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.

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

Learning styles and approaches to learning among medical undergraduates and postgraduates

PubMed Central

2013-01-01

Background The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. Methods We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. Results A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners. Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. Conclusions The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period. PMID:23521845

Learning styles and approaches to learning among medical undergraduates and postgraduates.

PubMed

Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka

2013-03-25

The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.

Magnetism and the interior of the moon

NASA Technical Reports Server (NTRS)

Dyal, P.; Parkin, C. W.; Daily, W. D.

1974-01-01

The application of lunar magnetic field measurements to the study of properties of the lunar crust and deep interior is reviewed. Following a brief description of lunar magnetometers and the lunar magnetic environment, measurements of lunar remanent fields and their interaction with the solar plasma are discussed. The magnetization induction mode is considered with reference to lunar magnetic permeability and iron abundance calculations. Finally, electrical conductivity and temperature calculations from analyses of poloidal induction, for data taken in both the solar wind and in the geomagnetic tail, are reviewed.

SchNet - A deep learning architecture for molecules and materials

NASA Astrophysics Data System (ADS)

Schütt, K. T.; Sauceda, H. E.; Kindermans, P.-J.; Tkatchenko, A.; Müller, K.-R.

2018-06-01

Deep learning has led to a paradigm shift in artificial intelligence, including web, text, and image search, speech recognition, as well as bioinformatics, with growing impact in chemical physics. Machine learning, in general, and deep learning, in particular, are ideally suitable for representing quantum-mechanical interactions, enabling us to model nonlinear potential-energy surfaces or enhancing the exploration of chemical compound space. Here we present the deep learning architecture SchNet that is specifically designed to model atomistic systems by making use of continuous-filter convolutional layers. We demonstrate the capabilities of SchNet by accurately predicting a range of properties across chemical space for molecules and materials, where our model learns chemically plausible embeddings of atom types across the periodic table. Finally, we employ SchNet to predict potential-energy surfaces and energy-conserving force fields for molecular dynamics simulations of small molecules and perform an exemplary study on the quantum-mechanical properties of C20-fullerene that would have been infeasible with regular ab initio molecular dynamics.

Applications of Deep Learning and Reinforcement Learning to Biological Data.

PubMed

Mahmud, Mufti; Kaiser, Mohammed Shamim; Hussain, Amir; Vassanelli, Stefano

2018-06-01

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. The growth in computational power accompanied by faster and increased data storage, and declining computing costs have already allowed scientists in various fields to apply these techniques on data sets that were previously intractable owing to their size and complexity. This paper provides a comprehensive survey on the application of DL, RL, and deep RL techniques in mining biological data. In addition, we compare the performances of DL techniques when applied to different data sets across various application domains. Finally, we outline open issues in this challenging research area and discuss future development perspectives.

[The Triumph of "Stupidity" : Deep Blue`s Victory over Garri Kasparov. The Controversy about its Impact on Artficial Intelligence Research].

PubMed

Heßler, Martina

2017-03-01

The competition between the chess computer Deep Blue and the former chess world champion Garri Kasparov in 1997 was a spectacle staged for the media. However, the chess game, like other games, was also a test field for artificial intelligence research. On the one hand Deep Blue's victory was called a "milestone" for AI research, on the other hand, a dead end, since the superiority of the chess computer was based on pure computing power and had nothing to do with "real" AI.The article questions the premises of these different interpretations and maps Deep Blue and its way of playing chess into the history of AI. This also requires an analysis of the underlying concepts of thinking. Finally, the essay calls for assuming different "ways of thinking" for man and computer. Instead of fundamental discussions of concepts of thinking, we should ask about the consequences of the human-machine division of labor.

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.

DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

PubMed

Wachinger, Christian; Reuter, Martin; Klein, Tassilo

2018-04-15

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classification. We propose a 3D patch-based approach, where we do not only predict the center voxel of the patch but also neighbors, which is formulated as multi-task learning. To address a class imbalance problem, we arrange two networks hierarchically, where the first one separates foreground from background, and the second one identifies 25 brain structures on the foreground. Since patches lack spatial context, we augment them with coordinates. To this end, we introduce a novel intrinsic parameterization of the brain volume, formed by eigenfunctions of the Laplace-Beltrami operator. As network architecture, we use three convolutional layers with pooling, batch normalization, and non-linearities, followed by fully connected layers with dropout. The final segmentation is inferred from the probabilistic output of the network with a 3D fully connected conditional random field, which ensures label agreement between close voxels. The roughly 2.7million parameters in the network are learned with stochastic gradient descent. Our results show that DeepNAT compares favorably to state-of-the-art methods. Finally, the purely learning-based method may have a high potential for the adaptation to young, old, or diseased brains by fine-tuning the pre-trained network with a small training sample on the target application, where the availability of larger datasets with manual annotations may boost the overall segmentation accuracy in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Confocal multispot microscope for fast and deep imaging in semicleared tissues

NASA Astrophysics Data System (ADS)

Adam, Marie-Pierre; Müllenbroich, Marie Caroline; Di Giovanna, Antonino Paolo; Alfieri, Domenico; Silvestri, Ludovico; Sacconi, Leonardo; Pavone, Francesco Saverio

2018-02-01

Although perfectly transparent specimens are imaged faster with light-sheet microscopy, less transparent samples are often imaged with two-photon microscopy leveraging its robustness to scattering; however, at the price of increased acquisition times. Clearing methods that are capable of rendering strongly scattering samples such as brain tissue perfectly transparent specimens are often complex, costly, and time intensive, even though for many applications a slightly lower level of tissue transparency is sufficient and easily achieved with simpler and faster methods. Here, we present a microscope type that has been geared toward the imaging of semicleared tissue by combining multispot two-photon excitation with rolling shutter wide-field detection to image deep and fast inside semicleared mouse brain. We present a theoretical and experimental evaluation of the point spread function and contrast as a function of shutter size. Finally, we demonstrate microscope performance in fixed brain slices by imaging dendritic spines up to 400-μm deep.

Solar-wind proton access deep into the near-Moon wake

NASA Astrophysics Data System (ADS)

Nishino, M. N.; Fujimoto, M.; Maezawa, K.; Saito, Y.; Yokota, S.; Asamura, K.; Tanaka, T.; Tsunakawa, H.; Matsushima, M.; Takahashi, F.; Terasawa, T.; Shibuya, H.; Shimizu, H.

2009-08-01

We study solar wind (SW) entry deep into the near-Moon wake using SELENE (KAGUYA) data. It has been known that SW protons flowing around the Moon access the central region of the distant lunar wake, while their intrusion deep into the near-Moon wake has never been expected. We show that SW protons sneak into the deepest lunar wake (anti-subsolar region at ˜100 km altitude), and that the entry yields strong asymmetry of the near-Moon wake environment. Particle trajectory calculations demonstrate that these SW protons are once scattered at the lunar dayside surface, picked-up by the SW motional electric field, and finally sneak into the deepest wake. Our results mean that the SW protons scattered at the lunar dayside surface and coming into the night side region are crucial for plasma environment in the wake, suggesting absorption of ambient SW electrons into the wake to maintain quasi-neutrality.

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

Electric Field Comparison between Microelectrode Recording and Deep Brain Stimulation Systems—A Simulation Study

PubMed Central

Johansson, Johannes; Wårdell, Karin; Hemm, Simone

2018-01-01

The success of deep brain stimulation (DBS) relies primarily on the localization of the implanted electrode. Its final position can be chosen based on the results of intraoperative microelectrode recording (MER) and stimulation tests. The optimal position often differs from the final one selected for chronic stimulation with the DBS electrode. The aim of the study was to investigate, using finite element method (FEM) modeling and simulations, whether lead design, electrical setup, and operating modes induce differences in electric field (EF) distribution and in consequence, the clinical outcome. Finite element models of a MER system and a chronic DBS lead were developed. Simulations of the EF were performed for homogenous and patient-specific brain models to evaluate the influence of grounding (guide tube vs. stimulator case), parallel MER leads, and non-active DBS contacts. Results showed that the EF is deformed depending on the distance between the guide tube and stimulating contact. Several parallel MER leads and the presence of the non-active DBS contacts influence the EF distribution. The DBS EF volume can cover the intraoperatively produced EF, but can also extend to other anatomical areas. In conclusion, EF deformations between stimulation tests and DBS should be taken into consideration as they can alter the clinical outcome. PMID:29415442

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network.

PubMed

Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

2016-02-11

We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods.

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network

PubMed Central

Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

2016-01-01

We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods. PMID:26864172

VizieR Online Data Catalog: Candidate clusters in 4 CFHTLS T0007 Wide fields (Sarron+, 2018)

NASA Astrophysics Data System (ADS)

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

2018-06-01

We have updated the Adami & MAzure Cluster FInder (AMACFI, Mazure et al., 2007A&A...467...49M) and applied it to the CFHTLS final data release T0007 photometric redshift (hereafter photo-z, symbol zphot) catalogues. The original AMACFI algorithm was already applied to the CFHTLS in previous studies: Mazure et al. (2007A&A...467...49M) for the Deep1 field, Adami et al. (2010, Cat. J/A+A/509/A81) for the T0004 data release, and Durret et al. (2011, Cat. J/A+A/535/A65) for the Wide fields of the T0006 data release. (2 data files).

Deep Bore Storage of Nuclear Waste Using MMW (Millimeter Wave) Technology. Full Project Final Report

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

Oglesby, Kenneth D.; Woskov, Paul; Einstein, Herbert

This DOE Nuclear STTR project DE-SC001238 investigated the use of MMW directed energy to form rock melt and steel plugs in deep wellbores to further isolate highly radioactive nuclear waste in ultra-deep basement rocks for long term storage. This current project builds upon a prior DOE project, DE-EE0005504, which developed the basic low power, low 28 GHz frequency waveguide setup, process and instruments. This research adds to our understanding of using MMW power to melt and vaporize rocks and steel/ metals and laid plans for future higher power field prototype testing. This technology also has potential for deep well drillingmore » for nuclear storage, geothermal and oil and gas industries. It also has the potential for simultaneously sealing and securing the wellbore with a thick rock melt liner as the wellbore is drilled, called 'mono-bore drilling'. This allows for higher levels of safety and protection of the environment during deep drilling operations while providing vast cost savings. The larger purpose of this project was to find answers to key questions in developing MMW technology for its many subsurface applications.« less

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.

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.

Discovery of bright z ≃ 7 galaxies in the UltraVISTA survey

NASA Astrophysics Data System (ADS)

Bowler, R. A. A.; Dunlop, J. S.; McLure, R. J.; McCracken, H. J.; Milvang-Jensen, B.; Furusawa, H.; Fynbo, J. P. U.; Le Fèvre, O.; Holt, J.; Ideue, Y.; Ihara, Y.; Rogers, A. B.; Taniguchi, Y.

2012-11-01

We have exploited the new, deep, near-infrared UltraVISTA imaging of the Cosmological Evolution Survey (COSMOS) field, in tandem with deep optical and mid-infrared imaging, to conduct a new search for luminous galaxies at redshifts z ≃ 7. The year-one UltraVISTA data provide contiguous Y, J, H, Ks imaging over 1.5 deg2, reaching a 5σ detection limit of Y + J ≃ 25 (AB mag, 2-arcsec-diameter aperture). The central ≃1 deg2 of this imaging coincides with the final deep optical (u*, g, r, i) data provided by the Canada-France-Hawaii Telescope (CFHT) Legacy Survey and new deep Subaru/Suprime-Cam z'-band imaging obtained specifically to enable full exploitation of UltraVISTA. It also lies within the Hubble Space Telescope (HST) I814 band and Spitzer/Infrared Array Camera imaging obtained as part of the COSMOS survey. We have utilized this unique multiwavelength dataset to select galaxy candidates at redshifts z > 6.5 by searching first for Y + J-detected objects which are undetected in the CFHT and HST optical data. This sample was then refined using a photometric redshift fitting code, enabling the rejection of lower redshift galaxy contaminants and cool galactic M, L, T dwarf stars. The final result of this process is a small sample of (at most) 10 credible galaxy candidates at z > 6.5 (from over 200 000 galaxies detected in the year-one UltraVISTA data) which we present in this paper. The first four of these appear to be robust galaxies at z > 6.5, and fitting to their stacked spectral energy distribution yields zphot = 6.98 ± 0.05 with a stellar mass M* ≃ 5 × 109 M⊙ and rest-frame ultraviolet (UV) spectral slope β ≃ -2.0 ± 0.2 (where fλ ∝ λβ). The next three are also good candidates for z > 6.5 galaxies, but the possibility that they are dwarf stars cannot be completely excluded. Our final subset of three additional candidates is afflicted not only by potential dwarf star contamination, but also contains objects likely to lie at redshifts just below z = 6.5. We show that the three even-brighter z ≳ 7 galaxy candidates reported in the COSMOS field by Capak et al. are in fact all lower redshift galaxies at z ≃ 1.5-3.5. Consequently the new z ≃ 7 galaxies reported here are the first credible z ≃ 7 Lyman-break galaxies discovered in the COSMOS field and, as the most UV luminous discovered to date at these redshifts, are prime targets for deep follow-up spectroscopy. We explore their physical properties, and briefly consider the implications of their inferred number density for the form of the galaxy luminosity function at z ≃ 7.

ESO imaging survey: optical deep public survey

NASA Astrophysics Data System (ADS)

Mignano, A.; Miralles, J.-M.; da Costa, L.; Olsen, L. F.; Prandoni, I.; Arnouts, S.; Benoist, C.; Madejsky, R.; Slijkhuis, R.; Zaggia, S.

2007-02-01

This paper presents new five passbands (UBVRI) optical wide-field imaging data accumulated as part of the DEEP Public Survey (DPS) carried out as a public survey by the ESO Imaging Survey (EIS) project. Out of the 3 square degrees originally proposed, the survey covers 2.75 square degrees, in at least one band (normally R), and 1.00 square degrees in five passbands. The median seeing, as measured in the final stacked images, is 0.97 arcsec, ranging from 0.75 arcsec to 2.0 arcsec. The median limiting magnitudes (AB system, 2´´ aperture, 5σ detection limit) are UAB=25.65, BAB=25.54, VAB=25.18, RAB = 24.8 and IAB =24.12 mag, consistent with those proposed in the original survey design. The paper describes the observations and data reduction using the EIS Data Reduction System and its associated EIS/MVM library. The quality of the individual images were inspected, bad images discarded and the remaining used to produce final image stacks in each passband, from which sources have been extracted. Finally, the scientific quality of these final images and associated catalogs was assessed qualitatively by visual inspection and quantitatively by comparison of statistical measures derived from these data with those of other authors as well as model predictions, and from direct comparison with the results obtained from the reduction of the same dataset using an independent (hands-on) software system. Finally to illustrate one application of this survey, the results of a preliminary effort to identify sub-mJy radio sources are reported. To the limiting magnitude reached in the R and I passbands the success rate ranges from 66 to 81% (depending on the fields). These data are publicly available at CDS. Based on observations carried out at the European Southern Observatory, La Silla, Chile under program Nos. 164.O-0561, 169.A-0725, and 267.A-5729. Appendices A, B and C are only available in electronic form at http://www.aanda.org

Influence of ionization on ultrafast gas-based nonlinear fiber optics.

PubMed

Chang, W; Nazarkin, A; Travers, J C; Nold, J; Hölzer, P; Joly, N Y; Russell, P St J

2011-10-10

We numerically investigate the effect of ionization on ultrashort high-energy pulses propagating in gas-filled kagomé-lattice hollow-core photonic crystal fibers by solving an established uni-directional field equation. We consider the dynamics of two distinct regimes: ionization induced blue-shift and resonant dispersive wave emission in the deep-UV. We illustrate how the system evolves between these regimes and the changing influence of ionization. Finally, we consider the effect of higher ionization stages.

Detection of z~2 Type IIn Supernovae

NASA Astrophysics Data System (ADS)

Cooke, Jeff; Sullivan, Mark; Barton, Elizabeth J.

2009-05-01

Type IIn supernovae (SNe IIn) result from the deaths of massive stars. The broad magnitude distribution of SNe IIn make these some of the most luminous SN events ever recorded. In addition, they are the most luminous SN type in the rest-frame UV which make them ideal targets for wide-field optical high redshift searches. We briefly describe our method to detect z~2 SNe IIn events that involves monitoring color-selected galaxies in deep stacked images and our program that applies this method to the CFHTLS survey. Initial results have detected four compelling photometric candidates from their subtracted images and light curves. SNe IIn spectra exhibit extremely bright narrow emission lines as a result of the interaction between the SN ejecta and the circumstellar material released in pre-explosion outbursts. These emission lines remain bright for years after outburst and are above the thresholds of current 8 m-class telescope sensitivities to z~3. The deep spectroscopy required to confirm z~2 host galaxies has the potential to detect the SN emission lines and measure their energies. Finally, planned deep, wide-field surveys have the capability to detect and confirm SNe IIn to z~6. The emission lines of such high-redshift events are expected to be above the sensitivity of future 30 m-class telescopes and the James Webb Space Telescope.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

PubMed Central

2017-01-01

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson's disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about 0.729 ± 0.16 for decoding movement from the resting state and about 0.671 ± 0.14 for decoding left and right visually cued movements. PMID:29201041

Quantum Simulation of the Quantum Rabi Model in a Trapped Ion

NASA Astrophysics Data System (ADS)

Lv, Dingshun; An, Shuoming; Liu, Zhenyu; Zhang, Jing-Ning; Pedernales, Julen S.; Lamata, Lucas; Solano, Enrique; Kim, Kihwan

2018-04-01

The quantum Rabi model, involving a two-level system and a bosonic field mode, is arguably the simplest and most fundamental model describing quantum light-matter interactions. Historically, due to the restricted parameter regimes of natural light-matter processes, the richness of this model has been elusive in the lab. Here, we experimentally realize a quantum simulation of the quantum Rabi model in a single trapped ion, where the coupling strength between the simulated light mode and atom can be tuned at will. The versatility of the demonstrated quantum simulator enables us to experimentally explore the quantum Rabi model in detail, including a wide range of otherwise unaccessible phenomena, as those happening in the ultrastrong and deep strong-coupling regimes. In this sense, we are able to adiabatically generate the ground state of the quantum Rabi model in the deep strong-coupling regime, where we are able to detect the nontrivial entanglement between the bosonic field mode and the two-level system. Moreover, we observe the breakdown of the rotating-wave approximation when the coupling strength is increased, and the generation of phonon wave packets that bounce back and forth when the coupling reaches the deep strong-coupling regime. Finally, we also measure the energy spectrum of the quantum Rabi model in the ultrastrong-coupling regime.

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.

Deep ultraviolet laser direct write for patterning sol-gel InGaZnO semiconducting micro/nanowires and improving field-effect mobility

PubMed Central

Lin, Hung-Cheng; Stehlin, Fabrice; Soppera, Olivier; Zan, Hsiao-Wen; Li, Chang-Hung; Wieder, Fernand; Ponche, Arnaud; Berling, Dominique; Yeh, Bo-Hung; Wang, Kuan-Hsun

2015-01-01

Deep-UV (DUV) laser was used to directly write indium-gallium-zinc-oxide (IGZO) precursor solution and form micro and nanoscale patterns. The directional DUV laser beam avoids the substrate heating and suppresses the diffraction effect. A IGZO precursor solution was also developed to fulfill the requirements for direct photopatterning and for achieving semi-conducting properties with thermal annealing at moderate temperature. The DUV-induced crosslinking of the starting material allows direct write of semi-conducting channels in thin-film transistors but also it improves the field-effect mobility and surface roughness. Material analysis has been carried out by XPS, FTIR, spectroscopic ellipsometry and AFM and the effect of DUV on the final material structure is discussed. The DUV irradiation step results in photolysis and a partial condensation of the inorganic network that freezes the sol-gel layer in a homogeneous distribution, lowering possibilities of thermally induced reorganization at the atomic scale. Laser irradiation allows high-resolution photopatterning and high-enough field-effect mobility, which enables the easy fabrication of oxide nanowires for applications in solar cell, display, flexible electronics, and biomedical sensors. PMID:26014902

Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

NASA Astrophysics Data System (ADS)

Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

2017-10-01

High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

Nuclear Power Plant Thermocouple Sensor-Fault Detection and Classification Using Deep Learning and Generalized Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.

2017-06-01

In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.

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.

GCR Simulator Development Status at the NASA Space Radiation Laboratory

NASA Technical Reports Server (NTRS)

Slaba, T. C.; Norbury, J. W.; Blattnig, S. R.

2015-01-01

There are large uncertainties connected to the biological response for exposure to galactic cosmic rays (GCR) on long duration deep space missions. In order to reduce the uncertainties and gain understanding about the basic mechanisms through which space radiation initiates cancer and other endpoints, radiobiology experiments are performed with mono-energetic ions beams. Some of the accelerator facilities supporting such experiments have matured to a point where simulating the broad range of particles and energies characteristic of the GCR environment in a single experiment is feasible from a technology, usage, and cost perspective. In this work, several aspects of simulating the GCR environment at the NASA Space Radiation Laboratory (NSRL) are discussed. 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, a reference environment for the GCR simulator and suitable for deep space missions is identified and described in terms of fluence and integrated dosimetric quantities. Analysis results are given to justify the use of a single reference field over a range of shielding conditions and solar activities. Third, an approach for simulating the reference field at NSRL is presented. The approach directly considers the hydrogen and helium energy spectra, and the heavier ions are collectively represented by considering the linear energy transfer (LET) spectrum. While many more aspects of the experimental setup need to be considered before final implementation of the GCR simulator, this preliminary study provides useful information that should aid the final design. Possible drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies.

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.

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

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

The Moon as Possible Calibration Reference for Microwave Radiometers

NASA Astrophysics Data System (ADS)

Burgdorf, Martin; Buehler, Stefan; Hans, Imke; Lang, Theresa; Michel, Simon

2016-04-01

Instruments on satellites for Earth observation on polar orbits usually employ a two-point calibration technique, in which deep space and an on-board calibration target provide two reference flux levels. As the direction of the deep space view is in general close to the celestial equator, the Moon moves sometimes through the field of view and introduces an unwelcome additional signal. One can take advantage of this intrusion, however, by using the Moon as a third flux standard, and this has actually been done for checking the lifetime stability of sensors operating at visible wavelengths. We discuss the advantages and problems of extending this concept to microwaves, concentrating on the frequency of appearances of the Moon in the deep space view, the factors limiting the accuracy of both measurements and models of the Moon's brightness, as well as benefits from complementing the naturally occurring appearances of the Moon with dedicated spacecraft maneuvers. Such pre-planned rotations of the instrument would allow to observe the Moon at a well-defined phase angle and to put it at the exact center of the field of view. This way they would eliminate the need for a model of the Moon's brightness temperature when checking instrumental stability. Finally we investigate the question, whether foreground emission from objects other than the Moon can contaminate the measurements of the Cosmic Microwave Background, which provides the low reference flux in the deep space view. We show that even the brightest discreet sources do not increase significantly the signal from a single scan.

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

NASA Astrophysics Data System (ADS)

Ohlsson, Stellan; Cosejo, David G.

2014-07-01

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 on a single theory for conceptual change, nor has any one theory been decisively falsified. One contributing reason is the difficulty of collecting informative data in this field. We propose that the commonly used methodologies of historical analysis, classroom interventions, and developmental studies, although indispensible, can be supplemented with studies of laboratory models of conceptual change. We introduce re- categorization, an experimental paradigm in which learners transition from one definition of a categorical concept to another, incompatible definition of the same concept, a simple form of conceptual change. We describe a re-categorization experiment, report some descriptive findings pertaining to the effects of category complexity, the temporal unfolding of learning, and the nature of the learner's final knowledge state. We end with a brief discussion of ways in which the re-categorization model can be improved.

Modelling of processes occurring in deep geological repository - Development of new modules in the GoldSim environment

NASA Astrophysics Data System (ADS)

Vopálka, D.; Lukin, D.; Vokál, A.

2006-01-01

Three new modules modelling the processes that occur in a deep geological repository have been prepared in the GoldSim computer code environment (using its Transport Module). These modules help to understand the role of selected parameters in the near-field region of the final repository and to prepare an own complex model of the repository behaviour. The source term module includes radioactive decay and ingrowth in the canister, first order degradation of fuel matrix, solubility limitation of the concentration of the studied nuclides, and diffusive migration through the surrounding bentonite layer controlled by the output boundary condition formulated with respect to the rate of water flow in the rock. The corrosion module describes corrosion of canisters made of carbon steel and transport of corrosion products in the near-field region. This module computes balance equations between dissolving species and species transported by diffusion and/or advection from the surface of a solid material. The diffusion module that includes also non-linear form of the interaction isotherm can be used for an evaluation of small-scale diffusion experiments.

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

PubMed

Duarte, Francisco; Martins, Bruno; Pinto, Cátia Sousa; Silva, Mário J

2018-04-01

We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep neural network that combines word embeddings, recurrent units, and neural attention, for the generation of intermediate representations of the textual contents. The neural network also explores the hierarchical nature of the input data, by building representations from the sequences of words within individual fields, which are then combined according to the sequences of fields that compose the inputs. Moreover, we explore innovative mechanisms for initializing the weights of the final nodes of the network, leveraging co-occurrences between classes together with the hierarchical structure of ICD-10. Experimental results attest to the contribution of the different neural network components. Our best model achieves accuracy scores over 89%, 81%, and 76%, respectively for ICD-10 chapters, blocks, and full-codes. Through examples, we also show that our method can produce interpretable results, useful for public health surveillance. Copyright © 2018 Elsevier Inc. All rights reserved.

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).

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.

Beta-gamma burst stimulations of the inferior olive induce high-frequency oscillations in the deep cerebellar nuclei.

PubMed

Cheron, Julian; Cheron, Guy

2018-02-20

The cerebellum displays various sorts of rhythmic activities covering both low- and high-frequency oscillations. These cerebellar high-frequency oscillations were observed in the cerebellar cortex. Here, we hypothesised that not only is the cerebellar cortex a generator of high-frequency oscillations but also that the deep cerebellar nuclei may also play a similar role. Thus, we analysed local field potentials and single-unit activities in the deep cerebellar nuclei before, during and after electric stimulation in the inferior olive of awake mice. A high-frequency oscillation of 350 Hz triggered by the stimulation of the inferior olive, within the beta-gamma range, was observed in the deep cerebellar nuclei. The amplitude and frequency of the oscillation were independent of the frequency of stimulation. This oscillation emerged during the period of stimulation and persisted after the end of the stimulation. The oscillation coincided with the inhibition of deep cerebellar neurons. As the inhibition of the deep cerebellar nuclei is related to inhibitory inputs from Purkinje cells, we speculate that the oscillation represents the unmasking of the synchronous activation of another subtype of deep cerebellar neuronal subtype, devoid of GABA receptors and under the direct control of the climbing fibres from the inferior olive. Still, the mechanism sustaining this oscillation remains to be deciphered. Our study sheds new light on the role of the olivo-cerebellar loop as the final output control of the intercerebellar circuitry. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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.

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.;

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.

Determination of Process Parameters in Multi-Stage Hydro-Mechanical Deep Drawing by FE Simulation

NASA Astrophysics Data System (ADS)

Kumar, D. Ravi; Manohar, M.

2017-09-01

In this work, analysis has been carried to simulate manufacturing of a near hemispherical bottom part with large depth by hydro-mechanical deep drawing with an aim to reduce the number of forming steps and to reduce the extent of thinning in the dome region. Inconel 718 has been considered as the material due to its importance in aerospace industry. It is a Ni-based super alloy and it is one of the most widely used of all super alloys primarily due to large-scale applications in aircraft engines. Using Finite Element Method (FEM), numerical simulations have been carried out for multi-stage hydro-mechanical deep drawing by using the same draw ratios and design parameters as in the case of conventional deep drawing in four stages. The results showed that the minimum thickness in the final part can be increased significantly when compared to conventional deep drawing. It has been found that the part could be deep drawn to the desired height (after trimming at the final stage) without any severe wrinkling. Blank holding force (BHF) and peak counter pressure have been found to have a strong influence on thinning in the component. Decreasing the coefficient of friction has marginally increased the minimum thickness in the final component. By increasing the draw ratio and optimizing BHF, counter pressure and die corner radius in the simulations, it has been found that it is possible to draw the final part in three stages. It has been found that thinning can be further reduced by decreasing the initial blank size without any reduction in the final height. This reduced the draw ratio at every stage and optimum combination of BHF and counter pressure have been found for the 3-stage process also.

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.;

77 FR 35850 - Safety Zone; F/V Deep Sea, Penn Cove, WA

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-15

... 1625-AA00 Safety Zone; F/V Deep Sea, Penn Cove, WA AGENCY: Coast Guard, DHS. ACTION: Temporary final rule. SUMMARY: The Coast Guard is establishing a safety zone around the Fishing Vessel (F/V) Deep Sea... with the sunken F/V Deep Sea. B. Basis and Purpose On the evening of May 13, 2012, the F/V Deep Sea...

On the controls of deep convection and lightning in the Amazon

NASA Astrophysics Data System (ADS)

Albrecht, R. I.; Giangrande, S. E.; Wang, D.; Morales, C. A.; Pereira, R. F. O.; Machado, L.; Silva Dias, M. A. F.

2017-12-01

Local observations and remote sensing have been extensively used to unravel cloud distribution and life cycle but yet their representativeness in cloud resolve models (CRMs) and global climate models (GCMs) are still very poor. In addition, the complex cloud-aerosol-precipitation interactions (CAPI), as well as thermodynamics, dynamics and large scale controls on convection have been the focus of many studies in the last two decades but still no final answer has been reached on the overall impacts of these interactions and controls on clouds, especially on deep convection. To understand the environmental and CAPI controls of deep convection, cloud electrification and lightning activity in the pristine region of Amazon basin, in this study we use long term satellite and field campaign measurements to depict the characteristics of deep convection and the relationships between lightning and convective fluxes in this region. Precipitation and lightning activity from the Tropical Rainfall Measuring Mission (TRMM) satellite are combined with estimates of aerosol concentrations and reanalysis data to delineate the overall controls on thunderstorms. A more detailed analysis is obtained studying these controls on the relationship between lightning activity and convective mass fluxes using radar wind profiler and 3D total lightning during GoAmazon 2014/15 field campaign. We find evidences that the large scale conditions control the distribution of the precipitation, with widespread and more frequent mass fluxes of moderate intensity during the wet season, resulting in less vigorous convection and lower lightning activity. Under higher convective available potential energy, lightning is enhanced in polluted and background aerosol conditions. The relationships found in this study can be used in model parameterizations and ensemble evaluations of both lightning activity and lightning NOx from seasonal forecasting to climate projections and in a broader sense to Earth Climate System Modeling.

NASA Habitat Demonstration Unit (HDU) Deep Space Habitat Analog

NASA Technical Reports Server (NTRS)

Howe, A. Scott; Kennedy, Kriss J.; Gill, Tracy

2013-01-01

The NASA Habitat Demonstration Unit (HDU) vertical cylinder habitat was established as a exploration habitat testbed platform for integration and testing of a variety of technologies and subsystems that will be required in a human-occupied planetary surface outpost or Deep Space Habitat (DSH). The HDU functioned as a medium-fidelity habitat prototype from 2010-2012 and allowed teams from all over NASA to collaborate on field analog missions, mission operations tests, and system integration tests to help shake out equipment and provide feedback for technology development cycles and crew training. This paper documents the final 2012 configuration of the HDU, and discusses some of the testing that took place. Though much of the higher-fidelity functionality has 'graduated' into other NASA programs, as of this writing the HDU, renamed Human Exploration Research Analog (HERA), will continue to be available as a volumetric and operational mockup for NASA Human Research Program (HRP) research from 2013 onward.

Unsupervised Feature Learning for Heart Sounds Classification Using Autoencoder

NASA Astrophysics Data System (ADS)

Hu, Wei; Lv, Jiancheng; Liu, Dongbo; Chen, Yao

2018-04-01

Cardiovascular disease seriously threatens the health of many people. It is usually diagnosed during cardiac auscultation, which is a fast and efficient method of cardiovascular disease diagnosis. In recent years, deep learning approach using unsupervised learning has made significant breakthroughs in many fields. However, to our knowledge, deep learning has not yet been used for heart sound classification. In this paper, we first use the average Shannon energy to extract the envelope of the heart sounds, then find the highest point of S1 to extract the cardiac cycle. We convert the time-domain signals of the cardiac cycle into spectrograms and apply principal component analysis whitening to reduce the dimensionality of the spectrogram. Finally, we apply a two-layer autoencoder to extract the features of the spectrogram. The experimental results demonstrate that the features from the autoencoder are suitable for heart sound classification.

Single- and dual-carrier microwave noise abatement in the deep space network. [microwave antennas

NASA Technical Reports Server (NTRS)

Bathker, D. A.; Brown, D. W.; Petty, S. M.

1975-01-01

The NASA/JPL Deep Space Network (DSN) microwave ground antenna systems are presented which simultaneously uplink very high power S-band signals while receiving very low level S- and X-band downlinks. Tertiary mechanisms associated with elements give rise to self-interference in the forms of broadband noise burst and coherent intermodulation products. A long-term program to reduce or eliminate both forms of interference is described in detail. Two DSN antennas were subjected to extensive interference testing and practical cleanup program; the initial performance, modification details, and final performance achieved at several planned stages are discussed. Test equipment and field procedures found useful in locating interference sources are discussed. Practices deemed necessary for interference-free operations in the DSN are described. Much of the specific information given is expected to be easily generalized for application in a variety of similar installations. Recommendations for future investigations and individual element design are given.

Jetted tidal disruptions of stars as a flag of intermediate mass black holes at high redshifts

NASA Astrophysics Data System (ADS)

Fialkov, Anastasia; Loeb, Abraham

2017-11-01

Tidal disruption events (TDEs) of stars by single or binary supermassive black holes (SMBHs) brighten galactic nuclei and reveal a population of otherwise dormant black holes. Adopting event rates from the literature, we aim to establish general trends in the redshift evolution of the TDE number counts and their observable signals. We pay particular attention to (I) jetted TDEs whose luminosity is boosted by relativistic beaming and (II) TDEs around binary black holes. We show that the brightest (jetted) TDEs are expected to be produced by massive black hole binaries if the occupancy of intermediate mass black holes (IMBHs) in low-mass galaxies is high. The same binary population will also provide gravitational wave sources for the evolved Laser Interferometer Space Antenna. In addition, we find that the shape of the X-ray luminosity function of TDEs strongly depends on the occupancy of IMBHs and could be used to constrain scenarios of SMBH formation. Finally, we make predictions for the expected number of TDEs observed by future X-ray telescopes finding that a 50 times more sensitive instrument than the Burst Alert Telescope (BAT) on board the Swift satellite is expected to trigger ˜10 times more events than BAT, while 6-20 TDEs are expected in each deep field observed by a telescope 50 times more sensitive than the Chandra X-ray Observatory if the occupation fraction of IMBHs is high. Because of their long decay times, high-redshift TDEs can be mistaken for fixed point sources in deep field surveys and targeted observations of the same deep field with year-long intervals could reveal TDEs.

Deep neuromuscular blockade improves surgical conditions during low-pressure pneumoperitoneum laparoscopic donor nephrectomy.

PubMed

Özdemir-van Brunschot, D M D; Braat, A E; van der Jagt, M F P; Scheffer, G J; Martini, C H; Langenhuijsen, J F; Dam, R E; Huurman, V A; Lam, D; d'Ancona, F C; Dahan, A; Warlé, M C

2018-01-01

Evidence indicates that low-pressure pneumoperitoneum (PNP) reduces postoperative pain and analgesic consumption. A lower insufflation pressure may hamper visibility and working space. The aim of the study is to investigate whether deep neuromuscular blockade (NMB) improves surgical conditions during low-pressure PNP. This study was a blinded randomized controlled multicenter trial. 34 kidney donors scheduled for laparoscopic donor nephrectomy randomly received low-pressure PNP (6 mmHg) with either deep (PTC 1-5) or moderate NMB (TOF 0-1). In case of insufficient surgical conditions, the insufflation pressure was increased stepwise. Surgical conditions were rated by the Leiden-Surgical Rating Scale (L-SRS) ranging from 1 (extremely poor) to 5 (optimal). Mean surgical conditions were significantly better for patients allocated to a deep NMB (SRS 4.5 versus 4.0; p < 0.01). The final insufflation pressure was 7.7 mmHg in patients with deep NMB as compared to 9.1 mmHg with moderate NMB (p = 0.19). The cumulative opiate consumption during the first 48 h was significantly lower in patients receiving deep NMB, while postoperative pain scores were similar. In four patients allocated to a moderate NMB, a significant intraoperative complication occurred, and in two of these patients a conversion to an open procedure was required. Our data show that deep NMB facilitates the use of low-pressure PNP during laparoscopic donor nephrectomy by improving the quality of the surgical field. The relatively high incidence of intraoperative complications indicates that the use of low pressure with moderate NMB may compromise safety during LDN. Clinicaltrials.gov identifier: NCT 02602964.

75 FR 27219 - Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-14

.... 100105009-0167-02] RIN 0648-AY51 Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic Deep-Sea Red Crab Specifications AGENCY: National Marine Fisheries Service (NMFS... final specifications for the 2010 Atlantic deep- sea red crab fishery, including a target total...

Deep-sea coral research and technology program: Alaska deep-sea coral and sponge initiative final report

USGS Publications Warehouse

Rooper, Chris; Stone, Robert P.; Etnoyer, Peter; Conrath, Christina; Reynolds, Jennifer; Greene, H. Gary; Williams, Branwen; Salgado, Enrique; Morrison, Cheryl L.; Waller, Rhian G.; Demopoulos, Amanda W.J.

2017-01-01

Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska’s marine waters. In some places, such as the central and western Aleutian Islands, deep-sea coral and sponge resources can be extremely diverse and may rank among the most abundant deep-sea coral and sponge communities in the world. Many different species of fishes and invertebrates are associated with deep-sea coral and sponge communities in Alaska. Because of their biology, these benthic invertebrates are potentially impacted by climate change and ocean acidification. Deepsea coral and sponge ecosystems are also vulnerable to the effects of commercial fishing activities. Because of the size and scope of Alaska’s continental shelf and slope, the vast majority of the area has not been visually surveyed for deep-sea corals and sponges. NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) sponsored a field research program in the Alaska region between 2012–2015, referred to hereafter as the Alaska Initiative. The priorities for Alaska were derived from ongoing data needs and objectives identified by the DSCRTP, the North Pacific Fishery Management Council (NPFMC), and Essential Fish Habitat-Environmental Impact Statement (EFH-EIS) process.This report presents the results of 15 projects conducted using DSCRTP funds from 2012-2015. Three of the projects conducted as part of the Alaska deep-sea coral and sponge initiative included dedicated at-sea cruises and fieldwork spread across multiple years. These projects were the eastern Gulf of Alaska Primnoa pacifica study, the Aleutian Islands mapping study, and the Gulf of Alaska fish productivity study. In all, there were nine separate research cruises carried out with a total of 109 at-sea days conducting research. The remaining projects either used data and samples collected by the three major fieldwork projects or were piggy-backed onto existing research programs at the Alaska Fisheries Science Center (AFSC).

A New Theory of Mix in Omega Capsule Implosions

NASA Astrophysics Data System (ADS)

Knoll, Dana; Chacon, Luis; Rauenzahn, Rick; Simakov, Andrei; Taitano, William; Welser-Sherrill, Leslie

2014-10-01

We put forth a new mix model that relies on the development of a charge-separation electrostatic double-layer at the fuel-pusher interface early in the implosion of an Omega plastic ablator capsule. The model predicts a sizable pusher mix (several atom %) into the fuel. The expected magnitude of the double-layer field is consistent with recent radial electric field measurements in Omega plastic ablator implosions. Our theory relies on two distinct physics mechanisms. First, and prior to shock breakout, the formation of a double layer at the fuel-pusher interface due to fast preheat-driven ionization. The double-layer electric field structure accelerates pusher ions fairly deep into the fuel. Second, after the double-layer mix has occurred, the inward-directed fuel velocity and temperature gradients behind the converging shock transports these pusher ions inward. We first discuss the foundations of this new mix theory. Next, we discuss our interpretation of the radial electric field measurements on Omega implosions. Then we discuss the second mechanism that is responsible for transporting the pusher material, already mixed via the double-layer deep into the fuel, on the shock convergence time scale. Finally we make a connection to recent mix motivated experimental data on. This work conducted under the auspices of the National Nuclear Security Administration of the U.S. Department of Energy at Los Alamos National Laboratory, managed by LANS, LLC under Contract DE-AC52-06NA25396.

Geophysical prospecting for the deep geothermal structure of the Zhangzhou basin, Southeast China

NASA Astrophysics Data System (ADS)

Wu, Chaofeng; Liu, Shuang; Hu, Xiangyun; Wang, Guiling; Lin, Wenjing

2017-04-01

Zhangzhou basin located at the Southeast margins of Asian plate is one of the largest geothermal fields in Fujian province, Southeast China. High-temperature natural springs and granite rocks are widely distributed in this region and the causes of geothermal are speculated to be involved the large number of magmatic activities from Jurassic to Cretaceous periods. To investigate the deep structure of Zhangzhou basin, magnetotelluric and gravity measurements were carried out and the joint inversion of magnetotelluric and gravity data delineated the faults and the granites distributions. The inversion results also indicated the backgrounds of heat reservoirs, heat fluid paths and whole geothermal system of the Zhangzhou basin. Combining with the surface geological investigation, the geophysical inversion results revealed that the faults activities and magma intrusions are the main reasons for the formation of geothermal resources of the Zhangzhou basin. Upwelling mantle provides enormous heats to the lower crust leading to metamorphic rocks to be partially melt generating voluminous magmas. Then the magmas migration and thermal convection along the faults warm up the upper crust. So finally, the cap rocks, basements and major faults are the three favorable conditions for the formation of geothermal fields of the Zhangzhou basin.

New insights on intraplate volcanism in French Polynesia from wavelet analysis of GRACE, CHAMP, and sea surface data

NASA Astrophysics Data System (ADS)

Panet, I.; Chambodut, A.; Diament, M.; Holschneider, M.; Jamet, O.

2006-09-01

In this paper, we discuss the origin of superswell volcanism on the basis of representation and analysis of recent gravity and magnetic satellite data with wavelets in spherical geometry. We computed a refined gravity field in the south central Pacific based on the GRACE satellite GGM02S global gravity field and the KMS02 altimetric grid, and a magnetic anomaly field based on CHAMP data. The magnetic anomalies are marked by the magnetic lineation of the seafloor spreading and by a strong anomaly in the Tuamotu region, which we interpret as evidence for crustal thickening. We interpret our gravity field through a continuous wavelet analysis that allows to get a first idea of the internal density distribution. We also compute the continuous wavelet analysis of the bathymetric contribution to discriminate between deep and superficial sources. According to the gravity signature of the different chains as revealed by our analysis, various processes are at the origin of the volcanism in French Polynesia. As evidence, we show a large-scale anomaly over the Society Islands that we interpret as the gravity signature of a deeply anchored mantle plume. The gravity signature of the Cook-Austral chain indicates a complex origin which may involve deep processes. Finally, we discuss the particular location of the Marquesas chain as suggesting that the origin of the volcanism may interfere with secondary convection rolls or may be controlled by lithospheric weakness due to the regional stress field, or else related to the presence of the nearby Tuamotu plateau.

Tracing the Mass-Dependent Star Formation History of Late-Type Galaxies using X-ray Emission: Results from the CHANDRA Deep Fields

NASA Technical Reports Server (NTRS)

Lehmer, B.D; Brandt, W.N.; Schneider, D.P.; Steffen, A.T.; Alexander, D.M.; Bell, E.F.; Hornschemeier, A.E.; McIntosh, D.H.; Bauer, F.E.; Gilli, R.;

An adaptive deep Q-learning strategy for handwritten digit recognition.

PubMed

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Prediction of Tissue Outcome and Assessment of Treatment Effect in Acute Ischemic Stroke Using Deep Learning.

PubMed

Nielsen, Anne; Hansen, Mikkel Bo; Tietze, Anna; Mouridsen, Kim

2018-06-01

Treatment options for patients with acute ischemic stroke depend on the volume of salvageable tissue. This volume assessment is currently based on fixed thresholds and single imagine modalities, limiting accuracy. We wish to develop and validate a predictive model capable of automatically identifying and combining acute imaging features to accurately predict final lesion volume. Using acute magnetic resonance imaging, we developed and trained a deep convolutional neural network (CNN deep ) to predict final imaging outcome. A total of 222 patients were included, of which 187 were treated with rtPA (recombinant tissue-type plasminogen activator). The performance of CNN deep was compared with a shallow CNN based on the perfusion-weighted imaging biomarker Tmax (CNN Tmax ), a shallow CNN based on a combination of 9 different biomarkers (CNN shallow ), a generalized linear model, and thresholding of the diffusion-weighted imaging biomarker apparent diffusion coefficient (ADC) at 600×10 -6 mm 2 /s (ADC thres ). To assess whether CNN deep is capable of differentiating outcomes of ±intravenous rtPA, patients not receiving intravenous rtPA were included to train CNN deep, -rtpa to access a treatment effect. The networks' performances were evaluated using visual inspection, area under the receiver operating characteristic curve (AUC), and contrast. CNN deep yields significantly better performance in predicting final outcome (AUC=0.88±0.12) than generalized linear model (AUC=0.78±0.12; P =0.005), CNN Tmax (AUC=0.72±0.14; P <0.003), and ADC thres (AUC=0.66±0.13; P <0.0001) and a substantially better performance than CNN shallow (AUC=0.85±0.11; P =0.063). Measured by contrast, CNN deep improves the predictions significantly, showing superiority to all other methods ( P ≤0.003). CNN deep also seems to be able to differentiate outcomes based on treatment strategy with the volume of final infarct being significantly different ( P =0.048). The considerable prediction improvement accuracy over current state of the art increases the potential for automated decision support in providing recommendations for personalized treatment plans. © 2018 American Heart Association, Inc.

Nonperturbative interpretation of the Bloch vector's path beyond the rotating-wave approximation

NASA Astrophysics Data System (ADS)

Benenti, Giuliano; Siccardi, Stefano; Strini, Giuliano

2013-09-01

The Bloch vector's path of a two-level system exposed to a monochromatic field exhibits, in the regime of strong coupling, complex corkscrew trajectories. By considering the infinitesimal evolution of the two-level system when the field is treated as a classical object, we show that the Bloch vector's rotation speed oscillates between zero and twice the rotation speed predicted by the rotating wave approximation. Cusps appear when the rotation speed vanishes. We prove analytically that in correspondence to cusps the curvature of the Bloch vector's path diverges. On the other hand, numerical data show that the curvature is very large even for a quantum field in the deep quantum regime with mean number of photons n¯≲1. We finally compute numerically the typical error size in a quantum gate when the terms beyond rotating wave approximation are neglected.

[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

Photometric Metallicities of the Small and Large Magellanic Clouds

NASA Astrophysics Data System (ADS)

Miller, Amy Elizabeth

2018-06-01

In the field of astronomy, the study of galaxies is vitally important to understanding the structure and evolution of the universe. Within the study of galaxies, of particular interest are the Small and Large Magellanic Clouds (SMC and LMC, respectively), two of the Milky Way’s closest and most massive satellite galaxies. Their close proximity make them ideal candidates for understanding astrophysical processes such as galaxy interactions. In order to fully understand the Magellanic Clouds, it is imperative that the metallicity of the clouds be mapped in detail. In order to accomplish this task, I will use data from the Survey of Magellanic Stellar History (SMASH) which is a deep, multi-band (ugriz) photometric survey of the Magellanic Clouds that contains approximately 400 million objects in 197 fully-calibrated fields. SMASH is an extensive and deep photometric data set that enables the full-scale study of the galactic structure in the Clouds. The SMASH u-band is sensitive to metallicity for main-sequence turn-off stars which we calibrate using SDSS spectroscopy in overlapping regions (mainly standard star fields). The final steps will be to make metallicity maps of the main bodies and peripheries of the LMC and SMC. Ultimately, these metallicity maps will help us trace out population gradients in the Clouds and uncover the origin of their very extended stellar peripheries.

Measurement of the hadronic final state in deep inelastic scattering at HERA

NASA Astrophysics Data System (ADS)

Ahmed, T.; Andreev, V.; Andrieu, B.; Arpagaus, M.; Babaev, A.; Bärwolff, H.; Bán, J.; Baranov, P.; Barrelet, E.; Bartel, W.; Bassler, U.; Beck, G. A.; Beck, H. P.; Behrend, H.-J.; Belousov, A.; Berger, Ch.; Bergstein, H.; Bernardi, G.; Bernet, R.; Berthon, U.; Bertrand-Coremans, G.; Besançon, M.; Biddulph, P.; Binder, E.; Bizot, J. C.; Blobel, V.; Borras, K.; Bosetti, P. C.; Boudry, V.; Bourdarios, C.; Brasse, F.; Braun, U.; Braunschweig, W.; Brisson, V.; Bruncko, D.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Buschhorn, G.; Campbell, A. J.; Carli, T.; Charles, F.; Clarke, D.; Clegg, A. B.; Colombo, M.; Coughlan, J. A.; Courau, A.; Coutures, Ch.; Cozzika, G.; Criegee, L.; Cvach, J.; Dainton, J. B.; Danilov, M.; Dann, A. W. E.; Dau, W. D.; David, M.; Deffur, E.; Delcourt, B.; Del Buono, L.; Devel, M.; De Roeck, A.; Dingus, P.; Dollfus, C.; Dowell, J. D.; Dreis, H. B.; Drescher, A.; Duboc, J.; Düllmann, D.; Dünger, O.; Duhm, H.; Eberle, M.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichenberger, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Ellis, N. N.; Ellison, R. J.; Elsen, E.; Erdmann, M.; Evrard, E.; Favart, L.; Fedotov, A.; Feeken, D.; Felst, R.; Feltesse, J.; Feng, Y.; Fensome, I. F.; Ferencei, J.; Ferrarotto, F.; Flauger, W.; Fleischer, M.; Flower, P. S.; Flügge, G.; Fomenko, A.; Fominykh, B.; Forbush, M.; Formánek, J.; Foster, J. M.; Franke, G.; Fretwurst, E.; Fuhrmann, P.; Gabathuler, E.; Gamerdinger, K.; Garvey, J.; Gayler, J.; Gellrich, A.; Gennis, M.; Gensch, U.; Genzel, H.; Gerhards, R.; Gillespie, D.; Godfrey, L.; Goerlach, U.; Goerlich, L.; Goldberg, M.; Goodall, A. M.; Gorelov, I.; Goritchev, P.; Grab, C.; Grässler, H.; Grässler, R.; Greenshaw, T.; Greif, H.; Grindhammer, G.; Gruber, C.; Haack, J.; Haidt, D.; Hajduk, L.; Hamon, O.; Handschuh, D.; Hanlon, E. M.; Hapke, M.; Haries, J.; Hartz, P.; Haydar, R.; Haynes, W. J.; Heatherington, J.; Hedberg, V.; Hedgecock, R.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Herma, R.; Herynek, I.; Hildesheim, W.; Hill, P.; Hilton, C. D.; Hladký, J.; Hoeger, K. C.; Huet, Ph.; Hufnagel, H.; Huot, N.; Ibbotson, M.; Jabiol, M. A.; Jacholkowska, A.; Jacobsson, C.; Jaffre, M.; Jöhnsson, L.; Johannsen, K.; Johnson, D. P.; Johnson, L.; Jung, H.; Kalmus, P. I. P.; Kasarian, S.; Kaschowitz, R.; Kasselmann, P.; Kathage, U.; Kaufmann, H. H.; Kenyon, I. R.; Kermiche, S.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Köhler, T.; Kolanoski, H.; Kole, F.; Kolya, S. D.; Korbel, V.; Korn, M.; Kostka, P.; Kotelnikov, S. K.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Krüger, U.; Kubenka, J. P.; Küster, H.; Kuhlen, M.; Kurça, T.; Kurzhöfer, J.; Kuznik, B.; Lander, R.; London, M. P. J.; Langkau, R.; Lanius, P.; Laporte, J. F.; Lebedev, A.; Lebedev, A.; Leuschner, A.; Leverenz, C.; Levin, D.; Levonian, S.; Ley, Ch.; Lindner, A.; Lindström, G.; Loch, P.; Lohmander, H.; Lopez, G. C.; Lüers, D.; Magnussen, N.; Malinovski, E.; Mani, S.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, R.; Martyn, H.-U.; Martyniak, J.; Masson, S.; Mavroidis, A.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Merz, T.; Meyer, C. A.; Meyer, H.; Meyer, J.; Mikocki, S.; Milone, V.; Monnier, E.; Moreau, F.; Moreels, J.; Morris, J. V.; Morton, J. M.; Müller, K.; Murín, P.; Murray, S. A.; Nagovizin, V.; Naroska, B.; Naumann, Th.; Newton, D.; Nguyen, H. K.; Niebergall, F.; Nisius, R.; Nowak, G.; Noyes, G. W.; Nyberg, M.; Oberlack, H.; Obrock, U.; Olsson, J. E.; Orenstein, S.; Ould-Saada, F.; Pascaud, C.; Patel, G. D.; Peppel, E.; Peters, S.; Phillips, H. T.; Phillips, J. P.; Pichler, Ch.; Pilgram, W.; Pitzl, D.; Prosi, R.; Raupach, F.; Rauschnabel, K.; Reimer, P.; Ribarics, P.; Riech, V.; Riedlberger, J.; Rietz, M.; Robertson, S. M.; Robmann, P.; Roosen, R.; Rostovtsev, A.; Royon, C.; Rudowicz, M.; Ruffer, M.; Rusakov, S.; Rybicki, K.; Ryseck, E.; Sacton, J.; Sahlmann, N.; Sanchez, E.; Sankey, D. P. C.; Savitsky, M.; Schacht, P.; Schleper, P.; von Schlippe, W.; Schmidt, C.; Schmidt, D.; Schmitz, W.; Schröder, V.; Schulz, M.; Schwind, A.; Scobel, W.; Seehausen, U.; Sell, R.; Seman, M.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shooshtari, H.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Smirnov, P.; Smith, J. R.; Smolik, L.; Soloviev, Y.; Spitzer, H.; Staroba, P.; Steenbock, M.; Steffen, P.; Steinberg, R.; Steiner, H.; Stella, B.; Stephens, K.; Stier, J.; Strachota, J.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Taylor, R. E.; Thompson, G.; Thompson, R. J.; Tichomirov, I.; Trenkel, C.; Truöl, P.; Tchernyshov, V.; Turnau, J.; Tutas, J.; Urban, L.; Usik, A.; Valkar, S.; Valkarova, A.; Vallee, C.; Van Esch, P.; Vartapetian, A.; Vazdik, Y.; Vecko, M.; Verrecchia, P.; Vick, R.; Villet, G.; Vogel, E.; Wacker, K.; Walker, I. W.; Walther, A.; Weber, G.; Wegener, D.; Wegner, A.; Wellisch, H. P.; Willard, S.; Winde, M.; Winter, G.-G.; Wolff, Th.; Womersley, L. A.; Wright, A. E.; Wulff, N.; Yiou, T. P.; Ząçek, J.; Závada, P.; Zeitnitz, C.; Ziaeepour, H.; Zimmer, M.; Zimmermann, W.; Zomer, F.; H1 Collaboration

1993-01-01

We report on the first experimental study of the hadronic final state in deep inelastic electron-proton scattering with the H1 detector at HERA. Energy flow and transverse momentum characteristics are measured and presented both in the laboratory and in the hadronic center of mass frames. Comparison is made with QCD models distinguished by their different treatment of parton emission.

Compact acoustic levitation device for studies in fluid dynamics and material science in the laboratory and microgravity

NASA Technical Reports Server (NTRS)

Trinh, E. H.

1985-01-01

An ultrasonic levitation device operable in both ordinary ground-based as well as in potential space-borne laboratories is described together with its various applications in the fields of fluid dynamics, material science, and light scattering. Some of the phenomena which can be studied by this instrument include surface waves on freely suspended liquids, the variations of the surface tension with temperature and contamination, the deep undercooling of materials with the temperature variations of their density and viscosity, and finally some of the optical diffraction properties of transparent substances.

Deep level defects in semiconductors. Final technical report 1 Jul 78-30 Jun 80

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

Sundaram, S.; Sharma, R.R.

1980-07-01

Using Racah's irreducible tensor operator formalism, a generalized and more refined treatment of the d-electron matrices for transition metal defects in crystals has been given. The resulting Coulomb and exchange interaction matrices have been used to calculate the electronic structures of GaAs:(2+)Cr(2+) and GaAs:Cr(3+) and interpret the optical data on MgF2:Co(2+) and MgF2:Mn(2+). The significance of the new theory is explained. From the photoluminescence and optical absorption data, the crystal field parameters have been derived.

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.

Simulating Radionuclide Migrations of Low-level Wastes in Nearshore Environment

NASA Astrophysics Data System (ADS)

Lu, C. C.; Li, M. H.; Chen, J. S.; Yeh, G. T.

2016-12-01

Tunnel disposal into nearshore mountains was tentatively selected as one of final disposal sites for low-level wastes in Taiwan. Safety assessment on radionuclide migrations in far-filed may involve geosphere processes under coastal environments and into nearshore ocean. In this study the 3-D HYDROFEOCHE5.6 numerical model was used to perform simulations of groundwater flow and radionuclide transport with decay chains. Domain of interest on the surface includes nearby watersheds delineated by digital elevation models and nearshore seabed. As deep as 800 m below the surface and 400 m below sea bed were considered for simulations. The disposal site was located at 200m below the surface. Release rates of radionuclides from near-field was estimated by analytical solutions of radionuclide diffusion with decay out of engineered barriers. Far-field safety assessments were performed starting from the release of radionuclides out of engineered barriers to a time scale of 10,000 years. Sensitivity analyses of geosphere and transport parameters were performed to improve our understanding of safety on final disposal of low-level waste in nearshore environments.

Reference field specification and preliminary beam selection strategy for accelerator-based GCR simulation

NASA Astrophysics Data System (ADS)

Slaba, Tony C.; Blattnig, Steve R.; Norbury, John W.; Rusek, Adam; La Tessa, Chiara

2016-02-01

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 and possible biological considerations. 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, a preliminary approach for selecting beams at NSRL to simulate the designated reference field is presented. This approach is not a final design for the GCR simulator, but rather a single step within a broader design strategy. It is shown that the beam selection methodology is tied directly to the reference environment, allows facility constraints to be incorporated, and may be adjusted to account for additional constraints imposed by biological or animal care considerations. The major biology questions are not addressed herein but are discussed in a companion paper published in the present issue of this journal. Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies.

Monitoring controlled graves representing common burial scenarios with ground penetrating radar

NASA Astrophysics Data System (ADS)

Schultz, John J.; Martin, Michael M.

2012-08-01

Implementing controlled geophysical research is imperative to understand the variables affecting detection of clandestine graves during real-life forensic searches. This study focused on monitoring two empty control graves (shallow and deep) and six burials containing a small pig carcass (Sus scrofa) representing different burial forensic scenarios: a shallow buried naked carcass, a deep buried naked carcass, a deep buried carcass covered by a layer of rocks, a deep buried carcass covered by a layer of lime, a deep buried carcass wrapped in an impermeable tarpaulin and a deep buried carcass wrapped in a cotton blanket. Multi-frequency, ground penetrating radar (GPR) data were collected monthly over a 12-month monitoring period. The research site was a cleared field within a wooded area in a humid subtropical environment, and the soil consisted of a Spodosol, a common soil type in Florida. This study compared 2D GPR reflection profiles and horizontal time slices obtained with both 250 and 500 MHz dominant frequency antennae to determine the utility of both antennae for grave detection in this environment over time. Overall, a combination of both antennae frequencies provided optimal detection of the targets. Better images were noted for deep graves, compared to shallow graves. The 250 MHz antenna provided better images for detecting deep graves, as less non-target anomalies were produced with lower radar frequencies. The 250 MHz antenna also provided better images detecting the disturbed ground. Conversely, the 500 MHz antenna provided better images when detecting the shallow pig grave. The graves that contained a pig carcass with associated grave items provided the best results, particularly the carcass covered with rocks and the carcass wrapped in a tarpaulin. Finally, during periods of increased soil moisture levels, there was increased detection of graves that was most likely related to conductive decompositional fluid from the carcasses.

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.

Parallel Radiofrequency Transmission for the Reduction of Heating in Deep Brain Stimulation Leads at 3T

NASA Astrophysics Data System (ADS)

McElcheran, Clare

Deep Brain Stimulation (DBS) is increasingly used to treat a variety of brain diseases by sending electrical impulses to deep brain nuclei through long, electrically conductive leads. Magnetic resonance imaging (MRI) of patients pre- and post-implantation is desirable to target and position the implant, to evaluate possible side-effects and to examine DBS patients who have other health conditions. Although MRI is the preferred modality for pre-operative planning, MRI post-implantation is limited due to the risk of high local power deposition, and therefore tissue heating, at the tip of the lead. The localized power deposition arises from currents induced in the leads caused by coupling with the radiofrequency (RF) transmission field during imaging. In this thesis, parallel RF transmission (pTx) is used to tailor the RF electric field to suppress coupling effects. Three pTx coil configurations with 2-elements, 4-elements, and 8-elements, respectively, were investigated. Optimal input voltages to minimize coupling, while maintaining RF magnetic field homogeneity, were determined using a Nelder-Mead optimization algorithm. Resulting electric and magnetic fields were compared to that of a 16-rung birdcage coil. Experimental validation was performed with a custom-built 4-element pTx coil. Three cases were investigated to develop and evaluate this technique. First, a Proof-of-Concept study was performed to investigate the case of a simple, uniform cylindrical phantom with a straight, perfectly conducting wire. Second, a heterogeneous subject with bilateral, curved implanted wires was investigated. Finally, the third case investigated realistic patient lead-trajectories obtained from intra-operative CT scans. In all three cases, specific absorption rate (SAR), a metric used to quantify power deposition which results in heating, was reduced by over 90%. Maximal reduction in SAR was obtained with the 8-element pTx coil. Magnetic field homogeneity was comparable to the birdcage coil for the 4- and 8-element pTx configurations. Although further research is required before clinical implementation, these initial results suggest that the concept of optimizing pTx to reduce DBS heating effects holds considerable promise.

A PUBLIC, K-SELECTED, OPTICAL-TO-NEAR-INFRARED CATALOG OF THE EXTENDED CHANDRA DEEP FIELD SOUTH (ECDFS) FROM THE MULTIWAVELENGTH SURVEY BY YALE-CHILE (MUSYC)

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

Taylor, Edward N.; Franx, Marijn; Quadri, Ryan F.

2009-08-01

We present a new, K-selected, optical-to-near infrared photometric catalog of the Extended Chandra Deep Field South (ECDFS), making it publicly available to the astronomical community.{sup 22}Imaging and spectroscopy data and catalogs are freely available through the MUSYC Public Data Release webpage: http://www.astro.yale.edu/MUSYC/. The data set is founded on publicly available imaging, supplemented by original z'JK imaging data collected as part of the MUltiwavelength Survey by Yale-Chile (MUSYC). The final photometric catalog consists of photometry derived from UU {sub 38} BVRIz'JK imaging covering the full 1/2 x 1/2 square circ of the ECDFS, plus H-band photometry for approximately 80% of themore » field. The 5{sigma} flux limit for point sources is K{sup (AB)}{sub tot}= 22.0. This is also the nominal completeness and reliability limit of the catalog: the empirical completeness for 21.75 < K < 22.00 is {approx}>85%. We have verified the quality of the catalog through both internal consistency checks, and comparisons to other existing and publicly available catalogs. As well as the photometric catalog, we also present catalogs of photometric redshifts and rest-frame photometry derived from the 10-band photometry. We have collected robust spectroscopic redshift determinations from published sources for 1966 galaxies in the catalog. Based on these sources, we have achieved a (1{sigma}) photometric redshift accuracy of {delta}z/(1 + z) = 0.036, with an outlier fraction of 7.8%. Most of these outliers are X-ray sources. Finally, we describe and release a utility for interpolating rest-frame photometry from observed spectral energy distributions, dubbed InterRest.{sup 23}InterRest is available via http://www.strw.leidenuniv.nl/{approx}ent/InterRest. Documentation and a complete walkthrough can be found at the same address.« less

A deep ALMA image of the Hubble Ultra Deep Field

NASA Astrophysics Data System (ADS)

Dunlop, J. S.; McLure, R. J.; Biggs, A. D.; Geach, J. E.; Michałowski, M. J.; Ivison, R. J.; Rujopakarn, W.; van Kampen, E.; Kirkpatrick, A.; Pope, A.; Scott, D.; Swinbank, A. M.; Targett, T. A.; Aretxaga, I.; Austermann, J. E.; Best, P. N.; Bruce, V. A.; Chapin, E. L.; Charlot, S.; Cirasuolo, M.; Coppin, K.; Ellis, R. S.; Finkelstein, S. L.; Hayward, C. C.; Hughes, D. H.; Ibar, E.; Jagannathan, P.; Khochfar, S.; Koprowski, M. P.; Narayanan, D.; Nyland, K.; Papovich, C.; Peacock, J. A.; Rieke, G. H.; Robertson, B.; Vernstrom, T.; Werf, P. P. van der; Wilson, G. W.; Yun, M.

2017-04-01

We present the results of the first, deep Atacama Large Millimeter Array (ALMA) imaging covering the full ≃4.5 arcmin2 of the Hubble Ultra Deep Field (HUDF) imaged with Wide Field Camera 3/IR on HST. Using a 45-pointing mosaic, we have obtained a homogeneous 1.3-mm image reaching σ1.3 ≃ 35 μJy, at a resolution of ≃0.7 arcsec. From an initial list of ≃50 > 3.5σ peaks, a rigorous analysis confirms 16 sources with S1.3 > 120 μJy. All of these have secure galaxy counterparts with robust redshifts ( = 2.15). Due to the unparalleled supporting data, the physical properties of the ALMA sources are well constrained, including their stellar masses (M*) and UV+FIR star formation rates (SFR). Our results show that stellar mass is the best predictor of SFR in the high-redshift Universe; indeed at z ≥ 2 our ALMA sample contains seven of the nine galaxies in the HUDF with M* ≥ 2 × 1010 M⊙, and we detect only one galaxy at z > 3.5, reflecting the rapid drop-off of high-mass galaxies with increasing redshift. The detections, coupled with stacking, allow us to probe the redshift/mass distribution of the 1.3-mm background down to S1.3 ≃ 10 μJy. We find strong evidence for a steep star-forming 'main sequence' at z ≃ 2, with SFR ∝M* and a mean specific SFR ≃ 2.2 Gyr-1. Moreover, we find that ≃85 per cent of total star formation at z ≃ 2 is enshrouded in dust, with ≃65 per cent of all star formation at this epoch occurring in high-mass galaxies (M* > 2 × 1010 M⊙), for which the average obscured:unobscured SF ratio is ≃200. Finally, we revisit the cosmic evolution of SFR density; we find this peaks at z ≃ 2.5, and that the star-forming Universe transits from primarily unobscured to primarily obscured at z ≃ 4.

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.

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

The effect of adjunctive noncontact low frequency ultrasound on deep tissue pressure injury.

PubMed

Honaker, Jeremy S; Forston, Michael R; Davis, Emily A; Weisner, Michelle M; Morgan, Jennifer A; Sacca, Emily

2016-11-01

The optimal treatment for deep tissue pressure injuries has not been determined. Deep tissue pressure injuries represent a more ominous early stage pressure injury that may evolve into full thickness ulceration despite implementing the standard of care for pressure injury. A longitudinal prospective historical case control study design was used to determine the effectiveness of noncontact low frequency ultrasound plus standard of care (treatment group) in comparison to standard of care (control group) in reducing deep tissue pressure injury severity, total surface area, and final pressure injury stage. The Honaker Suspected Deep Tissue Injury Severity Scale (range 3-18[more severe]) was used to determine deep tissue pressure injury severity at enrollment (Time 1) and discharge (Time 2). A total of 60 subjects (Treatment = 30; Control= 30) were enrolled in the study. In comparison to the control group mean deep tissue pressure injury total surface area change at Time 2 (0.3 cm 2 ), the treatment group had a greater decrease (8.8 cm 2 ) that was significant (t = 2.41, p = 0.014, r 2  = 0.10). In regards to the Honaker Suspected Deep Tissue Injury Severity Scale scores, the treatment group had a significantly lower score (7.6) in comparison to the control group (11.9) at time 2, with a mean difference of 4.6 (t = 6.146, p = 0.0001, r 2  = 0.39). When considering the final pressure ulcer stage at Time 2, the control group were mostly composed of unstageable pressure ulcer (57%) and deep tissue pressure injury severity (27%). In contrast, the treatment group final pressure ulcer stages were less severe and were mostly composed of stage 2 pressure injury (50%) and deep tissue pressure injury severity (23%) were the most common at time 2. The results of this study have shown that deep tissue pressure injury severity treated with noncontact low frequency ultrasound within 5 days of onset and in conjunction with standard of care may improve outcomes as compared to standard of care only. © 2016 by the Wound Healing Society.

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

THE MINIMUM OF SOLAR CYCLE 23: AS DEEP AS IT COULD BE?

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

Muñoz-Jaramillo, Andrés; Longcope, Dana W.; Senkpeil, Ryan R.

2015-05-01

In this work we introduce a new way of binning sunspot group data with the purpose of better understanding the impact of the solar cycle on sunspot properties and how this defined the characteristics of the extended minimum of cycle 23. Our approach assumes that the statistical properties of sunspots are completely determined by the strength of the underlying large-scale field and have no additional time dependencies. We use the amplitude of the cycle at any given moment (something we refer to as activity level) as a proxy for the strength of this deep-seated magnetic field. We find that themore » sunspot size distribution is composed of two populations: one population of groups and active regions and a second population of pores and ephemeral regions. When fits are performed at periods of different activity level, only the statistical properties of the former population, the active regions, are found to vary. Finally, we study the relative contribution of each component (small-scale versus large-scale) to solar magnetism. We find that when hemispheres are treated separately, almost every one of the past 12 solar minima reaches a point where the main contribution to magnetism comes from the small-scale component. However, due to asymmetries in cycle phase, this state is very rarely reached by both hemispheres at the same time. From this we infer that even though each hemisphere did reach the magnetic baseline, from a heliospheric point of view the minimum of cycle 23 was not as deep as it could have been.« less

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

FAST Model Calibration and Validation of the OC5-DeepCwind Floating Offshore Wind System Against Wave Tank Test Data

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

Wendt, Fabian F; Robertson, Amy N; Jonkman, Jason

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitchmore » and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.« less

A New Approach for Mining Order-Preserving Submatrices Based on All Common Subsequences.

PubMed

Xue, Yun; Liao, Zhengling; Li, Meihang; Luo, Jie; Kuang, Qiuhua; Hu, Xiaohui; Li, Tiechen

2015-01-01

Order-preserving submatrices (OPSMs) have been applied in many fields, such as DNA microarray data analysis, automatic recommendation systems, and target marketing systems, as an important unsupervised learning model. Unfortunately, most existing methods are heuristic algorithms which are unable to reveal OPSMs entirely in NP-complete problem. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs and are completely pruned by most popular methods. In this paper, we propose an exact method to discover all OPSMs based on frequent sequential pattern mining. First, an existing algorithm was adjusted to disclose all common subsequence (ACS) between every two row sequences, and therefore all deep OPSMs will not be missed. Then, an improved data structure for prefix tree was used to store and traverse ACS, and Apriori principle was employed to efficiently mine the frequent sequential pattern. Finally, experiments were implemented on gene and synthetic datasets. Results demonstrated the effectiveness and efficiency of this method.

Parametric study on the behavior of an innovative subsurface tension leg platform in ultra-deep water

NASA Astrophysics Data System (ADS)

Zhen, Xing-wei; Huang, Yi

2017-10-01

This study focuses on a new technology of Subsurface Tension Leg Platform (STLP), which utilizes the shallowwater rated well completion equipment and technology for the development of large oil and gas fields in ultra-deep water (UDW). Thus, the STLP concept offers attractive advantages over conventional field development concepts. STLP is basically a pre-installed Subsurface Sea-star Platform (SSP), which supports rigid risers and shallow-water rated well completion equipment. The paper details the results of the parametric study on the behavior of STLP at a water depth of 3000 m. At first, a general description of the STLP configuration and working principle is introduced. Then, the numerical models for the global analysis of the STLP in waves and current are presented. After that, extensive parametric studies are carried out with regarding to SSP/tethers system analysis, global dynamic analysis and riser interference analysis. Critical points are addressed on the mooring pattern and riser arrangement under the influence of ocean current, to ensure that the requirements on SSP stability and riser interference are well satisfied. Finally, conclusions and discussions are made. The results indicate that STLP is a competitive well and riser solution in up to 3000 m water depth for offshore petroleum production.

An improved multi-domain convolution tracking algorithm

NASA Astrophysics Data System (ADS)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

Along with the wide application of the Deep Learning in the field of Computer vision, Deep learning has become a mainstream direction in the field of object tracking. The tracking algorithm in this paper is based on the improved multidomain convolution neural network, and the VOT video set is pre-trained on the network by multi-domain training strategy. In the process of online tracking, the network evaluates candidate targets sampled from vicinity of the prediction target in the previous with Gaussian distribution, and the candidate target with the highest score is recognized as the prediction target of this frame. The Bounding Box Regression model is introduced to make the prediction target closer to the ground-truths target box of the test set. Grouping-update strategy is involved to extract and select useful update samples in each frame, which can effectively prevent over fitting. And adapt to changes in both target and environment. To improve the speed of the algorithm while maintaining the performance, the number of candidate target succeed in adjusting dynamically with the help of Self-adaption parameter Strategy. Finally, the algorithm is tested by OTB set, compared with other high-performance tracking algorithms, and the plot of success rate and the accuracy are drawn. which illustrates outstanding performance of the tracking algorithm in this paper.

Fast subsurface fingerprint imaging with full-field optical coherence tomography system equipped with a silicon camera

NASA Astrophysics Data System (ADS)

Auksorius, Egidijus; Boccara, A. Claude

2017-09-01

Images recorded below the surface of a finger can have more details and be of higher quality than the conventional surface fingerprint images. This is particularly true when the quality of the surface fingerprints is compromised by, for example, moisture or surface damage. However, there is an unmet need for an inexpensive fingerprint sensor that is able to acquire high-quality images deep below the surface in short time. To this end, we report on a cost-effective full-field optical coherent tomography system comprised of a silicon camera and a powerful near-infrared LED light source. The system, for example, is able to record 1.7 cm×1.7 cm en face images in 0.12 s with the spatial sampling rate of 2116 dots per inch and the sensitivity of 93 dB. We show that the system can be used to image internal fingerprints and sweat ducts with good contrast. Finally, to demonstrate its biometric performance, we acquired subsurface fingerprint images from 240 individual fingers and estimated the equal-error-rate to be ˜0.8%. The developed instrument could also be used in other en face deep-tissue imaging applications because of its high sensitivity, such as in vivo skin imaging.

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

Opening the Window on Galaxy Assembly: Ages and Structural Parameters of Globular Clusters Towards the Galactic Bulge

NASA Astrophysics Data System (ADS)

Cohen, Roger

2015-10-01

The primary aim of this program is to undertake a systematic investigation of highly reddened Galactic globular clusters (GGCs) located towards the Galactic bulge. These clusters have been excluded from deep space-based photometric surveys due to their severe total and differential extinction. We will exploit the photometric depth and homogeneity of two existing Treasury programs (the ACS GGC Treasury Survey and the WFC3 Bulge Treasury Program) along with the unique optical+IR parallel imaging capabilities of HST to finally place the bulge GGCs in the context of their optically well-studied counterparts. Specifically, by leveraging ACS/WFC together with WFC3/IR, we first exploit the reddening sensitivity at optical wavelengths to map severe, small-scale differential reddening in the cluster cores. Corrected two-color WFC3/IR photometry will then be used to measure cluster ages to better than 1 Gyr relative precision, finally completing the age-metallicity relation of the Milky Way GGC system. Ages are obtained using a demonstrated procedure which is strictly differential, and therefore insensitive to total distance, reddening, reddening law, or photometric calibration uncertainties. At the same time, deep archival Treasury survey imaging of the Galactic bulge will be used to decontaminate cluster luminosity functions, yielding measurements of bulge GGC mass functions and mass segregation on par with results from the ACS GGC Treasury survey. Finally, the imaging which we propose will be combined with existing wide-field near-IR PSF photometry, yielding complete radial number density profiles, structural and morphological parameters.

Autonomous Command Operation of the WIRE Spacecraft

NASA Technical Reports Server (NTRS)

Prior, Mike; Walyus, Keith; Saylor, Rick

1999-01-01

This paper presents the end-to-end design architecture for an autonomous commanding capability to be used on the Wide Field Infrared Explorer (WIRE) mission for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented an autonomous command loading capability. This capability allows completely unattended operations over a typical two-day weekend period.

Paleomagnetic field variability and chronostratigraphy of Brunhes-Chron deep-sea sediments from the Bering Sea: IODP Expedition 323

NASA Astrophysics Data System (ADS)

Lund, Steve; Stoner, Joseph; Okada, Makoto; Mortazavi, Emily

2016-03-01

IODP Expedition 323 recovered six complete and replicate records of Brunhes-Chron paleomagnetic field variability (0-780,000 years BP) in 2820 m core depth below sea floor (CSF) of deep-sea sediments. On shipboard, we made more than 220,000 paleomagnetic measurements on the recovered sediments. Since then, we have u-channel sampled more than 300 m of Brunhes Chron sediments to corroborate our shipboard measurements and improve our paleomagnetic and rock magnetic understanding of these sediments. Several intervals of distinctive paleomagnetic secular variation (PSV) have been identified that appear to be correlatable among sites 1343, 1344, and 1345. One magnetic field excursion is recorded in sediments of sites 1339, 1343, 1344, and 1345. We identify this to be excursion 7α/Iceland Basin Event (192,000 years BP), which is also seen in the high-latitude North Atlantic Ocean (Channell et al., 1997). We have verified in u-channels the placement of the Brunhes/Matuyama boundary (780,000 years BP) at sites 1341 and 1343. Finally, we have developed a medium-quality relative paleointensity record for these sediments that is correlatable among the sites, even though it is still biased by large-amplitude environmental variability. On the basis of these observations we have built a magnetic chronostratigraphy of Expedition 323 sediments suitable for regional correlation and dating over the last 1 million years, and compared this with oxygen-isotope chronostratigraphy from sites U1339 and U1345.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

PubMed

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain

PubMed Central

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L.; Aziz, Tipu Z.; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations. PMID:29695951

Programming and machining of complex parts based on CATIA solid modeling

NASA Astrophysics Data System (ADS)

Zhu, Xiurong

2017-09-01

The complex parts of the use of CATIA solid modeling programming and simulation processing design, elaborated in the field of CNC machining, programming and the importance of processing technology. In parts of the design process, first make a deep analysis on the principle, and then the size of the design, the size of each chain, connected to each other. After the use of backstepping and a variety of methods to calculate the final size of the parts. In the selection of parts materials, careful study, repeated testing, the final choice of 6061 aluminum alloy. According to the actual situation of the processing site, it is necessary to make a comprehensive consideration of various factors in the machining process. The simulation process should be based on the actual processing, not only pay attention to shape. It can be used as reference for machining.

Spinor helicity methods in high-energy factorization: Efficient momentum-space calculations in the Color Glass Condensate formalism

NASA Astrophysics Data System (ADS)

Ayala, Alejandro; Hentschinski, Martin; Jalilian-Marian, Jamal; Tejeda-Yeomans, Maria Elena

2017-07-01

We use the spinor helicity formalism to calculate the cross section for production of three partons of a given polarization in Deep Inelastic Scattering (DIS) off proton and nucleus targets at small Bjorken x. The target proton or nucleus is treated as a classical color field (shock wave) from which the produced partons scatter multiple times. We reported our result for the final expression for the production cross section and studied the azimuthal angular correlations of the produced partons in [1]. Here we provide the full details of the calculation of the production cross section using the spinor helicity methods.

Home - Deep Underground Neutrino ExperimentDeep Underground Neutrino

Science.gov Websites

understanding of neutrinos and their role in the universe. DUNE prototype detectors are under construction at understanding of neutrinos and their role in the universe. DUNE_Forces_011116_FINAL Unification of Forces With

Massive open star clusters using the VVV survey. I. Presentation of the data and description of the approach

NASA Astrophysics Data System (ADS)

Chené, A.-N.; Borissova, J.; Clarke, J. R. A.; Bonatto, C.; Majaess, D. J.; Moni Bidin, C.; Sale, S. E.; Mauro, F.; Kurtev, R.; Baume, G.; Feinstein, C.; Ivanov, V. D.; Geisler, D.; Catelan, M.; Minniti, D.; Lucas, P.; de Grijs, R.; Kumar, M. S. N.

2012-09-01

Context. The ESO Public Survey "VISTA Variables in the Vía Láctea" (VVV) provides deep multi-epoch infrared observations for unprecedented 562 sq. degrees of the Galactic bulge, and adjacent regions of the disk. Aims: The VVV observations will foster the construction of a sample of Galactic star clusters with reliable and homogeneously derived physical parameters (e.g., age, distance, and mass, etc.). In this first paper in a series, the methodology employed to establish cluster parameters for the envisioned database are elaborated upon by analysing four known young open clusters: Danks 1, Danks 2, RCW 79, and DBS 132. The analysis offers a first glimpse of the information that can be gleaned from the VVV observations for clusters in the final database. Methods: Wide-field, deep JHKs VVV observations, combined with new infrared spectroscopy, are employed to constrain fundamental parameters for a subset of clusters. Results: Results are inferred from VVV near-infrared photometry and numerous low resolution spectra (typically more than 10 per cluster). The high quality of the spectra and the deep wide-field VVV photometry enables us to precisely and independently determine the characteristics of the clusters studied, which we compare to previous determinations. An anomalous reddening law in the direction of the Danks clusters is found, specifically E(J - H)/E(H - Ks) = 2.20 ± 0.06, which exceeds published values for the inner Galaxy. The G305 star forming complex, which includes the Danks clusters, lies beyond the Sagittarius-Carina spiral arm and occupies the Centaurus arm. Finally, the first deep infrared colour-magnitude diagram of RCW 79 is presented, which reveals a sizeable pre-main sequence population. A list of candidate variable stars in G305 region is reported. Conclusions: This study demonstrates the strength of the dataset and methodology employed, and constitutes the first step of a broader study which shall include reliable parameters for a sizeable number of poorly characterised and/or newly discovered clusters. Based on observations made with NTT telescope at the La Silla Observatory, ESO, under programme ID 087.D-0490A, and with the Clay telescope at the Las Campanas Observatory under programme CN2011A-086. Also based on data from the VVV survey observed under program ID 172.B-2002.Tables 1, 5 and 6 are available in electronic form at http://www.aanda.org

Ab initio velocity-field curves in monoclinic β-Ga2O3

NASA Astrophysics Data System (ADS)

Ghosh, Krishnendu; Singisetti, Uttam

2017-07-01

We investigate the high-field transport in monoclinic β-Ga2O3 using a combination of ab initio calculations and full band Monte Carlo (FBMC) simulation. Scattering rate calculation and the final state selection in the FBMC simulation use complete wave-vector (both electron and phonon) and crystal direction dependent electron phonon interaction (EPI) elements. We propose and implement a semi-coarse version of the Wannier-Fourier interpolation method [Giustino et al., Phys. Rev. B 76, 165108 (2007)] for short-range non-polar optical phonon (EPI) elements in order to ease the computational requirement in FBMC simulation. During the interpolation of the EPI, the inverse Fourier sum over the real-space electronic grids is done on a coarse mesh while the unitary rotations are done on a fine mesh. This paper reports the high field transport in monoclinic β-Ga2O3 with deep insight into the contribution of electron-phonon interactions and velocity-field characteristics for electric fields ranging up to 450 kV/cm in different crystal directions. A peak velocity of 2 × 107 cm/s is estimated at an electric field of 200 kV/cm.

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.

Deep UV LEDs

NASA Astrophysics Data System (ADS)

Han, Jung; Amano, Hiroshi; Schowalter, Leo

2014-06-01

Deep ultraviolet (DUV) photons interact strongly with a broad range of chemical and biological molecules; compact DUV light sources could enable a wide range of applications in chemi/bio-sensing, sterilization, agriculture, and industrial curing. The much shorter wavelength also results in useful characteristics related to optical diffraction (for lithography) and scattering (non-line-of-sight communication). The family of III-N (AlGaInN) compound semiconductors offers a tunable energy gap from infrared to DUV. While InGaN-based blue light emitters have been the primary focus for the obvious application of solid state lighting, there is a growing interest in the development of efficient UV and DUV light-emitting devices. In the past few years we have witnessed an increasing investment from both government and industry sectors to further the state of DUV light-emitting devices. The contributions in Semiconductor Science and Technology 's special issue on DUV devices provide an up-to-date snapshot covering many relevant topics in this field. Given the expected importance of bulk AlN substrate in DUV technology, we are pleased to include a review article by Hartmann et al on the growth of AlN bulk crystal by physical vapour transport. The issue of polarization field within the deep ultraviolet LEDs is examined in the article by Braut et al. Several commercial companies provide useful updates in their development of DUV emitters, including Nichia (Fujioka et al ), Nitride Semiconductors (Muramoto et al ) and Sensor Electronic Technology (Shatalov et al ). We believe these articles will provide an excellent overview of the state of technology. The growth of AlGaN heterostructures by molecular beam epitaxy, in contrast to the common organo-metallic vapour phase epitaxy, is discussed by Ivanov et al. Since hexagonal boron nitride (BN) has received much attention as both a UV and a two-dimensional electronic material, we believe it serves readers well to include the article by Jiang et al on using BN for UV devices; potentially as a p-type wide band gap semiconductor contact. Finally, an in-depth discussion of one DUV application in defense, the non-line-of-sight (NLOS) communication, is given by Drost and Sadler. Overall, we believe that this special issue of Semiconductor Science and Technology provides a useful overview of the state-of-art in the field on DUV materials and devices. In view of the rapidly growing interest in this field, the demonstrated enhanced device performance, and the wide range of applications, this special issue can be considered a very timely contribution. Finally, we would like to thank the IOP editorial staff, in particular Alice Malhador, for their support and also like to thank all contributors for their efforts to make this special issue possible.

Current Status of The Romanian National Deep Geological Repository Program

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

Radu, M.; Nicolae, R.; Nicolae, D.

2008-07-01

Construction of a deep geological repository is a very demanding and costly task. By now, countries that have Candu reactors, have not processed the spent fuel passing to the interim storage as a preliminary step of final disposal within the nuclear fuel cycle back-end. Romania, in comparison to other nations, represents a rather small territory, with high population density, wherein the geological formation areas with radioactive waste storage potential are limited and restricted not only from the point of view of the selection criteria due to the rocks natural characteristics, but also from the point of view of their involvementmore » in social and economical activities. In the framework of the national R and D Programs, series of 'Map investigations' have been made regarding the selection and preliminary characterization of the host geological formation for the nation's spent fuel deep geological repository. The fact that Romania has many deposits of natural gas, oil, ore and geothermal water, and intensively utilizes soil and also is very forested, cause some of the apparent acceptable sites to be rejected in the subsequent analysis. Currently, according to the Law on the spent fuel and radioactive waste management, including disposal, The National Agency of Radioactive Waste is responsible and coordinates the national strategy in the field and, subsequently, further actions will be decided. The Romanian National Strategy, approved in 2004, projects the operation of a deep geological repository to begin in 2055. (authors)« less

John Falk and Lynn Dierking: building the field of informal/free-choice science education

NASA Astrophysics Data System (ADS)

Rennie, Léonie J.

2016-03-01

This article establishes the importance of "context", a concept that underpins the academic contributions that John Falk and Lynn Dierking have made in building the field of informal/free-choice learning in science education. I consider, in turn, the individual contributions made by each of them prior to their seminal co-authored work, entitled The Museum Experience. I then document their joint contributions to the field, pointing out that although their interests and skills overlap in complementary ways to produce their jointly authored works, both have continued to make their individual contributions; Falk in his work on identity and impact, and Dierking in her work on community, youth, family and equity. Finally I come to the present, describing how they each continue their research and publication in lifelong, life-wide, and life-deep learning, with a particular focus on free-choice learning and the role it can play in addressing critical issues in the world.

[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.

Coarse-to-fine deep neural network for fast pedestrian detection

NASA Astrophysics Data System (ADS)

Li, Yaobin; Yang, Xinmei; Cao, Lijun

2017-11-01

Pedestrian detection belongs to a category of object detection is a key issue in the field of video surveillance and automatic driving. Although recent object detection methods, such as Fast/Faster RCNN, have achieved excellent performance, it is difficult to meet real-time requirements and limits the application in real scenarios. A coarse-to-fine deep neural network for fast pedestrian detection is proposed in this paper. Two-stage approach is presented to realize fine trade-off between accuracy and speed. In the coarse stage, we train a fast deep convolution neural network to generate most pedestrian candidates at the cost of a number of false positives. The detector can cover the majority of scales, sizes, and occlusions of pedestrians. After that, a classification network is introduced to refine the pedestrian candidates generated from the previous stage. Refining through classification network, most of false detections will be excluded easily and the final pedestrian predictions with bounding box and confidence score are produced. Competitive results have been achieved on INRIA dataset in terms of accuracy, especially the method can achieve real-time detection that is faster than the previous leading methods. The effectiveness of coarse-to-fine approach to detect pedestrians is verified, and the accuracy and stability are also improved.

VizieR Online Data Catalog: Improved multi-band photometry from SERVS (Nyland+, 2017)

NASA Astrophysics Data System (ADS)

Nyland, K.; Lacy, M.; Sajina, A.; Pforr, J.; Farrah, D.; Wilson, G.; Surace, J.; Haussler, B.; Vaccari, M.; Jarvis, M.

2017-07-01

The Spitzer Extragalactic Representative Volume Survey (SERVS) sky footprint includes five well-studied astronomical deep fields with abundant multi-wavelength data spanning an area of ~18deg2 and a co-moving volume of ~0.8Gpc3. The five deep fields included in SERVS are the XMM-LSS field, Lockman Hole (LH), ELAIS-N1 (EN1), ELAIS-S1 (ES1), and Chandra Deep Field South (CDFS). SERVS provides NIR, post-cryogenic imaging in the 3.6 and 4.5um Spitzer/IRAC bands to a depth of ~2uJy. IRAC dual-band source catalogs generated using traditional catalog extraction methods are described in Mauduit+ (2012PASP..124..714M). The Spitzer IRAC data are complemented by ground-based NIR observations from the VISTA Deep Extragalactic Observations (VIDEO; Jarvis+ 2013MNRAS.428.1281J) survey in the south in the Z, Y, J, H, and Ks bands and UKIRT Infrared Deep Sky Survey (UKIDSS; Lawrence+ 2007, see II/319) in the north in the J and K bands. SERVS also provides substantial overlap with infrared data from SWIRE (Lonsdale+ 2003PASP..115..897L) and the Herschel Multitiered Extragalactic Survey (HerMES; Oliver+ 2012, VIII/95). As shown in Figure 1, one square degree of the XMM-LSS field overlaps with ground-based optical data from the Canada-France-Hawaii Telescope Legacy Survey Deep field 1 (CFHTLS-D1). The CFHTLS-D1 region is centered at RAJ2000=02:25:59, DEJ2000=-04:29:40 and includes imaging through the filter set u', g', r', i', and z'. Thus, in combination with the NIR data from SERVS and VIDEO that overlap with the CFHTLS-D1 region, multi-band imaging over a total of 12 bands is available. (2 data files).

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

PubMed Central

Yang, Yuedong; Gao, Jianzhao; Wang, Jihua; Heffernan, Rhys; Hanson, Jack; Paliwal, Kuldip; Zhou, Yaoqi

2018-01-01

Abstract Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82–84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88–90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction. PMID:28040746

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.

Anomalies of rupture velocity in deep earthquakes

NASA Astrophysics Data System (ADS)

Suzuki, M.; Yagi, Y.

2010-12-01

Explaining deep seismicity is a long-standing challenge in earth science. Deeper than 300 km, the occurrence rate of earthquakes with depth remains at a low level until ~530 km depth, then rises until ~600 km, finally terminate near 700 km. Given the difficulty of estimating fracture properties and observing the stress field in the mantle transition zone (410-660 km), the seismic source processes of deep earthquakes are the most important information for understanding the distribution of deep seismicity. However, in a compilation of seismic source models of deep earthquakes, the source parameters for individual deep earthquakes are quite varied [Frohlich, 2006]. Rupture velocities for deep earthquakes estimated using seismic waveforms range from 0.3 to 0.9Vs, where Vs is the shear wave velocity, a considerably wider range than the velocities for shallow earthquakes. The uncertainty of seismic source models prevents us from determining the main characteristics of the rupture process and understanding the physical mechanisms of deep earthquakes. Recently, the back projection method has been used to derive a detailed and stable seismic source image from dense seismic network observations [e.g., Ishii et al., 2005; Walker et al., 2005]. Using this method, we can obtain an image of the seismic source process from the observed data without a priori constraints or discarding parameters. We applied the back projection method to teleseismic P-waveforms of 24 large, deep earthquakes (moment magnitude Mw ≥ 7.0, depth ≥ 300 km) recorded since 1994 by the Data Management Center of the Incorporated Research Institutions for Seismology (IRIS-DMC) and reported in the U.S. Geological Survey (USGS) catalog, and constructed seismic source models of deep earthquakes. By imaging the seismic rupture process for a set of recent deep earthquakes, we found that the rupture velocities are less than about 0.6Vs except in the depth range of 530 to 600 km. This is consistent with the depth variation of deep seismicity: it peaks between about 530 and 600 km, where the fast rupture earthquakes (greater than 0.7Vs) are observed. Similarly, aftershock productivity is particularly low from 300 to 550 km depth and increases markedly at depth greater than 550 km [e.g., Persh and Houston, 2004]. We propose that large fracture surface energy (Gc) value for deep earthquakes generally prevent the acceleration of dynamic rupture propagation and generation of earthquakes between 300 and 700 km depth, whereas small Gc value in the exceptional depth range promote dynamic rupture propagation and explain the seismicity peak near 600 km.

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.

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

Exploring geo-tagged photos for land cover validation with deep learning

NASA Astrophysics Data System (ADS)

Xing, Hanfa; Meng, Yuan; Wang, Zixuan; Fan, Kaixuan; Hou, Dongyang

2018-07-01

Land cover validation plays an important role in the process of generating and distributing land cover thematic maps, which is usually implemented by high cost of sample interpretation with remotely sensed images or field survey. With an increasing availability of geo-tagged landscape photos, the automatic photo recognition methodologies, e.g., deep learning, can be effectively utilised for land cover applications. However, they have hardly been utilised in validation processes, as challenges remain in sample selection and classification for highly heterogeneous photos. This study proposed an approach to employ geo-tagged photos for land cover validation by using the deep learning technology. The approach first identified photos automatically based on the VGG-16 network. Then, samples for validation were selected and further classified by considering photos distribution and classification probabilities. The implementations were conducted for the validation of the GlobeLand30 land cover product in a heterogeneous area, western California. Experimental results represented promises in land cover validation, given that GlobeLand30 showed an overall accuracy of 83.80% with classified samples, which was close to the validation result of 80.45% based on visual interpretation. Additionally, the performances of deep learning based on ResNet-50 and AlexNet were also quantified, revealing no substantial differences in final validation results. The proposed approach ensures geo-tagged photo quality, and supports the sample classification strategy by considering photo distribution, with accuracy improvement from 72.07% to 79.33% compared with solely considering the single nearest photo. Consequently, the presented approach proves the feasibility of deep learning technology on land cover information identification of geo-tagged photos, and has a great potential to support and improve the efficiency of land cover validation.

Resolving the fine-scale velocity structure of continental hyperextension at the Deep Galicia Margin using full-waveform inversion

NASA Astrophysics Data System (ADS)

Davy, R. G.; Morgan, J. V.; Minshull, T. A.; Bayrakci, G.; Bull, J. M.; Klaeschen, D.; Reston, T. J.; Sawyer, D. S.; Lymer, G.; Cresswell, D.

2018-01-01

Continental hyperextension during magma-poor rifting at the Deep Galicia Margin is characterized by a complex pattern of faulting, thin continental fault blocks and the serpentinization, with local exhumation, of mantle peridotites along the S-reflector, interpreted as a detachment surface. In order to understand fully the evolution of these features, it is important to image seismically the structure and to model the velocity structure to the greatest resolution possible. Traveltime tomography models have revealed the long-wavelength velocity structure of this hyperextended domain, but are often insufficient to match accurately the short-wavelength structure observed in reflection seismic imaging. Here, we demonstrate the application of 2-D time-domain acoustic full-waveform inversion (FWI) to deep-water seismic data collected at the Deep Galicia Margin, in order to attain a high-resolution velocity model of continental hyperextension. We have used several quality assurance procedures to assess the velocity model, including comparison of the observed and modeled waveforms, checkerboard tests, testing of parameter and inversion strategy and comparison with the migrated reflection image. Our final model exhibits an increase in the resolution of subsurface velocities, with particular improvement observed in the westernmost continental fault blocks, with a clear rotation of the velocity field to match steeply dipping reflectors. Across the S-reflector, there is a sharpening in the velocity contrast, with lower velocities beneath S indicative of preferential mantle serpentinization. This study supports the hypothesis that normal faulting acts to hydrate the upper-mantle peridotite, observed as a systematic decrease in seismic velocities, consistent with increased serpentinization. Our results confirm the feasibility of applying the FWI method to sparse, deep-water crustal data sets.

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.

VizieR Online Data Catalog: ALMA submm galaxies multi-wavelength data (Simpson+, 2017)

NASA Astrophysics Data System (ADS)

Simpson, J. M.; Smail, I.; Swinbank, A. M.; Ivison, R. J.; Dunlop, J. S.; Geach, J. E.; Almaini, O.; Arumugam, V.; Bremer, M. N.; Chen, C.-C.; Conselice, C.; Coppin, K. E. K.; Farrah, D.; Ibar, E.; Hartley, W. G.; Ma, C. J.; Michalowski, M. J.; Scott, D.; Spaans, M.; Thomson, A. P.; van der Werf, P. P.

2017-11-01

In previous work, we presented the source catalog, number counts, and far-infrared morphologies of the 52 SMGs that were detected in 30 ALMA maps (see Simpson+ 2015ApJ...799...81S, 2015ApJ...807..128S). The UKIDSS observations of the ~0.8deg2 UDS comprise four Wide-Field Camera (WFCAM) pointings in the J-, H-, and K-bands. In this paper, we use the images and catalogs released as part of the UKIDSS data release 8 (DR8). The DR8 release contains data taken between 2005 and 2010, and the final J-, H-, and K-band mosaics have a median 5σ depth (2" apertures) of J=24.9, H=24.2, and K=24.6, respectively. Deep observations of the UDS have also been taken in the U-band with Megacam at the Canada-France-Hawaii Telescope (CFHT) and in the B, V, R, i', and z' bands with Suprime-cam at the Subaru telescope. Furthermore, deep Spitzer data, obtained as part of the SpUDS program (PI: J. Dunlop) provides imaging reaching a 5σ depth of m3.6=24.2 and m4.5=24.0 at 3.6um and 4.5um, respectively. The UDS field was observed at 250, 350, and 500um with the Spectral and Photometric Imaging Receiver (SPIRE) onboard the Herschel Space Observatory as part of the Herschel Multi-tiered Extragalactic Survey (HerMES). The UDS field was observed by the VLA at 1.4GHz as part of the project UDS20 (V. Arumugam et al. 2017, in preparation). A total of 14 pointings were used to mosaic an area of ~1.3deg2 centered on the UDS field. (2 data files).

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.

Going deeper in the automated identification of Herbarium specimens.

PubMed

Carranza-Rojas, Jose; Goeau, Herve; Bonnet, Pierre; Mata-Montero, Erick; Joly, Alexis

2017-08-11

Hundreds of herbarium collections have accumulated a valuable heritage and knowledge of plants over several centuries. Recent initiatives started ambitious preservation plans to digitize this information and make it available to botanists and the general public through web portals. However, thousands of sheets are still unidentified at the species level while numerous sheets should be reviewed and updated following more recent taxonomic knowledge. These annotations and revisions require an unrealistic amount of work for botanists to carry out in a reasonable time. Computer vision and machine learning approaches applied to herbarium sheets are promising but are still not well studied compared to automated species identification from leaf scans or pictures of plants in the field. In this work, we propose to study and evaluate the accuracy with which herbarium images can be potentially exploited for species identification with deep learning technology. In addition, we propose to study if the combination of herbarium sheets with photos of plants in the field is relevant in terms of accuracy, and finally, we explore if herbarium images from one region that has one specific flora can be used to do transfer learning to another region with other species; for example, on a region under-represented in terms of collected data. This is, to our knowledge, the first study that uses deep learning to analyze a big dataset with thousands of species from herbaria. Results show the potential of Deep Learning on herbarium species identification, particularly by training and testing across different datasets from different herbaria. This could potentially lead to the creation of a semi, or even fully automated system to help taxonomists and experts with their annotation, classification, and revision works.

Gemini Observations of Galaxies in Rich Early Environments (GOGREEN) I: survey description

NASA Astrophysics Data System (ADS)

Balogh, Michael L.; Gilbank, David G.; Muzzin, Adam; Rudnick, Gregory; Cooper, Michael C.; Lidman, Chris; Biviano, Andrea; Demarco, Ricardo; McGee, Sean L.; Nantais, Julie B.; Noble, Allison; Old, Lyndsay; Wilson, Gillian; Yee, Howard K. C.; Bellhouse, Callum; Cerulo, Pierluigi; Chan, Jeffrey; Pintos-Castro, Irene; Simpson, Rane; van der Burg, Remco F. J.; Zaritsky, Dennis; Ziparo, Felicia; Alonso, María Victoria; Bower, Richard G.; De Lucia, Gabriella; Finoguenov, Alexis; Lambas, Diego Garcia; Muriel, Hernan; Parker, Laura C.; Rettura, Alessandro; Valotto, Carlos; Wetzel, Andrew

2017-10-01

We describe a new Large Program in progress on the Gemini North and South telescopes: Gemini Observations of Galaxies in Rich Early Environments (GOGREEN). This is an imaging and deep spectroscopic survey of 21 galaxy systems at 1 < z < 1.5, selected to span a factor >10 in halo mass. The scientific objectives include measuring the role of environment in the evolution of low-mass galaxies, and measuring the dynamics and stellar contents of their host haloes. The targets are selected from the SpARCS, SPT, COSMOS, and SXDS surveys, to be the evolutionary counterparts of today's clusters and groups. The new red-sensitive Hamamatsu detectors on GMOS, coupled with the nod-and-shuffle sky subtraction, allow simultaneous wavelength coverage over λ ˜ 0.6-1.05 μm, and this enables a homogeneous and statistically complete redshift survey of galaxies of all types. The spectroscopic sample targets galaxies with AB magnitudes z΄ < 24.25 and [3.6] μm < 22.5, and is therefore statistically complete for stellar masses M* ≳ 1010.3 M⊙, for all galaxy types and over the entire redshift range. Deep, multiwavelength imaging has been acquired over larger fields for most systems, spanning u through K, in addition to deep IRAC imaging at 3.6 μm. The spectroscopy is ˜50 per cent complete as of semester 17A, and we anticipate a final sample of ˜500 new cluster members. Combined with existing spectroscopy on the brighter galaxies from GCLASS, SPT, and other sources, GOGREEN will be a large legacy cluster and field galaxy sample at this redshift that spectroscopically covers a wide range in stellar mass, halo mass, and clustercentric radius.

SMBH Seeds: Model Discrimination with High-energy Emission Based on Scaling Relation Evolution

NASA Astrophysics Data System (ADS)

Ben-Ami, Sagi; Vikhlinin, Alexey; Loeb, Abraham

2018-02-01

We explore the expected X-ray (0.5–2 keV) signatures from supermassive black holes (SMBHs) at high redshifts (z∼ 5{--}12) assuming various models for their seeding mechanism and evolution. Seeding models are approximated through deviations from the {M}{BH}{--}σ relation observed in the local universe, while N-body simulations of the large-scale structure are used to estimate the density of observable SMBHs. We focus on two seeding model families: (i) light seed BHs from remnants of Pop-III stars and (ii) heavy seeds from the direct collapse of gas clouds. We investigate several models for the accretion history, such as sub-Eddington accretion, slim disk models, and torque-limited growth models. We consider observations with two instruments: (i) the Chandra X-ray Observatory and (ii) the proposed Lynx. We find that all of the simulated models are in agreement with the current results from the Chandra Deep Field South, i.e., consistent with zero SMBHs in the field of view. In deep Lynx exposures, the number of observed objects is expected to become statistically significant. We demonstrate the capability to limit the phase space of plausible scenarios of the birth and evolution of SMBHs by performing deep observations at a flux limit of 1× {10}-19 {erg} {{cm}}-2 {{{s}}}-1. Finally, we show that our models are in agreement with current limits on the cosmic X-ray background (CXRB) and the expected contribution from unresolved quasars. We find that an analysis of CXRB contributions down to the Lynx confusion limit yields valuable information that can help identify the correct scenario for the birth and evolution of SMBHs.

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.

First high-resolution near-seafloor survey of magnetic anomalies of the South China Sea

NASA Astrophysics Data System (ADS)

Lin, J.; Xu, X.; Li, C.; Sun, Z.; Zhu, J.; Zhou, Z.; Qiu, N.

2013-12-01

We successfully conducted the first high-resolution near-seafloor magnetic survey of the Central, Southwest, and Northern Central Basins of the South China Sea (SCS) during two cruises on board Chinese R/V HaiYangLiuHao in October-November 2012 and March-April 2013, respectively. Measurements of magnetic field were made along four long survey lines, including (1) a NW-SE across-isochron profile transecting the Southwest Basin and covering all ages of the oceanic crust (Line CD); (2) a N-S across-isochron profile transecting the Central Basin (Line AB); and (3) two sub-parallel NE-SW across-isochron profiles transecting the Northern Central Basin of the SCS (Lines D and E). A three-axis magnetometer was mounted on a deep-tow vehicle, flying within 0.6 km above the seafloor. The position of the tow vehicle was provided by an ultra-short baseline navigation system along Lines D and E, while was estimated using shipboard GPS along Lines AB and CD. To investigate crustal magnetization, we first removed the International Geomagnetic Reference Field (IGRF) of 2010 from the measured magnetic data, and then downward continued the resultant magnetic field data to a horizontal plane at a water depth of 4.5 km to correct for variation due to the fishing depth of the deep-tow vehicle. Finally, we calculated magnetic anomalies at various water depths after reduction-to-the-pole corrections. We also constructed polarity reversal block (PRB) models of crustal magnetization by matching peaks and troughs of the observed magnetic field anomaly. Our analysis yielded the following results: (1) The near-bottom magnetic anomaly showed peak-to-trough amplitudes of more than 2,500 nT, which are several times of the anomaly amplitudes at the sea surface, illustrating that deep-tow measurements acquired much higher spatial resolutions. (2) The deep-tow data revealed several distinctive magnetic anomalies with wavelengths of 5-15 km and amplitudes of several hundred nT. These short-wavelength anomalies were unrecognized in sea surface measurements. (3) Preliminary results showed that the study regions might have experienced several episodes of magnetic reversal events that were not recognized in existing models. (4) We are currently investigating the geomagnetic timing of these relatively short-duration events to determine the detailed spreading history of the sub-basins of the SCS. These high-resolution near-seafloor magnetic survey lines are located close to the planned drilling sites of IODP Expedition 349 scheduled for January-March 2014.

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 DUNE Mission

NASA Astrophysics Data System (ADS)

Castander, F. J.

The Dark UNiverse Explorer (DUNE) is a wide-field imaging mission concept whose primary goal is the study of dark energy and dark matter with unprecedented precision. To this end, DUNE is optimised for weak gravitational lensing, and also uses complementary cosmological probes, such as baryonic oscillations, the integrated Sachs-Wolf effect, and cluster counts. Besides its observational cosmology goals, the mission capabilities of DUNE allow the study of galaxy evolution, galactic structure and the demographics of Earth-mass planets. DUNE is a medium class mission consisting of a 1.2m telescope designed to carry out an all-sky survey in one visible and three NIR bands. The final data of the DUNE mission will form a unique legacy for the astronomy community. DUNE has been selected jointly with SPACE for an ESA Assessment phase which has led to the Euclid merged mission concept which combines wide-field deep imaging with low resolution multi-object spectroscopy.

Massive stellar systems: observational challenges and perspectives in the E-ELT era

NASA Astrophysics Data System (ADS)

Bono, G.; Braga, V. F.; Ferraro, I.; Fiorentino, G.; Gilmozzi, R.; Iannicola, G.; Magurno, D.; Matsunaga, N.; Monelli, M.; Rastello, S.

2017-03-01

We introduce the empirical framework concerning optical and near-infrared (NIR) photometry of crowded stellar fields. In particular, we address the impact that linear detectors and analytical PSF played in improving the accuracy and the precision of multi-band color-magnitude diagrams (CMDs). We focus our attention on recent findings based on deep NIR images collected with Adaptive Optics (AO) systems at the 8-10m class telescopes and discuss pros and cons of the different approaches. We also discuss the estimate of the absolute age of globular clusters using a well defined knee along the lower main sequence. We mention the role which the current AO-assisted instruments will have in addressing longstanding astrophysical problems of the Galactic center. Finally, we outline the role of first generation of E-ELT instruments upon photometry and spectroscopy of crowded stellar fields.

Artificial intelligence in radiology.

PubMed

Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

2018-05-17

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

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

Kollias, Pavlos

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

Pulsating stars in ω Centauri. Near-IR properties and period-luminosity relations

NASA Astrophysics Data System (ADS)

Navarrete, Camila; Catelan, Márcio; Contreras Ramos, Rodrigo; Alonso-García, Javier; Gran, Felipe; Dékány, István; Minniti, Dante

2017-09-01

ω Centauri (NGC 5139) contains many variable stars of different types, including the pulsating type II Cepheids, RR Lyrae and SX Phoenicis stars. We carried out a deep, wide-field, near-infrared (IR) variability survey of ω Cen, using the VISTA telescope. We assembled an unprecedented homogeneous and complete J and KS near-IR catalog of variable stars in the field of ω Cen. In this paper we compare optical and near-IR light curves of RR Lyrae stars, emphasizing the main differences. Moreover, we discuss the ability of near-IR observations to detect SX Phoenicis stars given the fact that the amplitudes are much smaller in these bands compared to the optical. Finally, we consider the case in which all the pulsating stars in the three different variability types follow a single period-luminosity relation in the near-IR bands.

VizieR Online Data Catalog: SL2S galaxy-scale sample of lens candidates (Gavazzi+, 2014)

NASA Astrophysics Data System (ADS)

Gavazzi, R.; Marshall, P. J.; Treu, T.; Sonnenfeld, A.

2017-06-01

The CFHTLS5 is a major photometric survey of more than 450 nights over 5 yr (started on 2003 June 1) using the MegaCam wide-field imager, which covers ~1 deg2 on the sky, with a pixel size of 0.186". The CFHTLS has two components aimed at extragalactic studies: a Deep component consisting of four pencil-beam fields of 1 deg2 and a wide component consisting of four mosaics covering 150 deg2 in total. Both surveys are imaged through five broadband filters. The data are pre-reduced at CFHT with the Elixir pipeline (http://www.cfht.hawaii.edu/Instruments/Elixir/), which removes the instrumental artifacts in individual exposures. The CFHTLS images are then astrometrically calibrated, photometrically inter-calibrated, resampled and stacked by the Terapix group at the Institut d'Astrophysique de Paris, and finally archived at the Canadian Astronomy Data Centre. (2 data files).

Wave functions of symmetry-protected topological phases from conformal field theories

NASA Astrophysics Data System (ADS)

Scaffidi, Thomas; Ringel, Zohar

2016-03-01

We propose a method for analyzing two-dimensional symmetry-protected topological (SPT) wave functions using a correspondence with conformal field theories (CFTs) and integrable lattice models. This method generalizes the CFT approach for the fractional quantum Hall effect wherein the wave-function amplitude is written as a many-operator correlator in the CFT. Adopting a bottom-up approach, we start from various known microscopic wave functions of SPTs with discrete symmetries and show how the CFT description emerges at large scale, thereby revealing a deep connection between group cocycles and critical, sometimes integrable, models. We show that the CFT describing the bulk wave function is often also the one describing the entanglement spectrum, but not always. Using a plasma analogy, we also prove the existence of hidden quasi-long-range order for a large class of SPTs. Finally, we show how response to symmetry fluxes is easily described in terms of the CFT.

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.

Aerosol Retrievals Over Land and Water using Deep Blue Algorithm from SeaWiFS and MODIS during UAE2 Field Campaign

NASA Astrophysics Data System (ADS)

Hsu, N.

2005-12-01

The environment in Southwest Asia exhibits one of the most complex situations for aerosol remote sensing from space. Several air masses with different aerosol characteristics commonly converge in this region. In particular, there are often fine mode pollution particles generated from oil industry activities in the Persian Gulf colliding with coarse mode dust particles lifted from desert sources in the surrounding areas. During the course of the UAE field campaign (August-October, 2004), we provided near-real time information, calculated using the Deep Blue algorithm, of satellite aerosol optical thickness and Angstrom exponent over the Southwest Asia region, including the Arabian Peninsula, Iran, Afghanistan, Pakistan, and part of north Africa. In this paper, we will present results of aerosol characteristics retrieved from SeaWiFS and MODIS over the Arabian Peninsula, Persian Gulf, and the Arabian Sea during the UAE experiment. The spectral surface reflectance data base constructed using satellite reflectance from MODIS and SeaWiFS employed in our algorithm will be discussed. We will also compare the resulting satellite retrieved aerosol optical thickness and Angstrom exponent with those obtained from the ground based sun photometers from AERONET in the region. Finally, we will discuss the changes in shortwave and longwave fluxes at the top of atmosphere in response to changes in aerosol optical thickness (i.e. aerosol forcing).

SPECTROSCOPIC CONFIRMATION OF FAINT LYMAN BREAK GALAXIES NEAR REDSHIFT FIVE IN THE HUBBLE ULTRA DEEP FIELD

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

Rhoads, James E.; Malhotra, Sangeeta; Cohen, Seth

We present the faintest spectroscopically confirmed sample of z {approx} 5 Lyman break galaxies (LBGs) to date. The sample is based on slitless grism spectra of the Hubble Ultra Deep Field region from the Grism ACS Program for Extragalactic Science (GRAPES) and Probing Evolution and Reionization Spectroscopically (PEARS) projects, using the G800L grism on the Hubble Space Telescope Advanced Camera for Surveys. We report here confirmations of 39 galaxies, preselected as candidate LBGs using photometric selection criteria. We compare a 'traditional' V-dropout selection, based on the work of Giavalisco et al., to a more liberal one (with V - imore » > 0.9), and find that the traditional criteria are about 64% complete and 81% reliable. We also study the Ly{alpha} emission properties of our sample. We find that Ly{alpha} emission is detected in {approx}1/4 of the sample, and that the liberal V-dropout color selection includes {approx}55% of previously published line-selected Ly{alpha} sources. Finally, we examine our stacked two-dimensional spectra. We demonstrate that strong, spatially extended ({approx}1'') Ly{alpha} emission is not a generic property of these LBGs, but that a modest extension of the Ly{alpha} photosphere (compared to the starlight) may be present in those galaxies with prominent Ly{alpha} emission.« less

Fast subsurface fingerprint imaging with full-field optical coherence tomography system equipped with a silicon camera.

PubMed

Auksorius, Egidijus; Boccara, A Claude

2017-09-01

Images recorded below the surface of a finger can have more details and be of higher quality than the conventional surface fingerprint images. This is particularly true when the quality of the surface fingerprints is compromised by, for example, moisture or surface damage. However, there is an unmet need for an inexpensive fingerprint sensor that is able to acquire high-quality images deep below the surface in short time. To this end, we report on a cost-effective full-field optical coherent tomography system comprised of a silicon camera and a powerful near-infrared LED light source. The system, for example, is able to record 1.7  cm×1.7  cmen face images in 0.12 s with the spatial sampling rate of 2116 dots per inch and the sensitivity of 93 dB. We show that the system can be used to image internal fingerprints and sweat ducts with good contrast. Finally, to demonstrate its biometric performance, we acquired subsurface fingerprint images from 240 individual fingers and estimated the equal-error-rate to be ∼0.8%. The developed instrument could also be used in other en face deep-tissue imaging applications because of its high sensitivity, such as in vivo skin imaging. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Recognition of digital characteristics based new improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Meng; Xu, Guoqiang; Lin, Zihao

2017-08-01

In the field of digital signal processing, Estimating the characteristics of signal modulation parameters is an significant research direction. The paper determines the set of eigenvalue which can show the difference of the digital signal modulation based on the deep research of the new improved genetic algorithm. Firstly take them as the best gene pool; secondly, The best gene pool will be changed in the genetic evolvement by selecting, overlapping and eliminating each other; Finally, Adapting the strategy of futher enhance competition and punishment to more optimizer the gene pool and ensure each generation are of high quality gene. The simulation results show that this method not only has the global convergence, stability and faster convergence speed.

Identifying QCD Transition Using Deep Learning

NASA Astrophysics Data System (ADS)

Zhou, Kai; Pang, Long-gang; Su, Nan; Petersen, Hannah; Stoecker, Horst; Wang, Xin-Nian

2018-02-01

In this proceeding we review our recent work using supervised learning with a deep convolutional neural network (CNN) to identify the QCD equation of state (EoS) employed in hydrodynamic modeling of heavy-ion collisions given only final-state particle spectra ρ(pT, V). We showed that there is a traceable encoder of the dynamical information from phase structure (EoS) that survives the evolution and exists in the final snapshot, which enables the trained CNN to act as an effective "EoS-meter" in detecting the nature of the QCD transition.

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.

3He Abundances in Planetary Nebulae

NASA Astrophysics Data System (ADS)

Guzman-Ramirez, Lizette

2017-10-01

Determination of the 3He isotope is important to many fields of astrophysics, including stellar evolution, chemical evolution, and cosmology. The isotope is produced in stars which evolve through the planetary nebula phase. Planetary nebulae are the final evolutionary phase of low- and intermediate-mass stars, where the extensive mass lost by the star on the asymptotic giant branch is ionised by the emerging white dwarf. This ejecta quickly disperses and merges with the surrounding ISM. 3He abundances in planetary nebulae have been derived from the hyperfine transition of the ionised 3He, 3He+, at the radio rest frequency 8.665 GHz. 3He abundances in PNe can help test models of the chemical evolution of the Galaxy. Many hours have been put into trying to detect this line, using telescopes like the Effelsberg 100m dish of the Max Planck Institute for Radio Astronomy, the National Radio Astronomy Observatory (NRAO) 140-foot telescope, the NRAO Very Large Array, the Arecibo antenna, the Green Bank Telescope, and only just recently, the Deep Space Station 63 antenna from the Madrid Deep Space Communications Complex.

FAST Model Calibration and Validation of the OC5- DeepCwind Floating Offshore Wind System Against Wave Tank Test Data: Preprint

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

Wendt, Fabian F; Robertson, Amy N; Jonkman, Jason

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitchmore » and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.« less

Characterizing the Young Galaxies at Cosmic Dawn

NASA Astrophysics Data System (ADS)

Zheng, Wei

2013-10-01

We propose to analyze the data of the Hubble Frontier Fields, in order to discover and study galaxies at the highest redshifts and to an unprecedented depth. The redshift range of z 10-12 marks the beginning of the IGM reionization and remains as HST's last frontier. In the framework of the CLASH and related projects, our team has succeeded in finding the most distant galaxies. We will carry out a systematic search for galaxy candidates at z 10-12 in the proposed deep observations. At this redshift range, most of the spectral features are shifted longward of the WFC3/IR bands, and additional data are therefore needed in order to secure the candidates and study their intrinsic properties. We will {1} obtain deep photometry in complementary ground-based K-band observations; {2} estimate the global star-formation rate density; {3} measure the sources' UV continuum slope and {4} carry out ALMA observations to study the dust content. Finally, we will estimate the effect of these young galaxies in ionizing the IGM. Our study will serve as an ideal bridge between HST and JWST in exploring the cosmic dawn.

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.

Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach.

PubMed

Liu, Mengyun; Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng; Pan, Yuanjin

2017-12-08

After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to "see" which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas.

Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach

PubMed Central

Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng

2017-01-01

After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to “see” which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas. PMID:29292761

A search for higher twist effects in the hadronic distributions in deep inelastic muon proton scattering

NASA Astrophysics Data System (ADS)

Aubert, J. J.; Bassompierre, G.; Becks, K. H.; Benchouk, C.; Best, C.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Broll, C.; Brown, S.; Carr, J.; Clifft, R.; Cobb, J. H.; Coignet, G.; Combley, F.; Court, G. R.; D'Agostini, G.; Dau, W. D.; Davies, J. K.; Déclais, Y.; Dosselli, U.; Drees, J.; Edwards, A.; Edwards, M.; Favier, J.; Ferrero, M. I.; Flauger, W.; Forsbach, H.; Gabathuler, E.; Gamet, R.; Gayler, J.; Gerhardt, V.; Gössling, C.; Haas, J.; Hamacher, K.; Hayman, P.; Henckes, M.; Korbel, V.; Korzen, B.; Landgraf, U.; Leenen, M.; Maire, M.; Mohr, W.; Montgomery, H. E.; Moser, K.; Mount, R. P.; Nagy, E.; Nassalski, J.; Norton, P. R.; McNicholas, J.; Osborne, A. M.; Payre, P.; Peroni, C.; Peschel, H.; Pessard, H.; Pietrzyk, U.; Rith, K.; Schneegans, M.; Schneider, A.; Sloan, T.; Stier, H. E.; Stockhausen, W.; Thénard, J. M.; Thompson, J. C.; Urban, L.; Villers, M.; Wahlen, H.; Whalley, M.; Williams, D.; Williams, W. S. C.; Williamson, J.; Wimpenny, S. J.

1986-03-01

The hadronic distributions in Q 2, y, z, p T and ϕ in deep inelastic muon proton scattering have been studied to search for higher twist effects in the hadronic final state. The expected effects are not observed.

Breast cancer molecular subtype classification using deep features: preliminary results

NASA Astrophysics Data System (ADS)

Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

2018-02-01

Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

CMU DeepLens: deep learning for automatic image-based galaxy-galaxy strong lens finding

NASA Astrophysics Data System (ADS)

Lanusse, François; Ma, Quanbin; Li, Nan; Collett, Thomas E.; Li, Chun-Liang; Ravanbakhsh, Siamak; Mandelbaum, Rachel; Póczos, Barnabás

2018-01-01

Galaxy-scale strong gravitational lensing can not only provide a valuable probe of the dark matter distribution of massive galaxies, but also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as Large Synoptic Survey Telescope, Euclid and Wide-Field Infrared Survey Telescope. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on deep learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20 000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99 per cent, a completeness of 90 per cent can be achieved for lenses with Einstein radii larger than 1.4 arcsec and S/N larger than 20 on individual g-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens.

Drilling the centre of the Thuringian Basin, Germany, to decipher potential interrelation between shallow and deep fluid systems

NASA Astrophysics Data System (ADS)

Kukowski, Nina; Totsche, Kai Uwe; Abratis, Michael; Habisreuther, Annett; Ward, Timothy; Influins Drilling-Team

2014-05-01

To shed light on the coupled dynamics of near surface and deep fluids in a sedimentary basin on various scales, ranging from the pore scale to the extent of an entire basin, is of paramount importance to understand the functioning of sedimentary basins fluid systems and therefore e.g. drinking water supply. It is also the fundamental goal of INFLUINS (INtegrated FLuid dynamics IN Sedimentary basins), a research initiative of several groups from Friedrich-Schiller University of Jena and their partners. This research association is focusing on the nearby Thuringian basin, a well confined, small intra-continental sedimentary basin in Germany, as a natural geo laboratory. In a multidisciplinary approach, embracing different fields of geophysics like seismic reflection profiling or airborne geomagnetics, structural geology, sedimentology, hydrogeology, hydrochemistry and hydrology, remote sensing, microbiology and mineralogy, among others, and including both, field-based, laboratory-based and computer-based research, an integral INFLUINS topic is the potential interaction of aquifers within the basin and at its rims. The Thuringian basin, which is composed of sedimentary rocks from the latest Paleozoic and mainly Triassic, is particularly suited to undertake such research as it is of relative small size, about 50 to 100 km, easily accessible, and quite well known from previous studies, and therefore also a perfect candidate for deep drilling. After the acquisition of 76 km seismic reflection data in spring 2011, to get as much relevant data as possible from a deep drilling at the cross point between two seismic profiles with a limited financial budget, an optimated core sampling and measuring strategy including partial coring, borehole geophysics and pump tests as well as a drill hole design, which enables for later continuation of drilling down to the basement, had been developed. Drilling Triassic rocks from Keuper to lower Buntsandstein was successfully realised down to a final depth of 1179 m from late June to mid-September 2013. Here, we give an introduction into the layout of INFLUINS deep drilling together with a summary of preliminary results, e.g. on the nature of the boundaries between Muschelkalk and Buntsandstein, and between upper and middle Buntsandstein, a complete core recovery of upper Buntsandstein saliniferous formations as well as unexpectedly low porosity and permeability of potential aquifers.

Galaxy evolution at high-redshift: Millimeter-wavelength surveys with the AzTEC camera

NASA Astrophysics Data System (ADS)

Scott, Kimberly S.

Galaxies detected by their thermal dust emission at submillimeter (submm) and millimeter (mm) wavelengths comprise a population of massive, intensely star-forming systems in the early Universe. These "submm/mm- galaxies", or SMGs, likely represent an important phase in the assembly and/or evolution of massive galaxies and are thought to be the progenitors of massive elliptical galaxies. While their projected number density as a function of source brightness provides key constraints on models of galaxy evolution, SMG surveys carried out over the past twelve years with the first generation of submm/mm-wavelength cameras have not imaged a large enough area to sufficient depths to provide the statistical power needed to discriminate between competing galaxy evolution scenarios. In this dissertation, we present the results from SMG surveys carried out over the past four years using the new sensitive mm-wavelength camera AzTEC. With the improved mapping speed of the AzTEC camera combined with dedicated telescope time devoted to deep, large-area extragalactic surveys, we have tripled both the area surveyed towards blank- fields (that is, regions with no known galaxy over-densities) at submm/mm wavelengths and the total number of detected SMGs. Here, we describe the properties and performance of the AzTEC instrument while operating on the James Clerk Maxwell Telescope (JCMT) and the Atacama Submillimeter Telescope Experiment (ASTE). We then present the results from two of the blank-field regions imaged with AzTEC: the JCMT/COSMOS field, which we discovered is over- dense in the number of very bright SMGs, and the ASTE survey of the Great Observatories Origins Deep-South field, which represents one of the deepest surveys ever carried out at submm/mm wavelengths. Finally, we combine the results from all of the blank-fields imaged with AzTEC while operating on the JCMT and the ASTE to calculate the most accurate measurements to date of the SMG number counts.

Rangitoto Volcano Drilling Project: Life of a Small 'Monogenetic' Basaltic Shield in the Auckland Volcanic Field

NASA Astrophysics Data System (ADS)

Shane, P. A. R.; Linnell, T.; Lindsay, J. M.; Smith, I. E.; Augustinus, P. M.; Cronin, S. J.

2014-12-01

Rangitoto is a small basaltic shield volcano representing the most recent and most voluminous episode of volcanism in the Auckland Volcanic Field, New Zealand. Auckland City is built on the field, and hence, Rangitoto's importance in hazard-risk modelling. The symmetrical edifice, ~6 km wide and 260 m high, has volume of 1.78 km3. It comprises summit scoria cones and a lava field. However, the lack of deep erosion dissection has prevented the development of an eruptive stratigraphy. Previous studies suggested construction in a relatively short interval at 550-500 yrs BP. However, microscopic tephra have been interpreted as evidence of intermittent activity from 1498 +/- 140 to 504 +/- 6 yrs BP, a longevity of 1000 years. A 150-m-deep hole was drilled through the edifice in February 2014 to obtain a continuous core record. The result is an unparalleled stratigraphy of the evolution of a small shield volcano. The upper 128 m of core comprises at least 27 lava flows with thicknesses in the range 0.3-15 m, representing the main shield-building phase. Underlying marine sediments are interbedded with 8 m of pyroclastic lapilli, and a thin lava flow, representing the explosive phreatomagmatic birth of the volcano. Preliminary geochemical analyses reveal suite of relatively uniform transitional basalts (MgO = 8.1 to 9.7 wt %). However, 4 compositional groups are distinguished that were erupted in sequential order. High-MgO magmas were erupted first, followed by a two more heterogeneous groups displaying differentiation trends with time. Finally, distinct low-MgO basalts were erupted. Each magma type appears to represent a new magma batch. The core places the magma types in a time series, which can be correlated to the surface lava field. Hence, allowing a geometrical reconstruction of the shield growth. Additional petrologic investigations are providing insight to magmatic ascent processes, while radiocarbon and paleomagnetic secular variation studies will reveal the duration of activity.

CANDELS Visual Classifications: Scheme, Data Release, and First Results

NASA Technical Reports Server (NTRS)

Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Henry; Koo, David; Bassett, Robert;

Introducing Convective Cloud Microphysics to a Deep Convection Parameterization Facilitating Aerosol Indirect Effects

NASA Astrophysics Data System (ADS)

Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.

2012-12-01

Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.

Apache Clinical Text and Knowledge Extraction System (cTAKES) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The tool extracts deep phenotypic information from the clinical narrative at the document-, episode-, and patient-level. The final output is FHIR compliant patient-level phenotypic summary which can be consumed by research warehouses or the DeepPhe native visualization tool.

Planning of electroporation-based treatments using Web-based treatment-planning software.

PubMed

Pavliha, Denis; Kos, Bor; Marčan, Marija; Zupanič, Anže; Serša, Gregor; Miklavčič, Damijan

2013-11-01

Electroporation-based treatment combining high-voltage electric pulses and poorly permanent cytotoxic drugs, i.e., electrochemotherapy (ECT), is currently used for treating superficial tumor nodules by following standard operating procedures. Besides ECT, another electroporation-based treatment, nonthermal irreversible electroporation (N-TIRE), is also efficient at ablating deep-seated tumors. To perform ECT or N-TIRE of deep-seated tumors, following standard operating procedures is not sufficient and patient-specific treatment planning is required for successful treatment. Treatment planning is required because of the use of individual long-needle electrodes and the diverse shape, size and location of deep-seated tumors. Many institutions that already perform ECT of superficial metastases could benefit from treatment-planning software that would enable the preparation of patient-specific treatment plans. To this end, we have developed a Web-based treatment-planning software for planning electroporation-based treatments that does not require prior engineering knowledge from the user (e.g., the clinician). The software includes algorithms for automatic tissue segmentation and, after segmentation, generation of a 3D model of the tissue. The procedure allows the user to define how the electrodes will be inserted. Finally, electric field distribution is computed, the position of electrodes and the voltage to be applied are optimized using the 3D model and a downloadable treatment plan is made available to the user.

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

Final-state interactions in semi-inclusive deep inelastic scattering off the Deuteron

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

Wim Cosyn, Misak Sargsian

2011-07-01

Semi-inclusive deep inelastic scattering off the Deuteron with production of a slow nucleon in recoil kinematics is studied in the virtual nucleon approximation, in which the final state interaction (FSI) is calculated within general eikonal approximation. The cross section is derived in a factorized approach, with a factor describing the virtual photon interaction with the off-shell nucleon and a distorted spectral function accounting for the final-state interactions. One of the main goals of the study is to understand how much the general features of the diffractive high energy soft rescattering accounts for the observed features of FSI in deep inelasticmore » scattering (DIS). Comparison with the Jefferson Lab data shows good agreement in the covered range of kinematics. Most importantly, our calculation correctly reproduces the rise of the FSI in the forward direction of the slow nucleon production angle. By fitting our calculation to the data we extracted the W and Q{sup 2} dependences of the total cross section and slope factor of the interaction of DIS products, X, off the spectator nucleon. This analysis shows the XN scattering cross section rising with W and decreasing with an increase of Q{sup 2}. Finally, our analysis points at a largely suppressed off-shell part of the rescattering amplitude.« 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

Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning.

PubMed

DeChant, Chad; Wiesner-Hanks, Tyr; Chen, Siyuan; Stewart, Ethan L; Yosinski, Jason; Gore, Michael A; Nelson, Rebecca J; Lipson, Hod

2017-11-01

Northern leaf blight (NLB) can cause severe yield loss in maize; however, scouting large areas to accurately diagnose the disease is time consuming and difficult. We demonstrate a system capable of automatically identifying NLB lesions in field-acquired images of maize plants with high reliability. This approach uses a computational pipeline of convolutional neural networks (CNNs) that addresses the challenges of limited data and the myriad irregularities that appear in images of field-grown plants. Several CNNs were trained to classify small regions of images as containing NLB lesions or not; their predictions were combined into separate heat maps, then fed into a final CNN trained to classify the entire image as containing diseased plants or not. The system achieved 96.7% accuracy on test set images not used in training. We suggest that such systems mounted on aerial- or ground-based vehicles can help in automated high-throughput plant phenotyping, precision breeding for disease resistance, and reduced pesticide use through targeted application across a variety of plant and disease categories.

Rigorous Screening Technology for Identifying Suitable CO2 Storage Sites II

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

George J. Koperna Jr.; Vello A. Kuuskraa; David E. Riestenberg

2009-06-01

This report serves as the final technical report and users manual for the 'Rigorous Screening Technology for Identifying Suitable CO2 Storage Sites II SBIR project. Advanced Resources International has developed a screening tool by which users can technically screen, assess the storage capacity and quantify the costs of CO2 storage in four types of CO2 storage reservoirs. These include CO2-enhanced oil recovery reservoirs, depleted oil and gas fields (non-enhanced oil recovery candidates), deep coal seems that are amenable to CO2-enhanced methane recovery, and saline reservoirs. The screening function assessed whether the reservoir could likely serve as a safe, long-term CO2more » storage reservoir. The storage capacity assessment uses rigorous reservoir simulation models to determine the timing, ultimate storage capacity, and potential for enhanced hydrocarbon recovery. Finally, the economic assessment function determines both the field-level and pipeline (transportation) costs for CO2 sequestration in a given reservoir. The screening tool has been peer reviewed at an Electrical Power Research Institute (EPRI) technical meeting in March 2009. A number of useful observations and recommendations emerged from the Workshop on the costs of CO2 transport and storage that could be readily incorporated into a commercial version of the Screening Tool in a Phase III SBIR.« less

VizieR Online Data Catalog: Galaxy candidates in the Hubble Frontier Fields (Laporte+, 2016)

NASA Astrophysics Data System (ADS)

Laporte, N.; Infante, L.; Troncoso Iribarren, P.; Zheng, W.; Molino, A.; Bauer, F. E.; Bina, D.; Broadhurst, T.; Chilingarian, I.; Garcia, S.; Kim, S.; Marques-Chaves, R.; Moustakas, J.; Pello, R.; Perez-Fournon, I.; Shu, X.; Streblyanska, A.; Zitrin, A.

2018-02-01

The Frontier Field (FF) project is carried out using HST Director's Discretionary Time and will use 840 orbits during Cycles 21, 22, and 23 with six strong-lensing galaxy clusters as the main targets. For each cluster, the final data set is composed of three images from ACS/HST (F435W, F606W, and F814W) and four images from WFC3/HST (F105W, F125W, F140W, and F160W) reaching depths of ~29 mag at 5σ in a 0.4" diameter aperture. In this study, we used the final data release on MACS J0717.5+3745 (z=0.551, Ebeling et al. 2004ApJ...609L..49E; Medezinski et al. 2013ApJ...777...43M) made public on 2015 April 1. This third cluster in the FF list has been observed by HST through several observing programs, mainly those related to CLASH (ID: 12103, PI: M. Postman) and the FFs (ID: 13498, PI: J. Lotz). We matched the HST data with deep Spitzer/IRAC images obtained from observations (ID: 90259) carried out from 2013 August to 2015 January combined with archival data from 2007 November to 2013 June. (6 data files).

Final design of SITELLE: a wide-field imaging Fourier transform spectrometer for the Canada-France-Hawaii Telescope

NASA Astrophysics Data System (ADS)

Grandmont, F.; Drissen, L.; Mandar, Julie; Thibault, S.; Baril, Marc

2012-09-01

We report here on the current status of SITELLE, an imaging Fourier transform spectrometer to be installed on the Canada-France Hawaii Telescope in 2013. SITELLE is an Integral Field Unit (IFU) spectrograph capable of obtaining the visible (350 nm - 900 nm) spectrum of every pixel of a 2k x 2k CCD imaging a field of view of 11 x 11 arcminutes, with 100% spatial coverage and a spectral resolution ranging from R = 1 (deep panchromatic image) to R < 104 (for gas dynamics). SITELLE will cover a field of view 100 to 1000 times larger than traditional IFUs, such as GMOS-IFU on Gemini or the upcoming MUSE on the VLT. SITELLE follows on the legacy of BEAR, an imaging conversion of the CFHT FTS and the direct successor of SpIOMM, a similar instrument attached to the 1.6-m telescope of the Observatoire du Mont-Mégantic in Québec. SITELLE will be used to study the structure and kinematics of HII regions and ejecta around evolved stars in the Milky Way, emission-line stars in clusters, abundances in nearby gas-rich galaxies, and the star formation rate in distant galaxies.

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.

Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN.

PubMed

Xu, Xuanang; Zhou, Fugen; Liu, Bo

2018-03-19

Automatic approach for bladder segmentation from computed tomography (CT) images is highly desirable in clinical practice. It is a challenging task since the bladder usually suffers large variations of appearance and low soft-tissue contrast in CT images. In this study, we present a deep learning-based approach which involves a convolutional neural network (CNN) and a 3D fully connected conditional random fields recurrent neural network (CRF-RNN) to perform accurate bladder segmentation. We also propose a novel preprocessing method, called dual-channel preprocessing, to further advance the segmentation performance of our approach. The presented approach works as following: first, we apply our proposed preprocessing method on the input CT image and obtain a dual-channel image which consists of the CT image and an enhanced bladder density map. Second, we exploit a CNN to predict a coarse voxel-wise bladder score map on this dual-channel image. Finally, a 3D fully connected CRF-RNN refines the coarse bladder score map and produce final fine-localized segmentation result. We compare our approach to the state-of-the-art V-net on a clinical dataset. Results show that our approach achieves superior segmentation accuracy, outperforming the V-net by a significant margin. The Dice Similarity Coefficient of our approach (92.24%) is 8.12% higher than that of the V-net. Moreover, the bladder probability maps performed by our approach present sharper boundaries and more accurate localizations compared with that of the V-net. Our approach achieves higher segmentation accuracy than the state-of-the-art method on clinical data. Both the dual-channel processing and the 3D fully connected CRF-RNN contribute to this improvement. The united deep network composed of the CNN and 3D CRF-RNN also outperforms a system where the CRF model acts as a post-processing method disconnected from the CNN.

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

3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

PubMed

Montoya, J C; Li, Y; Strother, C; Chen, G-H

2018-05-01

Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral angiograms from a single contrast-enhanced C-arm conebeam CT acquisition in order to reduce image artifacts and radiation dose. A set of 105 3D rotational angiography examinations were randomly selected from an internal data base. All were acquired using a clinical system in conjunction with a standard injection protocol. More than 150 million labeled voxels from 35 subjects were used for training. A deep convolutional neural network was trained to classify each image voxel into 3 tissue types (vasculature, bone, and soft tissue). The trained deep learning angiography model was then applied for tissue classification into a validation cohort of 8 subjects and a final testing cohort of the remaining 62 subjects. The final vasculature tissue class was used to generate the 3D deep learning angiography images. To quantify the generalization error of the trained model, we calculated the accuracy, sensitivity, precision, and Dice similarity coefficients for vasculature classification in relevant anatomy. The 3D deep learning angiography and clinical 3D rotational angiography images were subjected to a qualitative assessment for the presence of intersweep motion artifacts. Vasculature classification accuracy and 95% CI in the testing dataset were 98.7% (98.3%-99.1%). No residual signal from osseous structures was observed for any 3D deep learning angiography testing cases except for small regions in the otic capsule and nasal cavity compared with 37% (23/62) of the 3D rotational angiographies. Deep learning angiography accurately recreated the vascular anatomy of the 3D rotational angiography reconstructions without a mask. Deep learning angiography reduced misregistration artifacts induced by intersweep motion, and it reduced radiation exposure required to obtain clinically useful 3D rotational angiography. © 2018 by American Journal of Neuroradiology.

Long-time predictability in disordered spin systems following a deep quench

NASA Astrophysics Data System (ADS)

Ye, J.; Gheissari, R.; Machta, J.; Newman, C. M.; Stein, D. L.

2017-04-01

We study the problem of predictability, or "nature vs nurture," in several disordered Ising spin systems evolving at zero temperature from a random initial state: How much does the final state depend on the information contained in the initial state, and how much depends on the detailed history of the system? Our numerical studies of the "dynamical order parameter" in Edwards-Anderson Ising spin glasses and random ferromagnets indicate that the influence of the initial state decays as dimension increases. Similarly, this same order parameter for the Sherrington-Kirkpatrick infinite-range spin glass indicates that this information decays as the number of spins increases. Based on these results, we conjecture that the influence of the initial state on the final state decays to zero in finite-dimensional random-bond spin systems as dimension goes to infinity, regardless of the presence of frustration. We also study the rate at which spins "freeze out" to a final state as a function of dimensionality and number of spins; here the results indicate that the number of "active" spins at long times increases with dimension (for short-range systems) or number of spins (for infinite-range systems). We provide theoretical arguments to support these conjectures, and also study analytically several mean-field models: the random energy model, the uniform Curie-Weiss ferromagnet, and the disordered Curie-Weiss ferromagnet. We find that for these models, the information contained in the initial state does not decay in the thermodynamic limit—in fact, it fully determines the final state. Unlike in short-range models, the presence of frustration in mean-field models dramatically alters the dynamical behavior with respect to the issue of predictability.

Long-time predictability in disordered spin systems following a deep quench.

PubMed

Ye, J; Gheissari, R; Machta, J; Newman, C M; Stein, D L

2017-04-01

We study the problem of predictability, or "nature vs nurture," in several disordered Ising spin systems evolving at zero temperature from a random initial state: How much does the final state depend on the information contained in the initial state, and how much depends on the detailed history of the system? Our numerical studies of the "dynamical order parameter" in Edwards-Anderson Ising spin glasses and random ferromagnets indicate that the influence of the initial state decays as dimension increases. Similarly, this same order parameter for the Sherrington-Kirkpatrick infinite-range spin glass indicates that this information decays as the number of spins increases. Based on these results, we conjecture that the influence of the initial state on the final state decays to zero in finite-dimensional random-bond spin systems as dimension goes to infinity, regardless of the presence of frustration. We also study the rate at which spins "freeze out" to a final state as a function of dimensionality and number of spins; here the results indicate that the number of "active" spins at long times increases with dimension (for short-range systems) or number of spins (for infinite-range systems). We provide theoretical arguments to support these conjectures, and also study analytically several mean-field models: the random energy model, the uniform Curie-Weiss ferromagnet, and the disordered Curie-Weiss ferromagnet. We find that for these models, the information contained in the initial state does not decay in the thermodynamic limit-in fact, it fully determines the final state. Unlike in short-range models, the presence of frustration in mean-field models dramatically alters the dynamical behavior with respect to the issue of predictability.

Stratification-Based Outlier Detection over the Deep Web.

PubMed

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

Stratification-Based Outlier Detection over the Deep Web

PubMed Central

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

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).

Deep Learning Methods for Quantifying Invasive Benthic Species in the Great Lakes

NASA Astrophysics Data System (ADS)

Billings, G.; Skinner, K.; Johnson-Roberson, M.

2017-12-01

In recent decades, invasive species such as the round goby and dreissenid mussels have greatly impacted the Great Lakes ecosystem. It is critical to monitor these species, model their distribution, and quantify the impacts on the native fisheries and surrounding ecosystem in order to develop an effective management response. However, data collection in underwater environments is challenging and expensive. Furthermore, the round goby is typically found in rocky habitats, which are inaccessible to standard survey techniques such as bottom trawling. In this work we propose a robotic system for visual data collection to automatically detect and quantify invasive round gobies and mussels in the Great Lakes. Robotic platforms equipped with cameras can perform efficient, cost-effective, low-bias benthic surveys. This data collection can be further optimized through automatic detection and annotation of the target species. Deep learning methods have shown success in image recognition tasks. However, these methods often rely on a labelled training dataset, with up to millions of labelled images. Hand labeling large numbers of images is expensive and often impracticable. Furthermore, data collected in the field may be sparse when only considering images that contain the objects of interest. It is easier to collect dense, clean data in controlled lab settings, but this data is not a realistic representation of real field environments. In this work, we propose a deep learning approach to generate a large set of labelled training data realistic of underwater environments in the field. To generate these images, first we draw random sample images of individual fish and mussels from a library of images captured in a controlled lab environment. Next, these randomly drawn samples will be automatically merged into natural background images. Finally, we will use a generative adversarial network (GAN) that incorporates constraints of the physical model of underwater light propagation to simulate the process of underwater image formation in various water conditions. The output of the GAN will be realistic looking annotated underwater images. This generated dataset of images will be used to train a classifier to identify round gobies and mussels in order to measure the biomass and abundance of these invasive species in the Great Lakes.

The MUSE Hubble Ultra Deep Field Survey. VI. The faint-end of the Lyα luminosity function at 2.91 < z < 6.64 and implications for reionisation

NASA Astrophysics Data System (ADS)

Drake, A. B.; Garel, T.; Wisotzki, L.; Leclercq, F.; Hashimoto, T.; Richard, J.; Bacon, R.; Blaizot, J.; Caruana, J.; Conseil, S.; Contini, T.; Guiderdoni, B.; Herenz, E. C.; Inami, H.; Lewis, J.; Mahler, G.; Marino, R. A.; Pello, R.; Schaye, J.; Verhamme, A.; Ventou, E.; Weilbacher, P. M.

2017-11-01

We present the deepest study to date of the Lyα luminosity function in a blank field using blind integral field spectroscopy from MUSE. We constructed a sample of 604 Lyα emitters (LAEs) across the redshift range 2.91 < z < 6.64 using automatic detection software in the Hubble Ultra Deep Field. The deep data cubes allowed us to calculate accurate total Lyα fluxes capturing low surface-brightness extended Lyα emission now known to be a generic property of high-redshift star-forming galaxies. We simulated realistic extended LAEs to fully characterise the selection function of our samples, and performed flux-recovery experiments to test and correct for bias in our determination of total Lyα fluxes. We find that an accurate completeness correction accounting for extended emission reveals a very steep faint-end slope of the luminosity function, α, down to luminosities of log10L erg s-1< 41.5, applying both the 1 /Vmax and maximum likelihood estimators. Splitting the sample into three broad redshift bins, we see the faint-end slope increasing from -2.03-0.07+ 1.42 at z ≈ 3.44 to -2.86-∞+0.76 at z ≈ 5.48, however no strong evolution is seen between the 68% confidence regions in L∗-α parameter space. Using the Lyα line flux as a proxy for star formation activity, and integrating the observed luminosity functions, we find that LAEs' contribution to the cosmic star formation rate density rises with redshift until it is comparable to that from continuum-selected samples by z ≈ 6. This implies that LAEs may contribute more to the star-formation activity of the early Universe than previously thought, as any additional intergalactic medium (IGM) correction would act to further boost the Lyα luminosities. Finally, assuming fiducial values for the escape of Lyα and LyC radiation, and the clumpiness of the IGM, we integrated the maximum likelihood luminosity function at 5.00

VizieR Online Data Catalog: WINGS: Deep optical phot. of 77 nearby clusters (Varela+, 2009)

NASA Astrophysics Data System (ADS)

Varela, J.; D'Onofrio, M.; Marmo, C.; Fasano, G.; Bettoni, D.; Cava, A.; Couch, J. W.; Dressler, A.; Kjaergaard, P.; Moles, M.; Pignatelli, E.; Poggianti, M. B.; Valentinuzzi, T.

2009-05-01

This is the second paper of a series devoted to the WIde Field Nearby Galaxy-cluster Survey (WINGS). WINGS is a long term project which is gathering wide-field, multi-band imaging and spectroscopy of galaxies in a complete sample of 77 X-ray selected, nearby clusters (0.04200deg). The main goal of this project is to establish a local reference for evolutionary studies of galaxies and galaxy clusters. This paper presents the optical (B,V) photometric catalogs of the WINGS sample and describes the procedures followed to construct them. We have paid special care to correctly treat the large extended galaxies (which includes the brightest cluster galaxies) and the reduction of the influence of the bright halos of very bright stars. We have constructed photometric catalogs based on wide-field images in B and V bands using SExtractor. Photometry has been performed on images in which large galaxies and halos of bright stars were removed after modeling them with elliptical isophotes. We publish deep optical photometric catalogs (90% complete at V21.7, which translates to ~ MV* + 6 at mean redshift), giving positions, geometrical parameters, and several total and aperture magnitudes for all the objects detected. For each field we have produced three catalogs containing galaxies, stars and objects of "unknown" classification (~16%). From simulations we found that the uncertainty of our photometry is quite dependent of the light profile of the objects with stars having the most robust photometry and de Vaucouleurs profiles showing higher uncertainties and also an additional bias of ~-0.2m. The star/galaxy classification of the bright objects (V<20) was checked visually making negligible the fraction of misclassified objects. For fainter objects, we found that simulations do not provide reliable estimates of the possible misclassification and therefore we have compared our data with that from deep counts of galaxies and star counts from models of our Galaxy. Both sets turned out to be consistent with our data within ~5% (in the ratio galaxies/total) up to V~24. Finally, we remark that the application of our special procedure to remove large halos improves the photometry of the large galaxies in our sample with respect to the use of blind automatic procedures and increases (~16%) the detection rate of objects projected onto them. (4 data files).

78 FR 13161 - Fisheries of the Exclusive Economic Zone Off Alaska; Gulf of Alaska; Final 2013 and 2014 Harvest...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-26

... halibut PSC trawl limits between the trawl gear deep-water and the shallow-water species fishery... for pollock, sablefish, deep-water flatfish, rex sole, Pacific ocean perch, northern rockfish... less than the ABCs for Pacific cod, shallow-water flatfish, arrowtooth flounder, flathead sole, ``other...

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

PubMed Central

Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references. PMID:29581722

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

PubMed

Yu, Yunlong; Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Smaller Footprint Drilling System for Deep and Hard Rock Environments; Feasibility of Ultra-High-Speed Diamond Drilling

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

Arnis Judzis; Homer Robertson; Alan Black

2006-06-22

The two phase program addresses long-term developments in deep well and hard rock drilling. TerraTek believes that significant improvements in drilling deep hard rock will be obtained by applying ultra-high rotational speeds (greater than 10,000 rpm). The work includes a feasibility of concept research effort aimed at development that will ultimately result in the ability to reliably drill ''faster and deeper'' possibly with smaller, more mobile rigs. The principle focus is on demonstration testing of diamond bits rotating at speeds in excess of 10,000 rpm to achieve high rate of penetration (ROP) rock cutting with substantially lower inputs of energymore » and loads. The significance of the ''ultra-high rotary speed drilling system'' is the ability to drill into rock at very low weights on bit and possibly lower energy levels. The drilling and coring industry today does not practice this technology. The highest rotary speed systems in oil field and mining drilling and coring today run less than 10,000 rpm-usually well below 5,000 rpm. This document details the progress at the end of Phase 1 on the program entitled ''Smaller Footprint Drilling System for Deep and Hard Rock Environments: Feasibility of Ultra-High-Speed Diamond Drilling'' for the period starting 1 March 2006 and concluding 30 June 2006. (Note: Results from 1 September 2005 through 28 February 2006 were included in the previous report (see Judzis, Black, and Robertson)). Summarizing the accomplished during Phase 1: {lg_bullet} TerraTek reviewed applicable literature and documentation and convened a project kickoff meeting with Industry Advisors in attendance (see Black and Judzis). {lg_bullet} TerraTek designed and planned Phase I bench scale experiments (See Black and Judzis). Some difficulties continued in obtaining ultra-high speed motors. Improvements were made to the loading mechanism and the rotational speed monitoring instrumentation. New drill bit designs were developed to provided a more consistent product with consistent performance. A test matrix for the final core bit testing program was completed. {lg_bullet} TerraTek concluded Task 3 ''Small-scale cutting performance tests.'' {sm_bullet} Significant testing was performed on nine different rocks. {sm_bullet} Five rocks were used for the final testing. The final tests were based on statistical design of experiments. {sm_bullet} Two full-faced bits, a small diameter and a large diameter, were run in Berea sandstone. {lg_bullet} Analysis of data was completed and indicates that there is decreased specific energy as the rotational speed increases (Task 4). Data analysis from early trials was used to direct the efforts of the final testing for Phase I (Task 5). {lg_bullet} Technology transfer (Task 6) was accomplished with technical presentations to the industry (see Judzis, Boucher, McCammon, and Black).« less

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.

Obtaining Unique, Comprehensive Deep Seismic Sounding Data Sets for CTBT Monitoring and Broad Seismological Studies

DTIC Science & Technology

2007-07-02

TYPE Final Report 3. DATES COVERED (From - To) 26-Sep-01 to 26-Jun-07 4. TITLE AND SUBTITLE OBTAINING UNIQUE, COMPREHENSIVE DEEP SEISMIC ... seismic records from 12 major Deep Seismic Sounding (DSS) projects acquired in 1970-1980’s in the former Soviet Union. The data include 3-component...records from 22 Peaceful Nuclear Explosions (PNEs) and over 500 chemical explosions recorded by a grid of linear, reversed seismic profiles covering a

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.

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

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.

PubMed

Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce

2018-06-15

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Super-resolved terahertz microscopy by knife-edge scan

NASA Astrophysics Data System (ADS)

Giliberti, V.; Flammini, M.; Ciano, C.; Pontecorvo, E.; Del Re, E.; Ortolani, M.

2017-08-01

We present a compact, all solid-state THz confocal microscope operating at 0.30 THz that achieves super-resolution by using the knife-edge scan approach. In the final reconstructed image, a lateral resolution of 60 μm ≍ λ/17 is demonstrated when the knife-edge is deep in the near-field of the sample surface. When the knife-edge is lifted up to λ/4 from the sample surface, a certain degree of super-resolution is maintained with a resolution of 0.4 mm, i.e. more than a factor 2 if compared to the diffraction-limited scheme. The present results open an interesting path towards super-resolved imaging with in-depth information that would be peculiar to THz microscopy systems.

The stratospheric arrival pair in infrasound propagation.

PubMed

Waxler, Roger; Evers, Läslo G; Assink, Jelle; Blom, Phillip

2015-04-01

The ideal case of a deep and well-formed stratospheric duct for long range infrasound propagation in the absence of tropospheric ducting is considered. A canonical form, that of a pair of arrivals, for ground returns of impulsive signals in a stratospheric duct is determined. The canonical form is derived from the geometrical acoustics approximation, and is validated and extended through full wave modeling. The full caustic structure of the field of ray paths is found and used to determine phase relations between the contributions to the wavetrain from different propagation paths. Finally, comparison with data collected from the 2005 fuel gas depot explosion in Buncefield, England is made. The correspondence between the theoretical results and the observations is shown to be quite good.

Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations

NASA Astrophysics Data System (ADS)

Liu, Dezi; Fu, Liping; Liu, Xiangkun; Radovich, Mario; Wang, Chao; Pan, Chuzhong; Fan, Zuhui; Covone, Giovanni; Vaccari, Mattia; Botticella, Maria Teresa; Capaccioli, Massimo; De Cicco, Demetra; Grado, Aniello; Miller, Lance; Napolitano, Nicola; Paolillo, Maurizio; Pignata, Giuliano

2018-05-01

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical ugri imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg2 down to rAB ˜ 26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for r-band images with seeing ≤ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of ˜3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of ˜0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to ˜0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.

Near Earth Asteroid Rendezvous (NEAR) Revised Eros Orbit Phase Trajectory Design

NASA Technical Reports Server (NTRS)

Helfrich, J; Miller, J. K.; Antreasian, P. G.; Carranza, E.; Williams, B. G.; Dunham, D. W.; Farquhar, R. W.; McAdams, J. V.

1999-01-01

Trajectory design of the orbit phase of the NEAR mission involves a new process that departs significantly from those procedures used in previous missions. In most cases, a precise spacecraft ephemeris is designed well in advance of arrival at the target body. For NEAR, the uncertainty in the dynamic environment around Eros does not allow the luxury of a precise spacecraft trajectory to be defined in advance. The principal cause of this uncertainty is the limited knowledge oi' the gravity field a,-id rotational state of Eros. As a result, the concept for the NEAR trajectory design is to define a number of rules for satisfying spacecraft, mission, and science constraints, and then apply these rules to various assumptions for the model of Eros. Nominal, high, and low Eros mass models are used for testing the trajectory design strategy and to bracket the ranges of parameter variations that are expected upon arrival at the asteroid. The final design is completed after arrival at Eros and determination of the actual gravity field and rotational state. As a result of the unplanned termination of the deep space rendezvous maneuver on December 20, 1998, the NEAR spacecraft passed within 3830 km of Eros on December 23, 1998. This flyby provided a brief glimpse of Eros, and allowed for a more accurate model of the rotational parameters and gravity field uncertainty. Furthermore, after the termination of the deep space rendezvous burn, contact with the spacecraft was lost and the NEAR spacecraft lost attitude control. During the subsequent gyrations of the spacecraft, hydrazine thruster firings were used to regain attitude control. This unplanned thruster activity used Much of the fuel margin allocated for the orbit phase. Consequently, minimizing fuel consumption is now even more important.

The second Herschel-ATLAS Data Release - III. Optical and near-infrared counterparts in the North Galactic Plane field

NASA Astrophysics Data System (ADS)

Furlanetto, C.; Dye, S.; Bourne, N.; Maddox, S.; Dunne, L.; Eales, S.; Valiante, E.; Smith, M. W.; Smith, D. J. B.; Ivison, R. J.; Ibar, E.

2018-05-01

This paper forms part of the second major public data release of the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS). In this work, we describe the identification of optical and near-infrared counterparts to the submillimetre detected sources in the 177 deg2 North Galactic Plane (NGP) field. We used the likelihood ratio method to identify counterparts in the Sloan Digital Sky Survey and in the United Kingdom InfraRed Telescope Imaging Deep Sky Survey within a search radius of 10 arcsec of the H-ATLAS sources with a 4σ detection at 250 μm. We obtained reliable (R ≥ 0.8) optical counterparts with r < 22.4 for 42 429 H-ATLAS sources (37.8 per cent), with an estimated completeness of 71.7 per cent and a false identification rate of 4.7 per cent. We also identified counterparts in the near-infrared using deeper K-band data which covers a smaller ˜25 deg2. We found reliable near-infrared counterparts to 61.8 per cent of the 250-μm-selected sources within that area. We assessed the performance of the likelihood ratio method to identify optical and near-infrared counterparts taking into account the depth and area of both input catalogues. Using catalogues with the same surface density of objects in the overlapping ˜25 deg2 area, we obtained that the reliable fraction in the near-infrared (54.8 per cent) is significantly higher than in the optical (36.4 per cent). Finally, using deep radio data which covers a small region of the NGP field, we found that 80-90 per cent of our reliable identifications are correct.

A Deep XMM-Newton Survey of M33: Point-source Catalog, Source Detection, and Characterization of Overlapping Fields

NASA Astrophysics Data System (ADS)

Williams, Benjamin F.; Wold, Brian; Haberl, Frank; Garofali, Kristen; Blair, William P.; Gaetz, Terrance J.; Kuntz, K. D.; Long, Knox S.; Pannuti, Thomas G.; Pietsch, Wolfgang; Plucinsky, Paul P.; Winkler, P. Frank

2015-05-01

We have obtained a deep 8 field XMM-Newton mosaic of M33 covering the galaxy out to the D25 isophote and beyond to a limiting 0.2-4.5 keV unabsorbed flux of 5 × 10-16 erg cm-2 s-1 (L \\gt 4 × 1034 erg s-1 at the distance of M33). These data allow complete coverage of the galaxy with high sensitivity to soft sources such as diffuse hot gas and supernova remnants (SNRs). Here, we describe the methods we used to identify and characterize 1296 point sources in the 8 fields. We compare our resulting source catalog to the literature, note variable sources, construct hardness ratios, classify soft sources, analyze the source density profile, and measure the X-ray luminosity function (XLF). As a result of the large effective area of XMM-Newton below 1 keV, the survey contains many new soft X-ray sources. The radial source density profile and XLF for the sources suggest that only ˜15% of the 391 bright sources with L \\gt 3.6 × 1035 erg s-1 are likely to be associated with M33, and more than a third of these are known SNRs. The log(N)-log(S) distribution, when corrected for background contamination, is a relatively flat power law with a differential index of 1.5, which suggests that many of the other M33 sources may be high-mass X-ray binaries. Finally, we note the discovery of an interesting new transient X-ray source, which we are unable to classify.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

PubMed

Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

2017-08-01

Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

Applying a punch with microridges in multistage deep drawing processes.

PubMed

Lin, Bor-Tsuen; Yang, Cheng-Yu

2016-01-01

The developers of high aspect ratio components aim to minimize the processing stages in deep drawing processes. This study elucidates the application of microridge punches in multistage deep drawing processes. A microridge punch improves drawing performance, thereby reducing the number of stages required in deep forming processes. As an example, the original eight-stage deep forming process for a copper cylindrical cup with a high aspect ratio was analyzed by finite element simulation. Microridge punch designs were introduced in Stages 4 and 7 to replace the original punches. In addition, Stages 3 and 6 were eliminated. Finally, these changes were verified through experiments. The results showed that the microridge punches reduced the number of deep drawing stages yielding similar thickness difference percentages. Further, the numerical and experimental results demonstrated good consistency in the thickness distribution.

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.

The effect of some heat treatment parameters on the dimensional stability of AISI D2

NASA Astrophysics Data System (ADS)

Surberg, Cord Henrik; Stratton, Paul; Lingenhöle, Klaus

2008-01-01

The tool steel AISI D2 is usually processed by vacuum hardening followed by multiple tempering cycles. It has been suggested that a deep cold treatment in between the hardening and tempering processes could reduce processing time and improve the final properties and dimensional stability. Hardened blocks were then subjected to various combinations of single and multiple tempering steps (520 and 540 °C) and deep cold treatments (-90, -120 and -150 °C). The greatest dimensional stability was achieved by deep cold treatments at the lowest temperature used and was independent of the deep cold treatment time.

Using SOTEM Method to Detect BIF Bodies Buried Under Very Thick and Conductive Quaternary Sediments, Huoqiu Deposit, China

NASA Astrophysics Data System (ADS)

Chen, Weiying; Xue, Guoqiang; Khan, Muhammad Younis; Li, Hai

2017-03-01

Huoqiu iron deposit is a typical Precambrian banded iron-formation (BIF) field which is located in the North China Craton (NCC). To detect the deep ore bodies around Dawangzhuang Village in Yingshang County, north of the Huoqiu deposit field, electromagnetic methods were tested. As the ore bodies are buried under very thick conductive Quaternary sediments, the use of EM methods is a great challenge. Short-offset transient electromagnetic method (SOTEM) was applied in the area as we wanted to test due to its detection depth and resolution. A 2D model was first built according to the geology information and magnetic measurement results. Then, 2D forward and 1D inversion were carried out using FDTD and Occam's algorithm, respectively. The synthetic modeling results helped us with the survey design and interpretation. Two 1400-m-long survey lines with offset of 500 and 1000 m were laid perpendicular to the BIF's strike, and the transmitting parameters were selected by a test measurement at the vicinity of a local village. Finally, the structure of survey area and BIF bodies were determined based on the 1D inversion results of real data, and showed a consistency with the subsequent drill results. Our application of SOTEM in detecting hidden BIF buried under very thick conductive layer has shown that the method is capable of penetrating great depth more than 1000 m even in a very conductive environment and will be an effective tool for deep resources investigation.

Cloud transitions: comparison of temporal variation in the southeastern Pacific with the spatial variation in the northeastern Pacific at low latitudes

DOE PAGES

Yu, Haiyang; Zhang, Minghua; Lin, Wuyin; ...

2016-10-14

The seasonal variation of clouds in the southeastern equatorial Pacific (SEP) is analysed and compared with the spatial variation of clouds in the northeastern Pacific along the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI) transect. A ‘seasonal cloud transition’ – from stratocumulus to shallow cumulus and eventually to deep convection – is found in the SEP from September to April, which is similar to the spatial cloud transition along the GPCI transect from the California coast to the equator. It is shown that this seasonal cloud transition in themore » SEP is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence, which are all similar to the spatial variation of these fields along the GPCI transect. There was a difference found such that the SEP cloud transition is associated with decreasing surface wind speed and surface latent heat flux, weaker larger-scale upward motion and convective instability, which lead to less deepening of the low clouds and less frequent deep convection than those in the GPCI transect. Finally, the seasonal cloud transition in the SEP provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double inter-tropical convergence zone (ITCZ) in most models.« less

Cloud transitions: comparison of temporal variation in the southeastern Pacific with the spatial variation in the northeastern Pacific at low latitudes

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

Yu, Haiyang; Zhang, Minghua; Lin, Wuyin

The seasonal variation of clouds in the southeastern equatorial Pacific (SEP) is analysed and compared with the spatial variation of clouds in the northeastern Pacific along the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI) transect. A ‘seasonal cloud transition’ – from stratocumulus to shallow cumulus and eventually to deep convection – is found in the SEP from September to April, which is similar to the spatial cloud transition along the GPCI transect from the California coast to the equator. It is shown that this seasonal cloud transition in themore » SEP is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence, which are all similar to the spatial variation of these fields along the GPCI transect. There was a difference found such that the SEP cloud transition is associated with decreasing surface wind speed and surface latent heat flux, weaker larger-scale upward motion and convective instability, which lead to less deepening of the low clouds and less frequent deep convection than those in the GPCI transect. Finally, the seasonal cloud transition in the SEP provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double inter-tropical convergence zone (ITCZ) in most models.« less

MAVEN observations of dayside peak electron densities in the ionosphere of Mars

NASA Astrophysics Data System (ADS)

Vogt, Marissa F.; Withers, Paul; Fallows, Kathryn; Andersson, Laila; Girazian, Zachary; Mahaffy, Paul R.; Benna, Mehdi; Elrod, Meredith K.; Connerney, John E. P.; Espley, Jared R.; Eparvier, Frank G.; Jakosky, Bruce M.

2017-01-01

The peak electron density in the dayside Martian ionosphere is a valuable diagnostic of the state of the ionosphere. Its dependence on factors like the solar zenith angle, ionizing solar irradiance, neutral scale height, and electron temperature has been well studied. The Mars Atmosphere and Volatile EvolutioN spacecraft's September 2015 "deep dip" orbits, in which the orbital periapsis was lowered to 125 km, provided the first opportunity since Viking to sample in situ a complete dayside electron density profile including the main peak. Here we present peak electron density measurements from 37 deep dip orbits and describe conditions at the altitude of the main peak, including the electron temperature and composition of the ionosphere and neutral atmosphere. We find that the dependence of the peak electron density and the altitude of the main peak on solar zenith angle are well described by analytical photochemical theory. Additionally, we find that the electron temperatures at the main peak display a dependence on solar zenith angle that is consistent with the observed variability in the peak electron density. Several peak density measurements were made in regions of large crustal magnetic field, but there is no clear evidence that the crustal magnetic field strength influences the peak electron density, peak altitude, or electron temperature. Finally, we find that the fractional abundance of O2+ and CO2+ at the peak altitude is variable but that the two species together consistently represent 95% of the total ion density.

A 1-D mechanistic model for the evolution of earthflow-prone hillslopes

NASA Astrophysics Data System (ADS)

Booth, Adam M.; Roering, Josh J.

2011-12-01

In mountainous terrain, deep-seated landslides transport large volumes of material on hillslopes, exerting a dominant control on erosion rates and landscape form. Here, we develop a mathematical landscape evolution model to explore interactions between deep-seated earthflows, soil creep, and gully processes at the drainage basin scale over geomorphically relevant (>103 year) timescales. In the model, sediment flux or incision laws for these three geomorphic processes combine to determine the morphology of actively uplifting and eroding steady state topographic profiles. We apply the model to three sites, one in the Gabilan Mesa, California, with no earthflow activity, and two along the Eel River, California, with different lithologies and varying levels of historic earthflow activity. Representative topographic profiles from these sites are consistent with model predictions in which the magnitude of a dimensionless earthflow number, based on a non-Newtonian flow rheology, reflects the magnitude of recent earthflow activity on the different hillslopes. The model accurately predicts the behavior of earthflow collection and transport zones observed in the field and estimates long-term average sediment fluxes that are due to earthflows, in agreement with historical rates at our field sites. Finally, our model predicts that steady state hillslope relief in earthflow-prone terrain increases nonlinearly with the tectonic uplift rate, suggesting that the mean hillslope angle may record uplift rate in earthflow-prone landscapes even at high uplift rates, where threshold slope processes normally limit further topographic development.

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

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.

RELICS of the Cosmic Dawn

NASA Astrophysics Data System (ADS)

Bradac, Marusa; Coe, Dan; Strait, Victoria; Salmon, Brett; Hoag, Austin; Bradley, Larry; Ryan, Russell; Dawson, Will; Zitrin, Adi; Jones, Christine; Sharon, Keren; Trenti, Michele; Stark, Daniel; Oesch, Pascal; Lam, Danel; Carrasco Nunez, Daniela Patricia; Paterno-Mahler, Rachel; Frye, Brenda

2018-05-01

When did galaxies start forming stars? What is the role of distant galaxies in galaxy formation models and epoch of reionization? Recent observations indicate at least two critical puzzles in these studies. (1) First galaxies might have started forming stars earlier than previously thought (<400Myr after the Big Bang). (2) It is still unclear what is their star formation history and whether these galaxies can reionize the Universe. Accurate knowledge of stellar masses, ages, and star formation rates at this epoch requires measuring both rest-frame UV and optical light, which only Spitzer and HST can probe at z 6-11 for a large enough sample of typical galaxies. To address this cosmic puzzle, we propose to complete deep Spitzer imaging of the fields behind the 10 most powerful cosmic telescopes selected using HST, Spitzer, and Planck data from the RELICS and SRELICS programs (Reionization Lensing Cluster Survey; 41 clusters, 190 HST orbits, 440 Spitzer hours). 6 clusters out of 10 are still lacking deep data. This proposal will be a valuable Legacy complement to the existing IRAC deep surveys, and it will open up a new parameter space by probing the ordinary yet magnified population with much improved sample variance. The program will allow us to study stellar properties of a large number, 60 galaxies at z 6-11. Deep Spitzer data will be crucial to unambiguously measure their stellar properties (age, SFR, M*). Finally this proposal will establish the presence (or absence) of an unusually early established stellar population, as was recently observed in MACS1149JD at z 9. If confirmed in a larger sample, this result will require a paradigm shift in our understanding of the earliest star formation.

Photometric redshifts for the CFHTLS T0004 deep and wide fields

NASA Astrophysics Data System (ADS)

Coupon, J.; Ilbert, O.; Kilbinger, M.; McCracken, H. J.; Mellier, Y.; Arnouts, S.; Bertin, E.; Hudelot, P.; Schultheis, M.; Le Fèvre, O.; Le Brun, V.; Guzzo, L.; Bardelli, S.; Zucca, E.; Bolzonella, M.; Garilli, B.; Zamorani, G.; Zanichelli, A.; Tresse, L.; Aussel, H.

2009-06-01

Aims: We compute photometric redshifts in the fourth public release of the Canada-France-Hawaii Telescope Legacy Survey. This unique multi-colour catalogue comprises u^*, g', r', i', z' photometry in four deep fields of 1 deg2 each and 35 deg2 distributed over three wide fields. Methods: We used a template-fitting method to compute photometric redshifts calibrated with a large catalogue of 16 983 high-quality spectroscopic redshifts from the VVDS-F02, VVDS-F22, DEEP2, and the zCOSMOS surveys. The method includes correction of systematic offsets, template adaptation, and the use of priors. We also separated stars from galaxies using both size and colour information. Results: Comparing with galaxy spectroscopic redshifts, we find a photometric redshift dispersion, σΔ z/(1+z_s), of 0.028-0.30 and an outlier rate, |Δ z| ≥ 0.15× (1+z_s), of 3-4% in the deep field at i'_AB < 24. In the wide fields, we find a dispersion of 0.037-0.039 and an outlier rate of 3-4% at i'_AB < 22.5. Beyond i'_AB = 22.5 in the wide fields the number of outliers rises from 5% to 10% at i'_AB < 23 and i'_AB < 24, respectively. For the wide sample the systematic redshift bias stays below 1% to i'_AB < 22.5, whereas we find no significant bias in the deep fields. We investigated the effect of tile-to-tile photometric variations and demonstrated that the accuracy of our photometric redshifts is reduced by at most 21%. Application of our star-galaxy classifier reduced the contamination by stars in our catalogues from 60% to 8% at i'_AB < 22.5 in our field with the highest stellar density while keeping a complete galaxy sample. Our CFHTLS T0004 photometric redshifts are distributed to the community. Our release includes 592891 (i'_AB < 22.5) and 244701 (i'_AB < 24) reliable galaxy photometric redshifts in the wide and deep fields, respectively. 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.

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.

Deep-tow geophysical survey above large exhumed mantle domains of the eastern Southwest Indian ridge

NASA Astrophysics Data System (ADS)

Bronner, A.; Munschy, M.; Sauter, D.; Carlut, J.; Searle, R.; Cannat, M.

2012-04-01

The recent discovery of a new type of seafloor, the "smooth seafloor", formed with no or very little volcanic activity along the easternmost part of the ultra-slow spreading Southwest Indian ridge (SWIR) shows an unexpected complexity in processes of generation of the oceanic lithosphere. There, detachment faulting is thought to be a mechanism for efficient exhumation of deep-seated mantle rocks. We present here a deep-tow geological-geophysical survey over smooth seafloor at the eastern SWIR (62-64°N) combining multibeam bathymetric data, magnetic data, geology mapping from sidescan sonar (TOBI) images and results from dredge sampling. We introduce a new type of calibration approach for deep-tow fluxgate magnetometer. We show that magnetic data can be corrected from the magnetic effect of the vehicle with no recourse to its attitude (pitch, roll and heading) but only using the 3 components recorded by the magnetometer and an approximation of the scalar intensity of the Earth magnetic field. The collected dredge samples as well as the sidescan sonar images confirm the presence of large areas of exhumed mantle-derived peridodites surrounded by a few volcanic constructions. We investigate the possibility that magnetic anomalies are either caused by serpentinized peridotites and/or magmatic intrusions. We show that the magnetic signature of the smooth seafloor is clearly weaker than the surrounding volcanic areas. Moreover, the calculated magnetization of a source layer as well as the comparison between deep-tow and sea-surface magnetic data argue for strong East-West variability in the distribution of the magnetized sources. This variability may result from fluid-rock interactions along the detachment faults as well as from the occurrence of small sized and thin volcanic patches and thus questions the seafloor spreading origin of the corresponding magnetic anomalies. Finally, we provide magnetic arguments, as calculation of block rotation or spreading asymmetry in order to better constrain tectonic mechanisms that occur during the formation of this peculiar seafloor.

Deep-tow magnetic survey above large exhumed mantle domains of the eastern Southwest Indian ridge

NASA Astrophysics Data System (ADS)

Bronner, A.; Munschy, M.; Carlut, J. H.; Searle, R. C.; Sauter, D.; Cannat, M.

2011-12-01

The recent discovery of a new type of seafloor, the "smooth seafloor", formed with no or very little volcanic activity along the ultra-slow spreading Southwest Indian ridge (SWIR) shows an unexpected complexity in processes of generation of the oceanic lithosphere. There, detachment faulting is thought to be a mechanism for efficient exhumation of deep-seated mantle rocks. We present here a deep-tow geological-geophysical survey over smooth seafloor at the eastern SWIR (62-64°N) combining magnetic data, geology mapping from side-scan sonar images and results from dredge sampling. We introduce a new type of calibration approach for deep-tow fluxgate magnetometer. We show that magnetic data can be corrected from the magnetic effect of the vehicle with no recourse to its attitude (pitch, roll and heading) but only using the 3 components recorded by the magnetometer and an approximation of the scalar intensity of the Earth magnetic field. The collected dredge samples as well as the side-scan images confirm the presence of large areas of exhumed mantle-derived peridodites surrounded by a few volcanic constructions. This allows us to hypothesis that magnetic anomalies are caused by serpentinized peridotites or magmatic intrusions. We show that the magnetic signature of the smooth seafloor is clearly weaker than the surrounding volcanic areas. Moreover, the calculated magnetization of a source layer as well as the comparison between deep-tow and sea-surface magnetic data argue for strong East-West variability in the distribution of the magnetized sources. This variability may results from fluid-rocks interaction along the detachment faults as well as from the repartition of the volcanic material and thus questions the seafloor spreading origin of the corresponding magnetic anomalies. Finally, we provide magnetic arguments, as calculation of block rotation or spreading asymmetry in order to better constrain tectonic mechanisms that occur during the formation of this peculiar seafloor.

The DEEP2 Galaxy Redshift Survey: The Voronoi-Delaunay Method Catalog of Galaxy Groups

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

Gerke, Brian F.; /UC, Berkeley; Newman, Jeffrey A.

2012-02-14

We use the first 25% of the DEEP2 Galaxy Redshift Survey spectroscopic data to identify groups and clusters of galaxies in redshift space. The data set contains 8370 galaxies with confirmed redshifts in the range 0.7 {<=} z {<=} 1.4, over one square degree on the sky. Groups are identified using an algorithm (the Voronoi-Delaunay Method) that has been shown to accurately reproduce the statistics of groups in simulated DEEP2-like samples. We optimize this algorithm for the DEEP2 survey by applying it to realistic mock galaxy catalogs and assessing the results using a stringent set of criteria for measuring group-findingmore » success, which we develop and describe in detail here. We find in particular that the group-finder can successfully identify {approx}78% of real groups and that {approx}79% of the galaxies that are true members of groups can be identified as such. Conversely, we estimate that {approx}55% of the groups we find can be definitively identified with real groups and that {approx}46% of the galaxies we place into groups are interloper field galaxies. Most importantly, we find that it is possible to measure the distribution of groups in redshift and velocity dispersion, n({sigma}, z), to an accuracy limited by cosmic variance, for dispersions greater than 350 km s{sup -1}. We anticipate that such measurements will allow strong constraints to be placed on the equation of state of the dark energy in the future. Finally, we present the first DEEP2 group catalog, which assigns 32% of the galaxies to 899 distinct groups with two or more members, 153 of which have velocity dispersions above 350 km s{sup -1}. We provide locations, redshifts and properties for this high-dispersion subsample. This catalog represents the largest sample to date of spectroscopically detected groups at z {approx} 1.« less

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.

75 FR 34929 - Safety Zones: Neptune Deep Water Port, Atlantic Ocean, Boston, MA

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-21

...-AA00 Safety Zones: Neptune Deep Water Port, Atlantic Ocean, Boston, MA AGENCY: Coast Guard, DHS. ACTION..., Boston, MA; Final Rule (USCG-2009-0589), to protect vessels from the hazard posed by the presence of the... read as follows: Sec. 165.T01-0542 Safety Zones: Neptune Deepwater Port, Atlantic Ocean, Boston, MA. (a...

Conceptual Tutoring Software for Promoting Deep Learning: A Case Study

ERIC Educational Resources Information Center

Stott, Angela; Hattingh, Annemarie

2015-01-01

The paper presents a case study of the use of conceptual tutoring software to promote deep learning of the scientific concept of density among 50 final year pre-service student teachers in a natural sciences course in a South African university. Individually-paced electronic tutoring is potentially an effective way of meeting the students' varied…

The Star Formation History of SHADES Sources

NASA Astrophysics Data System (ADS)

Aretxaga, Itziar; SHADES Consortium; AzTEC Team

2006-12-01

We present the redshift distribution of the SHADES 850um selected galaxy population based on the rest-frame radio-mm-FIR colours of 120 robustly detected sources in the Lockman Hole East (LH) and Subaru XMM-Newton Deep Field (SXDF). The redshift of sources constrained with at least two photometric bands peaks at z 2.4 and has a near-Gaussian distribution. The inclusion of sources detected only at 850um, for which only very weak redshift constraints are available, leads to the possibility of a high-redshit tail. We find a small difference between the redshift distributions in the two fields; the SXDF peaking at a slightly lower redshift than the LH, which we mainly attribute to the noise properties of the photometry used. We discuss the impact of the AzTEC data on the further precission of these results. Finally we present a brief comparison with sub-mm galaxy formation models and their predicted and assumed redshift distributions and derive the contribution of these sources to the star formation rate density at different epochs.

Estudio fotométrico de candidatos a cúmulos globulares en NGC 1316

NASA Astrophysics Data System (ADS)

Sesto, L. A.; Faifer, F. R.; Forte, J. C.

We present the first results obtained in the context of a photometric study of the globular cluster population associated with the early-type giant galaxy NGC 1316. We analyze here the first of a total of ten fields that form a deep mosaic, which was obtained using the Gemini Multi-Object Spectrograph camera. This field contains the nucleus of the galaxy. As a result of psf photometry, we construct color-magnitude and color-color diagrams, as well as spatial distribution and integrated color diagrams. The analysis shows that there is no clear evidence of bimodality in the studied region. However, we confirm the presence of a probable young subpopulation of clusters in this system. Finally, we present color maps of the galaxy, showing the presence of an interesting structure produced by interstellar dust which is surrounding the nucleus of NGC 1316. Our results indicate that no significant effect is observed due to dust on the objects in the studied region. FULL TEXT IN SPANISH

Laboratory Astrophysics Prize: Laboratory Astrophysics with Nuclei

NASA Astrophysics Data System (ADS)

Wiescher, Michael

2018-06-01

Nuclear astrophysics is concerned with nuclear reaction and decay processes from the Big Bang to the present star generation controlling the chemical evolution of our universe. Such nuclear reactions maintain stellar life, determine stellar evolution, and finally drive stellar explosion in the circle of stellar life. Laboratory nuclear astrophysics seeks to simulate and understand the underlying processes using a broad portfolio of nuclear instrumentation, from reactor to accelerator from stable to radioactive beams to map the broad spectrum of nucleosynthesis processes. This talk focuses on only two aspects of the broad field, the need of deep underground accelerator facilities in cosmic ray free environments in order to understand the nucleosynthesis in stars, and the need for high intensity radioactive beam facilities to recreate the conditions found in stellar explosions. Both concepts represent the two main frontiers of the field, which are being pursued in the US with the CASPAR accelerator at the Sanford Underground Research Facility in South Dakota and the FRIB facility at Michigan State University.

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.

Numerical and experimental results on the spectral wave transfer in finite depth

NASA Astrophysics Data System (ADS)

Benassai, Guido

2016-04-01

Determination of the form of the one-dimensional surface gravity wave spectrum in water of finite depth is important for many scientific and engineering applications. Spectral parameters of deep water and intermediate depth waves serve as input data for the design of all coastal structures and for the description of many coastal processes. Moreover, the wave spectra are given as an input for the response and seakeeping calculations of high speed vessels in extreme sea conditions and for reliable calculations of the amount of energy to be extracted by wave energy converters (WEC). Available data on finite depth spectral form is generally extrapolated from parametric forms applicable in deep water (e.g., JONSWAP) [Hasselmann et al., 1973; Mitsuyasu et al., 1980; Kahma, 1981; Donelan et al., 1992; Zakharov, 2005). The present paper gives a contribution in this field through the validation of the offshore energy spectra transfer from given spectral forms through the measurement of inshore wave heights and spectra. The wave spectra on deep water were recorded offshore Ponza by the Wave Measurement Network (Piscopia et al.,2002). The field regressions between the spectral parameters, fp and the nondimensional energy with the fetch length were evaluated for fetch-limited sea conditions. These regressions gave the values of the spectral parameters for the site of interest. The offshore wave spectra were transfered from the measurement station offshore Ponza to a site located offshore the Gulf of Salerno. The offshore local wave spectra so obtained were transfered on the coastline with the TMA model (Bouws et al., 1985). Finally the numerical results, in terms of significant wave heights, were compared with the wave data recorded by a meteo-oceanographic station owned by Naples Hydrographic Office on the coastline of Salerno in 9m depth. Some considerations about the wave energy to be potentially extracted by Wave Energy Converters were done and the results were discussed.

Deep CFHT Y-band Imaging of VVDS-F22 Field. I. Data Products and Photometric Redshifts

NASA Astrophysics Data System (ADS)

Liu, Dezi; Yang, Jinyi; Yuan, Shuo; Wu, Xue-Bing; Fan, Zuhui; Shan, Huanyuan; Yan, Haojing; Zheng, Xianzhong

2017-02-01

We present our deep Y-band imaging data of a 2 square degree field within the F22 region of the VIMOS VLT Deep Survey. The observations were conducted using the WIRCam instrument mounted at the Canada-France-Hawaii Telescope (CFHT). The total on-sky time was 9 hr, distributed uniformly over 18 tiles. The scientific goals of the project are to select faint quasar candidates at redshift z> 2.2 and constrain the photometric redshifts for quasars and galaxies. In this paper, we present the observation and the image reduction, as well as the photometric redshifts that we derived by combining our Y-band data with the CFHTLenS {u}* g\\prime r\\prime I\\prime z\\prime optical data and UKIDSS DXS JHK near-infrared data. With the J-band image as a reference, a total of ˜80,000 galaxies are detected in the final mosaic down to a Y-band 5σ point-source limiting depth of 22.86 mag. Compared with the ˜3500 spectroscopic redshifts, our photometric redshifts for galaxies with z< 1.5 and I\\prime ≲ 24.0 mag have a small systematic offset of | {{Δ }}z| ≲ 0.2, 1σ scatter 0.03< {σ }{{Δ }z}< 0.06, and less than 4.0% of catastrophic failures. We also compare with the CFHTLenS photometric redshifts and find that ours are more reliable at z≳ 0.6 because of the inclusion of the near-infrared bands. In particular, including the Y-band data can improve the accuracy at z˜ 1.0{--}2.0 because the location of the 4000 Å break is better constrained. The Y-band images, the multiband photometry catalog, and the photometric redshifts are released at http://astro.pku.edu.cn/astro/data/DYI.html.

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.

Impacts of Carrier Transport and Deep Level Defects on Delayed Cathodoluminescence in Droop-Mitigating InGaN/GaN LEDs

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

Zhao, Zhibo; Singh, Akshay; Chesin, Jordan

Prevalent droop mitigation strategies in InGaN-based LEDs require structural and/or compositional changes in the active region but are accompanied by a detrimental reduction in external quantum efficiency (EQE) due to increased Shockley-Read-Hall recombination. Understanding the optoelectronic impacts of structural modifications in InGaN/GaN quantum wells (QW) remains critical for emerging high-power LEDs. In this work, we use a combination of electron microscopy tools along with standard electrical characterization to investigate a wide range of low-droop InGaN/GaN QW designs. We find that chip-scale EQE is uncorrelated with extended well-width fluctuations observed in scanning transmission electron microscopy. Further, we observe delayed cathodoluminescence (CL)more » response from designs in which calculated band profiles suggest facile carrier escape from individual QWs. Samples with the slowest CL responses also exhibit the lowest EQEs and highest QW defect densities in deep level optical spectroscopy. We propose a model in which the electron beam (i) passivates deep level defect states and (ii) drives charge carrier accumulation and subsequent reduction of the built-in field across the multi-QW active region, resulting in delayed radiative recombination. Finally, we correlate CL rise dynamics with capacitance-voltage measurements and show that certain early-time components of the CL dynamics reflect the open circuit carrier population within one or more QWs.« less

Revisiting Stephan's Quintet with deep optical images

NASA Astrophysics Data System (ADS)

Duc, Pierre-Alain; Cuillandre, Jean-Charles; Renaud, Florent

2018-03-01

Stephan's Quintet, a compact group of galaxies, is often used as a laboratory to study a number of phenomena, including physical processes in the interstellar medium, star formation, galaxy evolution, and the formation of fossil groups. As such, it has been subject to intensive multiwavelength observation campaigns. Yet, models lack constrains to pin down the role of each galaxy in the assembly of the group. We revisit here this system with multiband deep optical images obtained with MegaCam on the Canada-France-Hawaii Telescope (CFHT), focusing on the detection of low surface brightness (LSB) structures. They reveal a number of extended LSB features, some new, and some already visible in published images but not discussed before. An extended diffuse, reddish, lopsided, halo is detected towards the early-type galaxy NGC 7317, the role of which had so far been ignored in models. The presence of this halo made of old stars may indicate that the group formed earlier than previously thought. Finally, a number of additional diffuse filaments are visible, some close to the foreground galaxy NGC 7331 located in the same field. Their structure and association with mid-infrared emission suggest contamination by emission from Galactic cirrus.

A deep survey of the X-ray binary populations in the SMC

NASA Astrophysics Data System (ADS)

Zezas, A.; Antoniou, V.

2017-10-01

The Small Magellanic Cloud (SMC) has been the subject of systematic X-ray surveys over the past two decades, which have yielded a rich population of high-mass X-ray binaries consisting predominantly of Be/X-ray binaries. We present results from our deep Chandra survey of the SMC which targeted regions with stellar populations ranging between ˜10-100 Myr. X-ray luminosities down to ˜3×10^{32} erg/s were reached, probing all active accreting binaries and extending well into the regime of quiescent accreting binaries and X-ray emitting normal stars. We measure the dependence of the formation efficiency of X-ray binaries on age. We also detect pulsations from 19 known and one new candidate pulsar. We construct the X-ray luminosity function in different regions of the SMC, which shows clear evidence for the propeller effect the centrifugal inhibition of accretion due to the interaction of the accretion flow with the pulsar's magnetic field. Finally we compare these results with predictions for the formation efficiency of X-ray binaries as a function of age from X-ray binary population synthesis models.

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.

An improved advertising CTR prediction approach based on the fuzzy deep neural network

PubMed Central

Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise. PMID:29727443

An improved advertising CTR prediction approach based on the fuzzy deep neural network.

PubMed

Jiang, Zilong; Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise.

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

Prediction of properties of wheat dough using intelligent deep belief networks

NASA Astrophysics Data System (ADS)

Guha, Paramita; Bhatnagar, Taru; Pal, Ishan; Kamboj, Uma; Mishra, Sunita

2017-11-01

In this paper, the rheological and chemical properties of wheat dough are predicted using deep belief networks. Wheat grains are stored at controlled environmental conditions. The internal parameters of grains viz., protein, fat, carbohydrates, moisture, ash are determined using standard chemical analysis and viscosity of the dough is measured using Rheometer. Here, fat, carbohydrates, moisture, ash and temperature are considered as inputs whereas protein and viscosity are chosen as outputs. The prediction algorithm is developed using deep neural network where each layer is trained greedily using restricted Boltzmann machine (RBM) networks. The overall network is finally fine-tuned using standard neural network technique. In most literature, it has been found that fine-tuning is done using back-propagation technique. In this paper, a new algorithm is proposed in which each layer is tuned using RBM and the final network is fine-tuned using deep neural network (DNN). It has been observed that with the proposed algorithm, errors between the actual and predicted outputs are less compared to the conventional algorithm. Hence, the given network can be considered as beneficial as it predicts the outputs more accurately. Numerical results along with discussions are presented.

Mechanisms underlying the cooling observed within the TTL during the active spells of organized deep convection of the Indian Summer Monsoon with COSMC RO and In-situ Measurements

NASA Astrophysics Data System (ADS)

Rao, Kusuma; Reddy, Narendra

Climate impact of the Asian monsoon as a tropical phenomena has been studied for decades in the past for its tropospheric component. However, the effort towards assessing the role of the Asian summer monsoon in the climate system with focus on the Upper Troposphere into the Lower Stratosphere (UTLS) is being addressed only in the recent times. Deep convective vertical fluxes of water and other chemical species penetrate and ventilate the TTL for redistribution of species in to stratosphere. However, the mechanisms underlying such convective transports are yet to be understood. Our specific goal here is to investigate the impact of organized deep moist convection of the Indian summer monsoon on thermal structure of UTLS, and to understand the underlying mechanisms. Since active monsoon spells are manifestations of organized deep convection embedded with overshooting convective elements, it becomes absolutely imperative to understand the impact of organized monsoon convection on three time scales, namely, (i) super synoptic scales of convectively intense active monsoon spells, (ii) on synoptic time scales of convectively disturbed conditions, and finally on (iii) cloud scales. Impact of deep convection on UTLS processes is examined here based on analysis of COSMIC RO and the METEOSAT data for the period, 2006-2011 and the in-situ measurements available from the national programme, PRWONAM during 2009-10 over the Indian land region and from the International field programme, JASMINE during 1999 over the Bay of Bengal. On all the three time scales during (i) the active monsoon spells, (ii) the disturbed periods and (iii) during the passage of deep core of MCSs, we inferred that the Coldpoint Tropopause Temperatures (CPT) lower at relatively lower CPT Altitudes (CPTA) unlike in the cases determined by normal temperature lapse rates; these unusual cases are described here as ‘Unlike Normal’ cases. TTL thickness shrinks during the convective conditions. During the passage of deep core of MCSs, cooling observed within the TTL is significantly higher than the cooling occuring on the other two time scales. The result that ‘Unlike Normal cases’ are associated with higher CAPE and higher surface equivalent potential temperatures lead to explain the possible mechanisms underlying the CPT cooling at relatively lower altitudes.

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.

Extension of the Cerro Prieto field and zones in the Mexicali Valley with geothermal possibilities in the future

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

Fonseca L, H.L.; de la Pena L, A.; Puente C, I.

This study concerns the possible extension of the Cerro Prieto field and identification of other zones in the Mexicali Valley with geothermal development potential by assessing the structural geologic conditions in relation to the regional tectonic framework and the integration of geologic and geophysical surveys carried out at Cerro Prieto. This study is based on data obtained from the wells drilled to date and the available geological and geophysical information. With this information, a geologic model of the field is developed as a general description of the geometry of what might be the geothermal reservoir of the Cerro Prieto field.more » In areas with geothermal potential within the Mexicali Valley, the location of irrigation wells with anomalous temperatures was taken as a point of departure for subsequent studies. Based on this initial information, gravity and magnetic surveys were made, followed by seismic reflection and refraction surveys and the drilling of 1200-m-deep multiple-use wells. Based on the results of the final integration of these studies with the geology of the region, it is suggested that the following areas should be explored further: east of Cerro Prieto, Tulecheck, Riito, Aeropuerto-Algodones, and San Luis Rio Colorado, Sonora.« less

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

Segmentation of human brain using structural MRI.

PubMed

Helms, Gunther

2016-04-01

Segmentation of human brain using structural MRI is a key step of processing in imaging neuroscience. The methods have undergone a rapid development in the past two decades and are now widely available. This non-technical review aims at providing an overview and basic understanding of the most common software. Starting with the basis of structural MRI contrast in brain and imaging protocols, the concepts of voxel-based and surface-based segmentation are discussed. Special emphasis is given to the typical contrast features and morphological constraints of cortical and sub-cortical grey matter. In addition to the use for voxel-based morphometry, basic applications in quantitative MRI, cortical thickness estimations, and atrophy measurements as well as assignment of cortical regions and deep brain nuclei are briefly discussed. Finally, some fields for clinical applications are given.

Physical techniques for delivering microwave energy to tissues.

PubMed Central

Hand, J. W.

1982-01-01

Some of the physical aspects of delivering microwave energy to tissues have been discussed. Effective penetration of a few cm may be achieved with external applicators whilst small coaxial or cylindrical devices can induce localized heating in sites accessible to catheters or to direct invasion. To heat deep tissue sites in general, systems of greater complexity involving a number of applicators with particular phase relationships between them are required. The problems of thermometry in the presence of electromagnetic fields fall outside the scope of this article. Their solution, however, is no less important to the future of clinical hyperthermia than the development of heating techniques. Finally, it should be remembered that physiological parameters such as blood flow have appreciable effects in determining the efficacy of the physical techniques described above. PMID:6950781

Event shape analysis of deep inelastic scattering events with a large rapidity gap at HERA

NASA Astrophysics Data System (ADS)

ZEUS Collaboration; Breitweg, J.; Derrick, M.; Krakauer, D.; Magill, S.; Mikunas, D.; Musgrave, B.; Repond, J.; Stanek, R.; Talaga, R. L.; Yoshida, R.; Zhang, H.; Mattingly, M. C. K.; Anselmo, F.; Antonioli, P.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Cara Romeo, G.; Castellini, G.; Cifarelli, L.; Cindolo, F.; Contin, A.; Corradi, M.; de Pasquale, S.; Gialas, I.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Margotti, A.; Massam, T.; Nania, R.; Palmonari, F.; Pesci, A.; Polini, A.; Ricci, F.; Sartorelli, G.; Zamora Garcia, Y.; Zichichi, A.; Amelung, C.; Bornheim, A.; Brock, I.; Coböken, K.; Crittenden, J.; Deffner, R.; Eckert, M.; Grothe, M.; Hartmann, H.; Heinloth, K.; Heinz, L.; Hilger, E.; Jakob, H.-P.; Katz, U. F.; Kerger, R.; Paul, E.; Pfeiffer, M.; Rembser, Ch.; Stamm, J.; Wedemeyer, R.; Wieber, H.; Bailey, D. S.; Campbell-Robson, S.; Cottingham, W. N.; Foster, B.; Hall-Wilton, R.; Hayes, M. E.; Heath, G. P.; Heath, H. F.; McFall, J. D.; Piccioni, D.; Roff, D. G.; Tapper, R. J.; Arneodo, M.; Ayad, R.; Capua, M.; Garfagnini, A.; Iannotti, L.; Schioppa, M.; Susinno, G.; Kim, J. Y.; Lee, J. H.; Lim, I. T.; Pac, M. Y.; Caldwell, A.; Cartiglia, N.; Jing, Z.; Liu, W.; Mellado, B.; Parsons, J. A.; Ritz, S.; Sampson, S.; Sciulli, F.; Straub, P. B.; Zhu, Q.; Borzemski, P.; Chwastowski, J.; Eskreys, A.; Figiel, J.; Klimek, K.; Przybycień , M. B.; Zawiejski, L.; Adamczyk, L.; Bednarek, B.; Bukowy, M.; Jeleń , K.; Kisielewska, D.; Kowalski, T.; Przybycień , M.; Rulikowska-Zarȩ Bska, E.; Suszycki, L.; Zaja C, J.; Duliń Ski, Z.; Kotań Ski, A.; Abbiendi, G.; Bauerdick, L. A. T.; Behrens, U.; Beier, H.; Bienlein, J. K.; Cases, G.; Deppe, O.; Desler, K.; Drews, G.; Fricke, U.; Gilkinson, D. J.; Glasman, C.; Göttlicher, P.; Haas, T.; Hain, W.; Hasell, D.; Johnson, K. F.; Kasemann, M.; Koch, W.; Kötz, U.; Kowalski, H.; Labs, J.; Lindemann, L.; Löhr, B.; Löwe, M.; Mań Czak, O.; Milewski, J.; Monteiro, T.; Ng, J. S. T.; Notz, D.; Ohrenberg, K.; Park, I. H.; Pellegrino, A.; Pelucchi, F.; Piotrzkowski, K.; Roco, M.; Rohde, M.; Roldán, J.; Ryan, J. J.; Savin, A. A.; Schneekloth, U.; Selonke, F.; Surrow, B.; Tassi, E.; Voß, T.; Westphal, D.; Wolf, G.; Wollmer, U.; Youngman, C.; Zsolararnecki, A. F.; Zeuner, W.; Burow, B. D.; Grabosch, H. J.; Meyer, A.; Schlenstedt, S.; Barbagli, G.; Gallo, E.; Pelfer, P.; Maccarrone, G.; Votano, L.; Bamberger, A.; Eisenhardt, S.; Markun, P.; Trefzger, T.; Wölfle, S.; Bromley, J. T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; MacDonald, N.; Saxon, D. H.; Sinclair, L. E.; Strickland, E.; Waugh, R.; Bohnet, I.; Gendner, N.; Holm, U.; Meyer-Larsen, A.; Salehi, H.; Wick, K.; Gladilin, L. K.; Horstmann, D.; Kçira, D.; Klanner, R.; Lohrmann, E.; Poelz, G.; Schott, W.; Zetsche, F.; Bacon, T. C.; Butterworth, I.; Cole, J. E.; Howell, G.; Hung, B. H. Y.; Lamberti, L.; Long, K. R.; Miller, D. B.; Pavel, N.; Prinias, A.; Sedgbeer, J. K.; Sideris, D.; Walker, R.; Mallik, U.; Wang, S. M.; Wu, J. T.; Cloth, P.; Filges, D.; Fleck, J. I.; Ishii, T.; Kuze, M.; Suzuki, I.; Tokushuku, K.; Yamada, S.; Yamauchi, K.; Yamazaki, Y.; Hong, S. J.; Lee, S. B.; Nam, S. W.; Park, S. K.; Barreiro, F.; Fernández, J. P.; García, G.; Graciani, R.; Hernández, J. M.; Hervás, L.; Labarga, L.; Martínez, M.; del Peso, J.; Puga, J.; Terrón, J.; de Trocóniz, J. F.; Corriveau, F.; Hanna, D. S.; Hartmann, J.; Hung, L. W.; Murray, W. N.; Ochs, A.; Riveline, M.; Stairs, D. G.; St-Laurent, M.; Ullmann, R.; Tsurugai, T.; Bashkirov, V.; Dolgoshein, B. A.; Stifutkin, A.; Bashindzhagyan, G. L.; Ermolov, P. F.; Golubkov, Yu. A.; Khein, L. A.; Korotkova, N. A.; Korzhavina, I. A.; Kuzmin, V. A.; Lukina, O. Yu.; Proskuryakov, A. S.; Shcheglova, L. M.; Solomin, A. N.; Zotkin, S. A.; Bokel, C.; Botje, M.; Brümmer, N.; Chlebana, F.; Engelen, J.; Koffeman, E.; Kooijman, P.; van Sighem, A.; Tiecke, H.; Tuning, N.; Verkerke, W.; Vossebeld, J.; Vreeswijk, M.; Wiggers, L.; de Wolf, E.; Acosta, D.; Bylsma, B.; Durkin, L. S.; Gilmore, J.; Ginsburg, C. M.; Kim, C. L.; Ling, T. Y.; Nylander, P.; Romanowski, T. A.; Blaikley, H. E.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Edmonds, J. K.; Große-Knetter, J.; Harnew, N.; Nath, C.; Noyes, V. A.; Quadt, A.; Ruske, O.; Tickner, J. R.; Uijterwaal, H.; Walczak, R.; Waters, D. S.; Bertolin, A.; Brugnera, R.; Carlin, R.; dal Corso, F.; Dosselli, U.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Bulmahn, J.; Oh, B. Y.; Okrasiń Ski, J. R.; Toothacker, W. S.; Whitmore, J. J.; Iga, Y.; D'Agostini, G.; Marini, G.; Nigro, A.; Raso, M.; Hart, J. C.; McCubbin, N. A.; Shah, T. P.; Epperson, D.; Heusch, C.; Rahn, J. T.; Sadrozinski, H. F.-W.; Seiden, A.; Wichmann, R.; Williams, D. C.; Schwarzer, O.; Walenta, A. H.; Abramowicz, H.; Briskin, G.; Dagan, S.; Kananov, S.; Levy, A.; Abe, T.; Fusayasu, T.; Inuzuka, M.; Nagano, K.; Umemori, K.; Yamashita, T.; Hamatsu, R.; Hirose, T.; Homma, K.; Kitamura, S.; Matsushita, T.; Cirio, R.; Costa, M.; Ferrero, M. I.; Maselli, S.; Monaco, V.; Peroni, C.; Petrucci, M. C.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Fagerstroem, C.-P.; Galea, R.; Hartner, G. F.; Joo, K. K.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Polenz, S.; Sabetfakhri, A.; Simmons, D.; Teuscher, R. J.; Butterworth, J. M.; Catterall, C. D.; Jones, T. W.; Lane, J. B.; Saunders, R. L.; Sutton, M. R.; Wing, M.; Ciborowski, J.; Grzelak, G.; Kasprzak, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Pawlak, R.; Tymieniecka, T.; Wróblewski, A. K.; Zakrzewski, J. A.; Adamus, M.; Coldewey, C.; Eisenberg, Y.; Hochman, D.; Karshon, U.; Badgett, W. F.; Chapin, D.; Cross, R.; Dasu, S.; Foudas, C.; Loveless, R. J.; Mattingly, S.; Reeder, D. D.; Smith, W. H.; Vaiciulis, A.; Wodarczyk, M.; Deshpande, A.; Dhawan, S.; Hughes, V. W.; Bhadra, S.; Frisken, W. R.; Khakzad, M.; Schmidke, W. B.

1998-03-01

A global event shape analysis of the multihadronic final states observed in neutral current deep inelastic scattering events with a large rapidity gap with respect to the proton direction is presented. The analysis is performed in the range 5<=Q2<=185 GeV2 and 160<=W<=250 GeV, where Q2 is the virtuality of the photon and W is the virtual-photon proton centre of mass energy. Particular emphasis is placed on the dependence of the shape variables, measured in the γ*-pomeron rest frame, on the mass of the hadronic final state, MX. With increasing MX the multihadronic final state becomes more collimated and planar. The experimental results are compared with several models which attempt to describe diffractive events. The broadening effects exhibited by the data require in these models a significant gluon component of the pomeron.

Deep Vadose Zone Treatability Test of Soil Desiccation for the Hanford Central Plateau: Final Report

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

Truex, Michael J.; Chronister, Glen B.; Strickland, Christopher E.

Some of the inorganic and radionuclide contaminants in the deep vadose zone at the Hanford Site are at depths where direct exposure pathways are not of concern, but may need to be remediated to protect groundwater. The Department of Energy developed a treatability test program for technologies to address Tc-99 and uranium in the deep vadose zone. These contaminants are mobile in the subsurface environment, have been detected at high concentrations deep in the vadose zone, and at some locations have reached groundwater. The treatability test of desiccation described herein was conducted as an element of the deep vadose zonemore » treatability test program. Desiccation was shown to be a potentially effective vadose zone remediation technology to protect groundwater when used in conjunction with a surface infiltration barrier.« less

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.

The Gravity Field of Mercury After the Messenger Low-Altitude Campaign

NASA Technical Reports Server (NTRS)

Mazarico, Erwan; Genova, Antonio; Goossens, Sander; Lemoine, Frank G.; Smith, David E.; Zuber, Maria T.; Neumann, Gary A.; Solomon, Sean C.

2015-01-01

The final year of the MESSENGER mission was designed to take advantage of the remaining propellant onboard to provide a series of lowaltitude observation campaigns and acquire novel scientific data about the innermost planet. The lower periapsis altitude greatly enhances the sensitivity to the short-wavelength gravity field, but only when the spacecraft is in view of Earth. After more than 3 years in orbit around Mercury, the MESSENGER spacecraft was tracked for the first time below 200-km altitude on 5 May 2014 by the NASA Deep Space Network (DSN). Between August and October, periapsis passages down to 25-km altitude were routinely tracked. These periods considerably improved the quality of the data coverage. Before the end of its mission, MESSENGER will fly at very low altitudes for extended periods of time. Given the orbital geometry, however the periapses will not be visible from Earth and so no new tracking data will be available for altitudes lower than 75 km. Nevertheless, the continuous tracking of MESSENGER in the northern hemisphere will help improve the uniformity of the spatial coverage at altitudes lower than 150 km, which will further improve the overall quality of the Mercury gravity field.

Delivering culturally sensitive health messages: the process of adapting brochures for grandparents raising grandchildren in Hawai'i.

PubMed

Yancura, Loriena A

2010-05-01

The efficacy of programs to reduce health disparities depends on their ability to deliver messages in a culturally sensitive manner. This article describes the process of designing a series of brochures for grandparents raising grandchildren. National source material on topics important to grandparents (self-care, service use, addiction, and grandchildren's difficult behaviors) was put into draft brochures and pilot tested in two focus groups drawn from Native Hawaiian Asian and Pacific Islander populations. Elements of surface and deep levels directed the form and content of the final brochures. On a surface level, these brochures reflect local culture through pictures and language. On a deep level, which integrates cultural beliefs and practices, they reflect the importance of indirect communication and harmonious relationships. The final brochures have been received favorably in the community. The process of adapting educational material with attention to surface and deep levels can serve as a guide for other health promotion materials.

CANDELS Visual Classifications: Scheme, Data Release, and First Results

NASA Astrophysics Data System (ADS)

Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Harry; Koo, David; Bassett, Robert; Bernyk, Maksym; Blancato, Kirsten; Bournaud, Frederic; Cassata, Paolo; Castellano, Marco; Cheung, Edmond; Conselice, Christopher J.; Croton, Darren; Dahlen, Tomas; de Mello, Duilia F.; DeGroot, Laura; Donley, Jennifer; Guedes, Javiera; Grogin, Norman; Hathi, Nimish; Hilton, Matt; Hollon, Brett; Koekemoer, Anton; Liu, Nick; Lucas, Ray A.; Martig, Marie; McGrath, Elizabeth; McPartland, Conor; Mobasher, Bahram; Morlock, Alice; O'Leary, Erin; Peth, Mike; Pforr, Janine; Pillepich, Annalisa; Rosario, David; Soto, Emmaris; Straughn, Amber; Telford, Olivia; Sunnquist, Ben; Trump, Jonathan; Weiner, Benjamin; Wuyts, Stijn; Inami, Hanae; Kassin, Susan; Lani, Caterina; Poole, Gregory B.; Rizer, Zachary

2015-11-01

We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H < 24.5 involving the dedicated efforts of over 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies spanning 0 < z < 4 over all the fields, with classifications from 3 to 5 independent classifiers for each galaxy. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, k-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed—GOODS-S, which has been classified at various depths. The wide area coverage spanning the full field (wide+deep+ERS) includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all of the visual classifications in GOODS-S along with the Perl/Tk GUI that we developed to classify galaxies. We present our initial results here, including an analysis of our internal consistency and comparisons among multiple classifiers as well as a comparison to the Sérsic index. We find that the level of agreement among classifiers is quite good (>70% across the full magnitude range) and depends on both the galaxy magnitude and the galaxy type, with disks showing the highest level of agreement (>50%) and irregulars the lowest (<10%). A comparison of our classifications with the Sérsic index and rest-frame colors shows a clear separation between disk and spheroid populations. Finally, we explore morphological k-corrections between the V-band and H-band observations and find that a small fraction (84 galaxies in total) are classified as being very different between these two bands. These galaxies typically have very clumpy and extended morphology or are very faint in the V-band.

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.

Approaches to learning for the ANZCA Final Examination and validation of the revised Study Process Questionnaire in specialist medical training.

PubMed

Weller, J M; Henning, M; Civil, N; Lavery, L; Boyd, M J; Jolly, B

2013-09-01

When evaluating assessments, the impact on learning is often overlooked. Approaches to learning can be deep, surface and strategic. To provide insights into exam quality, we investigated the learning approaches taken by trainees preparing for the Australian and New Zealand College of Anaesthetists (ANZCA) Final Exam. The revised two-factor Study Process Questionnaire (R-SPQ-2F) was modified and validated for this context and was administered to ANZCA advanced trainees. Additional questions were asked about perceived value for anaesthetic practice, study time and approaches to learning for each exam component. Overall, 236 of 690 trainees responded (34%). Responses indicated both deep and surface approaches to learning with a clear preponderance of deep approaches. The anaesthetic viva was valued most highly and the multiple choice question component the least. Despite this, respondents spent the most time studying for the multiple choice questions. The traditionally low short answer questions pass rate could not be explained by limited study time, perceived lack of value or study approaches. Written responses suggested that preparation for multiple choice questions was characterised by a surface approach, with rote memorisation of past questions. Minimal reference was made to the ANZCA syllabus as a guide for learning. These findings indicate that, although trainees found the exam generally relevant to practice and adopted predominantly deep learning approaches, there was considerable variation between the four components. These results provide data with which to review the existing ANZCA Final Exam and comparative data for future studies of the revisions to the ANZCA curriculum and exam process.

AUTOMATIC ENGLISH-TO-LOGIC TRANSLATION IN A SIMPLIFIED MODEL, A STUDY IN THE LOGIC OF GRAMMAR. FINAL REPORT.

ERIC Educational Resources Information Center

BACKER, P.O.; BOHNERT, H.G.

THE LATEST IN A SERIES OF ENGLISH-LIKE LANGUAGES IS DESCRIBED WHICH IS TRANSLATABLE INTO FORMS OF A FIRST-ORDER PREDICATE CALCULUS NOTATION. THE STUDY IS BASED ON THE HYPOTHESIS THAT SYNTACTIC AMBIGUITY ARISING FROM DIFFERENCES IN DEEP STRUCTURE CAN BE ADEQUATELY DESCRIBED ONLY IF THE DEEP STRUCTURES CAN BE SYSTEMATICALLY REPRESENTED. THE NOTATION…

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.

Deep learning for the detection of barchan dunes in satellite images

NASA Astrophysics Data System (ADS)

Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.

2017-12-01

Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the detection of mid-size to large size barchans, we noted that it was relatively difficult to detect smaller barchan dunes. Overall, deep learning allowed us to achieve a high accuracy in the detection of barchan dunes. The tracking of hundreds of barchans using this detection method would provide an insight into the understanding of the dynamics of this natural phenomenon.

Compact Deep-Space Optical Communications Transceiver

NASA Technical Reports Server (NTRS)

Roberts, W. Thomas; Charles, Jeffrey R.

2009-01-01

Deep space optical communication transceivers must be very efficient receivers and transmitters of optical communication signals. For deep space missions, communication systems require high performance well beyond the scope of mere power efficiency, demanding maximum performance in relation to the precious and limited mass, volume, and power allocated. This paper describes the opto-mechanical design of a compact, efficient, functional brassboard deep space transceiver that is capable of achieving megabyte-per-second rates at Mars ranges. The special features embodied to enhance the system operability and functionality, and to reduce the mass and volume of the system are detailed. System tests and performance characteristics are described in detail. Finally, lessons learned in the implementation of the brassboard design and suggestions for improvements appropriate for a flight prototype are covered.

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.

Higher Order Heavy Quark Corrections to Deep-Inelastic Scattering

NASA Astrophysics Data System (ADS)

Blümlein, Johannes; DeFreitas, Abilio; Schneider, Carsten

2015-04-01

The 3-loop heavy flavor corrections to deep-inelastic scattering are essential for consistent next-to-next-to-leading order QCD analyses. We report on the present status of the calculation of these corrections at large virtualities Q2. We also describe a series of mathematical, computer-algebraic and combinatorial methods and special function spaces, needed to perform these calculations. Finally, we briefly discuss the status of measuring αs (MZ), the charm quark mass mc, and the parton distribution functions at next-to-next-to-leading order from the world precision data on deep-inelastic scattering.

Pubface: Celebrity face identification based on deep learning

NASA Astrophysics Data System (ADS)

Ouanan, H.; Ouanan, M.; Aksasse, B.

2018-05-01

In this paper, we describe a new real time application called PubFace, which allows to recognize celebrities in public spaces by employs a new pose invariant face recognition deep neural network algorithm with an extremely low error rate. To build this application, we make the following contributions: firstly, we build a novel dataset with over five million faces labelled. Secondly, we fine tuning the deep convolutional neural network (CNN) VGG-16 architecture on our new dataset that we have built. Finally, we deploy this model on the Raspberry Pi 3 model B using the OpenCv dnn module (OpenCV 3.3).

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 learning decision fusion for the classification of urban remote sensing data

NASA Astrophysics Data System (ADS)

Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

2018-01-01

Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

Current evidence supporting mucosal healing and deep remission as important treatment goals for inflammatory bowel disease.

PubMed

Pineton de Chambrun, Guillaume; Blanc, Pierre; Peyrin-Biroulet, Laurent

2016-08-01

Mucosal healing (MH) is now considered as a major treatment goal in clinical trials and clinical practice for patients with inflammatory bowel disease (IBD). MH is associated with sustained clinical remission, steroid-free remission, and reduced rates of hospitalization and surgery. There is a well-known disconnect between clinical symptoms and mucosal lesions that is more pronounced in CD. More stringent therapeutic goals have been discussed recently such as deep remission defined as clinical remission associated with MH. Recent international guidelines from the IOIBD recommended deep remission as a treatment goal in clinical practice. However there is no validated definition of deep remission in IBD. Also, the efficacy of available drugs to induce and maintain deep remission in IBD is poorly known. Finally, whether deep remission is the best way to modify the course of IBD and whether it should be achieved before considering drug de-escalation have to be formally evaluated in upcoming disease-modification trials.

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.

A Science Portal and Archive for Extragalactic Globular Cluster Systems Data

NASA Astrophysics Data System (ADS)

Young, Michael; Rhode, Katherine L.; Gopu, Arvind

2015-01-01

For several years we have been carrying out a wide-field imaging survey of the globular cluster populations of a sample of giant spiral, S0, and elliptical galaxies with distances of ~10-30 Mpc. We use mosaic CCD cameras on the WIYN 3.5-m and Kitt Peak 4-m telescopes to acquire deep BVR imaging of each galaxy and then analyze the data to derive global properties of the globular cluster system. In addition to measuring the total numbers, specific frequencies, spatial distributions, and color distributions for the globular cluster populations, we have produced deep, high-quality images and lists of tens to thousands of globular cluster candidates for the ~40 galaxies included in the survey.With the survey nearing completion, we have been exploring how to efficiently disseminate not only the overall results, but also all of the relevant data products, to the astronomical community. Here we present our solution: a scientific portal and archive for extragalactic globular cluster systems data. With a modern and intuitive web interface built on the same framework as the WIYN One Degree Imager Portal, Pipeline, and Archive (ODI-PPA), our system will provide public access to the survey results and the final stacked mosaic images of the target galaxies. In addition, the astrometric and photometric data for thousands of identified globular cluster candidates, as well as for all point sources detected in each field, will be indexed and searchable. Where available, spectroscopic follow-up data will be paired with the candidates. Advanced imaging tools will enable users to overlay the cluster candidates and other sources on the mosaic images within the web interface, while metadata charting tools will allow users to rapidly and seamlessly plot the survey results for each galaxy and the data for hundreds of thousands of individual sources. Finally, we will appeal to other researchers with similar data products and work toward making our portal a central repository for data related to well-studied giant galaxy globular cluster systems. This work is supported by NSF Faculty Early Career Development (CAREER) award AST-0847109.

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.

Active semi-supervised learning method with hybrid deep belief networks.

PubMed

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

Utilizing the Upcoming Gravity Measurements from Cassini's Proximal Orbits for Studying the Atmospheric Dynamics of Saturn - How Deep Do the Winds Penetrate?

NASA Astrophysics Data System (ADS)

Kaspi, Y.; Galanti, E.

2014-12-01

At the end of the Cassini mission, the spacecraft will descend into close-by proximal orbits around Saturn. During those proximal orbits, Cassini will obtain high precision gravity measurements of the planet. In this talk, we will discuss how this data can be used to estimate the depth of the observed flows on the planet. This can be done in several ways: 1. measurements of the high order even harmonics which beyond J10 are dominated by the dynamics; 2. measurements of odd gravity harmonics which have no contribution from a static planet, and therefore are a pure signature of dynamics; 3. upper limits on the depth can be obtained by comparing low order even harmonics from dynamical models to the difference between the measured low order even harmonics and the largest possible values of a static planet; 4. direct latitudinally varying measurements of the gravity field exerted on the spacecraft. We will discuss how these methods may be applied and show that given the expected sensitivity of Cassini the odd harmonics J3 and J5 will have the best sensitivity to deep dynamics, allowing detection of winds reaching only O(100km) deep, if those exist on Saturn. We use a hierarchy of dynamical models ranging from full 3D dynamical circulation models to simplified dynamical models where the sensitivity of the gravity field to the dynamics can be explored. In order to invert the gravity field to be measured by Cassini into the depth dependent circulation, an adjoint inverse model is constructed for the dynamical models, thus allowing backward integration of the dynamical model. This tool can be used for examination of various scenarios, including cases in which the depth of the wind depends on latitudinal position. In summary, we expect that the very end of Cassini's tour holds an opportunity for gravity measurements that may finally allow answering one of the long-lasting puzzles in planetary science regarding the depth of the zonal jets on the gas giants. In fact, as Juno will be performing similar measurements we hope to be able to build a picture of the dynamics for both Jupiter and Saturn. Answering this puzzle, will likely help explain the origin of the multiple jet streams and strong equatorial superrotation on the gas giants.

The Effects of Test Trial and Processing Level on Immediate and Delayed Retention.

PubMed

Chang, Sau Hou

2017-03-01

The purpose of the present study was to investigate the effects of test trial and processing level on immediate and delayed retention. A 2 × 2 × 2 mixed ANOVAs was used with two between-subject factors of test trial (single test, repeated test) and processing level (shallow, deep), and one within-subject factor of final recall (immediate, delayed). Seventy-six college students were randomly assigned first to the single test (studied the stimulus words three times and took one free-recall test) and the repeated test trials (studied the stimulus words once and took three consecutive free-recall tests), and then to the shallow processing level (asked whether each stimulus word was presented in capital letter or in small letter) and the deep processing level (whether each stimulus word belonged to a particular category) to study forty stimulus words. The immediate test was administered five minutes after the trials, whereas the delayed test was administered one week later. Results showed that single test trial recalled more words than repeated test trial in immediate final free-recall test, participants in deep processing performed better than those in shallow processing in both immediate and delayed retention. However, the dominance of single test trial and deep processing did not happen in delayed retention. Additional study trials did not further enhance the delayed retention of words encoded in deep processing, but did enhance the delayed retention of words encoded in shallow processing.

The Effects of Test Trial and Processing Level on Immediate and Delayed Retention

PubMed Central

Chang, Sau Hou

2017-01-01

The purpose of the present study was to investigate the effects of test trial and processing level on immediate and delayed retention. A 2 × 2 × 2 mixed ANOVAs was used with two between-subject factors of test trial (single test, repeated test) and processing level (shallow, deep), and one within-subject factor of final recall (immediate, delayed). Seventy-six college students were randomly assigned first to the single test (studied the stimulus words three times and took one free-recall test) and the repeated test trials (studied the stimulus words once and took three consecutive free-recall tests), and then to the shallow processing level (asked whether each stimulus word was presented in capital letter or in small letter) and the deep processing level (whether each stimulus word belonged to a particular category) to study forty stimulus words. The immediate test was administered five minutes after the trials, whereas the delayed test was administered one week later. Results showed that single test trial recalled more words than repeated test trial in immediate final free-recall test, participants in deep processing performed better than those in shallow processing in both immediate and delayed retention. However, the dominance of single test trial and deep processing did not happen in delayed retention. Additional study trials did not further enhance the delayed retention of words encoded in deep processing, but did enhance the delayed retention of words encoded in shallow processing. PMID:28344679

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.

Prediction for the Flow-induced Gravity Field of Saturn: Implications for Cassini’s Grand Finale

NASA Astrophysics Data System (ADS)

Galanti, Eli; Kaspi, Yohai

2017-07-01

The Cassini measurements of Saturn’s gravity field during its Grand Finale might shed light on a long-standing question regarding the flow on Saturn. While the cloud-level winds are well known, little is known about whether these winds are confined to the outer layers of the planet or penetrate deep into the interior. An additional complexity is added by the uncertainty in the exact rotation period of Saturn, a key factor in determining the cloud-level winds, with an effect on the north-south symmetric part of the winds. Using Saturn’s cloud-level winds we relate the flow to the gravity harmonics. We give a prediction for the odd harmonics {J}3,{J}5,{J}7,{and} {J}9 as a function of the flow depth, identifying three ranges of depths. Since the odd harmonics depend solely on the flow, and are not influenced by Saturn’s shape and static density distribution, any measured value of the odd harmonics by Cassini can be used to uniquely determine the depth of the flow. We also discuss the flow-induced even harmonics {{Δ }}{J}2,{{Δ }}{J}4,\\ldots ,{{Δ }}{J}12 that are affected by Saturn’s rotation period. While the high-degree even harmonics might also be used to determine the flow depth, the lower-degree even harmonics serve as uncertainties for analysis of the planet’s interior structure and composition. Thus, the gravity harmonics measured during the Cassini Grand Finale may be used to get a first-order estimate of the flow structure and to better constrain the planet’s density structure and composition.

The Initial-Final Mass Relationship: Spectroscopy of White Dwarfs in NGC 2099 (M37)

NASA Astrophysics Data System (ADS)

Kalirai, Jasonjot Singh; Richer, Harvey B.; Reitzel, David; Hansen, Brad M. S.; Rich, R. Michael; Fahlman, Gregory G.; Gibson, Brad K.; von Hippel, Ted

2005-01-01

We present new observations of very faint white dwarfs (WDs) in the rich open star cluster NGC 2099 (M37). Following deep, wide-field imaging of the cluster using the Canada-France-Hawaii Telescope, we have now obtained spectroscopic observations of candidate WDs using both the Gemini Multi-Object Spectrograph on Gemini North and the Low-Resolution Imaging Spectrometer on Keck. Of our 24 WD candidates (all fainter than V=22.4), 21 are spectroscopically confirmed to be bona fide WDs, four or five of which are most likely field objects. Fitting 18 of the 21 WD spectra with model atmospheres, we find that most WDs in this cluster are quite massive (0.7-0.9 Msolar), as expected given the cluster's young age (650 Myr) and, hence, high turnoff mass (~2.4 Msolar). We determine a new initial-final mass relationship and almost double the number of existing data points from previous studies. The results indicate that stars with initial masses between 2.8 and 3.4 Msolar lose 70%-75% of their mass through stellar evolution. For the first time, we find some evidence of a metallicity dependence on the initial-final mass relationship. Based on observations with Gemini (run ID GN-2002B-Q-11) and Keck. Gemini is an international partnership managed by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation. The W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, was made possible by the generous financial support of the W. M. Keck Foundation.

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.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

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

Geographic differences in vertical connectivity in the Caribbean coral Montastraea cavernosa despite high levels of horizontal connectivity at shallow depths.

PubMed

Serrano, X; Baums, I B; O'Reilly, K; Smith, T B; Jones, R J; Shearer, T L; Nunes, F L D; Baker, A C

2014-09-01

The deep reef refugia hypothesis proposes that deep reefs can act as local recruitment sources for shallow reefs following disturbance. To test this hypothesis, nine polymorphic DNA microsatellite loci were developed and used to assess vertical connectivity in 583 coral colonies of the Caribbean depth-generalist coral Montastraea cavernosa. Samples were collected from three depth zones (≤10, 15-20 and ≥25 m) at sites in Florida (within the Upper Keys, Lower Keys and Dry Tortugas), Bermuda, and the U.S. Virgin Islands. Migration rates were estimated to determine the probability of coral larval migration from shallow to deep and from deep to shallow. Finally, algal symbiont (Symbiodinium spp.) diversity and distribution were assessed in a subset of corals to test whether symbiont depth zonation might indicate limited vertical connectivity. Overall, analyses revealed significant genetic differentiation by depth in Florida, but not in Bermuda or the U.S. Virgin Islands, despite high levels of horizontal connectivity between these geographic locations at shallow depths. Within Florida, greater vertical connectivity was observed in the Dry Tortugas compared to the Lower or Upper Keys. However, at all sites, and regardless of the extent of vertical connectivity, migration occurred asymmetrically, with greater likelihood of migration from shallow to intermediate/deep habitats. Finally, most colonies hosted a single Symbiodinium type (C3), ruling out symbiont depth zonation of the dominant symbiont type as a structuring factor. Together, these findings suggest that the potential for shallow reefs to recover from deep-water refugia in M. cavernosa is location-specific, varying among and within geographic locations likely as a consequence of local hydrology. © 2014 John Wiley & Sons Ltd.

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.

Learning Efficient Spatial-Temporal Gait Features with Deep Learning for Human Identification.

PubMed

Liu, Wu; Zhang, Cheng; Ma, Huadong; Li, Shuangqun

2018-02-06

The integration of the latest breakthroughs in bioinformatics technology from one side and artificial intelligence from another side, enables remarkable advances in the fields of intelligent security guard computational biology, healthcare, and so on. Among them, biometrics based automatic human identification is one of the most fundamental and significant research topic. Human gait, which is a biometric features with the unique capability, has gained significant attentions as the remarkable characteristics of remote accessed, robust and security in the biometrics based human identification. However, the existed methods cannot well handle the indistinctive inter-class differences and large intra-class variations of human gait in real-world situation. In this paper, we have developed an efficient spatial-temporal gait features with deep learning for human identification. First of all, we proposed a gait energy image (GEI) based Siamese neural network to automatically extract robust and discriminative spatial gait features for human identification. Furthermore, we exploit the deep 3-dimensional convolutional networks to learn the human gait convolutional 3D (C3D) as the temporal gait features. Finally, the GEI and C3D gait features are embedded into the null space by the Null Foley-Sammon Transform (NFST). In the new space, the spatial-temporal features are sufficiently combined with distance metric learning to drive the similarity metric to be small for pairs of gait from the same person, and large for pairs from different persons. Consequently, the experiments on the world's largest gait database show our framework impressively outperforms state-of-the-art methods.

A fast complex domain-matching pursuit algorithm and its application to deep-water gas reservoir detection

NASA Astrophysics Data System (ADS)

Zeng, Jing; Huang, Handong; Li, Huijie; Miao, Yuxin; Wen, Junxiang; Zhou, Fei

2017-12-01

The main emphasis of exploration and development is shifting from simple structural reservoirs to complex reservoirs, which all have the characteristics of complex structure, thin reservoir thickness and large buried depth. Faced with these complex geological features, hydrocarbon detection technology is a direct indication of changes in hydrocarbon reservoirs and a good approach for delimiting the distribution of underground reservoirs. It is common to utilize the time-frequency (TF) features of seismic data in detecting hydrocarbon reservoirs. Therefore, we research the complex domain-matching pursuit (CDMP) method and propose some improvements. First is the introduction of a scale parameter, which corrects the defect that atomic waveforms only change with the frequency parameter. Its introduction not only decomposes seismic signal with high accuracy and high efficiency but also reduces iterations. We also integrate jumping search with ergodic search to improve computational efficiency while maintaining the reasonable accuracy. Then we combine the improved CDMP with the Wigner-Ville distribution to obtain a high-resolution TF spectrum. A one-dimensional modeling experiment has proved the validity of our method. Basing on the low-frequency domain reflection coefficient in fluid-saturated porous media, we finally get an approximation formula for the mobility attributes of reservoir fluid. This approximation formula is used as a hydrocarbon identification factor to predict deep-water gas-bearing sand of the M oil field in the South China Sea. The results are consistent with the actual well test results and our method can help inform the future exploration of deep-water gas reservoirs.

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

Accumulation of antibiotics and heavy metals in meat duck deep litter and their role in persistence of antibiotic-resistant Escherichia coli in different flocks on one duck farm.

PubMed

Lin, Y; Zhao, W; Shi, Z D; Gu, H R; Zhang, X T; Ji, X; Zou, X T; Gong, J S; Yao, W

2017-04-01

Meat duck deep litter is considered to be an ideal environment for the evolution of bacterial antibiotic resistance if it is under poor management. The aim of this study was to characterize the accumulation of antibiotics and heavy metals in the deep litter and their role in the persistence of antibiotic resistance of Escherichia coli, and evaluate the service life of the deep litter. Samples were collected from initial, middle, and final stages of deep litter within 3 barns (zero, 4, and 8 rounds of meat duck fattening, d 34) and 9 flocks, with known consumption of antibiotics in the controlled trail. The feed and litter levels of consumed antibiotics and heavy metals were measured. E. coli (n = 147) was isolated and typed by Eric-PCR and the phylogenetic grouping technique, while minimal inhibitory concentrations of antibiotics and heavy metals were measured. This study confirmed the continuous accumulation of doxycycline and many heavy metals in the deep litter. The population of resistant certain bacteria to doxycycline (16 mg/L, 100 mg/L) or ofloxacin (8 g/mL, 50 g/mL) increased in the used deep litter (rounds 4 and 8). E. coli isolated from the 3 stages of sampling were highly resistant to ampicillin, tetracycline, florfenicol, and doxycycline. Increased resistance to ceftiofur, enrofloxacin, ofloxacin, and gentamicin were seen in the isolates from the final stage of deep litter. In addition, the percentage of isolates tolerant to zinc, copper, and cadmium and the numbers of Group-B2 isolates all increased in the used deep litter, and the isolates of each stage belonged predominantly to commensal groups. The antibiotic resistance of isolates with identical Eric-PCR patterns had improved from round 4 to 8, and differences still existed in the resistance profiles of isolates with identical Eric-PCR patterns from different barns of the same round. This study concluded that deep litter could be suitable for the evolution of bacterial antibiotic-resistance under conditions of continuous usage or accumulation of antibiotics and heavy metals without proper management. © 2016 Poultry Science Association Inc.

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.

Intercalated degrees, learning styles, and career preferences: prospective longitudinal study of UK medical students

PubMed Central

McManus, I C; Richards, P; Winder, B C

1999-01-01

Objectives To assess the effects of taking an intercalated degree (BSc) on the study habits and learning styles of medical students and on their interest in a career in medical research. Design Longitudinal questionnaire study of medical students at application to medical school and in their final year. Setting All UK medical schools. Participants 6901 medical school applicants for admission in 1991 were studied in the autumn of 1990. 3333 entered medical school in 1991 or 1992, and 2695 who were due to qualify in 1996 or 1997 were studied 3 months before the end of their clinical course. Response rates were 92% for applicants and 56% for final year students. Main outcome measures Study habits (surface, deep, and strategic learning style) and interest in different medical careers, including medical research. Identical questions were used at time of application and in final year. Results Students who had taken an intercalated degree had higher deep and strategic learning scores than at application to medical school. Those with highest degree classes had higher strategic and deep learning scores and lower surface learning scores. Students taking intercalated degrees showed greater interest in careers in medical research and laboratory medicine and less interest in general practice than their peers. The effects of the course on interest in medical research and learning styles were independent. The effect of the intercalated degree was greatest in schools where relatively few students took intercalated degrees. Conclusions Intercalated degrees result in a greater interest in research careers and higher deep and strategic learning scores. However, the effects are much reduced in schools where most students intercalate a degree. Introduction of intercalated degrees for all medical students without sufficient resources may not therefore achieve its expected effects. Key messagesAlthough intercalated degrees are well established, little is known about their effect on medical studentsIn this longitudinal study final year students who had taken intercalated degree were more interested in medical research, and had higher deep and strategic learning style scores than other studentsThe effects of the intercalated degree were dose dependent, being greatest in those gaining a first class degreeThe effects of the intercalated degree were greatest in medical schools where a relatively small proportion of medical students took the degree.Differences between medical schools are most easily explained by resource dilution PMID:10463892

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…

[Obsessive-compulsive disorder, a new model of basal ganglia dysfunction? Elements from deep brain stimulation studies].

PubMed

Haynes, W I A; Millet, B; Mallet, L

2012-01-01

Deep brain stimulation was first developed for movement disorders but is now being offered as a therapeutic alternative in severe psychiatric disorders after the failure of conventional therapies. One of such pathologies is obsessive-compulsive disorder. This disorder which associates intrusive thoughts (obsessions) and repetitive irrepressible rituals (compulsions) is characterized by a dysfunction of a cortico-subcortical loop. After having reviewed the pathophysiological evidence to show why deep brain stimulation was an interesting path to take for severe and resistant cases of obsessive-compulsive disorder, we will present the results of the different clinical trials. Finally, we will provide possible mechanisms for the effects of deep brain stimulation in this pathology. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Analyses of odours from concentrated animal feeding operations: A review

NASA Astrophysics Data System (ADS)

Guffanti, P.; Pifferi, V.; Falciola, L.; Ferrante, V.

2018-02-01

Concentrated Animal Feeding Operations (CAFOs) are widely present all over the world due to the high population demand for food and products of animal origin. However, they have generated several environmental concerns, including odour nuisance, which affects people health and quality of life. Odours from livestock are a very complex mixtures of molecules and their analytical investigation is highly demanding. Many works have been published regarding the study of odours from CAFOs, using different techniques and technologies to face the issue. Thus, the aim of this review paper is to summarize all the ways to study odours from CAFOs, starting from the sampling methods and then treating in general the principles of Dynamic Olfactometry, Gas Chromatography coupled with Mass Spectrometry and Electronic Noses. Finally, a deep literature summary of Gas Chromatography coupled with Mass Spectrometry and Electronic Noses applied to odours coming from poultry, dairy and swine feeding operations is reported. This work aims to make some order in this field and it wants to help future researchers to deal with this environmental problem, constituting a state-of-the-art in this field.

Probing Water Ice for Trace Organics using Raman Scattering in the Laboratory and Terrestrial Field Analogs

NASA Astrophysics Data System (ADS)

Winebrenner, D. P.; Kirby, J. P.; Marquardt, B.

2013-12-01

Trace constituents in (predominantly) water ice are key to understanding planetary and astrobiological processes on a wide variety of solar system bodies, including Europa, Enceladus, Titan, Ceres, Mars, and comets. Organic traces are of particular interest not only for astrobiology but also, for example, for understanding the fates of abiotic organics delivered by meteorites. Raman scattering is known for specificity in identifying bonds and compounds, but has generally been considered relatively insensitive to concentrations characteristic of trace constituents. Here we test in doped water ice a Raman probe system that was developed for industrial and environmental applications and that has characterized select traces at ppm-levels near a deep-sea hydrothermal vent. We report in particular results for 17 amino acids and for aromatic hydrocarbons. Finally, based on physically robust Raman optics developed for industrial environments, we proposal a concept for subsurface investigation of traces in terrestrial analog environments such as glaciers and ice sheets, by means of integrating a Raman probe with a thermal ice melt probe recently field-tested in Greenland.

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

Lipid production of microalga Chlorella sorokiniana CY1 is improved by light source arrangement, bioreactor operation mode and deep-sea water supplements.

PubMed

Chen, Chun-Yen; Chang, Hsin-Yueh

2016-03-01

Microalgae-based biodiesel has been recognized as a sustainable and promising alternative to fossil diesel. High lipid productivity of microalgae is required for economic production of biodiesel from microalgae. This study was undertaken to enhance the growth and oil accumulation of an indigenous microalga Chlorella sorokiniana CY1 by applying engineering strategies using deep-sea water as the medium. First, the microalga was cultivated using LED as the immersed light source, and the results showed that the immersed LED could effectively enhance the oil/lipid content and final microalgal biomass concentration to 53.8% and 2.5 g/l, respectively. Next, the semi-batch photobioreactor operation with deep-sea water was shown to improve lipid content and microalgal growth over those from using batch and continuous cultures under similar operating conditions. The optimal replacement ratio was 50%, resulting in an oil/lipid content and final biomass concentration of 61.5% and 2.8 g/l, respectively. A long-term semi-batch culture utilizing 50%-replaced medium was carried out for four runs. The final biomass concentration and lipid productivity were 2.5 g/L and 112.2 mg/L/d, respectively. The fatty acid composition of the microalgal lipids was predominant by palmitic acid, stearic acid, oleic acid and linoleic acid, and this lipid quality is suitable for biodiesel production. This demonstrates that optimizing light source arrangement, bioreactor operation and deep-sea water supplements could effectively promote the lipid production of C. sorokiniana CY1 for the applications in microalgae-based biodiesel industry. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

NASA's Space Launch System: A Transformative Capability for Deep Space Missions

NASA Technical Reports Server (NTRS)

Creech, Stephen D.

2017-01-01

Already making substantial progress toward its first launches, NASA’s Space Launch System (SLS) exploration-class launch vehicle presents game-changing new opportunities in spaceflight, enabling human exploration of deep space, as well as a variety of missions and mission profiles that are currently impossible. Today, the initial configuration of SLS, able to deliver more than 70 metric tons of payload to low Earth orbit (LEO), is well into final production and testing ahead of its planned first flight, which will send NASA’s new Orion crew vehicle around the moon and will deploy 13 CubeSats, representing multiple disciplines, into deep space. At the same time, production work is already underway toward the more-capable Block 1B configuration, planned to debut on the second flight of SLS, and capable of lofting 105 tons to LEO or of co-manifesting large exploration systems with Orion on launches to the lunar vicinity. Progress being made on the vehicle for that second flight includes initial welding of its core stage and testing of one of its engines, as well as development of new elements such as the powerful Exploration Upper Stage and the Universal Stage Adapter “payload bay.” Ultimately, SLS will evolve to a configuration capable of delivering more than 130 tons to LEO to support humans missions to Mars. In order to enable human deep-space exploration, SLS provides unrivaled mass, volume, and departure energy for payloads, offering numerous benefits for a variety of other missions. For robotic science probes to the outer solar system, for example, SLS can cut transit times to less than half that of currently available vehicles or substantially increased spacecraft mass. In the field of astrophysics, SLS’ high payload volume, in the form of payload fairings with a diameter of up to 10 meters, creates the opportunity for launch of large-aperture telescopes providing an unprecedented look at our universe. This presentation will give an overview of SLS’ capabilities and its current status, and discuss the vehicle’s potential for human exploration of deep space and other game-changing utilization opportunities.

Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data.

PubMed

Koutsoukas, Alexios; Monaghan, Keith J; Li, Xiaoli; Huan, Jun

2017-06-28

In recent years, research in artificial neural networks has resurged, now under the deep-learning umbrella, and grown extremely popular. Recently reported success of DL techniques in crowd-sourced QSAR and predictive toxicology competitions has showcased these methods as powerful tools in drug-discovery and toxicology research. The aim of this work was dual, first large number of hyper-parameter configurations were explored to investigate how they affect the performance of DNNs and could act as starting points when tuning DNNs and second their performance was compared to popular methods widely employed in the field of cheminformatics namely Naïve Bayes, k-nearest neighbor, random forest and support vector machines. Moreover, robustness of machine learning methods to different levels of artificially introduced noise was assessed. The open-source Caffe deep-learning framework and modern NVidia GPU units were utilized to carry out this study, allowing large number of DNN configurations to be explored. We show that feed-forward deep neural networks are capable of achieving strong classification performance and outperform shallow methods across diverse activity classes when optimized. Hyper-parameters that were found to play critical role are the activation function, dropout regularization, number hidden layers and number of neurons. When compared to the rest methods, tuned DNNs were found to statistically outperform, with p value <0.01 based on Wilcoxon statistical test. DNN achieved on average MCC units of 0.149 higher than NB, 0.092 than kNN, 0.052 than SVM with linear kernel, 0.021 than RF and finally 0.009 higher than SVM with radial basis function kernel. When exploring robustness to noise, non-linear methods were found to perform well when dealing with low levels of noise, lower than or equal to 20%, however when dealing with higher levels of noise, higher than 30%, the Naïve Bayes method was found to perform well and even outperform at the highest level of noise 50% more sophisticated methods across several datasets.

Improving the Multi-Wavelength Capability of Chandra Large Programs

NASA Astrophysics Data System (ADS)

Pacucci, Fabio

2017-09-01

In order to fully exploit the joint Chandra/JWST/HST ventures to detect faint sources, we urgently need an advanced matching algorithm between optical/NIR and X-ray catalogs/images. This will be of paramount importance in bridging the gap between upcoming optical/NIR facilities (JWST) and later X-ray ones (Athena, Lynx). We propose to develop an advanced and automated tool to improve the identification of Chandra X-ray counterparts detected in deep optical/NIR fields based on T-PHOT, a software widely used in the community. The developed code will include more than 20 years in advancements of X-ray data analysis and will be released to the public. Finally, we will release an updated catalog of X-ray sources in the CANDELS regions: a leap forward in our endeavor of charting the Universe.

Relaxation of vacuum energy in q-theory

NASA Astrophysics Data System (ADS)

Klinkhamer, F. R.; Savelainen, M.; Volovik, G. E.

2017-08-01

The q-theory formalism aims to describe the thermodynamics and dynamics of the deep quantum vacuum. The thermodynamics leads to an exact cancellation of the quantum-field zero-point-energies in equilibrium, which partly solves the main cosmological constant problem. But, with reversible dynamics, the spatially flat Friedmann-Robertson-Walker universe asymptotically approaches the Minkowski vacuum only if the Big Bang already started out in an initial equilibrium state. Here, we extend q-theory by introducing dissipation from irreversible processes. Neglecting the possible instability of a de-Sitter vacuum, we obtain different scenarios with either a de-Sitter asymptote or collapse to a final singularity. The Minkowski asymptote still requires fine-tuning of the initial conditions. This suggests that, within the q-theory approach, the decay of the de-Sitter vacuum is a necessary condition for the dynamical solution of the cosmological constant problem.

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

Assessing neurosurgical non-technical skills: an exploratory study of a new behavioural marker system.

PubMed

Michinov, Estelle; Jamet, Eric; Dodeler, Virginie; Haegelen, Claire; Jannin, Pierre

2014-10-01

The management of non-technical skills is a major factor affecting teamwork quality and patient safety. This article presents a behavioural marker system for assessing neurosurgical non-technical skills (BMS-NNTS). We tested the BMS during deep brain stimulation surgery. We developed the BMS in three stages. First, we drew up a provisional assessment tool based on the literature and observation tools developed for other surgical specialties. We then analysed videos made in an operating room (OR) during deep brain stimulation operations in order to ensure there were no significant omissions from the skills list. Finally, we used five videos of operations to identify the behavioural markers of non-technical skills in verbal communications. Analyses of more than six hours of observations revealed 3515 behaviours from which we determined the neurosurgeon's non-technical skills behaviour pattern. The neurosurgeon frequently engaged in explicit coordination, situation awareness and leadership behaviours. In addition, the neurosurgeon's behaviours differed according to the stage of the operation and the OR staff members with whom she was communicating. Our behavioural marker system provides a structured approach to assessing non-technical skills in the field of neurosurgery. It can also be transferred to other surgical specialties and used in surgeon training curricula. © 2014 John Wiley & Sons, Ltd.

Water management in Egypt for facing the future challenges

PubMed Central

Omar, Mohie El Din M.; Moussa, Ahmed M.A.

2016-01-01

The current water shortage in Egypt is 13.5 Billion cubic meter per year (BCM/yr) and is expected to continuously increase. Currently, this water shortage is compensated by drainage reuse which consequently deteriorates the water quality. Therefore, this research was commenced with the objective of assessing different scenarios for 2025 using the Water Evaluation and Planning (WEAP) model and by implementing different water sufficiency measures. Field data were assembled and analyzed, and different planning alternatives were proposed and tested in order to design three future scenarios. The findings indicated that water shortage in 2025 would be 26 BCM/yr in case of continuation of current policies. Planning alternatives were proposed to the irrigation canals, land irrigation timing, aquatic weeds in waterways and sugarcane areas in old agricultural lands. Other measures were suggested to pumping rates of deep groundwater, sprinkler and drip irrigation systems in new agricultural lands. Further measures were also suggested to automatic daily surveying for distribution leak and managing the pressure effectively in the domestic and industrial water distribution systems. Finally, extra measures for water supply were proposed including raising the permitted withdrawal limit from deep groundwater and the Nubian aquifer and developing the desalination resource. The proposed planning alternatives would completely eliminate the water shortage in 2025. PMID:27222745

Pore scale study of multiphase multicomponent reactive transport during CO2 dissolution trapping

NASA Astrophysics Data System (ADS)

Chen, Li; Wang, Mengyi; Kang, Qinjun; Tao, Wenquan

2018-06-01

Solubility trapping is crucial for permanent CO2 sequestration in deep saline aquifers. For the first time, a pore-scale numerical method is developed to investigate coupled scCO2-water two-phase flow, multicomponent (CO2(aq), H+, HCO3-, CO32- and OH-) mass transport, heterogeneous interfacial dissolution reaction, and homogeneous dissociation reactions. Pore-scale details of evolutions of multiphase distributions and concentration fields are presented and discussed. Time evolutions of several variables including averaged CO2(aq) concentration, scCO2 saturation, and pH value are analyzed. Specific interfacial length, an important variable which cannot be determined but is required by continuum models, is investigated in detail. Mass transport coefficient or efficient dissolution rate is also evaluated. The pore-scale results show strong non-equilibrium characteristics during solubility trapping due to non-uniform distributions of multiphase as well as slow mass transport process. Complicated coupling mechanisms between multiphase flow, mass transport and chemical reactions are also revealed. Finally, effects of wettability are also studied. The pore-scale studies provide deep understanding of non-linear non-equilibrium multiple physicochemical processes during CO2 solubility trapping processes, and also allow to quantitatively predict some important empirical relationships, such as saturation-interfacial surface area, for continuum models.

Analysis of simultaneous MEG and intracranial LFP recordings during Deep Brain Stimulation: a protocol and experimental validation

PubMed Central

Oswal, Ashwini; Jha, Ashwani; Neal, Spencer; Reid, Alphonso; Bradbury, David; Aston, Peter; Limousin, Patricia; Foltynie, Tom; Zrinzo, Ludvic; Brown, Peter; Litvak, Vladimir

2016-01-01

Background Deep Brain Stimulation (DBS) is an effective treatment for several neurological and psychiatric disorders. In order to gain insights into the therapeutic mechanisms of DBS and to advance future therapies a better understanding of the effects of DBS on large-scale brain networks is required. New method In this paper, we describe an experimental protocol and analysis pipeline for simultaneously performing DBS and intracranial local field potential (LFP) recordings at a target brain region during concurrent magnetoencephalography (MEG) measurement. Firstly we describe a phantom setup that allowed us to precisely characterise the MEG artefacts that occurred during DBS at clinical settings. Results Using the phantom recordings we demonstrate that with MEG beamforming it is possible to recover oscillatory activity synchronised to a reference channel, despite the presence of high amplitude artefacts evoked by DBS. Finally, we highlight the applicability of these methods by illustrating in a single patient with Parkinson's disease (PD), that changes in cortical-subthalamic nucleus coupling can be induced by DBS. Comparison with existing approaches To our knowledge this paper provides the first technical description of a recording and analysis pipeline for combining simultaneous cortical recordings using MEG, with intracranial LFP recordings of a target brain nucleus during DBS. PMID:26698227

Water management in Egypt for facing the future challenges.

PubMed

Omar, Mohie El Din M; Moussa, Ahmed M A

2016-05-01

The current water shortage in Egypt is 13.5 Billion cubic meter per year (BCM/yr) and is expected to continuously increase. Currently, this water shortage is compensated by drainage reuse which consequently deteriorates the water quality. Therefore, this research was commenced with the objective of assessing different scenarios for 2025 using the Water Evaluation and Planning (WEAP) model and by implementing different water sufficiency measures. Field data were assembled and analyzed, and different planning alternatives were proposed and tested in order to design three future scenarios. The findings indicated that water shortage in 2025 would be 26 BCM/yr in case of continuation of current policies. Planning alternatives were proposed to the irrigation canals, land irrigation timing, aquatic weeds in waterways and sugarcane areas in old agricultural lands. Other measures were suggested to pumping rates of deep groundwater, sprinkler and drip irrigation systems in new agricultural lands. Further measures were also suggested to automatic daily surveying for distribution leak and managing the pressure effectively in the domestic and industrial water distribution systems. Finally, extra measures for water supply were proposed including raising the permitted withdrawal limit from deep groundwater and the Nubian aquifer and developing the desalination resource. The proposed planning alternatives would completely eliminate the water shortage in 2025.

Variation in Clinical Placement Supervisors' Conceptions of and Approaches to Supervision in a Veterinary Internship Programme

ERIC Educational Resources Information Center

van Gelderen, Ingrid; Matthew, Susan M.; Hendry, Graham D.; Taylor, Rosanne

2018-01-01

Good teaching that supports final year students' learning in clinical placements is critical for students' successful transition from an academic environment to professional practice. Final year internship programmes are designed to encourage student-centred approaches to teaching and deep approaches to learning, but the extent to which clinical…

Living in Interesting Times: The Economics of a Chinese Currency Attack

DTIC Science & Technology

2008-01-01

predictor. See Frederic S. Mishkin , The Economics of Money, Banking, and Financial Markets , 5th ed. (Boston: Addison-Wesley, 1998), 171. Strategic...currency should come from a country (or countries) that have deep and liquid financial markets to provide a safe return on reserves. Finally, a fiat...perspective and the potential competitors. The most likely competitor, the euro, has large and deep financial markets and trades with much of the world

Computing the binding affinity of a ligand buried deep inside a protein with the hybrid steered molecular dynamics

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

Villarreal, Oscar D.; Yu, Lili; Department of Laboratory Medicine, Yancheng Vocational Institute of Health Sciences, Yancheng, Jiangsu 224006

Computing the ligand-protein binding affinity (or the Gibbs free energy) with chemical accuracy has long been a challenge for which many methods/approaches have been developed and refined with various successful applications. False positives and, even more harmful, false negatives have been and still are a common occurrence in practical applications. Inevitable in all approaches are the errors in the force field parameters we obtain from quantum mechanical computation and/or empirical fittings for the intra- and inter-molecular interactions. These errors propagate to the final results of the computed binding affinities even if we were able to perfectly implement the statistical mechanicsmore » of all the processes relevant to a given problem. And they are actually amplified to various degrees even in the mature, sophisticated computational approaches. In particular, the free energy perturbation (alchemical) approaches amplify the errors in the force field parameters because they rely on extracting the small differences between similarly large numbers. In this paper, we develop a hybrid steered molecular dynamics (hSMD) approach to the difficult binding problems of a ligand buried deep inside a protein. Sampling the transition along a physical (not alchemical) dissociation path of opening up the binding cavity- -pulling out the ligand- -closing back the cavity, we can avoid the problem of error amplifications by not relying on small differences between similar numbers. We tested this new form of hSMD on retinol inside cellular retinol-binding protein 1 and three cases of a ligand (a benzylacetate, a 2-nitrothiophene, and a benzene) inside a T4 lysozyme L99A/M102Q(H) double mutant. In all cases, we obtained binding free energies in close agreement with the experimentally measured values. This indicates that the force field parameters we employed are accurate and that hSMD (a brute force, unsophisticated approach) is free from the problem of error amplification suffered by many sophisticated approaches in the literature.« less

Spectrally-Based Bathymetric Mapping of a Dynamic, Sand-Bedded Channel: Niobrara River, Nebraska, USA

NASA Astrophysics Data System (ADS)

Dilbone, Elizabeth K.

Methods for spectrally-based bathymetric mapping of rivers mainly have been developed and tested on clear-flowing, gravel bedded channels, with limited application to turbid, sand-bedded rivers. Using hyperspectral images of the Niobrara River, Nebraska, and field-surveyed depth data, this study evaluated three methods of retrieving depth from remotely sensed data in a dynamic, sand-bedded channel. The first regression-based approach paired in situ depth measurements and image pixel values to predict depth via Optimal Band Ratio Analysis (OBRA). The second approach used ground-based reflectance measurements to calibrate an OBRA relationship. For this approach, CASI images were atmospherically corrected to units of apparent surface reflectance using an empirical line calibration. For the final technique, we used Image-to-Depth Quantile Transformation (IDQT) to predict depth by linking the cumulative distribution function (CDF) of depth to the CDF of an image derived variable. OBRA yielded the lowest overall depth retrieval error (0.0047 m) and highest observed versus predicted R2 (0.81). Although misalignment between field and image data were not problematic to OBRA's performance in this study, such issues present potential limitations to standard regression-based approaches like OBRA in dynamic, sand-bedded rivers. Field spectroscopy-based maps exhibited a slight shallow bias (0.0652 m) but provided reliable depth estimates for most of the study reach. IDQT had a strong deep bias, but still provided informative relative depth maps that portrayed general patterns of shallow and deep areas of the channel. The over-prediction of depth by IDQT highlights the need for an unbiased sampling strategy to define the CDF of depth. While each of the techniques tested in this study demonstrated the potential to provide accurate depth estimates in sand-bedded rivers, each method also was subject to certain constraints and limitations.

Inter-relationship between shallow and deep aquifers under the influence of deep groundwater exploitation in the North China Plain

NASA Astrophysics Data System (ADS)

Han, Dongmei; Cao, Guoliang; Love, Andrew J.

2017-04-01

In the North China Plain (NCP), the interaction between shallow and deep groundwater flow systems enhanced by groundwater extraction has been investigated using multi-isotopic and chemical tracers for understanding the mechanism of salt water transport, which has long been one of the major regional environmental hydrogeological problems in NCP. Information about the problem will be determined using multiple lines of evidence, including field surveys of drilling and water sampling, as well as laboratory experiments and physical and numerical simulations. A conceptual model of groundwater flow system along WE cross-section from piedmont area to coastal region (Shijiazhuang-Hengshui-Cangzhou) has been developed and verified by geochemical modeling. A combined hydrogeochemical and isotopic investigation using ion relationships such as Cl/Br ratios, and environment isotopes (δ 18O, δ 2H, δ 34SSO4-δ 18OSO4, δ 15NNO_3-δ 18ONO_3, δ 13C and 87Sr/86Sr) was reviewed and carried for determining the sources of aquifer recharge, the origin of solutes and the mixing processes in groundwater flow system under the anthropogenic pumping and pollution. Results indicate that hydrochemistry of groundwater is characterized by mixing between end-members coming directly from Piedmont recharge areas, saline groundwater formed during geohistorical transgression in the shallow aquifers of central plain, and to groundwater circulating in a deeply buried Quaternary sediments. We also reviewed the groundwater age (tritium contents, 14C ages, 3H-3He ages, basin-scale flow modeling ages of groundwater) to recognize the local distributed recharge in this strongly exploited aquifer system. Finally, combined with the 1-D Cl transport modeling for the pore water of clay-rich aquitard, we reveal that salt transport in the aquitard is primarily controlled by vertical diffusion on million years' time scale, and the observed the salinized groundwater in deep aquifer may be caused by passing through ``windows'' or preferential flow path, rather than vertical flow through the aquitard.

Final-state interactions in inclusive deep-inelastic scattering from the deuteron

DOE PAGES

Cosyn, Wim; Melnitchouk, Wally; Sargsian, Misak M.

2014-01-16

We explore the role of final-state interactions (FSI) in inclusive deep-inelastic scattering from the deuteron. Relating the inclusive cross section to the deuteron forward virtual Compton scattering amplitude, a general formula for the FSI contribution is derived in the generalized eikonal approximation, utilizing the diffractive nature of the effective hadron-nucleon interaction. The calculation uses a factorized model with a basis of three resonances with mass W~<2 GeV and a continuum contribution for larger W as the relevant set of effective hadron states entering the final-state interaction amplitude. The results show sizeable on-shell FSI contributions for Bjorken x ~> 0.6 andmore » Q 2 < 10 GeV 2 increasing in magnitude for lower Q 2, but vanishing in the high-Q 2 limit due to phase space constraints. The off-shell rescattering contributes at x ~> 0.8 and is taken as an uncertainty on the on-shell result.« less

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.

Smaller Footprint Drilling System for Deep and Hard Rock Environments; Feasibility of Ultra-High-Speed Diamond Drilling

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

Arnis Judzis; Alan Black; Homer Robertson

2006-03-01

The two phase program addresses long-term developments in deep well and hard rock drilling. TerraTek believes that significant improvements in drilling deep hard rock will be obtained by applying ultra-high rotational speeds (greater than 10,000 rpm). The work includes a feasibility of concept research effort aimed at development that will ultimately result in the ability to reliably drill ''faster and deeper'' possibly with smaller, more mobile rigs. The principle focus is on demonstration testing of diamond bits rotating at speeds in excess of 10,000 rpm to achieve high rate of penetration (ROP) rock cutting with substantially lower inputs of energymore » and loads. The significance of the ultra-high rotary speed drilling system is the ability to drill into rock at very low weights on bit and possibly lower energy levels. The drilling and coring industry today does not practice this technology. The highest rotary speed systems in oil field and mining drilling and coring today run less than 10,000 rpm--usually well below 5,000 rpm. This document details the progress to date on the program entitled ''Smaller Footprint Drilling System for Deep and Hard Rock Environments: Feasibility of Ultra-High-Speed Diamond Drilling'' for the period starting 1 October 2004 through 30 September 2005. Additionally, research activity from 1 October 2005 through 28 February 2006 is included in this report: (1) TerraTek reviewed applicable literature and documentation and convened a project kick-off meeting with Industry Advisors in attendance. (2) TerraTek designed and planned Phase I bench scale experiments. Some difficulties continue in obtaining ultra-high speed motors. Improvements have been made to the loading mechanism and the rotational speed monitoring instrumentation. New drill bit designs have been provided to vendors for production. A more consistent product is required to minimize the differences in bit performance. A test matrix for the final core bit testing program has been completed. (3) TerraTek is progressing through Task 3 ''Small-scale cutting performance tests''. (4) Significant testing has been performed on nine different rocks. (5) Bit balling has been observed on some rock and seems to be more pronounces at higher rotational speeds. (6) Preliminary analysis of data has been completed and indicates that decreased specific energy is required as the rotational speed increases (Task 4). This data analysis has been used to direct the efforts of the final testing for Phase I (Task 5). (7) Technology transfer (Task 6) has begun with technical presentations to the industry (see Judzis).« less

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.

Slitless spectroscopy with the James Webb Space Telescope Near-Infrared Camera (JWST NIRCam)

NASA Astrophysics Data System (ADS)

Greene, Thomas P.; Chu, Laurie; Egami, Eiichi; Hodapp, Klaus W.; Kelly, Douglas M.; Leisenring, Jarron; Rieke, Marcia; Robberto, Massimo; Schlawin, Everett; Stansberry, John

2016-07-01

The James Webb Space Telescope near-infrared camera (JWST NIRCam) has two 2.02 x 2.02 fields of view that are capable of either imaging or spectroscopic observations. Either of two R ~ 1500 grisms with orthogonal dispersion directions can be used for slitless spectroscopy over λ = 2.4 - 5.0 μm in each module, and shorter wavelength observations of the same fields can be obtained simultaneously. We present the latest predicted grism sensitivities, saturation limits, resolving power, and wavelength coverage values based on component measurements, instrument tests, and end-to-end modeling. Short wavelength (0.6 - 2.3 μm) imaging observations of the 2.4 - 5.0 μm spectroscopic field can be performed in one of several different filter bands, either in-focus or defocused via weak lenses internal to NIRCam. Alternatively, the possibility of 1.0 - 2.0 μm spectroscopy (simultaneously with 2.4 - 5.0 μm) using dispersed Hartmann sensors (DHSs) is being explored. The grisms, weak lenses, and DHS elements were included in NIRCam primarily for wavefront sensing purposes, but all have significant science applications. Operational considerations including subarray sizes, and data volume limits are also discussed. Finally, we describe spectral simulation tools and illustrate potential scientific uses of the grisms by presenting simulated observations of deep extragalactic fields, galactic dark clouds, and transiting exoplanets.

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

Modeling the intense 2012-2013 dense water formation event in the northwestern Mediterranean Sea: Evaluation with an ensemble simulation approach

NASA Astrophysics Data System (ADS)

Waldman, Robin; Somot, Samuel; Herrmann, Marine; Bosse, Anthony; Caniaux, Guy; Estournel, Claude; Houpert, Loic; Prieur, Louis; Sevault, Florence; Testor, Pierre

2017-02-01

The northwestern Mediterranean Sea is a well-observed ocean deep convection site. Winter 2012-2013 was an intense and intensely documented dense water formation (DWF) event. We evaluate this DWF event in an ensemble configuration of the regional ocean model NEMOMED12. We then assess for the first time the impact of ocean intrinsic variability on DWF with a novel perturbed initial state ensemble method. Finally, we identify the main physical mechanisms driving water mass transformations. NEMOMED12 reproduces accurately the deep convection chronology between late January and March, its location off the Gulf of Lions although with a southward shift and its magnitude. It fails to reproduce the Western Mediterranean Deep Waters salinification and warming, consistently with too strong a surface heat loss. The Ocean Intrinsic Variability modulates half of the DWF area, especially in the open-sea where the bathymetry slope is low. It modulates marginally (3-5%) the integrated DWF rate, but its increase with time suggests its impact could be larger at interannual timescales. We conclude that ensemble frameworks are necessary to evaluate accurately numerical simulations of DWF. Each phase of DWF has distinct diapycnal and thermohaline regimes: during preconditioning, the Mediterranean thermohaline circulation is driven by exchanges with the Algerian basin. During the intense mixing phase, surface heat fluxes trigger deep convection and internal mixing largely determines the resulting deep water properties. During restratification, lateral exchanges and internal mixing are enhanced. Finally, isopycnal mixing was shown to play a large role in water mass transformations during the preconditioning and restratification phases.

Transferring Files Between the Deep Impact Spacecrafts and the Ground Data System Using the CCSDS File Delivery Protocol (CFDP): A Case Study

NASA Technical Reports Server (NTRS)

Sanders, Felicia A.; Jones, Grailing, Jr.; Levesque, Michael

2006-01-01

The CCSDS File Delivery Protocol (CFDP) Standard could reshape ground support architectures by enabling applications to communicate over the space link using reliable-symmetric transport services. JPL utilized the CFDP standard to support the Deep Impact Mission. The architecture was based on layering the CFDP applications on top of the CCSDS Space Link Extension Services for data transport from the mission control centers to the ground stations. On July 4, 2005 at 1:52 A.M. EDT, the Deep Impact impactor successfully collided with comet Tempel 1. During the final 48 hours prior to impact, over 300 files were uplinked to the spacecraft, while over 6 thousand files were downlinked from the spacecraft using the CFDP. This paper uses the Deep Impact Mission as a case study in a discussion of the CFDP architecture, Deep Impact Mission requirements, and design for integrating the CFDP into the JPL deep space support services. Issues and recommendations for future missions using CFDP are also provided.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

PubMed

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

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.

The Galaxy-Halo Connection in High-redshift Universe: Details and Evolution of Stellar-to-halo Mass Ratios of Lyman Break Galaxies on CFHTLS Deep Fields

NASA Astrophysics Data System (ADS)

Ishikawa, Shogo; Kashikawa, Nobunari; Toshikawa, Jun; Tanaka, Masayuki; Hamana, Takashi; Niino, Yuu; Ichikawa, Kohei; Uchiyama, Hisakazu

2017-05-01

We present the results of clustering analyses of Lyman break galaxies (LBGs) at z˜ 3, 4, and 5 using the final data release of the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). Deep- and wide-field images of the CFHTLS Deep Survey enable us to obtain sufficiently accurate two-point angular correlation functions to apply a halo occupation distribution analysis. The mean halo masses, calculated as < {M}h> ={10}11.7{--}{10}12.8 {h}-1 {M}⊙ , increase with the stellar-mass limit of LBGs. The threshold halo mass to have a central galaxy, {M}\\min , follows the same increasing trend as the low-z results, whereas the threshold halo mass to have a satellite galaxy, M 1, shows higher values at z=3{--}5 than z=0.5{--}1.5, over the entire stellar mass range. Satellite fractions of dropout galaxies, even at less massive halos, are found to drop sharply, from z = 2 down to less than 0.04, at z=3{--}5. These results suggest that satellite galaxies form inefficiently within dark halos at z=3{--}5, even for less massive satellites with {M}\\star < {10}10 {M}⊙ . We compute stellar-to-halo mass ratios (SHMRs) assuming a main sequence of galaxies, which is found to provide SHMRs consistent with those derived from a spectral energy distribution fitting method. The observed SHMRs are in good agreement with model predictions based on the abundance-matching method, within 1σ confidence intervals. We derive observationally, for the first time, {M}{{h}}{pivot}, which is the halo mass at a peak in the star-formation efficiency, at 3< z< 5, and it shows a small increasing trend with cosmic time at z> 3. In addition, {M}{{h}}{pivot} and its normalization are found to be almost unchanged during 0< z< 5. Our study provides observational evidence that galaxy formation is ubiquitously most efficient near a halo mass of {M}{{h}}˜ {10}12 {M}⊙ over cosmic time.

Low temperature hydrothermal oil and associated biological precursors in serpentinites from Mid-Ocean Ridge

NASA Astrophysics Data System (ADS)

Pasini, Valerio; Brunelli, Daniele; Dumas, Paul; Sandt, Christophe; Frederick, Joni; Benzerara, Karim; Bernard, Sylvain; Ménez, Bénédicte

2013-09-01

The origin of light hydrocarbons discovered at serpentinite-hosted mid-ocean hydrothermal fields is generally attributed to the abiogenic reduction of carbon (di)oxide by molecular hydrogen released during the progressive hydration of mantle-derived peridotites. These serpentinization by-products represent a valuable source of carbon and energy and are known to support deep microbial ecosystems unrelated to photosynthesis. In addition, the pool of subsurface organic compounds could also include materials derived from the thermal degradation of biological material. We re-investigate the recently described relics of deep microbial ecosystems hosted in serpentinites of the Mid-Atlantic Ridge (4-6°N) in order to study the ageing and (hydro)thermal degradation of the preserved biomass. An integrated set of high resolution micro-imaging techniques (Scanning Electron Microscopy, High Resolution Transmission Electron Microscopy, Raman and Fourier Transform Infra-Red microspectroscopy, Confocal Laser Scanning Microscopy, and Scanning Transmission X-ray Microscopy at the carbon K-edge) has been applied to map the distribution of the different organic components at the micrometer scale and to characterize their speciation and structure. We show that biologically-derived material, containing aliphatic groups, along with carbonyl and amide functional groups, has experienced hydrothermal degradation and slight aromatization. In addition, aliphatic compounds up to C6-C10 with associated carboxylic functional groups wet the host bastite and the late serpentine veins crosscutting the rock. These compounds represent a light soluble organic fraction expelled after biomass degradation through oxidation and thermal cracking. The detected complex organic matter distribution recalls a typical petroleum system, where fossil organic matter of biological origin maturates, expelling the soluble fraction which then migrates from the source to the reservoir. Ecosystem-hosting serpentinites can thus be seen as source rocks generating a net transfer of hydrocarbons and/or fatty acids issued from oxidative processes and primary cracking reactions, then migrating upward through the serpentine vein network. This finally suggests that deep thermogenic organic compounds of biological origin can be a significant contributor to the organic carbon balance at and far below peridotite-hosted hydrothermal fields.

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.

Deep cooling of optically trapped atoms implemented by magnetic levitation without transverse confinement.

PubMed

Li, Chen; Zhou, Tianwei; Zhai, Yueyang; Xiang, Jinggang; Luan, Tian; Huang, Qi; Yang, Shifeng; Xiong, Wei; Chen, Xuzong

2017-05-01

We report a setup for the deep cooling of atoms in an optical trap. The deep cooling is implemented by eliminating the influence of gravity using specially constructed magnetic coils. Compared to the conventional method of generating a magnetic levitating force, the lower trap frequency achieved in our setup provides a lower limit of temperature and more freedoms to Bose gases with a simpler solution. A final temperature as low as ∼6nK is achieved in the optical trap, and the atomic density is decreased by nearly two orders of magnitude during the second stage of evaporative cooling. This deep cooling of optically trapped atoms holds promise for many applications, such as atomic interferometers, atomic gyroscopes, and magnetometers, as well as many basic scientific research directions, such as quantum simulations and atom optics.

Deep cooling of optically trapped atoms implemented by magnetic levitation without transverse confinement

NASA Astrophysics Data System (ADS)

Li, Chen; Zhou, Tianwei; Zhai, Yueyang; Xiang, Jinggang; Luan, Tian; Huang, Qi; Yang, Shifeng; Xiong, Wei; Chen, Xuzong

2017-05-01

We report a setup for the deep cooling of atoms in an optical trap. The deep cooling is implemented by eliminating the influence of gravity using specially constructed magnetic coils. Compared to the conventional method of generating a magnetic levitating force, the lower trap frequency achieved in our setup provides a lower limit of temperature and more freedoms to Bose gases with a simpler solution. A final temperature as low as ˜ 6 nK is achieved in the optical trap, and the atomic density is decreased by nearly two orders of magnitude during the second stage of evaporative cooling. This deep cooling of optically trapped atoms holds promise for many applications, such as atomic interferometers, atomic gyroscopes, and magnetometers, as well as many basic scientific research directions, such as quantum simulations and atom optics.

Gulfport Harbor, Mississippi. Final Environmental Impact Statement

DTIC Science & Technology

1989-06-01

deep by 1320 feet wide by 2640 feet long to 36 feet deep by 1126 feeL wide by 2640 feet long with enlargement of the entrance to the basil - from a point...and other pesticides which concentrated in the pelican’s aquatic food EIS-25 source. Since 1973, the species appears to have made a comeback...were lower than those reported for the Mississippi Delta Region (Dames and Moore 1979). Pesticide concentrations were below detectable levels, however

How Do They Research? An Ethnographic Study of Final Year Undergraduate Research Behavior in an Irish University

ERIC Educational Resources Information Center

Dunne, Siobhán

2016-01-01

The objectives of this study were to identify how, when, and where students research; the impact of learning environments on research productivity, and to recommend improved supports to facilitate research. An ethnographic approach that entailed following five students in the final six weeks of their program enabled deep level analysis. The study…

Cluster mass calibration at high redshift: HST weak lensing analysis of 13 distant galaxy clusters from the South Pole Telescope Sunyaev-Zel'dovich Survey

NASA Astrophysics Data System (ADS)

Schrabback, T.; Applegate, D.; Dietrich, J. P.; Hoekstra, H.; Bocquet, S.; Gonzalez, A. H.; von der Linden, A.; McDonald, M.; Morrison, C. B.; Raihan, S. F.; Allen, S. W.; Bayliss, M.; Benson, B. A.; Bleem, L. E.; Chiu, I.; Desai, S.; Foley, R. J.; de Haan, T.; High, F. W.; Hilbert, S.; Mantz, A. B.; Massey, R.; Mohr, J.; Reichardt, C. L.; Saro, A.; Simon, P.; Stern, C.; Stubbs, C. W.; Zenteno, A.

2018-02-01

We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (zmedian = 0.88) galaxy clusters discovered in the South Pole Telescope (SPT) Sunyaev-Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass-observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V - I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration-mass relation using simulations. In combination with temperature estimates from Chandra we constrain the normalization of the mass-temperature scaling relation ln (E(z)M500c/1014 M⊙) = A + 1.5ln (kT/7.2 keV) to A=1.81^{+0.24}_{-0.14}(stat.) {± } 0.09(sys.), consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to c_200c=5.6^{+3.7}_{-1.8}.

Identifying nearby field T dwarfs in the UKIDSS Galactic Clusters Survey

NASA Astrophysics Data System (ADS)

Lodieu, N.; Burningham, B.; Hambly, N. C.; Pinfield, D. J.

2009-07-01

We present the discovery of two new late-T dwarfs identified in the UKIRT Infrared Deep Sky Survey (UKIDSS) Galactic Clusters Survey (GCS) Data Release 2 (DR2). These T dwarfs are nearby old T dwarfs along the line of sight to star-forming regions and open clusters targeted by the UKIDSS GCS. They are found towards the αPer cluster and Orion complex, respectively, from a search in 54deg2 surveyed in five filters. Photometric candidates were picked up in two-colour diagrams, in a very similar manner to candidates extracted from the UKIDSS Large Area Survey (LAS) but taking advantage of the Z filter employed by the GCS. Both candidates exhibit near-infrared J-band spectra with strong methane and water absorption bands characteristic of late-T dwarfs. We derive spectral types of T6.5 +/- 0.5 and T7 +/- 1 and estimate photometric distances less than 50 pc for UGCS J030013.86+490142.5 and UGCS J053022.52-052447.4, respectively. The space density of T dwarfs found in the GCS seems consistent with discoveries in the larger areal coverage of the UKIDSS LAS, indicating one T dwarf in 6-11deg2. The final area surveyed by the GCS, 1000deg2 in five passbands, will allow expansion of the LAS search area by 25 per cent, increase the probability of finding ultracool brown dwarfs, and provide optimal estimates of contamination by old field brown dwarfs in deep surveys to identify such objects in open clusters and star-forming regions. Based on observations made with the United Kingdom Infrared Telescope, operated by the Joint Astronomy Centre on behalf of the U.K. Science Technology and Facility Council. E-mail: nlodieu@iac.es

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.

Rock Melt Borehole Sealing System, Final Technical Report for SBIR Phase I Grant No. DE-SC0011888

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

Osnes, John D.; Vining, Cody A.; Nopola, Jay R.

Purpose of Research Deep borehole disposal is one option that has received attention in recent years as a possible strategy for long-term disposal of the tens of thousands of tons of spent nuclear fuel. The feasibility of the deep borehole option relies upon designing and constructing an effective seal within the borehole to ensure that the waste package does not communicate with the shallow subsurface biosphere through the borehole itself. Some of the uncertainty associated with the long-term suitability of the deep borehole option is related to (1) the degradation of traditional sealing materials over time and (2) the inabilitymore » of traditional sealing methods to adequately seal a Disturbed Rock Zone surrounding the borehole. One possible system to address these concerns consists of encapsulating the waste in a melt generated from either the waste itself or a plug above the waste. This current project expanded on previous work to further advance the deep borehole disposal concept. Research Objectives & Findings The overarching objective of the study was to evaluate the feasibility of constructing a downhole heater that is capable of meeting the technical and logistical requirements to melt rock. This ultimate objective was accomplished by two primary approaches. The first approach was to define the heater requirements and conceptually design a system that is capable of melting rock. The second approach was to determine the feasibility of conducting an in situ, field-scale melting experiment to validate the suitability of the rock melt seal concept. The evaluation and conceptual design of the heater system resulted in the following primary findings: • Borehole wall temperatures capable of producing a partial melt are achievable under most expected thermal conductivities with a 12-kilowatt heater. • Commercially available components have been identified that meet the requirements of the heater system, including resistive elements that are capable of providing the required heat generation, container materials that can withstand the anticipated temperatures, and a system capable of providing power to the heater. Evaluating the feasibility of performing field-scale experiments resulted in the following major findings: • The Sanford Underground Research Facility (SURF) has been identified as a host site for field testing of prototype heaters. The technical and logistical requirements for performing the rock melt tests can be met by using or expanding the existing infrastructure at SURF with on-site personnel and contractors. • In situ hydraulic conductivity test using packers can test the effectiveness of the rock melt seal, while a mine back performed from a lower level can further evaluate the recrystallized melt. • Preliminary costing indicates that a field-scale melting experiment at SURF is feasible within a Phase II Small Business Innovation Research budget while allowing sufficient budget for refining the heater design, coordinating the test program, and interpreting the results. Application of Research The rock melt sealing concept has the potential to reduce uncertainty associated with the long-term storage of nuclear waste. Preliminary efforts of this study defined the requirements of a downhole heater system capable of melting rock and indicated that developing such a system is feasible using available technology. The next logical step is designing and manufacturing prototype heaters. Concurrent with prototype development is coordinating robust field-scale experiments that are capable of validating the design for marketing to potential users.« less

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.

Construction risk assessment of deep foundation pit in metro station based on G-COWA method

NASA Astrophysics Data System (ADS)

You, Weibao; Wang, Jianbo; Zhang, Wei; Liu, Fangmeng; Yang, Diying

2018-05-01

In order to get an accurate understanding of the construction safety of deep foundation pit in metro station and reduce the probability and loss of risk occurrence, a risk assessment method based on G-COWA is proposed. Firstly, relying on the specific engineering examples and the construction characteristics of deep foundation pit, an evaluation index system based on the five factors of “human, management, technology, material and environment” is established. Secondly, the C-OWA operator is introduced to realize the evaluation index empowerment and weaken the negative influence of expert subjective preference. The gray cluster analysis and fuzzy comprehensive evaluation method are combined to construct the construction risk assessment model of deep foundation pit, which can effectively solve the uncertainties. Finally, the model is applied to the actual project of deep foundation pit of Qingdao Metro North Station, determine its construction risk rating is “medium”, evaluate the model is feasible and reasonable. And then corresponding control measures are put forward and useful reference are provided.

Biogeochemical malfunctioning in sediments beneath a deep-water fish farm.

PubMed

Valdemarsen, Thomas; Bannister, Raymond J; Hansen, Pia K; Holmer, Marianne; Ervik, Arne

2012-11-01

We investigated the environmental impact of a deep water fish farm (190 m). Despite deep water and low water currents, sediments underneath the farm were heavily enriched with organic matter, resulting in stimulated biogeochemical cycling. During the first 7 months of the production cycle benthic fluxes were stimulated >29 times for CO(2) and O(2) and >2000 times for NH(4)(+), when compared to the reference site. During the final 11 months, however, benthic fluxes decreased despite increasing sedimentation. Investigations of microbial mineralization revealed that the sediment metabolic capacity was exceeded, which resulted in inhibited microbial mineralization due to negative feed-backs from accumulation of various solutes in pore water. Conclusions are that (1) deep water sediments at 8 °C can metabolize fish farm waste corresponding to 407 and 29 mmol m(-2) d(-1) POC and TN, respectively, and (2) siting fish farms at deep water sites is not a universal solution for reducing benthic impacts. Copyright © 2012 Elsevier Ltd. All rights reserved.

Part-based deep representation for product tagging and search

NASA Astrophysics Data System (ADS)

Chen, Keqing

2017-06-01

Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

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.

Landslide oil field, San Joaquin Valley, California

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

Collins, B.P.; March, K.A.; Caballero, J.S.

1988-03-01

The Landslide field, located at the southern margin of the San Joaquin basin, was discovered in 1985 by a partnership headed by Channel Exploration Company, on a farm out from Tenneco Oil Company. Initial production from the Tenneco San Emidio 63X-30 was 2064 BOPD, making landslide one of the largest onshore discoveries in California during the past decade. Current production is 7100 BOPD from a sandstone reservoir at 12,500 ft. Fifteen wells have been drilled in the field, six of which are water injectors. Production from the Landslide field occurs from a series of upper Miocene Stevens turbidite sandstones thatmore » lie obliquely across an east-plunging structural nose. These turbidite sandstones were deposited as channel-fill sequences within a narrowly bounded levied channel complex. Both the Landslide field and the larger Yowlumne field, located 3 mi to the northwest, comprise a single channel-fan depositional system that developed in the restricted deep-water portion of the San Joaquin basin. Information from the open-hole logs, three-dimensional surveys, vertical seismic profiles, repeat formation tester data, cores, and pressure buildup tests allowed continuous drilling from the initial discovery to the final waterflood injector, without a single dry hole. In addition, the successful application of three-dimensional seismic data in the Landslide development program has helped correctly image channel-fan anomalies in the southern Maricopa basin, where data quality and severe velocity problems have hampered previous efforts. New exploration targets are currently being evaluated on the acreage surrounding the Landslide discovery and should lead to an interesting new round of drilling activity in the Maricopa basin.« less

A whole new Mercury: MESSENGER reveals a dynamic planet at the last frontier of the inner solar system

NASA Astrophysics Data System (ADS)

Johnson, Catherine L.; Hauck, , Steven A.

2016-11-01

The MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission yielded a wealth of information about the innermost planet. For the first time, visible images of the entire planet, absolute altimetry measurements and a global gravity field, measurements of Mercury's surface composition, magnetic field, exosphere, and magnetosphere taken over more than four Earth years are available. From these data, two overarching themes emerge. First, multiple data sets and modeling efforts point toward a dynamic ancient history. Signatures of graphite in the crust suggest solidification of an early magma ocean, image data show extensive volcanism and tectonic features indicative of subsequent global contraction, and low-altitude measurements of magnetic fields reveal an ancient magnetic field. Second, the present-day Mercury environment is far from quiescent. Convective motions in the outer core support a modern magnetic field whose strength and geometry are unique among planets with global magnetic fields. Furthermore, periodic and aperiodic variations in the magnetosphere and exosphere have been observed, some of which couple to the surface and the planet's deep interior. Finally, signatures of geologically recent volatile activity at the surface have been detected. Mercury's early history and its present-day environment have common elements with the other inner solar system bodies. However, in each case there are also crucial differences and these likely hold the key to further understanding of Mercury and terrestrial planet evolution. MESSENGER's exploration of Mercury has enabled a new view of the innermost planet, and more importantly has set the stage for much-needed future exploration.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

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.

Galaxy Assembly and the Evolution of Structure over the First Third of Cosmic Time - III

NASA Astrophysics Data System (ADS)

Faber, Sandra

2011-10-01

This survey will document the first third of galactic evolution fromz=8 to 1.5 andtest for evolution in the properties of Type Ia supernovae to z 2 byimaging more than 250,000 galaxies with WFC3/IR and ACS. Five premiermulti-wavelength regions are selected from within the Spitzer SEDSsurvey, providing complementaryIRAC data down to 26.5 AB mag, a unique resource forstellar masses at high redshifts. The use of five widely separatedfields mitigates cosmic variance and yields statistically robustsamples of galaxies down to 10^9 M_Sun out to z 8.We adopt a two-tiered strategy with a "Wide" component {roughly 2orbits deep over 0.2 sq. degrees} and a "Deep" component {roughly 12orbits deep over 0.04 sq. degrees}. Combining these with ultra-deepimaging from the Cycle 17 HUDF09 program yields a three-tieredstrategy for efficient sampling of both rare/bright and faint/commonobjects.Three of the Wide-survey fields are located in COSMOS, EGS, andUKIDSS/UDS. Each of these consists of roughly 3x15 WFC3/IR tiles.Each WFC3 tile will be observed for 2 orbits, with single orbitsseparated in time to allow a search for high-redshift Type Ia SNe.The co-added exposure times will be approximately 2/3 orbit in J{F125W} and 4/3 orbit in H {F160W}. ACS parallels overlap most of theWFC3 area and will consist of roughly 2/3 orbits in V {F606W} and4/3 orbit in I {F814W}. Because of the larger area of ACS,this results in effective exposures that are twice as long {4/3 in V,8/3 in I}, making a very significant improvement to existing ACSmosaics in COSMOS and EGS and creating a new ACS mosaic in UDS/UKIDSSwhere none now exists. Other Wide-survey components are located inthe GOODS fields {North and South} surrounding the Deep-survey areas.The Deep-survey fields cover roughly half of each GOODS field, withexact areas and placements to be determined as part of the Phase-2process. Each WFC3/IR tile within the Deep regions will receiveapproximately 12 orbits of exposure time split between Y{F105W}, J {F125W}, and H {F160W}. Multi-epoch imaging will provide anefficient search for high-redshift Type Ia SNe here also. ACSparallels are also taken in the Deep regions, with the goal ofassembling enough total exposure time in F850LP and other filters toidentify high redshift z>6 galaxies in concert with WFC3/IR data usingthe Lyman break technique.A portion of the GOODS-N campaign will take place while the field isin the HST Continuous Viewing Zone {CVZ}. The bright time in thoseorbits will be used to obtain UV imaging with WFC3 in the F275W andF336W filters. The exact number of orbits will not be known untilPhase-2 planning is complete, but we anticipate that it will bepossible to schedule at least 100 orbits, resulting in 5-sigmapoint-source depths of 26.6, 26.4 in F275W and F336W,respectively. The science goals include measuring the Lyman-continuumescape fractions for galaxies at z 2.5 and identifying Lyman-breakgalaxies at z 2-3.The Type Ia supernova search program in this proposal is integratedwith that in the Postman cluster MCT proposal, with this one stressingthe more distant supernovae. A combined follow-up program will providelight curves and grism spectra of 15-20 of the best candidates atredshifts 17 galaxies in the Deep regions, inaddition to hundreds of highly-luminous candidates in the Wide regionsfor detailed follow-up. These samples will be used to construct aunified picture of star-formation and stellar mass buildup in earlygalaxies. Extremely deep X-ray data will reveal distant AGNs to z>6,shedding light on the earliest stages of BH growth. In the peak starformation/QSO era, z 2, we will document the properties of earlydisks, the build-up of bulges, the evolution of mergers, and thenature of AGN hosts to construct an integrated model for structuralevolution, star formation quenching, and AGN triggering. Finally, the 8 Type Ia SNe found beyond z>1.5 in the supernova programs willestablish the constancy of these standard candles independent of darkenergy and yield the first measurement of the Type Ia rate at z 2 todistinguish among different progenitor models. Lower-redshift SNe Iaat 1

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.

Radio-Optical Reference Frame Link Using the U.S. Naval Observatory Astrograph and Deep CCD Imaging

NASA Astrophysics Data System (ADS)

Zacharias, N.; Zacharias, M. I.

2014-05-01

Between 1997 and 2004 several observing runs were conducted, mainly with the CTIO 0.9 m, to image International Celestial Reference Frame (ICRF) counterparts (mostly QSOs) in order to determine accurate optical positions. Contemporary to these deep CCD images, the same fields were observed with the U.S. Naval Observatory astrograph in the same bandpass. They provide accurate positions on the Hipparcos/Tycho-2 system for stars in the 10-16 mag range used as reference stars for the deep CCD imaging data. Here we present final optical position results of 413 sources based on reference stars obtained by dedicated astrograph observations that were reduced following two different procedures. These optical positions are compared to radio very long baseline interferometry positions. The current optical system is not perfectly aligned to the ICRF radio system with rigid body rotation angles of 3-5 mas (= 3σ level) found between them for all three axes. Furthermore, statistically, the optical-radio position differences are found to exceed the total, combined, known errors in the observations. Systematic errors in the optical reference star positions and physical offsets between the centers of optical and radio emissions are both identified as likely causes. A detrimental, astrophysical, random noise component is postulated to be on about the 10 mas level. If confirmed by future observations, this could severely limit the Gaia to ICRF reference frame alignment accuracy to an error of about 0.5 mas per coordinate axis with the current number of sources envisioned to provide the link. A list of 36 ICRF sources without the detection of an optical counterpart to a limiting magnitude of about R = 22 is provided as well.

Real time coarse orientation detection in MR scans using multi-planar deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Bhatia, Parmeet S.; Reda, Fitsum; Harder, Martin; Zhan, Yiqiang; Zhou, Xiang Sean

2017-02-01

Automatically detecting anatomy orientation is an important task in medical image analysis. Specifically, the ability to automatically detect coarse orientation of structures is useful to minimize the effort of fine/accurate orientation detection algorithms, to initialize non-rigid deformable registration algorithms or to align models to target structures in model-based segmentation algorithms. In this work, we present a deep convolution neural network (DCNN)-based method for fast and robust detection of the coarse structure orientation, i.e., the hemi-sphere where the principal axis of a structure lies. That is, our algorithm predicts whether the principal orientation of a structure is in the northern hemisphere or southern hemisphere, which we will refer to as UP and DOWN, respectively, in the remainder of this manuscript. The only assumption of our method is that the entire structure is located within the scan's field-of-view (FOV). To efficiently solve the problem in 3D space, we formulated it as a multi-planar 2D deep learning problem. In the training stage, a large number coronal-sagittal slice pairs are constructed as 2-channel images to train a DCNN to classify whether a scan is UP or DOWN. During testing, we randomly sample a small number of coronal-sagittal 2-channel images and pass them through our trained network. Finally, coarse structure orientation is determined using majority voting. We tested our method on 114 Elbow MR Scans. Experimental results suggest that only five 2-channel images are sufficient to achieve a high success rate of 97.39%. Our method is also extremely fast and takes approximately 50 milliseconds per 3D MR scan. Our method is insensitive to the location of the structure in the FOV.

Discontinuum-Equivalent Continuum Analysis of the Stability of Tunnels in a Deep Coal Mine Using the Distinct Element Method

NASA Astrophysics Data System (ADS)

Shreedharan, Srisharan; Kulatilake, Pinnaduwa H. S. W.

2016-05-01

An imperative task for successful underground mining is to ensure the stability of underground structures. This is more so for deep excavations which may be under significantly high stresses. In this manuscript, we present stability studies on two tunnels, a horseshoe-shaped and an inverted arch-shaped tunnel, in a deep coal mine in China, performed using the 3DEC distinct element code. The rock mass mechanical property values for the tunnel shapes have been estimated through a back-analysis procedure using available field deformation data. The back-analysis has been carried out through a pseudo-time dependent support installation routine which incorporates the effect of time through a stress-relaxation mechanism. The back-analysis indicates that the rock mass cohesion, tensile strength, uniaxial compressive strength, and elastic modulus values are about 35-45 % of the corresponding intact rock property values. Additionally, the importance of incorporating stress relaxation before support installation has been illustrated through the increased support factor of safety and reduced grout failures. The calibrated models have been analyzed for different supported and unsupported cases to estimate the significance and adequacy of the current supports being used in the mine and to suggest a possible optimization. The effects of supports have been demonstrated using deformations and yield zones around the tunnels, and average factors of safety and grout failures of the supports. The use of longer supports and floor bolting has provided greater stability for the rock masses around the tunnels. Finally, a comparison between the two differently shaped tunnels establishes that the inverted arch tunnel may be more efficient in reducing roof sag and floor heave for the existing geo-mining conditions.

Radio-optical reference frame link using the U.S. Naval observatory astrograph and deep CCD imaging

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

Zacharias, N.; Zacharias, M. I., E-mail: nz@usno.navy.mil

2014-05-01

Between 1997 and 2004 several observing runs were conducted, mainly with the CTIO 0.9 m, to image International Celestial Reference Frame (ICRF) counterparts (mostly QSOs) in order to determine accurate optical positions. Contemporary to these deep CCD images, the same fields were observed with the U.S. Naval Observatory astrograph in the same bandpass. They provide accurate positions on the Hipparcos/Tycho-2 system for stars in the 10-16 mag range used as reference stars for the deep CCD imaging data. Here we present final optical position results of 413 sources based on reference stars obtained by dedicated astrograph observations that were reducedmore » following two different procedures. These optical positions are compared to radio very long baseline interferometry positions. The current optical system is not perfectly aligned to the ICRF radio system with rigid body rotation angles of 3-5 mas (= 3σ level) found between them for all three axes. Furthermore, statistically, the optical-radio position differences are found to exceed the total, combined, known errors in the observations. Systematic errors in the optical reference star positions and physical offsets between the centers of optical and radio emissions are both identified as likely causes. A detrimental, astrophysical, random noise component is postulated to be on about the 10 mas level. If confirmed by future observations, this could severely limit the Gaia to ICRF reference frame alignment accuracy to an error of about 0.5 mas per coordinate axis with the current number of sources envisioned to provide the link. A list of 36 ICRF sources without the detection of an optical counterpart to a limiting magnitude of about R = 22 is provided as well.« less

Retroarc extension in the last 6 Ma in the South-Central Andes (36°S-40°S) evaluated through a 3-D gravity modelling

NASA Astrophysics Data System (ADS)

Folguera, A.; Alasonati Tašárová, Z.; Götze, H.-J.; Rojas Vera, E.; Giménez, M.; Ramos, V. A.

2012-12-01

The Andean retroarc between 35° and 40°S is the locus of debate regarding its Pliocene to Quaternary tectonic setting. Retroarc volcanic eruptions since 6 Ma to the Present are, based on some hypotheses, associated with widespread extension. In these works, geological data point to the existence of normal faults affecting previous (Late Cretaceous to Miocene) contractional structures. In order to evaluate such interpretations we have collected data from various geological and geophysical studies and scales. Based on these data, an existing large-scale 3-D gravity model could be improved and used to investigate the lithospheric structure of this region. Moreover, using the gravity model, an attenuated crust could be localized and quantified throughout the retroarc area. Deep seismic data available from this region are limited to the forearc - arc area, while in general the retroarc zone lacks deep seismic constraints. The only deep seismic profile extending to the retroarc is a receiver function profile at 39°S, showing crustal attenuation. This observation correlates with the extensional activity recognized at the surface. When analysing the gravity field, positive residual anomalies are observed. They correlate with crustal attenuation at the areas of extension. Also, computed elastic thickness in the retroarc shows good correlation between the areas of crustal stretching and low flexural rigidity, explained by thermal processes. The present extensional deformation reflected in positive residual gravity anomalies points to the influence of reactivated Triassic rifting inherited from early phases of Pangea break-up. Finally, the present local uplift and consequent fluvial incision at the retroarc zone are explained by crustal stretching and not by crustal shortening, the common mechanism in Andean orogenesis.

Deep magmatic degassing versus scrubbing: Elevated CO2 emissions and C/S in the lead-up to the 2009 eruption of Redoubt Volcano, Alaska

USGS Publications Warehouse

Werner, Cynthia A.; Evans, William C.; Kelly, Peter; McGimsey, Robert G.; Pfeffer, Melissa; Doukas, Michael P.; Neal, Christina

2012-01-01

We report CO2, SO2, and H2S emission rates and C/S ratios during the five months leading up to the 2009 eruption of Redoubt Volcano, Alaska. CO2emission rates up to 9018 t/d and C/S ratios ≥30 measured in the months prior to the eruption were critical for fully informed forecasting efforts. Observations of ice-melt rates, meltwater discharge, and water chemistry suggest that surface waters represented drainage from surficial, perched reservoirs of condensed magmatic steam and glacial meltwater. These fluids scrubbed only a few hundred tonnes/day of SO2, not the >2100 t/d SO2expected from degassing of magma in the mid- to upper crust (3–6.5 km), where petrologic analysis shows the final magmatic equilibration occurred. All data are consistent with upflow of a CO2-rich magmatic gas for at least 5 months prior to eruption, and minimal scrubbing of SO2by near-surface groundwater. The high C/S ratios observed could reflect bulk degassing of mid-crustal magma followed by nearly complete loss of SO2in a deep magmatic-hydrothermal system. Alternatively, high C/S ratios could be attributed to decompressional degassing of low silica andesitic magma that intruded into the mid-crust in the 5 months prior to eruption, thereby mobilizing the pre-existing high silica andesite magma or mush in this region. The latter scenario is supported by several lines of evidence, including deep long-period earthquakes (−28 to −32 km) prior to and during the eruption, and far-field deformation following the onset of eruptive activity.

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.

Tectonic constraints on a deep-seated rock slide in weathered crystalline rocks

NASA Astrophysics Data System (ADS)

Borrelli, Luigi; Gullà, Giovanni

2017-08-01

Deep-seated rock slides (DSRSs), recognised as one of the most important mass wasting processes worldwide, involve large areas and cause several consequences in terms of environmental and economic damage; they result from a complex of controlling features and processes. DSRSs are common in Calabria (southern Italy) where the complex geo-structural setting plays a key role in controlling the geometry of the failure surface and its development. This paper describes an integrated multi-disciplinary approach to investigate a DSRS in Palaeozoic high-grade metamorphic rocks of the Sila Massif; it focuses on the definition of the internal structure and the predisposing factors of the Serra di Buda landslide near the town of Acri, which is a paradigm for numerous landslides in this area. An integrated interdisciplinary study based on geological, structural, and geomorphological investigations-including field observations of weathering grade of rocks, minero-petrographic characterisations, geotechnical investigations and, in particular, fifteen years of displacement monitoring-is presented. Stereoscopic analysis of aerial photographs and field observations indicate that the Serra di Buda landslide consists of two distinct compounded bodies: (i) an older and dormant body ( 7 ha) and (ii) a more recent and active body ( 13 ha) that overlies the previous one. The active landslide shows movement linked to a deep-seated translational rock slide (block slide); the velocity scale ranges from slow (1.6 m/year during paroxysmal stages) to extremely slow (< 16 mm/year during stable creep stages). The geological structures and rock weathering have played a key role in the landslide's initiation and further development. Steep slope angles, rugged topography, river deepening and erosion at the toe of the slope are also responsible for the formation of this landslide. In particular, the landslide shows a strongly tectonic constraint: the flanks are bounded by high-angle faults, and the main basal failure surface developed inside an E-W southward-dipping thrust fault zone. The entire active rock mass (total volume of approximately 6 Mm3) slid at one time on a failure surface that dipped < 27°, and the maximum depth, as determined by inclinometer measurements, was approximately 58 m. Petrographic and mineralogical analyses suggest that the rocks in the thrust zones, where the failure surfaces develop, are highly affected by weathering processes that significantly reduce the rock strength and facilitate the extensive failure of the Serra di Buda landslide. Finally, the landslide's internal structure, according to geotechnical investigations and displacement monitoring, is proposed. The proposed approach and the obtained results can be generalised to typify other deep landslides in similar geological settings.

Design and application of electromechanical actuators for deep space missions

NASA Technical Reports Server (NTRS)

Haskew, Tim A.; Wander, John

1995-01-01

This third semi-annual progress report covers the reporting period from August 16, 1994 through February 15, 1995 on NASA Grant NAG8-240, 'Design and Application of Electromechanical Actuators for Deep Space Missions'. There are two major report sections: Motor Control Status/Electrical Experiment Planning and Experiment Planning and Initial Results. The primary emphasis of our efforts during the reporting period has been final construction and testing of the laboratory facilities. As a result, this report is dedicated to that topic.

Deep-UV Emitters and Detectors Based on Lattice-Matched Cubic Oxide Semiconductors (4.2 Optoelectronics)

DTIC Science & Technology

2015-05-14

calculated   by   dividing   photo-­‐‑ generated  current  by  the  optical  power  spectrum  of  the   lamp .    A   UV ...the optimized parameters for growth. Efforts led to significant increases in solar?blind detector responsivity (up to 0.1 A/W) with sub-­ nanoamp...Aug-2014 Approved for Public Release; Distribution Unlimited Final Report: Deep- UV Emitters and Detectors Based on Lattice- Matched Cubic Oxide

The strange sea density and charm production in deep inelastic charged current processes

NASA Astrophysics Data System (ADS)

Glück, M.; Kretzer, S.; Reya, E.

1996-02-01

Charm production as related to the determination of the strange sea density in deep inelastic charged current processes is studied predominantly in the framework of the overlineMS fixed flavor factorization scheme. Perturbative stability within this formalism is demonstrated. The compatibility of recent next-to-leading order strange quark distributions with the available dimuon and F2νN data is investigated. It is shown that final conclusions concerning these distributions afford further analyses of presently available and/or forthcoming neutrino data.

GEOPHYSICS, ASTRONOMY AND ASTROPHYSICS: A two scale nonlinear fractal sea surface model in a one dimensional deep sea

NASA Astrophysics Data System (ADS)

Xie, Tao; Zou, Guang-Hui; William, Perrie; Kuang, Hai-Lan; Chen, Wei

2010-05-01

Using the theory of nonlinear interactions between long and short waves, a nonlinear fractal sea surface model is presented for a one dimensional deep sea. Numerical simulation results show that spectra intensity changes at different locations (in both the wave number domain and temporal-frequency domain), and the system obeys the energy conservation principle. Finally, a method to limit the fractal parameters is also presented to ensure that the model system does not become ill-posed.

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

PubMed

Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

2018-02-26

Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

Knowledge and power in integrated coastal management. For a political anthropology of the sea combined with the sciences of the marine environment

NASA Astrophysics Data System (ADS)

Mazé, Camille; Dahou, Tarik; Ragueneau, Olivier; Danto, Anatole; Mariat-Roy, Emilie; Raimonet, Mélanie; Weisbein, Julien

2017-10-01

This article presents an innovative collaborative approach, which aims to reinforce and institutionalize the field of the political anthropology of the sea combined with the natural sciences. It begins by relating the evolution in coastal areas, from integrated coastal zone management to the notion of adaptive co-management. It then sets out what contribution the social sciences of politics may bring to our understanding of the government/governance of the sea in terms of sustainable development, starting with political science and then highlighting the importance of a deep anthropological and socio-historical approach. Finally, it gives us a glimpse of the benefits of combining the human and social sciences with the natural sciences to produce a critical analysis of the categories of thought and action associated with the systemic management of the environment, especially the coastal areas.

Learning a generative model of images by factoring appearance and shape.

PubMed

Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John

2011-03-01

Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.

Self-regulation in self-propelled nematic fluids.

PubMed

Baskaran, A; Marchetti, M C

2012-09-01

We consider the hydrodynamic theory of an active fluid of self-propelled particles with nematic aligning interactions. This class of materials has polar symmetry at the microscopic level, but forms macrostates of nematic symmetry. We highlight three key features of the dynamics. First, as in polar active fluids, the control parameter for the order-disorder transition, namely the density, is dynamically convected by the order parameter via active currents. The resulting dynamical self-regulation of the order parameter is a generic property of active fluids and destabilizes the uniform nematic state near the mean-field transition. Secondly, curvature-driven currents render the system unstable deep in the nematic state, as found previously. Finally, and unique to self-propelled nematics, nematic order induces local polar order that in turn leads to the growth of density fluctuations. We propose this as a possible mechanism for the smectic order of polar clusters seen in numerical simulations.

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

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

Technical Report - FINAL

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

Barbara Luke, Director, UNLV Engineering Geophysics Laboratory

2007-04-25

Improve understanding of the earthquake hazard in the Las Vegas Valley and to assess the state of preparedness of the area's population and structures for the next big earthquake. 1. Enhance the seismic monitoring network in the Las Vegas Valley 2. Improve understanding of deep basin structure through active-source seismic refraction and reflection testing 3. Improve understanding of dynamic response of shallow sediments through seismic testing and correlations with lithology 4. Develop credible earthquake scenarios by laboratory and field studies, literature review and analyses 5. Refine ground motion expectations around the Las Vegas Valley through simulations 6. Assess current buildingmore » standards in light of improved understanding of hazards 7. Perform risk assessment for structures and infrastructures, with emphasis on lifelines and critical structures 8. Encourage and facilitate broad and open technical interchange regarding earthquake safety in southern Nevada and efforts to inform citizens of earthquake hazards and mitigation opportunities« less

ALMA Reveals a Compact Starburst Around a Hidden QSO at z˜5

NASA Astrophysics Data System (ADS)

Gilli, R.; Norman, C. A.; Vignali, C.

2015-12-01

We present ALMA 1.3mm observations of XID403, an SMG at z=4.75 in the Chandra Deep Field South hosting a heavily obscured, Compton-thick QSO. The ALMA data show that the dust heated by star formation is distributed within ˜0.9 kpc from the nucleus (effective radius). The SFR and dust temperature obtained from the Herschel+ALMA far-IR SED, reveal a warm and compact starburst with surface density of 200 M⊙ yr-1 kpc-2. Our analysis suggest that, besides the mass, SFR and gas consumption timescale, objects like XID403 have also the right size to be the progenitors of the compact quiescent massive galaxies seen at z˜3. It is finally shown that the density of the gas co-spatial with the dust provides a substantial contribution to the absorbing column density towards the QSO as measured from the X-rays.

T.Rex

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

2016-06-08

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

Cosmic Dawn with WFIRST

NASA Astrophysics Data System (ADS)

Rhoads, James

Central objectives: WFIRST-AFTA has tremendous potential for studying the epoch of "Cosmic Dawn" the period encompassing the formation of the first galaxies and quasars, and their impact on the surrounding universe through cosmological reionization. Our goal is to ensure that this potential is realized through the middle stages of mission planning, culminating in designs for both WFIRST and its core surveys that meet the core objectives in dark energy and exoplanet science, while maximizing the complementary Cosmic Dawn science. Methods: We will consider a combined approach to studying Cosmic Dawn using a judicious mixture of guest investigator data analysis of the primary WFIRST surveys, and a specifically designed Guest Observer program to complement those surveys. The Guest Observer program will serve primarily to obtain deep field observations, with particular attention to the capabilities of WFIRST for spectroscopic deep fields using the WFI grism. We will bring to bear our years of experience with slitless spectroscopy on the Hubble Space Telescope, along with an expectation of JWST slitless grism spectroscopy. We will use this experience to examine the implications of WFIRST’s grism resolution and wavelength coverage for deep field observations, and if appropriate, to suggest potential modifications of these parameters to optimize the science return on WFIRST. We have assembled a team of experts specializing in (1) Lyman Break Galaxies at redshifts higher than 7 (2) Quasars at high redshifts (3) Lyman-alpha galaxies as probes of reionization (4) Theoretical simulations of high-redshift galaxies (5) Simulations of grism observations (6) post-processing analysis to find emission line galaxies and high redshift galaxies (7) JWST observations and calibrations. With this team we intend to do end-to-end simulations starting with halo populations and expected spectra of high redshift galaxies and finally extracting what we can learn about (a) reionization using the Lyman-alpha test (b) the sources of reionization - both galaxies and AGN and (c) how to optimize WFIRST-AFTA surveys to maximize scientific output of this mission. Along the way, we will simulate the galaxy and AGN populations expected beyond redshift 7, and will simulate observations and data analysis of these populations with WFIRST. Significance of work: Cosmic Dawn is one of the central pillars of the "New Worlds, New Horizons" decadal survey. WFIRST's highly sensitive and wide-field near-infrared capabilities offer a natural tool to obtain statistically useful samples of faint galaxies and AGN beyond redshift 7. Thus, we expect Cosmic Dawn observations will constitute a major component of the GO program ultimately executed by WFIRST. By supporting our Science Investigation Team to consider the interplay between the mission parameters and the ultimate harvest of Cosmic Dawn science, NASA will help ensure the success of WFIRST as a broadly focused flagship mission.

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.

Charge structure of the hadronic final state in deep-inelastic muon-nucleon scattering

NASA Astrophysics Data System (ADS)

Arneodo, M.; Arvidson, A.; Aubert, J. J.; Bedełek, J.; Beaufays, J.; Bee, C. P.; Benchouk, C.; Berghoff, G.; Bird, I.; Blum, D.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Braun, H.; Broll, C.; Brown, S.; Brück, H.; Calen, H.; Chima, J. S.; Ciborowski, J.; Clifft, R.; Coignet, G.; Combley, F.; Coughlan, J.; D'Agostini, G.; Dahlgren, S.; Dengler, F.; Derado, I.; Dreyer, T.; Drees, J.; Düren, M.; Eckardt, V.; Edwards, A.; Edwards, M.; Ernst, T.; Eszes, G.; Favier, J.; Ferrero, M. I.; Figiel, J.; Flauger, W.; Foster, J.; Ftáčnik, J.; Gabathuler, E.; Gajewski, J.; Gamet, R.; Gayler, J.; Geddes, N.; Grafström, P.; Grard, F.; Haas, J.; Hagberg, E.; Hasert, F. J.; Hayman, P.; Heusse, P.; Jaffré, M.; Jachołkowska, A.; Janata, F.; Jancsó, G.; Johnson, A. S.; Kabuss, E. M.; Kellner, G.; Korbel, V.; Krüger, J.; Kullander, S.; Landgraf, U.; Lanske, D.; Loken, J.; Long, K.; Maire, M.; Malecki, P.; Manz, A.; Maselli, S.; Mohr, W.; Montanet, F.; Montgomery, H. E.; Nagy, E.; Nassalski, J.; Norton, P. R.; Oakham, F. G.; Osborne, A. M.; Pascaud, C.; Pawlik, B.; Payre, P.; Peroni, C.; Peschel, H.; Pessard, H.; Pettinghale, J.; Pietrzyk, B.; Pietrzyk, U.; Pönsgen, B.; Pötsch, M.; Renton, P.; Ribarics, P.; Rith, K.; Rondio, E.; Sandacz, A.; Scheer, M.; Schlagböhmer, A.; Schiemann, H.; Schmitz, N.; Schneegans, M.; Schneider, A.; Scholz, M.; Schröder, T.; Schultze, K.; Sloan, T.; Stier, H. E.; Studt, M.; Taylor, G. N.; Thénard, J. M.; Thompson, J. C.; de La Torre, A.; Toth, J.; Urban, L.; Wallucks, W.; Whalley, M.; Wheeler, S.; Williams, W. S. C.; Wimpenny, S. J.; Windmolders, R.; Wolf, G.

1988-09-01

The general charge properties of the hadronic final state produced in μ + p and μ + d interactions at 280 GeV are investigated. Quark charge retention and local charge compensation is observed. The ratio F {2/ n }/ F {2/ p } of the neutron to proton structure function is derived from the measurement of the average hadronic charge in μ d interactions.

WINGS: A WIde-field Nearby Galaxy-cluster Survey. II. Deep optical photometry of 77 nearby clusters

NASA Astrophysics Data System (ADS)

Varela, J.; D'Onofrio, M.; Marmo, C.; Fasano, G.; Bettoni, D.; Cava, A.; Couch, W. J.; Dressler, A.; Kjærgaard, P.; Moles, M.; Pignatelli, E.; Poggianti, B. M.; Valentinuzzi, T.

2009-04-01

Context: This is the second paper of a series devoted to the WIde Field Nearby Galaxy-cluster Survey (WINGS). WINGS is a long term project which is gathering wide-field, multi-band imaging and spectroscopy of galaxies in a complete sample of 77 X-ray selected, nearby clusters (0.04 < z < 0.07) located far from the galactic plane (|b|≥ 20°). The main goal of this project is to establish a local reference for evolutionary studies of galaxies and galaxy clusters. Aims: This paper presents the optical (B,V) photometric catalogs of the WINGS sample and describes the procedures followed to construct them. We have paid special care to correctly treat the large extended galaxies (which includes the brightest cluster galaxies) and the reduction of the influence of the bright halos of very bright stars. Methods: We have constructed photometric catalogs based on wide-field images in B and V bands using SExtractor. Photometry has been performed on images in which large galaxies and halos of bright stars were removed after modeling them with elliptical isophotes. Results: We publish deep optical photometric catalogs (90% complete at V ~ 21.7, which translates to ˜ M^*_V+6 at mean redshift), giving positions, geometrical parameters, and several total and aperture magnitudes for all the objects detected. For each field we have produced three catalogs containing galaxies, stars and objects of “unknown” classification (~6%). From simulations we found that the uncertainty of our photometry is quite dependent of the light profile of the objects with stars having the most robust photometry and de Vaucouleurs profiles showing higher uncertainties and also an additional bias of ~-0.2^m. The star/galaxy classification of the bright objects (V < 20) was checked visually making negligible the fraction of misclassified objects. For fainter objects, we found that simulations do not provide reliable estimates of the possible misclassification and therefore we have compared our data with that from deep counts of galaxies and star counts from models of our Galaxy. Both sets turned out to be consistent with our data within ~5% (in the ratio galaxies/total) up to V ~ 24. Finally, we remark that the application of our special procedure to remove large halos improves the photometry of the large galaxies in our sample with respect to the use of blind automatic procedures and increases (~16%) the detection rate of objects projected onto them. Based on observations taken at the Issac Newton Telescope (2.5 m-INT) sited at Roque de los Muchachos (La Palma, Spain), and the MPG/ESO-2.2 m Telescope sited at La Silla (Chile). Appendices are only available in electronic form at http://www.aanda.org Catalog is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/497/667

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.

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

PubMed

Xiao, Cao; Choi, Edward; Sun, Jimeng

2018-06-08

To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoing research and identify open challenges in building deep learning models of EHRs. We searched PubMed and Google Scholar for papers on deep learning studies using EHR data published between January 1, 2010, and January 31, 2018. We summarize them according to these axes: types of analytics tasks, types of deep learning model architectures, special challenges arising from health data and tasks and their potential solutions, as well as evaluation strategies. We surveyed and analyzed multiple aspects of the 98 articles we found and identified the following analytics tasks: disease detection/classification, sequential prediction of clinical events, concept embedding, data augmentation, and EHR data privacy. We then studied how deep architectures were applied to these tasks. We also discussed some special challenges arising from modeling EHR data and reviewed a few popular approaches. Finally, we summarized how performance evaluations were conducted for each task. Despite the early success in using deep learning for health analytics applications, there still exist a number of issues to be addressed. We discuss them in detail including data and label availability, the interpretability and transparency of the model, and ease of deployment.

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.

DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

PubMed

Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

2018-01-01

Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

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.