VizieR Online Data Catalog: z~3-6 protoclusters in the CFHTLS deep fields (Toshikawa+, 2016)

NASA Astrophysics Data System (ADS)

Toshikawa, J.; Kashikawa, N.; Overzier, R.; Malkan, M. A.; Furusawa, H.; Ishikawa, S.; Onoue, M.; Ota, K.; Tanaka, M.; Niino, Y.; Uchiyama, H.

2018-03-01

We made use of publicly available data from the CFHTLS (T0007: Gwyn 2012AJ....143...38G; Hudelot et al. 2012, Cat. II/317), which was obtained with MegaCam mounted at the prime focus of the CFHT. The Deep Fields of the CFHTLS were used in this study, which consist of four independent fields of about 1 deg2 area each (~4 deg2 area in total) observed in the u*, g', r', i', and z' bands. We selected z~3-6 galaxy candidates using the Lyman-break technique (u-, g-, r-, and i-dropout galaxies). We carried out spectroscopic observations using Subaru/FOCAS (Kashikawa et al. 2002PASJ...54..819K), Keck II/DEIMOS (Faber et al. 2003SPIE.4841.1657F), and Gemini-N/GMOS (Hook et al. 2004PASP..116..425H). In these observations, eight protocluster candidates from z~3 to z~6 were observed in total (two at each redshift). All these observations were conducted with Multi-Object Spectroscopy (MOS) mode. (2 data files).

Novel Gemini cationic surfactants as anti-corrosion for X-65 steel dissolution in oilfield produced water under sweet conditions: Combined experimental and computational investigations

NASA Astrophysics Data System (ADS)

Migahed, M. A.; elgendy, Amr.; EL-Rabiei, M. M.; Nady, H.; Zaki, E. G.

2018-05-01

Two new sequences of Gemini di-quaternary ammonium salts were synthesized characterized by FTIR and 1HNMR spectroscopic techniques and evaluated as corrosion inhibitor for X-65 steel dissolution in deep oil wells formation water saturated with CO2. The anti-corrosion performance of these compounds was studied by different electrochemical techniques i.e. (potentiodynamic polarization and AC impedance methods), Surface morphology (SEM and EDX) analysis and quantum chemical calculations. Results showed that the synthesized compounds were of mixed-type inhibitors and the inhibition capability was influenced by the inhibitor dose and the spacer substitution in their structure as indicated by Tafel plots. Surface active parameters were determined from the surface tension profile. The synthesized compounds adsorbed via Langmuir adsorption model with physiochemical adsorption as inferred from the standard free energy (ΔG°ads) values. Surface morphology (SEM and EDX) data for inhibitor (II) shows the development of adsorbed film on steel specimen. Finally, the experimental results were supported by the quantum chemical calculations using DFT theory.

Exploring a Massive Starburst in the Epoch of Reionization

NASA Astrophysics Data System (ADS)

Marrone, Daniel; Aravena, M.; Chapman, S.; De Breuck, C.; Gonzalez, A.; Hezavehe, S.; Litke, K.; Ma, J.; Malkan, M.; Spilker, J.; Stalder, B.; Stark, D.; Strandet, M.; Tang, M.; Vieira, J.; Weiss, A.; Welikala, N.

2016-08-01

We request deep multi-band imaging of a unique dusty galaxy in the Epoch of Reionization (EoR), selected via its millimeter-wavelength dust emission in the 2500-square-degree South Pole Telescope survey. Spectroscopically confirmed to lie at z=6.900, this galaxy has a large dust mass and is likely one of the most rapidly star-forming objects in the EoR. Using Gemini-S, we have identified z-band emission from this object that could be UV continuum emission at z=6.9 or from a foreground lens. Interpretation of this object, and a complete understanding of its meaning for the census of star formation in the EoR, requires that we establish the presence or absence of gravitational lensing. The dust mass observed in this source is also unexpectedly large for its era, and measurements of the assembled stellar population, through the UV-continuum slope and restframe optical color, will help characterize the stellar mass and dust properties in this very early galaxy, the most spectacular galaxy yet discovered by the SPT.

The ionization mechanism of NGC 185: how to fake a Seyfert galaxy?

NASA Astrophysics Data System (ADS)

Martins, L. P.; Lanfranchi, G.; Gonçalves, D. R.; Magrini, L.; Teodorescu, A. M.; Quireza, C.

2012-02-01

NGC 185 is a dwarf spheroidal satellite of the Andromeda galaxy. From mid-1990s onwards it was revealed that dwarf spheroidals often display a varied and in some cases complex star formation history. In an optical survey of bright nearby galaxies, NGC 185 was classified as a Seyfert galaxy based on its emission line ratios. However, although the emission lines in this object formally place it in the category of Seyferts, it is probable that this galaxy does not contain a genuine active nucleus. NGC 185 was not detected in radio surveys either in 6 or 20 cm, or X-ray observations, which means that the Seyfert-like line ratios may be produced by stellar processes. In this work, we try to identify the possible ionization mechanisms for this galaxy. We discussed the possibility of the line emissions being produced by planetary nebulae (PNe), using deep spectroscopy observations obtained with the Gemini Multi-Object Spectrograph - North (GMOS-N), at Gemini. Although the fluxes of the PNe are high enough to explain the integrated spectrum, the line ratios are very far from the values for the Seyfert classification. We then proposed that a mixture of supernova remnants and PNe could be the source of the ionization, and we show that a composition of these two objects do mimic Seyfert-like line ratios. We used chemical evolution models to predict the supernova rates and to support the idea that these supernova remnants should be present in the galaxy. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership.

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.

Human Exploration System Test-Bed for Integration and Advancement (HESTIA) Support of Future NASA Deep-Space Missions

NASA Technical Reports Server (NTRS)

Marmolejo, Jose; Ewert, Michael

2016-01-01

The Engineering Directorate at the NASA - Johnson Space Center is outfitting a 20-Foot diameter hypobaric chamber in Building 7 to support future deep-space Environmental Control & Life Support System (ECLSS) research as part of the Human Exploration System Test-bed for Integration and Advancement (HESTIA) Project. This human-rated chamber is the only NASA facility that has the unique experience, chamber geometry, infrastructure, and support systems capable of conducting this research. The chamber was used to support Gemini, Apollo, and SkyLab Missions. More recently, it was used to conduct 30-, 60-, and 90-day human ECLSS closed-loop testing in the 1990s to support the International Space Station and life support technology development. NASA studies show that both planetary surface and deep-space transit crew habitats will be 3-4 story cylindrical structures driven by human occupancy volumetric needs and launch vehicle constraints. The HESTIA facility offers a 3-story, 20-foot diameter habitat consistent with the studies' recommendations. HESTIA operations follow stringent processes by a certified test team that including human testing. Project management, analysis, design, acquisition, fabrication, assembly and certification of facility build-ups are available to support this research. HESTIA offers close proximity to key stakeholders including astronauts, Human Research Program (who direct space human research for the agency), Mission Operations, Safety & Mission Assurance, and Engineering Directorate. The HESTIA chamber can operate at reduced pressure and elevated oxygen environments including those proposed for deep-space exploration. Data acquisition, power, fluids and other facility resources are available to support a wide range of research. Recently completed HESTIA research consisted of unmanned testing of ECLSS technologies. Eventually, the HESTIA research will include humans for extended durations at reduced pressure and elevated oxygen to demonstrate very high reliability of critical ECLSS and other technologies.

Deep g'r'i'z' GMOS Imaging of the Dwarf Irregular Galaxy Kar 50

NASA Astrophysics Data System (ADS)

Davidge, T. J.

2002-11-01

Images obtained with the Gemini Multi-Object Spectrograph (GMOS) are used to investigate the stellar content and distance of the dwarf irregular galaxy Kar 50. The brightest object is an H II region, and the bright stellar content is dominated by stars with g'-r'<0. The tips of the main sequence and the red giant branch (RGB) are tentatively identified near r'=24.9 and i'=25.5, respectively. The galaxy has a blue integrated color and no significant color gradient, and we conclude that Kar 50 has experienced a recent galaxy-wide episode of star formation. The distance estimated from the brightest blue stars indicates that Kar 50 is behind the M81 group, and this is consistent with the tentative RGB-tip brightness. Kar 50 has a remarkably flat central surface brightness profile, even at wavelengths approaching 1 μm, although there is no evidence of a bar. In the absence of another large star-forming episode, Kar 50 will evolve into a very low surface brightness galaxy. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the Particle Physics and Astronomy Research Council (United Kingdom), the National Research Council of Canada (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNPq (Brazil), and CONICET (Argentina).

Potential Interference from Wireless Water Tank Transmitters at Goldstone

NASA Astrophysics Data System (ADS)

Ho, C.

2008-02-01

The Deep Space Network (DSN) facility in the Goldstone, California, area is considering installation of a new type of wireless transmitter (M2400S) within the facility. The transmitters will be used to monitor the water levels in several water tanks. Then these water-level signals will be transmitted to the nearby DSN facilities using transmitters operating in the UHF band (900-MHz) or S-band (2.4-GHz). This study is to evaluate the interference effects from the transmitters in adjacent DSN receiving stations. First we perform a terrain profile analysis to identify if there is a line of sight between each transmitter and the nearby DSN stations. After taking into account terrain shielding using high-resolution data, total propagation losses are calculated along each path. Then we perform the link analysis for each site to identify if the interference power exceeds the protection threshold of DSN receiving stations. As a result, we find that, because there is no bandpass filter installed in the transmitter system, interference power from the new transmitter at S-band will greatly exceed the protection criteria of broadband radio astronomy services (RAS) at S-band, such as Deep Space Station (DSS) 12 and DSS 28, by about 50 dB. The interference may also cause problems on all deep-space research stations at S-band, such as the Mars, Apollo, Venus, and Gemini sites. Without a sharp bandpass filter to suppress the out-of-band emissions in the frequency bands that the DSN station and RAS use, the author recommends not installing this type of transmitter within the Goldstone DSN facility area.

The Search for Wolf-Rayet Stars in IC10

NASA Astrophysics Data System (ADS)

Tehrani, Katie; Crowther, Paul; Archer, Isabelle

2017-11-01

We present a deep imaging and spectroscopic survey of the Local Group starburst galaxy IC10 using Gemini North/GMOS to unveil the global Wolf-Rayet population. It has previously been suggested that for IC10 to follow the WC/WN versus metallicity dependence seen in other Local Group galaxies, a large WN population must remain undiscovered. Our search revealed 3 new WN stars, and 5 candidates awaiting confirmation, providing little evidence to support this claim. We also compute an updated nebular derived metallicity of log(O/H)+12=8.40 +/- 0.04 for the galaxy using the direct method. Inspection of IC10 WR average line luminosities show these stars are more similar to their LMC, rather than SMC counterparts.

The Optical Counterpart of M101 ULX-1

NASA Technical Reports Server (NTRS)

Kuntz, K. D.; Gruendi, Robert A.; Chu, You-Hua; Chen, C.-H. Rosie; Still, Martin; Mukai, Koji; Musuotzky, Richard F.

2004-01-01

We have identified the optical counterpart of the Ultra-Luminous X-ray source Ml0l ULX-1 (CX- OKM101 J140332.74+542102), by comparing HST ACS images with Chandra ACIS-S images. The optical counterpart has V= 23.75 and colours consistent with those for a mid-B supergiant. Archival WFPC2 observations show that the source brightness is constant to within approximately 0.1 mag. The physical association of this source with the ULX is confirmed by Gemini GMOS spectroscopic observations which show spatially unresolved He II lambda4686 and He I lambda5876 emission. These results suggest that M10l ULX-1 is a HMXB but deep spectroscopic monitoring observations are needed to determine the detailed properties of this system.

Identification of old tidal dwarfs near early-type galaxies from deep imaging and H I observations

NASA Astrophysics Data System (ADS)

Duc, Pierre-Alain; Paudel, Sanjaya; McDermid, Richard M.; Cuillandre, Jean-Charles; Serra, Paolo; Bournaud, Frédéric; Cappellari, Michele; Emsellem, Eric

2014-05-01

It has recently been proposed that the dwarf spheroidal galaxies located in the Local Group discs of satellites (DoSs) may be tidal dwarf galaxies (TDGs) born in a major merger at least 5 Gyr ago. Whether TDGs can live that long is still poorly constrained by observations. As part of deep optical and H I surveys with the Canada-France-Hawaii Telescope (CFHT) MegaCam camera and Westerbork Synthesis Radio Telescope made within the ATLAS3D project, and follow-up spectroscopic observations with the Gemini-North telescope, we have discovered old TDG candidates around several early-type galaxies. At least one of them has an oxygen abundance close to solar, as expected for a tidal origin. This confirmed pre-enriched object is located within the gigantic, but very low surface brightness, tidal tail that emanates from the elliptical galaxy, NGC 5557. An age of 4 Gyr estimated from its SED fitting makes it the oldest securely identified TDG ever found so far. We investigated the structural and gaseous properties of the TDG and of a companion located in the same collisional debris, and thus most likely of tidal origin as well. Despite several Gyr of evolution close to their parent galaxies, they kept a large gas reservoir. Their central surface brightness is low and their effective radius much larger than that of typical dwarf galaxies of the same mass. This possibly provides us with criteria to identify tidal objects which can be more easily checked than the traditional ones requiring deep spectroscopic observations. In view of the above, we discuss the survival time of TDGs and question the tidal origin of the DoSs.

Linking Deep Astrometric Standards to the ICRF

NASA Astrophysics Data System (ADS)

Frey, S.; Platais, I.; Fey, A. L.

2007-07-01

The next-generation large aperature and large field-of-view telescopes will address fundamantal questions of astrophysica and cosmology such as the nature of dark matter and dark energy. For a variety of applications, the CCD mosaic detectors in the focal plane arrays require astronomic calibrationat the milli-arcsecond (mas) level. The existing optical reference frames are insufficient to support such calibrations. To address this problem, deep optical astronomic fields are being established near the Galactic plane. In order to achiev a 5-10-mas or better positional accuracyfor the Deepp Astrometric Standards (DAS), and to obtain bsolute stellar proper motions for the study of Galactic structure, it is crucial to link these fields to the International Celestial Reference Frame (ICRF). To this end, we selected 15 candidate compact extragalactic radio sources in the Gemini-Orion-Taurus (GOT) field. These sources were observed with the European VLBI Network (EVN) at 5 GHz in phase-reference mode. The bright compact calibrator source J0603+2159 and seven other sources were detected and imaged at the angular resolution of -1.5-8 mas. Relative astrometric positions were derived for these sources at a milli-arcsecond accuracy level. The detection of the optical counterparts of these extragalactic radio sources will allow us to establish a direct link to the ICRF locally in the GOT field.

Deep Broad-Band Infrared Nulling Using A Single-Mode Fiber Beam Combiner and Baseline Rotation

NASA Technical Reports Server (NTRS)

Mennesson, Bertrand; Haguenauer, P.; Serabyn, E.; Liewer, K.

2006-01-01

The basic advantage of single-mode fibers for deep nulling applications resides in their spatial filtering ability, and has now long been known. However, and as suggested more recently, a single-mode fiber can also be used for direct coherent recombination of spatially separated beams, i.e. in a 'multi-axial' nulling scheme. After the first successful demonstration of deep (<2e-6) visible LASER nulls using this technique (Haguenauer & Serabyn, Applied Optics 2006), we decided to work on an infrared extension for ground based astronomical observations, e.g. using two or more off-axis sub-apertures of a large ground based telescope. In preparation for such a system, we built and tested a laboratory infrared fiber nuller working in a wavelength regime where atmospheric turbulence can be efficiently corrected, over a pass band (approx.1.5 to 1.8 micron) broad enough to provide reasonable sensitivity. In addition, since no snapshot images are readily accessible with a (single) fiber nuller, we also tested baseline rotation as an approach to detect off-axis companions while keeping a central null. This modulation technique is identical to the baseline rotation envisioned for the TPF-I space mission. Within this context, we report here on early laboratory results showing deep stable broad-band dual polarization infrared nulls <5e-4 (currently limited by detector noise), and visible LASER nulls better than 3e-4 over a 360 degree rotation of the baseline. While further work will take place in the laboratory to achieve deeper stable broad-band nulls and test off-axis sources detection through rotation, the emphasis will be put on bringing such a system to a telescope as soon as possible. Detection capability at the 500:1 contrast ratio in the K band (2.2 microns) seem readily accessible within 50-100 mas of the optical axis, even with a first generation system mounted on a >5m AO equipped telescope such as the Palomar Hale 200 inch, the Keck, Subaru or Gemini telescopes.

Spectroscopy of Giant Arcs Behind the Strongest Lenses in the Universe

NASA Astrophysics Data System (ADS)

Hennawi, Joseph F.; Gladders, Michael; Oguri, Masamune; Koester, Benjamin; Bayliss, Matt; Dahle, Hakon; Natarajan, Priya

2009-02-01

We have conducted a deep ((mu)_g ≲ 24) imaging survey using the WIYN 4-m telescope, the UH 88-inch telescope, and the 2.5m Nordic Optical Telescope (NOT) to search for giant arcs behind the richest clusters identified in the Gpc^3 volume of the SDSS. By imaging nearly 500 massive clusters, this ongoing survey has uncovered some of the most dramatic examples of gravitational lensing ever discovered, similar to `poster-children' like Abell 1689 and CL0024+1654. We propose to use GMOS on Gemini-North and the Blue Channel Spectrograph on the MMT to determine arc redshifts in these new lenses. When combined with our GMOS data from a similar program in 2008A, this proposal will result in a sample of 60 gravitationally lensed galaxies behind ~ 25 clusters. These arc redshifts pinpoint the mass of dark matter interior to the Einstein radius in the cluster core (R < 200 kpc; comoving). The larger scale (R ~ 1-5 Mpc) weak lensing shear has been measured for more than half of our targets from deep imaging at NOT, WIYN, Subaru, and using archival data from HST. GMOS arc redshifts combined with weak and strong lensing will allow us to measure the density profile of dark matter halos on scales 200 kpc < R < 5 Mpc for the statistical sample of lensing clusters, providing a powerful test of the (Lambda)CDM paradigm.

Revealing the nebular properties and Wolf-Rayet population of IC10 with Gemini/GMOS

NASA Astrophysics Data System (ADS)

Tehrani, Katie; Crowther, Paul A.; Archer, I.

2017-12-01

We present a deep imaging and spectroscopic survey of the Local Group irregular galaxy IC10 using Gemini North and GMOS to unveil its global Wolf-Rayet (WR) population. We obtain a star formation rate (SFR) of 0.045 ± 0.023 M⊙ yr-1, for IC10 from the nebular H α luminosity, which is comparable to the Small Magellanic Cloud. We also present a revised nebular oxygen abundance of log(O/H) + 12 = 8.40 ± 0.04, comparable to the LMC. It has previously been suggested that for IC10 to follow the WR subtype-metallicity dependance seen in other Local Group galaxies, a large WN population awaits discovery. Our search revealed three new WN stars, and six candidates awaiting confirmation, providing little evidence to support this claim. The new global WR star total of 29 stars is consistent with the Large Magellanic Cloud population when scaled to the reduced SFR of IC10. For spectroscopically confirmed WR stars, the WC/WN ratio is lowered to 1.0; however, including all potential candidates, and assuming those unconfirmed to be WN stars, would reduce the ratio to ∼0.7. We attribute the high WC/WN ratio to the high star formation surface density of IC10 relative to the Magellanic Clouds, which enhances the frequency of high-mass stars capable of producing WC stars.

VizieR Online Data Catalog: PTF obs. of a precursor to SNHunt 275 2015 May event (Ofek+, 2016)

NASA Astrophysics Data System (ADS)

Ofek, E. O.; Cenko, S. B.; Shaviv, N. J.; Duggan, G.; Strotjohann, N.-L.; Rubin, A.; Kulkarni, S. R.; Gal-Yam, A.; Sullivan, M.; Cao, Y.; Nugent, P. E.; Kasliwal, M. M.; Sollerman, J.; Fransson, C.; Filippenko, A. V.; Perley, D. A.; Yaron, O.; Laher, R.

2016-08-01

The Palomar Transient Factory (PTF and iPTF; Law et al. 2009PASP..121.1395L; Rau et al. 2009PASP..121.1334R), using the 48inch Oschin Schmidt telescope, observed the field of SNHunt 275 starting in 2009 March. On 2013 December 12, PTF detected a new source at the location of the event, and the transient was named PTF 13efv (see Figure 1). Three images obtained between 2014 January 23 and April 25 were used as a reference. The PTF R-band photometry is listed in Table1. Most of the optical spectra were obtained with the Low Resolution Imaging Spectrometer (LRIS) on the Keck I 10m telescope, although a few spectra were also taken with the DEep Imaging Multi-Object Spectrograph (DEIMOS) on the Keck II 10m telescope, the Kast spectrograph on the Shane 3m telescope at Lick Observatory, and the Gemini-North Multiobject Spectrograph (GMOS) on the 8m Gemini-N telescope. The first spectrum was obtained during the 2013 December outburst. We used the Swift/UVOT observations of SNHunt 275, since 2008, to construct the bolometric light curve of the transient. The log of Swift-XRT observations, along with the source and background X-ray counts in the individual observations, is given in Table 5. (3 data files).

The Swift GRB Host Galaxy Legacy Survey

NASA Astrophysics Data System (ADS)

Perley, Daniel A.

2015-01-01

I introduce the Swift Host Galaxy Legacy Survey (SHOALS), a comprehensive multiwavelength program to characterize the demographics of the GRB host population across its entire redshift range. Using unbiased selection criteria we have designated a subset of 130 Swift gamma-ray bursts which are now being targeted with intensive observational follow-up. Deep Spitzer imaging of every field has already been obtained and analyzed, with major programs ongoing at Keck, GTC, and Gemini to obtain complementary optical/NIR photometry to enable full SED modeling and derivation of fundamental physical parameters such as mass, extinction, and star-formation rate. Using these data I will present an unbiased measurement of the GRB host-galaxy luminosity and mass functions and their evolution with redshift between z=0 and z=5, compare GRB hosts to other star-forming galaxy populations, and discuss implications for the nature of the GRB progenitor and the ability of GRBs to probe cosmic star-formation.

The first optical spectra of Wolf-Rayet stars in M101 revealed with Gemini/GMOS

NASA Astrophysics Data System (ADS)

Pledger, J. L.; Shara, M. M.; Wilde, M.; Crowther, P. A.; Long, K. S.; Zurek, D.; Moffat, A. F. J.

2018-01-01

Deep narrow-band Hubble Space Telescope (HST) imaging of the iconic spiral galaxy M101 has revealed over a thousand new Wolf-Rayet (WR) candidates. We report spectrographic confirmation of 10 He II-emission line sources hosting 15 WR stars. We find WR stars present at both sub- and super-solar metallicities with WC stars favouring more metal-rich regions compared to WN stars. We investigate the association of WR stars with H II regions using archival HST imaging and conclude that the majority of WR stars are in or associated with H II regions. Of the 10 emission lines sources, only one appears to be unassociated with a star-forming region. Our spectroscopic survey provides confidence that our narrow-band photometric candidates are in fact bona fide WR stars, which will allow us to characterize the progenitors of any core-collapse supernovae that erupt in the future in M101.

Cool White Dwarfs Found in the UKIRT Infrared Deep Sky Survey

NASA Astrophysics Data System (ADS)

Leggett, S. K.; Lodieu, N.; Tremblay, P.-E.; Bergeron, P.; Nitta, A.

2011-07-01

We present the results of a search for cool white dwarfs in the United Kingdom InfraRed Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). The UKIDSS LAS photometry was paired with the Sloan Digital Sky Survey to identify cool hydrogen-rich white dwarf candidates by their neutral optical colors and blue near-infrared colors, as well as faint reduced proper motion magnitudes. Optical spectroscopy was obtained at Gemini Observatory and showed the majority of the candidates to be newly identified cool degenerates, with a small number of G- to K-type (sub)dwarf contaminants. Our initial search of 280 deg2 of sky resulted in seven new white dwarfs with effective temperature T eff ≈ 6000 K. The current follow-up of 1400 deg2 of sky has produced 13 new white dwarfs. Model fits to the photometry show that seven of the newly identified white dwarfs have 4120 K <=T eff <= 4480 K, and cooling ages between 7.3 Gyr and 8.7 Gyr; they have 40 km s-1 <= v tan <= 85 km s-1 and are likely to be thick disk 10-11 Gyr-old objects. The other half of the sample has 4610 K <=T eff <= 5260 K, cooling ages between 4.3 Gyr and 6.9 Gyr, and 60 km s-1 <= v tan <= 100 km s-1. These are either thin disk remnants with unusually high velocities, or lower-mass remnants of thick disk or halo late-F or G stars.

SPLAT: Using Spectral Indices to Identify and Characterize Ultracool Stars, Brown Dwarfs and Exoplanets in Deep Surveys and as Companions to Nearby Stars

NASA Astrophysics Data System (ADS)

Aganze, Christian; Burgasser, Adam J.; Martin, Eduardo; Konopacky, Quinn; Masters, Daniel C.

2016-06-01

The majority of ultracool dwarf stars and brown dwarfs currently known were identified in wide-field red optical and infrared surveys, enabling measures of the local, typically isolated, population in a relatively shallow (<100 pc radius) volume. Constraining the properties of the wider Galactic population (scale height, radial distribution, Population II sources), and close brown dwarf and exoplanet companions to nearby stars, requires specialized instrumentation, such as high-contrast, coronagraphic spectrometers (e.g., Gemini/GPI, VLT/Sphere, Project 1640); and deep spectral surveys (e.g., HST/WFC3 parallel fields, Euclid). We present a set of quantitative methodologies to identify and robustly characterize sources for these specific populations, based on templates and tools developed as part of the SpeX Prism Library Analysis Toolkit. In particular, we define and characterize specifically-tuned sets spectral indices that optimize selection of cool dwarfs and distinguish rare populations (subdwarfs, young planetary-mass objects) based on low-resolution, limited-wavelength-coverage spectral data; and present a template-matching classification method for these instruments. We apply these techniques to HST/WFC3 parallel fields data in the WISPS and HST-3D programs, where our spectral index set allows high completeness and low contamination for searches of late M, L and T dwarfs to distances out to ~3 kpc.The material presented here is based on work supported by the National Aeronautics and Space Administration under Grant No. NNX15AI75G.

The Subaru/XMM-Newton Deep Survey (SXDS). V. Optically Faint Variable Object Survey

NASA Astrophysics Data System (ADS)

Morokuma, Tomoki; Doi, Mamoru; Yasuda, Naoki; Akiyama, Masayuki; Sekiguchi, Kazuhiro; Furusawa, Hisanori; Ueda, Yoshihiro; Totani, Tomonori; Oda, Takeshi; Nagao, Tohru; Kashikawa, Nobunari; Murayama, Takashi; Ouchi, Masami; Watson, Mike G.; Richmond, Michael W.; Lidman, Christopher; Perlmutter, Saul; Spadafora, Anthony L.; Aldering, Greg; Wang, Lifan; Hook, Isobel M.; Knop, Rob A.

2008-03-01

We present our survey for optically faint variable objects using multiepoch (8-10 epochs over 2-4 years) i'-band imaging data obtained with Subaru Suprime-Cam over 0.918 deg2 in the Subaru/XMM-Newton Deep Field (SXDF). We found 1040 optically variable objects by image subtraction for all the combinations of images at different epochs. This is the first statistical sample of variable objects at depths achieved with 8-10 m class telescopes or the Hubble Space Telescope. The detection limit for variable components is i'vari ~ 25.5 mag. These variable objects were classified into variable stars, supernovae (SNe), and active galactic nuclei (AGNs), based on the optical morphologies, magnitudes, colors, and optical-mid-infrared colors of the host objects, spatial offsets of variable components from the host objects, and light curves. Detection completeness was examined by simulating light curves for periodic and irregular variability. We detected optical variability for 36% +/- 2% (51% +/- 3% for a bright sample with i' < 24.4 mag) of X-ray sources in the field. Number densities of variable objects as functions of time intervals Δ t and variable component magnitudes i'vari are obtained. Number densities of variable stars, SNe, and AGNs are 120, 489, and 579 objects deg-2, respectively. Bimodal distributions of variable stars in the color-magnitude diagrams indicate that the variable star sample consists of bright (V ~ 22 mag) blue variable stars of the halo population and faint (V ~ 23.5 mag) red variable stars of the disk population. There are a few candidates of RR Lyrae providing a possible number density of ~10-2 kpc-3 at a distance of >150 kpc from the Galactic center. Based in part on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. Based on observations (program GN-2002B-Q-30) obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (US), the Particle Physics and Astronomy Research Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNPq (Brazil), and CONICET (Argentina).

The T dwarf population in the UKIDSS LAS .

NASA Astrophysics Data System (ADS)

Cardoso, C. V.; Burningham, B.; Smith, L.; Smart, R.; Pinfield, D.; Magazzù, A.; Ghinassi, F.; Lattanzi, M.

We present the most recent results from the UKIDSS Large Area Survey (LAS) census and follow up of new T brown dwarfs in the local field. The new brown dwarf candidates are identified using optical and infrared survey photometry (UKIDSS and SDSS) and followed up with narrow band methane photometry (TNG) and spectroscopy (Gemini and Subaru) to confirm their brown dwarf nature. Employing this procedure we have discovered several dozens of new T brown dwarfs in the field. Using methane differential photometry as a proxy for spectral type for T brown dwarfs has proved to be a very efficient technique. This method can be useful in the future to reliably identify brown dwarfs in deep surveys that produce large samples of faint targets where spectroscopy is not feasible for all candidates. With this statistical robust sample of the mid and late T brown dwarf field population we were also able to address the discrepancies between the observed field space density and the expected values given the most accepted forms of the IMF of young clusters.

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

The Swift GRB Host Galaxy Legacy Survey

NASA Astrophysics Data System (ADS)

Perley, Daniel

2015-08-01

I will describe the Swift Host Galaxy Legacy Survey (SHOALS), a comprehensive multiwavelength program to characterize the demographics of the GRB host population and its redshift evolution from z=0 to z=7. Using unbiased selection criteria we have designated a subset of 119 Swift gamma-ray bursts which are now being targeted with intensive observational follow-up. Deep Spitzer imaging of every field has already been obtained and analyzed, with major programs ongoing at Keck, GTC, Gemini, VLT, and Magellan to obtain complementary optical/NIR photometry and spectroscopy to enable full SED modeling and derivation of fundamental physical parameters such as mass, extinction, and star-formation rate. Using these data I will present an unbiased measurement of the GRB host-galaxy luminosity and mass distributions and their evolution with redshift, compare GRB hosts to other star-forming galaxy populations, and discuss implications for the nature of the GRB progenitor and the ability of GRBs to serve as tools for measuring and studying cosmic star-formation in the distant universe.

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.

Deep space communication - A one billion mile noisy channel

NASA Technical Reports Server (NTRS)

Smith, J. G.

1982-01-01

Deep space exploration is concerned with the study of natural phenomena in the solar system with the aid of measurements made at spacecraft on deep space missions. Deep space communication refers to communication between earth and spacecraft in deep space. The Deep Space Network is an earth-based facility employed for deep space communication. It includes a network of large tracking antennas located at various positions around the earth. The goals and achievements of deep space exploration over the past 20 years are discussed along with the broad functional requirements of deep space missions. Attention is given to the differences in space loss between communication satellites and deep space vehicles, effects of the long round-trip light time on spacecraft autonomy, requirements for the use of massive nuclear power plants on spacecraft at large distances from the sun, and the kinds of scientific return provided by a deep space mission. Problems concerning a deep space link of one billion miles are also explored.

Development of deep eutectic solvents applied in extraction and separation.

PubMed

Li, Xiaoxia; Row, Kyung Ho

2016-09-01

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

Deep Water Cooling | Climate Neutral Research Campuses | NREL

Science.gov Websites

the Cornell website. Additional examples of research campus geothermal cooling projects include Deep Water Cooling Deep Water Cooling Research campuses that are located near a deep lake or deep plan for your research campus. Considerations Sample Project Related Links Deep water cooling involves

Is Multitask Deep Learning Practical for Pharma?

PubMed

Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

2017-08-28

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

Decadal trends in deep ocean salinity and regional effects on steric sea level

NASA Astrophysics Data System (ADS)

Purkey, S. G.; Llovel, W.

2017-12-01

We present deep (below 2000 m) and abyssal (below 4000 m) global ocean salinity trends from the 1990s through the 2010s and assess the role of deep salinity in local and global sea level budgets. Deep salinity trends are assessed using all deep basins with available full-depth, high-quality hydrographic section data that have been occupied two or more times since the 1980s through either the World Ocean Circulation Experiment (WOCE) Hydrographic Program or the Global Ship-Based Hydrographic Investigations Program (GO-SHIP). All salinity data is calibrated to standard seawater and any intercruise offsets applied. While the global mean deep halosteric contribution to sea level rise is close to zero (-0.017 +/- 0.023 mm/yr below 4000 m), there is a large regional variability with the southern deep basins becoming fresher and northern deep basins becoming more saline. This meridional gradient in the deep salinity trend reflects different mechanisms driving the deep salinity variability. The deep Southern Ocean is freshening owing to a recent increased flux of freshwater to the deep ocean. Outside of the Southern Ocean, the deep salinity and temperature changes are tied to isopycnal heave associated with a falling of deep isopycnals in recent decades. Therefore, regions of the ocean with a deep salinity minimum are experiencing both a halosteric contraction with a thermosteric expansion. While the thermosteric expansion is larger in most cases, in some regions the halosteric compensates for as much as 50% of the deep thermal expansion, making a significant contribution to local sea level rise budgets.

A tracer study of the deep water renewal in the European polar seas

NASA Astrophysics Data System (ADS)

Heinze, Ch.; Schlosser, P.; Koltermann, K. P.; Meincke, J.

1990-09-01

A study of the deep water renewal in the European polar seas (Norwegian Sea, Greenland Sea and Eurasian Basin) based on the distribution of tritium ( 3H), 3He, chlorofluoromethane (F-11 = CCL 3F), salinity and potential temperature is presented. Four different versions of a kinematic box model calibrated with the tracer data yield production rates and turnover times due to deep convection for Greenland Sea Deep Water (0.47-0.59 Sv, 27-34 y) and Eurasian Basin Deep Water (0.97-1.07 Sv, 83-92 y). Model calculations with different deep advective flow patterns (exchange at equal rates between each of the deep water masses or an internal circuit Eurasian Basin-Greenland Sea-Norwegian Sea-Eurasian Basin) give estimates of the deep horizontal transports, resulting in a turnover time of 13-16 years for Norwegian Sea Deep Water. The total turnover times (convection and deep advection) of the Greenland Sea and the Eurasian Basin are estimated to about 10 and 50 years, respectively. Mean hydrographic characteristics of the source water for Greenland Sea Deep Water and Eurasian Basin Deep Water are estimated from minimization of the deviations between modelled and observed hydrographic deep water values. The fractions of surface waters and intermediate waters making up the deep water of the Greenland Sea are estimated to about 80 and 20%, respectively.

76 FR 66078 - Notice of Industry Workshop on Technical and Regulatory Challenges in Deep and Ultra-Deep Outer...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

...-0087] Notice of Industry Workshop on Technical and Regulatory Challenges in Deep and Ultra-Deep Outer... and gas exploration and production in deep and ultra-deep OCS waters. Through this workshop, BSEE will... structured venue for consultation among offshore deepwater oil and gas industry and regulatory experts in...

Do deep convolutional neural networks really need to be deep when applied for remote scene classification?

NASA Astrophysics Data System (ADS)

Luo, Chang; Wang, Jie; Feng, Gang; Xu, Suhui; Wang, Shiqiang

2017-10-01

Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, for remote scene classification, there are not sufficient images to train a very deep CNN from scratch. From two viewpoints of generalization power, we propose two promising kinds of deep CNNs for remote scenes and try to find whether deep CNNs need to be deep for remote scene classification. First, we transfer successful pretrained deep CNNs to remote scenes based on the theory that depth of CNNs brings the generalization power by learning available hypothesis for finite data samples. Second, according to the opposite viewpoint that generalization power of deep CNNs comes from massive memorization and shallow CNNs with enough neural nodes have perfect finite sample expressivity, we design a lightweight deep CNN (LDCNN) for remote scene classification. With five well-known pretrained deep CNNs, experimental results on two independent remote-sensing datasets demonstrate that transferred deep CNNs can achieve state-of-the-art results in an unsupervised setting. However, because of its shallow architecture, LDCNN cannot obtain satisfactory performance, regardless of whether in an unsupervised, semisupervised, or supervised setting. CNNs really need depth to obtain general features for remote scenes. This paper also provides baseline for applying deep CNNs to other remote sensing tasks.

Host Galaxies of Luminous Type 2 Quasars at z ~ 0.5

NASA Astrophysics Data System (ADS)

Liu, Xin; Zakamska, Nadia L.; Greene, Jenny E.; Strauss, Michael A.; Krolik, Julian H.; Heckman, Timothy M.

2009-09-01

We present deep Gemini GMOS optical spectroscopy of nine luminous quasars at redshifts z ~ 0.5, drawn from the Sloan Digital Sky Survey type 2 quasar sample. Our targets were selected to have high intrinsic luminosities (MV < -26 mag) as indicated by the [O III] λ5007 Å emission-line luminosity (L [O III]). Our sample has a median black hole mass of ~108.8 M sun inferred assuming the local M BH-σ* relation and a median Eddington ratio of ~0.7, using stellar velocity dispersions σ* measured from the G band. We estimate the contamination of the stellar continuum from scattered quasar light based on the strength of broad Hβ, and provide an empirical calibration of the contamination as a function of L [O III]; the scattered-light fraction is ~30% of L 5100 for objects with L [O III] = 109.5 L sun. Population synthesis indicates that young poststarburst populations (<0.1 Gyr) are prevalent in luminous type 2 quasars, in addition to a relatively old population (>1 Gyr) which dominates the stellar mass. Broad emission complexes around He II λ4686 Å with luminosities up to 108.3 L sun are unambiguously detected in three out of the nine targets, indicative of Wolf-Rayet (WR) populations. Population synthesis shows that ~5 Myr poststarburst populations contribute substantially to the luminosities (>50% of L 5100) of all three objects with WR detections. We find two objects with double cores and four with close companions. Our results may suggest that luminous type 2 quasars trace an early stage of galaxy interaction, perhaps responsible for both the quasar and the starburst activity. Based, in part, on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil), and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).

Hyperactivity and Dust Composition of Comet 103P/Hartley 2 During the EPOXI Encounter

NASA Astrophysics Data System (ADS)

Harker, David E.; Woodward, Charles E.; Kelley, Michael S. P.; Wooden, Diane H.

2018-05-01

Short-period comet 103P/Hartley 2 (103P) was the flyby target of the Deep Impact eXtended Investigation on 2010 November 4 UT. This comet has a small hyperactive nucleus, i.e., it has a high water production rate for its surface area. The underlying cause of the hyperactivity is unknown; the relative abundances of volatiles in the coma of 103P are not unusual. However, the dust properties of this comet have not been fully explored. We present four epochs of mid-infrared spectra and images of comet 103P observed from Gemini-South +T-ReCS on 2010 November 5, 7, 21 and December 13 UT, near and after the spacecraft encounter. Comet 103P exhibited a weak 10 μm emission feature ≃1.14 ± 0.01 above the underlying local 10 μm continuum. Thermal dust grain modeling of the spectra shows the grain composition (mineralogy) was dominated by amorphous carbon and amorphous pyroxene with evidence for Mg-rich crystalline olivine. The grain size has a peak grain radius range of a peak ∼ 0.5–0.9 μm. On average, the crystalline silicate mass fraction is ≃0.24, fairly typical of other short-period comets. In contrast, the silicate-to-carbon ratio of ≃0.48–0.64 is lower compared to other short-period comets, which indicates that the flux measured in the 10 μm region of 103P was dominated by amorphous carbon grains. We conclude that the hyperactivity in comet 103P is not revealing dust properties similar to the small grains seen with the Deep Impact experiment on comet 9P/Tempel 1 or from comet C/1995 O1 (Hale–Bopp).

White Dwarfs in the UKIRT Infrared Deep Sky Survey Data Release 9

NASA Astrophysics Data System (ADS)

Tremblay, P.-E.; Leggett, S. K.; Lodieu, N.; Freytag, B.; Bergeron, P.; Kalirai, J. S.; Ludwig, H.-G.

2014-06-01

We have identified 8 to 10 new cool white dwarfs from the Large Area Survey (LAS) Data Release 9 of the United Kingdom InfraRed Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS). The data set was paired with the Sloan Digital Sky Survey to obtain proper motions and a broad ugrizYJHK wavelength coverage. Optical spectroscopic observations were secured at Gemini Observatory and confirm the degenerate status for eight of our targets. The final sample includes two additional white dwarf candidates with no spectroscopic observations. We rely on improved one-dimensional model atmospheres and new multi-dimensional simulations with CO5BOLD to review the stellar parameters of the published LAS white dwarf sample along with our additional discoveries. Most of the new objects possess very cool atmospheres with effective temperatures below 5000 K, including two pure-hydrogen remnants with a cooling age between 8.5 and 9.0 Gyr, and tangential velocities in the range 40 km s-1 <=v tan <= 60 km s-1. They are likely thick disk 10-11 Gyr old objects. In addition, we find a resolved double degenerate system with v tan ~ 155 km s-1 and a cooling age between 3.0 and 5.0 Gyr. These white dwarfs could be disk remnants with a very high velocity or former halo G stars. We also compare the LAS sample with earlier studies of very cool degenerates and observe a similar deficit of helium-dominated atmospheres in the range 5000 < T eff (K) < 6000. We review the possible explanations for the spectral evolution from helium-dominated toward hydrogen-rich atmospheres at low temperatures.

Deep thermal infrared imaging of HR 8799 bcde: new atmospheric constraints and limits on a fifth planet

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

Currie, Thayne; Cloutier, Ryan; Jayawardhana, Ray

2014-11-10

We present new L' (3.8 μm) and Brα (4.05 μm) data and reprocessed archival L' data for the young, planet-hosting star HR 8799 obtained with Keck/NIRC2, VLT/NaCo, and Subaru/IRCS. We detect all four HR 8799 planets in each data set at a moderate to high signal-to-noise ratio (S/N ≳ 6-15). We fail to identify a fifth planet, 'HR 8799 f', at r < 15 AU at a 5σ confidence level: one suggestive, marginally significant residual at 0.''2 is most likely a point-spread function artifact. Assuming companion ages of 30 Myr and the Baraffe planet cooling models, we rule out anmore » HR 8799 f with a mass of 5 M{sub J} (7 M{sub J} ), 7 M{sub J} (10 M{sub J} ), or 12 M{sub J} (13 M{sub J} ) at r {sub proj} ∼ 12 AU, 9 AU, and 5 AU, respectively. All four HR 8799 planets have red early T dwarf-like L' – [4.05] colors, suggesting that their spectral energy distributions peak in between the L' and M' broadband filters. We find no statistically significant difference in HR 8799 cde's color. Atmosphere models assuming thick, patchy clouds appear to better match HR 8799 bcde's photometry than models assuming a uniform cloud layer. While non-equilibrium carbon chemistry is required to explain HR 8799 b and c's photometry/spectra, evidence for it from HR 8799 d and e's photometry is weaker. Future, deep-IR spectroscopy/spectrophotometry with the Gemini Planet Imager, SCExAO/CHARIS, and other facilities may clarify whether the planets are chemically similar or heterogeneous.« less

30 CFR 203.1 - What is MMS's authority to grant royalty relief?

Code of Federal Regulations, 2010 CFR

2010-07-01

... (water less than 400 meters deep) and you produce from an ultra-deep well (top of the perforated interval... less than 400 meters deep and you produce from a deep well (top of the perforated interval is at least... from any lease if: (1) Your lease is in deep water (water at least 200 meters deep); (2) Your lease is...

[Soil organic carbon mineralization of Black Locust forest in the deep soil layer of the hilly region of the Loess Plateau, China].

PubMed

Ma, Xin-Xin; Xu, Ming-Xiang; Yang, Kai

2012-11-01

The deep soil layer (below 100 cm) stores considerable soil organic carbon (SOC). We can reveal its stability and provide the basis for certification of the deep soil carbon sinks by studying the SOC mineralization in the deep soil layer. With the shallow soil layer (0-100 cm) as control, the SOC mineralization under the condition (temperature 15 degrees C, the soil water content 8%) of Black Locust forest in the deep soil layer (100-400 cm) of the hilly region of the Loess Plateau was studied. The results showed that: (1) There was a downward trend in the total SOC mineralization with the increase of soil depth. The total SOC mineralization in the sub-deep soil (100-200 cm) and deep soil (200-400 cm) were equivalent to approximately 88.1% and 67.8% of that in the shallow layer (0-100 cm). (2) Throughout the carbon mineralization process, the same as the shallow soil, the sub-deep and deep soil can be divided into 3 stages. In the rapid decomposition phase, the ratio of the mineralization or organic carbon to the total mineralization in the sub-deep and deep layer (0-10 d) was approximately 50% of that in the shallow layer (0-17 d). In the slow decomposition phase, the ratio of organic carbon mineralization to total mineralization in the sub-deep, deep layer (11-45 d) was 150% of that in the shallow layer (18-45 d). There was no significant difference in this ratio among these three layers (46-62 d) in the relatively stable stage. (3) There was no significant difference (P > 0.05) in the mineralization rate of SOC among the shallow, sub-deep, deep layers. The stability of SOC in the deep soil layer (100-400 cm) was similar to that in the shallow soil layer and the SOC in the deep soil layer was also involved in the global carbon cycle. The change of SOC in the deep soil layer should be taken into account when estimating the effects of soil carbon sequestration in the Hilly Region of the Loess Plateau, China.

How to study deep roots—and why it matters

PubMed Central

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

2013-01-01

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

DeepBase: annotation and discovery of microRNAs and other noncoding RNAs from deep-sequencing data.

PubMed

Yang, Jian-Hua; Qu, Liang-Hu

2012-01-01

Recent advances in high-throughput deep-sequencing technology have produced large numbers of short and long RNA sequences and enabled the detection and profiling of known and novel microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) at unprecedented sensitivity and depth. In this chapter, we describe the use of deepBase, a database that we have developed to integrate all public deep-sequencing data and to facilitate the comprehensive annotation and discovery of miRNAs and other ncRNAs from these data. deepBase provides an integrative, interactive, and versatile web graphical interface to evaluate miRBase-annotated miRNA genes and other known ncRNAs, explores the expression patterns of miRNAs and other ncRNAs, and discovers novel miRNAs and other ncRNAs from deep-sequencing data. deepBase also provides a deepView genome browser to comparatively analyze these data at multiple levels. deepBase is available at http://deepbase.sysu.edu.cn/.

30 CFR 203.43 - To which production do I apply the RSV earned from qualified deep wells or qualified phase 1...

Code of Federal Regulations, 2010 CFR

2010-07-01

... in water between 200 and 400 meters deep, you begin drilling an original deep well with a perforated... 200 meters deep; (ii) May 18, 2007, for an RSV earned by a qualified deep well on a lease that is located entirely in water more than 200 meters deep; or (iii) The date that the first qualified well that...

After Superficial Ablation for Superficial Reflux Associated with Primary Deep Axial Reflux, Can Variable Outcomes be Caused by Deep Venous Valve Anomalies?

PubMed

Maleti, O; Lugli, M; Perrin, M

2017-02-01

To identify which deep anatomical anomalies can explain variable hemodynamic outcomes in patients with superficial reflux associated with primary deep axial reflux who underwent isolated superficial vein ablation without improvement. This is a retrospective study of deep venous valve anomalies in patients who underwent superficial vein ablation for superficial and associated deep reflux. A group of 21 patients who were diagnosed with saphenous reflux associated with primary deep axial reflux, were submitted to great saphenous vein ablation. In 17 patients the deep reflux was not abolished. In this subgroup, surgical exploration of the deep valve was carried out using venotomy for possible valve repair. Among the 17 subgroup patients, four post-thrombotic lesions were discovered intra-operatively in four patients; they underwent different surgical procedures. In 13 of the subgroup patients, primary valve incompetence was confirmed intra-operatively. In 11 cases the leaflets were asymmetrical and in only two were they symmetrical. After valvuloplasty, deep reflux was abolished in all 13 patients. Clinical improvement was obtained in 12/13 patients (92%). It is noteworthy that abolition of deep reflux was associated with significant improvement in air plethysmography data as well as with improvement in clinical status measured on CEAP class, VCSS and the SF-36 questionnaire. Failure to correct deep axial reflux by superficial ablation in patients with superficial and associated primary deep axial reflux may be related to asymmetry in the leaflets of the incompetent deep venous valve. Copyright © 2016 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Numerical investigation of deep-crust behavior under lithospheric extension

NASA Astrophysics Data System (ADS)

Korchinski, Megan; Rey, Patrice F.; Mondy, Luke; Teyssier, Christian; Whitney, Donna L.

2018-02-01

What are the conditions under which lithospheric extension drives exhumation of the deep orogenic crust during the formation of gneiss domes? The mechanical link between extension of shallow crust and flow of deep crust is investigated using two-dimensional numerical experiments of lithospheric extension in which the crust is 60 km thick and the deep-crust viscosity and density parameter space is explored. Results indicate that the style of extension of the shallow crust and the path, magnitude, and rate of flow of deep crust are dynamically linked through the deep-crust viscosity, with density playing an important role in experiments with a high-viscosity deep crust. Three main groups of domes are defined based on their mechanisms of exhumation across the viscosity-density parameter space. In the first group (low-viscosity, low-density deep crust), domes develop by lateral and upward flow of the deep crust at km m.y-1 velocity rates (i.e. rate of experiment boundary extension). In this case, extension in the shallow crust is localized on a single interface, and the deep crust traverses the entire thickness of the crust to the Earth's near-surface in 5 m.y. This high exhuming power relies on the dynamic feedback between the flow of deep crust and the localization of extension in the shallow crust. The second group (intermediate-viscosity, low-density deep crust) has less exhuming power because the stronger deep crust flows less readily and instead accommodates more uniform extension, which imparts distributed extension to the shallow crust. The third group represents the upper limits of viscosity and density for the deep crust; in this case the low buoyancy of the deep crust results in localized thinning of the crust with large upward motion of the Moho and lithosphere-asthenosphere boundary. These numerical experiments test the exhuming power of the deep crust in the formation of extensional gneiss domes.

Extreme Longevity in Proteinaceous Deep-Sea Corals

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

Roark, E B; Guilderson, T P; Dunbar, R B

2009-02-09

Deep-sea corals are found on hard substrates on seamounts and continental margins world-wide at depths of 300 to {approx}3000 meters. Deep-sea coral communities are hotspots of deep ocean biomass and biodiversity, providing critical habitat for fish and invertebrates. Newly applied radiocarbon age date from the deep water proteinaceous corals Gerardia sp. and Leiopathes glaberrima show that radial growth rates are as low as 4 to 35 {micro}m yr{sup -1} and that individual colony longevities are on the order of thousands of years. The management and conservation of deep sea coral communities is challenged by their commercial harvest for the jewelrymore » trade and damage caused by deep water fishing practices. In light of their unusual longevity, a better understanding of deep sea coral ecology and their interrelationships with associated benthic communities is needed to inform coherent international conservation strategies for these important deep-sea ecosystems.« less

Does the Deep Layer of the Deep Temporalis Fascia Really Exist?

PubMed

Li, Hui; Li, Kaide; Jia, Wenhao; Han, Chaoying; Chen, Jinlong; Liu, Lei

2018-04-14

It has been widely accepted that a split of the deep temporal fascia occurs approximately 2 to 3 cm above the zygomatic arch and extends into the superficial and deep layers. The deep layer of the deep temporal fascia is between the superficial temporal fat pad and the temporal muscle. However, during procedures, the authors noted the absence of the deep layer of the deep temporal fascia between the superficial temporal fat pad and the temporal muscle. This prospective study was conducted to clarify the presence or absence of a deep layer of the deep temporal fascia. Anatomic layers of the soft tissues of the temporal region, with reference to the deep temporal fascia, were investigated in 130 cases operated on for zygomaticofacial fractures using the supratemporal approach from June 2013 to June 2017. Of 130 surgeries, the authors found the absence of a thick, obviously identifiable, fascial layer between the superficial temporal fat pad and the temporal muscle. In fact, the authors found nothing above the temporal muscle in most cases. In a few cases, the authors observed only a small amount of scattered loose connective tissue between the superficial temporal fat pad and the temporal muscle. This clinical study showed the absence of a thick, obviously identifiable, fascial layer between the superficial temporal fat pad and the temporal muscle, which suggests that a "deep layer of the deep temporal fascia" might not exist. Copyright © 2018. Published by Elsevier Inc.

30 CFR 203.31 - If I have a qualified phase 2 or qualified phase 3 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2010 CFR

2010-07-01

... water less than 400 meters deep (see § 203.30(a)), has no existing deep or ultra-deep wells and that the... depths partly or entirely less than 200 meters and has not previously produced from a deep well (§ 203.30... which is 16,000 feet TVD SS and your lease is located in water 100 meters deep. Then in 2008, you drill...

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

PubMed

Wang, Xinggang; Yang, Wei; Weinreb, Jeffrey; Han, Juan; Li, Qiubai; Kong, Xiangchuang; Yan, Yongluan; Ke, Zan; Luo, Bo; Liu, Tao; Wang, Liang

2017-11-13

Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning (P = 0.0007 < 0.001). The AUCs were 0.84 (95% CI 0.78-0.89) for deep learning method and 0.70 (95% CI 0.63-0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

The deep plantar arch in humans: constitution and topography.

PubMed

Gabrielli, C; Olave, E; Mandiola, E; Rodrigues, C F; Prates, J C

2001-01-01

The integrity of the various structures within the feet depends on their blood supply. Lesions of the feet often require revascularization, which if successful avoids the need for amputation. To provide greater anatomical detail to aid vascular surgery and imaging, the anatomy and constitution of the deep plantar arch was studied in 50 adult cadaveric feet. The arteries of the foot were injected with red neoprene latex and dissected under magnification. The deep plantar arch, present in all feet, was the result of anastomosis between the deep plantar artery and the deep branch of the lateral plantar artery. The deep plantar artery was predominant in 72% of specimens (Type I arches) and the lateral plantar artery in 22% (Type II), with the contribution being equal in 6% (Type III). The medial plantar artery contributed to the medial segment of the deep plantar arch by its deep branch in 12% of specimens. The distance between the deep plantar arch and each interdigital commissure was generally constant, averaging 29% of total foot length. The deep plantar arch was located in the middle third of the foot in all specimens, being in the distal part of this third in 90%. The deep plantar arch is, therefore formed mainly by the deep plantar artery, a branch of the dorsal artery of foot; its location can be estimated if foot length is known.

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

47 CFR 32.2424 - Submarine & deep sea cable.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Submarine & deep sea cable. 32.2424 Section 32... Submarine & deep sea cable. (a) This account shall include the original cost of submarine cable and deep sea... defined below, are to be maintained for nonmetallic submarine and deep sea cable and metallic submarine...

47 CFR 32.2424 - Submarine & deep sea cable.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 2 2014-10-01 2014-10-01 false Submarine & deep sea cable. 32.2424 Section 32... Submarine & deep sea cable. (a) This account shall include the original cost of submarine cable and deep sea... defined below, are to be maintained for nonmetallic submarine and deep sea cable and metallic submarine...

47 CFR 32.2424 - Submarine & deep sea cable.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Submarine & deep sea cable. 32.2424 Section 32... Submarine & deep sea cable. (a) This account shall include the original cost of submarine cable and deep sea... defined below, are to be maintained for nonmetallic submarine and deep sea cable and metallic submarine...

47 CFR 32.2424 - Submarine & deep sea cable.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 2 2013-10-01 2013-10-01 false Submarine & deep sea cable. 32.2424 Section 32... Submarine & deep sea cable. (a) This account shall include the original cost of submarine cable and deep sea... defined below, are to be maintained for nonmetallic submarine and deep sea cable and metallic submarine...

47 CFR 32.2424 - Submarine & deep sea cable.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 2 2012-10-01 2012-10-01 false Submarine & deep sea cable. 32.2424 Section 32... Submarine & deep sea cable. (a) This account shall include the original cost of submarine cable and deep sea... defined below, are to be maintained for nonmetallic submarine and deep sea cable and metallic submarine...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea... 46 Shipping 7 2011-10-01 2011-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea... 46 Shipping 7 2010-10-01 2010-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20...

The suborbicularis oculi fat (SOOF) and the fascial planes: has everything already been explained?

PubMed

Andretto Amodeo, Chiara; Casasco, Andrea; Icaro Cornaglia, Antonia; Kang, Robert; Keller, Gregory S

2014-01-01

During anatomic and surgical dissections, a connection was seen between the superficial layer of the deep temporal fascia and the prezygomatic area. These findings were in contrast to previous evaluations. This study defines this connection, which is important to understand from both surgical and anatomic standpoints. To define the connection between the superficial layer of the deep temporal fascia and the prezygomatic area and demonstrate the presence of a deep fascial layer in the midface. Anatomical study performed at the Laboratoire d'Anatomie de la Faculté de Médecine de Nice, Sophia Antipolis, France; at the Centre du Don des Corps de l'Université Paris Descartes, Paris, France; and at the Department of Experimental Medicine, Histology, and Embryology Unit of the University of Pavia, Pavia, Italy. Twenty-four hemifaces of 14 white cadavers were dissected to define the relationship between deep temporal fascia and the midface. Four biopsy samples were harvested for histologic analysis. Dissection of 24 hemifaces from the fresh cadavers revealed the following findings. There is a connection of the deep fascia of the temple (superficial layer of deep temporal fascia) to the midface that divides the fat deep to the orbicularis muscle into 2 layers. One layer of fat is the so-called suborbicularis oculi fat (SOOF), which is superficial to the deep fascia, and the other layer of fat (preperiosteal) is deep to the deep fascia and adherent to malar bone. These findings are in contrast to previous anatomical findings. RESULTS In 12 hemifaces, the superficial layer of the deep temporal fascia directly reached the prezygomatic area as a continuous fascial layer. In 16 hemifaces, the superficial sheet of the deep temporal fascia inserted at the level of the zygomatic and lateral orbital rim and continued as a deep fascial layer over the prezygomatic area. In all specimens, a deep fascial layer was present in the prezygomatic-infraorbital area. This deep fascial layer is adherent to the muscles of the infraorbital area, and it divided the fat located deep to the orbicularis oculi muscle into 2 layers: the SOOF and a deeper layer. Histologic examination of the biopsy samples confirmed these findings. This study demonstrates the existence of a deep fascial layer in the midface. This fascia is connected to the superficial layer of the deep temporal fascia, and it divides the fat deep to the orbicularis oculi muscle into 2 layers. This new finding carries interesting implications related to the classic concept of the superficial musculoaponeurotic system. NA.

The Black Hole in the Most Massive Ultracompact Dwarf Galaxy M59-UCD3

NASA Astrophysics Data System (ADS)

Ahn, Christopher P.; Seth, Anil C.; Cappellari, Michele; Krajnović, Davor; Strader, Jay; Voggel, Karina T.; Walsh, Jonelle L.; Bahramian, Arash; Baumgardt, Holger; Brodie, Jean; Chilingarian, Igor; Chomiuk, Laura; den Brok, Mark; Frank, Matthias; Hilker, Michael; McDermid, Richard M.; Mieske, Steffen; Neumayer, Nadine; Nguyen, Dieu D.; Pechetti, Renuka; Romanowsky, Aaron J.; Spitler, Lee

2018-05-01

We examine the internal properties of the most massive ultracompact dwarf galaxy (UCD), M59-UCD3, by combining adaptive-optics-assisted near-IR integral field spectroscopy from Gemini/NIFS and Hubble Space Telescope (HST) imaging. We use the multiband HST imaging to create a mass model that suggests and accounts for the presence of multiple stellar populations and structural components. We combine these mass models with kinematics measurements from Gemini/NIFS to find a best-fit stellar mass-to-light ratio (M/L) and black hole (BH) mass using Jeans anisotropic models (JAMs), axisymmetric Schwarzschild models, and triaxial Schwarzschild models. The best-fit parameters in the JAM and axisymmetric Schwarzschild models have BHs between 2.5 and 5.9 million solar masses. The triaxial Schwarzschild models point toward a similar BH mass but show a minimum χ 2 at a BH mass of ∼0. Models with a BH in all three techniques provide better fits to the central V rms profiles, and thus we estimate the BH mass to be {4.2}-1.7+2.1× {10}6 M ⊙ (estimated 1σ uncertainties). We also present deep radio imaging of M59-UCD3 and two other UCDs in Virgo with dynamical BH mass measurements, and we compare these to X-ray measurements to check for consistency with the fundamental plane of BH accretion. We detect faint radio emission in M59cO but find only upper limits for M60-UCD1 and M59-UCD3 despite X-ray detections in both these sources. The BH mass and nuclear light profile of M59-UCD3 suggest that it is the tidally stripped remnant of a ∼109–1010 M ⊙ galaxy.

No evidence for Lyman α emission in spectroscopy of z > 7 candidate galaxies

NASA Astrophysics Data System (ADS)

Caruana, Joseph; Bunker, Andrew J.; Wilkins, Stephen M.; Stanway, Elizabeth R.; Lacy, Mark; Jarvis, Matt J.; Lorenzoni, Silvio; Hickey, Samantha

2012-12-01

We present Gemini/Gemini Near Infrared Spectrograph (GNIRS) spectroscopic observations of four z-band (z ≈ 7) dropout galaxies and Very Large Telescope (VLT)/XSHOOTER observations of one z-band dropout and three Y-band (z ≈ 8-9) dropout galaxies in the Hubble Ultra Deep Field, which were selected with Wide Field Camera 3 imaging on the Hubble Space Telescope. We find no evidence of Lyman α emission with a typical 5σ sensitivity of 5 × 10-18 erg cm-2 s-1, and use the upper limits on Lyman α flux and the broad-band magnitudes to constrain the rest-frame equivalent widths for this line emission. Accounting for incomplete spectral coverage, we survey 3.0 z-band dropouts and 2.9 Y-band dropouts to a Lyman α rest-frame equivalent width limit >120 Å (for an unresolved emission line); for an equivalent width limit of 50 Å the effective numbers of drop-outs surveyed fall to 1.2 z-band drop-outs and 1.5 Y-band drop-outs. A simple model where the fraction of high rest-frame equivalent width emitters follows the trend seen at z = 3-6.5 is inconsistent with our non-detections at z = 7-9 at the ≈1σ level for spectrally unresolved lines, which may indicate that a significant neutral H I fraction in the intergalactic medium suppresses the Lyman α line in z-drop and Y-drop galaxies at z > 7. Based on observations collected at the European Organization for Astronomical Research in the Southern Hemisphere, Chile, as part of programme 086.A-0968(B).

THE MULTIPHASE STRUCTURE AND POWER SOURCES OF GALACTIC WINDS IN MAJOR MERGERS

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

Rupke, David S. N.; Veilleux, Sylvain, E-mail: drupke@gmail.com

2013-05-01

Massive, galaxy-scale outflows are known to be ubiquitous in major mergers of disk galaxies in the local universe. In this paper, we explore the multiphase structure and power sources of galactic winds in six ultraluminous infrared galaxies (ULIRGs) at z < 0.06 using deep integral field spectroscopy with the Gemini Multi-Object Spectrograph (GMOS) on Gemini North. We probe the neutral, ionized, and dusty gas phases using Na I D, strong emission lines ([O I], H{alpha}, and [N II]), and continuum colors, respectively. We separate outflow motions from those due to rotation and tidal perturbations, and find that all of themore » galaxies in our sample host high-velocity flows on kiloparsec scales. The properties of these outflows are consistent with multiphase (ionized, neutral, and dusty) collimated bipolar winds emerging along the minor axis of the nuclear disk to scales of 1-2 kpc. In two cases, these collimated winds take the form of bipolar superbubbles, identified by clear kinematic signatures. Less collimated (but still high-velocity) flows are also present on scales up to 5 kpc in most systems. The three galaxies in our sample with obscured QSOs host higher velocity outflows than those in the three galaxies with no evidence for an active galactic nucleus. The peak outflow velocity in each of the QSOs is in the range 1450-3350 km s{sup -1}, and the highest velocities (2000-3000 km s{sup -1}) are seen only in ionized gas. The outflow energy and momentum in the QSOs are difficult to produce from a starburst alone, but are consistent with the QSO contributing significantly to the driving of the flow. Finally, when all gas phases are accounted for, the outflows are massive enough to provide negative feedback to star formation.« less

The Next Generation Virgo Cluster Survey. XII. Stellar Populations and Kinematics of Compact, Low-mass Early-type Galaxies from Gemini GMOS-IFU Spectroscopy

NASA Astrophysics Data System (ADS)

Guérou, Adrien; Emsellem, Eric; McDermid, Richard M.; Côté, Patrick; Ferrarese, Laura; Blakeslee, John P.; Durrell, Patrick R.; MacArthur, Lauren A.; Peng, Eric W.; Cuillandre, Jean-Charles; Gwyn, Stephen

2015-05-01

We present Gemini Multi Object Spectrograph integral-field unit (GMOS-IFU) data of eight compact, low-mass early-type galaxies (ETGs) in the Virgo cluster. We analyze their stellar kinematics and stellar population and present two-dimensional maps of these properties covering the central 5″ × 7″ region. We find a large variety of kinematics, from nonrotating to highly rotating objects, often associated with underlying disky isophotes revealed by deep images from the Next Generation Virgo Cluster Survey. In half of our objects, we find a centrally concentrated younger and more metal-rich stellar population. We analyze the specific stellar angular momentum through the λR parameter and find six fast rotators and two slow rotators, one having a thin counterrotating disk. We compare the local galaxy density and stellar populations of our objects with those of 39 more extended low-mass Virgo ETGs from the SMAKCED survey and 260 massive (M > 1010 {{M}⊙ }) ETGs from the ATLAS3D sample. The compact low-mass ETGs in our sample are located in high-density regions, often close to a massive galaxy, and have, on average, older and more metal-rich stellar populations than less compact low-mass galaxies. We find that the stellar population parameters follow lines of constant velocity dispersion in the mass-size plane, smoothly extending the comparable trends found for massive ETGs. Our study supports a scenario where low-mass compact ETGs have experienced long-lived interactions with their environment, including ram-pressure stripping and gravitational tidal forces, that may be responsible for their compact nature.

First glimpse into Lower Jurassic deep-sea biodiversity: in situ diversification and resilience against extinction

PubMed Central

Thuy, Ben; Kiel, Steffen; Dulai, Alfréd; Gale, Andy S.; Kroh, Andreas; Lord, Alan R.; Numberger-Thuy, Lea D.; Stöhr, Sabine; Wisshak, Max

2014-01-01

Owing to the assumed lack of deep-sea macrofossils older than the Late Cretaceous, very little is known about the geological history of deep-sea communities, and most inference-based hypotheses argue for repeated recolonizations of the deep sea from shelf habitats following major palaeoceanographic perturbations. We present a fossil deep-sea assemblage of echinoderms, gastropods, brachiopods and ostracods, from the Early Jurassic of the Glasenbach Gorge, Austria, which includes the oldest known representatives of a number of extant deep-sea groups, and thus implies that in situ diversification, in contrast to immigration from shelf habitats, played a much greater role in shaping modern deep-sea biodiversity than previously thought. A comparison with coeval shelf assemblages reveals that, at least in some of the analysed groups, significantly more extant families/superfamilies have endured in the deep sea since the Early Jurassic than in the shelf seas, which suggests that deep-sea biota are more resilient against extinction than shallow-water ones. In addition, a number of extant deep-sea families/superfamilies found in the Glasenbach assemblage lack post-Jurassic shelf occurrences, implying that if there was a complete extinction of the deep-sea fauna followed by replacement from the shelf, it must have happened before the Late Jurassic. PMID:24850917

1. Deep Creek Road, picnic pavilion Great Smoky Mountains ...

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

1. Deep Creek Road, picnic pavilion - Great Smoky Mountains National Park Roads & Bridges, Deep Creek Road, Between Park Boundary near Bryson City & Deep Creek Campground, Gatlinburg, Sevier County, TN

Functional correlates of the therapeutic and adverse effects evoked by thalamic stimulation for essential tremor

PubMed Central

Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki

2016-01-01

Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768

Controls on deep drainage beneath the root soil zone in snowmelt-dominated environments

NASA Astrophysics Data System (ADS)

Hammond, J. C.; Harpold, A. A.; Kampf, S. K.

2017-12-01

Snowmelt is the dominant source of streamflow generation and groundwater recharge in many high elevation and high latitude locations, yet we still lack a detailed understanding of how snowmelt is partitioned between the soil, deep drainage, and streamflow under a variety of soil, climate, and snow conditions. Here we use Hydrus 1-D simulations with historical inputs from five SNOTEL snow monitoring sites in each of three regions, Cascades, Sierra, and Southern Rockies, to investigate how inter-annual variability on water input rate and duration affects soil saturation and deep drainage. Each input scenario was run with three different soil profiles of varying hydraulic conductivity, soil texture, and bulk density. We also created artificial snowmelt scenarios to test how snowmelt intermittence affects deep drainage. Results indicate that precipitation is the strongest predictor (R2 = 0.83) of deep drainage below the root zone, with weaker relationships observed between deep drainage and snow persistence, peak snow water equivalent, and melt rate. The ratio of deep drainage to precipitation shows a stronger positive relationship to melt rate suggesting that a greater fraction of input becomes deep drainage at higher melt rates. For a given amount of precipitation, rapid, concentrated snowmelt may create greater deep drainage below the root zone than slower, intermittent melt. Deep drainage requires saturation below the root zone, so saturated hydraulic conductivity serves as a primary control on deep drainage magnitude. Deep drainage response to climate is mostly independent of soil texture because of its reliance on saturated conditions. Mean water year saturations of deep soil layers can predict deep drainage and may be a useful way to compare sites in soils with soil hydraulic porosities. The unit depth of surface runoff often is often greater than deep drainage at daily and annual timescales, as snowmelt exceeds infiltration capacity in near-surface soil layers. These results suggest that processes affecting the duration of saturation below the root zone could compromise deep recharge, including changes in snowmelt rate and duration as well as the depth and rate of ET losses from the soil profile.

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 Vein Thrombosis

MedlinePlus

Deep vein thrombosis, or DVT, is a blood clot that forms in a vein deep in the body. Most ... vein swells, the condition is called thrombophlebitis. A deep vein thrombosis can break loose and cause a serious problem ...

2. Deep Creek Road, old bridge at campground entrance. ...

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

2. Deep Creek Road, old bridge at campground entrance. - Great Smoky Mountains National Park Roads & Bridges, Deep Creek Road, Between Park Boundary near Bryson City & Deep Creek Campground, Gatlinburg, Sevier County, TN

In situ Detection of Microbial Life in the Deep Biosphere in Igneous Ocean Crust.

PubMed

Salas, Everett C; Bhartia, Rohit; Anderson, Louise; Hug, William F; Reid, Ray D; Iturrino, Gerardo; Edwards, Katrina J

2015-01-01

The deep biosphere is a major frontier to science. Recent studies have shown the presence and activity of cells in deep marine sediments and in the continental deep biosphere. Volcanic lavas in the deep ocean subsurface, through which substantial fluid flow occurs, present another potentially massive deep biosphere. We present results from the deployment of a novel in situ logging tool designed to detect microbial life harbored in a deep, native, borehole environment within igneous oceanic crust, using deep ultraviolet native fluorescence spectroscopy. Results demonstrate the predominance of microbial-like signatures within the borehole environment, with densities in the range of 10(5) cells/mL. Based on transport and flux models, we estimate that such a concentration of microbial cells could not be supported by transport through the crust, suggesting in situ growth of these communities.

Large Occurrence Patterns of New Zealand Deep Earthquakes: Characterization by Use of a Switching Poisson Model

NASA Astrophysics Data System (ADS)

Shaochuan, Lu; Vere-Jones, David

2011-10-01

The paper studies the statistical properties of deep earthquakes around North Island, New Zealand. We first evaluate the catalogue coverage and completeness of deep events according to cusum (cumulative sum) statistics and earlier literature. The epicentral, depth, and magnitude distributions of deep earthquakes are then discussed. It is worth noting that strong grouping effects are observed in the epicentral distribution of these deep earthquakes. Also, although the spatial distribution of deep earthquakes does not change, their occurrence frequencies vary from time to time, active in one period, relatively quiescent in another. The depth distribution of deep earthquakes also hardly changes except for events with focal depth less than 100 km. On the basis of spatial concentration we partition deep earthquakes into several groups—the Taupo-Bay of Plenty group, the Taranaki group, and the Cook Strait group. Second-order moment analysis via the two-point correlation function reveals only very small-scale clustering of deep earthquakes, presumably limited to some hot spots only. We also suggest that some models usually used for shallow earthquakes fit deep earthquakes unsatisfactorily. Instead, we propose a switching Poisson model for the occurrence patterns of deep earthquakes. The goodness-of-fit test suggests that the time-varying activity is well characterized by a switching Poisson model. Furthermore, detailed analysis carried out on each deep group by use of switching Poisson models reveals similar time-varying behavior in occurrence frequencies in each group.

Dermis, acellular dermal matrix, and fibroblasts from different layers of pig skin exhibit different profibrotic characteristics: evidence from in vivo study

PubMed Central

Zuo, Yanhai; Lu, Shuliang

2017-01-01

To explore the profibrotic characteristics of the autografted dermis, acellular dermal matrix, and dermal fibroblasts from superficial/deep layers of pig skin, 93 wounds were established on the dorsa of 7 pigs. 72 wounds autografted with the superficial/deep dermis and acellular dermal matrix served as the superficial/deep dermis and acellular dermal matrix group, respectively, and were sampled at 2, 4, and 8 weeks post-wounding. 21 wounds autografted with/without superficial/deep dermal fibroblasts served as the superficial/deep dermal fibroblast group and the control group, respectively, and were sampled at 2 weeks post-wounding. The hematoxylin and eosin staining showed that the wounded skin thicknesses in the deep dermis group (superficial acellular dermal matrix group) were significantly greater than those in the superficial dermis group (deep acellular dermal matrix group) at each time point, the thickness of the cutting plane in the deep dermal fibroblast group was significantly greater than that in the superficial dermal fibroblast group and the control group. The western blots showed that the α-smooth muscle actin expression in the deep dermis group (superficial acellular dermal matrix group) was significantly greater than that in the superficial dermis group (deep acellular dermal matrix group) at each time point. In summary, the deep dermis and dermal fibroblasts exhibited more profibrotic characteristics than the superficial ones, on the contrary, the deep acellular dermal matrix exhibited less profibrotic characteristics than the superficial one. PMID:28423561

Isospin diffusion in binary collisions of 32S+Ca,4840 and 32S+48Ti at 17.7 MeV/nucleon

NASA Astrophysics Data System (ADS)

Piantelli, S.; Valdré, S.; Barlini, S.; Casini, G.; Colonna, M.; Baiocco, G.; Bini, M.; Bruno, M.; Camaiani, A.; Carboni, S.; Cicerchia, M.; Cinausero, M.; D'Agostino, M.; Degerlier, M.; Fabris, D.; Gelli, N.; Gramegna, F.; Gruyer, D.; Kravchuk, V. L.; Mabiala, J.; Marchi, T.; Morelli, L.; Olmi, A.; Ottanelli, P.; Pasquali, G.; Pastore, G.

2017-09-01

The systems 32S+Ca,4840 and 32S+48Ti at 17.7 MeV/nucleon were investigated with the setup general array for fragment identification and for emitted light particles in dissipative collisions (GARFIELD) plus ring counter (RCo) at Laboratori Nazionali di Legnaro (LNL) of Istituto Nazionale di Fisica Nucleare (INFN). Fusion evaporation (FE), fusion fission (FF), and deep inelastic (DIC) events were identified, also through the comparison with the prediction of a transport model (stochastic mean field, SMF), coupled to GEMINI++ as an afterburner. This work mainly deals with the study of isospin transport phenomena in DIC events. In particular, the isospin diffusion is highlighted by comparing the average isotopic content of the quasiprojectile (QP) remnants observed when the target is the N =Z nucleus 40Ca and when it is the neutron-rich 48Ca. Also, the d /p and t /p ratios for particles forward emitted with respect to the QP were found to increase with increasing N /Z of the target.

Deep learning methods for protein torsion angle prediction.

PubMed

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

2017-09-18

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

Deep tissue massage: What are we talking about?

PubMed

Koren, Yogev; Kalichman, Leonid

2018-04-01

Massage is a common treatment in complementary and integrative medicine. Deep tissue massage, a form of therapeutic massage, has become more and more popular in recent years. Hence, the use of massage generally and deep tissue massage specifically, should be evaluated as any other modality of therapy to establish its efficacy and safety. To determine the definitions used for deep tissue massage in the scientific literature and to review the current scientific evidence for its efficacy and safety. Narrative review. There is no commonly accepted definition of deep tissue massage in the literature. The definition most frequently used is the intention of the therapist. We suggest separating the definitions of deep massage and deep tissue massage as follows: deep massage should be used to describe the intention of the therapist to treat deep tissue by using any form of massage and deep tissue massage should be used to describe a specific and independent method of massage therapy, utilizing the specific set of principles and techniques as defined by Riggs: "The understanding of the layers of the body, and the ability to work with tissue in these layers to relax, lengthen, and release holding patterns in the most effective and energy efficient way possible within the client's parameters of comfort". Heterogeneity of techniques and protocols used in published studies have made it difficult to draw any clear conclusions. Favorable outcomes may result from deep tissue massage in pain populations and patients with decreased range of motion. In addition, several rare serious adverse events were found related to deep tissue massage, probably as a result of the forceful application of massage therapy. Future research of deep tissue massage should be based on a common definition, classification system and the use of common comparators as controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incidence of deep vein thrombosis in patients undergoing breast reconstruction with autologous tissue transfer.

PubMed

Konoeda, Hisato; Yamaki, Takashi; Hamahata, Atsumori; Ochi, Masakazu; Osada, Atsuyoshi; Hasegawa, Yuki; Kirita, Miho; Sakurai, Hiroyuki

2017-05-01

Background Breast reconstruction is associated with multiple risk factors for venous thromboembolism. However, the incidence of deep vein thrombosis in patients undergoing breast reconstruction is uncertain. Objective The aim of this study was to prospectively evaluate the incidence of deep vein thrombosis in patients undergoing breast reconstruction using autologous tissue transfer and to identify potential risk factors for deep vein thrombosis. Methods Thirty-five patients undergoing breast reconstruction were enrolled. We measured patients' preoperative characteristics including age, body mass index (kg/m 2 ), and risk factors for deep vein thrombosis. The preoperative diameter of each venous segment in the deep veins was measured using duplex ultrasound. All patients received intermittent pneumatic pump and elastic compression stockings for postoperative thromboprophylaxis. Results Among the 35 patients evaluated, 11 (31.4%) were found to have deep vein thrombosis postoperatively, and one patient was found to have pulmonary embolism postoperatively. All instances of deep vein thrombosis developed in the calf and were asymptomatic. Ten of 11 patients underwent free flap transfer, and the remaining one patient received a latissimus dorsi pedicled flap. Deep vein thrombosis incidence did not significantly differ between patients with a free flap or pedicled flap (P = 0.13). Documented risk factors for deep vein thrombosis demonstrated no significant differences between patients with and without deep vein thrombosis. The diameter of the common femoral vein was significantly larger in patients who developed postoperative deep vein thrombosis than in those who did not ( P < 0.05). Conclusions The morbidity of deep vein thrombosis in patients who underwent breast reconstruction using autologous tissue transfer was relatively high. Since only the diameter of the common femoral vein was predictive of developing postoperative deep vein thrombosis, postoperative pharmacological thromboprophylaxis should be considered for all patients undergoing breast reconstruction regardless of operative procedure.

A Modeling Study of Deep Water Renewal in the Red Sea

NASA Astrophysics Data System (ADS)

Yao, F.; Hoteit, I.

2016-02-01

Deep water renewal processes in the Red Sea are examined in this study using a 50-year numerical simulation from 1952-2001. The deep water in the Red Sea below the thermocline ( 200 m) exhibits a near-uniform vertical structure in temperature and salinity, but geochemical tracer distributions, such as 14C and 3He, and dissolved oxygen concentrations indicate that the deep water is renewed on time scales as short as 36 years. The renewal process is accomplished through a deep overturning cell that consists of a southward bottom current and a northward returning current at depths of 400-600 m. Three sources regions are proposed for the formation of the deep water, including two deep outflows from the Gulfs of Aqaba and Suez and winter deep convections in the northern Red Sea. The MITgcm (MIT general circulation model), which has been used to simulate the shallow overturning circulations in the Red Sea, is configured in this study with increased resolutions in the deep water. During the 50 years of simulation, artificial passive tracers added in the model indicate that the deep water in the Red Sea was only episodically renewed during some anomalously cold years; two significant episodes of deep water renewal are reproduced in the winters of 1983 and 1992, in accordance with reported historical hydrographic observations. During these renewal events, deep convections reaching the bottom of the basin occurred, which further facilitated deep sinking of the outflows from the Gulfs of Aqaba and Suez. Ensuing spreading of the newly formed deep water along the bottom caused upward displacements of thermocline, which may have profound effects on the water exchanges in the Strait of Bab el Mandeb between the Red Sea and the Gulf of Aden and the functioning of the ecosystem in the Red Sea by changing the vertical distributions of nutrients.

Transcriptomes and expression profiling of deep-sea corals from the Red Sea provide insight into the biology of azooxanthellate corals.

PubMed

Yum, Lauren K; Baumgarten, Sebastian; Röthig, Till; Roder, Cornelia; Roik, Anna; Michell, Craig; Voolstra, Christian R

2017-07-25

Despite the importance of deep-sea corals, our current understanding of their ecology and evolution is limited due to difficulties in sampling and studying deep-sea environments. Moreover, a recent re-evaluation of habitat limitations has been suggested after characterization of deep-sea corals in the Red Sea, where they live at temperatures of above 20 °C at low oxygen concentrations. To gain further insight into the biology of deep-sea corals, we produced reference transcriptomes and studied gene expression of three deep-sea coral species from the Red Sea, i.e. Dendrophyllia sp., Eguchipsammia fistula, and Rhizotrochus typus. Our analyses suggest that deep-sea coral employ mitochondrial hypometabolism and anaerobic glycolysis to manage low oxygen conditions present in the Red Sea. Notably, we found expression of genes related to surface cilia motion that presumably enhance small particle transport rates in the oligotrophic deep-sea environment. This is the first study to characterize transcriptomes and in situ gene expression for deep-sea corals. Our work offers several mechanisms by which deep-sea corals might cope with the distinct environmental conditions present in the Red Sea As such, our data provide direction for future research and further insight to organismal response of deep-sea coral to environmental change and ocean warming.

Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks.

PubMed

Tran, Son N; d'Avila Garcez, Artur S

2018-02-01

Developments in deep learning have seen the use of layerwise unsupervised learning combined with supervised learning for fine-tuning. With this layerwise approach, a deep network can be seen as a more modular system that lends itself well to learning representations. In this paper, we investigate whether such modularity can be useful to the insertion of background knowledge into deep networks, whether it can improve learning performance when it is available, and to the extraction of knowledge from trained deep networks, and whether it can offer a better understanding of the representations learned by such networks. To this end, we use a simple symbolic language-a set of logical rules that we call confidence rules-and show that it is suitable for the representation of quantitative reasoning in deep networks. We show by knowledge extraction that confidence rules can offer a low-cost representation for layerwise networks (or restricted Boltzmann machines). We also show that layerwise extraction can produce an improvement in the accuracy of deep belief networks. Furthermore, the proposed symbolic characterization of deep networks provides a novel method for the insertion of prior knowledge and training of deep networks. With the use of this method, a deep neural-symbolic system is proposed and evaluated, with the experimental results indicating that modularity through the use of confidence rules and knowledge insertion can be beneficial to network performance.

The deep space network, volume 18. [Deep Space Instrumentation Facility, Ground Communication Facility, and Network Control System

NASA Technical Reports Server (NTRS)

1973-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.

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

PubMed

Choi, Hongyoon

2018-04-01

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

In situ Detection of Microbial Life in the Deep Biosphere in Igneous Ocean Crust

PubMed Central

Salas, Everett C.; Bhartia, Rohit; Anderson, Louise; Hug, William F.; Reid, Ray D.; Iturrino, Gerardo; Edwards, Katrina J.

2015-01-01

The deep biosphere is a major frontier to science. Recent studies have shown the presence and activity of cells in deep marine sediments and in the continental deep biosphere. Volcanic lavas in the deep ocean subsurface, through which substantial fluid flow occurs, present another potentially massive deep biosphere. We present results from the deployment of a novel in situ logging tool designed to detect microbial life harbored in a deep, native, borehole environment within igneous oceanic crust, using deep ultraviolet native fluorescence spectroscopy. Results demonstrate the predominance of microbial-like signatures within the borehole environment, with densities in the range of 105 cells/mL. Based on transport and flux models, we estimate that such a concentration of microbial cells could not be supported by transport through the crust, suggesting in situ growth of these communities. PMID:26617595

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...

30 CFR 203.43 - To which production do I apply the RSV earned from qualified deep wells or qualified phase 1...

Code of Federal Regulations, 2011 CFR

2011-07-01

... INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.43 To... less than 200 meters deep, you began drilling an original deep well with a perforated interval the top...

Deep-Sea Biodiversity in the Mediterranean Sea: The Known, the Unknown, and the Unknowable

PubMed Central

Danovaro, Roberto; Company, Joan Batista; Corinaldesi, Cinzia; D'Onghia, Gianfranco; Galil, Bella; Gambi, Cristina; Gooday, Andrew J.; Lampadariou, Nikolaos; Luna, Gian Marco; Morigi, Caterina; Olu, Karine; Polymenakou, Paraskevi; Ramirez-Llodra, Eva; Sabbatini, Anna; Sardà, Francesc; Sibuet, Myriam; Tselepides, Anastasios

2010-01-01

Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hot spot of terrestrial and coastal marine biodiversity but has been supposed to be impoverished of deep-sea species richness. We summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns. We show that in contrast to what was expected from the sharp decrease in organic carbon fluxes and reduced faunal abundance, the deep-sea biodiversity of both the eastern and the western basins of the Mediterranean Sea is similarly high. All of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deep-water corals showed that the deep basins were the least diverse. Rarefaction curves allowed us to estimate the expected number of species for each benthic component in different bathymetric ranges. A large fraction of exclusive species was associated with each specific habitat or ecosystem. Thus, each deep-sea ecosystem contributes significantly to overall biodiversity. From theoretical extrapolations we estimate that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2805 species of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. Data reported here provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity. PMID:20689848

Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable.

PubMed

Danovaro, Roberto; Company, Joan Batista; Corinaldesi, Cinzia; D'Onghia, Gianfranco; Galil, Bella; Gambi, Cristina; Gooday, Andrew J; Lampadariou, Nikolaos; Luna, Gian Marco; Morigi, Caterina; Olu, Karine; Polymenakou, Paraskevi; Ramirez-Llodra, Eva; Sabbatini, Anna; Sardà, Francesc; Sibuet, Myriam; Tselepides, Anastasios

2010-08-02

Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hot spot of terrestrial and coastal marine biodiversity but has been supposed to be impoverished of deep-sea species richness. We summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns. We show that in contrast to what was expected from the sharp decrease in organic carbon fluxes and reduced faunal abundance, the deep-sea biodiversity of both the eastern and the western basins of the Mediterranean Sea is similarly high. All of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deep-water corals showed that the deep basins were the least diverse. Rarefaction curves allowed us to estimate the expected number of species for each benthic component in different bathymetric ranges. A large fraction of exclusive species was associated with each specific habitat or ecosystem. Thus, each deep-sea ecosystem contributes significantly to overall biodiversity. From theoretical extrapolations we estimate that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2805 species of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. Data reported here provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity.

Deep Crustal Melting and the Survival of Continental Crust

NASA Astrophysics Data System (ADS)

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

2017-12-01

Plate convergence involving continental lithosphere leads to crustal melting, which ultimately stabilizes the crust because it drives rapid upward flow of hot deep crust, followed by rapid cooling at shallow levels. Collision drives partial melting during crustal thickening (at 40-75 km) and/or continental subduction (at 75-100 km). These depths are not typically exceeded by crustal rocks that are exhumed in each setting because partial melting significantly decreases viscosity, facilitating upward flow of deep crust. Results from numerical models and nature indicate that deep crust moves laterally and then vertically, crystallizing at depths as shallow as 2 km. Deep crust flows en masse, without significant segregation of melt into magmatic bodies, over 10s of kms of vertical transport. This is a major mechanism by which deep crust is exhumed and is therefore a significant process of heat and mass transfer in continental evolution. The result of vertical flow of deep, partially molten crust is a migmatite dome. When lithosphere is under extension or transtension, the deep crust is solicited by faulting of the brittle upper crust, and the flow of deep crust in migmatite domes traverses nearly the entire thickness of orogenic crust in <10 million years. This cycle of burial, partial melting, rapid ascent, and crystallization/cooling preserves the continents from being recycled into the mantle by convergent tectonic processes over geologic time. Migmatite domes commonly preserve a record of high-T - low-P metamorphism. Domes may also contain rocks or minerals that record high-T - high-P conditions, including high-P metamorphism broadly coeval with host migmatite, evidence for the deep crustal origin of migmatite. There exists a spectrum of domes, from entirely deep-sourced to mixtures of deep and shallow sources. Controlling factors in deep vs. shallow sources are relative densities of crustal layers and rate of extension: fast extension (cm/yr) promotes efficient ascent of deep crust, whereas slow extension (mm/yr) produces significantly less exhumation. Recognition of the importance of migmatite (gneiss) domes as archives of orogenic deep crust is applicable to determining the chemical and physical properties of continental crust, as well as mechanisms and timescales of crustal differentiation.

Factor V Leiden

MedlinePlus

... and where it travels. A clot in a deep vein This is known as deep vein thrombosis (DVT). Deep vein thrombosis may not cause any symptoms. If ... as a pulmonary embolism, this occurs when a deep vein clot breaks free and travels through the ...

Stable architectures for deep neural networks

NASA Astrophysics Data System (ADS)

Haber, Eldad; Ruthotto, Lars

2018-01-01

Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

30 CFR 203.42 - What conditions and limitations apply to royalty relief for deep wells and phase 1 ultra-deep wells?

Code of Federal Regulations, 2013 CFR

2013-07-01

... or deeper, your lease cannot earn an RSV under § 203.41 as a result of drilling any subsequent deep wells or phase 1 ultra-deep wells. (b) You determine RSV under § 203.41 for the first qualified deep... wells, that determination establishes the total RSV available for that drilling depth interval on your...

30 CFR 203.41 - If I have a qualified deep well or a qualified phase 1 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2014 CFR

2014-07-01

... qualified deep well or qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (b) of this... a qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (c) of this section. (b) If your lease meets the requirements in paragraph (a)(1) of this section, it earns the RSV prescribed in...

30 CFR 203.41 - If I have a qualified deep well or a qualified phase 1 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2012 CFR

2012-07-01

... qualified deep well or qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (b) of this... a qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (c) of this section. (b) If your lease meets the requirements in paragraph (a)(1) of this section, it earns the RSV prescribed in...

30 CFR 203.41 - If I have a qualified deep well or a qualified phase 1 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2013 CFR

2013-07-01

... qualified deep well or qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (b) of this... a qualified phase 1 ultra-deep well, earns an RSV specified in paragraph (c) of this section. (b) If your lease meets the requirements in paragraph (a)(1) of this section, it earns the RSV prescribed in...

30 CFR 203.42 - What conditions and limitations apply to royalty relief for deep wells and phase 1 ultra-deep wells?

Code of Federal Regulations, 2014 CFR

2014-07-01

... or deeper, your lease cannot earn an RSV under § 203.41 as a result of drilling any subsequent deep wells or phase 1 ultra-deep wells. (b) You determine RSV under § 203.41 for the first qualified deep... wells, that determination establishes the total RSV available for that drilling depth interval on your...

30 CFR 203.42 - What conditions and limitations apply to royalty relief for deep wells and phase 1 ultra-deep wells?

Code of Federal Regulations, 2012 CFR

2012-07-01

... or deeper, your lease cannot earn an RSV under § 203.41 as a result of drilling any subsequent deep wells or phase 1 ultra-deep wells. (b) You determine RSV under § 203.41 for the first qualified deep... wells, that determination establishes the total RSV available for that drilling depth interval on your...

30 CFR 203.41 - If I have a qualified deep well or a qualified phase 1 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.41 If I have... not . . . And if it later . . . Then your lease . . . (1) produced gas or oil from any deep well or...

30 CFR 203.40 - Which leases are eligible for royalty relief as a result of drilling a deep well or a phase 1...

Code of Federal Regulations, 2011 CFR

2011-07-01

... a result of drilling a deep well or a phase 1 ultra-deep well? 203.40 Section 203.40 Mineral... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.40 Which...

Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

PubMed

Sadeghi, Zahra

2016-09-01

In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

Deep-sea piezosphere and piezophiles: geomicrobiology and biogeochemistry.

PubMed

Fang, Jiasong; Zhang, Li; Bazylinski, Dennis A

2010-09-01

The deep-sea piezosphere accounts for approximately 75% of the total ocean volume and hosts active and diverse biological communities. Evidence obtained thus far suggests that the microbial biomass present in the piezosphere is significant. Continued international interest in exploring the deep ocean provides impetus to increase our understanding of the deep-sea piezosphere and of the influence of piezophilic microbial communities on the global ocean environment and on biogeochemical cycling occurring in the deep sea. Here, we review the diversity, metabolic characteristics, geomicrobiology and biogeochemistry of the deep-sea piezophiles. Copyright 2010 Elsevier Ltd. All rights reserved.

Iris Transponder-Communications and Navigation for Deep Space

NASA Technical Reports Server (NTRS)

Duncan, Courtney B.; Smith, Amy E.; Aguirre, Fernando H.

2014-01-01

The Jet Propulsion Laboratory has developed the Iris CubeSat compatible deep space transponder for INSPIRE, the first CubeSat to deep space. Iris is 0.4 U, 0.4 kg, consumes 12.8 W, and interoperates with NASA's Deep Space Network (DSN) on X-Band frequencies (7.2 GHz uplink, 8.4 GHz downlink) for command, telemetry, and navigation. This talk discusses the Iris for INSPIRE, it's features and requirements; future developments and improvements underway; deep space and proximity operations applications for Iris; high rate earth orbit variants; and ground requirements, such as are implemented in the DSN, for deep space operations.

The deep-sea under global change.

PubMed

Danovaro, Roberto; Corinaldesi, Cinzia; Dell'Anno, Antonio; Snelgrove, Paul V R

2017-06-05

The deep ocean encompasses 95% of the oceans' volume and is the largest and least explored biome of Earth's Biosphere. New life forms are continuously being discovered. The physiological mechanisms allowing organisms to adapt to extreme conditions of the deep ocean (high pressures, from very low to very high temperatures, food shortage, lack of solar light) are still largely unknown. Some deep-sea species have very long life-spans, whereas others can tolerate toxic compounds at high concentrations; these characteristics offer an opportunity to explore the specialized biochemical and physiological mechanisms associated with these responses. Widespread symbiotic relationships play fundamental roles in driving host functions, nutrition, health, and evolution. Deep-sea organisms communicate and interact through sound emissions, chemical signals and bioluminescence. Several giants of the oceans hunt exclusively at depth, and new studies reveal a tight connection between processes in the shallow water and some deep-sea species. Limited biological knowledge of the deep-sea limits our capacity to predict future response of deep-sea organisms subject to increasing human pressure and changing global environmental conditions. Molecular tools, sensor-tagged animals, in situ and laboratory experiments, and new technologies can enable unprecedented advancement of deep-sea biology, and facilitate the sustainable management of deep ocean use under global change. Copyright © 2017. Published by Elsevier Ltd.

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model

PubMed Central

Luque, Niceto R.; Garrido, Jesús A.; Naveros, Francisco; Carrillo, Richard R.; D'Angelo, Egidio; Ros, Eduardo

2016-01-01

Deep cerebellar nuclei neurons receive both inhibitory (GABAergic) synaptic currents from Purkinje cells (within the cerebellar cortex) and excitatory (glutamatergic) synaptic currents from mossy fibers. Those two deep cerebellar nucleus inputs are thought to be also adaptive, embedding interesting properties in the framework of accurate movements. We show that distributed spike-timing-dependent plasticity mechanisms (STDP) located at different cerebellar sites (parallel fibers to Purkinje cells, mossy fibers to deep cerebellar nucleus cells, and Purkinje cells to deep cerebellar nucleus cells) in close-loop simulations provide an explanation for the complex learning properties of the cerebellum in motor learning. Concretely, we propose a new mechanistic cerebellar spiking model. In this new model, deep cerebellar nuclei embed a dual functionality: deep cerebellar nuclei acting as a gain adaptation mechanism and as a facilitator for the slow memory consolidation at mossy fibers to deep cerebellar nucleus synapses. Equipping the cerebellum with excitatory (e-STDP) and inhibitory (i-STDP) mechanisms at deep cerebellar nuclei afferents allows the accommodation of synaptic memories that were formed at parallel fibers to Purkinje cells synapses and then transferred to mossy fibers to deep cerebellar nucleus synapses. These adaptive mechanisms also contribute to modulate the deep-cerebellar-nucleus-output firing rate (output gain modulation toward optimizing its working range). PMID:26973504

DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-03-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy.

PubMed

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A; Kapur, Tina; Wells, William M; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-02-11

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

Deep-sea bioluminescence blooms after dense water formation at the ocean surface.

PubMed

Tamburini, Christian; Canals, Miquel; Durrieu de Madron, Xavier; Houpert, Loïc; Lefèvre, Dominique; Martini, Séverine; D'Ortenzio, Fabrizio; Robert, Anne; Testor, Pierre; Aguilar, Juan Antonio; Samarai, Imen Al; Albert, Arnaud; André, Michel; Anghinolfi, Marco; Anton, Gisela; Anvar, Shebli; Ardid, Miguel; Jesus, Ana Carolina Assis; Astraatmadja, Tri L; Aubert, Jean-Jacques; Baret, Bruny; Basa, Stéphane; Bertin, Vincent; Biagi, Simone; Bigi, Armando; Bigongiari, Ciro; Bogazzi, Claudio; Bou-Cabo, Manuel; Bouhou, Boutayeb; Bouwhuis, Mieke C; Brunner, Jurgen; Busto, José; Camarena, Francisco; Capone, Antonio; Cârloganu, Christina; Carminati, Giada; Carr, John; Cecchini, Stefano; Charif, Ziad; Charvis, Philippe; Chiarusi, Tommaso; Circella, Marco; Coniglione, Rosa; Costantini, Heide; Coyle, Paschal; Curtil, Christian; Decowski, Patrick; Dekeyser, Ivan; Deschamps, Anne; Donzaud, Corinne; Dornic, Damien; Dorosti, Hasankiadeh Q; Drouhin, Doriane; Eberl, Thomas; Emanuele, Umberto; Ernenwein, Jean-Pierre; Escoffier, Stéphanie; Fermani, Paolo; Ferri, Marcelino; Flaminio, Vincenzo; Folger, Florian; Fritsch, Ulf; Fuda, Jean-Luc; Galatà, Salvatore; Gay, Pascal; Giacomelli, Giorgio; Giordano, Valentina; Gómez-González, Juan-Pablo; Graf, Kay; Guillard, Goulven; Halladjian, Garadeb; Hallewell, Gregory; van Haren, Hans; Hartman, Joris; Heijboer, Aart J; Hello, Yann; Hernández-Rey, Juan Jose; Herold, Bjoern; Hößl, Jurgen; Hsu, Ching-Cheng; de Jong, Marteen; Kadler, Matthias; Kalekin, Oleg; Kappes, Alexander; Katz, Uli; Kavatsyuk, Oksana; Kooijman, Paul; Kopper, Claudio; Kouchner, Antoine; Kreykenbohm, Ingo; Kulikovskiy, Vladimir; Lahmann, Robert; Lamare, Patrick; Larosa, Giuseppina; Lattuada, Dario; Lim, Gordon; Presti, Domenico Lo; Loehner, Herbert; Loucatos, Sotiris; Mangano, Salvatore; Marcelin, Michel; Margiotta, Annarita; Martinez-Mora, Juan Antonio; Meli, Athina; Montaruli, Teresa; Moscoso, Luciano; Motz, Holger; Neff, Max; Nezri, Emma Nuel; Palioselitis, Dimitris; Păvălaş, Gabriela E; Payet, Kevin; Payre, Patrice; Petrovic, Jelena; Piattelli, Paolo; Picot-Clemente, Nicolas; Popa, Vlad; Pradier, Thierry; Presani, Eleonora; Racca, Chantal; Reed, Corey; Riccobene, Giorgio; Richardt, Carsten; Richter, Roland; Rivière, Colas; Roensch, Kathrin; Rostovtsev, Andrei; Ruiz-Rivas, Joaquin; Rujoiu, Marius; Russo, Valerio G; Salesa, Francisco; Sánchez-Losa, Augustin; Sapienza, Piera; Schöck, Friederike; Schuller, Jean-Pierre; Schussler, Fabian; Shanidze, Rezo; Simeone, Francesco; Spies, Andreas; Spurio, Maurizio; Steijger, Jos J M; Stolarczyk, Thierry; Taiuti, Mauro G F; Toscano, Simona; Vallage, Bertrand; Van Elewyck, Véronique; Vannoni, Giulia; Vecchi, Manuela; Vernin, Pascal; Wijnker, Guus; Wilms, Jorn; de Wolf, Els; Yepes, Harold; Zaborov, Dmitry; De Dios Zornoza, Juan; Zúñiga, Juan

2013-01-01

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as "open-sea convection". It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy

PubMed Central

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-01-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose “DeepInfer” – an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections. PMID:28615794

Electron paramagnetic resonance of deep boron in silicon carbide

NASA Astrophysics Data System (ADS)

Baranov, P. G.; Mokhov, E. N.

1996-04-01

In this article we report the first EPR observation of deep boron centres in silicon carbide. A direct identification of the boron atom involved in the defect centre, considered as deep boron, has been established by the presence of a hyperfine interaction with 0268-1242/11/4/005/img1 and 0268-1242/11/4/005/img2 nuclei in isotope-enriched 6H-SiC:B crystals. Deep boron centres were shown from EPR spectra to have axial symmetry along the hexagonal axis. A correspondence between the EPR spectra and the luminescence, ODMR and DLTS spectra of deep boron centres has been indicated. The structural model for a deep boron centre as a boron - vacancy pair is presented and the evidence for bistable behaviour of deep boron centres is discussed.

Parallel Distributed Processing Theory in the Age of Deep Networks.

PubMed

Bowers, Jeffrey S

2017-12-01

Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

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.

Ancient origin of the modern deep-sea fauna.

PubMed

Thuy, Ben; Gale, Andy S; Kroh, Andreas; Kucera, Michal; Numberger-Thuy, Lea D; Reich, Mike; Stöhr, Sabine

2012-01-01

The origin and possible antiquity of the spectacularly diverse modern deep-sea fauna has been debated since the beginning of deep-sea research in the mid-nineteenth century. Recent hypotheses, based on biogeographic patterns and molecular clock estimates, support a latest Mesozoic or early Cenozoic date for the origin of key groups of the present deep-sea fauna (echinoids, octopods). This relatively young age is consistent with hypotheses that argue for extensive extinction during Jurassic and Cretaceous Oceanic Anoxic Events (OAEs) and the mid-Cenozoic cooling of deep-water masses, implying repeated re-colonization by immigration of taxa from shallow-water habitats. Here we report on a well-preserved echinoderm assemblage from deep-sea (1000-1500 m paleodepth) sediments of the NE-Atlantic of Early Cretaceous age (114 Ma). The assemblage is strikingly similar to that of extant bathyal echinoderm communities in composition, including families and genera found exclusively in modern deep-sea habitats. A number of taxa found in the assemblage have no fossil record at shelf depths postdating the assemblage, which precludes the possibility of deep-sea recolonization from shallow habitats following episodic extinction at least for those groups. Our discovery provides the first key fossil evidence that a significant part of the modern deep-sea fauna is considerably older than previously assumed. As a consequence, most major paleoceanographic events had far less impact on the diversity of deep-sea faunas than has been implied. It also suggests that deep-sea biota are more resilient to extinction events than shallow-water forms, and that the unusual deep-sea environment, indeed, provides evolutionary stability which is very rarely punctuated on macroevolutionary time scales.

Flood frequency matters: Why climate change degrades deep-water quality of peri-alpine lakes

NASA Astrophysics Data System (ADS)

Fink, Gabriel; Wessels, Martin; Wüest, Alfred

2016-09-01

Sediment-laden riverine floods transport large quantities of dissolved oxygen into the receiving deep layers of lakes. Hence, the water quality of deep lakes is strongly influenced by the frequency of riverine floods. Although flood frequency reflects climate conditions, the effects of climate variability on the water quality of deep lakes is largely unknown. We quantified the effects of climate variability on the potential shifts in the flood regime of the Alpine Rhine, the main catchment of Lake Constance, and determined the intrusion depths of riverine density-driven underflows and the subsequent effects on water exchange rates in the lake. A simplified hydrodynamic underflow model was developed and validated with observed river inflow and underflow events. The model was implemented to estimate underflow statistics for different river inflow scenarios. Using this approach, we integrated present and possible future flood frequencies to underflow occurrences and intrusion depths in Lake Constance. The results indicate that more floods will increase the number of underflows and the intensity of deep-water renewal - and consequently will cause higher deep-water dissolved oxygen concentrations. Vice versa, fewer floods weaken deep-water renewal and lead to lower deep-water dissolved oxygen concentrations. Meanwhile, a change from glacial nival regime (present) to a nival pluvial regime (future) is expected to decrease deep-water renewal. While flood frequencies are not expected to change noticeably for the next decades, it is most likely that increased winter discharge and decreased summer discharge will reduce the number of deep density-driven underflows by 10% and favour shallower riverine interflows in the upper hypolimnion. The renewal in the deepest layers is expected to be reduced by nearly 27%. This study underlines potential consequences of climate change on the occurrence of deep river underflows and water residence times in deep lakes.

30 CFR 203.42 - What conditions and limitations apply to royalty relief for deep wells and phase 1 ultra-deep wells?

Code of Federal Regulations, 2010 CFR

2010-07-01

... ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not... royalty relief under § 203.41. If . . . Then . . . (a) Your lease has produced gas or oil from a well with... RSV under § 203.41 as a result of drilling any subsequent deep wells or phase 1 ultra-deep wells. (b...

Measurement of Venous Blood Flow in the Lower Limbs: Prevention of Deep Vein Thrombosis during Prolonged Sitting

DTIC Science & Technology

2004-06-01

Abstract. The venous blood flow during stretching and deep breathing in the sitting posture was examined in the present study. First, an...increase in the venous return. Therefore, we suggest that stretching and deep breathing can be used sometimes as preventive measures for deep vein...thrombosis during prolonged sitting. Keywords. Venous blood flow, Near infrared spectroscopy, Deep vein thrombosis. 1. Introduction It has been

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

Duplex sonography for detection of deep vein thrombosis of upper extremities: a 13-year experience.

PubMed

Chung, Amy S Y; Luk, W H; Lo, Adrian X N; Lo, C F

2015-04-01

To determine the prevalence and characteristics of sonographically evident upper-extremity deep vein thrombosis in symptomatic Chinese patients and identify its associated risk factors. Regional hospital, Hong Kong. Data on patients undergoing upper-extremity venous sonography examinations during a 13-year period from November 1999 to October 2012 were retrieved. Variables including age, sex, history of smoking, history of lower-extremity deep vein thrombosis, major surgery within 30 days, immobilisation within 30 days, cancer (history of malignancy), associated central venous or indwelling catheter, hypertension, diabetes mellitus, sepsis within 30 days, and stroke within 30 days were tested using binary logistic regression to understand the risk factors for upper-extremity deep vein thrombosis. The presence of upper-extremity deep vein thrombosis identified. Overall, 213 patients with upper-extremity sonography were identified. Of these patients, 29 (13.6%) had upper-extremity deep vein thrombosis. The proportion of upper-extremity deep vein thrombosis using initial ultrasound was 0.26% of all deep vein thrombosis ultrasound requests. Upper limb swelling was the most common presentation seen in a total of 206 (96.7%) patients. Smoking (37.9%), history of cancer (65.5%), and hypertension (27.6%) were the more prevalent conditions among patients in the upper-extremity deep vein thrombosis-positive group. No statistically significant predictor of upper-extremity deep vein thrombosis was noted if all variables were included. After backward stepwise logistic regression, the final model was left with only age (P=0.119), female gender (P=0.114), and history of malignancy (P=0.024) as independent variables. History of malignancy remained predictive of upper-extremity deep vein thrombosis. Upper-extremity deep vein thrombosis is uncommon among symptomatic Chinese population. The most common sign is swelling and the major risk factor for upper-extremity deep vein thrombosis identified in this study is malignancy.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

PubMed

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

2017-04-01

Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson's disease, and helps inform how adaptive deep brain stimulation might best be delivered. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease

PubMed Central

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M.; Tan, Huiling

2017-01-01

Abstract Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson’s disease, elevations in beta activity (13–35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson’s disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson’s disease, and helps inform how adaptive deep brain stimulation might best be delivered. PMID:28334851

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

PubMed Central

Preuer, Kristina; Lewis, Richard P I; Hochreiter, Sepp; Bender, Andreas; Bulusu, Krishna C; Klambauer, Günter

2018-01-01

Abstract Motivation While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a normalization strategy to account for input data heterogeneity, and conical layers to model drug synergies. Results DeepSynergy was compared to other machine learning methods such as Gradient Boosting Machines, Random Forests, Support Vector Machines and Elastic Nets on the largest publicly available synergy dataset with respect to mean squared error. DeepSynergy significantly outperformed the other methods with an improvement of 7.2% over the second best method at the prediction of novel drug combinations within the space of explored drugs and cell lines. At this task, the mean Pearson correlation coefficient between the measured and the predicted values of DeepSynergy was 0.73. Applying DeepSynergy for classification of these novel drug combinations resulted in a high predictive performance of an AUC of 0.90. Furthermore, we found that all compared methods exhibit low predictive performance when extrapolating to unexplored drugs or cell lines, which we suggest is due to limitations in the size and diversity of the dataset. We envision that DeepSynergy could be a valuable tool for selecting novel synergistic drug combinations. Availability and implementation DeepSynergy is available via www.bioinf.jku.at/software/DeepSynergy. Contact klambauer@bioinf.jku.at Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253077

Deep Learning and Its Applications in Biomedicine.

PubMed

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

2018-02-01

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

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Deep-sea vent chemoautotrophs: diversity, biochemistry and ecological significance.

PubMed

Nakagawa, Satoshi; Takai, Ken

2008-07-01

Deep-sea vents support productive ecosystems driven primarily by chemoautotrophs. Chemoautotrophs are organisms that are able to fix inorganic carbon using a chemical energy obtained through the oxidation of reduced compounds. Following the discovery of deep-sea vent ecosystems in 1977, there has been an increasing knowledge that deep-sea vent chemoautotrophs display remarkable physiological and phylogenetic diversity. Cultivation-dependent and -independent studies have led to an emerging view that the majority of deep-sea vent chemoautotrophs have the ability to derive energy from a variety of redox couples other than the conventional sulfur-oxygen couple, and fix inorganic carbon via the reductive tricarboxylic acid cycle. In addition, recent genomic, metagenomic and postgenomic studies have considerably accelerated the comprehensive understanding of molecular mechanisms of deep-sea vent chemoautotrophy, even in yet uncultivable endosymbionts of vent fauna. Genomic analysis also suggested that there are previously unrecognized evolutionary links between deep-sea vent chemoautotrophs and important human/animal pathogens. This review summarizes chemoautotrophy in deep-sea vents, highlighting recent biochemical and genomic discoveries.

Deep-water longline fishing has reduced impact on Vulnerable Marine Ecosystems

PubMed Central

Pham, Christopher K.; Diogo, Hugo; Menezes, Gui; Porteiro, Filipe; Braga-Henriques, Andreia; Vandeperre, Frederic; Morato, Telmo

2014-01-01

Bottom trawl fishing threatens deep-sea ecosystems, modifying the seafloor morphology and its physical properties, with dramatic consequences on benthic communities. Therefore, the future of deep-sea fishing relies on alternative techniques that maintain the health of deep-sea ecosystems and tolerate appropriate human uses of the marine environment. In this study, we demonstrate that deep-sea bottom longline fishing has little impact on vulnerable marine ecosystems, reducing bycatch of cold-water corals and limiting additional damage to benthic communities. We found that slow-growing vulnerable species are still common in areas subject to more than 20 years of longlining activity and estimate that one deep-sea bottom trawl will have a similar impact to 296–1,719 longlines, depending on the morphological complexity of the impacted species. Given the pronounced differences in the magnitude of disturbances coupled with its selectivity and low fuel consumption, we suggest that regulated deep-sea longlining can be an alternative to deep-sea bottom trawling. PMID:24776718

Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks.

PubMed

Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin

2018-05-01

Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.

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 Dyspareunia in Endometriosis: A Proposed Framework Based on Pain Mechanisms and Genito-Pelvic Pain Penetration Disorder.

PubMed

Yong, Paul J

2017-10-01

Endometriosis is a common chronic disease affecting 1 in 10 women of reproductive age, with half of women with endometriosis experiencing deep dyspareunia. A review of research studies on endometriosis indicates a need for a validated question or questionnaire for deep dyspareunia. Moreover, placebo-controlled randomized trials have yet to demonstrate a clear benefit for traditional treatments of endometriosis for the outcome of deep dyspareunia. The reason some patients might not respond to traditional treatments is the multifactorial nature of deep dyspareunia in endometriosis, which can include comorbid conditions (eg, interstitial cystitis and bladder pain syndrome) and central sensitization underlying genito-pelvic pain penetration disorder. In general, there is a lack of a framework that integrates these multifactorial causes to provide a standardized approach to deep dyspareunia in endometriosis. To propose a clinical framework for deep dyspareunia based on a synthesis of pain mechanisms with genito-pelvic pain penetration disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Narrative review after literature search with the terms (endometriosis AND dyspareunia) OR (dyspareunia AND deep) and after analysis of placebo-controlled randomized trials. Deep dyspareunia presence or absence or deep dyspareunia severity on a numeric rating scale or visual analog scale. Four types of deep dyspareunia are proposed in women with endometriosis: type I that is directly due to endometriosis; type II that is related to a comorbid condition; type III in which genito-pelvic pain penetration disorder is primary; and type IV that is secondary to a combination of types I to III. Four types of deep dyspareunia in endometriosis are proposed, which can be used as a framework in research studies and in clinical practice. Research trials could phenotype or stratify patients by each type. The framework also could give rise to more personalized care for patients by targeting appropriate treatments to each deep dyspareunia type. Yong PJ. Deep Dyspareunia in Endometriosis: A Proposed Framework Based on Pain Mechanisms and Genito-Pelvic Pain Penetration Disorder. Sex Med Rev 2017;5:495-507. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Digital Modeling and Testing Research on Digging Mechanism of Deep Rootstalk Crops

NASA Astrophysics Data System (ADS)

Yang, Chuanhua; Xu, Ma; Wang, Zhoufei; Yang, Wenwu; Liao, Xinglong

The digital model of the laboratory bench parts of digging deep rootstalk crops were established through adopting the parametric model technology based on feature. The virtual assembly of the laboratory bench of digging deep rootstalk crops was done and the digital model of the laboratory bench parts of digging deep rootstalk crops was gained. The vibrospade, which is the key part of the laboratory bench of digging deep rootstalk crops was simulated and the movement parametric curves of spear on the vibrospade were obtained. The results show that the spear was accorded with design requirements. It is propitious to the deep rootstalk.

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

PubMed

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

Rising to the challenge: Deep acting is more beneficial when tasks are appraised as challenging.

PubMed

Huang, Jason L; Chiaburu, Dan S; Zhang, Xin-an; Li, Ning; Grandey, Alicia A

2015-09-01

Cumulative research indicates that deep acting has a nonsignificant relationship with employee exhaustion, despite arguments that deep acting can be beneficial. To illuminate when deep acting leads to more positive employee outcomes, we draw on the resource conservation perspective to propose a within-individual model of deep acting that focuses on service employees' daily fluctuation of emotional labor and emotional exhaustion. Specifically, we propose that the ongoing experience of felt challenge is a within-person boundary condition that moderates deep acting's relationship with emotional exhaustion, and model emotional exhaustion as a mediating mechanism that subsequently predicts momentary job satisfaction and daily customer conflict handling. Using an experience sampling design, we collected data from 84 service employees over a 3-week period. Deep acting was less emotionally exhausting for service providers when they saw their tasks as more challenging. Furthermore, emotional exhaustion mediated the deep acting by felt challenge interaction effect on momentary job satisfaction and daily customer conflict handling. The findings contribute to a better understanding of the deep acting experience at work, while highlighting customer conflict handling as a key behavioral outcome of emotional labor. (c) 2015 APA, all rights reserved).

Vulnerability of deep groundwater in the Bengal Aquifer System to contamination by arsenic

USGS Publications Warehouse

Burgess, W.G.; Hoque, M.A.; Michael, H.A.; Voss, C.I.; Breit, G.N.; Ahmed, K.M.

2010-01-01

Shallow groundwater, the primary water source in the Bengal Basin, contains up to 100 times the World Health Organization (WHO) drinking-water guideline of 10g l 1 arsenic (As), threatening the health of 70 million people. Groundwater from a depth greater than 150m, which almost uniformly meets the WHO guideline, has become the preferred alternative source. The vulnerability of deep wells to contamination by As is governed by the geometry of induced groundwater flow paths and the geochemical conditions encountered between the shallow and deep regions of the aquifer. Stratification of flow separates deep groundwater from shallow sources of As in some areas. Oxidized sediments also protect deep groundwater through the ability of ferric oxyhydroxides to adsorb As. Basin-scale groundwater flow modelling suggests that, over large regions, deep hand-pumped wells for domestic supply may be secure against As invasion for hundreds of years. By contrast, widespread deep irrigation pumping might effectively eliminate deep groundwater as an As-free resource within decades. Finer-scale models, incorporating spatial heterogeneity, are needed to investigate the security of deep municipal abstraction at specific urban locations. ?? 2010 Macmillan Publishers Limited. All rights reserved.

[Search for life in deep biospheres].

PubMed

Naganuma, Takeshi

2003-12-01

The life in deep biospheres bridges conventional biology and future exobiology. This review focuses the microbiological studies from the selected deep biospheres, i.e., deep-sea hydrothermal vents, sub-hydrothermal vents, terrestrial subsurface and a sub-glacier lake. The dark biospheres facilitate the emergence of organisms and communities dependent on chemolithoautotrophy, which are overwhelmed by photoautotrophy (photosynthesis) in the surface biospheres. The life at deep-sea hydrothermal vents owes much to chemolithoautotrophy based on the oxidation of sulfide emitted from the vents. It is likely that similarly active bodies such as the Jovian satellite Europa may have hydrothermal vents and associated biological communities. Anoxic or anaerobic condition is characteristic of deep subsurface biospheres. Subsurface microorganisms exploit available oxidants, or terminal electron acceptors (TEA), for anaerobic respiration. Sulfate, nitrate, iron (III) and CO2 are the representative TEAs in the deep subsurface. Below the 3000-4000 m-thick glacier on Antarctica, there have been >70 lakes with liquid water located. One of such sub-glacial lakes, Lake Vostok, is about to be drill-penetrated for microbiological studies. These deep biosphere "platforms" provide new knowledge about the diversity and potential of the Earth's life. The expertise obtained from the deep biosphere expeditions will facilitate the capability of exobiologial exploration.

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.

Deep Space Telecommunications

NASA Technical Reports Server (NTRS)

Kuiper, T. B. H.; Resch, G. M.

2000-01-01

The increasing load on NASA's deep Space Network, the new capabilities for deep space missions inherent in a next-generation radio telescope, and the potential of new telescope technology for reducing construction and operation costs suggest a natural marriage between radio astronomy and deep space telecommunications in developing advanced radio telescope concepts.

Spatial Statistics of Deep-Water Ambient Noise; Dispersion Relations for Sound Waves and Shear Waves

DTIC Science & Technology

2015-09-30

propagation in very fine-grained sediments (silt and clay ). OBJECTIVES 1) The scientific objective of the deep-water ambient noise research is to...forces in silts and clays and the role they play in controlling wave speeds and attenuations. On a 2 quantum mechanical level, these forces are... clays . APPROACH 1) Deep-water ambient noise Three deep-diving, autonomous instrument platforms, known as Deep Sound I, II, & III, have been

30 CFR 203.49 - May I substitute the deep gas drilling provisions in § 203.0 and §§ 203.40 through 203.47 for the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.49 May I substitute the deep gas drilling provisions in § 203.0 and §§ 203.40... 30 Mineral Resources 2 2011-07-01 2011-07-01 false May I substitute the deep gas drilling...

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).

PubMed

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Xu, Kai; Wei, Haibin; Feng, Fangjun; Li, Tiemei; Pang, Xiaomeng; Shi, Caiping; Luo, Lijun; Zhong, Yang

2017-01-01

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.)

PubMed Central

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Xu, Kai; Wei, Haibin; Feng, Fangjun; Li, Tiemei; Pang, Xiaomeng; Shi, Caiping; Luo, Lijun; Zhong, Yang

2017-01-01

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots. PMID:28798764

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Deep-Sea Bioluminescence Blooms after Dense Water Formation at the Ocean Surface

PubMed Central

Tamburini, Christian; Canals, Miquel; Durrieu de Madron, Xavier; Houpert, Loïc; Lefèvre, Dominique; Martini, Séverine; D'Ortenzio, Fabrizio; Robert, Anne; Testor, Pierre; Aguilar, Juan Antonio; Samarai, Imen Al; Albert, Arnaud; André, Michel; Anghinolfi, Marco; Anton, Gisela; Anvar, Shebli; Ardid, Miguel; Jesus, Ana Carolina Assis; Astraatmadja, Tri L.; Aubert, Jean-Jacques; Baret, Bruny; Basa, Stéphane; Bertin, Vincent; Biagi, Simone; Bigi, Armando; Bigongiari, Ciro; Bogazzi, Claudio; Bou-Cabo, Manuel; Bouhou, Boutayeb; Bouwhuis, Mieke C.; Brunner, Jurgen; Busto, José; Camarena, Francisco; Capone, Antonio; Cârloganu, Christina; Carminati, Giada; Carr, John; Cecchini, Stefano; Charif, Ziad; Charvis, Philippe; Chiarusi, Tommaso; Circella, Marco; Coniglione, Rosa; Costantini, Heide; Coyle, Paschal; Curtil, Christian; Decowski, Patrick; Dekeyser, Ivan; Deschamps, Anne; Donzaud, Corinne; Dornic, Damien; Dorosti, Hasankiadeh Q.; Drouhin, Doriane; Eberl, Thomas; Emanuele, Umberto; Ernenwein, Jean-Pierre; Escoffier, Stéphanie; Fermani, Paolo; Ferri, Marcelino; Flaminio, Vincenzo; Folger, Florian; Fritsch, Ulf; Fuda, Jean-Luc; Galatà, Salvatore; Gay, Pascal; Giacomelli, Giorgio; Giordano, Valentina; Gómez-González, Juan-Pablo; Graf, Kay; Guillard, Goulven; Halladjian, Garadeb; Hallewell, Gregory; van Haren, Hans; Hartman, Joris; Heijboer, Aart J.; Hello, Yann; Hernández-Rey, Juan Jose; Herold, Bjoern; Hößl, Jurgen; Hsu, Ching-Cheng; de Jong, Marteen; Kadler, Matthias; Kalekin, Oleg; Kappes, Alexander; Katz, Uli; Kavatsyuk, Oksana; Kooijman, Paul; Kopper, Claudio; Kouchner, Antoine; Kreykenbohm, Ingo; Kulikovskiy, Vladimir; Lahmann, Robert; Lamare, Patrick; Larosa, Giuseppina; Lattuada, Dario; Lim, Gordon; Presti, Domenico Lo; Loehner, Herbert; Loucatos, Sotiris; Mangano, Salvatore; Marcelin, Michel; Margiotta, Annarita; Martinez-Mora, Juan Antonio; Meli, Athina; Montaruli, Teresa; Motz, Holger; Neff, Max; Nezri, Emma nuel; Palioselitis, Dimitris; Păvălaş, Gabriela E.; Payet, Kevin; Payre, Patrice; Petrovic, Jelena; Piattelli, Paolo; Picot-Clemente, Nicolas; Popa, Vlad; Pradier, Thierry; Presani, Eleonora; Racca, Chantal; Reed, Corey; Riccobene, Giorgio; Richardt, Carsten; Richter, Roland; Rivière, Colas; Roensch, Kathrin; Rostovtsev, Andrei; Ruiz-Rivas, Joaquin; Rujoiu, Marius; Russo, Valerio G.; Salesa, Francisco; Sánchez-Losa, Augustin; Sapienza, Piera; Schöck, Friederike; Schuller, Jean-Pierre; Schussler, Fabian; Shanidze, Rezo; Simeone, Francesco; Spies, Andreas; Spurio, Maurizio; Steijger, Jos J. M.; Stolarczyk, Thierry; Taiuti, Mauro G. F.; Toscano, Simona; Vallage, Bertrand; Van Elewyck, Véronique; Vannoni, Giulia; Vecchi, Manuela; Vernin, Pascal; Wijnker, Guus; Wilms, Jorn; de Wolf, Els; Yepes, Harold; Zaborov, Dmitry; De Dios Zornoza, Juan; Zúñiga, Juan

2013-01-01

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as “open-sea convection”. It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts. PMID:23874425

DeepQA: improving the estimation of single protein model quality with deep belief networks.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

Simulator Studies of the Deep Stall

NASA Technical Reports Server (NTRS)

White, Maurice D.; Cooper, George E.

1965-01-01

Simulator studies of the deep-stall problem encountered with modern airplanes are discussed. The results indicate that the basic deep-stall tendencies produced by aerodynamic characteristics are augmented by operational considerations. Because of control difficulties to be anticipated in the deep stall, it is desirable that adequate safeguards be provided against inadvertent penetrations.

Deep-Elaborative Learning of Introductory Management Accounting for Business Students

ERIC Educational Resources Information Center

Choo, Freddie; Tan, Kim B.

2005-01-01

Research by Choo and Tan (1990; 1995) suggests that accounting students, who engage in deep-elaborative learning, have a better understanding of the course materials. The purposes of this paper are: (1) to describe a deep-elaborative instructional approach (hereafter DEIA) that promotes deep-elaborative learning of introductory management…

77 FR 12245 - Deep Seabed Mining: Request for Extension of Exploration Licenses

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-29

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Deep Seabed Mining: Request.... Department of Commerce. ACTION: Notice of receipt of application to extend Deep Seabed Mining Exploration... received an application for five-year extensions of Deep Seabed Mining Exploration Licenses USA-1 and USA-4...

Deep Reconditioning Testing for near Earth Orbits

NASA Technical Reports Server (NTRS)

Betz, F. E.; Barnes, W. L.

1984-01-01

The problems and benefits of deep reconditioning to near Earth orbit missions with high cycle life and shallow discharge depth requirements is discussed. A simple battery level approach to deep reconditioning of nickel cadmium batteries in near Earth orbit is considered. A test plan was developed to perform deep reconditioning in direct comparison with an alternative trickle charge approach. The results demonstrate that the deep reconditioning procedure described for near Earth orbit application is inferior to the alternative of trickle charging.

Deep X-ray lithography for the fabrication of microstructures at ELSA

NASA Astrophysics Data System (ADS)

Pantenburg, F. J.; Mohr, J.

2001-07-01

Two beamlines at the Electron Stretcher Accelerator (ELSA) of Bonn University are dedicated for the production of microstructures by deep X-ray lithography with synchrotron radiation. They are equipped with state-of-the-art X-ray scanners, maintained and used by Forschungszentrum Karlsruhe. Polymer microstructure heights between 30 and 3000 μm are manufactured regularly for research and industrial projects. This requires different characteristic energies. Therefore, ELSA operates routinely at 1.6, 2.3 and 2.7 GeV, for high-resolution X-ray mask fabrication, deep and ultra-deep X-ray lithography, respectively. The experimental setup, as well as the structure quality of deep and ultra deep X-ray lithographic microstructures are described.

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.

First biological measurements of deep-sea corals from the Red Sea

PubMed Central

Roder, C.; Berumen, M. L.; Bouwmeester, J.; Papathanassiou, E.; Al-Suwailem, A.; Voolstra, C. R.

2013-01-01

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with ‘deep-sea’ and ‘cold-water’ corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited. PMID:24091830

Exploitation of deep-sea resources: the urgent need to understand the role of high pressure in the toxicity of chemical pollutants to deep-sea organisms.

PubMed

Mestre, Nélia C; Calado, Ricardo; Soares, Amadeu M V M

2014-02-01

The advent of industrial activities in the deep sea will inevitably expose deep-sea organisms to potentially toxic compounds. Although international regulations require environmental risk assessment prior to exploitation activities, toxicity tests remain focused on shallow-water model species. Moreover, current tests overlook potential synergies that may arise from the interaction of chemicals with natural stressors, such as the high pressures prevailing in the deep sea. As pressure affects chemical reactions and the physiology of marine organisms, it will certainly affect the toxicity of pollutants arising from the exploitation of deep-sea resources. We emphasize the need for environmental risk assessments based on information generated from ecotoxicological trials that mimic, as close as possible, the deep-sea environment, with emphasis to a key environmental factor - high hydrostatic pressure. Copyright © 2013 Elsevier Ltd. All rights reserved.

First biological measurements of deep-sea corals from the Red Sea.

PubMed

Roder, C; Berumen, M L; Bouwmeester, J; Papathanassiou, E; Al-Suwailem, A; Voolstra, C R

2013-10-03

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with 'deep-sea' and 'cold-water' corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited.

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

Deep Web video

ScienceCinema

None Available

2018-02-06

To make the web work better for science, OSTI has developed state-of-the-art technologies and services including a deep web search capability. The deep web includes content in searchable databases available to web users but not accessible by popular search engines, such as Google. This video provides an introduction to the deep web search engine.

50 CFR 229.37 - False Killer Whale Take Reduction Plan.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Hawaii Pelagic and Hawaii Insular stocks of false killer whales in the Hawaii-based deep-set and shallow... section have the following meanings: (1) Deep-set or Deep-setting has the same meaning as the definition... this title. (c) Gear requirements. (1) While deep-setting, the owner and operator of a vessel...

50 CFR 229.37 - False Killer Whale Take Reduction Plan.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Hawaii Pelagic and Hawaii Insular stocks of false killer whales in the Hawaii-based deep-set and shallow... section have the following meanings: (1) Deep-set or Deep-setting has the same meaning as the definition... this title. (c) Gear requirements. (1) While deep-setting, the owner and operator of a vessel...

47 CFR 32.6424 - Submarine and deep sea cable expense.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Submarine and deep sea cable expense. 32.6424... Submarine and deep sea cable expense. (a) This account shall include expenses associated with submarine and deep sea cable. (b) Subsidiary record categories shall be maintained as provided in § 32.2424. [67 FR...

47 CFR 32.6424 - Submarine and deep sea cable expense.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 2 2013-10-01 2013-10-01 false Submarine and deep sea cable expense. 32.6424... Submarine and deep sea cable expense. (a) This account shall include expenses associated with submarine and deep sea cable. (b) Subsidiary record categories shall be maintained as provided in § 32.2424. [67 FR...

47 CFR 32.6424 - Submarine and deep sea cable expense.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 2 2012-10-01 2012-10-01 false Submarine and deep sea cable expense. 32.6424... Submarine and deep sea cable expense. (a) This account shall include expenses associated with submarine and deep sea cable. (b) Subsidiary record categories shall be maintained as provided in § 32.2424. [67 FR...

47 CFR 32.6424 - Submarine and deep sea cable expense.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 2 2014-10-01 2014-10-01 false Submarine and deep sea cable expense. 32.6424... Submarine and deep sea cable expense. (a) This account shall include expenses associated with submarine and deep sea cable. (b) Subsidiary record categories shall be maintained as provided in § 32.2424. [67 FR...

47 CFR 32.6424 - Submarine and deep sea cable expense.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Submarine and deep sea cable expense. 32.6424... Submarine and deep sea cable expense. (a) This account shall include expenses associated with submarine and deep sea cable. (b) Subsidiary record categories shall be maintained as provided in § 32.2424. [67 FR...

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.

The deep lymphatic anatomy of the hand.

PubMed

Ma, Chuan-Xiang; Pan, Wei-Ren; Liu, Zhi-An; Zeng, Fan-Qiang; Qiu, Zhi-Qiang

2018-07-01

The deep lymphatic anatomy of the hand still remains the least described in medical literature. Eight hands were harvested from four nonembalmed human cadavers amputated above the wrist. A small amount of 6% hydrogen peroxide was employed to detect the lymphatic vessels around the superficial and deep palmar vascular arches, in webs from the index to little fingers, the thenar and hypothenar areas. A 30-gauge needle was inserted into the vessels and injected with a barium sulphate compound. Each specimen was dissected, photographed and radiographed to demonstrate deep lymphatic distribution of the hand. Five groups of deep collecting lymph vessels were found in the hand: superficial palmar arch lymph vessel (SPALV); deep palmar arch lymph vessel (DPALV); thenar lymph vessel (TLV); hypothenar lymph vessel (HTLV); deep finger web lymph vessel (DFWLV). Each group of vessels drained in different directions first, then all turned and ran towards the wrist in different layers. The deep lymphatic drainage of the hand has been presented. The results will provide an anatomical basis for clinical management, educational reference and scientific research. Copyright © 2018 Elsevier GmbH. All rights reserved.

Neurophysiological study on the effect of various short durations of deep breathing: A randomized controlled trial.

PubMed

Cheng, Kok Suen; Han, Ray P S; Lee, Poh Foong

2018-02-01

The study aims to study the effects of short duration deep breathing on the EEG power with topography based on parallel group randomized controlled trial design which was lacking in prior reports. 50 participants were split into 4 groups: control (CONT), deep breathing (DB) for 5 (DB5), 7 (DB7), and 9 (DB9) minutes. EEG recordings were obtained during baseline, deep breathing session, after deep breathing, and a follow-up session after 7 days of consecutive practice. Frontal theta power of DB5 and DB9 was significantly larger than that of CONT after the deep breathing session (p = 0.027 and p = 0.006, respectively) and the profound finding showed that the theta topography obtained a central-focused distribution for DB7 and DB9. The result obtained was consistent with previous literature, albeit for certain deep breathing durations only, indicating a possible linkage between the deep breathing duration and the neurophysiology of the brain. Copyright © 2017 Elsevier B.V. All rights reserved.

The effect of ocean alkalinity and carbon transfer on deep-sea carbonate ion concentration during the past five glacial cycles

NASA Astrophysics Data System (ADS)

Kerr, Joanna; Rickaby, Rosalind; Yu, Jimin; Elderfield, Henry; Sadekov, Aleksey Yu.

2017-08-01

Glacial-interglacial deep Indo-Pacific carbonate ion concentration ([CO32-]) changes were mainly driven by two mechanisms that operated on different timescales: 1) a long-term increase during glaciation caused by a carbonate deposition reduction on shelves (i.e., the coral reef hypothesis), and 2) transient carbonate compensation responses to deep ocean carbon storage changes. To investigate these mechanisms, we have used benthic foraminiferal B/Ca to reconstruct deep-water [CO32-] in cores from the deep Indian and Equatorial Pacific Oceans during the past five glacial cycles. Based on our reconstructions, we suggest that the shelf-to-basin shift of carbonate deposition raised deep-water [CO32-], on average, by 7.3 ± 0.5 (SE) μmol/kg during glaciations. Oceanic carbon reorganisations during major climatic transitions caused deep-water [CO32-] deviations away from the long-term trend, and carbonate compensation processes subsequently acted to restore the ocean carbonate system to new steady state conditions. Deep-water [CO32-] showed similar patterns to sediment carbonate content (%CaCO3) records on glacial-interglacial timescales, suggesting that past seafloor %CaCO3 variations were dominated by deep-water carbonate preservation changes at our studied sites.

The dynamics of biogeographic ranges in the deep sea.

PubMed

McClain, Craig R; Hardy, Sarah Mincks

2010-12-07

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

The dynamics of biogeographic ranges in the deep sea

PubMed Central

McClain, Craig R.; Hardy, Sarah Mincks

2010-01-01

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

MR Anatomy of Deep Brain Nuclei with Special Reference to Specific Diseases and Deep Brain Stimulation Localization

PubMed Central

Telford, Ryan; Vattoth, Surjith

2014-01-01

Summary Diseases affecting the basal ganglia and deep brain structures vary widely in etiology and include metabolic, infectious, ischemic, and neurodegenerative conditions. Some neurologic diseases, such as Wernicke encephalopathy or pseudohypoparathyroidism, require specific treatments, which if unrecognized could lead to further complications. Other pathologies, such as hypertrophic olivary degeneration, if not properly diagnosed may be mistaken for a primary medullary neoplasm and create unnecessary concern. The deep brain structures are complex and can be difficult to distinguish on routine imaging. It is imperative that radiologists first understand the intrinsic anatomic relationships between the different basal ganglia nuclei and deep brain structures with magnetic resonance (MR) imaging. It is important to understand the "normal" MR signal characteristics, locations, and appearances of these structures. This is essential to recognizing diseases affecting the basal ganglia and deep brain structures, especially since most of these diseases result in symmetrical, and therefore less noticeable, abnormalities. It is also crucial that neurosurgeons correctly identify the deep brain nuclei presurgically for positioning deep brain stimulator leads, the most important being the subthalamic nucleus for Parkinson syndromes and the thalamic ventral intermediate nucleus for essential tremor. Radiologists will be able to better assist clinicians in diagnosis and treatment once they are able to accurately localize specific deep brain structures. PMID:24571832

From Offshore to Onshore: Multiple Origins of Shallow-Water Corals from Deep-Sea Ancestors

PubMed Central

Lindner, Alberto; Cairns, Stephen D.; Cunningham, Clifford W.

2008-01-01

Shallow-water tropical reefs and the deep sea represent the two most diverse marine environments. Understanding the origin and diversification of this biodiversity is a major quest in ecology and evolution. The most prominent and well-supported explanation, articulated since the first explorations of the deep sea, holds that benthic marine fauna originated in shallow, onshore environments, and diversified into deeper waters. In contrast, evidence that groups of marine organisms originated in the deep sea is limited, and the possibility that deep-water taxa have contributed to the formation of shallow-water communities remains untested with phylogenetic methods. Here we show that stylasterid corals (Cnidaria: Hydrozoa: Stylasteridae)—the second most diverse group of hard corals—originated and diversified extensively in the deep sea, and subsequently invaded shallow waters. Our phylogenetic results show that deep-water stylasterid corals have invaded the shallow-water tropics three times, with one additional invasion of the shallow-water temperate zone. Our results also show that anti-predatory innovations arose in the deep sea, but were not involved in the shallow-water invasions. These findings are the first robust evidence that an important group of tropical shallow-water marine animals evolved from deep-water ancestors. PMID:18560569

A nonintrusive temperature measuring system for estimating deep body temperature in bed.

PubMed

Sim, S Y; Lee, W K; Baek, H J; Park, K S

2012-01-01

Deep body temperature is an important indicator that reflects human being's overall physiological states. Existing deep body temperature monitoring systems are too invasive to apply to awake patients for a long time. Therefore, we proposed a nonintrusive deep body temperature measuring system. To estimate deep body temperature nonintrusively, a dual-heat-flux probe and double-sensor probes were embedded in a neck pillow. When a patient uses the neck pillow to rest, the deep body temperature can be assessed using one of the thermometer probes embedded in the neck pillow. We could estimate deep body temperature in 3 different sleep positions. Also, to reduce the initial response time of dual-heat-flux thermometer which measures body temperature in supine position, we employed the curve-fitting method to one subject. And thereby, we could obtain the deep body temperature in a minute. This result shows the possibility that the system can be used as practical temperature monitoring system with appropriate curve-fitting model. In the next study, we would try to establish a general fitting model that can be applied to all of the subjects. In addition, we are planning to extract meaningful health information such as sleep structure analysis from deep body temperature data which are acquired from this system.

Temperature impacts on deep-sea biodiversity.

PubMed

Yasuhara, Moriaki; Danovaro, Roberto

2016-05-01

Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity. Here we synthesize current knowledge on temperature-diversity relationships in the deep sea. Our results from both present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible that temperature is important only when at relatively high and low levels but does not play a major role in the intermediate temperature range. Possible mechanisms explaining the temperature-biodiversity relationship include the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea temperatures due to human-induced climate change may have more adverse consequences than expected considering the sensitivity of deep-sea ecosystems to temperature changes. © 2014 Cambridge Philosophical Society.

Deep cerebral venous thrombosis mimicking influenza-associated acute necrotizing encephalopathy: a case report.

PubMed

Taniguchi, Daisuke; Nakajima, Sho; Hayashida, Arisa; Kuroki, Takuma; Eguchi, Hiroto; Machida, Yutaka; Hattori, Nobutaka; Miwa, Hideto

2017-09-26

Acute necrotizing encephalopathy is one of the most devastating neurological complications of influenza virus infection. Acute necrotizing encephalopathy preferentially affects the thalamus bilaterally, as does deep cerebral venous thrombosis, which can lead to misdiagnosis. A 52-year-old Japanese woman infected with seasonal influenza B virus presented to the emergency care unit in our hospital with progressive alteration of her level of consciousness. Bilateral thalamic lesions were demonstrated by magnetic resonance imaging, leading to a tentative diagnosis of acute necrotizing encephalopathy. However, she had deep cerebral venous thrombosis, and the presence of diminished signal and enlargement of deep cerebral veins on T2*-weighted imaging contributed to a revised diagnosis of deep cerebral venous thrombosis. Anticoagulant therapy was initiated, leading to her gradual recovery, with recanalization of the deep venous system and straight sinus. To the best of our knowledge, these results represent the first report of deep cerebral venous thrombosis associated with influenza infection. It is clinically important to recognize that deep cerebral venous thrombosis, although rare, might be one of the neurological complications of influenza infection. In the presence of bilateral thalamic lesions in patients with influenza infection, deep cerebral venous thrombosis should be considered in addition to acute necrotizing encephalopathy. Delays in diagnosis and commencement of anticoagulant therapy can lead to unfavorable outcomes.

Differential impact of thalamic versus subthalamic deep brain stimulation on lexical processing.

PubMed

Krugel, Lea K; Ehlen, Felicitas; Tiedt, Hannes O; Kühn, Andrea A; Klostermann, Fabian

2014-10-01

Roles of subcortical structures in language processing are vague, but, interestingly, basal ganglia and thalamic Deep Brain Stimulation can go along with reduced lexical capacities. To deepen the understanding of this impact, we assessed word processing as a function of thalamic versus subthalamic Deep Brain Stimulation. Ten essential tremor patients treated with thalamic and 14 Parkinson׳s disease patients with subthalamic Deep Brain Stimulation performed an acoustic Lexical Decision Task ON and OFF stimulation. Combined analysis of task performance and event-related potentials allowed the determination of processing speed, priming effects, and N400 as neurophysiological correlate of lexical stimulus processing. 12 age-matched healthy participants acted as control subjects. Thalamic Deep Brain Stimulation prolonged word decisions and reduced N400 potentials. No comparable ON-OFF effects were present in patients with subthalamic Deep Brain Stimulation. In the latter group of patients with Parkinson' disease, N400 amplitudes were, however, abnormally low, whether under active or inactive Deep Brain Stimulation. In conclusion, performance speed and N400 appear to be influenced by state functions, modulated by thalamic, but not subthalamic Deep Brain Stimulation, compatible with concepts of thalamo-cortical engagement in word processing. Clinically, these findings specify cognitive sequels of Deep Brain Stimulation in a target-specific way. Copyright © 2014 Elsevier Ltd. All rights reserved.

Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers

USGS Publications Warehouse

Marienthal, Alex; Hendrikx, Jordy; Birkeland, Karl; Irvine, Kathryn M.

2015-01-01

Deep slab avalanches are particularly challenging to forecast. These avalanches are difficult to trigger, yet when they release they tend to propagate far and can result in large and destructive avalanches. We utilized a 44-year record of avalanche control and meteorological data from Bridger Bowl ski area in southwest Montana to test the usefulness of meteorological variables for predicting seasons and days with deep slab avalanches. We defined deep slab avalanches as those that failed on persistent weak layers deeper than 0.9 m, and that occurred after February 1st. Previous studies often used meteorological variables from days prior to avalanches, but we also considered meteorological variables over the early months of the season. We used classification trees and random forests for our analyses. Our results showed seasons with either dry or wet deep slabs on persistent weak layers typically had less precipitation from November through January than seasons without deep slabs on persistent weak layers. Days with deep slab avalanches on persistent weak layers often had warmer minimum 24-hour air temperatures, and more precipitation over the prior seven days, than days without deep slabs on persistent weak layers. Days with deep wet slab avalanches on persistent weak layers were typically preceded by three days of above freezing air temperatures. Seasonal and daily meteorological variables were found useful to aid forecasting dry and wet deep slab avalanches on persistent weak layers, and should be used in combination with continuous observation of the snowpack and avalanche activity.

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

2018-03-01

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

NASA Astrophysics Data System (ADS)

Mahanama, S. P.; Koster, R. D.; Liu, P.

2006-05-01

Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

North Atlantic deep water formation and AMOC in CMIP5 models

NASA Astrophysics Data System (ADS)

Heuzé, Céline

2017-07-01

Deep water formation in climate models is indicative of their ability to simulate future ocean circulation, carbon and heat uptake, and sea level rise. Present-day temperature, salinity, sea ice concentration and ocean transport in the North Atlantic subpolar gyre and Nordic Seas from 23 CMIP5 (Climate Model Intercomparison Project, phase 5) models are compared with observations to assess the biases, causes and consequences of North Atlantic deep convection in models. The majority of models convect too deep, over too large an area, too often and too far south. Deep convection occurs at the sea ice edge and is most realistic in models with accurate sea ice extent, mostly those using the CICE model. Half of the models convect in response to local cooling or salinification of the surface waters; only a third have a dynamic relationship between freshwater coming from the Arctic and deep convection. The models with the most intense deep convection have the warmest deep waters, due to a redistribution of heat through the water column. For the majority of models, the variability of the Atlantic Meridional Overturning Circulation (AMOC) is explained by the volumes of deep water produced in the subpolar gyre and Nordic Seas up to 2 years before. In turn, models with the strongest AMOC have the largest heat export to the Arctic. Understanding the dynamical drivers of deep convection and AMOC in models is hence key to realistically forecasting Arctic oceanic warming and its consequences for the global ocean circulation, cryosphere and marine life.

Shear Strengthening of RC Deep Beam Using Externally Bonded GFRP Fabrics

NASA Astrophysics Data System (ADS)

Kumari, A.; Patel, S. S.; Nayak, A. N.

2018-06-01

This work presents the experimental investigation of RC deep beams wrapped with externally bonded Glass Fibre Reinforced Polymer (GFRP) fabrics in order to study the Load versus deflection behavior, cracking pattern, failure modes and ultimate shear strength. A total number of five deep beams have been casted, which is designed with conventional steel reinforcement as per IS: 456 (Indian standard plain and reinforced concrete—code for practice, Bureau of Indian Standards, New Delhi, 2000). The spans to depth ratio for all RC deep beams have been kept less than 2 as per the above specification. Out of five RC deep beams, one without retrofitting serves as a reference beam and the rest four have been wrapped with GFRP fabrics in multiple layers and tested with two point loading condition. The first cracking load, ultimate load and the shear contribution of GFRP to the deep beams have been observed. A critical discussion is made with respect to the enhancement of the strength, behaviour and performance of retrofitted deep beams in comparison to the deep beam without GFRP in order to explore the potential use of GFRP for strengthening the RC deep beams. Test results have demonstrated that the deep beams retrofitted with GFRP shows a slower development of the diagonal cracks and improves shear carrying capacity of the RC deep beam. A comparative study of the experimental results with the theoretical ones predicted by various researchers available in the literatures has also been presented. It is observed that the ultimate load of the beams retrofitted with GFRP fabrics increases with increase of number of GFRP layers up to a specific number of layers, i.e. 3 layers, beyond which it decreases.

Effectiveness of complementary pain treatment for women with deep endometriosis through Transcutaneous Electrical Nerve Stimulation (TENS): randomized controlled trial.

PubMed

Mira, Ticiana A A; Giraldo, Paulo C; Yela, Daniela A; Benetti-Pinto, Cristina L

2015-11-01

Evaluate TENS effectiveness as a complementary treatment of chronic pelvic pain and deep dyspareunia in women with deep endometriosis. This randomized controlled trial was performed in a tertiary health care center, including twenty-two women with deep endometriosis undergoing hormone therapy with persistent pelvic pain and/or deep dyspareunia. This study was registered in the Brazilian Record of Clinical Trials (ReBEC), under n RBR-3rndh6. TENS application for 8 weeks followed a randomized allocation into two groups: Group 1 - acupuncture-like TENS (Frequency: 8Hz, pulse duration: 250μs) - VIF (n=11) and Group 2 - self-applied TENS (Frequency: 85Hz, pulse duration: 75μs) (n=11). The intensity applied was "strong, but comfortable". We evaluated patients before and after treatment by the use of the Visual Analogue Scale, Deep Dyspareunia Scale and Endometriosis Quality of Life Questionnaire. We used the Wilcoxon and Mann-Whitney tests to compare before and after treatment conditions. Despite the use of hormone therapy for 1.65±2.08 years, the 22 women with deep endometriosis sustained pelvic pain complaints (VAS=5.95±2.13 and 2.45±2.42, p<.001) and/or deep dyspareunia (DDS=2.29±0.46 and 1.20±1.01, p=.001). We observed significant improvement for chronic pelvic pain, deep dyspareunia and quality of life by the use of TENS. Both application types of TENS were effective for improving the evaluated types of pain. Both resources (acupuncture-like TENS and self-applied TENS) demonstrated effectiveness as a complementary treatment of pelvic pain and deep dyspareunia, improving quality of life in women with deep endometriosis regardless of the device used for treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Deep-sea ciliates: Recorded diversity and experimental studies on pressure tolerance

NASA Astrophysics Data System (ADS)

Schoenle, Alexandra; Nitsche, Frank; Werner, Jennifer; Arndt, Hartmut

2017-10-01

Microbial eukaryotes play an important role in biogeochemical cycles not only in productive surface waters but also in the deep sea. Recent studies based on metagenomics report deep-sea protistan assemblages totally different from continental slopes and shelf waters. To give an overview about the ciliate fauna recorded from the deep sea we summarized the available information on ciliate occurrence in the deep sea. Our literature review revealed that representatives of the major phylogenetic groups of ciliates were recorded from the deep sea (> 1000 m depth): Karyorelictea, Heterotrichea, Spirotrichea (Protohypotrichia, Euplotia, Oligotrichia, Choreotrichia, Hypotrichia), Armophorea (Armophorida), Litostomatea (Haptoria), Conthreep (Phyllopharyngea incl. Cyrtophoria, Chonotrichia, Suctoria; Nassophorea incl. Microthoracida, Synhymeniida, Nassulida; Colpodea incl. Bursariomorphida, Cyrtolophosidida; Prostomatea; Plagiopylea incl. Plagiopylida, Odontostomatida; Oligohymenophorea incl. Peniculia, Scuticociliatia, Hymenostomatia, Apostomatia, Peritrichia, Astomatia). Species occurring in both habitats, deep sea and shallow water, are rarely found to our knowledge to date. This indicates a high deep-sea specific ciliate fauna. Our own studies of similar genotypes (SSU rDNA and cox1 gene) revealed that two small scuticociliate species (Pseudocohnilembus persalinus and Uronema sp.) could be isolated from surface as well as deep waters (2687 m, 5276 m, 5719 m) of the Pacific. The adaptation to deep-sea conditions was investigated by exposing the ciliate isolates directly or stepwise to different hydrostatic pressures ranging from 1 to 550 atm at temperatures of 2 °C and 13 °C. Although the results indicated no general barophilic behavior, all four isolated strains survived the highest established pressure. A better survival at 550 atm could be observed for the lower temperature. Among microbial eukaryotes, ciliates should be considered as a diverse and potentially important component of deep-sea microeukaryote communities.

Deep-Sea Coral Image Catalog: Northeast Pacific

NASA Astrophysics Data System (ADS)

Freed, J. C.

2016-02-01

In recent years, deep-sea exploration in the Northeast Pacific ocean has been on the rise using submersibles and remotely operated vehicles (ROVs), acquiring a plethora of underwater videos and photographs. Analysis of deep-sea fauna revealed by this research has been hampered by the lack of catalogs or guides that allow identification of species in the field. Deep-sea corals are of particular conservation concern, but currently, there are few catalogs which describe and provide detailed information on deep-sea corals from the Northeast Pacific and those that exist are focused on small, specific areas. This project, in collaboration with NOAA's Deep-Sea Coral Ecology Laboratory at the Center for Coastal Environmental Health and Biomolecular Research (CCEHBR) and the Southwest Fisheries Science Center (SWFSC), developed pages for a deep-sea coral identification guide that provides photos and information on the visual identification, distributions, and habitats of species found in the Northeast Pacific. Using online databases, photo galleries, and literature, this catalog has been developed to be a living document open to future additions. This project produced 12 entries for the catalog on a variety of different deep-sea corals. The catalog is intended to be used during underwater surveys in the Northeast Pacific, but will also assist in identification of deep-sea coral by-catch by fishing vessels, and for general educational use. These uses will advance NOAA's ability to identify and protect sensitive deep-sea habitats that act as biological hotspots. The catalog is intended to be further developed into an online resource with greater interactive features with links to other resources and featured on NOAA's Deep-Sea Coral Data Portal.

Shear Strengthening of RC Deep Beam Using Externally Bonded GFRP Fabrics

NASA Astrophysics Data System (ADS)

Kumari, A.; Patel, S. S.; Nayak, A. N.

2018-02-01

This work presents the experimental investigation of RC deep beams wrapped with externally bonded Glass Fibre Reinforced Polymer (GFRP) fabrics in order to study the Load versus deflection behavior, cracking pattern, failure modes and ultimate shear strength. A total number of five deep beams have been casted, which is designed with conventional steel reinforcement as per IS: 456 (Indian standard plain and reinforced concrete—code for practice, Bureau of Indian Standards, New Delhi, 2000). The spans to depth ratio for all RC deep beams have been kept less than 2 as per the above specification. Out of five RC deep beams, one without retrofitting serves as a reference beam and the rest four have been wrapped with GFRP fabrics in multiple layers and tested with two point loading condition. The first cracking load, ultimate load and the shear contribution of GFRP to the deep beams have been observed. A critical discussion is made with respect to the enhancement of the strength, behaviour and performance of retrofitted deep beams in comparison to the deep beam without GFRP in order to explore the potential use of GFRP for strengthening the RC deep beams. Test results have demonstrated that the deep beams retrofitted with GFRP shows a slower development of the diagonal cracks and improves shear carrying capacity of the RC deep beam. A comparative study of the experimental results with the theoretical ones predicted by various researchers available in the literatures has also been presented. It is observed that the ultimate load of the beams retrofitted with GFRP fabrics increases with increase of number of GFRP layers up to a specific number of layers, i.e. 3 layers, beyond which it decreases.

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

PubMed

Yuan, Yuchen; Shi, Yi; Li, Changyang; Kim, Jinman; Cai, Weidong; Han, Zeguang; Feng, David Dagan

2016-12-23

With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types.

Workshop to develop deep-life continental scientific drilling projects

DOE PAGES

Kieft, T. L.; Onstott, T. C.; Ahonen, L.; ...

2015-05-29

The International Continental Scientific Drilling Program (ICDP) has long espoused studies of deep subsurface life, and has targeted fundamental questions regarding subsurface life, including the following: "(1) What is the extent and diversity of deep microbial life and what are the factors limiting it? (2) What are the types of metabolism/carbon/energy sources and the rates of subsurface activity? (3) How is deep microbial life adapted to subsurface conditions? (4) How do subsurface microbial communities affect energy resources? And (5) how does the deep biosphere interact with the geosphere and atmosphere?" (Horsfield et al., 2014) Many ICDP-sponsored drilling projects have includedmore » a deep-life component; however, to date, not one project has been driven by deep-life goals, in part because geomicrobiologists have been slow to initiate deep biosphere-driven ICDP projects. Therefore, the Deep Carbon Observatory (DCO) recently partnered with the ICDP to sponsor a workshop with the specific aim of gathering potential proponents for deep-life-driven ICDP projects and ideas for candidate drilling sites. Twenty-two participants from nine countries proposed projects and sites that included compressional and extensional tectonic environments, evaporites, hydrocarbon-rich shales, flood basalts, Precambrian shield rocks, subglacial and subpermafrost environments, active volcano–tectonic systems, megafan deltas, and serpentinizing ultramafic environments. The criteria and requirements for successful ICDP applications were presented. Deep-life-specific technical requirements were discussed and it was concluded that, while these procedures require adequate planning, they are entirely compatible with the sampling needs of other disciplines. As a result of this workshop, one drilling workshop proposal on the Basin and Range Physiographic Province (BRPP) has been submitted to the ICDP, and several other drilling project proponents plan to submit proposals for ICDP-sponsored drilling workshops in 2016.« less

Sensory processing of deep tissue nociception in the rat spinal cord and thalamic ventrobasal complex.

PubMed

Sikandar, Shafaq; West, Steven J; McMahon, Stephen B; Bennett, David L; Dickenson, Anthony H

2017-07-01

Sensory processing of deep somatic tissue constitutes an important component of the nociceptive system, yet associated central processing pathways remain poorly understood. Here, we provide a novel electrophysiological characterization and immunohistochemical analysis of neural activation in the lateral spinal nucleus (LSN). These neurons show evoked activity to deep, but not cutaneous, stimulation. The evoked responses of neurons in the LSN can be sensitized to somatosensory stimulation following intramuscular hypertonic saline, an acute model of muscle pain, suggesting this is an important spinal relay site for the processing of deep tissue nociceptive inputs. Neurons of the thalamic ventrobasal complex (VBC) mediate both cutaneous and deep tissue sensory processing, but in contrast to the lateral spinal nucleus our electrophysiological studies do not suggest the existence of a subgroup of cells that selectively process deep tissue inputs. The sensitization of polymodal and thermospecific VBC neurons to mechanical somatosensory stimulation following acute muscle stimulation with hypertonic saline suggests differential roles of thalamic subpopulations in mediating cutaneous and deep tissue nociception in pathological states. Overall, our studies at both the spinal (lateral spinal nucleus) and supraspinal (thalamic ventrobasal complex) levels suggest a convergence of cutaneous and deep somatosensory inputs onto spinothalamic pathways, which are unmasked by activation of muscle nociceptive afferents to produce consequent phenotypic alterations in spinal and thalamic neural coding of somatosensory stimulation. A better understanding of the sensory pathways involved in deep tissue nociception, as well as the degree of labeled line and convergent pathways for cutaneous and deep somatosensory inputs, is fundamental to developing targeted analgesic therapies for deep pain syndromes. © 2017 University College London. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

Does a conservative tibial cut in conventional total knee arthroplasty violate the deep medial collateral ligament?

PubMed

Maes, Michael; Luyckx, Thomas; Bellemans, Johan

2014-11-01

Based on the anatomy of the deep medial collateral ligament (MCL), it was hypothesized that at least part of its cross-sectional insertion area is jeopardized while performing a standard tibial cut in conventional total knee arthroplasty (TKA). The aim of this study was to determine whether it is anatomically possible to preserve the tibial deep MCL insertion during conventional TKA. Thirty-three unpaired cadaveric knee specimens were used for this study. Knees with severe varus/valgus deformity or damage to the medial structures of the knee were excluded. In the first part of the study, the dimensions of the tibial insertion of the deep MCL and its relationship to the joint line were recorded. Next, the cross-sectional area of the deep MCL insertion was determined using calibrated digital photographic analysis. In the second part, the effect of a standard 9-mm 3° sloped tibial cut on the structural integrity of the deep MCL cross-sectional insertion area was determined using conventional instrumentation. The proximal border of the deep MCL insertion site on the tibia was located on average 4.7 ± 1.2 mm distally to the joint line. After performing a standard 9-mm 3° sloped tibial cut, on average 54% of the deep MCL insertion area was resected. In 29% of the cases, the deep MCL insertion area was completely excised. The deep MCL cannot routinely be preserved in conventional TKA. The deep MCL insertion is at risk and may be jeopardized in case of a tibial cut 9 mm below the native joint line. As the deep MCL is a distinct medial stabilizer and plays an important role in rotational stability, this may have implications in future designs of both unicondylar and total knee arthroplasty, but further research is necessary.

One hundred years of hydrographic measurements in the Baltic Sea

NASA Astrophysics Data System (ADS)

Fonselius, Stig; Valderrama, Jorge

2003-06-01

The first measurements of salinity of the deep water in the open Baltic Sea were made in the last decades of the 1800s. At a Scandinavian science meeting in Copenhagen in 1892, Professor Otto Pettersson from Sweden suggested that regular measurements of hydrographic parameters should be carried out at some important deep stations in the Baltic Sea. His suggestion was adopted and since that time we have rather complete hydrographical data from the Bornholm Deep, the Gotland Deep, and the Landsort Deep and from some stations in the Gulf of Bothnia. The measurements were interrupted in the Baltic Proper during the two World Wars. At the beginning only salinity, temperature and dissolved oxygen were measured and one or two expeditions were carried out annually, mostly in summer. In the 1920s also alkalinity and pH were occasionally measured and total carbonate was calculated. A few nutrient measurements were also carried out. After World War II we find results from four or more expeditions every year and intercalibration of methods was arranged. Results of temperature, salinity and dissolved oxygen measurements from the Bornholm Deep, the Gotland Deep, the Landsort Deep and salinity measurements from three stations in the Gulf of Bothnia, covering the whole 20th century are presented and discussed. The salinity distribution and the variations between oxygen and hydrogen sulphide periods in the deep water of the Gotland Deep and the Landsort Deep are demonstrated. Series of phosphate and nitrate distribution in the Gotland Deep are shown from the 1950s to the present and the effects of the stagnant conditions are briefly discussed. Two large inflows of highly saline water, the first during the First World War and the second in 1951, are demonstrated. The 20th century minimum salinity of the bottom water in the Baltic Proper in 1992 is discussed.

Deep South Atlantic carbonate chemistry and increased interocean deep water exchange during last deglaciation

NASA Astrophysics Data System (ADS)

Yu, Jimin; Anderson, Robert F.; Jin, Zhangdong; Menviel, Laurie; Zhang, Fei; Ryerson, Fredrick J.; Rohling, Eelco J.

2014-04-01

Carbon release from the deep ocean at glacial terminations is a critical component of past climate change, but the underlying mechanisms remain poorly understood. We present a 28,000-year high-resolution record of carbonate ion concentration, a key parameter of the global carbon cycle, at 5-km water depth in the South Atlantic. We observe similar carbonate ion concentrations between the Last Glacial Maximum and the late Holocene, despite elevated concentrations in the glacial surface ocean. This strongly supports the importance of respiratory carbon accumulation in a stratified deep ocean for atmospheric CO2 reduction during the last ice age. After ˜9 μmol/kg decline during Heinrich Stadial 1, deep South Atlantic carbonate ion concentration rose by ˜24 μmol/kg from the onset of Bølling to Pre-boreal, likely caused by strengthening North Atlantic Deep Water formation (Bølling) or increased ventilation in the Southern Ocean (Younger Drays) or both (Pre-boreal). The ˜15 μmol/kg decline in deep water carbonate ion since ˜10 ka is consistent with extraction of alkalinity from seawater by deep-sea CaCO3 compensation and coral reef growth on continental shelves during the Holocene. Between 16,600 and 15,000 years ago, deep South Atlantic carbonate ion values converged with those at 3.4-km water depth in the western equatorial Pacific, as did carbon isotope and radiocarbon values. These observations suggest a period of enhanced lateral exchange of carbon between the deep South Atlantic and Pacific Oceans, probably due to an increased transfer of momentum from southern westerlies to the Southern Ocean. By spreading carbon-rich deep Pacific waters around Antarctica for upwelling, invigorated interocean deep water exchange would lead to more efficient CO2 degassing from the Southern Ocean, and thus to an atmospheric CO2 rise, during the early deglaciation.

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

PubMed

Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

2018-04-11

The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes by using deep learning on high-dimensional and small-scale biology data.

Advances in deep-sea biology: biodiversity, ecosystem functioning and conservation. An introduction and overview

NASA Astrophysics Data System (ADS)

Cunha, Marina R.; Hilário, Ana; Santos, Ricardo S.

2017-03-01

Once considered as monotonous and devoid of life, the deep sea was revealed during the last century as an environment with a plethora of life forms and extremely high species richness (Rex and Etter, 2010). Underwater vehicle developments allowed direct observations of the deep, disclosing unique habitats and diverse seascapes, and other technological advances enabled manipulative experimentation and unprecedented prospects to pursue novel research topics (Levin and Sibuet, 2012; Danovaro et al., 2014). Alongside, the growing human population greatly increased the pressure on deep-sea ecosystems and the services they provide (Ramirez-Llodra et al., 2011; Thurber et al., 2014; Levin et al., 2016). Societal changes further intensified worldwide competition for natural resources, extending the present footprint of impacts over most of the global ocean (Halpern et al., 2008). In this socio-economic context, and in tandem with cutting edge technological advances and an unclear legal framework to regulate access to natural resources (Boyes and Elliott, 2014), the deep sea has emerged as a new opportunity for industrial exploitation and novel economic activities. The expanding use of the deep sea prompted a rapid reply from deep-sea scientists that recommended "a move from a frontier mentality of exploitation and single-sector management to a precautionary system that balances use of living marine resources, energy, and minerals from the deep ocean with maintenance of a productive and healthy marine environment, while improving knowledge and collaboration" and proposed "three directions to advance deep-ocean stewardship: i) protection and mitigation, ii) research, and iii) collaborative governance" (Mengerink et al., 2014). The European Marine Board position paper 22 (Rogers et al., 2015) further examined the key societal and environmental drivers confronting the deep sea and the role of deep-sea research to deliver future knowledge needs for science and society; a clear and consistent message from consultation with wider stakeholders was the need for fundamental knowledge of deep-sea ecosystems. Enhanced deep-sea knowledge is crucial to establish baselines and assess long term impact of human activity on ecosystems and it is also instrumental to inform environmental impact assessments, strategic management plans, effective decision making, environmental regulation and ocean governance (Rogers et al., 2015).

Deep Learning as an Individual, Conditional, and Contextual Influence on First-Year Student Outcomes

ERIC Educational Resources Information Center

Reason, Robert D.; Cox, Bradley E.; McIntosh, Kadian; Terenzini, Patrick T.

2010-01-01

For years, educators have drawn a distinction between deep cognitive processing and surface-level cognitive processing, with the former resulting in greater learning. In recent years, researchers at NSSE have created DEEP Learning scales, which consist of items related to students' experiences which are believed to encourage deep processing. In…

Demonstration of Remotely Operated Vehicles to Aid Underwater Inspection of Corps of Engineers Navigation Structures. Winfield Locks and Dam 13-17 August 2007

DTIC Science & Technology

2008-09-01

2 Deep Ocean Engineering Triggerfish ...Figures Figure 1. Deep Ocean Engineering Triggerfish ROV carried by two divers (top)................................... 4 Figure 2. SeaBotix...the physical parameters and approximate costs of the systems as tested. Deep Ocean Engineering Triggerfish Figure 1 shows the Deep Ocean

Deep Time Framework: A Preliminary Study of U.K. Primary Teachers' Conceptions of Geological Time and Perceptions of Geoscience.

ERIC Educational Resources Information Center

Trend, Roger David

2001-01-01

Studies (n=51) inservice school teachers with regard to their orientations toward geoscience phenomena in general and deep time in particular. Aims to identify the nature of idiosyncratic conceptions of deep time and propose a curricular Deep Time Framework for teacher education. (Contains 29 references.) (Author/YDS)

75 FR 38939 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Catcher...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-07

.... 0910131362-0087-02] RIN 0648-XX33 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...; closure. SUMMARY: NMFS is prohibiting directed fishing for species that comprise the deep-water species... Pacific halibut prohibited species catch (PSC) sideboard limit specified for the deep-water species...

75 FR 49420 - Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-13

.... 100513223-0289-02] RIN 0648-AY88 Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic Deep-Sea Red Crab Specifications In- season Adjustment AGENCY: National Marine...-sea (DAS) allocation for the Atlantic deep- sea red crab fishery that were implemented in May 2010...

75 FR 7435 - Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-19

.... 100105009-0053-01] 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... comments. SUMMARY: NMFS proposes 2010 specifications for the Atlantic deep-sea red crab fishery, including...

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...

The Deep Space Network: A Radio Communications Instrument for Deep Space Exploration

NASA Technical Reports Server (NTRS)

Renzetti, N. A.; Stelzried, C. T.; Noreen, G. K.; Slobin, S. D.; Petty, S. M.; Trowbridge, D. L.; Donnelly, H.; Kinman, P. W.; Armstrong, J. W.; Burow, N. A.

1983-01-01

The primary purpose of the Deep Space Network (DSN) is to serve as a communications instrument for deep space exploration, providing communications between the spacecraft and the ground facilities. The uplink communications channel provides instructions or commands to the spacecraft. The downlink communications channel provides command verification and spacecraft engineering and science instrument payload data.

Document Analyses of Student Use of a Blogging-Mapping Tool to Explore Evidence of Deep and Reflective Learning

ERIC Educational Resources Information Center

Xie, Ying

2008-01-01

Theories about reflective thinking and deep-surface learning abound. In order to arrive at the definition for "reflective thinking toward deep learning," this study establishes that reflective thinking toward deep learning refers to a learner's purposeful and conscious activity of manipulating ideas toward meaningful learning and knowledge…

The Network Concept of Creativity and Deep Thinking: Applications to Social Opinion Formation and Talent Support

ERIC Educational Resources Information Center

Csermely, Peter

2017-01-01

Our century has unprecedented new challenges, which need creative solutions and deep thinking. Contemplative, deep thinking became an "endangered species" in our rushing world of Tweets, elevator pitches, and fast decisions. Here, we describe how important aspects of both creativity and deep thinking can be understood as network…

33 CFR 207.640 - Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Sacramento Deep Water Ship... REGULATIONS § 207.640 Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and navigation. (a) Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use...

33 CFR 207.640 - Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Sacramento Deep Water Ship... REGULATIONS § 207.640 Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and navigation. (a) Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use...

33 CFR 207.640 - Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Sacramento Deep Water Ship... REGULATIONS § 207.640 Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use, administration, and navigation. (a) Sacramento Deep Water Ship Channel Barge Lock and Approach Canals; use...

Deep space communication - Past, present, and future

NASA Technical Reports Server (NTRS)

Posner, E. C.; Stevens, R.

1984-01-01

This paper reviews the progress made in deep space communication from its beginnings until now, describes the development and applications of NASA's Deep Space Network, and indicates directions for the future. Limiting factors in deep space communication are examined using the upcoming Voyager encounter with Uranus, centered on the downlink telemetry from spacecraft to earth, as an example. A link calculation for Voyager at Uranus over Australia is exhibited. Seven basic deep space communication functions are discussed, and technical aspects of spacecraft communication equipment, ground antennas, and ground electronics and processing are considered.

DeepSig: deep learning improves signal peptide detection in proteins.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita

2018-05-15

The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. pierluigi.martelli@unibo.it. Supplementary data are available at Bioinformatics online.

The Deep Space Network, volume 17

NASA Technical Reports Server (NTRS)

1973-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.

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.

An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

PubMed

Park, Seong-Wook; Park, Junyoung; Bong, Kyeongryeol; Shin, Dongjoo; Lee, Jinmook; Choi, Sungpill; Yoo, Hoi-Jun

2015-12-01

Deep Learning algorithm is widely used for various pattern recognition applications such as text recognition, object recognition and action recognition because of its best-in-class recognition accuracy compared to hand-crafted algorithm and shallow learning based algorithms. Long learning time caused by its complex structure, however, limits its usage only in high-cost servers or many-core GPU platforms so far. On the other hand, the demand on customized pattern recognition within personal devices will grow gradually as more deep learning applications will be developed. This paper presents a SoC implementation to enable deep learning applications to run with low cost platforms such as mobile or portable devices. Different from conventional works which have adopted massively-parallel architecture, this work adopts task-flexible architecture and exploits multiple parallelism to cover complex functions of convolutional deep belief network which is one of popular deep learning/inference algorithms. In this paper, we implement the most energy-efficient deep learning and inference processor for wearable system. The implemented 2.5 mm × 4.0 mm deep learning/inference processor is fabricated using 65 nm 8-metal CMOS technology for a battery-powered platform with real-time deep inference and deep learning operation. It consumes 185 mW average power, and 213.1 mW peak power at 200 MHz operating frequency and 1.2 V supply voltage. It achieves 411.3 GOPS peak performance and 1.93 TOPS/W energy efficiency, which is 2.07× higher than the state-of-the-art.

Deep-sea macrourid fishes scavenge on plant material: Evidence from in situ observations

NASA Astrophysics Data System (ADS)

Jeffreys, Rachel M.; Lavaleye, Marc S. S.; Bergman, Magda J. N.; Duineveld, Gerard C. A.; Witbaard, Rob; Linley, Thom

2010-04-01

Deep-sea benthic communities primarily rely on an allochthonous food source. This may be in the form of phytodetritus or as food falls e.g. sinking carcasses of nekton or debris of marine macrophyte algae. Deep-sea macrourids are the most abundant demersal fish in the deep ocean. Macrourids are generally considered to be the apex predators/scavengers in deep-sea communities. Baited camera experiments and stable isotope analyses have demonstrated that animal carrion derived from the surface waters is an important component in the diets of macrourids; some macrourid stomachs also contained vegetable/plant material e.g. onion peels, oranges, algae. The latter observations led us to the question: is plant material an attractive food source for deep-sea scavenging fish? We simulated a plant food fall using in situ benthic lander systems equipped with a baited time-lapse camera. Abyssal macrourids and cusk-eels were attracted to the bait, both feeding vigorously on the bait, and the majority of the bait was consumed in <30 h. These observations indicate (1) plant material can produce an odour plume similar to that of animal carrion and attracts deep-sea fish, and (2) deep-sea fish readily eat plant material. This represents to our knowledge the first in situ documentation of deep-sea fish ingesting plant material and highlights the variability in the scavenging nature of deep-sea fishes. This may have implications for food webs in areas where macrophyte/seagrass detritus is abundant at the seafloor e.g. canyon systems and continental shelves close to seagrass meadows (Bahamas and Mediterranean).

Evidence for Extending the Duration of Chemoprophylaxis following Free Flap Harvest from the Lower Extremity: Prospective Screening for Deep Venous Thrombosis.

PubMed

Rau, Aline S; Harry, Brian L; Leem, Ted H; Song, John I; Deleyiannis, Frederic W-B

2016-08-01

The purpose of this study was to investigate the incidence of symptomatic and asymptomatic deep venous thrombosis in patients undergoing harvest of a free flap from the lower extremity who were receiving standard chemoprophylaxis while hospitalized. A retrospective review of 65 consecutive patients undergoing surgery between 2011 and 2013 was performed to determine the incidence of symptomatic deep venous thrombosis. These patients were screened for deep venous thrombosis based on development of symptoms. Prospective evaluation of a similar consecutive population of 37 patients between 2014 and 2015 was then performed to determine the incidence of asymptomatic deep venous thrombosis. These patients underwent routine duplex ultrasonography of both legs at postoperative weeks 1 and 4. Symptomatic deep venous thrombosis occurred in 2.9 percent of all patients. In the prospective cohort, 8.1 percent of the patients were found to have an acute deep venous thrombosis by postoperative week 1. At postoperative week 4, 16.7 percent of the patients developed a new, acute deep venous thrombosis. The estimated costs of screening and treating deep venous thrombosis in the retrospective group and the prospective group were $222 and $2259, respectively. The cost of routine chemoprophylaxis without duplex screening for an additional 14 days after discharge was $125 per patient. The rate of asymptomatic deep venous thrombosis may be much higher than previously appreciated in this population of very high-risk patients, especially during the 2 weeks after discharge. Extending the duration of chemoprophylaxis to 4 weeks after surgery may be warranted. Therapeutic, IV.

Climate, carbon cycling, and deep-ocean ecosystems.

PubMed

Smith, K L; Ruhl, H A; Bett, B J; Billett, D S M; Lampitt, R S; Kaufmann, R S

2009-11-17

Climate variation affects surface ocean processes and the production of organic carbon, which ultimately comprises the primary food supply to the deep-sea ecosystems that occupy approximately 60% of the Earth's surface. Warming trends in atmospheric and upper ocean temperatures, attributed to anthropogenic influence, have occurred over the past four decades. Changes in upper ocean temperature influence stratification and can affect the availability of nutrients for phytoplankton production. Global warming has been predicted to intensify stratification and reduce vertical mixing. Research also suggests that such reduced mixing will enhance variability in primary production and carbon export flux to the deep sea. The dependence of deep-sea communities on surface water production has raised important questions about how climate change will affect carbon cycling and deep-ocean ecosystem function. Recently, unprecedented time-series studies conducted over the past two decades in the North Pacific and the North Atlantic at >4,000-m depth have revealed unexpectedly large changes in deep-ocean ecosystems significantly correlated to climate-driven changes in the surface ocean that can impact the global carbon cycle. Climate-driven variation affects oceanic communities from surface waters to the much-overlooked deep sea and will have impacts on the global carbon cycle. Data from these two widely separated areas of the deep ocean provide compelling evidence that changes in climate can readily influence deep-sea processes. However, the limited geographic coverage of these existing time-series studies stresses the importance of developing a more global effort to monitor deep-sea ecosystems under modern conditions of rapidly changing climate.

Deep learning for computational chemistry

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

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

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

Deep-brain-stimulation does not impair deglutition in Parkinson's disease.

PubMed

Lengerer, Sabrina; Kipping, Judy; Rommel, Natalie; Weiss, Daniel; Breit, Sorin; Gasser, Thomas; Plewnia, Christian; Krüger, Rejko; Wächter, Tobias

2012-08-01

A large proportion of patients with Parkinson's disease develop dysphagia during the course of the disease. Dysphagia in Parkinson's disease affects different phases of deglutition, has a strong impact on quality of life and may cause severe complications, i.e., aspirational pneumonia. So far, little is known on how deep-brain-stimulation of the subthalamic nucleus influences deglutition in PD. Videofluoroscopic swallowing studies on 18 patients with Parkinson's disease, which had been performed preoperatively, and postoperatively with deep-brain-stimulation-on and deep-brain-stimulation-off, were analyzed retrospectively. The patients were examined in each condition with three consistencies (viscous, fluid and solid). The 'New Zealand index for multidisciplinary evaluation of swallowing (NZIMES) Subscale One' for qualitative and 'Logemann-MBS-Parameters' for quantitative evaluation were assessed. Preoperatively, none of the patients presented with clinically relevant signs of dysphagia. While postoperatively, the mean daily levodopa equivalent dosage was reduced by 50% and deep-brain-stimulation led to a 50% improvement in motor symptoms measured by the UPDRS III, no clinically relevant influence of deep-brain-stimulation-on swallowing was observed using qualitative parameters (NZIMES). However quantitative parameters (Logemann scale) found significant changes of pharyngeal parameters with deep-brain-stimulation-on as compared to preoperative condition and deep-brain-stimulation-off mostly with fluid consistency. In Parkinson patients without dysphagia deep-brain-stimulation of the subthalamic nucleus modulates the pharyngeal deglutition phase but has no clinically relevant influence on deglutition. Further studies are needed to test if deep-brain-stimulation is a therapeutic option for patients with swallowing disorders. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effect of Minerals on Intestinal IgA Production Using Deep Sea Water Drinks.

PubMed

Shiraishi, Hisashi; Fujino, Maho; Shirakawa, Naoki; Ishida, Nanao; Funato, Hiroki; Hirata, Ayumu; Abe, Noriaki; Iizuka, Michiro; Jobu, Kohei; Yokota, Junko; Miyamura, Mitsuhiko

2017-01-01

Minerals are essential for life, as they are a vital part of protein constituents, enzyme cofactors, and other components in living organisms. Deep sea water is characterized by its cleanliness and stable low temperature, and its possible health- and medical benefits are being studied. However, no study has yet evaluated the physical properties of the numerous commercially available deep sea water products, which have varying water sources and production methods. We analyzed these products' mineral content and investigated their effect on living organism, focusing on immune functions, and investigated the relation between physiological immunoactivities and mineral intake. We qualitatively analyzed the mineral compositions of the deep sea water drinks and evaluated the drinks' physical properties using principal component analysis, a type of multivariate analysis, of their mineral content. We create an iron and copper-deficient rat model and administered deep sea water drinks for 8 weeks. We then measured their fecal immunoglobulin A (IgA) to evaluate immune function. Principal component analysis suggested that physical properties of deep sea water drinks could be determined by their sources. Administration of deep sea water drinks increased fecal IgA, thus tending to stimulate immune function, but the extent of this effect varied by drink. Of the minerals contained in deep sea water, iron showed positive correlations with the fecal IgA. The principal component analysis used in this study is suitable for evaluating deep sea water containing many minerals, and our results form a useful basis for comparative evaluations of deep sea water's bioactivity.

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.

Deep Pyriform Space: Anatomical Clarifications and Clinical Implications.

PubMed

Surek, Christopher K; Vargo, James; Lamb, Jerome

2016-07-01

The purpose of this study was to define the anatomical boundaries, transformation in the aging face, and clinical implications of the Ristow space. The authors propose a title of deep pyriform space for anatomical continuity. The deep pyriform space was dissected in 12 hemifacial fresh cadaver dissections. Specimens were divided into three separate groups. For group 1, dimensions were measured and plaster molds were fashioned to evaluate shape and contour. For group 2, the space was injected percutaneously with dyed hyaluronic acid to examine proximity relationships to adjacent structures. For group 3, the space was pneumatized to evaluate its cephalic extension. The average dimensions of the deep pyriform space are 1.1 × 0.9 cm. It is bounded medially by the depressor septi nasi and cradled laterally and superficially in a "half-moon" shape by the deep medial cheek fat and lip elevators. The angular artery courses on the roof of the space within a septum between the space and deep medial cheek fat. Pneumatization of the space traverses cephalic to the level of the tear trough ligament in a plane deep to the premaxillary space. The deep pyriform space is a midface cavity cradled by the pyriform aperture and deep medial cheek compartment. Bony recession of the maxilla with age predisposes this space for use as a potential area of deep volumization to support overlying cheek fat and draping lip elevators. The position of the angular artery in the roof of the space allows safe injection on the bone without concern for vascular injury.

Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss.

PubMed

Danovaro, Roberto; Gambi, Cristina; Dell'Anno, Antonio; Corinaldesi, Cinzia; Fraschetti, Simonetta; Vanreusel, Ann; Vincx, Magda; Gooday, Andrew J

2008-01-08

Recent investigations suggest that biodiversity loss might impair the functioning and sustainability of ecosystems. Although deep-sea ecosystems are the most extensive on Earth, represent the largest reservoir of biomass, and host a large proportion of undiscovered biodiversity, the data needed to evaluate the consequences of biodiversity loss on the ocean floor are completely lacking. Here, we present a global-scale study based on 116 deep-sea sites that relates benthic biodiversity to several independent indicators of ecosystem functioning and efficiency. We show that deep-sea ecosystem functioning is exponentially related to deep-sea biodiversity and that ecosystem efficiency is also exponentially linked to functional biodiversity. These results suggest that a higher biodiversity supports higher rates of ecosystem processes and an increased efficiency with which these processes are performed. The exponential relationships presented here, being consistent across a wide range of deep-sea ecosystems, suggest that mutually positive functional interactions (ecological facilitation) can be common in the largest biome of our biosphere. Our results suggest that a biodiversity loss in deep-sea ecosystems might be associated with exponential reductions of their functions. Because the deep sea plays a key role in ecological and biogeochemical processes at a global scale, this study provides scientific evidence that the conservation of deep-sea biodiversity is a priority for a sustainable functioning of the worlds' oceans.

Deep water characteristics and circulation in the South China Sea

NASA Astrophysics Data System (ADS)

Wang, Aimei; Du, Yan; Peng, Shiqiu; Liu, Kexiu; Huang, Rui Xin

2018-04-01

This study investigates the deep circulation in the South China Sea (SCS) using oceanographic observations combined with results from a bottom layer reduced gravity model. The SCS water, 2000 m below the surface, is quite different from that in the adjacent Pacific Ocean, and it is characterized by its low dissolved oxygen (DO), high temperature and low salinity. The horizontal distribution of deep water properties indicates a basin-scale cyclonic circulation driven by the Luzon overflow. The results of the bottom layer reduced gravity model are consistent with the existence of the cyclonic circulation in the deep SCS. The circulation is stronger at the northern/western boundary. After overflowing the sill of the Luzon Strait, the deep water moves broadly southwestward, constrained by the 3500 m isobath. The broadening of the southward flow is induced by the downwelling velocity in the interior of the deep basin. The main deep circulation bifurcates into two branches after the Zhongsha Islands. The southward branch continues flowing along the 3500 m isobath, and the eastward branch forms the sub-basin scale cyclonic circulation around the seamounts in the central deep SCS. The returning flow along the east boundary is fairly weak. The numerical experiments of the bottom layer reduced gravity model reveal the important roles of topography, bottom friction, and the upwelling/downwelling pattern in controlling the spatial structure, particularly the strong, deep western boundary current.

Meteorological variables associated with deep slab avalanches on persistent weak layers

USGS Publications Warehouse

Marienthal, Alex; Hendrikx, Jordy; Birkeland, Karl; Irvine, Kathryn M.

2014-01-01

Deep slab avalanches are a particularly challenging avalanche forecasting problem. These avalanches are typically difficult to trigger, yet when they are triggered they tend to propagate far and result in large and destructive avalanches. For this work we define deep slab avalanches as those that fail on persistent weak layers deeper than 0.9m (3 feet), and that occur after February 1st. We utilized a 44-year record of avalanche control and meteorological data from Bridger Bowl Ski Area to test the usefulness of meteorological variables for predicting deep slab avalanches. As in previous studies, we used data from the days preceding deep slab cycles, but we also considered meteorological metrics over the early months of the season. We utilized classification trees for our analyses. Our results showed warmer temperatures in the prior twenty-four hours and more loading over the seven days before days with deep slab avalanches on persistent weak layers. In line with previous research, extended periods of above freezing temperatures led to days with deep wet slab avalanches on persistent weak layers. Seasons with either dry or wet avalanches on deep persistent weak layers typically had drier early months, and often had some significant snow depth prior to those dry months. This paper provides insights for ski patrollers, guides, and avalanche forecasters who struggle to forecast deep slab avalanches on persistent weak layers late in the season.

Deep-water zooplankton in the Mediterranean Sea: Results from a continuous, synchronous sampling over different regions using sediment traps

NASA Astrophysics Data System (ADS)

Danovaro, R.; Carugati, L.; Boldrin, A.; Calafat, A.; Canals, M.; Fabres, J.; Finlay, K.; Heussner, S.; Miserocchi, S.; Sanchez-Vidal, A.

2017-08-01

Information on the dynamics of deep-sea biota is extremely scant particularly for long-term time series on deep-sea zooplankton. Here, we present the results of a deep-sea zooplankton investigation over one annual cycle based on samples from sediment trap moorings in three sub-basins along the Mediterranean Sea. Deep-sea zooplankton assemblages were dominated by copepods, as in shallow waters, only in the Adriatic Sea (>60% of total abundance), but not in the deep Ionian Sea, where ostracods represented >80%, neither in the deep Alboran Sea, where polychaetes were >70%. We found that deep-sea zooplankton assemblages: i) are subjected to changes in their abundance and structure over time, ii) are characterized by different dominant taxa in different basins, and iii) display clear taxonomic segregation between shallow and near-bottom waters. Zooplankton biodiversity decreases with increasing water depth, but the equitability increases. We suggest here that variations of zooplankton abundance and assemblage structure are likely influenced by the trophic condition characterizing the basins. Our findings provide new insights on this largely unknown component of the deep ocean, and suggest that changes in the export of organic matter from the photic zone, such as those expected as a consequence of global change, can significantly influence zooplankton assemblages in the largest biome on Earth.

A record of deep-ocean dissolved O2 from the oxidation state of iron in submarine basalts.

PubMed

Stolper, Daniel A; Keller, C Brenhin

2018-01-18

The oxygenation of the deep ocean in the geological past has been associated with a rise in the partial pressure of atmospheric molecular oxygen (O 2 ) to near-present levels and the emergence of modern marine biogeochemical cycles. It has also been linked to the origination and diversification of early animals. It is generally thought that the deep ocean was largely anoxic from about 2,500 to 800 million years ago, with estimates of the occurrence of deep-ocean oxygenation and the linked increase in the partial pressure of atmospheric oxygen to levels sufficient for this oxygenation ranging from about 800 to 400 million years ago. Deep-ocean dissolved oxygen concentrations over this interval are typically estimated using geochemical signatures preserved in ancient continental shelf or slope sediments, which only indirectly reflect the geochemical state of the deep ocean. Here we present a record that more directly reflects deep-ocean oxygen concentrations, based on the ratio of Fe 3+ to total Fe in hydrothermally altered basalts formed in ocean basins. Our data allow for quantitative estimates of deep-ocean dissolved oxygen concentrations from 3.5 billion years ago to 14 million years ago and suggest that deep-ocean oxygenation occurred in the Phanerozoic (541 million years ago to the present) and potentially not until the late Palaeozoic (less than 420 million years ago).

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.

A record of deep-ocean dissolved O2 from the oxidation state of iron in submarine basalts

NASA Astrophysics Data System (ADS)

Stolper, Daniel A.; Keller, C. Brenhin

2018-01-01

The oxygenation of the deep ocean in the geological past has been associated with a rise in the partial pressure of atmospheric molecular oxygen (O2) to near-present levels and the emergence of modern marine biogeochemical cycles. It has also been linked to the origination and diversification of early animals. It is generally thought that the deep ocean was largely anoxic from about 2,500 to 800 million years ago, with estimates of the occurrence of deep-ocean oxygenation and the linked increase in the partial pressure of atmospheric oxygen to levels sufficient for this oxygenation ranging from about 800 to 400 million years ago. Deep-ocean dissolved oxygen concentrations over this interval are typically estimated using geochemical signatures preserved in ancient continental shelf or slope sediments, which only indirectly reflect the geochemical state of the deep ocean. Here we present a record that more directly reflects deep-ocean oxygen concentrations, based on the ratio of Fe3+ to total Fe in hydrothermally altered basalts formed in ocean basins. Our data allow for quantitative estimates of deep-ocean dissolved oxygen concentrations from 3.5 billion years ago to 14 million years ago and suggest that deep-ocean oxygenation occurred in the Phanerozoic (541 million years ago to the present) and potentially not until the late Palaeozoic (less than 420 million years ago).

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

PubMed

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

De novo peptide sequencing by deep learning

PubMed Central

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

2017-01-01

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

The Making of Deep Impact

NASA Image and Video Library

2006-10-19

This image shows NASA Deep Impact spacecraft being built at Ball Aerospace & Technologies Corporation, Boulder, Colo. on July 2, 2005. The spacecraft impactor was released from Deep Impact flyby spacecraft.

The deep space network, volume 7

NASA Technical Reports Server (NTRS)

1972-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Space Flight Operations Facility are described.

Summer School in Deep Ecology.

ERIC Educational Resources Information Center

Macmillan, Catherine Hume

1995-01-01

Describes one teacher's experiences at the Institute for Deep Ecology Education (IDEE) Summer School in Applied Deep Ecology. Reviews the program offered and the focus on interactive, experiential activities. (LZ)

49 CFR 195.246 - Installation of pipe in a ditch.

Code of Federal Regulations, 2011 CFR

2011-10-01

... in a ditch must be installed in a manner that minimizes the introduction of secondary stresses and... waters less than 15 feet deep, all offshore pipe in water at least 12 feet deep (3.7 meters) but not more than 200 feet deep (61 meters) deep as measured from the mean low water must be installed so that the...

49 CFR 195.246 - Installation of pipe in a ditch.

Code of Federal Regulations, 2010 CFR

2010-10-01

... in a ditch must be installed in a manner that minimizes the introduction of secondary stresses and... waters less than 15 feet deep, all offshore pipe in water at least 12 feet deep (3.7 meters) but not more than 200 feet deep (61 meters) deep as measured from the mean low water must be installed so that the...

77 FR 46338 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Vessels Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-03

.... 111207737-2141-02] RIN 0648-XC142 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery by... apportionment of the Pacific halibut bycatch allowance specified for the deep-water species fishery in the GOA...

78 FR 30242 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Vessels Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-22

.... 120918468-3111-02] RIN 0648-XC675 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery by... apportionment of the Pacific halibut bycatch allowance specified for the deep-water species fishery in the GOA...

75 FR 38937 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Catcher...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-07

... directed fishing for the deep-water species fisheries. DATES: Effective 1200 hrs, Alaska local time (A.l.t.... 0910131362-0087-02] RIN 0648-XX32 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery for...

76 FR 39790 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Catcher...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-07

... directed fishing for the deep-water species fisheries. DATES: Effective 1200 hrs, Alaska local time (A.l.t.... 101126522-0640-02] RIN 0648-XA536 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery for...

75 FR 23189 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Vessels Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-03

.... 0910131362-0087-02] RIN 0648-XW20 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery by... apportionment of the Pacific halibut bycatch allowance specified for the deep-water species fishery in the GOA...

77 FR 24154 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Vessels Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-23

.... 111207737-2141-02] RIN 0648-XC001 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery by... apportionment of the Pacific halibut bycatch allowance specified for the deep-water species fishery in the GOA...

76 FR 23511 - Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species Fishery by Vessels Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-27

.... 101126522-0640-02] RIN 0648-XA394 Fisheries of the Economic Exclusive Zone Off Alaska; Deep-Water Species...: NMFS is prohibiting directed fishing for species that comprise the deep-water species fishery by... apportionment of the Pacific halibut bycatch allowance specified for the deep-water species fishery in the GOA...

75 FR 35435 - Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-22

.... 100513223-0254-01] RIN 0648-AY88 Fisheries of the Northeastern United States; Atlantic Deep-Sea Red Crab Fisheries; 2010 Atlantic Deep-Sea Red Crab Specifications In- season Adjustment AGENCY: National Marine... deep-sea red crab fishery, including a target total allowable catch (TAC) and a fleet-wide days-at-sea...

46 CFR 153.250 - Double-bottom and deep tanks as cargo tanks.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 5 2011-10-01 2011-10-01 false Double-bottom and deep tanks as cargo tanks. 153.250... Equipment Cargo Tanks § 153.250 Double-bottom and deep tanks as cargo tanks. Except in those cases in which Commandant (CG-522) specifically approves another arrangement, such as a double-bottom or deep tank as a...

46 CFR 153.250 - Double-bottom and deep tanks as cargo tanks.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 5 2013-10-01 2013-10-01 false Double-bottom and deep tanks as cargo tanks. 153.250... Equipment Cargo Tanks § 153.250 Double-bottom and deep tanks as cargo tanks. Except in those cases in which Commandant (CG-ENG) specifically approves another arrangement, such as a double-bottom or deep tank as a...

46 CFR 153.250 - Double-bottom and deep tanks as cargo tanks.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 5 2010-10-01 2010-10-01 false Double-bottom and deep tanks as cargo tanks. 153.250... Equipment Cargo Tanks § 153.250 Double-bottom and deep tanks as cargo tanks. Except in those cases in which Commandant (CG-522) specifically approves another arrangement, such as a double-bottom or deep tank as a...

46 CFR 153.250 - Double-bottom and deep tanks as cargo tanks.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 5 2014-10-01 2014-10-01 false Double-bottom and deep tanks as cargo tanks. 153.250... Equipment Cargo Tanks § 153.250 Double-bottom and deep tanks as cargo tanks. Except in those cases in which Commandant (CG-ENG) specifically approves another arrangement, such as a double-bottom or deep tank as a...

46 CFR 153.250 - Double-bottom and deep tanks as cargo tanks.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 5 2012-10-01 2012-10-01 false Double-bottom and deep tanks as cargo tanks. 153.250... Equipment Cargo Tanks § 153.250 Double-bottom and deep tanks as cargo tanks. Except in those cases in which Commandant (CG-ENG) specifically approves another arrangement, such as a double-bottom or deep tank as a...

The LCO/Gemini-South campaign for Deep Impact target Comet 9P/Tempel 1: Temporally resolved wide-field narrowband imaging results

NASA Astrophysics Data System (ADS)

Lederer, S. M.; Osip, D. J.; Thomas-Osip, J. E.; DeBuizer, J. M.; Mondragon, L. A.; Schweiger, D. L.; Viehweg, J.; SB Collaboration

2005-08-01

An extensive observing campaign to monitor Comet 9P/Tempel 1 will be conducted from 20 June to 19 July, 2005 at Las Campanas Observatory, Chile. These observations will precede and follow the impact of the Deep Impact projectile, which is likely to create a crater on the nucleus that will act as a fresh active area on the surface of the comet. Discreet nucleus active areas, believed to be the source of coma gas and dust jets, will likely result in changing morphology in the coma. We present the initial results of the wide-field narrowband visible imaging of the comet. Data will be taken with the 2.5m DuPont telescope from 27 June - 9 July, following the comet from 4 rotations prior to impact, to 4 rotations after impact using the narrowband Hale-Bopp filters, including CN, C2, and two continuum filters. These data will allow an accurate determination of the rotation state of the embedded nucleus immediately preceding the impact event as well as a measure of any changes to the rotation state due to the impact. In addition, modeling of these data will provide the total dust and gas production rates from the unaltered nucleus compared to the enhanced dust and gas emission from the newly created active region and freely sublimating pieces of mantle material ejected into the coma by the impactor. We will monitor temporal changes (on hours and days time-scales) in the morphology of both the gas and refractory components. We will use coma morphology studies to estimate the dust and gas outflow velocities and infer the presence of discreet nucleus source regions (pre- and post-impact). Of particular interest is the study of the gas-to-dust ratio and the ratio of the minor carbon species emitted from the newly created active region relative to the pre-impact coma environment.

A SYSTEMATIC SURVEY OF PROTOCLUSTERS AT z ∼ 3–6 IN THE CFHTLS DEEP FIELDS

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

Toshikawa, Jun; Kashikawa, Nobunari; Furusawa, Hisanori

2016-08-01

We present the discovery of three protoclusters at z ∼ 3–4 with spectroscopic confirmation in the Canada–France–Hawaii Telescope Legacy Survey Deep Fields. In these fields, we investigate the large-scale projected sky distribution of z ∼ 3–6 Lyman-break galaxies and identify 21 protocluster candidates from regions that are overdense at more than 4 σ overdensity significance. Based on cosmological simulations, it is expected that more than 76% of these candidates will evolve into a galaxy cluster of at least a halo mass of 10{sup 14} M {sub ⊙} at z = 0. We perform follow-up spectroscopy for eight of the candidatesmore » using Subaru/FOCAS, Keck II/DEIMOS, and Gemini-N/GMOS. In total we target 462 dropout candidates and obtain 138 spectroscopic redshifts. We confirm three real protoclusters at z = 3–4 with more than five members spectroscopically identified and find one to be an incidental overdense region by mere chance alignment. The other four candidate regions at z ∼ 5–6 require more spectroscopic follow-up in order to be conclusive. A z = 3.67 protocluster, which has 11 spectroscopically confirmed members, shows a remarkable core-like structure composed of a central small region (<0.5 physical Mpc) and an outskirts region (∼1.0 physical Mpc). The Ly α equivalent widths of members of the protocluster are significantly smaller than those of field galaxies at the same redshift, while there is no difference in the UV luminosity distributions. These results imply that some environmental effects start operating as early as at z ∼ 4 along with the growth of the protocluster structure. This study provides an important benchmark for our analysis of protoclusters in the upcoming Subaru/HSC imaging survey and its spectroscopic follow-up with the Subaru/PFS that will detect thousands of protoclusters up to z ∼ 6.« less

The SPT+Herschel+ALMA+Spitzer Legacy Survey: The stellar content of high redshift strongly lensed systems

NASA Astrophysics Data System (ADS)

Vieira, Joaquin; Ashby, Matt; Carlstrom, John; Chapman, Scott; DeBreuck, Carlos; Fassnacht, Chris; Gonzalez, Anthony; Phadke, Kedar; Marrone, Dan; Malkan, Matt; Reuter, Cassie; Rotermund, Kaja; Spilker, Justin; Weiss, Axel

2018-05-01

The South Pole Telescope (SPT) has systematically identified 90 high-redshift strongly gravitationally lensed submillimeter galaxies (SMGs) in a 2500 square-degree cosmological survey of the millimeter (mm) sky. These sources are selected by their extreme mm flux, which is largely independent of redshift and lensing configuration. We are undertaking a comprehensive and systematic followup campaign to use these "cosmic magnifying glasses" to study the infrared background in unprecedented detail, inform the condition of the interstellar medium in starburst galaxies at high redshift, and place limits on dark matter substructure. Here we ask for 115.4 hours of deep Spitzer/IRAC imaging to complete our survey of 90 systems to a uniform depth of 30min integrations at 3.6um and 60min at 4.5um. In our sample of 90 systems, 16 have already been fully observed, 30 have been partially observed, and 44 have not been observed at all. Our immediate goals are to: 1) constrain the specific star formation rates of the background high-redshift submillimeter galaxies by combining these Spitzer observations with our APEX, Herschel, and ALMA data, 2) robustly determine the stellar masses and mass-to-light ratios of all the foreground lensing galaxies in the sample by combining these observations with our VLT and Gemini data, the Dark Energy Survey, and ALMA; and 3) provide complete, deep, and uniform NIR coverage of our entire sample of lensed systems to characterize the environments of high redshift SMGs, maximize the discovery potential for additional spectacular and rare sources, and prepare for JWST. This program will provide the cornerstone data set for two PhD theses: Kedar Phadke at Illinois will lead the analysis of stellar masses for the background SMGs, and Kaja Rotermund at Dalhousie will lead the analysis of stellar masses for the foreground lenses.

A Systematic Survey of Protoclusters at z ~ 3-6 in the CFHTLS Deep Fields

NASA Astrophysics Data System (ADS)

Toshikawa, Jun; Kashikawa, Nobunari; Overzier, Roderik; Malkan, Matthew A.; Furusawa, Hisanori; Ishikawa, Shogo; Onoue, Masafusa; Ota, Kazuaki; Tanaka, Masayuki; Niino, Yuu; Uchiyama, Hisakazu

2016-08-01

We present the discovery of three protoclusters at z ˜ 3-4 with spectroscopic confirmation in the Canada-France-Hawaii Telescope Legacy Survey Deep Fields. In these fields, we investigate the large-scale projected sky distribution of z ˜ 3-6 Lyman-break galaxies and identify 21 protocluster candidates from regions that are overdense at more than 4σ overdensity significance. Based on cosmological simulations, it is expected that more than 76% of these candidates will evolve into a galaxy cluster of at least a halo mass of 1014 M ⊙ at z = 0. We perform follow-up spectroscopy for eight of the candidates using Subaru/FOCAS, Keck II/DEIMOS, and Gemini-N/GMOS. In total we target 462 dropout candidates and obtain 138 spectroscopic redshifts. We confirm three real protoclusters at z = 3-4 with more than five members spectroscopically identified and find one to be an incidental overdense region by mere chance alignment. The other four candidate regions at z ˜ 5-6 require more spectroscopic follow-up in order to be conclusive. A z = 3.67 protocluster, which has 11 spectroscopically confirmed members, shows a remarkable core-like structure composed of a central small region (<0.5 physical Mpc) and an outskirts region (˜1.0 physical Mpc). The Lyα equivalent widths of members of the protocluster are significantly smaller than those of field galaxies at the same redshift, while there is no difference in the UV luminosity distributions. These results imply that some environmental effects start operating as early as at z ˜ 4 along with the growth of the protocluster structure. This study provides an important benchmark for our analysis of protoclusters in the upcoming Subaru/HSC imaging survey and its spectroscopic follow-up with the Subaru/PFS that will detect thousands of protoclusters up to z ˜ 6.

On the Nature of Ultra-faint Dwarf Galaxy Candidates. I. DES1, Eridanus III, and Tucana V

NASA Astrophysics Data System (ADS)

Conn, Blair C.; Jerjen, Helmut; Kim, Dongwon; Schirmer, Mischa

2018-01-01

We use deep Gemini/GMOS-S g, r photometry to study the three ultra-faint dwarf galaxy candidates DES1, Eridanus III (Eri III), and Tucana V (Tuc V). Their total luminosities, M V (DES1) = ‑1.42 ± 0.50 and M V (Eri III) = ‑2.07 ± 0.50, and mean metallicities, [{Fe}/{{H}}]=-{2.38}-0.19+0.21 and [{Fe}/{{H}}]=-{2.40}-0.12+0.19, are consistent with them being ultra-faint dwarf galaxies, as they fall just outside the 1σ confidence band of the luminosity–metallicity relation for Milky Way satellite galaxies. However, their positions in the size–luminosity relation suggest that they are star clusters. Interestingly, DES1 and Eri III are at relatively large Galactocentric distances, with DES1 located at {D}{GC}=74+/- 4 {kpc} and Eri III at {D}{GC}=91+/- 4 {kpc}. In projection, both objects are in the tail of gaseous filaments trailing the Magellanic Clouds and have similar 3D separations from the Small Magellanic Cloud (SMC): {{Δ }}{D}{SMC,{DES}1}=31.7 kpc and {{Δ }}{D}{SMC,{Eri}{III}}=41.0 kpc, respectively. It is plausible that these stellar systems are metal-poor SMC satellites. Tuc V represents an interesting phenomenon in its own right. Our deep photometry at the nominal position of Tuc V reveals a low-level excess of stars at various locations across the GMOS field without a well-defined center. An SMC Northern Overdensity–like isochrone would be an adequate match to the Tuc V color–magnitude diagram, and the proximity to the SMC (12.°1 {{Δ }}{D}{SMC,{Tuc}{{V}}}=13 kpc) suggests that Tuc V is either a chance grouping of stars related to the SMC halo or a star cluster in an advanced stage of dissolution.

Frequency and morphology of tropical tropopause layer cirrus from CALIPSO observations: Are isolated cirrus different from those connected to deep convection?

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

Riihimaki, Laura D.; McFarlane, Sally A.

2010-09-16

Tropical Tropopause Layer cirrus (TTLC) profiles identified from CALIPSO LIDAR measurements are grouped into cloud objects and classified according to whether or not they are connected to deep convection. TTLC objects connected to deep convection are optically and physically thicker than isolated objects, consistent with what would be expected if connected objects were formed from convective detrainment and isolated objects formed in situ. In the tropics (±20 Latitude), 36% of TTLC profiles are classified as connected to deep convection, 43% as isolated, and the remaining 21% are part of lower, thicker cirrus clouds. Regions with higher occurence of deep convectionmore » also have higher occurrence of TTLC, and a greater percentage of those TTLC are connected to deep convection. Cloud top heights of both isolated and connected clouds are distributed similarly with respect to the height of the cold point tropopause. No difference in thickness or optical depth was found between TTLC above deep convection or above clear sky, though both cloud base and top heights are higher over deep convection than over clear sky.« less

Incidence of intravenous contrast extravasation: increased risk for patients with deep brachial catheter placement from the emergency department.

PubMed

Hardie, Andrew D; Kereshi, Borko

2014-06-01

Deep brachial intravenous catheter (IV) placement can be performed in emergency department patients with difficult vascular access, but the safety of deep brachial IV for iodinated contrast administration has not been assessed. This study compares the relative risk for extravasation of deep brachial IV compared with antecubital IV during power injected computed tomography (CT) examinations. A departmental practice quality improvement was performed to assess the rate of IV extravasation for all CT examinations during a 1 year period. De-identified data was analyzed with a waiver of informed consent to identify the rate and relative risk of iodinated contrast extravasation by catheter type. A total of 10,750 injections were performed, with 82 extravasation events (0.8 %). There were 51 extravasations of antecubital IV from approximately 8,599 placed (0.6 %). For 123 deep brachial IV placed, there were eight extravasations (6.5 %). The relative risk of a deep brachial IV extravasation was 9.4 compared to 0.4 for antecubital placement. Deep brachial IV demonstrated a markedly higher rate of contrast extravasation than antecubital IV. For power injected iodinated contrast administration, it is recommended to avoid the use of deep brachial IV whenever possible.

Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

2017-05-01

Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

PubMed

Wang, Duolin; Zeng, Shuai; Xu, Chunhui; Qiu, Wangren; Liang, Yanchun; Joshi, Trupti; Xu, Dong

2017-12-15

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction. We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data. MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep. xudong@missouri.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Automated analysis of high-content microscopy data with deep learning.

PubMed

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Numerical simulation of phenomenon on zonal disintegration in deep underground mining in case of unsupported roadway

NASA Astrophysics Data System (ADS)

Han, Fengshan; Wu, Xinli; Li, Xia; Zhu, Dekang

2018-02-01

Zonal disintegration phenomenon was found in deep mining roadway surrounding rock. It seriously affects the safety of mining and underground engineering and it may lead to the occurrence of natural disasters. in deep mining roadway surrounding rock, tectonic stress in deep mining roadway rock mass, horizontal stress is much greater than the vertical stress, When the direction of maximum principal stress is parallel to the axis of the roadway in deep mining, this is the main reasons for Zonal disintegration phenomenon. Using ABAQUS software to numerical simulation of the three-dimensional model of roadway rupture formation process systematically, and the study shows that when The Direction of maximum main stress in deep underground mining is along the roadway axial direction, Zonal disintegration phenomenon in deep underground mining is successfully reproduced by our numerical simulation..numerical simulation shows that using ABAQUA simulation can reproduce Zonal disintegration phenomenon and the formation process of damage of surrounding rock can be reproduced. which have important engineering practical significance.

Improvements of deep vein reflux following radiofrequency ablation for saphenous vein incompetence.

PubMed

Kim, Suh Min; Jung, In Mok; Chung, Jung Kee

2017-02-01

Objectives The aim of this study was to describe the changes of deep vein reflux after radiofrequency ablation for great saphenous vein incompetence. Method The data on 139 limbs which were treated with radiofrequency ablation for great saphenous vein incompetence were prospectively collected and reviewed. Results Deep vein reflux was present in 43 of 139 limbs (30.9%). There were no significant differences in the rate of successful closure, the incidence of procedure-related complications, and the improvements of symptoms and quality of life between the limbs with or without deep vein reflux. With a mean follow-up of 5.9 months, the peak reflux velocity and duration of reflux were improved in all limbs with deep vein reflux and it was completely corrected in 13 limbs (30.2%) after radiofrequency ablation. Conclusions The presence of deep vein reflux does not affect the treatment outcomes of radiofrequency ablation for great saphenous vein incompetence and is improved in all patients. Deep vein reflux is not a barrier to performing radiofrequency ablation.

A. V. Peyve — the founder of the concept of deep faults

NASA Astrophysics Data System (ADS)

Sherman, S. I.

2009-03-01

The further development of Peyve’s concept of deep faults in the Earth’s crust and brittle part of the lithosphere is discussed. Three aspects are accentuated in this paper: (1) the modern definition of the term deep fault; (2) the parameters of deep faults as ruptures of the geological medium and three-dimensional, often boundary, geological bodies; and (3) reactivation of deep faults, including the development of this process in real time. Peyve’s idea of deep faults readily fitted into the concept of new global tectonics (plate tectonics). This was facilitated, first of all, by the extensive efforts made to elaborate Peyve’s ideas by a large group of researchers at the Geological Institute of the Russian Academy of Sciences (GIN RAS) and other scientists. At present, the term deep fault has been extended and transformed to cover three-dimensional geological bodies; the geological and geophysical properties and parameters of these bodies, as well as their reactivation (recurrent activation) in real time, have been studied.

Deep levels in osmium doped p-type GaAs grown by metal organic chemical vapor deposition

NASA Astrophysics Data System (ADS)

Iqbal, M. Zafar; Majid, A.; Dadgar, A.; Bimberg, D.

2005-06-01

Results of a preliminary study on deep level transient spectroscopy (DLTS) investigations of osmium (Os) impurity in p-type GaAs, introduced in situ during MOCVD crystal growth, are reported for the first time. Os is clearly shown to introduce two prominent deep levels in the lower half-bandgap of GaAs at energy positions Ev + 0.42 eV (OsA) and Ev + 0.72 eV (OsB). A minority-carrier emitting defect feature observed in the upper half-bandgap is shown to consist of a band of Os-related deep levels with a concentration significantly higher than that of the majority carrier emitting deep levels. Detailed data on the emission rate signatures and related parameters of the Os-related deep levels are reported.

Deep crustal earthquakes associated with continental rifts

NASA Astrophysics Data System (ADS)

Doser, Diane I.; Yarwood, Dennis R.

1994-01-01

Deep (> 20 km) crustal earthquakes have occurred within or along the margins of at least four continental rift zones. The largest of these deep crustal earthquakes ( M ⩾ 5.0) have strike-slip or oblique-slip mechanisms with T-axes oriented similarly to those associated with shallow normal faulting within the rift zones. The majority of deep crustal earthquakes occur along the rift margins in regions that have cooler, thicker crust. Several deep crustal events, however, occur in regions of high heat flow. These regions also appear to be regions of high strain, a factor that could account for the observed depths. We believe the deep crustal earthquakes represent either the relative motion of rift zones with respect to adjacent stable regions or the propagation of rifting into stable regions.

A role for the deep orange and carnation eye color genes in lysosomal delivery in Drosophila.

PubMed

Sevrioukov, E A; He, J P; Moghrabi, N; Sunio, A; Krämer, H

1999-10-01

Deep orange and carnation are two of the classic eye color genes in Drosophila. Here, we demonstrate that Deep orange is part of a protein complex that localizes to endosomal compartments. A second component of this complex is Carnation, a homolog of Sec1p-like regulators of membrane fusion. Because complete loss of deep orange function is lethal, the role of this complex in intracellular trafficking was analyzed in deep orange mutant clones. Retinal cells devoid of deep orange function completely lacked pigmentation and exhibited exaggerated multivesicular structures. Furthermore, a defect in endocytic trafficking was visualized in developing photoreceptor cells. These results provide direct evidence that eye color mutations of the granule group also disrupt vesicular trafficking to lysosomes.

Deep Learning for Computer Vision: A Brief Review

PubMed Central

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

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

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.

PubMed

Hohman, Fred; Hodas, Nathan; Chau, Duen Horng

2017-05-01

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

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.

New pharmacokinetic methods. III. Two simple test for deep pool effect

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

Browne, T.R.; Greenblatt, D.J.; Schumacher, G.E.

1990-08-01

If a portion of administered drug is distributed into a deep peripheral compartment, the drug's actual elimination half-life during the terminal exponential phase of elimination may be longer than determined by a single dose study or a tracer dose study (deep pool effect). Two simple methods of testing for deep pool effect applicable to drugs with either linear or nonlinear pharmacokinetic properties are described. The methods are illustrated with stable isotope labeled (13C15N2) tracer dose studies of phenytoin. No significant (P less than .05) deep pool effect was detected.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.

PubMed

Funane, Tsukasa; Atsumori, Hirokazu; Katura, Takusige; Obata, Akiko N; Sato, Hiroki; Tanikawa, Yukari; Okada, Eiji; Kiguchi, Masashi

2014-01-15

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals. Copyright © 2013 Elsevier Inc. All rights reserved.

Development and applications of an acoustic package for deep-sea sub-bottom profiling and detailed seafloor imaging

NASA Astrophysics Data System (ADS)

Nishimura, Kiyokazu; Kisimoto, Kiyoyuki; Joshima, Masato; Arai, Kohsaku

In the deep-sea geological survey, good survey results are difficult to obtain by a conventional surface-towed acoustic survey system, because the horizontal resolution is limited due to the long distance between the sensor and the target (seafloor). In order to improve the horizontal resolution, a deep-tow system, which tows the sensor in the vicinity of seafloor, is most practical, and many such systems have been developed and used until today. It is not easy, however, to carry out a high-density survey in a small area by maneuvering the towing body altitude sufficiently close to the seafloor with rugged topography. A ROV (Remotely Operated Vehicle) can be used to solve this problem. The ROV makes a high-density 2D survey feasible because of its maneuverability, although a long-distance survey is difficult with it. Accordingly, we have developed an acoustic survey system installed on a ROV. The system named DAIPACK (Deep-sea Acoustic Imaging Package) consists of (1) a deep-sea sub-bottom profiler and (2) a deep-sea sidescan sonar. (1) Deep-sea sub-bottom profiler A light-weight and compact sub-bottom profiler for shallow water was chosen to improve and repackage for the deep sea usage. The system is composed of three units; a transducer, an electronic unit and a notebook computer for system control and data acquisition. The source frequency is 10kHz. To convert the system for the deep sea, the transducer was exchanged for the deep sea model, and the electronic unit was improved accordingly. The electronic unit and the notebook computer were installed in a spherical pressure vessel. (2) Deep-sea sidescan sonar We remodeled a compact shallow sea sidescan sonar(water depth limitation is 30m ) into a deep sea one. This sidescan sonar is composed of a sonar towfish (transducers and an electronic unit ), a cable and a notebook computer (data processor). To accommodate in the deep water, the transducers were remodeled into a high pressure resistance type, and the electronic unit and the computer unit were stored in a spherical pressure vessel. The frequency output of the sidescan sonar is 330kHz, and the ranging distance is variable from 15m to 120m (one side).

Research Possibilities Beyond Deep Space Gateway

NASA Astrophysics Data System (ADS)

Smitherman, D. V.; Needham, D. H.; Lewis, R.

2018-02-01

This abstract explores the possibilities for a large research facilities module attached to the Deep Space Gateway, using the same large module design and basic layout planned for the Deep Space Transport.

The Deep Space Network. [tracking and communication functions and facilities

NASA Technical Reports Server (NTRS)

1974-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.

Taoism and Deep Ecology.

ERIC Educational Resources Information Center

Sylvan, Richard; Bennett, David

1988-01-01

Contrasted are the philosophies of Deep Ecology and ancient Chinese. Discusses the cosmology, morality, lifestyle, views of power, politics, and environmental philosophies of each. Concludes that Deep Ecology could gain much from Taoism. (CW)

Theory of Semiconducting Superlattices and Microstructures

DTIC Science & Technology

1992-03-01

theory elucidated the various factors affecting deep levels, sets forth the conditions for obtaining shallow-deep transitions, and predicts that Si (a...theory elucidates the various factors affecting deep levels, sets forth the conditions for obtaining shallow-deep transitions, and predicts that Si (a...ondenotes the anion vacancy, which can be thought any quantitative theoretical factor are theof as originating from Column-O of the Period strengths of

Deep Space Network equipment performance, reliability, and operations management information system

NASA Technical Reports Server (NTRS)

Cooper, T.; Lin, J.; Chatillon, M.

2002-01-01

The Deep Space Mission System (DSMS) Operations Program Office and the DeepSpace Network (DSN) facilities utilize the Discrepancy Reporting Management System (DRMS) to collect, process, communicate and manage data discrepancies, equipment resets, physical equipment status, and to maintain an internal Station Log. A collaborative effort development between JPL and the Canberra Deep Space Communication Complex delivered a system to support DSN Operations.

The Deep Space Network. An instrument for radio navigation of deep space probes

NASA Technical Reports Server (NTRS)

Renzetti, N. A.; Jordan, J. F.; Berman, A. L.; Wackley, J. A.; Yunck, T. P.

1982-01-01

The Deep Space Network (DSN) network configurations used to generate the navigation observables and the basic process of deep space spacecraft navigation, from data generation through flight path determination and correction are described. Special emphasis is placed on the DSN Systems which generate the navigation data: the DSN Tracking and VLBI Systems. In addition, auxiliary navigational support functions are described.

The deep space network, volume 13

NASA Technical Reports Server (NTRS)

1973-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The deep space instrumentation facility, the ground communications facility, and the network control system are described. Other areas reported include: Helios Mission support, DSN support of the Mariner Mars 1971 extended mission, Mariner Venus/Mercury 1973 mission support, Viking mission support, radio science, tracking and ground-based navigation, network control and data processing, and deep space stations.

Corrosion-Fatigue Assessment Program

DTIC Science & Technology

2008-03-31

22 Figure 3.2.1-4 Deep -focus image of Specimen 598-7 – Crack 1...at Feature #2 .........................22 Figure 3.2.1-5 Deep -focus image of Specimen 598-7 – Crack 2 at Feature #5 .........................23...Figure 3.2.1-6 Deep -focus image of Specimen 598-7 – Crack 3 at Feature #3 .........................23 Figure 3.2.1-7 Deep -focus image of Specimen 598-7

Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets

DTIC Science & Technology

2015-04-24

Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Learning sparse feature representations is a useful instru- ment for solving an...novel framework for the classifi cation of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets... Learning Sparse Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Report Title Learning sparse feature representations is a useful

Deep Mapping the Biome: The Biology of Place in Don Gayton's "The Wheatgrass Mechanism" and John Janovy Jr.'s "Dunwoody Pond"

ERIC Educational Resources Information Center

Maher, Susan Naramore

2005-01-01

The term "deep map" is the invention of writer William Least Heat-Moon, whose extended essay "PrairyErth (a deep map)" has given definition to this form. Deep-map writing is marked by its intertextual, interdisciplinary, and multivocal nature. It is also self-consciously cartographic, presenting maps, following maps, and redrawing maps. Deep…

Quantitative Comparison of the in situ Microbial Communities in Different Biomes

DTIC Science & Technology

1995-09-01

70 60 50 40 [ a: 30 Ŕ ~ 20 10 o Neotrop. Neotrop_ Antartic . Antartic . -Deep Sea Deep Sea Austral. USA East West Surface 9·10 em...surface (n = 20) (21). ’" LL -’ a. " 2 𔃺 C w 2 ’" a. 60 50 40 30 20 10 o Neotrop. Neolrop. Antartic . Antartic . Deep Sea Deep Sea Austral

Deep vein thrombosis in hospitalized patients: a review of evidence-based guidelines for prevention.

PubMed

Kehl-Pruett, Wendy

2006-01-01

Deep vein thrombosis affects many hospitalized patients because of decreased activity and therapeutic equipment. This article reviews known risk factors for developing deep vein thrombosis, current prevention methods, and current evidence-based guidelines in order to raise nurses' awareness of early prevention methods in all hospitalized patients. Early prophylaxis can reduce patient risk of deep vein thrombosis and its complications.

77 FR 56791 - Main Hawaiian Islands Deep 7 Bottomfish Annual Catch Limits and Accountability Measures for 2012-13

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-14

... of the State's bottomfish restricted areas. The analyses in the most recent (2010) MHI Deep 7.... 120628195-2414-02] RIN 0648-XC089 Main Hawaiian Islands Deep 7 Bottomfish Annual Catch Limits and... specifies a quota of 325,000 lb of Deep 7 bottomfish in the main Hawaiian Islands for the 2012-13 fishing...

33 CFR 148.215 - What if a port has plans for a deep draft channel and harbor?

Code of Federal Regulations, 2010 CFR

2010-07-01

... General § 148.215 What if a port has plans for a deep draft channel and harbor? (a) If a State port will be directly connected by pipeline to a proposed deepwater port, and has existing plans for a deep... deep draft channel and harbor? 148.215 Section 148.215 Navigation and Navigable Waters COAST GUARD...

APL-UW Deep Water Propagation 2015-2017: Philippine Sea Data Analysis

DTIC Science & Technology

2015-09-30

DISTRIBUTION STATEMENT A: Approved for public release: distribution is unlimited APL-UW Deep Water Propagation 2015-2017: Philippine Sea Data...the fundamental statistics of broadband low-frequency acoustical signals evolve during propagation through a dynamically-varying deep ocean. OBJECTIVES...Current models of signal randomization over long ranges in the deep ocean were developed for and tested in the North Pacific Ocean gyre. The

Cosmopolitanism and Biogeography of the Genus Manganonema (Nematoda: Monhysterida) in the Deep Sea

PubMed Central

Zeppilli, Daniela; Vanreusel, Ann; Danovaro, Roberto

2011-01-01

Simple Summary The deep sea comprises more than 60% of the Earth surface, and likely represents the largest reservoir of as yet undiscovered biodiversity. Nematodes are the most abundant taxon on Earth and are particularly abundant and diverse in the deep sea. Nevertheless, knowledge of their biogeography especially in the deep sea is still at its infancy. This article explores the distribution of the genus Manganonema in the deep Atlantic Ocean and Mediterranean Sea providing new insights about this apparently rare deep-sea genus. Abstract Spatial patterns of species diversity provide information about the mechanisms that regulate biodiversity and are important for setting conservation priorities. Present knowledge of the biogeography of meiofauna in the deep sea is scarce. This investigation focuses on the distribution of the deep-sea nematode genus Manganonema, which is typically extremely rare in deep-sea sediment samples. Forty-four specimens of eight different species of this genus were recorded from different Atlantic and Mediterranean regions. Four out of the eight species encountered are new to science. We report here that this genus is widespread both in the Atlantic and in the Mediterranean Sea. These new findings together with literature information indicate that Manganonema is a cosmopolitan genus, inhabiting a variety of deep-sea habitats and oceans. Manganonema shows the highest diversity at water depths >4,000 m. Our data, therefore, indicate that this is preferentially an abyssal genus that is able, at the same time, to colonize specific habitats at depths shallower than 1,000 m. The analysis of the distribution of the genus Manganonema indicates the presence of large differences in dispersal strategies among different species, ranging from locally endemic to cosmopolitan. Lacking meroplanktonic larvae and having limited dispersal ability due to their small size, it has been hypothesized that nematodes have limited dispersal potential. However, the investigated deep-sea nematodes were present across different oceans covering macro-scale distances. Among the possible explanations (hydrological conditions, geographical and geological pathways, long-term processes, specific historical events), their apparent preference of colonizing highly hydrodynamic systems, could suggest that these infaunal organisms are transported by means of deep-sea benthic storms and turbidity currents over long distances. PMID:26486501

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.

[Effects of deep plowing time during the fallow period on water storage-consumption characteristics and wheat yield in dry-land soil.

PubMed

Dang, Jian You; Pei, Xue Xia; Zhang, Ding Yi; Wang, Jiao Ai; Zhang, Jing; Wu, Xue Ping

2016-09-01

Through a three-year field trail, effects of deep plowing time during the fallow period on water storage of 0-200 cm soil before sowing, water consumption of growth period, and growth and development of wheat were investigated. Results demonstrated that soil water storage (SWS) of the fallow period was influenced by deep plowing time, precipitation, and rainfall distribution. With postponing the time of deep plowing in the fallow period, SWS was increased firstly, and then decreased. SWS with deep plowing in early or middle of August was 23.9-45.8 mm more than that with deep plowing in mid-July. It would benefit SWS when more precipitation occurred in the fallow period or more rainfall was distributed in August and September. Deep plowing at a proper time could facilitate SWS, N and P absorption of wheat, and the number of stems before winter and the spike number. The yield of wheat with deep plowing in early or middle August was 3.67%-18.2% higher than that with deep plowing in mid-July, and it was positively correlated with water storage of 0-200 cm soil during the fallow period and SWS of each soil layer during the wheat growth period. However, this correlation coefficient would be weakened by adequate rainfall in spring, the critical growing period for wheat. The time of deep plowing mainly affected the water consumption at soil layer of 60-140 cm during wheat growth. Under current farming conditions of south Shanxi, the increased grain yield of wheat could be achieved by combining the measures of high wheat stubble and wheat straw covering for holding soil water and deep plowing between the Beginning of Autumn (August 6th) and the Limit of Heat (August 21st) for promoting soil water penetration characteristics to improve the number of stems before winter and spike.

Anatomical variations of the deep head of Cruveilhier of the flexor pollicis brevis and its significance for the evolution of the precision grip.

PubMed

Dunlap, Samuel S; Aziz, M Ashraf; Ziermann, Janine M

2017-01-01

Cruveilhier described in 1834 the human flexor pollicis brevis (FPB), a muscle of the thenar compartment, as having a superficial and a deep head, respectively, inserted onto the radial and ulnar sesamoids of the thumb. Since then, Cruveilhier's deep head has been controversially discussed. Often this deep head is confused with Henle's "interosseous palmaris volaris" or said to be a slip of the oblique adductor pollicis. In the 1960s, Day and Napier described anatomical variations of the insertions of Cruveilhier's deep head, including its absence, and hypothesized, that the shift of the deep head's insertion from ulnar to radial facilitated "true opposability" in anthropoids. Their general thesis for muscular arrangements underlying the power and precision grip is sound, but they did not delineate their deep head from Henle's muscle or the adductor pollicis, and their description of the attachments of Cruveilhier's deep head were too vague and not supported by a significant portion of the anatomical literature. Here, we reinvestigated Cruveilhier's deep head to resolve the controversy about it and because many newer anatomy textbooks do not describe this muscle, while it is often an obvious functionally (writing, texting, precision grip) and clinically significant thenar muscle. For the first time, we empirically delineated Cruveilhier's deep head from neighboring muscles with which it was previously confused. We observed 100% occurrence of the uncontested deep head in 80 human hands, displaying a similar variability of insertions as Day and Napier, but in significantly different numbers. Furthermore, we found variability in the origin and included as important landmarks the trapezoid and the ligamentum carpi radiatum. We tested the assertion regarding the evolutionary morphology and its role in the improvements in thumb movements during various precision grips. Our overall conclusions differ with respect to the developmental and evolutionary origin of the FPB heads.

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

Anatomical variations of the deep head of Cruveilhier of the flexor pollicis brevis and its significance for the evolution of the precision grip

PubMed Central

Aziz, M. Ashraf

2017-01-01

Cruveilhier described in 1834 the human flexor pollicis brevis (FPB), a muscle of the thenar compartment, as having a superficial and a deep head, respectively, inserted onto the radial and ulnar sesamoids of the thumb. Since then, Cruveilhier’s deep head has been controversially discussed. Often this deep head is confused with Henle’s “interosseous palmaris volaris” or said to be a slip of the oblique adductor pollicis. In the 1960s, Day and Napier described anatomical variations of the insertions of Cruveilhier’s deep head, including its absence, and hypothesized, that the shift of the deep head’s insertion from ulnar to radial facilitated “true opposability” in anthropoids. Their general thesis for muscular arrangements underlying the power and precision grip is sound, but they did not delineate their deep head from Henle’s muscle or the adductor pollicis, and their description of the attachments of Cruveilhier’s deep head were too vague and not supported by a significant portion of the anatomical literature. Here, we reinvestigated Cruveilhier’s deep head to resolve the controversy about it and because many newer anatomy textbooks do not describe this muscle, while it is often an obvious functionally (writing, texting, precision grip) and clinically significant thenar muscle. For the first time, we empirically delineated Cruveilhier’s deep head from neighboring muscles with which it was previously confused. We observed 100% occurrence of the uncontested deep head in 80 human hands, displaying a similar variability of insertions as Day and Napier, but in significantly different numbers. Furthermore, we found variability in the origin and included as important landmarks the trapezoid and the ligamentum carpi radiatum. We tested the assertion regarding the evolutionary morphology and its role in the improvements in thumb movements during various precision grips. Our overall conclusions differ with respect to the developmental and evolutionary origin of the FPB heads. PMID:29121048

Out of Their Depth? Isolated Deep Populations of the Cosmopolitan Coral Desmophyllum dianthus May Be Highly Vulnerable to Environmental Change

PubMed Central

Miller, Karen J.; Rowden, Ashley A.; Williams, Alan; Häussermann, Vreni

2011-01-01

Deep sea scleractinian corals will be particularly vulnerable to the effects of climate change, facing loss of up to 70% of their habitat as the Aragonite Saturation Horizon (below which corals are unable to form calcium carbonate skeletons) rises. Persistence of deep sea scleractinian corals will therefore rely on the ability of larvae to disperse to, and colonise, suitable shallow-water habitat. We used DNA sequence data of the internal transcribed spacer (ITS), the mitochondrial ribosomal subunit (16S) and mitochondrial control region (MtC) to determine levels of gene flow both within and among populations of the deep sea coral Desmophyllum dianthus in SE Australia, New Zealand and Chile to assess the ability of corals to disperse into different regions and habitats. We found significant genetic subdivision among the three widely separated geographic regions consistent with isolation and limited contemporary gene flow. Furthermore, corals from different depth strata (shallow <600 m, mid 1000–1500 m, deep >1500 m) even on the same or nearby seamounts were strongly differentiated, indicating limited vertical larval dispersal. Genetic differentiation with depth is consistent with the stratification of the Subantarctic Mode Water, Antarctic Intermediate Water, the Circumpolar Deep and North Pacific Deep Waters in the Southern Ocean, and we propose that coral larvae will be retained within, and rarely migrate among, these water masses. The apparent absence of vertical larval dispersal suggests deep populations of D. dianthus are unlikely to colonise shallow water as the aragonite saturation horizon rises and deep waters become uninhabitable. Similarly, assumptions that deep populations will act as refuges for shallow populations that are impacted by activities such as fishing or mining are also unlikely to hold true. Clearly future environmental management strategies must consider both regional and depth-related isolation of deep-sea coral populations. PMID:21611159

Understanding deep roots and their functions in ecosystems: an advocacy for more unconventional research

PubMed Central

Pierret, Alain; Maeght, Jean-Luc; Clément, Corentin; Montoroi, Jean-Pierre; Hartmann, Christian; Gonkhamdee, Santimaitree

2016-01-01

Background Deep roots are a common trait among a wide range of plant species and biomes, and are pivotal to the very existence of ecosystem services such as pedogenesis, groundwater and streamflow regulation, soil carbon sequestration and moisture content in the lower troposphere. Notwithstanding the growing realization of the functional significance of deep roots across disciplines such as soil science, agronomy, hydrology, ecophysiology or climatology, research efforts allocated to the study of deep roots remain incommensurate with those devoted to shallow roots. This is due in part to the fact that, despite technological advances, observing and measuring deep roots remains challenging. Scope Here, other reasons that explain why there are still so many fundamental unresolved questions related to deep roots are discussed. These include the fact that a number of hypotheses and models that are widely considered as verified and sufficiently robust are only partly supported by data. Evidence has accumulated that deep rooting could be a more widespread and important trait among plants than usually considered based on the share of biomass that it represents. Examples that indicate that plant roots have different structures and play different roles with respect to major biochemical cycles depending on their position within the soil profile are also examined and discussed. Conclusions Current knowledge gaps are identified and new lines of research for improving our understanding of the processes that drive deep root growth and functioning are proposed. This ultimately leads to a reflection on an alternative paradigm that could be used in the future as a unifying framework to describe and analyse deep rooting. Despite the many hurdles that pave the way to a practical understanding of deep rooting functions, it is anticipated that, in the relatively near future, increased knowledge about the deep rooting traits of a variety of plants and crops will have direct and tangible influence on how we manage natural and cultivated ecosystems. PMID:27390351

Deep breathing after surgery

MedlinePlus

... and taking big breaths can be uncomfortable. A device called an incentive spirometer can help you take deep breaths correctly. If you do not have this device, you can still practice deep breathing on your ...

Thrombophlebitis

MedlinePlus

... the surface of your skin (superficial thrombophlebitis) or deep within a muscle (deep vein thrombosis, or DVT). Causes include trauma, surgery ... pain in the affected area Redness and swelling Deep vein thrombosis signs and symptoms include: Pain Swelling ...

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

PubMed

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

Deep neural networks to enable real-time multimessenger astrophysics

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-02-01

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

Deep subsurface microbial processes

USGS Publications Warehouse

Lovley, D.R.; Chapelle, F.H.

1995-01-01

Information on the microbiology of the deep subsurface is necessary in order to understand the factors controlling the rate and extent of the microbially catalyzed redox reactions that influence the geophysical properties of these environments. Furthermore, there is an increasing threat that deep aquifers, an important drinking water resource, may be contaminated by man's activities, and there is a need to predict the extent to which microbial activity may remediate such contamination. Metabolically active microorganisms can be recovered from a diversity of deep subsurface environments. The available evidence suggests that these microorganisms are responsible for catalyzing the oxidation of organic matter coupled to a variety of electron acceptors just as microorganisms do in surface sediments, but at much slower rates. The technical difficulties in aseptically sampling deep subsurface sediments and the fact that microbial processes in laboratory incubations of deep subsurface material often do not mimic in situ processes frequently necessitate that microbial activity in the deep subsurface be inferred through nonmicrobiological analyses of ground water. These approaches include measurements of dissolved H2, which can predict the predominant microbially catalyzed redox reactions in aquifers, as well as geochemical and groundwater flow modeling, which can be used to estimate the rates of microbial processes. Microorganisms recovered from the deep subsurface have the potential to affect the fate of toxic organics and inorganic contaminants in groundwater. Microbial activity also greatly influences 1 the chemistry of many pristine groundwaters and contributes to such phenomena as porosity development in carbonate aquifers, accumulation of undesirably high concentrations of dissolved iron, and production of methane and hydrogen sulfide. Although the last decade has seen a dramatic increase in interest in deep subsurface microbiology, in comparison with the study of other habitats, the study of deep subsurface microbiology is still in its infancy.

Insights into Deep-Sea Sediment Fungal Communities from the East Indian Ocean Using Targeted Environmental Sequencing Combined with Traditional Cultivation

PubMed Central

Zhang, Xiao-yong; Tang, Gui-ling; Xu, Xin-ya; Nong, Xu-hua; Qi, Shu-Hua

2014-01-01

The fungal diversity in deep-sea environments has recently gained an increasing amount attention. Our knowledge and understanding of the true fungal diversity and the role it plays in deep-sea environments, however, is still limited. We investigated the fungal community structure in five sediments from a depth of ∼4000 m in the East India Ocean using a combination of targeted environmental sequencing and traditional cultivation. This approach resulted in the recovery of a total of 45 fungal operational taxonomic units (OTUs) and 20 culturable fungal phylotypes. This finding indicates that there is a great amount of fungal diversity in the deep-sea sediments collected in the East Indian Ocean. Three fungal OTUs and one culturable phylotype demonstrated high divergence (89%–97%) from the existing sequences in the GenBank. Moreover, 44.4% fungal OTUs and 30% culturable fungal phylotypes are new reports for deep-sea sediments. These results suggest that the deep-sea sediments from the East India Ocean can serve as habitats for new fungal communities compared with other deep-sea environments. In addition, different fungal community could be detected when using targeted environmental sequencing compared with traditional cultivation in this study, which suggests that a combination of targeted environmental sequencing and traditional cultivation will generate a more diverse fungal community in deep-sea environments than using either targeted environmental sequencing or traditional cultivation alone. This study is the first to report new insights into the fungal communities in deep-sea sediments from the East Indian Ocean, which increases our knowledge and understanding of the fungal diversity in deep-sea environments. PMID:25272044

Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning

NASA Astrophysics Data System (ADS)

Shi, Bibo; Hou, Rui; Mazurowski, Maciej A.; Grimm, Lars J.; Ren, Yinhao; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2018-02-01

Purpose: To determine whether domain transfer learning can improve the performance of deep features extracted from digital mammograms using a pre-trained deep convolutional neural network (CNN) in the prediction of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy. Method: In this study, we collected digital mammography magnification views for 140 patients with DCIS at biopsy, 35 of which were subsequently upstaged to invasive cancer. We utilized a deep CNN model that was pre-trained on two natural image data sets (ImageNet and DTD) and one mammographic data set (INbreast) as the feature extractor, hypothesizing that these data sets are increasingly more similar to our target task and will lead to better representations of deep features to describe DCIS lesions. Through a statistical pooling strategy, three sets of deep features were extracted using the CNNs at different levels of convolutional layers from the lesion areas. A logistic regression classifier was then trained to predict which tumors contain occult invasive disease. The generalization performance was assessed and compared using repeated random sub-sampling validation and receiver operating characteristic (ROC) curve analysis. Result: The best performance of deep features was from CNN model pre-trained on INbreast, and the proposed classifier using this set of deep features was able to achieve a median classification performance of ROC-AUC equal to 0.75, which is significantly better (p<=0.05) than the performance of deep features extracted using ImageNet data set (ROCAUC = 0.68). Conclusion: Transfer learning is helpful for learning a better representation of deep features, and improves the prediction of occult invasive disease in DCIS.

Too Deep or Not Too Deep?: A Propensity-Matched Comparison of the Analgesic Effects of a Superficial Versus Deep Serratus Fascial Plane Block for Ambulatory Breast Cancer Surgery.

PubMed

Abdallah, Faraj W; Cil, Tulin; MacLean, David; Madjdpour, Caveh; Escallon, Jaime; Semple, John; Brull, Richard

2018-07-01

Serratus fascial plane block can reduce pain following breast surgery, but the question of whether to inject the local anesthetic superficial or deep to the serratus muscle has not been answered. This cohort study compares the analgesic benefits of superficial versus deep serratus plane blocks in ambulatory breast cancer surgery patients at Women's College Hospital between February 2014 and December 2016. We tested the joint hypothesis that deep serratus block is noninferior to superficial serratus block for postoperative in-hospital (pre-discharge) opioid consumption and pain severity. One hundred sixty-six patients were propensity matched among 2 groups (83/group): superficial and deep serratus blocks. The cohort was used to evaluate the effect of blocks on postoperative oral morphine equivalent consumption and area under the curve for rest pain scores. We considered deep serratus block to be noninferior to superficial serratus block if it were noninferior for both outcomes, within 15 mg morphine and 4 cm·h units margins. Other outcomes included intraoperative fentanyl requirements, time to first analgesic request, recovery room stay, and incidence of postoperative nausea and vomiting. Deep serratus block was associated with postoperative morphine consumption and pain scores area under the curve that were noninferior to those of the superficial serratus block. Intraoperative fentanyl requirements, time to first analgesic request, recovery room stay, and postoperative nausea and vomiting were not different between blocks. The postoperative in-hospital analgesia associated with deep serratus block is as effective (within an acceptable margin) as superficial serratus block following ambulatory breast cancer surgery. These new findings are important to inform both current clinical practices and future prospective studies.

Permeability Surface of Deep Middle Cerebral Artery Territory on Computed Tomographic Perfusion Predicts Hemorrhagic Transformation After Stroke.

PubMed

Li, Qiao; Gao, Xinyi; Yao, Zhenwei; Feng, Xiaoyuan; He, Huijin; Xue, Jing; Gao, Peiyi; Yang, Lumeng; Cheng, Xin; Chen, Weijian; Yang, Yunjun

2017-09-01

Permeability surface (PS) on computed tomographic perfusion reflects blood-brain barrier permeability and is related to hemorrhagic transformation (HT). HT of deep middle cerebral artery (MCA) territory can occur after recanalization of proximal large-vessel occlusion. We aimed to determine the relationship between HT and PS of deep MCA territory. We retrospectively reviewed 70 consecutive acute ischemic stroke patients presenting with occlusion of the distal internal carotid artery or M1 segment of the MCA. All patients underwent computed tomographic perfusion within 6 hours after symptom onset. Computed tomographic perfusion data were postprocessed to generate maps of different perfusion parameters. Risk factors were identified for increased deep MCA territory PS. Receiver operating characteristic curve analysis was performed to calculate the optimal PS threshold to predict HT of deep MCA territory. Increased PS was associated with HT of deep MCA territory. After adjustments for age, sex, onset time to computed tomographic perfusion, and baseline National Institutes of Health Stroke Scale, poor collateral status (odds ratio, 7.8; 95% confidence interval, 1.67-37.14; P =0.009) and proximal MCA-M1 occlusion (odds ratio, 4.12; 95% confidence interval, 1.03-16.52; P =0.045) were independently associated with increased deep MCA territory PS. Relative PS most accurately predicted HT of deep MCA territory (area under curve, 0.94; optimal threshold, 2.89). Increased PS can predict HT of deep MCA territory after recanalization therapy for cerebral proximal large-vessel occlusion. Proximal MCA-M1 complete occlusion and distal internal carotid artery occlusion in conjunction with poor collaterals elevate deep MCA territory PS. © 2017 American Heart Association, Inc.

Deep Ocean Circulation and Nutrient Contents from Atlantic-Pacific Gradients of Neodymium and Carbon Isotopes During the Last 1 Ma

NASA Astrophysics Data System (ADS)

Piotrowski, A. M.; Elderfield, H.; Howe, J. N. W.

2014-12-01

The last few million years saw changing boundary conditions to the Earth system which set the stage for bi-polar glaciation and Milankovich-forced glacial-interglacial cycles which dominate Quaternary climate variability. Recent studies have highlighted the relative importance of temperature, ice volume and ocean circulation changes during the Mid-Pleistocene Transition at ~900 ka (Elderfield et al., 2012, Pena and Goldstein, 2014). Reconstructing the history of global deep water mass propagation and its carbon content is important for fully understanding the ocean's role in amplifying Milankovich changes to cause glacial-interglacial transitions. A new foraminiferal-coating Nd isotope record from ODP Site 1123 on the deep Chatham Rise is interpreted as showing glacial-interglacial changes in the bottom water propagation of Atlantic-sourced waters into the Pacific via the Southern Ocean during the last 1 million years. This is compared to globally-distributed bottom water Nd isotope records; including a new deep western equatorial Atlantic Ocean record from ODP Site 929, as well as published records from ODP 1088 and Site 1090 in the South Atlantic (Pena and Goldstein, 2014), and ODP 758 in the deep Indian Ocean (Gourlan et al., 2010). Atlantic-to-Pacific gradients in deep ocean neodymium isotopes are constructed for key time intervals to elucidate changes in deep water sourcing and circulation pathways through the global ocean. Benthic carbon isotopes are used to estimate deep water nutrient contents of deep water masses and constrain locations and modes of deep water formation. References: Elderfield et al. Science 337, 704 (2012) Pena and Goldstein, Science 345, 318 (2014) Gourlan et al., Quaternary Science Reviews 29, 2484-2498 (2010)

Topsoil and Deep Soil Organic Carbon Concentration and Stability Vary with Aggregate Size and Vegetation Type in Subtropical China

PubMed Central

Fang, Xiang-Min; Chen, Fu-Sheng; Wan, Song-Ze; Yang, Qing-Pei; Shi, Jian-Min

2015-01-01

The impact of reforestation on soil organic carbon (OC), especially in deep layer, is poorly understood and deep soil OC stabilization in relation with aggregation and vegetation type in afforested area is unknown. Here, we collected topsoil (0–15 cm) and deep soil (30–45 cm) from six paired coniferous forests (CF) and broad-leaved forests (BF) reforested in the early 1990s in subtropical China. Soil aggregates were separated by size by dry sieving and OC stability was measured by closed-jar alkali-absorption in 71 incubation days. Soil OC concentration and mean weight diameter were higher in BF than CF. The cumulative carbon mineralization (Cmin, mg CO2-C kg-1 soil) varied with aggregate size in BF and CF topsoils, and in deep soil, it was higher in larger aggregates than in smaller aggregates in BF, but not CF. The percentage of soil OC mineralized (SOCmin, % SOC) was in general higher in larger aggregates than in smaller aggregates. Meanwhile, SOCmin was greater in CF than in BF at topsoil and deep soil aggregates. In comparison to topsoil, deep soil aggregates generally exhibited a lower Cmin, and higher SOCmin. Total nitrogen (N) and the ratio of carbon to phosphorus (C/P) were generally higher in BF than in CF in topsoil and deep soil aggregates, while the same trend of N/P was only found in deep soil aggregates. Moreover, the SOCmin negatively correlated with OC, total N, C/P and N/P. This work suggests that reforested vegetation type might play an important role in soil OC storage through internal nutrient cycling. Soil depth and aggregate size influenced OC stability, and deep soil OC stability could be altered by vegetation reforested about 20 years. PMID:26418563

Morphological divergence between three Arctic charr morphs - the significance of the deep-water environment.

PubMed

Skoglund, Sigrid; Siwertsson, Anna; Amundsen, Per-Arne; Knudsen, Rune

2015-08-01

Morphological divergence was evident among three sympatric morphs of Arctic charr (Salvelinus alpinus (L.)) that are ecologically diverged along the shallow-, deep-water resource axis in a subarctic postglacial lake (Norway). The two deep-water (profundal) spawning morphs, a benthivore (PB-morph) and a piscivore (PP-morph), have evolved under identical abiotic conditions with constant low light and temperature levels in their deep-water habitat, and were morphologically most similar. However, they differed in important head traits (e.g., eye and mouth size) related to their different diet specializations. The small-sized PB-morph had a paedomorphic appearance with a blunt head shape, large eyes, and a deep body shape adapted to their profundal lifestyle feeding on submerged benthos from soft, deep-water sediments. The PP-morph had a robust head, large mouth with numerous teeth, and an elongated body shape strongly related to their piscivorous behavior. The littoral spawning omnivore morph (LO-morph) predominantly utilizes the shallow benthic-pelagic habitat and food resources. Compared to the deep-water morphs, the LO-morph had smaller head relative to body size. The LO-morph exhibited traits typical for both shallow-water benthic feeding (e.g., large body depths and small eyes) and planktivorous feeding in the pelagic habitat (e.g., streamlined body shape and small mouth). The development of morphological differences within the same deep-water habitat for the PB- and PP-morphs highlights the potential of biotic factors and ecological interactions to promote further divergence in the evolution of polymorphism in a tentative incipient speciation process. The diversity of deep-water charr in this study represents a novelty in the Arctic charr polymorphism as a truly deep-water piscivore morph has to our knowledge not been described elsewhere.

Deep Space Quantum Link

NASA Astrophysics Data System (ADS)

Mohageg, M.; Strekalov, D.; Dolinar, S.; Shaw, M.; Yu, N.

2018-02-01

The Deep Space Quantum Link will test the effects of gravity on quantum systems, test the non-locality of quantum states at deep space distances, and perform long distance quantum teleportation to an Earth-based receiver.

Asthma Inhalers: Which One's Right for You?

MedlinePlus

... medication in these inhalers by breathing in a deep, fast breath. There are multiple-dose devices, which ... and convenient to carry. Doesn't require a deep, fast, inhaled breath. Doesn't require a deep, ...

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.

Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

Dining in the Deep: The Feeding Ecology of Deep-Sea Fishes

NASA Astrophysics Data System (ADS)

Drazen, Jeffrey C.; Sutton, Tracey T.

2017-01-01

Deep-sea fishes inhabit ˜75% of the biosphere and are a critical part of deep-sea food webs. Diet analysis and more recent trophic biomarker approaches, such as stable isotopes and fatty-acid profiles, have enabled the description of feeding guilds and an increased recognition of the vertical connectivity in food webs in a whole-water-column sense, including benthic-pelagic coupling. Ecosystem modeling requires data on feeding rates; the available estimates indicate that deep-sea fishes have lower per-individual feeding rates than coastal and epipelagic fishes, but the overall predation impact may be high. A limited number of studies have measured the vertical flux of carbon by mesopelagic fishes, which appears to be substantial. Anthropogenic activities are altering deep-sea ecosystems and their services, which are mediated by trophic interactions. We also summarize outstanding data gaps.

Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions

PubMed Central

2014-01-01

Deep sequencing harnesses the high throughput nature of next generation sequencing technologies to generate population samples, treating information contained in individual reads as meaningful. Here, we review applications of deep sequencing to pathogen evolution. Pioneering deep sequencing studies from the virology literature are discussed, such as whole genome Roche-454 sequencing analyses of the dynamics of the rapidly mutating pathogens hepatitis C virus and HIV. Extension of the deep sequencing approach to bacterial populations is then discussed, including the impacts of emerging sequencing technologies. While it is clear that deep sequencing has unprecedented potential for assessing the genetic structure and evolutionary history of pathogen populations, bioinformatic challenges remain. We summarise current approaches to overcoming these challenges, in particular methods for detecting low frequency variants in the context of sequencing error and reconstructing individual haplotypes from short reads. PMID:24428920

Velocity and stress distributions of deep seismic zone under Izu-Bonin, Japan

NASA Astrophysics Data System (ADS)

Jiang, Guoming; Zhang, Guibin; Jia, Zhengyuan

2017-04-01

Deep earthquakes can provide the deep information of the Earth directly. We have collected the waveform data from 77 deep earthquakes with depth greater than 300 km under Izu-Bonin in Japan. To obtain the velocity structures of P- and S-wave, we have inversed the double-differences of travel times from deep event-pairs. These velocity anomalies can further yield the Poisson's ratio and the porosity. Our results show that the average P-wave velocity anomaly is lower 6%, however the S-wave anomaly is higher 2% than the iasp91 model. The corresponding Poisson's ratio and porosity anomaly are -24% and -4%, respectively, which suggest that the possibility of water in the deep seismic zone is very few and the porosity might be richer. To obtain the stress distribution, we have used the ISOLA method to analyse the non-double-couple components of moment tensors of 77 deep earthquakes. The focal mechanism results show that almost half of all earthquakes have larger double-couple (DC) components, but others have clear isotropic (ISO) or compensated linear vector dipole (CLVD) components. The non-double-couple components (ISO and CLVD) seem to represent the volume around a deep earthquake changes as it occurs, which could be explained the metastable olivine phase transition. All results indicate that the metastable olivine wedge (MOW) might exist in the Pacific slab under the Izu-Bonin region and the deep earthquakes might be induced by the phase change of metastable olivine.

Focused Crawling of the Deep Web Using Service Class Descriptions

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

Rocco, D; Liu, L; Critchlow, T

2004-06-21

Dynamic Web data sources--sometimes known collectively as the Deep Web--increase the utility of the Web by providing intuitive access to data repositories anywhere that Web access is available. Deep Web services provide access to real-time information, like entertainment event listings, or present a Web interface to large databases or other data repositories. Recent studies suggest that the size and growth rate of the dynamic Web greatly exceed that of the static Web, yet dynamic content is often ignored by existing search engine indexers owing to the technical challenges that arise when attempting to search the Deep Web. To address thesemore » challenges, we present DynaBot, a service-centric crawler for discovering and clustering Deep Web sources offering dynamic content. DynaBot has three unique characteristics. First, DynaBot utilizes a service class model of the Web implemented through the construction of service class descriptions (SCDs). Second, DynaBot employs a modular, self-tuning system architecture for focused crawling of the DeepWeb using service class descriptions. Third, DynaBot incorporates methods and algorithms for efficient probing of the Deep Web and for discovering and clustering Deep Web sources and services through SCD-based service matching analysis. Our experimental results demonstrate the effectiveness of the service class discovery, probing, and matching algorithms and suggest techniques for efficiently managing service discovery in the face of the immense scale of the Deep Web.« less

The influence of tourniquet use and operative time on the incidence of deep vein thrombosis in total knee arthroplasty.

PubMed

Hernandez, Arnaldo José; Almeida, Adriano Marques de; Fávaro, Edmar; Sguizzato, Guilherme Turola

2012-09-01

To evaluate the association between tourniquet and total operative time during total knee arthroplasty and the occurrence of deep vein thrombosis. Seventy-eight consecutive patients from our institution underwent cemented total knee arthroplasty for degenerative knee disorders. The pneumatic tourniquet time and total operative time were recorded in minutes. Four categories were established for total tourniquet time: <60, 61 to 90, 91 to 120, and >120 minutes. Three categories were defined for operative time: <120, 121 to 150, and >150 minutes. Between 7 and 12 days after surgery, the patients underwent ascending venography to evaluate the presence of distal or proximal deep vein thrombosis. We evaluated the association between the tourniquet time and total operative time and the occurrence of deep vein thrombosis after total knee arthroplasty. In total, 33 cases (42.3%) were positive for deep vein thrombosis; 13 (16.7%) cases involved the proximal type. We found no statistically significant difference in tourniquet time or operative time between patients with or without deep vein thrombosis. We did observe a higher frequency of proximal deep vein thrombosis in patients who underwent surgery lasting longer than 120 minutes. The mean total operative time was also higher in patients with proximal deep vein thrombosis. The tourniquet time did not significantly differ in these patients. We concluded that surgery lasting longer than 120 minutes increases the risk of proximal deep vein thrombosis.

Observations of open-ocean deep convection in the northwestern Mediterranean Sea: Seasonal and interannual variability of mixing and deep water masses for the 2007-2013 Period

NASA Astrophysics Data System (ADS)

Houpert, L.; Durrieu de Madron, X.; Testor, P.; Bosse, A.; D'Ortenzio, F.; Bouin, M. N.; Dausse, D.; Le Goff, H.; Kunesch, S.; Labaste, M.; Coppola, L.; Mortier, L.; Raimbault, P.

2016-11-01

We present here a unique oceanographic and meteorological data set focus on the deep convection processes. Our results are essentially based on in situ data (mooring, research vessel, glider, and profiling float) collected from a multiplatform and integrated monitoring system (MOOSE: Mediterranean Ocean Observing System on Environment), which monitored continuously the northwestern Mediterranean Sea since 2007, and in particular high-frequency potential temperature, salinity, and current measurements from the mooring LION located within the convection region. From 2009 to 2013, the mixed layer depth reaches the seabed, at a depth of 2330m, in February. Then, the violent vertical mixing of the whole water column lasts between 9 and 12 days setting up the characteristics of the newly formed deep water. Each deep convection winter formed a new warmer and saltier "vintage" of deep water. These sudden inputs of salt and heat in the deep ocean are responsible for trends in salinity (3.3 ± 0.2 × 10-3/yr) and potential temperature (3.2 ± 0.5 × 10-3 C/yr) observed from 2009 to 2013 for the 600-2300 m layer. For the first time, the overlapping of the three "phases" of deep convection can be observed, with secondary vertical mixing events (2-4 days) after the beginning of the restratification phase, and the restratification/spreading phase still active at the beginning of the following deep convection event.

The DEEP-South: Scheduling and Data Reduction Software System

NASA Astrophysics Data System (ADS)

Yim, Hong-Suh; Kim, Myung-Jin; Bae, Youngho; Moon, Hong-Kyu; Choi, Young-Jun; Roh, Dong-Goo; the DEEP-South Team

2015-08-01

The DEep Ecliptic Patrol of the Southern sky (DEEP-South), started in October 2012, is currently in test runs with the first Korea Microlensing Telescope Network (KMTNet) 1.6 m wide-field telescope located at CTIO in Chile. While the primary objective for the DEEP-South is physical characterization of small bodies in the Solar System, it is expected to discover a large number of such bodies, many of them previously unknown.An automatic observation planning and data reduction software subsystem called "The DEEP-South Scheduling and Data reduction System" (the DEEP-South SDS) is currently being designed and implemented for observation planning, data reduction and analysis of huge amount of data with minimum human interaction. The DEEP-South SDS consists of three software subsystems: the DEEP-South Scheduling System (DSS), the Local Data Reduction System (LDR), and the Main Data Reduction System (MDR). The DSS manages observation targets, makes decision on target priority and observation methods, schedules nightly observations, and archive data using the Database Management System (DBMS). The LDR is designed to detect moving objects from CCD images, while the MDR conducts photometry and reconstructs lightcurves. Based on analysis made at the LDR and the MDR, the DSS schedules follow-up observation to be conducted at other KMTNet stations. In the end of 2015, we expect the DEEP-South SDS to achieve a stable operation. We also have a plan to improve the SDS to accomplish finely tuned observation strategy and more efficient data reduction in 2016.

Quantitative Trait Locus Analysis for Deep-Sowing Germination Ability in the Maize IBM Syn10 DH Population

PubMed Central

Liu, Hongjun; Zhang, Lin; Wang, Jiechen; Li, Changsheng; Zeng, Xing; Xie, Shupeng; Zhang, Yongzhong; Liu, Sisi; Hu, Songlin; Wang, Jianhua; Lee, Michael; Lübberstedt, Thomas; Zhao, Guangwu

2017-01-01

Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51–7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize. PMID:28588594

Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

2016-10-01

The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

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.

DEEP: a general computational framework for predicting enhancers

PubMed Central

Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/. PMID:25378307

DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks.

PubMed

Li, Chao; Wang, Xinggang; Liu, Wenyu; Latecki, Longin Jan

2018-04-01

Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis. Nowadays mitosis counting is mainly performed by pathologists manually, which is extremely arduous and time-consuming. In this paper, we propose an accurate method for detecting the mitotic cells from histopathological slides using a novel multi-stage deep learning framework. Our method consists of a deep segmentation network for generating mitosis region when only a weak label is given (i.e., only the centroid pixel of mitosis is annotated), an elaborately designed deep detection network for localizing mitosis by using contextual region information, and a deep verification network for improving detection accuracy by removing false positives. We validate the proposed deep learning method on two widely used Mitosis Detection in Breast Cancer Histological Images (MITOSIS) datasets. Experimental results show that we can achieve the highest F-score on the MITOSIS dataset from ICPR 2012 grand challenge merely using the deep detection network. For the ICPR 2014 MITOSIS dataset that only provides the centroid location of mitosis, we employ the segmentation model to estimate the bounding box annotation for training the deep detection network. We also apply the verification model to eliminate some false positives produced from the detection model. By fusing scores of the detection and verification models, we achieve the state-of-the-art results. Moreover, our method is very fast with GPU computing, which makes it feasible for clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative Trait Locus Analysis for Deep-Sowing Germination Ability in the Maize IBM Syn10 DH Population.

PubMed

Liu, Hongjun; Zhang, Lin; Wang, Jiechen; Li, Changsheng; Zeng, Xing; Xie, Shupeng; Zhang, Yongzhong; Liu, Sisi; Hu, Songlin; Wang, Jianhua; Lee, Michael; Lübberstedt, Thomas; Zhao, Guangwu

2017-01-01

Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51-7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize.

Pathogenesis of deep endometriosis.

PubMed

Gordts, Stephan; Koninckx, Philippe; Brosens, Ivo

2017-12-01

The pathophysiology of (deep) endometriosis is still unclear. As originally suggested by Cullen, change the definition "deeper than 5 mm" to "adenomyosis externa." With the discovery of the old European literature on uterine bleeding in 5%-10% of the neonates and histologic evidence that the bleeding represents decidual shedding, it is postulated/hypothesized that endometrial stem/progenitor cells, implanted in the pelvic cavity after birth, may be at the origin of adolescent and even the occasionally premenarcheal pelvic endometriosis. Endometriosis in the adolescent is characterized by angiogenic and hemorrhagic peritoneal and ovarian lesions. The development of deep endometriosis at a later age suggests that deep infiltrating endometriosis is a delayed stage of endometriosis. Another hypothesis is that the endometriotic cell has undergone genetic or epigenetic changes and those specific changes determine the development into deep endometriosis. This is compatible with the hereditary aspects, and with the clonality of deep and cystic ovarian endometriosis. It explains the predisposition and an eventual causal effect by dioxin or radiation. Specific genetic/epigenetic changes could explain the various expressions and thus typical, cystic, and deep endometriosis become three different diseases. Subtle lesions are not a disease until epi(genetic) changes occur. A classification should reflect that deep endometriosis is a specific disease. In conclusion the pathophysiology of deep endometriosis remains debated and the mechanisms of disease progression, as well as the role of genetics and epigenetics in the process, still needs to be unraveled. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

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.

Multiplying Mars Lander Opportunities with Marsdrop Microlanders

NASA Technical Reports Server (NTRS)

Staehle, Robert L.; Spangelo, Sara; Lane, Marc S.; Aaron, Kim M.; Bhartia, Rohit; Boland, Justin S.; Christensen, Lance E.; Forouhar, Siamak; de la Torre Juarez, Manuel; Trawny, Nikolas;

The Population of Supernova Remnants in M51

NASA Astrophysics Data System (ADS)

Long, Knox S.; Blair, William P.; Kuntz, K. D.; Winkler, P. Frank

2017-08-01

The nearby, actively star-forming, nearly face-on spiral galaxy, M51 (NGC 5194/5), has been the site of four supernovae since 1941. As a result it should have a rich population of young supernova remnants (SNRs). Here we describe a search for optical SNRs in M51 among the 298 X-ray sources discovered inside the D25 contour in deep Chandra observations. The search uses interference filter images obtained with the WFC3 on Hubble Space Telescope and more recent images from GMOS on Gemini North. Of 80 emission nebulae identified in the HST images as SNR candidates based on elevated [SII]: Ha ratios compared to HII regions, 40 have X-ray counterparts. The diameters of the SNRs and SNR candidates detected with HST are systematically smaller than seen in SNR populations of other galaxies at comparable distances. However, this is most likely an instrumental effect, which our ongoing analysis of the new GMOS images will correct. At that point, we will be able to make of fair multi-wavelength comparison of the SNR population in M51 with other nearby, actively star-forming spiral galaxies, such as M83 and NGC6946.

12 CFR 220.122 - “Deep in the money put and call options” as extensions of credit.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 3 2013-01-01 2013-01-01 false âDeep in the money put and call optionsâ as...) Interpretations § 220.122 “Deep in the money put and call options” as extensions of credit. (a) The Board of Governors has been asked to determine whether the business of selling instruments described as “deep in the...

30 CFR 203.31 - If I have a qualified phase 2 or qualified phase 3 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2011 CFR

2011-07-01

... INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.31... applies if your lease: (i) Has produced gas or oil from a deep well with a perforated interval the top of...

30 CFR 203.34 - To which production may an RSV earned by qualified phase 2 and phase 3 ultra-deep wells on my...

Code of Federal Regulations, 2010 CFR

2010-07-01

..., on a lease that is located entirely or partly in water less than 200 meters deep; or (2) May 18, 2007, on a lease that is located entirely in water more than 200 meters deep. ... Leases Not Subject to Deep Water Royalty Relief § 203.34 To which production may an RSV earned by...

12 CFR 220.122 - “Deep in the money put and call options” as extensions of credit.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 3 2011-01-01 2011-01-01 false âDeep in the money put and call optionsâ as....122 “Deep in the money put and call options” as extensions of credit. (a) The Board of Governors has been asked to determine whether the business of selling instruments described as “deep in the money put...

12 CFR 220.122 - “Deep in the money put and call options” as extensions of credit.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 3 2012-01-01 2012-01-01 false âDeep in the money put and call optionsâ as....122 “Deep in the money put and call options” as extensions of credit. (a) The Board of Governors has been asked to determine whether the business of selling instruments described as “deep in the money put...

12 CFR 220.122 - “Deep in the money put and call options” as extensions of credit.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 3 2014-01-01 2014-01-01 false âDeep in the money put and call optionsâ as...) Interpretations § 220.122 “Deep in the money put and call options” as extensions of credit. (a) The Board of Governors has been asked to determine whether the business of selling instruments described as “deep in the...

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

PubMed Central

Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

2014-01-01

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

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).

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.

Break-up of the Atlantic deep western boundary current into eddies at 8 degrees S.

PubMed

Dengler, M; Schott, F A; Eden, C; Brandt, P; Fischer, J; Zantopp, R J

2004-12-23

The existence in the ocean of deep western boundary currents, which connect the high-latitude regions where deep water is formed with upwelling regions as part of the global ocean circulation, was postulated more than 40 years ago. These ocean currents have been found adjacent to the continental slopes of all ocean basins, and have core depths between 1,500 and 4,000 m. In the Atlantic Ocean, the deep western boundary current is estimated to carry (10-40) x 10(6) m3 s(-1) of water, transporting North Atlantic Deep Water--from the overflow regions between Greenland and Scotland and from the Labrador Sea--into the South Atlantic and the Antarctic circumpolar current. Here we present direct velocity and water mass observations obtained in the period 2000 to 2003, as well as results from a numerical ocean circulation model, showing that the Atlantic deep western boundary current breaks up at 8 degrees S. Southward of this latitude, the transport of North Atlantic Deep Water into the South Atlantic Ocean is accomplished by migrating eddies, rather than by a continuous flow. Our model simulation indicates that the deep western boundary current breaks up into eddies at the present intensity of meridional overturning circulation. For weaker overturning, continuation as a stable, laminar boundary flow seems possible.

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

PubMed

Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

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

Adaptation and evolution of deep-sea scale worms (Annelida: Polynoidae): insights from transcriptome comparison with a shallow-water species

NASA Astrophysics Data System (ADS)

Zhang, Yanjie; Sun, Jin; Chen, Chong; Watanabe, Hiromi K.; Feng, Dong; Zhang, Yu; Chiu, Jill M. Y.; Qian, Pei-Yuan; Qiu, Jian-Wen

2017-04-01

Polynoid scale worms (Polynoidae, Annelida) invaded deep-sea chemosynthesis-based ecosystems approximately 60 million years ago, but little is known about their genetic adaptation to the extreme deep-sea environment. In this study, we reported the first two transcriptomes of deep-sea polynoids (Branchipolynoe pettiboneae, Lepidonotopodium sp.) and compared them with the transcriptome of a shallow-water polynoid (Harmothoe imbricata). We determined codon and amino acid usage, positive selected genes, highly expressed genes and putative duplicated genes. Transcriptome assembly produced 98,806 to 225,709 contigs in the three species. There were more positively charged amino acids (i.e., histidine and arginine) and less negatively charged amino acids (i.e., aspartic acid and glutamic acid) in the deep-sea species. There were 120 genes showing clear evidence of positive selection. Among the 10% most highly expressed genes, there were more hemoglobin genes with high expression levels in both deep-sea species. The duplicated genes related to DNA recombination and metabolism, and gene expression were only enriched in deep-sea species. Deep-sea scale worms adopted two strategies of adaptation to hypoxia in the chemosynthesis-based habitats (i.e., rapid evolution of tetra-domain hemoglobin in Branchipolynoe or high expression of single-domain hemoglobin in Lepidonotopodium sp.).

Mechanism of deep-sea fish α-actin pressure tolerance investigated by molecular dynamics simulations.

PubMed

Wakai, Nobuhiko; Takemura, Kazuhiro; Morita, Takami; Kitao, Akio

2014-01-01

The pressure tolerance of monomeric α-actin proteins from the deep-sea fish Coryphaenoides armatus and C. yaquinae was compared to that of non-deep-sea fish C. acrolepis, carp, and rabbit/human/chicken actins using molecular dynamics simulations at 0.1 and 60 MPa. The amino acid sequences of actins are highly conserved across a variety of species. The actins from C. armatus and C. yaquinae have the specific substitutions Q137K/V54A and Q137K/L67P, respectively, relative to C. acrolepis, and are pressure tolerant to depths of at least 6000 m. At high pressure, we observed significant changes in the salt bridge patterns in deep-sea fish actins, and these changes are expected to stabilize ATP binding and subdomain arrangement. Salt bridges between ATP and K137, formed in deep-sea fish actins, are expected to stabilize ATP binding even at high pressure. At high pressure, deep-sea fish actins also formed a greater total number of salt bridges than non-deep-sea fish actins owing to the formation of inter-helix/strand and inter-subdomain salt bridges. Free energy analysis suggests that deep-sea fish actins are stabilized to a greater degree by the conformational energy decrease associated with pressure effect.

Adaptation and evolution of deep-sea scale worms (Annelida: Polynoidae): insights from transcriptome comparison with a shallow-water species

PubMed Central

Zhang, Yanjie; Sun, Jin; Chen, Chong; Watanabe, Hiromi K.; Feng, Dong; Zhang, Yu; Chiu, Jill M.Y.; Qian, Pei-Yuan; Qiu, Jian-Wen

2017-01-01

Polynoid scale worms (Polynoidae, Annelida) invaded deep-sea chemosynthesis-based ecosystems approximately 60 million years ago, but little is known about their genetic adaptation to the extreme deep-sea environment. In this study, we reported the first two transcriptomes of deep-sea polynoids (Branchipolynoe pettiboneae, Lepidonotopodium sp.) and compared them with the transcriptome of a shallow-water polynoid (Harmothoe imbricata). We determined codon and amino acid usage, positive selected genes, highly expressed genes and putative duplicated genes. Transcriptome assembly produced 98,806 to 225,709 contigs in the three species. There were more positively charged amino acids (i.e., histidine and arginine) and less negatively charged amino acids (i.e., aspartic acid and glutamic acid) in the deep-sea species. There were 120 genes showing clear evidence of positive selection. Among the 10% most highly expressed genes, there were more hemoglobin genes with high expression levels in both deep-sea species. The duplicated genes related to DNA recombination and metabolism, and gene expression were only enriched in deep-sea species. Deep-sea scale worms adopted two strategies of adaptation to hypoxia in the chemosynthesis-based habitats (i.e., rapid evolution of tetra-domain hemoglobin in Branchipolynoe or high expression of single-domain hemoglobin in Lepidonotopodium sp.). PMID:28397791

Mechanism of Deep-Sea Fish α-Actin Pressure Tolerance Investigated by Molecular Dynamics Simulations

PubMed Central

Wakai, Nobuhiko; Takemura, Kazuhiro; Morita, Takami; Kitao, Akio

2014-01-01

The pressure tolerance of monomeric α-actin proteins from the deep-sea fish Coryphaenoides armatus and C. yaquinae was compared to that of non-deep-sea fish C. acrolepis, carp, and rabbit/human/chicken actins using molecular dynamics simulations at 0.1 and 60 MPa. The amino acid sequences of actins are highly conserved across a variety of species. The actins from C. armatus and C. yaquinae have the specific substitutions Q137K/V54A and Q137K/L67P, respectively, relative to C. acrolepis, and are pressure tolerant to depths of at least 6000 m. At high pressure, we observed significant changes in the salt bridge patterns in deep-sea fish actins, and these changes are expected to stabilize ATP binding and subdomain arrangement. Salt bridges between ATP and K137, formed in deep-sea fish actins, are expected to stabilize ATP binding even at high pressure. At high pressure, deep-sea fish actins also formed a greater total number of salt bridges than non-deep-sea fish actins owing to the formation of inter-helix/strand and inter-subdomain salt bridges. Free energy analysis suggests that deep-sea fish actins are stabilized to a greater degree by the conformational energy decrease associated with pressure effect. PMID:24465747

Survival of marine heterotrophic flagellates isolated from the surface and the deep sea at high hydrostatic pressure: Literature review and own experiments

NASA Astrophysics Data System (ADS)

Živaljić, Suzana; Schoenle, Alexandra; Nitsche, Frank; Hohlfeld, Manon; Piechocki, Julia; Reif, Farina; Shumo, Marwa; Weiss, Alexandra; Werner, Jennifer; Witt, Madeleine; Voss, Janine; Arndt, Hartmut

2018-02-01

Although the abyssal seafloor represents the most common benthic environment on Earth, eukaryotic microbial life at abyssal depths is still an uncharted territory. This is in striking contrast to their potential importance regarding the material flux and bacteria consumption in the deep sea. Flagellate genotypes determined from sedimentary DNA deep-sea samples might originate from vital deep-sea populations or from cysts of organisms sedimented down from surface waters. The latter one may have never been active under deep-sea conditions. We wanted to analyze the principal ability of cultivable heterotrophic flagellates of different phylogenetic groups (choanoflagellates, ancyromonads, euglenids, kinetoplastids, bicosoecids, chrysomonads, and cercozoans) to survive exposure to high hydrostatic pressure (up to 670 bar). We summarized our own studies and the few available data from literature on pressure tolerances of flagellates isolated from different marine habitats. Our results demonstrated that many different flagellate species isolated from the surface waters and deep-sea sediments survived drastic changes in hydrostatic pressure. Barophilic behavior was also recorded for several species isolated from the deep sea indicating their possible genetic adaptation to high pressures. This is in accordance with records of heterotrophic flagellates present in environmental DNA surveys based on clone libraries established for deep-sea environments.

How does mesoscale impact deep convection? Answers from ensemble Northwestern Mediterranean Sea simulations.

NASA Astrophysics Data System (ADS)

Waldman, Robin; Herrmann, Marine; Somot, Samuel; Arsouze, Thomas; Benshila, Rachid; Bosse, Anthony; Chanut, Jérôme; Giordani, Hervé; Pennel, Romain; Sevault, Florence; Testor, Pierre

2017-04-01

Ocean deep convection is a major process of interaction between surface and deep ocean. The Gulf of Lions is a well-documented deep convection area in the Mediterranean Sea, and mesoscale dynamics is a known factor impacting this phenomenon. However, previous modelling studies don't allow to address the robustness of its impact with respect to the physical configuration and ocean intrinsic variability. In this study, the impact of mesoscale on ocean deep convection in the Gulf of Lions is investigated using a multi-resolution ensemble simulation of the northwestern Mediterranean sea. The eddy-permitting Mediterranean model NEMOMED12 (6km resolution) is compared to its eddy-resolving counterpart with the 2-way grid refinement AGRIF in the northwestern Mediterranean (2km resolution). We focus on the well-documented 2012-2013 period and on the multidecadal timescale (1979-2013). The impact of mesoscale on deep convection is addressed in terms of its mean and variability, its impact on deep water transformations and on associated dynamical structures. Results are interpreted by diagnosing regional mean and eddy circulation and using buoyancy budgets. We find a mean inhibition of deep convection by mesoscale with large interannual variability. It is associated with a large impact on mean and transient circulation and a large air-sea flux feedback.

Function and structure of the deep cervical extensor muscles in patients with neck pain.

PubMed

Schomacher, Jochen; Falla, Deborah

2013-10-01

The deep cervical extensors are anatomically able to control segmental movements of the cervical spine in concert with the deep cervical flexors. Several investigations have confirmed changes in cervical flexor muscle control in patients with neck pain and as a result, effective evidence-based therapeutic exercises have been developed to address such dysfunctions. However, knowledge on how the deep extensor muscles behave in patients with neck pain disorders is scare. Structural changes such as higher concentration of fat within the muscle, variable cross-sectional area and higher proportions of type II fibres have been observed in the deep cervical extensors of patients with neck pain compared to healthy controls. These findings suggest that the behaviour of the deep extensors may be altered in patients with neck pain. Consistent with this hypothesis, a recent series of studies confirm that patients display reduced activation of the deep cervical extensors as well as less defined activation patterns. This article provides an overview of the various different structural and functional changes in the deep neck extensor muscles documented in patients with neck pain. Relevant recommendations for the management of muscle dysfunction in patients with neck pain are presented. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

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

2018-06-06

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

Integrated Metagenomic and Metatranscriptomic Analyses of Microbial Communities in the Meso- and Bathypelagic Realm of North Pacific Ocean

PubMed Central

Wu, Jieying; Gao, Weimin; Johnson, Roger H.; Zhang, Weiwen; Meldrum, Deirdre R.

2013-01-01

Although emerging evidence indicates that deep-sea water contains an untapped reservoir of high metabolic and genetic diversity, this realm has not been studied well compared with surface sea water. The study provided the first integrated meta-genomic and -transcriptomic analysis of the microbial communities in deep-sea water of North Pacific Ocean. DNA/RNA amplifications and simultaneous metagenomic and metatranscriptomic analyses were employed to discover information concerning deep-sea microbial communities from four different deep-sea sites ranging from the mesopelagic to pelagic ocean. Within the prokaryotic community, bacteria is absolutely dominant (~90%) over archaea in both metagenomic and metatranscriptomic data pools. The emergence of archaeal phyla Crenarchaeota, Euryarchaeota, Thaumarchaeota, bacterial phyla Actinobacteria, Firmicutes, sub-phyla Betaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria, and the decrease of bacterial phyla Bacteroidetes and Alphaproteobacteria are the main composition changes of prokaryotic communities in the deep-sea water, when compared with the reference Global Ocean Sampling Expedition (GOS) surface water. Photosynthetic Cyanobacteria exist in all four metagenomic libraries and two metatranscriptomic libraries. In Eukaryota community, decreased abundance of fungi and algae in deep sea was observed. RNA/DNA ratio was employed as an index to show metabolic activity strength of microbes in deep sea. Functional analysis indicated that deep-sea microbes are leading a defensive lifestyle. PMID:24152557

The Immediate Effects of Deep Pressure on Young People with Autism and Severe Intellectual Difficulties: Demonstrating Individual Differences

PubMed Central

Bestbier, Lana

2017-01-01

Background Deep pressure is widely used by occupational therapists for people with autism spectrum disorders. There is limited research evaluating deep pressure. Objective To evaluate the immediate effects of deep pressure on young people with autism and severe intellectual disabilities. Methods Mood and behaviour were rated for 13 pupils with ASD and severe ID before and after deep pressure sessions. Results Sufficient data was available from 8 participants to be analysed using Tau-U, a nonparametric technique that allows for serial dependence in data. Six showed benefits statistically. Five of these showed benefits across all domains, and one showed benefits on three out of five domains. Relevance to Clinical Practice Deep pressure appears to be of immediate benefit to this population with autism and severe ID, but the heterogeneity of response suggests that careful monitoring of response should be used and deep pressure discontinued when it is no longer of benefit. Limitations This is an open label evaluation study using rating scales. Recommendations for Future Research Future studies of the use of deep pressure should use physiological response measures, in addition to blinded raters for aspects of behaviours such as attitude to learning psychological health not captured physiologically. PMID:29097980

Refinement of Strut-and-Tie Model for Reinforced Concrete Deep Beams

PubMed Central

Panjehpour, Mohammad; Chai, Hwa Kian; Voo, Yen Lei

2015-01-01

Deep beams are commonly used in tall buildings, offshore structures, and foundations. According to many codes and standards, strut-and-tie model (STM) is recommended as a rational approach for deep beam analyses. This research focuses on the STM recommended by ACI 318-11 and AASHTO LRFD and uses experimental results to modify the strut effectiveness factor in STM for reinforced concrete (RC) deep beams. This study aims to refine STM through the strut effectiveness factor and increase result accuracy. Six RC deep beams with different shear span to effective-depth ratios (a/d) of 0.75, 1.00, 1.25, 1.50, 1.75, and 2.00 were experimentally tested under a four-point bending set-up. The ultimate shear strength of deep beams obtained from non-linear finite element modeling and STM recommended by ACI 318-11 as well as AASHTO LRFD (2012) were compared with the experimental results. An empirical equation was proposed to modify the principal tensile strain value in the bottle-shaped strut of deep beams. The equation of the strut effectiveness factor from AASHTTO LRFD was then modified through the aforementioned empirical equation. An investigation on the failure mode and crack propagation in RC deep beams subjected to load was also conducted. PMID:26110268

Challenging Oil Bioremediation at Deep-Sea Hydrostatic Pressure

PubMed Central

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

2016-01-01

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

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

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

Hohman, Frederick M.; Hodas, Nathan O.; Chau, Duen Horng

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

The deep ocean under climate change

NASA Astrophysics Data System (ADS)

Levin, Lisa A.; Le Bris, Nadine

2015-11-01

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems.

Ocean science: Radiocarbon variability in the western North Atlantic during the last deglaciation

USGS Publications Warehouse

Robinson, L.F.; Adkins, J.F.; Keigwin, L.D.; Southon, J.; Fernandez, D.P.; Wang, S.-L.; Scheirer, D.S.

2005-01-01

We present a detailed history of glacial to Holocene radiocarbon in the deep western North Atlantic from deep-sea corals and paired benthic-planktonic foraminifera. The deglaciation is marked by switches between radiocarbon-enriched and -depleted waters, leading to large radiocarbon gradients in the water column. These changes played an important role in modulating atmospheric radiocarbon. The deep-ocean record supports the notion of a bipolar seesaw with increased Northern-source deep-water formation linked to Northern Hemisphere warming and the reverse. In contrast, the more frequent radiocarbon variations in the intermediate/deep ocean are associated with roughly synchronous changes at the poles.

Hot and sour in the deep ocean

NASA Astrophysics Data System (ADS)

Sabine, Christopher L.

2017-12-01

Stable layering in the ocean limits the rate that human-derived carbon dioxide can acidify the deep ocean. Now observations show that ocean warming, however, can enhance deep-ocean acidification through increased organic matter decomposition.

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

PubMed

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

2016-08-01

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

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.

deepTools2: a next generation web server for deep-sequencing data analysis.

PubMed

Ramírez, Fidel; Ryan, Devon P; Grüning, Björn; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S; Heyne, Steffen; Dündar, Friederike; Manke, Thomas

2016-07-08

We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

deepTools: a flexible platform for exploring deep-sequencing data.

PubMed

Ramírez, Fidel; Dündar, Friederike; Diehl, Sarah; Grüning, Björn A; Manke, Thomas

2014-07-01

We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg.de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Warming trend in the western Mediterranean deep water

NASA Astrophysics Data System (ADS)

Bethoux, J. P.; Gentili, B.; Raunet, J.; Tailliez, D.

1990-10-01

THE western Mediterranean Sea comprises three water masses: a surface layer (from 0 to ~150 m depth), an intermediate layer (~150-400 m) issuing from the eastern basin, and a deep water mass at depths below 400 m. The deep water is homogeneous and has maintained a more or less constant temperature and salinity from the start of the century until recently1. Here we report measurements from the Medatlante cruises of December 1988 and August 1989, which show the deep layer to be 0.12 °C warmer and ~0.03 p.s.u. more saline than in 1959. Taking these data together with those from earlier cruises, we find a trend of continuously increasing temperatures over the past three decades. These deep-water records reflect the averaged evolution of climate conditions at the surface during the winter, when the deep water is formed. Consideration of the heat budget and water flux in the Mediterranean2,3 leads to the possibility that the deep-water temperature trend may be the result of greenhouse-gas-induced local warming.

Towards ecosystem based management and monitoring of the deep Mediterranean, North-East Atlantic and Beyond

NASA Astrophysics Data System (ADS)

Grehan, Anthony J.; Arnaud-Haond, Sophie; D'Onghia, Gianfranco; Savini, Alessandra; Yesson, Chris

2017-11-01

The deep sea covers 65% of the earth's surface and 95% of the biosphere but only a very small fraction (less than 0.0001%) of this has been explored (Rogers et al., 2015; Taylor and Roterman, 2017). However, current knowledge indicates that the deep ocean is characterized by a high level of biodiversity and by the presence of important biological and non-renewable resources. As well as vast flat and muddy plains, the topography of the deep ocean contains a variety of complex and heterogeneous seafloor features, such as canyons, seamounts, cold seeps, hydrothermal vents and biogenic (deep-water coral) reefs and sponge bioherms that harbour an unquantified and diverse array of organisms. The deep sea, despite its remoteness, provides a variety of supporting, provisioning, regulating and cultural, ecosystem goods and services (Thurber et al., 2014). The recent push for 'Blue Growth', to unlock the potential of seas and oceans (European Commission, 2017) has increased the focus on the potential to exploit resources in the deep-sea and consequently the need for improved management (Thurber et al., 2014).

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Processing-Induced Electrically Active Defects in Black Silicon Nanowire Devices.

PubMed

Carapezzi, Stefania; Castaldini, Antonio; Mancarella, Fulvio; Poggi, Antonella; Cavallini, Anna

2016-04-27

Silicon nanowires (Si NWs) are widely investigated nowadays for implementation in advanced energy conversion and storage devices, as well as many other possible applications. Black silicon (BSi)-NWs are dry etched NWs that merge the advantages related to low-dimensionality with the special industrial appeal connected to deep reactive ion etching (RIE). In fact, RIE is a well established technique in microelectronics manufacturing. However, RIE processing could affect the electrical properties of BSi-NWs by introducing deep states into their forbidden gap. This work applies deep level transient spectroscopy (DLTS) to identify electrically active deep levels and the associated defects in dry etched Si NW arrays. Besides, the successful fitting of DLTS spectra of BSi-NWs-based Schottky barrier diodes is an experimental confirmation that the same theoretical framework of dynamic electronic behavior of deep levels applies in bulk as well as in low dimensional structures like NWs, when quantum confinement conditions do not occur. This has been validated for deep levels associated with simple pointlike defects as well as for deep levels associated with defects with richer structures, whose dynamic electronic behavior implies a more complex picture.

Extracting Databases from Dark Data with DeepDive.

PubMed

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data : the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data - scientific papers, Web classified ads, customer service notes, and so on - were instead in a relational database, it would give analysts a massive and valuable new set of "big data." DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference.

Identification of the spatial location of deep trap states in AlGaN/GaN heterostructures by surface photovoltage spectroscopy

NASA Astrophysics Data System (ADS)

Jana, Dipankar; Porwal, S.; Sharma, T. K.

2017-12-01

Spatial and spectral origin of deep level defects in molecular beam epitaxy grown AlGaN/GaN heterostructures are investigated by using surface photovoltage spectroscopy (SPS) and pump-probe SPS techniques. A deep trap center ∼1 eV above the valence band is observed in SPS measurements which is correlated with the yellow luminescence feature in GaN. Capture of electrons and holes is resolved by performing temperature dependent SPS and pump-probe SPS measurements. It is found that the deep trap states are distributed throughout the sample while their dominance in SPS spectra depends on the density, occupation probability of deep trap states and the background electron density of GaN channel layer. Dynamics of deep trap states associated with GaN channel layer is investigated by performing frequency dependent photoluminescence (PL) and SPS measurements. A time constant of few millisecond is estimated for the deep defects which might limit the dynamic performance of AlGaN/GaN based devices.

Species-energy relationship in the deep sea: A test using the Quaternary fossil record

USGS Publications Warehouse

Hunt, G.; Cronin, T. M.; Roy, K.

2005-01-01

Little is known about the processes regulating species richness in deep-sea communities. Here we take advantage of natural experiments involving climate change to test whether predictions of the species-energy hypothesis hold in the deep sea. In addition, we test for the relationship between temperature and species richness predicted by a recent model based on biochemical kinetics of metabolism. Using the deep-sea fossil record of benthic foraminifera and statistical meta-analyses of temperature-richness and productivity-richness relationships in 10 deep-sea cores, we show that temperature but not productivity is a significant predictor of species richness over the past c. 130 000 years. Our results not only show that the temperature-richness relationship in the deep-sea is remarkably similar to that found in terrestrial and shallow marine habitats, but also that species richness tracks temperature change over geological time, at least on scales of c. 100 000 years. Thus, predicting biotic response to global climate change in the deep sea would require better understanding of how temperature regulates the occurrences and geographical ranges of species. ??2005 Blackwell Publishing Ltd/CNRS.

Key Challenges for Life Science Payloads on the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Anthony, J. H.; Niederwieser, T.; Zea, L.; Stodieck, L.

2018-02-01

Compared to ISS, Deep Space Gateway life science payloads will be challenged by deep space radiation and non-continuous habitation. The impacts of these two differences on payload requirements, design, and operations are discussed.

The Gateway Garden — A Prototype Food Production Facility for Deep Space Exploration

NASA Astrophysics Data System (ADS)

Fritsche, R. F.; Romeyn, M. W.; Massa, G.

2018-02-01

CIS-lunar space provides a unique opportunity to perform deep space microgravity crop science research while also addressing and advancing food production technologies that will be deployed on the Deep Space Transport.

Eco-Philosophy and Deep Ecology.

ERIC Educational Resources Information Center

Skolimowski, Henryk

1988-01-01

Criticizes the Deep Ecology Movement as a new ecological world view. Discusses the limits of this philosophy including its views of destiny, evolution and cosmology. Concludes that although its intentions are admirable, Deep Ecology leaves too much unanswered. (CW)

Microbial Life in the Deep Subsurface: Deep, Hot and Radioactive

NASA Technical Reports Server (NTRS)

DeStefano, Andrea L.; Ford, Jill C.; Winsor, Seana K.; Allen, Carlton C.; Miller, Judith; McNamara, Karen M.; Gibson, Everett K., Jr.

2000-01-01

Recent studies, motivated in part by the search for extraterrestrial life, continue to expand the recognized limits of Earth's biosphere. This work explored evidence for life a high-temperature, radioactive environment in the deep subsurface.

Compact, High-Power, Fiber-Laser-Based Coherent Sources Tunable in the Mid-Infrared and THz Spectrum

DTIC Science & Technology

2015-02-20

conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 μm. We have successfully developed... oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 µm. We have successfully developed tunable deep mid-IR systems in both...the advancement of nonlinear frequency conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid- IR) spectral

30 CFR 203.49 - May I substitute the deep gas drilling provisions in § 203.0 and §§ 203.40 through 203.47 for the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false May I substitute the deep gas drilling... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.49 May I...

Towards deep learning with segregated dendrites

PubMed Central

Guerguiev, Jordan; Lillicrap, Timothy P

2017-01-01

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations—the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons. PMID:29205151

Towards deep learning with segregated dendrites.

PubMed

Guerguiev, Jordan; Lillicrap, Timothy P; Richards, Blake A

2017-12-05

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations-the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons.

Deep learning with convolutional neural network in radiology.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Kiryu, Shigeru; Abe, Osamu

2018-04-01

Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the learning process is not required. Important features can be automatically learned. Thanks to the development of hardware and software in addition to techniques regarding deep learning, application of this technique to radiological images for predicting clinically useful information, such as the detection and the evaluation of lesions, etc., are beginning to be investigated. This article illustrates basic technical knowledge regarding deep learning with CNNs along the actual course (collecting data, implementing CNNs, and training and testing phases). Pitfalls regarding this technique and how to manage them are also illustrated. We also described some advanced topics of deep learning, results of recent clinical studies, and the future directions of clinical application of deep learning techniques.

Microplastic pollution in deep-sea sediments.

PubMed

Van Cauwenberghe, Lisbeth; Vanreusel, Ann; Mees, Jan; Janssen, Colin R

2013-11-01

Microplastics are small plastic particles (<1 mm) originating from the degradation of larger plastic debris. These microplastics have been accumulating in the marine environment for decades and have been detected throughout the water column and in sublittoral and beach sediments worldwide. However, up to now, it has never been established whether microplastic presence in sediments is limited to accumulation hot spots such as the continental shelf, or whether they are also present in deep-sea sediments. Here we show, for the first time ever, that microplastics have indeed reached the most remote of marine environments: the deep sea. We found plastic particles sized in the micrometre range in deep-sea sediments collected at four locations representing different deep-sea habitats ranging in depth from 1100 to 5000 m. Our results demonstrate that microplastic pollution has spread throughout the world's seas and oceans, into the remote and largely unknown deep sea. Copyright © 2013. Published by Elsevier Ltd.

Possible seasonality in large deep-focus earthquakes

NASA Astrophysics Data System (ADS)

Zhan, Zhongwen; Shearer, Peter M.

2015-09-01

Large deep-focus earthquakes (magnitude > 7.0, depth > 500 km) have exhibited strong seasonality in their occurrence times since the beginning of global earthquake catalogs. Of 60 such events from 1900 to the present, 42 have occurred in the middle half of each year. The seasonality appears strongest in the northwest Pacific subduction zones and weakest in the Tonga region. Taken at face value, the surplus of northern hemisphere summer events is statistically significant, but due to the ex post facto hypothesis testing, the absence of seasonality in smaller deep earthquakes, and the lack of a known physical triggering mechanism, we cannot rule out that the observed seasonality is just random chance. However, we can make a testable prediction of seasonality in future large deep-focus earthquakes, which, given likely earthquake occurrence rates, should be verified or falsified within a few decades. If confirmed, deep earthquake seasonality would challenge our current understanding of deep earthquakes.

Interaction of deep and shallow convection is key to Madden-Julian Oscillation simulation

NASA Astrophysics Data System (ADS)

Zhang, Guang J.; Song, Xiaoliang

2009-05-01

This study investigates the role of the interaction between deep and shallow convection in MJO simulation using the NCAR CAM3. Two simulations were performed, one using a revised Zhang-McFarlane convection scheme for deep convection and the Hack scheme for shallow convection, and the other disallowing shallow convection below 700 mb in the tropical belt. The two simulations produce dramatically different MJO characteristics. While the control simulation produces realistic MJOs, the simulation without shallow convection has very weak MJO signals in the Indian Ocean and western Pacific. Composite analysis finds that shallow convection serves to precondition the lower troposphere by moistening it ahead of deep convection. It also produces enhanced low-level mass convergence below 850 mb ahead of deep convection. This work, together with previous studies, suggests that a correct simulation of the interaction between deep and shallow convection is key to MJO simulation in global climate models.

Occult pulmonary embolism: a common occurrence in deep venous thrombosis

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

Dorfman, G.S.; Cronan, J.J.; Tupper, T.B.

1987-02-01

Ventilation-perfusion scans were used in a prospective study to determine the prevalence of occult pulmonary embolus in proven deep venous thrombosis. Fifty-eight patients without symptoms of pulmonary embolism, but with venographically proven deep venous thrombosis, were subjected to chest radiographs, /sup 99m/Tc macroaggregated-albumin perfusion scans, and /sup 133/Xe ventilation scans. Of the 49 patients with deep venous thrombosis proximal to the calf veins, 17 (35%) had high-probability scans. Of all 58 patients, only 12 (21%) had normal scans. When the study population was compared with a group of 430 patients described in reports of pulmonary perfusion in asymptomatic persons, amore » significantly higher percentage of high-probability scans was found in the study population with deep venous thrombosis. Baseline ventilation-perfusion lung scanning is valuable for patients with proven above-knee deep venous thrombosis.« less

Deep-Sea Microbes: Linking Biogeochemical Rates to -Omics Approaches

NASA Astrophysics Data System (ADS)

Herndl, G. J.; Sintes, E.; Bayer, B.; Bergauer, K.; Amano, C.; Hansman, R.; Garcia, J.; Reinthaler, T.

2016-02-01

Over the past decade substantial progress has been made in determining deep ocean microbial activity and resolving some of the enigmas in understanding the deep ocean carbon flux. Also, metagenomics approaches have shed light onto the dark ocean's microbes but linking -omics approaches to biogeochemical rate measurements are generally rare in microbial oceanography and even more so for the deep ocean. In this presentation, we will show by combining metagenomics, -proteomics and biogeochemical rate measurements on the bulk and single-cell level that deep-sea microbes exhibit characteristics of generalists with a large genome repertoire, versatile in utilizing substrate as revealed by metaproteomics. This is in striking contrast with the apparently rather uniform dissolved organic matter pool in the deep ocean. Combining the different -omics approaches with metabolic rate measurements, we will highlight some major inconsistencies and enigmas in our understanding of the carbon cycling and microbial food web structure in the dark ocean.

Thermal quenching effect of an infrared deep level in Mg-doped p-type GaN films

NASA Astrophysics Data System (ADS)

Kim, Keunjoo; Chung, Sang Jo

2002-03-01

The thermal quenching of an infrared deep level of 1.2-1.5 eV has been investigated on Mg-doped p-type GaN films, using one- and two-step annealing processes and photocurrent measurements. The deep level appeared in the one-step annealing process at a relatively high temperature of 900 °C, but disappeared in the two-step annealing process with a low-temperature step and a subsequent high-temperature step. The persistent photocurrent was residual in the sample including the deep level, while it was terminated in the sample without the deep level. This indicates that the deep level is a neutral hole center located above a quasi-Fermi level, estimated with an energy of EpF=0.1-0.15 eV above the valence band at a hole carrier concentration of 2.0-2.5×1017/cm3.

Fluorescence characteristics in the deep waters of South Gulf of México.

PubMed

Schifter, I; Sánchez-Reyna, G; González-Macías, C; Salazar-Coria, L; González-Lozano, C

2017-10-15

Vertical profiles of deep-water fluorescence determined by the chlorophyll sensor, polycyclic aromatic hydrocarbons, biomarkers, and other miscellaneous parameters measured in the southern Gulf of Mexico are reported. In the course of the survey, unexpected deep fluorescences were recorded (>1100m depth) in half of the 40 stations studied, a novel finding in this area of the Gulf. Currently, the deep-water fluorescence phenomenon is not completely understood, however we observe linear correlation between the fluorescence intensity and chlorophyll-α concentrations and coincidence of higher number of hydrocarbonoclastic bacteria in samples collected precisely in the deep-water fluorescence. This information is particularly interesting in relation to the Deepwater Horizon oil spill in 2010, in view that the aftermaths of the spill can be observed till today as oil plumes trapped in deep water layers that may disturb the natural water ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vertical distribution of living ostracods in deep-sea sediments, North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Jöst, Anna B.; Yasuhara, Moriaki; Okahashi, Hisayo; Ostmann, Alexandra; Arbizu, Pedro Martínez; Brix, Saskia

2017-04-01

The depth distribution of living specimens of deep-sea benthic ostracods (small crustaceans with calcareous shells that are preserved as microfossils) in sediments is poorly understood, despite the importance of this aspect of basic ostracod biology for paleoecologic and paleoceanographic interpretations. Here, we investigated living benthic ostracod specimens from deep-sea multiple core samples, to reveal their depths distributions within sediment cores. The results showed shallow distribution and low population density of living deep-sea benthic ostracods (which are mostly composed of Podocopa). The living specimens are concentrated in the top 1 cm of the sediment, hence deep-sea benthic ostracods are either epifauna or shallow infauna. This observation is consistent with the information from shallow-water species. We also confirmed shallow infaunal (0.5-2 cm) and very shallow infaunal (0-1 cm) habitats of the deep-sea ostracod genera Krithe and Argilloecia, respectively.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

PubMed

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

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.

Multiscale deep features learning for land-use scene recognition

NASA Astrophysics Data System (ADS)

Yuan, Baohua; Li, Shijin; Li, Ning

2018-01-01

The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.

Effect of swift heavy ion irradiation on deep levels in Au /n-Si (100) Schottky diode studied by deep level transient spectroscopy

NASA Astrophysics Data System (ADS)

Kumar, Sandeep; Katharria, Y. S.; Kumar, Sugam; Kanjilal, D.

2007-12-01

In situ deep level transient spectroscopy has been applied to investigate the influence of 100MeV Si7+ ion irradiation on the deep levels present in Au/n-Si (100) Schottky structure in a wide fluence range from 5×109to1×1012ions cm-2. The swift heavy ion irradiation introduces a deep level at Ec-0.32eV. It is found that initially, trap level concentration of the energy level at Ec-0.40eV increases with irradiation up to a fluence value of 1×1010cm-2 while the deep level concentration decreases as irradiation fluence increases beyond the fluence value of 5×1010cm-2. These results are discussed, taking into account the role of energy transfer mechanism of high energy ions in material.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Changes in chemical composition of frozen coated fish products during deep-frying.

PubMed

Pérez-Palacios, Trinidad; Petisca, Catarina; Casal, Susana; Ferreira, Isabel M P L V O

2014-03-01

This work evaluates the influence of deep-frying coated fish products on total fat, fatty acid (FA) and amino acid profile, and on the formation of volatile compounds, with special attention on furan and its derivatives due to their potential harmful characteristics. As expected, deep-frying in sunflower oil increased linoleic acid content, but total fat amount increased only by 2% on a dry basis. Eicosapentanoic and docosahexanoic acids were preserved while γ- and α-linoleic acids were oxidised. Deep-frying also induces proteolysis, releasing free AA, and the formation of volatile compounds, particularly aldehydes and ketones arising from polyunsaturated FA. In addition, high quantities of furanic compounds, particularly furan and furfuryl alcohol, are generated during deep-frying coated fish. The breaded crust formed could contribute simultaneously for the low uptake of fat, preservation of long chain n-3 FA, and for the high amounts of furanic compounds formed during the deep-frying process.

Introduction: From pathogenesis to therapy, deep endometriosis remains a source of controversy.

PubMed

Donnez, Jacques

2017-12-01

Deep endometriosis remains a source of controversy. A number of theories may explain its pathogenesis and many arguments support the hypothesis that genetic or epigenetic changes are a prerequisite for development of lesions into deep endometriosis. Deep endometriosis is frequently responsible for pelvic pain, dysmenorrhea, and/or deep dyspareunia, but can also cause obstetrical complications. Diagnosis may be improved by high-quality imaging. Therapeutic approaches are a source of contention as well. In this issue's Views and Reviews, medical and surgical strategies are discussed, and it is emphasized that treatment should be designed according to a patient's symptoms and individual needs. It is also vital that referral centers have the knowledge and experience to treat deep endometriosis medically and/or surgically. The debate must continue because emerging trends in therapy need to be followed and investigated for optimal management. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Deep Direct Reinforcement Learning for Financial Signal Representation and Trading.

PubMed

Deng, Yue; Bao, Feng; Kong, Youyong; Ren, Zhiquan; Dai, Qionghai

2017-03-01

Can we train the computer to beat experienced traders for financial assert trading? In this paper, we try to address this challenge by introducing a recurrent deep neural network (NN) for real-time financial signal representation and trading. Our model is inspired by two biological-related learning concepts of deep learning (DL) and reinforcement learning (RL). In the framework, the DL part automatically senses the dynamic market condition for informative feature learning. Then, the RL module interacts with deep representations and makes trading decisions to accumulate the ultimate rewards in an unknown environment. The learning system is implemented in a complex NN that exhibits both the deep and recurrent structures. Hence, we propose a task-aware backpropagation through time method to cope with the gradient vanishing issue in deep training. The robustness of the neural system is verified on both the stock and the commodity future markets under broad testing conditions.

Immediate versus delayed intramedullary nailing for open fractures of the tibial shaft: a multivariate analysis of factors affecting deep infection and fracture healing.

PubMed

Yokoyama, Kazuhiko; Itoman, Moritoshi; Uchino, Masataka; Fukushima, Kensuke; Nitta, Hiroshi; Kojima, Yoshiaki

2008-10-01

The purpose of this study was to evaluate contributing factors affecting deep infection and fracture healing of open tibia fractures treated with locked intramedullary nailing (IMN) by multivariate analysis. We examined 99 open tibial fractures (98 patients) treated with immediate or delayed locked IMN in static fashion from 1991 to 2002. Multivariate analyses following univariate analyses were derived to determine predictors of deep infection, nonunion, and healing time to union. The following predictive variables of deep infection were selected for analysis: age, sex, Gustilo type, fracture grade by AO type, fracture location, timing or method of IMN, reamed or unreamed nailing, debridement time (< or =6 h or >6 h), method of soft-tissue management, skin closure time (< or =1 week or >1 week), existence of polytrauma (ISS< 18 or ISS> or =18), existence of floating knee injury, and existence of superficial/pin site infection. The predictive variables of nonunion selected for analysis was the same as those for deep infection, with the addition of deep infection for exchange of pin site infection. The predictive variables of union time selected for analysis was the same as those for nonunion, excluding of location, debridement time, and existence of floating knee and superficial infection. Six (6.1%; type II Gustilo n=1, type IIIB Gustilo n=5) of the 99 open tibial fractures developed deep infections. Multivariate analysis revealed that timing or method of IMN, debridement time, method of soft-tissue management, and existence of superficial or pin site infection significantly correlated with the occurrence of deep infection (P< 0.0001). In the immediate nailing group alone, the deep infection rate in type IIIB + IIIC was significantly higher than those in type I + II and IIIA (P = 0.016). Nonunion occurred in 17 fractures (20.3%, 17/84). Multivariate analysis revealed that Gustilo type, skin closure time, and existence of deep infection significantly correlated with occurrence of nonunion (P < 0.05). Gustilo type and existence of deep infection were significantly correlated with healing time to union on multivariate analysis (r(2) = 0.263, P = 0.0001). Multivariate analyses for open tibial fractures treated with IMN showed that IMN after EF (especially in existence of pin site infection) was at high risk of deep infection, and that debridement within 6 h and appropriate soft-tissue managements were also important factor in preventing deep infections. These analyses postulated that both the Gustilo type and the existence of deep infection is related with fracture healing in open fractures treated with IMN. In addition, immediate IMN for type IIIB and IIIC is potentially risky, and canal reaming did not increase the risk of complication for open tibial fractures treated with IMN.

Responses of the deep ocean carbonate system to carbon reorganization during the Last Glacial-interglacial cycle

NASA Astrophysics Data System (ADS)

Yu, Jimin; Anderson, Robert F.; Jin, Zhangdong; Rae, James W. B.; Opdyke, Bradley N.; Eggins, Stephen M.

2013-09-01

We present new deep water carbonate ion concentration ([CO32-]) records, reconstructed using Cibicidoides wuellerstorfi B/Ca, for one core from Caribbean Basin (water depth = 3623 m, sill depth = 1.8 km) and three cores located at 2.3-4.3 km water depth from the equatorial Pacific Ocean during the Last Glacial-interglacial cycle. The pattern of deep water [CO32-] in the Caribbean Basin roughly mirrors that of atmospheric CO2, reflecting a dominant influence from preformed [CO32-] in the North Atlantic Ocean. Compared to the amplitude of ˜65 μmol/kg in the deep Caribbean Basin, deep water [CO32-] in the equatorial Pacific Ocean has varied by no more than ˜15 μmol/kg due to effective buffering of CaCO3 on deep-sea pH in the Pacific Ocean. Our results suggest little change in the global mean deep ocean [CO32-] between the Last Glacial Maximum (LGM) and the Late Holocene. The three records from the Pacific Ocean show long-term increases in [CO32-] by ˜7 μmol/kg from Marine Isotope Stage (MIS) 5c to mid MIS 3, consistent with the response of the deep ocean carbonate system to a decline in neritic carbonate production associated with ˜60 m drop in sea-level (the “coral-reef” hypothesis). Superimposed upon the long-term trend, deep water [CO32-] in the Pacific Ocean displays transient changes, which decouple with δ13C in the same cores, at the start and end of MIS 4. These changes in [CO32-] and δ13C are consistent with what would be expected from vertical nutrient fractionation and carbonate compensation. The observed ˜4 μmol/kg [CO32-] decline in the two Pacific cores at >3.4 km water depth from MIS 3 to the LGM indicate further strengthening of deep ocean stratification, which contributed to the final step of atmospheric CO2 drawdown during the last glaciation. The striking similarity between deep water [CO32-] and 230Th-normalized CaCO3 flux at two adjacent sites from the central equatorial Pacific Ocean provides convincing evidence that deep-sea carbonate dissolution dominantly controlled CaCO3 preservation at these sites in the past. Our results offer new and quantitative constraints from deep ocean carbonate chemistry to understand roles of various mechanisms in atmospheric CO2 changes over the Last Glacial-interglacial cycle.

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.

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

PubMed

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

Cyriax's deep friction massage application parameters: Evidence from a cross-sectional study with physiotherapists.

PubMed

Chaves, Paula; Simões, Daniela; Paço, Maria; Pinho, Francisco; Duarte, José Alberto; Ribeiro, Fernando

2017-12-01

Deep friction massage is one of several physiotherapy interventions suggested for the management of tendinopathy. To determine the prevalence of deep friction massage use in clinical practice, to characterize the application parameters used by physiotherapists, and to identify empirical model-based patterns of deep friction massage application in degenerative tendinopathy. observational, analytical, cross-sectional and national web-based survey. 478 physiotherapists were selected through snow-ball sampling method. The participants completed an online questionnaire about personal and professional characteristics as well as specific questions regarding the use of deep friction massage. Characterization of deep friction massage parameters used by physiotherapists were presented as counts and proportions. Latent class analysis was used to identify the empirical model-based patterns. Crude and adjusted odds ratios and 95% confidence intervals were computed. The use of deep friction massage was reported by 88.1% of the participants; tendinopathy was the clinical condition where it was most frequently used (84.9%) and, from these, 55.9% reported its use in degenerative tendinopathy. The "duration of application" parameters in chronic phase and "frequency of application" in acute and chronic phases are those that diverge most from those recommended by the author of deep friction massage. We found a high prevalence of deep friction massage use, namely in degenerative tendinopathy. Our results have shown that the application parameters are heterogeneous and diverse. This is reflected by the identification of two application patterns, although none is in complete agreement with Cyriax's description. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of deep moonquake source parameters: Implication for fault characteristics and thermal state

NASA Astrophysics Data System (ADS)

Kawamura, Taichi; Lognonné, Philippe; Nishikawa, Yasuhiro; Tanaka, Satoshi

2017-07-01

While deep moonquakes are seismic events commonly observed on the Moon, their source mechanism is still unexplained. The two main issues are poorly constrained source parameters and incompatibilities between the thermal profiles suggested by many studies and the apparent need for brittle properties at these depths. In this study, we reinvestigated the deep moonquake data to reestimate its source parameters and uncover the characteristics of deep moonquake faults that differ from those on Earth. We first improve the estimation of source parameters through spectral analysis using "new" broadband seismic records made by combining those of the Apollo long- and short-period seismometers. We use the broader frequency band of the combined spectra to estimate corner frequencies and DC values of spectra, which are important parameters to constrain the source parameters. We further use the spectral features to estimate seismic moments and stress drops for more than 100 deep moonquake events from three different source regions. This study revealed that deep moonquake faults are extremely smooth compared to terrestrial faults. Second, we reevaluate the brittle-ductile transition temperature that is consistent with the obtained source parameters. We show that the source parameters imply that the tidal stress is the main source of the stress glut causing deep moonquakes and the large strain rate from tides makes the brittle-ductile transition temperature higher. Higher transition temperatures open a new possibility to construct a thermal model that is consistent with deep moonquake occurrence and pressure condition and thereby improve our understandings of the deep moonquake source mechanism.

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

Deep-sea genetic resources: New frontiers for science and stewardship in areas beyond national jurisdiction

NASA Astrophysics Data System (ADS)

Harden-Davies, Harriet

2017-03-01

The deep-sea is a large source of marine genetic resources (MGR), which have many potential uses and are a growing area of research. Much of the deep-sea lies in areas beyond national jurisdiction (ABNJ), including 65% of the global ocean. MGR in ABNJ occupy a significant gap in the international legal framework. Access and benefit sharing of MGR is a key issue in the development of a new international legally-binding instrument under the United Nations Convention on the Law of the Sea (UNCLOS) for the conservation and sustainable use of marine biological diversity in ABNJ. This paper examines how this is relevant to deep-sea scientific research and identifies emerging challenges and opportunities. There is no internationally agreed definition of MGR, however, deep-sea genetic resources could incorporate any biological material including genes, proteins and natural products. Deep-sea scientific research is the key actor accessing MGR in ABNJ and sharing benefits such as data, samples and knowledge. UNCLOS provides the international legal framework for marine scientific research, international science cooperation, capacity building and marine technology transfer. Enhanced implementation could support access and benefit sharing of MGR in ABNJ. Deep-sea scientific researchers could play an important role in informing practical new governance solutions for access and benefit sharing of MGR that promote scientific research in ABNJ and support deep-sea stewardship. Advancing knowledge of deep-sea biodiversity in ABNJ, enhancing open-access to data and samples, standardisation and international marine science cooperation are significant potential opportunity areas.

Semantic Typicality Effects in Acquired Dyslexia: Evidence for Semantic Impairment in Deep Dyslexia.

PubMed

Riley, Ellyn A; Thompson, Cynthia K

2010-06-01

BACKGROUND: Acquired deep dyslexia is characterized by impairment in grapheme-phoneme conversion and production of semantic errors in oral reading. Several theories have attempted to explain the production of semantic errors in deep dyslexia, some proposing that they arise from impairments in both grapheme-phoneme and lexical-semantic processing, and others proposing that such errors stem from a deficit in phonological production. Whereas both views have gained some acceptance, the limited evidence available does not clearly eliminate the possibility that semantic errors arise from a lexical-semantic input processing deficit. AIMS: To investigate semantic processing in deep dyslexia, this study examined the typicality effect in deep dyslexic individuals, phonological dyslexic individuals, and controls using an online category verification paradigm. This task requires explicit semantic access without speech production, focusing observation on semantic processing from written or spoken input. METHODS #ENTITYSTARTX00026; PROCEDURES: To examine the locus of semantic impairment, the task was administered in visual and auditory modalities with reaction time as the primary dependent measure. Nine controls, six phonological dyslexic participants, and five deep dyslexic participants completed the study. OUTCOMES #ENTITYSTARTX00026; RESULTS: Controls and phonological dyslexic participants demonstrated a typicality effect in both modalities, while deep dyslexic participants did not demonstrate a typicality effect in either modality. CONCLUSIONS: These findings suggest that deep dyslexia is associated with a semantic processing deficit. Although this does not rule out the possibility of concomitant deficits in other modules of lexical-semantic processing, this finding suggests a direction for treatment of deep dyslexia focused on semantic processing.

StarNet: An application of deep learning in the analysis of stellar spectra

NASA Astrophysics Data System (ADS)

Kielty, Collin; Bialek, Spencer; Fabbro, Sebastien; Venn, Kim; O'Briain, Teaghan; Jahandar, Farbod; Monty, Stephanie

2018-06-01

In an era when spectroscopic surveys are capable of collecting spectra for hundreds of thousands of stars, fast and efficient analysis methods are required to maximize scientific impact. These surveys provide a homogeneous database of stellar spectra that are ideal for machine learning applications. In this poster, we present StarNet: a convolutional neural network model applied to the analysis of both SDSS-III APOGEE DR13 and synthetic stellar spectra. When trained on synthetic spectra alone, the calculated stellar parameters (temperature, surface gravity, and metallicity) are of excellent precision and accuracy for both APOGEE data and synthetic data, over a wide range of signal-to-noise ratios. While StarNet was developed using the APOGEE observed spectra and corresponding ASSeT synthetic grid, we suggest that this technique is applicable to other spectral resolutions, spectral surveys, and wavelength regimes. As a demonstration of this, we present a StarNet model trained on lower resolution, R=6000, IR synthetic spectra, describing the spectra delivered by Gemini/NIFS and the forthcoming Gemini/GIRMOS instrument (PI Sivanandam, UToronto). Preliminary results suggest that the stellar parameters determined from this low resolution StarNet model are comparable in precision to the high-resolution APOGEE results. The success of StarNet at lower resolution can be attributed to (1) a large training set of synthetic spectra (N ~200,000) with a priori stellar labels, and (2) the use of the entire spectrum in the solution rather than a few weighted windows, which are common methods in other spectral analysis tools (e.g. FERRE or The Cannon). Remaining challenges in our StarNet applications include rectification, continuum normalization, and wavelength coverage. Solutions to these problems could be used to guide decisions made in the development of future spectrographs, spectroscopic surveys, and data reduction pipelines, such as for the future MSE.

VizieR Online Data Catalog: Imaging and spectroscopy in Lynx W (Jorgensen+, 2014)

NASA Astrophysics Data System (ADS)

Jorgensen, I.; Chiboucas, K.; Toft, S.; Bergmann, M.; Zirm, A.; Schiavon, R. P.; Grutzbauch, R.

2017-01-01

Ground-based imaging of RX J0848.6+4453 was obtained primarily to show the performance gain provided by replacing the original E2V charge-coupled devices (E2V CCDs) in Gemini Multi-Object Spectrograph on Gemini North (GMOS-N) with E2V Deep Depletion CCDs (E2V DD CCDs). This replacement was done in 2011 October. Imaging of RX J0848.6+4453 was obtained with the original E2V CCDs in 2011 October (UT 2011 Oct 1 to 2011 Oct 2; Program ID: GN-2011B-DD-3) and repeated with the E2V DD CCDs in 2011 November. The imaging was done in the z' filter. For the observations with the original E2V CCDs the total exposure time was 60 minutes (obtained as 12 five-minute exposures) and the co-added image had an image quality of FWHM=0.52'' measured from point sources in the field. For the E2V DD CCDs a total exposure time of 55 minutes was obtained and the resulting image quality was FWHM=0.51''. Imaging of RX J0848.6+4453 was also obtained with Hubble Space Telescope /Advanced Camera for Surveys (HST/ACS using the filters F775W and F850LP) under the program ID 9919. The spectroscopic observations were obtained in multi-object spectroscopic (MOS) mode with GMOS-N (UT 2011 Nov 24 to 2012 Jan 4, Program ID: GN-2011B-DD-5; UT 2013 Mar 9 to 2013 May 18, Program ID: GN-2013A-Q-65). Table10 lists the photometric parameters for the spectroscopic sample as derived from the HST/ACS observations in F850LP and F775W. Tables 11 and 12 list the results from the template fitting and the derived line strengths, respectively. (3 data files).

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

NASA Astrophysics Data System (ADS)

Bhattacharya, S.

2018-02-01

Life science research on the Deep Space Gateway platform is an important precursor for long term human exploration of deep space. Ideas for utilizing flight hardware and well characterized model organisms will be discussed.

Blood Clots That Kill: Preventing DVT | NIH MedlinePlus the Magazine

MedlinePlus

... please turn Javascript on. Feature: Deep Vein Thrombosis Blood Clots That Kill: Preventing DVT Past Issues / Spring 2011 ... Contents Deep vein thrombosis, or DVT, is a blood clot that forms in a vein deep in the ...

Implementation Experience with Deep Discount Fares

DOT National Transportation Integrated Search

1994-09-01

This report reviews the experiences of transit agencies across the country with Deep Discount fares, a new public transit pricing strategy, between 1988 and 1993. Based on new market research findings, Deep Discounting has shown that it is possible t...

Trophic Pathways of the Mid-North Atlantic

EPA Science Inventory

Because deep-sea fisheries are increasing as coastal fisheries decline, fisheries scientists need baseline data on deep-sea ecosystems prior to further development of deep-water fisheries. We present preliminary results and ongoing efforts to characterize the trophic structure a...

Enhanced Experience Replay for Deep Reinforcement Learning

DTIC Science & Technology

2015-11-01

ARL-TR-7538 ● NOV 2015 US Army Research Laboratory Enhanced Experience Replay for Deep Reinforcement Learning by David Doria...Experience Replay for Deep Reinforcement Learning by David Doria, Bryan Dawson, and Manuel Vindiola Computational and Information Sciences Directorate...

Genetics Home Reference: prothrombin thrombophilia

MedlinePlus

... risk for a type of clot called a deep venous thrombosis , which typically occurs in the deep veins of the legs. Affected people also have ... 3 links) GeneReview: Prothrombin-Related Thrombophilia MedlinePlus Encyclopedia: Deep venous ... Encyclopedia: Pulmonary embolus General Information ...

Depleted deep South China Sea δ13C paleoceanographic events in response to tectonic evolution in Taiwan-Luzon Strait since Middle Miocene

NASA Astrophysics Data System (ADS)

Chen, Wen-Huang; Huang, Chi-Yue; Lin, Yen-Jun; Zhao, Quanhong; Yan, Yi; Chen, Duofu; Zhang, Xinchang; Lan, Qing; Yu, Mengming

2015-12-01

The most distinctive feature of the deep South China Sea (SCS) paleoceanography is the occurrence of long-term depleted deep-sea benthic foraminiferal δ13C values. They are lower than the global and the Pacific composite records in the last 16 Ma, especially at 13.2, 10.5, 6.5, 3.0 and 1.2-0.4 Ma. This distinct deep SCS paleoceanograhic history coincides with the subduction-collision history in the Taiwan region where waters of the West Pacific (WP) and the SCS exchange. The depleted deep-sea benthic foraminiferal δ13C events indicate that the SCS deep basin became progressively a stagnant environment in the last 16 Ma due to either closure of the connection with the WP bottom water or temporary reduction of the WP deep water flowing into the deep SCS. Both the Taiwan accretionary prism and the Luzon arc became the main tectono-morphological barriers for the WP bottom water flowing into the SCS deep basin when eastward subduction of the SCS oceanic lithosphere beneath the Philippine Sea Plate started from the Middle Miocene (18-16 Ma). This began a long-term trend of depleted SCS deep-sea benthic δ13C values in the last 16 Ma. The oblique arc-continent collision since ~6.5 Ma uplifted the Taiwan accretionary prism rapidly above sea level and further isolated the SCS from the open Pacific. The collision simultaneously causes backthrusting deformations in the North Luzon Trough forearc basin and sequentially closes interarc water gates between volcanic islands from north to south. The Loho and the Taitung interarc water gates in the advanced collision zone were closed at ~3.0 Ma and ~1.2 Ma, coinciding with the very low SCS deep-sea benthic δ13C events at 3.0 and 1.2-0.4 Ma, respectively. The Taitung Canyon between the Lutao and Lanyu volcanic islands in the incipient collision zone is semi-closed presently. These closure events also lead to the result that the WP deep water intrudes westward into the SCS principally through the Bashi Channel between the Lanyu and Batan volcanic islands in the subduction zone.

In situ seismic anisotropy around deep earthquakes in Japan subduction slabs using Japan Meteorological Agency moment tensors

NASA Astrophysics Data System (ADS)

Li, J.; Zheng, Y.; Thomsen, L.

2017-12-01

Knowing the in situ seismic anisotropy around deep earthquakes in slabs is important in understanding deep-earthquake mechanism as it may provide critically needed information about the rock fabric where deep earthquakes occur. It has been recognized for about 50 years that many deep earthquakes are not double-couple (DC) events. Previously we showed that in situ anisotropy around deep earthquakes could explain such observed non-DC events. Traditionally, the shear wave splitting method has been used to infer such anisotropy around deep earthquakes but this is challenging because it will need many crossing ray paths for the method to localize the anisotropic region (Long 2013). In this abstract, we adopt the same procedure to obtain anisotropy in the Pacific slab under Japan using moment tensors provided by the Japan Meteorological Agency using the F-net data. We directly probe the in situ anisotropy within the subducting slabs using the radiation patterns (represented by the moment tensors) of deep earthquakes (with depth greater than 60 km). By assuming a group of shear dislocation events embedded in a common tilted transversely isotropic (TTI) medium, we used the moment tensors as our input data to invert for the anisotropy in Mariana-Japan-Kuril subducting zone. The TTI medium is characterized by the P and S wave velocities along the symmetry axis (described by two free angles) and three Thomsen parameters. We divided the deep earthquake events into 9 groups by their spatial proximity using the k-means clustering method (Hartigan and Wong 1979). These 9 groups include 2 intermediate-depth groups (depth from 60 km to 300 km) and 7 deep-focus groups (depth greater than 300 km). Our inversion results show that the inverted TTI symmetry axes are perpendicular to the slab interface for two intermediate-depth groups (consistent with dehydration metamorphic reactions) and parallel to the slab interface for 7 deep-focus group. The shear wave anisotropy is best resolved by our inversion algorithm with a typical value of around 28% (ranging from 25% to 41%). Our inverted anisotropy provides direct information of stress and rock fabric inside the subducting slab and may help explain the mechanisms of deep earthquakes.

Colonization of the deep sea by fishes

PubMed Central

Priede, I G; Froese, R

2013-01-01

Analysis of maximum depth of occurrence of 11 952 marine fish species shows a global decrease in species number (N) with depth (x; m): log10N = −0·000422x + 3·610000 (r2 = 0·948). The rate of decrease is close to global estimates for change in pelagic and benthic biomass with depth (−0·000430), indicating that species richness of fishes may be limited by food energy availability in the deep sea. The slopes for the Classes Myxini (−0·000488) and Actinopterygii (−0·000413) follow this trend but Chondrichthyes decrease more rapidly (−0·000731) implying deficiency in ability to colonize the deep sea. Maximum depths attained are 2743, 4156 and 8370 m for Myxini, Chondrichthyes and Actinopterygii, respectively. Endemic species occur in abundance at 7–7800 m depth in hadal trenches but appear to be absent from the deepest parts of the oceans, >9000 m deep. There have been six global oceanic anoxic events (OAE) since the origin of the major fish taxa in the Devonian c. 400 million years ago (mya). Colonization of the deep sea has taken place largely since the most recent OAE in the Cretaceous 94 mya when the Atlantic Ocean opened up. Patterns of global oceanic circulation oxygenating the deep ocean basins became established coinciding with a period of teleost diversification and appearance of the Acanthopterygii. Within the Actinopterygii, there is a trend for greater invasion of the deep sea by the lower taxa in accordance with the Andriashev paradigm. Here, 31 deep-sea families of Actinopterygii were identified with mean maximum depth >1000 m and with >10 species. Those with most of their constituent species living shallower than 1000 m are proposed as invasive, with extinctions in the deep being continuously balanced by export of species from shallow seas. Specialized families with most species deeper than 1000 m are termed deep-sea endemics in this study; these appear to persist in the deep by virtue of global distribution enabling recovery from regional extinctions. Deep-sea invasive families such as Ophidiidae and Liparidae make the greatest contribution to fish fauna at depths >6000 m. PMID:24298950

Rivaroxaban attenuates thrombosis by targeting the NF-κB signaling pathway in a rat model of deep venous thrombus

PubMed Central

Ma, Junhao; Li, Xinxi; Wang, Yang; Yang, Zhenwei; Luo, Jun

2017-01-01

Anticoagulant therapy is commonly used for the prevention and treatment of patients with deep venous thrombus. Evidence has shown that rivaroxaban is a potential oral anticoagulant drug for the acute treatment of venous thromboembolism. However, the rivaroxaban-mediated molecular mechanism involved in the progression of deep venous thrombosis has not been investigated. In the present study, we investigated the efficacy of rivaroxaban and the underlying signaling pathways in the prevention and treatment of rats with deep venous thrombosis. A rat model with deep vein thrombus formation was established and received treatment with rivaroxaban or PBS as control. The thrombin-activatable fibrinolysis inhibitor (TAFI) and plasminogen activator inhibitor-1 (PAI-1) were analyzed both in vitro and in vivo. The progression of thrombosis and stroke was evaluated after treatment with rivaroxaban or PBS. Nuclear factor-κB (NF-κB) signaling pathway in venous endothelial cells and in the rat model of deep venous thrombus was assessed. The therapeutic effects of rivaroxaban were evaluated as determined by changes in deep venous thrombosis in the rat model. Our results showed that rivaroxaban markedly inhibited TAFI and PAI-1 expression levels, neutrophils, tissue factor, neutrophil extracellular traps (NETs), myeloperoxidase and macrophages in venous endothelial cells and in the rat model of deep venous thrombus. Expression levels of ADP, PAIs, von Willebrand factor (vWF) and thromboxane were downregulated in vein endothelial cells and in serum from the experimental rats. Importantly, the incidences of inferior vena cava filter thrombus were protected by rivaroxaban during heparin-induced thrombolysis deep venous thrombosis in the rat model. We observed that activity of the NF-κB signaling pathway was inhibited by rivaroxaban in vein endothelial cells both in vitro and in vivo. Notably, immunohistology indicated that rivaroxaban attenuated deep venous thrombosis and the accumulation of inflammatory factors in the lesions in venous thrombus. Matrix metalloproteinase (MMP) expression and activity were downregulated in rivaroxaban-treated rats with deep venous thrombus. Rivaroxaban inhibited the elasticity of the extracellular matrix and collagen-elastin fibers. On the whole, these results indicate that rivaroxaban attenuates deep venous thrombus through MMP-9-mediated NF-κB signaling pathway. PMID:29039441

Rivaroxaban attenuates thrombosis by targeting the NF-κB signaling pathway in a rat model of deep venous thrombus.

PubMed

Ma, Junhao; Li, Xinxi; Wang, Yang; Yang, Zhenwei; Luo, Jun

2017-12-01

Anticoagulant therapy is commonly used for the prevention and treatment of patients with deep venous thrombus. Evidence has shown that rivaroxaban is a potential oral anticoagulant drug for the acute treatment of venous thromboembolism. However, the rivaroxaban-mediated molecular mechanism involved in the progression of deep venous thrombosis has not been investigated. In the present study, we investigated the efficacy of rivaroxaban and the underlying signaling pathways in the prevention and treatment of rats with deep venous thrombosis. A rat model with deep vein thrombus formation was established and received treatment with rivaroxaban or PBS as control. The thrombin-activatable fibrinolysis inhibitor (TAFI) and plasminogen activator inhibitor-1 (PAI-1) were analyzed both in vitro and in vivo. The progression of thrombosis and stroke was evaluated after treatment with rivaroxaban or PBS. Nuclear factor-κB (NF-κB) signaling pathway in venous endothelial cells and in the rat model of deep venous thrombus was assessed. The therapeutic effects of rivaroxaban were evaluated as determined by changes in deep venous thrombosis in the rat model. Our results showed that rivaroxaban markedly inhibited TAFI and PAI-1 expression levels, neutrophils, tissue factor, neutrophil extracellular traps (NETs), myeloperoxidase and macrophages in venous endothelial cells and in the rat model of deep venous thrombus. Expression levels of ADP, PAIs, von Willebrand factor (vWF) and thromboxane were downregulated in vein endothelial cells and in serum from the experimental rats. Importantly, the incidences of inferior vena cava filter thrombus were protected by rivaroxaban during heparin-induced thrombolysis deep venous thrombosis in the rat model. We observed that activity of the NF-κB signaling pathway was inhibited by rivaroxaban in vein endothelial cells both in vitro and in vivo. Notably, immunohistology indicated that rivaroxaban attenuated deep venous thrombosis and the accumulation of inflammatory factors in the lesions in venous thrombus. Matrix metalloproteinase (MMP) expression and activity were downregulated in rivaroxaban-treated rats with deep venous thrombus. Rivaroxaban inhibited the elasticity of the extracellular matrix and collagen-elastin fibers. On the whole, these results indicate that rivaroxaban attenuates deep venous thrombus through MMP-9-mediated NF-κB signaling pathway.

The deep ocean under climate change.

PubMed

Levin, Lisa A; Le Bris, Nadine

2015-11-13

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems. Copyright © 2015, American Association for the Advancement of Science.

Deep Sea Actinomycetes and Their Secondary Metabolites

PubMed Central

Kamjam, Manita; Sivalingam, Periyasamy; Deng, Zinxin; Hong, Kui

2017-01-01

Deep sea is a unique and extreme environment. It is a hot spot for hunting marine actinomycetes resources and secondary metabolites. The novel deep sea actinomycete species reported from 2006 to 2016 including 21 species under 13 genera with the maximum number from Microbacterium, followed by Dermacoccus, Streptomyces and Verrucosispora, and one novel species for the other 9 genera. Eight genera of actinomycetes were reported to produce secondary metabolites, among which Streptomyces is the richest producer. Most of the compounds produced by the deep sea actinomycetes presented antimicrobial and anti-cancer cell activities. Gene clusters related to biosynthesis of desotamide, heronamide, and lobophorin have been identified from the deep sea derived Streptomyces. PMID:28507537

Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

NASA Astrophysics Data System (ADS)

Ramirez-Llodra, E.; Brandt, A.; Danovaro, R.; Escobar, E.; German, C. R.; Levin, L. A.; Martinez Arbizu, P.; Menot, L.; Buhl-Mortensen, P.; Narayanaswamy, B. E.; Smith, C. R.; Tittensor, D. P.; Tyler, P. A.; Vanreusel, A.; Vecchione, M.

2010-04-01

The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna. Investigations of deep-sea habitats and their fauna began in the late 19th Century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 27 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st Century. However, for most of these habitats, the global area covered is unknown or has been only very roughly estimated; an even smaller - indeed, minimal - proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation, thus, shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps, where chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold-water corals have an increased productivity through specific physical processes, such as topographic modification of currents and enhanced transport of particles and detrital matter. Because of its unique abiotic attributes, the deep sea hosts a specialized fauna. Although there are no phyla unique to deep waters, at lower taxonomic levels the composition of the fauna is distinct from that found in the upper ocean. Amongst other characteristic patterns, deep-sea species may exhibit either gigantism or dwarfism, related to the decrease in food availability with depth. Food limitation on the seafloor and water column is also reflected in the trophic structure of deep-sea communities, which are adapted to low energy availability. In most of the heterotrophic deep-sea settings, the dominant megafauna is composed of detritivores, while filter feeders are abundant in habitats with hard substrata (e.g. mid-ocean ridges, seamounts, canyon walls and coral reefs) and chemoautotrophy through symbiotic relationships is dominant in reducing habitats. Deep-sea biodiversity is among of the highest on the planet, mainly composed of macro and meiofauna, with high evenness. This is true for most of the continental margins and abyssal plains with hot spots of diversity such as seamounts or cold-water corals. However, in some ecosystems with particularly "extreme" physicochemical processes (e.g. hydrothermal vents), biodiversity is low but abundance and biomass are high and the communities are dominated by a few species. Two large-scale diversity patterns have been discussed for deep-sea benthic communities. First, a unimodal relationship between diversity and depth is observed, with a peak at intermediate depths (2000-3000 m), although this is not universal and particular abiotic processes can modify the trend. Secondly, a poleward trend of decreasing diversity has been discussed, but this remains controversial and studies with larger and more robust datasets are needed. Because of the paucity in our knowledge of habitat coverage and species composition, biogeographic studies are mostly based on regional data or on specific taxonomic groups. Recently, global biogeographic provinces for the pelagic and benthic deep ocean have been described, using environmental and, where data were available, taxonomic information. This classification described 30 pelagic provinces and 38 benthic provinces divided into 4 depth ranges, as well as 10 hydrothermal vent provinces. One of the major issues faced by deep-sea biodiversity and biogeographical studies is related to the high number of species new to science that are collected regularly, together with the slow description rates for these new species. Taxonomic coordination at the global scale is particularly difficult but is essential if we are to analyse large diversity and biogeographic trends. Because of their remoteness, anthropogenic impacts on deep-sea ecosystems have not been addressed very thoroughly until recently. The depletion of biological and mineral resources on land and in shallow waters, coupled with technological developments, is promoting the increased interest in services provided by deep-water resources. Although often largely unknown, evidence for the effects of human activities in deep-water ecosystems - such as deep-sea mining, hydrocarbon exploration and exploitation, fishing, dumping and littering - is already accumulating. Because of our limited knowledge of deep-sea biodiversity and ecosystem functioning and because of the specific life-history adaptations of many deep-sea species (e.g. slow growth and delayed maturity), it is essential that the scientific community works closely with industry, conservation organisations and policy makers to develop conservation and management options.

Comet Dust After Deep Impact

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Harker, David E.; Woodward, Charles E.

2006-01-01

When the Deep Impact Mission hit Jupiter Family comet 9P/Tempel 1, an ejecta crater was formed and an pocket of volatile gases and ices from 10-30 m below the surface was exposed (A Hearn et aI. 2005). This resulted in a gas geyser that persisted for a few hours (Sugita et al, 2005). The gas geyser pushed dust grains into the coma (Sugita et a1. 2005), as well as ice grains (Schulz et al. 2006). The smaller of the dust grains were submicron in radii (0-25.3 micron), and were primarily composed of highly refractory minerals including amorphous (non-graphitic) carbon, and silicate minerals including amorphous (disordered) olivine (Fe,Mg)2SiO4 and pyroxene (Fe,Mg)SiO3 and crystalline Mg-rich olivine. The smaller grains moved faster, as expected from the size-dependent velocity law produced by gas-drag on grains. The mineralogy evolved with time: progressively larger grains persisted in the near nuclear region, having been imparted with slower velocities, and the mineralogies of these larger grains appeared simpler and without crystals. The smaller 0.2-0.3 micron grains reached the coma in about 1.5 hours (1 arc sec = 740 km), were more diverse in mineralogy than the larger grains and contained crystals, and appeared to travel through the coma together. No smaller grains appeared at larger coma distances later (with slower velocities), implying that if grain fragmentation occurred, it happened within the gas acceleration zone. These results of the high spatial resolution spectroscopy (GEMINI+Michelle: Harker et 4. 2005, 2006; Subaru+COMICS: Sugita et al. 2005) revealed that the grains released from the interior were different from the nominally active areas of this comet by their: (a) crystalline content, (b) smaller size, (c) more diverse mineralogy. The temporal changes in the spectra, recorded by GEMIM+Michelle every 7 minutes, indicated that the dust mineralogy is inhomogeneous and, unexpectedly, the portion of the size distribution dominated by smaller grains has a more diverse mineralogy. The lower spatial resolution, high sensitivity Spitzer IRS data reveal resonances of refractory minerals (those seen by GEMINI+Michelle plus ortho-pyroxene)) as well resonances that can be attributed to phillosilicates (layer lattice silicates such as Montmorillonite) (Lisse et al. 2006). Pre- and post-impact, micron to submicron grains were deciphered to be present in the coma by the modeling the high spatial resolution images to account for nucleus plus inner coma fluxes (Wooden et al. 2005, 2006; Harker et al. 2005, 2006a). Note also that crystalline silicates were released from the interior of 73P-B/SW-3 as it disintegrated (Harker et al. 2006b). From the Deep Impact and the disintegration of 73P-B, we are led to ask the questians: Why is the mineralogy of the dust released from a volatile-rich pocket beneath the surface different from the dust that is released from the nominally active areas? Could the most volatile pockets be exhausted quickly? Why would crystalline silicates be associated with more volatile materials? Perhaps the structure of the comet is so inhomogeneous, e.g., the layered pile mode2 of the nucleus (Belton et al. 2006), that a reservoir of crystalline silicate and submicron grains just happens to not be released by the nominally active areas of comet 9P? Perhaps comets lose matter through their mantles from below their surfaces, thus preserving ancient topographic structures and radiation damaged silicates and carbon? We will discuss and ponder different scenarios. We will discuss future directions for coordinated observations of JF comets.

Improving deep vein thrombosis prophylaxis with mechanical modalities in surgical intensive care unit.

PubMed

Restrepo, Paula; Jameson, Deborah L; Carroll, Diane L

2015-01-01

Deep vein thrombosis remains a source of adverse outcomes in surgical patients. Deep vein thrombosis is preventable with prophylactic intervention. The success of noninvasive mechanical modalities for prophylaxis relies on compliance with correct application. The goals of this project were to create a guideline that reflected current evidence and expert thinking about mechanical modalities use, assess compliance with mechanical modalities, and develop strategies to disseminate an evidence-based guideline for deep vein thrombosis prophylaxis.

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.

North Atlantic deep water formation and AMOC in CMIP5 models

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Wåhlin, Anna

2017-04-01

North Atlantic deep water formation processes and properties in climate models are indicative of their ability to simulate future ocean circulation, ventilation, carbon and heat uptake, and sea level rise. Historical time series of temperature, salinity, sea ice concentration and ocean transport in the North Atlantic subpolar gyre and Nordic Seas from 23 CMIP5 (Climate Model Intercomparison Project, phase 5) models are compared with observations to reveal the causes and consequences of North Atlantic deep water formation in models. Deep convection occurs at the sea ice edge and is most realistic in models with accurate sea ice extent, mostly those using the CICE model. The trigger of deep convection varies among models; for one third it is intense surface cooling only, while the remaining two thirds also need upward mixing of subsurface warm salty water. The models with the most intense deep convection have the most accurate deep water properties, which are warmer and fresher than in the other models. They also have the strongest Atlantic Meridional Overturning Circulation (AMOC). For over half of the models, 40% of the variability of the AMOC is explained by the volumes of deep water produced in the subpolar gyre and Nordic Seas, with 3 and 4 years lag respectively. Understanding the dynamical drivers of the AMOC in models is key to realistically forecast a possible slow down and its consequences on the global circulation and marine life.

Soil moisture depletion under simulated drought in the Amazon: impacts on deep root uptake.

PubMed

Markewitz, Daniel; Devine, Scott; Davidson, Eric A; Brando, Paulo; Nepstad, Daniel C

2010-08-01

*Deep root water uptake in tropical Amazonian forests has been a major discovery during the last 15 yr. However, the effects of extended droughts, which may increase with climate change, on deep soil moisture utilization remain uncertain. *The current study utilized a 1999-2005 record of volumetric water content (VWC) under a throughfall exclusion experiment to calibrate a one-dimensional model of the hydrologic system to estimate VWC, and to quantify the rate of root uptake through 11.5 m of soil. *Simulations with root uptake compensation had a relative root mean square error (RRMSE) of 11% at 0-40 cm and < 5% at 350-1150 cm. The simulated contribution of deep root uptake under the control was c. 20% of water demand from 250 to 550 cm and c. 10% from 550 to 1150 cm. Furthermore, in years 2 (2001) and 3 (2002) of throughfall exclusion, deep root uptake increased as soil moisture was available but then declined to near zero in deep layers in 2003 and 2004. *Deep root uptake was limited despite high VWC (i.e. > 0.30 cm(3) cm(-3)). This limitation may partly be attributable to high residual water contents (theta(r)) in these high-clay (70-90%) soils or due to high soil-to-root resistance. The ability of deep roots and soils to contribute increasing amounts of water with extended drought will be limited.

Conservation of deep pelagic biodiversity.

PubMed

Robison, Bruce H

2009-08-01

The deep ocean is home to the largest ecosystems on our planet. This vast realm contains what may be the greatest number of animal species, the greatest biomass, and the greatest number of individual organisms in the living world. Humans have explored the deep ocean for about 150 years, and most of what is known is based on studies of the deep seafloor. In contrast, the water column above the deep seabed comprises more than 90% of the living space, yet less than 1% of this biome has been explored. The deep pelagic biota is the largest and least-known major faunal group on Earth despite its obvious importance at the global scale. Pelagic species represent an incomparable reservoir of biodiversity. Although we have yet to discover and describe the majority of these species, the threats to their continued existence are numerous and growing. Conserving deep pelagic biodiversity is a problem of global proportions that has never been addressed comprehensively. The potential effects of these threats include the extensive restructuring of entire ecosystems, changes in the geographical ranges of many species, large-scale elimination of taxa, and a decline in biodiversity at all scales. This review provides an initial framework of threat assessment for confronting the challenge of conserving deep pelagic biodiversity; and it outlines the need for baseline surveys and protected areas as preliminary policy goals.

[Isolated true aneurysm of the deep femoral artery].

PubMed

Salomon du Mont, L; Holzer, T; Kazandjian, C; Saucy, F; Corpataux, J M; Rinckenbach, S; Déglise, S

2016-07-01

Aneurysms of the deep femoral artery, accounting for 5% of all femoral aneurysms, are uncommon. There is a serious risk of rupture. We report the case of an 83-year-old patient with a painless pulsatile mass in the right groin due to an aneurysm of the deep femoral artery. History taking revealed no cardiovascular risk factors and no other aneurysms at other localizations. The etiology remained unclear because no recent history of local trauma or puncture was found. ACT angiography was performed, revealing a true isolated aneurysm of the deep femoral artery with a diameter of 90mm, beginning 1cm after its origin. There were no signs of rupture or distal emboli. Due to unsuitable anatomy for an endovascular approach, the patient underwent open surgery, with exclusion of the aneurysm and interposition of an 8-mm Dacron graft to preserve deep femoral artery flow. Due to their localization, the diagnosis and the management of aneurysms of the deep femoral artery can be difficult. Options are surgical exclusion or an endovascular approach in the absence of symptoms or as a bridging therapy. If possible, blood flow to the distal deep femoral artery should be maintained, the decision depending also on the patency of the superficial femoral artery. In case of large size, aneurysms of the deep femoral artery should be treated without any delay. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Concurrent deep-superficial dyspareunia: prevalence, associations, and outcomes in a multidisciplinary vulvodynia program.

PubMed

Yong, Paul J; Sadownik, Leslie; Brotto, Lori A

2015-01-01

Little is known about women with concurrent diagnoses of deep dyspareunia and superficial dyspareunia. The aim of this study was to determine the prevalence, associations, and outcome of women with concurrent deep-superficial dyspareunia. This is a prospective study of a multidisciplinary vulvodynia program (n = 150; mean age 28.7 ± 6.4 years). Women with superficial dyspareunia due to provoked vestibulodynia were divided into two groups: those also having deep dyspareunia (i.e., concurrent deep-superficial dyspareunia) and those with only superficial dyspareunia due to provoked vestibulodynia. Demographics, dyspareunia-related factors, other pain conditions, and psychological variables at pretreatment were tested for an association with concurrent deep-superficial dyspareunia. Outcome in both groups was assessed to 6 months posttreatment. Level of dyspareunia pain (0-10) and Female Sexual Distress Scale were the main outcome measures. The prevalence of concurrent deep-superficial dyspareunia was 44% (66/150) among women with superficial dyspareunia due to provoked vestibulodynia. At pretreatment, on multiple logistic regression, concurrent deep-superficial dyspareunia was independently associated with a higher level of dyspareunia pain (odds ratio [OR] = 1.19 [1.01-1.39], P = 0.030), diagnosis of endometriosis (OR = 4.30 [1.16-15.90], P = 0.022), history of bladder problems (OR = 3.84 [1.37-10.76], P = 0.008), and more depression symptoms (OR = 1.07 [1.02-1.12], P = 0.007), with no difference in the Female Sexual Distress Scale. At 6 months posttreatment, women with concurrent deep-superficial dyspareunia improved in the level of dyspareunia pain and in the Female Sexual Distress Scale to the same degree as women with only superficial dyspareunia due to provoked vestibulodynia. Concurrent deep-superficial dyspareunia is reported by almost half of women in a multidisciplinary vulvodynia program. In women with provoked vestibulodynia, concurrent deep-superficial dyspareunia may be related to endometriosis or interstitial cystitis, and is associated with depression and more severe dyspareunia symptoms. Standardized multidisciplinary care is effective for women with concurrent dyspareunia. © 2014 International Society for Sexual Medicine.

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.

The formation of Greenland Sea Deep Water: double diffusion or deep convection?

NASA Astrophysics Data System (ADS)

Clarke, R. Allyn; Swift, James H.; Reid, Joseph L.; Koltermann, K. Peter

1990-09-01

An examination of the extensive hydrographic data sets collected by C.S.S. Hudson and F.S. Meteor in the Norwegian and Greenland Seas during February-June 1982 reveals property distributions and circulation patterns broadly similar to those seen in earlier data sets. These data sets, however, reveal the even stronger role played by topography, with evidence of separate circulation patterns and separate water masses in each of the deep basins. The high precision temperature, salinity and oxygen data obtained reveals significant differences in the deep and bottom waters found in the various basins of the Norwegian and Greenland Seas. A comparison of the 1982 data set with earlier sets shows that the renewal of Greenland Sea Deep Water must have taken place sometime over the last decade; however there is no evidence that deep convective renewal of any of the deep and bottom waters in this region was taking place at the time of the observations. The large-scale density fields, however, do suggest that deep convection to the bottom is most likely to occure in the Greenland Basin due to its deep cyclonic circulation. The hypothesis that Greenland Sea Deep Water (GSDW) is formed through dipycnal mixing processes acting on the warm salty core of Atlantic Water entering the Greenland Sea is examined. θ-S correlations and oxygen concentrations suggest that the salinity maxima in the Greenland Sea are the product of at least two separate mixing processes, not the hypothesized single mixing process leading to GSDW. A simple one-dimensional mixed layer model with ice growth and decay demonstrates that convective renewal of GSDW would have occurred within the Greenland Sea had the winter been a little more severe. The new GSDW produced would have only 0.003 less salt and less than 0.04 ml 1 -1 greater oxygen concentration than that already in the basin. Consequently, detection of whether new deep water has been produced following a winter cooling season could be difficult even with the best of modern accuracy.

Sensitivity of simulated deep ocean natural radiocarbon to gas exchange velocity and historical atmospheric Δ14C variations

NASA Astrophysics Data System (ADS)

Wagner, Hannes; Koeve, Wolfgang; Kriest, Iris; Oschlies, Andreas

2015-04-01

Simulated deep ocean natural radiocarbon is frequently used to assess model performance of deep ocean ventilation in Ocean General Circulation Models (OGCMs). It has been shown to be sensitive to a variety of model parameters, such as the mixing parameterization, convection scheme and vertical resolution. Here we use three different ocean models (MIT2.8, ECCO, UVic) to evaluate the sensitivity of simulated deep ocean natural radiocarbon to two other factors, while keeping the model physics constant: (1) the gas exchange velocity and (2) historic variations in atmospheric Δ^1^4C boundary conditions. We find that simulated natural Δ^1^4C decreases by 14-20 ‰ throughout the deep ocean and consistently in all three models, if the gas exchange velocity is lowered by 30 % with respect to the OCMIP-2 protocol, to become more consistent with newer estimates of the oceans uptake of bomb derived ^1^4C. Simulated deep ocean natural Δ^1^4C furthermore decreases by 3-9 ‰ throughout the deep Pacific, Indian and Southern Oceans and consistently in all three models, if the models are forced with the observed atmospheric Δ^1^4C history, instead of an often made pragmatic assumption of a constant atmospheric Δ^1^4C value of zero. Applying both improvements (gas exchange reduction, as well as atmospheric Δ^1^4C history implementation) concomitantly and accounting for the present uncertainty in gas exchange velocity estimates (between 10 and 40 % reduction with respect to the OCMIP-2 protocol) simulated deep ocean Δ^1^4C decreases by 10-30 ‰ throughout the deep Pacific, Indian and Southern Ocean. This translates to a ^1^4C-age increase of 100-300 years and indicates, that models, which in former assessments (based on the OCMIP-2 protocol) had been identified to have an accurate deep ocean ventilation, should now be regarded as rather having a bit too sluggish a ventilation. Models, which on the other hand had been identified to have a bit too fast a deep ocean ventilation, should now be regarded as rather having a more accurate ventilation.

Tractography patterns of subthalamic nucleus deep brain stimulation.

PubMed

Vanegas-Arroyave, Nora; Lauro, Peter M; Huang, Ling; Hallett, Mark; Horovitz, Silvina G; Zaghloul, Kareem A; Lungu, Codrin

2016-04-01

Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effect of Dimethyl Sulfoxide on Bond Strength of a Self-Etch Primer and an Etch and Rinse Adhesive to Surface and Deep Dentin.

PubMed

Sharafeddin, Farahnaz; Salehi, Raha; Feizi, Negar

2016-09-01

Composite bond to dentin is crucial in many clinical conditions particularly in deep cavities without enamel margins due to insufficient penetration of adhesive into demineralized dentin. The aim of this study was to assess the shear bond strength (SBS) of a methacrylate-based and a silorane-based composite resin to surface and deep dentin after pretreatment with dimethyl sulfoxide (DMSO). Eighty extracted human premolars were randomly divided into two groups of flat occlusal dentin with different cuts as A: surface group (sections just below the dentinoenamel junction (DEJ) and B: deep group (2 mm below DEJ). Each group was randomly assigned to 4 subgroups and their samples were restored with Adper Single bond (ASB) and Filtek Z350 or Silorane system Adhesive (SA) and Filtek P90 composite resins, using a 3×3mm cylindrical plastic mold. following these steps , the subgroups were assigned as SubgroupA 1 : surface dentin+ Silorane System Primer (SSP)+ Silorane System Bonding (SSB)+ P90; Subgroup A 2 : surface dentin+ 37% etchant (E37%) + Adper Single Bond (ASB)+ Z350; Subgroup A 3 : surface dentin+ DMSO+ SSP+ SSB+ P90; Subgroup A 4 : surface dentin+ E37%+ DMSO+ ASB+ Z350; Subgroup B 1 : deep dentin+ SSP+ SSB+ P90; Subgroup B 2 : deep dentin+ E37%+ ASB+ Z350; Subgroup B 3 : deep dentin+ DMSO+ SSP+ SSB+ P90; Subgroup B 4 :dentin +E37% +DMSO +ASB +Z350. The specimens were thermocycled at 5± 2/55± 2°C for 1000 cycles and then tested for SBS. Using DMSO as dentin conditioner increased SBS of ASB to deep dentin (p< 0.001) and SBS of SA to surface dentin (p= 0.003) but had no effect on SBS of SA to deep dentin (p= 1.00). The ability of DMSO to increase SBS of ASB to deep dentin provides a basis for improving bonding of this composite resin in deep cavities.

Upper extremity deep venous thrombosis after port insertion: What are the risk factors?

PubMed

Tabatabaie, Omidreza; Kasumova, Gyulnara G; Kent, Tara S; Eskander, Mariam F; Fadayomi, Ayotunde B; Ng, Sing Chau; Critchlow, Jonathan F; Tawa, Nicholas E; Tseng, Jennifer F

2017-08-01

Totally implantable venous access devices (ports) are widely used, especially for cancer chemotherapy. Although their use has been associated with upper extremity deep venous thrombosis, the risk factors of upper extremity deep venous thrombosis in patients with a port are not studied adequately. The Healthcare Cost and Utilization Project's Florida State Ambulatory Surgery and Services Database was queried between 2007 and 2011 for patients who underwent outpatient port insertion, identified by Current Procedural Terminology code. Patients were followed in the State Ambulatory Surgery and Services Database, State Inpatient Database, and State Emergency Department Database for upper extremity deep venous thrombosis occurrence. The cohort was divided into a test cohort and a validation cohort based on the year of port placement. A multivariable logistic regression model was developed to identify risk factors for upper extremity deep venous thrombosis in patients with a port. The model then was tested on the validation cohort. Of the 51,049 patients in the derivation cohort, 926 (1.81%) developed an upper extremity deep venous thrombosis. On multivariate analysis, independently significant predictors of upper extremity deep venous thrombosis included age <65 years (odds ratio = 1.22), Elixhauser score of 1 to 2 compared with zero (odds ratio = 1.17), end-stage renal disease (versus no kidney disease; odds ratio = 2.63), history of any deep venous thrombosis (odds ratio = 1.77), all-cause 30-day revisit (odds ratio = 2.36), African American race (versus white; odds ratio = 1.86), and other nonwhite races (odds ratio = 1.35). Additionally, compared with genitourinary malignancies, patients with gastrointestinal (odds ratio = 1.55), metastatic (odds ratio = 1.76), and lung cancers (odds ratio = 1.68) had greater risks of developing an upper extremity deep venous thrombosis. This study identified major risk factors of upper extremity deep venous thrombosis. Further studies are needed to evaluate the appropriateness of thromboprophylaxis in patients at greater risk of upper extremity deep venous thrombosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Low endemism, continued deep-shallow interchanges, and evidence for cosmopolitan distributions in free-living marine nematodes (order Enoplida)

PubMed Central

2010-01-01

Background Nematodes represent the most abundant benthic metazoa in one of the largest habitats on earth, the deep sea. Characterizing major patterns of biodiversity within this dominant group is a critical step towards understanding evolutionary patterns across this vast ecosystem. The present study has aimed to place deep-sea nematode species into a phylogenetic framework, investigate relationships between shallow water and deep-sea taxa, and elucidate phylogeographic patterns amongst the deep-sea fauna. Results Molecular data (18 S and 28 S rRNA) confirms a high diversity amongst deep-sea Enoplids. There is no evidence for endemic deep-sea lineages in Maximum Likelihood or Bayesian phylogenies, and Enoplids do not cluster according to depth or geographic location. Tree topologies suggest frequent interchanges between deep-sea and shallow water habitats, as well as a mixture of early radiations and more recently derived lineages amongst deep-sea taxa. This study also provides convincing evidence of cosmopolitan marine species, recovering a subset of Oncholaimid nematodes with identical gene sequences (18 S, 28 S and cox1) at trans-Atlantic sample sites. Conclusions The complex clade structures recovered within the Enoplida support a high global species richness for marine nematodes, with phylogeographic patterns suggesting the existence of closely related, globally distributed species complexes in the deep sea. True cosmopolitan species may additionally exist within this group, potentially driven by specific life history traits of Enoplids. Although this investigation aimed to intensively sample nematodes from the order Enoplida, specimens were only identified down to genus (at best) and our sampling regime focused on an infinitesimal small fraction of the deep-sea floor. Future nematode studies should incorporate an extended sample set covering a wide depth range (shelf, bathyal, and abyssal sites), utilize additional genetic loci (e.g. mtDNA) that are informative at the species level, and apply high-throughput sequencing methods to fully assay community diversity. Finally, further molecular studies are needed to determine whether phylogeographic patterns observed in Enoplids are common across other ubiquitous marine groups (e.g. Chromadorida, Monhysterida). PMID:21167065

Heliophysics Radio Observations Enabled by the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Kasper, J. C.

2018-02-01

This presentation reviews the scientific potential of low frequency radio imaging from space, the SunRISE radio interferometer, and the scientific value of larger future arrays in deep space and how they would benefit from the Deep Space Gateway.

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 Space Chronicle: A Chronology of Deep Space and Planetary Probes 1958-2000

NASA Technical Reports Server (NTRS)

Siddiqi, Asif A.; Launius, Roger (Technical Monitor)

2002-01-01

This monograph contains brief descriptions of all robotic deep space missions attempted since the opening of the space age in 1957. The missions are listed strictly chronologically in order of launch date (not by planetary encounter).

Advantages of Science Cubesat and Microsat Deployment Using DSG Deep Space Exploration Robotics

NASA Astrophysics Data System (ADS)

Shaw, A.; Rembala, R.; Fulford, P.

2018-02-01

Important scientific missions can be accomplished with cubesats/microsats. These missions would benefit from advantages offered by having an independent cubesat/microsat deployment capability as part of Deep Space Gateway's Deep Space Exploration Robotics system.

A randomized controlled trial of light versus deep propofol sedation for elective outpatient colonoscopy: recall, procedural conditions, and recovery.

PubMed

Allen, Megan; Leslie, Kate; Hebbard, Geoffrey; Jones, Ian; Mettho, Tejinder; Maruff, Paul

2015-11-01

This study aimed to determine if the incidence of recall was equivalent between light and deep sedation for colonoscopy. Secondary analysis included complications, patient clinical recovery, and post-procedure cognitive impairment. Two hundred patients undergoing elective outpatient colonoscopy were randomized to light (bispectral index [BIS] 70-80) or deep (BIS < 60) sedation with propofol and fentanyl. Recall was assessed by the modified Brice questionnaire, and cognition at baseline and discharge was assessed using a Cogstate test battery. The median (interquartile range [IQR]) BIS values were different in the two groups (69 [65-74] light sedation vs 53 [46-59] deep sedation; P < 0.0001). The incidence of recall was 12% in the light sedation group and 1% in the deep sedation group. The risk difference for recall was 0.11 (90% confidence interval, 0.05 to 0.17) in the intention-to-treat analysis, thus refuting equivalence in recall between light and deep sedation (0.05 significance level; 10% equivalence margin). Overall sedation-related complications were more frequent with deep sedation than with light sedation (66% vs 47%, respectively; P = 0.008). Recovery was more rapid with light sedation than with deep sedation as determined by the mean (SD) time to reach a score of 5 on the Modified Observer's Assessment of Alertness/Sedation Scale [3 (4) min vs 7 (4) min, respectively; P < 0.001] and by the median [IQR] time to readiness for hospital discharge (65 [57-80] min vs 74 [63-86] min, respectively; P = 0.001). The incidence of post-procedural cognitive impairment was similar in those randomized to light (19%) vs deep (16%) sedation (P = 0.554). Light sedation was not equivalent to deep sedation for procedural recall, the spectrum of complications, or recovery times. This study provides evidence to inform discussions with patients about sedation for colonoscopy. This trial was registered at the Australian and New Zealand Clinical Trials Registry, number 12611000320954.

Deep Sleep and Parietal Cortex Gene Expression Changes Are Related to Cognitive Deficits with Age

PubMed Central

Buechel, Heather M.; Popovic, Jelena; Searcy, James L.; Porter, Nada M.; Thibault, Olivier; Blalock, Eric M.

2011-01-01

Background Age-related cognitive deficits negatively affect quality of life and can presage serious neurodegenerative disorders. Despite sleep disruption's well-recognized negative influence on cognition, and its prevalence with age, surprisingly few studies have tested sleep's relationship to cognitive aging. Methodology We measured sleep stages in young adult and aged F344 rats during inactive (enhanced sleep) and active (enhanced wake) periods. Animals were behaviorally characterized on the Morris water maze and gene expression profiles of their parietal cortices were taken. Principal Findings Water maze performance was impaired, and inactive period deep sleep was decreased with age. However, increased deep sleep during the active period was most strongly correlated to maze performance. Transcriptional profiles were strongly associated with behavior and age, and were validated against prior studies. Bioinformatic analysis revealed increased translation and decreased myelin/neuronal pathways. Conclusions The F344 rat appears to serve as a reasonable model for some common sleep architecture and cognitive changes seen with age in humans, including the cognitively disrupting influence of active period deep sleep. Microarray analysis suggests that the processes engaged by this sleep are consistent with its function. Thus, active period deep sleep appears temporally misaligned but mechanistically intact, leading to the following: first, aged brain tissue appears capable of generating the slow waves necessary for deep sleep, albeit at a weaker intensity than in young. Second, this activity, presented during the active period, seems disruptive rather than beneficial to cognition. Third, this active period deep sleep may be a cognitively pathologic attempt to recover age-related loss of inactive period deep sleep. Finally, therapeutic strategies aimed at reducing active period deep sleep (e.g., by promoting active period wakefulness and/or inactive period deep sleep) may be highly relevant to cognitive function in the aging community. PMID:21483696

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.

Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099

USGS Publications Warehouse

Wood, Tamara M.; Wherry, Susan A.; Piccolroaz, Sebastiano; Girdner, Scott F

2016-05-04

The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.

Regional distribution of the high-altitude clouds over the Indian subcontinent and surrounding oceanic regions based on seven years of satellite observations

NASA Astrophysics Data System (ADS)

Meenu, S.; Rajeev, K.; Parameswaran, K.; Suresh Raju, C.

2006-12-01

Quantitative estimates of the spatio-temporal variations in deep convective events over the Indian subcontinent, Arabian Sea, Bay of Bengal, and tropical Indian Ocean are carried out using the data obtained from Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-14 and NOAA-16 during the period 1996-2003. Pixels having thermal IR brightness temperature (BT) less than 245K are considered as high altitude clouds and those having BT<220 K are considered as very high altitude clouds. Very deep convective clouds are observed over north Bay of Bengal during the Asian summer monsoon season when the mean cloud top temperature reaches as low as 190K. Over the Head Bay of Bengal (HBoB) from June to September, more than 50% of the observed clouds are deep convective type and more than half of these deep convective clouds are very deep convective clouds. Histogram analysis of the cloud top temperatures during this period shows that over HBoB the most prominent cloud top temperature of the deep convective clouds is ~205K over the HBoB while that over southeast Arabian Sea (SEAS) is ~220K. This indicates that most probably the cloud top altitude over HBoB is ~2 km larger than that over SEAS during the Asian summer monsoon period. Another remarkable feature observed during the Asian summer monsoon period is the significantly low values of deep convective clouds observed over the south Bay of Bengal close to Srilanka, which appears as a large pool of reduced cloud amount surrounded by regions of large-scale deep convection. Over both SEAS and HBoB, the total, deep convective and very deep convective cloud amounts as well as their corresponding cloud top temperatures (or the altitude of the cloud top) undergo large seasonal variations, while such variations are less prominent over the eastern equatorial Indian Ocean.

Ocean sunfish rewarm at the surface after deep excursions to forage for siphonophores.

PubMed

Nakamura, Itsumi; Goto, Yusuke; Sato, Katsufumi

2015-05-01

Ocean sunfish (Mola mola) were believed to be inactive jellyfish feeders because they are often observed lying motionless at the sea surface. Recent tracking studies revealed that they are actually deep divers, but there has been no evidence of foraging in deep water. Furthermore, the surfacing behaviour of ocean sunfish was thought to be related to behavioural thermoregulation, but there was no record of sunfish body temperature. Evidence of ocean sunfish feeding in deep water was obtained using a combination of an animal-borne accelerometer and camera with a light source. Siphonophores were the most abundant prey items captured by ocean sunfish and were typically located at a depth of 50-200 m where the water temperature was <12 °C. Ocean sunfish were diurnally active, made frequently deep excursions and foraged mainly at 100-200 m depths during the day. Ocean sunfish body temperatures were measured under natural conditions. The body temperatures decreased during deep excursions and recovered during subsequent surfacing periods. Heat-budget models indicated that the whole-body heat-transfer coefficient between sunfish and the surrounding water during warming was 3-7 times greater than that during cooling. These results suggest that the main function of surfacing is the recovery of body temperature, and the fish might be able to increase heat gain from the warm surface water by physiological regulation. The thermal environment of ocean sunfish foraging depths was lower than their thermal preference (c. 16-17 °C). The behavioural and physiological thermoregulation enables the fish to increase foraging time in deep, cold water. Feeding rate during deep excursions was not related to duration or depth of the deep excursions. Cycles of deep foraging and surface warming were explained by a foraging strategy, to maximize foraging time with maintaining body temperature by vertical temperature environment. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

A comparative experimental approach to ecotoxicology in shallow-water and deep-sea holothurians suggests similar behavioural responses.

PubMed

Brown, Alastair; Wright, Roseanna; Mevenkamp, Lisa; Hauton, Chris

2017-10-01

Exploration of deep-sea mineral resources is burgeoning, raising concerns regarding ecotoxicological impacts on deep-sea fauna. Assessing toxicity in deep-sea species is technologically challenging, which promotes interest in establishing shallow-water ecotoxicological proxy species. However, the effects of temperature and hydrostatic pressure on toxicity, and how adaptation to deep-sea environmental conditions might moderate these effects, are unknown. To address these uncertainties we assessed behavioural and physiological (antioxidant enzyme activity) responses to exposure to copper-spiked artificial sediments in a laboratory experiment using a shallow-water holothurian (Holothuria forskali), and in an in situ experiment using a deep-sea holothurian (Amperima sp.). Both species demonstrated sustained avoidance behaviour, evading contact with contaminated artificial sediment. However, A. sp. demonstrated sustained avoidance of 5mgl -1 copper-contaminated artificial sediment whereas H. forskali demonstrated only temporary avoidance of 5mgl -1 copper-contaminated artificial sediment, suggesting that H. forskali may be more tolerant of metal exposure over 96h. Nonetheless, the acute behavioural response appears consistent between the shallow-water species and the deep-sea species, suggesting that H. forskali may be a suitable ecotoxicological proxy for A. sp. in acute (≤24h) exposures, which may be representative of deep-sea mining impacts. No antioxidant response was observed in either species, which was interpreted to be the consequence of avoiding copper exposure. Although these data suggest that shallow-water taxa may be suitable ecotoxicological proxies for deep-sea taxa, differences in methodological and analytical approaches, and in sex and reproductive stage of experimental subjects, require caution in assessing the suitability of H. forskali as an ecotoxicological proxy for A. sp. Nonetheless, avoidance behaviour may have bioenergetic consequences that affect growth and/or reproductive output, potentially impacting fecundity and/or offspring fitness, and thus influencing source-sink dynamics and persistence of wider deep-sea populations. Copyright © 2017 Elsevier B.V. All rights reserved.

The change in deep cervical flexor activity after training is associated with the degree of pain reduction in patients with chronic neck pain.

PubMed

Falla, Deborah; O'Leary, Shaun; Farina, Dario; Jull, Gwendolen

2012-09-01

Altered activation of the deep cervical flexors (longus colli and longus capitis) has been found in individuals with neck pain disorders but the response to training has been variable. Therefore, this study investigated the relationship between change in deep cervical flexor muscle activity and symptoms in response to specific training. Fourteen women with chronic neck pain undertook a 6-week program of specific training that consisted of a craniocervical flexion exercise performed twice per day (10 to 20 min) for the duration of the trial. The exercise targets the deep flexor muscles of the upper cervical region. At baseline and follow-up, measures were taken of neck pain intensity (visual analogue scale, 0 to 10), perceived disability (Neck Disability Index, 0 to 50) and electromyography (EMG) of the deep cervical flexors (by a nasopharyngeal electrode suctioned over the posterior oropharyngeal wall) during performance of craniocervical flexion. After training, the activation of the deep cervical flexors increased (P<0.0001) with the greatest change occurring in patients with the lowest values of deep cervical flexor EMG amplitude at baseline (R(2)=0.68; P<0.001). There was a significant relationship between initial pain intensity, change in pain level with training, and change in EMG amplitude for the deep cervical flexors during craniocervical flexion (R(2)=0.34; P<0.05). Specific training of the deep cervical flexor muscles in women with chronic neck pain reduces pain and improves the activation of these muscles, especially in those with the least activation of their deep cervical flexors before training. This finding suggests that the selection of exercise based on a precise assessment of the patients' neuromuscular control and targeted exercise interventions based on this assessment are likely to be the most beneficial to patients with neck pain.

Sonographically guided deep plantar fascia injections: where does the injectate go?

PubMed

Maida, Eugene; Presley, James C; Murthy, Naveen; Pawlina, Wojciech; Smith, Jay

2013-08-01

To determine the distribution of sonographically guided deep plantar fascia injections in an unembalmed cadaveric model. A single experienced operator completed 10 sonographically guided deep plantar fascia injections in 10 unembalmed cadaveric specimens (5 right and 5 left) obtained from 6 donors (2 male and 4 female) aged 49 to 95 years (mean, 77.5 years) with a mean body mass index of 23.2 kg/m(2) (range, 18.4-26.3 kg/m(2)). A 12-3-MHz linear array transducer was used to direct a 22-gauge, 38-mm stainless steel needle deep to the plantar fascia at the anterior aspect of the calcaneus using an in-plane, medial-to-lateral approach. In each case, 1.5 mL of 50% diluted colored latex was injected deep to the plantar fascia. After a minimum of 72 hours, study coinvestigators dissected each specimen to assess injectate placement. All 10 injections accurately placed latex adjacent to the deep side of the plantar fascia at the anterior calcaneus. However, the flexor digitorum brevis (FDB) origin from the plantar fascia variably limited direct latex contact with the plantar fascia, and small amounts of latex interdigitated with the FDB origin in 90% (9 of 10). In all 10 specimens, latex also covered the traversing first branch of the lateral plantar nerve (FBLPN, ie, Baxter nerve) between the FDB and quadratus plantae muscles. No latex was found in the plantar fat pad or plantar fascia in any specimen. Sonographically guided deep plantar fascia injections reliably deliver latex deep to the plantar fascia while avoiding intrafascial injection. However, the extent of direct plantar fascia contact is variable due to the intervening FDB. On the contrary, the traversing FBLPN is reliably covered by the injection. Deep plantar fascia injections may have a role in the management of refractory plantar fasciitis, particularly following failed superficial perifascial or intrafascial injections, in cases of preferential deep plantar fascia involvement, or when entrapment/irritation of the distal FBLPN is suspected.

Distributed deep learning networks among institutions for medical imaging.

PubMed

Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

2018-03-29

Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

The Future of the Deep Space Network: Technology Development for K2-Band Deep Space Communications

NASA Technical Reports Server (NTRS)

Bhanji, Alaudin M.

1999-01-01

Projections indicate that in the future the number of NASA's robotic deep space missions is likely to increase significantly. A launch rate of up to 4-6 launches per year is projected with up to 25 simultaneous missions active [I]. Future high resolution mapping missions to other planetary bodies as well as other experiments are likely to require increased downlink capacity. These future deep space communications requirements will, according to baseline loading analysis, exceed the capacity of NASA's Deep Space Network in its present form. There are essentially two approaches for increasing the channel capacity of the Deep Space Network. Given the near-optimum performance of the network at the two deep space communications bands, S-Band (uplink 2.025-2.120 GHz, downlink 2.2-2.3 GHz), and X-Band (uplink 7.145-7.19 GHz, downlink 8.48.5 GHz), additional improvements bring only marginal return for the investment. Thus the only way to increase channel capacity is simply to construct more antennas, receivers, transmitters and other hardware. This approach is relatively low-risk but involves increasing both the number of assets in the network and operational costs.

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.

3-D movies using microprocessor-controlled optoelectronic spectacles

NASA Astrophysics Data System (ADS)

Jacobs, Ken; Karpf, Ron

2012-02-01

Despite rapid advances in technology, 3-D movies are impractical for general movie viewing. A new approach that opens all content for casual 3-D viewing is needed. 3Deeps--advanced microprocessor controlled optoelectronic spectacles--provides such a new approach to 3-D. 3Deeps works on a different principle than other methods for 3-D. 3-D movies typically use the asymmetry of dual images to produce stereopsis, necessitating costly dual-image content, complex formatting and transmission standards, and viewing via a corresponding selection device. In contrast, all 3Deeps requires to view movies in realistic depth is an illumination asymmetry--a controlled difference in optical density between the lenses. When a 2-D movie has been projected for viewing, 3Deeps converts every scene containing lateral motion into realistic 3-D. Put on 3Deeps spectacles for 3-D viewing, or remove them for viewing in 2-D. 3Deeps works for all analogue and digital 2-D content, by any mode of transmission, and for projection screens, digital or analogue monitors. An example using aerial photography is presented. A movie consisting of successive monoscopic aerial photographs appears in realistic 3-D when viewed through 3Deeps spectacles.

Deepwater Program: Lophelia II, continuing ecological research on deep-sea corals and deep-reef habitats in the Gulf of Mexico

USGS Publications Warehouse

Demopoulos, Amanda W.J.; Ross, Steve W.; Kellogg, Christina A.; Morrison, Cheryl L.; Nizinski, Martha S.; Prouty, Nancy G.; Bourque, Jill R.; Galkiewicz, Julie P.; Gray, Michael A.; Springmann, Marcus J.; Coykendall, D. Katharine; Miller, Andrew; Rhode, Mike; Quattrini, Andrea; Ames, Cheryl L.; Brooke, Sandra D.; McClain Counts, Jennifer; Roark, E. Brendan; Buster, Noreen A.; Phillips, Ryan M.; Frometa, Janessy

2017-12-11

The deep sea is a rich environment composed of diverse habitat types. While deep-sea coral habitats have been discovered within each ocean basin, knowledge about the ecology of these habitats and associated inhabitants continues to grow. This report presents information and results from the Lophelia II project that examined deep-sea coral habitats in the Gulf of Mexico. The Lophelia II project focused on Lophelia pertusa habitats along the continental slope, at depths ranging from 300 to 1,000 meters. The chapters are authored by several scientists from the U.S. Geological Survey, National Oceanic and Atmospheric Administration, University of North Carolina Wilmington, and Florida State University who examined the community ecology (from microbes to fishes), deep-sea coral age, growth, and reproduction, and population connectivity of deep-sea corals and inhabitants. Data from these studies are presented in the chapters and appendixes of the report as well as in journal publications. This study was conducted by the Ecosystems Mission Area of the U.S. Geological Survey to meet information needs identified by the Bureau of Ocean Energy Management.

Potential impact of global climate change on benthic deep-sea microbes.

PubMed

Danovaro, Roberto; Corinaldesi, Cinzia; Dell'Anno, Antonio; Rastelli, Eugenio

2017-12-15

Benthic deep-sea environments are the largest ecosystem on Earth, covering ∼65% of the Earth surface. Microbes inhabiting this huge biome at all water depths represent the most abundant biological components and a relevant portion of the biomass of the biosphere, and play a crucial role in global biogeochemical cycles. Increasing evidence suggests that global climate changes are affecting also deep-sea ecosystems, both directly (causing shifts in bottom-water temperature, oxygen concentration and pH) and indirectly (through changes in surface oceans' productivity and in the consequent export of organic matter to the seafloor). However, the responses of the benthic deep-sea biota to such shifts remain largely unknown. This applies particularly to deep-sea microbes, which include bacteria, archaea, microeukaryotes and their viruses. Understanding the potential impacts of global change on the benthic deep-sea microbial assemblages and the consequences on the functioning of the ocean interior is a priority to better forecast the potential consequences at global scale. Here we explore the potential changes in the benthic deep-sea microbiology expected in the coming decades using case studies on specific systems used as test models. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Deep Unfolding for Topic Models.

PubMed

Chien, Jen-Tzung; Lee, Chao-Hsi

2018-02-01

Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.

Deep-sea ostracods from the South Atlantic sector of the Southern ocean during the Last 370,000 years

USGS Publications Warehouse

Yasuhara, Moriaki; Cronin, T. M.; Hunt, G.; Hodell, D.A.

2009-01-01

We report changes of deep-sea ostracod fauna during the last 370,000 yr from the Ocean Drilling Program (ODP) Hole 704A in the South Atlantic sector of the Southern Ocean. The results show that faunal changes are coincident with glacial/interglacial-scale deep-water circulation changes, even though our dataset is relatively small and the waters are barren of ostracods until mid-MIS (Marine Isotope Stage) 5. Krithe and Poseidonamicus were dominant during the Holocene interglacial period and the latter part of MIS 5, when this site was under the influence of North Atlantic Deep Water (NADW). Conversely, Henryhowella and Legitimocythere were dominant during glacial periods, when this site was in the path of Circumpolar Deep Water (CPDW). Three new species (Aversovalva brandaoae, Poseidonamicus hisayoae, and Krithe mazziniae) are described herein. This is the first report of Quaternary glacial/interglacial scale deep-sea ostracod faunal changes in the Southern and South Atlantic Oceans, a key region for understanding Quaternary climate and deep-water circulation, although the paucity of Quaternary ostracods in this region necessitates further research. ?? 2009 The Paleontological Society.

Arsenic migration to deep groundwater in Bangladesh influenced by adsorption and water demand.

PubMed

Radloff, K A; Zheng, Y; Michael, H A; Stute, M; Bostick, B C; Mihajlov, I; Bounds, M; Huq, M R; Choudhury, I; Rahman, M W; Schlosser, P; Ahmed, K M; van Geen, A

2011-10-01

Drinking shallow groundwater with naturally elevated concentrations of arsenic is causing widespread disease in many parts of South and Southeast Asia. In the Bengal Basin, growing reliance on deep (>150 m) groundwater has lowered exposure. In the most affected districts of Bangladesh, shallow groundwater concentrations average 100 to 370 μg L(-1), while deep groundwater is typically < 10 μg L(-1). Groundwater flow simulations have suggested that, even when deep pumping is restricted to domestic use, deep groundwater in some areas of the Bengal Basin is at risk of contamination. However, these simulations have neglected the impedance of As migration by adsorption to aquifer sediments. Here we quantify for the first time As sorption on deeper sediments in situ by replicating the intrusion of shallow groundwater through injection of 1,000 L of deep groundwater modified with 200 μg L(-1) of As into a deeper aquifer. Arsenic concentrations in the injected water were reduced by 70% due to adsorption within a single day. Basin-scale modelling indicates that while As adsorption extends the sustainable use of deep groundwater, some areas remain vulnerable; these areas can be prioritized for management and monitoring.

Syringe Port: A Convenient, Safe, and Cost-Effective Tubular Retractor for Transportal Removal of Deep-Seated Lesions of the Brain.

PubMed

Singh, Harnarayan; Patir, Rana; Vaishya, Sandeep; Miglani, Rahul; Kaur, Amandeep

2018-06-01

Minimally invasive transportal resection of deep intracranial lesions has become a widely accepted surgical technique. Many disposable, mountable port systems are available in the market for this purpose, like the ViewSite Brain Access System. The objective of this study was to find a cost-effective substitute for these systems. Deep-seated brain lesions were treated with a port system made from disposable syringes. The syringe port could be inserted through minicraniotomies placed and planned with navigation. All deep-seated lesions like ventricular tumours, colloid cysts, deep-seated gliomas, and basal ganglia hemorrhages were treated with this syringe port system and evaluated for safety, operative site hematomas, and blood loss. 62 patients were operated on during the study period from January 2015 to July 2017, using this innovative syringe port system for deep-seated lesions of the brain. No operative site hematoma or contusions were seen along the port entry site and tract. Syringe port is a cost-effective and safe alternative to the costly disposable brain port systems, especially for neurosurgical setups in developing countries for minimally invasive transportal resection of deep brain lesions. Copyright © 2018 Elsevier Inc. All rights reserved.

Extracting Databases from Dark Data with DeepDive

PubMed Central

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data: the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data — scientific papers, Web classified ads, customer service notes, and so on — were instead in a relational database, it would give analysts a massive and valuable new set of “big data.” DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference. PMID:28316365

Using geophysical data to assess scour development

USGS Publications Warehouse

Placzek, Gary; Haeni, Peter F.; Trent, Roy; ,

1993-01-01

The development of scour holes in the Connecticut River near the new Baldwin Bridge has been documented by comparing geophysical records collected before (1989), during (1990), and after (1992) bridge construction. Eight piers that support the 570-m (meter) span over the Connecticut River were protected by 12-m wide cofferdams during construction. The maximum flow during the study was equivalent to a 3-year recurrence-interval flood, indicating no significant floods. Fathometer data indicate that deep scour holes, 1.5 to 6.4 m deep, developed north of piers 6, 7, and 8. Scour holes, less than 1.3 m-deep, developed south of these piers. The deepest scour hole was north of pier 7, where data show a flat river bottom in 1989, a scour 3.3-m deep in 1990, and a scour hole 6.4-m deep in 1992. Continuous seismic-profiling (CSP) data show that a 1.5 -m deep scour hole north of pier 6 in 1990 was filled in with 1.5-m of material by 1992. No infilling was detected in the scour holes north of piers 7 and 8. Numerous subbottom reflectors from geologic layers, up to 7.6 -m deep were identified in the CSP records.

Comparative histometric analysis of the effects of high-intensity focused ultrasound and radiofrequency on skin.

PubMed

Suh, Dong Hye; Choi, Jeong Hwee; Lee, Sang Jun; Jeong, Ki-Heon; Song, Kye Yong; Shin, Min Kyung

2015-01-01

High-intensity focused ultrasound (HIFU) and radiofrequency (RF) are used for non-invasive skin tightening. Neocollagenesis and neoelastogenesis have been reported to have a mechanism of controlled thermal injury. To compare neocollagenesis and neoelastogenesis in each layer of the dermis after each session of HIFU and monopolar RF. We analyzed the area fraction of collagen and elastic fibers using the Masson's Trichrome and Victoria blue special stains, respectively, before and after 2 months of treatments. Histometric analyses were performed in each layer of the dermis, including the papillary dermis, and upper, mid, and deep reticular dermis. Monopolar RF led to neocollagenesis in the papillary dermis, and upper, mid, and deep reticular dermis, and neoelastogenesis in the papillary dermis, and upper and mid reticular dermis. HIFU led to neocollagenesis in the mid and deep reticular dermis and neoelastogenesis in the deep reticular dermis. Among these treatment methods, HIFU showed the highest level of neocollagenesis and neoelastogenesis in the deep reticular dermis. HIFU affects deep tissues and impacts focal regions. Monopolar RF also affects deep tissues, but impacts diffuse regions. We believe these data provide further insight into effective skin tightening.

Predicting healthcare trajectories from medical records: A deep learning approach.

PubMed

Pham, Trang; Tran, Truyen; Phung, Dinh; Venkatesh, Svetha

2017-05-01

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, stored in electronic medical records are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors and models patient health state trajectories by the memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces methods to handle irregularly timed events by moderating the forgetting and consolidation of memory. DeepCare also explicitly models medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden - diabetes and mental health - the results show improved prediction accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Practice It: Deep Conscious Breathing Exercise

Cancer.gov

No time to sit and breathe? No problem; take your breathing practice with you! Deep conscious breathing can also be done with the eyes open wherever you happen to be—simply pause and take two to three full deep breaths (inhale deeply and exhale completely).

Interpreting the strongest deep earthquake ever observed

NASA Astrophysics Data System (ADS)

Schultz, Colin

2013-12-01

Massive earthquakes that strike deep within the Earth may be more efficient at dissipating pent-up energy than similar quakes near the surface, according to new research by Wei et al. The authors analyzed the rupture of the most powerful deep earthquake ever recorded.

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.

Advances in Planetary Protection at the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Spry, J. A.; Siegel, B.; Race, M.; Rummel, J. D.; Pugel, D. E.; Groen, F. J.; Kminek, G.; Conley, C. A.; Carosso, N. J.

2018-02-01

Planetary protection knowledge gaps that can be addressed by science performed at the Deep Space Gateway in the areas of human health and performance, space biology, and planetary sciences that enable future exploration in deep space, at Mars, and other targets.

The Deep Space Network

NASA Technical Reports Server (NTRS)

1979-01-01

Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations.

DSN test and training system

NASA Technical Reports Server (NTRS)

Thorman, H. C.

1975-01-01

Key characteristics of the Deep Space Network Test and Training System were presented. Completion of the Mark III-75 system implementation is reported. Plans are summarized for upgrading the system to a Mark III-77 configuration to support Deep Space Network preparations for the Mariner Jupiter/Saturn 1977 and Pioneer Venus 1978 missions. A general description of the Deep Space Station, Ground Communications Facility, and Network Operations Control Center functions that comprise the Deep Space Network Test and Training System is also presented.

Double seismic zone for deep earthquakes in the izu-bonin subduction zone.

PubMed

Iidaka, T; Furukawa, Y

1994-02-25

A double seismic zone for deep earthquakes was found in the Izu-Bonin region. An analysis of SP-converted phases confirms that the deep seismic zone consists of two layers separated by approximately 20 kilometers. Numerical modeling of the thermal structure implies that the hypocenters are located along isotherms of 500 degrees to 550 degrees C, which is consistent with the hypothesis that deep earthquakes result from the phase transition of metastable olivine to a high-pressure phase in the subducting slab.

Homology between genes for aromatic hydrocarbon degradation in surface and deep-subsurface sphingomonas strains

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

Kim, E.; Aversano, P.J.; Zylstra, G.J.

The cloned genes for aromatic hydrocarbon degradation from Sphingomonas yanoikuyae B1 were utilized in Southern hybridization experiments with Sphingomonas strains from the surface and deep-subsurface environments. One hybridization pattern was obtained with BamHI-digested genomic DNAs for two surface strains, while a differing pattern was seen for five deep-subsurface strains. The cross-hybridizing genes were located in the chromosomes of the surface strains and on plasmids in the deep-subsurface strains. 31 refs., 3 figs., 1 tab.

Deep Water Ocean Acoustics

DTIC Science & Technology

2015-04-15

0 A S S PROGRESS REPORT NO. QSR-14C0172-0CEAN ACOUSTICS-033115 Contract No. N00014-14-C-0172 Office of Naval Research Task Reporting: Deep ...AND SUBTITLE Deep Water Ocean Acoustics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Cost Summary OASIS, INC. JOB STATUS RB’ORT 1172 DEEP WATER ACOUSTICS FOP. 9/27f13-316/16

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.

Acute Lower Extremity Deep Venous Thrombosis: The Data, Where We Are, and How It Is Done.

PubMed

Ramaswamy, Raja S; Akinwande, Olaguoke; Giardina, Joseph D; Kavali, Pavan K; Marks, Christina G

2018-06-01

The incidence of venous thromboembolism, including both deep vein thrombosis and pulmonary embolism, is estimated at 300,000-600,000 per year. Although thrombosis may occur anywhere, it is thrombosis of the deep veins of the lower extremities that is of interest as this is where thrombosis occurs most often within the venous system. This article discusses the evaluation and interventions, including endovascular catheter-direct treatments, for patients with acute deep venous thrombosis. Published by Elsevier Inc.

Low-flow characteristics and profiles for the Deep River in the Cape Fear River basin, North Carolina

USGS Publications Warehouse

Weaver, J.C.

1997-01-01

Drainage area and low-flow discharge profiles are presented for the Deep River. The drainage-area profile shows downstream increases in basin size. At the mouth, the drainage area for the Deep River is 1,441 square miles. Low-flow discharge profiles for the Deep River include 7Q10, 30Q2, W7Q10, and 7Q2 discharges in a continuous profile with contributions from major tributaries included.

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

PubMed

Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

2018-03-01

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Deep Operations in Airland Battle Doctrine: The Employment of U.S. Ground Forces in Deep Operational Maneuver

DTIC Science & Technology

1989-05-16

development and is manifested today in the Operational .Maneuver Group. As the name implies, the Soviet emphiasis is at the operational level. The mission of...high-intensity war! 10 answer this question I (1) analyze Soviet deep operations theory to determine how their concept developed and what they expect...USA, 32 pageF., In Soviet Army doctrine, deep operations has been a long time in development and is manifested today in the Operational Maneuver Group

Deep learning applications in ophthalmology.

PubMed

Rahimy, Ehsan

2018-05-01

To describe the emerging applications of deep learning in ophthalmology. Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the posterior segment of the eye with high accuracy. Most of the initial studies have centered around detection of referable diabetic retinopathy, age-related macular degeneration, and glaucoma. Deep learning has shown promising results in automated image analysis of fundus photographs and optical coherence tomography images. Additional testing and research is required to clinically validate this technology.

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.

Deep and surface learning in problem-based learning: a review of the literature.

PubMed

Dolmans, Diana H J M; Loyens, Sofie M M; Marcq, Hélène; Gijbels, David

2016-12-01

In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review investigates: (1) the effects of PBL on students' deep and surface approaches to learning, (2) whether and why these effects do differ across (a) the context of the learning environment (single vs. curriculum wide implementation), and (b) study quality. Studies were searched dealing with PBL and students' approaches to learning. Twenty-one studies were included. The results indicate that PBL does enhance deep learning with a small positive average effect size of .11 and a positive effect in eleven of the 21 studies. Four studies show a decrease in deep learning and six studies show no effect. PBL does not seem to have an effect on surface learning as indicated by a very small average effect size (.08) and eleven studies showing no increase in the surface approach. Six studies demonstrate a decrease and four an increase in surface learning. It is concluded that PBL does seem to enhance deep learning and has little effect on surface learning, although more longitudinal research using high quality measurement instruments is needed to support this conclusion with stronger evidence. Differences cannot be explained by the study quality but a curriculum wide implementation of PBL has a more positive impact on the deep approach (effect size .18) compared to an implementation within a single course (effect size of -.05). PBL is assumed to enhance active learning and students' intrinsic motivation, which enhances deep learning. A high perceived workload and assessment that is perceived as not rewarding deep learning are assumed to enhance surface learning.

White blood cells identification system based on convolutional deep neural learning networks.

PubMed

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

The development of deep karst in the anticlinal aquifer structure based on the coupling of multistage flow systems

NASA Astrophysics Data System (ADS)

Xu, M.; Zhong, L.; Yang, Y.

2017-12-01

Under the background of neotectonics, the multistage underground flow system has been form due the different responses of main stream and tributaries to crust uplift. The coupling of multistage underground flow systems influences the development of karst thoroughly. At first, the research area is divided into vadose area, shunted area and exorheic area based on the development characteristics of transverse valley. Combining the controlling-drain action with topographic index and analyzing the coupling features of multistage underground flow system. And then, based on the coupling of multistage underground flow systems, the characteristics of deep karst development were verified by the lossing degree of surface water, water bursting and karst development characteristics of tunnels. The vadose area is regional water system based, whose deep karst developed well. It resulted the large water inflow of tunnels and the surface water drying up. The shunted area, except the region near the transverse valleys, is characterized by regional water system. The developed deep karst make the surface water connect with deep ground water well, Which caused the relatively large water flow of tunnels and the serious leakage of surface water. The deep karst relatively developed poor in the regions near transverse valleys which is characterized by local water system. The exorheic area is local water system based, whose the deep karst developed poor, as well as the connection among surface water and deep ground water. It has result in the poor lossing of the surface water under the tunnel construction. This study broadens the application field of groundwater flow systems theory, providing a new perspective for the study of Karst development theory. Meanwhile it provides theoretical guidance for hazard assessment and environmental negative effect in deep-buried Karst tunnel construction.

Using environmental isotopes along with major hydro-geochemical compositions to assess deep groundwater formation and evolution in eastern coastal China

NASA Astrophysics Data System (ADS)

Xu, Naizheng; Gong, Jianshi; Yang, Guoqiang

2018-01-01

Hydrochemical analysis and environmental isotopic tracing are successfully applied to study groundwater evolution processes. Located in eastern China, the Jiangsu Coastal Plain is characterized by an extensively exploited deep groundwater system, and groundwater salinization has become the primary water environmental problem. This paper provides a case study on the use of a hydrochemical and environmental isotopic approach to assess possible mixing and evolution processes at Yoco Port, Jiangsu Province, China. Hydrochemical and isotopic patterns of deep groundwater allow one to distinguish different origins in deep water systems. HCO3- is the dominant anion in the freshwater samples, whereas Na+ and Cl- are the dominant major ions in the saline samples. According to δ18O, δ2H and 14C dating, the fresh water is derived from precipitation under a colder climate during the Glacial Maximum (Dali Glacial), while the saline groundwater is influenced by glacial-interglacial cycles during the Holocene Hypsithermal. The δ18O, δ2H and 3H data confirm that deep groundwater in some boreholes is mixed with overlying saline water. The deep groundwater reservoir can be divided into a saline water sector and a fresh water sector, and each show distinct hydrochemical and isotopic compositions. The saline groundwater found in the deep aquifer cannot be associated with present seawater intrusion. Since the Last Glacial Maximum in the Late Pleistocene, the deep groundwater flow system has evolved to its current status with the decrease in ice cover and the rising of sea level. However, the hydraulic connection is strengthened by continuous overexploitation, and deep groundwater is mixed with shallow groundwater at some points.