about field research…

Field testing of jet-grouted piles and drilled shafts.

DOT National Transportation Integrated Search

2014-01-01

A field study of deep foundations supporting high mast lighting and signage was undertaken in typical Florida : soils. Three drilled shafts (48 in x12 ft and two 48 in x18 ft) and two jet-grouted piles (28 in x18 ft) were : constructed in Keystone He...

Sediment Transportation Induced by Deep-Seated Landslides in a Debris Flow Basin in Taiwan

NASA Astrophysics Data System (ADS)

Lin, Meei Ling; Chen, Te Wei; Chen, Yong Sheng; Sin Jhuang, Han

2016-04-01

Typhoon Morakot brought huge amount of rainfall to the southern Taiwan in 2009 and caused severe landslides and debris flow hazard. After Typhoon Morakot, it was found that the volume of sediment transported by the debris flow and its effects on the affected area were much more significant compared to previous case history, which may due to the huge amount of rainfall causing significant deep-seated landslides in the basin. In this study, the effects and tendency of the sediment transportation in a river basin following deep-seated landslides caused by typhoon Morakot were evaluated. We used LiDAR, DEM, and aerial photo to identify characteristics of deep-seated landslides in a debris flow river basin, KSDF079 in Liuoguey District, Kaohsiung City, Taiwan. Eight deep-seated landslides were identified in the basin. To estimate the potential landslide volume associated with the deep-seated landslides, the stability analysis was conducted to locate the critical sliding surface, and the potential landside volume was estimated based on the estimation equation proposed by the International Geotechnical Societies' UNESCO Working Party on World Landslide Inventory (WP/WLI, 1990). The total potential landslide volume of the eight deep-seated landslides in KSDF079 basin was about 28,906,856 m3. Topographic analysis was performed by using DEM before and LiDAR derived DEM after typhoon Morakot to calculate the landslide volume transported. The result of erosion volume and deposition volume lead to a run out volume of 5,832,433 m3. The results appeared to consist well with the field condition and aerial photo. Comparing the potential landslide volume and run out volume of eight deep-seated landslides, it was found that the remaining potential landslide volume was about 80%. Field investigation and topographic analysis of the KSDF079 debris flow revealed that a significant amount of sediment deposition remained in the river channel ranging from the middle to the downstream section of the channel, and the channel has been widen. Such large proportion of landslide volume remained in the basin on deep-seated landslide scars and debris flow river channel would likely to cause further debris transportation in the future events. The stability analysis used in this study provided a feasible method and satisfactory results for estimating sediment volume transportation associated with the deep-seated landslides in the study area. Combination of the stability analysis results and the topographic analysis provided estimation of sediment transportation caused by the deep-seated landslides, and trend variation of further sediment transport of the basin, which could provide vital information for hazard mitigation. Keyword: deep-seated landslide, sediment transport, DEM, LiDAR, stability analysis

30 CFR 203.64 - How many applications may I file on a field or a development project?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 2 2011-07-01 2011-07-01 false How many applications may I file on a field or... ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Pre-Act Deep Water Leases and for Development and Expansion Projects § 203.64 How many applications may I file on a field or a development...

The MUSE Hubble Ultra Deep Field Survey. V. Spatially resolved stellar kinematics of galaxies at redshift 0.2 ≲ z ≲ 0.8

NASA Astrophysics Data System (ADS)

Guérou, Adrien; Krajnović, Davor; Epinat, Benoit; Contini, Thierry; Emsellem, Eric; Bouché, Nicolas; Bacon, Roland; Michel-Dansac, Leo; Richard, Johan; Weilbacher, Peter M.; Schaye, Joop; Marino, Raffaella Anna; den Brok, Mark; Erroz-Ferrer, Santiago

2017-11-01

We present spatially resolved stellar kinematic maps, for the first time, for a sample of 17 intermediate redshift galaxies (0.2 ≲ z ≲ 0.8). We used deep MUSE/VLT integral field spectroscopic observations in the Hubble Deep Field South (HDFS) and Hubble Ultra Deep Field (HUDF), resulting from ≈30 h integration time per field, each covering 1' × 1' field of view, with ≈ 0.̋65 spatial resolution. We selected all galaxies brighter than 25 mag in the I band and for which the stellar continuum is detected over an area that is at least two times larger than the spatial resolution. The resulting sample contains mostly late-type disk, main-sequence star-forming galaxies with 108.5 M⊙ ≲ M∗ ≲ 1010.5 M⊙. Using a full-spectrum fitting technique, we derive two-dimensional maps of the stellar and gas kinematics, including the radial velocity V and velocity dispersion σ. We find that most galaxies in the sample are consistent with having rotating stellar disks with roughly constant velocity dispersions and that the second order velocity moments Vrms = √V2+σ2 of the gas and stars, a scaling proxy for the galaxy gravitational potential, compare well to each other. These spatially resolved observations of the stellar kinematics of intermediate redshift galaxies suggest that the regular stellar kinematics of disk galaxies that is observed in the local Universe was already in place 4-7 Gyr ago and that their gas kinematics traces the gravitational potential of the galaxy, thus is not dominated by shocks and turbulent motions. Finally, we build dynamical axisymmetric Jeans models constrained by the derived stellar kinematics for two specific galaxies and derive their dynamical masses. These are in good agreement (within 25%) with those derived from simple exponential disk models based on the gas kinematics. The obtained mass-to-light ratios hint towards dark matter dominated systems within a few effective radii. Based on observations made with ESO telescopes at the La Silla-Paranal Observatory under programmes 094.A-0289(B), 095.A-0010(A), 096.A-0045(A) and 096.A-0045(B).

Control of deep lithospheric roots on crustal scale GOCE gravity and gradient fields evident in Gondwana reconstructions

NASA Astrophysics Data System (ADS)

Braitenberg, Carla; Mariani, Patrizia

2015-04-01

The GOCE gravity field is globally homogeneous at the resolution of about 80km or better allowing for the first time to analyze tectonic structures at continental scale. Geologic correlation studies based on age determination and mineral composition of rock samples propose to continue the tectonic lineaments across continents to the pre-breakup position. Tectonic events which induce density changes, as metamorphic events and magmatic events, should then show up in the gravity field. Therefore gravity can be used as a globally available supportive tool for interpolation of isolated samples. Applying geodynamic plate reconstructions to the GOCE gravity field places today's observed field at the pre-breakup position. In order to test the possible deep control of the crustal features, the same reconstruction is applied to the seismic velocity models, and a joint gravity-velocity analysis is performed. The geophysical fields allow to control the likeliness of the hypothesized continuation of lineations based on sparse surface outcrops. Total absence of a signal, makes the cross-continental continuation of the lineament improbable, as continental-wide lineaments are controlled by rheologic and compositional differences of lithospheric mantle. It is found that the deep lithospheric roots as those found below cratons control the position of the positive gravity values. The explanation is that the deep lithospheric roots focus asthenospheric upwelling outboard of the root protecting the overlying craton from magmatic intrusions. The study is carried out over the African and South American continents. The background for the study can be found in the following publications where the techniques which have been used are described: Braitenberg, C., Mariani, P. and De Min, A. (2013). The European Alps and nearby orogenic belts sensed by GOCE, Boll. Bollettino di Geofisica Teorica ed Applicata, 54(4), 321-334. doi:10.4430/bgta0105 Braitenberg, C. and Mariani, P. (2015). Geological implications from complete Gondwana GOCE-products reconstructions and link to lithospheric roots. Proceedings of 5th International GOCE User Workshop, 25 - 28 November 2014. Braitenberg, C. (2015). Exploration of tectonic structures with GOCE in Africa and across-continents. Int. J.Appl. Earth Observ. Geoinf. 35, 88-95. http://dx.doi.org/10.1016/j.jag.2014.01.013 Braitenberg, C. (2015). A grip on geological units with GOCE, IAG Symp. 141, in press.

DeepSurveyCam--A Deep Ocean Optical Mapping System.

PubMed

Kwasnitschka, Tom; Köser, Kevin; Sticklus, Jan; Rothenbeck, Marcel; Weiß, Tim; Wenzlaff, Emanuel; Schoening, Timm; Triebe, Lars; Steinführer, Anja; Devey, Colin; Greinert, Jens

2016-01-28

Underwater photogrammetry and in particular systematic visual surveys of the deep sea are by far less developed than similar techniques on land or in space. The main challenges are the rough conditions with extremely high pressure, the accessibility of target areas (container and ship deployment of robust sensors, then diving for hours to the ocean floor), and the limitations of localization technologies (no GPS). The absence of natural light complicates energy budget considerations for deep diving flash-equipped drones. Refraction effects influence geometric image formation considerations with respect to field of view and focus, while attenuation and scattering degrade the radiometric image quality and limit the effective visibility. As an improvement on the stated issues, we present an AUV-based optical system intended for autonomous visual mapping of large areas of the seafloor (square kilometers) in up to 6000 m water depth. We compare it to existing systems and discuss tradeoffs such as resolution vs. mapped area and show results from a recent deployment with 90,000 mapped square meters of deep ocean floor.

Survey on deep learning for radiotherapy.

PubMed

Meyer, Philippe; Noblet, Vincent; Mazzara, Christophe; Lallement, Alex

2018-07-01

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quick acquisition and recognition method for the beacon in deep space optical communications.

PubMed

Wang, Qiang; Liu, Yuefei; Ma, Jing; Tan, Liying; Yu, Siyuan; Li, Changjiang

2016-12-01

In deep space optical communications, it is very difficult to acquire the beacon given the long communication distance. Acquisition efficiency is essential for establishing and holding the optical communication link. Here we proposed a quick acquisition and recognition method for the beacon in deep optical communications based on the characteristics of the deep optical link. To identify the beacon from the background light efficiently, we utilized the maximum similarity between the collecting image and the reference image for accurate recognition and acquisition of the beacon in the area of uncertainty. First, the collecting image and the reference image were processed by Fourier-Mellin. Second, image sampling and image matching were applied for the accurate positioning of the beacon. Finally, the field programmable gate array (FPGA)-based system was used to verify and realize this method. The experimental results showed that the acquisition time for the beacon was as fast as 8.1s. Future application of this method in the system design of deep optical communication will be beneficial.

Neuronal inhibition and synaptic plasticity of basal ganglia neurons in Parkinson's disease

PubMed Central

Milosevic, Luka; Kalia, Suneil K; Hodaie, Mojgan; Lozano, Andres M; Fasano, Alfonso; Popovic, Milos R; Hutchison, William D

2018-01-01

Abstract Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease symptoms. The therapeutic benefits of deep brain stimulation are frequency-dependent, but the underlying physiological mechanisms remain unclear. To advance deep brain stimulation therapy an understanding of fundamental mechanisms is critical. The objectives of this study were to (i) compare the frequency-dependent effects on cell firing in subthalamic nucleus and substantia nigra pars reticulata; (ii) quantify frequency-dependent effects on short-term plasticity in substantia nigra pars reticulata; and (iii) investigate effects of continuous long-train high frequency stimulation (comparable to conventional deep brain stimulation) on synaptic plasticity. Two closely spaced (600 µm) microelectrodes were advanced into the subthalamic nucleus (n = 27) and substantia nigra pars reticulata (n = 14) of 22 patients undergoing deep brain stimulation surgery for Parkinson’s disease. Cell firing and evoked field potentials were recorded with one microelectrode during stimulation trains from the adjacent microelectrode across a range of frequencies (1–100 Hz, 100 µA, 0.3 ms, 50–60 pulses). Subthalamic firing attenuated with ≥20 Hz (P < 0.01) stimulation (silenced at 100 Hz), while substantia nigra pars reticulata decreased with ≥3 Hz (P < 0.05) (silenced at 50 Hz). Substantia nigra pars reticulata also exhibited a more prominent increase in transient silent period following stimulation. Patients with longer silent periods after 100 Hz stimulation in the subthalamic nucleus tended to have better clinical outcome after deep brain stimulation. At ≥30 Hz the first evoked field potential of the stimulation train in substantia nigra pars reticulata was potentiated (P < 0.05); however, the average amplitude of the subsequent potentials was rapidly attenuated (P < 0.01). This is suggestive of synaptic facilitation followed by rapid depression. Paired pulse ratios calculated at the beginning of the train revealed that 20 Hz (P < 0.05) was the minimum frequency required to induce synaptic depression. Lastly, the average amplitude of evoked field potentials during 1 Hz pulses showed significant inhibitory synaptic potentiation after long-train high frequency stimulation (P < 0.001) and these increases were coupled with increased durations of neuronal inhibition (P < 0.01). The subthalamic nucleus exhibited a higher frequency threshold for stimulation-induced inhibition than the substantia nigra pars reticulata likely due to differing ratios of GABA:glutamate terminals on the soma and/or the nature of their GABAergic inputs (pallidal versus striatal). We suggest that enhancement of inhibitory synaptic plasticity, and frequency-dependent potentiation and depression are putative mechanisms of deep brain stimulation. Furthermore, we foresee that future closed-loop deep brain stimulation systems (with more frequent off stimulation periods) may benefit from inhibitory synaptic potentiation that occurs after high frequency stimulation. PMID:29236966

Reversal Frequency, Core-Mantle Conditions, and the SCOR-field Hypothesis

NASA Astrophysics Data System (ADS)

Hoffman, K. A.

2009-12-01

One of the most intriguing results from paleomagnetic data spanning the past 108 yr comes from the work of McFadden et al. (1991) who found that the variation in the rate of polarity reversal is apparently tied to the temporal variation in the harmonic content of the full-polarity field. Their finding indicates that it is the relative importance of the two dynamo families--i.e. the Primary Family (PF), the field antisymmetric about the equator, and the Secondary Family (SF), the field symmetric about the equator--that largely determines reversal frequency. More specifically, McFadden et al. found that as the relative significance of the SF increases, as is observed during the Cenozoic, so too does reversal rate. Such a finding is reminiscent of the seminal work of Allan Cox who some forty years ago proposed that interactions with the non-dipole field may provide the trigger for reversal of the axial dipole (AD) field. Hence, new questions arise: Do the two dynamo family fields interact in this manner, and, if so, how can such an interaction physically occur in the fluid core? Gaussian coefficient terms comprising the PF and SF have degree and order (n + m) that sum to an odd and even number, respectively. The most significant field term in the PF is by far that of the axial dipole (g10). The entire SF, starting with the equatorial dipole terms (g11 and h11) and the axial quadrupole (g20), are constituents of the non-axial dipole (NAD) field. By way of both paleomagnetic transition and geomagnetic data Hoffman and Singer (2008) recently proposed (1) that field sources exist within the shallow core (SCOR-field) associated with fluid motions affected by long-lived core-mantle boundary conditions; (2) that these SCOR-field sources are largely separated from, i.e. in “poor communication” with, deep field convection roll-generated sources; and (3) that the deep sources are largely responsible for the AD field, leaving the SCOR-field to be the primary source for the NAD-field. This SCOR-field would almost exclusively contain the observed SF field, while the AD-field sources deeper within the core would be most responsible for the observed PF field. If so, the McFadden et al. result may be explained as follows: That the observed increasing significance of the SF field during the Cenozoic is the result of intensifying interactions between shallow core SCOR-field sources and deep core AD-field sources. This then suggests a progressive enhancement in the variability of physical conditions along the CMB which may indicate an accelerating influx of descended lithospheric plates and/or increasing number of plume roots during the Cenozoic.

Giddings Austin chalk enters deep lean-gas phase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moritis, G.

1995-12-25

Deep lean gas is the latest phase in the growth of the Giddings field Austin chalk play. The first phase involved drilling vertical oil and gas wells. Next came the horizontal well boom in the shallower Austin chalk area, which is still continuing. And now this third phase places horizontal laterals in the Austen chalk at about 14,000--15,000 ft to produce lean gas. The article describes the producing wells and gas gathering.

HDU Deep Space Habitat (DSH) Overview

NASA Technical Reports Server (NTRS)

Kennedy, Kriss J.

2011-01-01

This paper gives an overview of the National Aeronautics and Space Administration (NASA) led multi-center Habitat Demonstration Unit (HDU) project Deep Space Habitat (DSH) analog that will be field-tested during the 2011 Desert Research and Technologies Studies (D-RATS) field tests. The HDU project is a technology pull project that integrates technologies and innovations from multiple NASA centers. This project will repurpose the HDU Pressurized Excursion Module (PEM) that was field tested in the 2010 D-RATS, adding habitation functionality to the prototype unit. The 2010 configuration of the HDU-PEM consisted of a lunar surface laboratory module that was used to bring over 20 habitation-related technologies together in a single platform that could be tested as an advanced habitation analog in the context of mission architectures and surface operations. The 2011 HDU-DSH configuration will build upon the PEM work, and emphasize validity of crew operations (habitation and living, etc), EVA operations, mission operations, logistics operations, and science operations that might be required in a deep space context for Near Earth Object (NEO) exploration mission architectures. The HDU project consists of a multi-center team brought together in a skunkworks approach to quickly build and validate hardware in analog environments. The HDU project is part of the strategic plan from the Exploration Systems Mission Directorate (ESMD) Directorate Integration Office (DIO) and the Exploration Mission Systems Office (EMSO) to test destination elements in analog environments. The 2011 analog field test will include Multi Mission Space Exploration Vehicles (MMSEV) and the DSH among other demonstration elements to be brought together in a mission architecture context. This paper will describe overall objectives, various habitat configurations, strategic plan, and technology integration as it pertains to the 2011 field tests.

Exploring a deep meridional flow hypothesis for a circulation dominated solar dynamo model

NASA Astrophysics Data System (ADS)

Guerrero, G. A.; Muñoz, J. D.; de Gouveia dal Pino, E. M.

2005-09-01

Circulation-dominated solar dynamo models, which employ a helioseismic rotation profile and a fixed meridional flow, give a good approximation to the large scale solar magnetic phenomena, such as the 11-year cycle or the so called Hale's law of polarities. Nevertheless, the larger amplitude of the radial shear ∂Ω/∂r at the high latitudes makes the dynamo to produce a strong toroidal magnetic field at high latitudes, in contradiction with the observations of the sunspots (Sporer's Law). A possible solution was proposed by Nandy and Choudhuri in which a deep meridional flow can conduct the magnetic field inside of a stable layer (the radiative core) and then allow that it erupts just at lower latitudes. Although they obtain good results, this hypothesis generates new problems like the mixture of elements in the radiative core (that alters the abundance of the elements) and the transfer of angular momentum. We have recently explored this hypothesis in a different approximation, using the magnetic buoyancy mechanism proposed by Dikpati and Charbonneau (1999) and found that a deep meridional flow pushes the maximum of the toroidal magnetic field towards the solar equator, but, in contrast to Nandy and Choudhuri (2002 ), a second zone of maximum fields remains at the poles. In that work, we have also introduced a bipolytropic density profile in order to better reproduce the stratification in the radiative zone. We here review these results and also discuss a new possible scenario where the tachocline has an ellipsoidal shape, following early helioseismologic observations, and find that the modification of the geometry of the tachocline can lead to results which are in good agreement with observations and opens the possibility to explore in more detail, through the dynamo model, the place where the magnetic field could be really stored.

Clustering properties of g -selected galaxies at z ~ 0.8

DOE PAGES

Favole, Ginevra; Comparat, Johan; Prada, Francisco; ...

2016-06-21

In current and future large redshift surveys, as the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) or the Dark Energy Spectroscopic Instrument (DESI), we will use emission-line galaxies (ELGs) to probe cosmological models by mapping the large-scale structure of the Universe in the redshift range 0.6 < z < 1.7. We explore the halo-galaxy connection, with current data and by measuring three clustering properties of g-selected ELGs as matter tracers in the redshift range 0.6 < z < 1: (i) the redshift-space two-point correlation function using spectroscopic redshifts from the BOSS ELG sample and VIPERS; (ii)more » the angular two-point correlation function on the footprint of the CFHT-LS; (iii) the galaxy-galaxy lensing signal around the ELGs using the CFHTLenS. Furthermore, we interpret these observations by mapping them on to the latest high-resolution MultiDark Planck N-body simulation, using a novel (Sub)Halo-Abundance Matching technique that accounts for the ELG incompleteness. ELGs at z ~ 0.8 live in haloes of (1 ± 0.5) × 10 12 h -1 M⊙ and 22.5 ± 2.5 per cent of them are satellites belonging to a larger halo. The halo occupation distribution of ELGs indicates that we are sampling the galaxies in which stars form in the most efficient way, according to their stellar-to-halo mass ratio.« less

Next Generation Virgo Cluster Survey. XXI. The Weak Lensing Masses of the CFHTLS and NGVS RedGOLD Galaxy Clusters and Calibration of the Optical Richness

NASA Astrophysics Data System (ADS)

Parroni, Carolina; Mei, Simona; Erben, Thomas; Van Waerbeke, Ludovic; Raichoor, Anand; Ford, Jes; Licitra, Rossella; Meneghetti, Massimo; Hildebrandt, Hendrik; Miller, Lance; Côté, Patrick; Covone, Giovanni; Cuillandre, Jean-Charles; Duc, Pierre-Alain; Ferrarese, Laura; Gwyn, Stephen D. J.; Puzia, Thomas H.

2017-10-01

We measured stacked weak lensing cluster masses for a sample of 1323 galaxy clusters detected by the RedGOLD algorithm in the Canada-France-Hawaii Telescope Legacy Survey W1 and the Next Generation Virgo Cluster Survey at 0.2< z< 0.5, in the optical richness range 10< λ < 70. This is the most comprehensive lensing study of a ˜ 100 % complete and ˜ 80 % pure optical cluster catalog in this redshift range. We test different mass models, and our final model includes a basic halo model with a Navarro Frenk and White profile, as well as correction terms that take into account cluster miscentering, non-weak shear, the two-halo term, the contribution of the Brightest Cluster Galaxy, and an a posteriori correction for the intrinsic scatter in the mass-richness relation. With this model, we obtain a mass-richness relation of {log}{M}200/{M}⊙ =(14.46+/- 0.02)+(1.04+/- 0.09){log}(λ /40) (statistical uncertainties). This result is consistent with other published lensing mass-richness relations. We give the coefficients of the scaling relations between the lensing mass and X-ray mass proxies, L X and T X, and compare them with previous results. When compared to X-ray masses and mass proxies, our results are in agreement with most previous results and simulations, and consistent with the expected deviations from self-similarity.

Ultramafics-Hydrothermalism-Hydrogenesis-HyperSLiME (UltraH3) Linkage is a key for Occurrence of Last Universal Common Ancestral (LUCA) Community: Where is it, Lost City or Kairei (Rainbow)?

NASA Astrophysics Data System (ADS)

Takai, K.; Inagaki, F.; Nakamura, K.; Suzuki, K.; Kumagai, H.

2005-12-01

Deep-sea hydrothermal system has been recognized one of the most plausible places for origin of life in this planet. This hypothesis has been supported by evidences from multidisciplinary scientific fields. In geology, it has been demonstrated that the potentially most ancient microbial fossils are retrieved from the paleoenvironment, that might be related with deep-sea hydrothermal systems in the Archean. Chemical reactions suggesting prebiotic chemical evolution (synthesis of amino acids, nucleic acids and hydrocarbon, and polymerization of these molecules) are observed under the simulated physical and chemical conditions of the deep-sea hydrothermal vents in the laboratory. In addition, phylogenetic analyses of all the lives in this planet have clearly revealed that hyperthermophiles inhabiting deep-sea hydrothermal systems represent the deepest lineage of the life. Supposed that the Archean deep-sea hydrothermal system hosted the origin of life, what was the first life? We are pursuing the energy metabolism of our last universal common ancestor (LUCA) and the environmental settings hosting the LUCA. It is definitely expected that the genesis of LUCA occurred at high temperatures of locally organics-rich microenvironment around deep-sea hydrothermal field and the first energy metabolism depended on fermentation of simple amino acids, organic acids and sugars. However, these organics were immediately consumed by the hyperthermophilic LUCA activity. Inheritance of the LUCA needed to evolve the energy and carbon acquisitions to more stable and efficient mode. Chemolithoautotrophy might be the best because a plenty of reductive gas components were always provided by the hydrothermal activity. Hyperthermophilic chemolithoautotrophs could serve as the primary producers and could foster the heterotrophic fellows. This was the genesis of the last universal common ancestral (LUCA) community of life. We hypothesize that the LUCA community was metabolically approximated to hyperthermophilic subsurface lithoautotrophic microbial ecosystem (HyperSLiME) currently discovered beneath the Central Indian Ridge hydrothermal field. The environmental settings for the occurrence of HyperSLiME are now being characterized and an important linkage among the occurrence of HyperSLiME, extraordinary amount of hydrogen in the hydrothermal fluids and ultramfics-hosted hydrothermal systems is proposed. This ultramafics-hydrothermalism-hydrogen-HyperSLiME (UltraH3) linkage is very likely a key for the genesis of the LUCA community. We would like to discuss the possible UltraH3 linkage in the Archean earth. In addition, we would like to discuss which of modern deep-sea hydrothermal systems is the most plausible proxy for the Archean LUCA habitats.

Preliminary Results on Lunar Interior Properties from the GRAIL Mission

NASA Technical Reports Server (NTRS)

Williams, James G.; Konopliv, Alexander S.; Asmar, Sami W.; Lemoine, H. Jay; Melosh, H. Jay; Neumann, Gregory A.; Phillips, Roger J.; Smith, David E.; Solomon, Sean C.; Watkins, Michael M.;

Drag Reduction of an Airfoil Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, Chiyu; Sun, Anzhu; Marcus, Philip

2017-11-01

We reduced the drag of a 2D airfoil by starting with a NACA-0012 airfoil and used deep learning methods. We created a database which consists of simulations of 2D external flow over randomly generated shapes. We then developed a machine learning framework for external flow field inference given input shapes. Past work which utilized machine learning in Computational Fluid Dynamics focused on estimations of specific flow parameters, but this work is novel in the inference of entire flow fields. We further showed that learned flow patterns are transferable to cases that share certain similarities. This study illustrates the prospects of deeper integration of data-based modeling into current CFD simulation frameworks for faster flow inference and more accurate flow modeling.

First columbellid species (Gastropoda: Buccinoidea) from deep-sea hydrothermal vents, discovered in Okinawa Trough, Japan.

PubMed

Chen, Chong; Watanabe, Hiromi Kayama; Araya, Juan Francisco

2017-12-12

The molluscan diversity of deep-sea chemosynthetic ecosystems in Japan has been in general well documented with about 80 described species, of which over half are gastropods (Sasaki et al. 2005; Fujikura et al. 2012; Sasaki et al. 2016). Recently, however, a number of novel hydrothermal vent sites were discovered in the area using multibeam echo-sounding (Nakamura et al. 2015), providing opportunities for new discoveries. As a part of ongoing studies documenting the biodiversity of such sites, we present the first record of Columbellidae from hydrothermal vents, with a new species recovered from Natsu and Aki sites, in the Iheya North hydrothermal field (for map and background on the vent field see Nakamura et al. 2015).

Europa's differentiated internal structure: inferences from two Galileo encounters.

PubMed

Anderson, J D; Lau, E L; Sjogren, W L; Schubert, G; Moore, W B

1997-05-23

Doppler data generated with the Galileo spacecraft's radio carrier wave during two Europa encounters on 19 December 1996 (E4) and 20 February 1997 (E6) were used to measure Europa's external gravitational field. The measurements indicate that Europa has a predominantly water ice-liquid outer shell about 100 to 200 kilometers thick and a deep interior with a density in excess of about 4000 kilograms per cubic meter. The deep interior could be a mixture of metal and rock or it could consist of a metal core with a radius about 40 percent of Europa's radius surrounded by a rock mantle with a density of 3000 to 3500 kilograms per cubic meter. The metallic core is favored if Europa has a magnetic field.

GCR Simulator Reference Field and a Spectral Approach for Laboratory Simulation

NASA Technical Reports Server (NTRS)

Slaba, Tony C.; Blattnig, Steve R.; Norbury, John W.; Rusek, Adam; La Tessa, Chiara; Walker, Steven A.

2015-01-01

The galactic cosmic ray (GCR) simulator at the NASA Space Radiation Laboratory (NSRL) is intended to deliver the broad spectrum of particles and energies encountered in deep space to biological targets in a controlled laboratory setting. In this work, certain aspects of simulating the GCR environment in the laboratory are discussed. Reference field specification and beam selection strategies at NSRL are the main focus, but the analysis presented herein may be modified for other facilities. First, comparisons are made between direct simulation of the external, free space GCR field and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at NSRL limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, variation in the induced tissue field associated with shielding configuration and solar activity is addressed. It is found that the observed variation is likely within the uncertainty associated with representing any GCR reference field with discrete ion beams in the laboratory, given current facility constraints. A single reference field for deep space missions is subsequently identified. Third, an approach for selecting beams at NSRL to simulate the designated reference field is presented. Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies. The neutron component and track structure characteristics of the simulated field are discussed in this context.

Building the Next Generation of Earth Scientists: the Deep Carbon Observatory Early Career Scientist Workshops

NASA Astrophysics Data System (ADS)

Pratt, K.; Fellowes, J.; Giovannelli, D.; Stagno, V.

2016-12-01

Building a network of collaborators and colleagues is a key professional development activity for early career scientists (ECS) dealing with a challenging job market. At large conferences, young scientists often focus on interacting with senior researchers, competing for a small number of positions in leading laboratories. However, building a strong, international network amongst their peers in related disciplines is often as valuable in the long run. The Deep Carbon Observatory (DCO) began funding a series of workshops in 2014 designed to connect early career researchers within its extensive network of multidisciplinary scientists. The workshops, by design, are by and for early career scientists, thus removing any element of competition and focusing on peer-to-peer networking, collaboration, and creativity. The successful workshops, organized by committees of early career deep carbon scientists, have nucleated a lively community of like-minded individuals from around the world. Indeed, the organizers themselves often benefit greatly from the leadership experience of pulling together an international workshop on budget and on deadline. We have found that a combination of presentations from all participants in classroom sessions, professional development training such as communication and data management, and field-based relationship building and networking is a recipe for success. Small groups within the DCO ECS network have formed; publishing papers together, forging new research directions, and planning novel and ambitious field campaigns. Many DCO ECS also have come together to convene sessions at major international conferences, including the AGU Fall Meeting. Most of all, there is a broad sense of camaraderie and accessibility within the DCO ECS Community, providing the foundation for a career in the new, international, and interdisciplinary field of deep carbon science.

Generation and evaluation of an ultra-high-field atlas with applications in DBS planning

NASA Astrophysics Data System (ADS)

Wang, Brian T.; Poirier, Stefan; Guo, Ting; Parrent, Andrew G.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Purpose Deep brain stimulation (DBS) is a common treatment for Parkinson's disease (PD) and involves the use of brain atlases or intrinsic landmarks to estimate the location of target deep brain structures, such as the subthalamic nucleus (STN) and the globus pallidus pars interna (GPi). However, these structures can be difficult to localize with conventional clinical magnetic resonance imaging (MRI), and thus targeting can be prone to error. Ultra-high-field imaging at 7T has the ability to clearly resolve these structures and thus atlases built with these data have the potential to improve targeting accuracy. Methods T1 and T2-weighted images of 12 healthy control subjects were acquired using a 7T MR scanner. These images were then used with groupwise registration to generate an unbiased average template with T1w and T2w contrast. Deep brain structures were manually labelled in each subject by two raters and rater reliability was assessed. We compared the use of this unbiased atlas with two other methods of atlas-based segmentation (single-template and multi-template) for subthalamic nucleus (STN) segmentation on 7T MRI data. We also applied this atlas to clinical DBS data acquired at 1.5T to evaluate its efficacy for DBS target localization as compared to using a standard atlas. Results The unbiased templates provide superb detail of subcortical structures. Through one-way ANOVA tests, the unbiased template is significantly (p <0.05) more accurate than a single-template in atlas-based segmentation and DBS target localization tasks. Conclusion The generated unbiased averaged templates provide better visualization of deep brain nuclei and an increase in accuracy over single-template and lower field strength atlases.

Deep Vadose Zone Treatability Test for the Hanford Central Plateau: Interim Post-Desiccation Monitoring Results, Fiscal Year 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truex, Michael J.; Strickland, Christopher E.; Johnson, Christian D.

Over decades of operation, the U.S. Department of Energy (DOE) and its predecessors have released nearly 2 trillion L (450 billion gal.) of liquid into the vadose zone at the Hanford Site. Much of this discharge of liquid waste into the vadose zone occurred in the Central Plateau, a 200 km 2 (75 mi 2) area that includes approximately 800 waste sites. Some of the inorganic and radionuclide contaminants in the deep vadose zone at the Hanford Site are at depths below the limit of direct exposure pathways, but may need to be remediated to protect groundwater. The Tri-Party Agenciesmore » (DOE, U.S. Environmental Protection Agency, and Washington State Department of Ecology) established Milestone M 015 50, which directed DOE to submit a treatability test plan for remediation of technetium-99 (Tc-99) and uranium in the deep vadose zone. These contaminants are mobile in the subsurface environment and have been detected at high concentrations deep in the vadose zone, and at some locations have reached groundwater. Testing technologies for remediating Tc-99 and uranium will also provide information relevant for remediating other contaminants in the vadose zone. A field test of desiccation is being conducted as an element of the DOE test plan published in March 2008 to meet Milestone M 015 50. The active desiccation portion of the test has been completed. Monitoring data have been collected at the field test site during the post-desiccation period and are reported herein. This is an interim data summary report that includes about 3 years of post-desiccation monitoring data. The DOE field test plan proscribes a total of 5 years of post-desiccation monitoring.« less

A new InterRidge Working Group : Biogeochemical Interactions at Deep-sea Vents

NASA Astrophysics Data System (ADS)

Le Bris, N.; Boetius, A.; Tivey, M. K.; Luther, G. W.; German, C. R.; Wenzhoefer, F.; Charlou, J.; Seyfried, W. E.; Fortin, D.; Ferris, G.; Takai, K.; Baross, J. A.

2004-12-01

A new Working Group on `Biogeochemical Interactions at deep-sea vents' has been created at the initiative of the InterRidge programme. This interdisciplinary group comprises experts in chemistry, geochemistry, biogeochemistry, and microbial ecology addressing questions of biogeochemical interactions in different MOR and BAB environments. The past decade has raised major issues concerning the interactions between biotic and abiotic compartments of deep-sea hydrothermal environments and the role they play in the microbial turnover of C, S, N, Fe, fluxes from the geosphere to hydrosphere, the formation of biominerals, the functioning of vent ecosystems and life in extreme environments, the deep-biosphere, and the origin of life. Recent multidisciplinary studies have provided some new insights to these issues. Results of some of these studies will be presented here. They point out the variability and complexity of geobiological systems at vents in space and time and highlight the need for interactions across the fields of chemistry, geochemistry, biogeochemistry, and microbial ecology of hydrothermal environments. Limitation for advances in these fields include the availability of seafloor observation/experimentation time, and of underwater instrumentation allowing quantitative, in situ measurements of chemical and biological fluxes, as well as physical and chemical sensing and sampling along small scale gradients and repeated observation of study sites. The aim of this new Working Group is to strengthen the scientific exchange among chemists, geochemists, biogeochemists and microbial ecologists to favor collaboration in field studies including intercomparison of methods and planning of integrated experiments. The Biogeochemical Interactions working group will also foster development of underwater instrumentation for in situ biogeochemical measurements and microscale sampling, and promote exchange and collaboration with students and scientists of neighboring disciplines, particularly with vent biologists, ecologists and geologists .

Variation in toxicity response of Ceriodaphnia dubia to Athabasca oil sands coke leachates.

PubMed

Puttaswamy, Naveen; Turcotte, Dominique; Liber, Karsten

2010-07-01

Coke from the Athabasca (Alberta, Canada) oil sands operations may someday be integrated into reclamation landscapes. It is hypothesized that the metals associated with the solid coke may leach into the surrounding environment. Therefore, the main objectives of this study were to characterize the toxicity and chemistry of coke leachates collected from two field lysimeters (i.e. shallow lysimeter and deep lysimeter) over a period of 20months, as well as from other oil sands coke storage sites. In addition, a batch renewal leaching of coke was conducted to examine the rate of metals release. Chronic toxicity of key metals (e.g. Al, Mn, Ni and V) found in lysimeter coke leachate was evaluated separately. Toxicity test results revealed that whole coke leachates (100% v/v) were acutely toxic to Ceriodaphnia dubia; the 7-day LC50 values were always <25% v/v coke leachate. The deep lysimeter leachate was generally more toxic than the shallow lysimeter leachate, likely because of significantly higher concentrations of vanadium (V) found in the deep lysimeter leachate at all sampling times. Vanadium concentrations were higher than all other metals found in the leachate from both lysimeters, and in the batch renewal leaching study. Furthermore, V found in leachates collected from other oil sands field sites showed a concentration-response relationship with C. dubia survival. Mass balance calculations indicated that 94-98% of potentially leachable V fraction was still present in the coke from two field lysimeters. Evidence gathered from these assessments, including toxic unit (TU) calculations for the elements of concern, suggests that V was the likely cause of toxicity of the deep lysimeter leachate, whereas in the shallow lysimeter leachate both Ni and V could be responsible for the observed toxicity. 2010 Elsevier Ltd. All rights reserved.

The DEEP-South: Scheduling and Data Reduction Software System

NASA Astrophysics Data System (ADS)

Yim, Hong-Suh; Kim, Myung-Jin; Bae, Youngho; Moon, Hong-Kyu; Choi, Young-Jun; Roh, Dong-Goo; the DEEP-South Team

2015-08-01

The DEep Ecliptic Patrol of the Southern sky (DEEP-South), started in October 2012, is currently in test runs with the first Korea Microlensing Telescope Network (KMTNet) 1.6 m wide-field telescope located at CTIO in Chile. While the primary objective for the DEEP-South is physical characterization of small bodies in the Solar System, it is expected to discover a large number of such bodies, many of them previously unknown.An automatic observation planning and data reduction software subsystem called "The DEEP-South Scheduling and Data reduction System" (the DEEP-South SDS) is currently being designed and implemented for observation planning, data reduction and analysis of huge amount of data with minimum human interaction. The DEEP-South SDS consists of three software subsystems: the DEEP-South Scheduling System (DSS), the Local Data Reduction System (LDR), and the Main Data Reduction System (MDR). The DSS manages observation targets, makes decision on target priority and observation methods, schedules nightly observations, and archive data using the Database Management System (DBMS). The LDR is designed to detect moving objects from CCD images, while the MDR conducts photometry and reconstructs lightcurves. Based on analysis made at the LDR and the MDR, the DSS schedules follow-up observation to be conducted at other KMTNet stations. In the end of 2015, we expect the DEEP-South SDS to achieve a stable operation. We also have a plan to improve the SDS to accomplish finely tuned observation strategy and more efficient data reduction in 2016.

Elastic parabolic equation solutions for underwater acoustic problems using seismic sources.

PubMed

Frank, Scott D; Odom, Robert I; Collis, Jon M

2013-03-01

Several problems of current interest involve elastic bottom range-dependent ocean environments with buried or earthquake-type sources, specifically oceanic T-wave propagation studies and interface wave related analyses. Additionally, observed deep shadow-zone arrivals are not predicted by ray theoretic methods, and attempts to model them with fluid-bottom parabolic equation solutions suggest that it may be necessary to account for elastic bottom interactions. In order to study energy conversion between elastic and acoustic waves, current elastic parabolic equation solutions must be modified to allow for seismic starting fields for underwater acoustic propagation environments. Two types of elastic self-starter are presented. An explosive-type source is implemented using a compressional self-starter and the resulting acoustic field is consistent with benchmark solutions. A shear wave self-starter is implemented and shown to generate transmission loss levels consistent with the explosive source. Source fields can be combined to generate starting fields for source types such as explosions, earthquakes, or pile driving. Examples demonstrate the use of source fields for shallow sources or deep ocean-bottom earthquake sources, where down slope conversion, a known T-wave generation mechanism, is modeled. Self-starters are interpreted in the context of the seismic moment tensor.

A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking

PubMed Central

Shafiee, Mohammad Javad; Azimifar, Zohreh; Wong, Alexander

2015-01-01

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering. PMID:26313943

Evolution Of The Galaxy Major Merger Rate Since Z 6 In The Muse Hubble Ultra Deep Field Survey.

NASA Astrophysics Data System (ADS)

Ventou, E.; Contini, T.; MUSE-GTO Collaboration

2017-06-01

Over the past two decades, strong evidence that galaxies have undergone a significant evolution over cosmic time were found. Do galaxy mergers, one of the main driving mechanisms behind the growth of galaxies, played a key role in their evolution at significant look-back time? Due to the difficulty to identify these violent interactions between galaxies at high redshifts, the major merger rate, involving two galaxies of similar masses, was constrained so far up to redshift z 3, from previous studies of spectrocopic pair counts. Thanks to MUSE, which is perfectly suited to identify close pairs of galaxies with secure spectroscopic redshifts, we are now able to extend such studies up to z 6. I will present the results obtained from deep (10-30h) MUSE observations in the Hubble Ultra Deep Field. We provide the first constraints on the galaxy major merger evolution over 12 Gyrs (0.2 < z < 6) and over a broad range of stellar masses, showing that there is a flattening of the major merger rate evolution at very high redshift.

Neurostimulation for Drug-Resistant Epilepsy

PubMed Central

DeGiorgio, Christopher M.; Krahl, Scott E.

2013-01-01

Purpose of Review: The purpose of this review is to provide an evidence-based update on the neurostimulation options available for patients with drug-resistant epilepsy in the United States and in European countries. Recent Findings: The field of neurostimulation for epilepsy has grown dramatically since 1997, when vagus nerve stimulation became the first device to be approved for epilepsy by the US Food and Drug Administration (FDA). New data from recently completed randomized controlled trials are available for deep brain stimulation of the anterior thalamus, responsive neurostimulation, and trigeminal nerve stimulation. Although vagus nerve stimulation is the only device currently approved in the United States, deep brain stimulation and responsive neurostimulation devices are awaiting FDA approval. Deep brain stimulation, trigeminal nerve stimulation, and transcutaneous vagus nerve stimulation are now approved for epilepsy in the European Union. In this article, the mechanisms of action, safety, and efficacy of new neurostimulation devices are reviewed, and the key advantages and disadvantages of each are discussed. Summary: The exponential growth of the field of neuromodulation for epilepsy is an exciting development; these new devices provide physicians with new options for patients with drug-resistant epilepsy. PMID:23739108

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ha, Jin Gwan; Moon, Hyeonjoon; Kwak, Jin Tae; Hassan, Syed Ibrahim; Dang, Minh; Lee, O. New; Park, Han Yong

2017-10-01

Recently, unmanned aerial vehicles (UAVs) have gained much attention. In particular, there is a growing interest in utilizing UAVs for agricultural applications such as crop monitoring and management. We propose a computerized system that is capable of detecting Fusarium wilt of radish with high accuracy. The system adopts computer vision and machine learning techniques, including deep learning, to process the images captured by UAVs at low altitudes and to identify the infected radish. The whole radish field is first segmented into three distinctive regions (radish, bare ground, and mulching film) via a softmax classifier and K-means clustering. Then, the identified radish regions are further classified into healthy radish and Fusarium wilt of radish using a deep convolutional neural network (CNN). In identifying radish, bare ground, and mulching film from a radish field, we achieved an accuracy of ≥97.4%. In detecting Fusarium wilt of radish, the CNN obtained an accuracy of 93.3%. It also outperformed the standard machine learning algorithm, obtaining 82.9% accuracy. Therefore, UAVs equipped with computational techniques are promising tools for improving the quality and efficiency of agriculture today.

Ultraviolet Raman Wide-Field Hyperspectral Imaging Spectrometer for Standoff Trace Explosive Detection.

PubMed

Hufziger, Kyle T; Bykov, Sergei V; Asher, Sanford A

2017-02-01

We constructed the first deep ultraviolet (UV) Raman standoff wide-field imaging spectrometer. Our novel deep UV imaging spectrometer utilizes a photonic crystal to select Raman spectral regions for detection. The photonic crystal is composed of highly charged, monodisperse 35.5 ± 2.9 nm silica nanoparticles that self-assemble in solution to produce a face centered cubic crystalline colloidal array that Bragg diffracts a narrow ∼1.0 nm full width at half-maximum (FWHM) UV spectral region. We utilize this photonic crystal to select and image two different spectral regions containing resonance Raman bands of pentaerythritol tetranitrate (PETN) and NH 4 NO 3 (AN). These two deep UV Raman spectral regions diffracted were selected by angle tuning the photonic crystal. We utilized this imaging spectrometer to measure 229 nm excited UV Raman images containing ∼10-1000 µg/cm 2 samples of solid PETN and AN on aluminum surfaces at 2.3 m standoff distances. We estimate detection limits of ∼1 µg/cm 2 for PETN and AN films under these experimental conditions.

Photoinduced current transient spectroscopy of deep levels and transport mechanisms in iron-doped GaN thin films grown by low pressure-metalorganic vapor phase epitaxy

NASA Astrophysics Data System (ADS)

Muret, P.; Pernot, J.; Azize, M.; Bougrioua, Z.

2007-09-01

Electrical transport and deep levels are investigated in GaN:Fe layers epitaxially grown on sapphire by low pressure metalorganic vapor phase epitaxy. Photoinduced current transient spectroscopy and current detected deep level spectroscopy are performed between 200 and 650 K on three Fe-doped samples and an undoped sample. A detailed study of the detected deep levels assigns dominant centers to a deep donor 1.39 eV below the conduction band edge EC and to a deep acceptor 0.75 eV above the valence band edge EV at low electric field. A strong Poole-Frenkel effect is evidenced for the donor. Schottky diodes characteristics and transport properties in the bulk GaN:Fe layer containing a homogenous concentration of 1019 Fe/cm3 are typical of a compensated semiconductor. They both indicate that the bulk Fermi level is located typically 1.4 eV below EC, in agreement with the neutrality equation and dominance of the deep donor concentration. This set of results demonstrates unambiguously that electrical transport in GaN:Fe is governed by both types, either donor or acceptor, of the iron impurity, either substitutional in gallium sites or associated with other defects.

Deep-Sea Coral Image Catalog: Northeast Pacific

NASA Astrophysics Data System (ADS)

Freed, J. C.

2016-02-01

In recent years, deep-sea exploration in the Northeast Pacific ocean has been on the rise using submersibles and remotely operated vehicles (ROVs), acquiring a plethora of underwater videos and photographs. Analysis of deep-sea fauna revealed by this research has been hampered by the lack of catalogs or guides that allow identification of species in the field. Deep-sea corals are of particular conservation concern, but currently, there are few catalogs which describe and provide detailed information on deep-sea corals from the Northeast Pacific and those that exist are focused on small, specific areas. This project, in collaboration with NOAA's Deep-Sea Coral Ecology Laboratory at the Center for Coastal Environmental Health and Biomolecular Research (CCEHBR) and the Southwest Fisheries Science Center (SWFSC), developed pages for a deep-sea coral identification guide that provides photos and information on the visual identification, distributions, and habitats of species found in the Northeast Pacific. Using online databases, photo galleries, and literature, this catalog has been developed to be a living document open to future additions. This project produced 12 entries for the catalog on a variety of different deep-sea corals. The catalog is intended to be used during underwater surveys in the Northeast Pacific, but will also assist in identification of deep-sea coral by-catch by fishing vessels, and for general educational use. These uses will advance NOAA's ability to identify and protect sensitive deep-sea habitats that act as biological hotspots. The catalog is intended to be further developed into an online resource with greater interactive features with links to other resources and featured on NOAA's Deep-Sea Coral Data Portal.

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

NASA Astrophysics Data System (ADS)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging mapping task, DeepLab can detect small, irregular-shaped thermal erosion gullies with high accuracy. (2) Automatic detection is critical for mapping thermal erosion gully since manual mapping or field work may miss some targets even in a relatively small region. (3) The quantity and quality of training data are crucial for detection accuracy.

Deep 12 and 25 Micron Imaging with the Wide Field Infrared Explorer

NASA Technical Reports Server (NTRS)

Londsdale, Carol J.

1997-01-01

The Wide Field Infrared Explorer is a new NASA Small Explorer class observatory to be launced in late 1998. It will survey hundreds of square degrees of high latitude sky in the mid-infrared 12 and 25 micron bands to flux densities up to a factor of 1000 better than IRAS.

Hybrid Contactless Heating and Levitation

NASA Technical Reports Server (NTRS)

Lee, M. C.

1985-01-01

Acoustic and electromagnetic fields applied. In contactless processing apparatus, acoustic and electromagnetic levitating fields employed alternately or simultaneously with amplitude of each controlled to produce various combinations of heating, cooling, and levitation. Apparatus provides rapid heating and cooling or slow heating and cooling for such processes as nucleation, crystallization, incubation, deep undercooling, and heterogeneity control.

Interdisciplinary Expansion of Conceptual Foundations: Insights from beyond Our Field

ERIC Educational Resources Information Center

Ambrose, Don

2005-01-01

The field of gifted education is very complex, covering broad and deep conceptual terrain. Insights about giftedness and talent are available from diverse academic disciplines and at multiple levels of analysis. These levels are captured in an interpretive framework that moves from the macrolevels of broad sociopolitical, cultural, and economic…

Development of improved space sampling strategies for ocean chemical properties: Total carbon dioxide and dissolved nitrate

NASA Technical Reports Server (NTRS)

Goyet, Catherine; Davis, Daniel; Peltzer, Edward T.; Brewer, Peter G.

1995-01-01

Large-scale ocean observing programs such as the Joint Global Ocean Flux Study (JGOFS) and the World Ocean Circulation Experiment (WOCE) today, must face the problem of designing an adequate sampling strategy. For ocean chemical variables, the goals and observing technologies are quite different from ocean physical variables (temperature, salinity, pressure). We have recently acquired data on the ocean CO2 properties on WOCE cruises P16c and P17c that are sufficiently dense to test for sampling redundancy. We use linear and quadratic interpolation methods on the sampled field to investigate what is the minimum number of samples required to define the deep ocean total inorganic carbon (TCO2) field within the limits of experimental accuracy (+/- 4 micromol/kg). Within the limits of current measurements, these lines were oversampled in the deep ocean. Should the precision of the measurement be improved, then a denser sampling pattern may be desirable in the future. This approach rationalizes the efficient use of resources for field work and for estimating gridded (TCO2) fields needed to constrain geochemical models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardin, Ernest; Su, Jiann-Cherng; Peretz, Fred

The primary purpose of the preclosure radiological safety assessment (that this document supports) is to identify risk factors for disposal operations, to aid in design for the deep borehole field test (DBFT) engineering demonstration.

Efficacy of enzymatic debridement of deeply burned hands.

PubMed

Krieger, Yuval; Bogdanov-Berezovsky, Alexander; Gurfinkel, Reuven; Silberstein, Eldad; Sagi, Amiram; Rosenberg, Lior

2012-02-01

The burned hand is a common and difficult to care-for entity in the field of burns. Due to the anatomy of the hand (important and delicate structures crowded in a small limited space without sub-dermal soft tissue), surgical debridement of the burned tissue is technically difficult and may cause considerable complications and, therefore, should be performed judiciously. Selective enzymatic debridement of the burn wound can preserve the spontaneous epithelialisation potential and reduce the added injury to the traumatised tissue added by a surgical debridement. The aim of the study was to assess the implication of a selective enzymatic compound (Debrase(®) - Ds) in the special field of deep hand burns, by comparing the actual burn area that required surgical coverage after enzymatic debridement to the burn area clinically judged to require skin grafting prior to debridement. This was a retrospective data collection and analysis from 154 complete files of prospective, open-label study in 275 hospitalised, Ds-treated burn patients. A total of 69 hand burns diagnosed as 'deep' was analysed; 36% of the wounds required surgical intervention after enzymatic debridement; 28.6% of the total burned area estimated initially as deep was covered by skin graft (statistically significant p<0.001). Debridement of deep-hand burns with a selective enzymatic agent decreased the perceived full-thickness wound area and skin-graft use. Copyright © 2011 Elsevier Ltd and ISBI. All rights reserved.

Comprehensive database of wellbore temperatures and drilling mud weight pressures by depth for Judge Digby field, Louisiana

USGS Publications Warehouse

Burke, Lauri

2010-01-01

This document serves as the repository for the unprocessed data used in the investigation of temperature and overpressure relations within the deep Tuscaloosa Formation in Judge Digby field. It is a compilation of all the publicly accessible wellbore temperature and pressure data for Judge Digby field, a prolific natural gas field producing from the Upper Cretaceous lower part of the Tuscaloosa Formation in the Gulf Coast region. This natural gas field is in Pointe Coupee Parish in the southern part of onshore Louisiana.

A search for Vega-like fields in OB stars

NASA Astrophysics Data System (ADS)

Neiner, C.; Folsom, C. P.; Blazere, A.

2014-12-01

Very weak magnetic fields (with a longitudinal component below 1 Gauss) have recently been discovered in the A star Vega as well as in a few Am stars. According to fossil field scenarios, such weak fields should also exist in more massive stars. In the framework of the ANR project Imagine, we have started to investigate the existence of this new class of very weakly magnetic stars among O and B stars thanks to ultra-deep spectropolarimetric observations. The first results and future plans are presented.

MAVEN-Measured Meteoritic Ions on Mars - Tracers of Lower Ionosphere Processes With and Without Analogues On Earth

NASA Astrophysics Data System (ADS)

Benna, M.; Grebowsky, J. M.; Collinson, G.; Plane, J. M. C.; Mitchell, D.; Srivastava, N.

2017-12-01

MAVEN observations of meteoritic metal ion populations during "deep dip" campaigns at Mars have revealed unique non-Earth like behavior that are not yet understood. These deep dip campaigns (6 so far) consisted each of more than a score of repeated orbits through the Martian molecular-ion-dominated lower ionosphere, whose terrestrial parallel (Earth's E-region) has been rather sparcely surveyed in situ by sounding rockets. In regions of weak Mars magnetic fields, MAVEN found ordered exponentially decreasing metal ion concentrations above the altitude of peak meteor ablation. Such an ordered trend has never been observed on Earth. Isolated anomalous high-altitude layers in the metal ion are also encountered, typically on deep dip campaigns in the southern hemisphere where large localized surface remanent magnetic fields prevail. The source of these anomalous layers is not yet evident, although the occurrences of some high-altitude metal ion enhancements were in regions with measured perturbed magnetic fields, indicative of localized electrical currents. Further investigation shows that those currents are also sometimes associated with superthermal/energetic electron bursts offering evidence that that impact ionization of neutral metal populations persisting at high altitudes are the source of metal ion enhancement - a rather difficult assumption to accept far above the ablation region where the metal neutrals are deposited. The relationship of the anomalous layers to the coincident electron populations as well as to the orientation of the magnetic fields which can play a role in the neutral wind generated ion convergences as on Earth is investigated.

The Simulation of Temperature Field Based on 3D Modeling and Its Comparison versus Measured Temperature Distribution of Daqing Oilfield, NE China

NASA Astrophysics Data System (ADS)

Shi, Y.; Jiang, G.; Hu, S.

2017-12-01

Daqing, as the largest oil field of China with more than 50 years of exploration and production history for oil and gas, its geothermal energy utilization was started in 2000, with a main focus on district heating and direct use. In our ongoing study, data from multiple sources are collected, including BHT, DST, steady state temperature measurements in deep wells and thermophysical properties of formations. Based on these measurements, an elaborate investigation of the temperature field of Daqing Oilfield is made. Moreover, through exploration for oil and gas, subsurface geometry, depth, thickness and properties of the stratigraphic layers have been extensively delineated by well logs and seismic profiles. A 3D model of the study area is developed incorporating the information of structure, stratigraphy, basal heat flow, and petrophysical and thermophysical properties of strata. Based on the model, a simulation of the temperature field of Daqing Oilfield is generated. A purely conductive regime is presumed, as demonstrated by measured temperature log in deep wells. Wells W1, W2 and SK2 are used as key wells for model calibration. Among them, SK2, as part of the International Continental Deep Drilling Program, has a designed depth of 6400m, the steady state temperature measurement in the borehole has reached the depth of 4000m. The results of temperature distribution generated from simulation and investigation are compared, in order to evaluate the potential of applying the method to other sedimentary basins with limited borehole temperature measurements but available structural, stratigraphic and thermal regime information.

Optical Spectroscopy of Distant Red Galaxies

NASA Astrophysics Data System (ADS)

Wuyts, Stijn; van Dokkum, Pieter G.; Franx, Marijn; Förster Schreiber, Natascha M.; Illingworth, Garth D.; Labbé, Ivo; Rudnick, Gregory

2009-11-01

We present optical spectroscopic follow-up of a sample of distant red galaxies (DRGs) with K tot s,Vega < 22.5, selected by (J - K)Vega>2.3, in the Hubble Deep Field South (HDFS), the MS 1054-03 field, and the Chandra Deep Field South (CDFS). Spectroscopic redshifts were obtained for 15 DRGs. Only two out of 15 DRGs are located at z < 2, suggesting a high efficiency to select high-redshift sources. From other spectroscopic surveys in the CDFS targeting intermediate to high-redshift populations selected with different criteria, we find spectroscopic redshifts for a further 30 DRGs. We use the sample of spectroscopically confirmed DRGs to establish the high quality (scatter in Δz/(1 + z) of ~0.05) of their photometric redshifts in the considered deep fields, as derived with EAZY. Combining the spectroscopic and photometric redshifts, we find that 74% of DRGs with K tot s,Vega < 22.5 lie at z>2. The combined spectroscopic and photometric sample is used to analyze the distinct intrinsic and observed properties of DRGs at z < 2 and z>2. In our photometric sample to K tot s,Vega < 22.5, low-redshift DRGs are brighter in Ks than high-redshift DRGs by 0.7 mag, and more extincted by 1.2 mag in AV . Our analysis shows that the DRG criterion selects galaxies with different properties at different redshifts. Such biases can be largely avoided by selecting galaxies based on their rest-frame properties, which requires very good multi-band photometry and high quality photometric redshifts.

Deep Learning: A Primer for Radiologists.

PubMed

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

Using deep learning in image hyper spectral segmentation, classification, and detection

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Su, Zhenyu

2018-02-01

Recent years have shown that deep learning neural networks are a valuable tool in the field of computer vision. Deep learning method can be used in applications like remote sensing such as Land cover Classification, Detection of Vehicle in Satellite Images, Hyper spectral Image classification. This paper addresses the use of the deep learning artificial neural network in Satellite image segmentation. Image segmentation plays an important role in image processing. The hue of the remote sensing image often has a large hue difference, which will result in the poor display of the images in the VR environment. Image segmentation is a pre processing technique applied to the original images and splits the image into many parts which have different hue to unify the color. Several computational models based on supervised, unsupervised, parametric, probabilistic region based image segmentation techniques have been proposed. Recently, one of the machine learning technique known as, deep learning with convolution neural network has been widely used for development of efficient and automatic image segmentation models. In this paper, we focus on study of deep neural convolution network and its variants for automatic image segmentation rather than traditional image segmentation strategies.

DeepVel: Deep learning for the estimation of horizontal velocities at the solar surface

NASA Astrophysics Data System (ADS)

Asensio Ramos, A.; Requerey, I. S.; Vitas, N.

2017-07-01

Many phenomena taking place in the solar photosphere are controlled by plasma motions. Although the line-of-sight component of the velocity can be estimated using the Doppler effect, we do not have direct spectroscopic access to the components that are perpendicular to the line of sight. These components are typically estimated using methods based on local correlation tracking. We have designed DeepVel, an end-to-end deep neural network that produces an estimation of the velocity at every single pixel, every time step, and at three different heights in the atmosphere from just two consecutive continuum images. We confront DeepVel with local correlation tracking, pointing out that they give very similar results in the time and spatially averaged cases. We use the network to study the evolution in height of the horizontal velocity field in fragmenting granules, supporting the buoyancy-braking mechanism for the formation of integranular lanes in these granules. We also show that DeepVel can capture very small vortices, so that we can potentially expand the scaling cascade of vortices to very small sizes and durations. The movie attached to Fig. 3 is available at http://www.aanda.org

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Investigation of holder pressure and size effects in micro deep drawing of rectangular work pieces driven by piezoelectric actuator.

PubMed

Aminzahed, Iman; Mashhadi, Mahmoud Mosavi; Sereshk, Mohammad Reza Vaziri

2017-02-01

Micro forming is a manufacturing process to fabricate micro parts with high quality and a cost effective manner. Deep drawing could be a favorable method for production of complicated parts in macro and micro sizes. In this paper piezoelectric actuator is used as a novel approach in the field of micro manufacturing. Also, in current work, investigations are conducted with four rectangular punches and blanks with various thicknesses. Blank holder pressure effects on thickness distributions, punch force, and springback are studied. According to the results of this work, increasing of blank holder pressure in scaled deep drawing, in contrast to thickness of drawn part, leads to decrease in the punch forces and springback. Furthermore, it is shown that in micro deep drawing, the effects of holder pressure on mentioned parameters can be ignored. Copyright © 2016 Elsevier B.V. All rights reserved.

Numerical Analysis on Seepage in the deep overburden CFRD

NASA Astrophysics Data System (ADS)

Zeyu, GUO; Junrui, CHAI; Yuan, QIN

2017-12-01

There are many problems in the construction of hydraulic structures on deep overburden because of its complex foundation structure and poor geological condition. Seepage failure is one of the main problems. The Combination of the seepage control system of the face rockfill dam and the deep overburden can effectively control the seepage of construction of the concrete face rockfill dam on the deep overburden. Widely used anti-seepage measures are horizontal blanket, waterproof wall, curtain grouting and so on, but the method, technique and its effect of seepage control still have many problems thus need further study. Due to the above considerations, Three-dimensional seepage field numerical analysis based on practical engineering case is conducted to study the seepage prevention effect under different seepage prevention methods, which is of great significance to the development of dam technology and the development of hydropower resources in China.

Biofilm development in a hotspot of mixing between shallow and deep groundwater in a fractured aquifer: field evidence from joint flow, chemical and microbiological characterization

NASA Astrophysics Data System (ADS)

Bochet, Olivier; Le Borgne, Tanguy; Pédrot, Mathieu; Labasque, Thierry; Lavenant, Nicolas; Petton, Christophe; Dufresne, Alexis; Ben Maamar, Sarah; Chatton, Eliot; De la Bernardie, Jérôme; Aquilina, Luc

2015-04-01

Biofilm development in a hotspot of mixing between shallow and deep groundwater in a fractured aquifer: field evidence from joint flow, chemical and microbiological characterization Olivier Bochet1, Tanguy Le Borgne1, Mathieu Pédrot1, Thierry Labasque1, Nicolas Lavenant1, Christophe Petton1, Alexis Dufresne2,Sarah Ben Maamar1-2, Eliot Chatton1, Jérôme de la Bernardie1, Luc Aquilina1 1: Géosciences Rennes, CNRS UMR 6118, Université de Rennes 1, Campus de Beaulieu bât 14B, Rennes, France 2: Ecobio, CNRS UMR 6553, Université de Rennes 1, Campus de Beaulieu, bât 14, Rennes, France Biofilms play a major role in controlling the fluxes and reactivity of chemical species transported in hydrological systems. Their development can have either positive impacts on groundwater quality (e.g. attenuation of contaminants under natural or stimulated conditions), or possible negative effects on subsurface operations (e.g. bio-clogging of geothermal dipoles or artificial recharge systems). Micro-organisms require both electron donors and electron acceptors for cellular growth, proliferation and maintenance of their metabolic functions. The mechanisms controlling these reactions derive from the interactions occurring at the micro-scale that depend on mineral compositions, the biota of subsurface environment, but also fluid mixing, which determines the local concentrations of nutriments, electron donors and electron acceptors. Hence, mixing zones between oxygen and nutriment rich shallow groundwater and mineralized deep groundwater are often considered as potential hotspots of microbial activity, although relatively few field data document flow distributions, transport properties, chemical gradients and micro-organisms distributions across these mixing interfaces. Here we investigate the origin of a localized biofilm development observed in the fractured granite aquifer at the Ploemeur observatory (H+ network hplus.ore.fr).This biofilm composed of ferro-oxidizing bacteria is observed in an 130m deep artesian well. Borehole video logs show an important colonization of the well by the biofilm in the shallower part (0 to 60m), while it is inexistent in the deeper part (60 to 130m). As flow is localized in a few deep and shallow fractures, we presume that the spatial distribution of biofilm is controlled by mixing between shallow and deep groundwater. To verify this hypothesis we conducted a field campaign with joint characterization of the flow and chemical composition of water flowing from the different fractures, as well as the microbiological composition of the biofilm at different depth, using pyrosequencing techniques. We will discuss in this presentation the results of this interdisciplinary dataset and their implications for the occurrence of hotspots of microbiological activity in the subsurface.

My Most Memorable AAS Meeting, or How Stephen Hawking's Chauffeur and Chubby Wise's Fiddle Are Related to the Hubble Deep Field (At Least In My Mind and Experience!)

NASA Astrophysics Data System (ADS)

Lucas, R. A.

1999-05-01

Sometimes, in the most extraordinary conditions and times, strange things happen which remind us of just how small a world we really inhabit, and how so many varied things may suddenly be juxtaposed in our lives, and in the lives of others. My most memorable AAS meeting involves not only the meeting but events while getting there. It was January 1996, and we had just finished our observations and initial data reduction of the Hubble Deep Field, the members of the HDF working group doggedly coming in to the STScI by various means over the December holidays and the New Year, in the midst of several blizzards which even closed STScI for a number of days. Not surprisingly, work on the HDF AAS presentations was ongoing until the last minute, until people left snowy Baltimore for sunny San Antonio. My street was plowed for the first time in a week a few hours before my 6AM flight, so after digging out my car, with no time for sleep, between 3AM and 6AM on the morning I left, I soon discovered my own surprising connections between Stephen Hawking's chauffeur, Chubby Wise's fiddle, and the Hubble Deep Field. I'll elaborate in this paper if you're curious!

A Brief Review of Facial Emotion Recognition Based on Visual Information.

PubMed

Ko, Byoung Chul

2018-01-30

Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling "end-to-end" learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work.

A Brief Review of Facial Emotion Recognition Based on Visual Information

PubMed Central

2018-01-01

Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling “end-to-end” learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work. PMID:29385749

Comparative Analysis of Microbial Communities in Iron-Dominated Flocculent Mats in Deep-Sea Hydrothermal Environments

PubMed Central

Kikuchi, Sakiko; Mitsunobu, Satoshi; Takaki, Yoshihiro; Yamanaka, Toshiro; Toki, Tomohiro; Noguchi, Takuroh; Nakamura, Kentaro; Abe, Mariko; Hirai, Miho; Yamamoto, Masahiro; Uematsu, Katsuyuki; Miyazaki, Junichi; Nunoura, Takuro; Takahashi, Yoshio; Takai, Ken

2016-01-01

ABSTRACT It has been suggested that iron is one of the most important energy sources for photosynthesis-independent microbial ecosystems in the ocean crust. Iron-metabolizing chemolithoautotrophs play a key role as primary producers, but little is known about their distribution and diversity and their ecological role as submarine iron-metabolizing chemolithotrophs, particularly the iron oxidizers. In this study, we investigated the microbial communities in several iron-dominated flocculent mats found in deep-sea hydrothermal fields in the Mariana Volcanic Arc and Trough and the Okinawa Trough by culture-independent molecular techniques and X-ray mineralogical analyses. The abundance and composition of the 16S rRNA gene phylotypes demonstrated the ubiquity of zetaproteobacterial phylotypes in iron-dominated mat communities affected by hydrothermal fluid input. Electron microscopy with energy-dispersive X-ray microanalysis and X-ray absorption fine structure (XAFS) analysis revealed the chemical and mineralogical signatures of biogenic Fe-(oxy)hydroxide species and the potential contribution of Zetaproteobacteria to the in situ generation. These results suggest that putative iron-oxidizing chemolithoautotrophs play a significant ecological role in producing iron-dominated flocculent mats and that they are important for iron and carbon cycles in deep-sea low-temperature hydrothermal environments. IMPORTANCE We report novel aspects of microbiology from iron-dominated flocculent mats in various deep-sea environments. In this study, we examined the relationship between Zetaproteobacteria and iron oxides across several hydrothermally influenced sites in the deep sea. We analyzed iron-dominated mats using culture-independent molecular techniques and X-ray mineralogical analyses. The scanning electron microscopy–energy-dispersive X-ray spectroscopy SEM-EDS analysis and X-ray absorption fine structure (XAFS) analysis revealed chemical and mineralogical signatures of biogenic Fe-(oxy)hydroxide species as well as the potential contribution of the zetaproteobacterial population to the in situ production. These key findings provide important information for understanding the mechanisms of both geomicrobiological iron cycling and the formation of iron-dominated mats in deep-sea hydrothermal fields. PMID:27422841

Spatial-heterodyne sampling requirements in the off-axis pupil plane recording geometry for deep-turbulence wavefront sensing

NASA Astrophysics Data System (ADS)

Banet, Matthias T.; Spencer, Mark F.

2017-09-01

Spatial-heterodyne interferometry is a robust solution for deep-turbulence wavefront sensing. With that said, this paper analyzes the focal-plane array sampling requirements for spatial-heterodyne systems operating in the off-axis pupil plane recording geometry. To assess spatial-heterodyne performance, we use a metric referred to as the field-estimated Strehl ratio. We first develop an analytical description of performance with respect to the number of focal-plane array pixels across the Fried coherence diameter and then verify our results with wave-optics simulations. The analysis indicates that at approximately 5 focal-plane array pixels across the Fried coherence diameter, the field-estimated Strehl ratios begin to exceed 0:9 which is indicative of largely diffraction-limited results.

Rotation-induced grain growth and stagnation in phase-field crystal models.

PubMed

Bjerre, Mathias; Tarp, Jens M; Angheluta, Luiza; Mathiesen, Joachim

2013-08-01

We consider grain growth and stagnation in polycrystalline microstructures. From the phase-field crystal modeling of the coarsening dynamics, we identify a transition from a grain-growth stagnation upon deep quenching below the melting temperature T(m) to a continuous coarsening at shallower quenching near T(m). The grain evolution is mediated by local grain rotations. In the deep quenching regime, the grain assembly typically reaches a metastable state where the kinetic barrier for recrystallization across boundaries is too large and grain rotation with subsequent coalescence or boundary motion is infeasible. For quenching near T(m), we find that the grain growth depends on the average rate of grain rotation, and follows a power-law behavior with time, with a scaling exponent that depends on the quenching depth.

A Chandra Survey of high-redshift (0.7 < z < 0.8) clusters selected in the 100 deg^2 SPT-Pol Deep Field

NASA Astrophysics Data System (ADS)

Garmire, Gordon

2016-09-01

We propose to observe a complete sample of 10 galaxy clusters at 1e14 < M500 < 5e14 and 0.7 < z < 0.8. These systems were selected from the 100 deg^2 deep field of the SPT-Pol SZ survey. This survey are has significant complementary data, including uniform depth ATCA, Herschel, Spitzer, and DES imaging, enabling a wide variety of astrophysical and cosmological studies. This sample complements the successful SPT-XVP survey, which has a broad redshift range and a narrow mass range, by including clusters over a narrow redshift range and broad mass range. These systems are such low mass and high redshift that they will not be detected in the eRosita all-sky survey.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holcomb, R.T.; Moore, J.G.; Lipman, P.W.

The GLORIA long-range sonar imaging system has revealed fields of large lava flows in the Hawaiian Trough east and south of Hawaii in water as deep as 5.5 km. Flows in the most extensive field (110 km long) have erupted from the deep submarine segment of Kilauea's east rift zone. Other flows have been erupted from Loihi and Mauna Loa. This discovery confirms a suspicion, long held from subaerial studies, that voluminous submarine flows are erupted from Hawaiian volcanoes, and it supports an inference that summit calderas repeatedly collapse and fill at intervals of centuries to millenia owing to voluminousmore » eruptions. These extensive flows differ greatly in form from pillow lavas found previously along shallower segments of the rift zones; therefore, revision of concepts of volcano stratigraphy and structure may be required.« less

Field Test to Evaluate Deep Borehole Disposal.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardin, Ernest; Brady, Patrick Vane.; Clark, Andrew Jordan

The U.S. Department of Energy (DOE) has embarked on the Deep Borehole Field Test (DBFT), which will investigate whether conditions suitable for disposal of radioactive waste can be found at a depth of up to 5 km in the earth’s crust. As planned, the DBFT will demonstrate drilling and construction of two boreholes, one for initial scientific characterization, and the other at a larger diameter such as could be appropriate for waste disposal (the DBFT will not involve radioactive waste). A wide range of geoscience activities is planned for the Characterization Borehole, and an engineering demonstration of test package emplacementmore » and retrieval is planned for the larger Field Test Borehole. Characterization activities will focus on measurements and samples that are important for evaluating the long-term isolation capability of the Deep Borehole Disposal (DBD) concept. Engineering demonstration activities will focus on providing data to evaluate the concept’s operational safety and practicality. Procurement of a scientifically acceptable DBFT site and a site management contractor is now underway. The concept of deep borehole disposal (DBD) for radioactive wastes is not new. It was considered by the National Academy of Science (NAS 1957) for liquid waste, studied in the 1980’s in the U.S. (Woodward–Clyde 1983), and has been evaluated by European waste disposal R&D programs in the past few decades (for example, Grundfelt and Crawford 2014; Grundfelt 2010). Deep injection of wastewater including hazardous wastes is ongoing in the U.S. and regulated by the Environmental Protection Agency (EPA 2001). The DBFT is being conducted with a view to use the DBD concept for future disposal of smaller-quantity, DOE-managed wastes from nuclear weapons production (i.e., Cs/Sr capsules and granular solid wastes). However, the concept may also have broader applicability for nations that have a need to dispose of limited amounts of spent fuel from nuclear power reactors. For such nations the cost for disposing of volumetrically limited waste streams could be lower than mined geologic repositories.« less

Charge Diffusion Variations in Pan-STARRS1 CCDs

NASA Astrophysics Data System (ADS)

Magnier, Eugene A.; Tonry, J. L.; Finkbeiner, D.; Schlafly, E.; Burgett, W. S.; Chambers, K. C.; Flewelling, H. A.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Metcalfe, N.; Wainscoat, R. J.; Waters, C. Z.

2018-06-01

Thick back-illuminated deep-depletion CCDs have superior quantum efficiency over previous generations of thinned and traditional thick CCDs. As a result, they are being used for wide-field imaging cameras in several major projects. We use observations from the Pan-STARRS 3π survey to characterize the behavior of the deep-depletion devices used in the Pan-STARRS 1 Gigapixel Camera. We have identified systematic spatial variations in the photometric measurements and stellar profiles that are similar in pattern to the so-called “tree rings” identified in devices used by other wide-field cameras (e.g., DECam and Hypersuprime Camera). The tree-ring features identified in these other cameras result from lateral electric fields that displace the electrons as they are transported in the silicon to the pixel location. In contrast, we show that the photometric and morphological modifications observed in the GPC1 detectors are caused by variations in the vertical charge transportation rate and resulting charge diffusion variations.

A connection to deep groundwater alters ecosystem carbon fluxes and budgets: Example from a Costa Rican rainforest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Genereux, David P.; Nagy, Laura A.; Osburn, Christopher L.

Field studies of watershed carbon fluxes and budgets are critical for understanding the carbon cycle, but the role of deep regional groundwater is poorly known and field examples are lacking. Here we show that discharge of regional groundwater into a lowland Costa Rican rainforest has a major influence on ecosystem carbon fluxes. Furthermore, this influence is observable through chemical, isotopic, and flux signals in groundwater, surface water, and air. Not addressing the influence of regional groundwater in the field measurement program and data analysis would give a misleading impression of the overall carbon source or sink status of the rainforest.more » In quantifying a carbon budget with the traditional "small watershed" mass-balance approach, it would be critical at this site and likely many others to consider watershed inputs or losses associated with exchange between the ecosystem and the deeper hydrogeological system on which it sits.« less

Electro-Quasistatic Simulations in Bio-Systems Engineering and Medical Engineering

NASA Astrophysics Data System (ADS)

van Rienen, U.; Flehr, J.; Schreiber, U.; Schulze, S.; Gimsa, U.; Baumann, W.; Weiss, D. G.; Gimsa, J.; Benecke, R.; Pau, H.-W.

2005-05-01

Slowly varying electromagnetic fields play a key role in various applications in bio-systems and medical engineering. Examples are the electric activity of neurons on neurochips used as biosensors, the stimulating electric fields of implanted electrodes used for deep brain stimulation in patients with Morbus Parkinson and the stimulation of the auditory nerves in deaf patients, respectively. In order to simulate the neuronal activity on a chip it is necessary to couple Maxwell's and Hodgkin-Huxley's equations. First numerical results for a neuron coupling to a single electrode are presented. They show a promising qualitative agreement with the experimentally recorded signals. Further, simulations are presented on electrodes for deep brain stimulation in animal experiments where the question of electrode ageing and energy deposition in the surrounding tissue are of major interest. As a last example, electric simulations for a simple cochlea model are presented comparing the field in the skull bones for different electrode types and stimulations in different positions.

A connection to deep groundwater alters ecosystem carbon fluxes and budgets: Example from a Costa Rican rainforest

DOE PAGES

Genereux, David P.; Nagy, Laura A.; Osburn, Christopher L.; ...

2013-05-28

Field studies of watershed carbon fluxes and budgets are critical for understanding the carbon cycle, but the role of deep regional groundwater is poorly known and field examples are lacking. Here we show that discharge of regional groundwater into a lowland Costa Rican rainforest has a major influence on ecosystem carbon fluxes. Furthermore, this influence is observable through chemical, isotopic, and flux signals in groundwater, surface water, and air. Not addressing the influence of regional groundwater in the field measurement program and data analysis would give a misleading impression of the overall carbon source or sink status of the rainforest.more » In quantifying a carbon budget with the traditional "small watershed" mass-balance approach, it would be critical at this site and likely many others to consider watershed inputs or losses associated with exchange between the ecosystem and the deeper hydrogeological system on which it sits.« less

Selecting AGN through Variability in SN Datasets

NASA Astrophysics Data System (ADS)

Boutsia, K.; Leibundgut, B.; Trevese, D.; Vagnetti, F.

2010-07-01

Variability is a main property of Active Galactic Nuclei (AGN) and it was adopted as a selection criterion using multi epoch surveys conducted for the detection of supernovae (SNe). We have used two SN datasets. First we selected the AXAF field of the STRESS project, centered in the Chandra Deep Field South where, besides the deep X-ray surveys also various optical catalogs exist. Our method yielded 132 variable AGN candidates. We then extended our method including the dataset of the ESSENCE project that has been active for 6 years, producing high quality light curves in the R and I bands. We obtained a sample of ˜4800 variable sources, down to R=22, in the whole 12 deg2 ESSENCE field. Among them, a subsample of ˜500 high priority AGN candidates was created using as secondary criterion the shape of the structure function. In a pilot spectroscopic run we have confirmed the AGN nature for nearly all of our candidates.

Near-field hazard assessment of March 11, 2011 Japan Tsunami sources inferred from different methods

USGS Publications Warehouse

Wei, Y.; Titov, V.V.; Newman, A.; Hayes, G.; Tang, L.; Chamberlin, C.

2011-01-01

Tsunami source is the origin of the subsequent transoceanic water waves, and thus the most critical component in modern tsunami forecast methodology. Although impractical to be quantified directly, a tsunami source can be estimated by different methods based on a variety of measurements provided by deep-ocean tsunameters, seismometers, GPS, and other advanced instruments, some in real time, some in post real-time. Here we assess these different sources of the devastating March 11, 2011 Japan tsunami by model-data comparison for generation, propagation and inundation in the near field of Japan. This study provides a comparative study to further understand the advantages and shortcomings of different methods that may be potentially used in real-time warning and forecast of tsunami hazards, especially in the near field. The model study also highlights the critical role of deep-ocean tsunami measurements for high-quality tsunami forecast, and its combination with land GPS measurements may lead to better understanding of both the earthquake mechanisms and tsunami generation process. ?? 2011 MTS.

Development of the Vertical Electro Magnetic Profiling (VEMP) method

NASA Astrophysics Data System (ADS)

Miura, Yasuo; Osato, Kazumi; Takasugi, Shinji; Muraoka, Hirofumi; Yasukawa, Kasumi

1996-09-01

As a part of the "Deep-Seated Geothermal Resources Survey (DSGR)" project being undertaken by the New Energy and Industrial Technology Development Organization (NEDO), the "Vertical Electro Magnetic Profiling (VEMP)" method is being developed to accurately obtain deep resistivity structures. The VEMP method takes multi-frequency three-component magnetic field data in an open hole well using controlled source transmitters emitted at the surface (either loop or grounded-wire sources). Numerical simulations using EM3D have demonstrated that phase data of the VEMP method is not only very sensitive to the general resistivity structure, but will also indicate the presence of deeper anomalies. Forward modelling was used to determine the required transmitter moments for various grounded-wire and loop sources for a field test using the WD-1 well in the Kakkonda geothermal area. VEMP logging of the WD-1 well was carried out in May 1994 and the processed field data matches the computer simulations quite well.

Simulation of double stage hall thruster with double-peaked magnetic field

NASA Astrophysics Data System (ADS)

Ding, Yongjie; Li, Peng; Sun, Hezhi; Wei, Liqiu; Xu, Yu; Peng, Wuji; Su, Hongbo; Li, Hong; Yu, Daren

2017-07-01

This study adopts double permanent magnetic rings and four permanent magnetic rings to form two symmetrical magnetic peaks and two asymmetrical magnetic peaks in the channel of a Hall thruster, and uses a 2D-3V PIC-MCC model to analyze the influence of magnetic strength on the discharge characteristic and performance of Hall thrusters with an intermediate electrode and double-peaked magnetic field. As opposed to the two symmetrical magnetic peaks formed by double permanent magnetic rings, increasing the magnetic peak value deep within the channel can cause propellant ionization to occur; with the increase in the magnetic peak deep in the channel, the propellant utilization, thrust, and anode efficiency of the thruster are significantly improved. Double-peaked magnetic field can realize separate control of ionization and acceleration in a Hall thruster, and provide technical means for further improving thruster performance. Contribution to the Topical Issue "Physics of Ion Beam Sources", edited by Holger Kersten and Horst Neumann.

Arctic geodynamics: Continental shelf and deep ocean geophysics. ERS-1 satellite altimetry: A first look

NASA Technical Reports Server (NTRS)

Anderson, Allen Joel; Sandwell, David T.; Marquart, Gabriele; Scherneck, Hans-Georg

1993-01-01

An overall review of the Arctic Geodynamics project is presented. A composite gravity field model of the region based upon altimetry data from ERS-1, Geosat, and Seasat is made. ERS-1 altimetry covers unique Arctic and Antarctic latitudes above 72 deg. Both areas contain large continental shelf areas, passive margins, as well as recently formed deep ocean areas. Until ERS-1 it was not possible to study these areas with satellite altimetry. Gravity field solutions for the Barents sea, portions of the Arctic ocean, and the Norwegian sea north of Iceland are shown. The gravity anomalies around Svalbard (Spitsbergen) and Bear island are particularly large, indicating large isostatic anomalies which remain from the recent breakup of Greenland from Scandinavian. Recently released gravity data from the Armed Forces Topographic Service of Russia cover a portion of the Barents and Kara seas. A comparison of this data with the ERS-1 produced gravity field is shown.

Deep neural networks to enable real-time multimessenger astrophysics

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-02-01

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

Video Documentaries in the Assessment of Human Geography Field Courses

ERIC Educational Resources Information Center

Mavroudi, Elizabeth; Jons, Heike

2011-01-01

This paper critically reviews the use of video documentaries in the assessment of human geography field courses. It aims to contribute to recent debates about the role of visual methods for developing active and deep learning in student-centred teaching. Based on four days of group work in Crete, 30 third-year students produced individual…

Chloride concentration gradients in tank-stored hydraulic fracturing fluids following flowback

Treesearch

Pamela J. Edwards; Linda L. Tracy; William K. Wilson

2011-01-01

A natural gas well in West Virginia was hydraulically fractured and the flowback was recovered and stored in an 18-foot-deep tank. Both in situ field test kit and laboratory measurements of electrical conductivity and chloride concentrations increased substantially with depth, although the laboratory measurements showed a greater increase. The field test kit also...

Summer Fallowinng Improves Survival and Growth of Cottonwood on Old Fields

Treesearch

James B. Baker; B. G. Blackmon

1973-01-01

Fallowing an old-field site during the summer prior to planting and applying a herbicide in September improved survival and growth of eastern cottonwood cuttings. Summer fallowing without applying herbicide also improved height growth of cottonwood through age 2. Deep plowing and cover cropping, alone or in combination, did not influence growth or survival during the...

Technology and the Deep Play of Intercultural Teacher Education: A Reflection on Two Seminal Writings of Clifford Geertz

ERIC Educational Resources Information Center

Ferdig, Richard E.; Dawson, Kara

2005-01-01

The selection of a seminal piece on intercultural issues in technology and teacher education was challenging. Researchers interested in the field come from numerous fields of study, including education, anthropology, sociology, psychology, economics, business, international relations, and communication. The two essays by Cliffort Gertz (1973a, b)…

Effect of deep injection on field-scale emissions of 1,3-dichloropropene and chloropicrin from bare soil

USDA-ARS?s Scientific Manuscript database

Fumigating soil is important for the production of many high-value vegetable, fruit, and tree crops, but fumigants are toxic and highly volatile which can lead to significant atmospheric emissions. A field experiment was conducted to measure emissions and subsurface diffusion of a mixture of 1,3-di...

LUMINOUS AND HIGH STELLAR MASS CANDIDATE GALAXIES AT z Almost-Equal-To 8 DISCOVERED IN THE COSMIC ASSEMBLY NEAR-INFRARED DEEP EXTRAGALACTIC LEGACY SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan Haojing; Finkelstein, Steven L.; Huang, Kuang-Han

One key goal of the Hubble Space Telescope Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey is to track galaxy evolution back to z Almost-Equal-To 8. Its two-tiered ''wide and deep'' strategy bridges significant gaps in existing near-infrared surveys. Here we report on z Almost-Equal-To 8 galaxy candidates selected as F105W-band dropouts in one of its deep fields, which covers 50.1 arcmin{sup 2} to 4 ks depth in each of three near-infrared bands in the Great Observatories Origins Deep Survey southern field. Two of our candidates have J < 26.2 mag, and are >1 mag brighter than any previously known F105W-dropouts.more » We derive constraints on the bright end of the rest-frame ultraviolet luminosity function of galaxies at z Almost-Equal-To 8, and show that the number density of such very bright objects is higher than expected from the previous Schechter luminosity function estimates at this redshift. Another two candidates are securely detected in Spitzer Infrared Array Camera images, which are the first such individual detections at z Almost-Equal-To 8. Their derived stellar masses are on the order of a few Multiplication-Sign 10{sup 9} M{sub Sun }, from which we obtain the first measurement of the high-mass end of the galaxy stellar mass function at z Almost-Equal-To 8. The high number density of very luminous and very massive galaxies at z Almost-Equal-To 8, if real, could imply a large stellar-to-halo mass ratio and an efficient conversion of baryons to stars at such an early time.« less

Deep Spitzer/IRAC Imaging of the Subaru Deep Field

NASA Astrophysics Data System (ADS)

Jiang, Linhua; Egami, Eiichi; Cohen, Seth; Fan, Xiaohui; Ly, Chun; Mechtley, Matthew; Windhorst, Rogier

2013-10-01

The last decade saw great progress in our understanding of the distant Universe as a number of objects at z > 6 were discovered. The Subaru Deep Field (SDF) project has played an important role on study of high-z galaxies. The SDF is unique: it covers a large area of 850 sq arcmin; it has extremely deep optical images in a series of broad and narrow bands; it has the largest sample of spectroscopically-confirmed galaxies known at z >= 6, including ~100 Lyman alpha emitters (LAEs) and ~50 Lyman break galaxies (LBGs). Here we propose to carry out deep IRAC imaging observations of the central 75% of the SDF. The proposed observations together with those from our previous Spitzer programs will reach a depth of ~10 hours, and enable the first complete census of physical properties and stellar populations of spectroscopically-confirmed galaxies at the end of cosmic reionization. IRAC data is the key to measure stellar masses and constrain stellar populations in high-z galaxies. From SED modeling with secure redshifts, we will characterize the physical properties of these galaxies, and trace their mass assembly and star formation history. In particular, it allows us, for the first time, to study stellar populations in a large sample of z >=6 LAEs. We will also address some critical questions, such as whether LAEs and LBGs represent physically different galaxy populations. All these will help us to understand the earliest galaxy formation and evolution, and better constrain the galaxy contribution to reionization. The IRAC data will also cover 10,000 emission-line selected galaxies at z < 1.5, 50,000 UV and mass selected LBGs at 1.5 < z < 3, and more than 5,000 LBGs at 3 < z < 6. It will have a legacy value for SDF-related programs.

Formation of ore minerals in metamorphic rocks of the German continental deep drilling site (KTB)

NASA Astrophysics Data System (ADS)

Kontny, A.; Friedrich, G.; Behr, H. J.; de Wall, H.; Horn, E. E.; Möller, P.; Zulauf, G.

1997-08-01

The German Continental Deep Drilling Program (KTB) drilled a 9.1 km deep profile through amphibolite facies metamorphic rocks and reached in situ temperatures of 265°C. Each lithologic unit is characterized by typical ore mineral assemblages related to the regional metamorphic conditions. Paragneisses contain pyrrhotite + rutile + ilmenite ± graphite, metabasic units bear ilmenite + rutile + pyrrhotite ± pyrite, and additionally, the so-called variegated units yield pyrrhotite + titanite assemblages. In the latter unit, magnetite + ilmenite + rutile + titanite assemblages related to the lower amphibolite facies breakdown of ilmenite-hematite solid solution also occur locally. Retrograde hydrothermal mineralization which commenced during Upper Carboniferous times is characterized by the following geochemical conditions: (1) low saline Na-K-Mg-Cl fluids with sulfur and oxygen fugacities at the pyrite-pyrrhotite buffer and temperatures of 400-500°C, (2) fluids with CO2, CH4±N2, andpH, Eh, sulfur, and oxygen fugacity in the stability field of graphite + pyrite at temperatures of 280-350° and (3) moderate to high saline Ca-Na-Cl fluids with CH4+ N2; sulfur and oxygen fugacity are in the stability field of pyrrhotite at temperatures <300°C. The latter environment is confirmed by in situ conditions found at the bottom of the deep drilling. Monoclinic, ferrimagnetic pyrrhotite is the main carrier of magnetization which disappears below about 8.6 km, corresponding to in situ temperatures of about 250°C. Below this depth, hexagonal antiferromagnetic pyrrhotite with a Curie temperature of 260°C is the stable phase. Temperature-dependent transformation of pyrrhotite and the reaching of its Curie isotherm within the Earth crust are one of the striking results of the KTB deep drilling project.

Quantify Lateral Dispersion and Turbulent Mixing by Spatial Array of chi-EM-APEX Floats

DTIC Science & Technology

2013-09-30

pattern), 18-hour background field on the R/V Oceanus. ii) 10 km, 4-hour butterfly following dye on R/V Endeavor. iii) Dye following to track the...analysis of drogue observations, Deep- Sea Research, 23, 349-352. PUBLICATIONS (wholly or in part supported by this grant) Sanford, T.B. (2013...Spatial Structure of Thermocline and Abyssal Internal Waves, Deep- Sea Res. Part II. 85, 195-209. [published, refereed] Szuts, Z.B. and T. B. Sanford

An Environmental Survey of Canton Atoll Lagoon, 1973

DTIC Science & Technology

1976-06-01

isolated /’e)ll~opora heads. Observation track perpendicular to shoreline. Numnerous sea 4 ~ urchins (L~Ivnomo’ra sp.) in surf zone. 200 m - ,-observation...narrowest and shallowest point Is approximately 150 m wide and 5 m deep. In his original field notes, E. H -. Bryan. Jr. I(notes at Whitney South Sea ...a height ot over 5 in1 above sea leyel. 1’ho turning basin wits cleared and the deep channel was prouhubly dredged front the lagoon side, Later, the

Finite difference time domain (FDTD) modeling of implanted deep brain stimulation electrodes and brain tissue.

PubMed

Gabran, S R I; Saad, J H; Salama, M M A; Mansour, R R

2009-01-01

This paper demonstrates the electromagnetic modeling and simulation of an implanted Medtronic deep brain stimulation (DBS) electrode using finite difference time domain (FDTD). The model is developed using Empire XCcel and represents the electrode surrounded with brain tissue assuming homogenous and isotropic medium. The model is created to study the parameters influencing the electric field distribution within the tissue in order to provide reference and benchmarking data for DBS and intra-cortical electrode development.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

RaptorX-Property: a web server for protein structure property prediction.

PubMed

Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo

2016-07-08

RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

DeepSurveyCam—A Deep Ocean Optical Mapping System

PubMed Central

Kwasnitschka, Tom; Köser, Kevin; Sticklus, Jan; Rothenbeck, Marcel; Weiß, Tim; Wenzlaff, Emanuel; Schoening, Timm; Triebe, Lars; Steinführer, Anja; Devey, Colin; Greinert, Jens

2016-01-01

Underwater photogrammetry and in particular systematic visual surveys of the deep sea are by far less developed than similar techniques on land or in space. The main challenges are the rough conditions with extremely high pressure, the accessibility of target areas (container and ship deployment of robust sensors, then diving for hours to the ocean floor), and the limitations of localization technologies (no GPS). The absence of natural light complicates energy budget considerations for deep diving flash-equipped drones. Refraction effects influence geometric image formation considerations with respect to field of view and focus, while attenuation and scattering degrade the radiometric image quality and limit the effective visibility. As an improvement on the stated issues, we present an AUV-based optical system intended for autonomous visual mapping of large areas of the seafloor (square kilometers) in up to 6000 m water depth. We compare it to existing systems and discuss tradeoffs such as resolution vs. mapped area and show results from a recent deployment with 90,000 mapped square meters of deep ocean floor. PMID:26828495

Deep learning for studies of galaxy morphology

NASA Astrophysics Data System (ADS)

Tuccillo, D.; Huertas-Company, M.; Decencière, E.; Velasco-Forero, S.

2017-06-01

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

Optimizing interplanetary trajectories with deep space maneuvers. M.S. Thesis

NASA Technical Reports Server (NTRS)

Navagh, John

1993-01-01

Analysis of interplanetary trajectories is a crucial area for both manned and unmanned missions of the Space Exploration Initiative. A deep space maneuver (DSM) can improve a trajectory in much the same way as a planetary swingby. However, instead of using a gravitational field to alter the trajectory, the on-board propulsion system of the spacecraft is used when the vehicle is not near a planet. The purpose is to develop an algorithm to determine where and when to use deep space maneuvers to reduce the cost of a trajectory. The approach taken to solve this problem uses primer vector theory in combination with a non-linear optimizing program to minimize Delta(V). A set of necessary conditions on the primer vector is shown to indicate whether a deep space maneuver will be beneficial. Deep space maneuvers are applied to a round trip mission to Mars to determine their effect on the launch opportunities. Other studies which were performed include cycler trajectories and Mars mission abort scenarios. It was found that the software developed was able to locate quickly DSM's which lower the total Delta(V) on these trajectories.

Optimizing interplanetary trajectories with deep space maneuvers

NASA Astrophysics Data System (ADS)

Navagh, John

1993-09-01

Analysis of interplanetary trajectories is a crucial area for both manned and unmanned missions of the Space Exploration Initiative. A deep space maneuver (DSM) can improve a trajectory in much the same way as a planetary swingby. However, instead of using a gravitational field to alter the trajectory, the on-board propulsion system of the spacecraft is used when the vehicle is not near a planet. The purpose is to develop an algorithm to determine where and when to use deep space maneuvers to reduce the cost of a trajectory. The approach taken to solve this problem uses primer vector theory in combination with a non-linear optimizing program to minimize Delta(V). A set of necessary conditions on the primer vector is shown to indicate whether a deep space maneuver will be beneficial. Deep space maneuvers are applied to a round trip mission to Mars to determine their effect on the launch opportunities. Other studies which were performed include cycler trajectories and Mars mission abort scenarios. It was found that the software developed was able to locate quickly DSM's which lower the total Delta(V) on these trajectories.

Deep features for efficient multi-biometric recognition with face and ear images

NASA Astrophysics Data System (ADS)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

Natural gas production and anomalous geothermal gradients of the deep Tuscaloosa Formation

USGS Publications Warehouse

Burke, Lauri

2011-01-01

For the largest producing natural gas fields in the onshore Gulf of Mexico Basin, the relation between temperature versus depth was investigated. Prolific natural gas reservoirs with the highest temperatures were found in the Upper Cretaceous downdip Tuscaloosa trend in Louisiana. Temperature and production trends from the deepest field, Judge Digby field, in Pointe Coupe Parish, Louisiana, were investigated to characterize the environment of natural gas in the downdip Tuscaloosa trend. The average production depth in the Judge Digby field is approximately 22,000 ft. Temperatures as high as 400 degrees F are typically found at depth in Judge Digby field and are anomalously low when compared to temperature trends extrapolated to similar depths regionally. At 22,000 ft, the minimum and maximum temperatures for all reservoirs in Gulf Coast producing gas fields are 330 and 550 degrees F, respectively; the average temperature is 430 degrees F. The relatively depressed geothermal gradients in the Judge Digby field may be due to high rates of sediment preservation, which may have delayed the thermal equilibration of the sediment package with respect to the surrounding rock. Analyzing burial history and thermal maturation indicates that the deep Tuscaloosa trend in the Judge Digby field is currently in the gas generation window. Using temperature trends as an exploration tool may have important implications for undiscovered hydrocarbons at greater depths in currently producing reservoirs, and for settings that are geologically analogous to the Judge Digby fiel

A hybrid deep learning approach to predict malignancy of breast lesions using mammograms

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Heidari, Morteza; Mirniaharikandehei, Seyedehnafiseh; Gong, Jing; Qian, Wei; Qiu, Yuchen; Zheng, Bin

2018-03-01

Applying deep learning technology to medical imaging informatics field has been recently attracting extensive research interest. However, the limited medical image dataset size often reduces performance and robustness of the deep learning based computer-aided detection and/or diagnosis (CAD) schemes. In attempt to address this technical challenge, this study aims to develop and evaluate a new hybrid deep learning based CAD approach to predict likelihood of a breast lesion detected on mammogram being malignant. In this approach, a deep Convolutional Neural Network (CNN) was firstly pre-trained using the ImageNet dataset and serve as a feature extractor. A pseudo-color Region of Interest (ROI) method was used to generate ROIs with RGB channels from the mammographic images as the input to the pre-trained deep network. The transferred CNN features from different layers of the CNN were then obtained and a linear support vector machine (SVM) was trained for the prediction task. By applying to a dataset involving 301 suspicious breast lesions and using a leave-one-case-out validation method, the areas under the ROC curves (AUC) = 0.762 and 0.792 using the traditional CAD scheme and the proposed deep learning based CAD scheme, respectively. An ensemble classifier that combines the classification scores generated by the two schemes yielded an improved AUC value of 0.813. The study results demonstrated feasibility and potentially improved performance of applying a new hybrid deep learning approach to develop CAD scheme using a relatively small dataset of medical images.

Deep hypothermia-enhanced autophagy protects PC12 cells against oxygen glucose deprivation via a mitochondrial pathway.

PubMed

Tang, Dang; Wang, Cheng; Gao, Yongjun; Pu, Jun; Long, Jiang; Xu, Wei

2016-10-06

Deep hypothermia is known for its organ-preservation properties, which is introduced into surgical operations on the brain and heart, providing both safety in stopping circulation as well as an attractive bloodless operative field. However, the molecular mechanisms have not been clearly identified. This study was undertaken to determine the influence of deep hypothermia on neural apoptosis and the potential mechanism of these effects in PC12 cells following oxygen-glucose deprivation. Deep hypothermia (18°C) was given to PC12 cells while the model of oxygen-glucose deprivation (OGD) induction for 1h. After 24h of reperfusion, the results showed that deep hypothermia decreased the neural apoptosis, and significantly suppressed overexpression of Bax, CytC, Caspase 3, Caspase 9 and cleaved PARP-1, and inhibited the reduction of Bcl-2 expression. While deep hypothermia increased the LC3II/LC3I and Beclin 1, an autophagy marker, which can be inhibited by 3-methyladenine (3-MA), indicating that deep hypothermia-enhanced autophagy ameliorated apoptotic cell death in PC12 cells subjected to OGD. Based on these findings we propose that deep hypothermia protects against neural apoptosis after the induction of OGD by attenuating the mitochondrial apoptosis pathway, moreover, the mechanism of these antiapoptosis effects is related to the enhancement of autophagy, which autophagy might provide a means of neuroprotection against OGD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Oceanic Impacts: A Growing Field of Fundamental Geoscience

NASA Technical Reports Server (NTRS)

Gersonde, Rainer; Deutsch, Alexander; Ivanov, Boris A.; Kyte, Frank T.

2002-01-01

The importance of oceanic impacts of collisional events and resulting energy release, are briefly described. Data collection methods from the Eltanin (a mesosiderite projectile) deep water impact, are presented.

Mega-precovery and data mining of near-Earth asteroids and other Solar System objects

NASA Astrophysics Data System (ADS)

Popescu, M.; Vaduvescu, O.; Char, F.; Curelaru, L.; Euronear Team

2014-07-01

The vast collection of CCD images and photographic plate archives available from the world-wide archives and telescopes is still insufficiently exploited. Within the EURONEAR project we designed two data mining software with the purpose to search very large collections of archives for images which serendipitously include known asteroids or comets in their field, with the main aims to extend the arc and improve the orbits. In this sense, ''Precovery'' (published in 2008, aiming to search all known NEAs in few archives via IMCCE's SkyBoT server) and ''Mega-Precovery'' (published in 2010, querying the IMCCE's Miriade server) were made available to the community via the EURONEAR website (euronear.imcce.fr). Briefly, Mega-Precovery aims to search one or a few known asteroids or comets in a mega-collection including millions of images from some of the largest observatory archives: ESO (15 instruments served by ESO Archive including VLT), NVO (8 instruments served by U.S. NVO Archive), CADC (11 instruments, including HST and Gemini), plus other important instrument archives: SDSS, CFHTLS, INT-WFC, Subaru-SuprimeCam and AAT-WFI, adding together 39 instruments and 4.3 million images (Mar 2014), and our Mega-Archive is growing. Here we present some of the most important results obtained with our data-mining software and some new planned search options of Mega-Precovery. Particularly, the following capabilities will be added soon: the ING archive (all imaging cameras) will be included and new search options will be made available (such as query by orbital elements and by observations) to be able to target new Solar System objects such as Virtual Impactors, bolides, planetary satellites, TNOs (besides the comets added recently). In order to better characterize the archives, we introduce the ''AOmegaA'' factor (archival etendue) proportional to the AOmega (etendue) and the number of images in an archive. With the aim to enlarge the Mega-Archive database, we invite the observatories (particularly those storing their images online and also those that own plate archives which could be scanned on request) to contact us in order to add their instrument archives (consisting of an ASCII file with telescope pointings in a simple format) to our Mega-Precovery open project. We intend for the future to synchronise our service with the Virtual Observatory.

AzTEC half square degree survey of the SHADES fields - I. Maps, catalogues and source counts

NASA Astrophysics Data System (ADS)

Austermann, J. E.; Dunlop, J. S.; Perera, T. A.; Scott, K. S.; Wilson, G. W.; Aretxaga, I.; Hughes, D. H.; Almaini, O.; Chapin, E. L.; Chapman, S. C.; Cirasuolo, M.; Clements, D. L.; Coppin, K. E. K.; Dunne, L.; Dye, S.; Eales, S. A.; Egami, E.; Farrah, D.; Ferrusca, D.; Flynn, S.; Haig, D.; Halpern, M.; Ibar, E.; Ivison, R. J.; van Kampen, E.; Kang, Y.; Kim, S.; Lacey, C.; Lowenthal, J. D.; Mauskopf, P. D.; McLure, R. J.; Mortier, A. M. J.; Negrello, M.; Oliver, S.; Peacock, J. A.; Pope, A.; Rawlings, S.; Rieke, G.; Roseboom, I.; Rowan-Robinson, M.; Scott, D.; Serjeant, S.; Smail, I.; Swinbank, A. M.; Stevens, J. A.; Velazquez, M.; Wagg, J.; Yun, M. S.

2010-01-01

We present the first results from the largest deep extragalactic mm-wavelength survey undertaken to date. These results are derived from maps covering over 0.7deg2, made at λ = 1.1mm, using the AzTEC continuum camera mounted on the James Clerk Maxwell Telescope. The maps were made in the two fields originally targeted at λ = 850μm with the Submillimetre Common-User Bolometer Array (SCUBA) in the SCUBA Half-Degree Extragalactic Survey (SHADES) project, namely the Lockman Hole East (mapped to a depth of 0.9-1.3 mJy rms) and the Subaru/XMM-Newton Deep Field (mapped to a depth of 1.0-1.7 mJy rms). The wealth of existing and forthcoming deep multifrequency data in these two fields will allow the bright mm source population revealed by these new wide-area 1.1mm images to be explored in detail in subsequent papers. Here, we present the maps themselves, a catalogue of 114 high-significance submillimetre galaxy detections, and a thorough statistical analysis leading to the most robust determination to date of the 1.1mm source number counts. These new maps, covering an area nearly three times greater than the SCUBA SHADES maps, currently provide the largest sample of cosmological volumes of the high-redshift Universe in the mm or sub-mm. Through careful comparison, we find that both the Cosmic Evolution Survey (COSMOS) and the Great Observatories Origins Deep Survey (GOODS) North fields, also imaged with AzTEC, contain an excess of mm sources over the new 1.1mm source-count baseline established here. In particular, our new AzTEC/SHADES results indicate that very luminous high-redshift dust enshrouded starbursts (S1.1mm > 3mJy) are 25-50 per cent less common than would have been inferred from these smaller surveys, thus highlighting the potential roles of cosmic variance and clustering in such measurements. We compare number count predictions from recent models of the evolving mm/sub-mm source population to these sub-mm bright galaxy surveys, which provide important constraints for the ongoing refinement of semi-analytic and hydrodynamical models of galaxy formation, and find that all available models overpredict the number of bright submillimetre galaxies found in this survey.

Subsurface microbial habitats on Mars

NASA Technical Reports Server (NTRS)

Boston, P. J.; Mckay, C. P.

1991-01-01

We developed scenarios for shallow and deep subsurface cryptic niches for microbial life on Mars. Such habitats could have considerably prolonged the persistence of life on Mars as surface conditions became increasingly inhospitable. The scenarios rely on geothermal hot spots existing below the near or deep subsurface of Mars. Recent advances in the comparatively new field of deep subsurface microbiology have revealed previously unsuspected rich aerobic and anaerobic microbal communities far below the surface of the Earth. Such habitats, protected from the grim surface conditions on Mars, could receive warmth from below and maintain water in its liquid state. In addition, geothermally or volcanically reduced gases percolating from below through a microbiologically active zone could provide the reducing power needed for a closed or semi-closed microbial ecosystem to thrive.

Environmental projects. Volume 7: Environmental resources document

NASA Technical Reports Server (NTRS)

Kushner, Len; Kroll, Glenn

1988-01-01

The Goldstone Deep Space Communications Complex (GDSCC) in Barstow, California, is part of the NASA Deep Space Network, one of the world's largest and most sensitive scientific telecommunications and radio navigation networks. Goldstone is managed, directed and operated by the Jet Propulsion Laboratory of Pasadena, California. The GDSCC includes five distinct operational sites: Echo, Venus, Mars, Apollo, and Mojave Base. Within each site is a Deep Space Station (DPS), consisting of a large dish antenna and its support facilities. As required by NASA directives concerning the implementation of the National Environmental Policy Act, each NASA field installation is to publish an Environmental Resources Document describing the current environment at the installation, including any adverse effects that NASA operations may have on the local environment.

Gas Classification Using Deep Convolutional Neural Networks.

PubMed

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-08

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

Gas Classification Using Deep Convolutional Neural Networks

PubMed Central

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-01

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

Correlation between low level fluctuations in the x ray background and faint galaxies

NASA Technical Reports Server (NTRS)

Tolstoy, Eline; Griffiths, R. E.

1993-01-01

A correlation between low-level x-ray fluctuations in the cosmic x-ray background flux and the large numbers of galaxies found in deep optical imaging, to m(sub v) is less than or equal to 24 - 26, is desired. These (faint) galaxies by their morphology and color in deep multi-color CCD images and plate material were optically identified. Statistically significant correlations between these galaxies and low-level x-ray fluctuations at the same positions in multiple deep Einstein HRI observations in PAVO and in a ROSAT PSPC field were searched for. Our aim is to test the hypothesis that faint 'star burst' galaxies might contribute significantly to the cosmic x-ray background (at approximately 1 keV).

3T deep gray matter T2 hypointensity correlates with disability over time in stable relapsing-remitting multiple sclerosis: a 3-year pilot study.

PubMed

Zhang, Y; Metz, L M; Yong, V W; Mitchell, J R

2010-10-15

Abnormally decreased deep gray matter (GM) signal intensity on T2-weighted MRI (T2 hypointensity) is associated with brain atrophy and disability progression in patients with multiple sclerosis (MS) and is believed to represent excessive iron deposition. We investigated the time course of deep GM T2 hypointensity and its relationship with disability at 3T in 8 stable relapsing-remitting (RR) MS patients treated with minocycline over 3years. MRI and disability measurements were compared at baseline, 6, 12, 24, and 36months. Grand mean deep GM T2 hypointensity was negatively correlated with EDSS over time (r=-0.94, P=0.02). This correlation was strongest in the head of caudate (r=-0.95, P=0.01) and putamen (r=-0.89, P=0.04). Additionally, baseline grand mean deep GM T2 hypointensity appears to predict third year EDSS (r=-0.72, P=0.04). These results suggest that iron associated deep GM injury correlates with patient disability in stable RRMS. Measurements of deep GM T2 hypointensity at high field MRI may prove to be useful in monitoring individuals with MS. Further studies are required to confirm these results in a large sample and to determine if T2 hypointensity changes in clinically active MS patients. Copyright 2010 Elsevier B.V. All rights reserved.

Hourly air pollution concentrations and their important predictors over Houston, Texas using deep neural networks: case study of DISCOVER-AQ time period

NASA Astrophysics Data System (ADS)

Eslami, E.; Choi, Y.; Roy, A.

2017-12-01

Air quality forecasting carried out by chemical transport models often show significant error. This study uses a deep-learning approach over the Houston-Galveston-Brazoria (HGB) area to overcome this forecasting challenge, for the DISCOVER-AQ period (September 2013). Two approaches, deep neural network (DNN) using a Multi-Layer Perceptron (MLP) and Restricted Boltzmann Machine (RBM) were utilized. The proposed approaches analyzed input data by identifying features abstracted from its previous layer using a stepwise method. The approaches predicted hourly ozone and PM in September 2013 using several predictors of prior three days, including wind fields, temperature, relative humidity, cloud fraction, precipitation along with PM, ozone, and NOx concentrations. Model-measurement comparisons for available monitoring sites reported Indexes of Agreement (IOA) of around 0.95 for both DNN and RBM. A standard artificial neural network (ANN) (IOA=0.90) with similar architecture showed poorer performance than the deep networks, clearly demonstrating the superiority of the deep approaches. Additionally, each network (both deep and standard) performed significantly better than a previous CMAQ study, which showed an IOA of less than 0.80. The most influential input variables were identified using their associated weights, which represented the sensitivity of ozone to input parameters. The results indicate deep learning approaches can achieve more accurate ozone forecasting and identify the important input variables for ozone predictions in metropolitan areas.

Role Stratospheric Balloon Magnetic Surveys in Development of Analytical Global Models of the Geomagnetic Field

NASA Astrophysics Data System (ADS)

Brekhov, O. M.; Tsvetkov, Yu. P.; Ivanov, V. V.; Filippov, S. V.; Tsvetkova, N. M.

2015-09-01

The results of stratospheric balloon gradient geomagnetic surveys at an altitude of ‘-~3O km with the use of the long (6 km) measuring base oriented along the vertical line are considered. The purposes of these surveys are the study of the magnetic field formed by deep sources, and the estimation of errors in modern analytical models of the geomagnetic field. The independent method of determination of errors in global analytical models of the normal magnetic field of the Earth (MFE) is substantiated. The new technique of identification of magnetic anomalies from surveys on long routes is considered. The analysis of gradient magnetic surveys on board the balloon, revealed the previously unknown features of the geomagnetic field. Using the balloon data, the EMM/720 model of the geomagnetic field (http://www.ngdc.noaa.gov/geomag/EMM) is investigated, and it is shown that this model unsatisfactorily represents the anomalous MFE, at least, at an altitude of 30 km, in the area our surveys. The unsatisfactory quality of aeromagnetic (ground-based) data is also revealed by the method of wavelet analysis of the ground-based and balloon magnetic profiles. It is shown, that the ground-based profiles do not contain inhomogeneities more than 1 30 km in size, whereas the balloon profiles (1000 km in the strike extent) contain inhomogeneities up to 600 km in size an the location of the latte coincides with the location of the satellite magnetic anomaly. On the basis of balloon data is shown, it that low-altitude aeromagnetic surveys, due to fundamental reasons, incorrectly reproduce the magnetic field of deep sources. This prevents the reliable conversion of ground-based magnetic anomalies upward from the surface of the Earth. It is shown, that an adequate global model of magnetic anomalies in the circumterrestrial space, developed up to 720 spherical harmonics, must be constructed only in accordance with the data obtained at satellite and stratospheric altitudes. Such a model can serve as a basis for the refined study of the structure and magnetic properties of the Earth's crust at its deep horizons, in order to search for resources at them, and so on.

XMM-Newton 13H deep field - I. X-ray sources

NASA Astrophysics Data System (ADS)

Loaring, N. S.; Dwelly, T.; Page, M. J.; Mason, K.; McHardy, I.; Gunn, K.; Moss, D.; Seymour, N.; Newsam, A. M.; Takata, T.; Sekguchi, K.; Sasseen, T.; Cordova, F.

2005-10-01

We present the results of a deep X-ray survey conducted with XMM-Newton, centred on the UK ROSAT13H deep field area. This region covers 0.18 deg2, and is the first of the two areas covered with XMM-Newton as part of an extensive multiwavelength survey designed to study the nature and evolution of the faint X-ray source population. We have produced detailed Monte Carlo simulations to obtain a quantitative characterization of the source detection procedure and to assess the reliability of the resultant sourcelist. We use the simulations to establish a likelihood threshold, above which we expect less than seven (3 per cent) of our sources to be spurious. We present the final catalogue of 225 sources. Within the central 9 arcmin, 68 per cent of source positions are accurate to 2 arcsec, making optical follow-up relatively straightforward. We construct the N(>S) relation in four energy bands: 0.2-0.5, 0.5-2, 2-5 and 5-10 keV. In all but our highest energy band we find that the source counts can be represented by a double power law with a bright-end slope consistent with the Euclidean case and a break around 10-14yergcm-2s-1. Below this flux, the counts exhibit a flattening. Our source counts reach densities of 700, 1300, 900 and 300 deg-2 at fluxes of 4.1 × 10-16,4.5 × 10-16,1.1 × 10-15 and 5.3 × 10-15ergcm-2s-1 in the 0.2-0.5, 0.5-2, 2-5 and 5-10 keV energy bands, respectively. We have compared our source counts with those in the two Chandra deep fields and Lockman hole, and found our source counts to be amongst the highest of these fields in all energy bands. We resolve >51 per cent (>50 per cent) of the X-ray background emission in the 1-2 keV (2-5 keV) energy bands.

Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

NASA Technical Reports Server (NTRS)

Mansour, Nagi N.; Wray, Alan A.; Mehrotra, Piyush; Henney, Carl; Arge, Nick; Godinez, H.; Manchester, Ward; Koller, J.; Kosovichev, A.; Scherrer, P.;

Modeling Stratigraphic Architecture of Deep-water Deposits Using a Small Unmanned Aircraft: Neogene Thin-bedded Turbidites, East Coast Basin, New Zealand

NASA Astrophysics Data System (ADS)

Nieminski, N.; Graham, S. A.

2014-12-01

One of the outstanding challenges of field geology is inaccessibility of exposure. The ability to view and characterize outcrops that are difficult to study from the ground is greatly improved by aerial investigation. Detailed stratigraphic architecture of such exposures is best addressed by using advances and availability of small unmanned aircraft systems (sUAS) that can safely navigate from high-altitude overviews of study areas to within a meter of the exposure of interest. High-resolution photographs acquired at various elevations and azimuths by sUAS are then used to convert field measurements to digital representations in three-dimensions at a fine scale. Photogrammetric software is used to capture complex, detailed topography by creating digital surface models with a range imaging technique that estimates three-dimensional structures from two-dimensional image sequences. The digital surface model is overlain by detailed, high-resolution photography. Pairing sUAS technology with readily available photogrammetry software that requires little processing time and resources offers a revolutionary and cost-effective methodology for geoscientists to investigate and quantify stratigraphic and structural complexity of field studies from the convenience of the office. These methods of imaging and modeling remote outcrops are demonstrated in the East Coast Basin, New Zealand, where wave-cut platform exposures of Miocene deep-water deposits offer a unique opportunity to investigate the flow processes and resulting characteristics of thin-bedded turbidite deposits. Stratigraphic architecture of wavecut platform and vertically-dipping exposures of these thin-bedded turbidites is investigated with sUAS coupled with Structure from Motion (SfM) photogrammetry software. This approach allows the geometric and spatial variation of deep-water architecture to be characterized continuously along 2,000 meters of lateral exposure, as well as to measure and quantify cyclic variations in thin-bedded turbidites at centimeter scale. Results yield a spatial and temporal understanding of a deep-water depositional system at a scale that was previously unattainable using conventional field geology techniques, and a virtual outcrop that can be used for classroom education.

Clusters, Groups, and Filaments in the Chandra Deep Field-South up to Redshift 1

NASA Astrophysics Data System (ADS)

Dehghan, S.; Johnston-Hollitt, M.

2014-03-01

We present a comprehensive structure detection analysis of the 0.3 deg2 area of the MUSYC-ACES field, which covers the Chandra Deep Field-South (CDFS). Using a density-based clustering algorithm on the MUSYC and ACES photometric and spectroscopic catalogs, we find 62 overdense regions up to redshifts of 1, including clusters, groups, and filaments. We also present the detection of a relatively small void of ~10 Mpc2 at z ~ 0.53. All structures are confirmed using the DBSCAN method, including the detection of nine structures previously reported in the literature. We present a catalog of all structures present, including their central position, mean redshift, velocity dispersions, and classification based on their morphological and spectroscopic distributions. In particular, we find 13 galaxy clusters and 6 large groups/small clusters. Comparison of these massive structures with published XMM-Newton imaging (where available) shows that 80% of these structures are associated with diffuse, soft-band (0.4-1 keV) X-ray emission, including 90% of all objects classified as clusters. The presence of soft-band X-ray emission in these massive structures (M 200 >= 4.9 × 1013 M ⊙) provides a strong independent confirmation of our methodology and classification scheme. In the closest two clusters identified (z < 0.13) high-quality optical imaging from the Deep2c field of the Garching-Bonn Deep Survey reveals the cD galaxies and demonstrates that they sit at the center of the detected X-ray emission. Nearly 60% of the clusters, groups, and filaments are detected in the known enhanced density regions of the CDFS at z ~= 0.13, 0.52, 0.68, and 0.73. Additionally, all of the clusters, bar the most distant, are found in these overdense redshift regions. Many of the clusters and groups exhibit signs of ongoing formation seen in their velocity distributions, position within the detected cosmic web, and in one case through the presence of tidally disrupted central galaxies exhibiting trails of stars. These results all provide strong support for hierarchical structure formation up to redshifts of 1.

[Effect of static magnetic field on deep wound healing of SD rats].

PubMed

Shen, Jian-Guo; Chen, Wei-Shan; Wang, Chang-Xing; Jiang, Tao; Dong, Li-Qiang

2009-05-01

To investigate the effect of static magnetic field on deep wound healing of SD rats and VEGF during the wound healing and different strength static magnetic field on deep wound healing of SD rats. Divided forty-eight SD rats into three groups: 0.16 T magnetic disk treatment (0.16 T group), 0.32 T magnetic disk treatment (0.32 T group), control group. General wounds healing situation was observated on the 3, 6, 9, 12 day. The area of every wound was calculated. The tissue of granulation was dyeing by immune tissue chemical decoration method, in which VEGF protein content with its range in tissue was measured. The healing index of 0.16 T magnetic group wounds were larger than that of control group on 6th and 9th day, there were statistical difference. The healing index of 0.32 T magnetic group wounds were larger than that of control group on 3rd, 6th, 9th and 12th day, there were statistical difference. The healing index of 0.32 T group wounds contrasted to that of 0.16 T group wounds had no statistical significance. Observation of VEGF at the course of wound healing:the expressing of VEGF in magnetic group wounds on 3rd and 6th was stronger than in control group wounds, there were statistical difference. While there were no obvious difference between them on 9th and 12th day (P>0.05). But the contrast between that in 0.32 T group and in 0.16 T group had no statistical difference. The expressing strength of VEGF in magnetic group reached the peak amplitude on the 6th day, and that in control group reached peak amplitude on 9th day. And the peak amplitude of magnetic group was stronger than that of control group. Static magnetic disc of 0.16T and 0.32 T can promote deep wound of SD rats heal. The mechanism of static magnetic field promoting wound heal may be relative to the expressing highly of VEGF during early and middle time.

Soil Physical Constraints on Intrinsic Biodegradation of Petroleum Vapors in a Layered Subsurface

PubMed Central

Kristensen, Andreas H.; Henriksen, Kaj; Mortensen, Lars; Scow, Kate M.; Moldrup, Per

2011-01-01

Naturally occurring biodegradation of petroleum hydrocarbons in the vadose zone depends on the physical soil environment influencing field-scale gas exchange and pore-scale microbial metabolism. In this study, we evaluated the effect of soil physical heterogeneity on biodegradation of petroleum vapors in a 16-m-deep, layered vadose zone. Soil slurry experiments (soil/water ratio 10:30 w/w, 25°C) on benzene biodegradation under aerobic and well-mixed conditions indicated that the biodegradation potential in different textured soil samples was related to soil type rather than depth, in the order: sandy loam > fine sand > limestone. Similarly, O2 consumption rates during in situ respiration tests performed at the site were higher in the sandy loam than in the fine sand, although the difference was less significant than in the slurries. Laboratory and field data generally agreed well and suggested a significant potential for aerobic biodegradation, even with nutrient-poor and deep subsurface conditions. In slurries of the sandy loam, the biodegradation potential declined with increasing in situ water saturation (i.e., decreasing air-filled porosity in the field). This showed a relation between antecedent undisturbed field conditions and the slurry biodegradation potential, and suggested airfilled porosity to be a key factor for the intrinsic biodegradation potential in the field. PMID:21617737

Linking Deep Astrometric Standards to the ICRF

NASA Astrophysics Data System (ADS)

Frey, S.; Platais, I.; Fey, A. L.

2007-07-01

The next-generation large aperature and large field-of-view telescopes will address fundamantal questions of astrophysica and cosmology such as the nature of dark matter and dark energy. For a variety of applications, the CCD mosaic detectors in the focal plane arrays require astronomic calibrationat the milli-arcsecond (mas) level. The existing optical reference frames are insufficient to support such calibrations. To address this problem, deep optical astronomic fields are being established near the Galactic plane. In order to achiev a 5-10-mas or better positional accuracyfor the Deepp Astrometric Standards (DAS), and to obtain bsolute stellar proper motions for the study of Galactic structure, it is crucial to link these fields to the International Celestial Reference Frame (ICRF). To this end, we selected 15 candidate compact extragalactic radio sources in the Gemini-Orion-Taurus (GOT) field. These sources were observed with the European VLBI Network (EVN) at 5 GHz in phase-reference mode. The bright compact calibrator source J0603+2159 and seven other sources were detected and imaged at the angular resolution of -1.5-8 mas. Relative astrometric positions were derived for these sources at a milli-arcsecond accuracy level. The detection of the optical counterparts of these extragalactic radio sources will allow us to establish a direct link to the ICRF locally in the GOT field.

Geological Implications From Complete Gondwana GOCE- Products Reconstructions and Link to Lithospheric Roots

NASA Astrophysics Data System (ADS)

Braitenberg, Carla; Mariani, Patrizia

2015-03-01

The GOCE gravity field is globally homogeneous at the resolution of about 80km or better allowing for the first time to analyze tectonic structures at continental scale. Geologic correlation studies propose to continue the tectonic lineaments across continents to the pre-breakup position. Tectonic events that induce density changes, as metamorphic events and magmatic events, should then show up in the gravity field. Applying geodynamic plate reconstructions to the GOCE gravity field places today’s observed field at the pre-breakup position. The same reconstruction can be applied to the seismic velocity models, to allow a joint gravity-velocity analysis. The geophysical fields allow to control the likeliness of the hypothesized continuation of lineations based on sparse surface outcrops. Total absence of a signal, makes the cross-continental continuation of the lineament improbable, as continental-wide lineaments are controlled by rheologic and compositional differences of lithospheric mantle. It is found that the deep lithospheric roots as those found below cratons control the position of the positive gravity values. The explanation is that the deep lithospheric roots focus asthenospheric upwelling outboard of the root protecting the overlying craton from magmatic intrusions. The study is carried out over the African and South American continents.

The effect of an exogenous magnetic field on neural coding in deep spiking neural networks.

PubMed

Guo, Lei; Zhang, Wei; Zhang, Jialei

2018-01-01

A ten-layer feed forward network is constructed in the presence of an exogenous alternating magnetic field. Specifically, our results indicate that for rate coding, the firing rate is significantly increased in the presence of an exogenous alternating magnetic field and particularly with increasing enhancement of the alternating magnetic field amplitude. For temporal coding, the interspike intervals of the spiking sequence are decreased and the distribution of the interspike intervals of the spiking sequence tends to be uniform in the presence of alternating magnetic field.

Extragalactic Fields Optimized for Adaptive Optics

DTIC Science & Technology

2011-03-01

DAVID MONETIO Received 2010 luly 19; accepted 2010 December 30; published 2011 March 1 ABSTRACT. In this article we present the coordinates of 67 55’ x...Window, contains most of the patches we have identified. Our optimal field, centered at R.A.: 7h24m3s, decl.: - 1 °27󈧓", has an additional advantage of...equivalent observations undertaken in existing deep fields. Online material: color figures 1 . INTRODUCTION Our understanding of the high-redshift

Investigations of a novel fauna from hydrothermal vents along the Arctic Mid-Ocean Ridge (AMOR) (Invited)

NASA Astrophysics Data System (ADS)

Rapp, H.; Schander, C.; Halanych, K. M.; Levin, L. A.; Sweetman, A.; Tverberg, J.; Hoem, S.; Steen, I.; Thorseth, I. H.; Pedersen, R.

2010-12-01

The Arctic deep ocean hosts a variety of habitats ranging from fairly uniform sedimentary abyssal plains to highly variable hard bottoms on mid ocean ridges, including biodiversity hotspots like seamounts and hydrothermal vents. Deep-sea hydrothermal vents are usually associated with a highly specialized fauna, and since their discovery in 1977 more than 400 species of animals have been described. This fauna includes various animal groups of which the most conspicuous and well known are annelids, mollusks and crustaceans. The newly discovered deep sea hydrothermal vents on the Mohns-Knipovich ridge north of Iceland harbour unique biodiversity. The Jan Mayen field consists of two main areas with high-temperature white smoker venting and wide areas with low-temperature seepage, located at 5-700 m, while the deeper Loki Castle vent field at 2400 m depth consists of a large area with high temperature black smokers surrounded by a sedimentary area with more diffuse low-temperature venting and barite chimneys. The Jan Mayen sites show low abundance of specialized hydrothermal vent fauna. Single groups have a few specialized representatives but groups otherwise common in hydrothermal vent areas are absent. Slightly more than 200 macrofaunal species have been identified from this vent area, comprising mainly an assortment of bathyal species known from the surrounding area. Analysis of stable isotope data also indicates that the majority of the species present are feeding on phytodetritus and/or phytoplankton. However, the deeper Loki Castle vent field contains a much more diverse vent endemic fauna with high abundances of specialized polychaetes, gastropods and amphipods. These specializations also include symbioses with a range of chemosynthetic microorganisms. Our data show that the fauna composition is a result of high degree of local specialization with some similarities to the fauna of cold seeps along the Norwegian margin and wood-falls in the abyssal Norwegian Sea. Few species are common to both the deep and the shallow vents, but some gastropod species show a structured population difference between the sites. Our data indicate that there has been a migration of vent fauna into the Arctic Ocean from the Pacific Ocean rather than from the known vent sites further south in the Atlantic Ocean. The discovery and sampling of these new arctic vent fields provide unique data to further understand the migration of vent organisms and interactions between different deep sea chemosynthetic environments. Based on the high degree of local adaptation and specialization of fauna from the studied sites we propose the AMOR to be a new zoogeographical province for vent fauna.

Orientation selective deep brain stimulation

NASA Astrophysics Data System (ADS)

Lehto, Lauri J.; Slopsema, Julia P.; Johnson, Matthew D.; Shatillo, Artem; Teplitzky, Benjamin A.; Utecht, Lynn; Adriany, Gregor; Mangia, Silvia; Sierra, Alejandra; Low, Walter C.; Gröhn, Olli; Michaeli, Shalom

2017-02-01

Objective. Target selectivity of deep brain stimulation (DBS) therapy is critical, as the precise locus and pattern of the stimulation dictates the degree to which desired treatment responses are achieved and adverse side effects are avoided. There is a clear clinical need to improve DBS technology beyond currently available stimulation steering and shaping approaches. We introduce orientation selective neural stimulation as a concept to increase the specificity of target selection in DBS. Approach. This concept, which involves orienting the electric field along an axonal pathway, was tested in the corpus callosum of the rat brain by freely controlling the direction of the electric field on a plane using a three-electrode bundle, and monitoring the response of the neurons using functional magnetic resonance imaging (fMRI). Computational models were developed to further analyze axonal excitability for varied electric field orientation. Main results. Our results demonstrated that the strongest fMRI response was observed when the electric field was oriented parallel to the axons, while almost no response was detected with the perpendicular orientation of the electric field relative to the primary fiber tract. These results were confirmed by computational models of the experimental paradigm quantifying the activation of radially distributed axons while varying the primary direction of the electric field. Significance. The described strategies identify a new course for selective neuromodulation paradigms in DBS based on axonal fiber orientation.

Active Galactic Nuclei, Quasars, BL Lac Objects and X-Ray Background

NASA Technical Reports Server (NTRS)

Mushotzky, Richard (Technical Monitor); Elvis, Martin

2005-01-01

The XMM COSMOS survey is producing the large surface density of X-ray sources anticipated. The first batch of approx. 200 sources is being studied in relation to the large scale structure derived from deep optical/near-IR imaging from Subaru and CFHT. The photometric redshifts from the opt/IR imaging program allow a first look at structure vs. redshift, identifying high z clusters. A consortium of SAO, U. Arizona and the Carnegie Institute of Washington (Pasadena) has started a large program using the 6.5meter Magellan telescopes in Chile with the prime objective of identifying the XMM X-ray sources in the COSMOS field. The first series of observing runs using the new IMACS multi-slit spectrograph on Magellan will take place in January and February of 2005. Some 300 spectra per field will be taken, including 70%-80% of the XMM sources in each field. The four first fields cover the center of the COSMOS field. A VLT consortium is set to obtain bulk redshifts of the field galaxies. The added accuracy of the spectroscopic redshifts over the photo-z's will allow much lower density structures to be seen, voids and filaments. The association of X-ray selected AGNs, and quasars with these filaments, is a major motivation for our studies. Comparison to the deep VLA radio data now becoming available is about to begin.

Chandra survey in the AKARI North Ecliptic Pole Deep Field - I. X-ray data, point-like source catalogue, sensitivity maps, and number counts

NASA Astrophysics Data System (ADS)

Krumpe, M.; Miyaji, T.; Brunner, H.; Hanami, H.; Ishigaki, T.; Takagi, T.; Markowitz, A. G.; Goto, T.; Malkan, M. A.; Matsuhara, H.; Pearson, C.; Ueda, Y.; Wada, T.

2015-01-01

We present data products from the 300 ks Chandra survey in the AKARI North Ecliptic Pole Deep Field. This field has a unique set of nine-band infrared photometry covering 2-24 μm from the AKARI Infrared Camera, including mid-infrared (MIR) bands not covered by Spitzer. The survey is one of the deepest ever achieved at ˜15 μm, and is by far the widest among those with similar depths in the MIR. This makes this field unique for the MIR-selection of AGN at z ˜ 1. We design a source detection procedure, which performs joint maximum likelihood PSF (point spread function) fits on all of our 15 mosaicked Chandra pointings covering an area of 0.34 deg2. The procedure has been highly optimized and tested by simulations. We provide a point source catalogue with photometry and Bayesian-based 90 per cent confidence upper limits in the 0.5-7, 0.5-2, 2-7, 2-4, and 4-7 keV bands. The catalogue contains 457 X-ray sources and the spurious fraction is estimated to be ˜1.7 per cent. Sensitivity and 90 per cent confidence upper flux limits maps in all bands are provided as well. We search for optical-MIR counterparts in the central 0.25 deg2, where deep Subaru Suprime-Cam multiband images exist. Among the 377 X-ray sources detected there, ˜80 per cent have optical counterparts and ˜60 per cent also have AKARI MIR counterparts. We cross-match our X-ray sources with MIR-selected AGN from Hanami et al. Around 30 per cent of all AGN that have MIR SEDs purely explainable by AGN activity are strong Compton-thick AGN candidates.

Variability-selected active galactic nuclei from supernova search in the Chandra deep field south

NASA Astrophysics Data System (ADS)

Trevese, D.; Boutsia, K.; Vagnetti, F.; Cappellaro, E.; Puccetti, S.

2008-09-01

Context: Variability is a property shared by virtually all active galactic nuclei (AGNs), and was adopted as a criterion for their selection using data from multi epoch surveys. Low Luminosity AGNs (LLAGNs) are contaminated by the light of their host galaxies, and cannot therefore be detected by the usual colour techniques. For this reason, their evolution in cosmic time is poorly known. Consistency with the evolution derived from X-ray detected samples has not been clearly established so far, also because the low luminosity population consists of a mixture of different object types. LLAGNs can be detected by the nuclear optical variability of extended objects. Aims: Several variability surveys have been, or are being, conducted for the detection of supernovae (SNe). We propose to re-analyse these SNe data using a variability criterion optimised for AGN detection, to select a new AGN sample and study its properties. Methods: We analysed images acquired with the wide field imager at the 2.2 m ESO/MPI telescope, in the framework of the STRESS supernova survey. We selected the AXAF field centred on the Chandra Deep Field South where, besides the deep X-ray survey, various optical data exist, originating in the EIS and COMBO-17 photometric surveys and the spectroscopic database of GOODS. Results: We obtained a catalogue of 132 variable AGN candidates. Several of the candidates are X-ray sources. We compare our results with an HST variability study of X-ray and IR detected AGNs, finding consistent results. The relatively high fraction of confirmed AGNs in our sample (60%) allowed us to extract a list of reliable AGN candidates for spectroscopic follow-up observations. Table [see full text] is only available in electronic form at http://www.aanda.org

CANDELS: The Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey

NASA Technical Reports Server (NTRS)

Grogin, Norman A.; Koekemoer, anton M.; Faber, S. M.; Ferguson, Henry C.; Kocevski, Dale D.; Riess, Adam G.; Acquaviva, Viviana; Alexander, David M.; Almaini, Omar; Ashby, Matthew L. N.;

Vertical movements following intracontinental magmatism: An example from southern Israel

NASA Astrophysics Data System (ADS)

Gvirtzman, Zohar; Garfunkel, Zvi

1997-02-01

We present a quantitative thermal model for vertical movements following continental magmatism, focusing on how the associated elevation changes depend on the depth of intrusion. When an intrusion is emplaced within the lithosphere, its buoyancy causes a quick initial movement which is followed by long-term movements caused by thermal relaxation. Intrusions emplaced within the gabbro stability field produce initial uplifting which is about 12% of their thickness. Subsequent thermal relaxation reduces the uplift to a residual value of 9-10% of the intrusion thickness. In contrast, intrusions emplaced within the eclogite stability field produce a small subsidence from the very beginning which is slowly increased by thermal relaxation and may reach a residual value of some 4% of the intrusion thickness. In both cases the rates of the thermal subsidence depend on the depth of intrusion: it is relatively fast when the intrusions are shallow but considerably slower when the intrusions are deep. The model enables us to infer volumes and depths of intrusions from amplitudes and rates of vertical movements. As an example we apply the model to analyze the geodynamic evolution of the central Negev, southern Israel, during the Early Cretaceous. Two distinct magmatic pulses that were recognized there represent the two basic situations envisaged by the model, i.e., shallow magma emplacement in the gabbro field associated with uplifting, and deep intrusion in the eclogite field associated with subsidence. In a wider context we think that this model may help in understanding intracratonic basins in nonextensional settings. In particular, deep and thick eclogite intrusions can explain subsidence of regions which were not extended nor uplifted and in regions where crustal magmatism and heating were not observed.

Hubble Goes to the eXtreme to Assemble Farthest-Ever View of the Universe

NASA Image and Video Library

2017-12-08

NASA image release September 25, 2012 Like photographers assembling a portfolio of best shots, astronomers have assembled a new, improved portrait of mankind's deepest-ever view of the universe. Called the eXtreme Deep Field, or XDF, the photo was assembled by combining 10 years of NASA Hubble Space Telescope photographs taken of a patch of sky at the center of the original Hubble Ultra Deep Field. The XDF is a small fraction of the angular diameter of the full moon. The Hubble Ultra Deep Field is an image of a small area of space in the constellation Fornax, created using Hubble Space Telescope data from 2003 and 2004. By collecting faint light over many hours of observation, it revealed thousands of galaxies, both nearby and very distant, making it the deepest image of the universe ever taken at that time. The new full-color XDF image is even more sensitive, and contains about 5,500 galaxies even within its smaller field of view. The faintest galaxies are one ten-billionth the brightness of what the human eye can see. To read more go to:http://www.nasa.gov/mission_pages/hubble/science/xdf.html Credit: NASA; ESA; G. Illingworth, D. Magee, and P. Oesch, University of California, Santa Cruz; R. Bouwens, Leiden University; and the HUDF09 Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Deep Borehole Field Test Laboratory and Borehole Testing Strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhlman, Kristopher L.; Brady, Patrick V.; MacKinnon, Robert J.

2016-09-19

Deep Borehole Disposal (DBD) of high-level radioactive wastes has been considered an option for geological isolation for many years (Hess et al. 1957). Recent advances in drilling technology have decreased costs and increased reliability for large-diameter (i.e., ≥50 cm [19.7”]) boreholes to depths of several kilometers (Beswick 2008; Beswick et al. 2014). These advances have therefore also increased the feasibility of the DBD concept (Brady et al. 2009; Cornwall 2015), and the current field test design will demonstrate the DBD concept and these advances. The US Department of Energy (DOE) Strategy for the Management and Disposal of Used Nuclear Fuelmore » and High-Level Radioactive Waste (DOE 2013) specifically recommended developing a research and development plan for DBD. DOE sought input or expression of interest from States, local communities, individuals, private groups, academia, or any other stakeholders willing to host a Deep Borehole Field Test (DBFT). The DBFT includes drilling two boreholes nominally 200m [656’] apart to approximately 5 km [16,400’] total depth, in a region where crystalline basement is expected to begin at less than 2 km depth [6,560’]. The characterization borehole (CB) is the smaller-diameter borehole (i.e., 21.6 cm [8.5”] diameter at total depth), and will be drilled first. The geologic, hydrogeologic, geochemical, geomechanical and thermal testing will take place in the CB. The field test borehole (FTB) is the larger-diameter borehole (i.e., 43.2 cm [17”] diameter at total depth). Surface handling and borehole emplacement of test package will be demonstrated using the FTB to evaluate engineering feasibility and safety of disposal operations (SNL 2016).« less

Completing the Legacy of Spitzer/IRAC over COSMOS

NASA Astrophysics Data System (ADS)

Labbe, Ivo; Caputi, Karina; McLeod, Derek; Cowley, Will; Dayal, Pratika; Behroozi, Peter; Ashby, Matt; Franx, Marijn; Dunlop, James; Le Fevre, Olivier; Fynbo, Johan; McCracken, Henry; Milvang-Jensen, Bo; Ilbert, Olivier; Tasca, Lidia; de Barros, Stephane; Oesch, Pascal; Bouwens, Rychard; Muzzin, Adam; Illingworth, Garth; Stefanon, Mauro; Schreiber, Corentin; Hutter, Anne; van Dokkum, Pieter

2016-08-01

We propose to complete the legacy of Spitzer/IRAC over COSMOS by extending the deep coverage to the full 1.8 sq degree field, producing a nearly homogenous and contiguous map unparalleled in terms of area and depth. Ongoing and scheduled improvements in the supporting optical-to-NIR data down to ultradeep limits have reconfirmed COSMOS as a unique field for probing the bright end of the z=6-11 universe and the formation of large-scale structures. However, currently only one-third of the field has received sufficiently deep IRAC coverage to match the new optical/near-IR limits. Here we request deep matching IRAC data over the full 1.8 sq degree field to detect almost one million galaxies. The proposed observations will allow us to 1) constrain the galaxy stellar mass function during the epoch of reionization at z=6-8 with ~10,000 galaxies at these redshifts, 2) securely identify the brightest galaxies at 9 < z < 11, 3) trace the growth of stellar mass at 1 < z < 8 and the co-evolution of galaxies and their dark matter halos, 4) identify (proto)clusters and large scale structures, and 5) reveal dust enshrouded starbursts and the first quiescent galaxies at 3 < z < 6. The Spitzer Legacy over COSMOS will enable a wide range of discoveries beyond these science goals owing to the unique array of multiwavelength data from the X-ray to the radio. COSMOS is a key target for ongoing and future studies with ALMA and for spectroscopy from the ground, and with the timely addition of the Spitzer Legacy it will prove to be a crucial treasury for efficient planning and early follow-up with JWST.

Effect of deep injection on field-scale emissions of 1,3-dichloropropene and chloropicrin from bare soil

NASA Astrophysics Data System (ADS)

Yates, S. R.; Ashworth, D. J.; Zheng, W.; Knuteson, J.; van Wesenbeeck, I. J.

2016-07-01

Fumigating soil is important for the production of many high-value vegetable, fruit, and tree crops, but fumigants are toxic pesticides with relatively high volatility, which can lead to significant atmospheric emissions. A field experiment was conducted to measure emissions and subsurface diffusion of a mixture of 1,3-dichloropropene (1,3-D) and chloropicrin after shank injection to bare soil at 61 cm depth (i.e., deep injection). Three on-field methods, the aerodynamic (ADM), integrated horizontal flux (IHF), and theoretical profile shape (TPS) methods, were used to obtain fumigant flux density and cumulative emission values. Two air dispersion models (CALPUFF and ISCST3) were also used to back-calculate the flux density using air concentration measurements surrounding the fumigated field. Emissions were continuously measured for 16 days and the daily peak emission rates for the five methods ranged from 13 to 33 μg m-2 s-1 for 1,3-D and 0.22-3.2 μg m-2 s-1 for chloropicrin. Total 1,3-D mass lost to the atmosphere was approximately 23-41 kg ha-1, or 15-27% of the applied active ingredient and total mass loss of chloropicrin was <2%. Based on the five methods, deep injection reduced total emissions by approximately 2-24% compared to standard fumigation practices where fumigant injection is at 46 cm depth. Given the relatively wide range in emission-reduction percentages, a fumigant diffusion model was used to predict the percentage reduction in emissions by injecting at 61 cm, which yielded a 21% reduction in emissions. Significant reductions in emissions of 1,3-D and chloropicrin are possible by injecting soil fumigants deeper in soil.

Deep Learning for Image-Based Cassava Disease Detection.

PubMed

Ramcharan, Amanda; Baranowski, Kelsee; McCloskey, Peter; Ahmed, Babuali; Legg, James; Hughes, David P

2017-01-01

Cassava is the third largest source of carbohydrates for human food in the world but is vulnerable to virus diseases, which threaten to destabilize food security in sub-Saharan Africa. Novel methods of cassava disease detection are needed to support improved control which will prevent this crisis. Image recognition offers both a cost effective and scalable technology for disease detection. New deep learning models offer an avenue for this technology to be easily deployed on mobile devices. Using a dataset of cassava disease images taken in the field in Tanzania, we applied transfer learning to train a deep convolutional neural network to identify three diseases and two types of pest damage (or lack thereof). The best trained model accuracies were 98% for brown leaf spot (BLS), 96% for red mite damage (RMD), 95% for green mite damage (GMD), 98% for cassava brown streak disease (CBSD), and 96% for cassava mosaic disease (CMD). The best model achieved an overall accuracy of 93% for data not used in the training process. Our results show that the transfer learning approach for image recognition of field images offers a fast, affordable, and easily deployable strategy for digital plant disease detection.

Singlet gradient index lens for deep in vivo multiphoton microscopy

NASA Astrophysics Data System (ADS)

Murray, Teresa A.; Levene, Michael J.

2012-02-01

Micro-optical probes, including gradient index (GRIN) lenses and microprisms, have expanded the range of in vivo multiphoton microscopy to reach previously inaccessible deep brain structures such as deep cortical layers and the underlying hippocampus in mice. Yet imaging with GRIN lenses has been fundamentally limited by large amounts of spherical aberration and the need to construct compound lenses that limit the field-of-view. Here, we demonstrate the use of 0.5-mm-diameter, 1.7-mm-long GRIN lens singlets with 0.6 numerical aperture in conjunction with a cover glass and a conventional microscope objective correction collar to balance spherical aberrations. The resulting system achieves a lateral resolution of 618 nm and an axial resolution of 5.5 μm, compared to lateral and axial resolutions of ~1 μm and ~15 μm, respectively, for compound GRIN lenses of similar diameter. Furthermore, the GRIN lens singlets display fields-of-view in excess of 150 μm, compared with a few tens of microns for compound GRIN lenses. The GRIN lens/cover glass combination presented here is easy to assemble and inexpensive enough for use as a disposable device, enabling ready adoption by the neuroscience community.

q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.

PubMed

Golkov, Vladimir; Dosovitskiy, Alexey; Sperl, Jonathan I; Menzel, Marion I; Czisch, Michael; Samann, Philipp; Brox, Thomas; Cremers, Daniel

2016-05-01

Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines. An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive microstructure assessment method with a prominent application in neuroimaging. Advanced diffusion models providing accurate microstructural characterization so far have required long acquisition times and thus have been inapplicable for children and adults who are uncooperative, uncomfortable, or unwell. We show that the long scan time requirements are mainly due to disadvantages of classical data processing. We demonstrate how deep learning, a group of algorithms based on recent advances in the field of artificial neural networks, can be applied to reduce diffusion MRI data processing to a single optimized step. This modification allows obtaining scalar measures from advanced models at twelve-fold reduced scan time and detecting abnormalities without using diffusion models. We set a new state of the art by estimating diffusion kurtosis measures from only 12 data points and neurite orientation dispersion and density measures from only 8 data points. This allows unprecedentedly fast and robust protocols facilitating clinical routine and demonstrates how classical data processing can be streamlined by means of deep learning.

3D numerical simulation of flow field with incompletely flaring gate pier in large unit discharge and deep tail water project

NASA Astrophysics Data System (ADS)

Zhao, Zhou; Junxing, Wang

2018-06-01

Limited by large unit discharge above the overflow weir and deep tail water inside the stilling basin, the incoming flow inside stilling basin is seriously short of enough energy dissipation and outgoing flow still carries much energy with large velocity, bound to result in secondary hydraulic jump outside stilling basin and scour downstream river bed. Based on the RNG k-ɛ turbulence model and the VOF method, this paper comparatively studies flow field between the conventional flat gate pier program and the incompletely flaring gate pier program to reveal energy dissipation mechanism of incomplete flaring gate pier. Results show that incompletely flaring gate pier can greatly promote the longitudinally stretched water jet to laterally diffuse and collide in the upstream region of stilling basin due to velocity gradients between adjacent inflow from each chamber through shrinking partial overflow flow chamber weir chamber, which would lead to large scale vertical axis vortex from the bottom to the surface and enhance mutual shear turbulence dissipation. This would significantly increase energy dissipation inside stilling basin to reduce outgoing velocity and totally solve the common hydraulic problems in large unit discharge and deep tail water projects.

DEEP U BAND AND R IMAGING OF GOODS-SOUTH: OBSERVATIONS, DATA REDUCTION AND FIRST RESULTS ,

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nonino, M.; Cristiani, S.; Vanzella, E.

2009-08-01

We present deep imaging in the U band covering an area of 630 arcmin{sup 2} centered on the southern field of the Great Observatories Origins Deep Survey (GOODS). The data were obtained with the VIMOS instrument at the European Southern Observatory (ESO) Very Large Telescope. The final images reach a magnitude limit U {sub lim} {approx} 29.8 (AB, 1{sigma}, in a 1'' radius aperture), and have good image quality, with full width at half-maximum {approx}0.''8. They are significantly deeper than previous U-band images available for the GOODS fields, and better match the sensitivity of other multiwavelength GOODS photometry. The deepermore » U-band data yield significantly improved photometric redshifts, especially in key redshift ranges such as 2 < z < 4, and deeper color-selected galaxy samples, e.g., Lyman break galaxies at z {approx} 3. We also present the co-addition of archival ESO VIMOS R-band data, with R {sub lim} {approx} 29 (AB, 1{sigma}, 1'' radius aperture), and image quality {approx}0.''75. We discuss the strategies for the observations and data reduction, and present the first results from the analysis of the co-added images.« less

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

PubMed

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal shape deep learning: applications to pediatric lung field segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovany; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, local- ization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0:927 using only the four highest modes of variation (compared to 0:888 with classical ASM1 (p-value=0:01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Farm water budgets for semiarid irrigated floodplains of northern New Mexico: characterizing the surface water-groundwater interactions

NASA Astrophysics Data System (ADS)

Gutierrez, K. Y.; Fernald, A.; Ochoa, C. G.; Guldan, S. J.

2013-12-01

KEY WORDS - Hydrology, Water budget, Deep percolation, Surface water-Groundwater interactions. With the recent projections for water scarcity, water balances have become an indispensable water management tool. In irrigated floodplains, deep percolation from irrigation can represent one of the main aquifer recharge sources. A better understanding of surface water and groundwater interactions in irrigated valleys is needed for properly assessing the water balances in these systems and estimating potential aquifer recharge. We conducted a study to quantify the parameters and calculate the water budgets in three flood irrigated hay fields with relatively low, intermediate and, high water availability in northern New Mexico. We monitored different hydrologic parameters including total amount of water applied, change in soil moisture, drainage below the effective root zone, and shallow water level fluctuations in response to irrigation. Evapotranspiration was calculated from weather station data collected in-situ using the Samani-Hargreaves. Previous studies in the region have estimated deep percolation as a residual parameter of the water balance equation. In this study, we used both, the water balance method and actual measurements of deep percolation using passive lysimeters. Preliminary analyses for the three fields show a relatively rapid movement of water through the upper 50 cm of the vadose zone and a quick response of the shallow aquifer under flood irrigation. Further results from this study will provide a better understanding of surface water-groundwater interactions in flood irrigated valleys in northern New Mexico.