Small-angle X-Ray analysis of macromolecular structure: the structure of protein NS2 (NEP) in solution

Science.gov (United States)

Shtykova, E. V.; Bogacheva, E. N.; Dadinova, L. A.; Jeffries, C. M.; Fedorova, N. V.; Golovko, A. O.; Baratova, L. A.; Batishchev, O. V.

2017-11-01

A complex structural analysis of nuclear export protein NS2 (NEP) of influenza virus A has been performed using bioinformatics predictive methods and small-angle X-ray scattering data. The behavior of NEP molecules in a solution (their aggregation, oligomerization, and dissociation, depending on the buffer composition) has been investigated. It was shown that stable associates are formed even in a conventional aqueous salt solution at physiological pH value. For the first time we have managed to get NEP dimers in solution, to analyze their structure, and to compare the models obtained using the method of the molecular tectonics with the spatial protein structure predicted by us using the bioinformatics methods. The results of the study provide a new insight into the structural features of nuclear export protein NS2 (NEP) of the influenza virus A, which is very important for viral infection development.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

Science.gov (United States)

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.

Anomalous Capacitive Sheath with Deep Radio Frequency Electric Field Penetration

International Nuclear Information System (INIS)

Kaganovich, Igor D.

2002-01-01

A novel nonlinear effect of anomalously deep penetration of an external radio-frequency electric field into a plasma is described. A self-consistent kinetic treatment reveals a transition region between the sheath and the plasma. Because of the electron velocity modulation in the sheath, bunches in the energetic electron density are formed in the transition region adjusted to the sheath. The width of the region is of order V(subscript T)/omega, where V(subscript T) is the electron thermal velocity, and w is frequency of the electric field. The presence of the electric field in the transition region results in a cooling of the energetic electrons and an additional heating of the cold electrons in comparison with the case when the transition region is neglected

Deep Borehole Field Test Research Activities at LBNL

Energy Technology Data Exchange (ETDEWEB)

Dobson, Patrick [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tsang, Chin-Fu [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kneafsey, Timothy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Borglin, Sharon [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piceno, Yvette [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Andersen, Gary [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nakagawa, Seiji [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nihei, Kurt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rutqvist, Jonny [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Doughty, Christine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Reagan, Matthew [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-08-19

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

Deep Borehole Field Test Research Activities at LBNL

International Nuclear Information System (INIS)

Dobson, Patrick; Tsang, Chin-Fu; Kneafsey, Timothy; Borglin, Sharon; Piceno, Yvette; Andersen, Gary; Nakagawa, Seiji; Nihei, Kurt; Rutqvist, Jonny; Doughty, Christine; Reagan, Matthew

2016-01-01

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

GLOBEC NEP Northern California Current Bird Data NH0005, 2000-2000, 0007

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — GLOBEC (GLOBal Ocean ECosystems Dynamics) NEP (Northeast Pacific) Northern California Current Bird Data from R/V New Horizon cruises NH0005 and 0007. As a part of...

Fracture network evaluation program (FraNEP): A software for analyzing 2D fracture trace-line maps

Science.gov (United States)

Zeeb, Conny; Gomez-Rivas, Enrique; Bons, Paul D.; Virgo, Simon; Blum, Philipp

2013-10-01

Fractures, such as joints, faults and veins, strongly influence the transport of fluids through rocks by either enhancing or inhibiting flow. Techniques used for the automatic detection of lineaments from satellite images and aerial photographs, LIDAR technologies and borehole televiewers significantly enhanced data acquisition. The analysis of such data is often performed manually or with different analysis software. Here we present a novel program for the analysis of 2D fracture networks called FraNEP (Fracture Network Evaluation Program). The program was developed using Visual Basic for Applications in Microsoft Excel™ and combines features from different existing software and characterization techniques. The main novelty of FraNEP is the possibility to analyse trace-line maps of fracture networks applying the (1) scanline sampling, (2) window sampling or (3) circular scanline and window method, without the need of switching programs. Additionally, binning problems are avoided by using cumulative distributions, rather than probability density functions. FraNEP is a time-efficient tool for the characterisation of fracture network parameters, such as density, intensity and mean length. Furthermore, fracture strikes can be visualized using rose diagrams and a fitting routine evaluates the distribution of fracture lengths. As an example of its application, we use FraNEP to analyse a case study of lineament data from a satellite image of the Oman Mountains.

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

International Nuclear Information System (INIS)

Straughn, Amber N.; Eufrasio, Rafael T.; Gardner, Jonathan P.; Voyer, Elysse N.; Mello, Duilia de; Soto, Emmaris; Petty, Sara; Kassin, Susan; Ravindranath, Swara

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Straughn, Amber N.; Eufrasio, Rafael T.; Gardner, Jonathan P. [Astrophysics Science Division, Goddard Space Flight Center, Code 665, Greenbelt, MD 20771 (United States); Voyer, Elysse N. [Randstad at Google, 1129 San Antonio Road, Palo Alto, CA (United States); Mello, Duilia de; Soto, Emmaris [Department of Physics, The Catholic University of America, Washington, DC 20064 (United States); Petty, Sara [Department of Physics, Virginia Tech, Blacksburg, VA 24061 (United States); Kassin, Susan; Ravindranath, Swara [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States)

2015-12-01

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

Measurement of Neutron Field Characteristics at Nuclear-Physics Instalations for Personal Radiation Monitoring

CERN Document Server

Alekseev, A G; Britvich, G I; Kosyanenko, E V; Pikalov, V A; Gomonov, I P

2003-01-01

n this work the observed data of neutron spectra on Rostov NEP, Kursk NEP and Smolensk NEP and on the reactor IRT MIPHI are submitted. For measurement of neutron spectra two types of spectrometer were used: SHANS (IHEP design ) and SDN-MS01 (FEI design). The comparison of the data measurements per-formed by those spectrometers above one-type cells on the reactor RBMK is submitted. On the basis of the 1-st horizontal experimental channel HEC-1 of the IRT reactor 4 reference fields of neutrons are investigated. It is shown, that spectra of neutrons of reference fields can be used for imitation of neutron spectra for conditions of NEP with VVER and RBMK type reactors.

GLOBEC NEP Northern California Current Cetacean Survey Data, NH0005, 2000-2000, 0007

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — GLOBEC (GLOBal Ocean ECosystems Dynamics) NEP (Northeast Pacific) Northern California Current Cetacean Survey Data from R/V New Horizon cruises NH0005 and 0007....

Survivin selective inhibitor YM155 induce apoptosis in SK-NEP-1 Wilms tumor cells

International Nuclear Information System (INIS)

Tao, Yan-Fang; Wu, Dong; Wang, Na; Feng, Xing; Li, Yan-Hong; Ni, Jian; Wang, Jian; Pan, Jian; Lu, Jun; Du, Xiao-Juan; Sun, Li-Chao; Zhao, Xuan; Peng, Liang; Cao, Lan; Xiao, Pei-Fang; Pang, Li

2012-01-01

Survivin, a member of the family of inhibitor of apoptosis proteins, functions as a key regulator of mitosis and programmed cell death. YM155, a novel molecular targeted agent, suppresses survivin, which is overexpressed in many tumor types. The aim of this study was to determine the antitumor activity of YM155 in SK-NEP-1 cells. SK-NEP-1 cell growth in vitro and in vivo was assessed by MTT and nude mice experiments. Annexin V/propidium iodide staining followed by flow cytometric analysis was used to detect apoptosis in cell culture. Then gene expression profile of tumor cells treated with YM155 was analyzed with real-time PCR arrays. We then analyzed the expression data with MEV (Multi Experiment View) cluster software. Datasets representing genes with altered expression profile derived from cluster analyses were imported into the Ingenuity Pathway Analysis tool. YM155 treatment resulted in inhibition of cell proliferation of SK-NEP-1cells in a dose-dependent manner. Annexin V assay, cell cycle, and activation of caspase-3 demonstrates that YM155 induced apoptosis in SK-NEP-1 cells. YM155 significantly inhibited growth of SK-NEP-1 xenografts (YM155 5 mg/kg: 1.45 ± 0.77 cm 3 ; YM155 10 mg/kg: 0.95 ± 0.55 cm 3 ) compared to DMSO group (DMSO: 3.70 ± 2.4 cm 3 ) or PBS group cells (PBS: 3.78 ± 2.20 cm 3 , ANOVA P < 0.01). YM155 treatment decreased weight of tumors (YM155 5 mg/kg: 1.05 ± 0.24 g; YM155 10 mg/kg: 0.72 ± 0.17 g) compared to DMSO group (DMSO: 2.06 ± 0.38 g) or PBS group cells (PBS: 2.36 ± 0.43 g, ANOVA P < 0.01). Real-time PCR array analysis showed between Test group and control group there are 32 genes significantly up-regulated and 54 genes were significantly down-regulated after YM155 treatment. Ingenuity pathway analysis (IPA) showed cell death was the highest rated network with 65 focus molecules and the significance score of 44. The IPA analysis also groups the differentially expressed genes into biological mechanisms that are related to cell

Saturn's Internal Magnetic Field Revealed by Cassini Grand Finale

Science.gov (United States)

Cao, H.; Dougherty, M. K.; Khurana, K. K.; Hunt, G. J.; Provan, G.; Kellock, S.; Burton, M. E.; Burk, T. A.

2017-12-01

Saturn's internal magnetic field has been puzzling since the first in-situ measurements during the Pioneer 11 Saturn flyby. Cassini magnetometer measurements prior to the Grand Finale phase established 1) the highly axisymmetric nature of Saturn's internal magnetic field with a dipole tilt smaller than 0.06 degrees, 2) at least an order of magnitude slower secular variation rate compared to that of the current geomagnetic field, and 3) expulsion of magnetic fluxes from the equatorial region towards high latitude. The highly axisymmetric nature of Saturn's intrinsic magnetic field not only challenges dynamo theory but also makes an accurate determination of the interior rotation rate of Saturn extremely difficult. The Cassini spacecraft entered the Grand Finale phase in April 2017, during which time the spacecraft dived through the gap between Saturn's atmosphere and the inner edge of the D-ring 22 times before descending into the deep atmosphere of Saturn. The unprecedented proximity to Saturn (reaching 2500 km above the cloud deck) and the highly inclined nature of the Grand Finale orbits provided an ideal opportunity to decode Saturn's internal magnetic field. The fluxgate magnetometer onboard Cassini made precise vector measurements during the Grand Finale phase. Magnetic signals from the interior of the planet, the magnetospheric ring current, the high-latitude field-aligned current (FAC) modulated by the 10.7 hour planetary period oscillation, and low-latitude FACs were observed during the Grand Finale phase. Here we report the magnetometer measurements during the Cassini Grand Finale phase, new features of Saturn's internal magnetic field revealed by these measurements (e.g., the high degree magnetic moments of Saturn, the level of axisymmetry beyond dipole), and implications for the deep interior of Saturn.

Nuclear electric propulsion /NEP/ spacecraft for the outer planet orbiter mission

International Nuclear Information System (INIS)

Garrison, P.W.; Nock, K.T.

1982-01-01

The design, operating features, and a possible Neptune orbit for the spacecraft powered by the SP-100 nuclear electric propulsion (NEP) system under study by NASA and the DOE are described. The system features a reactor and a payload situated on opposite ends of a 0.5 m diam, 11 m long astromast. Mercury-ion thrusters are located beneath the reactor for side thrusting, and no contamination of the payload or obstruction of the viewing angles for scientific objectives occurs with the system, which would not degrade in performance even under high insolation during near-sun maneuvers. Results of a theoretical study of earth escapes are presented to show that an NEP powered spiral trajectory out of a 700 km Shuttle orbit and using a Triton gravity assist would be superior to departing from a 300 km orbit with a Centaur boost. The mission profile includes a 1249 kg Galileo payload. The SP-100 has a 1.4 MWth reactor with UO2 fuel tiles and weighs 19,904 kg

NEP (Children@School): An Instrument for Measuring Environmental Attitudes in Middle Childhood

Science.gov (United States)

Izadpanahi, Parisa; Tucker, Richard

2018-01-01

While there are many environmental education programs for children, few studies have used an appropriately developed scale for evaluating how such education might have on impact on children's environmental orientations. The research presented in this article adapted the NEP (New Ecological Paradigm) for Children scale to develop a new instrument…

The New Ecological Paradigm Revisited: Anchoring the NEP Scale in Environmental Ethics

Science.gov (United States)

Lundmark, Carina

2007-01-01

The New Environmental or Ecological Paradigm (NEP) is widely acknowledged as a reliable multiple-item scale to capture environmental attitudes or beliefs. It has been used in statistical analyses for almost 30 years, primarily by psychologists, but also by political scientists, sociologists and geographers. The scale's theoretical foundation is,…

Deep Borehole Field Test Requirements and Controlled Assumptions.

Energy Technology Data Exchange (ETDEWEB)

Hardin, Ernest [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-07-01

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

Comparative and functional analysis of the widely occurring family of Nep1-like proteins

NARCIS (Netherlands)

Oome, Stan; van den Ackerveken, Guido

2014-01-01

Nep1-like proteins (NLP) are best known for their cytotoxic activity in dicot plants. NLP are taxonomically widespread among microbes with very different lifestyles. To learn more about this enigmatic protein family, we analyzed more than 500 available NLP protein sequences from fungi, oomycetes,

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

Directory of Open Access Journals (Sweden)

Peter Christiansen

2016-11-01

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

A PILOT FOR A VERY LARGE ARRAY H I DEEP FIELD

International Nuclear Information System (INIS)

Fernández, Ximena; Van Gorkom, J. H.; Schiminovich, David; Hess, Kelley M.; Pisano, D. J.; Kreckel, Kathryn; Momjian, Emmanuel; Popping, Attila; Oosterloo, Tom; Chomiuk, Laura; Verheijen, M. A. W.; Henning, Patricia A.; Bershady, Matthew A.; Wilcots, Eric M.; Scoville, Nick

2013-01-01

High-resolution 21 cm H I deep fields provide spatially and kinematically resolved images of neutral hydrogen at different redshifts, which are key to understanding galaxy evolution across cosmic time and testing predictions of cosmological simulations. Here we present results from a pilot for an H I deep field done with the Karl G. Jansky Very Large Array (VLA). We take advantage of the newly expanded capabilities of the telescope to probe the redshift interval 0 < z < 0.193 in one observation. We observe the COSMOS field for 50 hr, which contains 413 galaxies with optical spectroscopic redshifts in the imaged field of 34' × 34' and the observed redshift interval. We have detected neutral hydrogen gas in 33 galaxies in different environments spanning the probed redshift range, including three without a previously known spectroscopic redshift. The detections have a range of H I and stellar masses, indicating the diversity of galaxies we are probing. We discuss the observations, data reduction, results, and highlight interesting detections. We find that the VLA's B-array is the ideal configuration for H I deep fields since its long spacings mitigate radio frequency interference. This pilot shows that the VLA is ready to carry out such a survey, and serves as a test for future H I deep fields planned with other Square Kilometer Array pathfinders.

A PILOT FOR A VERY LARGE ARRAY H I DEEP FIELD

Energy Technology Data Exchange (ETDEWEB)

Fernandez, Ximena; Van Gorkom, J. H.; Schiminovich, David [Department of Astronomy, Columbia University, New York, NY 10027 (United States); Hess, Kelley M. [Department of Astronomy, Astrophysics, Cosmology and Gravity Centre, University of Cape Town, Private Bag X3, Rondebosch 7701 (South Africa); Pisano, D. J. [Department of Physics, West Virginia University, P.O. Box 6315, Morgantown, WV 26506 (United States); Kreckel, Kathryn [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany); Momjian, Emmanuel [National Radio Astronomy Observatory, Socorro, NM 87801 (United States); Popping, Attila [International Centre for Radio Astronomy Research (ICRAR), The University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia); Oosterloo, Tom [Netherlands Institute for Radio Astronomy (ASTRON), Postbus 2, NL-7990 AA Dwingeloo (Netherlands); Chomiuk, Laura [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); Verheijen, M. A. W. [Kapteyn Astronomical Institute, University of Groningen, Postbus 800, NL-9700 AV Groningen (Netherlands); Henning, Patricia A. [Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM 87131 (United States); Bershady, Matthew A.; Wilcots, Eric M. [Department of Astronomy, University of Wisconsin-Madison, Madison, WI 53706 (United States); Scoville, Nick, E-mail: ximena@astro.columbia.edu [Department of Astronomy, California Institute of Technology, Pasadena, CA 91125 (United States)

2013-06-20

High-resolution 21 cm H I deep fields provide spatially and kinematically resolved images of neutral hydrogen at different redshifts, which are key to understanding galaxy evolution across cosmic time and testing predictions of cosmological simulations. Here we present results from a pilot for an H I deep field done with the Karl G. Jansky Very Large Array (VLA). We take advantage of the newly expanded capabilities of the telescope to probe the redshift interval 0 < z < 0.193 in one observation. We observe the COSMOS field for 50 hr, which contains 413 galaxies with optical spectroscopic redshifts in the imaged field of 34' Multiplication-Sign 34' and the observed redshift interval. We have detected neutral hydrogen gas in 33 galaxies in different environments spanning the probed redshift range, including three without a previously known spectroscopic redshift. The detections have a range of H I and stellar masses, indicating the diversity of galaxies we are probing. We discuss the observations, data reduction, results, and highlight interesting detections. We find that the VLA's B-array is the ideal configuration for H I deep fields since its long spacings mitigate radio frequency interference. This pilot shows that the VLA is ready to carry out such a survey, and serves as a test for future H I deep fields planned with other Square Kilometer Array pathfinders.

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

Science.gov (United States)

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.

Impact of clinically tested NEP/ACE inhibitors on tumor uptake of [(111)In-DOTA]MG11-first estimates for clinical translation.

Science.gov (United States)

Kaloudi, Aikaterini; Nock, Berthold A; Lymperis, Emmanouil; Valkema, Roelf; Krenning, Eric P; de Jong, Marion; Maina, Theodosia

2016-12-01

We have recently shown that treatment of mice with the neutral endopeptidase (NEP) inhibitor phosphoramidon (PA) improves the bioavailability and tumor uptake of biodegradable radiopeptides. For the truncated gastrin radiotracer [(111)In-DOTA]MG11 ([(DOTA)DGlu(10)]gastrin(10-17)), this method led to impressively high tumor-to-kidney ratios. Translation of this concept in the clinic requires the use of certified NEP inhibitors, such as thiorphan (TO) and its orally administered prodrug racecadotril (Race). Besides NEP, angiotensin-converting enzyme (ACE) has also been implicated in the catabolism of gastrin analogs. In the present study, we first compared the effects induced by NEP inhibition (using PA, TO, or Race) and/or by ACE inhibition (using lisinopril, Lis) on the biodistribution profile of [(111)In-DOTA]MG11 in mice. In addition, we compared the efficacy of PA and TO at different administered doses to enhance tumor uptake. [(111)In-DOTA]MG11 was coinjected with (a) vehicle, (b) PA (300 μg), (c) TO (150 μg), (d) Lis (100 μg), (e) PA (300 μg) plus Lis (100 μg), or (f) 30-40 min after intraperitoneal (ip) injection of Race (3 mg) in SCID mice bearing AR42J xenografts. In addition, [(111)In-DOTA]MG11 was coinjected with vehicle, or with progressively increasing amounts of PA (3, 30, or 300 μg) or TO (1.5, 15, and 150 μg) in SCID mice bearing twin A431-CCK2R(+/-) tumors. In all above cases, biodistribution was conducted at 4 h postinjection (pi). During NEP inhibition, the uptake of [(111)In-DOTA]MG11 in the AR42J tumors impressively increased from 1.8 ± 1.0 % ID/g (controls) to 15.3 ± 4.7 % ID/g (PA) and 12.3 ± 3.6 % ID/g (TO), while with Race tumor values reached 6.8 ± 2.8 % ID/g. Conversely, Lis had no effect on tumor uptake and no additive effect when coinjected with PA. During the dose dependence study in mice, PA turned out to be more efficacious in enhancing tumor uptake of [(111)In-DOTA]MG11 in the CCK2R

Deep brain stimulation reveals emotional impact processing in ventromedial prefrontal cortex

DEFF Research Database (Denmark)

Gjedde, Albert; Geday, Jacob

2009-01-01

We tested the hypothesis that modulation of monoaminergic tone with deep-brain stimulation (DBS) of subthalamic nucleus would reveal a site of reactivity in the ventromedial prefrontal cortex that we previously identified by modulating serotonergic and noradrenergic mechanisms by blocking serotonin......-noradrenaline reuptake sites. We tested the hypothesis in patients with Parkinson's disease in whom we had measured the changes of blood flow everywhere in the brain associated with the deep brain stimulation of the subthalamic nucleus. We determined the emotional reactivity of the patients as the average impact...

Altered Gene Expression in Three Plant Species in Response to Treatment with Nep1, a Fungal Protein That Causes Necrosis

Science.gov (United States)

Keates, Sarah E.; Kostman, Todd A.; Anderson, James D.; Bailey, Bryan A.

2003-01-01

Nep1 is an extracellular fungal protein that causes necrosis when applied to many dicotyledonous plants, including invasive weed species. Using transmission electron microscopy, it was determined that application of Nep1 (1.0 μg mL–1, 0.1% [v/v] Silwet-L77) to Arabidopsis and two invasive weed species, spotted knapweed (Centaurea maculosa) and dandelion (Taraxacum officinale), caused a reduction in the thickness of the cuticle and a breakdown of chloroplasts 1 to 4 h after treatment. Membrane breakdown was most severe in cells closest to the surface of application. Differential display was used to isolate cDNA clones from the three species showing differential expression in response to Nep1 treatment. Differential gene expression was observed for a putative serpin (CmSER-1) and a calmodulin-like (CmCAL-1) protein from spotted knapweed, and a putative protein phosphatase 2C (ToPP2C-1) and cytochrome P-450 (ToCYP-1) protein from dandelion. In addition, differential expression was observed for genes coding for a putative protein kinase (AtPK-1), a homolog (AtWI-12) of wound-induced WI12, a homolog (AtLEA-1) of late embryogenesis abundant LEA-5, a WRKY-18 DNA-binding protein (AtWRKY-18), and a phospholipase D (AtPLD-1) from Arabidopsis. Genes showing elevated mRNA levels in Nep1-treated (5 μg mL–1, 0.1% [v/v] Silwet-L77) leaves 15 min after Nep1 treatment included CmSER-1 and CmCAL-1 for spotted knapweed, ToCYP-1 and CmCAL-1 for dandelion, and AtPK-1, AtWRKY-18, AtWI-12, and AtLEA-1 for Arabidopsis. Levels of mRNA for AtPLD-1 (Arabidopsis) and ToPP2C-1 (dandelion) decreased rapidly in Silwet-l77-treated plants between 15 min and 4 h of treatment, but were maintained or decreased more slowly over time in Nep1-treated (5 μg mL–1, 0.1% [v/v] Silwet-L77) leaves. In general, increases in mRNA band intensities were in the range of two to five times, with only ToCYP-1 in dandelion exceeding an increase of 10 times. The identified genes have been shown to be involved

THE SPITZER DEEP, WIDE-FIELD SURVEY

International Nuclear Information System (INIS)

Ashby, M. L. N.; Brodwin, M.; Stern, D.; Griffith, R.; Eisenhardt, P.; Gorjian, V.; Kozlowski, S.; Kochanek, C. S.; Bock, J. J.; Borys, C.; Brand, K.; Grogin, N. A.; Brown, M. J. I.; Cool, R.; Cooray, A.; Croft, S.; Dey, A.; Eisenstein, D.; Gonzalez, A. H.; Ivison, R. J.

2009-01-01

The Spitzer Deep, Wide-Field Survey (SDWFS) is a four-epoch infrared survey of 10 deg. 2 in the Booetes field of the NOAO Deep Wide-Field Survey using the IRAC instrument on the Spitzer Space Telescope. SDWFS, a Spitzer Cycle 4 Legacy project, occupies a unique position in the area-depth survey space defined by other Spitzer surveys. The four epochs that make up SDWFS permit-for the first time-the selection of infrared-variable and high proper motion objects over a wide field on timescales of years. Because of its large survey volume, SDWFS is sensitive to galaxies out to z ∼ 3 with relatively little impact from cosmic variance for all but the richest systems. The SDWFS data sets will thus be especially useful for characterizing galaxy evolution beyond z ∼ 1.5. This paper explains the SDWFS observing strategy and data processing, presents the SDWFS mosaics and source catalogs, and discusses some early scientific findings. The publicly released, full-depth catalogs contain 6.78, 5.23, 1.20, and 0.96 x 10 5 distinct sources detected to the average 5σ, 4''-diameter, aperture-corrected limits of 19.77, 18.83, 16.50, and 15.82 Vega mag at 3.6, 4.5, 5.8, and 8.0 μm, respectively. The SDWFS number counts and color-color distribution are consistent with other, earlier Spitzer surveys. At the 6 minute integration time of the SDWFS IRAC imaging, >50% of isolated Faint Images of the Radio Sky at Twenty cm radio sources and >80% of on-axis XBooetes sources are detected out to 8.0 μm. Finally, we present the four highest proper motion IRAC-selected sources identified from the multi-epoch imaging, two of which are likely field brown dwarfs of mid-T spectral class.

The GISMO two-millimeter deep field in GOODS-N

Energy Technology Data Exchange (ETDEWEB)

Staguhn, Johannes G. [The Henry A. Rowland Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Kovács, Attila [California Institute of Technology 301-17, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Arendt, Richard G.; Benford, Dominic J.; Dwek, Eli; Fixsen, Dale J.; Jhabvala, Christine A.; Maher, Stephen F.; Miller, Timothy M.; Moseley, S. Harvey; Sharp, Elmer H.; Wollack, Edward J. [Observational Cosmology Lab, Code 665, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Decarli, Roberto; Walter, Fabian [Max-Planck-Institute für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Hilton, Gene C.; Irwin, Kent D. [NIST Quantum Devices Group, 325 Broadway Mailcode 817.03, Boulder, CO 80305 (United States); Karim, Alexander [Department of Physics, Durham University, South Road, Durham DH1 3LE (United Kingdom); Leclercq, Samuel [Institut de Radio Astronomie Millimétrique, 300 Rue de la Piscine, F-38406 Saint Martin d' Heres (France)

2014-07-20

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

THE 2012 HUBBLE ULTRA DEEP FIELD (UDF12): OBSERVATIONAL OVERVIEW

Energy Technology Data Exchange (ETDEWEB)

Koekemoer, Anton M. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Ellis, Richard S.; Schenker, Matthew A. [Department of Astrophysics, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States); McLure, Ross J.; Dunlop, James S.; Bowler, Rebecca A. A.; Rogers, Alexander B.; Curtis-Lake, Emma; Cirasuolo, Michele; Wild, V.; Targett, T. [Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ (United Kingdom); Robertson, Brant E.; Schneider, Evan; Stark, Daniel P. [Department of Astronomy and Steward Observatory, University of Arizona, Tucson, AZ 85721 (United States); Ono, Yoshiaki; Ouchi, Masami [Institute for Cosmic Ray Research, University of Tokyo, Kashiwa City, Chiba 277-8582 (Japan); Charlot, Stephane [UPMC-CNRS, UMR7095, Institut d' Astrophysique de Paris, F-75014, Paris (France); Furlanetto, Steven R. [Department of Physics and Astronomy, University of California, Los Angeles, CA 90095 (United States)

2013-11-01

We present the 2012 Hubble Ultra Deep Field campaign (UDF12), a large 128 orbit Cycle 19 Hubble Space Telescope program aimed at extending previous Wide Field Camera 3 (WFC3)/IR observations of the UDF by quadrupling the exposure time in the F105W filter, imaging in an additional F140W filter, and extending the F160W exposure time by 50%, as well as adding an extremely deep parallel field with the Advanced Camera for Surveys (ACS) in the F814W filter with a total exposure time of 128 orbits. The principal scientific goal of this project is to determine whether galaxies reionized the universe; our observations are designed to provide a robust determination of the star formation density at z ∼> 8, improve measurements of the ultraviolet continuum slope at z ∼ 7-8, facilitate the construction of new samples of z ∼ 9-10 candidates, and enable the detection of sources up to z ∼ 12. For this project we committed to combining these and other WFC3/IR imaging observations of the UDF area into a single homogeneous dataset to provide the deepest near-infrared observations of the sky. In this paper we present the observational overview of the project and describe the procedures used in reducing the data as well as the final products that were produced. We present the details of several special procedures that we implemented to correct calibration issues in the data for both the WFC3/IR observations of the main UDF field and our deep 128 orbit ACS/WFC F814W parallel field image, including treatment for persistence, correction for time-variable sky backgrounds, and astrometric alignment to an accuracy of a few milliarcseconds. We release the full, combined mosaics comprising a single, unified set of mosaics of the UDF, providing the deepest near-infrared blank-field view of the universe currently achievable, reaching magnitudes as deep as AB ∼ 30 mag in the near-infrared, and yielding a legacy dataset on this field.

THE 2012 HUBBLE ULTRA DEEP FIELD (UDF12): OBSERVATIONAL OVERVIEW

International Nuclear Information System (INIS)

Koekemoer, Anton M.; Ellis, Richard S.; Schenker, Matthew A.; McLure, Ross J.; Dunlop, James S.; Bowler, Rebecca A. A.; Rogers, Alexander B.; Curtis-Lake, Emma; Cirasuolo, Michele; Wild, V.; Targett, T.; Robertson, Brant E.; Schneider, Evan; Stark, Daniel P.; Ono, Yoshiaki; Ouchi, Masami; Charlot, Stephane; Furlanetto, Steven R.

2013-01-01

We present the 2012 Hubble Ultra Deep Field campaign (UDF12), a large 128 orbit Cycle 19 Hubble Space Telescope program aimed at extending previous Wide Field Camera 3 (WFC3)/IR observations of the UDF by quadrupling the exposure time in the F105W filter, imaging in an additional F140W filter, and extending the F160W exposure time by 50%, as well as adding an extremely deep parallel field with the Advanced Camera for Surveys (ACS) in the F814W filter with a total exposure time of 128 orbits. The principal scientific goal of this project is to determine whether galaxies reionized the universe; our observations are designed to provide a robust determination of the star formation density at z ∼> 8, improve measurements of the ultraviolet continuum slope at z ∼ 7-8, facilitate the construction of new samples of z ∼ 9-10 candidates, and enable the detection of sources up to z ∼ 12. For this project we committed to combining these and other WFC3/IR imaging observations of the UDF area into a single homogeneous dataset to provide the deepest near-infrared observations of the sky. In this paper we present the observational overview of the project and describe the procedures used in reducing the data as well as the final products that were produced. We present the details of several special procedures that we implemented to correct calibration issues in the data for both the WFC3/IR observations of the main UDF field and our deep 128 orbit ACS/WFC F814W parallel field image, including treatment for persistence, correction for time-variable sky backgrounds, and astrometric alignment to an accuracy of a few milliarcseconds. We release the full, combined mosaics comprising a single, unified set of mosaics of the UDF, providing the deepest near-infrared blank-field view of the universe currently achievable, reaching magnitudes as deep as AB ∼ 30 mag in the near-infrared, and yielding a legacy dataset on this field

UV--Visible observations with HST in the JWST North Ecliptic Pole Time-Domain Field

Science.gov (United States)

Jansen, Rolf A.; Windhorst, Rogier; Grogin, Norman; Koekemoer, Anton; Royle, Patricia; Hathi, Nimish; Jones, Victoria; Cohen, Seth; Ashcraft, Teresa; Willmer, Christopher; Conselice, Christopher; White, Cameron; Frye, Brenda; HST-GO-15278 team; and the Webb Medium Deep Fields IDS GTO team.

2018-01-01

We report the first results from a UV–Visible HST imaging survey of the JWST North Ecliptic Pole (NEP) Time-Domain Field (TDF). Using CVZ and near-CVZ opportunities we observed the first two out of nine tiles with WFC3/UVIS in F275W and with ACS/WFC in F435W and F606W. Over the course of the next 13 months, this survey is designed to provide near-contiguous 3-filter coverage of the central r ≤ 5‧ of this new community field for time-domain science with JWST. The JWST NEP TDF is located within JWST's northern Continuous Viewing Zone, will span ~14‧ in diameter (~10‧ with NIRISS coverage), is devoid of sources bright enough to saturate the NIRCam detectors, has low Galactic foreground extinction, and will be roughly circular in shape (initially sampled during Cycle 1 at 4 distinct orientations with JWST/NIRCam — the JWST “windmill”). NIRISS slitless grism spectroscopy will be taken in parallel, overlapping an alternate NIRCam orientation. This is the only region in the sky where JWST can observe a clean extragalactic deep survey field of this size at arbitrary cadence or at arbitrary orientation. This will crucially enable a wide range of new and exciting time-domain science, including high redshift transient searches and monitoring (e.g., SNe), variability studies from Active Galactic Nuclei to brown dwarf atmospheres, as well as proper motions of extreme scattered Kuiper Belt and Oort Cloud Objects, and of nearby Galactic brown dwarfs, low-mass stars, and ultracool white dwarfs. Ancillary data across the electromagnetic spectrum will exist for this field when JWST science operations commence in the second half of 2019. This includes deep (mAB ~ 26 mag) wide-field (~23‧×25‧) Ugriz photometry of this field and its surroundings from LBT/LBC and Subaru/HSC, JHK from MMT/MMIRS, VLA 3 GHz and VLBA 4.5 GHz radio observations, and Chandra/ACIS X-ray images. Proposals for (sub)mm observations and spectroscopy to mAB ~ 24 mag are pending.

A review on the formation, causes, measurement, implications and reduction of neps during cotton processing

CSIR Research Space (South Africa)

Van der Sluijs, MHJ

2016-12-01

Full Text Available and processing as far back as the late 1700s, no comprehensive review has been published on the formation, composition, measurement, consequences and ways to reduce the effects of neps, only a limited review has been published in 1999 [1 M.H.J. van der Sluijs...

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

Science.gov (United States)

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.

Use of High-Power Brayton Nuclear Electric Propulsion (NEP) for a 2033 Mars Round-Trip Mission

International Nuclear Information System (INIS)

McGuire, Melissa L.; Martini, Michael C.; Packard, Thomas W.; Weglian, John E.; Gilland, James H.

2006-01-01

The Revolutionary Aerospace Systems Concepts (RASC) team, led by the NASA Langley Research Center, is tasked with exploring revolutionary new approaches to enabling NASA to achieve its strategic goals and objectives in future missions. This paper provides the details from the 2004-2005 RASC study of a point-design that uses a high-power nuclear electric propulsion (NEP) based space transportation architecture to support a manned mission to Mars. The study assumes a high-temperature liquid-metal cooled fission reactor with a Brayton power conversion system to generate the electrical power required by magnetoplasmadynamic (MPD) thrusters. The architecture includes a cargo vehicle with an NEP system providing 5 MW of electrical power and a crewed vehicle with an NEP system with two reactors providing a combined total of 10 MW of electrical power. Both vehicles use a low-thrust, high-efficiency (5000 sec specific impulse) MPD system to conduct a spiral-out of the Earth gravity well, a low-thrust heliocentric trajectory, and a spiral-in at Mars with arrival late in 2033. The cargo vehicle carries two moon landers to Mars and arrives shortly before the crewed vehicle. The crewed vehicle and cargo vehicle rendezvous in Mars orbit and, over the course of the 60-day stay, the crew conducts nine-day excursions to Phobos and Deimos with the landers. The crewed vehicle then spirals out of Martian orbit and returns via a low-thrust trajectory to conduct an Earth flyby. The crew separates from the vehicle prior to Earth flyby and aerobrakes for a direct-entry landing

Test Research of Reducing Combed Yarn Neps%降低精梳纱棉结的试验研究

Institute of Scientific and Technical Information of China (English)

赵建伟

2011-01-01

Technology measures of reducing combed yarn neps were discussed.Causes of combed yarn neps formation and changing rules in spinning were analyzed.Cotton assorting and processing configurations in each process were modified and optimized.Basic management works were enhanced such as raw cotton selection, equipment clean, operation clean and temperature & humidity control.Finally neps of CJ 18.2 tex cheese and CJ 22.4 tex cheese could be kept below 31 per kilometer and 25 per kilometer.It is pointed out that processing in cotton assorting,carding and combing process should be set rationally,reducing neps is a system project,the key points should be focused, whole process control should be implemented and basic management should be strengthened, finally the better effect could be got.%探讨降低精梳纱棉结的技术措施.分析了精梳纱棉结的形成原因及纺纱过程中的变化规律,通过对配棉及各工序的工艺进行改进和优化配置,加强原棉、设备揩车和运转清洁工作及温湿度等各项基础管理工作,结果使CJ 18.2 tex、CJ 22.4 tex筒纱棉结长期保持在31个/km和25个/km以下.指出:减少精梳纱棉结是一项系统工程,仅仅依靠配棉、梳棉、精梳工序的作用是不够的,应突出重点实行纺纱全过程控制并切实加强基础性管理工作,才能收到较好效果.

Dual NEP/ECE inhibition improves endothelial function in mesenteric resistance arteries of 32-week-old SHR

DEFF Research Database (Denmark)

Lemkens, Pieter; Spijkers, Leon Ja; Meens, Merlijn J

2017-01-01

Endothelin 1 (ET-1), a potent vasoconstrictor, pro-mitogenic and pro-inflammatory peptide, may promote development of endothelial dysfunction and arterial remodeling. ET-1 can be formed through cleavage of big-ET-1 by endothelin-converting enzyme (ECE) or neutral endopeptidase (NEP). We investiga...

Purification, crystallization and preliminary X-ray diffraction analysis of an oomycete-derived Nep1-like protein

NARCIS (Netherlands)

Luberacki, B.; Weyand, M.; Seitz, H.U.; Koch, W.; Oecking, C.; Ottmann, C.

2008-01-01

The elicitor protein Nep1-like protein from the plant pathogen Pythium aphanidermatum was purified and crystallized using the hanging-drop vapour-diffusion method. A native data set was collected to 1.35 angstrom resolution at 100 K using synchrotron radiation. Since selenomethionine-labelled

Deep Vadose Zone–Applied Field Research Initiative Fiscal Year 2012 Annual Report

Energy Technology Data Exchange (ETDEWEB)

Wellman, Dawn M.; Truex, Michael J.; Johnson, Timothy C.; Bunn, Amoret L.; Golovich, Elizabeth C.

2013-03-14

This annual report describes the background of the Deep Vadose Zone-Applied Field Research Initiative, and some of the programmatic approaches and transformational technologies in groundwater and deep vadose zone remediation developed during fiscal year 2012.

The transcriptome of Bathymodiolus azoricus gill reveals expression of genes from endosymbionts and free-living deep-sea bacteria.

Science.gov (United States)

Egas, Conceição; Pinheiro, Miguel; Gomes, Paula; Barroso, Cristina; Bettencourt, Raul

2012-08-01

Deep-sea environments are largely unexplored habitats where a surprising number of species may be found in large communities, thriving regardless of the darkness, extreme cold, and high pressure. Their unique geochemical features result in reducing environments rich in methane and sulfides, sustaining complex chemosynthetic ecosystems that represent one of the most surprising findings in oceans in the last 40 years. The deep-sea Lucky Strike hydrothermal vent field, located in the Mid Atlantic Ridge, is home to large vent mussel communities where Bathymodiolus azoricus represents the dominant faunal biomass, owing its survival to symbiotic associations with methylotrophic or methanotrophic and thiotrophic bacteria. The recent transcriptome sequencing and analysis of gill tissues from B. azoricus revealed a number of genes of bacterial origin, hereby analyzed to provide a functional insight into the gill microbial community. The transcripts supported a metabolically active microbiome and a variety of mechanisms and pathways, evidencing also the sulfur and methane metabolisms. Taxonomic affiliation of transcripts and 16S rRNA community profiling revealed a microbial community dominated by thiotrophic and methanotrophic endosymbionts of B. azoricus and the presence of a Sulfurovum-like epsilonbacterium.

Making Data Mobile: The Hubble Deep Field Academy iPad app

Science.gov (United States)

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

2013-01-01

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

Deep Brain Stimulation of the H Fields of Forel Alleviates Tics in Tourette Syndrome

Directory of Open Access Journals (Sweden)

Clemens Neudorfer

2017-06-01

Full Text Available The current rationale for target selection in Tourette syndrome revolves around the notion of cortico-basal ganglia circuit involvement in the pathophysiology of the disease. However, despite extensive research, the ideal target for deep brain stimulation (DBS is still under debate, with many structures being neglected and underexplored. Based on clinical observations and taking into account the prevailing hypotheses of network processing in Tourette syndrome, we chose the fields of Forel, namely field H1, as a target for DBS. The fields of Forel constitute the main link between the striatopallidal system and the thalamocortical network, relaying pallidothalamic projections from core anatomical structures to the thalamic ventral nuclear group. In a retrospective study we investigated two patients suffering from chronic, medically intractable Tourette syndrome who underwent bilateral lead implantation in field H1 of Forel. Clinical scales revealed significant alleviation of tics and comorbid symptoms, namely depression and anxiety, in the postoperative course in both patients.

EMPIRICAL PREDICTIONS FOR (SUB-)MILLIMETER LINE AND CONTINUUM DEEP FIELDS

Energy Technology Data Exchange (ETDEWEB)

Da Cunha, Elisabete; Walter, Fabian; Decarli, Roberto; Rix, Hans-Walter [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); Bertoldi, Frank [Argelander Institute for Astronomy, University of Bonn, Auf dem Huegel 71, D-53121 Bonn (Germany); Carilli, Chris [National Radio Astronomy Observatory, Pete V. Domenici Array Science Center, P.O. Box O, Socorro, NM 87801 (United States); Daddi, Emanuele; Elbaz, David; Sargent, Mark [Laboratoire AIM, CEA/DSM-CNRS-Universite Paris Diderot, Irfu/Service d' Astrophysique, CEA Saclay, Orme des Merisiers, F-91191 Gif-sur-Yvette Cedex (France); Ivison, Rob [UK Astronomy Technology Centre, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Maiolino, Roberto [Cavendish Laboratory, University of Cambridge, 19 J.J. Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Riechers, Dominik [Astronomy Department, California Institute of Technology, MC 249-17, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Smail, Ian [Institute for Computational Cosmology, Durham University, South Road, Durham DH1 3LE (United Kingdom); Weiss, Axel, E-mail: cunha@mpia.de [Max-Planck-Institut fuer Radioastronomie, Auf dem Huegel 69, D-53121 Bonn (Germany)

2013-03-01

Modern (sub-)millimeter/radio interferometers such as ALMA, JVLA, and the PdBI successor NOEMA will enable us to measure the dust and molecular gas emission from galaxies that have luminosities lower than the Milky Way, out to high redshifts and with unprecedented spatial resolution and sensitivity. This will provide new constraints on the star formation properties and gas reservoir in galaxies throughout cosmic times through dedicated deep field campaigns targeting the CO/[C II] lines and dust continuum emission in the (sub-)millimeter regime. In this paper, we present empirical predictions for such line and continuum deep fields. We base these predictions on the deepest available optical/near-infrared Advanced Camera for Surveys and NICMOS data on the Hubble Ultra Deep Field (over an area of about 12 arcmin{sup 2}). Using a physically motivated spectral energy distribution model, we fit the observed optical/near-infrared emission of 13,099 galaxies with redshifts up to z = 5, and obtain median-likelihood estimates of their stellar mass, star formation rate, dust attenuation, and dust luminosity. We combine the attenuated stellar spectra with a library of infrared emission models spanning a wide range of dust temperatures to derive statistical constraints on the dust emission in the infrared and (sub-)millimeter which are consistent with the observed optical/near-infrared emission in terms of energy balance. This allows us to estimate, for each galaxy, the (sub-)millimeter continuum flux densities in several ALMA, PdBI/NOEMA, and JVLA bands. As a consistency check, we verify that the 850 {mu}m number counts and extragalactic background light derived using our predictions are consistent with previous observations. Using empirical relations between the observed CO/[C II] line luminosities and the infrared luminosity of star-forming galaxies, we infer the luminosity of the CO(1-0) and [C II] lines from the estimated infrared luminosity of each galaxy in our sample

Deep Borehole Field Test Conceptual Design Report

Energy Technology Data Exchange (ETDEWEB)

Hardin, Ernest L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-09-30

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

Techniques for Field Operation of Straddle-packer System in Deep Borehole

International Nuclear Information System (INIS)

Kim, Kyung Su; Park, Kyung Woo; Kim, Geon Young; Ji, Sung Hoon; Koh, Yong Kwon; Choi, Jong Won

2010-05-01

It is necessary to establish an appropriate hydro-testing tool for the qualified characterization of deep geological environments, especially for the hydraulic properties of rock formation. This research project had been initiated for the purpose of establishment of advanced infra-structures in KURT. The straddle packer system was developed for hydraulic characterization of geological formation using deep borehole. This technical report consists of design concept, basic requirements, function of each part, field operation procedures and techniques, detail design drawings, and specifications. The qualified hydro-testing tool, which is suitable for medium to low permeable formation, using large and deep borehole, has been developed. This tool will be applied for the research project on development of HLW disposal technologies and the site characterization activities of LILW disposal project. Prior to field operation using this hydro-testing equipment, every researchers should be well acquainted with this technical report

THE HST EXTREME DEEP FIELD (XDF): COMBINING ALL ACS AND WFC3/IR DATA ON THE HUDF REGION INTO THE DEEPEST FIELD EVER

International Nuclear Information System (INIS)

Illingworth, G. D.; Magee, D.; Oesch, P. A.; Bouwens, R. J.; Labbé, I.; Franx, M.; Stiavelli, M.; Van Dokkum, P. G.; Trenti, M.; Carollo, C. M.; Gonzalez, V.

2013-01-01

The eXtreme Deep Field (XDF) combines data from 10 years of observations with the Hubble Space Telescope Advanced Camera for Surveys (ACS) and the Wide-Field Camera 3 Infra-Red (WFC3/IR) into the deepest image of the sky ever in the optical/near-IR. Since the initial observations of the Hubble Ultra-Deep Field (HUDF) in 2003, numerous surveys and programs, including supernovae follow-up, HUDF09, CANDELS, and HUDF12, have contributed additional imaging data across this region. However, these images have never been combined and made available as one complete ultra-deep image dataset. We combine them now with the XDF program. Our new and improved processing techniques provide higher quality reductions of the total dataset. All WFC3/IR and optical ACS data sets have been fully combined and accurately matched, resulting in the deepest imaging ever taken at these wavelengths, ranging from 29.1 to 30.3 AB mag (5σ in a 0.''35 diameter aperture) in 9 filters. The combined image therefore reaches to 31.2 AB mag 5σ (32.9 at 1σ) for a flat f ν source. The gains in the optical for the four filters done in the original ACS HUDF correspond to a typical improvement of 0.15 mag, with gains of 0.25 mag in the deepest areas. Such gains are equivalent to adding ∼130 to ∼240 orbits of ACS data to the HUDF. Improved processing alone results in a typical gain of ∼0.1 mag. Our 5σ (optical+near-IR) SExtractor catalogs reveal about 14,140 sources in the full field and about 7121 galaxies in the deepest part of the XDF

Ancient Biomolecules from Deep Ice Cores Reveal a Forested Southern Greenland

Science.gov (United States)

Willerslev, Eske; Cappellini, Enrico; Boomsma, Wouter; Nielsen, Rasmus; Hebsgaard, Martin B.; Brand, Tina B.; Hofreiter, Michael; Bunce, Michael; Poinar, Hendrik N.; Dahl-Jensen, Dorthe; Johnsen, Sigfus; Steffensen, Jørgen Peder; Bennike, Ole; Schwenninger, Jean-Luc; Nathan, Roger; Armitage, Simon; de Hoog, Cees-Jan; Alfimov, Vasily; Christl, Marcus; Beer, Juerg; Muscheler, Raimund; Barker, Joel; Sharp, Martin; Penkman, Kirsty E.H.; Haile, James; Taberlet, Pierre; Gilbert, M. Thomas P.; Casoli, Antonella; Campani, Elisa; Collins, Matthew J.

2009-01-01

One of the major difficulties in paleontology is the acquisition of fossil data from the 10% of Earth’s terrestrial surface that is covered by thick glaciers and ice sheets. Here we reveal that DNA and amino acids from buried organisms can be recovered from the basal sections of deep ice cores and allow reconstructions of past flora and fauna. We show that high altitude southern Greenland, currently lying below more than two kilometers of ice, was once inhabited by a diverse array of conifer trees and insects that may date back more than 450 thousand years. The results provide the first direct evidence in support of a forested southern Greenland and suggest that many deep ice cores may contain genetic records of paleoenvironments in their basal sections. PMID:17615355

Deep inelastic lepton-nucleus scattering from the light-cone quantum field theory

International Nuclear Information System (INIS)

Boqiang Ma; Ji Sun

1990-01-01

We show that for deep inelastic lepton-nucleus scattering, the conditions which validate the impulse approximation are hardly satisfied when using ordinary instant form dynamics in the rest frame of the nucleus, whereas they are well satisfied when using instant form dynamics in the infinite-momentum frame, or using light-front form dynamics in an ordinary frame. Therefore a reliable theoretical treatment of deep inelastic lepton-nucleus scattering should be performed in the time-ordered perturbation theory in the infinite-momentum frame, or its equivalent, the light-cone perturbation theory in an ordinary frame. To this end, we extend the light-cone quantum field theory to the baryon-meson field to establish a relativistic composite model of nuclei. We then apply the impulse approximation to deep inelastic lepton-nucleus scattering in this model.(author)

Metagenomic Signatures of Microbial Communities in Deep-Sea Hydrothermal Sediments of Azores Vent Fields.

Science.gov (United States)

Cerqueira, Teresa; Barroso, Cristina; Froufe, Hugo; Egas, Conceição; Bettencourt, Raul

2018-01-21

The organisms inhabiting the deep-seafloor are known to play a crucial role in global biogeochemical cycles. Chemolithoautotrophic prokaryotes, which produce biomass from single carbon molecules, constitute the primary source of nutrition for the higher organisms, being critical for the sustainability of food webs and overall life in the deep-sea hydrothermal ecosystems. The present study investigates the metabolic profiles of chemolithoautotrophs inhabiting the sediments of Menez Gwen and Rainbow deep-sea vent fields, in the Mid-Atlantic Ridge. Differences in the microbial community structure might be reflecting the distinct depth, geology, and distance from vent of the studied sediments. A metagenomic sequencing approach was conducted to characterize the microbiome of the deep-sea hydrothermal sediments and the relevant metabolic pathways used by microbes. Both Menez Gwen and Rainbow metagenomes contained a significant number of genes involved in carbon fixation, revealing the largely autotrophic communities thriving in both sites. Carbon fixation at Menez Gwen site was predicted to occur mainly via the reductive tricarboxylic acid cycle, likely reflecting the dominance of sulfur-oxidizing Epsilonproteobacteria at this site, while different autotrophic pathways were identified at Rainbow site, in particular the Calvin-Benson-Bassham cycle. Chemolithotrophy appeared to be primarily driven by the oxidation of reduced sulfur compounds, whether through the SOX-dependent pathway at Menez Gwen site or through reverse sulfate reduction at Rainbow site. Other energy-yielding processes, such as methane, nitrite, or ammonia oxidation, were also detected but presumably contributing less to chemolithoautotrophy. This work furthers our knowledge of the microbial ecology of deep-sea hydrothermal sediments and represents an important repository of novel genes with potential biotechnological interest.

99mTc-labeled gastrins of varying peptide chain length: Distinct impact of NEP/ACE-inhibition on stability and tumor uptake in mice

International Nuclear Information System (INIS)

Kaloudi, Aikaterini; Nock, Berthold A.; Lymperis, Emmanouil; Krenning, Eric P.; Jong, Marion de; Maina, Theodosia

2016-01-01

Introduction: In situ inhibition of neutral endopeptidase (NEP) has been recently shown to impressively increase the bioavailability and tumor uptake of biodegradable gastrin radioligands. Furthermore, angiotensin converting enzyme (ACE) has been previously shown to cleave gastrin analogs in vitro. In the present study, we have assessed the effects induced by single or dual NEP/ACE-inhibition on the pharmacokinetic profile of three 99m Tc-labeled gastrins of varying peptide chain length: [ 99m Tc]SG6 ([ 99m Tc-N 4 -Gln 1 ]gastrin(1–17)), [ 99m Tc]DG2 ([ 99m Tc-N 4 -Gly 4 ,DGlu 5 ]gastrin(4–17)) and [ 99m Tc]DG4 ([ 99m Tc-N 4 -DGlu 10 ]gastrin(10–17)). Methods: Mouse blood samples were collected 5 min after injection of each of [ 99m Tc]SG6/DG2/DG4 together with: a) vehicle, b) the NEP-inhibitor phosphoramidon (PA), c) the ACE-inhibitor lisinopril (Lis), or d) PA plus Lis and were analyzed by RP-HPLC for radiometabolite detection. Biodistribution was studied in SCID mice bearing A431-CCK2R(+/−) xenografts at 4 h postinjection (pi). [ 99m Tc]SG6 or [ 99m Tc]DG4 was coinjected with either vehicle or the above described NEP/ACE-inhibitor regimens; for [ 99m Tc]DG2 control and PA animal groups were only included. Results: Treatment of mice with PA induced significant stabilization of 99m Tc-radiotracers in peripheral blood, while treatment with Lis or Lis + PA affected the stability of des(Glu) 5 [ 99m Tc]DG4 only. In line with these findings, PA coinjection led to notable amplification of tumor uptake of radiopeptides compared to controls (P < 0.01). Only [ 99m Tc]DG4 profited by single Lis (2.06 ± 0.39%ID/g vs 0.99 ± 0.13%ID/g in controls) or combined Lis + PA coinjection (8.91 ± 1.61%ID/g vs 4.89 ± 1.33%ID/g in PA-group). Furthermore, kidney uptake remained favourably low and unaffected by PA and/or Lis coinjection only in the case of [ 99m Tc]DG4 (< 1.9%ID/g) resulting in the most optimal tumor-to-kidney ratios. Conclusions: In situ NEP

The Transcriptome of Bathymodiolus azoricus Gill Reveals Expression of Genes from Endosymbionts and Free-Living Deep-Sea Bacteria

Directory of Open Access Journals (Sweden)

Raul Bettencourt

2012-08-01

Full Text Available Deep-sea environments are largely unexplored habitats where a surprising number of species may be found in large communities, thriving regardless of the darkness, extreme cold, and high pressure. Their unique geochemical features result in reducing environments rich in methane and sulfides, sustaining complex chemosynthetic ecosystems that represent one of the most surprising findings in oceans in the last 40 years. The deep-sea Lucky Strike hydrothermal vent field, located in the Mid Atlantic Ridge, is home to large vent mussel communities where Bathymodiolus azoricus represents the dominant faunal biomass, owing its survival to symbiotic associations with methylotrophic or methanotrophic and thiotrophic bacteria. The recent transcriptome sequencing and analysis of gill tissues from B. azoricus revealed a number of genes of bacterial origin, hereby analyzed to provide a functional insight into the gill microbial community. The transcripts supported a metabolically active microbiome and a variety of mechanisms and pathways, evidencing also the sulfur and methane metabolisms. Taxonomic affiliation of transcripts and 16S rRNA community profiling revealed a microbial community dominated by thiotrophic and methanotrophic endosymbionts of B. azoricus and the presence of a Sulfurovum-like epsilonbacterium.

DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields

Directory of Open Access Journals (Sweden)

Sheng Wang

2015-07-01

Full Text Available Intrinsically disordered proteins or protein regions are involved in key biological processes including regulation of transcription, signal transduction, and alternative splicing. Accurately predicting order/disorder regions ab initio from the protein sequence is a prerequisite step for further analysis of functions and mechanisms for these disordered regions. This work presents a learning method, weighted DeepCNF (Deep Convolutional Neural Fields, to improve the accuracy of order/disorder prediction by exploiting the long-range sequential information and the interdependency between adjacent order/disorder labels and by assigning different weights for each label during training and prediction to solve the label imbalance issue. Evaluated by the CASP9 and CASP10 targets, our method obtains 0.855 and 0.898 AUC values, which are higher than the state-of-the-art single ab initio predictors.

Andrographolide promotes vincristine-induced SK-NEP-1 tumor cell death via PI3K-AKT-p53 signaling pathway

Science.gov (United States)

Zhang, Mingsheng; Xue, Enda; Shao, Wei

2016-01-01

Background Nephroblastoma (Wilms’ tumor [WT]) is the most common malignant renal cancer in children. Although the outcome of WT has significantly improved as a result of the combination of surgery, chemotherapy, and radiotherapy; in some cases WT results in severe complications. Thus, novel strategies that would decrease treatment burden are required. The aim of the current study was to investigate the synergistic antitumor effect of andrographolide (AND) in combination with vincristine (VCR) on WT cells. Methods Cell Counting Kit-8 assay was used to investigate the synergistic antiproliferation effect of AND and/or VCR on SK-NEP-1 cells in vitro. Meanwhile, SK-NEP-1 xenografts were used to detect the antitumor effect in vivo. Apoptosis and autophagy were then detected by Annexin V, monodansylcadaverine staining. Finally, the underlying signaling transduction was determined with Western blotting. Results The combination of AND with VCR significantly suppressed SK-NEP-1 cell proliferation in vitro and inhibited xenograft tumor growth in vivo, compared with AND or VCR treatment alone. In addition, the synergistic antitumor effect of AND on the cells was due to an increased apoptosis, not autophagy. Moreover, PI3K-AKT-p53 signaling pathway was involved in the process of combination treatment, which was confirmed when a selective AKT activator was applied. Conclusion The combination of AND with VCR has a strong synergistic antitumor effect on WT via PI3K-AKT-p53 signaling pathway, thereby representing a potential treatment for WT in the near future. PMID:27729773

MOVING OBJECTS IN THE HUBBLE ULTRA DEEP FIELD

Energy Technology Data Exchange (ETDEWEB)

Kilic, Mukremin; Gianninas, Alexandros [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, 440 W. Brooks St., Norman, OK 73019 (United States); Von Hippel, Ted, E-mail: kilic@ou.edu, E-mail: alexg@nhn.ou.edu, E-mail: ted.vonhippel@erau.edu [Embry-Riddle Aeronautical University, 600 S. Clyde Morris Blvd., Daytona Beach, FL 32114 (United States)

2013-09-01

We identify proper motion objects in the Hubble Ultra Deep Field (UDF) using the optical data from the original UDF program in 2004 and the near-infrared data from the 128 orbit UDF 2012 campaign. There are 12 sources brighter than I = 27 mag that display >3{sigma} significant proper motions. We do not find any proper motion objects fainter than this magnitude limit. Combining optical and near-infrared photometry, we model the spectral energy distribution of each point-source using stellar templates and state-of-the-art white dwarf models. For I {<=} 27 mag, we identify 23 stars with K0-M6 spectral types and two faint blue objects that are clearly old, thick disk white dwarfs. We measure a thick disk white dwarf space density of 0.1-1.7 Multiplication-Sign 10{sup -3} pc{sup -3} from these two objects. There are no halo white dwarfs in the UDF down to I = 27 mag. Combining the Hubble Deep Field North, South, and the UDF data, we do not see any evidence for dark matter in the form of faint halo white dwarfs, and the observed population of white dwarfs can be explained with the standard Galactic models.

DeepCotton: in-field cotton segmentation using deep fully convolutional network

Science.gov (United States)

Li, Yanan; Cao, Zhiguo; Xiao, Yang; Cremers, Armin B.

2017-09-01

Automatic ground-based in-field cotton (IFC) segmentation is a challenging task in precision agriculture, which has not been well addressed. Nearly all the existing methods rely on hand-crafted features. Their limited discriminative power results in unsatisfactory performance. To address this, a coarse-to-fine cotton segmentation method termed "DeepCotton" is proposed. It contains two modules, fully convolutional network (FCN) stream and interference region removal stream. First, FCN is employed to predict initially coarse map in an end-to-end manner. The convolutional networks involved in FCN guarantee powerful feature description capability, simultaneously, the regression analysis ability of neural network assures segmentation accuracy. To our knowledge, we are the first to introduce deep learning to IFC segmentation. Second, our proposed "UP" algorithm composed of unary brightness transformation and pairwise region comparison is used for obtaining interference map, which is executed to refine the coarse map. The experiments on constructed IFC dataset demonstrate that our method outperforms other state-of-the-art approaches, either in different common scenarios or single/multiple plants. More remarkable, the "UP" algorithm greatly improves the property of the coarse result, with the average amplifications of 2.6%, 2.4% on accuracy and 8.1%, 5.5% on intersection over union for common scenarios and multiple plants, separately.

Topography characterization of a deep grating using near-field imaging

DEFF Research Database (Denmark)

Gregersen, Niels; Tromborg, Bjarne; Volkov, Valentyn S.

2006-01-01

Using near-field optical microscopy at the wavelength of 633 nm, we image light intensity distributions at several distances above an ~2-mm deep and a 1-mm-period glass grating illuminated from below under the condition of total internal reflection. The intensity distributions are numerically mod...

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

Science.gov (United States)

Treder, M; Eter, N

2018-04-19

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

(99m)Tc-labeled gastrins of varying peptide chain length: Distinct impact of NEP/ACE-inhibition on stability and tumor uptake in mice.

Science.gov (United States)

Kaloudi, Aikaterini; Nock, Berthold A; Lymperis, Emmanouil; Krenning, Eric P; de Jong, Marion; Maina, Theodosia

2016-06-01

In situ inhibition of neutral endopeptidase (NEP) has been recently shown to impressively increase the bioavailability and tumor uptake of biodegradable gastrin radioligands. Furthermore, angiotensin converting enzyme (ACE) has been previously shown to cleave gastrin analogs in vitro. In the present study, we have assessed the effects induced by single or dual NEP/ACE-inhibition on the pharmacokinetic profile of three (99m)Tc-labeled gastrins of varying peptide chain length: [(99m)Tc]SG6 ([(99m)Tc-N4-Gln(1)]gastrin(1-17)), [(99m)Tc]DG2 ([(99m)Tc-N4-Gly(4),DGlu(5)]gastrin(4-17)) and [(99m)Tc]DG4 ([(99m)Tc-N4-DGlu(10)]gastrin(10-17)). Mouse blood samples were collected 5min after injection of each of [(99m)Tc]SG6/DG2/DG4 together with: a) vehicle, b) the NEP-inhibitor phosphoramidon (PA), c) the ACE-inhibitor lisinopril (Lis), or d) PA plus Lis and were analyzed by RP-HPLC for radiometabolite detection. Biodistribution was studied in SCID mice bearing A431-CCK2R(+/-) xenografts at 4h postinjection (pi). [(99m)Tc]SG6 or [(99m)Tc]DG4 was coinjected with either vehicle or the above described NEP/ACE-inhibitor regimens; for [(99m)Tc]DG2 control and PA animal groups were only included. Treatment of mice with PA induced significant stabilization of (99m)Tc-radiotracers in peripheral blood, while treatment with Lis or Lis+PA affected the stability of des(Glu)5 [(99m)Tc]DG4 only. In line with these findings, PA coinjection led to notable amplification of tumor uptake of radiopeptides compared to controls (PTc]DG4 profited by single Lis (2.06±0.39%ID/g vs 0.99±0.13%ID/g in controls) or combined Lis+PA coinjection (8.91±1.61%ID/g vs 4.89±1.33%ID/g in PA-group). Furthermore, kidney uptake remained favourably low and unaffected by PA and/or Lis coinjection only in the case of [(99m)Tc]DG4 (Tc-radioligands based on different-length gastrins. Truncated [(99m)Tc]DG4 exhibited overall the most attractive profile during combined NEP/ACE-inhibition in mouse models, providing new

Use of Land Use Land Cover Change Mapping Products in Aiding Coastal Habitat Conservation and Restoration Efforts of the Mobile Bay NEP

Science.gov (United States)

Spruce, Joseph P.; Swann, Roberta; Smooth, James

2010-01-01

The Mobile Bay region has undergone significant land use land cover change (LULC) over the last 35 years, much of which is associated with urbanization. These changes have impacted the region s water quality and wildlife habitat availability. In addition, much of the region is low-lying and close to the Gulf, which makes the region vulnerable to hurricanes, climate change (e.g., sea level rise), and sometimes man-made disasters such as the Deepwater Horizon (DWH) oil spill. Land use land cover change information is needed to help coastal zone managers and planners to understand and mitigate the impacts of environmental change on the region. This presentation discusses selective results of a current NASA-funded project in which Landsat data over a 34-year period (1974-2008) is used to produce, validate, refine, and apply land use land cover change products to aid coastal habitat conservation and restoration needs of the Mobile Bay National Estuary Program (MB NEP). The project employed a user defined classification scheme to compute LULC change mapping products for the entire region, which includes the majority of Mobile and Baldwin counties. Additional LULC change products have been computed for select coastal HUC-12 sub-watersheds adjacent to either Mobile Bay or the Gulf of Mexico, as part of the MB NEP watershed profile assessments. This presentation will include results of additional analyses of LULC change for sub-watersheds that are currently high priority areas, as defined by MB NEP. Such priority sub-watersheds include those that are vulnerable to impacts from the DWH oil spill, as well as sub-watersheds undergoing urbanization. Results demonstrating the nature and permanence of LULC change trends for these higher priority sub-watersheds and results characterizing change for the entire 34-year period and at approximate 10-year intervals across this period will also be presented. Future work will include development of value-added coastal habitat quality

Observations of the Hubble Deep Field with the Infrared Space Observatory .4. Association of sources with Hubble Deep Field galaxies

DEFF Research Database (Denmark)

Mann, R.G.; Oliver, S.J.; Serjeant, S.B.G.

1997-01-01

We discuss the identification of sources detected by the Infrared Space Observatory (ISO) at 6.7 and 15 mu m in the Hubble Deep Field (HDF) region. We conservatively associate ISO sources with objects in existing optical and near-infrared HDF catalogues using the likelihood ratio method, confirming...... these results (and, in one case, clarifying them) with independent visual searches, We find 15 ISO sources to be reliably associated with bright [I-814(AB) HDF, and one with an I-814(AB)=19.9 star, while a further 11 are associated with objects in the Hubble Flanking Fields (10 galaxies...... and one star), Amongst optically bright HDF galaxies, ISO tends to detect luminous, star-forming galaxies at fairly high redshift and with disturbed morphologies, in preference to nearby ellipticals....

Clusters, groups, and filaments in the Chandra deep field-south up to redshift 1

International Nuclear Information System (INIS)

Dehghan, S.; Johnston-Hollitt, M.

2014-01-01

We present a comprehensive structure detection analysis of the 0.3 deg 2 area of the MUSYC-ACES field, which covers the Chandra Deep Field-South (CDFS). Using a density-based clustering algorithm on the MUSYC and ACES photometric and spectroscopic catalogs, we find 62 overdense regions up to redshifts of 1, including clusters, groups, and filaments. We also present the detection of a relatively small void of ∼10 Mpc 2 at z ∼ 0.53. All structures are confirmed using the DBSCAN method, including the detection of nine structures previously reported in the literature. We present a catalog of all structures present, including their central position, mean redshift, velocity dispersions, and classification based on their morphological and spectroscopic distributions. In particular, we find 13 galaxy clusters and 6 large groups/small clusters. Comparison of these massive structures with published XMM-Newton imaging (where available) shows that 80% of these structures are associated with diffuse, soft-band (0.4-1 keV) X-ray emission, including 90% of all objects classified as clusters. The presence of soft-band X-ray emission in these massive structures (M 200 ≥ 4.9 × 10 13 M ☉ ) provides a strong independent confirmation of our methodology and classification scheme. In the closest two clusters identified (z < 0.13) high-quality optical imaging from the Deep2c field of the Garching-Bonn Deep Survey reveals the cD galaxies and demonstrates that they sit at the center of the detected X-ray emission. Nearly 60% of the clusters, groups, and filaments are detected in the known enhanced density regions of the CDFS at z ≅ 0.13, 0.52, 0.68, and 0.73. Additionally, all of the clusters, bar the most distant, are found in these overdense redshift regions. Many of the clusters and groups exhibit signs of ongoing formation seen in their velocity distributions, position within the detected cosmic web, and in one case through the presence of tidally disrupted central galaxies

Clusters, groups, and filaments in the Chandra deep field-south up to redshift 1

Energy Technology Data Exchange (ETDEWEB)

Dehghan, S.; Johnston-Hollitt, M., E-mail: siamak.dehghan@vuw.ac.nz [School of Chemical and Physical Sciences, Victoria University of Wellington, P.O. Box 600, Wellington 6140 (New Zealand)

2014-03-01

We present a comprehensive structure detection analysis of the 0.3 deg{sup 2} area of the MUSYC-ACES field, which covers the Chandra Deep Field-South (CDFS). Using a density-based clustering algorithm on the MUSYC and ACES photometric and spectroscopic catalogs, we find 62 overdense regions up to redshifts of 1, including clusters, groups, and filaments. We also present the detection of a relatively small void of ∼10 Mpc{sup 2} at z ∼ 0.53. All structures are confirmed using the DBSCAN method, including the detection of nine structures previously reported in the literature. We present a catalog of all structures present, including their central position, mean redshift, velocity dispersions, and classification based on their morphological and spectroscopic distributions. In particular, we find 13 galaxy clusters and 6 large groups/small clusters. Comparison of these massive structures with published XMM-Newton imaging (where available) shows that 80% of these structures are associated with diffuse, soft-band (0.4-1 keV) X-ray emission, including 90% of all objects classified as clusters. The presence of soft-band X-ray emission in these massive structures (M {sub 200} ≥ 4.9 × 10{sup 13} M {sub ☉}) provides a strong independent confirmation of our methodology and classification scheme. In the closest two clusters identified (z < 0.13) high-quality optical imaging from the Deep2c field of the Garching-Bonn Deep Survey reveals the cD galaxies and demonstrates that they sit at the center of the detected X-ray emission. Nearly 60% of the clusters, groups, and filaments are detected in the known enhanced density regions of the CDFS at z ≅ 0.13, 0.52, 0.68, and 0.73. Additionally, all of the clusters, bar the most distant, are found in these overdense redshift regions. Many of the clusters and groups exhibit signs of ongoing formation seen in their velocity distributions, position within the detected cosmic web, and in one case through the presence of tidally

The final optical identification content of the Einstein deep x-ray field in Pavo.

Science.gov (United States)

Danziger, J. I.; Gilmozzi, R.

1997-07-01

The optical identification of all sources revealed in the final analysis of the Einstein deep field observations in Pavo has been completed to the viable limits accessible to spectroscopy. This work combined with previously published data results in the identification of 16 AGN's with the real possibility of 3 further such identifications, while a further 2 probably are spurious. Another AGN is identified in an IPC exposure just outside the boundary of the four HRI exposures. One elliptical galaxy (or cluster) and one dMe star complete the tally. In a log N-log S plot the point represented by these 16-19 AGN's falls precisely on the extension of the line defined by the EMSS data, and somewhat below the line defined by the more recent deep field ROSAT data. It extends to fainter sensitivities than the previously published work from the Einstein observations of the same field. It is consistent with the more recently published data for Pavo obtained with ROSAT even though this latter reaches a slightly fainter sensitivity. This identification work therefore sets a firm lower limit to the AGN content of the X-ray identifications in Pavo. By virtue of having selected in this survey intrinsically fainter-than-average AGN's it has been possible to show, by combination with data for higher luminosity quasars, that a correlation exists between the luminosities and (B-V) colours extending over a luminosity range of 6 magnitudes. This sequence coincides with the sequence obtained by plotting data for all AGN's in the same redshift range taken from the Veron and Veron catalogue. It is argued that the magnitude of this effect cannot be explained by the translation of various strong emission lines through the band-passes of the relevant filters. It may be explained by the influence of host galaxies.

Andrographolide promotes vincristine-induced SK-NEP-1 tumor cell death via PI3K-AKT-p53 signaling pathway

Directory of Open Access Journals (Sweden)

Zhang M

2016-09-01

Full Text Available Mingsheng Zhang, Enda Xue, Wei Shao Department of Pediatric Surgery, Liaocheng People’s Hospital, Liaocheng, Shandong Province, People’s Republic of China Background: Nephroblastoma (Wilms’ tumor [WT] is the most common malignant renal cancer in children. Although the outcome of WT has significantly improved as a result of the combination of surgery, chemotherapy, and radiotherapy; in some cases WT results in severe complications. Thus, novel strategies that would decrease treatment burden are required. The aim of the current study was to investigate the synergistic antitumor effect of andrographolide (AND in combination with vincristine (VCR on WT cells.Methods: Cell Counting Kit-8 assay was used to investigate the synergistic antiproliferation effect of AND and/or VCR on SK-NEP-1 cells in vitro. Meanwhile, SK-NEP-1 xenografts were used to detect the antitumor effect in vivo. Apoptosis and autophagy were then detected by Annexin V, monodansylcadaverine staining. Finally, the underlying signaling transduction was determined with Western blotting.Results: The combination of AND with VCR significantly suppressed SK-NEP-1 cell proliferation in vitro and inhibited xenograft tumor growth in vivo, compared with AND or VCR treatment alone. In addition, the synergistic antitumor effect of AND on the cells was due to an increased apoptosis, not autophagy. Moreover, PI3K-AKT-p53 signaling pathway was involved in the process of combination treatment, which was confirmed when a selective AKT activator was applied.Conclusion: The combination of AND with VCR has a strong synergistic antitumor effect on WT via PI3K-AKT-p53 signaling pathway, thereby representing a potential treatment for WT in the near future. Keywords: andrographolide, vincristine, p53, drug combination

A diagnostic carbon flux model to monitor the effects of disturbance and interannual variation in climate on regional NEP.

Science.gov (United States)

D.P. Turner; W.D. Ritts; J.M. Styles; Z. Yang; W.B. Cohen; B.E. Law; P.E. Thornton

2006-01-01

Net ecosystem production (NEP) was estimated over a 10.9 x 104 km2 forested region in western Oregon USA for 2 yr (2002-2003) using a combination of remote sensing, distributed meteorological data, and a carbon cycle model (CFLUX). High spatial resolution satellite data (Landsat, 30 m) provided information on land cover and...

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

Directory of Open Access Journals (Sweden)

Mai Lu

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

Deep Vadose Zone-Applied Field Research Initiative Fiscal Year 2011 Annual Report

International Nuclear Information System (INIS)

Wellman, Dawn M.; Johnson, Timothy C.; Smith, Ronald M.; Truex, Michael J.; Matthews, Hope E.

2011-01-01

This annual report describes the background of the Deep Vadose Zone-Applied Field Research Initiative, and some of the programmatic approaches and transformational technologies in groundwater and deep vadose zone remediation developed during fiscal year 2011. The Department of Energy (DOE) Office of Technology Innovation and Development's (OTID) mission is to transform science into viable solutions for environmental cleanup. In 2010, OTID developed the Impact Plan, Science and Technology to Reduce the Life Cycle Cost of Closure to outline the benefits of research and development of the lifecycle cost of cleanup across the DOE complex. This plan outlines OTID's ability to reduce by $50 billion, the $200 billion life-cycle cost in waste processing, groundwater and soil, nuclear materials, and deactivation and decommissioning. The projected life-cycle costs and return on investment are based on actual savings realized from technology innovation, development, and insertion into remedial strategies and schedules at the Fernald, Mound, and Ashtabula sites. To achieve our goals, OTID developed Applied Field Research Initiatives to facilitate and accelerate collaborative development and implementation of new tools and approaches that reduce risk, cost and time for site closure. The primary mission of the Deep Vadose Zone-Applied Field Research Initiative (DVZ-AFRI) is to protect our nation's water resources, keeping them clean and safe for future generations. The DVZ-AFRI was established for the DOE to develop effective, science-based solutions for remediating, characterizing, monitoring, and predicting the behavior and fate of deep vadose zone contamination. Subsurface contaminants include radionuclides, metals, organics, and liquid waste that originated from various sources, including legacy waste from the nation's nuclear weapons complexes. The DVZ-AFRI project team is translating strategy into action by working to solve these complex challenges in a collaborative

Star Formation at z ~ 6: The Hubble Ultra Deep Parallel Fields

Science.gov (United States)

Bouwens, R. J.; Illingworth, G. D.; Thompson, R. I.; Blakeslee, J. P.; Dickinson, M. E.; Broadhurst, T. J.; Eisenstein, D. J.; Fan, X.; Franx, M.; Meurer, G.; van Dokkum, P.

2004-05-01

We report on the i-dropouts detected in two exceptionally deep Advanced Camera for Surveys fields (B435, V606, i775, and z850 with 10σ limits of 28.8, 29.0, 28.5, and 27.8, respectively) taken in parallel with the Ultra Deep Field Near-Infrared Camera and Multi-Object Spectrometer observations. Using an i-z>1.4 cut, we find 30 i-dropouts over 21 arcmin2 down to z850,AB=28.1, or 1.4 i-dropouts arcmin-2, with significant field-to-field variation (as expected from cosmic variance). This extends i-dropout searches some ~0.9 mag further down the luminosity function than was possible in the Great Observatories Origins Deep Survey (GOODS) fields, yielding a ~7 times increase in surface density. An estimate of the size evolution for UV-bright objects is obtained by comparing the composite radial flux profile of the bright i-dropouts (z850,ABdropouts. The best fit is found with a (1+z)-1.57+0.50-0.53 scaling in size (for fixed luminosity), extending lower redshift (1dropouts from both GOODS fields, we make incompleteness estimates and construct a z~6 luminosity function (LF) in the rest-frame continuum UV (~1350 Å) over a 3.5 mag baseline, finding a shape consistent with that found at lower redshift. To evaluate the evolution in the LF from z~3.8, we make comparisons against different scalings of a lower redshift B-dropout sample. Although a strong degeneracy is found between luminosity and density evolution, our best-fit model scales as (1+z)-2.8 in number and (1+z)0.1 in luminosity, suggesting a rest-frame continuum UV luminosity density at z~6 that is just 0.38+0.09-0.07 times that at z~3.8. Our inclusion of the size evolution makes the present estimate lower than previous z~6 estimates. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. These observations are associated with program 9803.

Spontaneous and Widespread Electricity Generation in Natural Deep-Sea Hydrothermal Fields.

Science.gov (United States)

Yamamoto, Masahiro; Nakamura, Ryuhei; Kasaya, Takafumi; Kumagai, Hidenori; Suzuki, Katsuhiko; Takai, Ken

2017-05-15

Deep-sea hydrothermal vents discharge abundant reductive energy into oxidative seawater. Herein, we demonstrated that in situ measurements of redox potentials on the surfaces of active hydrothermal mineral deposits were more negative than the surrounding seawater potential, driving electrical current generation. We also demonstrated that negative potentials in the surface of minerals were widespread in the hydrothermal fields, regardless of the proximity to hydrothermal fluid discharges. Lab experiments verified that the negative potential of the mineral surface was induced by a distant electron transfer from the hydrothermal fluid through the metallic and catalytic properties of minerals. These results indicate that electric current is spontaneously and widely generated in natural mineral deposits in deep-sea hydrothermal fields. Our discovery provides important insights into the microbial communities that are supported by extracellular electron transfer and the prebiotic chemical and metabolic evolution of the ocean hydrothermal systems. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Progress report on understanding AFIS seed coat nep levels in pre-opened slivers on the Advanced Fiber Information System (AFIS)

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The Advanced Fiber Information System (AFIS) is utilized in this segment of the research project to study how seed coat neps are measured. A patent search was conducted, and studied to assist with the understanding of the AFIS measurement of this impurity in raw cotton. The older AFIS 2 is primari...

Deep underground disposal of radioactive wastes: Near field effects

International Nuclear Information System (INIS)

1985-01-01

This report reviews the important near-field effects of the disposal of wastes in deep rock formations. The basic characteristics of waste form, container and package, buffer and backfill materials and potential host-rock types are discussed from the perspective of the performance requirements of the total repository system. Effects of waste emplacement on the separate system components and on the system as a whole are discussed. The effects include interactions between groundwater and brines and the other system components, thermal and thermo-mechanical effects, and chemical and geochemical reactions. Special consideration is given to the radiation field that exists in proximity to the waste containers and also to the coupled effects of different phenomena

Palynofacies reveal fresh terrestrial organic matter inputs in the terminal lobes of the Congo deep-sea fan

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Schnyder, Johann; Stetten, Elsa; Baudin, François; Pruski, Audrey M.; Martinez, Philippe

2017-08-01

The Congo deep-sea fan is directly connected to the Congo River by a unique submarine canyon. The Congo River delivers up to 2×1012gPOC/yr, a part of which is funnelled by the submarine canyon and feeds the deep-sea environments. The more distal part of the Congo deep-sea fan, the terminal lobe area, has a surface of 2500 km2 and is situated up to 800 km offshore at depths of 4750-5000 m. It is a remarkable place to study the fate and distribution of the organic matter transferred from the continent to the deep ocean via turbidity currents. Forty-two samples were analyzed from the terminal lobes, including sites from the active channel, one of its levees and an abandoned distal channel. Samples were collected using multitube cores and push-cores using a Victor 6000 ROV, which surveyed the dense chemosynthetic habitats that locally characterize the terminal lobes. Palynofacies reveal a remarkably well-preserved, dominantly terrestrial particulate organic matter assemblage, that has been transferred from the continent into the deep-sea by turbidity currents. Delicate plant structures, cuticle fragments and plant cellular material is often preserved, highlighting the efficiency of turbidity currents to transfer terrestrial organic matter to the sea-floor, where it is preserved. Moreover, the palynofacies data reveal a general sorting by density or buoyancy of the organic particles, as the turbulent currents escaped the active channel, feeding the levees and the more distal, abandoned channel area. Finally, in addition to aforementioned hydrodynamic factors controlling the organic matter accumulation, a secondary influence of chemosynthetic habitats on organic matter preservation is also apparent. Palynofacies is therefore a useful tool to record the distribution of organic matter in recent and ancient deep-sea fan environments, an important topic for both academic and petroleum studies.

EVOLUTION OF THE SIZES OF GALAXIES OVER 7 < z < 12 REVEALED BY THE 2012 HUBBLE ULTRA DEEP FIELD CAMPAIGN

Energy Technology Data Exchange (ETDEWEB)

Ono, Yoshiaki; Ouchi, Masami [Institute for Cosmic Ray Research, The University of Tokyo, Kashiwa 277-8582 (Japan); Curtis-Lake, Emma; McLure, Ross J.; Dunlop, James S.; Bowler, Rebecca A. A.; Rogers, Alexander B.; Cirasuolo, Michele [Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ (United Kingdom); Schenker, Matthew A.; Ellis, Richard S. [Department of Astrophysics, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States); Robertson, Brant E.; Schneider, Evan; Stark, Daniel P. [Department of Astronomy and Steward Observatory, University of Arizona, Tucson, AZ 85721 (United States); Koekemoer, Anton M. [Space Telescope Science Institute, Baltimore, MD 21218 (United States); Charlot, Stephane [UPMC-CNRS, UMR7095, Institut d' Astrophysique, F-75014 Paris (France); Shimasaku, Kazuhiro [Department of Astronomy, Graduate School of Science, The University of Tokyo, Tokyo 113-0033 (Japan); Furlanetto, Steven R., E-mail: ono@icrr.u-tokyo.ac.jp [Department of Physics and Astronomy, University of California, Los Angeles, CA 90095 (United States)

2013-11-10

We analyze the redshift- and luminosity-dependent sizes of dropout galaxy candidates in the redshift range z ∼ 7-12 using deep images from the 2012 Hubble Ultra Deep Field (UDF12) campaign, which offers two advantages over that used in earlier work. First, we utilize the increased signal-to-noise ratio offered by the UDF12 imaging to provide improved measurements for known galaxies at z ≅ 6.5-8 in the HUDF. Second, because the UDF12 data have allowed the construction of the first robust galaxy sample in the HUDF at z > 8, we have been able to extend the measurement of average galaxy size out to higher redshifts. Restricting our measurements to sources detected at >15σ, we confirm earlier indications that the average half-light radii of z ∼ 7-12 galaxies are extremely small, 0.3-0.4 kpc, comparable to the sizes of giant molecular associations in local star-forming galaxies. We also confirm that there is a clear trend of decreasing half-light radius with increasing redshift, and provide the first evidence that this trend continues beyond z ≅ 8. Modeling the evolution of the average half-light radius as a power law, ∝(1 + z) {sup s}, we obtain a best-fit index of s=-1.30{sup +0.12}{sub -0.14} over z ∼ 4-12. A clear size-luminosity relation is evident in our dropout samples. This relation can be interpreted in terms of a constant surface density of star formation over a range in luminosity of 0.05-1.0 L{sub z=3}. The average star formation surface density in dropout galaxies is 2-3 orders of magnitude lower than that found in extreme starburst galaxies, but is comparable to that seen today in the centers of normal disk galaxies.

EVOLUTION OF THE SIZES OF GALAXIES OVER 7 < z < 12 REVEALED BY THE 2012 HUBBLE ULTRA DEEP FIELD CAMPAIGN

International Nuclear Information System (INIS)

Ono, Yoshiaki; Ouchi, Masami; Curtis-Lake, Emma; McLure, Ross J.; Dunlop, James S.; Bowler, Rebecca A. A.; Rogers, Alexander B.; Cirasuolo, Michele; Schenker, Matthew A.; Ellis, Richard S.; Robertson, Brant E.; Schneider, Evan; Stark, Daniel P.; Koekemoer, Anton M.; Charlot, Stephane; Shimasaku, Kazuhiro; Furlanetto, Steven R.

2013-01-01

We analyze the redshift- and luminosity-dependent sizes of dropout galaxy candidates in the redshift range z ∼ 7-12 using deep images from the 2012 Hubble Ultra Deep Field (UDF12) campaign, which offers two advantages over that used in earlier work. First, we utilize the increased signal-to-noise ratio offered by the UDF12 imaging to provide improved measurements for known galaxies at z ≅ 6.5-8 in the HUDF. Second, because the UDF12 data have allowed the construction of the first robust galaxy sample in the HUDF at z > 8, we have been able to extend the measurement of average galaxy size out to higher redshifts. Restricting our measurements to sources detected at >15σ, we confirm earlier indications that the average half-light radii of z ∼ 7-12 galaxies are extremely small, 0.3-0.4 kpc, comparable to the sizes of giant molecular associations in local star-forming galaxies. We also confirm that there is a clear trend of decreasing half-light radius with increasing redshift, and provide the first evidence that this trend continues beyond z ≅ 8. Modeling the evolution of the average half-light radius as a power law, ∝(1 + z) s , we obtain a best-fit index of s=-1.30 +0.12 -0.14 over z ∼ 4-12. A clear size-luminosity relation is evident in our dropout samples. This relation can be interpreted in terms of a constant surface density of star formation over a range in luminosity of 0.05-1.0 L z=3 . The average star formation surface density in dropout galaxies is 2-3 orders of magnitude lower than that found in extreme starburst galaxies, but is comparable to that seen today in the centers of normal disk galaxies

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

Science.gov (United States)

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

2016-04-01

We are characterizing stress fields in Korea using two types of stress data: earthquake focal mechanism inversions (FMF) and hydraulic fracturing stress measurements (HF). The earthquake focal mechanism inversion data represent stress conditions at 2-20 km depths, whereas the hydraulic fracturing stress measurements, mostly conducted for geotechnical purposes, have been carried out at depths shallower than 1 km. We classified individual stress data based on the World Stress Map quality ranking scheme. A total of 20 FMF data were classified into A-B quality, possibly representing tectonic stress fields. A total of 83 HF data out of compiled 226 data were classified into B-C quality, which we use for shallow stress field characterization. The tectonic stress, revealed from the FMF data, is characterized by a remarkable consistency in its maximum stress (σ1) directions in and around Korea (N79±2° E), indicating a quite uniform deep stress field throughout. On the other hand, the shallow stress field, represented by HF data, exhibits local variations in σ1 directions, possibly due to effects of topography and geologic structures such as faults. Nonetheless, there is a general similarity in σ1 directions between deep and shallow stress fields. To investigate the shallow stress field statistically, we follow 'the mean orientation and wavelength analysis' suggested by Reiter et al. (2014). After the stress pattern analysis, the resulting stress points distribute sporadically over the country, not covering the entire region evenly. In the western part of Korea, the shallow σ1directions are generally uniform with their search radius reaching 100 km, where the average stress direction agrees well with those of the deep tectonic stress. We note two noticeable differences between shallow and deep stresses in the eastern part of Korea. First, the shallow σ1 orientations are markedly non-uniform in the southeastern part of Korea with their search radius less than 25 km

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

Science.gov (United States)

Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

XMM-Newton 13H deep field - I. X-ray sources

Science.gov (United States)

Loaring, N. S.; Dwelly, T.; Page, M. J.; Mason, K.; McHardy, I.; Gunn, K.; Moss, D.; Seymour, N.; Newsam, A. M.; Takata, T.; Sekguchi, K.; Sasseen, T.; Cordova, F.

2005-10-01

We present the results of a deep X-ray survey conducted with XMM-Newton, centred on the UK ROSAT13H deep field area. This region covers 0.18 deg2, and is the first of the two areas covered with XMM-Newton as part of an extensive multiwavelength survey designed to study the nature and evolution of the faint X-ray source population. We have produced detailed Monte Carlo simulations to obtain a quantitative characterization of the source detection procedure and to assess the reliability of the resultant sourcelist. We use the simulations to establish a likelihood threshold, above which we expect less than seven (3 per cent) of our sources to be spurious. We present the final catalogue of 225 sources. Within the central 9 arcmin, 68 per cent of source positions are accurate to 2 arcsec, making optical follow-up relatively straightforward. We construct the N(>S) relation in four energy bands: 0.2-0.5, 0.5-2, 2-5 and 5-10 keV. In all but our highest energy band we find that the source counts can be represented by a double power law with a bright-end slope consistent with the Euclidean case and a break around 10-14yergcm-2s-1. Below this flux, the counts exhibit a flattening. Our source counts reach densities of 700, 1300, 900 and 300 deg-2 at fluxes of 4.1 × 10-16,4.5 × 10-16,1.1 × 10-15 and 5.3 × 10-15ergcm-2s-1 in the 0.2-0.5, 0.5-2, 2-5 and 5-10 keV energy bands, respectively. We have compared our source counts with those in the two Chandra deep fields and Lockman hole, and found our source counts to be amongst the highest of these fields in all energy bands. We resolve >51 per cent (>50 per cent) of the X-ray background emission in the 1-2 keV (2-5 keV) energy bands.

Phylogenetic and genome-wide deep-sequencing analyses of canine parvovirus reveal co-infection with field variants and emergence of a recent recombinant strain.

Directory of Open Access Journals (Sweden)

Ruben Pérez

Full Text Available Canine parvovirus (CPV, a fast-evolving single-stranded DNA virus, comprises three antigenic variants (2a, 2b, and 2c with different frequencies and genetic variability among countries. The contribution of co-infection and recombination to the genetic variability of CPV is far from being fully elucidated. Here we took advantage of a natural CPV population, recently formed by the convergence of divergent CPV-2c and CPV-2a strains, to study co-infection and recombination. Complete sequences of the viral coding region of CPV-2a and CPV-2c strains from 40 samples were generated and analyzed using phylogenetic tools. Two samples showed co-infection and were further analyzed by deep sequencing. The sequence profile of one of the samples revealed the presence of CPV-2c and CPV-2a strains that differed at 29 nucleotides. The other sample included a minor CPV-2a strain (13.3% of the viral population and a major recombinant strain (86.7%. The recombinant strain arose from inter-genotypic recombination between CPV-2c and CPV-2a strains within the VP1/VP2 gene boundary. Our findings highlight the importance of deep-sequencing analysis to provide a better understanding of CPV molecular diversity.

Phylogenetic and Genome-Wide Deep-Sequencing Analyses of Canine Parvovirus Reveal Co-Infection with Field Variants and Emergence of a Recent Recombinant Strain

Science.gov (United States)

Pérez, Ruben; Calleros, Lucía; Marandino, Ana; Sarute, Nicolás; Iraola, Gregorio; Grecco, Sofia; Blanc, Hervé; Vignuzzi, Marco; Isakov, Ofer; Shomron, Noam; Carrau, Lucía; Hernández, Martín; Francia, Lourdes; Sosa, Katia; Tomás, Gonzalo; Panzera, Yanina

2014-01-01

Canine parvovirus (CPV), a fast-evolving single-stranded DNA virus, comprises three antigenic variants (2a, 2b, and 2c) with different frequencies and genetic variability among countries. The contribution of co-infection and recombination to the genetic variability of CPV is far from being fully elucidated. Here we took advantage of a natural CPV population, recently formed by the convergence of divergent CPV-2c and CPV-2a strains, to study co-infection and recombination. Complete sequences of the viral coding region of CPV-2a and CPV-2c strains from 40 samples were generated and analyzed using phylogenetic tools. Two samples showed co-infection and were further analyzed by deep sequencing. The sequence profile of one of the samples revealed the presence of CPV-2c and CPV-2a strains that differed at 29 nucleotides. The other sample included a minor CPV-2a strain (13.3% of the viral population) and a major recombinant strain (86.7%). The recombinant strain arose from inter-genotypic recombination between CPV-2c and CPV-2a strains within the VP1/VP2 gene boundary. Our findings highlight the importance of deep-sequencing analysis to provide a better understanding of CPV molecular diversity. PMID:25365348

Conceptual definition of a 50-100 kWe NEP system for planetary science missions

Science.gov (United States)

Friedlander, Alan

1993-01-01

The Phase 1 objective of this project is to assess the applicability of a common Nuclear Electric Propulsion (NEP) flight system of the 50-100 kWe power class to meet the advanced transportation requirements of a suite of planetary science (robotic) missions, accounting for differences in mission-specific payloads and delivery requirements. The candidate missions are as follows: (1) Comet Nucleus Sample Return; (2) Multiple Mainbelt Asteroid Rendezvous; (3) Jupiter Grand Tour (Galilean satellites and magnetosphere); (4) Uranus Orbiter/Probe (atmospheric entry and landers); (5) Neptune Orbiter/Probe (atmospheric entry and landers); and (6) Pluto-Charon Orbiter/Lander. The discussion is presented in vugraph form.

Application of AMT in detecting deep geological structures in Lejia district of Xiangshan uranium ore field

International Nuclear Information System (INIS)

Duan Shuxin; Liu Hu

2014-01-01

In recent years, exploration in Xiangshan uranium ore field shows that the intersection of faults and the interface of different rock formation and the basement is an important sign of deep ore- prospecting. In order to evaluate deep uranium resource in Lejia district, audio magnetotelluric method (AMT) was undertaken to carry out profile investigation. With that method, we discerned the interface of different rock formation and the basement successfully, and faults in the deep, which provides a good basis for the prediction of deep uranium resource. Drilling results show that AMT method has an obvious advantage in detecting deep geological structures in Xiangshan. (authors)

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

Science.gov (United States)

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

2014-07-03

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

Deep Borehole Field Test Laboratory and Borehole Testing Strategy

Energy Technology Data Exchange (ETDEWEB)

Kuhlman, Kristopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brady, Patrick V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Herrick, Courtney G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jensen, Richard P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gardner, W. Payton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sevougian, S. David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bryan, Charles R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jang, Je-Hun [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Emily R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauer, Stephen J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Daley, Tom [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Freifeld, Barry M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Birkholzer, Jens [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Spane, Frank A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-09-19

Deep Borehole Disposal (DBD) of high-level radioactive wastes has been considered an option for geological isolation for many years (Hess et al. 1957). Recent advances in drilling technology have decreased costs and increased reliability for large-diameter (i.e., ≥50 cm [19.7”]) boreholes to depths of several kilometers (Beswick 2008; Beswick et al. 2014). These advances have therefore also increased the feasibility of the DBD concept (Brady et al. 2009; Cornwall 2015), and the current field test design will demonstrate the DBD concept and these advances. The US Department of Energy (DOE) Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste (DOE 2013) specifically recommended developing a research and development plan for DBD. DOE sought input or expression of interest from States, local communities, individuals, private groups, academia, or any other stakeholders willing to host a Deep Borehole Field Test (DBFT). The DBFT includes drilling two boreholes nominally 200m [656’] apart to approximately 5 km [16,400’] total depth, in a region where crystalline basement is expected to begin at less than 2 km depth [6,560’]. The characterization borehole (CB) is the smaller-diameter borehole (i.e., 21.6 cm [8.5”] diameter at total depth), and will be drilled first. The geologic, hydrogeologic, geochemical, geomechanical and thermal testing will take place in the CB. The field test borehole (FTB) is the larger-diameter borehole (i.e., 43.2 cm [17”] diameter at total depth). Surface handling and borehole emplacement of test package will be demonstrated using the FTB to evaluate engineering feasibility and safety of disposal operations (SNL 2016).

Discovery of z ~ 8 Galaxies in the Hubble Ultra Deep Field from Ultra-Deep WFC3/IR Observations

Science.gov (United States)

Bouwens, R. J.; Illingworth, G. D.; Oesch, P. A.; Stiavelli, M.; van Dokkum, P.; Trenti, M.; Magee, D.; Labbé, I.; Franx, M.; Carollo, C. M.; Gonzalez, V.

2010-02-01

We utilize the newly acquired, ultra-deep WFC3/IR observations over the Hubble Ultra Deep Field (HUDF) to search for star-forming galaxies at z ~ 8-8.5, only 600 million years from recombination, using a Y 105-dropout selection. The new 4.7 arcmin2 WFC3/IR observations reach to ~28.8 AB mag (5σ) in the Y 105 J 125 H 160 bands. These remarkable data reach ~1.5 AB mag deeper than the previous data over the HUDF, and now are an excellent match to the HUDF optical ACS data. For our search criteria, we use a two-color Lyman break selection technique to identify z ~ 8-8.5Y 105-dropouts. We find five likely z ~ 8-8.5 candidates. The sources have H 160-band magnitudes of ~28.3 AB mag and very blue UV-continuum slopes, with a median estimated β of lsim-2.5 (where f λ vprop λβ). This suggests that z ~ 8 galaxies are not only essentially dust free but also may have very young ages or low metallicities. The observed number of Y 105-dropout candidates is smaller than the 20 ± 6 sources expected assuming no evolution from z ~ 6, but is consistent with the five expected extrapolating the Bouwens et al. luminosity function (LF) results to z ~ 8. These results provide evidence that the evolution in the LF seen from z ~ 7 to z ~ 3 continues to z ~ 8. The remarkable improvement in the sensitivity of WFC3/IR has enabled Hubble Space Telescope to cross a threshold, revealing star-forming galaxies at z~ 8-9. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs 11563, 9797.

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.

Science.gov (United States)

Young, Jonathan D; Cai, Chunhui; Lu, Xinghua

2017-10-03

One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep learning is a group of machine learning algorithms that use multiple layers of hidden units to capture hierarchically related, alternative representations of the input data. We hypothesize that this hierarchical structure learned by deep learning will be related to the cellular signaling system. Robust deep learning model selection identified a network architecture that is biologically plausible. Our model selection results indicated that the 1st hidden layer of our deep learning model should contain about 1300 hidden units to most effectively capture the covariance structure of the input data. This agrees with the estimated number of human transcription factors, which is approximately 1400. This result lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene expression data may represent signals related to transcription factor activation. Using the 3rd hidden layer representation of each tumor as learned by our unsupervised deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery of clusters of glioblastoma multiforme with differential survival. One of these clusters contained all of the glioblastoma samples with G-CIMP, a known methylation phenotype driven by the IDH1 mutation and associated with favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations captured a methylation signal without explicitly using methylation data as input. We also found differentially expressed genes and well-known mutations (NF1, IDH1, EGFR) that were uniquely correlated with each of these clusters. Exploring these unique genes and mutations will allow us to

Regional two-dimensional magnetotelluric profile in West Bohemia/Vogtland reveals deep conductive channel into the earthquake swarm region

Science.gov (United States)

Muñoz, Gerard; Weckmann, Ute; Pek, Josef; Kováčiková, Světlana; Klanica, Radek

2018-03-01

The West Bohemia/Vogtland region, characterized by the intersection of the Eger (Ohře) Rift and the Mariánské Lázně fault, is a geodynamically active area exhibiting repeated occurrence of earthquake swarms, massive CO2 emanations and mid Pleistocene volcanism. The Eger Rift is the only known intra-continental region in Europe where such deep seated, active lithospheric processes currently take place. We present an image of electrical resistivity obtained from two-dimensional inversion of magnetotelluric (MT) data acquired along a regional profile crossing the Eger Rift. At the near surface, the Cheb basin and the aquifer feeding the mofette fields of Bublák and Hartoušov have been imaged as part of a region of very low resistivity. The most striking resistivity feature, however, is a deep reaching conductive channel which extends from the surface into the lower crust spatially correlated with the hypocentres of the seismic events of the Nový Kostel Focal Zone. This channel has been interpreted as imaging a pathway from a possible mid-crustal fluid reservoir to the surface. The resistivity model reinforces the relation between the fluid circulation along deep-reaching faults and the generation of the earthquakes. Additionally, a further conductive channel has been revealed to the south of the profile. This other feature could be associated to fossil hydrothermal alteration related to Mýtina and/or Neualbenreuth Maar structures or alternatively could be the signature of a structure associated to the suture between the Saxo-Thuringian and Teplá-Barrandian zones, whose surface expression is located only a few kilometres away.

Conceptual Design and Requirements for Characterization and Field Test Boreholes: Deep Borehole Field Test

Energy Technology Data Exchange (ETDEWEB)

Kuhlman, Kristopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brady, Patrick Vane [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Herrick, Courtney G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jensen, Richard P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rigali, Mark J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sevougian, S. David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Birkholzer, Jens [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Freifeld, Barry M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Daley, Tom [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-09-24

Deep Borehole Disposal (DBD) of high-level radioactive wastes has been considered an option for geological isolation for many years (Hess et al. 1957). Recent advances in drilling technology have decreased costs and increased reliability for large-diameter (i.e., ≥50 cm [19.7”]) boreholes to depths of several kilometers (Beswick 2008; Beswick et al. 2014). These advances have therefore also increased the feasibility of the DBD concept (Brady et al. 2009; Cornwall 2015), and the current field test, introduced herein, is a demonstration of the DBD concept and these advances.

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

Science.gov (United States)

Raongjant, Werasak; Jing, Meng

2013-06-01

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

DISCOVERY OF z ∼ 8 GALAXIES IN THE HUBBLE ULTRA DEEP FIELD FROM ULTRA-DEEP WFC3/IR OBSERVATIONS

International Nuclear Information System (INIS)

Bouwens, R. J.; Illingworth, G. D.; Magee, D.; Gonzalez, V.; Oesch, P. A.; Carollo, C. M.; Stiavelli, M.; Van Dokkum, P.; Trenti, M.; Labbe, I.; Franx, M.

2010-01-01

We utilize the newly acquired, ultra-deep WFC3/IR observations over the Hubble Ultra Deep Field (HUDF) to search for star-forming galaxies at z ∼ 8-8.5, only 600 million years from recombination, using a Y 105 -dropout selection. The new 4.7 arcmin 2 WFC3/IR observations reach to ∼28.8 AB mag (5σ) in the Y 105 J 125 H 160 bands. These remarkable data reach ∼1.5 AB mag deeper than the previous data over the HUDF, and now are an excellent match to the HUDF optical ACS data. For our search criteria, we use a two-color Lyman break selection technique to identify z ∼ 8-8.5Y 105 -dropouts. We find five likely z ∼ 8-8.5 candidates. The sources have H 160 -band magnitudes of ∼28.3 AB mag and very blue UV-continuum slopes, with a median estimated β of ∼ λ ∝ λ β ). This suggests that z ∼ 8 galaxies are not only essentially dust free but also may have very young ages or low metallicities. The observed number of Y 105 -dropout candidates is smaller than the 20 ± 6 sources expected assuming no evolution from z ∼ 6, but is consistent with the five expected extrapolating the Bouwens et al. luminosity function (LF) results to z ∼ 8. These results provide evidence that the evolution in the LF seen from z ∼ 7 to z ∼ 3 continues to z ∼ 8. The remarkable improvement in the sensitivity of WFC3/IR has enabled Hubble Space Telescope to cross a threshold, revealing star-forming galaxies at z∼ 8-9.

Nogo-66 receptor antagonist peptide (NEP1-40) administration promotes functional recovery and axonal growth after lateral funiculus injury in the adult rat

NARCIS (Netherlands)

Cao, Y.; Shumsky, J. S.; Sabol, M. A.; Kushner, R. A.; Strittmatter, S.; Hamers, F. P. T.; Lee, D. H. S.; Rabacchi, S. A.; Murray, M.

2008-01-01

Objective. The myelin protein Nogo inhibits axon regeneration by binding to its receptor (NgR) on axons. Intrathecal delivery of an NgR antagonist (NEP1-40) promotes growth of injured corticospinal axons and recovery of motor function following a dorsal hemisection. The authors used a similar design

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

Science.gov (United States)

Uga, Yusaku; Okuno, Kazutoshi; Yano, Masahiro

2011-05-01

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

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

Science.gov (United States)

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

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

Science.gov (United States)

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

2005-08-01

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

Field development. Concept selection in deep water environment offshore Angola

Energy Technology Data Exchange (ETDEWEB)

Guenot, A.; Berger, J.C.; Limet, N. [TotalFinaElf, la Defense 6, Rosa-Lirio Project Group, 92 - Courbevoie (France)

2002-10-01

The significant oil discoveries made at the end of the 90's in the deep water environment offshore the coast of Angola, has led to a considerable amount of development activities. The first field in production was the turnkey development of the Kuito field on the Block 14 operated by Chevron. More recently the Girassol field has been put successfully in production on the Block 17, operated by TotalFinaElf. Both developments are making use of sub-sea wells connected to a moored dedicated FPSO. On the western side of the Girassol field, several discoveries have been made. They are known as the Rosa Lirio pole, from the names of two of the main channels. Values for water depth are in the same range than on Girassol (1300- 1400 m). A project group has been established in 1999 to evaluate the development of these discoveries. The purpose of this paper is to present the conceptual work which as been carried out, and in particular to show that even if many different concepts have been evaluated, the final choice has been also to make use of sub-sea trees. (authors)

Deep Ly alpha imaging of two z=2.04 GRB host galaxy fields

DEFF Research Database (Denmark)

Fynbo, J.P.U.; Møller, Per; Thomsen, Bente

2002-01-01

We report on the results of deep narrow-band Lyalpha and broad-band U and I imaging of the fields of two Gamma-Ray bursts at redshift z = 2.04 (GRB 000301C and GRB 000926). We find that the host galaxy of GRB 000926 is an extended (more than 2 arcsec), strong Lyalpha emitter with a rest-frame equ......We report on the results of deep narrow-band Lyalpha and broad-band U and I imaging of the fields of two Gamma-Ray bursts at redshift z = 2.04 (GRB 000301C and GRB 000926). We find that the host galaxy of GRB 000926 is an extended (more than 2 arcsec), strong Lyalpha emitter with a rest...... - I colour than the eastern component, suggesting the presence of at least some dust. We do not detect the host galaxy of GRB 000301C in neither Lyalpha emission nor in U and I broad-band images. The strongest limit comes from combining the narrow and U-band imaging where we infer a limit of U...

Galaxy Size Evolution at High Redshift and Surface Brightness Selection Effects: Constraints from the Hubble Ultra Deep Field

Science.gov (United States)

Bouwens, R. J.; Illingworth, G. D.; Blakeslee, J. P.; Broadhurst, T. J.; Franx, M.

2004-08-01

We use the exceptional depth of the Ultra Deep Field (UDF) and UDF-parallel Advanced Camera for Surveys fields to study the sizes of high-redshift (z~2-6) galaxies and address long-standing questions about possible biases in the cosmic star formation rate due to surface brightness dimming. Contrasting B-, V-, and i-dropout samples culled from the deeper data with those obtained from the shallower Great Observatories Origins Deep Survey fields, we demonstrate that the shallower data are essentially complete at bright magnitudes to z~0.4", >~3 kpc) low surface brightness galaxies are rare. A simple comparison of the half-light radii of the Hubble Deep Field-North + Hubble Deep Field-South U-dropouts with B-, V-, and i-dropouts from the UDF shows that the sizes follow a (1+z)-1.05+/-0.21 scaling toward high redshift. A more rigorous measurement compares different scalings of our U-dropout sample with the mean profiles for a set of intermediate-magnitude (26.0dropouts from the UDF. The best fit is found with a (1+z)-0.94+0.19-0.25 size scaling (for fixed luminosity). This result is then verified by repeating this experiment with different size measures, low-redshift samples, and magnitude ranges. Very similar scalings are found for all comparisons. A robust measurement of size evolution is thereby demonstrated for galaxies from z~6 to 2.5 using data from the UDF. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555.

UNUSUAL LONG AND LUMINOUS OPTICAL TRANSIENT IN THE SUBARU DEEP FIELD

International Nuclear Information System (INIS)

Urata, Yuji; Tsai, Patrick P.; Huang, Kuiyun; Morokuma, Tomoki; Motohara, Kentaro; Yasuda, Naoki; Tanaka, Masaomi; Hayashi, Masao; Kashikawa, Nobunari; Ly, Chun; Malkan, Matthew A.

2012-01-01

We present observations of SDF-05M05, an unusual optical transient discovered in the Subaru Deep Field (SDF). The duration of the transient is > ∼ 800 days in the observer frame, and the maximum brightness during observation reached approximately 23 mag in the i' and z' bands. The faint host galaxy is clearly identified in all five optical bands of the deep SDF images. The photometric redshift of the host yields z ∼ 0.6 and the corresponding absolute magnitude at maximum is ∼ – 20. This implies that this event shone with an absolute magnitude brighter than –19 mag for approximately 300 days in the rest frame, which is significantly longer than a typical supernova and ultraluminous supernova. The total radiated energy during our observation was 1 × 10 51 erg. The light curves and color evolution are marginally consistent with some luminous IIn supernovae. We suggest that the transient may be a unique and peculiar supernova at intermediate redshift.

UNUSUAL LONG AND LUMINOUS OPTICAL TRANSIENT IN THE SUBARU DEEP FIELD

Energy Technology Data Exchange (ETDEWEB)

Urata, Yuji; Tsai, Patrick P. [Institute of Astronomy, National Central University, Chung-Li 32054, Taiwan (China); Huang, Kuiyun [Academia Sinica Institute of Astronomy and Astrophysics, Taipei 106, Taiwan (China); Morokuma, Tomoki; Motohara, Kentaro [Institute of Astronomy, Graduate School of Science, University of Tokyo, Mitaka, Tokyo 181-0015 (Japan); Yasuda, Naoki [Institute for the Physics and Mathematics of the Universe, University of Tokyo, Kashiwa 277-8568 (Japan); Tanaka, Masaomi; Hayashi, Masao; Kashikawa, Nobunari [Optical and Infrared Astronomy Division, National Astronomical Observatory, Mitaka, Tokyo 181-8588 (Japan); Ly, Chun [Space Telescope Science Institute, Baltimore, MD (United States); Malkan, Matthew A., E-mail: urata@astro.ncu.edu.tw [Department of Physics and Astronomy, UCLA, Box 951547, Los Angeles, CA (United States)

2012-11-20

We present observations of SDF-05M05, an unusual optical transient discovered in the Subaru Deep Field (SDF). The duration of the transient is > {approx} 800 days in the observer frame, and the maximum brightness during observation reached approximately 23 mag in the i' and z' bands. The faint host galaxy is clearly identified in all five optical bands of the deep SDF images. The photometric redshift of the host yields z {approx} 0.6 and the corresponding absolute magnitude at maximum is {approx} - 20. This implies that this event shone with an absolute magnitude brighter than -19 mag for approximately 300 days in the rest frame, which is significantly longer than a typical supernova and ultraluminous supernova. The total radiated energy during our observation was 1 Multiplication-Sign 10{sup 51} erg. The light curves and color evolution are marginally consistent with some luminous IIn supernovae. We suggest that the transient may be a unique and peculiar supernova at intermediate redshift.

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

Energy Technology Data Exchange (ETDEWEB)

Perry, Frank Vinton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kelley, Richard E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-14

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

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

Science.gov (United States)

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

2017-03-01

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

Deep recurrent conditional random field network for protein secondary prediction

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

2017-01-01

Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

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

Science.gov (United States)

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

2017-11-01

We provide, for the first time, robust observational constraints on the galaxy major merger fraction up to z ≈ 6 using spectroscopic close pair counts. Deep Multi Unit Spectroscopic Explorer (MUSE) observations in the Hubble Ultra Deep Field (HUDF) and Hubble Deep Field South (HDF-S) are used to identify 113 secure close pairs of galaxies among a parent sample of 1801 galaxies spread over a large redshift range (0.2 separation limit of 109.5 M⊙ or the median value of stellar mass computed in each redshift bin. Overall, the major close pair fraction for low-mass and massive galaxies follows the same trend. These new, homogeneous, and robust estimates of the major merger fraction since z ≈ 6 are in good agreement with recent predictions of cosmological numerical simulations. Based on observations made with ESO telescopes at the La Silla-Paranal Observatory under programmes 094.A-0289(B), 095.A-0010(A), 096.A-0045(A) and 096.A-0045(B).

Catwell and Sherdaps for deep-water production fields

Energy Technology Data Exchange (ETDEWEB)

Hopper, H.P.; Rey, R. [Cameron, 34 - Beziers (France)

2000-07-01

The names Catwell and SherDaps are derived from: - Catenary Well - Subsea Horizontal Extended Reach Drilling And Production System. Both systems use the technique of being able to drill a well in deep-water either through a platform catenary carrier pipe or a catenary drilling riser. They also offer, in addition, significant advantages when drilling into shallow reservoirs and the ability to enhance production using platform artificial lift systems or easily serviceable pumps either in the well or at the mud-line. Catwell is a platform system with surface wellheads/trees whereas SherDaps uses a group of subsea wellheads/trees/BOP's that are accessible from one permanent catenary drilling riser. Both systems allow drilling/completing and future well intervention from a central location that otherwise would have required several drilling centres (i.e. platforms or subsea) if the conventional approach was followed. It is envisaged that well targets close to a platform will use well conductors possibly with mud-line wellheads, then Catwell to reach the medium range well targets and SherDaps for long range wells. It is considered that this arrangement would allow a single surface drilling/ production centre to have access to well targets giving a foot print range of up to a 20 km diameter. The total Capex savings on a Deep-water Field Development could be in the region of $200 m on a $1 billion development. Opex will be lower with the ability from the drilling center to quickly access any problem well and rectify any faults, minimising lost production. (authors)

UVUDF: Ultraviolet Imaging of the Hubble Ultra Deep Field with Wide-Field Camera 3

Science.gov (United States)

Teplitz, Harry I.; Rafelski, Marc; Kurczynski, Peter; Bond, Nicholas A.; Grogin, Norman; Koekemoer, Anton M.; Atek, Hakim; Brown, Thomas M.; Coe, Dan; Colbert, James W.; Ferguson, Henry C.; Finkelstein, Steven L.; Gardner, Jonathan P.; Gawiser, Eric; Giavalisco, Mauro; Gronwall, Caryl; Hanish, Daniel J.; Lee, Kyoung-Soo; de Mello, Duilia F.; Ravindranath, Swara; Ryan, Russell E.; Siana, Brian D.; Scarlata, Claudia; Soto, Emmaris; Voyer, Elysse N.; Wolfe, Arthur M.

2013-12-01

We present an overview of a 90 orbit Hubble Space Telescope treasury program to obtain near-ultraviolet imaging of the Hubble Ultra Deep Field using the Wide Field Camera 3 UVIS detector with the F225W, F275W, and F336W filters. This survey is designed to: (1) investigate the episode of peak star formation activity in galaxies at 1 dropouts at redshifts 1.7, 2.1, and 2.7 is largely consistent with the number predicted by published luminosity functions. We also confirm that the image mosaics have sufficient sensitivity and resolution to support the analysis of the evolution of star-forming clumps, reaching 28-29th magnitude depth at 5σ in a 0.''2 radius aperture depending on filter and observing epoch. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are #12534.

Observations of the Hubble Deep Field with the Infrared Space Observatory .1. Data reduction, maps and sky coverage

DEFF Research Database (Denmark)

Serjeant, S.B.G.; Eaton, N.; Oliver, S.J.

1997-01-01

We present deep imaging at 6.7 and 15 mu m from the CAM instrument on the Infrared Space Observatory (ISO), centred on the Hubble Deep Field (HDF). These are the deepest integrations published to date at these wavelengths in any region of sky. We discuss the observational strategy and the data...... reduction. The observed source density appears to approach the CAM confusion limit at 15 mu m, and fluctuations in the 6.7-mu m sky background may be identifiable with similar spatial fluctuations in the HDF galaxy counts. ISO appears to be detecting comparable field galaxy populations to the HDF, and our...

Development costs for a nuclear electric propulsion stage.

Science.gov (United States)

Mondt, J. F.; Prickett, W. Z.

1973-01-01

Development costs are presented for an unmanned nuclear electric propulsion (NEP) stage based upon a liquid metal cooled, in-core thermionic reactor. A total of 120 kWe are delivered to the thrust subsystem which employs mercury ion engines for electric propulsion. This study represents the most recent cost evaluation of the development of a reactor power system for a wide range of nuclear space power applications. These include geocentric, and outer planet and other deep space missions. The development program is described for the total NEP stage, based upon specific development programs for key NEP stage components and subsystems.

FRONTIER FIELDS CLUSTERS: DEEP CHANDRA OBSERVATIONS OF THE COMPLEX MERGER MACS J1149.6+2223

Energy Technology Data Exchange (ETDEWEB)

Ogrean, G. A.; Weeren, R. J. van; Jones, C.; Forman, W.; Andrade-Santos, F.; Murray, S. S.; Nulsen, P.; Bulbul, E.; Kraft, R.; Randall, S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Dawson, W. A. [Lawrence Livermore National Lab, 7000 East Avenue, Livermore, CA 94550 (United States); Golovich, N. [University of California, One Shields Avenue, Davis, CA 95616 (United States); Roediger, E. [Astronomy and Astrophysics Section, Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, Dublin 2 (Ireland); Zitrin, A.; Sayers, J. [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, MC 249-17, Pasadena, CA 91125 (United States); Goulding, A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Umetsu, K. [Institute of Astronomy and Astrophysics, Academia Sinica, P.O. Box 23-141, Taipei 10617, Taiwan (China); Mroczkowski, T. [U.S. Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375 (United States); Bonafede, A. [Hamburger Sternwarte, Universität Hamburg, Gojenbergsweg 112, D-21029 Hamburg (Germany); Churazov, E., E-mail: gogrean@cfa.harvard.edu [Max Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741, Garching (Germany); and others

2016-03-10

The Hubble Space Telescope Frontier Fields cluster MACS J1149.6+2223 is one of the most complex merging clusters, believed to consist of four dark matter halos. We present results from deep (365 ks) Chandra observations of the cluster, which reveal the most distant cold front (z  =  0.544) discovered to date. In the cluster outskirts, we also detect hints of a surface brightness edge that could be the bow shock preceding the cold front. The substructure analysis of the cluster identified several components with large relative radial velocities, thus indicating that at least some collisions occur almost along the line of sight. The inclination of the mergers with respect to the plane of the sky poses significant observational challenges at X-ray wavelengths. MACS J1149.6+2223 possibly hosts a steep-spectrum radio halo. If the steepness of the radio halo is confirmed, then the radio spectrum, combined with the relatively regular ICM morphology, could indicate that MACS J1149.6+2223 is an old merging cluster.

Propulsion Utilizing Laser-Driven Ponderomotive Fields for Deep-Space Missions

International Nuclear Information System (INIS)

Williams, George J.; Gilland, James H.

2009-01-01

The generation of large amplitude electric fields in plasmas by high-power lasers has been studied for several years in the context of high-energy particle acceleration. Fields on the order of GeV/m are generated in the plasma wake of the laser by non-linear ponderomotive forces. The laser fields generate longitudinal and translational electron plasma waves with phase velocities close to the speed of light. These fields and velocities offer the potential to revolutionize spacecraft propulsion, leading to extended deep space robotic probes. Based on these initial calculations, plasma acceleration by means of laser-induced ponderomotive forces appears to offer significant potential for spacecraft propulsion. Relatively high-efficiencies appear possible with proper beam conditioning, resulting in an order of magnitude more thrust than alternative concepts for high I SP (>10 5 s) and elimination of the primary life-limiting erosion phenomena associated with conventional electric propulsion systems. Ponderomotive propulsion readily lends itself to beamed power which might overcome some of the constraints of power-limited propulsion concepts. A preliminary assessment of the impact of these propulsion systems for several promising configurations on mission architectures has been conducted. Emphasizing interstellar and interstellar-precursor applications, performance and technical requirements are identified for a number of missions. The use of in-situ plasma and gas for propellant is evaluated as well.

SEDS: THE SPITZER EXTENDED DEEP SURVEY. SURVEY DESIGN, PHOTOMETRY, AND DEEP IRAC SOURCE COUNTS

International Nuclear Information System (INIS)

Ashby, M. L. N.; Willner, S. P.; Fazio, G. G.; Huang, J.-S.; Hernquist, L.; Hora, J. L.; Arendt, R.; Barmby, P.; Barro, G.; Faber, S.; Guhathakurta, P.; Bell, E. F.; Bouwens, R.; Cattaneo, A.; Croton, D.; Davé, R.; Dunlop, J. S.; Egami, E.; Finlator, K.; Grogin, N. A.

2013-01-01

The Spitzer Extended Deep Survey (SEDS) is a very deep infrared survey within five well-known extragalactic science fields: the UKIDSS Ultra-Deep Survey, the Extended Chandra Deep Field South, COSMOS, the Hubble Deep Field North, and the Extended Groth Strip. SEDS covers a total area of 1.46 deg 2 to a depth of 26 AB mag (3σ) in both of the warm Infrared Array Camera (IRAC) bands at 3.6 and 4.5 μm. Because of its uniform depth of coverage in so many widely-separated fields, SEDS is subject to roughly 25% smaller errors due to cosmic variance than a single-field survey of the same size. SEDS was designed to detect and characterize galaxies from intermediate to high redshifts (z = 2-7) with a built-in means of assessing the impact of cosmic variance on the individual fields. Because the full SEDS depth was accumulated in at least three separate visits to each field, typically with six-month intervals between visits, SEDS also furnishes an opportunity to assess the infrared variability of faint objects. This paper describes the SEDS survey design, processing, and publicly-available data products. Deep IRAC counts for the more than 300,000 galaxies detected by SEDS are consistent with models based on known galaxy populations. Discrete IRAC sources contribute 5.6 ± 1.0 and 4.4 ± 0.8 nW m –2 sr –1 at 3.6 and 4.5 μm to the diffuse cosmic infrared background (CIB). IRAC sources cannot contribute more than half of the total CIB flux estimated from DIRBE data. Barring an unexpected error in the DIRBE flux estimates, half the CIB flux must therefore come from a diffuse component.

Deep learning for computational chemistry

Energy Technology Data Exchange (ETDEWEB)

Goh, Garrett B. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Hodas, Nathan O. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Vishnu, Abhinav [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354

2017-03-08

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. In 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.

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

Science.gov (United States)

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

2009-10-01

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

Photoionization spectroscopy of deep defects responsible for current collapse in nitride-based field effect transistors

International Nuclear Information System (INIS)

Klein, P B; Binari, S C

2003-01-01

This review is concerned with the characterization and identification of the deep centres that cause current collapse in nitride-based field effect transistors. Photoionization spectroscopy is an optical technique that has been developed to probe the characteristics of these defects. Measured spectral dependences provide information on trap depth, lattice coupling and on the location of the defects in the device structure. The spectrum of an individual trap may also be regarded as a 'fingerprint' of the defect, allowing the trap to be followed in response to the variation of external parameters. The basis for these measurements is derived through a modelling procedure that accounts quantitatively for the light-induced drain current increase in the collapsed device. Applying the model to fit the measured variation of drain current increase with light illumination provides an estimate of the concentrations and photoionization cross-sections of the deep defects. The results of photoionization studies of GaN metal-semiconductor field effect transistors and AlGaN/GaN high electron mobility transistors (HEMTs) grown by metal-organic chemical vapour deposition (MOCVD) are presented and the conclusions regarding the nature of the deep traps responsible are discussed. Finally, recent photoionization studies of current collapse induced by short-term (several hours) bias stress in AlGaN/GaN HEMTs are described and analysed for devices grown by both MOCVD and molecular beam epitaxy. (topical review)

Real-life efficacy of pregabalin for the treatment of peripheral neuropathic pain in daily clinical practice in Denmark: the NEP-TUNE study

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Crawford ME

2016-05-01

Full Text Available Michael E Crawford,1 Peter Bo Poulsen,2 Berit Schiøttz-Christensen,3 Andreas Habicht,4 Mette Strand,2 Flemming W Bach5 1Copenhagen City Pain Clinic, Copenhagen K, 2Pfizer Denmark ApS, Ballerup, 3Spine Center Southern Denmark, Lillebælt Hospital, Middelfart, 4Signifikans ApS, Vedbæk, 5Department of Neurology, Aalborg University Hospital, Aalborg, Denmark Objective: The aim of this study was to provide evidence regarding the real-life efficacy of pregabalin in the treatment of peripheral neuropathic pain (NeP in Denmark. Methods: In this prospective, observational, noninterventional study, pregabalin (Lyrica® was prescribed following usual clinical practice. Compared with baseline, the primary study end points after 3 months of observation were changes in 1 the average level of pain during the past week, 2 the worst level of pain during the past week, and 3 the least level of pain during the past week. The Wilcoxon signed-rank test was used to perform paired analyses, and a multivariate regression analysis investigated factors driving change in pain. Results: A total of 86 of the 128 patients included were regarded as efficacy evaluable (those completing 3 months of pregabalin treatment. Patients (59 years were long-time sufferers of peripheral NeP, and 38% of them had comorbidities. The majority had previously been treated with tricyclic antidepressants or gabapentin. The average dose of pregabalin was 81.5 mg/d at baseline and 240 mg/d after 3 months. A clinically and statistically significant improvement of 2.2 points in the average level of pain intensity was found after 3 months. The higher the pain intensity at baseline, the higher was the reduction of the pain score. Positive results were also found for pain-related sleep interference, patients’ global impression of change, quality of life, and work and productivity impairment. Twenty-one patients reported 28 adverse events. Conclusion: This real-life study indicates that for some

Overview of deep learning in medical imaging.

Science.gov (United States)

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

Challenging oil bioremediation at deep-sea hydrostatic pressure

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Alberto Scoma

2016-08-01

Full Text Available The Deepwater Horizon (DWH 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 (biotechnology presently available to combat deep-sea spills. Many questions about the fate of petroleum-hydrocarbons at deep-sea remain unanswered, as much as the main constraints limiting bioremediation under increased hydrostatic pressures and low temperatures. The microbial pathways fueling oil take up 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 and that of hydrocarbons degradation rates was largely overlooked, as 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. 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.

Infrared Faint Radio Sources in the Extended Chandra Deep Field South

Science.gov (United States)

Huynh, Minh T.

2009-01-01

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

Revealing Holobiont Structure and Function of Three Red Sea Deep-Sea Corals

KAUST Repository

Yum, Lauren

2014-12-01

Deep-sea corals have long been regarded as cold-water coral; however a reevaluation of their habitat limitations has been suggested after the discovery of deep-sea coral in the Red Sea where temperatures exceed 20˚C. To gain further insight into the biology of deep-sea corals at these temperatures, the work in this PhD employed a holotranscriptomic approach, looking at coral animal host and bacterial symbiont gene expression in Dendrophyllia sp., Eguchipsammia fistula, and Rhizotrochus sp. sampled from the deep Red Sea. Bacterial community composition was analyzed via amplicon-based 16S surveys and cultured bacterial strains were subjected to bioprospecting in order to gauge the pharmaceutical potential of coralassociated microbes. Coral host transcriptome data suggest that coral can employ mitochondrial hypometabolism, anaerobic glycolysis, and surface cilia to enhance mass transport rates to manage the low oxygen and highly oligotrophic Red Sea waters. In the microbial community associated with these corals, ribokinases and retron-type reverse transcriptases are abundantly expressed. In its first application to deep-sea coral associated microbial communities, 16S-based next-generation sequencing found that a single operational taxonomic unit can comprise the majority of sequence reads and that a large number of low abundance populations are present, which cannot be visualized with first generation sequencing. Bioactivity testing of selected bacterial isolates was surveyed over 100 cytological parameters with high content screening, covering several major organelles and key proteins involved in a variety of signaling cascades. Some of these cytological profiles were similar to those of several reference pharmacologically active compounds, which suggest that the bacteria isolates produce compounds with similar mechanisms of action as the reference compounds. The sum of this work offers several mechanisms by which Red Sea deep-sea corals cope with environmental

A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking.

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Mohammad Javad Shafiee

Full Text Available In this work, we introduce a deep-structured conditional random field (DS-CRF model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.

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

Science.gov (United States)

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

2017-04-01

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

Deep sequencing analysis of the developing mouse brain reveals a novel microRNA

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Piltz Sandra

2011-04-01

Full Text Available Abstract Background MicroRNAs (miRNAs are small non-coding RNAs that can exert multilevel inhibition/repression at a post-transcriptional or protein synthesis level during disease or development. Characterisation of miRNAs in adult mammalian brains by deep sequencing has been reported previously. However, to date, no small RNA profiling of the developing brain has been undertaken using this method. We have performed deep sequencing and small RNA analysis of a developing (E15.5 mouse brain. Results We identified the expression of 294 known miRNAs in the E15.5 developing mouse brain, which were mostly represented by let-7 family and other brain-specific miRNAs such as miR-9 and miR-124. We also discovered 4 putative 22-23 nt miRNAs: mm_br_e15_1181, mm_br_e15_279920, mm_br_e15_96719 and mm_br_e15_294354 each with a 70-76 nt predicted pre-miRNA. We validated the 4 putative miRNAs and further characterised one of them, mm_br_e15_1181, throughout embryogenesis. Mm_br_e15_1181 biogenesis was Dicer1-dependent and was expressed in E3.5 blastocysts and E7 whole embryos. Embryo-wide expression patterns were observed at E9.5 and E11.5 followed by a near complete loss of expression by E13.5, with expression restricted to a specialised layer of cells within the developing and early postnatal brain. Mm_br_e15_1181 was upregulated during neurodifferentiation of P19 teratocarcinoma cells. This novel miRNA has been identified as miR-3099. Conclusions We have generated and analysed the first deep sequencing dataset of small RNA sequences of the developing mouse brain. The analysis revealed a novel miRNA, miR-3099, with potential regulatory effects on early embryogenesis, and involvement in neuronal cell differentiation/function in the brain during late embryonic and early neonatal development.

Deep Vadose Zone Applied Field Research Center: Transformational Technology Development For Environmental Remediation

International Nuclear Information System (INIS)

Wellman, Dawn M.; Triplett, Mark B.; Freshley, Mark D.; Truex, Michael J.; Gephart, Roy E.; Johnson, Timothy C.; Chronister, Glen B.; Gerdes, Kurt D.; Chamberlain, Skip; Marble, Justin; Ramirez, Rosa

2011-01-01

DOE-EM, Office of Groundwater and Soil Remediation and DOE Richland, in collaboration with the Hanford site and Pacific Northwest National Laboratory, have established the Deep Vadose Zone Applied Field Research Center (DVZ-AFRC). The DVZ-AFRC leverages DOE investments in basic science from the Office of Science, applied research from DOE EM Office of Technology Innovation and Development, and site operation (e.g., site contractors [CH2M HILL Plateau Remediation Contractor and Washington River Protection Solutions], DOE-EM RL and ORP) in a collaborative effort to address the complex region of the deep vadose zone. Although the aim, goal, motivation, and contractual obligation of each organization is different, the integration of these activities into the framework of the DVZ-AFRC brings the resources and creativity of many to provide sites with viable alternative remedial strategies to current baseline approaches for persistent contaminants and deep vadose zone contamination. This cooperative strategy removes stove pipes, prevents duplication of efforts, maximizes resources, and facilitates development of the scientific foundation needed to make sound and defensible remedial decisions that will successfully meet the target cleanup goals for one of DOE EM's most intractable problems, in a manner that is acceptable by regulators.

Deep 20-GHz survey of the Chandra Deep Field South and SDSS Stripe 82: source catalogue and spectral properties

Science.gov (United States)

Franzen, Thomas M. O.; Sadler, Elaine M.; Chhetri, Rajan; Ekers, Ronald D.; Mahony, Elizabeth K.; Murphy, Tara; Norris, Ray P.; Waldram, Elizabeth M.; Whittam, Imogen H.

2014-04-01

We present a source catalogue and first results from a deep, blind radio survey carried out at 20 GHz with the Australia Telescope Compact Array, with follow-up observations at 5.5, 9 and 18 GHz. The Australia Telescope 20 GHz (AT20G) deep pilot survey covers a total area of 5 deg2 in the Chandra Deep Field South and in Stripe 82 of the Sloan Digital Sky Survey. We estimate the survey to be 90 per cent complete above 2.5 mJy. Of the 85 sources detected, 55 per cent have steep spectra (α _{1.4}^{20} law spectra between 1.4 and 18 GHz, while the spectral indices of the flat- or inverted-spectrum sources tend to steepen with frequency. Among the 18 inverted-spectrum (α _{1.4}^{20} ≥ 0.0) sources, 10 have clearly defined peaks in their spectra with α _{1.4}^{5.5} > 0.15 and α 9^{18} Cambridge and Tenth Cambridge surveys: there is a shift towards a steeper-spectrum population when going from ˜1 Jy to ˜5 mJy, which is followed by a shift back towards a flatter-spectrum population below ˜5 mJy. The 5-GHz source-count model by Jackson & Wall, which only includes contributions from FRI and FRII sources, and star-forming galaxies, does not reproduce the observed flattening of the flat-spectrum counts below ˜5 mJy. It is therefore possible that another population of sources is contributing to this effect.

Natural gas geological characteristics and great discovery of large gas fields in deep-water area of the western South China Sea

Directory of Open Access Journals (Sweden)

Zhenfeng Wang

2015-12-01

Full Text Available To accelerate the petroleum exploration in deep sea of China, since the period of “the 11th Five-Year Plan”, the sedimentary process, source rock formation and hydrocarbon generation and expulsion process in deep-water area of the Qiongdongnan Basin in the western South China Sea have been studied systematically using the data like large-area 3D seismic survey, logging, drill core (cuttings and geochemical analysis, providing three innovative understandings, i.e. excellent hydrocarbon source conditions, good accumulation conditions, and grouping and zonal distribution of large exploration targets. From the study, the following conclusions are drawn. First, the deep-water area located in the southern and central parts of the Qiongdongnan Basin was formed under the control of such tectonic events as Indosinian–Eurasian Plate collision, Himalayan uplifting and South China Sea expansion, and experienced Paleogene lift and Neogene depression stages. Second, accompanied by lacustrine deposition, faulting activity was violent in Eocene; whereas in Early Oligocene, rift continued to develop under a sedimentary environment of marine–terrestrial transitional facies and littoral-neritic facies. Third, oil generation predominated Eocene lacustrine mudstone and gas generation predominated Lower Oligocene marine–terrestrial transitional facies coal-measure strata compose two sets of major source rocks. Fourth, analysis in respect of thermal evolution level, hydrocarbon generation volume and hydrocarbon generation intensity shows that Ledong, Lingshui, Baodao and Changchang sags belong to potential hydrocarbon-rich kitchens, among which Ledong and Lingshui sags have been proved to have great hydrocarbon generation potential by drilling. Fifth, researches of deep-water sedimentology and hydrocarbon accumulation dynamics reveal that Paleogene and Neogene plays are developed vertically, and favorable hydrocarbon accumulation zones like the Central

The opposing effects of calmodulin, adenosine 5 prime -triphosphate, and pertussis toxin on phorbol ester induced inhibition of atrial natriuretic factor stimulated guanylate cyclase in SK-NEP-1 cells

Energy Technology Data Exchange (ETDEWEB)

Sekiya, M.; Frohlich, E.D.; Cole, F.E. (Alton Ochsner Medical Foundation, New Orleans, LA (USA))

1991-01-01

In the present study, we investigated the effects of calmodulin, adenosine 5{prime}-triphosphate (ATP) and pertussis toxin (PT) on phorbol ester (PMA) induced inhibition of ANF-stimulated cyclic GMP formation in cells from the human renal cell line, SK-NEP-1. PMA inhibited ANF-stimulated guanylate cyclase activity in particulate membranes by about 65%. Calmodulin reversed this inhibition in a dose dependent manner. ATP potentiated Mg++ but not Mn++ supported guanylate cyclase activity. In PMA treated membranes, ATP potentiating effects were abolished. PMA also inhibited ANF-stimulated cGMP accumulation, but pretreatment with PT prevented this PMA inhibition. PT did not affect basal or ANF-stimulated cGMP accumulation. In conclusion, these results demonstrated that PMA inhibited ANF stimulation of particulate guanylate cyclase in opposition to the activating effects of calmodulin or ATP in SK-NEP-1 cells. The protein kinase C inhibitory effects appeared to be mediated via a PT-sensitive G protein.

DEEP KECK u-BAND IMAGING OF THE HUBBLE ULTRA DEEP FIELD: A CATALOG OF z ∼ 3 LYMAN BREAK GALAXIES

International Nuclear Information System (INIS)

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

2009-01-01

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

Numerical Simulation and Experimental Study of Deep Bed Corn Drying Based on Water Potential

Directory of Open Access Journals (Sweden)

Zhe Liu

2015-01-01

Full Text Available The concept and the model of water potential, which were widely used in agricultural field, have been proved to be beneficial in the application of vacuum drying model and have provided a new way to explore the grain drying model since being introduced to grain drying and storage fields. Aiming to overcome the shortcomings of traditional deep bed drying model, for instance, the application range of this method is narrow and such method does not apply to systems of which pressure would be an influential factor such as vacuum drying system in a way combining with water potential drying model. This study established a numerical simulation system of deep bed corn drying process which has been proved to be effective according to the results of numerical simulation and corresponding experimental investigation and has revealed that desorption and adsorption coexist in deep bed drying.

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Geomechanical Considerations for the Deep Borehole Field Test

Science.gov (United States)

Park, B. Y.

2015-12-01

Deep borehole disposal of high-level radioactive waste is under consideration as a potential alternative to shallower mined repositories. The disposal concept consists of drilling a borehole into crystalline basement rocks to a depth of 5 km, emplacement of canisters containing solid waste in the lower 2 km, and plugging and sealing the upper 3 km of the borehole. Crystalline rocks such as granites are particularly attractive for borehole emplacement because of their low permeability and porosity at depth, and high mechanical strength to resist borehole deformation. In addition, high overburden pressures contribute to sealing of some of the fractures that provide transport pathways. We present geomechanical considerations during construction (e.g., borehole breakouts, disturbed rock zone development, and creep closure), relevant to both the smaller-diameter characterization borehole (8.5") and the larger-diameter field test borehole (17"). Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Horizontal-Longitudinal Correlations of Acoustic Field in Deep Water

International Nuclear Information System (INIS)

Li Jun; Li Zheng-Lin; Ren Yun; Li Wen; Zhang Ren-He

2015-01-01

The horizontal-longitudinal correlations of the acoustic field in deep water are investigated based on the experimental data obtained in the South China Sea. It is shown that the horizontal-longitudinal correlation coefficients in the convergence zone are high, and the correlation length is consistent with the convergence zone width, which depends on the receiver depth and range. The horizontal-longitudinal correlation coefficients in the convergence zone also have a division structure for the deeper receiver. The signals from the second part of the convergence zone are still correlated with the reference signal in the first part. The horizontal-longitudinal correlation coefficients in the shadow zone are lower than that in the convergence zone, and the correlation length in the shadow zone is also much shorter than that in the convergence zone. The numerical simulation results by using the normal modes theory are qualitatively consistent with the experimental results. (paper)

Industrial automation in floating production vessels for deep water oil and gas fields

International Nuclear Information System (INIS)

de Garcia, A.L.; Ferrante, A.J.

1990-01-01

The process supervision in offshore platforms was performed in the past through the use of local pneumatic instrumentation, based on relays, semi-graphic panels and button operated control panels. Considering the advanced technology used in the new floating production projects for deep water, it became mandatory to develop supervision systems capable of integrating different control panels, increasing the level of monitorization and reducing the number of operators and control rooms. From the point of view of field integration, a standardized architecture makes the communication between different production platforms and the regional headquarters, where all the equipment and support infrastructure for the computerized network is installed, possible. This test paper describes the characteristics of the initial systems, the main problems observed, the studies performed and the results obtained in relation to the design and implementation of computational systems with open architecture for automation of process control in floating production systems for deep water in Brazil

Sub-mm emission line deep fields: CO and [C II] luminosity functions out to z = 6

NARCIS (Netherlands)

Popping, Gergö; van Kampen, Eelco; Decarli, Roberto; Spaans, Marco; Somerville, Rachel S.; Trager, Scott C.

2016-01-01

Now that Atacama Large (Sub)Millimeter Array is reaching its full capabilities, observations of sub-mm emission line deep fields become feasible. We couple a semi-analytic model of galaxy formation with a radiative transfer code to make predictions for the luminosity function of CO J =1-0 out to CO

Invited talk: Deep Learning Meets Physics

CERN Multimedia

CERN. Geneva

2018-01-01

Deep Learning has emerged as one of the most successful fields of machine learning and artificial intelligence with overwhelming success in industrial speech, text and vision benchmarks. Consequently it evolved into the central field of research for IT giants like Google, facebook, Microsoft, Baidu, and Amazon. Deep Learning is founded on novel neural network techniques, the recent availability of very fast computers, and massive data sets. In its core, Deep Learning discovers multiple levels of abstract representations of the input. The main obstacle to learning deep neural networks is the vanishing gradient problem. The vanishing gradient impedes credit assignment to the first layers of a deep network or to early elements of a sequence, therefore limits model selection. Major advances in Deep Learning can be related to avoiding the vanishing gradient like stacking, ReLUs, residual networks, highway networks, and LSTM. For Deep Learning, we suggested self-normalizing neural networks (SNNs) which automatica...

A novel approach reveals high zooplankton standing stock deep in the sea

Directory of Open Access Journals (Sweden)

A. Vereshchaka

2016-11-01

Full Text Available In a changing ocean there is a critical need to understand global biogeochemical cycling, particularly regarding carbon. We have made strides in understanding upper ocean dynamics, but the deep ocean interior (> 1000 m is still largely unknown, despite representing the overwhelming majority of Earth's biosphere. Here we present a method for estimating deep-pelagic zooplankton biomass on an ocean-basin scale. We have made several new discoveries about the Atlantic, which likely apply to the world ocean. First, multivariate analysis showed that depth and Chl were the basic factors affecting the wet biomass of the main plankton groups. Wet biomass of all major groups was significantly correlated with Chl. Second, zooplankton biomass in the upper bathypelagic domain is higher than expected. Third, the majority of this biomass comprises macroplanktonic shrimps, which have been historically underestimated. These findings, coupled with recent findings of increased global deep-pelagic fish biomass, suggest that the contribution of the deep-ocean pelagic fauna for biogeochemical cycles may be more important than previously thought.

Physical and Numerical Modeling of the Stability of Deep Caverns in Tahe Oil Field in China

Directory of Open Access Journals (Sweden)

Chao Wang

2017-06-01

Full Text Available Cave collapses emerge during the process of oil reservoir development, seriously affecting oil production. To reveal the collapse and failure mechanism of the carbonate cavern with a buried depth of 5600 m in Tahe Oil Field, using a self-developed ultra-high pressure model test system with the intelligent numerical control function, the model simulation material of carbonate rocks developed to carry out the 3D geo-mechanical model test. The model test and numerical results indicate that: (1 collapse and failure mechanism of the deep-buried caves mainly involve the failure mode of tensile shear. The rupture plane on the side wall is approximately parallel to the direction of maximum principal compressive stress. The V-type tension and split rupture plane then emerges. (2 In the process of forming holes in the model caverns, micro cracks are generated at the foot of the left and right side walls of the caverns, and the roof panels are constantly moving downward. The shorter the distance to the cave wall, the severer the destructiveness of the surrounding rocks will be. (3 The displacement of the top of the model cavern is relatively large and uniform, indicating that the cave roof moves downward as a whole. The area of the cavity suffering damage is 2.3 times as large as the cave span. The research results in this paper lay a solid test basis for revealing the cave collapse and failure mechanism in super depth.

Bridging the gap between the deep Earth and lithospheric gravity field

Science.gov (United States)

Root, B. C.; Ebbing, J.; Martinec, Z.; van der Wal, W.

2017-12-01

Global gravity field data obtained by dedicated satellite missions can be used to study the density distribution of the lithosphere. The gravitational signal from the deep Earth is usually removed by high-pass filtering of the data. However, this will also remove any long-wavelength signal of the lithosphere. Furthermore, it is still unclear what value for the truncation limit is best suited. An alternative is to forward model the deep situated mass anomalies and subtract the gravitational signal from the observed data. This requires knowledge of the mantle mass anomalies, dynamic topography, and CMB topography. Global tomography provides the VS distribution in the mantle, which is related to the density distribution in the mantle. There are difficulties in constructing a density model from this data. Tomography relies on regularisation which smoothens the mantle anomalies. Also, the VS anomalies need to be converted to density anomalies with uncertain conversion factors. We study the observed reduction in magnitude of the density anomalies due to the regularisation of the global tomography models. The reduced magnitude of the anomalies cannot be recovered by increasing the conversion factor from VS-to-density transformation. The reduction of the tomographic results seems to resemble the effect of a spatial Gaussian filter. By determining the spectral difference between tomographic and gravimetric models a reverse filter can be constructed to reproduce correct density variations in the complete mantle. The long-wavelengths of the global tomography models are less affected by the regularisation and can fix the value of the conversion factor. However, the low degree gravity signals are also dominated by the D" region. Therefore, different approaches are used to determine the effect of this region on the gravity field. The density anomalies in the mantle, as well as the effect of CMB undulations, are forward modelled into their gravitational potential field, such that

Lyman Break Galaxies in the Hubble Ultra Deep Field through Deep U-Band Imaging

Science.gov (United States)

Rafelski, Marc; Wolfe, A. M.; Cooke, J.; Chen, H. W.; Armandroff, T. E.; Wirth, G. D.

2009-12-01

We introduce an extremely deep U-band image taken of the Hubble Ultra Deep Field (HUDF), with a one sigma depth of 30.7 mag arcsec-2 and a detection limiting magnitude of 28 mag arcsec-2. The observations were carried out on the Keck I telescope using the LRIS-B detector. The U-band image substantially improves the accuracy of photometric redshift measurements of faint galaxies in the HUDF at z=[2.5,3.5]. The U-band for these galaxies is attenuated by lyman limit absorption, allowing for more reliable selections of candidate Lyman Break Galaxies (LBGs) than from photometric redshifts without U-band. We present a reliable sample of 300 LBGs at z=[2.5,3.5] in the HUDF. Accurate redshifts of faint galaxies at z=[2.5,3.5] are needed to obtain empirical constraints on the star formation efficiency of neutral gas at high redshift. Wolfe & Chen (2006) showed that the star formation rate (SFR) density in damped Ly-alpha absorption systems (DLAs) at z=[2.5,3.5] is significantly lower than predicted by the Kennicutt-Schmidt law for nearby galaxies. One caveat to this result that we wish to test is whether LBGs are embedded in DLAs. If in-situ star formation is occurring in DLAs, we would see it as extended low surface brightness emission around LBGs. We shall use the more accurate photometric redshifts to create a sample of LBGs around which we will look for extended emission in the more sensitive and higher resolution HUDF images. The absence of extended emission would put limits on the SFR density of DLAs associated with LBGs at high redshift. On the other hand, detection of faint emission on scales large compared to the bright LBG cores would indicate the presence of in situ star formation in those DLAs. Such gas would presumably fuel the higher star formation rates present in the LBG cores.

SuperSpec, The On-Chip Spectrometer: Improved NEP and Antenna Performance

Science.gov (United States)

Wheeler, Jordan; Hailey-Dunsheath, S.; Shirokoff, E.; Barry, P. S.; Bradford, C. M.; Chapman, S.; Che, G.; Doyle, S.; Glenn, J.; Gordon, S.; Hollister, M.; Kovács, A.; LeDuc, H. G.; Mauskopf, P.; McGeehan, R.; McKenney, C.; Reck, T.; Redford, J.; Ross, C.; Shiu, C.; Tucker, C.; Turner, J.; Walker, S.; Zmuidzinas, J.

2018-05-01

SuperSpec is a new technology for mm and sub-mm spectroscopy. It is an on-chip spectrometer being developed for multi-object, moderate-resolution (R˜ 300 ), large bandwidth survey spectroscopy of high-redshift galaxies for the 1 mm atmospheric window. This band accesses the CO ladder in the redshift range of z = 0-4 and the [CII] 158 μm line from redshift z = 5-9. SuperSpec employs a novel architecture in which detectors are coupled to a series of resonant filters along a single microwave feedline instead of using dispersive optics. This construction allows for the creation of a full spectrometer occupying only ˜ 10 cm^2 of silicon, a reduction in size of several orders of magnitude when compared to standard grating spectrometers. This small profile enables the production of future multi-beam spectroscopic instruments envisioned for the millimeter band to measure the redshifts of dusty galaxies efficiently. The SuperSpec collaboration is currently pushing toward the deployment of a SuperSpec demonstration instrument in fall of 2018. The progress with the latest SuperSpec prototype devices is presented; reporting increased responsivity via a reduced inductor volume (2.6 μm^3 ) and the incorporation of a new broadband antenna. A detector NEP of 3-4 × 10^{-18} W/Hz^{0.5} is obtained, sufficient for background-limited observation on mountaintop sites. In addition, beam maps and efficiency measurements of a new wide-band dual bow-tie slot antenna are shown.

Thermophilic hydrogen-producing bacteria inhabiting deep-sea hydrothermal environments represented by Caloranaerobacter.

Science.gov (United States)

Jiang, Lijing; Xu, Hongxiu; Zeng, Xiang; Wu, Xiaobing; Long, Minnan; Shao, Zongze

2015-11-01

Hydrogen is an important energy source for deep-sea hydrothermal vent ecosystems. However, little is known about microbes and their role in hydrogen turnover in the environment. In this study, the diversity and physiological characteristics of fermentative hydrogen-producing microbes from deep-sea hydrothermal vent fields were described for the first time. Seven enrichments were obtained from hydrothermal vent sulfides collected from the Southwest Indian Ocean, East Pacific and South Atlantic. 16S rRNA gene analysis revealed that members of the Caloranaerobacter genus were the dominant component in these enrichments. Subsequently, three thermophilic hydrogen producers, strains H363, H53214 and DY22619, were isolated. They were phylogenetically related to species of the genus Caloranaerobacter. The H2 yields of strains H363, H53214, DY22619 and MV107, which was the type species of genus Caloranaerobacter, were 0.11, 1.21, 3.13 and 2.85 mol H2/mol glucose, respectively. Determination of the main soluble metabolites revealed that strains H363, H53214 and MV107 performed heterolactic fermentations, while strain DY22619 performed butyric acid fermentation, indicating distinct fermentation patterns among members of the genus. Finally, a diversity of forms of [FeFe]-hydrogenase with different modular structures was revealed based on draft genomic data of Caloranaerobacter strains. This highlights the complexity of hydrogen metabolism in Caloranaerobacter, reflecting adaptations to environmental conditions in hydrothermal vent systems. Collectively, results suggested that Caloranaerobacter species might be ubiquitous and play a role in biological hydrogen generation in deep-sea hydrothermal vent fields. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Observations of the Hubble Deep Field with the Infrared Space Observatory .2. Source detection and photometry

DEFF Research Database (Denmark)

Goldschmidt, P.; Oliver, S.J.; Serjeant, S.B.G.

1997-01-01

We present positions and fluxes of point sources found in the Infrared Space Observatory (ISO) images of the Hubble Deep Field (HDF) at 6.7 and 15 mu m. We have constructed algorithmically selected 'complete' flux-limited samples of 19 sources in the 15-mu m image, and seven sources in the 6.7-mu m...

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

Science.gov (United States)

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.

An Advanced Light Weight Recuperator for Space Power Systems, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Nuclear Electric Propulsion (NEP) technology holds great promise for power and propulsion demands of NASA current and future deep space explorations. Closed Brayton...

Deep Learning Microscopy

KAUST Repository

Rivenson, Yair

2017-05-12

We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably better resolution, matching the performance of higher numerical aperture lenses, also significantly surpassing their limited field-of-view and depth-of-field. These results are transformative for various fields that use microscopy tools, including e.g., life sciences, where optical microscopy is considered as one of the most widely used and deployed techniques. Beyond such applications, our presented approach is broadly applicable to other imaging modalities, also spanning different parts of the electromagnetic spectrum, and can be used to design computational imagers that get better and better as they continue to image specimen and establish new transformations among different modes of imaging.

Uranium facilitated transport by water-dispersible colloids in field and soil columns

International Nuclear Information System (INIS)

Crancon, P.; Pili, E.; Charlet, L.

2010-01-01

The transport of uranium through a sandy podzolic soil has been investigated in the field and in column experiments. Field monitoring, numerous years after surface contamination by depleted uranium deposits, revealed a 20 cm deep uranium migration in soil. Uranium retention in soil is controlled by the 238 U initially present in the soil column and 233 U brought by input solution are desorbed. The mobilization process observed experimentally after a drop of ionic strength may account for a rapid uranium migration in the field after a rainfall event, and for the significant uranium concentrations found in deep soil horizons and in groundwater, 1 km downstream from the pollution source.

[Class Climate, Academic Well-Being and Self-Rated Health Among School Children in Germany: Findings of the National Educational Panel Study (NEPS)].

Science.gov (United States)

Rathmann, Katharina; Herke, Max; Hurrelmann, Klaus; Richter, Matthias

2018-04-01

The aim of this study was to examine the associations between features of class climate and school wellbeing, based on self-rated health and reports of absence from school due to illness among adolescents in secondary schools, by using data from the German National Educational Panel Study (NEPS). Data was obtained from the National Educational Panel Study (NEPS). The sample includes (n=7,348) seventh grade students in regular schools (Starting Cohort 3, Wave 3, 2012). Measures of class climate comprise indicators about demands, control and orientation, autonomy and interaction among students as well as teaching quality in German language class. School wellbeing was measured by satisfaction with school and helplessness in main school subjects. Bivariate and logistic multilevel logistic regression techniques are applied, by controlling for student age, gender and school type attended. Multilevel results showed that particularly among students with higher school satisfaction, there was a higher likelihood of self-rated health and less school absence due to illness. In contrast, perceived helplessness in major subjects and learning orientation were negatively associated with both outcomes. Further, students attending low track schools had a higher risk of school absence than students in high track schools. The results highlight the fact that particularly students' school wellbeing in terms of school satisfaction and perceived helplessness in the subjects German and mathematics are associated with self-rated poorer health and school absence due to illness. Therefore, health promotion initiatives should particularly focus on students' school wellbeing as well as on students attending low track schools. © Georg Thieme Verlag KG Stuttgart · New York.

Worldwide Analysis of Sedimentary DNA Reveals Major Gaps in Taxonomic Knowledge of Deep-Sea Benthos

DEFF Research Database (Denmark)

Sinniger, Frédéric; Pawlowski, Jan; Harii, Saki

2016-01-01

in 39 deep-sea sediment samples from bathyal and abyssal depths worldwide. The eDNA dataset was dominated by meiobenthic taxa and we identified all animal phyla commonly found in the deep-sea benthos; yet, the diversity within these phyla remains largely unknown. The large numbers of taxonomically...... for pure and applied deep-sea environmental research but also emphasizes the necessity to integrate such new approaches with traditional morphology-based examination of deep-sea organisms....

Efficient collective swimming by harnessing vortices through deep reinforcement learning.

Science.gov (United States)

Verma, Siddhartha; Novati, Guido; Koumoutsakos, Petros

2018-06-05

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

Deep Learning and Its Applications in Biomedicine.

Science.gov (United States)

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.

STAR FORMATION IN THE CHANDRA DEEP FIELD SOUTH: OBSERVATIONS CONFRONT SIMULATIONS

International Nuclear Information System (INIS)

Damen, Maaike; Franx, Marijn; Foerster Schreiber, Natascha M.; Labbe, Ivo; Toft, Sune; Van Dokkum, Pieter G.; Wuyts, Stijn

2009-01-01

We investigate the star formation history of the universe using FIREWORKS, a multiwavelength survey of the Chandra Deep Field South. We study the evolution of the specific star formation rate (sSFR) with redshift in different mass bins from z = 0 to z ∼ 3. We find that the sSFR increases with redshift for all masses. The logarithmic increase of the sSFR with redshift is nearly independent of mass, but this cannot yet be verified at the lowest-mass bins at z>0.8, due to incompleteness. We convert the sSFRs to a dimensionless growth rate to facilitate a comparison with a semianalytic galaxy formation model that was implemented on the Millennium Simulation. The model predicts that the growth rates and sSFRs increase similarly with redshift for all masses, consistent with the observations. However, we find that for all masses, the inferred observed growth rates increase more rapidly with redshift than the model predictions. We discuss several possible causes for this discrepancy, ranging from field-to-field variance, conversions to SFR, and shape of the initial mass function. We find that none of these can solve the discrepancy completely. We conclude that the models need to be adapted to produce the steep increase in growth rate between redshift z = 0 and z = 1.

Deep Learning in Drug Discovery.

Science.gov (United States)

Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert

2016-01-01

Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

Koo, David C.; Kron, Richard G.

1987-01-01

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

Biogeography of Persephonella in deep-sea hydrothermal vents of the Western Pacific.

Directory of Open Access Journals (Sweden)

Sayaka eMino

2013-04-01

Full Text Available Deep-sea hydrothermal vent fields are areas on the seafloor with high biological productivity fueled by microbial chemosynthesis. Members of the Aquificales genus Persephonella are obligately chemosynthetic bacteria, and appear to be key players in carbon, sulfur, and nitrogen cycles in high temperature habitats at deep-sea vents. Although this group of bacteria has cosmopolitan distribution in deep-sea hydrothermal ecosystem around the world, little is known about their population structure such as intraspecific genomic diversity, distribution pattern, and phenotypic diversity. We developed the multi-locus sequence analysis (MLSA scheme for their genomic characterization. Sequence variation was determined in five housekeeping genes and one functional gene of 36 P. hydrogeniphila strains originated from the Okinawa Trough and the South Mariana Trough. Although the strains share > 98.7% similarities in 16S rRNA gene sequences, MLSA revealed 35 different sequence types, indicating their extensive genomic diversity. A phylogenetic tree inferred from all concatenated gene sequences revealed the clustering of isolates according to the geographic origin. In addition, the phenotypic clustering pattern inferred from whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS analysis can be correlated to their MLSA clustering pattern. This study represents the first MLSA combined with phenotypic analysis indicative of allopatric speciation of deep-sea hydrothermal vent bacteria.

Adrenal Chromaffin Cells Exposed to 5-ns Pulses Require Higher Electric Fields to Porate Intracellular Membranes than the Plasma Membrane: An Experimental and Modeling Study.

Science.gov (United States)

Zaklit, Josette; Craviso, Gale L; Leblanc, Normand; Yang, Lisha; Vernier, P Thomas; Chatterjee, Indira

2017-10-01

Nanosecond-duration electric pulses (NEPs) can permeabilize the endoplasmic reticulum (ER), causing release of Ca 2+ into the cytoplasm. This study used experimentation coupled with numerical modeling to understand the lack of Ca 2+ mobilization from Ca 2+ -storing organelles in catecholamine-secreting adrenal chromaffin cells exposed to 5-ns pulses. Fluorescence imaging determined a threshold electric (E) field of 8 MV/m for mobilizing intracellular Ca 2+ whereas whole-cell recordings of membrane conductance determined a threshold E-field of 3 MV/m for causing plasma membrane permeabilization. In contrast, a 2D numerical model of a chromaffin cell, which was constructed with internal structures representing a nucleus, mitochondrion, ER, and secretory granule, predicted that exposing the cell to the same 5-ns pulse electroporated the plasma and ER membranes at the same E-field amplitude, 3-4 MV/m. Agreement of the numerical simulations with the experimental results was obtained only when the ER interior conductivity was 30-fold lower than that of the cytoplasm and the ER membrane permittivity was twice that of the plasma membrane. A more realistic intracellular geometry for chromaffin cells in which structures representing multiple secretory granules and an ER showed slight differences in the thresholds necessary to porate the membranes of the secretory granules. We conclude that more sophisticated cell models together with knowledge of accurate dielectric properties are needed to understand the effects of NEPs on intracellular membranes in chromaffin cells, information that will be important for elucidating how NEPs porate organelle membranes in other cell types having a similarly complex cytoplasmic ultrastructure.

Ultradeep Near-Infrared ISAAC Observations of the Hubble Deep Field South: Observations, Reduction, Multicolor Catalog, and Photometric Redshifts

Science.gov (United States)

Labbé, Ivo; Franx, Marijn; Rudnick, Gregory; Schreiber, Natascha M. Förster; Rix, Hans-Walter; Moorwood, Alan; van Dokkum, Pieter G.; van der Werf, Paul; Röttgering, Huub; van Starkenburg, Lottie; van der Wel, Arjen; Kuijken, Konrad; Daddi, Emanuele

2003-03-01

We present deep near-infrared (NIR) Js-, H-, and Ks-band ISAAC imaging of the Wide Field Planetary Camera 2 (WFPC2) field of the Hubble Deep Field South (HDF-S). The 2.5‧×2.5‧ high Galactic latitude field was observed with the Very Large Telescope under the best seeing conditions, with integration times amounting to 33.6 hr in Js, 32.3 hr in H, and 35.6 hr in Ks. We reach total AB magnitudes for point sources of 26.8, 26.2, and 26.2, respectively (3 σ), which make it the deepest ground-based NIR observation to date and the deepest Ks-band data in any field. The effective seeing of the co-added images is ~0.45" in Js, ~0.48" in H, and ~0.46" in Ks. Using published WFPC2 optical data, we constructed a Ks-limited multicolor catalog containing 833 sources down to Ktots,AB2.3 (in Johnson magnitudes). Because they are extremely faint in the observed optical, they would be missed by ultraviolet-optical selection techniques, such as the U-dropout method. Based on service mode observations collected at the European Southern Observatory, Paranal, Chile (ESO Program 164.O-0612). Also based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS 5-26555.

A Study on the Improvement Effect and Field Applicability of the Deep Soft Ground by Ground Heating Method

Directory of Open Access Journals (Sweden)

Mincheol Park

2018-05-01

Full Text Available The soft ground in coastal areas should be treated when it needs to be used for the sustainably developed of urban or industrial complex constructions. The ground heating method for soft ground improvement was applied in Eastern Europe in the 1960s, but it was not widely used due to economic and environmental problems. The author developed a device for improving soft ground using an electric heating pipe. This paper investigates the improvement effect and field application of deep soft ground by the ground heating method using the electric heating pipe. Ground heating increases the temperature of the deep soft ground and increases the tip resistance of the static electronic piezo-cone penetration test. Additionally, the pressure of the pore water decreases because the pore water is evaporated due to the ground heating. As a result of the experiment, it was verified that there was an improvement in the effect of deep soft ground by the ground heating method. With ground heating for 96 h, the tip resistance was increased by 61% at a point 0.35 m horizontally away from the electric heat pipe, 22% at 0.97 m, and 2% at 1.31 m. As a result of the field test, it was found that there were no problems in the power supply of the diesel generator and the control panel. It was easy to install the electric heating pipes in the deep soft ground. However, due to boring, the ground was disturbed and water vapor was discharged through this gap. To minimize the discharge of water vapor, it is necessary to drive the electric heating pipe.

Irreversible magnetization deep in the vortex-liquid state of a 2D superconductor at high magnetic fields

International Nuclear Information System (INIS)

Maniv, T; Zhuravlev, V; Wosnitza, J; Hagel, J

2004-01-01

The remarkable phenomenon of weak magnetization hysteresis loops, observed recently deep in the vortex-liquid state of a nearly two-dimensional (2D) superconductor at low temperatures and high magnetic fields, is shown to reflect the existence of an unusual vortex-liquid state, consisting of collectively pinned crystallites of easily sliding vortex chains. (letter to the editor)

Historical and projected carbon balance of mature black spruce ecosystems across north america: The role of carbon-nitrogen interactions

Science.gov (United States)

Clein, Joy S.; McGuire, A.D.; Zhang, X.; Kicklighter, D.W.; Melillo, J.M.; Wofsy, S.C.; Jarvis, P.G.; Massheder, J.M.

2002-01-01

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO2 in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C-N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R2= 0.77, 0.88 for GPP and RESP; uncoupled: R2 = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R2 = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and

Status report on nuclear electric propulsion systems

Science.gov (United States)

Stearns, J. W.

1975-01-01

Progress in nuclear electric propulsion (NEP) systems for a multipayload multimission vehicle needed in both deep-space missions and a variety of geocentric missions is reviewed. The space system power level is a function of the initial launch vehicle mass, but developments in out-of-core nuclear thermionic direct conversion have broadened design options. Cost, design, and performance parameters are compared for reusable chemical space tugs and NEP reusable space tugs. Improvements in heat pipes, ion engines, and magnetoplasmadynamic arc jet thrust subsystems are discussed.

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

Science.gov (United States)

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

2017-11-01

We have conducted a two-layered spectroscopic survey (1' × 1' ultra deep and 3' × 3' deep regions) in the Hubble Ultra Deep Field (HUDF) with the Multi Unit Spectroscopic Explorer (MUSE). The combination of a large field of view, high sensitivity, and wide wavelength coverage provides an order of magnitude improvement in spectroscopically confirmed redshifts in the HUDF; i.e., 1206 secure spectroscopic redshifts for Hubble Space Telescope (HST) continuum selected objects, which corresponds to 15% of the total (7904). The redshift distribution extends well beyond z> 3 and to HST/F775W magnitudes as faint as ≈ 30 mag (AB, 1σ). In addition, 132 secure redshifts were obtained for sources with no HST counterparts that were discovered in the MUSE data cubes by a blind search for emission-line features. In total, we present 1338 high quality redshifts, which is a factor of eight increase compared with the previously known spectroscopic redshifts in the same field. We assessed redshifts mainly with the spectral features [O II] at zcolor selection (dropout) diagrams of high-z galaxies. The selection condition for F336W dropouts successfully captures ≈ 80% of the targeted z 2.7 galaxies. However, for higher redshift selections (F435W, F606W, and F775W dropouts), the success rates decrease to ≈ 20-40%. We empirically redefine the selection boundaries to make an attempt to improve them to ≈ 60%. The revised boundaries allow bluer colors that capture Lyα emitters with high Lyα equivalent widths falling in the broadbands used for the color-color selection. Along with this paper, we release the redshift and line flux catalog. Based on observations made with ESO telescopes at the La Silla Paranal Observatory under program IDs 094.A-0289(B), 095.A-0010(A), 096.A-0045(A) and 096.A-0045(B).MUSE Ultra Deep Field redshift catalogs (Full Table A.1) are available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http

The deep structure of the Sichuan basin and adjacent orogenic zones revealed by the aggregated deep seismic profiling datum

Science.gov (United States)

Xiong, X.; Gao, R.; Li, Q.; Wang, H.

2012-12-01

The sedimentary basin and the orogenic belt are the basic two tectonic units of the continental lithosphere, and form the basin-mountain coupling system, The research of which is the key element to the oil and gas exploration, the global tectonic theory and models and the development of the geological theory. The Sichuan basin and adjacent orogenic belts is one of the most ideal sites to research the issues above, in particular by the recent deep seismic profiling datum. From the 1980s to now, there are 11 deep seismic sounding profiles and 6 deep seismic reflection profiles and massive seismic broadband observation stations deployed around and crossed the Sichuan basin, which provide us a big opportunity to research the deep structure and other forward issues in this region. Supported by the National Natural Science Foundation of China (Grant No. 41104056) and the Fundamental Research Funds of the Institute of Geological Sciences, CAGS (No. J1119), we sampled the Moho depth and low-velocity zone depth and the Pn velocity of these datum, then formed the contour map of the Moho depth and Pn velocity by the interpolation of the sampled datum. The result shows the Moho depth beneath Sichuan basin ranges from 40 to 44 km, the sharp Moho offset appears in the western margin of the Sichuan basin, and there is a subtle Moho depression in the central southern part of the Sichuan basin; the P wave velocity can be 6.0 km/s at ca. 10 km deep, and increases gradually deeper, the average P wave velocity in this region is ca. 6.3 km/s; the Pn velocity is ca. 8.0-8.02 km/s in Sichuan basin, and 7.70-7.76 km/s in Chuan-Dian region; the low velocity zone appears in the western margin of the Sichuan basin, which maybe cause the cause of the earthquake.

Modelling of far-field gas migration from a deep radioactive waste repository

International Nuclear Information System (INIS)

Rodwell, W.R.; Nash, P.J.

1992-01-01

In assessing the post-closure safety of a deep radioactive waste repository, it is necessary to show that gas generated within the repository can migrate away, through the far-field geology, without affecting repository safety. This paper discusses the contribution of various mechanisms to gas migration through the far field; for example, diffusion of dissolved gas versus gas-phase movement, and bubble flow versus formation of a connected gas stream. It outlines different approaches to modelling gas movement from a repository, with simple semi-analytical models furnishing physical insights into the factors controlling gas migration in the absence of directly applicable experimental data, and more comprehensive numerical computations allowing the exploration of more detailed behaviour when appropriate data is obtained. If gas can induce groundwater movement, this could accelerate the transport of water-borne contaminants. Processes by which this could occur are noted, and the current status of work on possible effects of gas migration on groundwater movement in fractured hard rocks is indicated. 14 refs., 4 figs

Deep learning for computational chemistry.

Science.gov (United States)

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.

Basement-involved faults and deep structures in the West Philippine Basin: constrains from gravity field

Science.gov (United States)

Wang, Gang; Jiang, Suhua; Li, Sanzhong; Zhang, Huixuan; Lei, Jianping; Gao, Song; Zhao, Feiyu

2017-06-01

To reveal the basement-involved faults and deep structures of the West Philippine Basin (WPB), the gravitational responses caused by these faults are observed and analyzed based on the latest spherical gravity model: WGM2012 Model. By mapping the free-air and Bouguer gravity anomalies, several main faults and some other linear structures are located and observed in the WPB. Then, by conducting a 2D discrete multi-scale wavelet decomposition, the Bouguer anomalies are decomposed into the first- to eighth-order detail and approximation fields (the first- to eighth-order Details and Approximations). The first- to third-order Details reflect detailed and localized geological information of the crust at different depths, and of which the higher-order reflects gravity field of the deeper depth. The first- to fourth-order Approximations represent the regional gravity fields at different depths of the crust, respectively. The fourth-order Approximation represents the regional gravity fluctuation caused by the density inhomogeneity of Moho interface. Therefore, taking the fourth-order Approximation as input, and adopting Parker-Oldenburg interactive inversion, We calculated the depth of Moho interface in the WPB. Results show that the Moho interface depth in the WPB ranges approximately from 8 to 12 km, indicating that there is typical oceanic crust in the basin. In the Urdaneta Plateau and the Benham Rise, the Moho interface depths are about 14 and 16 km, respectively, which provides a piece of evidence to support that the Banham Rise could be a transitional crust caused by a large igneous province. The second-order vertical derivative and the horizontal derivatives in direction 0° and 90° are computed based on the data of the third-order Detail, and most of the basement-involved faults and structures in the WPB, such as the Central Basin Fault Zone, the Gagua Ridge, the Luzon-Okinawa Fault Zone, and the Mindanao Fault Zone are interpreted by the gravity derivatives.

Distinction between the Poole-Frenkel and tunneling models of electric-field-stimulated carrier emission from deep levels in semiconductors

International Nuclear Information System (INIS)

Ganichev, S. D.; Ziemann, E.; Prettl, W.; Yassievich, I. N.; Istratov, A. A.; Weber, E. R.

2000-01-01

The enhancement of the emission rate of charge carriers from deep-level defects in electric field is routinely used to determine the charge state of the defects. However, only a limited number of defects can be satisfactorily described by the Poole-Frenkel theory. An electric field dependence different from that expected from the Poole-Frenkel theory has been repeatedly reported in the literature, and no unambiguous identification of the charge state of the defect could be made. In this article, the electric field dependencies of emission of carriers from DX centers in Al x Ga 1-x As:Te, Cu pairs in silicon, and Ge:Hg have been studied applying static and terahertz electric fields, and analyzed by using the models of Poole-Frenkel and phonon assisted tunneling. It is shown that phonon assisted tunneling and Poole-Frenkel emission are two competitive mechanisms of enhancement of emission of carriers, and their relative contribution is determined by the charge state of the defect and by the electric-field strength. At high-electric field strengths carrier emission is dominated by tunneling independently of the charge state of the impurity. For neutral impurities, where Poole-Frenkel lowering of the emission barrier does not occur, the phonon assisted tunneling model describes well the experimental data also in the low-field region. For charged impurities the transition from phonon assisted tunneling at high fields to Poole-Frenkel effect at low fields can be traced back. It is suggested that the Poole-Frenkel and tunneling models can be distinguished by plotting logarithm of the emission rate against the square root or against the square of the electric field, respectively. This analysis enables one to unambiguously determine the charge state of a deep-level defect. (c) 2000 The American Physical Society

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

Science.gov (United States)

2001-01-01

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

pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

Science.gov (United States)

Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

2017-12-05

In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.

Analyses of the deep borehole drilling status for a deep borehole disposal system

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Youl; Choi, Heui Joo; Lee, Min Soo; Kim, Geon Young; Kim, Kyung Su [KAERI, Daejeon (Korea, Republic of)

2016-05-15

The purpose of disposal for radioactive wastes is not only to isolate them from humans, but also to inhibit leakage of any radioactive materials into the accessible environment. Because of the extremely high level and long-time scale radioactivity of HLW(High-level radioactive waste), a mined deep geological disposal concept, the disposal depth is about 500 m below ground, is considered as the safest method to isolate the spent fuels or high-level radioactive waste from the human environment with the best available technology at present time. Therefore, as an alternative disposal concept, i.e., deep borehole disposal technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general status of deep drilling technologies was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, very preliminary applicability of deep drilling technology for deep borehole disposal analyzed. In this paper, as one of key technologies of deep borehole disposal system, the general status of deep drilling technologies in oil industry, geothermal industry and geo scientific field was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, the very preliminary applicability of deep drilling technology for deep borehole disposal such as relation between depth and diameter, drilling time and feasibility classification was analyzed.

Building Program Vector Representations for Deep Learning

OpenAIRE

Mou, Lili; Li, Ge; Liu, Yuxuan; Peng, Hao; Jin, Zhi; Xu, Yan; Zhang, Lu

2014-01-01

Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, whi...

The multiple gas-liquid subsea separation system: development and qualification of a novel solution for deep water field production

Energy Technology Data Exchange (ETDEWEB)

Abrand, Stephanie; Butin, Nicolas; Shaiek, Sadia; Hallot, Raymond [Saipem S.p.A., Milano (Italy)

2012-07-01

Subsea processing is more and more considered as a viable solution for the development of deep and ultra deep water fields. SAIPEM has developed a deep water gas separation and liquid boosting system, based on its proprietary 'Multi pipe' separator concept, providing a good flexibility in handling a wide range of steady and un-steady multiphase input streams using a relatively simple mechanical arrangement. The Multi pipe Concept features an array of vertical pipes for gas/liquid separation by gravity and adequate liquid hold up volumes. The operating principle is the same as standard gravity vessels. Specific inlet pipe arrangements have been worked out to enhance the separation efficiency and internals can be implemented to further optimize the performances. The limited diameter and wall thickness of the vertical pipes make the Multi pipe Concept particularly suited for deep and ultra-deep water applications and/or high pressure conditions where the selection of a single separator vessel could lead to unpractical wall thicknesses. In most cases, standard API or ASME pipes can be utilized for the Multi pipe Separator, thus enabling conventional fabrication methods, and in turn reducing cost and delivery time and opening opportunities for local content. The qualification testing program has seen two subsequent phases. The first qualification phase aimed at the confirmation of the hydrodynamic behavior of the system. In particular, the homogeneous distribution of the multiphase stream into the pipes and the stability of the liquid levels under un-steady inlet conditions were continuously assessed during the tests. This first qualification phase gave confidence in the viability of the Multi pipe and in its good hydrodynamic behavior under the different inlet conditions that can be encountered during field production. It proved that, having the same liquid level in all the separator pipes, whatever the inlet conditions are, the Multi pipe separator can be

MRI Texture Analysis Reveals Deep Gray Nuclei Damage in Amyotrophic Lateral Sclerosis.

Science.gov (United States)

de Albuquerque, Milena; Anjos, Lara G V; Maia Tavares de Andrade, Helen; de Oliveira, Márcia S; Castellano, Gabriela; Junqueira Ribeiro de Rezende, Thiago; Nucci, Anamarli; França Junior, Marcondes Cavalcante

2016-01-01

Amyotrophic Lateral Sclerosis (ALS) is characterized by extensive corticospinal damage, but extrapyramidal involvement is suggested in pathological studies. Texture analysis (TA) is an image processing technique that evaluates the distribution of gray levels between pixels in a given region of interest (ROI). It provides quantitative data and has been employed in several neurodegenerative disorders. Here, we used TA to investigate possible deep gray nuclei (DGN) abnormalities in a cohort of ALS patients. Thirty-two ALS patients and 32 healthy controls underwent MRI in a 3T scanner. The T1 volumetric sequence was used for DGN segmentation and extraction of 11 texture parameters using the MaZda software. Statistical analyses were performed using the Mann-Whitney non-parametric test, with a significance level set at α = 0.025 (FDR-corrected) for TA. Patients had significantly higher values for the parameter correlation (CO) in both thalami and in the right caudate nucleus compared to healthy controls. Also, the parameter Inverse Difference Moment or Homogeneity (IDM) presented significantly smaller values in the ALS group in both thalami. TA of T1 weighted images revealed DGN alterations in patients with ALS, namely in the thalami and caudate nuclei. Copyright © 2015 by the American Society of Neuroimaging.

Multi-aged Forest: an Optimal Management Strategy for Carbon Sequestration

Science.gov (United States)

Yao, L.; Tang, X.; Ma, M.

2017-12-01

Disturbances and climatic changes significantly affect forest ecosystem productivity, water use efficiency (WUE) and carbon (C) flux dynamics. A deep understanding of terrestrial feedbacks to such effects and recovery mechanisms in forests across contrasting climatic regimes is essential to predict future regional/global C and water budgets, which are also closely related to the potential forest management decisions. However, the resilience of multi-aged and even-aged forests to disturbances has been debated for more than 60 years because of technical measurement constraints. Here we evaluated 62 site-years of eddy covariance measurements of net ecosystem production (NEP), evapotranspiration (ET), the estimates of gross primary productivity (GPP), ecosystem respiration (Re) and ecosystem-level WUE, as well as the relationships with environmental controls in three chronosequences of multi- and even-aged coniferous forests covering the Mediterranean, temperate and boreal regions. Age-specific dynamics in multi-year mean annual NEP and WUE revealed that forest age is a key variable that determines the sign and magnitude of recovering forest C source-sink strength from disturbances. However, the trends of annual NEP and WUE across succession stages between two stand structures differed substantially. The successional patterns of NEP exhibited an inverted-U trend with age at the two even-aged chronosequences, whereas NEP of the multi-aged chronosequence increased steadily through time. Meanwhile, site-level WUE of even-aged forests decreased gradually from young to mature, whereas an apparent increase occurred for the same forest age in multi-aged stands. Compared with even-aged forests, multi-aged forests sequestered more CO2 with forest age and maintained a relatively higher WUE in the later succession periods. With regard to the available flux measurements in this study, these behaviors are independent of tree species, stand ages and climate conditions . We also

Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT.

Science.gov (United States)

Han, Yoseob; Ye, Jong Chul

2018-06-01

X-ray computed tomography (CT) using sparse projection views is a recent approach to reduce the radiation dose. However, due to the insufficient projection views, an analytic reconstruction approach using the filtered back projection (FBP) produces severe streaking artifacts. Recently, deep learning approaches using large receptive field neural networks such as U-Net have demonstrated impressive performance for sparse-view CT reconstruction. However, theoretical justification is still lacking. Inspired by the recent theory of deep convolutional framelets, the main goal of this paper is, therefore, to reveal the limitation of U-Net and propose new multi-resolution deep learning schemes. In particular, we show that the alternative U-Net variants such as dual frame and tight frame U-Nets satisfy the so-called frame condition which makes them better for effective recovery of high frequency edges in sparse-view CT. Using extensive experiments with real patient data set, we demonstrate that the new network architectures provide better reconstruction performance.

Meeting the flow assurance challenges of deep water developments - from CAPEX development to field start up

Energy Technology Data Exchange (ETDEWEB)

Jordan, M.M.; Feasey, N.D. [National Aluminium Company Ltd. (Nalco), Cheshire (United Kingdom); Afonso, M.; Silva, D. [NALCO Brasil Ltda., Sao Paulo, SP (Brazil)

2008-07-01

As oil accumulations in easily accessible locations around the world become less available developments in deeper water become a more common target for field development. Deep water projects, particularly sub sea development, present a host of challenges in terms of flow assurance and integrity. In this paper the focus will be on the chemical control of flow assurance challenges in hydrate control, scale control and wax/asphaltene control within deep water (>750 meter) developments. The opportunities for kinetic hydrate control vs. conventional thermodynamic hydrate control will be outlined with examples of where these technologies have been applied and the limitations that still exist. The development of scale control chemical formulations specifically for sub sea application and the challenges of monitoring such control programs will be highlighted with developments in real time and near real time monitoring. Organic deposit control (wax/asphaltene) will focus on the development of new chemicals that have higher activity but lower viscosity than currently used chemicals hence allowing deployment at colder temperatures and over longer distances. The factors that need to be taken into account when selecting chemicals for deep water application will be highlighted. Fluid viscosity, impact of hydrostatic head on injectivity, product stability at low temperature and interaction with other production chemicals will be reviewed as they pertain to effective flow assurance. This paper brings learning from other deep water basins with examples from the Gulf of Mexico, West Africa and Brazil, which will be used to highlight these challenges and some of the solutions currently available along with the technology gaps that exist. (author)

Surface Brightness Profiles of Composite Images of Compact Galaxies at Z approximately equal 4-6 in the Hubble Ultra Deep Field

National Research Council Canada - National Science Library

Hathi, N. P; Jansen, R. A; Windhorst, R. A; Cohen, S. H; Keel, W. C; Corbin, M. R; Ryan, Jr, R. E

2007-01-01

The Hubble Ultra Deep Field (HUDF) contains a significant number of B-, V-, and iota'-band dropout objects, many of which were recently confirmed to be young star-forming galaxies at Z approximately equal 4-6...

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

Science.gov (United States)

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

2017-01-01

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

Deep learning in bioinformatics.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-01-01

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

Automatic Segmentation and Deep Learning of Bird Sounds

NARCIS (Netherlands)

Koops, Hendrik Vincent; Van Balen, J.M.H.; Wiering, F.

2015-01-01

We present a study on automatic birdsong recognition with deep neural networks using the BIRDCLEF2014 dataset. Through deep learning, feature hierarchies are learned that represent the data on several levels of abstraction. Deep learning has been applied with success to problems in fields such as

Learning Transferable Features with Deep Adaptation Networks

OpenAIRE

Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

2015-01-01

Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

NATURAL GAS RESOURCES IN DEEP SEDIMENTARY BASINS

Energy Technology Data Exchange (ETDEWEB)

Thaddeus S. Dyman; Troy Cook; Robert A. Crovelli; Allison A. Henry; Timothy C. Hester; Ronald C. Johnson; Michael D. Lewan; Vito F. Nuccio; James W. Schmoker; Dennis B. Riggin; Christopher J. Schenk

2002-02-05

From a geological perspective, deep natural gas resources are generally defined as resources occurring in reservoirs at or below 15,000 feet, whereas ultra-deep gas occurs below 25,000 feet. From an operational point of view, ''deep'' is often thought of in a relative sense based on the geologic and engineering knowledge of gas (and oil) resources in a particular area. Deep gas can be found in either conventionally-trapped or unconventional basin-center accumulations that are essentially large single fields having spatial dimensions often exceeding those of conventional fields. Exploration for deep conventional and unconventional basin-center natural gas resources deserves special attention because these resources are widespread and occur in diverse geologic environments. In 1995, the U.S. Geological Survey estimated that 939 TCF of technically recoverable natural gas remained to be discovered or was part of reserve appreciation from known fields in the onshore areas and State waters of the United. Of this USGS resource, nearly 114 trillion cubic feet (Tcf) of technically-recoverable gas remains to be discovered from deep sedimentary basins. Worldwide estimates of deep gas are also high. The U.S. Geological Survey World Petroleum Assessment 2000 Project recently estimated a world mean undiscovered conventional gas resource outside the U.S. of 844 Tcf below 4.5 km (about 15,000 feet). Less is known about the origins of deep gas than about the origins of gas at shallower depths because fewer wells have been drilled into the deeper portions of many basins. Some of the many factors contributing to the origin of deep gas include the thermal stability of methane, the role of water and non-hydrocarbon gases in natural gas generation, porosity loss with increasing thermal maturity, the kinetics of deep gas generation, thermal cracking of oil to gas, and source rock potential based on thermal maturity and kerogen type. Recent experimental simulations

A tripolar current-steering stimulator ASIC for field shaping in deep brain stimulation.

Science.gov (United States)

Valente, Virgilio; Demosthenous, Andreas; Bayford, Richard

2012-06-01

A significant problem with clinical deep brain stimulation (DBS) is the high variability of its efficacy and the frequency of side effects, related to the spreading of current beyond the anatomical target area. This is the result of the lack of control that current DBS systems offer on the shaping of the electric potential distribution around the electrode. This paper presents a stimulator ASIC with a tripolar current-steering output stage, aiming at achieving more selectivity and field shaping than current DBS systems. The ASIC was fabricated in a 0.35-μ m CMOS technology occupying a core area of 0.71 mm(2). It consists of three current sourcing/sinking channels. It is capable of generating square and exponential-decay biphasic current pulses with five different time constants up to 28 ms and delivering up to 1.85 mA of cathodic current, in steps of 4 μA, from a 12 V power supply. Field shaping was validated by mapping the potential distribution when injecting current pulses through a multicontact DBS electrode in saline.

Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Science.gov (United States)

André, M.; Caballé, A.; van der Schaar, M.; Solsona, A.; Houégnigan, L.; Zaugg, S.; Sánchez, A. M.; Castell, J. V.; Solé, M.; Vila, F.; Djokic, D.; Adrián-Martínez, S.; Albert, A.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J.-J.; Avgitas, T.; Baret, B.; Barrios-Martí, J.; Basa, S.; Bertin, V.; Biagi, S.; Bormuth, R.; Bouwhuis, M. C.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Celli, S.; Chiarusi, T.; Circella, M.; Coleiro, A.; Coniglione, R.; Costantini, H.; Coyle, P.; Creusot, A.; Deschamps, A.; de Bonis, G.; Distefano, C.; di Palma, I.; Donzaud, C.; Dornic, D.; Drouhin, D.; Eberl, T.; El Bojaddaini, I.; Elsässer, D.; Enzenhöfer, A.; Fehn, K.; Felis, I.; Fusco, L. A.; Galatà, S.; Gay, P.; Geißelsöder, S.; Geyer, K.; Giordano, V.; Gleixner, A.; Glotin, H.; Gracia-Ruiz, R.; Graf, K.; Hallmann, S.; van Haren, H.; Heijboer, A. J.; Hello, Y.; Hernandez-Rey, J. J.; Hößl, J.; Hofestädt, J.; Hugon, C.; Illuminati, G.; James, C. W.; de Jong, M.; Jongen, M.; Kadler, M.; Kalekin, O.; Katz, U.; Kießling, D.; Kouchner, A.; Kreter, M.; Kreykenbohm, I.; Kulikovskiy, V.; Lachaud, C.; Lahmann, R.; Lefèvre, D.; Leonora, E.; Loucatos, S.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martínez-Mora, J. A.; Mathieu, A.; Melis, K.; Michael, T.; Migliozzi, P.; Moussa, A.; Mueller, C.; Nezri, E.; Păvălaş, G. E.; Pellegrino, C.; Perrina, C.; Piattelli, P.; Popa, V.; Pradier, T.; Racca, C.; Riccobene, G.; Roensch, K.; Saldaña, M.; Samtleben, D. F. E.; Sanguineti, M.; Sapienza, P.; Schnabel, J.; Schüssler, F.; Seitz, T.; Sieger, C.; Spurio, M.; Stolarczyk, Th.; Sánchez-Losa, A.; Taiuti, M.; Trovato, A.; Tselengidou, M.; Turpin, D.; Tönnis, C.; Vallage, B.; Vallée, C.; van Elewyck, V.; Vivolo, D.; Wagner, S.; Wilms, J.; Zornoza, J. D.; Zuñiga, J.

2017-04-01

Despite dedicated research has been carried out to adequately map the distribution of the sperm whale in the Mediterranean Sea, unlike other regions of the world, the species population status is still presently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARES neutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probably associated with the availability of cephalopods in the region. The presence of the Ligurian Sea sperm whales was demonstrated through the real-time analysis of audio data streamed from a cabled-to-shore deep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviour on the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surface shipping noise would apparently not condition the foraging behaviour of the sperm whale in the area, since shipping noise was almost always present when sperm whales were acoustically detected. The continuous presence of the sperm whale in the region confirms the ecological value of the Ligurian sea and the importance of ANTARES to help monitoring its ecosystems.

Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Science.gov (United States)

André, M.; Caballé, A.; van der Schaar, M.; Solsona, A.; Houégnigan, L.; Zaugg, S.; Sánchez, A. M.; Castell, J. V.; Solé, M.; Vila, F.; Djokic, D.; Adrián-Martínez, S.; Albert, A.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J.-J.; Avgitas, T.; Baret, B.; Barrios-Martí, J.; Basa, S.; Bertin, V.; Biagi, S.; Bormuth, R.; Bouwhuis, M. C.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Celli, S.; Chiarusi, T.; Circella, M.; Coleiro, A.; Coniglione, R.; Costantini, H.; Coyle, P.; Creusot, A.; Deschamps, A.; De Bonis, G.; Distefano, C.; Di Palma, I.; Donzaud, C.; Dornic, D.; Drouhin, D.; Eberl, T.; El Bojaddaini, I.; Elsässer, D.; Enzenhöfer, A.; Fehn, K.; Felis, I.; Fusco, L. A.; Galatà, S.; Gay, P.; Geißelsöder, S.; Geyer, K.; Giordano, V.; Gleixner, A.; Glotin, H.; Gracia-Ruiz, R.; Graf, K.; Hallmann, S.; van Haren, H.; Heijboer, A. J.; Hello, Y.; Hernandez-Rey, J. J.; Hößl, J.; Hofestädt, J.; Hugon, C.; Illuminati, G.; James, C. W.; de Jong, M.; Jongen, M.; Kadler, M.; Kalekin, O.; Katz, U.; Kießling, D.; Kouchner, A.; Kreter, M.; Kreykenbohm, I.; Kulikovskiy, V.; Lachaud, C.; Lahmann, R.; Lefèvre, D.; Leonora, E.; Loucatos, S.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martínez-Mora, J. A.; Mathieu, A.; Melis, K.; Michael, T.; Migliozzi, P.; Moussa, A.; Mueller, C.; Nezri, E.; Păvălaş, G. E.; Pellegrino, C.; Perrina, C.; Piattelli, P.; Popa, V.; Pradier, T.; Racca, C.; Riccobene, G.; Roensch, K.; Saldaña, M.; Samtleben, D. F. E.; Sanguineti, M.; Sapienza, P.; Schnabel, J.; Schüssler, F.; Seitz, T.; Sieger, C.; Spurio, M.; Stolarczyk, Th.; Sánchez-Losa, A.; Taiuti, M.; Trovato, A.; Tselengidou, M.; Turpin, D.; Tönnis, C.; Vallage, B.; Vallée, C.; Van Elewyck, V.; Vivolo, D.; Wagner, S.; Wilms, J.; Zornoza, J. D.; Zuñiga, J.

2017-01-01

Despite dedicated research has been carried out to adequately map the distribution of the sperm whale in the Mediterranean Sea, unlike other regions of the world, the species population status is still presently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARES neutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probably associated with the availability of cephalopods in the region. The presence of the Ligurian Sea sperm whales was demonstrated through the real-time analysis of audio data streamed from a cabled-to-shore deep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviour on the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surface shipping noise would apparently not condition the foraging behaviour of the sperm whale in the area, since shipping noise was almost always present when sperm whales were acoustically detected. The continuous presence of the sperm whale in the region confirms the ecological value of the Ligurian sea and the importance of ANTARES to help monitoring its ecosystems. PMID:28401960

Deep Learning Microscopy

KAUST Repository

Rivenson, Yair; Gorocs, Zoltan; Gunaydin, Harun; Zhang, Yibo; Wang, Hongda; Ozcan, Aydogan

2017-01-01

regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably

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

Science.gov (United States)

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

2017-08-25

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

Deep amplicon sequencing reveals mixed phytoplasma infection within single grapevine plants

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Contaldo, Nicoletta; Makarova, Olga

2011-01-01

The diversity of phytoplasmas within single plants has not yet been fully investigated. In this project, deep amplicon sequencing was used to generate 50,926 phytoplasma sequences from 11 phytoplasma-infected grapevine samples from a PCR amplicon in the 5' end of the 16S region. After clustering ...

Deep Mapping and Spatial Anthropology

Directory of Open Access Journals (Sweden)

Les Roberts

2016-01-01

Full Text Available This paper provides an introduction to the Humanities Special Issue on “Deep Mapping”. It sets out the rationale for the collection and explores the broad-ranging nature of perspectives and practices that fall within the “undisciplined” interdisciplinary domain of spatial humanities. Sketching a cross-current of ideas that have begun to coalesce around the concept of “deep mapping”, the paper argues that rather than attempting to outline a set of defining characteristics and “deep” cartographic features, a more instructive approach is to pay closer attention to the multivalent ways deep mapping is performatively put to work. Casting a critical and reflexive gaze over the developing discourse of deep mapping, it is argued that what deep mapping “is” cannot be reduced to the otherwise a-spatial and a-temporal fixity of the “deep map”. In this respect, as an undisciplined survey of this increasing expansive field of study and practice, the paper explores the ways in which deep mapping can engage broader discussion around questions of spatial anthropology.

Observations of the Hubble Deep Field with the Infrared Space Observatory .3. Source counts and P(D) analysis

DEFF Research Database (Denmark)

Oliver, S.J.; Goldschmidt, P.; Franceschini, A.

1997-01-01

We present source counts at 6.7 and 15 mu m from our maps of the Hubble Deep Field (HDF) region, reaching 38.6 mu Jy at 6.7 mu m and 255 mu Jy at 15 mu m. These are the first ever extragalactic number counts to be presented at 6.7 mu m, and are three decades fainter than IRAS at 12 mu m. Both...

Rhythms and community dynamics of a hydrothermal tubeworm assemblage at main endeavour field - a multidisciplinary deep-sea observatory approach.

Directory of Open Access Journals (Sweden)

Daphne Cuvelier

Full Text Available The NEPTUNE cabled observatory network hosts an ecological module called TEMPO-mini that focuses on hydrothermal vent ecology and time series, granting us real-time access to data originating from the deep sea. In 2011-2012, during TEMPO-mini's first deployment on the NEPTUNE network, the module recorded high-resolution imagery, temperature, iron (Fe and oxygen on a hydrothermal assemblage at 2186 m depth at Main Endeavour Field (North East Pacific. 23 days of continuous imagery were analysed with an hourly frequency. Community dynamics were analysed in detail for Ridgeia piscesae tubeworms, Polynoidae, Pycnogonida and Buccinidae, documenting faunal variations, natural change and biotic interactions in the filmed tubeworm assemblage as well as links with the local environment. Semi-diurnal and diurnal periods were identified both in fauna and environment, revealing the influence of tidal cycles. Species interactions were described and distribution patterns were indicative of possible microhabitat preference. The importance of high-resolution frequencies (<1 h to fully comprehend rhythms in fauna and environment was emphasised, as well as the need for the development of automated or semi-automated imagery analysis tools.

Effects of applying an external magnetic field during the deep cryogenic heat treatment on the corrosion resistance and wear behavior of 1.2080 tool steel

International Nuclear Information System (INIS)

Akhbarizadeh, Amin; Amini, Kamran; Javadpour, Sirus

2012-01-01

Highlights: ► Deep cryogenic increases the carbide percentage and make a more homogenous distribution. ► Deep cryogenic improve the wear resistance and corrosion behavior of 1.2080 tool steel. ► Applying the magnetic field weaker the carbide distribution and decreases the carbides percentage. ► Magnetized samples showed weaker corrosion and wear behavior. -- Abstract: This work concerns with the effect of applying an external magnetic field on the corrosion behavior, wear resistance and microstructure of 1.2080 (D2) tool steel during the deep cryogenic heat treatment. These analyses were performed via scanning electron microscope (SEM), optical microscope (OM), transmission electron microscope (TEM) and X-ay diffraction (XRD) to study the microstructure, a pin-on-disk wear testing machine to study the wear behavior, and linear sweep voltammetry to study the corrosion behavior of the samples. It was shown that the deep cryogenic heat treatment eliminates retained austenite and makes a more uniform carbide distribution with higher percentage. It was also observed that the deep cryogenic heat treatment improves the wear behavior and corrosion resistance of 1.2080 tool steel. In comparison between the magnetized and non-magnetized samples, the carbide percentage decreases and the carbide distribution weakened in the magnetized samples; subsequently, the wear behavior and corrosion resistance attenuated compared in the magnetized samples.

Dwarf Galaxies with Gentle Star Formation and the Counts of Galaxies in the Hubble Deep Field

OpenAIRE

Campos, Ana

1997-01-01

In this paper the counts and colors of the faint galaxies observed in the Hubble Deep Field are fitted by means of simple luminosity evolution models that incorporate a numerous population of fading dwarfs. The observed color distribution of the very faint galaxies now allows us to put constraints on the star formation history in dwarfs. It is shown that the star-forming activity in these small systems has to proceed in a gentle way, i.e., through episodes where each one lasts much longer tha...

THE TAIWAN ECDFS NEAR-INFRARED SURVEY: ULTRA-DEEP J AND K{sub S} IMAGING IN THE EXTENDED CHANDRA DEEP FIELD-SOUTH

Energy Technology Data Exchange (ETDEWEB)

Hsieh, Bau-Ching; Wang, Wei-Hao; Hsieh, Chih-Chiang; Lin, Lihwai; Lim, Jeremy; Ho, Paul T. P. [Institute of Astrophysics and Astronomy, Academia Sinica, P.O. Box 23-141, Taipei 106, Taiwan (China); Yan Haojing [Department of Physics and Astronomy, University of Missouri, Columbia, MO 65211 (United States)

2012-12-15

We present ultra-deep J and K{sub S} imaging observations covering a 30' Multiplication-Sign 30' area of the Extended Chandra Deep Field-South (ECDFS) carried out by our Taiwan ECDFS Near-Infrared Survey (TENIS). The median 5{sigma} limiting magnitudes for all detected objects in the ECDFS reach 24.5 and 23.9 mag (AB) for J and K{sub S} , respectively. In the inner 400 arcmin{sup 2} region where the sensitivity is more uniform, objects as faint as 25.6 and 25.0 mag are detected at 5{sigma}. Thus, this is by far the deepest J and K{sub S} data sets available for the ECDFS. To combine TENIS with the Spitzer IRAC data for obtaining better spectral energy distributions of high-redshift objects, we developed a novel deconvolution technique (IRACLEAN) to accurately estimate the IRAC fluxes. IRACLEAN can minimize the effect of blending in the IRAC images caused by the large point-spread functions and reduce the confusion noise. We applied IRACLEAN to the images from the Spitzer IRAC/MUSYC Public Legacy in the ECDFS survey (SIMPLE) and generated a J+K{sub S} -selected multi-wavelength catalog including the photometry of both the TENIS near-infrared and the SIMPLE IRAC data. We publicly release the data products derived from this work, including the J and K{sub S} images and the J+K{sub S} -selected multi-wavelength catalog.

The UDF05 Follow-up of the Hubble Ultra Deep Field. III. The Luminosity Function at z ~ 6

Science.gov (United States)

Su, Jian; Stiavelli, Massimo; Oesch, Pascal; Trenti, Michele; Bergeron, Eddie; Bradley, Larry; Carollo, Marcella; Dahlen, Tomas; Ferguson, Henry C.; Giavalisco, Mauro; Koekemoer, Anton; Lilly, Simon; Lucas, Ray A.; Mobasher, Bahram; Panagia, Nino; Pavlovsky, Cheryl

2011-09-01

In this paper, we present a derivation of the rest-frame 1400 Å luminosity function (LF) at redshift six from a new application of the maximum likelihood method by exploring the five deepest Hubble Space Telescope/Advanced Camera for Surveys (HST/ACS) fields, i.e., the Hubble Ultra Deep Field, two UDF05 fields, and two Great Observatories Origins Deep Survey fields. We work on the latest improved data products, which makes our results more robust than those of previous studies. We use unbinned data and thereby make optimal use of the information contained in the data set. We focus on the analysis to a magnitude limit where the completeness is larger than 50% to avoid possibly large errors in the faint end slope that are difficult to quantify. We also take into account scattering in and out of the dropout sample due to photometric errors by defining for each object a probability that it belongs to the dropout sample. We find the best-fit Schechter parameters to the z ~ 6 LF are α = 1.87 ± 0.14, M * = -20.25 ± 0.23, and phi* = 1.77+0.62 -0.49 × 10-3 Mpc-3. Such a steep slope suggests that galaxies, especially the faint ones, are possibly the main sources of ionizing photons in the universe at redshift six. We also combine results from all studies at z ~ 6 to reach an agreement in the 95% confidence level that -20.45 Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program 10632 and 11563.

Crustal structure revealed by a deep seismic sounding profile of Baijing-Gaoming-Jinwan in the Pearl River Delta

Science.gov (United States)

Zhang, Xiang; Ye, Xiuwei; Lv, Jinshui; Sun, Jinlong; Wang, Xiaona

2018-02-01

The Pearl River Estuary area, located in the middle part of the southern China coastal seismic belt, has long been considered a potential source of strong earthquakes above magnitude 7.0. To scientifically assess the potential strong earthquake risk in this area, a three-dimensional artificial seismic sounding experiment, consisting of a receiving array and seabed seismograph, was performed to reveal the deep crustal structure in this region. We used artificial ship-borne air-gun excitation shots as sources, and fixed and mobile stations as receivers to record seismic data from May to August 2015. This paper presents results along a line from the western side of the Pearl River Estuary to the western side of the Baijing-Gaoming-Jinwan profile. A two-dimensional velocity structure was constructed using seismic travel-time tomography. The inversion results show that the Moho depth is 27 km in the coastal area and 30 km in the northwest of the Pearl River Estuary area, indicating that the crust thins from land to sea. Two structural discontinuities and multiple low-velocity anomalies appear in the crustal section. Inside both discontinuity zones, a low-velocity layer, with a minimum velocity of 6.05 km s-1, exists at a depth of about 15 km, and another, with a minimum velocity of 6.37 km s-1, exists at a depth of about 21.5 km between the middle and lower crust. These low velocities suggest that the discontinuities may consist of partly molten material. Earthquakes with magnitudes higher than 5.0 occurred in the low-velocity layer along the profile. The deep Kaiping-Enping fault, rooted in the crust, may be one of the most important channels for deep material upwelling and is related to tectonic movement since the Cretaceous in the Pearl River Delta tectonic rift basin.

Deep-water northern Gulf of Mexico hydrocarbon plays

International Nuclear Information System (INIS)

Peterson, R.H.; Cooke, D.W.

1995-01-01

The geologic setting in the deep-water (depths greater than 1,500 feet) Gulf of Mexico is very favorable for the existence of large, commercial hydrocarbon accumulations. These areas have active salt tectonics that create abundant traps, underlying mature Mesozoic source rocks that can be observed expelling oil and gas to the ocean surface, and good quality reservoirs provided by turbidite sand deposits. Despite the limited amount of drilling in the deep-water Gulf of Mexico, 11 deep-water accumulations have been discovered which, when developed, will rank in the top 100 largest fields in the Gulf of Mexico. Proved field discoveries (those with announced development plans) have added over 1 billion barrels of oil equivalent to Gulf of Mexico reserves, and unproved field discoveries may add to additional billion barrels of oil equivalent. The Minerals Management Service, United States Department of the Interior, has completed a gulf-wide review of over 1,086 oil and gas fields and placed every pay sand in each field into a hydrocarbon play (plays are defined by chronostratigraphy, lithostratigraph, structure, and production). Seven productive hydrocarbon plays were identified in the deep-water northern Gulf of Mexico. Regional maps illustrate the productive limits of each play. In addition, field data, dry holes, and wells with sub-economic pay were added to define the facies and structural limits for each play. Areas for exploration potential are identified for each hydrocarbon play. A type field for each play is chosen to demonstrate the play's characteristics

Tic related local field potentials in the thalamus and the effect of deep brain stimulation in Tourette syndrome : Report of three cases

NARCIS (Netherlands)

Bour, L. J.; Ackermans, L.; Foncke, E. M. J.; Cath, D.; van der Linden, C.; Vandewalle, V. Visser; Tijssen, M. A.

Objective: Three patients with intractable Tourette syndrome (TS) underwent thalamic deep brain stimulation (DBS). To investigate the role of thalamic electrical activity in tic generation, local field potentials (LFP), EEG and EMG simultaneously were recorded. Methods: Event related potentials and

Deep processes in non-relativistic confining potentials

International Nuclear Information System (INIS)

Fishbane, P.M.; Grisaru, M.T.

1978-01-01

The authors study deep inelastic and hard scattering processes for non-relativistic particles confined in deep potentials. The mechanisms by which the effects of confinement disappear and the particles scatter as if free are useful in understanding the analogous results for a relativistic field theory. (Auth.)

Theory of deep inelastic lepton-hadron scattering

International Nuclear Information System (INIS)

Geyer, B.; Robaschik, D.; Wieczorek, E.

1979-01-01

The description of deep inelastic lepton-nucleon scattering in the lowest order of the electromagnetic and weak coupling constants leads to a study of virtual Compton amplitudes and their absorptive parts. Some aspects of quantum chromodynamics are discussed. Deep inelastic scattering enables a central quantity of quantum field theory, namely the light cone behaviour of the current commutator. The moments of structure functions are used for the description of deep inelastic scattering. (author)

Deepest X-Rays Ever Reveal universe Teeming With Black Holes

Science.gov (United States)

2001-03-01

For the first time, astronomers believe they have proof black holes of all sizes once ruled the universe. NASA's Chandra X-ray Observatory provided the deepest X-ray images ever recorded, and those pictures deliver a novel look at the past 12 billion years of black holes. Two independent teams of astronomers today presented images that contain the faintest X-ray sources ever detected, which include an abundance of active super massive black holes. "The Chandra data show us that giant black holes were much more active in the past than at present," said Riccardo Giacconi, of Johns Hopkins University and Associated Universities, Inc., Washington, DC. The exposure is known as "Chandra Deep Field South" since it is located in the Southern Hemisphere constellation of Fornax. "In this million-second image, we also detect relatively faint X-ray emission from galaxies, groups, and clusters of galaxies". The images, known as Chandra Deep Fields, were obtained during many long exposures over the course of more than a year. Data from the Chandra Deep Field South will be placed in a public archive for scientists beginning today. "For the first time, we are able to use X-rays to look back to a time when normal galaxies were several billion years younger," said Ann Hornschemeier, Pennsylvania State University, University Park. The group’s 500,000-second exposure included the Hubble Deep Field North, allowing scientists the opportunity to combine the power of Chandra and the Hubble Space Telescope, two of NASA's Great Observatories. The Penn State team recently acquired an additional 500,000 seconds of data, creating another one-million-second Chandra Deep Field, located in the constellation of Ursa Major. Chandra Deep Field North/Hubble Deep Field North Press Image and Caption The images are called Chandra Deep Fields because they are comparable to the famous Hubble Deep Field in being able to see further and fainter objects than any image of the universe taken at X

Comparative metagenomic analysis of the microbial communities in the surroundings of Iheya north and Iheya ridge hydrothermal fields reveals insights into the survival strategy of microorganisms in deep-sea environments

Science.gov (United States)

Wang, Hai-liang; Sun, Li

2018-04-01

In this study, metagenomic analysis was performed to investigate the taxonomic compositions and metabolic profiles of the microbial communities inhabiting the sediments in the surroundings of Iheya North and Iheya Ridge hydrothermal fields. The microbial communities in four different samples were found to be dominated by bacteria and, to a much lesser extent, archaea belonging to the phyla Proteobacteria, Actinobacteria, Planctomycetes, Firmicutes, Deinococcus-Thermus, and Nitrospirae, which play important roles in the cycling of carbon, nitrogen, and sulfur. All four microbial communities (i) contained chemoautotrophs and heterotrophs, the former probably fixed CO2 via various carbon fixation pathways, and the latter may degrade organic matters using nitrate and sulfate as electron acceptors, (ii) exhibited an abundance of DNA repair genes and bacterial sulfur oxidation mediated by reverse sulfate reduction, and (iii) harbored bacteria and archaea involved in anaerobic methane oxidation via intra-aerobic denitrification and reverse methanogenesis, which were found for the first time in hydrothermal areas. Furthermore, genes involved in DNA repair, reductive acetyl-CoA pathway, and ammonia metabolism were possibly affected by distance to the vent fields. These findings facilitate our understanding of the strategies of the microbial communities to adapt to the environments in deep sea areas associated with hydrothermal vents.

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

Science.gov (United States)

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

2016-04-15

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

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

Science.gov (United States)

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

Deep geothermics

International Nuclear Information System (INIS)

Anon.

1995-01-01

The hot-dry-rocks located at 3-4 km of depth correspond to low permeable rocks carrying a large amount of heat. The extraction of this heat usually requires artificial hydraulic fracturing of the rock to increase its permeability before water injection. Hot-dry-rocks geothermics or deep geothermics is not today a commercial channel but only a scientific and technological research field. The Soultz-sous-Forets site (Northern Alsace, France) is characterized by a 6 degrees per meter geothermal gradient and is used as a natural laboratory for deep geothermal and geological studies in the framework of a European research program. Two boreholes have been drilled up to 3600 m of depth in the highly-fractured granite massif beneath the site. The aim is to create a deep heat exchanger using only the natural fracturing for water transfer. A consortium of german, french and italian industrial companies (Pfalzwerke, Badenwerk, EdF and Enel) has been created for a more active participation to the pilot phase. (J.S.). 1 fig., 2 photos

A study of the deep structure of the energy landscape of glassy polystyrene: the exponential distribution of the energy barriers revealed by high-field electron spin resonance spectroscopy

International Nuclear Information System (INIS)

Bercu, V; Martinelli, M; Massa, C A; Pardi, L A; Leporini, D

2004-01-01

The reorientation of one small paramagnetic molecule (spin probe) in glassy polystyrene (PS) is studied by high-field electron spin resonance spectroscopy at two different Larmor frequencies (190 and 285 GHz). The exponential distribution of the energy barriers for the rotational motion of the spin probe is unambiguously evidenced at both 240 and 270 K. The same shape for the distribution of the energy barriers of PS was evidenced by the master curves provided by previous mechanical and light scattering studies. The breadth of the energy barrier distribution of the spin probe is in the range of the estimates of the breadth of the PS energy barrier distribution. The evidence that the deep structure of the energy landscape of PS exhibits the exponential shape of the energy barrier distribution agrees with the results from extreme-value statistics (Bouchaud and Mezard 1997 J. Phys. A: Math. Gen. 30 7997) and the trap model by Bouchaud and co-workers (1996 J. Phys. A: Math. Gen. 29 3847, 2001 Phys. Rev. B 64 104417). (letter to the editor)

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

Science.gov (United States)

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

2018-06-01

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

Different continuous cropping spans significantly affect microbial community membership and structure in a vanilla-grown soil as revealed by deep pyrosequencing.

Science.gov (United States)

Xiong, Wu; Zhao, Qingyun; Zhao, Jun; Xun, Weibing; Li, Rong; Zhang, Ruifu; Wu, Huasong; Shen, Qirong

2015-07-01

In the present study, soil bacterial and fungal communities across vanilla continuous cropping time-series fields were assessed through deep pyrosequencing of 16S ribosomal RNA (rRNA) genes and internal transcribed spacer (ITS) regions. The results demonstrated that the long-term monoculture of vanilla significantly altered soil microbial communities. Soil fungal diversity index increased with consecutive cropping years, whereas soil bacterial diversity was relatively stable. Bray-Curtis dissimilarity cluster and UniFrac-weighted principal coordinate analysis (PCoA) revealed that monoculture time was the major determinant for fungal community structure, but not for bacterial community structure. The relative abundances (RAs) of the Firmicutes, Actinobacteria, Bacteroidetes, and Basidiomycota phyla were depleted along the years of vanilla monoculture. Pearson correlations at the phyla level demonstrated that Actinobacteria, Armatimonadetes, Bacteroidetes, Verrucomicrobia, and Firmicutes had significant negative correlations with vanilla disease index (DI), while no significant correlation for fungal phyla was observed. In addition, the amount of the pathogen Fusarium oxysporum accumulated with increasing years and was significantly positively correlated with vanilla DI. By contrast, the abundance of beneficial bacteria, including Bradyrhizobium and Bacillus, significantly decreased over time. In sum, soil weakness and vanilla stem wilt disease after long-term continuous cropping can be attributed to the alteration of the soil microbial community membership and structure, i.e., the reduction of the beneficial microbes and the accumulation of the fungal pathogen.

Deep pelagic food web structure as revealed by in situ feeding observations.

Science.gov (United States)

Choy, C Anela; Haddock, Steven H D; Robison, Bruce H

2017-12-06

Food web linkages, or the feeding relationships between species inhabiting a shared ecosystem, are an ecological lens through which ecosystem structure and function can be assessed, and thus are fundamental to informing sustainable resource management. Empirical feeding datasets have traditionally been painstakingly generated from stomach content analysis, direct observations and from biochemical trophic markers (stable isotopes, fatty acids, molecular tools). Each approach carries inherent biases and limitations, as well as advantages. Here, using 27 years (1991-2016) of in situ feeding observations collected by remotely operated vehicles (ROVs), we quantitatively characterize the deep pelagic food web of central California within the California Current, complementing existing studies of diet and trophic interactions with a unique perspective. Seven hundred and forty-three independent feeding events were observed with ROVs from near-surface waters down to depths approaching 4000 m, involving an assemblage of 84 different predators and 82 different prey types, for a total of 242 unique feeding relationships. The greatest diversity of prey was consumed by narcomedusae, followed by physonect siphonophores, ctenophores and cephalopods. We highlight key interactions within the poorly understood 'jelly web', showing the importance of medusae, ctenophores and siphonophores as key predators, whose ecological significance is comparable to large fish and squid species within the central California deep pelagic food web. Gelatinous predators are often thought to comprise relatively inefficient trophic pathways within marine communities, but we build upon previous findings to document their substantial and integral roles in deep pelagic food webs. © 2017 The Authors.

Molecular analyses reveal high levels of eukaryotic richness associated with enigmatic deep-sea protists (Komokiacea)

DEFF Research Database (Denmark)

Lecroq, Beatrice; Gooday, Andrew John; Cedhagen, Tomas

2009-01-01

Komokiaceans are testate agglutinated protists, extremely diverse and abundant in the deep sea. About 40 species are described and share the same main morpholog- ical feature: a test consisting of narrow branching tubules forming a complex system. In some species, the interstices between the tubu......Komokiaceans are testate agglutinated protists, extremely diverse and abundant in the deep sea. About 40 species are described and share the same main morpholog- ical feature: a test consisting of narrow branching tubules forming a complex system. In some species, the interstices between...... suggest strongly that komokiaceans, and probably many other large testate protists, provide a habitat structure for a large spectrum of eukaryotes, significantly contributing to maintaining the biodiversity of micro- and meiofaunal communities in the deep sea....

Short-term Memory of Deep RNN

OpenAIRE

Gallicchio, Claudio

2018-01-01

The extension of deep learning towards temporal data processing is gaining an increasing research interest. In this paper we investigate the properties of state dynamics developed in successive levels of deep recurrent neural networks (RNNs) in terms of short-term memory abilities. Our results reveal interesting insights that shed light on the nature of layering as a factor of RNN design. Noticeably, higher layers in a hierarchically organized RNN architecture results to be inherently biased ...

Producing deep-water hydrocarbons

International Nuclear Information System (INIS)

Pilenko, Thierry

2011-01-01

Several studies relate the history and progress made in offshore production from oil and gas fields in relation to reserves and the techniques for producing oil offshore. The intention herein is not to review these studies but rather to argue that the activities of prospecting and producing deep-water oil and gas call for a combination of technology and project management and, above all, of devotion and innovation. Without this sense of commitment motivating men and women in this industry, the human adventure of deep-water production would never have taken place

IDENTIFICATIONS AND PHOTOMETRIC REDSHIFTS OF THE 2 Ms CHANDRA DEEP FIELD-SOUTH SOURCES

International Nuclear Information System (INIS)

Luo, B.; Brandt, W. N.; Xue, Y. Q.; Rafferty, D. A.; Schneider, D. P.; Brusa, M.; Alexander, D. M.; Lehmer, B. D.; Bauer, F. E.; Comastri, A.; Koekemoer, A.; Mainieri, V.; Silverman, J. D.; Vignali, C.

2010-01-01

We present reliable multiwavelength identifications and high-quality photometric redshifts for the 462 X-ray sources in the ∼2 Ms Chandra Deep Field-South (CDF-S) survey. Source identifications are carried out using deep optical-to-radio multiwavelength catalogs, and are then combined to create lists of primary and secondary counterparts for the X-ray sources. We identified reliable counterparts for 442 (95.7%) of the X-ray sources, with an expected false-match probability of ∼ 6.2%; we also selected four additional likely counterparts. The majority of the other 16 X-ray sources appear to be off-nuclear sources, sources associated with galaxy groups and clusters, high-redshift active galactic nuclei (AGNs), or spurious X-ray sources. A likelihood-ratio method is used for source matching, which effectively reduces the false-match probability at faint magnitudes compared to a simple error-circle matching method. We construct a master photometric catalog for the identified X-ray sources including up to 42 bands of UV-to-infrared data, and then calculate their photometric redshifts (photo-z's). High accuracy in the derived photo-z's is accomplished owing to (1) the up-to-date photometric data covering the full spectral energy distributions (SEDs) of the X-ray sources, (2) more accurate photometric data as a result of source deblending for ∼10% of the sources in the infrared bands and a few percent in the optical and near-infrared bands, (3) a set of 265 galaxy, AGN, and galaxy/AGN hybrid templates carefully constructed to best represent all possible SEDs, (4) the Zurich Extragalactic Bayesian Redshift Analyzer used to derive the photo-z's, which corrects the SED templates to best represent the SEDs of real sources at different redshifts and thus improves the photo-z quality. The reliability of the photo-z's is evaluated using the subsample of 220 sources with secure spectroscopic redshifts. We achieve an accuracy of |Δz|/(1 + z) ∼ 1% and an outlier [with |�

Research Proposal for Distributed Deep Web Search

NARCIS (Netherlands)

Tjin-Kam-Jet, Kien

2010-01-01

This proposal identifies two main problems related to deep web search, and proposes a step by step solution for each of them. The first problem is about searching deep web content by means of a simple free-text interface (with just one input field, instead of a complex interface with many input

Deep brain stimulation as a functional scalpel.

Science.gov (United States)

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

2006-01-01

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

Deep learning with convolutional neural networks for EEG decoding and visualization.

Science.gov (United States)

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Deep learning with convolutional neural networks for EEG decoding and visualization

Science.gov (United States)

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

The implicit effect of texturizing field on the elastic properties of magnetic elastomers revealed by SANS

Energy Technology Data Exchange (ETDEWEB)

Balasoiu, M., E-mail: balas@jinr.ru [Joint Institute of Nuclear Research, Dubna (Russian Federation); Horia Hulubei National Institute for Physics and Nuclear Engineering, Bucharest (Romania); Lebedev, V.T. [St.Petersburg Nuclear Physics Institute NRC KI, Gatchina (Russian Federation); Raikher, Yu.L. [Institute of Continuous Media Mechanics, Russian Academy of Sciences, Ural Branch, Perm (Russian Federation); Bica, I.; Bunoiu, M. [West University of Timisoara, Department of Physics (Romania)

2017-06-01

Small angle neutron scattering method (SANS) is used to characterize the structure properties of the polymer matrix of magnetic elastomers (MEs) of the same material content but with different magnetic textures. For that, series of silicone-rubber elastomers mixed with a ferrofluid and polymerized with/without external magnetic field were studied. In the species of pure rubber and the ME samples synthesized without field, SANS reveals a substantial number of large polymer coils (blobs) which are vertically prolate. The case of MEs polymerized under the magnetic field that is also vertically directed, is different. SANS data indicates that there the blobs are preferably elongated in the direction normal to the field. - Highlights: • SANS method is used to determine the structure of SR elastomers polymerized with ferrofluid in/no external magnetic field. • In the rubber and ME samples synthesized without field, SANS reveals a substantial number of vertically prolate blobs. • For MEs polymerized in vertical magnetic field, results that the blobs are elongated in the direction normal to the field. • Isotropic and texturized MEs differ by the filler structure and by intrinsic elastic properties of the matrix as well.

Preliminary discussion on deep-sourced uranium metallogenesis and deep prospecting

International Nuclear Information System (INIS)

Huang Shijie

2006-01-01

Prospecting for hydrothermal type uranium deposits should be aimed at medium-to large-sized deposits, and be guided by mantle-sourced, superimposed, deep-sourced metallogenic theory and the establishment of a multifactor, composite, deep-sourced metallogenic model. The author suggests that hydrothermal uranium deposits may be classified into three genetic types, i.e. hydrothermal circulation concentration, postmagmatic hydrothermal and mantle fluid concentration. These types of uranium deposits are characterized by their own metallogenic features and are concentrated in the same mineralization-concentrated area forming a metallogenic series. Large-sized uranium ore fields and rich-large uranium deposits are usually closely associated with mantle-sourced metallogenesis and the formation of such uranium ore fields and deposits is characterized by specific and unique regional geologic environments. Recognition criteria of mantle-sourced metallogenesis are preliminarily proposed in the paper. It is pointed out that prospecting in the future should follow the metallogenic model proper for the specific genetic type, and the establishment of operable prospecting model to realize the model-guided prospecting. (authors)

UVUDF: Ultraviolet imaging of the Hubble ultra deep field with wide-field camera 3

Energy Technology Data Exchange (ETDEWEB)

Teplitz, Harry I.; Rafelski, Marc; Colbert, James W.; Hanish, Daniel J. [Infrared Processing and Analysis Center, MS 100-22, Caltech, Pasadena, CA 91125 (United States); Kurczynski, Peter; Gawiser, Eric [Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854 (United States); Bond, Nicholas A.; Gardner, Jonathan P.; De Mello, Duilia F. [Laboratory for Observational Cosmology, Astrophysics Science Division, Code 665, Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Grogin, Norman; Koekemoer, Anton M.; Brown, Thomas M.; Coe, Dan; Ferguson, Henry C. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Atek, Hakim [Laboratoire d' Astrophysique, École Polytechnique Fédérale de Lausanne (EPFL), Observatoire, CH-1290 Sauverny (Switzerland); Finkelstein, Steven L. [Department of Astronomy, The University of Texas at Austin, Austin, TX 78712 (United States); Giavalisco, Mauro [Astronomy Department, University of Massachusetts, Amherst, MA 01003 (United States); Gronwall, Caryl [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Lee, Kyoung-Soo [Department of Physics, Purdue University, 525 Northwestern Avenue, West Lafayette, IN 47907 (United States); Ravindranath, Swara, E-mail: hit@ipac.caltech.edu [Inter-University Centre for Astronomy and Astrophysics, Pune (India); and others

2013-12-01

We present an overview of a 90 orbit Hubble Space Telescope treasury program to obtain near-ultraviolet imaging of the Hubble Ultra Deep Field using the Wide Field Camera 3 UVIS detector with the F225W, F275W, and F336W filters. This survey is designed to: (1) investigate the episode of peak star formation activity in galaxies at 1 < z < 2.5; (2) probe the evolution of massive galaxies by resolving sub-galactic units (clumps); (3) examine the escape fraction of ionizing radiation from galaxies at z ∼ 2-3; (4) greatly improve the reliability of photometric redshift estimates; and (5) measure the star formation rate efficiency of neutral atomic-dominated hydrogen gas at z ∼ 1-3. In this overview paper, we describe the survey details and data reduction challenges, including both the necessity of specialized calibrations and the effects of charge transfer inefficiency. We provide a stark demonstration of the effects of charge transfer inefficiency on resultant data products, which when uncorrected, result in uncertain photometry, elongation of morphology in the readout direction, and loss of faint sources far from the readout. We agree with the STScI recommendation that future UVIS observations that require very sensitive measurements use the instrument's capability to add background light through a 'post-flash'. Preliminary results on number counts of UV-selected galaxies and morphology of galaxies at z ∼ 1 are presented. We find that the number density of UV dropouts at redshifts 1.7, 2.1, and 2.7 is largely consistent with the number predicted by published luminosity functions. We also confirm that the image mosaics have sufficient sensitivity and resolution to support the analysis of the evolution of star-forming clumps, reaching 28-29th magnitude depth at 5σ in a 0.''2 radius aperture depending on filter and observing epoch.

Optical colours of AGN in the Extended Chandra Deep Field South: Obscured black holes in early type galaxies

OpenAIRE

Rovilos, E.; Georgantopoulos, I.

2007-01-01

We investigate the optical colours of X-ray sources from the Extended Chandra Deep Field South (ECDFS) using photometry from the COMBO-17 survey, aiming to explore AGN - galaxy feedback models. The X-ray sources populate both the ``blue'' and the ``red sequence'' on the colour-magnitude diagram. However, sources in the ``red sequence'' appear systematically more obscured. HST imaging from the GEMS survey demonstrates that the nucleus does not affect significantly the observed colours, and the...

A new macrofaunal limit in the deep biosphere revealed by extreme burrow depths in ancient sediments.

Science.gov (United States)

Cobain, S L; Hodgson, D M; Peakall, J; Wignall, P B; Cobain, M R D

2018-01-10

Macrofauna is known to inhabit the top few 10s cm of marine sediments, with rare burrows up to two metres below the seabed. Here, we provide evidence from deep-water Permian strata for a previously unrecognised habitat up to at least 8 metres below the sediment-water interface. Infaunal organisms exploited networks of forcibly injected sand below the seabed, forming living traces and reworking sediment. This is the first record that shows sediment injections are responsible for hosting macrofaunal life metres below the contemporaneous seabed. In addition, given the widespread occurrence of thick sandy successions that accumulate in deep-water settings, macrofauna living in the deep biosphere are likely much more prevalent than considered previously. These findings should influence future sampling strategies to better constrain the depth range of infaunal animals living in modern deep-sea sands. One Sentence Summary: The living depth of infaunal macrofauna is shown to reach at least 8 metres in new habitats associated with sand injections.

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

Directory of Open Access Journals (Sweden)

Mohammad S. Islam

2017-01-01

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

Using the TensorFlow Deep Neural Network to Classify Mainland China Visitor Behaviours in Hong Kong from Check-in Data

Directory of Open Access Journals (Sweden)

Shanshan Han

2018-04-01

Full Text Available Over the past decade, big data, including Global Positioning System (GPS data, mobile phone tracking data and social media check-in data, have been widely used to analyse human movements and behaviours. Tourism management researchers have noted the potential of applying these data to study tourist behaviours, and many studies have shown that social media check-in data can provide new opportunities for extracting tourism activities and tourist behaviours. However, traditional methods may not be suitable for extracting comprehensive tourist behaviours due to the complexity and diversity of human behaviours. Studies have shown that deep neural networks have outpaced the abilities of human beings in many fields and that deep neural networks can be explained in a psychological manner. Thus, deep neural network methods can potentially be used to understand human behaviours. In this paper, a deep learning neural network constructed in TensorFlow is applied to classify Mainland China visitor behaviours in Hong Kong, and the characteristics of these visitors are analysed to verify the classification results. For the social science classification problem investigated in this study, the deep neural network classifier in TensorFlow provides better accuracy and more lucid visualisation than do traditional neural network methods, even for erratic classification rules. Furthermore, the results of this study reveal that TensorFlow has considerable potential for application in the human geography field.

FIRST RESULTS FROM Pan-STARRS1: FAINT, HIGH PROPER MOTION WHITE DWARFS IN THE MEDIUM-DEEP FIELDS

Energy Technology Data Exchange (ETDEWEB)

Tonry, J. L.; Flewelling, H. A.; Deacon, N. R.; Burgett, W. S.; Chambers, K. C.; Kaiser, N.; Kudritzki, R.-P.; Hodapp, K. W.; Magnier, E. A.; Morgan, J. S.; Wainscoat, R. J. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Stubbs, C. W.; Kilic, M.; Chornock, R.; Berger, E. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Price, P. A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2012-01-20

The Pan-STARRS1 survey has obtained multi-epoch imaging in five bands (Pan-STARRS1 g{sub P1}, r{sub P1}, i{sub P1}, z{sub P1}, and y{sub P1}) on 12 'Medium-Deep fields', each of which spans a 3.{sup 0}3 circle. For the period between 2009 April and 2011 April these fields were observed 50-200 times. Using a reduced proper motion diagram, we have extracted a list of 47 white dwarf (WD) candidates whose Pan-STARRS1 astrometry indicates a non-zero proper motion at the 6{sigma} level, with a typical 1{sigma} proper motion uncertainty of 10 mas yr{sup -1}. We also used astrometry from the Sloan Digital Sky Survey (when available) and USNO-B to assess our proper motion fits. None of the WD candidates exhibits evidence of statistically significant parallaxes, with a typical 1{sigma} uncertainty of 8 mas. Twelve of these candidates are known WDs, including the high proper motion (1.''7 yr{sup -1}) WD LHS 291. We confirm seven more objects as WDs through optical spectroscopy. Based on the Pan-STARRS1 colors, ten of the stars are likely to be cool WDs with 4170 K Deep Field Survey and the 3{pi} survey, Pan-STARRS1 should find many more high proper motion WDs that are part of the old thick disk and halo.

High-resolution deep sequencing reveals biodiversity, population structure, and persistence of HIV-1 quasispecies within host ecosystems

Directory of Open Access Journals (Sweden)

Yin Li

2012-12-01

Full Text Available Abstract Background Deep sequencing provides the basis for analysis of biodiversity of taxonomically similar organisms in an environment. While extensively applied to microbiome studies, population genetics studies of viruses are limited. To define the scope of HIV-1 population biodiversity within infected individuals, a suite of phylogenetic and population genetic algorithms was applied to HIV-1 envelope hypervariable domain 3 (Env V3 within peripheral blood mononuclear cells from a group of perinatally HIV-1 subtype B infected, therapy-naïve children. Results Biodiversity of HIV-1 Env V3 quasispecies ranged from about 70 to 270 unique sequence clusters across individuals. Viral population structure was organized into a limited number of clusters that included the dominant variants combined with multiple clusters of low frequency variants. Next generation viral quasispecies evolved from low frequency variants at earlier time points through multiple non-synonymous changes in lineages within the evolutionary landscape. Minor V3 variants detected as long as four years after infection co-localized in phylogenetic reconstructions with early transmitting viruses or with subsequent plasma virus circulating two years later. Conclusions Deep sequencing defines HIV-1 population complexity and structure, reveals the ebb and flow of dominant and rare viral variants in the host ecosystem, and identifies an evolutionary record of low-frequency cell-associated viral V3 variants that persist for years. Bioinformatics pipeline developed for HIV-1 can be applied for biodiversity studies of virome populations in human, animal, or plant ecosystems.

Hello World Deep Learning in Medical Imaging.

Science.gov (United States)

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.

Deep Learning from Crowds

DEFF Research Database (Denmark)

Rodrigues, Filipe; Pereira, Francisco Camara

Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the stateof-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets. Recently...... networks from crowds. We begin by describing an EM algorithm for jointly learning the parameters of the network and the reliabilities of the annotators. Then, a novel general-purpose crowd layer is proposed, which allows us to train deep neural networks end-to-end, directly from the noisy labels......, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of data in a scalable manner, but it often requires aggregating labels from multiple noisy contributors with different levels of expertise. In this paper, we address the problem of learning deep neural...

Microbial metagenomes from three aquifers in the Fennoscandian shield terrestrial deep biosphere reveal metabolic partitioning among populations.

Science.gov (United States)

Wu, Xiaofen; Holmfeldt, Karin; Hubalek, Valerie; Lundin, Daniel; Åström, Mats; Bertilsson, Stefan; Dopson, Mark

2016-05-01

Microorganisms in the terrestrial deep biosphere host up to 20% of the earth's biomass and are suggested to be sustained by the gases hydrogen and carbon dioxide. A metagenome analysis of three deep subsurface water types of contrasting age (from 86% coverage. The populations were dominated by Proteobacteria, Candidate divisions, unclassified archaea and unclassified bacteria. The estimated genome sizes of the biosphere. The data were finally used to create a combined metabolic model of the deep terrestrial biosphere microbial community.

Numerical simulation of a TLD pulsed laser-heating scheme for determination of shallow dose and deep dose in low-LET radiation fields

International Nuclear Information System (INIS)

Kearfott, K.J.; Han, S.; Wagner, E.C.; Samei, E.; Wang, C.-K.C.

2000-01-01

A new method is described to determine the depth-dose distribution in low-LET radiation fields using a thick thermoluminescent dosimeter (TLD) with a pulsed laser-heating scheme to obtain TL glow output. The computational simulation entails heat conduction and glow curve production processes. An iterative algorithm is used to obtain the dose distribution in the detector. The simulation results indicate that the method can predict the shallow and deep dose in various radiation fields with relative errors less than 20%

Development and application of deep convolutional neural network in target detection

Science.gov (United States)

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.

Coaxial nuclear radiation detector with deep junction and radial field gradient

International Nuclear Information System (INIS)

Hall, R.N.

1979-01-01

Germanium radiation detectors are manufactured by diffusion lithium into high purity p-type germanium. The diffusion is most readily accomplished from a lithium-lead-bismuth alloy at approximately 430 0 and is monitored by a quartz half cell containing a standard composition of this alloy. Detectors having n-type cores may be constructed by converting high purity p-type germanium to n-type by a lithium diffusion and subsequently diffusing some of the lithium back out through the surface to create a deep p-n junction. Coaxial germanium detectors comprising deep p-n junctions are produced by the lithium diffusion process

Miniature ingestible telemeter devices to measure deep-body temperature

Science.gov (United States)

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.

Modeling of Antenna for Deep Target Hydrocarbon Exploration

Directory of Open Access Journals (Sweden)

Nadeem Nasir

2017-11-01

Full Text Available Nowadays control source electromagnetic method is used for offshore hydrocarbon exploration. Hydrocarbon detection in sea bed logging (SBL is a very challenging task for deep target hydrocarbon reservoir. Response of electromagnetic (EM field from marine environment is very low and it is very difficult to predict deep target reservoir below 2km from the sea floor. This work premise deals with modeling of new antenna for deep water deep target hydrocarbon exploration. Conventional and new EM antennas at 0.125Hz frequency are used in modeling for the detection of deep target hydrocarbon  reservoir.  The  proposed  area  of  the  seabed model   (40km ´ 40km   was   simulated   by using CST (computer simulation technology EM studio based on Finite Integration Method (FIM. Electromagnetic field components were compared at 500m target depth and it was concluded that Ex and Hz components shows better resistivity contrast. Comparison of conventional and new antenna for different target  depths  was  done in  our  proposed  model.  From  the results, it was observed that conventional antenna at 0.125Hz shows 70% ,86% resistivity contrast at target depth of 1000m where   as   new   antenna   showed   329%, 355%   resistivity contrast at the same target depth for Ex and Hz field respectively.  It  was  also  investigated  that  at  frequency of0.125Hz, new antenna gave 46% better delineation of hydrocarbon at 4000m target depth. This is due to focusing of electromagnetic waves by using new antenna. New antenna design gave 125% more extra depth than straight antenna for deep target hydrocarbon detection. Numerical modeling for straight  and  new antenna  was also done to know general equation for electromagnetic field behavior with target depth. From this numerical model it was speculated that this new antenna can detect up to 4.5 km target depth. This new EM antenna may open new frontiers for oil and gas

THE UDF05 FOLLOW-UP OF THE HUBBLE ULTRA DEEP FIELD. III. THE LUMINOSITY FUNCTION AT z ∼ 6

International Nuclear Information System (INIS)

Su Jian; Stiavelli, Massimo; Bergeron, Eddie; Bradley, Larry; Dahlen, Tomas; Ferguson, Henry C.; Koekemoer, Anton; Lucas, Ray A.; Panagia, Nino; Pavlovsky, Cheryl; Oesch, Pascal; Carollo, Marcella; Lilly, Simon; Trenti, Michele; Giavalisco, Mauro; Mobasher, Bahram

2011-01-01

In this paper, we present a derivation of the rest-frame 1400 A luminosity function (LF) at redshift six from a new application of the maximum likelihood method by exploring the five deepest Hubble Space Telescope/Advanced Camera for Surveys (HST/ACS) fields, i.e., the Hubble Ultra Deep Field, two UDF05 fields, and two Great Observatories Origins Deep Survey fields. We work on the latest improved data products, which makes our results more robust than those of previous studies. We use unbinned data and thereby make optimal use of the information contained in the data set. We focus on the analysis to a magnitude limit where the completeness is larger than 50% to avoid possibly large errors in the faint end slope that are difficult to quantify. We also take into account scattering in and out of the dropout sample due to photometric errors by defining for each object a probability that it belongs to the dropout sample. We find the best-fit Schechter parameters to the z ∼ 6 LF are α = 1.87 ± 0.14, M * = -20.25 ± 0.23, and φ * = 1.77 +0.62 -0.49 x 10 -3 Mpc -3 . Such a steep slope suggests that galaxies, especially the faint ones, are possibly the main sources of ionizing photons in the universe at redshift six. We also combine results from all studies at z ∼ 6 to reach an agreement in the 95% confidence level that -20.45 * < -20.05 and -1.90 < α < -1.55. The luminosity density has been found not to evolve significantly between z ∼ 6 and z ∼ 5, but considerable evolution is detected from z ∼ 6 to z ∼ 3.

Mechanisms Underlying Decision-Making as Revealed by Deep-Brain Stimulation in Patients with Parkinson's Disease.

Science.gov (United States)

Herz, Damian M; Little, Simon; Pedrosa, David J; Tinkhauser, Gerd; Cheeran, Binith; Foltynie, Tom; Bogacz, Rafal; Brown, Peter

2018-04-23

To optimally balance opposing demands of speed and accuracy during decision-making, we must flexibly adapt how much evidence we require before making a choice. Such adjustments in decision thresholds have been linked to the subthalamic nucleus (STN), and therapeutic STN deep-brain stimulation (DBS) has been shown to interfere with this function. Here, we performed continuous as well as closed-loop DBS of the STN while Parkinson's disease patients performed a perceptual decision-making task. Closed-loop STN DBS allowed temporally patterned STN stimulation and simultaneous recordings of STN activity. This revealed that DBS only affected patients' ability to adjust decision thresholds if applied in a specific temporally confined time window during deliberation. Only stimulation in that window diminished the normal slowing of response times that occurred on difficult trials when DBS was turned off. Furthermore, DBS eliminated a relative, time-specific increase in STN beta oscillations and compromised its functional relationship with trial-by-trial adjustments in decision thresholds. Together, these results provide causal evidence that the STN is involved in adjusting decision thresholds in distinct, time-limited processing windows during deliberation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifications and Photometric Redshifts of the 2 Ms Chandra Deep Field-South Sources

Science.gov (United States)

Luo, B.; Brandt, W. N.; Xue, Y. Q.; Brusa, M.; Alexander, D. M.; Bauer, F. E.; Comastri, A.; Koekemoer, A.; Lehmer, B. D.; Mainieri, V.; Rafferty, D. A.; Schneider, D. P.; Silverman, J. D.; Vignali, C.

2010-04-01

We present reliable multiwavelength identifications and high-quality photometric redshifts for the 462 X-ray sources in the ≈2 Ms Chandra Deep Field-South (CDF-S) survey. Source identifications are carried out using deep optical-to-radio multiwavelength catalogs, and are then combined to create lists of primary and secondary counterparts for the X-ray sources. We identified reliable counterparts for 442 (95.7%) of the X-ray sources, with an expected false-match probability of ≈ 6.2%; we also selected four additional likely counterparts. The majority of the other 16 X-ray sources appear to be off-nuclear sources, sources associated with galaxy groups and clusters, high-redshift active galactic nuclei (AGNs), or spurious X-ray sources. A likelihood-ratio method is used for source matching, which effectively reduces the false-match probability at faint magnitudes compared to a simple error-circle matching method. We construct a master photometric catalog for the identified X-ray sources including up to 42 bands of UV-to-infrared data, and then calculate their photometric redshifts (photo-z's). High accuracy in the derived photo-z's is accomplished owing to (1) the up-to-date photometric data covering the full spectral energy distributions (SEDs) of the X-ray sources, (2) more accurate photometric data as a result of source deblending for ≈10% of the sources in the infrared bands and a few percent in the optical and near-infrared bands, (3) a set of 265 galaxy, AGN, and galaxy/AGN hybrid templates carefully constructed to best represent all possible SEDs, (4) the Zurich Extragalactic Bayesian Redshift Analyzer used to derive the photo-z's, which corrects the SED templates to best represent the SEDs of real sources at different redshifts and thus improves the photo-z quality. The reliability of the photo-z's is evaluated using the subsample of 220 sources with secure spectroscopic redshifts. We achieve an accuracy of |Δz|/(1 + z) ≈ 1% and an outlier [with |�

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

Science.gov (United States)

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

2017-10-01

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

Long-term behaviour of waste-forms in the near-field environment of a deep underground storage site, overview

International Nuclear Information System (INIS)

Toulhoat, P.; Lassabatere, Th.; Galle, Ch.; Cranga, M.; Trotignon, L.; Maillard, S.; Iracane, D.

1997-01-01

CEA (French Atomic Energy Commission) is responsible for the achievement of high activity and/or long life waste conditioning processes. Various waste-forms are used (glass, bitumen, etc...). ANDRA (French National Agency for Nuclear Waste Management) has to integrate the long-term durability of such waste-forms in the conception of a deep disposal and the assessment of its long-term confinement performances. The influence of near-field and of the boundary conditions imposed by the far-field on the long-term evolution is being more and more documented. Transport properties and reactivity of silica in the near field is one of the best examples of such effects. A coherent framework with relevant successive events (site re-saturation, chemical evolution of the engineered barrier, overpack corrosion) and a thorough analysis of hierarchized couplings are necessary to evaluate the long term durability of waste-form, and finally, to deliver a near-field-integrated source-term of radionuclides versus lime. We present hereafter some preliminary results obtained in the framework of the CEA 'C3P' project - long-term behaviour of waste-forms in their near-field environment. (authors)

The NuSTAR Extragalactic Surveys: Initial Results and Catalog from the Extended Chandra Deep Field South

DEFF Research Database (Denmark)

Mullaney, J. R.; Del-Moro, A.; Aird, J.

2015-01-01

We present the initial results and the source catalog from the Nuclear Spectroscopic Telescope Array (NuSTAR) survey of the Extended Chandra Deep Field South (hereafter, ECDFS)—currently the deepest contiguous component of the NuSTAR extragalactic survey program. The survey covers the full ≈30......V fluxes) span the range L10 40 keV (0.7 300) 10 erg s» - ´ 43 1 -- ,sampling below the “knee” of the X-ray luminosity function out to z ~ 0.8-1. Finally, we identify oneNuSTAR source that has neither a Chandra nor an XMM-Newton counterpart, but that shows evidence of nuclearactivity at infrared...

A Survey on Deep Learning in Medical Image Analysis

NARCIS (Netherlands)

Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

2017-01-01

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

Deep Sequence Analysis of AgoshRNA Processing Reveals 3' A Addition and Trimming.

Science.gov (United States)

Harwig, Alex; Herrera-Carrillo, Elena; Jongejan, Aldo; van Kampen, Antonius Hubertus; Berkhout, Ben

2015-07-14

The RNA interference (RNAi) pathway, in which microprocessor and Dicer collaborate to process microRNAs (miRNA), was recently expanded by the description of alternative processing routes. In one of these noncanonical pathways, Dicer action is replaced by the Argonaute2 (Ago2) slicer function. It was recently shown that the stem-length of precursor-miRNA or short hairpin RNA (shRNA) molecules is a major determinant for Dicer versus Ago2 processing. Here we present the results of a deep sequence study on the processing of shRNAs with different stem length and a top G·U wobble base pair (bp). This analysis revealed some unexpected properties of these so-called AgoshRNA molecules that are processed by Ago2 instead of Dicer. First, we confirmed the gradual shift from Dicer to Ago2 processing upon shortening of the hairpin length. Second, hairpins with a stem larger than 19 base pair are inefficiently cleaved by Ago2 and we noticed a shift in the cleavage site. Third, the introduction of a top G·U bp in a regular shRNA can promote Ago2-cleavage, which coincides with a loss of Ago2-loading of the Dicer-cleaved 3' strand. Fourth, the Ago2-processed AgoshRNAs acquire a short 3' tail of 1-3 A-nucleotides (nt) and we present evidence that this product is subsequently trimmed by the poly(A)-specific ribonuclease (PARN).

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

Science.gov (United States)

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

2018-05-01

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

The Deep Physics Hidden within the Field Expressions of the Radiation Fields of Lightning Return Strokes

Directory of Open Access Journals (Sweden)

Vernon Cooray

2016-01-01

Full Text Available Based on the electromagnetic fields generated by a current pulse propagating from one point in space to another, a scenario that is frequently used to simulate return strokes in lightning flashes, it is shown that there is a deep physical connection between the electromagnetic energy dissipated by the system, the time over which this energy is dissipated and the charge associated with the current. For a given current pulse, the product of the energy dissipated and the time over which this energy is dissipated, defined as action in this paper, depends on the length of the channel, or the path, through which the current pulse is propagating. As the length of the channel varies, the action plotted against the length of the channel exhibits a maximum value. The location of the maximum value depends on the ratio of the length of the channel to the characteristic length of the current pulse. The latter is defined as the product of the duration of the current pulse and the speed of propagation of the current pulse. The magnitude of this maximum depends on the charge associated with the current pulse. The results show that when the charge associated with the current pulse approaches the electronic charge, the value of this maximum reaches a value close to h/8π where h is the Plank constant. From this result, one can deduce that the time-energy uncertainty principle is the reason for the fact that the smallest charge that can be detected from the electromagnetic radiation is equal to the electronic charge. Since any system that generates electromagnetic radiation can be represented by a current pulse propagating from one point in space to another, the result is deemed valid for electromagnetic radiation fields in general.

Deep Space Gateway Science Opportunities

Science.gov (United States)

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

2018-01-01

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

Women on the Edge of Time: Representations of revolutionary motherhood in the NEP-era Soviet Union

Directory of Open Access Journals (Sweden)

Hannah Proctor

2015-01-01

Full Text Available Following the October revolution of 1917 the fledgling Soviet government legalized divorce and abortion, secularized marriage, and decriminalized homosexuality. Utopians dreamed of the withering away of the family and the transformation of women's roles in the home and the workplace. But at least for the time being, only some bodies were capable of bearing children. Women's bodies became contested territory, a site of paradox. On the one hand the image of woman was re-imagined as a de-libidinalized fellow comrade, but this was combined with a continued emphasis on women's biological role as the privileged carriers of the future generation. Rather than circumventing this seeming contradiction, Soviet artworks of the 1920s confronted it, depicting motherhood as an emancipatory and revolutionary act. And this crucially does not only relate to bodies but to emotions. Revolutionary maternal love has a positive, affective dimension that provides an alternative to sexual love. The figure of the revolutionary mother prefigures the still hazily defined qualitative richness of the communist future. This article examines the figure of the revolutionary mother through a discussion of key artworks from the NEP era (1921-1928 concluding by considering how the representation of motherhood shifted in the Stalin era. The article asks what these historical ideas might still teach us today.

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

Science.gov (United States)

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

2018-03-01

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

DeepPy: Pythonic deep learning

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo

This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...... be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available at http...

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

Science.gov (United States)

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.

Lessons from Suiyo Seamount studies, for understanding extreme (ancient?) microbial ecosystems in the deep-sea hydrothermal fields

Science.gov (United States)

Maruyama, A.; Higashi, Y.; Sunamura, M.; Urabe, T.

2004-12-01

Deep-sea hydrothermal ecosystems are driven with various geo-thermally modified, mainly reduced, compounds delivered from extremely hot subsurface environments. To date, several unique microbes including thermophilic archaeons have been isolated from/around vent chimneys. However, there is little information about microbes in over-vent and sub-vent fields. Here, we report several new findings on microbial diversity and ecology of the Suiyo Seamount that locates on the Izu-Bonin Arc in the northwest Pacific Ocean, as a result of the Japanese Archaean Park project, with special concern to the sub-vent biosphere. At first, we succeeded to reveal a very unique microbial ecosystem in hydrothermal plume reserved within the outer rim of the seamount crater, that is, it consisted of almost all metabolically active microbes belonged to only two Bacteria phylotypes, probably of sulfur oxidizers. In the center of the caldera seafloor (ca. 1,388-m deep) consisted mainly of whitish sands and pumices, we found many small chimneys (ca. 5-10 cm) and bivalve colonies distributed looking like gray to black patches. These geo/ecological features of the seafloor were supposed to be from a complex mixing of hydrothermal venting and strong water current near the seafloor. Through quantitative FISH analysis for various environmental samples, one of the two representative groups in the plume was assessed to be from some of the bivalve colonies. Using the Benthic Multi-coring System (BMS), total 10 points were drilled and 6 boreholes were maintained with stainless or titanium casing pipes. In the following submersible surveys, newly developed catheter- and column-type in situ growth chambers were deployed in and on the boreholes, respectively, for collecting indigenous sub-vent microbes. Finally, we succeeded to detect several new phylotypes of microbes in these chamber samples, e.g., within epsilon-Proteobacteria, a photosynthetic group of alpha-Proteobacteria, and hyperthermophile

Deep phenotyping of 89 xeroderma pigmentosum patients reveals unexpected heterogeneity dependent on the precise molecular defect

Science.gov (United States)

Fassihi, Hiva; Sethi, Mieran; Fawcett, Heather; Wing, Jonathan; Chandler, Natalie; Mohammed, Shehla; Craythorne, Emma; Morley, Ana M. S.; Lim, Rongxuan; Turner, Sally; Henshaw, Tanya; Garrood, Isabel; Giunti, Paola; Hedderly, Tammy; Abiona, Adesoji; Naik, Harsha; Harrop, Gemma; McGibbon, David; Jaspers, Nicolaas G. J.; Botta, Elena; Nardo, Tiziana; Stefanini, Miria; Young, Antony R.; Sarkany, Robert P. E.; Lehmann, Alan R.

2016-01-01

Xeroderma pigmentosum (XP) is a rare DNA repair disorder characterized by increased susceptibility to UV radiation (UVR)-induced skin pigmentation, skin cancers, ocular surface disease, and, in some patients, sunburn and neurological degeneration. Genetically, it is assigned to eight complementation groups (XP-A to -G and variant). For the last 5 y, the UK national multidisciplinary XP service has provided follow-up for 89 XP patients, representing most of the XP patients in the United Kingdom. Causative mutations, DNA repair levels, and more than 60 clinical variables relating to dermatology, ophthalmology, and neurology have been measured, using scoring systems to categorize disease severity. This deep phenotyping has revealed unanticipated heterogeneity of clinical features, between and within complementation groups. Skin cancer is most common in XP-C, XP-E, and XP-V patients, previously considered to be the milder groups based on cellular analyses. These patients have normal sunburn reactions and are therefore diagnosed later and are less likely to adhere to UVR protection. XP-C patients are specifically hypersensitive to ocular damage, and XP-F and XP-G patients appear to be much less susceptible to skin cancer than other XP groups. Within XP groups, different mutations confer susceptibility or resistance to neurological damage. Our findings on this large cohort of XP patients under long-term follow-up reveal that XP is more heterogeneous than has previously been appreciated. Our data now enable provision of personalized prognostic information and management advice for each XP patient, as well as providing new insights into the functions of the XP proteins. PMID:26884178

Investigating the astrophysical 22Ne(p, γ23Na and 22Mg(p, γ23Al reactions with a multi-channel scattering formalism

Directory of Open Access Journals (Sweden)

Fraser P. R.

2014-03-01

Full Text Available The reaction 22Ne(p, γ23Na is key to the NeNa cycle of stellar nucleogenesis, and better understanding of the 22Mg(p, γ23Al reaction is needed to understand the 22Na puzzle in ONe white dwarf novae. We aim to study these reactions using a multi-channel algebraic scattering (MCAS formalism for low-energy nucleon-nucleus scattering, recently expanded to investigate radiative capture. As a first step towards this goal, we here calculate the energy levels of the mass-23 (Ne, Mg, Na, Al nuclei. This is not only because the resonant structure of these nuclei are related to the astrophysical -rates of interest, but also because the interaction parameters determined for describing the energy levels are an integral part of the future calculation of the astrophysical reactions when using the MCAS scheme.

Subsea innovative boosting technologies on deep water scenarios -- Impacts and demands

International Nuclear Information System (INIS)

Caetano, E.F.; Mendonca, J.E.; Pagot, P.R.; Cotrim, M.L.; Camargo, R.M.T.; Assayag, M.I.

1995-01-01

This paper presents the importance of deep water scenario for Brazil, the PETROBRAS Deep and Ultra-Deep Water R and D Program (PROCAP-2000) and the candidate fields for the deployment of subsea innovative boosting technologies (ESPS -- electrical submersible pump in subsea wells, SSS -- subsea separation systems and SBMS -- subsea multiphase flow pumping system) as well as the problems associated with the flow assurance in such conditions. The impact of those innovative systems, their technological stage and remaining demands to make them available for deployment in offshore subsea areas, mainly in giant deepwater fields, are discussed and predicted

In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz

Science.gov (United States)

Onton, Julie A.; Matthews, Scott C.; Kang, Dae Y.; Coleman, Todd P.

2018-01-01

Veterans with posttraumatic stress disorder (PTSD) often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG) with concurrent collection of electrodermal activity (EDA) and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1–3 Hz), Lo Deep (Deep (p = 0.001) sleep, while spending a larger percentage of the night in Hi Deep (p Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs (p Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study (p deep sleep related to PTSD could not be linked to any known factor. With several medications [prazosin, selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs); p < 0.03], as well as SSRIs were associated with less sleep efficiency (b = -3.3 ± 0.95; p = 0.0005) and more sleep fragmentation (b = -1.7 ± 0.51; p = 0.0009). Anti-psychotics were associated with less sleep efficiency (b = -4.9 ± 1.4; p = 0.0004). Sleep efficiency was negatively impacted by SSRIs, antipsychotic medications, and depression (p < 0.008). Increased sleep fragmentation was associated with SSRIs, SNRIs, and anxiety (p < 0.009), while prazosin and

Characterization of deep level defects and thermally stimulated depolarization phenomena in La-doped TlInS2 layered semiconductor

International Nuclear Information System (INIS)

Seyidov, MirHasan Yu.; Suleymanov, Rauf A.; Mikailzade, Faik A.; Kargın, Elif Orhan; Odrinsky, Andrei P.

2015-01-01

deep level defects, are aligned in the direction of the applied electric field and the equilibrium polarization can be reached in a relatively short time. When the polarization field is maintained, while cooling the temperature of sample to a sufficiently low degrees, the relaxation times of the aligned dipoles drastically increases. Practically, frozen internal electric field or electrets states remain inside the TlInS 2 :La when the applied bias field is switched off. The influence of deep level defects on TSDC spectra of TlInS 2 :La has been revealed for the first time

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

Directory of Open Access Journals (Sweden)

Qiaojun Lou

2017-07-01

Full Text Available 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.).

Science.gov (United States)

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.

Deep Learning for Computer Vision: A Brief Review

Science.gov (United States)

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

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

Deep Learning for Computer Vision: A Brief Review

Directory of Open Access Journals (Sweden)

Athanasios Voulodimos

2018-01-01

Full Text Available 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.

Deep Learning for Computer Vision: A Brief Review.

Science.gov (United States)

Voulodimos, Athanasios; 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.

Deep diving odontocetes foraging strategies and their prey field as determined by acoustic techniques

Science.gov (United States)

Giorli, Giacomo

Deep diving odontocetes, like sperm whales, beaked whales, Risso's dolphins, and pilot whales are known to forage at deep depths in the ocean on squid and fish. These marine mammal species are top predators and for this reason are very important for the ecosystems they live in, since they can affect prey populations and control food web dynamics through top-down effects. The studies presented in this thesis investigate deep diving odontocetes. foraging strategies, and the density and size of their potential prey in the deep ocean using passive and active acoustic techniques. Ecological Acoustic Recorders (EAR) were used to monitor the foraging activity of deep diving odontocetes at three locations around the world: the Josephine Seamount High Sea Marine Protected Area (JHSMPA), the Ligurian Sea, and along the Kona coast of the island of Hawaii. In the JHSMPA, sperm whales. and beaked whales. foraging rates do not differ between night-time and day-time. However, in the Ligurian Sea, sperm whales switch to night-time foraging as the winter approaches, while beaked whales alternate between hunting mainly at night, and both at night and at day. Spatial differences were found in deep diving odontocetes. foraging activity in Hawaii where they forage most in areas with higher chlorophyll concentrations. Pilot whales (and false killer whales, clustered together in the category "blackfishes") and Risso's dolphins forage mainly at night at all locations. These two species adjust their foraging activity with the length of the night. The density and size of animals living in deep sea scattering layers was studied using a DIDSON imaging sonar at multiple stations along the Kona coast of Hawaii. The density of animals was affected by location, depth, month, and the time of day. The size of animals was influenced by station and month. The DIDSON proved to be a successful, non-invasive technique to study density and size of animals in the deep sea. Densities were found to be an

Inversion kinematics at deep-seated gravity slope deformations revealed by trenching techniques

OpenAIRE

Pasquaré Mariotto, Federico; Tibaldi, Alessandro

2016-01-01

We compare data from three deep-seated gravitational slope deformations (DSGSDs) where palaeoseismological techniques were applied in artificial trenches. At all trenches, located in metamorphic rocks of the Italian Alps, there is evidence of extensional deformation given by normal movements along slip planes dipping downhill or uphill, and/or fissures, as expected in gravitational failure. However, we document and illustrate – with the aid of trenching – evidenc...

Using Deep Learning Techniques to Forecast Environmental Consumption Level

Directory of Open Access Journals (Sweden)

Donghyun Lee

2017-10-01

Full Text Available Artificial intelligence is a promising futuristic concept in the field of science and technology, and is widely used in new industries. The deep-learning technology leads to performance enhancement and generalization of artificial intelligence technology. The global leader in the field of information technology has declared its intention to utilize the deep-learning technology to solve environmental problems such as climate change, but few environmental applications have so far been developed. This study uses deep-learning technologies in the environmental field to predict the status of pro-environmental consumption. We predicted the pro-environmental consumption index based on Google search query data, using a recurrent neural network (RNN model. To verify the accuracy of the index, we compared the prediction accuracy of the RNN model with that of the ordinary least square and artificial neural network models. The RNN model predicts the pro-environmental consumption index better than any other model. We expect the RNN model to perform still better in a big data environment because the deep-learning technologies would be increasingly sophisticated as the volume of data grows. Moreover, the framework of this study could be useful in environmental forecasting to prevent damage caused by climate change.

Biodiversity's big wet secret: the global distribution of marine biological records reveals chronic under-exploration of the deep pelagic ocean.

Directory of Open Access Journals (Sweden)

Thomas J Webb

Full Text Available BACKGROUND: Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean--the largest biome on Earth--is chronically under-represented in global databases of marine biodiversity. METHODOLOGY/PRINCIPAL FINDINGS: We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented. CONCLUSIONS/SIGNIFICANCE: The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem.

Geophysical Properties of Hard Rock for Investigation of Stress Fields in Deep Mines

Science.gov (United States)

Tibbo, M.; Young, R. P.; Schmitt, D. R.; Milkereit, B.

2014-12-01

A complication in geophysical monitoring of deep mines is the high-stress dependency of the physical properties of hard rocks. In-mine observations show anisotropic variability of the in situ P- and S-wave velocities and resistivity of the hard rocks that are likely related to stress field changes. As part of a comprehensive study in a deep, highly stressed mine located in Sudbury, Ontario, Canada, data from in situ monitoring of the seismicity, conductivity, stress, and stress dependent physical properties has been obtain. In-laboratory experiments are also being performed on borehole cores from the Sudbury mines. These experiments will measure the Norite borehole core's properties including elastic modulus, bulk modulus, P- and S-wave velocities, and density. Hydraulic fracturing has been successfully implemented in industries such as oil and gas and enhanced geothermal systems, and is currently being investigated as a potential method for preconditioning in mining. However, further research is required to quantify how hydraulic fractures propagate through hard, unfractured rock as well as naturally fractured rock typically found in mines. These in laboratory experiments will contribute to a hydraulic fracturing project evaluating the feasibility and effectiveness of hydraulic fracturing as a method of de-stressing hard rock mines. A tri-axial deformation cell equipped with 18 Acoustic Emission (AE) sensors will be used to bring the borehole cores to a tri-axial state of stress. The cores will then be injected with fluid until the the hydraulic fracture has propagated to the edge of the core, while AE waveforms will be digitized continuously at 10 MHz and 12-bit resolution for the duration of each experiment. These laboratory hydraulic fracture experiments will contribute to understanding how parameters including stress ratio, fluid injection rate, and viscosity, affect the fracturing process.

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

Science.gov (United States)

Embley, Robert W.; Rubin, Kenneth H.

2018-04-01

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

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

Science.gov (United States)

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).

The Canada-France deep fields survey-II: Lyman-break galaxies and galaxy clustering at z ~ 3

Science.gov (United States)

Foucaud, S.; McCracken, H. J.; Le Fèvre, O.; Arnouts, S.; Brodwin, M.; Lilly, S. J.; Crampton, D.; Mellier, Y.

2003-10-01

We present a large sample of z ~ 3 U-band dropout galaxies extracted from the Canada-France deep fields survey (CFDF). Our catalogue covers an effective area of ~ 1700 arcmin2 divided between three large, contiguous fields separated widely on the sky. To IAB=24.5, the survey contains 1294 Lyman-break candidates, in agreement with previous measurements by other authors, after appropriate incompleteness corrections have been applied to our data. Based on comparisons with spectroscopic observations and simulations, we estimate that our sample of Lyman-break galaxies is contaminated by stars and interlopers (lower-redshift galaxies) at no more than { ~ } 30%. We find that omega (theta ) is well fitted by a power-law of fixed slope, gamma =1.8, even at small (theta University of Hawaii, and at the Cerro Tololo Inter-American Observatory and Mayall 4-meter Telescopes, divisions of the National Optical Astronomy Observatories, which are operated by the Association of Universities for Research in Astronomy, Inc. under cooperative agreement with the National Science Foundation.

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

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

2016-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Seyidov, MirHasan Yu., E-mail: smirhasan@gyte.edu.tr; Suleymanov, Rauf A.; Mikailzade, Faik A. [Department of Physics, Gebze Technical University, Gebze, Kocaeli 41400 (Turkey); Institute of Physics of NAS of Azerbaijan, H. Javid ave. 33, Baku AZ-1143 (Azerbaijan); Kargın, Elif Orhan [Department of Physics, Gebze Technical University, Gebze, Kocaeli 41400 (Turkey); Odrinsky, Andrei P. [Institute of Technical Acoustics, National Academy of Sciences of Belarus, Lyudnikov ave. 13, Vitebsk 210717 (Belarus)

2015-06-14

, which are originated from the charged B5 deep level defects, are aligned in the direction of the applied electric field and the equilibrium polarization can be reached in a relatively short time. When the polarization field is maintained, while cooling the temperature of sample to a sufficiently low degrees, the relaxation times of the aligned dipoles drastically increases. Practically, frozen internal electric field or electrets states remain inside the TlInS{sub 2}:La when the applied bias field is switched off. The influence of deep level defects on TSDC spectra of TlInS{sub 2}:La has been revealed for the first time.

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

OpenAIRE

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) w...

Research on deep electromagnetic induction methods (Fy 1985)

Energy Technology Data Exchange (ETDEWEB)

Murakami, Hiroshi; Uchida, Toshihiro; Tanaka, Shin' ichi

1987-06-01

Geological Survey of Japan started from FY 1984 a research of deep electomagnetic induction methods as a part of the research on deep geothermal resources prospecting technology, the Sunshine Project. This article is the report of its second fiscal year. These methods are a generic term of the methods to survey specific resistance structure in the deep part of the earth by utilizing the technique of the electromagnetic induction method and the time domain CSMT method aiming to survey about estimated depth of 5Km as well as the CA method to estimate the general structure of the earth of the depth of 5Km or more are now being developed. This article reports the respective methods separately. Concerning the former, the reception of useful signals were successfully made during the FY 1984 field experiment and based on this, field experiments in a geothermal area were conducted in FY 1985 verifying its effectivenss. With regard to the latter, following FY 1984, CA observations were conducted in the northern part of Tohoku Region and the deep specific resistance structure in a wide area was surveyed. (43 figs, 1 tab, 11 refs)

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

Science.gov (United States)

Mitton, S. A.

2017-12-01

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

Fibrillation mechanism of a model intrinsically disordered protein revealed by 2D correlation deep UV resonance Raman spectroscopy.

Science.gov (United States)

Sikirzhytski, Vitali; Topilina, Natalya I; Takor, Gaius A; Higashiya, Seiichiro; Welch, John T; Uversky, Vladimir N; Lednev, Igor K

2012-05-14

Understanding of numerous biological functions of intrinsically disordered proteins (IDPs) is of significant interest to modern life science research. A large variety of serious debilitating diseases are associated with the malfunction of IDPs including neurodegenerative disorders and systemic amyloidosis. Here we report on the molecular mechanism of amyloid fibrillation of a model IDP (YE8) using 2D correlation deep UV resonance Raman spectroscopy. YE8 is a genetically engineered polypeptide, which is completely unordered at neutral pH yet exhibits all properties of a fibrillogenic protein at low pH. The very first step of the fibrillation process involves structural rearrangements of YE8 at the global structure level without the detectable appearance of secondary structural elements. The formation of β-sheet species follows the global structural changes and proceeds via the simultaneous formation of turns and β-strands. The kinetic mechanism revealed is an important new contribution to understanding of the general fibrillation mechanism proposed for IDP.

DeepVel: Deep learning for the estimation of horizontal velocities at the solar surface

Science.gov (United States)

Asensio Ramos, A.; Requerey, I. S.; Vitas, N.

2017-07-01

Many phenomena taking place in the solar photosphere are controlled by plasma motions. Although the line-of-sight component of the velocity can be estimated using the Doppler effect, we do not have direct spectroscopic access to the components that are perpendicular to the line of sight. These components are typically estimated using methods based on local correlation tracking. We have designed DeepVel, an end-to-end deep neural network that produces an estimation of the velocity at every single pixel, every time step, and at three different heights in the atmosphere from just two consecutive continuum images. We confront DeepVel with local correlation tracking, pointing out that they give very similar results in the time and spatially averaged cases. We use the network to study the evolution in height of the horizontal velocity field in fragmenting granules, supporting the buoyancy-braking mechanism for the formation of integranular lanes in these granules. We also show that DeepVel can capture very small vortices, so that we can potentially expand the scaling cascade of vortices to very small sizes and durations. The movie attached to Fig. 3 is available at http://www.aanda.org

Climate, carbon cycling, and deep-ocean ecosystems.

Science.gov (United States)

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 Sequence Analysis of AgoshRNA Processing Reveals 3’ A Addition and Trimming

Directory of Open Access Journals (Sweden)

Alex Harwig

2015-01-01

Full Text Available The RNA interference (RNAi pathway, in which microprocessor and Dicer collaborate to process microRNAs (miRNA, was recently expanded by the description of alternative processing routes. In one of these noncanonical pathways, Dicer action is replaced by the Argonaute2 (Ago2 slicer function. It was recently shown that the stem-length of precursor-miRNA or short hairpin RNA (shRNA molecules is a major determinant for Dicer versus Ago2 processing. Here we present the results of a deep sequence study on the processing of shRNAs with different stem length and a top G·U wobble base pair (bp. This analysis revealed some unexpected properties of these so-called AgoshRNA molecules that are processed by Ago2 instead of Dicer. First, we confirmed the gradual shift from Dicer to Ago2 processing upon shortening of the hairpin length. Second, hairpins with a stem larger than 19 base pair are inefficiently cleaved by Ago2 and we noticed a shift in the cleavage site. Third, the introduction of a top G·U bp in a regular shRNA can promote Ago2-cleavage, which coincides with a loss of Ago2-loading of the Dicer-cleaved 3’ strand. Fourth, the Ago2-processed AgoshRNAs acquire a short 3’ tail of 1–3 A-nucleotides (nt and we present evidence that this product is subsequently trimmed by the poly(A-specific ribonuclease (PARN.

Strain hardening of aluminium alloy 3004 in the deep drawing and ironing processes

International Nuclear Information System (INIS)

Courbon, J.; Duval, J.L.

1993-01-01

The evolution of material hardening resulting from the canmaking operations on aluminium beverage cans has been investigated. Tensile tests in cup walls revealed that deep drawing induced softening in the hoop direction and hardening in the meridian direction. This anisotropy is retained in the ironing operation. Changes in strain path on a heavily cold-rolled material probably cause such a complex behaviour. To determine hardening laws for deep drawing, simple shear tests were thus performed because of the strain path similarity. They allowed to determine hardening laws over larger strains than tension could reach and revealed a saturation of stress. Altogether they proved adapted to the understanding of deep drawing. (orig.)

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

Science.gov (United States)

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

Deep inelastic scattering and asymptotic freedom

International Nuclear Information System (INIS)

Nachtmann, O.

1985-01-01

I recall some facets of the history of the field of deep inelastic scattering. I show how there was a very fruitful interplay between phenomenology on the one side and more abstract field theoretical considerations on the other side, where Kurt Symanzik, whose memory we honour today, made important contributions. Finally I make some remarks on the most recent developments in this field which have to do with the so-called EMC-effect, where EMC stands for European Muon Collaboration. (orig./HSI)

Ground States of Ultracold Spin-1 Atoms in a Deep Double-Well Optical Superlattice in a Weak Magnetic Field

International Nuclear Information System (INIS)

Zheng Gong-Ping; Qin Shuai-Feng; Wang Shou-Yang; Jian Wen-Tian

2013-01-01

The ground states of the ultracold spin-1 atoms trapped in a deep one-dimensional double-well optical superlattice in a weak magnetic field are obtained. It is shown that the ground-state diagrams of the reduced double-well model are remarkably different for the antiferromagnetic and ferromagnetic condensates. The transition between the singlet state and nematic state is observed for the antiferromagnetic interaction atoms, which can be realized by modulating the tunneling parameter or the quadratic Zeeman energy. An experiment to distinguish the different spin states is suggested. (general)

Deep sea biophysics

International Nuclear Information System (INIS)

Yayanos, A.A.

1982-01-01

A collection of deep-sea bacterial cultures was completed. Procedures were instituted to shelter the culture collection from accidential warming. A substantial data base on the rates of reproduction of more than 100 strains of bacteria from that collection was obtained from experiments and the analysis of that data was begun. The data on the rates of reproduction were obtained under conditions of temperature and pressure found in the deep sea. The experiments were facilitated by inexpensively fabricated pressure vessels, by the streamlining of the methods for the study of kinetics at high pressures, and by computer-assisted methods. A polybarothermostat was used to study the growth of bacteria along temperature gradients at eight distinct pressures. This device should allow for the study of microbial processes in the temperature field simulating the environment around buried HLW. It is small enough to allow placement in a radiation field in future studies. A flow fluorocytometer was fabricated. This device will be used to determine the DNA content per cell in bacteria grown in laboratory culture and in microorganisms in samples from the ocean. The technique will be tested for its rapidity in determining the concentration of cells (standing stock of microorganisms) in samples from the ocean

Model United Nations and Deep Learning: Theoretical and Professional Learning

Science.gov (United States)

Engel, Susan; Pallas, Josh; Lambert, Sarah

2017-01-01

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

PHOTOMETRY AND PHOTOMETRIC REDSHIFT CATALOGS FOR THE LOCKMAN HOLE DEEP FIELD

International Nuclear Information System (INIS)

Fotopoulou, S.; Salvato, M.; Hasinger, G.; Rovilos, E.; Brusa, M.; Lutz, D.; Burwitz, V.; Egami, E.; Henry, J. P.; Huang, J. H.; Rigopoulou, D.; Vaccari, M.

2012-01-01

We present broadband photometry and photometric redshifts for 187,611 sources located in ∼0.5 deg 2 in the Lockman Hole area. The catalog includes 388 X-ray-detected sources identified with the very deep XMM-Newton observations available for an area of 0.2 deg 2 . The source detection was performed on the R c -, z'-, and B-band images and the available photometry is spanning from the far-ultraviolet to the mid-infrared, reaching in the best-case scenario 21 bands. Astrometry corrections and photometric cross-calibrations over the entire data set allowed the computation of accurate photometric redshifts. Special treatment is undertaken for the X-ray sources, the majority of which are active galactic nuclei (AGNs). For normal galaxies, comparing the photometric redshifts to the 253 available spectroscopic redshifts, we achieve an accuracy of σ Δz/(1+z) = 0.036, with 12.6% outliers. For the X-ray-detected sources, compared to 115 spectroscopic redshifts, the accuracy is σ Δz/(1+z) = 0.069, with 18.3% outliers, where the outliers are defined as sources with |z phot – z spec | > 0.15 × (1 + z spec ). These results are a significant improvement over the previously available photometric redshifts for normal galaxies in the Lockman Hole, while it is the first time that photometric redshifts are computed and made public for AGNs for this field.

DeepFlavour in CMS

CERN Multimedia

CERN. Geneva

2017-01-01

Flavour-tagging of jets is an important task in collider based high energy physics and a field where machine learning tools are applied by all major experiments. A new tagger (DeepFlavour) was developed and commissioned in CMS that is based on an advanced machine learning procedure. A deep neural network is used to do multi-classification of jets that origin from a b-quark, two b-quarks, a c-quark, two c-quarks or light colored particles (u, d, s-quark or gluon). The performance was measured in both, data and simulation. The talk will also include the measured performance of all taggers in CMS. The different taggers and results will be discussed and compared with some focus on details of the newest tagger.

SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY REVEALS INTERNAL LIMITING MEMBRANE PEELING ALTERS DEEP RETINAL VASCULATURE.

Science.gov (United States)

Michalewska, Zofia; Nawrocki, Jerzy

2018-04-30

To describe morphology of retinal and choroidal vessels in swept-source optical coherence tomography angiography before and after vitrectomy with the temporal inverted internal limiting membrane (ILM) flap technique for full-thickness macular holes. Prospective, observational study of 36 eyes of 33 patients with full-thickness macular holes swept-source optical coherence tomography angiography was performed in patients before and 1 month after vitrectomy. Vitrectomy with the temporal inverted ILM flap technique was performed. In this method, ILM is peeled only at one side of the fovea. An ILM flap is created to cover the macular hole. Comparison of retina vasculature in the areas of ILM peeling vs. no ILM peeling at 1 and 3 months after successful vitrectomy was performed. The study demonstrated lower density of vessels in the deep retinal plexus in the area where ILM was peeled as compared to the rest of the fovea. Visual acuity and central retinal thickness 1 month after surgery correlates with fovea avascular zone diameter in deep retinal layers at the same time point (P = 0.001). This study confirmed that ILM peeling might alter blood flow in deep retinal vessels below the peeling area in the early postoperative period. The area of the fovea avascular zone corresponds to functional results at the same time point.

On the necessity of taking into account the contribution of multiphoton exchanges into electron-proton deep inelastic scattering

International Nuclear Information System (INIS)

Savrin, V.I.

1979-01-01

The hypothesis that the multiphoton exchanges give a substantial contribution to the electron-proton inclusive scattering is formulated. The hypothesis explains the observed violation of the Bjorken scaling law. As it is shown, the mechanism of such intensification of multiple exchanges may by connected with the properties of the processes of hadron multiproduction in the deep inelastic field. This results in the necessity to calculate the inclusive cross section in all electromagnetic coupling constant orders. This has been done in the framework of the density matrix method. As a result the deep inelastic scattering cross section calculated without application of the perturbation theory reveals a new property of the scaling invariance and leads to the natural relationship of structural functions with electromagnetic proton form-factors on the exclusive threshold

Deep Learning in Medical Image Analysis.

Science.gov (United States)

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

2017-06-21

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

Evaluating lysimeter drainage against soil deep percolation modeled with profile soil moisture, field tracer propagation, and lab measured soil hydraulic properties

DEFF Research Database (Denmark)

Vasquez, Vicente; Thomsen, Anton Gårde; Iversen, Bo Vangsø

them have been reported. To compare among methods, one year of four large-scale lysimeters drainage (D) was evaluated against modeled soil deep percolation using either profile soil moisture, bromide breakthrough curves from suction cups, or measured soil hydraulic properties in the laboratory....... Measured volumetric soil water content (q) was 3-4% higher inside lysimeters than in the field probably due to a zero tension lower boundary condition inside lysimeters. D from soil hydraulic properties measured in the laboratory resulted in a 15% higher evapotranspiration and 12% lower drainage...... predictions than the model calibrated with field measured q. Bromide (Br) breakthrough curves indicated high variability between lysimeters and field suction cups with mean Br velocities at first arrival time of 110 and 33 mm/d, respectively. D was 520 mm/yr with lysimeters, 613 mm/yr with the calibrated...

Field trip method as an effort to reveal student environmental literacy on biodiversity issue and context

Science.gov (United States)

Rijal, M.; Saefudin; Amprasto

2018-05-01

Field trip method through investigation of local biodiversity cases can give educational experiences for students. This learning activity was efforts to reveal students environmental literacy on biodiversity. The aim of study were (1) to describe the activities of students get information about the biodiversity issue and its context through field trip, (2) to describe the students findings during field trip, and (3) to reveal students environmental literacy based on pre test and post test. The research method used weak-experiment and involved 34 participants at senior high school students in Bandung-Indonesia. The research instruments for collecting data were environmental literacy test, observation sheets and questionnaire sheets for students. The analysis of data was quantitative descriptive. The results show that more than 79% of the students gave positive view for each field trip activity, i.e students activity during work (97%-100%); students activity during gather information (79%- 100%); students activity during exchange information with friend (82%-100%); and students interested to Biodiversity after field trip activity (85%-100%). Students gain knowledge about the diversity of animal vertebrate and its characteristics, the status and condition of animals, and the source of animal with the cases of animal diversity. The students environmental literacy tends to be moderate level based on test. Meanwhile, the average of the attitudes and action greater than the components of knowledge and cognitive skills.

Factors Influencing Public-Sphere Pro-Environmental Behavior among Mongolian College Students: A Test of Value–Belief–Norm Theory

Directory of Open Access Journals (Sweden)

Xianwei Liu

2018-05-01

Full Text Available Value–belief–norm (VBN theory provides a valuable framework for identifying the social-psychological determinants of various types of pro-environmental behavior. However, limited empirical study has tested the applicability of VBN theory in the western minority areas of China. Given Mongolian college students’ crucial role in promoting the sustainable development of the Inner Mongolia Autonomous Region (IMAR of China, this study investigates how VBN clusters of variables, namely, values, the new environmental paradigm (NEP and pro-environmental personal norms (PPN, influence Mongolian college students’ self-reported public-sphere pro-environmental behavior (PSPB. The subjects were 1034 Mongolian college students from three large public universities in Hohhot. A structural equation model (SEM and bootstrapping analyses revealed that: (1 altruistic values have a significant positive influence on PSPB, egoistic values negatively influence PSPB, and biospheric values have no significant influence on PSPB; (2 egoistic values negatively predict NEP and biospheric values positively predict NEP, whereas altruistic values have no direct impact on NEP; (3 NEP has a positive influence on PPN; (4 PPN has a significant positive impact on PSPB; and (5 biospheric and egoistic values have an indirect effect on PSPB through NEP and PPN. The findings provided evidence for the cross-cultural applicability of VBN theory in a Mongolian college student sample. Theoretical and practical implications were discussed, and recommended directions for future research were suggested.

Invertebrate population genetics across Earth's largest habitat: The deep-sea floor.

Science.gov (United States)

Taylor, M L; Roterman, C N

2017-10-01

Despite the deep sea being the largest habitat on Earth, there are just 77 population genetic studies of invertebrates (115 species) inhabiting non-chemosynthetic ecosystems on the deep-sea floor (below 200 m depth). We review and synthesize the results of these papers. Studies reveal levels of genetic diversity comparable to shallow-water species. Generally, populations at similar depths were well connected over 100s-1,000s km, but studies that sampled across depth ranges reveal population structure at much smaller scales (100s-1,000s m) consistent with isolation by adaptation across environmental gradients, or the existence of physical barriers to connectivity with depth. Few studies were ocean-wide (under 4%), and 48% were Atlantic-focused. There is strong emphasis on megafauna and commercial species with research into meiofauna, "ecosystem engineers" and other ecologically important species lacking. Only nine papers account for ~50% of the planet's surface (depths below 3,500 m). Just two species were studied below 5,000 m, a quarter of Earth's seafloor. Most studies used single-locus mitochondrial genes revealing a common pattern of non-neutrality, consistent with demographic instability or selective sweeps; similar to deep-sea hydrothermal vent fauna. The absence of a clear difference between vent and non-vent could signify that demographic instability is common in the deep sea, or that selective sweeps render single-locus mitochondrial studies demographically uninformative. The number of population genetics studies to date is miniscule in relation to the size of the deep sea. The paucity of studies constrains meta-analyses where broad inferences about deep-sea ecology could be made. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

`Human nature': Chemical engineering students' ideas about human relationships with the natural world

Science.gov (United States)

Goldman, Daphne; Ben-Zvi Assaraf, Orit; Shemesh, Julia

2014-05-01

While importance of environmental ethics, as a component of sustainable development, in preparing engineers is widely acknowledged, little research has addressed chemical engineers' environmental concerns. This study aimed to address this void by exploring chemical engineering students' values regarding human-nature relationships. The study was conducted with 247 3rd-4th year chemical engineering students in Israeli Universities. It employed the New Ecological Paradigm (NEP)-questionnaire to which students added written explanations. Quantitative analysis of NEP-scale results shows that the students demonstrated moderately ecocentric orientation. Explanations to the NEP-items reveal diverse, ambivalent ideas regarding the notions embodied in the NEP, strong scientific orientation and reliance on technology for addressing environmental challenges. Endorsing sustainability implies that today's engineers be equipped with an ecological perspective. The capacity of Higher Education to enable engineers to develop dispositions about human-nature interrelationships requires adaptation of curricula towards multidisciplinary, integrative learning addressing social-political-economic-ethical perspectives, and implementing critical-thinking within the socio-scientific issues pedagogical approach.

Environmental genomics reveals a single species ecosystem deep within the Earth

Energy Technology Data Exchange (ETDEWEB)

Chivian, Dylan; Brodie, Eoin L.; Alm, Eric J.; Culley, David E.; Dehal, Paramvir S.; DeSantis, Todd Z.; Gihring, Thomas M.; Lapidus, Alla; Lin, Li-Hung; Lowry, Stephen R.; Moser, Duane P.; Richardson, Paul; Southam, Gordon; Wanger, Greg; Pratt, Lisa M.; Andersen, Gary L.; Hazen, Terry C.; Brockman, Fred J.; Arkin, Adam P.; Onstott, Tullis C.

2008-09-17

DNA from low biodiversity fracture water collected at 2.8 km depth in a South African gold mine was sequenced and assembled into a single, complete genome. This bacterium, Candidatus Desulforudis audaxviator, comprises>99.9percent of the microorganisms inhabiting the fluid phase of this particular fracture. Its genome indicates a motile, sporulating, sulfate reducing, chemoautotrophic thermophile that can fix its own nitrogen and carbon using machinery shared with archaea. Candidatus Desulforudis audaxviator is capable of an independent lifestyle well suited to long-term isolation from the photosphere deep within Earth?s crust, and offers the first example of a natural ecosystem that appears to have its biological component entirely encoded within a single genome.

Deep sequencing reveals double mutations in cis of MPL exon 10 in myeloproliferative neoplasms.

Science.gov (United States)

Pietra, Daniela; Brisci, Angela; Rumi, Elisa; Boggi, Sabrina; Elena, Chiara; Pietrelli, Alessandro; Bordoni, Roberta; Ferrari, Maurizio; Passamonti, Francesco; De Bellis, Gianluca; Cremonesi, Laura; Cazzola, Mario

2011-04-01

Somatic mutations of MPL exon 10, mainly involving a W515 substitution, have been described in JAK2 (V617F)-negative patients with essential thrombocythemia and primary myelofibrosis. We used direct sequencing and high-resolution melt analysis to identify mutations of MPL exon 10 in 570 patients with myeloproliferative neoplasms, and allele specific PCR and deep sequencing to further characterize a subset of mutated patients. Somatic mutations were detected in 33 of 221 patients (15%) with JAK2 (V617F)-negative essential thrombocythemia or primary myelofibrosis. Only one patient with essential thrombocythemia carried both JAK2 (V617F) and MPL (W515L). High-resolution melt analysis identified abnormal patterns in all the MPL mutated cases, while direct sequencing did not detect the mutant MPL in one fifth of them. In 3 cases carrying double MPL mutations, deep sequencing analysis showed identical load and location in cis of the paired lesions, indicating their simultaneous occurrence on the same chromosome.

DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

Science.gov (United States)

Wachinger, Christian; Reuter, Martin; Klein, Tassilo

2018-04-15

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

Deep-red semiconductor monolithic mode-locked lasers

International Nuclear Information System (INIS)

Kong, L.; Bajek, D.; White, S. E.; Forrest, A. F.; Cataluna, M. A.; Wang, H. L.; Pan, J. Q.; Wang, X. L.; Cui, B. F.; Ding, Y.

2014-01-01

A deep-red semiconductor monolithic mode-locked laser is demonstrated. Multi-section laser diodes based on an AlGaAs multi-quantum-well structure were passively mode-locked, enabling the generation of picosecond optical pulses at 752 nm, at pulse repetition rates of 19.37 GHz. An investigation of the dependence of the pulse duration as a function of reverse bias revealed a predominantly exponential decay trend of the pulse duration, varying from 10.5 ps down to 3.5 ps, which can be associated with the concomitant reduction of absorption recovery time with increasing applied field. A 30-MHz-tunability of the pulse repetition rate with bias conditions is also reported. The demonstration of such a compact, efficient and versatile ultrafast laser in this spectral region paves the way for its deployment in a wide range of applications such as biomedical microscopy, pulsed terahertz generation as well as microwave and millimeter-wave generation, with further impact on sensing, imaging and optical communications

Preliminary results from NOAMP deep drifting floats

International Nuclear Information System (INIS)

Ollitrault, M.

1989-01-01

This paper is a very brief and preliminary outline of first results obtained with deep SOFAR floats in the NOAMP area. The work is now going toward more precise statistical estimations of mean and variable currents, together with better tracking to resolve submesoscales and estimate diffusivities due to mesoscale and smaller scale motions. However the preliminary results confirm that the NOAMP region (and surroundings) has a deep mesoscale eddy field that is considerably more energetic that the mean field (r.m.s. velocities are of order 5 cm s -1 ), although both values are diminished compared to the western basin. A data report containing trajectories and statistics is scheduled to be published by IFREMER in the near future. The project main task is to especially study the dispersion of radioactive substances

Impact of the Mountain Pine Beetle on the Forest Carbon Cycle in British Columbia from 1999 TO 2008 (Invited)

Science.gov (United States)

Chen, J. M.; Czurylowicz, P.; Mo, G.; Black, T. A.

2013-12-01

The unprecedented mountain pine beetle (Dendroctonus ponderosae) (MPB) outbreak in British Columbia starting in 1998 affected about 50% of the lodgepole pine (Pinus contorta var. latifolia) forests occupying about 50% of the land area of the province. The impact of this outbreak on the C cycle is assessed in this study. Annual leaf area index (LAI) maps of the affected area from 1999 to 2008 were produced using SPOT VEGETATION data, and net ecosystem production (NEP) was modeled using inputs of LAI, land cover, soil texture and daily meteorological data with the Boreal Ecosystem Productivity Simulator (BEPS). Both LAI and NEP were validated using field measurements. LAI was found to decrease on average by 20% compared to pre-outbreak conditions, while NEP decreased on average by 90%. Annual NEP values ranged from 2.4 to -8.0 Tg C between 1999 and 2008, with the ecosystem changing from a carbon sink to a carbon source in 2000. The annual average NEP was -2.9 Tg C over the 10 years, resulting in a total loss of carbon of 29 Tg C to the atmosphere. The inter-annual variability of both LAI and NEP was characterized by substantial initial decreases followed by steady increases from 2006 to 2008 with NEP returning to near carbon neutrality in 2008 (-1.8 Pg C/y). The impact of this MPB outbreak appears to be less dramatic than previously anticipated. The apparent fast recovery of LAI and NEP after MPB attacks is examined under the framework of ecosystem resilience which was manifested in the form of secondary overstory and understory growth and increased production of non-attacked host trees.

Survey on deep learning for radiotherapy.

Science.gov (United States)

Meyer, Philippe; Noblet, Vincent; Mazzara, Christophe; Lallement, Alex

2018-05-17

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deep-Subwavelength Resolving and Manipulating of Hidden Chirality in Achiral Nanostructures.

Science.gov (United States)

Zu, Shuai; Han, Tianyang; Jiang, Meiling; Lin, Feng; Zhu, Xing; Fang, Zheyu

2018-04-24

The chiral state of light plays a vital role in light-matter interactions and the consequent revolution of nanophotonic devices and advanced modern chiroptics. As the light-matter interaction goes into the nano- and quantum world, numerous chiroptical technologies and quantum devices require precise knowledge of chiral electromagnetic modes and chiral radiative local density of states (LDOS) distributions in detail, which directly determine the chiral light-matter interaction for applications such as chiral light detection and emission. With classical optical techniques failing to directly measure the chiral radiative LDOS, deep-subwavelength imaging and control of circular polarization (CP) light associated phenomena are introduced into the agenda. Here, we simultaneously reveal the hidden chiral electromagnetic mode and acquire its chiral radiative LDOS distribution of a single symmetric nanostructure at the deep-subwavelength scale by using CP-resolved cathodoluminescence (CL) microscopy. The chirality of the symmetric nanostructure under normally incident light excitation, resulting from the interference between the symmetric and antisymmetric modes of the V-shaped nanoantenna, is hidden in the near field with a giant chiral distribution (∼99%) at the arm-ends, which enables the circularly polarized CL emission from the radiative LDOS hot-spot and the following active helicity control at the deep-subwavelength scale. The proposed V-shaped nanostructure as a functional unit is further applied to the helicity-dependent binary encoding and the two-dimensional display applications. The proposed physical principle and experimental configuration can promote the future chiral characterization and manipulation at the deep-subwavelength scale and provide direct guidelines for the optimization of chiral light-matter interactions for future quantum studies.

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

Science.gov (United States)

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.

Environmental challenges of deep water activities

International Nuclear Information System (INIS)

Sande, Arvid

1998-01-01

In this presentation there are discussed the experiences of petroleum industry, and the projects that have been conducted in connection with the planning and drilling of the first deep water wells in Norway. There are also presented views on where to put more effort in the years to come, so as to increase the knowledge of deep water areas. Attention is laid on exploration drilling as this is the only activity with environmental potential that will take place during the next five years or so. The challenges for future field developments in these water depths are briefly discussed. 7 refs

Quantitative phase microscopy using deep neural networks

Science.gov (United States)

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

2018-02-01

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

Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles

Energy Technology Data Exchange (ETDEWEB)

Callister, S.J.; Wilkins, M.J.; Nicora, C.D.; Williams, K.H.; Banfield, J.F.; VerBerkmoes, N.C.; Hettich, R.L.; NGuessan, A.L.; Mouser, P.J.; Elifantz, H.; Smith, R.D.; Lovley, D.R.; Lipton, M.S.; Long, P.E.

2010-07-15

Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetate-amended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or “pseudo-metagenomes”, for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally, a shift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.

Post-drilling changes in seabed landscape and megabenthos in a deep-sea hydrothermal system, the Iheya North field, Okinawa Trough.

Science.gov (United States)

Nakajima, Ryota; Yamamoto, Hiroyuki; Kawagucci, Shinsuke; Takaya, Yutaro; Nozaki, Tatsuo; Chen, Chong; Fujikura, Katsunori; Miwa, Tetsuya; Takai, Ken

2015-01-01

There has been an increasing interest in seafloor exploitation such as mineral mining in deep-sea hydrothermal fields, but the environmental impact of anthropogenic disturbance to the seafloor is poorly known. In this study, the effect of such anthropogenic disturbance by scientific drilling operations (IODP Expedition 331) on seabed landscape and megafaunal habitation was surveyed for over 3 years using remotely operated vehicle video observation in a deep-sea hydrothermal field, the Iheya North field, in the Okinawa Trough. We focused on observations from a particular drilling site (Site C0014) where the most dynamic change of landscape and megafaunal habitation was observed among the drilling sites of IODP Exp. 331. No visible hydrothermal fluid discharge had been observed at the sedimentary seafloor at Site C0014, where Calyptogena clam colonies were known for more than 10 years, before the drilling event. After drilling commenced, the original Calyptogena colonies were completely buried by the drilling deposits. Several months after the drilling, diffusing high-temperature hydrothermal fluid began to discharge from the sedimentary subseafloor in the area of over 20 m from the drill holes, 'artificially' creating a new hydrothermal vent habitat. Widespread microbial mats developed on the seafloor with the diffusing hydrothermal fluids and the galatheid crab Shinkaia crosnieri endemic to vents dominated the new vent community. The previously soft, sedimentary seafloor was hardened probably due to barite/gypsum mineralization or silicification, becoming rough and undulated with many fissures after the drilling operation. Although the effects of the drilling operation on seabed landscape and megafaunal composition are probably confined to an area of maximally 30 m from the drill holes, the newly established hydrothermal vent ecosystem has already lasted 2 years and is like to continue to exist until the fluid discharge ceases and thus the ecosystem in the area has

Deep Learning: A Primer for Radiologists.

Science.gov (United States)

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz

Directory of Open Access Journals (Sweden)

Julie A. Onton

2018-05-01

Full Text Available Veterans with posttraumatic stress disorder (PTSD often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG with concurrent collection of electrodermal activity (EDA and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1–3 Hz, Lo Deep (<1 Hz, and rapid eye movement (REM sleep stages, as well as sleep efficiency and fragmentation. The results showed a significant tendency for PTSD sleepers to spend a smaller percentage of the night in REM (p < 0.0001 and Lo Deep (p = 0.001 sleep, while spending a larger percentage of the night in Hi Deep (p < 0.0001 sleep. The percentage of combined Hi+Lo Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs (p < 0.02, while decreased Lo Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study (p < 0.005. Linear regression models with only the PTSD group showed that decreased REM correlated with self-reported depression, as measured with the Depression, Anxiety, and Stress Scales (DASS; p < 0.00001. DASS anxiety was associated with increased REM time (p < 0.0001. This study shows altered sleep patterns in sleepers with PTSD that can be partially accounted

Gene expression in the deep biosphere.

Science.gov (United States)

Orsi, William D; Edgcomb, Virginia P; Christman, Glenn D; Biddle, Jennifer F

2013-07-11

Scientific ocean drilling has revealed a deep biosphere of widespread microbial life in sub-seafloor sediment. Microbial metabolism in the marine subsurface probably has an important role in global biogeochemical cycles, but deep biosphere activities are not well understood. Here we describe and analyse the first sub-seafloor metatranscriptomes from anaerobic Peru Margin sediment up to 159 metres below the sea floor, represented by over 1 billion complementary DNA (cDNA) sequence reads. Anaerobic metabolism of amino acids, carbohydrates and lipids seem to be the dominant metabolic processes, and profiles of dissimilatory sulfite reductase (dsr) transcripts are consistent with pore-water sulphate concentration profiles. Moreover, transcripts involved in cell division increase as a function of microbial cell concentration, indicating that increases in sub-seafloor microbial abundance are a function of cell division across all three domains of life. These data support calculations and models of sub-seafloor microbial metabolism and represent the first holistic picture of deep biosphere activities.

Opportunities and obstacles for deep learning in biology and medicine

Science.gov (United States)

2018-01-01

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

Opportunities and obstacles for deep learning in biology and medicine.

Science.gov (United States)

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

2018-04-01

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

North Jamaican Deep Fore-Reef Sponges

NARCIS (Netherlands)

Lehnert, Helmut; Soest, van R.W.M.

1996-01-01

An unexpectedly high amount of new species, revealed within only one hour of summarized bottom time, leads to the conclusion that the sponge fauna of the steep slopes of the deep fore-reef is still largely unknown. Four mixed gas dives at depths between 70 and 90 m, performed in May and June, 1993,

Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE

DEFF Research Database (Denmark)

Valen, Eivind; Pascarella, Giovanni; Chalk, Alistair

2009-01-01

in a given tissue. Here, we present a new method for high-throughput sequencing of 5' cDNA tags-DeepCAGE: merging the Cap Analysis of Gene Expression method with ultra-high-throughput sequence technology. We apply DeepCAGE to characterize 1.4 million sequenced TSS from mouse hippocampus and reveal a wealth...

Stability of deep features across CT scanners and field of view using a physical phantom

Science.gov (United States)

Paul, Rahul; Shafiq-ul-Hassan, Muhammad; Moros, Eduardo G.; Gillies, Robert J.; Hall, Lawrence O.; Goldgof, Dmitry B.

2018-02-01

Radiomics is the process of analyzing radiological images by extracting quantitative features for monitoring and diagnosis of various cancers. Analyzing images acquired from different medical centers is confounded by many choices in acquisition, reconstruction parameters and differences among device manufacturers. Consequently, scanning the same patient or phantom using various acquisition/reconstruction parameters as well as different scanners may result in different feature values. To further evaluate this issue, in this study, CT images from a physical radiomic phantom were used. Recent studies showed that some quantitative features were dependent on voxel size and that this dependency could be reduced or removed by the appropriate normalization factor. Deep features extracted from a convolutional neural network, may also provide additional features for image analysis. Using a transfer learning approach, we obtained deep features from three convolutional neural networks pre-trained on color camera images. An we examination of the dependency of deep features on image pixel size was done. We found that some deep features were pixel size dependent, and to remove this dependency we proposed two effective normalization approaches. For analyzing the effects of normalization, a threshold has been used based on the calculated standard deviation and average distance from a best fit horizontal line among the features' underlying pixel size before and after normalization. The inter and intra scanner dependency of deep features has also been evaluated.

A Human Open Field Test Reveals Thigmotaxis Related to Agoraphobic Fear.

Science.gov (United States)

Walz, Nora; Mühlberger, Andreas; Pauli, Paul

2016-09-01

Thigmotaxis refers to a specific behavior of animals (i.e., to stay close to walls when exploring an open space). Such behavior can be assessed with the open field test (OFT), which is a well-established indicator of animal fear. The detection of similar open field behavior in humans may verify the translational validity of this paradigm. Enhanced thigmotaxis related to anxiety may suggest the relevance of such behavior for anxiety disorders, especially agoraphobia. A global positioning system was used to analyze the behavior of 16 patients with agoraphobia and 18 healthy individuals with a risk for agoraphobia (i.e., high anxiety sensitivity) during a human OFT and compare it with appropriate control groups (n = 16 and n = 19). We also tracked 17 patients with agoraphobia and 17 control participants during a city walk that involved walking through an open market square. Our human OFT triggered thigmotaxis in participants; patients with agoraphobia and participants with high anxiety sensitivity exhibited enhanced thigmotaxis. This behavior was evident in increased movement lengths along the wall of the natural open field and fewer entries into the center of the field despite normal movement speed and length. Furthermore, participants avoided passing through the market square during the city walk, indicating again that thigmotaxis is related to agoraphobia. This study is the first to our knowledge to verify the translational validity of the OFT and to reveal that thigmotaxis, an evolutionarily adaptive behavior shown by most species, is related to agoraphobia, a pathologic fear of open spaces, and anxiety sensitivity, a risk factor for agoraphobia. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Deep inelastic scattering

International Nuclear Information System (INIS)

Zakharov, V.I.

1977-01-01

The present status of the quark-parton-gluon picture of deep inelastic scattering is reviewed. The general framework is mostly theoretical and covers investigations since 1970. Predictions of the parton model and of the asymptotically free field theories are compared with experimental data available. The valence quark approximation is concluded to be valid in most cases, but fails to account for the data on the total momentum transfer. On the basis of gluon corrections introduced to the parton model certain predictions concerning both the deep inelastic structure functions and form factors are made. The contributions of gluon exchanges and gluon bremsstrahlung are highlighted. Asymptotic freedom is concluded to be very attractive and provide qualitative explanation to some experimental observations (scaling violations, breaking of the Drell-Yan-West type relations). Lepton-nuclear scattering is pointed out to be helpful in probing the nature of nuclear forces and studying the space-time picture of the parton model

In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz.

Science.gov (United States)

Onton, Julie A; Matthews, Scott C; Kang, Dae Y; Coleman, Todd P

2018-01-01

Veterans with posttraumatic stress disorder (PTSD) often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG) with concurrent collection of electrodermal activity (EDA) and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1-3 Hz), Lo Deep (spend a smaller percentage of the night in REM ( p spending a larger percentage of the night in Hi Deep ( p < 0.0001) sleep. The percentage of combined Hi+Lo Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs ( p < 0.02), while decreased Lo Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study ( p < 0.005). Linear regression models with only the PTSD group showed that decreased REM correlated with self-reported depression, as measured with the Depression, Anxiety, and Stress Scales (DASS; p < 0.00001). DASS anxiety was associated with increased REM time ( p < 0.0001). This study shows altered sleep patterns in sleepers with PTSD that can be partially accounted for by age and medication use; however, differences in deep sleep related to PTSD could not be linked to any known factor. With several medications [prazosin, selective serotonin reuptake inhibitors (SSRIs

ModelHub: Towards Unified Data and Lifecycle Management for Deep Learning

OpenAIRE

Miao, Hui; Li, Ang; Davis, Larry S.; Deshpande, Amol

2016-01-01

Deep learning has improved state-of-the-art results in many important fields, and has been the subject of much research in recent years, leading to the development of several systems for facilitating deep learning. Current systems, however, mainly focus on model building and training phases, while the issues of data management, model sharing, and lifecycle management are largely ignored. Deep learning modeling lifecycle generates a rich set of data artifacts, such as learned parameters and tr...

A search for planetary eclipses of white dwarfs in the Pan-STARRS1 medium-deep fields

Energy Technology Data Exchange (ETDEWEB)

Fulton, B. J.; Tonry, J. L.; Flewelling, H.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Huber, M. E.; Kaiser, N.; Wainscoat, R. J.; Waters, C. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States)

2014-12-01

We present a search for eclipses of ∼1700 white dwarfs (WDs) in the Pan-STARRS1 medium-deep fields. Candidate eclipse events are selected by identifying low outliers in over 4.3 million light curve measurements. We find no short-duration eclipses consistent with being caused by a planetary size companion. This large data set enables us to place strong constraints on the close-in planet occurrence rates around WDs for planets as small as 2 R {sub ⊕}. Our results indicate that gas giant planets orbiting just outside the Roche limit are rare, occurring around less than 0.5% of WDs. Habitable-zone super-Earths and hot super-Earths are less abundant than similar classes of planets around main-sequence stars. These constraints provide important insight into the ultimate fate of the large population of exoplanets orbiting main-sequence stars.

Permeability in fractured rocks from deep geothermal boreholes in the Upper Rhine Graben

Science.gov (United States)

Vidal, Jeanne; Whitechurch, Hubert; Genter, Albert; Schmittbuhl, Jean; Baujard, Clément

2015-04-01

Permeability in fractured rocks from deep geothermal boreholes in the Upper Rhine Graben Vidal J.1, Whitechurch H.1, Genter A.2, Schmittbuhl J.1, Baujard C.2 1 EOST, Université de Strasbourg 2 ES-Géothermie, Strasbourg The thermal regime of the Upper Rhine Graben (URG) is characterized by a series of geothermal anomalies on its French part near Soultz-sous-Forêts, Rittershoffen and in the surrounding area of Strasbourg. Sedimentary formations of these areas host oil field widely exploited in the past which exhibit exceptionally high temperature gradients. Thus, geothermal anomalies are superimposed to the oil fields which are interpreted as natural brine advection occurring inside a nearly vertical multi-scale fracture system cross-cutting both deep-seated Triassic sediments and Paleozoic crystalline basement. The sediments-basement interface is therefore very challenging for geothermal industry because most of the geothermal resource is trapped there within natural fractures. Several deep geothermal projects exploit local geothermal energy to use the heat or produce electricity and thus target permeable fractured rocks at this interface. In 1980, a geothermal exploration well was drilled close to Strasbourg down to the Permian sediments at 3220 m depth. Bottom hole temperature was estimated to 148°C but the natural flow rate was too low for an economic profitability (geothermal site by drilling five boreholes, three of which extend to 5 km depth. They identified a temperature of 200° C at 5 km depth in the granitic basement but with a variable flow rate. Hydraulic and chemical stimulation operations were applied in order to increase the initial low permeability by reactivating and dissolving sealed fractures in basement. The productivity was considerably improved and allows geothermal exploitation at 165° C and 20 L/s. Recent studies revealed the occurrences of permeable fractures in the limestones of Muschelkalk and the sandstones of Buntsandstein also. For

The Deep-Sea Microbial Community from the Amazonian Basin Associated with Oil Degradation.

Science.gov (United States)

Campeão, Mariana E; Reis, Luciana; Leomil, Luciana; de Oliveira, Louisi; Otsuki, Koko; Gardinali, Piero; Pelz, Oliver; Valle, Rogerio; Thompson, Fabiano L; Thompson, Cristiane C

2017-01-01

One consequence of oil production is the possibility of unplanned accidental oil spills; therefore, it is important to evaluate the potential of indigenous microorganisms (both prokaryotes and eukaryotes) from different oceanic basins to degrade oil. The aim of this study was to characterize the microbial response during the biodegradation process of Brazilian crude oil, both with and without the addition of the dispersant Corexit 9500, using deep-sea water samples from the Amazon equatorial margin basins, Foz do Amazonas and Barreirinhas, in the dark and at low temperatures (4°C). We collected deep-sea samples in the field (about 2570 m below the sea surface), transported the samples back to the laboratory under controlled environmental conditions (5°C in the dark) and subsequently performed two laboratory biodegradation experiments that used metagenomics supported by classical microbiological methods and chemical analysis to elucidate both taxonomic and functional microbial diversity. We also analyzed several physical-chemical and biological parameters related to oil biodegradation. The concomitant depletion of dissolved oxygen levels, oil droplet density characteristic to oil biodegradation, and BTEX concentration with an increase in microbial counts revealed that oil can be degraded by the autochthonous deep-sea microbial communities. Indigenous bacteria (e.g., Alteromonadaceae, Colwelliaceae , and Alcanivoracaceae ), archaea (e.g., Halobacteriaceae, Desulfurococcaceae , and Methanobacteriaceae ), and eukaryotic microbes (e.g., Microsporidia, Ascomycota, and Basidiomycota) from the Amazonian margin deep-sea water were involved in biodegradation of Brazilian crude oil within less than 48-days in both treatments, with and without dispersant, possibly transforming oil into microbial biomass that may fuel the marine food web.

Deep learning methods for protein torsion angle prediction.

Science.gov (United States)

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.

Revealing Buried Interfaces to Understand the Origins of Threshold Voltage Shifts in Organic Field-Effect Transistors

NARCIS (Netherlands)

Mathijssen, Simon G. J.; Spijkman, Mark-Jan; Andringa, Anne-Marije; van Hal, Paul A.; McCulloch, Iain; Kemerink, Martijn; Janssen, Rene A. J.; de Leeuw, Dago M.

2010-01-01

The semiconductor of an organic field-effect transistor is stripped with adhesive tape, yielding an exposed gate dielectric, accessible for various characterization techniques. By using scanning Kelvin probe microscopy we reveal that trapped charges after gate bias stress are located at the gate

Magnetotelluric images of deep crustal structure of the Rehai geothermal field near Tengchong, southern China

Science.gov (United States)

Bai, Denghai; Meju, Maxwell A.; Liao, Zhijie

2001-12-01

Broadband (0.004-4096s) magnetotelluric (MT) soundings have been applied to the determination of the deep structure across the Rehai geothermal field in a Quaternary volcanic area near the Indo-Eurasian collisional margin. Tensorial analysis of the data show evidence of weak to strong 3-D effects but for approximate 2-D imaging, we obtained dual-mode MT responses for an assumed strike direction coincident with the trend of the regional-scale faults and with the principal impedance azimuth at long periods. The data were subsequently inverted using different approaches. The rapid relaxation inversion models are comparable to the sections constructed from depth-converted invariant impedance phase data. The results from full-domain 2-D conjugate-gradient inversion with different initial models are concordant and evoke a picture of a dome-like structure consisting of a conductive (50-1000 Ωm) cap which is about 5-6km thick in the central part of the known geothermal field and thickens outwards to about 15-20km. The anomalous structure rests on a mid-crustal zone of 20-30 Ωm resistivity extending down to about 25km depth where there appears to be a moderately resistive (>30 Ωm) substratum. The MT images are shown to be in accord with published geological, isotopic and geochemical results that suggested the presence of a magma body underneath the area of study.

The dynamics of biogeographic ranges in the deep sea.

Science.gov (United States)

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.

Meta-analysis of expression and function of neprilysin in Alzheimer's disease.

Science.gov (United States)

Zhang, Huifeng; Liu, Dan; Wang, Yixing; Huang, Huanhuan; Zhao, Yujia; Zhou, Hui

2017-09-14

Neprilysin (NEP) is one of the most important Aβ-degrading enzymes, and its expression and activity in Alzheimer's brain have been widely reported, but the results remain debatable. Thus, the meta-analysis was performed to elucidate the role of NEP in Alzheimer's disease (AD). The relevant case-control or cohort studies were retrieved according to our inclusion/exclusion criteria. Six studies with 123 controls and 141 AD cases, seven studies with 102 controls and 90 AD cases, and four studies with 93 controls and 132 AD cases were included in meta-analysis of NEP's protein, mRNA, and enzyme activity respectively. We conducted Meta regression to detect the sources of heterogeneity and further performed cumulative meta-analysis or subgroup analysis. Our meta-analysis revealed a significantly lower level of NEP mRNA (SMD=-0.44, 95%CI: -0.87, -0.00, p=0.049) in AD cases than in non-AD cases, and such pattern was not altered over time in the cumulative meta-analysis. However, the decrease of NEP protein (SMD=-0.18, 95%CI: -0.62, 0.25) and enzyme activity (SMD=-0.35, 95%CI: -1.03, 0.32) in AD cases did not pass the significance check, while the cumulative meta-analysis by average age showed the pooled effect became insignificant as adding the studies with younger subjects, which indicates that the protein expression and enzyme activity of NEP in the cortex are affected by age. Therefore, the present meta-analysis suggests the need of further investigation of roles of NEP in AD pathogenesis and treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2017-01-01

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

Deep Echo State Network (DeepESN): A Brief Survey

OpenAIRE

Gallicchio, Claudio; Micheli, Alessio

2017-01-01

The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced deep Echo State Network (deepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of deepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions ...

Deep inelastic scattering in spontaneously broken gauge models

International Nuclear Information System (INIS)

Goloskokov, S.V.; Mikhov, S.G.; Morozov, P.T.; Stamenov, D.B.

1975-01-01

Deep inelastic lepton hadron scattering in the simplest spontaneously broken symmetry (the Kibble model) is analyzed. A hypothesis that the invariant coupling constant of the quartic selfinteraction for large spacelike momenta tends to a finite asymptotic value without spoiling the asymptotic freedom for the invariant coupling constant of the Yang-Mills field is used. It is shown that Biorken scaling for the moments of the structure functions of the deep inelastic lepton hadron scattering is violated by powers of logarithms

Deep learning—Accelerating Next Generation Performance Analysis Systems?

Directory of Open Access Journals (Sweden)

Heike Brock

2018-02-01

Full Text Available Deep neural network architectures show superior performance in recognition and prediction tasks of the image, speech and natural language domains. The success of such multi-layered networks encourages their implementation in further application scenarios as the retrieval of relevant motion information for performance enhancement in sports. However, to date deep learning is only seldom applied to activity recognition problems of the human motion domain. Therefore, its use for sports data analysis might remain abstract to many practitioners. This paper provides a survey on recent works in the field of high-performance motion data and examines relevant technologies for subsequent deployment in real training systems. In particular, it discusses aspects of data acquisition, processing and network modeling. Analysis suggests the advantage of deep neural networks under difficult and noisy data conditions. However, further research is necessary to confirm the benefit of deep learning for next generation performance analysis systems.

Assessment of deep geological environment condition

International Nuclear Information System (INIS)

Bae, Dae Seok; Han, Kyung Won; Joen, Kwan Sik

2003-05-01

The main tasks of geoscientific study in the 2nd stage was characterized focusing mainly on a near-field condition of deep geologic environment, and aimed to generate the geologic input data for a Korean reference disposal system for high level radioactive wastes and to establish site characterization methodology, including neotectonic features, fracture systems and mechanical properties of plutonic rocks, and hydrogeochemical characteristics. The preliminary assessment of neotectonics in the Korean peninsula was performed on the basis of seismicity recorded, Quarternary faults investigated, uplift characteristics studied on limited areas, distribution of the major regional faults and their characteristics. The local fracture system was studied in detail from the data obtained from deep boreholes in granitic terrain. Through this deep drilling project, the geometrical and hydraulic properties of different fracture sets are statistically analysed on a block scale. The mechanical properties of intact rocks were evaluated from the core samples by laboratory testing and the in-situ stress conditions were estimated by a hydro fracturing test in the boreholes. The hydrogeochemical conditions in the deep boreholes were characterized based on hydrochemical composition and isotopic signatures and were attempted to assess the interrelation with a major fracture system. The residence time of deep groundwater was estimated by C-14 dating. For the travel time of groundwater between the boreholes, the methodology and equipment for tracer test were established

Understanding a Deep Learning Technique through a Neuromorphic System a Case Study with SpiNNaker Neuromorphic Platform

OpenAIRE

Sugiarto Indar; Pasila Felix

2018-01-01

Deep learning (DL) has been considered as a breakthrough technique in the field of artificial intelligence and machine learning. Conceptually, it relies on a many-layer network that exhibits a hierarchically non-linear processing capability. Some DL architectures such as deep neural networks, deep belief networks and recurrent neural networks have been developed and applied to many fields with incredible results, even comparable to human intelligence. However, many researchers are still scept...

Field-reversed bubble in deep plasma channels for high quality electron acceleration

CERN Document Server

Pukhov, A; Tueckmantel, T; Thomas, J; Yu, I; Kostyukov, Yu

2014-01-01

We study hollow plasma channels with smooth boundaries for laser-driven electron acceleration in the bubble regime. Contrary to the uniform plasma case, the laser forms no optical shock and no etching at the front. This increases the effective bubble phase velocity and energy gain. The longitudinal field has a plateau that allows for mono-energetic acceleration. We observe as low as 10−3 r.m.s. relative witness beam energy uncertainty in each cross-section and 0.3% total energy spread. By varying plasma density profile inside a deep channel, the bubble fields can be adjusted to balance the laser depletion and dephasing lengths. Bubble scaling laws for the deep channel are derived. Ultra-short pancake-like laser pulses lead to the highest energies of accelerated electrons per Joule of laser pulse energy.

Large-eddy simulation of maritime deep tropical convection

Directory of Open Access Journals (Sweden)

Peter A Bogenschutz

2009-12-01

Full Text Available This study represents an attempt to apply Large-Eddy Simulation (LES resolution to simulate deep tropical convection in near equilibrium for 24 hours over an area of about 205 x 205 km2, which is comparable to that of a typical horizontal grid cell in a global climate model. The simulation is driven by large-scale thermodynamic tendencies derived from mean conditions during the GATE Phase III field experiment. The LES uses 2048 x 2048 x 256 grid points with horizontal grid spacing of 100 m and vertical grid spacing ranging from 50 m in the boundary layer to 100 m in the free troposphere. The simulation reaches a near equilibrium deep convection regime in 12 hours. The simulated vertical cloud distribution exhibits a trimodal vertical distribution of deep, middle and shallow clouds similar to that often observed in Tropics. A sensitivity experiment in which cold pools are suppressed by switching off the evaporation of precipitation results in much lower amounts of shallow and congestus clouds. Unlike the benchmark LES where the new deep clouds tend to appear along the edges of spreading cold pools, the deep clouds in the no-cold-pool experiment tend to reappear at the sites of the previous deep clouds and tend to be surrounded by extensive areas of sporadic shallow clouds. The vertical velocity statistics of updraft and downdraft cores below 6 km height are compared to aircraft observations made during GATE. The comparison shows generally good agreement, and strongly suggests that the LES simulation can be used as a benchmark to represent the dynamics of tropical deep convection on scales ranging from large turbulent eddies to mesoscale convective systems. The effect of horizontal grid resolution is examined by running the same case with progressively larger grid sizes of 200, 400, 800, and 1600 m. These runs show a reasonable agreement with the benchmark LES in statistics such as convective available potential energy, convective inhibition

Los Alamos NEP research in advanced plasma thrusters

Science.gov (United States)

Schoenberg, Kurt; Gerwin, Richard

1991-01-01

Research was initiated in advanced plasma thrusters that capitalizes on lab capabilities in plasma science and technology. The goal of the program was to examine the scaling issues of magnetoplasmadynamic (MPD) thruster performance in support of NASA's MPD thruster development program. The objective was to address multi-megawatt, large scale, quasi-steady state MPD thruster performance. Results to date include a new quasi-steady state operating regime which was obtained at space exploration initiative relevant power levels, that enables direct coaxial gun-MPD comparisons of thruster physics and performance. The radiative losses are neglible. Operation with an applied axial magnetic field shows the same operational stability and exhaust plume uniformity benefits seen in MPD thrusters. Observed gun impedance is in close agreement with the magnetic Bernoulli model predictions. Spatial and temporal measurements of magnetic field, electric field, plasma density, electron temperature, and ion/neutral energy distribution are underway. Model applications to advanced mission logistics are also underway.

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

Science.gov (United States)

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

2017-09-05

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

MOBIUS-STRIP-LIKE COLUMNAR FUNCTIONAL CONNECTIONS ARE REVEALED IN SOMATO-SENSORY RECEPTIVE FIELD CENTROIDS.

Directory of Open Access Journals (Sweden)

James Joseph Wright

2014-10-01

Full Text Available Receptive fields of neurons in the forelimb region of areas 3b and 1 of primary somatosensory cortex, in cats and monkeys, were mapped using extracellular recordings obtained sequentially from nearly radial penetrations. Locations of the field centroids indicated the presence of a functional system, in which cortical homotypic representations of the limb surfaces are entwined in three-dimensional Mobius-strip-like patterns of synaptic connections. Boundaries of somatosensory receptive field in nested groups irregularly overlie the centroid order, and are interpreted as arising from the superposition of learned connections upon the embryonic order. Since the theory of embryonic synaptic self-organisation used to model these results was devised and earlier used to explain findings in primary visual cortex, the present findings suggest the theory may be of general application throughout cortex, and may reveal a modular functional synaptic system, which, only in some parts of the cortex, and in some species, is manifest as anatomical ordering into columns.

Uranium-thorium series radionuclides in brines and reservoir rocks from two deep geothermal boreholes in the Salton Sea geothermal field, southeastern California

International Nuclear Information System (INIS)

Zukin, J.G.; Hammond, D.E.; Ku, Tehlung; Elders, W.A.

1987-01-01

Naturally occurring U and Th series radionuclides have been analyzed in high temperature brines (∼ 300 degree C, 25 wt% dissolved solids) and associated rocks from two deep geothermal wells located on the northeastern margin of the Salton Sea Geothermal Field (SSGF). These data are part of a study of the SSGF as a natural analog of possible radionuclide behavior near a nuclear waste repository constructed in salt beds, and permit evaluation of some characteristics of water-rock interaction in the SSGF

Supercement for Annular Seal and Long-Term Integrity in Deep, Hot Wells "DeepTrek"

Energy Technology Data Exchange (ETDEWEB)

CSI Technologies

2007-08-31

The purpose of this project is to formulate a 'Supercement' designed for improving the long-term sealing integrity in HPHT wells. Phase I concentrated on chemistry studies and screening tests to design and evaluate Portland-based, hybrid Portland, and non-Portland-based cement systems suitable for further scale-up testing. Phase II work concentrated on additional lab and field testing to reduce the candidate materials list to two systems, as well as scaleup activities aimed at verifying performance at the field scale. Phase II was extended thorough a proposal to develop additional testing capabilities aimed at quantifying cementing material properties and performance that were previously not possible. Phase III focused on bringing the material(s) developed in previous Phases to commercialization, through Field Trials, Cost/Benefit Analysis, and Technology Transfer. Extensive development and testing work throughout the project led to Phase III commercialization of two very different materials: (1) Highly-expansive cement (Portland-based), patent pending as 'PRESTRESSED CEMENT'; and (2) Epoxy Resin (non-Portland-based), patent pending. Trade name is Ultra Seal-R. In Phase III, work concentrated on application of the Supercement materials in various increasingly-challenging wells. Previous testing revealed that PRESTRESSED CEMENT, when applied in weak or unconsolidated formations, tends to expand away from the central pipe, restricting the applicability of this material to competent formations. Tests were devised to quantify this effect so the material could be applied in appropriate wells. Additionally, the testing was needed because of industry resistance to expansive cements, due to previous marketing attempts with other materials that were less than successful. Field trials with the Epoxy Resin currently numbers in the hundreds of jobs at up to 295 deg F, with a large percentage being completely successful. Both the PRESTRESSED CEMENT as well

Deep learning for studies of galaxy morphology

Science.gov (United States)

Tuccillo, D.; Huertas-Company, M.; Decencière, E.; Velasco-Forero, S.

2017-06-01

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

Occipital deep white matter hyperintensity as seen by MRI, 1

International Nuclear Information System (INIS)

Miyazaki, Masahito; Hashimoto, Toshiaki; Tayama, Masanobu; Kuroda, Yasuhiro

1992-01-01

Magnetic resonance imaging was performed in 270 patients with various neurologic complaints (1-15Y) with a 0.5 tesla superconducting imaging system using a field echo T1-weighted sequence and spin echo T2-weighted and PD-weighted sequences. Twenty-seven of them had deep white matter hyperintensity (DWMH) in the occipital lobe on T2-weighted images. The frequency of mild DWMH differed in different age groups, suggesting that mild DWMH may result from delayed myelination in the central nervous system. However, the frequency of severe DWMH, which was revealed as isointense relative to cerebrospinal fluid, did not differ in different age groups and it was significantly more common in severely retarded patients. Classification of DWMH based on the signal intensity is valuable to distinguish white matter abnormalities in the occipital lobe from delayed myelination in the same site. (author)

Characterization of majority and minority carrier deep levels in p-type GaN:Mg grown by molecular beam epitaxy using deep level optical spectroscopy

International Nuclear Information System (INIS)

Armstrong, A.; Caudill, J.; Ringel, S. A.; Corrion, A.; Poblenz, C.; Mishra, U. K.; Speck, J. S.

2008-01-01

Deep level defects in p-type GaN:Mg grown by molecular beam epitaxy were characterized using steady-state photocapacitance and deep level optical spectroscopy (DLOS). Low frequency capacitance measurements were used to alleviate dispersion effects stemming from the deep Mg acceptor. Use of DLOS enabled a quantitative survey of both deep acceptor and deep donor levels, the latter being particularly important due to the limited understanding of minority carrier states for p-type GaN. Simultaneous electron and hole photoemissions resulted in a convoluted deep level spectrum that was decoupled by emphasizing either majority or minority carrier optical emission through control of the thermal filling time conditions. In this manner, DLOS was able to resolve and quantify the properties of deep levels residing near both the conduction and valence bandedges in the same sample. Bandgap states through hole photoemission were observed at E v +3.05 eV, E v +3.22 eV and E v +3.26 eV. Additionally, DLOS revealed levels at E c -3.24 eV and E c -2.97 eV through electron emission to the conduction band with the former attributed to the Mg acceptor itself. The detected deep donor concentration is less than 2% of activated [Mg] and demonstrates the excellent quality of the film

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

Science.gov (United States)

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

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

Science.gov (United States)

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

2017-12-01

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

Deep Visual Attention Prediction

Science.gov (United States)

Wang, Wenguan; Shen, Jianbing

2018-05-01

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

Succeeding in deep water by combining technology qualification and production forecasting

Energy Technology Data Exchange (ETDEWEB)

Hussain, A.; Oiungen, B.; Raposo, C. [Det Norske Veritas (DNV), Rio de Janeiro, RJ (Brazil)

2008-07-01

All the easy oil and gas is gone, and, as a result the Oil and Gas industry is continuously targeting deeper and more remote fields. The exploration and development of deep water oil and gas fields is associated with enormous costs and multiple uncertainties with regard to equipment reliability and performance. Proper risk management can be used to evaluate the impact of these uncertainties thereby helping to ensure optimal business performance of the future assets, as well as helping the decision maker target investment towards areas where the financial impact will be the greatest. This paper reviews the principles of Technology Qualification and Production Forecasting methodology, both of which are risk management solutions with a proven track record for deep water field developments. (author)

30 CFR 203.71 - How does MMS allocate a field's suspension volume between my lease and other leases on my field?

Science.gov (United States)

2010-07-01

... RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Pre-Act Deep Water Leases and for Development... or post-November 2000 deep water lease to your field after we approve your application We will not..., or the minimum suspension volume of the authorized field, whichever is greater (i) You toll the time...

Dalia integrated production bundle (IPB): an innovative riser solution for deep water fields

Energy Technology Data Exchange (ETDEWEB)

Reals, Th Boscals de; Gloaguen, M.; Roche, F. [Total E and P (Angola); Marion, A.; Poincheval, A. [Technip, Paris (France)

2008-07-01

The Dalia field is located 210 km north west of Luanda (Angola), about 140 km from shore in 1400 meter water-depth. It was the second major discovery out of 15 made in the block 17 operated by Total. The Dalia Umbilical, Flow lines and Risers EPCI Contract was awarded in 2003. The sea-line network to connect and control the 71 wells and 9 manifolds consist of the following: 40 km of insulated pipe in pipe (12 inches into 17 inches) production flow lines; 45 km of 12 inches water and gas injection lines; 6 off 1.7 km flexible water and gas injection risers; 8 off 1.65 km flexible Integrated Production Bundle (IPB) risers; 75 km of control umbilicals. The flow assurance and associated insulation requirement of the production transport system was one of the main challenges of the project. With a crude temperature of 45 deg C at the wellhead and the required minimum temperature of 35 deg C on arrival at the FPSO, this problem was complex. Understanding that, due to the Joule Thompson effect of the riser gas lift, a 'built in' loss of about 5 deg C is induced and together with further losses through the sub sea pipelines, some up to 6 km long, the agreed solution was 'pipe in pipe' for the production flow lines. The innovative flexible IPB riser, incorporating gas lift and heating to keep the fluid temperature above hydrate formation zone, was the selected riser solution. The IPB is new technology for deep water, developed by Technip for Dalia, and consists of a 12 inches nominal central flexible, surrounded by layers of heat tracing cables, small bore gas lift lines, optical fibres and many insulation layers with an Overall Heat Transfer Coefficient of approximately 3,4 W/m{sup 2}K. After an earlier research and development programme, a further extensive qualification programme was conducted during the course of the project, culminating with the deep water testing phase offshore Brazil. The IPB was then approved for fabrication and installation

Quantum dot-based local field imaging reveals plasmon-based interferometric logic in silver nanowire networks.

Science.gov (United States)

Wei, Hong; Li, Zhipeng; Tian, Xiaorui; Wang, Zhuoxian; Cong, Fengzi; Liu, Ning; Zhang, Shunping; Nordlander, Peter; Halas, Naomi J; Xu, Hongxing

2011-02-09

We show that the local electric field distribution of propagating plasmons along silver nanowires can be imaged by coating the nanowires with a layer of quantum dots, held off the surface of the nanowire by a nanoscale dielectric spacer layer. In simple networks of silver nanowires with two optical inputs, control of the optical polarization and phase of the input fields directs the guided waves to a specific nanowire output. The QD-luminescent images of these structures reveal that a complete family of phase-dependent, interferometric logic functions can be performed on these simple networks. These results show the potential for plasmonic waveguides to support compact interferometric logic operations.

Why & When Deep Learning Works: Looking Inside Deep Learnings

OpenAIRE

Ronen, Ronny

2017-01-01

The Intel Collaborative Research Institute for Computational Intelligence (ICRI-CI) has been heavily supporting Machine Learning and Deep Learning research from its foundation in 2012. We have asked six leading ICRI-CI Deep Learning researchers to address the challenge of "Why & When Deep Learning works", with the goal of looking inside Deep Learning, providing insights on how deep networks function, and uncovering key observations on their expressiveness, limitations, and potential. The outp...

A new procedure for deep sea mining tailings disposal

OpenAIRE

Ma, W.; Schott, D.L.; Lodewijks, G.

2017-01-01

Deep sea mining tailings disposal is a new environmental challenge related to water pollution, mineral crust waste handling, and ocean biology. The objective of this paper is to propose a new tailings disposal procedure for the deep sea mining industry. Through comparisons of the tailings disposal methods which exist in on-land mining and the coastal mining fields, a new tailings disposal procedure, i.e., the submarine–backfill–dam–reuse (SBDR) tailings disposal procedure, is proposed. It com...

DeepBlow - a Lagrangian plume model for deep water blowouts

International Nuclear Information System (INIS)

Johansen, Oeistein

2000-01-01

This paper presents a sub-sea blowout model designed with special emphasis on deep-water conditions. The model is an integral plume model based on a Lagrangian concept. This concept is applied to multiphase discharges in the formation of water, oil and gas in a stratified water column with variable currents. The gas may be converted to hydrate in combination with seawater, dissolved into the plume water, or leaking out of the plume due to the slip between rising gas bubbles and the plume trajectory. Non-ideal behaviour of the gas is accounted for by the introduction of pressure- and temperature-dependent compressibility z-factor in the equation of state. A number of case studies are presented in the paper. One of the cases (blowout from 100 m depth) is compared with observations from a field experiment conducted in Norwegian waters in June 1996. The model results are found to compare favourably with the field observations when dissolution of gas into seawater is accounted in the model. For discharges at intermediate to shallow depths (100-250 m), the two major processes limiting plume rise will be: (a) dissolution of gas into ambient water, or (b) bubbles rising out of the inclined plume. These processes tend to be self-enforcing, i.e., when a gas is lost by either of these processes, plume rise tends to slow down and more time will be available for dissolution. For discharges in deep waters (700-1500 m depth), hydrate formation is found to be a dominating process in limiting plume rise. (Author)

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

Science.gov (United States)

Pang, Bo; Becker, Frank

2017-04-28

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

A survey on deep learning in medical image analysis.

Science.gov (United States)

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

2017-12-01

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

The use of interaction matrices for identification, structuring and ranking of FEPs in a repository system. Application on the far-field of a deep geological repository for spent fuel

Energy Technology Data Exchange (ETDEWEB)

Skagius, K; Wiborgh, M [Kemakta, Stockholm (Sweden); Stroem, A [Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden)

1995-11-01

The basic device in the Rock Engineering Systems approach, the interaction matrix, has been used to identify, structure and rank Features, Events, and Processes (FEPs) describing barrier performance and radionuclide behaviour in the far-field of a deep geologic repository for spent fuel. The result is a first version of the Process System (PS), for the far-field of a deep repository, structured in an interaction matrix with supporting documentation. The documentation is compiled in databases, one containing matrix specific information and one containing general FEP descriptions. The study has shown that an interaction matrix is feasible to use both for the structuring of the PS and for visualisation of the PS. The developed documentation system increases the transparency of the system description and makes it possible to trace back the judgements made during the construction of the matrix. This will facilitate review work and future revisions as well as consistent treatment of different issues in the system. This study is a first step in the application of a systematic method to establish a structured description of the PS for a deep repository for spent fuel. The work could be seen as a part of the preparation for the forthcoming performance and safety analysis. The next step would be to develop the PS for the remaining parts of the repository system to the same level as has been done for the far-field system. Before the PS is evaluated for different selected system premises, a scientific review of the contents of the PS for the whole repository system would be beneficial. 5 refs.

The use of interaction matrices for identification, structuring and ranking of FEPs in a repository system. Application on the far-field of a deep geological repository for spent fuel

International Nuclear Information System (INIS)

Skagius, K.; Wiborgh, M.; Stroem, A.

1995-11-01

The basic device in the Rock Engineering Systems approach, the interaction matrix, has been used to identify, structure and rank Features, Events, and Processes (FEPs) describing barrier performance and radionuclide behaviour in the far-field of a deep geologic repository for spent fuel. The result is a first version of the Process System (PS), for the far-field of a deep repository, structured in an interaction matrix with supporting documentation. The documentation is compiled in databases, one containing matrix specific information and one containing general FEP descriptions. The study has shown that an interaction matrix is feasible to use both for the structuring of the PS and for visualisation of the PS. The developed documentation system increases the transparency of the system description and makes it possible to trace back the judgements made during the construction of the matrix. This will facilitate review work and future revisions as well as consistent treatment of different issues in the system. This study is a first step in the application of a systematic method to establish a structured description of the PS for a deep repository for spent fuel. The work could be seen as a part of the preparation for the forthcoming performance and safety analysis. The next step would be to develop the PS for the remaining parts of the repository system to the same level as has been done for the far-field system. Before the PS is evaluated for different selected system premises, a scientific review of the contents of the PS for the whole repository system would be beneficial. 5 refs

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

Science.gov (United States)

Simcoe, Robert

2017-08-01

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

Preface: Deep Slab and Mantle Dynamics

Science.gov (United States)

Suetsugu, Daisuke; Bina, Craig R.; Inoue, Toru; Wiens, Douglas A.

2010-11-01

We are pleased to publish this special issue of the journal Physics of the Earth and Planetary Interiors entitled "Deep Slab and Mantle Dynamics". This issue is an outgrowth of the international symposium "Deep Slab and Mantle Dynamics", which was held on February 25-27, 2009, in Kyoto, Japan. This symposium was organized by the "Stagnant Slab Project" (SSP) research group to present the results of the 5-year project and to facilitate intensive discussion with well-known international researchers in related fields. The SSP and the symposium were supported by a Grant-in-Aid for Scientific Research (16075101) from the Ministry of Education, Culture, Sports, Science and Technology of the Japanese Government. In the symposium, key issues discussed by participants included: transportation of water into the deep mantle and its role in slab-related dynamics; observational and experimental constraints on deep slab properties and the slab environment; modeling of slab stagnation to constrain its mechanisms in comparison with observational and experimental data; observational, experimental and modeling constraints on the fate of stagnant slabs; eventual accumulation of stagnant slabs on the core-mantle boundary and its geodynamic implications. This special issue is a collection of papers presented in the symposium and other papers related to the subject of the symposium. The collected papers provide an overview of the wide range of multidisciplinary studies of mantle dynamics, particularly in the context of subduction, stagnation, and the fate of deep slabs.

The Deep-Sea Microbial Community from the Amazonian Basin Associated with Oil Degradation

Directory of Open Access Journals (Sweden)

Mariana E. Campeão

2017-06-01

Full Text Available One consequence of oil production is the possibility of unplanned accidental oil spills; therefore, it is important to evaluate the potential of indigenous microorganisms (both prokaryotes and eukaryotes from different oceanic basins to degrade oil. The aim of this study was to characterize the microbial response during the biodegradation process of Brazilian crude oil, both with and without the addition of the dispersant Corexit 9500, using deep-sea water samples from the Amazon equatorial margin basins, Foz do Amazonas and Barreirinhas, in the dark and at low temperatures (4°C. We collected deep-sea samples in the field (about 2570 m below the sea surface, transported the samples back to the laboratory under controlled environmental conditions (5°C in the dark and subsequently performed two laboratory biodegradation experiments that used metagenomics supported by classical microbiological methods and chemical analysis to elucidate both taxonomic and functional microbial diversity. We also analyzed several physical–chemical and biological parameters related to oil biodegradation. The concomitant depletion of dissolved oxygen levels, oil droplet density characteristic to oil biodegradation, and BTEX concentration with an increase in microbial counts revealed that oil can be degraded by the autochthonous deep-sea microbial communities. Indigenous bacteria (e.g., Alteromonadaceae, Colwelliaceae, and Alcanivoracaceae, archaea (e.g., Halobacteriaceae, Desulfurococcaceae, and Methanobacteriaceae, and eukaryotic microbes (e.g., Microsporidia, Ascomycota, and Basidiomycota from the Amazonian margin deep-sea water were involved in biodegradation of Brazilian crude oil within less than 48-days in both treatments, with and without dispersant, possibly transforming oil into microbial biomass that may fuel the marine food web.

Benchmarking Deep Learning Models on Large Healthcare Datasets.

Science.gov (United States)

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

2018-06-04

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

Review of excavation methods and their implications for the near-field barrier of a deep underground repository

International Nuclear Information System (INIS)

Young, D.K.

1993-01-01

The report reviews excavation techniques for use in the construction of deep underground radioactive waste repositories, gives a summary of responses of the host rock to excavation and the means of measuring that response and discusses techniques for predicting that response. The review of excavation techniques included technical developments and current practice. To this end an extensive database was developed reviewing major excavations in rock types relevant to disposal and the techniques employed. Creation of an underground opening alters the properties of the rock mass around it. This study identifies stress, displacement, rock mass deformability and permeability as key parameters and reviews how they may be determined. Finally the report discusses the techniques available for predicting the behaviour of the near-field host rock. This concentrates on methods of numerical analysis since existing empirical or analytical methods are not considered suitable. (author)

Beyond annual budgets: carbon flux at different temporal scales in fire-prone Siberian Scots pine forests

International Nuclear Information System (INIS)

Wirth, C.; Czimczik, C.I.; Schulze, E.D.

2002-01-01

pools and organic layer accumulation as a function of time since the last surface fire, but ignores carbon dynamics in the mineral soil. In burned mature lichen type stands, NEP S was 6.2 ± 2.6 mol C/m 2 /yr (74 ± 31 g C/m 2 /yr) and thus five times higher than NEP C at the respective age (1.2 ± 0.6 mol C/m 2 /yr or 14 ± 7 g C/m 2 /yr). Comparing NEP S and NEP C of mature stands, we estimate that 48% of NPP are consumed by heterotrophic respiration and additional 35% are consumed by recurrent surface fires. As expected, in unburned stands NEP C and NEP S were of similar magnitude. Exploring a site specific model of CWD production and decomposition we estimated that fire reduces the carbon pool of newly produced CWD by 70%. Direct observation revealed that surface fire events consume 50% of the soil organic layer carbon pool (excluding CWD). We conclude that surface fires strongly reduced NEP C . In ecosystems with frequent fire events direct flux measurements using eddy covariance are likely to record high rates of carbon uptake, since they describe the behaviour of ecosystems recovering from fire without capturing the sporadic but substantial fire-related carbon losses

Stable and Variable Parts of Microbial Community in Siberian Deep Subsurface Thermal Aquifer System Revealed in a Long-Term Monitoring Study

OpenAIRE

Frank, Yulia A.; Kadnikov, Vitaly V.; Gavrilov, Sergey N.; Banks, David; Gerasimchuk, Anna L.; Podosokorskaya, Olga A.; Merkel, Alexander Y.; Chernyh, Nikolai A.; Mardanov, Andrey V.; Ravin, Nikolai V.; Karnachuk, Olga V.; Bonch-Osmolovskaya, Elizaveta A.

2016-01-01

The goal of this work was to study the diversity of microorganisms inhabiting a deep subsurface aquifer system in order to understand their functional roles and interspecies relations formed in the course of buried organic matter degradation. A microbial community of a deep subsurface thermal aquifer in the Tomsk Region, Western Siberia was monitored over the course of five years via a 2.7 km deep borehole 3P, drilled down to a Palaeozoic basement. The borehole water discharges with a tempera...

DEEP CHANDRA OBSERVATIONS OF NGC 1404: CLUSTER PLASMA PHYSICS REVEALED BY AN INFALLING EARLY-TYPE GALAXY

Energy Technology Data Exchange (ETDEWEB)

Su, Yuanyuan; Kraft, Ralph P.; Nulsen, Paul; Forman, William R.; Randall, Scott W.; Jones, Christine; Machacek, Marie E. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Roediger, Elke [E.A. Milne Centre for Astrophysics, Department of Physics and Mathematics, University of Hull, Hull, HU6 7RX (United Kingdom); Churazov, Eugene, E-mail: yuanyuan.su@cfa.harvard.edu [Max Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741, Garching (Germany)

2017-01-01

The intracluster medium (ICM), as a magnetized and highly ionized fluid, provides an ideal laboratory to study plasma physics under extreme conditions that cannot be achieved on Earth. NGC 1404 is a bright elliptical galaxy that is being gas stripped as it falls through the ICM of the Fornax Cluster. We use the new Chandra X-ray observations of NGC 1404 to study ICM microphysics. The interstellar medium of NGC 1404 is characterized by a sharp leading edge, 8 kpc from the Galaxy center, and a short downstream gaseous tail. Contact discontinuities are resolved on unprecedented spatial scales (0.″5 = 45 pc) due to the combination of the proximity of NGC 1404, the superb spatial resolution of Chandra , and the very deep (670 ks) exposure. At the leading edge, we observe sub-kiloparsec-scale eddies generated by Kelvin–Helmholtz instability (KHI) and put an upper limit of 5% Spitzer on the isotropic viscosity of the hot cluster plasma. We also observe mixing between the hot cluster gas and the cooler galaxy gas in the downstream stripped tail, which provides further evidence of a low viscosity plasma. The assumed ordered magnetic fields in the ICM ought to be smaller than 5 μ G to allow KHI to develop. The lack of an evident magnetic draping layer just outside the contact edge is consistent with such an upper limit.

Deep-water subsea lifting operations

Energy Technology Data Exchange (ETDEWEB)

Nestegaard, Arne; Boee, Tormod

2010-07-01

Significant costs are related to marine operations in the installation phase of deep water subsea field developments. In order to establish safe operational criteria and procedures for the installation, detailed planning is necessary, including numerical modelling and analysis of the environmental conditions and hydrodynamic loads on the installed object as well as the installation equipment. This paper presents recommendations for modelling and analysis of deep water subsea lifting operations developed for the new DNV RP-H103 [1]. During installation of subsea structures, the highest dynamic forces are most often encountered in the splash zone. Recommendations for estimation of maximum forces will be presented. For small structures and tools, installation through the moon pool of a small installation vessel is often preferred. Calculation methods for loading on structures installed through a moon pool will be presented. During intervention or installation in deep water a significant amplification of amplitude and forces can be experienced when the frequency range of vertical crane tip motion coincides with the natural vertical oscillation of the lift wire and load. Vertical resonance may reduce the operability of the operation. Simplified calculation methods for such operations are presented. (Author)

Field-Assisted Splitting of Pure Water Based on Deep-Sub-Debye-Length Nanogap Electrochemical Cells.

Science.gov (United States)

Wang, Yifei; Narayanan, S R; Wu, Wei

2017-08-22

Owing to the low conductivity of pure water, using an electrolyte is common for achieving efficient water electrolysis. In this paper, we have fundamentally broken through this common sense by using deep-sub-Debye-length nanogap electrochemical cells to achieve efficient electrolysis of pure water (without any added electrolyte) at room temperature. A field-assisted effect resulted from overlapped electrical double layers can greatly enhance water molecules ionization and mass transport, leading to electron-transfer limited reactions. We have named this process "virtual breakdown mechanism" (which is completely different from traditional mechanisms) that couples the two half-reactions together, greatly reducing the energy losses arising from ion transport. This fundamental discovery has been theoretically discussed in this paper and experimentally demonstrated in a group of electrochemical cells with nanogaps between two electrodes down to 37 nm. On the basis of our nanogap electrochemical cells, the electrolysis current density from pure water can be significantly larger than that from 1 mol/L sodium hydroxide solution, indicating the much better performance of pure water splitting as a potential for on-demand clean hydrogen production.

Solar wind charge exchange emission in the Chandra deep field north

Energy Technology Data Exchange (ETDEWEB)

Slavin, Jonathan D.; Wargelin, Bradford J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Koutroumpa, Dimitra [LATMOS/IPSL, CNRS, Université Versailles Saint Quentin, 11 Boulevard d' Alembert, F-78280, Guyancourt (France)

2013-12-10

The diffuse soft X-ray background comes from distant galaxies, from hot Galactic gas, and from within the solar system. The latter emission arises from charge exchange between highly charged solar wind ions and neutral gas. This so-called solar wind charge exchange (SWCX) emission is spatially and temporally variable and interferes with our measurements of more distant cosmic emission while also providing important information on the nature of the solar wind-interstellar medium interaction. We present the results of our analysis of eight Chandra observations of the Chandra Deep Field North (CDFN) with the goal of measuring the cosmic and SWCX contributions to the X-ray background. Our modeling of both geocoronal and heliospheric SWCX emission is the most detailed for any observation to date. After allowing for ∼30% uncertainty in the SWCX emission and subtracting it from the observational data, we estimate that the flux of cosmic background for the CDFN in the O VII Kα, Kβ, and O VIII Lyα lines totals 5.8 ± 1.1 photons s{sup –1} cm{sup –2} sr{sup –1} (or LU). Heliospheric SWCX emission varied for each observation due to differences in solar wind conditions and the line of sight through the solar system, but was typically about half as strong as the cosmic background (i.e., one-third of the total) in those lines. The modeled geocoronal emission was 0.82 LU in one observation but averaged only 0.15 LU in the others. Our measurement of the cosmic background is lower than but marginally consistent with previous estimates based on XMM-Newton data.

Solar wind charge exchange emission in the Chandra deep field north

International Nuclear Information System (INIS)

Slavin, Jonathan D.; Wargelin, Bradford J.; Koutroumpa, Dimitra

2013-01-01

The diffuse soft X-ray background comes from distant galaxies, from hot Galactic gas, and from within the solar system. The latter emission arises from charge exchange between highly charged solar wind ions and neutral gas. This so-called solar wind charge exchange (SWCX) emission is spatially and temporally variable and interferes with our measurements of more distant cosmic emission while also providing important information on the nature of the solar wind-interstellar medium interaction. We present the results of our analysis of eight Chandra observations of the Chandra Deep Field North (CDFN) with the goal of measuring the cosmic and SWCX contributions to the X-ray background. Our modeling of both geocoronal and heliospheric SWCX emission is the most detailed for any observation to date. After allowing for ∼30% uncertainty in the SWCX emission and subtracting it from the observational data, we estimate that the flux of cosmic background for the CDFN in the O VII Kα, Kβ, and O VIII Lyα lines totals 5.8 ± 1.1 photons s –1 cm –2 sr –1 (or LU). Heliospheric SWCX emission varied for each observation due to differences in solar wind conditions and the line of sight through the solar system, but was typically about half as strong as the cosmic background (i.e., one-third of the total) in those lines. The modeled geocoronal emission was 0.82 LU in one observation but averaged only 0.15 LU in the others. Our measurement of the cosmic background is lower than but marginally consistent with previous estimates based on XMM-Newton data.

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

Science.gov (United States)

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

2017-04-01

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

Inhibition of CRM1-mediated nuclear export of influenza A nucleoprotein and nuclear export protein as a novel target for antiviral drug development

Energy Technology Data Exchange (ETDEWEB)

Chutiwitoonchai, Nopporn; Mano, Takafumi; Kakisaka, Michinori; Sato, Hirotaka [Viral Infectious Disease Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Kondoh, Yasumitsu; Osada, Hiroyuki [Chemical Biology Research Group, RIKEN Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Kotani, Osamu; Yokoyama, Masaru; Sato, Hironori [Laboratory of Viral Genomics, Pathogen Genomics Center, National Institute of Infectious Diseases, 4-7-1 Gakuen, Musashimurayama, Tokyo 208-0011 (Japan); Aida, Yoko, E-mail: aida@riken.jp [Viral Infectious Disease Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan)

2017-07-15

An anti-influenza compound, DP2392-E10 based on inhibition of the nuclear export function of the viral nucleoprotein-nuclear export signal 3 (NP-NES3) domain was successfully identified by our previous high-throughput screening system. Here, we demonstrated that DP2392-E10 exerts its antiviral effect by inhibiting replication of a broad range of influenza A subtypes. In regard to the molecular mechanism, we revealed that DP2392-E10 inhibits nuclear export of both viral NP and nuclear export protein (NEP). More specifically, in vitro pull-down assays revealed that DP2392-E10 directly binds cellular CRM1, which mediates nuclear export of NP and NEP. In silico docking suggested that DP2392-E10 binds at a region close to the HEAT9 and HEAT10 domains of CRM1. Together, these results indicate that the CRM1-mediated nuclear export function of influenza virus represents a new potential target for antiviral drug development, and also provide a core structure for a novel class of inhibitors that target this function. - Highlights: •DP2392-E10 inhibits replication of a broad range of influenza A subtypes. •DP2392-E10 inhibits nuclear exports of NP and NEP via their NP-NES3 and NEP-NES2 domains, respectively. •DP2392-E10 is predicted to directly bind CRM1 in the region near the HEAT9 and HEAT10 repeats.

Inhibition of CRM1-mediated nuclear export of influenza A nucleoprotein and nuclear export protein as a novel target for antiviral drug development

International Nuclear Information System (INIS)

Chutiwitoonchai, Nopporn; Mano, Takafumi; Kakisaka, Michinori; Sato, Hirotaka; Kondoh, Yasumitsu; Osada, Hiroyuki; Kotani, Osamu; Yokoyama, Masaru; Sato, Hironori; Aida, Yoko

2017-01-01

An anti-influenza compound, DP2392-E10 based on inhibition of the nuclear export function of the viral nucleoprotein-nuclear export signal 3 (NP-NES3) domain was successfully identified by our previous high-throughput screening system. Here, we demonstrated that DP2392-E10 exerts its antiviral effect by inhibiting replication of a broad range of influenza A subtypes. In regard to the molecular mechanism, we revealed that DP2392-E10 inhibits nuclear export of both viral NP and nuclear export protein (NEP). More specifically, in vitro pull-down assays revealed that DP2392-E10 directly binds cellular CRM1, which mediates nuclear export of NP and NEP. In silico docking suggested that DP2392-E10 binds at a region close to the HEAT9 and HEAT10 domains of CRM1. Together, these results indicate that the CRM1-mediated nuclear export function of influenza virus represents a new potential target for antiviral drug development, and also provide a core structure for a novel class of inhibitors that target this function. - Highlights: •DP2392-E10 inhibits replication of a broad range of influenza A subtypes. •DP2392-E10 inhibits nuclear exports of NP and NEP via their NP-NES3 and NEP-NES2 domains, respectively. •DP2392-E10 is predicted to directly bind CRM1 in the region near the HEAT9 and HEAT10 repeats.

Bacterial diversity and biogeography in deep-sea sediments of the South Atlantic Ocean

DEFF Research Database (Denmark)

Schauer, Regina; Bienhold, Christina; Ramette, Alban

2010-01-01

in 1051 sequences. Phylotypes affiliated with Gammaproteobacteria, Deltaproteobacteria and Acidobacteria were present in all three basins. The distribution of these shared phylotypes seemed to be influenced neither by the Walvis Ridge nor by different deep water masses, suggesting a high dispersal......Microbial biogeographic patterns in the deep sea depend on the ability of microorganisms to disperse. One possible limitation to microbial dispersal may be the Walvis Ridge that separates the Antarctic Lower Circumpolar Deep Water from the North Atlantic Deep Water. We examined bacterial...... communities in three basins of the eastern South Atlantic Ocean to determine diversity and biogeography of bacterial communities in deep-sea surface sediments. The analysis of 16S ribosomal RNA (rRNA) gene clone libraries in each basin revealed a high diversity, representing 521 phylotypes with 98% identity...

Ultra-deep sequencing reveals high prevalence and broad structural diversity of hepatitis B surface antigen mutations in a global population.

Science.gov (United States)

Gencay, Mikael; Hübner, Kirsten; Gohl, Peter; Seffner, Anja; Weizenegger, Michael; Neofytos, Dionysios; Batrla, Richard; Woeste, Andreas; Kim, Hyon-Suk; Westergaard, Gaston; Reinsch, Christine; Brill, Eva; Thu Thuy, Pham Thi; Hoang, Bui Huu; Sonderup, Mark; Spearman, C Wendy; Pabinger, Stephan; Gautier, Jérémie; Brancaccio, Giuseppina; Fasano, Massimo; Santantonio, Teresa; Gaeta, Giovanni B; Nauck, Markus; Kaminski, Wolfgang E

2017-01-01

The diversity of the hepatitis B surface antigen (HBsAg) has a significant impact on the performance of diagnostic screening tests and the clinical outcome of hepatitis B infection. Neutralizing or diagnostic antibodies against the HBsAg are directed towards its highly conserved major hydrophilic region (MHR), in particular towards its "a" determinant subdomain. Here, we explored, on a global scale, the genetic diversity of the HBsAg MHR in a large, multi-ethnic cohort of randomly selected subjects with HBV infection from four continents. A total of 1553 HBsAg positive blood samples of subjects originating from 20 different countries across Africa, America, Asia and central Europe were characterized for amino acid variation in the MHR. Using highly sensitive ultra-deep sequencing, we found 72.8% of the successfully sequenced subjects (n = 1391) demonstrated amino acid sequence variation in the HBsAg MHR. This indicates that the global variation frequency in the HBsAg MHR is threefold higher than previously reported. The majority of the amino acid mutations were found in the HBV genotypes B (28.9%) and C (25.4%). Collectively, we identified 345 distinct amino acid mutations in the MHR. Among these, we report 62 previously unknown mutations, which extends the worldwide pool of currently known HBsAg MHR mutations by 22%. Importantly, topological analysis identified the "a" determinant upstream flanking region as the structurally most diverse subdomain of the HBsAg MHR. The highest prevalence of "a" determinant region mutations was observed in subjects from Asia, followed by the African, American and European cohorts, respectively. Finally, we found that more than half (59.3%) of all HBV subjects investigated carried multiple MHR mutations. Together, this worldwide ultra-deep sequencing based genotyping study reveals that the global prevalence and structural complexity of variation in the hepatitis B surface antigen have, to date, been significantly underappreciated.

Optimizing interplanetary trajectories with deep space maneuvers

Science.gov (United States)

Navagh, John

1993-09-01

Analysis of interplanetary trajectories is a crucial area for both manned and unmanned missions of the Space Exploration Initiative. A deep space maneuver (DSM) can improve a trajectory in much the same way as a planetary swingby. However, instead of using a gravitational field to alter the trajectory, the on-board propulsion system of the spacecraft is used when the vehicle is not near a planet. The purpose is to develop an algorithm to determine where and when to use deep space maneuvers to reduce the cost of a trajectory. The approach taken to solve this problem uses primer vector theory in combination with a non-linear optimizing program to minimize Delta(V). A set of necessary conditions on the primer vector is shown to indicate whether a deep space maneuver will be beneficial. Deep space maneuvers are applied to a round trip mission to Mars to determine their effect on the launch opportunities. Other studies which were performed include cycler trajectories and Mars mission abort scenarios. It was found that the software developed was able to locate quickly DSM's which lower the total Delta(V) on these trajectories.

UV Luminosity Functions at z~4, 5, and 6 from the Hubble Ultra Deep Field and Other Deep Hubble Space Telescope ACS Fields: Evolution and Star Formation History

Science.gov (United States)

Bouwens, R. J.; Illingworth, G. D.; Franx, Marijn; Ford, Holland

2007-12-01

We use the ACS BViz data from the HUDF and all other deep HST ACS fields (including the GOODS fields) to find large samples of star-forming galaxies at z~4 and ~5 and to extend our previous z~6 sample. These samples contain 4671, 1416, and 627 B-, V-, and i-dropouts, respectively, and reach to extremely low luminosities [(0.01-0.04)L*z=3 or MUV~-16 to -17], allowing us to determine the rest-frame UV LF and faint-end slope α at z~4-6 to high accuracy. We find faint-end slopes α=-1.73+/-0.05, -1.66+/-0.09, and -1.74+/-0.16 at z~4, ~5, and ~6, respectively, suggesting that the faint-end slope is very steep and shows little evolution with cosmic time. We find that M*UV brightens considerably in the 0.7 Gyr from z~6 to ~4 (by ~0.7 mag from M*UV=-20.24+/-0.19 to -20.98+/-0.10). The observed increase in the characteristic luminosity over this range is almost identical to that expected for the halo mass function, suggesting that the observed evolution is likely due to the hierarchical coalescence and merging of galaxies. The evolution in φ* is not significant. The UV luminosity density at z~6 is modestly lower than (0.45+/-0.09 times) that at z~4 (integrated to -17.5 mag) although a larger change is seen in the dust-corrected SFR density. We thoroughly examine published LF results and assess the reasons for their wide dispersion. We argue that the results reported here are the most robust available. The extremely steep faint-end slopes α found here suggest that lower luminosity galaxies play a significant role in reionizing the universe. Finally, recent search results for galaxies at z~7-8 are used to extend our estimates of the evolution of M* from z~7-8 to z~4. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs 9425, 9575, 9803, 9978, 10189, 10339, 10340, and 10632.

The Bush/Cheney Energy Strategy: Implications for U.S. Foreign and Military Policy

Energy Technology Data Exchange (ETDEWEB)

Klare, Michael T. [Hampshire College, Amherst, MA (United States). Peace and World Security Studies

2003-07-01

The 'National Energy Policy' (NEP) released by the Bush Administration on May 17, 2001 was supposedly intended to meet growing U.S. energy requirements in the first two decades of the 21st Century while also diminishing U.S. dependence on imported oil. This was to be accomplished, the White House suggested, by increasing production at existing oil fields in the United States and by commencing drilling on the Artic National Wildlife Refuge (ANWR) in Alaska. So great was the furor over drilling on ANWR that most people never bothered to examine the NEP closely. This is unfortunate, as a close reading of the NEP report reveals a very different picture than that suggested by White House pronouncements: far from promoting energy 'independence', the NEP assumes that the United States will become MORE, not less dependent on imported petroleum in the years ahead and therefore calls on the Federal Government to take whatever steps are necessary to promote enhanced U.S. access to foreign oil. In particular, the NEP calls on the U.S. Government to seek additional petroleum from the Persian Gulf area, Russia, the Caspian Sea basin, Mexico, Venezuela, Angola, and Nigeria. As is implied by the report, the United States must acquire more oil from these countries in order to permit increased oil consumption in the United States at a time of declining domestic production. Even leaving aside the question of whether these countries will be able to boost their production sufficiently to satisfy steadily rising demand in the United States, this strategy poses enormous challenges for the United States because most of these areas are highly unstable and house anti-American governments and forces. It is likely, then, that U.S. efforts to acquire more oil from these countries will entail the increased presence of U.S. military forces in the area and periodic U.S. military intervention. Indeed, the requirement for increased military action in support of U.S. foreign

Studies of the incidence of post-operative deep-vein thrombosis in Sudan, using 125I-fibrinogen

International Nuclear Information System (INIS)

Hassan, M.A.

1974-01-01

Sudanese patients undergoing surgery in Khartoum Civil Hospital were investigated for evidence of post-operative deep vein thrombosis by means of the 125 I-fibrinogen test. An analysis of the results obtained in an initial series of 100 patients undergoing various operations including prostatectomy (transvesical or retropubic), vagotomy and drainage, cholocystectomy, various operations on the urinary bladder, various operations on the hip, splenectomy, herniorrhaphy, nephrectomy and haemorrhoidectomy revealed an incidence of post-operative deep vein thrombosis of 12.0%. There was no significant variation of incidence with age or sex. A subsequent analysis of the results obtained in 104 patients undergoing prostatectomy (transvesical or retropubic) revealed an incidence of deep vein thrombosis of 9.6%. These values differ markedly from the incidences of 21-47% reported in Sweden and UK. It is suggested that the indicence of post-operative deep vein thrombosis is lower in Sudan than in European countries

Terahertz detectors for long wavelength multi-spectral imaging.

Energy Technology Data Exchange (ETDEWEB)

Lyo, Sungkwun Kenneth; Wanke, Michael Clement; Reno, John Louis; Shaner, Eric Arthur; Grine, Albert D.

2007-10-01

The purpose of this work was to develop a wavelength tunable detector for Terahertz spectroscopy and imaging. Our approach was to utilize plasmons in the channel of a specially designed field-effect transistor called the grating-gate detector. Grating-gate detectors exhibit narrow-linewidth, broad spectral tunability through application of a gate bias, and no angular dependence in their photoresponse. As such, if suitable sensitivity can be attained, they are viable candidates for Terahertz multi-spectral focal plane arrays. When this work began, grating-gate gate detectors, while having many promising characteristics, had a noise-equivalent power (NEP) of only 10{sup -5} W/{radical}Hz. Over the duration of this project, we have obtained a true NEP of 10{sup -8} W/{radical}Hz and a scaled NEP of 10{sup -9}W/{radical}Hz. The ultimate goal for these detectors is to reach a NEP in the 10{sup -9{yields}-10}W/{radical}Hz range; we have not yet seen a roadblock to continued improvement.

Characteristic features of the behaviour of deep centers in especially pure germanium

International Nuclear Information System (INIS)

Gloriozova, R.I.; Kolesnik, L.I.

1993-01-01

Method of capacitive relaxation spectroscopy was used to study spectrum of deep centers in germanium crystals of p-type conductivity with 10 11 -10 13 cm -3 charge carrier concentration, depending on dislocation density and thermal treatment. Existence of two types of centers with 0.24 and 0.32 eV ionization energies, dictating the maximum near 140 K, was established. Change of deep center concentration with time was revealed

Deep water characteristics and circulation in the South China Sea

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Qiulong Yang

2018-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Time series current meter data from buoys in the North Atlantic as part of the Deep Circulation in the Gulf of Maine Field Program from platforms GYRE and MARY LOUISE between July 25th, 1985 and August 2nd, 1987 (NODC Accession 0053940)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A two-year field study to investigate the deep flow between the major basins in the Gulf of Maine. This deep flow of warm-salty Slope water is an important driving...

Draft genome of an Aerophobetes bacterium reveals a facultative lifestyle in deep-sea anaerobic sediments

KAUST Repository

Wang, Yong

2016-07-01

Aerophobetes (or CD12) is a recently defined bacterial phylum, of which the metabolic processes and ecological importance remain unclear. In the present study, we obtained the draft genome of an Aerophobetes bacterium TCS1 from saline sediment near the Thuwal cold seep in the Red Sea using a genome binning method. Analysis of 16S rRNA genes of TCS1 and close relatives revealed wide distribution of Aerophobetes in deep-sea sediments. Phylogenetic relationships showed affinity between Aerophobetes TCS1 and some thermophilic bacterial phyla. The genome of TCS1 (at least 1.27 Mbp) contains a full set of genes encoding core metabolic pathways, including glycolysis and pyruvate fermentation to produce acetyl-CoA and acetate. The identification of cross-membrane sugar transporter genes further indicates its potential ability to consume carbohydrates preserved in the sediment under the microbial mat. Aerophobetes bacterium TCS1 therefore probably carried out saccharolytic and fermentative metabolism. The genes responsible for autotrophic synthesis of acetyl-CoA via the Wood–Ljungdahl pathway were also found in the genome. Phylogenetic study of the essential genes for the Wood–Ljungdahl pathway implied relative independence of Aerophobetes bacterium from the known acetogens and methanogens. Compared with genomes of acetogenic bacteria, Aerophobetes bacterium TCS1 genome lacks the genes involved in nitrogen metabolism, sulfur metabolism, signal transduction and cell motility. The metabolic activities of TCS1 might depend on geochemical conditions such as supplies of CO2, hydrogen and sugars, and therefore the TCS1 might be a facultative bacterium in anaerobic saline sediments near cold seeps. © 2016, Science China Press and Springer-Verlag Berlin Heidelberg.

Coherence effects in deep inelastic scattering

International Nuclear Information System (INIS)

Andersson, B.; Gustafson, G.; Loennblad, L.; Pettersson, U.

1988-09-01

We present a framework for deep inelastic scattering, with bound state properties in accordance with a QCD force field acting like a vortex line in a colour superconducting vacuum, which implies some simple coherence effects. Within this scheme one may describe the results of present energies very well, but one obtains an appreciable depletion of gluon radiation in the HERA energy regime. (authors)

Galaxies at z~7-8: z850-Dropouts in the Hubble Ultra Deep Field

Science.gov (United States)

Bouwens, R. J.; Thompson, R. I.; Illingworth, G. D.; Franx, M.; van Dokkum, P. G.; Fan, X.; Dickinson, M. E.; Eisenstein, D. J.; Rieke, M. J.

2004-12-01

We have detected likely z~7-8 galaxies in the 144''×144'' Near-Infrared Camera and Multi-Object Spectrometer (NICMOS) observations of the Hubble Ultra Deep Field. Objects are required to be >=3 σ detections in both NICMOS bands, J110 and H160. The selection criteria for this sample are (z850-J110)AB>0.8, (z850-J110)AB>0.66(J110-H160)AB+0.8, (J110-H160)ABdropout galaxies and are clustered within a 1 arcmin2 region. Because all five sources are near the limit of the NICMOS data, we have carefully evaluated their reality. Each of the candidates is visible in different splits of the data and a median stack. We analyzed several noise images and estimate the number of spurious sources to be 1+/-1. A search using an independent reduction of this same data set clearly revealed three of the five candidates and weakly detected a fourth candidate, suggesting that the contamination could be higher. For comparison with predictions from lower redshift samples, we take a conservative approach and adopt four z~7-8 galaxies as our sample. With the same detection criteria on simulated data sets, assuming no evolution from z~3.8, we predict 10 sources at z~7-8, or 14 if we use a more realistic (1+z)-1 size scaling. We estimate that the rest-frame continuum UV (~1800 Å) luminosity density at z~7.5 (integrated down to 0.3L*z=3) is just 0.20+0.12-0.08 times that found at z~3.8 (or 0.20+0.23-0.12 times this quantity including cosmic variance). Effectively this sets an upper limit on the luminosity density down to 0.3L*z=3 and is consistent with significant evolution at the bright end of the luminosity function from z~7.5 to 3.8. Even with the lower UV luminosity density at z~7.5, it appears that galaxies could still play an important role in reionization at these redshifts, although definitive measurements remain to be made. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under

Exploring deep potential aquifer in water scarce crystalline rocks

Indian Academy of Sciences (India)

out to explore deep groundwater potential zone in a water scarce granitic area. As existing field condi- ... Decision support tool developed in granitic ter- .... cially in terms of fracture system, the aquifer char- acteristics ... Methodologies used.

Deep learning in jet reconstruction at CMS

CERN Document Server

Stoye, Markus

2017-01-01

Deep learning has led to several breakthroughs outside the field of high energy physics, yet in jet reconstruction for the CMS experiment at the CERN LHC it has not been used so far. This report shows results of applying deep learning strategies to jet reconstruction at the stage of identifying the original parton association of the jet (jet tagging), which is crucial for physics analyses at the LHC experiments. We introduce a custom deep neural network architecture for jet tagging. We compare the performance of this novel method with the other established approaches at CMS and show that the proposed strategy provides a significant improvement. The strategy provides the first multi-class classifier, instead of the few binary classifiers that previously were used, and thus yields more information and in a more convenient way. The performance results obtained with simulation imply a significant improvement for a large number of important physics analysis at the CMS experiment.

Oceanography related to deep sea waste disposal

International Nuclear Information System (INIS)

1978-09-01

In connection with studies on the feasibility of the safe disposal of radioactive waste, from a large scale nuclear power programme, either on the bed of the deep ocean or within the deep ocean bed, preparation of the present document was commissioned by the (United Kingdom) Department of the Environment. It attempts (a) to summarize the present state of knowledge of the deep ocean environment relevant to the disposal options and assess the processes which could aid or hinder dispersal of material released from its container; (b) to identify areas of research in which more work is needed before the safety of disposal on, or beneath, the ocean bed can be assessed; and (c) to indicate which areas of research can or should be undertaken by British scientists. The programmes of international cooperation in this field are discussed. The report is divided into four chapters dealing respectively with geology and geophysics, geochemistry, physical oceanography and marine biology. (U.K.)

Magnetically tunable oil droplet lens of deep-sea shrimp

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

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

2012-11-01

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

Automated Morphological Classification in Deep Hubble Space Telescope UBVI Fields: Rapidly and Passively Evolving Faint Galaxy Populations

Science.gov (United States)

Odewahn, Stephen C.; Windhorst, Rogier A.; Driver, Simon P.; Keel, William C.

1996-11-01

We analyze deep Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) images in U, B, V, I using artificial neural network (ANN) classifiers, which are based on galaxy surface brightness and light profile (but not on color nor on scale length, rhl). The ANN distinguishes quite well between E/S0, Sabc, and Sd/Irr+M galaxies (M for merging systems) for BJ ~ 24 mag. The faint blue galaxy counts in the B band are dominated by Sd/Irr+M galaxies and can be explained by a moderately steep local luminosity function (LF) undergoing strong luminosity evolution. We suggest that these faint late-type objects (24 mag <~ BJ <~ 28 mag) are a combination of low-luminosity lower redshift dwarf galaxies, plus compact star-forming galaxies and merging systems at z ~= 1--3, possibly the building blocks of the luminous early-type galaxies seen today.

Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.

Science.gov (United States)

Zheng, Yu-Jun; Sheng, Wei-Guo; Sun, Xing-Ming; Chen, Sheng-Yong

2017-12-01

Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profiling. The center of our approach is a Pythagorean fuzzy deep Boltzmann machine (PFDBM), whose parameters are expressed by Pythagorean fuzzy numbers such that each neuron can learn how a feature affects the production of the correct output from both the positive and negative sides. We propose a hybrid algorithm combining a gradient-based method and an evolutionary algorithm for training the PFDBM. Based on the novel learning model, we develop a deep neural network (DNN) for classifying normal passengers and potential attackers, and further develop an integrated DNN for identifying group attackers whose individual features are insufficient to reveal the abnormality. Experiments on data sets from Air China show that our approach provides much higher learning ability and classification accuracy than existing profilers. It is expected that the fuzzy deep learning approach can be adapted for a variety of complex pattern analysis tasks.

Tectonics, Deep-Seated Structure and Recent Geodynamics of the Caucasus

Science.gov (United States)

Amanatashvili, I.; Adamia, Sh.; Lursmanashvili, N.; Sadradze, N.; Meskhia, V.; Koulakov, I.; Zabelina, I.; Jakovlev, A.

2012-04-01

The tectonics and deep-seated structure of the Caucasus are determined by its position between the still converging Eurasian and Africa-Arabian plates, within a wide zone of continental collision. The region in the Late Proterozoic - Early Cenozoic belonged to the Tethys Ocean and its Eurasian and Africa-Arabian margins. During Oligocene-Middle Miocene and Late Miocene-Quaternary time as a result of collision back-arc basins were inverted to form fold-thrust mountain belts and the Transcaucasian intermontane lowlands. The Caucasus is divided into platform and fold-thrust units, and forelands superimposed mainly on the rigid platform zones. The youngest structural units composed of Neogene-Quaternary continental volcanic formations of the Armenian and Javakheti highlands and extinct volcanoes of the Great Caucasus. As a result of detailed geophysical study of the gravity, magnetic, seismic, and thermal fields, the main features of the deep crustal structure of the Caucasus have been determined. Knowledge on the deep lithospheric structure of the Caucasus region is based on surface geology and deep and super deep drilling data combined with gravity, seismic, heat flow, and magnetic investigations. Close correlation between the geology and its deep-seated structures appears in the peculiarities of spatial distribution of gravitational, thermal and magnetic fields, particularly generally expressed in orientation of regional anomalies that is in good agreement with general tectonic structures. In this study we present two tomographic models derived for the region based on two different tomographic approaches. In the first case, we use the travel time data on regional seismicity recorded by networks located in Caucasus. The tomographic inversion is based on the LOTOS code which enables simultaneous determination of P and S velocity distributions and source locations. The obtained model covers the crustal and uppermost mantle depths. The second model, which is constructed

Iron oxide reduction in methane-rich deep Baltic Sea sediments

DEFF Research Database (Denmark)

Egger, Matthias; Hagens, Mathilde; Sapart, Celia J.

2017-01-01

/L transition. Our results reveal a complex interplay between production, oxidation and transport of methane showing that besides organoclastic Fe reduction, oxidation of downward migrating methane with Fe oxides may also explain the elevated concentrations of dissolved ferrous Fe in deep Baltic Sea sediments...... profiles and numerical modeling, we propose that a potential coupling between Fe oxide reduction and methane oxidation likely affects deep Fe cycling and related biogeochemical processes, such as burial of phosphorus, in systems subject to changes in organic matter loading or bottom water salinity....

Extensive Left Iliac Veins and Inferior Vena Cava Thrombosis Revealing a Giant Uterine Myoma.

Science.gov (United States)

Cărbunaru, Ana; Herlea; Ionescu, M; Dumitraşcu, T

2016-01-01

A deep vein thrombosis was rarely associated with uterine myomas. Hereby, it is presented the case of a 40-year-old woman in which the clinical manifestation of the deep vein thrombosis revealed the further diagnosis of a large uterine myoma. The diagnosis, management and clinical outcome of the patient are emphasized and discussed. The management of a patient with a uterine myoma and deep vein thrombosis is challenging and implies a multidisciplinary team.

Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

OpenAIRE

R.Anita; V.Ganga Bharani; N.Nityanandam; Pradeep Kumar Sahoo

2011-01-01

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based app...

Research on Daily Objects Detection Based on Deep Neural Network

Science.gov (United States)

Ding, Sheng; Zhao, Kun

2018-03-01

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

Deep multi-scale convolutional neural network for hyperspectral image classification

Science.gov (United States)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

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

The Atlantic Multidecadal Variability in surface and deep ocean temperature and salinity fields from unperturbed climate simulations

Science.gov (United States)

Zanchettin, D.; Jungclaus, J. H.

2013-12-01

Large multidecadal fluctuations in basin-average sea-surface temperature (SST) are a known feature of observed, reconstructed and simulated variability in the North Atlantic Ocean. This phenomenon is often referred to as Multidecadal Atlantic Variability or AMV. Historical AMV fluctuations are associated with analog basin-scale changes in sea-surface salinity, so that warming corresponds to salinification and cooling to freshening [Polyakov et al., 2005]. The surface imprint of the AMV further corresponds to same-sign fluctuations in the shallow ocean and with opposite-sign fluctuations in the deep ocean for both temperature and salinity [Polyakov et al., 2005]. This out-of-phase behavior reflects the thermohaline overturning circulation shaping North Atlantic's low-frequency variability. Several processes contribute to the AMV, involving both ocean-atmosphere coupled processes and deep ocean circulation [e.g., Grossmann and Klotzbach, 2009]. In particular, recirculation in the North Atlantic subpolar gyre region of salinity anomalies from Arctic freshwater export may trigger multidecadal variability in the Atlantic meridional overturning circulation, and therefore may be part of the AMV [Jungclaus et al., 2005; Dima and Lohmann, 2007]. With this contribution, we aim to improve the physical interpretation of the AMV by investigating spatial and temporal patterns of temperature and salinity fields in the shallow and deep ocean. We focus on two unperturbed millennial-scale simulations performed with the Max Planck Institute Earth system model in its paleo (MPI-ESM-P) and low-resolution (MPI-ESM-LR) configurations, which provide reference control climates for assessments of pre-industrial and historical climate simulations. The two model configurations only differ for the presence, in MPI-ESM-LR, of an active module for dynamical vegetation. We use spatial-average indices and empirical orthogonal functions/principal components to track the horizontal and vertical

Borehole geophysical investigations of Lavia deep testhole, Finland

International Nuclear Information System (INIS)

Saksa, Pauli

1985-02-01

According to the Goverment's decision in principle in 1983 Industrial Power Company Ltd (TVO) is making preparations for all the steps of final disposal of the spent fuel produced by its power plants. Before the actual site investigation phase, TVO drilled a deep borehole in Lavia, Western Finland. The borehole is used during 1984-85 for testing investigation techniques and methods used for bedrock characterization. Borehole geophysical loggings performed in Lavia consisted of galvanic electrical, transient electromagnetic, radiometric, temperature, seismic and magnetic msurements. This composite survey provided both lithological and structural information of rock mass. The neutron-neutron, density, natural gamma radiation and susceptibility methods characterized rock type. Fracturing and its type could be interpreted most effectively with resistivity, acoustic P-wave velocity and density logs. Temperature and tube-wave measurements revealed several fractured zones related to possible water flow in rock. Lavia investigations indicated that a high quality of instrumentation and careful calibration are necessary for site investigations. The large amount of log data also requires efficient data collection and processing systems both in the field and laboratory. (author)

The DEEP-South: Scheduling and Data Reduction Software System

Science.gov (United States)

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.

Deep learning of unsteady laminar flow over a cylinder

Science.gov (United States)

Lee, Sangseung; You, Donghyun

2017-11-01

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

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

Science.gov (United States)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

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

Impact of deep levels on the electrical conductivity and luminescence of gallium nitride codoped with carbon and silicon

International Nuclear Information System (INIS)

Armstrong, A.; Arehart, A.R.; Green, D.; Mishra, U.K.; Speck, J.S.; Ringel, S.A.

2005-01-01

The impact of C incorporation on the deep level spectrum of n-type and semi-insulating GaN:C:Si films grown by rf plasma-assisted molecular-beam epitaxy (MBE) was investigated by the combination of deep level transient spectroscopy, steady-state photocapacitance, and transient deep level optical spectroscopy. The deep level spectra of the GaN:C:Si samples exhibited several band-gap states. A monotonic relation between systematic doping with C and quantitative trap concentration revealed C-related deep levels. A deep acceptor at E c -2.05 eV and a deep donor at E c -0.11 eV are newly reported states, and the latter is the first directly observed deep level attributed to the C Ga defect. A configuration-coordinate model involving localized lattice distortion revealed strong evidence that C-related deep levels at E c -3.0 eV and E ν +0.9 eV are likely identical and associated with the yellow luminescence in C-doped GaN films. Of the deep levels whose trap concentration increase with C doping, the band-gap states at E c -3.0 and 3.28 eV had the largest concentration, implying that free-carrier compensation by these deep levels is responsible for the semi-insulating behavior of GaN:C:Si films grown by MBE. The differing manner by which C incorporation in GaN may impact electrical conductivity in films grown by MBE and metal-organic chemical-vapor deposition is discussed

Impact of proton irradiation on deep level states in n-GaN

International Nuclear Information System (INIS)

Zhang, Z.; Arehart, A. R.; Cinkilic, E.; Ringel, S. A.; Chen, J.; Zhang, E. X.; Fleetwood, D. M.; Schrimpf, R. D.; McSkimming, B.; Speck, J. S.

2013-01-01

Deep levels in 1.8 MeV proton irradiated n-type GaN were systematically characterized using deep level transient spectroscopies and deep level optical spectroscopies. The impacts of proton irradiation on the introduction and evolution of those deep states were revealed as a function of proton fluences up to 1.1 × 10 13 cm −2 . The proton irradiation introduced two traps with activation energies of E C - 0.13 eV and 0.16 eV, and a monotonic increase in the concentration for most of the pre-existing traps, though the increase rates were different for each trap, suggesting different physical sources and/or configurations for these states. Through lighted capacitance voltage measurements, the deep levels at E C - 1.25 eV, 2.50 eV, and 3.25 eV were identified as being the source of systematic carrier removal in proton-damaged n-GaN as a function of proton fluence

Electrodril system field test program. Phase II: Task C-1-deep drilling system demonstration. Final report for Phase II: Task C-1

Energy Technology Data Exchange (ETDEWEB)

Taylor, P D

1981-04-01

The Electrodril Deep Drilling System field test demonstrations were aborted in July 1979, due to connector problems. Subsequent post test analyses concluded that the field replacable connectors were the probable cause of the problems encountered. The designs for both the male and female connectors, together with their manufacturing processes, were subsequently modified, as was the acceptance test procedures. A total of nine male and nine female connectors were manufactured and delivered during the 2nd Quarter 1980. Exhaustive testing was then conducted on each connector as a precursor to formal qualification testing conducted during the month of October 1980, at the Brown Oil Tool test facility located in Houston, Texas. With this report, requirements under Phase II, Task C-1 are satisfied. The report documents the results of the connector qualification test program which was successfully completed October 28, 1980. In general, it was concluded that connector qualification had been achieved and plans are now in progress to resume the field test demonstration program so that Electrodril System performance predictions and economic viability can be evaluated.

Head pose estimation algorithm based on deep learning

Science.gov (United States)

Cao, Yuanming; Liu, Yijun

2017-05-01

Head pose estimation has been widely used in the field of artificial intelligence, pattern recognition and intelligent human-computer interaction and so on. Good head pose estimation algorithm should deal with light, noise, identity, shelter and other factors robustly, but so far how to improve the accuracy and robustness of attitude estimation remains a major challenge in the field of computer vision. A method based on deep learning for pose estimation is presented. Deep learning with a strong learning ability, it can extract high-level image features of the input image by through a series of non-linear operation, then classifying the input image using the extracted feature. Such characteristics have greater differences in pose, while they are robust of light, identity, occlusion and other factors. The proposed head pose estimation is evaluated on the CAS-PEAL data set. Experimental results show that this method is effective to improve the accuracy of pose estimation.

A New Calculation Method of Dynamic Kill Fluid Density Variation during Deep Water Drilling

Directory of Open Access Journals (Sweden)

Honghai Fan

2017-01-01

Full Text Available There are plenty of uncertainties and enormous challenges in deep water drilling due to complicated shallow flow and deep strata of high temperature and pressure. This paper investigates density of dynamic kill fluid and optimum density during the kill operation process in which dynamic kill process can be divided into two stages, that is, dynamic stable stage and static stable stage. The dynamic kill fluid consists of a single liquid phase and different solid phases. In addition, liquid phase is a mixture of water and oil. Therefore, a new method in calculating the temperature and pressure field of deep water wellbore is proposed. The paper calculates the changing trend of kill fluid density under different temperature and pressure by means of superposition method, nonlinear regression, and segment processing technique. By employing the improved model of kill fluid density, deep water kill operation in a well is investigated. By comparison, the calculated density results are in line with the field data. The model proposed in this paper proves to be satisfactory in optimizing dynamic kill operations to ensure the safety in deep water.

Multiple SNP markers reveal fine-scale population and deep phylogeographic structure in European anchovy (Engraulis encrasicolus L.).

KAUST Repository

Zarraonaindia, Iratxe; Iriondo, Mikel; Albaina, Aitor; Pardo, Miguel Angel; Manzano, Carmen; Grant, W Stewart; Irigoien, Xabier; Estonba, Andone

2012-01-01

DNA SNPs define two deep phylogroups that reflect ancient dispersals and colonizations. These markers define two ecological groups. One major group of Iberian-Atlantic populations is associated with upwelling areas on narrow continental shelves and includes

Extensive Left Iliac Veins and Inferior Vena Cava Thrombosis Revealing a Giant Uterine Myoma

Directory of Open Access Journals (Sweden)

Cărbunaru Ana

2016-03-01

Full Text Available A deep vein thrombosis was rarely associated with uterine myomas. Hereby, it is presented the case of a 40-year-old woman in which the clinical manifestation of the deep vein thrombosis revealed the further diagnosis of a large uterine myoma. The diagnosis, management and clinical outcome of the patient are emphasized and discussed. The management of a patient with a uterine myoma and deep vein thrombosis is challenging and implies a multidisciplinary team.

Quantum field theory

CERN Document Server

Sadovskii, Michael V

2013-01-01

This book discusses the main concepts of the Standard Model of elementary particles in a compact and straightforward way. The work illustrates the unity of modern theoretical physics by combining approaches and concepts of the quantum field theory and modern condensed matter theory. The inductive approach allows a deep understanding of ideas and methods used for solving problems in this field.

Age-dependent mixing of deep-sea sediments

International Nuclear Information System (INIS)

Smith, C.R.; Maggaard, L.; Pope, R.H.; DeMaster, D.J.

1993-01-01

Rates of bioturbation measured in deep-sea sediments commonly are tracer dependent; in particular, shorter lived radiotracers (such as 234 Th) often yield markedly higher diffusive mixing coefficients than their longer-lived counterparts (e.g., 210 Pb). At a single station in the 1,240-m deep Santa Catalina Basin, the authors document a strong negative correlation between bioturbation rate and tracer half-life. Sediment profiles of 234 Th (half-life = 24 days) yield an average mixing coefficient (60 cm 2 y -1 ) two orders of magnitude greater than that for 210 Pb (half-life = 22 y, mean mixing coefficient = 0.4 cm 2 y -1 ). A similar negative relationship between mixing rate and tracer time scale is observed at thirteen other deep-sea sites in which multiple radiotracers have been used to assess diffusive mixing rates. This relationship holds across a variety of radiotracer types and time scales. The authors hypothesize that this negative relationship results from age-dependent mixing, a process in which recently sedimented, food-rich particles are ingested and mixed at higher rates by deposit feeders than are older, food-poor particles. Results from an age-dependent mixing model demonstrate that this process indeed can yield the bioturbation-rate vs. tracer-time-scale correlations observed in deep-sea sediments. Field data on mixing rates of recently sedimented particles, as well as the radiotracer activity of deep-sea deposit feeders, provide strong support for the age-dependent mixing model. The presence of age-dependent mixing in deep-sea sediments may have major implications for diagenetic modeling, requiring a match between the characteristic time scales of mixing tracers and modeled reactants. 102 refs., 6 figs., 5 tabs

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

Science.gov (United States)

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

2017-05-01

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

Nitrate Contamination of Deep Aquifers in the Salinas Valley, California

Science.gov (United States)

Moran, J. E.; Esser, B. K.; Hillegonds, D. J.; Holtz, M.; Roberts, S. K.; Singleton, M. J.; Visser, A.; Kulongoski, J. T.; Belitz, K.

2011-12-01

The Salinas Valley, known as 'the salad bowl of the world', has been an agricultural center for more than 100 years. Irrigated row crops such as lettuce and strawberries dominate both land use and water use. Groundwater is the exclusive supply for both irrigation and drinking water. Some irrigation wells and most public water supply wells in the Salinas Valley are constructed to draw water from deep portions of the aquifer system, where contamination by nitrate is less likely than in the shallow portions of the aquifer system. However, a number of wells with top perforations greater than 75 m deep, screened below confining or semi-confining units, have nitrate concentrations greater than the Maximum Contaminant Limit (MCL) of 45 mg/L as NO3-. This study uses nitrate concentrations from several hundred irrigation, drinking water, and monitoring wells (Monterey County Water Resources Agency, 1997), along with tritium-helium groundwater ages acquired at Lawrence Livermore National Laboratory through the State of California Groundwater Monitoring and Assessment (GAMA) program (reported in Kulongoski et al., 2007 and in Moran et al., in press), to identify nitrate 'hot spots' in the deep aquifer and to examine possible modes of nitrate transport to the deep aquifer. In addition, observed apparent groundwater ages are compared with the results of transport simulations that use particle tracking and a stochastic-geostatistical framework to incorporate aquifer heterogeneity to determine the distribution of travel times from the water table to each well (Fogg et al., 1999). The combined evidence from nitrate, tritium, tritiogenic 3He, and radiogenic 4He concentrations, reveals complex recharge and flow to the capture zone of the deep drinking water wells. Widespread groundwater pumping for irrigation accelerates vertical groundwater flow such that high nitrate groundwater reaches some deep drinking water wells. Deeper portions of the wells often draw in water that recharged

Methodology for Radiological Risk Assessment of Deep Borehole Disposal Operations

Energy Technology Data Exchange (ETDEWEB)

Hardin, Ernest; Su, Jiann-Cherng; Peretz, Fred(ORNL)

2017-03-01

The primary purpose of the preclosure radiological safety assessment (that this document supports) is to identify risk factors for disposal operations, to aid in design for the deep borehole field test (DBFT) engineering demonstration.

Atomic force microscopy stiffness tomography on living Arabidopsis thaliana cells reveals the mechanical properties of surface and deep cell-wall layers during growth.

Science.gov (United States)

Radotić, Ksenija; Roduit, Charles; Simonović, Jasna; Hornitschek, Patricia; Fankhauser, Christian; Mutavdžić, Dragosav; Steinbach, Gabor; Dietler, Giovanni; Kasas, Sandor

2012-08-08

Cell-wall mechanical properties play a key role in the growth and the protection of plants. However, little is known about genuine wall mechanical properties and their growth-related dynamics at subcellular resolution and in living cells. Here, we used atomic force microscopy (AFM) stiffness tomography to explore stiffness distribution in the cell wall of suspension-cultured Arabidopsis thaliana as a model of primary, growing cell wall. For the first time that we know of, this new imaging technique was performed on living single cells of a higher plant, permitting monitoring of the stiffness distribution in cell-wall layers as a function of the depth and its evolution during the different growth phases. The mechanical measurements were correlated with changes in the composition of the cell wall, which were revealed by Fourier-transform infrared (FTIR) spectroscopy. In the beginning and end of cell growth, the average stiffness of the cell wall was low and the wall was mechanically homogenous, whereas in the exponential growth phase, the average wall stiffness increased, with increasing heterogeneity. In this phase, the difference between the superficial and deep wall stiffness was highest. FTIR spectra revealed a relative increase in the polysaccharide/lignin content. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The Anisotropy of the Microwave Background to l = 3500: Deep Field Observations with the Cosmic Background Imager

Science.gov (United States)

Mason, B. S.; Pearson, T. J.; Readhead, A. C. S.; Shepherd, M. C.; Sievers, J.; Udomprasert, P. S.; Cartwright, J. K.; Farmer, A. J.; Padin, S.; Myers, S. T.;

The discovery of deep-water seagrass meadows in a pristine Indian Ocean wilderness revealed by tracking green turtles.

Science.gov (United States)

Esteban, N; Unsworth, R K F; Gourlay, J B Q; Hays, G C

2018-03-21

Our understanding of global seagrass ecosystems comes largely from regions characterized by human impacts with limited data from habitats defined as notionally pristine. Seagrass assessments also largely focus on shallow-water coastal habitats with comparatively few studies on offshore deep-water seagrasses. We satellite tracked green turtles (Chelonia mydas), which are known to forage on seagrasses, to a remote, pristine deep-water environment in the Western Indian Ocean, the Great Chagos Bank, which lies in the heart of one of the world's largest marine protected areas (MPAs). Subsequently we used in-situ SCUBA and baited video surveys to survey the day-time sites occupied by turtles and discovered extensive monospecific seagrass meadows of Thalassodendron ciliatum. At three sites that extended over 128 km, mean seagrass cover was 74% (mean range 67-88% across the 3 sites at depths to 29 m. The mean species richness of fish in seagrass meadows was 11 species per site (mean range 8-14 across the 3 sites). High fish abundance (e.g. Siganus sutor: mean MaxN.site -1  = 38.0, SD = 53.7, n = 5) and large predatory shark (Carcharhinus amblyrhynchos) (mean MaxN.site -1  = 1.5, SD = 0.4, n = 5) were recorded at all sites. Such observations of seagrass meadows with large top predators, are limited in the literature. Given that the Great Chagos Bank extends over approximately 12,500 km 2 and many other large deep submerged banks exist across the world's oceans, our results suggest that deep-water seagrass may be far more abundant than previously suspected. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

An environmental model study of the deep layers of the North East Atlantic

International Nuclear Information System (INIS)

Bork, I.

1989-01-01

The field work of the north Atlantic monitoring Program (NOAMP) was supplemented by numerical simulations of the transport of radionuclides in the North Atlantic Ocean by annual mean flows and mixing processes. During the last year of NOAMP, a different attempt was made to compute the current field and three-dimensional trajectories of particles released in deep layers of the NOAMP area. It is the subject of this paper. The model used is of Bryan/Semtner type, but with smoothed topography and climatological (winter) temperature and salinity data. The results form a compromise between interpretation of climatological temperature and salinity data and the complete prediction of the current field by prognostic calculations, which yields a deep flow pattern that agrees with some ideas of the abyssal circulation

Imaging beneath the skin of large tropical rivers: System morphodynamics of the Fly and Beni Rivers revealed by novel sub-surface sonar, deep coring, and modelling

Science.gov (United States)

Aalto, R. E.; Grenfell, M.; Lauer, J. W.

2011-12-01

Tropical rivers dominate Earth's fluvial fluxes for water, carbon, and mineral sediment. They are characterized by large channels and floodplains, old system histories, prolonged periods of flooding, and a clay-dominated sediment flux. However, the underlying bed & floodplain strata are poorly understood. Available data commonly stem from skin-deep approaches such as GIS analysis of imagery, shallow sampling & topographic profiling during lower river stages. Given the large temporal & spatial scales, new approaches are needed to see below lag deposits on mobile sandy beds & deep into expansive floodbasins. Furthermore, such data are needed to test whether we can interpret large tropical river morphology using analogies to small temperate systems. Systems in a dynamic state of response to sea level rise or an increase/contrast in sediment load would provide especially valuable insight. Last August we conducted a field campaign along the Fly and Strickland Rivers in Papua New Guinea (discharge ~5,350 CMS) and this September we investigated the Beni River in Northern Bolivia (discharge ~3,500 CMS). Results were obtained using a novel measurement method: a high-power (>4kW) dual-frequency SyQwest sub-bottom profiler customized to best image 10-20m below the river/lake bed in shallow water. We were able to distinguish sandy deposits from harder clay and silt lenses and also collected bed grab samples to verify our sonar results. Deep borehole samples (5-15m), bank samples, and push cores confirmed observations from the sonar profiling. We simultaneously collected side-scan sonar imagery plus DGPS records of water/bed elevations that could be used to parameterize numerical models. We have now analyzed these results in some detail. Findings for the Fly River include: 1) The prevalence of hard clay beneath the bed of the Lower Fly River and many locations along the Strickland River, retarding migration; 2) Unusual bed morphology along the lower Middle Fly River, where the

Deep neural networks to enable real-time multimessenger astrophysics

Science.gov (United States)

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.

Roles of deep and shallow convection and microphysics in the MJO simulated by the Model for Prediction Across Scales

Science.gov (United States)

Pilon, Romain; Zhang, Chidong; Dudhia, Jimy

2016-09-01

The November event of the Madden-Julian oscillation (MJO) during the Dynamics of North Atlantic Models (DYNAMO) field campaign was simulated using the global compressible nonhydrostatic Model for Prediction Across Scales with global coarse (60 and 15 km) and regional (the Indian Ocean) cloud-permitting (3 km) meshes. The purpose of this study is to compare roles of parameterized deep and shallow cumulus and microphysics in MJO simulations. Two cumulus schemes were used: Tiedtke and Grell-Freitas. The deep and shallow components of Tiedtke scheme can be turned on and off individually. The results reveal that microphysics alone (without cumulus parameterization) is able to produce strong signals of the MJO in precipitation with 3 km mesh and weak MJO signals with 15 km mesh. A shallow scheme (Tiedtke) along with microphysics strengthens the MJO signals but makes them less well organized on large scales. A deep cumulus scheme can either improve the large-scale organization of MJO precipitation produced by microphysics and shallow convection (Tiedtke) or impair them (Grell-Freitas). The deep scheme of Tiedtke cannot reproduce the MJO well without its shallow counterpart. The main role of shallow convection in the model is to transport moisture upward to the lower to middle troposphere. By doing so, it removes dry biases in the lower to middle troposphere, a distinct feature in simulations with weak or no MJO signals, and enhances total precipitation and diabatic heating produced by microphysics and deep cumulus schemes. Changing model grid spacing from 60 to 15 km makes a little difference in the model fidelity of reproducing the MJO. All roles of shallow convection in 15 km simulations with parameterized deep convection cannot be reproduced in 3 km simulations without parameterized deep convection. Results from this study suggest that we should pay more attention to the treatment of shallow convection and its connection to other parameterized processes for improving

AMID: Accurate Magnetic Indoor Localization Using Deep Learning

Directory of Open Access Journals (Sweden)

Namkyoung Lee

2018-05-01

Full Text Available Geomagnetic-based indoor positioning has drawn a great attention from academia and industry due to its advantage of being operable without infrastructure support and its reliable signal characteristics. However, it must overcome the problems of ambiguity that originate with the nature of geomagnetic data. Most studies manage this problem by incorporating particle filters along with inertial sensors. However, they cannot yield reliable positioning results because the inertial sensors in smartphones cannot precisely predict the movement of users. There have been attempts to recognize the magnetic sequence pattern, but these attempts are proven only in a one-dimensional space, because magnetic intensity fluctuates severely with even a slight change of locations. This paper proposes accurate magnetic indoor localization using deep learning (AMID, an indoor positioning system that recognizes magnetic sequence patterns using a deep neural network. Features are extracted from magnetic sequences, and then the deep neural network is used for classifying the sequences by patterns that are generated by nearby magnetic landmarks. Locations are estimated by detecting the landmarks. AMID manifested the proposed features and deep learning as an outstanding classifier, revealing the potential of accurate magnetic positioning with smartphone sensors alone. The landmark detection accuracy was over 80% in a two-dimensional environment.

Magnetic Fields Versus Gravity

Science.gov (United States)

Hensley, Kerry

2018-04-01

Deep within giant molecular clouds, hidden by dense gas and dust, stars form. Unprecedented data from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the intricate magnetic structureswoven throughout one of the most massive star-forming regions in the Milky Way.How Stars Are BornThe Horsehead Nebulasdense column of gas and dust is opaque to visible light, but this infrared image reveals the young stars hidden in the dust. [NASA/ESA/Hubble Heritage Team]Simple theory dictates that when a dense clump of molecular gas becomes massive enough that its self-gravity overwhelms the thermal pressure of the cloud, the gas collapses and forms a star. In reality, however, star formation is more complicated than a simple give and take between gravity and pressure. Thedusty molecular gas in stellar nurseries is permeated with magnetic fields, which are thought to impede the inward pull of gravity and slow the rate of star formation.How can we learn about the magnetic fields of distant objects? One way is by measuring dust polarization. An elongated dust grain will tend to align itself with its short axis parallel to the direction of the magnetic field. This systematic alignment of the dust grains along the magnetic field lines polarizes the dust grains emission perpendicular to the local magnetic field. This allows us to infer the direction of the magnetic field from the direction of polarization.Magnetic field orientations for protostars e2 and e8 derived from Submillimeter Array observations (panels a through c) and ALMA observations (panels d and e). Click to enlarge. [Adapted from Koch et al. 2018]Tracing Magnetic FieldsPatrick Koch (Academia Sinica, Taiwan) and collaborators used high-sensitivity ALMA observations of dust polarization to learn more about the magnetic field morphology of Milky Way star-forming region W51. W51 is one of the largest star-forming regions in our galaxy, home to high-mass protostars e2, e8, and North.The ALMA observations reveal

Phenomenology of deep-inelastic processes

International Nuclear Information System (INIS)

Moretto, L.G.

1983-03-01

The field of heavy-ion deep-inelastic reactions is reviewed with particular attention to the experimental picture. The most important degrees of freedom involved in the process are identified and illustrated with relevant experiments. Energy dissipation and mass transfer are discussed in terms of particles and/or phonons exchanged in the process. The equilibration of the fragment neutron-to-proton ratios is inspected for evidence of giant isovector resonances. The angular momentum effects are observed in the fragment angular distributions and the angular momentum transfer is inferred from the magnitude and alignment of the fragments spins. The possible sources of light particles accompanying the deep-inelastic reactions are discussed. The use of the sequentially emitted particles as angular momentum probes is illustrated. The significance and uses of a thermalized component emitted by the dinucleus is reviewed. The possible presence of Fermi jets in the prompt component is shown to be critical to the justification of the one-body theories

Deep groundwater flow at Palmottu

International Nuclear Information System (INIS)

Niini, H.; Vesterinen, M.; Tuokko, T.

1993-01-01

Further observations, measurements, and calculations aimed at determining the groundwater flow regimes and periodical variations in flow at deeper levels were carried out in the Lake Palmottu (a natural analogue study site for radioactive waste disposal in southwestern Finland) drainage basin. These water movements affect the migration of radionuclides from the Palmottu U-Th deposit. The deep water flow is essentially restricted to the bedrock fractures which developed under, and are still affected by, the stress state of the bedrock. Determination of the detailed variations was based on fracture-tectonic modelling of the 12 most significant underground water-flow channels that cross the surficial water of the Palmottu area. According to the direction of the hydraulic gradient the deep water flow is mostly outwards from the Palmottu catchment but in the westernmost section it is partly towards the centre. Estimation of the water flow through the U-Th deposit by the water-balance method is still only approximate and needs continued observation series and improved field measurements

Opportunities and Challenges in Deep Mining: A Brief Review

Directory of Open Access Journals (Sweden)

Pathegama G. Ranjith

2017-08-01

Full Text Available Mineral consumption is increasing rapidly as more consumers enter the market for minerals and as the global standard of living increases. As a result, underground mining continues to progress to deeper levels in order to tackle the mineral supply crisis in the 21st century. However, deep mining occurs in a very technical and challenging environment, in which significant innovative solutions and best practice are required and additional safety standards must be implemented in order to overcome the challenges and reap huge economic gains. These challenges include the catastrophic events that are often met in deep mining engineering: rockbursts, gas outbursts, high in situ and redistributed stresses, large deformation, squeezing and creeping rocks, and high temperature. This review paper presents the current global status of deep mining and highlights some of the newest technological achievements and opportunities associated with rock mechanics and geotechnical engineering in deep mining. Of the various technical achievements, unmanned working-faces and unmanned mines based on fully automated mining and mineral extraction processes have become important fields in the 21st century.

Gas Classification Using Deep Convolutional Neural Networks

Science.gov (United States)

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-01

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

Gas Classification Using Deep Convolutional Neural Networks.

Science.gov (United States)

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-08

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

Testing deep-sea biodiversity paradigms on abyssal nematode genera and Acantholaimus species

Science.gov (United States)

Lins, Lidia; da Silva, Maria Cristina; Neres, Patrícia; Esteves, André Morgado; Vanreusel, Ann

2018-02-01

Biodiversity patterns in the deep sea have been extensively studied in the last decades. In this study, we investigated whether reputable concepts in deep-sea ecology also explain diversity and distribution patterns of nematode genera and species in the abyss. Among them, three paradigms were tackled: (1) the deep sea is a highly diverse environment at a local scale, while on a regional and even larger geographical scale, species and genus turnover is limited; (2) the biodiversity of deep-sea nematode communities changes with the nature and amount of organic matter input from the surface; and (3) patch-mosaic dynamics of the deep-sea environment drive local diversity. To test these hypotheses, diversity and density of nematode assemblages and of species of the genus Acantholaimus were studied along two abyssal E-W transects. These two transects were situated in the Southern Ocean ( 50°S) and the North Atlantic ( 10°N). Four different hierarchical scales were used to compare biodiversity: at the scale of cores, between stations from the same region, and between regions. Results revealed that the deep sea harbours a high diversity at a local scale (alpha diversity), but that turnover can be shaped by different environmental drivers. Therefore, these results question the second part of the paradigm about limited species turnover in the deep sea. Higher surface primary productivity was correlated with greater nematode densities, whereas diversity responses to the augmentation of surface productivity showed no trend. Areas subjected to a constant and low food input revealed similar nematode communities to other oligotrophic abyssal areas, while stations under high productivity were characterized by different dominant genera and Acantholaimus species, and by a generally low local diversity. Our results corroborate the species-energy hypothesis, where productivity can set a limit to the richness of an ecosystem. Finally, we observed no correlation between sediment

Opportunities and constraints of deep water projects

International Nuclear Information System (INIS)

Anon.

1995-01-01

While oil output from deep water areas still is scarce, it however has become a reality in water depths over 300 m. Specific constraints linked to these developments lead to the selection of appropriate concepts for production supports. First deep water developments occurred off Brazil (see other articles in this issue) and the Gulf of Mexico and now expand to other areas worldwide, such as the West of Shetland discoveries, the Northern part of the Norwegian waters and potentially West Africa, the Barents sea and South-East Asia. Fixed platforms and compliant towers have shown their limits (in terms of water depth capacity) and new deep water projects mainly rely on tension leg platforms (TLP) and floaters, either FPSOs or semi-sub based. Research is at work on alternative materials for lighter flexible risers and mooring systems. Operators and manufacturers are eager to develop for the 300 m range systems and equipments that could be used with little modification for oil fields located in deeper waters. (author). 1 fig., 1 tab

Deep learning

CERN Document Server

Goodfellow, Ian; Courville, Aaron

2016-01-01

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

Simple techniques for improving deep neural network outcomes on commodity hardware

Science.gov (United States)

Colina, Nicholas Christopher A.; Perez, Carlos E.; Paraan, Francis N. C.

2017-08-01

We benchmark improvements in the performance of deep neural networks (DNN) on the MNIST data test upon imple-menting two simple modifications to the algorithm that have little overhead computational cost. First is GPU parallelization on a commodity graphics card, and second is initializing the DNN with random orthogonal weight matrices prior to optimization. Eigenspectra analysis of the weight matrices reveal that the initially orthogonal matrices remain nearly orthogonal after training. The probability distributions from which these orthogonal matrices are drawn are also shown to significantly affect the performance of these deep neural networks.

Key roles for freshwater Actinobacteria revealed by deep metagenomic sequencing.

Science.gov (United States)

Ghai, Rohit; Mizuno, Carolina Megumi; Picazo, Antonio; Camacho, Antonio; Rodriguez-Valera, Francisco

2014-12-01

Freshwater ecosystems are critical but fragile environments directly affecting society and its welfare. However, our understanding of genuinely freshwater microbial communities, constrained by our capacity to manipulate its prokaryotic participants in axenic cultures, remains very rudimentary. Even the most abundant components, freshwater Actinobacteria, remain largely unknown. Here, applying deep metagenomic sequencing to the microbial community of a freshwater reservoir, we were able to circumvent this traditional bottleneck and reconstruct de novo seven distinct streamlined actinobacterial genomes. These genomes represent three new groups of photoheterotrophic, planktonic Actinobacteria. We describe for the first time genomes of two novel clades, acMicro (Micrococcineae, related to Luna2,) and acAMD (Actinomycetales, related to acTH1). Besides, an aggregate of contigs belonged to a new branch of the Acidimicrobiales. All are estimated to have small genomes (approximately 1.2 Mb), and their GC content varied from 40 to 61%. One of the Micrococcineae genomes encodes a proteorhodopsin, a rhodopsin type reported for the first time in Actinobacteria. The remarkable potential capacity of some of these genomes to transform recalcitrant plant detrital material, particularly lignin-derived compounds, suggests close linkages between the terrestrial and aquatic realms. Moreover, abundances of Actinobacteria correlate inversely to those of Cyanobacteria that are responsible for prolonged and frequently irretrievable damage to freshwater ecosystems. This suggests that they might serve as sentinels of impending ecological catastrophes. © 2014 John Wiley & Sons Ltd.

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

Directory of Open Access Journals (Sweden)

Christian Tamburini

Full Text Available 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.

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

Science.gov (United States)

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.

Deep venous thrombosis due to massive compression by uterine myoma

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Aleksandra Brucka

2010-10-01

Full Text Available A 42-year-old woman, gravida 3, para 3 was admitted to hospital because of painful oedema of her right lower extremity. Initial physical examination revealed a gross, firm tumour filling the entire peritoneal cavity. Doppler ultrasound scan revealed a thrombus in the right common iliac vein, extending to the right femur and popliteal veins, and partially into the calf deep vein. Computed tomography confirmed the existence of an abdominal tumour probably deriving from the genital organs and the presence of a thrombus in the said veins.The patient underwent hysterectomy where a myomatous uterine was removed. She was put on subcutaneous enoxaparine and compressive therapy of the lower extremities. Such symptoms as pain and oedema receded. Control Doppler scan showed fibrinolysis, partial organization of the thrombus and final vein recanalisation. After exclusion of other risk factors of deep vein thrombosis apart from stasis, we conclude that the described pathology was the effect of compression of regional pelvic structures by a uterine myoma.