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Sample records for distinct deep short-axon

  1. Deep Levels of Processing Elicit a Distinctiveness Heuristic: Evidence from the Criterial Recollection Task

    Science.gov (United States)

    Gallo, David A.; Meadow, Nathaniel G.; Johnson, Elizabeth L.; Foster, Katherine T.

    2008-01-01

    Thinking about the meaning of studied words (deep processing) enhances memory on typical recognition tests, relative to focusing on perceptual features (shallow processing). One explanation for this levels-of-processing effect is that deep processing leads to the encoding of more distinctive representations (i.e., more unique semantic or…

  2. Unique prokaryotic consortia in geochemically distinct sediments from Red Sea Atlantis II and discovery deep brine pools.

    KAUST Repository

    Siam, Rania; Mustafa, Ghada A; Sharaf, Hazem; Moustafa, Ahmed; Ramadan, Adham R; Antunes, Andre; Bajic, Vladimir B.; Stingl, Ulrich; Marsis, Nardine G R; Coolen, Marco J L; Sogin, Mitchell; Ferreira, Ari J S; Dorry, Hamza El

    2012-01-01

    )-rich Atlantis II and one nitrogen (N)-rich Discovery Deep section contained distinct microbial populations that differed from those found in the other sediment samples examined. Proteobacteria, Actinobacteria, Cyanobacteria, Deferribacteres, and Euryarchaeota

  3. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

    Science.gov (United States)

    Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

    2016-05-01

    Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the

  4. Distinctive Microbial Community Structure in Highly Stratified Deep-Sea Brine Water Columns

    KAUST Repository

    Bougouffa, Salim; Yang, J. K.; Lee, O. O.; Wang, Y.; Batang, Zenon B.; Al-Suwailem, Abdulaziz M.; Qian, P. Y.

    2013-01-01

    Atlantis II and Discovery are two hydrothermal and hypersaline deep-sea pools in the Red Sea rift that are characterized by strong thermohalo-stratification and temperatures steadily peaking near the bottom. We conducted comprehensive vertical profiling of the microbial populations in both pools and highlighted the influential environmental factors. Pyrosequencing of the 16S rRNA genes revealed shifts in community structures vis-à-vis depth. High diversity and low abundance were features of the deepest convective layers despite the low cell density. Surprisingly, the brine interfaces had significantly higher cell counts than the overlying deep-sea water, yet they were lowest in diversity. Vertical stratification of the bacterial populations was apparent as we moved from the Alphaproteobacteria-dominated deep sea to the Planctomycetaceae- or Deferribacteres-dominated interfaces to the Gammaproteobacteria-dominated brine layers. Archaeal marine group I was dominant in the deep-sea water and interfaces, while several euryarchaeotic groups increased in the brine. Across sites, microbial phylotypes and abundances varied substantially in the brine interface of Discovery compared with Atlantis II, despite the near-identical populations in the overlying deep-sea waters. The lowest convective layers harbored interestingly similar microbial communities, even though temperature and heavy metal concentrations were very different. Multivariate analysis indicated that temperature and salinity were the major influences shaping the communities. The harsh conditions and the low-abundance phylotypes could explain the observed correlation in the brine pools.

  5. Distinctive Microbial Community Structure in Highly Stratified Deep-Sea Brine Water Columns

    KAUST Repository

    Bougouffa, Salim

    2013-03-29

    Atlantis II and Discovery are two hydrothermal and hypersaline deep-sea pools in the Red Sea rift that are characterized by strong thermohalo-stratification and temperatures steadily peaking near the bottom. We conducted comprehensive vertical profiling of the microbial populations in both pools and highlighted the influential environmental factors. Pyrosequencing of the 16S rRNA genes revealed shifts in community structures vis-à-vis depth. High diversity and low abundance were features of the deepest convective layers despite the low cell density. Surprisingly, the brine interfaces had significantly higher cell counts than the overlying deep-sea water, yet they were lowest in diversity. Vertical stratification of the bacterial populations was apparent as we moved from the Alphaproteobacteria-dominated deep sea to the Planctomycetaceae- or Deferribacteres-dominated interfaces to the Gammaproteobacteria-dominated brine layers. Archaeal marine group I was dominant in the deep-sea water and interfaces, while several euryarchaeotic groups increased in the brine. Across sites, microbial phylotypes and abundances varied substantially in the brine interface of Discovery compared with Atlantis II, despite the near-identical populations in the overlying deep-sea waters. The lowest convective layers harbored interestingly similar microbial communities, even though temperature and heavy metal concentrations were very different. Multivariate analysis indicated that temperature and salinity were the major influences shaping the communities. The harsh conditions and the low-abundance phylotypes could explain the observed correlation in the brine pools.

  6. Olfactory bulb short axon cell release of GABA and dopamine produces a temporally biphasic inhibition-excitation response in external tufted cells.

    Science.gov (United States)

    Liu, Shaolin; Plachez, Celine; Shao, Zuoyi; Puche, Adam; Shipley, Michael T

    2013-02-13

    Evidence for coexpression of two or more classic neurotransmitters in neurons has increased, but less is known about cotransmission. Ventral tegmental area (VTA) neurons corelease dopamine (DA), the excitatory transmitter glutamate, and the inhibitory transmitter GABA onto target cells in the striatum. Olfactory bulb (OB) short axon cells (SACs) form interglomerular connections and coexpress markers for DA and GABA. Using an optogenetic approach, we provide evidence that mouse OB SACs release both GABA and DA onto external tufted cells (ETCs) in other glomeruli. Optical activation of channelrhodopsin specifically expressed in DAergic SACs produced a GABA(A) receptor-mediated monosynaptic inhibitory response, followed by DA-D(1)-like receptor-mediated excitatory response in ETCs. The GABA(A) receptor-mediated hyperpolarization activates I(h) current in ETCs; synaptically released DA increases I(h), which enhances postinhibitory rebound spiking. Thus, the opposing actions of synaptically released GABA and DA are functionally integrated by I(h) to generate an inhibition-to-excitation "switch" in ETCs. Consistent with the established role of I(h) in ETC burst firing, we show that endogenous DA release increases ETC spontaneous bursting frequency. ETCs transmit sensory signals to mitral/tufted output neurons and drive intraglomerular inhibition to shape glomerulus output to downstream olfactory networks. GABA and DA cotransmission from SACs to ETCs may play a key role in regulating output coding across the glomerular array.

  7. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease

    NARCIS (Netherlands)

    Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

    2016-01-01

    Oswal et al. characterise the effect of deep brain stimulation (DBS) on STN-cortical synchronisation in Parkinson-s disease. They propose that cortical driving of the STN in beta frequencies is subdivided anatomically and spectrally, corresponding to the hyperdirect and indirect pathways. DBS

  8. Unique Prokaryotic Consortia in Geochemically Distinct Sediments from Red Sea Atlantis II and Discovery Deep Brine Pools

    Science.gov (United States)

    Siam, Rania; Mustafa, Ghada A.; Sharaf, Hazem; Moustafa, Ahmed; Ramadan, Adham R.; Antunes, Andre; Bajic, Vladimir B.; Stingl, Uli; Marsis, Nardine G. R.; Coolen, Marco J. L.; Sogin, Mitchell; Ferreira, Ari J. S.; Dorry, Hamza El

    2012-01-01

    The seafloor is a unique environment, which allows insights into how geochemical processes affect the diversity of biological life. Among its diverse ecosystems are deep-sea brine pools - water bodies characterized by a unique combination of extreme conditions. The ‘polyextremophiles’ that constitute the microbial assemblage of these deep hot brines have not been comprehensively studied. We report a comparative taxonomic analysis of the prokaryotic communities of the sediments directly below the Red Sea brine pools, namely, Atlantis II, Discovery, Chain Deep, and an adjacent brine-influenced site. Analyses of sediment samples and high-throughput pyrosequencing of PCR-amplified environmental 16S ribosomal RNA genes (16S rDNA) revealed that one sulfur (S)-rich Atlantis II and one nitrogen (N)-rich Discovery Deep section contained distinct microbial populations that differed from those found in the other sediment samples examined. Proteobacteria, Actinobacteria, Cyanobacteria, Deferribacteres, and Euryarchaeota were the most abundant bacterial and archaeal phyla in both the S- and N-rich sections. Relative abundance-based hierarchical clustering of the 16S rDNA pyrotags assigned to major taxonomic groups allowed us to categorize the archaeal and bacterial communities into three major and distinct groups; group I was unique to the S-rich Atlantis II section (ATII-1), group II was characteristic for the N-rich Discovery sample (DD-1), and group III reflected the composition of the remaining sediments. Many of the groups detected in the S-rich Atlantis II section are likely to play a dominant role in the cycling of methane and sulfur due to their phylogenetic affiliations with bacteria and archaea involved in anaerobic methane oxidation and sulfate reduction. PMID:22916172

  9. Unique prokaryotic consortia in geochemically distinct sediments from Red Sea Atlantis II and discovery deep brine pools.

    Directory of Open Access Journals (Sweden)

    Rania Siam

    Full Text Available The seafloor is a unique environment, which allows insights into how geochemical processes affect the diversity of biological life. Among its diverse ecosystems are deep-sea brine pools - water bodies characterized by a unique combination of extreme conditions. The 'polyextremophiles' that constitute the microbial assemblage of these deep hot brines have not been comprehensively studied. We report a comparative taxonomic analysis of the prokaryotic communities of the sediments directly below the Red Sea brine pools, namely, Atlantis II, Discovery, Chain Deep, and an adjacent brine-influenced site. Analyses of sediment samples and high-throughput pyrosequencing of PCR-amplified environmental 16S ribosomal RNA genes (16S rDNA revealed that one sulfur (S-rich Atlantis II and one nitrogen (N-rich Discovery Deep section contained distinct microbial populations that differed from those found in the other sediment samples examined. Proteobacteria, Actinobacteria, Cyanobacteria, Deferribacteres, and Euryarchaeota were the most abundant bacterial and archaeal phyla in both the S- and N-rich sections. Relative abundance-based hierarchical clustering of the 16S rDNA pyrotags assigned to major taxonomic groups allowed us to categorize the archaeal and bacterial communities into three major and distinct groups; group I was unique to the S-rich Atlantis II section (ATII-1, group II was characteristic for the N-rich Discovery sample (DD-1, and group III reflected the composition of the remaining sediments. Many of the groups detected in the S-rich Atlantis II section are likely to play a dominant role in the cycling of methane and sulfur due to their phylogenetic affiliations with bacteria and archaea involved in anaerobic methane oxidation and sulfate reduction.

  10. Unique prokaryotic consortia in geochemically distinct sediments from Red Sea Atlantis II and discovery deep brine pools.

    KAUST Repository

    Siam, Rania

    2012-08-20

    The seafloor is a unique environment, which allows insights into how geochemical processes affect the diversity of biological life. Among its diverse ecosystems are deep-sea brine pools - water bodies characterized by a unique combination of extreme conditions. The \\'polyextremophiles\\' that constitute the microbial assemblage of these deep hot brines have not been comprehensively studied. We report a comparative taxonomic analysis of the prokaryotic communities of the sediments directly below the Red Sea brine pools, namely, Atlantis II, Discovery, Chain Deep, and an adjacent brine-influenced site. Analyses of sediment samples and high-throughput pyrosequencing of PCR-amplified environmental 16S ribosomal RNA genes (16S rDNA) revealed that one sulfur (S)-rich Atlantis II and one nitrogen (N)-rich Discovery Deep section contained distinct microbial populations that differed from those found in the other sediment samples examined. Proteobacteria, Actinobacteria, Cyanobacteria, Deferribacteres, and Euryarchaeota were the most abundant bacterial and archaeal phyla in both the S- and N-rich sections. Relative abundance-based hierarchical clustering of the 16S rDNA pyrotags assigned to major taxonomic groups allowed us to categorize the archaeal and bacterial communities into three major and distinct groups; group I was unique to the S-rich Atlantis II section (ATII-1), group II was characteristic for the N-rich Discovery sample (DD-1), and group III reflected the composition of the remaining sediments. Many of the groups detected in the S-rich Atlantis II section are likely to play a dominant role in the cycling of methane and sulfur due to their phylogenetic affiliations with bacteria and archaea involved in anaerobic methane oxidation and sulfate reduction.

  11. deep-orange and carnation define distinct stages in late endosomal biogenesis in Drosophila melanogaster

    OpenAIRE

    Sriram, V.; Krishnan, K.S.; Mayor, Satyajit

    2003-01-01

    Endosomal degradation is severely impaired in primary hemocytes from larvae of eye color mutants of Drosophila. Using high resolution imaging and immunofluorescence microscopy in these cells, products of eye color genes, deep-orange (dor) and carnation (car), are localized to large multivesicular Rab7-positive late endosomes containing Golgi-derived enzymes. These structures mature into small sized Dor-negative, Car-positive structures, which subsequently fuse to form tubular lysosomes. Defec...

  12. deep-orange and carnation define distinct stages in late endosomal biogenesis in Drosophila melanogaster.

    Science.gov (United States)

    Sriram, V; Krishnan, K S; Mayor, Satyajit

    2003-05-12

    Endosomal degradation is severely impaired in primary hemocytes from larvae of eye color mutants of Drosophila. Using high resolution imaging and immunofluorescence microscopy in these cells, products of eye color genes, deep-orange (dor) and carnation (car), are localized to large multivesicular Rab7-positive late endosomes containing Golgi-derived enzymes. These structures mature into small sized Dor-negative, Car-positive structures, which subsequently fuse to form tubular lysosomes. Defective endosomal degradation in mutant alleles of dor results from a failure of Golgi-derived vesicles to fuse with morphologically arrested Rab7-positive large sized endosomes, which are, however, normally acidified and mature with wild-type kinetics. This locates the site of Dor function to fusion of Golgi-derived vesicles with the large Rab7-positive endocytic compartments. In contrast, endosomal degradation is not considerably affected in car1 mutant; fusion of Golgi-derived vesicles and maturation of large sized endosomes is normal. However, removal of Dor from small sized Car-positive endosomes is slowed, and subsequent fusion with tubular lysosomes is abolished. Overexpression of Dor in car1 mutant aggravates this defect, implicating Car in the removal of Dor from endosomes. This suggests that, in addition to an independent role in fusion with tubular lysosomes, the Sec1p homologue, Car, regulates Dor function.

  13. Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

    Science.gov (United States)

    Kim, Jung H; Dhanasekaran, Saravana M; Prensner, John R; Cao, Xuhong; Robinson, Daniel; Kalyana-Sundaram, Shanker; Huang, Christina; Shankar, Sunita; Jing, Xiaojun; Iyer, Matthew; Hu, Ming; Sam, Lee; Grasso, Catherine; Maher, Christopher A; Palanisamy, Nallasivam; Mehra, Rohit; Kominsky, Hal D; Siddiqui, Javed; Yu, Jindan; Qin, Zhaohui S; Chinnaiyan, Arul M

    2011-07-01

    Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.

  14. Electroretinogram (ERG) to photic stimuli should be carefully distinct from photic brainstem reflex in patients with deep coma.

    Science.gov (United States)

    Mitsuhashi, Masahiro; Hitomi, Takefumi; Aoyama, Akihiro; Kaido, Toshimi; Ikeda, Akio; Takahashi, Ryosuke

    2017-08-31

    Patient 1: A 35-year-old woman became deep coma because of intracranial hemorrhage after pulmonary surgery. Patient 2: A 39-year-old woman became deep coma because of cerebellar hemorrhage after hepatic surgery. Scalp-recorded digital electroencephalography (EEG) showed electrocerebral inactivity in both cases. In addition, both EEG showed repetitive discharges at bilateral frontopolar electrodes in response to photic stimuli. The amplitude and latency of the discharges was 17 μV and 24 msec in case 1, and 9 μV and 27 msec in case 2 respectively. The activity at left frontopolar electrode disappeared after coverage of the ipsilateral eye. Based on these findings, we could exclude the possibility of brainstem response and judged it as electroretinogram (ERG). Photic stimulation is a useful activation method in EEG recording, and we can also evaluate brainstem function by checking photic blink reflex if it is evoked. However, we should be cautious about the distinction of ERG from photic blink reflex when brain death is clinically suspected.

  15. Deep-sea seabed habitats: Do they support distinct mega-epifaunal communities that have different vulnerabilities to anthropogenic disturbance?

    Science.gov (United States)

    Bowden, David A.; Rowden, Ashley A.; Leduc, Daniel; Beaumont, Jennifer; Clark, Malcolm R.

    2016-01-01

    Growing economic interest in seabed resources in the deep-sea highlights the need for information about the spatial distribution and vulnerability to disturbance of benthic habitats and fauna. Categorisation of seabed habitats for management is often based on topographic features such as canyons and seamounts that can be distinguished using regional bathymetry ('mega-habitats'). This is practical but because such habitats are contiguous with others, there is potential for overlap in the communities associated with them. Because concepts of habitat and community vulnerability are based on the traits of individual taxa, the nature and extent of differences between communities have implications for strategies to manage the environmental effects of resource use. Using towed video camera transects, we surveyed mega-epifaunal communities of three topographically-defined habitats (canyon, seamount or knoll, and continental slope) and two physico-chemically defined meso-scale habitats (cold seep and hydrothermal vent) in two regions off New Zealand to assess whether each supports a distinct type of community. Cold seep and hydrothermal vent communities were strongly distinct from those in other habitats. Across the other habitats, however, distinctions between communities were often weak and were not consistent between regions. Dissimilarities among communities across all habitats were stronger and the density of filter-feeding taxa was higher in the Bay of Plenty than on the Hikurangi Margin, whereas densities of predatory and scavenging taxa were higher on the Hikurangi Margin. Substratum diversity at small spatial scales (the general utility of topographically-defined mega-habitats in environmental management, (2) fine-scale survey of individual features is necessary to identify the locations, characteristics, and extents of ecologically important or vulnerable seabed communities, and (3) evaluation of habitat vulnerability to future events should be in the context of

  16. Distinct Bacterial Microbiomes Associate with the Deep-Sea Coral Eguchipsammia fistula from the Red Sea and from Aquaria Settings

    KAUST Repository

    Röthig, Till

    2017-08-10

    Microbial communities associated with deep-sea corals are beginning to be studied in earnest and the contribution of the microbiome to host organismal function remains to be investigated. In this regard, the ability of the microbiome to adjust to prevailing environmental conditions might provide clues to its functional importance. In this study, we characterized bacterial community composition associated with the deep-sea coral Eguchipsammia fistula under natural (in situ) and aquaria (ex situ) settings using 16S rRNA gene amplicon sequencing. We compared freshly collected Red Sea coral specimens with those reared for >1 year at conditions that partially differed from the natural environment, in particular regarding increased oxygen and food availability under ex situ conditions. We found substantial differences between the microbiomes associated with corals under both environmental settings. The core microbiome comprised only six bacterial taxa consistently present in all corals, whereas the majority of bacteria were exclusively associated either with freshly collected corals or corals under long-term reared aquaria settings. Putative functional profiling of microbial communities showed that corals in their natural habitat were enriched for processes indicative of a carbon- and nitrogen-limited environment, which might be reflective of differences in diet under in situ and ex situ conditions. The ability of E. fistula to harbor distinct microbiomes under different environmental settings might contribute to the flexibility and phenotypic plasticity of this cosmopolitan coral. Future efforts should further assess the role of these different bacteria in holobiont function, in particular since E. fistula is naturally present in markedly different environments.

  17. Distinct Bacterial Microbiomes Associate with the Deep-Sea Coral Eguchipsammia fistula from the Red Sea and from Aquaria Settings

    KAUST Repository

    Rö thig, Till; Roik, Anna Krystyna; Yum, Lauren; Voolstra, Christian R.

    2017-01-01

    Microbial communities associated with deep-sea corals are beginning to be studied in earnest and the contribution of the microbiome to host organismal function remains to be investigated. In this regard, the ability of the microbiome to adjust to prevailing environmental conditions might provide clues to its functional importance. In this study, we characterized bacterial community composition associated with the deep-sea coral Eguchipsammia fistula under natural (in situ) and aquaria (ex situ) settings using 16S rRNA gene amplicon sequencing. We compared freshly collected Red Sea coral specimens with those reared for >1 year at conditions that partially differed from the natural environment, in particular regarding increased oxygen and food availability under ex situ conditions. We found substantial differences between the microbiomes associated with corals under both environmental settings. The core microbiome comprised only six bacterial taxa consistently present in all corals, whereas the majority of bacteria were exclusively associated either with freshly collected corals or corals under long-term reared aquaria settings. Putative functional profiling of microbial communities showed that corals in their natural habitat were enriched for processes indicative of a carbon- and nitrogen-limited environment, which might be reflective of differences in diet under in situ and ex situ conditions. The ability of E. fistula to harbor distinct microbiomes under different environmental settings might contribute to the flexibility and phenotypic plasticity of this cosmopolitan coral. Future efforts should further assess the role of these different bacteria in holobiont function, in particular since E. fistula is naturally present in markedly different environments.

  18. Subsurface Rock Physical Properties by Downhole Loggings - Case Studies of Continental Deep Drilling in Kanto Distinct, Japan

    Science.gov (United States)

    Omura, K.

    2014-12-01

    In recent years, many examples of physical logging have been carried out in deep boreholes. The loggings are direct in-situ measurements of rock physical properties under the ground. They provide significant basic data for the geological, geophysical and geotechnical investigations, e.g., tectonic history, seismic wave propagation, and ground motion prediction. Since about 1980's, Natl. Res. Inst. for Earth Sci. and Disast. Prev. (NIED) dug deep boreholes (from 200m to 3000m depth) in sedimentary basin of Kanto distinct, Japan, for purposes of installing seismographs and hydrological instruments, and in-situ stress and pore pressure measurements. At that time, downhole physical loggings were conducted in the boreholes: spontaneous potential, electrical resistance, elastic wave velocity, formation density, neutron porosity, total gamma ray, caliper, temperature loggings. In many cases, digital data values were provided every 2m or 1m or 0.1m. In other cases, we read printed graphs of logging plots and got digital data values. Data from about 30 boreholes are compiled. Especially, particular change of logging data at the depth of an interface between a shallow part (soft sedimentary rock) and a base rock (equivalent to hard pre-Neogene rock) is examined. In this presentation, the correlations among physical properties of rock (especially, formation density, elastic wave velocity and electrical resistance) are introduced and the relation to the lithology is discussed. Formation density, elastic wave velocity and electric resistance data indicate the data are divide in two groups that are higher or lower than 2.5g/cm3: the one correspond to a shallow part and the other correspond to a base rock part. In each group, the elastic wave velocity and electric resistance increase with increase of formation density. However the rates of increases in the shallow part are smaller than in the base rock part. The shallow part has lower degree of solidification and higher porosity

  19. Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

    Science.gov (United States)

    Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

    2018-03-07

    Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

  20. Evidence for two distinct defects contributing to the H4 deep-level transient spectroscopy peak in electron-irradiated InP

    International Nuclear Information System (INIS)

    Darwich, R.; Massarani, B.; Kaaka, M.; Awad, F.

    2000-01-01

    Deep-level transient spectroscopy (DLTS) has been used to study the dominant deep-level H4 produced in InP by electron irradiation. The characteristics of the H4 peak in Zn-doped Inp has been studied as a function of pulse duration (t p ) before and after annealing. The results show that at least two traps contribute to the H4 peak: one is a fast trap (labeled H4 f ) and the other is a show trap (labeled H4 s ). This is show through several results concerning the activation energy, the capture cross section, the full width at half-maximum, and the peak temperature shift. It is shown that both traps are irradiation defects created in P sublattice. (authors)

  1. 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

  2. Deep sequencing of small RNA libraries from human prostate epithelial and stromal cells reveal distinct pattern of microRNAs primarily predicted to target growth factors.

    Science.gov (United States)

    Singh, Savita; Zheng, Yun; Jagadeeswaran, Guru; Ebron, Jey Sabith; Sikand, Kavleen; Gupta, Sanjay; Sunker, Ramanjulu; Shukla, Girish C

    2016-02-28

    Complex epithelial and stromal cell interactions are required during the development and progression of prostate cancer. Regulatory small non-coding microRNAs (miRNAs) participate in the spatiotemporal regulation of messenger RNA (mRNA) and regulation of translation affecting a large number of genes involved in prostate carcinogenesis. In this study, through deep-sequencing of size fractionated small RNA libraries we profiled the miRNAs of prostate epithelial (PrEC) and stromal (PrSC) cells. Over 50 million reads were obtained for PrEC in which 860,468 were unique sequences. Similarly, nearly 76 million reads for PrSC were obtained in which over 1 million were unique reads. Expression of many miRNAs of broadly conserved and poorly conserved miRNA families were identified. Sixteen highly expressed miRNAs with significant change in expression in PrSC than PrEC were further analyzed in silico. ConsensusPathDB showed the target genes of these miRNAs were significantly involved in adherence junction, cell adhesion, EGRF, TGF-β and androgen signaling. Let-7 family of tumor-suppressor miRNAs expression was highly pervasive in both, PrEC and PrSC cells. In addition, we have also identified several miRNAs that are unique to PrEC or PrSC cells and their predicted putative targets are a group of transcription factors. This study provides perspective on the miRNA expression in PrEC and PrSC, and reveals a global trend in miRNA interactome. We conclude that the most abundant miRNAs are potential regulators of development and differentiation of the prostate gland by targeting a set of growth factors. Additionally, high level expression of the most members of let-7 family miRNAs suggests their role in the fine tuning of the growth and proliferation of prostate epithelial and stromal cells. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Distinctive Citizenship

    DEFF Research Database (Denmark)

    Kaur, Ravinder

    2009-01-01

    The refugee, in India's Partition history, appears as an enigmatic construct - part pitiful, part heroic, though mostly shorn of agency - representing the surface of the human tragedy of Partition. Yet this archetype masks the undercurrent of social distinctions that produced hierarchies of post...

  4. Quantum Distinction: Quantum Distinctiones!

    OpenAIRE

    Zeps, Dainis

    2009-01-01

    10 pages; How many distinctions, in Latin, quantum distinctiones. We suggest approach of anthropic principle based on anthropic reference system which should be applied equally both in theoretical physics and in mathematics. We come to principle that within reference system of life subject of mathematics (that of thinking) should be equated with subject of physics (that of nature). For this reason we enter notions of series of distinctions, quantum distinction, and argue that quantum distinct...

  5. Deep frying

    NARCIS (Netherlands)

    Koerten, van K.N.

    2016-01-01

    Deep frying is one of the most used methods in the food processing industry. Though practically any food can be fried, French fries are probably the most well-known deep fried products. The popularity of French fries stems from their unique taste and texture, a crispy outside with a mealy soft

  6. 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...

  7. Intergroup Leadership Across Distinct Subgroups and Identities.

    Science.gov (United States)

    Rast, David E; Hogg, Michael A; van Knippenberg, Daan

    2018-03-01

    Resolving intergroup conflict is a significant and often arduous leadership challenge, yet existing theory and research rarely, if ever, discuss or examine this situation. Leaders confront a significant challenge when they provide leadership across deep divisions between distinct subgroups defined by self-contained identities-The challenge is to avoid provoking subgroup identity distinctiveness threat. Drawing on intergroup leadership theory, three studies were conducted to test the core hypothesis that, where identity threat exists, leaders promoting an intergroup relational identity will be better evaluated and are more effective than leaders promoting a collective identity; in the absence of threat, leaders promoting a collective identity will prevail. Studies 1 and 2 ( N = 170; N = 120) supported this general proposition. Study 3 ( N = 136) extended these findings, showing that leaders promoting an intergroup relational identity, but not a collective identity, improved intergroup attitudes when participants experienced an identity distinctiveness threat.

  8. Deep Learning

    DEFF Research Database (Denmark)

    Jensen, Morten Bornø; Bahnsen, Chris Holmberg; Nasrollahi, Kamal

    2018-01-01

    I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning.......I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning....

  9. 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

  10. How to study deep roots - and why it matters

    OpenAIRE

    Maeght, Jean-Luc; Rewald, B.; Pierret, Alain

    2013-01-01

    The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of "deep roots" is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydr...

  11. Deep smarts.

    Science.gov (United States)

    Leonard, Dorothy; Swap, Walter

    2004-09-01

    When a person sizes up a complex situation and rapidly comes to a decision that proves to be not just good but brilliant, you think, "That was smart." After you watch him do this a few times, you realize you're in the presence of something special. It's not raw brainpower, though that helps. It's not emotional intelligence, either, though that, too, is often involved. It's deep smarts. Deep smarts are not philosophical--they're not"wisdom" in that sense, but they're as close to wisdom as business gets. You see them in the manager who understands when and how to move into a new international market, in the executive who knows just what kind of talk to give when her organization is in crisis, in the technician who can track a product failure back to an interaction between independently produced elements. These are people whose knowledge would be hard to purchase on the open market. Their insight is based on know-how more than on know-what; it comprises a system view as well as expertise in individual areas. Because deep smarts are experienced based and often context specific, they can't be produced overnight or readily imported into an organization. It takes years for an individual to develop them--and no time at all for an organization to lose them when a valued veteran walks out the door. They can be taught, however, with the right techniques. Drawing on their forthcoming book Deep Smarts, Dorothy Leonard and Walter Swap say the best way to transfer such expertise to novices--and, on a larger scale, to make individual knowledge institutional--isn't through PowerPoint slides, a Web site of best practices, online training, project reports, or lectures. Rather, the sage needs to teach the neophyte individually how to draw wisdom from experience. Companies have to be willing to dedicate time and effort to such extensive training, but the investment more than pays for itself.

  12. 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

  13. Touch communicates distinct emotions.

    Science.gov (United States)

    Hertenstein, Matthew J; Keltner, Dacher; App, Betsy; Bulleit, Brittany A; Jaskolka, Ariane R

    2006-08-01

    The study of emotional signaling has focused almost exclusively on the face and voice. In 2 studies, the authors investigated whether people can identify emotions from the experience of being touched by a stranger on the arm (without seeing the touch). In the 3rd study, they investigated whether observers can identify emotions from watching someone being touched on the arm. Two kinds of evidence suggest that humans can communicate numerous emotions with touch. First, participants in the United States (Study 1) and Spain (Study 2) could decode anger, fear, disgust, love, gratitude, and sympathy via touch at much-better-than-chance levels. Second, fine-grained coding documented specific touch behaviors associated with different emotions. In Study 3, the authors provide evidence that participants can accurately decode distinct emotions by merely watching others communicate via touch. The findings are discussed in terms of their contributions to affective science and the evolution of altruism and cooperation. (c) 2006 APA, all rights reserved

  14. Distinction between epigenic and hypogenic maze caves

    Science.gov (United States)

    Palmer, Arthur N.

    2011-11-01

    Certain caves formed by dissolution of bedrock have maze patterns composed of closed loops in which many intersecting fractures or pores have enlarged simultaneously. Their origin can be epigenic (by shallow circulation of meteoric groundwater) or hypogenic (by rising groundwater or production of deep-seated solutional aggressiveness). Epigenic mazes form by diffuse infiltration through a permeable insoluble caprock or by floodwater supplied by sinking streams. Most hypogenic caves involve deep sources of aggressiveness. Transverse hypogenic cave origin is a recently proposed concept in which groundwater of mainly meteoric origin rises across strata in the distal portions of large flow systems, to form mazes in soluble rock sandwiched between permeable but insoluble strata. The distinction between maze types is debated and is usually based on examination of diagnostic cave features and relation of caves to their regional setting. In this paper, the principles of mass transfer are applied to clarify the limits of each model, to show how cave origin is related to groundwater discharge, dissolution rate, and time. The results show that diffuse infiltration and floodwater can each form maze caves at geologically feasible rates (typically within 500 ka). Transverse hypogenic mazes in limestone, to enlarge significantly within 1 Ma, require an unusually high permeability of the non-carbonate beds (generally ≥ 10-4 cm/s), large discharge, and calcite saturation no greater than 90%, which is rare in deep diffuse flow in sedimentary rocks. Deep sources of aggressiveness are usually required. The origin of caves by transverse hypogenic flow is much more favorable in evaporite rocks than in carbonate rocks.

  15. 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...

  16. Greedy Deep Dictionary Learning

    OpenAIRE

    Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank

    2016-01-01

    In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...

  17. Counselor Identity: Conformity or Distinction?

    Science.gov (United States)

    McLaughlin, Jerry E.; Boettcher, Kathryn

    2009-01-01

    The authors explore 3 debates in other disciplines similar to counseling's identity debate in order to learn about common themes and outcomes. Conformity, distinction, and cohesion emerged as common themes. They conclude that counselors should retain their distinctive, humanistic approach rather than conforming to the dominant, medical approach.

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

    Science.gov (United States)

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

    2010-01-01

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

  19. Taoism and Deep Ecology.

    Science.gov (United States)

    Sylvan, Richard; Bennett, David

    1988-01-01

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

  20. Deep Incremental Boosting

    OpenAIRE

    Mosca, Alan; Magoulas, George D

    2017-01-01

    This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each incremental Ensemble member. We show a set of experiments that outlines some preliminary results on some common Deep Learning datasets and discuss the potential improvements Deep In...

  1. Deep Space Telecommunications

    Science.gov (United States)

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

    2000-01-01

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

  2. Distinction

    OpenAIRE

    2010-01-01

    Pr Serge Haroche La Médaille d’or 2009 du CNRS est décernée au Pr Serge Haroche, titulaire de la chaire de Physique quantique depuis 2001. Serge Haroche est spécialiste de physique atomique et d’optique quantique. Il est l’un des fondateurs de l’électrodynamique quantique en cavité, domaine qui permet, par des expériences conceptuellement simples, d’éclairer les fondements de la théorie quantique et de réaliser des prototypes de systèmes de traitement quantique de l’information. Serge Haroche...

  3. Genetic divergence correlates with morphological and ecological subdivision in the deep-water elk kelp, Pelagophycus porra (phaeophyceae)

    NARCIS (Netherlands)

    Miller, KA; Olsen, JL; Stam, WT

    2000-01-01

    Pelagophycus porra (Leman) Setchell has a narrow distribution confined to deep water from the Channel Islands off the southern California coast to central Baja California, Mexico. Distinct morphotypes are consistently correlated with distinctive habitats, that is, windward exposures characterized by

  4. Deep learning with Python

    CERN Document Server

    Chollet, Francois

    2018-01-01

    DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

  5. Deep learning evaluation using deep linguistic processing

    OpenAIRE

    Kuhnle, Alexander; Copestake, Ann

    2017-01-01

    We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value ...

  6. Defining poverty as distinctively human

    Directory of Open Access Journals (Sweden)

    H.P.P. Lötter

    2007-05-01

    Full Text Available While it is relatively easy for most people to identify human beings suffering from poverty, it is rather more difficult to come to a proper understanding of poverty. In this article the author wants to deepen our understanding of poverty by interpreting the conventional definitions of poverty in a new light. The article starts with a defence of a claim that poverty is a concept uniquely applicable to humans. It then present a critical discussion of the distinction between absolute and relative poverty and it is then argued that a revision of this distinction can provide general standards applicable to humans everywhere.

  7. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  8. Deep Vein Thrombosis

    African Journals Online (AJOL)

    OWNER

    Deep Vein Thrombosis: Risk Factors and Prevention in Surgical Patients. Deep Vein ... preventable morbidity and mortality in hospitalized surgical patients. ... the elderly.3,4 It is very rare before the age ... depends on the risk level; therefore an .... but also in the post-operative period. ... is continuing uncertainty regarding.

  9. 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 ...

  10. 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.

  11. Deep subsurface microbial processes

    Science.gov (United States)

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

    1995-01-01

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

  12. Presidential address: distinction or extinction.

    Science.gov (United States)

    Pressman, Barry D

    2008-10-01

    Despite its continuing scientific successes in imaging, radiology as a specialty is faced with a very difficult and competitive environment. Nonradiologists are more and more interested in vertically integrating imaging into their practices, while teleradiology and picture archiving and communication systems are resulting in the greater isolation of radiologists. Commoditization is a realistic and devastating threat to the survival and professionalism of the specialty. To remain viable as a specialty, radiologists must elevate their practice by subspecializing, becoming more involved with clinical care, and actively interacting with patients and referring clinicians. Distinction will prevent extinction.

  13. Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution.

    Science.gov (United States)

    Kendall, Michelle; Colijn, Caroline

    2016-10-01

    Evolutionary relationships are frequently described by phylogenetic trees, but a central barrier in many fields is the difficulty of interpreting data containing conflicting phylogenetic signals. We present a metric-based method for comparing trees which extracts distinct alternative evolutionary relationships embedded in data. We demonstrate detection and resolution of phylogenetic uncertainty in a recent study of anole lizards, leading to alternate hypotheses about their evolutionary relationships. We use our approach to compare trees derived from different genes of Ebolavirus and find that the VP30 gene has a distinct phylogenetic signature composed of three alternatives that differ in the deep branching structure. phylogenetics, evolution, tree metrics, genetics, sequencing. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  14. The True Self: A Psychological Concept Distinct From the Self.

    Science.gov (United States)

    Strohminger, Nina; Knobe, Joshua; Newman, George

    2017-07-01

    A long tradition of psychological research has explored the distinction between characteristics that are part of the self and those that lie outside of it. Recently, a surge of research has begun examining a further distinction. Even among characteristics that are internal to the self, people pick out a subset as belonging to the true self. These factors are judged as making people who they really are, deep down. In this paper, we introduce the concept of the true self and identify features that distinguish people's understanding of the true self from their understanding of the self more generally. In particular, we consider recent findings that the true self is perceived as positive and moral and that this tendency is actor-observer invariant and cross-culturally stable. We then explore possible explanations for these findings and discuss their implications for a variety of issues in psychology.

  15. Deep Water Survey Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The deep water biodiversity surveys explore and describe the biodiversity of the bathy- and bentho-pelagic nekton using Midwater and bottom trawls centered in the...

  16. Deep Space Habitat Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Deep Space Habitat was closed out at the end of Fiscal Year 2013 (September 30, 2013). Results and select content have been incorporated into the new Exploration...

  17. Deep Learning in Neuroradiology.

    Science.gov (United States)

    Zaharchuk, G; Gong, E; Wintermark, M; Rubin, D; Langlotz, C P

    2018-02-01

    Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging. Because of the high volume and wealth of multimodal imaging information acquired in typical studies, neuroradiology is poised to be an early adopter of deep learning. Compelling deep learning research applications have been demonstrated, and their use is likely to grow rapidly. This review article describes the reasons, outlines the basic methods used to train and test deep learning models, and presents a brief overview of current and potential clinical applications with an emphasis on how they are likely to change future neuroradiology practice. Facility with these methods among neuroimaging researchers and clinicians will be important to channel and harness the vast potential of this new method. © 2018 by American Journal of Neuroradiology.

  18. Deep inelastic lepton scattering

    International Nuclear Information System (INIS)

    Nachtmann, O.

    1977-01-01

    Deep inelastic electron (muon) nucleon and neutrino nucleon scattering as well as electron positron annihilation into hadrons are reviewed from a theoretical point of view. The emphasis is placed on comparisons of quantum chromodynamics with the data. (orig.) [de

  19. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  20. Pathogenesis of deep endometriosis.

    Science.gov (United States)

    Gordts, Stephan; Koninckx, Philippe; Brosens, Ivo

    2017-12-01

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

  1. 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...

  2. Deep Play. Rationality in the Life World with Special Reference to Sailing

    Science.gov (United States)

    Goold, Patrick

    2014-01-01

    In an essay on the rationality of play, the author characterizes rationality by the three distinct demands it makes on the individual--demands for autonomy, solidarity, and integrity. He develops each of these as they apply to the sport of sailing, using the example of two deep-ocean expeditions to arrive at a concept of deep play he sees as one…

  3. Auxiliary Deep Generative Models

    DEFF Research Database (Denmark)

    Maaløe, Lars; Sønderby, Casper Kaae; Sønderby, Søren Kaae

    2016-01-01

    Deep generative models parameterized by neural networks have recently achieved state-of-the-art performance in unsupervised and semi-supervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave...... the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge...... faster with better results. We show state-of-the-art performance within semi-supervised learning on MNIST (0.96%), SVHN (16.61%) and NORB (9.40%) datasets....

  4. 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...

  5. Deep boreholes; Tiefe Bohrloecher

    Energy Technology Data Exchange (ETDEWEB)

    Bracke, Guido [Gesellschaft fuer Anlagen- und Reaktorsicherheit gGmbH Koeln (Germany); Charlier, Frank [NSE international nuclear safety engineering gmbh, Aachen (Germany); Geckeis, Horst [Karlsruher Institut fuer Technologie (Germany). Inst. fuer Nukleare Entsorgung; and others

    2016-02-15

    The report on deep boreholes covers the following subject areas: methods for safe enclosure of radioactive wastes, requirements concerning the geological conditions of possible boreholes, reversibility of decisions and retrievability, status of drilling technology. The introduction covers national and international activities. Further chapters deal with the following issues: basic concept of the storage in deep bore holes, status of the drilling technology, safe enclosure, geomechanics and stability, reversibility of decisions, risk scenarios, compliancy with safe4ty requirements and site selection criteria, research and development demand.

  6. Deep Water Acoustics

    Science.gov (United States)

    2016-06-28

    the Deep Water project and participate in the NPAL Workshops, including Art Baggeroer (MIT), J. Beron- Vera (UMiami), M. Brown (UMiami), T...Kathleen E . Wage. The North Pacific Acoustic Laboratory deep-water acoustic propagation experiments in the Philippine Sea. J. Acoust. Soc. Am., 134(4...estimate of the angle α during PhilSea09, made from ADCP measurements at the site of the DVLA. Sim. A B1 B2 B3 C D E F Prof. # 0 4 4 4 5 10 16 20 α

  7. Deep diode atomic battery

    International Nuclear Information System (INIS)

    Anthony, T.R.; Cline, H.E.

    1977-01-01

    A deep diode atomic battery is made from a bulk semiconductor crystal containing three-dimensional arrays of columnar and lamellar P-N junctions. The battery is powered by gamma rays and x-ray emission from a radioactive source embedded in the interior of the semiconductor crystal

  8. Deep Learning Policy Quantization

    NARCIS (Netherlands)

    van de Wolfshaar, Jos; Wiering, Marco; Schomaker, Lambertus

    2018-01-01

    We introduce a novel type of actor-critic approach for deep reinforcement learning which is based on learning vector quantization. We replace the softmax operator of the policy with a more general and more flexible operator that is similar to the robust soft learning vector quantization algorithm.

  9. Deep-sea fungi

    Digital Repository Service at National Institute of Oceanography (India)

    Raghukumar, C; Damare, S.R.

    significant in terms of carbon sequestration (5, 8). In light of this, the diversity, abundance, and role of fungi in deep-sea sediments may form an important link in the global C biogeochemistry. This review focuses on issues related to collection...

  10. Deep inelastic scattering

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    Deep inelastic lepton-nucleon interaction experiments are renewed. Singlet and non-singlet structure functions are measured and the consistency of the different results is checked. A detailed analysis of the scaling violation is performed in terms of the quantum chromodynamics predictions [fr

  11. Deep Vein Thrombosis

    Centers for Disease Control (CDC) Podcasts

    2012-04-05

    This podcast discusses the risk for deep vein thrombosis in long-distance travelers and ways to minimize that risk.  Created: 4/5/2012 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 4/5/2012.

  12. 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

  13. The deep universe

    CERN Document Server

    Sandage, AR; Longair, MS

    1995-01-01

    Discusses the concept of the deep universe from two conflicting theoretical viewpoints: firstly as a theory embracing the evolution of the universe from the Big Bang to the present; and secondly through observations gleaned over the years on stars, galaxies and clusters.

  14. Teaching for Deep Learning

    Science.gov (United States)

    Smith, Tracy Wilson; Colby, Susan A.

    2007-01-01

    The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixty-four teachers in seventeen different states (Smith et al. 2005) indicated that most of the learning in these classrooms…

  15. Deep Trawl Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Otter trawl (36' Yankee and 4-seam net deepwater gear) catches from mid-Atlantic slope and canyons at 200 - 800 m depth. Deep-sea (200-800 m depth) flat otter trawls...

  16. [Deep vein thrombosis prophylaxis.

    Science.gov (United States)

    Sandoval-Chagoya, Gloria Alejandra; Laniado-Laborín, Rafael

    2013-01-01

    Background: despite the proven effectiveness of preventive therapy for deep vein thrombosis, a significant proportion of patients at risk for thromboembolism do not receive prophylaxis during hospitalization. Our objective was to determine the adherence to thrombosis prophylaxis guidelines in a general hospital as a quality control strategy. Methods: a random audit of clinical charts was conducted at the Tijuana General Hospital, Baja California, Mexico, to determine the degree of adherence to deep vein thrombosis prophylaxis guidelines. The instrument used was the Caprini's checklist for thrombosis risk assessment in adult patients. Results: the sample included 300 patient charts; 182 (60.7 %) were surgical patients and 118 were medical patients. Forty six patients (15.3 %) received deep vein thrombosis pharmacologic prophylaxis; 27.1 % of medical patients received deep vein thrombosis prophylaxis versus 8.3 % of surgical patients (p < 0.0001). Conclusions: our results show that adherence to DVT prophylaxis at our hospital is extremely low. Only 15.3 % of our patients at risk received treatment, and even patients with very high risk received treatment in less than 25 % of the cases. We have implemented strategies to increase compliance with clinical guidelines.

  17. 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.

  18. 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

  19. Deep Energy Retrofit

    DEFF Research Database (Denmark)

    Zhivov, Alexander; Lohse, Rüdiger; Rose, Jørgen

    Deep Energy Retrofit – A Guide to Achieving Significant Energy User Reduction with Major Renovation Projects contains recommendations for characteristics of some of core technologies and measures that are based on studies conducted by national teams associated with the International Energy Agency...... Energy Conservation in Buildings and Communities Program (IEA-EBC) Annex 61 (Lohse et al. 2016, Case, et al. 2016, Rose et al. 2016, Yao, et al. 2016, Dake 2014, Stankevica et al. 2016, Kiatreungwattana 2014). Results of these studies provided a base for setting minimum requirements to the building...... envelope-related technologies to make Deep Energy Retrofit feasible and, in many situations, cost effective. Use of energy efficiency measures (EEMs) in addition to core technologies bundle and high-efficiency appliances will foster further energy use reduction. This Guide also provides best practice...

  20. Deep groundwater chemistry

    International Nuclear Information System (INIS)

    Wikberg, P.; Axelsen, K.; Fredlund, F.

    1987-06-01

    Starting in 1977 and up till now a number of places in Sweden have been investigated in order to collect the necessary geological, hydrogeological and chemical data needed for safety analyses of repositories in deep bedrock systems. Only crystalline rock is considered and in many cases this has been gneisses of sedimentary origin but granites and gabbros are also represented. Core drilled holes have been made at nine sites. Up to 15 holes may be core drilled at one site, the deepest down to 1000 m. In addition to this a number of boreholes are percussion drilled at each site to depths of about 100 m. When possible drilling water is taken from percussion drilled holes. The first objective is to survey the hydraulic conditions. Core drilled boreholes and sections selected for sampling of deep groundwater are summarized. (orig./HP)

  1. Deep Reinforcement Fuzzing

    OpenAIRE

    Böttinger, Konstantin; Godefroid, Patrice; Singh, Rishabh

    2018-01-01

    Fuzzing is the process of finding security vulnerabilities in input-processing code by repeatedly testing the code with modified inputs. In this paper, we formalize fuzzing as a reinforcement learning problem using the concept of Markov decision processes. This in turn allows us to apply state-of-the-art deep Q-learning algorithms that optimize rewards, which we define from runtime properties of the program under test. By observing the rewards caused by mutating with a specific set of actions...

  2. Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network

    Science.gov (United States)

    He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang

    2017-03-01

    Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.

  3. 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.

  4. An Analysis of the Distinction between Deep and Shallow Expert Systems

    Science.gov (United States)

    1989-08-01

    Standards Yorktown Heighta, NY 10500 Gaithersburg, MD 20896 Dr. Saul Amarel Dept. of Computer Science Dr. Harold Bamford CDR Robert Carter Rutgero...Michigan Marina Del Ray, CA 00232 320 Packard Read Ann Arbor, MI 48103 Mr. Colin Sheppard Dr. Diana We.r-e AXC2 Block I Mr. Prasad Tadepalli Department of

  5. Social conformity despite individual preferences for distinctiveness.

    Science.gov (United States)

    Smaldino, Paul E; Epstein, Joshua M

    2015-03-01

    We demonstrate that individual behaviours directed at the attainment of distinctiveness can in fact produce complete social conformity. We thus offer an unexpected generative mechanism for this central social phenomenon. Specifically, we establish that agents who have fixed needs to be distinct and adapt their positions to achieve distinctiveness goals, can nevertheless self-organize to a limiting state of absolute conformity. This seemingly paradoxical result is deduced formally from a small number of natural assumptions and is then explored at length computationally. Interesting departures from this conformity equilibrium are also possible, including divergence in positions. The effect of extremist minorities on these dynamics is discussed. A simple extension is then introduced, which allows the model to generate and maintain social diversity, including multimodal distinctiveness distributions. The paper contributes formal definitions, analytical deductions and counterintuitive findings to the literature on individual distinctiveness and social conformity.

  6. Extracting Databases from Dark Data with DeepDive.

    Science.gov (United States)

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

    2016-01-01

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

  7. Deep Red (Profondo Rosso)

    CERN Multimedia

    Cine Club

    2015-01-01

    Wednesday 29 April 2015 at 20:00 CERN Council Chamber    Deep Red (Profondo Rosso) Directed by Dario Argento (Italy, 1975) 126 minutes A psychic who can read minds picks up the thoughts of a murderer in the audience and soon becomes a victim. An English pianist gets involved in solving the murders, but finds many of his avenues of inquiry cut off by new murders, and he begins to wonder how the murderer can track his movements so closely. Original version Italian; English subtitles

  8. Reversible deep disposal

    International Nuclear Information System (INIS)

    2009-10-01

    This presentation, given by the national agency of radioactive waste management (ANDRA) at the meeting of October 8, 2009 of the high committee for the nuclear safety transparency and information (HCTISN), describes the concept of deep reversible disposal for high level/long living radioactive wastes, as considered by the ANDRA in the framework of the program law of June 28, 2006 about the sustainable management of radioactive materials and wastes. The document presents the social and political reasons of reversibility, the technical means considered (containers, disposal cavities, monitoring system, test facilities and industrial prototypes), the decisional process (progressive development and blocked off of the facility, public information and debate). (J.S.)

  9. Deep inelastic neutron scattering

    International Nuclear Information System (INIS)

    Mayers, J.

    1989-03-01

    The report is based on an invited talk given at a conference on ''Neutron Scattering at ISIS: Recent Highlights in Condensed Matter Research'', which was held in Rome, 1988, and is intended as an introduction to the techniques of Deep Inelastic Neutron Scattering. The subject is discussed under the following topic headings:- the impulse approximation I.A., scaling behaviour, kinematical consequences of energy and momentum conservation, examples of measurements, derivation of the I.A., the I.A. in a harmonic system, and validity of the I.A. in neutron scattering. (U.K.)

  10. [Deep mycoses rarely described].

    Science.gov (United States)

    Charles, D

    1986-01-01

    Beside deep mycoses very well known: histoplasmosis, candidosis, cryptococcosis, there are other mycoses less frequently described. Some of them are endemic in some countries: South American blastomycosis in Brazil, coccidioidomycosis in California; some others are cosmopolitan and may affect everyone: sporotrichosis, or may affect only immunodeficient persons: mucormycosis. They do not spare Africa, we may encounter basidiobolomycosis, rhinophycomycosis, dermatophytosis, sporotrichosis and, more recently reported, rhinosporidiosis. Important therapeutic progresses have been accomplished with amphotericin B and with antifungus imidazole compounds (miconazole and ketoconazole). Surgical intervention is sometime recommended in chromomycosis and rhinosporidiosis.

  11. Deep penetration calculations

    International Nuclear Information System (INIS)

    Thompson, W.L.; Deutsch, O.L.; Booth, T.E.

    1980-04-01

    Several Monte Carlo techniques are compared in the transport of neutrons of different source energies through two different deep-penetration problems each with two parts. The first problem involves transmission through a 200-cm concrete slab. The second problem is a 90 0 bent pipe jacketed by concrete. In one case the pipe is void, and in the other it is filled with liquid sodium. Calculations are made with two different Los Alamos Monte Carlo codes: the continuous-energy code MCNP and the multigroup code MCMG

  12. Vertically distinct microbial communities in the Mariana and Kermadec trenches

    Science.gov (United States)

    Donaldson, Sierra; Osuntokun, Oladayo; Xia, Qing; Nelson, Alex; Blanton, Jessica; Allen, Eric E.; Church, Matthew J.; Bartlett, Douglas H.

    2018-01-01

    Hadal trenches, oceanic locations deeper than 6,000 m, are thought to have distinct microbial communities compared to those at shallower depths due to high hydrostatic pressures, topographical funneling of organic matter, and biogeographical isolation. Here we evaluate the hypothesis that hadal trenches contain unique microbial biodiversity through analyses of the communities present in the bottom waters of the Kermadec and Mariana trenches. Estimates of microbial protein production indicate active populations under in situ hydrostatic pressures and increasing adaptation to pressure with depth. Depth, trench of collection, and size fraction are important drivers of microbial community structure. Many putative hadal bathytypes, such as members related to the Marinimicrobia, Rhodobacteraceae, Rhodospirilliceae, and Aquibacter, are similar to members identified in other trenches. Most of the differences between the two trench microbiomes consists of taxa belonging to the Gammaproteobacteria whose distributions extend throughout the water column. Growth and survival estimates of representative isolates of these taxa under deep-sea conditions suggest that some members may descend from shallower depths and exist as a potentially inactive fraction of the hadal zone. We conclude that the distinct pelagic communities residing in these two trenches, and perhaps by extension other trenches, reflect both cosmopolitan hadal bathytypes and ubiquitous genera found throughout the water column. PMID:29621268

  13. Deep Super Learner: A Deep Ensemble for Classification Problems

    OpenAIRE

    Young, Steven; Abdou, Tamer; Bener, Ayse

    2018-01-01

    Deep learning has become very popular for tasks such as predictive modeling and pattern recognition in handling big data. Deep learning is a powerful machine learning method that extracts lower level features and feeds them forward for the next layer to identify higher level features that improve performance. However, deep neural networks have drawbacks, which include many hyper-parameters and infinite architectures, opaqueness into results, and relatively slower convergence on smaller datase...

  14. Deep-inelastic scattering in 124,136Xe+58,64Ni at energies near the Coulomb barrier

    International Nuclear Information System (INIS)

    Gehring, J.; Back, B.B.; Chan, K.C.; Freer, M.; Henderson, D.; Jiang, C.L.; Rehm, K.E.; Schiffer, J.P.; Wolanski, M.; Wuosmaa, A.H.; Gehring, J.; Wolanski, M.

    1997-01-01

    Cross sections, angular distributions, and mass distributions have been measured for deep-inelastic scattering in 124 Xe+ 58 Ni and 136 Xe+ 64 Ni at laboratory energies in the vicinity of the Coulomb barrier. The mass distributions show distinct components due to deep-inelastic and fissionlike processes. The strength of deep-inelastic scattering is similar in the two systems measured and comparable to previous measurements in 58 Ni+ 112,124 Sn. copyright 1997 The American Physical Society

  15. Deep Learning in Radiology.

    Science.gov (United States)

    McBee, Morgan P; Awan, Omer A; Colucci, Andrew T; Ghobadi, Comeron W; Kadom, Nadja; Kansagra, Akash P; Tridandapani, Srini; Auffermann, William F

    2018-03-29

    As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  16. 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.

  17. Deep Transfer Metric Learning.

    Science.gov (United States)

    Junlin Hu; Jiwen Lu; Yap-Peng Tan; Jie Zhou

    2016-12-01

    Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML, where the output of both the hidden layers and the top layer are optimized jointly. To preserve the local manifold of input data points in the metric space, we present two new methods, DTML with autoencoder regularization and DSTML with autoencoder regularization. Experimental results on face verification, person re-identification, and handwritten digit recognition validate the effectiveness of the proposed methods.

  18. Plastic microfibre ingestion by deep-sea organisms

    Science.gov (United States)

    Taylor, M. L.; Gwinnett, C.; Robinson, L. F.; Woodall, L. C.

    2016-09-01

    Plastic waste is a distinctive indicator of the world-wide impact of anthropogenic activities. Both macro- and micro-plastics are found in the ocean, but as yet little is known about their ultimate fate and their impact on marine ecosystems. In this study we present the first evidence that microplastics are already becoming integrated into deep-water organisms. By examining organisms that live on the deep-sea floor we show that plastic microfibres are ingested and internalised by members of at least three major phyla with different feeding mechanisms. These results demonstrate that, despite its remote location, the deep sea and its fragile habitats are already being exposed to human waste to the extent that diverse organisms are ingesting microplastics.

  19. Deep Reinforcement Learning: An Overview

    OpenAIRE

    Li, Yuxi

    2017-01-01

    We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start with background of machine learning, deep learning and reinforcement learning. Next we discuss core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration. After that, we discuss important mechanisms for RL, including attention and memory, unsuperv...

  20. Deep Feature Consistent Variational Autoencoder

    OpenAIRE

    Hou, Xianxu; Shen, Linlin; Sun, Ke; Qiu, Guoping

    2016-01-01

    We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent deep learning works such as style transfer, we employ a pre-trained deep convolutional neural net...

  1. Deep learning for image classification

    Science.gov (United States)

    McCoppin, Ryan; Rizki, Mateen

    2014-06-01

    This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

  2. Validity of Sensory Systems as Distinct Constructs

    OpenAIRE

    Su, Chia-Ting; Parham, L. Diane

    2014-01-01

    Confirmatory factor analysis testing whether sensory questionnaire items represented distinct sensory system constructs found, using data from two age groups, that such constructs can be measured validly using questionnaire data.

  3. Visual distinctiveness can enhance recency effects.

    Science.gov (United States)

    Bornstein, B H; Neely, C B; LeCompte, D C

    1995-05-01

    Experimental efforts to meliorate the modality effect have included attempts to make the visual stimulus more distinctive. McDowd and Madigan (1991) failed to find an enhanced recency effect in serial recall when the last item was made more distinct in terms of its color. In an attempt to extend this finding, three experiments were conducted in which visual distinctiveness was manipulated in a different manner, by combining the dimensions of physical size and coloration (i.e., whether the stimuli were solid or outlined in relief). Contrary to previous findings, recency was enhanced when the size and coloration of the last item differed from the other items in the list, regardless of whether the "distinctive" item was larger or smaller than the remaining items. The findings are considered in light of other research that has failed to obtain a similar enhanced recency effect, and their implications for current theories of the modality effect are discussed.

  4. Deep learning? What deep learning? | Fourie | South African ...

    African Journals Online (AJOL)

    In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability ...

  5. Deep sea radionuclides

    International Nuclear Information System (INIS)

    Kanisch, G.; Vobach, M.

    1993-01-01

    Every year since 1979, either in sping or in summer, the fishing research vessel 'Walther Herwig' goes to the North Atlantic disposal areas of solid radioactive wastes, and, for comparative purposes, to other areas, in order to collect water samples, plankton and nekton, and, from the deep sea bed, sediment samples and benthos organisms. In addition to data on the radionuclide contents of various media, information about the plankton, nekton and benthos organisms living in those areas and about their biomasses could be gathered. The investigations are aimed at acquiring scientifically founded knowledge of the uptake of radioactive substances by microorganisms, and their migration from the sea bottom to the areas used by man. (orig.) [de

  6. Deep inelastic phenomena

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    The experimental situation of the deep inelastic scattering for electrons (muons) is reviewed. A brief history of experimentation highlights Mohr and Nicoll's 1932 experiment on electron-atom scattering and Hofstadter's 1950 experiment on electron-nucleus scattering. The phenomenology of electron-nucleon scattering carried out between 1960 and 1970 is described, with emphasis on the parton model, and scaling. Experiments at SLAC and FNAL since 1974 exhibit scaling violations. Three muon-nucleon scattering experiments at BFP, BCDMA, and EMA, currently producing new results in the high Q 2 domain suggest a rather flat behaviour of the structure function at fixed x as a function of Q 2 . It is seen that the structure measured in DIS can then be projected into a pure hadronic process to predict a cross section. Protonneutron difference, moment analysis, and Drell-Yan pairs are also considered

  7. Deep Help in Complex Project Work: Guiding and Path-Clearing Across Difficult Terrain

    OpenAIRE

    Fisher, Colin M.; Pillemer, Julianna; Amabile, Teresa M.

    2017-01-01

    How do teams working on complex projects get the help they need? Our qualitative investigation of the help provided to project teams at a prominent design firm revealed two distinct helping processes, both characterized by deep, sustained engagement that far exceeds the brief interactions described in the helping literature. Such deep help consisted of (1) guiding a team through a difficult juncture by working with its members in several prolonged, tightly clustered sessions, or (2) path-clea...

  8. Context and Deep Learning Design

    Science.gov (United States)

    Boyle, Tom; Ravenscroft, Andrew

    2012-01-01

    Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across…

  9. Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory.

    Science.gov (United States)

    Bastos, André M; Loonis, Roman; Kornblith, Simon; Lundqvist, Mikael; Miller, Earl K

    2018-01-30

    All of the cerebral cortex has some degree of laminar organization. These different layers are composed of neurons with distinct connectivity patterns, embryonic origins, and molecular profiles. There are little data on the laminar specificity of cognitive functions in the frontal cortex, however. We recorded neuronal spiking/local field potentials (LFPs) using laminar probes in the frontal cortex (PMd, 8A, 8B, SMA/ACC, DLPFC, and VLPFC) of monkeys performing working memory (WM) tasks. LFP power in the gamma band (50-250 Hz) was strongest in superficial layers, and LFP power in the alpha/beta band (4-22 Hz) was strongest in deep layers. Memory delay activity, including spiking and stimulus-specific gamma bursting, was predominately in superficial layers. LFPs from superficial and deep layers were synchronized in the alpha/beta bands. This was primarily unidirectional, with alpha/beta bands in deep layers driving superficial layer activity. The phase of deep layer alpha/beta modulated superficial gamma bursting associated with WM encoding. Thus, alpha/beta rhythms in deep layers may regulate the superficial layer gamma bands and hence maintenance of the contents of WM. Copyright © 2018 the Author(s). Published by PNAS.

  10. Distinctiveness of Saudi Arabian EFL Learners

    Directory of Open Access Journals (Sweden)

    Manssour Habbash

    2016-04-01

    Full Text Available In view of the increasing concern among English language teachers dealing with students from Saudi Arabia, as it manifests in TESOL community discussions, about the uniqueness of Saudi Arabian EFL learners, this paper attempts to document the outcome of a study of their distinctiveness from the perspective of expatriate teachers working for PYPs (Preparatory Year Programs in Saudi Arabia. This study examines the distinctiveness with regard to the learning attitudes of Saudi students that are often cultivated by the culture and academic environment in their homeland. Employing an emic approach for collecting the required data an analysis was carried out in light of the other studies on ‘education’ in Saudi Arabia that have particular reference to the factors that can positively influence student motivation, student success and the academic environment. The findings were used in constructing the rationale behind such distinctiveness. Assuming that the outcome of the discussion on the findings of this exploration can be helpful for teachers in adapting their teaching methodology and improving their teacher efficacy in dealing with students both from the kingdom and in the kingdom, some recommendations are made. Keywords: China Distinctiveness, Saudi Arabian University context, Expatriate teachers’ perspective, Distinctiveness Theory

  11. Does processing a shallow and a deep orthography produce different brain activity patterns? An ERP study conducted in Hebrew.

    Science.gov (United States)

    Bar-Kochva, Irit

    2011-01-01

    Orthographies range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Two forms of script transcribe the Hebrew language: the shallow pointed script (with diacritics) and the deep unpointed script (without diacritics). This study was set out to examine whether the reading of these scripts evokes distinct brain activity. Preliminary results indicate distinct Event-related-potentials (ERPs). As an equivalent finding was absent when ERPs of non-orthographic stimuli with and without meaningless diacritics were compared, the results imply that print-specific aspects of processing account for the distinct activity elicited by the pointed and unpointed scripts.

  12. On Hobbes’s distinction of accidents

    Directory of Open Access Journals (Sweden)

    Lupoli Agostino

    2012-06-01

    Full Text Available An interpolation introduced by K. Schuhmann in his critical edition of "De corpore" (chap. VI, § 13 diametrically overturns the meaning of Hobbes’s doctrine of distinction of accidents in comparison with all previous editions. The article focuses on the complexity of this crucial juncture in "De corpore" argument on which depends the interpretation of Hobbes’s whole conception of science. It discusses the reasons pro and contra Schuhmann’s interpolation and concludes against it, because it is not compatible with the rationale underlying the complex architecture of "De corpore", which involves a symmetry between the ‘logical’ distinction of accidents and the ‘metaphysical’ distinction of phantasms.

  13. What makes health promotion research distinct?

    Science.gov (United States)

    Woodall, James; Warwick-Booth, Louise; South, Jane; Cross, Ruth

    2018-02-01

    There have been concerns about the decline of health promotion as a practice and discipline and, alongside this, calls for a clearer articulation of health promotion research and what, if anything, makes it distinct. This discussion paper, based on a review of the literature, the authors' own experiences in the field, and a workshop delivered by two of the authors at the 8th Nordic Health Promotion Conference, seeks to state the reasons why health promotion research is distinctive. While by no means exhaustive, the paper suggests four distinctive features. The paper hopes to be a catalyst to enable health promotion researchers to be explicit in their practice and to begin the process of developing an agreed set of research principles.

  14. Distinctive Dynamic Capabilities for New Business Creation

    DEFF Research Database (Denmark)

    Rosenø, Axel; Enkel, Ellen; Mezger, Florian

    2013-01-01

    This study examines the distinctive dynamic capabilities for new business creation in established companies. We argue that these are very different from those for managing incremental innovation within a company's core business. We also propose that such capabilities are needed in both slow...... and fast-paced industries, and that similarities exist across industries. Hence, the study contributes to dynamic capabilities literature by: 1) identifying the distinctive dynamic capabilities for new business creation; 2) shifting focus away from dynamic capabilities in environments characterised by high...... clock-speed and uncertainty towards considering dynamic capabilities for the purpose of developing new businesses, which also implies a high degree of uncertainty. Based on interviews with 33 companies, we identify distinctive dynamic capabilities for new business creation, find that dynamic...

  15. Is there a distinct continental slope fauna in the Antarctic?

    Science.gov (United States)

    Kaiser, Stefanie; Griffiths, Huw J.; Barnes, David K. A.; Brandão, Simone N.; Brandt, Angelika; O'Brien, Philip E.

    2011-02-01

    The Antarctic continental slope spans the depths from the shelf break (usually between 500 and 1000 m) to ˜3000 m, is very steep, overlain by 'warm' (2-2.5 °C) Circumpolar Deep Water (CDW), and life there is poorly studied. This study investigates whether life on Antarctica's continental slope is essentially an extension of the shelf or the abyssal fauna, a transition zone between these or clearly distinct in its own right. Using data from several cruises to the Weddell Sea and Scotia Sea, including the ANDEEP (ANtarctic benthic DEEP-sea biodiversity, colonisation history and recent community patterns) I-III, BIOPEARL (BIOdiversity, Phylogeny, Evolution and Adaptive Radiation of Life in Antarctica) 1 and EASIZ (Ecology of the Antarctic Sea Ice Zone) II cruises as well as current databases (SOMBASE, SCAR-MarBIN), four different taxa were selected (i.e. cheilostome bryozoans, isopod and ostracod crustaceans and echinoid echinoderms) and two areas, the Weddell Sea and the Scotia Sea, to examine faunal composition, richness and affinities. The answer has important ramifications to the link between physical oceanography and ecology, and the potential of the slope to act as a refuge and resupply zone to the shelf during glaciations. Benthic samples were collected using Agassiz trawl, epibenthic sledge and Rauschert sled. By bathymetric definition, these data suggest that despite eurybathy in some of the groups examined and apparent similarity of physical conditions in the Antarctic, the shelf, slope and abyssal faunas were clearly separated in the Weddell Sea. However, no such separation of faunas was apparent in the Scotia Sea (except in echinoids). Using a geomorphological definition of the slope, shelf-slope-abyss similarity only changed significantly in the bryozoans. Our results did not support the presence of a homogenous and unique Antarctic slope fauna despite a high number of species being restricted to the slope. However, it remains the case that there may be

  16. Deep Learning Fluid Mechanics

    Science.gov (United States)

    Barati Farimani, Amir; Gomes, Joseph; Pande, Vijay

    2017-11-01

    We have developed a new data-driven model paradigm for the rapid inference and solution of the constitutive equations of fluid mechanic by deep learning models. Using generative adversarial networks (GAN), we train models for the direct generation of solutions to steady state heat conduction and incompressible fluid flow without knowledge of the underlying governing equations. Rather than using artificial neural networks to approximate the solution of the constitutive equations, GANs can directly generate the solutions to these equations conditional upon an arbitrary set of boundary conditions. Both models predict temperature, velocity and pressure fields with great test accuracy (>99.5%). The application of our framework for inferring and generating the solutions of partial differential equations can be applied to any physical phenomena and can be used to learn directly from experiments where the underlying physical model is complex or unknown. We also have shown that our framework can be used to couple multiple physics simultaneously, making it amenable to tackle multi-physics problems.

  17. Deep video deblurring

    KAUST Repository

    Su, Shuochen

    2016-11-25

    Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on aligning nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task which requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-to-end to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high framerate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

  18. Deep space telescopes

    CERN Multimedia

    CERN. Geneva

    2006-01-01

    The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo’s telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics throughout the complete electromagnetic spectrum. Such information is there for the taking, from millimiter wavelengths to gamma rays. Forty years astronomy from space, covering now most of the e.m. spectrum, have thus given us a better understanding of our physical Universe then t...

  19. Deep inelastic final states

    International Nuclear Information System (INIS)

    Girardi, G.

    1980-11-01

    In these lectures we attempt to describe the final states of deep inelastic scattering as given by QCD. In the first section we shall briefly comment on the parton model and give the main properties of decay functions which are of interest for the study of semi-inclusive leptoproduction. The second section is devoted to the QCD approach to single hadron leptoproduction. First we recall basic facts on QCD log's and derive after that the evolution equations for the fragmentation functions. For this purpose we make a short detour in e + e - annihilation. The rest of the section is a study of the factorization of long distance effects associated with the initial and final states. We then show how when one includes next to leading QCD corrections one induces factorization breaking and describe the double moments useful for testing such effects. The next section contains a review on the QCD jets in the hadronic final state. We begin by introducing the notion of infrared safe variable and defining a few useful examples. Distributions in these variables are studied to first order in QCD, with some comments on the resummation of logs encountered in higher orders. Finally the last section is a 'gaullimaufry' of jet studies

  20. Fermionic bound states in distinct kinklike backgrounds

    Energy Technology Data Exchange (ETDEWEB)

    Bazeia, D. [Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, Paraiba (Brazil); Mohammadi, A. [Universidade Federal de Campina Grande, Departamento de Fisica, Caixa Postal 10071, Campina Grande, Paraiba (Brazil)

    2017-04-15

    This work deals with fermions in the background of distinct localized structures in the two-dimensional spacetime. Although the structures have a similar topological character, which is responsible for the appearance of fractionally charged excitations, we want to investigate how the geometric deformations that appear in the localized structures contribute to the change in the physical properties of the fermionic bound states. We investigate the two-kink and compact kinklike backgrounds, and we consider two distinct boson-fermion interactions, one motivated by supersymmetry and the other described by the standard Yukawa coupling. (orig.)

  1. 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.

  2. 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.

  3. 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.

  4. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu; Han, Renmin; Bi, Chongwei; Li, Mo; Wang, Sheng; Gao, Xin

    2017-01-01

    or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments

  5. Common and distinct components in data fusion

    DEFF Research Database (Denmark)

    Smilde, Age Klaas; Mage, Ingrid; Næs, Tormod

    2016-01-01

    and understanding their relative merits. This paper provides a unifying framework for this subfield of data fusion by using rigorous arguments from linear algebra. The most frequently used methods for distinguishing common and distinct components are explained in this framework and some practical examples are given...

  6. Knowledge Affords Distinctive Processing in Memory

    Science.gov (United States)

    Hunt, R. Reed; Rawson, Katherine A.

    2011-01-01

    The effect of knowledge on memory generally is processing. However, both conceptual and empirical reasons exist to suspect that the organizational account is incomplete. Recently a revised version of that account has been proposed under the rubric of distinctiveness theory (Rawson & Van Overschelde, 2008). The goal of the experiments reported…

  7. Distinctiveness of Saudi Arabian EFL Learners

    Science.gov (United States)

    Habbash, Manssour; Idapalapati, Srinivasa Rao

    2016-01-01

    In view of the increasing concern among English language teachers dealing with students from Saudi Arabia, as it manifests in TESOL community discussions, about the uniqueness of Saudi Arabian EFL learners, this paper attempts to document the outcome of a study of their distinctiveness from the perspective of expatriate teachers working for PYPs…

  8. Deep UV LEDs

    Science.gov (United States)

    Han, Jung; Amano, Hiroshi; Schowalter, Leo

    2014-06-01

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

  9. DEEP INFILTRATING ENDOMETRIOSIS

    Directory of Open Access Journals (Sweden)

    Martina Ribič-Pucelj

    2018-02-01

    Full Text Available Background: Endometriosis is not considered a unified disease, but a disease encompassing three differ- ent forms differentiated by aetiology and pathogenesis: peritoneal endometriosis, ovarian endometriosis and deep infiltrating endometriosis (DIE. The disease is classified as DIE when the lesions penetrate 5 mm or more into the retroperitoneal space. The estimated incidence of endometriosis in women of reproductive age ranges from 10–15 % and that of DIE from 3–10 %, the highest being in infertile women and in those with chronic pelvic pain. The leading symptoms of DIE are chronic pelvic pain which increases with age and correlates with the depth of infiltration and infertility. The most important diagnostic procedures are patient’s history and proper gynecological examination. The diagnosis is confirmed with laparoscopy. DIE can affect, beside reproductive organs, also bowel, bladder and ureters, therefore adi- tional diagnostic procedures must be performed preopertively to confirm or to exclude the involvement of the mentioned organs. Endometriosis is hormon dependent disease, there- fore several hormonal treatment regims are used to supress estrogen production but the symptoms recurr soon after caesation of the treatment. At the moment, surgical treatment with excision of all lesions, including those of bowel, bladder and ureters, is the method of choice but requires frequently interdisciplinary approach. Surgical treatment significantly reduces pain and improves fertility in inferile patients. Conclusions: DIE is not a rare form of endometriosis characterized by chronic pelvic pain and infertility. Medical treatment is not efficient. The method of choice is surgical treatment with excision of all lesions. It significantly reduces pelvic pain and enables high spontaneus and IVF preg- nacy rates.Therefore such patients should be treated at centres with experience in treatment of DIE and with possibility of interdisciplinary approach.

  10. Telepresence for Deep Space Missions

    Data.gov (United States)

    National Aeronautics and Space Administration — Incorporating telepresence technologies into deep space mission operations can give the crew and ground personnel the impression that they are in a location at time...

  11. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-01-01

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during

  12. Deep Learning and Bayesian Methods

    OpenAIRE

    Prosper Harrison B.

    2017-01-01

    A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such meth...

  13. Density functionals from deep learning

    OpenAIRE

    McMahon, Jeffrey M.

    2016-01-01

    Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep learning is developed to approximate this functional. Deep learning allows computational models that are capable of naturally discovering intricate structure in large and/or high-dimensional data sets, with multiple levels of abstraction. As no assumptions are ...

  14. Deep Unfolding for Topic Models.

    Science.gov (United States)

    Chien, Jen-Tzung; Lee, Chao-Hsi

    2018-02-01

    Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.

  15. Hot, deep origin of petroleum: deep basin evidence and application

    Science.gov (United States)

    Price, Leigh C.

    1978-01-01

    Use of the model of a hot deep origin of oil places rigid constraints on the migration and entrapment of crude oil. Specifically, oil originating from depth migrates vertically up faults and is emplaced in traps at shallower depths. Review of petroleum-producing basins worldwide shows oil occurrence in these basins conforms to the restraints of and therefore supports the hypothesis. Most of the world's oil is found in the very deepest sedimentary basins, and production over or adjacent to the deep basin is cut by or directly updip from faults dipping into the basin deep. Generally the greater the fault throw the greater the reserves. Fault-block highs next to deep sedimentary troughs are the best target areas by the present concept. Traps along major basin-forming faults are quite prospective. The structural style of a basin governs the distribution, types, and amounts of hydrocarbons expected and hence the exploration strategy. Production in delta depocenters (Niger) is in structures cut by or updip from major growth faults, and structures not associated with such faults are barren. Production in block fault basins is on horsts next to deep sedimentary troughs (Sirte, North Sea). In basins whose sediment thickness, structure and geologic history are known to a moderate degree, the main oil occurrences can be specifically predicted by analysis of fault systems and possible hydrocarbon migration routes. Use of the concept permits the identification of significant targets which have either been downgraded or ignored in the past, such as production in or just updip from thrust belts, stratigraphic traps over the deep basin associated with major faulting, production over the basin deep, and regional stratigraphic trapping updip from established production along major fault zones.

  16. Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation.

    Directory of Open Access Journals (Sweden)

    Guoshi Li

    2017-10-01

    Full Text Available The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh and norepinephrine (NE and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.

  17. Embarrassment: its distinct form and appeasement functions.

    Science.gov (United States)

    Keltner, D; Buswell, B N

    1997-11-01

    The authors address 2 questions about embarrassment. First, Is embarrassment a distinct emotion? The evidence indicates that the antecedents, experience, and display of embarrassment, and to a limited extent its autonomic physiology, are distinct from shame, guilt, and amusement and share the dynamic, temporal characteristics of emotion. Second, What are the theoretical accounts of embarrassment? Three accounts focus on the causes of embarrassment, positioning that it follows the loss of self-esteem, concern for others' evaluations, or absence of scripts to guide interactions. A fourth account focuses on the effects of the remedial actions of embarrassment, which correct preceding transgressions. A fifth account focuses on the functional parallels between embarrassment and nonhuman appeasement. The discussion focuses on unanswered questions about embarrassment.

  18. Distinctive skeletal dysplasia in Cockayne syndrome

    International Nuclear Information System (INIS)

    Silengo, M.C.; Franceschini, P.; Bianco, R.; Biagioli, M.; Pastorin, L.; Vista, N.; Baldassar, A.; Benso, L.

    1986-01-01

    Cockayne syndrom is a well-known autosomal recessive form of dwarfism with senile-like appearance. Skeletal changes such as flattening of vertebral bodies, ivory epiphyses and thickening of cranial vault, have been observed in some patients with this condition. We describe here a 5.5-year-old girl with the typical clinical signs of Cockayne syndrome and a distinctive form of bone dysplasia with major involvment of the spine. (orig.)

  19. Distinctive skeletal dysplasia in Cockayne syndrome

    Energy Technology Data Exchange (ETDEWEB)

    Silengo, M.C.; Franceschini, P.; Bianco, R.; Biagioli, M.; Pastorin, L.; Vista, N.; Baldassar, A.; Benso, L.

    1986-03-01

    Cockayne syndrome is a well-known autosomal recessive form of dwarfism with senile-like appearance. Skeletal changes such as flattening of vertebral bodies, ivory epiphyses and thickening of cranial vault, have been observed in some patients with this condition. We describe here a 5.5-year-old girl with the typical clinical signs of Cockayne syndrome and a distinctive form of bone dysplasia with major involvement of the spine.

  20. Army nurses in wartime: distinction and pride.

    Science.gov (United States)

    Higgins, L P

    1996-08-01

    Nurses have served with distinction in wartime since Florence Nightingale went to the Crimea. Women often accompanied their husbands to battle during the Revolutionary and Civil Wars, caring for the sick and wounded. Although not officially given officer status until 1920, Army nurses served in the Spanish-American War and World War I. As officers, thousands of nurses served in subsequent wars, distinguishing themselves by their heroism, devotion to duty, and sheer tenacity of spirit.

  1. Connectivity between surface and deep waters determines prokaryotic diversity in the North Atlantic Deep Water.

    Science.gov (United States)

    Frank, Alexander H; Garcia, Juan A L; Herndl, Gerhard J; Reinthaler, Thomas

    2016-06-01

    To decipher the influence of depth stratification and surface provincialism on the dark ocean prokaryotic community composition, we sampled the major deep-water masses in the eastern North Atlantic covering three biogeographic provinces. Their diversity was evaluated using ordination and canonical analysis of 454 pyrotag sequences. Variance partitioning suggested that 16% of the variation in the bacterial community composition was based on depth stratification while 9% of the variation was due to geographic location. General linear mixed effect models showed that the community of the subsurface waters was connected to the dark ocean prokaryotic communities in different biogeographic provinces. Cluster analysis indicated that some prokaryotic taxa are specific to distinct regions in bathypelagic water masses. Taken together, our data suggest that the dark ocean prokaryotic community composition of the eastern North Atlantic is primed by the formation and the horizontal transport of water masses. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

  2. Observation of two-jet production in deep inelastic scattering at HERA

    Science.gov (United States)

    Derrick, M.; Krakauer, D.; Magill, S.; Musgrave, B.; Repond, J.; Repond, S.; Stanek, R.; Talaga, R. L.; Thron, J.; Arzarello, F.; Ayad, R.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Bruni, P.; Cara Romeo, G.; Castellini, G.; Chiarini, M.; Cifarelli, L.; Cindolo, F.; Ciralli, F.; Contin, A.; D'Auria, S.; Del Papa, C.; Frasconi, F.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Lin, Q.; Lisowski, B.; Maccarrone, G.; Margotti, A.; Massam, T.; Nania, R.; Nemoz, C.; Palmonari, F.; Sartorelli, G.; Timellini, R.; Zamora Garcia, Y.; Zichichi, A.; Bargende, A.; Crittenden, J.; Dabbous, H.; Desch, K.; Diekmann, B.; Doeker, T.; Geerts, M.; Geitz, G.; Gutjahr, B.; Hartmann, H.; Haun, D.; Heinloth, K.; Hilger, E.; Jakob, H.-P.; Kramarczyk, S.; Kückes, M.; Mass, A.; Mengel, S.; Mollen, J.; Monaldi, D.; Müsch, H.; Paul, E.; Schattevoy, R.; Schneider, J.-L.; Wedemeyer, R.; Cassidy, A.; Cussans, D. G.; Dyce, N.; Fawcett, H. F.; Foster, B.; Gilmore, R.; Heath, G. P.; Lancaster, M.; Llewellyn, T. J.; Malos, J.; Morgado, C. J. S.; Tapper, R. J.; Wilson, S. S.; Rau, R. R.; Arneodo, M.; Barillari, T.; Schioppa, M.; Susinno, G.; Bernstein, A.; Caldwell, A.; Gialas, I.; Parsons, J. A.; Ritz, S.; Sciulli, F.; Straub, P. B.; Wai, L.; Yang, S.; Chwastowski, J.; Dwuraźny, A.; Eskreys, A.; Jakubowski, Z.; Niziom̵, B.; Piotrzkowski, K.; Zachara, M.; Zawiejski, L.; Bednarek, B.; Borzemski, P.; Eskreys, K.; Jeleń, K.; Kisielewska, D.; Kowalski, T.; Rulikowska-Zarȩbska, E.; Suszycki, L.; Zajaç, J.; Kȩdzierski, T.; Kotański, A.; Przybycień, M.; Bauerdick, L. A. T.; Behrens, U.; Bienlein, J. K.; Coldewey, C.; Dannemann, A.; Drews, G.; Erhard, P.; Flasiński, M.; Fleck, I.; Gläser, R.; Göttlicher, P.; Haas, T.; Hagge, L.; Hain, W.; Hasell, D.; Hultschig, H.; Jahnen, G.; Joos, P.; Kasemann, M.; Klanner, R.; Koch, W.; Kötz, U.; Kowalski, H.; Krüger, J.; Labs, J.; Ladage, A.; Löhr, B.; Löwe, M.; Lüke, D.; Mainusch, J.; Manczak, O.; Momayezi, M.; Ng, J. S. T.; Nickel, S.; Notz, D.; Park, I. H.; Pösnecker, K.-U.; Rohde, M.; Roldán, J.; Ros, E.; Schneekloth, U.; Schroeder, J.; Schulz, W.; Selonke, F.; Stiliaris, E.; Tscheslog, E.; Tsurugai, T.; Turkot, F.; Vogel, W.; Wolf, G.; Youngman, C.; Grabosch, H. J.; Leich, A.; Meyer, A.; Rethfeldt, C.; Schlenstedt, S.; Barbagli, G.; Francescato, A.; Nuti, M.; Pelfer, P.; Anzivino, G.; Casaccia, R.; De Pasquale, S.; Qian, S.; Votano, L.; Bamberger, A.; Freidhof, A.; Poser, T.; Söldner-Rembold, S.; Theisen, G.; Trefzger, T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; Forbes, J. R.; Jamieson, V. A.; Raine, C.; Saxon, D. H.; Brückmann, H.; Gloth, G.; Holm, U.; Kammerlocher, H.; Krebs, B.; Neumann, T.; Wick, K.; Fürtjes, A.; Kröger, W.; Lohrmann, E.; Milewski, J.; Nakahata, M.; Pavel, N.; Poelz, G.; Seidman, A.; Schott, W.; Terron, J.; Wiik, B. H.; Zetsche, F.; Bacon, T. C.; Butterworth, I.; Markou, C.; McQuillan, D.; Miller, D. B.; Mobayyen, M. M.; Prinias, A.; Vorvolakos, A.; Bienz, T.; Kreutzmann, H.; Mallik, U.; McCliment, E.; Roco, M.; Wang, M. Z.; Cloth, P.; Filges, D.; Chen, L.; Imlay, R.; Kartik, S.; Kim, H.-J.; McNeil, R. R.; Metcalf, W.; Barreiro, F.; Cases, G.; Hervás, L.; Labarga, L.; del Peso, J.; de Trocóniz, J. F.; Ikraiam, F.; Mayer, J. K.; Smith, G. R.; Corriveau, F.; Gilkinson, D. J.; Hanna, D. S.; Hartmann, J.; Hung, L. W.; Lim, J. N.; Meijer Drees, R.; Mitchell, J. W.; Patel, P. M.; Sinclair, L. E.; Stairs, D. G.; Ullmann, R.; Bashindzhagyan, G. L.; Ermolov, P. F.; Gladilin, L. K.; Golubkov, Y. A.; Kuzmin, V. A.; Kuznetsov, E. N.; Savin, A. A.; Voronin, A. G.; Zotov, N. P.; Bentvelsen, S.; Botje, M.; Dake, A.; Engelen, J.; de Jong, P.; de Kamps, M.; Kooijman, P.; Kruse, A.; van der Lugt, H.; O'Dell, V.; Tenner, A.; Tiecke, H.; Uijterwaal, H.; Vreeswijk, M.; Wiggers, L.; de Wolf, E.; van Woudenberg, R.; Yoshida, R.; Bylsma, B.; Durkin, L. S.; Honscheid, K.; Li, C.; Ling, T. Y.; McLean, K. W.; Murray, W. N.; Park, S. K.; Romanowski, T. A.; Seidlein, R.; Blair, G. A.; Byrne, A.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Gingrich, D. M.; Hallam-Baker, P. M.; Harnew, N.; Khatri, T.; Long, K. R.; Luffman, P.; McArthur, I.; Morawitz, P.; Nash, J.; Smith, S. J. P.; Roocroft, N. C.; Wilson, F. F.; Abbiendi, G.; Brugnera, R.; Carlin, R.; Dal Corso, F.; De Giorgi, M.; Dosselli, U.; Gasparini, F.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Butterworth, J. M.; Bulmahn, J.; Field, G.; Oh, B. Y.; Whitmore, J.; Contino, U.; D'Agostini, G.; Guida, M.; Iori, M.; Mari, S. M.; Marini, G.; Mattioli, M.; Nigro, A.; Hart, J. C.; McCubbin, N. A.; Prytz, K.; Shah, T. P.; Short, T. L.; Barberis, E.; Cartiglia, N.; Heusch, C.; Hubbard, B.; Leslie, J.; Lockman, W.; O'Shaughnessy, K.; Sadrozinski, H. F.; Seiden, A.; Badura, E.; Biltzinger, J.; Chaves, H.; Rost, M.; Seifert, R. J.; Walenta, A. H.; Weihs, W.; Zech, G.; Dagan, S.; Levy, A.; Zer-Zion, D.; Hasegawa, T.; Hazumi, M.; Ishii, T.; Kasai, S.; Kuze, M.; Nagasawa, Y.; Nakao, M.; Okuno, H.; Tokushuku, K.; Watanabe, T.; Yamada, S.; Chiba, M.; Hamatsu, R.; Hirose, T.; Kitamura, S.; Nagayama, S.; Nakamitsu, Y.; Cirio, R.; Costa, M.; Ferrero, M. I.; Lamberti, L.; Maselli, S.; Peroni, C.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Bandyopadhyay, D.; Benard, F.; Bhadra, S.; Brkic, M.; Burow, B. D.; Chlebana, F. S.; Crombie, M. B.; Hartner, G. F.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Prentice, J. D.; Sampson, C. R.; Stairs, G. G.; Teuscher, R. J.; Yoon, T.-S.; Bullock, F. W.; Catterall, C. D.; Giddings, J. C.; Jones, T. W.; Khan, A. M.; Lane, J. B.; Makkar, P. L.; Shaw, D.; Shulman, J.; Blankenship, K.; Gibaut, D. B.; Kochocki, J.; Lu, B.; Mo, L. W.; Charchum̵a, K.; Ciborowski, J.; Gajewski, J.; Grzelak, G.; Kasprzak, M.; Krzyżanowski, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Stopczyński, A.; Tymieniecka, T.; Walczak, R.; Wróblewski, A. K.; Zakrzewski, J. A.; Żarnecki, A. F.; Adamus, M.; Abramowicz, H.; Eisenberg, Y.; Glasman, C.; Karshon, U.; Montag, A.; Revel, D.; Shapira, A.; Foudas, C.; Fordham, C.; Loveless, R. J.; Goussiou, A.; Ali, I.; Behrens, B.; Dasu, S.; Reeder, D. D.; Smith, W. H.; Silverstein, S.; Frisken, W. R.; Furutani, K. M.; Iga, Y.; ZEUS Collaboration

    1993-05-01

    A sample of events with two distinct jets, in addition to the proton remnant, has been identified in deep inelastic, neutral current ep interactions recorded at HERA by the ZEUS experiment. For these events, the mass of the hadronic system ranges from 40 to 260 GeV. The salient features of the observed jet production agree with the predictions of higher order QCD.

  3. How Stressful Is "Deep Bubbling"?

    Science.gov (United States)

    Tyrmi, Jaana; Laukkanen, Anne-Maria

    2017-03-01

    Water resistance therapy by phonating through a tube into the water is used to treat dysphonia. Deep submersion (≥10 cm in water, "deep bubbling") is used for hypofunctional voice disorders. Using it with caution is recommended to avoid vocal overloading. This experimental study aimed to investigate how strenuous "deep bubbling" is. Fourteen subjects, half of them with voice training, repeated the syllable [pa:] in comfortable speaking pitch and loudness, loudly, and in strained voice. Thereafter, they phonated a vowel-like sound both in comfortable loudness and loudly into a glass resonance tube immersed 10 cm into the water. Oral pressure, contact quotient (CQ, calculated from electroglottographic signal), and sound pressure level were studied. The peak oral pressure P(oral) during [p] and shuttering of the outer end of the tube was measured to estimate the subglottic pressure P(sub) and the mean P(oral) during vowel portions to enable calculation of transglottic pressure P(trans). Sensations during phonation were reported with an open-ended interview. P(sub) and P(oral) were higher in "deep bubbling" and P(trans) lower than in loud syllable phonation, but the CQ did not differ significantly. Similar results were obtained for the comparison between loud "deep bubbling" and strained phonation, although P(sub) did not differ significantly. Most of the subjects reported "deep bubbling" to be stressful only for respiratory and lip muscles. No big differences were found between trained and untrained subjects. The CQ values suggest that "deep bubbling" may increase vocal fold loading. Further studies should address impact stress during water resistance exercises. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  4. 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.

  5. 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.

  6. Accelerating Deep Learning with Shrinkage and Recall

    OpenAIRE

    Zheng, Shuai; Vishnu, Abhinav; Ding, Chris

    2016-01-01

    Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large. Inspired from the shrinking technique used in accelerating computation of Support Vector Machines (SVM) algorithm and screening technique used in LASSO, we propose a shrinking Deep Learning with recall (sDLr) approach to speed up deep learning computation. We experiment shrinking Deep Lea...

  7. What Really is Deep Learning Doing?

    OpenAIRE

    Xiong, Chuyu

    2017-01-01

    Deep learning has achieved a great success in many areas, from computer vision to natural language processing, to game playing, and much more. Yet, what deep learning is really doing is still an open question. There are a lot of works in this direction. For example, [5] tried to explain deep learning by group renormalization, and [6] tried to explain deep learning from the view of functional approximation. In order to address this very crucial question, here we see deep learning from perspect...

  8. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

    Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.

  9. 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.

  10. Eric Davidson and deep time.

    Science.gov (United States)

    Erwin, Douglas H

    2017-10-13

    Eric Davidson had a deep and abiding interest in the role developmental mechanisms played in generating evolutionary patterns documented in deep time, from the origin of the euechinoids to the processes responsible for the morphological architectures of major animal clades. Although not an evolutionary biologist, Davidson's interests long preceded the current excitement over comparative evolutionary developmental biology. Here I discuss three aspects at the intersection between his research and evolutionary patterns in deep time: First, understanding the mechanisms of body plan formation, particularly those associated with the early diversification of major metazoan clades. Second, a critique of early claims about ancestral metazoans based on the discoveries of highly conserved genes across bilaterian animals. Third, Davidson's own involvement in paleontology through a collaborative study of the fossil embryos from the Ediacaran Doushantuo Formation in south China.

  11. Current Status of Deep Geological Repository Development

    International Nuclear Information System (INIS)

    Budnitz, R J

    2005-01-01

    electricity generated by the power reactors that have produced the waste. Of course, the current international situation is that no nation is currently willing to take any radioactive waste from another nation for deep disposal. This means that every nation will ultimately need to develop its own deep repository. This makes no sense, however--many nations have only a modest amount of waste, or do not have appropriate geological settings for a repository, or both. Ultimately, the need for one or more multi-national or international repositories will emerge, although so far this has not happened. Only one nation, Russia, has announced a policy permitting the import of radioactive wastes from other countries, but Russia's policy is not to import the wastes for deep disposal, but for chemical reprocessing. Various nations have made very different choices as to the schedule for proceeding with a repository. The rationales for each national choice differ significantly. The decision, different from country to country, comes down to balancing various seemingly conflicting values, including (a) whether the technology for deep disposal is judged to be mature enough; (b) whether surface storage during a lengthy delay is judged adequately safe against accidents and adequately secure against terrorists; (c) whether technologies for separating some of the waste constituents for re-use or recycle into reactors, or technologies for transmuting some waste constituents, are sufficiently promising to merit delaying until those technologies are more mature; (d) issues of the cost of disposal and who should bear that cost; (e) issues related to disposal of wastes from nuclear weapons programs, as distinct from wastes from reactor operations; and (f) issues about the linkage between disposal and the future of nuclear power. Finally, the decision to proceed with a repository often is governed by whether the government has the political will or ability to proceed, taking account of public opinion

  12. A distinction of two discourses concerning wellbeing

    DEFF Research Database (Denmark)

    Wistoft, Karen; Qvortrup, Lars

    2017-01-01

    and behavioral mental health interventions, while the latter defines wellbeing in positive terms with a focus on wellbeing as the result of learning and with pedagogical interventions that only indirectly can support the individual’s learning activity. The former sees wellbeing as the result of a “wellbeing cure......The article concerns the current discourses concerning well-being with the point that it is important to make a distinction between a healthcare oriented discourse and a learning oriented discourse. The former defines wellbeing in negative terms and looks at causally oriented aspects of wellbeing......”, while the latter sees wellbeing as the result of wellbeing learning processes....

  13. Approaching the Distinction between Intuition and Insight.

    Science.gov (United States)

    Zhang, Zhonglu; Lei, Yi; Li, Hong

    2016-01-01

    Intuition and insight share similar cognitive and neural basis. Though, there are still some essential differences between the two. Here in this short review, we discriminated between intuition, and insight in two aspects. First, intuition, and insight are toward different aspects of information processing. Whereas intuition involves judgment about "yes or no," insight is related to "what" is the solution. Second, tacit knowledge play different roles in between intuition and insight. On the one hand, tacit knowledge is conducive to intuitive judgment. On the other hand, tacit knowledge may first impede but later facilitate insight occurrence. Furthermore, we share theoretical, and methodological views on how to access the distinction between intuition and insight.

  14. Deep Learning in Gastrointestinal Endoscopy.

    Science.gov (United States)

    Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

    2016-01-01

    Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

  15. Deep mycoses in Amazon region.

    Science.gov (United States)

    Talhari, S; Cunha, M G; Schettini, A P; Talhari, A C

    1988-09-01

    Patients with deep mycoses diagnosed in dermatologic clinics of Manaus (state of Amazonas, Brazil) were studied from November 1973 to December 1983. They came from the Brazilian states of Amazonas, Pará, Acre, and Rondônia and the Federal Territory of Roraima. All of these regions, with the exception of Pará, are situated in the western part of the Amazon Basin. The climatic conditions in this region are almost the same: tropical forest, high rainfall, and mean annual temperature of 26C. The deep mycoses diagnosed, in order of frequency, were Jorge Lobo's disease, paracoccidioidomycosis, chromomycosis, sporotrichosis, mycetoma, cryptococcosis, zygomycosis, and histoplasmosis.

  16. 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

  17. The neural signatures of distinct psychopathic traits.

    Science.gov (United States)

    Carré, Justin M; Hyde, Luke W; Neumann, Craig S; Viding, Essi; Hariri, Ahmad R

    2013-01-01

    Recent studies suggest that psychopathy may be associated with dysfunction in the neural circuitry supporting both threat- and reward-related processes. However, these studies have involved small samples and often focused on extreme groups. Thus, it is unclear to what extent current findings may generalize to psychopathic traits in the general population. Furthermore, no studies have systematically and simultaneously assessed associations between distinct psychopathy facets and both threat- and reward-related brain function in the same sample of participants. Here, we examined the relationship between threat-related amygdala reactivity and reward-related ventral striatum (VS) reactivity and variation in four facets of self-reported psychopathy in a sample of 200 young adults. Path models indicated that amygdala reactivity to fearful facial expressions is negatively associated with the interpersonal facet of psychopathy, whereas amygdala reactivity to angry facial expressions is positively associated with the lifestyle facet. Furthermore, these models revealed that differential VS reactivity to positive versus negative feedback is negatively associated with the lifestyle facet. There was suggestive evidence for gender-specific patterns of association between brain function and psychopathy facets. Our findings are the first to document differential associations between both threat- and reward-related neural processes and distinct facets of psychopathy and thus provide a more comprehensive picture of the pattern of neural vulnerabilities that may predispose to maladaptive outcomes associated with psychopathy.

  18. The Distinction Between Curative and Assistive Technology.

    Science.gov (United States)

    Stramondo, Joseph A

    2018-05-01

    Disability activists have sometimes claimed their disability has actually increased their well-being. Some even say they would reject a cure to keep these gains. Yet, these same activists often simultaneously propose improvements to the quality and accessibility of assistive technology. However, for any argument favoring assistive over curative technology (or vice versa) to work, there must be a coherent distinction between the two. This line is already vague and will become even less clear with the emergence of novel technologies. This paper asks and tries to answer the question: what is it about the paradigmatic examples of curative and assistive technologies that make them paradigmatic and how can these defining features help us clarify the hard cases? This analysis will begin with an argument that, while the common views of this distinction adequately explain the paradigmatic cases, they fail to accurately pick out the relevant features of those technologies that make them paradigmatic and to provide adequate guidance for parsing the hard cases. Instead, it will be claimed that these categories of curative or assistive technologies are defined by the role the technologies play in establishing a person's relational narrative identity as a member of one of two social groups: disabled people or non-disabled people.

  19. Corticosteroid receptors adopt distinct cyclical transcriptional signatures.

    Science.gov (United States)

    Le Billan, Florian; Amazit, Larbi; Bleakley, Kevin; Xue, Qiong-Yao; Pussard, Eric; Lhadj, Christophe; Kolkhof, Peter; Viengchareun, Say; Fagart, Jérôme; Lombès, Marc

    2018-05-07

    Mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) are two closely related hormone-activated transcription factors that regulate major pathophysiologic functions. High homology between these receptors accounts for the crossbinding of their corresponding ligands, MR being activated by both aldosterone and cortisol and GR essentially activated by cortisol. Their coexpression and ability to bind similar DNA motifs highlight the need to investigate their respective contributions to overall corticosteroid signaling. Here, we decipher the transcriptional regulatory mechanisms that underlie selective effects of MRs and GRs on shared genomic targets in a human renal cellular model. Kinetic, serial, and sequential chromatin immunoprecipitation approaches were performed on the period circadian protein 1 ( PER1) target gene, providing evidence that both receptors dynamically and cyclically interact at the same target promoter in a specific and distinct transcriptional signature. During this process, both receptors regulate PER1 gene by binding as homo- or heterodimers to the same promoter region. Our results suggest a novel level of MR-GR target gene regulation, which should be considered for a better and integrated understanding of corticosteroid-related pathophysiology.-Le Billan, F., Amazit, L., Bleakley, K., Xue, Q.-Y., Pussard, E., Lhadj, C., Kolkhof, P., Viengchareun, S., Fagart, J., Lombès, M. Corticosteroid receptors adopt distinct cyclical transcriptional signatures.

  20. Distinct types of eigenvector localization in networks

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Castellano, Claudio

    2016-01-01

    The spectral properties of the adjacency matrix provide a trove of information about the structure and function of complex networks. In particular, the largest eigenvalue and its associated principal eigenvector are crucial in the understanding of nodes’ centrality and the unfolding of dynamical processes. Here we show that two distinct types of localization of the principal eigenvector may occur in heterogeneous networks. For synthetic networks with degree distribution P(q) ~ q-γ, localization occurs on the largest hub if γ > 5/2 for γ < 5/2 a new type of localization arises on a mesoscopic subgraph associated with the shell with the largest index in the K-core decomposition. Similar evidence for the existence of distinct localization modes is found in the analysis of real-world networks. Our results open a new perspective on dynamical processes on networks and on a recently proposed alternative measure of node centrality based on the non-backtracking matrix.

  1. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu

    2017-12-23

    Motivation: Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals. Results: Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. Availability: The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

  2. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    None

    2003-09-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a study to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. An assessment of historical deep gas well drilling activity and forecast of future trends was completed during the first six months of the project; this segment of the project was covered in Technical Project Report No. 1. The second progress report covers the next six months of the project during which efforts were primarily split between summarizing rock mechanics and fracture growth in deep reservoirs and contacting operators about case studies of deep gas well stimulation.

  3. STIMULATION TECHNOLOGIES FOR DEEP WELL COMPLETIONS

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2003-06-01

    The Department of Energy (DOE) is sponsoring a Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a project to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. Phase 1 was recently completed and consisted of assessing deep gas well drilling activity (1995-2007) and an industry survey on deep gas well stimulation practices by region. Of the 29,000 oil, gas and dry holes drilled in 2002, about 300 were drilled in the deep well; 25% were dry, 50% were high temperature/high pressure completions and 25% were simply deep completions. South Texas has about 30% of these wells, Oklahoma 20%, Gulf of Mexico Shelf 15% and the Gulf Coast about 15%. The Rockies represent only 2% of deep drilling. Of the 60 operators who drill deep and HTHP wells, the top 20 drill almost 80% of the wells. Six operators drill half the U.S. deep wells. Deep drilling peaked at 425 wells in 1998 and fell to 250 in 1999. Drilling is expected to rise through 2004 after which drilling should cycle down as overall drilling declines.

  4. Deep water overflow in the Faroe Bank Channel; modelling, processes, and impact

    DEFF Research Database (Denmark)

    Rullyanto, Arief

    , creating new water masses with distinct temperature, salinity and density characteristics. The change of water mass characteristics not only affects the local environment, but also far distant regions. The Faroe Bank Channel, which is located in the southern part of Faroe Islands, is one of the most...... under different circumstances. The focus is on the Faroe Bank Channel, a relatively small region, which has a significant impact on the global ocean circulation and marine organisms that live in its environment....... or tides, but also deep beneath the surface, where deep-water currents circulate waters throughout the world’s oceans. In certain very-localized regions, the flow of the deep-water has to travel over a sill in a narrow submarine channel. This overflow process mixes the deep water with overlying waters...

  5. Deep Space Climate Observatory (DSCOVR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Deep Space Climate ObserVatoRy (DSCOVR) satellite is a NOAA operated asset at the first Lagrange (L1) point. The primary space weather instrument is the PlasMag...

  6. Ploughing the deep sea floor.

    Science.gov (United States)

    Puig, Pere; Canals, Miquel; Company, Joan B; Martín, Jacobo; Amblas, David; Lastras, Galderic; Palanques, Albert

    2012-09-13

    Bottom trawling is a non-selective commercial fishing technique whereby heavy nets and gear are pulled along the sea floor. The direct impact of this technique on fish populations and benthic communities has received much attention, but trawling can also modify the physical properties of seafloor sediments, water–sediment chemical exchanges and sediment fluxes. Most of the studies addressing the physical disturbances of trawl gear on the seabed have been undertaken in coastal and shelf environments, however, where the capacity of trawling to modify the seafloor morphology coexists with high-energy natural processes driving sediment erosion, transport and deposition. Here we show that on upper continental slopes, the reworking of the deep sea floor by trawling gradually modifies the shape of the submarine landscape over large spatial scales. We found that trawling-induced sediment displacement and removal from fishing grounds causes the morphology of the deep sea floor to become smoother over time, reducing its original complexity as shown by high-resolution seafloor relief maps. Our results suggest that in recent decades, following the industrialization of fishing fleets, bottom trawling has become an important driver of deep seascape evolution. Given the global dimension of this type of fishery, we anticipate that the morphology of the upper continental slope in many parts of the world’s oceans could be altered by intensive bottom trawling, producing comparable effects on the deep sea floor to those generated by agricultural ploughing on land.

  7. FOSTERING DEEP LEARNING AMONGST ENTREPRENEURSHIP ...

    African Journals Online (AJOL)

    An important prerequisite for this important objective to be achieved is that lecturers ensure that students adopt a deep learning approach towards entrepreneurship courses been taught, as this will enable them to truly understand key entrepreneurial concepts and strategies and how they can be implemented in the real ...

  8. Deep Space Gateway "Recycler" Mission

    Science.gov (United States)

    Graham, L.; Fries, M.; Hamilton, J.; Landis, R.; John, K.; O'Hara, W.

    2018-02-01

    Use of the Deep Space Gateway provides a hub for a reusable planetary sample return vehicle for missions to gather star dust as well as samples from various parts of the solar system including main belt asteroids, near-Earth asteroids, and Mars moon.

  9. Deep freezers with heat recovery

    Energy Technology Data Exchange (ETDEWEB)

    Kistler, J.

    1981-09-02

    Together with space and water heating systems, deep freezers are the biggest energy consumers in households. The article investigates the possibility of using the waste heat for water heating. The design principle of such a system is presented in a wiring diagram.

  10. A Deep-Sea Simulation.

    Science.gov (United States)

    Montes, Georgia E.

    1997-01-01

    Describes an activity that simulates exploration techniques used in deep-sea explorations and teaches students how this technology can be used to take a closer look inside volcanoes, inspect hazardous waste sites such as nuclear reactors, and explore other environments dangerous to humans. (DDR)

  11. Barbabos Deep-Water Sponges

    NARCIS (Netherlands)

    Soest, van R.W.M.; Stentoft, N.

    1988-01-01

    Deep-water sponges dredged up in two locations off the west coast of Barbados are systematically described. A total of 69 species is recorded, among which 16 are new to science, viz. Pachymatisma geodiformis, Asteropus syringiferus, Cinachyra arenosa, Theonella atlantica. Corallistes paratypus,

  12. Deep learning for visual understanding

    NARCIS (Netherlands)

    Guo, Y.

    2017-01-01

    With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically. Deep learning, served as one of the most significant breakthroughs, has brought revolutionary success in diverse visual applications,

  13. Deep-Sky Video Astronomy

    CERN Document Server

    Massey, Steve

    2009-01-01

    A guide to using modern integrating video cameras for deep-sky viewing and imaging with the kinds of modest telescopes available commercially to amateur astronomers. It includes an introduction and a brief history of the technology and camera types. It examines the pros and cons of this unrefrigerated yet highly efficient technology

  14. DM Considerations for Deep Drilling

    OpenAIRE

    Dubois-Felsmann, Gregory

    2016-01-01

    An outline of the current situation regarding the DM plans for the Deep Drilling surveys and an invitation to the community to provide feedback on what they would like to see included in the data processing and visualization of these surveys.

  15. Lessons from Earth's Deep Time

    Science.gov (United States)

    Soreghan, G. S.

    2005-01-01

    Earth is a repository of data on climatic changes from its deep-time history. Article discusses the collection and study of these data to predict future climatic changes, the need to create national study centers for the purpose, and the necessary cooperation between different branches of science in climatic research.

  16. Digging Deeper: The Deep Web.

    Science.gov (United States)

    Turner, Laura

    2001-01-01

    Focuses on the Deep Web, defined as Web content in searchable databases of the type that can be found only by direct query. Discusses the problems of indexing; inability to find information not indexed in the search engine's database; and metasearch engines. Describes 10 sites created to access online databases or directly search them. Lists ways…

  17. Deep Learning and Music Adversaries

    DEFF Research Database (Denmark)

    Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

    2015-01-01

    the minimal perturbation of the input image such that the system misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the system inputs are magnitude spectral frames, which require...

  18. Molecular Technique to Understand Deep Microbial Diversity

    Science.gov (United States)

    Vaishampayan, Parag A.; Venkateswaran, Kasthuri J.

    2012-01-01

    Current sequencing-based and DNA microarray techniques to study microbial diversity are based on an initial PCR (polymerase chain reaction) amplification step. However, a number of factors are known to bias PCR amplification and jeopardize the true representation of bacterial diversity. PCR amplification of the minor template appears to be suppressed by the exponential amplification of the more abundant template. It is widely acknowledged among environmental molecular microbiologists that genetic biosignatures identified from an environment only represent the most dominant populations. The technological bottleneck has overlooked the presence of the less abundant minority population, and underestimated their role in the ecosystem maintenance. To generate PCR amplicons for subsequent diversity analysis, bacterial l6S rRNA genes are amplified by PCR using universal primers. Two distinct PCR regimes are employed in parallel: one using normal and the other using biotinlabeled universal primers. PCR products obtained with biotin-labeled primers are mixed with streptavidin-labeled magnetic beads and selectively captured in the presence of a magnetic field. Less-abundant DNA templates that fail to amplify in this first round of PCR amplification are subjected to a second round of PCR using normal universal primers. These PCR products are then subjected to downstream diversity analyses such as conventional cloning and sequencing. A second round of PCR amplified the minority population and completed the deep diversity picture of the environmental sample.

  19. Physiologically anaerobic microorganisms of the deep subsurface

    International Nuclear Information System (INIS)

    Stevens, S.E. Jr.; Chung, K.T.

    1993-10-01

    Anaerobic bacteria were isolated from deep subsurface sediment samples taken at study sites in Idaho (INEL) and Washington (HR) by culturing on dilute and concentrated medium. Morphologically distinct colonies were purified, and their responses to 21 selected physiological tests were determined. Although the number of isolates was small (18 INEL, 27 HR) some general patterns could be determined. Most strains could utilize all the carbon sources, however the glycerol and melizitose utilization was positive for 50% or less of the HR isolates. Catalase activity (27.78% at INEL, 74.07% at HR) and tryptophan metabolism (11.12% at INEL, 40.74% at HR) were significantly different between the two study sites. MPN and viable counts indicate that sediments near the water table yield the greatest numbers of anaerobes. Deeper sediments also appear to be more selective with the greatest number of viable counts on low-nutrient mediums. Likewise, only strictly obligate anaerobes were found in the deepest sediment samples. Selective media indicated the presence of methanogens, acetogens, and sulfate reducers at only the HR site

  20. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2005-06-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies conducted a study to evaluate the stimulation of deep wells. The objective of the project was to review U.S. deep well drilling and stimulation activity, review rock mechanics and fracture growth in deep, high-pressure/temperature wells and evaluate stimulation technology in several key deep plays. This report documents results from this project.

  1. Entrepreneurship research in Spain: developments and distinctiveness.

    Science.gov (United States)

    Sánchez, José C; Gutiérrez, Andrea

    2011-08-01

    This article presents a review of research on entrepreneurship in Spain, paying particular attention to its beginnings, nature and main focus of interest. We have developed a database based on the review of 471 works produced between 1977 and 2009, including articles published in national and international journals and dissertations (read in Spain) that allowed us to extract the following results. There is a preference for qualitative methods, conceptual contributions and the entrepreneurial process as the privileged research theme. There is also a strong focus of interest on micro and small enterprises. These characteristics of Spanish research in areas of entrepreneurship can make a distinctive contribution to international research. However, the dissemination of knowledge and inadequate strategies for international publication limit the diffusion of Spanish research in entrepreneurship. Lastly, we discuss the implications for future research.

  2. 10 distinct stellar populations in omega Centauri.

    Science.gov (United States)

    Bellini, Andrea; Anderson, Jay; Bedin, Luigi R.; Cool, Adrienne; King, Ivan R.; van der marel, roeland p.

    2015-08-01

    We are constructing the most comprehensive catalog of photometry and proper motions ever assembled for a globular cluster. The core of omega Centauri has been imaged over 600 times through WFC3’s UVIS and IR channels for the purposes of detector calibration. There exist ~30 exposures each for 26 filters, stretching uniformly from F225W in the UV to F160W in the infrared. Furthermore, the 12-year baseline between this data and a 2002 ACS survey will more than triple both the accuracy and the number of well-measured stars compared to previous studies.This totally unprecedented complete spectral coverage for over 400,000 stars, from the red-giant branch down to the white dwarfs, provides the best chance yet to understand the multiple-population phenomenon in any globular cluster. A preliminary analysis of the color-magnitude diagrams in different bands already allows us to identify 10 distinct sequences.

  3. Anticancer properties of distinct antimalarial drug classes.

    Directory of Open Access Journals (Sweden)

    Rob Hooft van Huijsduijnen

    Full Text Available We have tested five distinct classes of established and experimental antimalarial drugs for their anticancer potential, using a panel of 91 human cancer lines. Three classes of drugs: artemisinins, synthetic peroxides and DHFR (dihydrofolate reductase inhibitors effected potent inhibition of proliferation with IC50s in the nM- low µM range, whereas a DHODH (dihydroorotate dehydrogenase and a putative kinase inhibitor displayed no activity. Furthermore, significant synergies were identified with erlotinib, imatinib, cisplatin, dasatinib and vincristine. Cluster analysis of the antimalarials based on their differential inhibition of the various cancer lines clearly segregated the synthetic peroxides OZ277 and OZ439 from the artemisinin cluster that included artesunate, dihydroartemisinin and artemisone, and from the DHFR inhibitors pyrimethamine and P218 (a parasite DHFR inhibitor, emphasizing their shared mode of action. In order to further understand the basis of the selectivity of these compounds against different cancers, microarray-based gene expression data for 85 of the used cell lines were generated. For each compound, distinct sets of genes were identified whose expression significantly correlated with compound sensitivity. Several of the antimalarials tested in this study have well-established and excellent safety profiles with a plasma exposure, when conservatively used in malaria, that is well above the IC50s that we identified in this study. Given their unique mode of action and potential for unique synergies with established anticancer drugs, our results provide a strong basis to further explore the potential application of these compounds in cancer in pre-clinical or and clinical settings.

  4. Anticancer Properties of Distinct Antimalarial Drug Classes

    Science.gov (United States)

    Hooft van Huijsduijnen, Rob; Guy, R. Kiplin; Chibale, Kelly; Haynes, Richard K.; Peitz, Ingmar; Kelter, Gerhard; Phillips, Margaret A.; Vennerstrom, Jonathan L.; Yuthavong, Yongyuth; Wells, Timothy N. C.

    2013-01-01

    We have tested five distinct classes of established and experimental antimalarial drugs for their anticancer potential, using a panel of 91 human cancer lines. Three classes of drugs: artemisinins, synthetic peroxides and DHFR (dihydrofolate reductase) inhibitors effected potent inhibition of proliferation with IC50s in the nM- low µM range, whereas a DHODH (dihydroorotate dehydrogenase) and a putative kinase inhibitor displayed no activity. Furthermore, significant synergies were identified with erlotinib, imatinib, cisplatin, dasatinib and vincristine. Cluster analysis of the antimalarials based on their differential inhibition of the various cancer lines clearly segregated the synthetic peroxides OZ277 and OZ439 from the artemisinin cluster that included artesunate, dihydroartemisinin and artemisone, and from the DHFR inhibitors pyrimethamine and P218 (a parasite DHFR inhibitor), emphasizing their shared mode of action. In order to further understand the basis of the selectivity of these compounds against different cancers, microarray-based gene expression data for 85 of the used cell lines were generated. For each compound, distinct sets of genes were identified whose expression significantly correlated with compound sensitivity. Several of the antimalarials tested in this study have well-established and excellent safety profiles with a plasma exposure, when conservatively used in malaria, that is well above the IC50s that we identified in this study. Given their unique mode of action and potential for unique synergies with established anticancer drugs, our results provide a strong basis to further explore the potential application of these compounds in cancer in pre-clinical or and clinical settings. PMID:24391728

  5. Neurophysiological Distinction between Schizophrenia and Schizoaffective Disorder

    Science.gov (United States)

    Mathalon, Daniel H.; Hoffman, Ralph E.; Watson, Todd D.; Miller, Ryan M.; Roach, Brian J.; Ford, Judith M.

    2009-01-01

    Schizoaffective disorder (SA) is distinguished from schizophrenia (SZ) based on the presence of prominent mood symptoms over the illness course. Despite this clinical distinction, SA and SZ patients are often combined in research studies, in part because data supporting a distinct pathophysiological boundary between the disorders are lacking. Indeed, few studies have addressed whether neurobiological abnormalities associated with SZ, such as the widely replicated reduction and delay of the P300 event-related potential (ERP), are also present in SA. Scalp EEG was acquired from patients with DSM-IV SA (n = 15) or SZ (n = 22), as well as healthy controls (HC; n = 22) to assess the P300 elicited by infrequent target (15%) and task-irrelevant distractor (15%) stimuli in separate auditory and visual ”oddball” tasks. P300 amplitude was reduced and delayed in SZ, relative to HC, consistent with prior studies. These SZ abnormalities did not interact with stimulus type (target vs. task-irrelevant distractor) or modality (auditory vs. visual). Across sensory modality and stimulus type, SA patients exhibited normal P300 amplitudes (significantly larger than SZ patients and indistinguishable from HC). However, P300 latency and reaction time were both equivalently delayed in SZ and SA patients, relative to HC. P300 differences between SA and SZ patients could not be accounted for by variation in symptom severity, socio-economic status, education, or illness duration. Although both groups show similar deficits in processing speed, SA patients do not exhibit the P300 amplitude deficits evident in SZ, consistent with an underlying pathophysiological boundary between these disorders. PMID:20140266

  6. Deep Web and Dark Web: Deep World of the Internet

    OpenAIRE

    Çelik, Emine

    2018-01-01

    The Internet is undoubtedly still a revolutionary breakthrough in the history of humanity. Many people use the internet for communication, social media, shopping, political and social agenda, and more. Deep Web and Dark Web concepts not only handled by computer, software engineers but also handled by social siciensists because of the role of internet for the States in international arenas, public institutions and human life. By the moving point that very importantrole of internet for social s...

  7. 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.

  8. Deep Phenotyping: Deep Learning For Temporal Phenotype/Genotype Classification

    OpenAIRE

    Najafi, Mohammad; Namin, Sarah; Esmaeilzadeh, Mohammad; Brown, Tim; Borevitz, Justin

    2017-01-01

    High resolution and high throughput, genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. Complex developmental phenotypes are observed by imaging a variety of accessions in different environment conditions, however extracting the genetically heritable traits is challenging. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Long-Short Term Memories (LSTMs), h...

  9. The pursuit of optimal distinctiveness and consumer preferences.

    Science.gov (United States)

    He, Lingnan; Cong, Feng; Liu, Yanping; Zhou, Xinyue

    2010-10-01

    This article investigates the effect of optimal distinctiveness on consumer product consumption. The authors argue that consumers acquire and display material possessions to restore their optimal levels of distinctiveness. Results showed that placing consumers in a state of low distinctiveness increased desire to acquire distinctive products, whereas perceptions of high distinctiveness reduced desire to acquire such products. Consumers' desire for distinctiveness-related products held true for various consumer choices, including willingness to pay more for limited-edition products and preference for unpopular gifts. This finding has implications for understanding consumer choice in expressing identity. © 2010 The Authors. Scandinavian Journal of Psychology © 2010 The Scandinavian Psychological Associations.

  10. Deep Neuromuscular Blockade Improves Laparoscopic Surgical Conditions

    DEFF Research Database (Denmark)

    Rosenberg, Jacob; Herring, W Joseph; Blobner, Manfred

    2017-01-01

    INTRODUCTION: Sustained deep neuromuscular blockade (NMB) during laparoscopic surgery may facilitate optimal surgical conditions. This exploratory study assessed whether deep NMB improves surgical conditions and, in doing so, allows use of lower insufflation pressures during laparoscopic cholecys...

  11. Joint Training of Deep Boltzmann Machines

    OpenAIRE

    Goodfellow, Ian; Courville, Aaron; Bengio, Yoshua

    2012-01-01

    We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at a time, or do not perform well on classifi- cation tasks.

  12. 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...

  13. Is Multitask Deep Learning Practical for Pharma?

    Science.gov (United States)

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

    2017-08-28

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

  14. Evaluation of the DeepWind concept

    DEFF Research Database (Denmark)

    Schmidt Paulsen, Uwe; Borg, Michael; Gonzales Seabra, Luis Alberto

    The report describes the DeepWind 5 MW conceptual design as a baseline for results obtained in the scientific and technical work packages of the DeepWind project. A comparison of DeepWi nd with existing VAWTs and paper projects are carried out and the evaluation of the concept in terms of cost...

  15. Consolidated Deep Actor Critic Networks (DRAFT)

    NARCIS (Netherlands)

    Van der Laan, T.A.

    2015-01-01

    The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with

  16. Simulator Studies of the Deep Stall

    Science.gov (United States)

    White, Maurice D.; Cooper, George E.

    1965-01-01

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

  17. TOPIC MODELING: CLUSTERING OF DEEP WEBPAGES

    OpenAIRE

    Muhunthaadithya C; Rohit J.V; Sadhana Kesavan; E. Sivasankar

    2015-01-01

    The internet is comprised of massive amount of information in the form of zillions of web pages.This information can be categorized into the surface web and the deep web. The existing search engines can effectively make use of surface web information.But the deep web remains unexploited yet. Machine learning techniques have been commonly employed to access deep web content.

  18. Does the reading of different orthographies produce distinct brain activity patterns? An ERP study.

    Science.gov (United States)

    Bar-Kochva, Irit; Breznitz, Zvia

    2012-01-01

    Orthographies vary in the degree of transparency of spelling-sound correspondence. These range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Only a few studies have examined whether orthographic depth is reflected in brain activity. In these studies a between-language design was applied, making it difficult to isolate the aspect of orthographic depth. In the present work this question was examined using a within-subject-and-language investigation. The participants were speakers of Hebrew, as they are skilled in reading two forms of script transcribing the same oral language. One form is the shallow pointed script (with diacritics), and the other is the deep unpointed script (without diacritics). Event-related potentials (ERPs) were recorded while skilled readers carried out a lexical decision task in the two forms of script. A visual non-orthographic task controlled for the visual difference between the scripts (resulting from the addition of diacritics to the pointed script only). At an early visual-perceptual stage of processing (~165 ms after target onset), the pointed script evoked larger amplitudes with longer latencies than the unpointed script at occipital-temporal sites. However, these effects were not restricted to orthographic processing, and may therefore have reflected, at least in part, the visual load imposed by the diacritics. Nevertheless, the results implied that distinct orthographic processing may have also contributed to these effects. At later stages (~340 ms after target onset) the unpointed script elicited larger amplitudes than the pointed one with earlier latencies. As this latency has been linked to orthographic-linguistic processing and to the classification of stimuli, it is suggested that these differences are associated with distinct lexical processing of a shallow and a deep orthography.

  19. Does the reading of different orthographies produce distinct brain activity patterns? An ERP study.

    Directory of Open Access Journals (Sweden)

    Irit Bar-Kochva

    Full Text Available Orthographies vary in the degree of transparency of spelling-sound correspondence. These range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Only a few studies have examined whether orthographic depth is reflected in brain activity. In these studies a between-language design was applied, making it difficult to isolate the aspect of orthographic depth. In the present work this question was examined using a within-subject-and-language investigation. The participants were speakers of Hebrew, as they are skilled in reading two forms of script transcribing the same oral language. One form is the shallow pointed script (with diacritics, and the other is the deep unpointed script (without diacritics. Event-related potentials (ERPs were recorded while skilled readers carried out a lexical decision task in the two forms of script. A visual non-orthographic task controlled for the visual difference between the scripts (resulting from the addition of diacritics to the pointed script only. At an early visual-perceptual stage of processing (~165 ms after target onset, the pointed script evoked larger amplitudes with longer latencies than the unpointed script at occipital-temporal sites. However, these effects were not restricted to orthographic processing, and may therefore have reflected, at least in part, the visual load imposed by the diacritics. Nevertheless, the results implied that distinct orthographic processing may have also contributed to these effects. At later stages (~340 ms after target onset the unpointed script elicited larger amplitudes than the pointed one with earlier latencies. As this latency has been linked to orthographic-linguistic processing and to the classification of stimuli, it is suggested that these differences are associated with distinct lexical processing of a shallow and a deep orthography.

  20. How deep-sea wood falls sustain chemosynthetic life.

    Directory of Open Access Journals (Sweden)

    Christina Bienhold

    Full Text Available Large organic food falls to the deep sea--such as whale carcasses and wood logs--are known to serve as stepping stones for the dispersal of highly adapted chemosynthetic organisms inhabiting hot vents and cold seeps. Here we investigated the biogeochemical and microbiological processes leading to the development of sulfidic niches by deploying wood colonization experiments at a depth of 1690 m in the Eastern Mediterranean for one year. Wood-boring bivalves of the genus Xylophaga played a key role in the degradation of the wood logs, facilitating the development of anoxic zones and anaerobic microbial processes such as sulfate reduction. Fauna and bacteria associated with the wood included types reported from other deep-sea habitats including chemosynthetic ecosystems, confirming the potential role of large organic food falls as biodiversity hot spots and stepping stones for vent and seep communities. Specific bacterial communities developed on and around the wood falls within one year and were distinct from freshly submerged wood and background sediments. These included sulfate-reducing and cellulolytic bacterial taxa, which are likely to play an important role in the utilization of wood by chemosynthetic life and other deep-sea animals.

  1. How Deep-Sea Wood Falls Sustain Chemosynthetic Life

    Science.gov (United States)

    Bienhold, Christina; Pop Ristova, Petra; Wenzhöfer, Frank; Dittmar, Thorsten; Boetius, Antje

    2013-01-01

    Large organic food falls to the deep sea – such as whale carcasses and wood logs – are known to serve as stepping stones for the dispersal of highly adapted chemosynthetic organisms inhabiting hot vents and cold seeps. Here we investigated the biogeochemical and microbiological processes leading to the development of sulfidic niches by deploying wood colonization experiments at a depth of 1690 m in the Eastern Mediterranean for one year. Wood-boring bivalves of the genus Xylophaga played a key role in the degradation of the wood logs, facilitating the development of anoxic zones and anaerobic microbial processes such as sulfate reduction. Fauna and bacteria associated with the wood included types reported from other deep-sea habitats including chemosynthetic ecosystems, confirming the potential role of large organic food falls as biodiversity hot spots and stepping stones for vent and seep communities. Specific bacterial communities developed on and around the wood falls within one year and were distinct from freshly submerged wood and background sediments. These included sulfate-reducing and cellulolytic bacterial taxa, which are likely to play an important role in the utilization of wood by chemosynthetic life and other deep-sea animals. PMID:23301092

  2. 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.

  3. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  4. Deep Space Habitat Concept Demonstrator

    Science.gov (United States)

    Bookout, Paul S.; Smitherman, David

    2015-01-01

    This project will develop, integrate, test, and evaluate Habitation Systems that will be utilized as technology testbeds and will advance NASA's understanding of alternative deep space mission architectures, requirements, and operations concepts. Rapid prototyping and existing hardware will be utilized to develop full-scale habitat demonstrators. FY 2014 focused on the development of a large volume Space Launch System (SLS) class habitat (Skylab Gen 2) based on the SLS hydrogen tank components. Similar to the original Skylab, a tank section of the SLS rocket can be outfitted with a deep space habitat configuration and launched as a payload on an SLS rocket. This concept can be used to support extended stay at the Lunar Distant Retrograde Orbit to support the Asteroid Retrieval Mission and provide a habitat suitable for human missions to Mars.

  5. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-08-10

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during semiconductor manufacturing for deep reactive etches. Such a manufacturing process may include depositing a first mask material on a substrate; depositing a second mask material on the first mask material; depositing a third mask material on the second mask material; patterning the third mask material with a pattern corresponding to one or more trenches for transfer to the substrate; transferring the pattern from the third mask material to the second mask material; transferring the pattern from the second mask material to the first mask material; and/or transferring the pattern from the first mask material to the substrate.

  6. Soft-Deep Boltzmann Machines

    OpenAIRE

    Kiwaki, Taichi

    2015-01-01

    We present a layered Boltzmann machine (BM) that can better exploit the advantages of a distributed representation. It is widely believed that deep BMs (DBMs) have far greater representational power than its shallow counterpart, restricted Boltzmann machines (RBMs). However, this expectation on the supremacy of DBMs over RBMs has not ever been validated in a theoretical fashion. In this paper, we provide both theoretical and empirical evidences that the representational power of DBMs can be a...

  7. Evolving Deep Networks Using HPC

    Energy Technology Data Exchange (ETDEWEB)

    Young, Steven R. [ORNL, Oak Ridge; Rose, Derek C. [ORNL, Oak Ridge; Johnston, Travis [ORNL, Oak Ridge; Heller, William T. [ORNL, Oak Ridge; Karnowski, thomas P. [ORNL, Oak Ridge; Potok, Thomas E. [ORNL, Oak Ridge; Patton, Robert M. [ORNL, Oak Ridge; Perdue, Gabriel [Fermilab; Miller, Jonathan [Santa Maria U., Valparaiso

    2017-01-01

    While a large number of deep learning networks have been studied and published that produce outstanding results on natural image datasets, these datasets only make up a fraction of those to which deep learning can be applied. These datasets include text data, audio data, and arrays of sensors that have very different characteristics than natural images. As these “best” networks for natural images have been largely discovered through experimentation and cannot be proven optimal on some theoretical basis, there is no reason to believe that they are the optimal network for these drastically different datasets. Hyperparameter search is thus often a very important process when applying deep learning to a new problem. In this work we present an evolutionary approach to searching the possible space of network hyperparameters and construction that can scale to 18, 000 nodes. This approach is applied to datasets of varying types and characteristics where we demonstrate the ability to rapidly find best hyperparameters in order to enable practitioners to quickly iterate between idea and result.

  8. 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.

  9. Endpoint distinctiveness facilitates analogical mapping in pigeons.

    Science.gov (United States)

    Hagmann, Carl Erick; Cook, Robert G

    2015-03-01

    Analogical thinking necessitates mapping shared relations across two separate domains. We investigated whether pigeons could learn faster with ordinal mapping of relations across two physical dimensions (circle size & choice spatial position) relative to random mapping of these relations. Pigeons were trained to relate six circular samples of different sizes to horizontally positioned choice locations in a six alternative matching-to-sample task. Three pigeons were trained in a mapped condition in which circle size mapped directly onto choice spatial position. Three other pigeons were trained in a random condition in which the relations between size and choice position were arbitrarily assigned. The mapped group showed an advantage over the random group in acquiring this task. In a subsequent second phase, relations between the dimensions were ordinally reversed for the mapped group and re-randomized for the random group. There was no difference in how quickly matching accuracy re-emerged in the two groups, although the mapped group eventually performed more accurately. Analyses suggested this mapped advantage was likely due to endpoint distinctiveness and the benefits of proximity errors during choice responding rather than a conceptual or relational advantage attributable to the common or ordinal mapping of the two dimensions. This potential difficulty in mapping relations across dimensions may limit the pigeons' capacity for more advanced types of analogical reasoning. This article is part of a Special Issue entitled: Tribute to Tom Zentall. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Endpoint Distinctiveness Facilitates Analogical Mapping in Pigeons

    Science.gov (United States)

    Hagmann, Carl Erick; Cook, Robert G.

    2015-01-01

    Analogical thinking necessitates mapping shared relations across two separate domains. We investigated whether pigeons could learn faster with ordinal mapping of relations across two physical dimensions (circle size & choice spatial position) relative to random mapping of these relations. Pigeons were trained to relate six circular samples of different sizes to horizontally positioned choice locations in a six alternative matching-to-sample task. Three pigeons were trained in a mapped condition in which circle size mapped directly onto choice spatial position. Three other pigeons were trained in a random condition in which the relations between size and choice position were arbitrarily assigned. The mapped group showed an advantage over the random group in acquiring this task. In a subsequent second phase, reassignment, relations between the dimensions were ordinally reversed for the mapped group and re-randomized for the random group. There was no difference in how quickly matching accuracy re-emerged in the two groups, although the mapped group eventually performed more accurately. Analyses suggested this mapped advantage was likely due endpoint distinctiveness and the benefits of proximity errors during choice responding rather than a conceptual or relational advantage attributable to the common or ordinal map of the two dimensions. This potential difficulty in mapping relations across dimensions may limit the pigeons’ capacity for more advanced types of analogical reasoning. PMID:25447511

  11. Reservoir floodplains support distinct fish assemblages

    Science.gov (United States)

    Miranda, Leandro E.; Wigen, S. L.; Dagel, Jonah D.

    2014-01-01

    Reservoirs constructed on floodplain rivers are unique because the upper reaches of the impoundment may include extensive floodplain environments. Moreover, reservoirs that experience large periodic water level fluctuations as part of their operational objectives seasonally inundate and dewater floodplains in their upper reaches, partly mimicking natural inundations of river floodplains. In four flood control reservoirs in Mississippi, USA, we explored the dynamics of connectivity between reservoirs and adjacent floodplains and the characteristics of fish assemblages that develop in reservoir floodplains relative to those that develop in reservoir bays. Although fish species richness in floodplains and bays were similar, species composition differed. Floodplains emphasized fish species largely associated with backwater shallow environments, often resistant to harsh environmental conditions. Conversely, dominant species in bays represented mainly generalists that benefit from the continuous connectivity between the bay and the main reservoir. Floodplains in the study reservoirs provided desirable vegetated habitats at lower water level elevations, earlier in the year, and more frequently than in bays. Inundating dense vegetation in bays requires raising reservoir water levels above the levels required to reach floodplains. Therefore, aside from promoting distinct fish assemblages within reservoirs and helping promote diversity in regulated rivers, reservoir floodplains are valued because they can provide suitable vegetated habitats for fish species at elevations below the normal pool, precluding the need to annually flood upland vegetation that would inevitably be impaired by regular flooding. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

  12. Health and morality: two conceptually distinct categories?

    Science.gov (United States)

    Tengland, Per-Anders

    2012-03-01

    When seeing immoral actions, criminal or not, we sometimes deem the people who perform them unhealthy. This is especially so if the actions are of a serious nature, e.g. involving murder, assault, or rape. We turn our moral evaluation into an evaluation about health and illness. This tendency is partly supported by some diagnoses found in the DMS-IV, such as Antisocial personality disorder, and the ICD-10, such as Dissocial personality disorder. The aim of the paper is to answer the question: How analytically sound is the inclusion of morality into a theory of health? The holistic theory of Lennart Nordenfelt is used as a starting point, and it is used as an example of a theory where morality and health are conceptually distinct categories. Several versions of a pluralistic holistic theory are then discussed in order to see if, and if so, how, morality can be conceptually related to health. It is concluded that moral abilities (and dispositions) can be seen as being part of the individual's health. It is harder to incorporate moral virtues and moral actions into such a theory. However, if immoral actions "cluster" in an individual, and are of a severe kind, causing serious harm to other people, it is more likely that the person, for those reasons only, be deemed unhealthy.

  13. Are empathy and concern psychologically distinct?

    Science.gov (United States)

    Jordan, Matthew R; Amir, Dorsa; Bloom, Paul

    2016-12-01

    Researchers have long been interested in the relationship between feeling what you believe others feel-often described as empathy-and caring about the welfare of others-often described as compassion or concern. Many propose that empathy is a prerequisite for concern and is therefore the ultimate motivator of prosocial actions. To assess this hypothesis, the authors developed the Empathy Index, which consists of 2 novel scales, and explored their relationship to a measure of concern as well as to measures of cooperative and altruistic behavior. A series of factor analyses reveal that empathy and concern consistently load on different factors. Furthermore, they show that empathy and concern motivate different behaviors: concern for others is a uniquely positive predictor of prosocial action whereas empathy is either not predictive or negatively predictive of prosocial actions. Together these studies suggest that empathy and concern are psychologically distinct and empathy plays a more limited role in our moral lives than many believe. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  14. Medical student empathy: interpersonal distinctions and correlates.

    Science.gov (United States)

    Jordan, Kevin D; Foster, Penni Smith

    2016-12-01

    Attention to interpersonal behaviors, communication, and relational factors is taking on increasing importance in medical education. Medical student empathy is one aspect of the physician-patient relationship that is often involved in beneficial interactions leading to improved clinical outcomes and patient satisfaction. As an interpersonal quality, empathy is a social behavior well-suited to be examined from an interpersonal perspective. The present study used the interpersonal theory of clinical, personality, and social psychology to examine the construct of empathy and theorize about likely interpersonal correlates. One hundred and sixty-three students from an academic health center in the southeastern United States participated in this study. The medical student version of the Jefferson Scale of Empathy was used to assess empathy and its factors: Perspective taking, compassionate care, and walking in the patient's shoes. Interpersonal assessments included the International Personality Item Pool-Interpersonal Circumplex, the Interpersonal Support Evaluation List, and the UCLA Loneliness Scale. Distinct interpersonal styles and correlates emerged among empathy and its factors. While all factors of empathy were related to interpersonal warmth, perspective taking and compassionate care were also associated with submissiveness. Of note, only walking in the patient's shoes was correlated with both social support and less loneliness. These findings are discussed in light of interpersonal theory with particular attention paid to the implications for medical education and professional development.

  15. Deep learning classification in asteroseismology

    DEFF Research Database (Denmark)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2017-01-01

    In the power spectra of oscillating red giants, there are visually distinct features defining stars ascending the red giant branch from those that have commenced helium core burning. We train a 1D convolutional neural network by supervised learning to automatically learn these visual features from...

  16. Deep water recycling through time.

    Science.gov (United States)

    Magni, Valentina; Bouilhol, Pierre; van Hunen, Jeroen

    2014-11-01

    We investigate the dehydration processes in subduction zones and their implications for the water cycle throughout Earth's history. We use a numerical tool that combines thermo-mechanical models with a thermodynamic database to examine slab dehydration for present-day and early Earth settings and its consequences for the deep water recycling. We investigate the reactions responsible for releasing water from the crust and the hydrated lithospheric mantle and how they change with subduction velocity ( v s ), slab age ( a ) and mantle temperature (T m ). Our results show that faster slabs dehydrate over a wide area: they start dehydrating shallower and they carry water deeper into the mantle. We parameterize the amount of water that can be carried deep into the mantle, W (×10 5 kg/m 2 ), as a function of v s (cm/yr), a (Myrs), and T m (°C):[Formula: see text]. We generally observe that a 1) 100°C increase in the mantle temperature, or 2) ∼15 Myr decrease of plate age, or 3) decrease in subduction velocity of ∼2 cm/yr all have the same effect on the amount of water retained in the slab at depth, corresponding to a decrease of ∼2.2×10 5 kg/m 2 of H 2 O. We estimate that for present-day conditions ∼26% of the global influx water, or 7×10 8 Tg/Myr of H 2 O, is recycled into the mantle. Using a realistic distribution of subduction parameters, we illustrate that deep water recycling might still be possible in early Earth conditions, although its efficiency would generally decrease. Indeed, 0.5-3.7 × 10 8 Tg/Myr of H 2 O could still be recycled in the mantle at 2.8 Ga. Deep water recycling might be possible even in early Earth conditions We provide a scaling law to estimate the amount of H 2 O flux deep into the mantle Subduction velocity has a a major control on the crustal dehydration pattern.

  17. Vision in the deep sea.

    Science.gov (United States)

    Warrant, Eric J; Locket, N Adam

    2004-08-01

    The deep sea is the largest habitat on earth. Its three great faunal environments--the twilight mesopelagic zone, the dark bathypelagic zone and the vast flat expanses of the benthic habitat--are home to a rich fauna of vertebrates and invertebrates. In the mesopelagic zone (150-1000 m), the down-welling daylight creates an extended scene that becomes increasingly dimmer and bluer with depth. The available daylight also originates increasingly from vertically above, and bioluminescent point-source flashes, well contrasted against the dim background daylight, become increasingly visible. In the bathypelagic zone below 1000 m no daylight remains, and the scene becomes entirely dominated by point-like bioluminescence. This changing nature of visual scenes with depth--from extended source to point source--has had a profound effect on the designs of deep-sea eyes, both optically and neurally, a fact that until recently was not fully appreciated. Recent measurements of the sensitivity and spatial resolution of deep-sea eyes--particularly from the camera eyes of fishes and cephalopods and the compound eyes of crustaceans--reveal that ocular designs are well matched to the nature of the visual scene at any given depth. This match between eye design and visual scene is the subject of this review. The greatest variation in eye design is found in the mesopelagic zone, where dim down-welling daylight and bio-luminescent point sources may be visible simultaneously. Some mesopelagic eyes rely on spatial and temporal summation to increase sensitivity to a dim extended scene, while others sacrifice this sensitivity to localise pinpoints of bright bioluminescence. Yet other eyes have retinal regions separately specialised for each type of light. In the bathypelagic zone, eyes generally get smaller and therefore less sensitive to point sources with increasing depth. In fishes, this insensitivity, combined with surprisingly high spatial resolution, is very well adapted to the

  18. The deep Canary poleward undercurrent

    Science.gov (United States)

    Velez-Belchi, P. J.; Hernandez-Guerra, A.; González-Pola, C.; Fraile, E.; Collins, C. A.; Machín, F.

    2012-12-01

    Poleward undercurrents are well known features in Eastern Boundary systems. In the California upwelling system (CalCEBS), the deep poleward flow has been observed along the entire outer continental shelf and upper-slope, using indirect methods based on geostrophic estimates and also using direct current measurements. The importance of the poleward undercurrents in the CalCEBS, among others, is to maintain its high productivity by means of the transport of equatorial Pacific waters all the way northward to Vancouver Island and the subpolar gyre but there is also concern about the low oxygen concentration of these waters. However, in the case of the Canary Current Eastern Boundary upwelling system (CanCEBS), there are very few observations of the poleward undercurrent. Most of these observations are short-term mooring records, or drifter trajectories of the upper-slope flow. Hence, the importance of the subsurface poleward flow in the CanCEBS has been only hypothesized. Moreover, due to the large differences between the shape of the coastline and topography between the California and the Canary Current system, the results obtained for the CalCEBS are not completely applicable to the CanCEBS. In this study we report the first direct observations of the continuity of the deep poleward flow of the Canary Deep Poleward undercurrent (CdPU) in the North-Africa sector of the CanCEBS, and one of the few direct observations in the North-Africa sector of the Canary Current eastern boundary. The results indicate that the Canary Island archipelago disrupts the deep poleward undercurrent even at depths where the flow is not blocked by the bathymetry. The deep poleward undercurrent flows west around the eastern-most islands and north east of the Conception Bank to rejoin the intermittent branch that follows the African slope in the Lanzarote Passage. This hypothesis is consistent with the AAIW found west of Lanzarote, as far as 17 W. But also, this hypothesis would be coherent

  19. 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...

  20. Distinctiveness of Initial Preform Properties in Renovation

    Directory of Open Access Journals (Sweden)

    V. M. Yaroslavtsev

    2015-01-01

    Full Text Available Technologies of renovation form a special group of resource-and energy saving technological processes as they are, by definition, already aimed either at increasing resource of the objects satisfying needs of the society life support and practical activities in different spheres, or at extension of their life cycle including a reuse of material from which they are made. Renovation is used where there is a material object, which does not meet requirements of standard or technical documentation.A characteristic feature of the renovation technologies is lack of procedure for a choice of the preform as in all cases an initial preform is the renovation object itself. Thus each object, acting as an initial preform, has the exclusively individual properties, including technological ones.Distinctiveness of renovation object properties is correlated, first of all, with the personified conditions of formation and (or change of condition of their properties in time at all stages of life cycle (production – transportation – warehousing – operation starting with a preform material when manufacturing under all types of loadings (technological and operational. As a result each object forms its "history" of loading and damages and, therefore, its information base which has to consider the phenomenon of “heredity of life cycle”. The term "heredity of life cycle" characterizes information support of object at any moment under review, including both information of technological inheritance, and data of operational heredity.As a result at every moment of time we have a product with a set of new, uncertain properties caused by the phenomena of heredity of life cycle. These properties are individual for each object to be renovated, which changed its status for the status of initial preform for different types of renovation technologies. This is one of the most important distinctions of renovation technology from the technology used to manufacture a new

  1. Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation

    OpenAIRE

    Lea-Anne Henry; Sankha S. Mukherjee; Neil M. Roberston; Laurence De Clippele; J. Murray Roberts

    2016-01-01

    The mismatch between human capacity and the acquisition of Big Data such as Earth imagery undermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. Artificial intelligence (AI) solutions to Big Data issues are urgently needed as these could prove to be faster, more accurate, and cheaper. Reducing costs of managing protected areas in remote deep waters and in the High Seas is of great importance, and this is a realm where autonomous technology will be transformative.

  2. 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...

  3. Distinct genetic alterations in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Hassan Ashktorab

    Full Text Available BACKGROUND: Colon cancer (CRC development often includes chromosomal instability (CIN leading to amplifications and deletions of large DNA segments. Epidemiological, clinical, and cytogenetic studies showed that there are considerable differences between CRC tumors from African Americans (AAs and Caucasian patients. In this study, we determined genomic copy number aberrations in sporadic CRC tumors from AAs, in order to investigate possible explanations for the observed disparities. METHODOLOGY/PRINCIPAL FINDINGS: We applied genome-wide array comparative genome hybridization (aCGH using a 105k chip to identify copy number aberrations in samples from 15 AAs. In addition, we did a population comparative analysis with aCGH data in Caucasians as well as with a widely publicized list of colon cancer genes (CAN genes. There was an average of 20 aberrations per patient with more amplifications than deletions. Analysis of DNA copy number of frequently altered chromosomes revealed that deletions occurred primarily in chromosomes 4, 8 and 18. Chromosomal duplications occurred in more than 50% of cases on chromosomes 7, 8, 13, 20 and X. The CIN profile showed some differences when compared to Caucasian alterations. CONCLUSIONS/SIGNIFICANCE: Chromosome X amplification in male patients and chromosomes 4, 8 and 18 deletions were prominent aberrations in AAs. Some CAN genes were altered at high frequencies in AAs with EXOC4, EPHB6, GNAS, MLL3 and TBX22 as the most frequently deleted genes and HAPLN1, ADAM29, SMAD2 and SMAD4 as the most frequently amplified genes. The observed CIN may play a distinctive role in CRC in AAs.

  4. Municipal solid waste landfills harbor distinct microbiomes

    Science.gov (United States)

    Stamps, Blake W.; Lyles, Christopher N.; Suflita, Joseph M.; Masoner, Jason R.; Cozzarelli, Isabelle M.; Kolpin, Dana W.; Stevenson, Bradley S.

    2016-01-01

    Landfills are the final repository for most of the discarded material from human society and its “built environments.” Microorganisms subsequently degrade this discarded material in the landfill, releasing gases (largely CH4 and CO2) and a complex mixture of soluble chemical compounds in leachate. Characterization of “landfill microbiomes” and their comparison across several landfills should allow the identification of environmental or operational properties that influence the composition of these microbiomes and potentially their biodegradation capabilities. To this end, the composition of landfill microbiomes was characterized as part of an ongoing USGS national survey studying the chemical composition of leachates from 19 non-hazardous landfills across 16 states in the continental U.S. The landfills varied in parameters such as size, waste composition, management strategy, geography, and climate zone. The diversity and composition of bacterial and archaeal populations in leachate samples were characterized by 16S rRNA gene sequence analysis, and compared against a variety of physical and chemical parameters in an attempt to identify their impact on selection. Members of the Epsilonproteobacteria, Gammaproteobacteria, Clostridia, and candidate division OP3 were the most abundant. The distribution of the observed phylogenetic diversity could best be explained by a combination of variables and was correlated most strongly with the concentrations of chloride and barium, rate of evapotranspiration, age of waste, and the number of detected household chemicals. This study illustrates how leachate microbiomes are distinct from those of other natural or built environments, and sheds light on the major selective forces responsible for this microbial diversity.

  5. Municipal Solid Waste Landfills Harbor Distinct Microbiomes

    Directory of Open Access Journals (Sweden)

    Blake Warren Stamps

    2016-04-01

    Full Text Available Landfills are the final repository for most of the discarded material from human society and its built environments. Microorganisms subsequently degrade this discarded material in the landfill, releasing gases (largely CH4 and CO2 and a complex mixture of soluble chemical compounds in leachate. Characterization of landfill microbiomes and their comparison across several landfills should allow the identification of environmental or operational properties that influence the composition of these microbiomes and potentially their biodegradation capabilities. To this end, the composition of landfill microbiomes was characterized as part of an ongoing USGS national survey studying the chemical composition of leachates from 19 non-hazardous landfills across 16 states in the continental U.S. The landfills varied in parameters such as size, waste composition, management strategy, geography, and climate zone. The diversity and composition of bacterial and archaeal populations in leachate samples were characterized by 16S rRNA gene sequence analysis, and compared against a variety of physical and chemical parameters in an attempt to identify their impact on selection. Members of the Epsilonproteobacteria, Gammaproteobacteria, Clostridia, and candidate division OP3 were the most abundant. The distribution of the observed phylogenetic diversity could best be explained by a combination of variables and was correlated most strongly with the concentrations of chloride and barium, rate of evapotranspiration, age of waste, and the number of detected household chemicals. This study illustrates how leachate microbiomes are distinct from those of other natural or built environments, and sheds light on the major selective forces responsible for this microbial diversity.

  6. Two distinct neural mechanisms underlying indirect reciprocity.

    Science.gov (United States)

    Watanabe, Takamitsu; Takezawa, Masanori; Nakawake, Yo; Kunimatsu, Akira; Yamasue, Hidenori; Nakamura, Mitsuhiro; Miyashita, Yasushi; Masuda, Naoki

    2014-03-18

    Cooperation is a hallmark of human society. Humans often cooperate with strangers even if they will not meet each other again. This so-called indirect reciprocity enables large-scale cooperation among nonkin and can occur based on a reputation mechanism or as a succession of pay-it-forward behavior. Here, we provide the functional and anatomical neural evidence for two distinct mechanisms governing the two types of indirect reciprocity. Cooperation occurring as reputation-based reciprocity specifically recruited the precuneus, a region associated with self-centered cognition. During such cooperative behavior, the precuneus was functionally connected with the caudate, a region linking rewards to behavior. Furthermore, the precuneus of a cooperative subject had a strong resting-state functional connectivity (rsFC) with the caudate and a large gray matter volume. In contrast, pay-it-forward reciprocity recruited the anterior insula (AI), a brain region associated with affective empathy. The AI was functionally connected with the caudate during cooperation occurring as pay-it-forward reciprocity, and its gray matter volume and rsFC with the caudate predicted the tendency of such cooperation. The revealed difference is consistent with the existing results of evolutionary game theory: although reputation-based indirect reciprocity robustly evolves as a self-interested behavior in theory, pay-it-forward indirect reciprocity does not on its own. The present study provides neural mechanisms underlying indirect reciprocity and suggests that pay-it-forward reciprocity may not occur as myopic profit maximization but elicit emotional rewards.

  7. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lijuan Duan

    2017-01-01

    Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

  8. Two distinct origins for Archean greenstone belts

    Science.gov (United States)

    Smithies, R. Hugh; Ivanic, Tim J.; Lowrey, Jack R.; Morris, Paul A.; Barnes, Stephen J.; Wyche, Stephen; Lu, Yong-Jun

    2018-04-01

    Applying the Th/Yb-Nb/Yb plot of Pearce (2008) to the well-studied Archean greenstone sequences of Western Australia shows that individual volcanic sequences evolved through one of two distinct processes reflecting different modes of crust-mantle interaction. In the Yilgarn Craton, the volcanic stratigraphy of the 2.99-2.71 Ga Youanmi Terrane mainly evolved through processes leading to Th/Yb-Nb/Yb trends with a narrow range of Th/Nb ('constant-Th/Nb' greenstones). In contrast, the 2.71-2.66 Ga volcanic stratigraphy of the Eastern Goldfields Superterrane evolved through processes leading to Th/Yb-Nb/Yb trends showing a continuous range in Th/Nb ('variable-Th/Nb' greenstones). Greenstone sequences of the Pilbara Craton show a similar evolution, with constant-Th/Nb greenstone evolution between 3.13 and 2.95 Ga and variable-Th/Nb greenstone evolution between 3.49 and 3.23 Ga and between 2.77 and 2.68 Ga. The variable-Th/Nb trends dominate greenstone sequences in Australia and worldwide, and are temporally associated with peaks in granite magmatism, which promoted crustal preservation. The increasing Th/Nb in basalts correlates with decreasing εNd, reflecting variable amounts of crustal assimilation during emplacement of mantle-derived magmas. These greenstones are typically accompanied in the early stages by komatiite, and can probably be linked to mantle plume activity. Thus, regions such as the Eastern Goldfields Superterrane simply developed as plume-related rifts over existing granite-greenstone crust - in this case the Youanmi Terrane. Their Th/Nb trends are difficult to reconcile with modern-style subduction processes. The constant-Th/Nb trends may reflect derivation from a mantle source already with a high and constant Th/Nb ratio. This, and a lithological association including boninite-like lavas, basalts, and calc-alkaline andesites, all within a narrow Th/Nb range, resembles compositions typical of modern-style subduction settings. These greenstones are very

  9. Deep remission: a new concept?

    Science.gov (United States)

    Colombel, Jean-Frédéric; Louis, Edouard; Peyrin-Biroulet, Laurent; Sandborn, William J; Panaccione, Remo

    2012-01-01

    Crohn's disease (CD) is a chronic inflammatory disorder characterized by periods of clinical remission alternating with periods of relapse defined by recurrent clinical symptoms. Persistent inflammation is believed to lead to progressive bowel damage over time, which manifests with the development of strictures, fistulae and abscesses. These disease complications frequently lead to a need for surgical resection, which in turn leads to disability. So CD can be characterized as a chronic, progressive, destructive and disabling disease. In rheumatoid arthritis, treatment paradigms have evolved beyond partial symptom control alone toward the induction and maintenance of sustained biological remission, also known as a 'treat to target' strategy, with the goal of improving long-term disease outcomes. In CD, there is currently no accepted, well-defined, comprehensive treatment goal that entails the treatment of both clinical symptoms and biologic inflammation. It is important that such a treatment concept begins to evolve for CD. A treatment strategy that delays or halts the progression of CD to increasing damage and disability is a priority. As a starting point, a working definition of sustained deep remission (that includes long-term biological remission and symptom control) with defined patient outcomes (including no disease progression) has been proposed. The concept of sustained deep remission represents a goal for CD management that may still evolve. It is not clear if the concept also applies to ulcerative colitis. Clinical trials are needed to evaluate whether treatment algorithms that tailor therapy to achieve deep remission in patients with CD can prevent disease progression and disability. Copyright © 2012 S. Karger AG, Basel.

  10. Topics in deep inelastic scattering

    International Nuclear Information System (INIS)

    Wandzura, S.M.

    1977-01-01

    Several topics in deep inelastic lepton--nucleon scattering are discussed, with emphasis on the structure functions appearing in polarized experiments. The major results are: infinite set of new sum rules reducing the number of independent spin dependent structure functions (for electroproduction) from two to one; the application of the techniques of Nachtmann to extract the coefficients appearing in the Wilson operator product expansion; and radiative corrections to the Wilson coefficients of free field theory. Also discussed are the use of dimensional regularization to simplify the calculation of these radiative corrections

  11. Getting Inside Knowledge: The Application of Entwistle's Model of Surface/Deep Processing in Producing Open Learning Materials.

    Science.gov (United States)

    Evans, Barbara; Honour, Leslie

    1997-01-01

    Reports on a study that required student teachers training in business education to produce open learning materials on intercultural communication. Analysis of stages and responses to this assignment revealed a distinction between "deep" and "surface" learning. Includes charts delineating the characteristics of these two types…

  12. 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

  13. Deep ocean model penetrator experiments

    International Nuclear Information System (INIS)

    Freeman, T.J.; Burdett, J.R.F.

    1986-01-01

    Preliminary trials of experimental model penetrators in the deep ocean have been conducted as an international collaborative exercise by participating members (national bodies and the CEC) of the Engineering Studies Task Group of the Nuclear Energy Agency's Seabed Working Group. This report describes and gives the results of these experiments, which were conducted at two deep ocean study areas in the Atlantic: Great Meteor East and the Nares Abyssal Plain. Velocity profiles of penetrators of differing dimensions and weights have been determined as they free-fell through the water column and impacted the sediment. These velocity profiles are used to determine the final embedment depth of the penetrators and the resistance to penetration offered by the sediment. The results are compared with predictions of embedment depth derived from elementary models of a penetrator impacting with a sediment. It is tentatively concluded that once the resistance to penetration offered by a sediment at a particular site has been determined, this quantity can be used to sucessfully predict the embedment that penetrators of differing sizes and weights would achieve at the same site

  14. Academic Training: Deep Space Telescopes

    CERN Multimedia

    Françoise Benz

    2006-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 20, 21, 22, 23, 24 February from 11:00 to 12:00 - Council Chamber on 20, 21, 23, 24 February, TH Auditorium, bldg 4 - 3-006, on 22 February Deep Space Telescopes G. BIGNAMI / CNRS, Toulouse, F & Univ. di Pavia, I The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo's telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics thro...

  15. Effect of Deep Brain Stimulation on Speech Performance in Parkinson's Disease

    OpenAIRE

    Skodda, Sabine

    2012-01-01

    Deep brain stimulation (DBS) has been reported to be successful in relieving the core motor symptoms of Parkinson's disease (PD) and motor fluctuations in the more advanced stages of the disease. However, data on the effects of DBS on speech performance are inconsistent. While there are some series of patients documenting that speech function was relatively unaffected by DBS of the nucleus subthalamicus (STN), other investigators reported on improvements of distinct parameters of oral control...

  16. Prediction and control of rock burst of coal seam contacting gas in deep mining

    Energy Technology Data Exchange (ETDEWEB)

    En-yuan Wang; Xiao-fei Liu; En-lai Zhao; Zhen-tang Liu [China University of Mining and Technology, Xuzhou (China). School of Safety Engineering

    2009-06-15

    By analyzing the characteristics and the production mechanism of rock burst that goes with abnormal gas emission in deep coal seams, the essential method of eliminating abnormal gas emission by eliminating the occurrence of rock burst or depressing the magnitude of rock burst was considered. The No.237 working face in Nanshan coal mine was selected as the typical working face contacting gas in deep mining; aimed at this working face, a system of rock burst prediction and control for coal seam contacting gas in deep mining was established using the three-dimensional distinct element code software 3DEC. This system includes three parts: (1) regional prediction of rock burst hazard before mining; (2) local prediction of rock burst hazard during mining; and (3) rock burts control by an electromagnetic radiation method and specific drilling method. 8 refs., 4 figs., 1 tab.

  17. Distinguishing bulk traps and interface states in deep-level transient spectroscopy

    International Nuclear Information System (INIS)

    Coelho, A V P; Adam, M C; Boudinov, H

    2011-01-01

    A new method for the distinction of discrete bulk deep levels and interface states related peaks in deep-level transient spectroscopy spectra is proposed. The measurement of two spectra using different reverse voltages while keeping pulse voltage fixed causes different peak maximum shifts in each case: for a reverse voltage modulus increase, a bulk deep-level related peak maximum will remain unchanged or shift towards lower temperatures while only interface states related peak maximum will be able to shift towards higher temperatures. This method has the advantage of being non-destructive and also works in the case of bulk traps with strong emission rate dependence on the electric field. Silicon MOS capacitors and proton implanted GaAs Schottky diodes were employed to experimentally test the method.

  18. NSAID gastropathy and enteropathy: distinct pathogenesis likely necessitates distinct prevention strategies.

    Science.gov (United States)

    Wallace, John L

    2012-01-01

    The mechanisms underlying the ability of nonsteroidal anti-inflammatory drugs (NSAIDs) to cause ulceration in the stomach and proximal duodenum are well understood, and this injury can largely be prevented through suppression of gastric acid secretion (mainly with proton pump inhibitors). In contrast, the pathogenesis of small intestinal injury induced by NSAIDs is less well understood, involving more complex mechanisms than those in the stomach and proximal duodenum. There is clear evidence for important contributions to NSAID enteropathy of enteric bacteria, bile and enterohepatic recirculation of the NSAID. There is no evidence that suppression of gastric acid secretion will reduce the incidence or severity of NSAID enteropathy. Indeed, clinical data suggest little, if any, benefit. Animal studies suggest a significant exacerbation of NSAID enteropathy when proton pump inhibitors are co-administered with the NSAID. This worsening of damage appears to be linked to changes in the number and types of bacteria in the small intestine during proton pump inhibitor therapy. The distinct mechanisms of NSAID-induced injury in the stomach/proximal duodenum versus the more distal small intestine likely dictate distinct strategies for prevention. © 2011 The Author. British Journal of Pharmacology © 2011 The British Pharmacological Society.

  19. Image Captioning with Deep Bidirectional LSTMs

    OpenAIRE

    Wang, Cheng; Yang, Haojin; Bartz, Christian; Meinel, Christoph

    2016-01-01

    This work presents an end-to-end trainable deep bidirectional LSTM (Long-Short Term Memory) model for image captioning. Our model builds on a deep convolutional neural network (CNN) and two separate LSTM networks. It is capable of learning long term visual-language interactions by making use of history and future context information at high level semantic space. Two novel deep bidirectional variant models, in which we increase the depth of nonlinearity transition in different way, are propose...

  20. Deep inelastic processes and the parton model

    International Nuclear Information System (INIS)

    Altarelli, G.

    The lecture was intended as an elementary introduction to the physics of deep inelastic phenomena from the point of view of theory. General formulae and facts concerning inclusive deep inelastic processes in the form: l+N→l'+hadrons (electroproduction, neutrino scattering) are first recalled. The deep inelastic annihilation e + e - →hadrons is then envisaged. The light cone approach, the parton model and their relation are mainly emphasized

  1. Deep inelastic electron and muon scattering

    International Nuclear Information System (INIS)

    Taylor, R.E.

    1975-07-01

    From the review of deep inelastic electron and muon scattering it is concluded that the puzzle of deep inelastic scattering versus annihilation was replaced with the challenge of the new particles, that the evidence for the simplest quark-algebra models of deep inelastic processes is weaker than a year ago. Definite evidence of scale breaking was found but the specific form of that scale breaking is difficult to extract from the data. 59 references

  2. Fast, Distributed Algorithms in Deep Networks

    Science.gov (United States)

    2016-05-11

    shallow networks, additional work will need to be done in order to allow for the application of ADMM to deep nets. The ADMM method allows for quick...Quock V Le, et al. Large scale distributed deep networks. In Advances in Neural Information Processing Systems, pages 1223–1231, 2012. [11] Ken-Ichi...A TRIDENT SCHOLAR PROJECT REPORT NO. 446 Fast, Distributed Algorithms in Deep Networks by Midshipman 1/C Ryan J. Burmeister, USN

  3. 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...

  4. Creating fair lineups for suspects with distinctive features

    OpenAIRE

    Zarkadi, Theodora; Wade, Kimberley A.; Stewart, Neil

    2009-01-01

    In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineup...

  5. An overview of latest deep water technologies

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    The 8th Deep Offshore Technology Conference (DOT VIII, Rio de Janeiro, October 30 - November 3, 1995) has brought together renowned specialists in deep water development projects, as well as managers from oil companies and engineering/service companies to discuss state-of-the-art technologies and ongoing projects in the deep offshore. This paper is a compilation of the session summaries about sub sea technologies, mooring and dynamic positioning, floaters (Tension Leg Platforms (TLP) and Floating Production Storage and Off loading (FPSO)), pipelines and risers, exploration and drilling, and other deep water techniques. (J.S.)

  6. Deep learning in neural networks: an overview.

    Science.gov (United States)

    Schmidhuber, Jürgen

    2015-01-01

    In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

  7. The deep ocean under climate change

    Science.gov (United States)

    Levin, Lisa A.; Le Bris, Nadine

    2015-11-01

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

  8. Docker Containers for Deep Learning Experiments

    OpenAIRE

    Gerke, Paul K.

    2017-01-01

    Deep learning is a powerful tool to solve problems in the area of image analysis. The dominant compute platform for deep learning is Nvidia’s proprietary CUDA, which can only be used together with Nvidia graphics cards. The nivida-docker project allows exposing Nvidia graphics cards to docker containers and thus makes it possible to run deep learning experiments in docker containers.In our department, we use deep learning to solve problems in the area of medical image analysis and use docker ...

  9. Deep Brain Stimulation for Parkinson's Disease

    Science.gov (United States)

    ... about the BRAIN initiative, see www.nih.gov/science/brain . Show More Show Less Search Disorders SEARCH SEARCH Definition Treatment Prognosis Clinical Trials Organizations Publications Definition Deep ...

  10. Cultivating the Deep Subsurface Microbiome

    Science.gov (United States)

    Casar, C. P.; Osburn, M. R.; Flynn, T. M.; Masterson, A.; Kruger, B.

    2017-12-01

    Subterranean ecosystems are poorly understood because many microbes detected in metagenomic surveys are only distantly related to characterized isolates. Cultivating microorganisms from the deep subsurface is challenging due to its inaccessibility and potential for contamination. The Deep Mine Microbial Observatory (DeMMO) in Lead, SD however, offers access to deep microbial life via pristine fracture fluids in bedrock to a depth of 1478 m. The metabolic landscape of DeMMO was previously characterized via thermodynamic modeling coupled with genomic data, illustrating the potential for microbial inhabitants of DeMMO to utilize mineral substrates as energy sources. Here, we employ field and lab based cultivation approaches with pure minerals to link phylogeny to metabolism at DeMMO. Fracture fluids were directed through reactors filled with Fe3O4, Fe2O3, FeS2, MnO2, and FeCO3 at two sites (610 m and 1478 m) for 2 months prior to harvesting for subsequent analyses. We examined mineralogical, geochemical, and microbiological composition of the reactors via DNA sequencing, microscopy, lipid biomarker characterization, and bulk C and N isotope ratios to determine the influence of mineralogy on biofilm community development. Pre-characterized mineral chips were imaged via SEM to assay microbial growth; preliminary results suggest MnO2, Fe3O4, and Fe2O3 were most conducive to colonization. Solid materials from reactors were used as inoculum for batch cultivation experiments. Media designed to mimic fracture fluid chemistry was supplemented with mineral substrates targeting metal reducers. DNA sequences and microscopy of iron oxide-rich biofilms and fracture fluids suggest iron oxidation is a major energy source at redox transition zones where anaerobic fluids meet more oxidizing conditions. We utilized these biofilms and fluids as inoculum in gradient cultivation experiments targeting microaerophilic iron oxidizers. Cultivation of microbes endemic to DeMMO, a system

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

    KAUST Repository

    Yum, Lauren

    2017-07-19

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

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

    Science.gov (United States)

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

    2017-07-25

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

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

    KAUST Repository

    Yum, Lauren; Baumgarten, Sebastian; Rö thig, Till; Roder, Cornelia; Roik, Anna Krystyna; Michell, Craig; Voolstra, Christian R.

    2017-01-01

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

  14. The Skin Bacterium Propionibacterium acnes Employs Two Variants of Hyaluronate Lyase with Distinct Properties

    DEFF Research Database (Denmark)

    Nazipi, Seven; Stødkilde-Jørgensen, Kristian; Scavenius, Carsten

    2017-01-01

    Hyaluronic acid (HA) and other glycosaminoglycans are extracellular matrix components in the human epidermis and dermis. One of the most prevalent skin microorganisms, Propionibacterium acnes, possesses HA-degrading activity, possibly conferred by the enzyme hyaluronate lyase (HYL). In this study......, we identified the HYL of P. acnes and investigated the genotypic and phenotypic characteristics. Investigations include the generation of a P. acneshyl knockout mutant and HYL activity assays to determine the substrate range and formed products. We found that P. acnes employs two distinct variants...... of the observed differences between P. acnes phylotype IA and IB/II strains. Whereas type IA strains are primarily found on the skin surface and associated with acne vulgaris, type IB/II strains are more often associated with soft and deep tissue infections, which would require elaborate tissue invasion...

  15. The Distinct Character of a Capital? From Formality to Regularity of Our Ancient Capitals

    Science.gov (United States)

    Kelly, T.

    2018-04-01

    Many cities were shaped by dynamics political and commercial factors and man-made layers whereas other capitals have been modeled spontaneously by natural influence, London is great sample of this approach and was described as a natural city planned over decades by many hands with great appreciation to natural terrain. Contrary mode is obvious in China where several factors behind the distinct identity of Chinese architecture and urban planning. Among those influences are the Metaphysics Philosophies or Emperor guidance who encouraged uniformity in many aspects in China including city planning. The aim of this paper is to highlight the impact of various forces and mankind dogmas in shaping up a unique character of famous capitals. Hence London and Beijing are the two contradictory case studies subject to deep analysis in parallel with other theories such as Yin - Yan and Fengs Shui principles, to examine their impacts on urban planning in China.

  16. Precision of Discrete and Rhythmic Forelimb Movements Requires a Distinct Neuronal Subpopulation in the Interposed Anterior Nucleus

    Directory of Open Access Journals (Sweden)

    Aloysius Y.T. Low

    2018-02-01

    Full Text Available The deep cerebellar nuclei (DCN represent output channels of the cerebellum, and they transmit integrated sensorimotor signals to modulate limb movements. But the functional relevance of identifiable neuronal subpopulations within the DCN remains unclear. Here, we examine a genetically tractable population of neurons in the mouse interposed anterior nucleus (IntA. We show that these neurons represent a subset of glutamatergic neurons in the IntA and constitute a specific element of an internal feedback circuit within the cerebellar cortex and cerebello-thalamo-cortical pathway associated with limb control. Ablation and optogenetic stimulation of these neurons disrupt efficacy of skilled reach and locomotor movement and reveal that they control positioning and timing of the forelimb and hindlimb. Together, our findings uncover the function of a distinct neuronal subpopulation in the deep cerebellum and delineate the anatomical substrates and kinematic parameters through which it modulates precision of discrete and rhythmic limb movements.

  17. Deep inelastic scattering and disquarks

    International Nuclear Information System (INIS)

    Anselmino, M.

    1993-01-01

    The most comprehensive and detailed analyses of the existing data on the structure function F 2 (x, Q 2 ) of free nucleons, from the deep inelastic scattering (DIS) of charged leptons on hydrogen and deuterium targets, have proved beyond any doubt that higher twist, 1/Q 2 corrections are needed in order to obtain a perfect agreement between perturbative QCD predictions and the data. These higher twist corrections take into account two quark correlations inside the nucleon; it is then natural to try to model them in the quark-diquark model of the proton. In so doing all interactions between the two quarks inside the diquark, both perturbative and non perturbative, are supposed to be taken into account. (orig./HSI)

  18. Detector for deep well logging

    International Nuclear Information System (INIS)

    1976-01-01

    A substantial improvement in the useful life and efficiency of a deep-well scintillation detector is achieved by a unique construction wherein the steel cylinder enclosing the sodium iodide scintillation crystal is provided with a tapered recess to receive a glass window which has a high transmittance at the critical wavelength and, for glass, a high coefficient of thermal expansion. A special high-temperature epoxy adhesive composition is employed to form a relatively thick sealing annulus which keeps the glass window in the tapered recess and compensates for the differences in coefficients of expansion between the container and glass so as to maintain a hermetic seal as the unit is subjected to a wide range of temperature

  19. Deep borehole disposal of plutonium

    International Nuclear Information System (INIS)

    Gibb, F. G. F.; Taylor, K. J.; Burakov, B. E.

    2008-01-01

    Excess plutonium not destined for burning as MOX or in Generation IV reactors is both a long-term waste management problem and a security threat. Immobilisation in mineral and ceramic-based waste forms for interim safe storage and eventual disposal is a widely proposed first step. The safest and most secure form of geological disposal for Pu yet suggested is in very deep boreholes and we propose here that the key to successful combination of these immobilisation and disposal concepts is the encapsulation of the waste form in small cylinders of recrystallized granite. The underlying science is discussed and the results of high pressure and temperature experiments on zircon, depleted UO 2 and Ce-doped cubic zirconia enclosed in granitic melts are presented. The outcomes of these experiments demonstrate the viability of the proposed solution and that Pu could be successfully isolated from its environment for many millions of years. (authors)

  20. Automatic Differentiation and Deep Learning

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Statistical learning has been getting more and more interest from the particle-physics community in recent times, with neural networks and gradient-based optimization being a focus. In this talk we shall discuss three things: automatic differention tools: tools to quickly build DAGs of computation that are fully differentiable. We shall focus on one such tool "PyTorch".  Easy deployment of trained neural networks into large systems with many constraints: for example, deploying a model at the reconstruction phase where the neural network has to be integrated into CERN's bulk data-processing C++-only environment Some recent models in deep learning for segmentation and generation that might be useful for particle physics problems.

  1. Jets in deep inelastic scattering

    International Nuclear Information System (INIS)

    Joensson, L.

    1995-01-01

    Jet production in deep inelastic scattering provides a basis for the investigation of various phenomena related to QCD. Two-jet production at large Q 2 has been studied and the distributions with respect to the partonic scaling variables have been compared to models and to next to leading order calculations. The first observations of azimuthal asymmetries of jets produced in first order α s processes have been obtained. The gluon initiated boson-gluon fusion process permits a direct determination of the gluon density of the proton from an analysis of the jets produced in the hard scattering process. A comparison of these results with those from indirect extractions of the gluon density provides an important test of QCD. (author)

  2. NESTOR Deep Sea Neutrino Telescope

    International Nuclear Information System (INIS)

    Aggouras, G.; Anassontzis, E.G.; Ball, A.E.; Bourlis, G.; Chinowsky, W.; Fahrun, E.; Grammatikakis, G.; Green, C.; Grieder, P.; Katrivanos, P.; Koske, P.; Leisos, A.; Markopoulos, E.; Minkowsky, P.; Nygren, D.; Papageorgiou, K.; Przybylski, G.; Resvanis, L.K.; Siotis, I.; Sopher, J.; Staveris-Polikalas, A.; Tsagli, V.; Tsirigotis, A.; Tzamarias, S.; Zhukov, V.A.

    2006-01-01

    One module of NESTOR, the Mediterranean deep-sea neutrino telescope, was deployed at a depth of 4000m, 14km off the Sapienza Island, off the South West coast of Greece. The deployment site provides excellent environmental characteristics. The deployed NESTOR module is constructed as a hexagonal star like latticed titanium star with 12 Optical Modules and an one-meter diameter titanium sphere which houses the electronics. Power and data were transferred through a 30km electro-optical cable to the shore laboratory. In this report we describe briefly the detector and the detector electronics and discuss the first physics data acquired and give the zenith angular distribution of the reconstructed muons

  3. Deep Borehole Disposal Safety Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Freeze, Geoffrey A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Stein, Emily [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Price, Laura L. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Tillman, Jack Bruce [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    This report presents a preliminary safety analysis for the deep borehole disposal (DBD) concept, using a safety case framework. A safety case is an integrated collection of qualitative and quantitative arguments, evidence, and analyses that substantiate the safety, and the level of confidence in the safety, of a geologic repository. This safety case framework for DBD follows the outline of the elements of a safety case, and identifies the types of information that will be required to satisfy these elements. At this very preliminary phase of development, the DBD safety case focuses on the generic feasibility of the DBD concept. It is based on potential system designs, waste forms, engineering, and geologic conditions; however, no specific site or regulatory framework exists. It will progress to a site-specific safety case as the DBD concept advances into a site-specific phase, progressing through consent-based site selection and site investigation and characterization.

  4. DeepRT: deep learning for peptide retention time prediction in proteomics

    OpenAIRE

    Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

    2017-01-01

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

  5. Handwritten recognition of Tamil vowels using deep learning

    Science.gov (United States)

    Ram Prashanth, N.; Siddarth, B.; Ganesh, Anirudh; Naveen Kumar, Vaegae

    2017-11-01

    We come across a large volume of handwritten texts in our daily lives and handwritten character recognition has long been an important area of research in pattern recognition. The complexity of the task varies among different languages and it so happens largely due to the similarity between characters, distinct shapes and number of characters which are all language-specific properties. There have been numerous works on character recognition of English alphabets and with laudable success, but regional languages have not been dealt with very frequently and with similar accuracies. In this paper, we explored the performance of Deep Belief Networks in the classification of Handwritten Tamil vowels, and conclusively compared the results obtained. The proposed method has shown satisfactory recognition accuracy in light of difficulties faced with regional languages such as similarity between characters and minute nuances that differentiate them. We can further extend this to all the Tamil characters.

  6. State of the Art: Novel Applications for Deep Brain Stimulation.

    Science.gov (United States)

    Roy, Holly A; Green, Alexander L; Aziz, Tipu Z

    2018-02-01

    Deep brain stimulation (DBS) is a rapidly developing field of neurosurgery with potential therapeutic applications that are relevant to conditions traditionally viewed as beyond the limits of neurosurgery. Our objective, in this review, is to highlight some of the emerging applications of DBS within three distinct but overlapping spheres, namely trauma, neuropsychiatry, and autonomic physiology. An extensive literature review was carried out in MEDLINE, to identify relevant studies and review articles describing applications of DBS in the areas of trauma, neuropsychiatry and autonomic neuroscience. A wide range of applications of DBS in these spheres was identified, some having only been tested in one or two cases, others much better studied. We have identified various avenues for DBS to be applied for patient benefit in cases relevant to trauma, neuropsychiatry and autonomic neuroscience. Further developments in DBS technology and clinical trial design will enable these novel applications to be effectively and rigorously assessed and utilized most effectively. © 2017 International Neuromodulation Society.

  7. Identity-specific motivation: How distinct identities direct self-regulation across distinct situations.

    Science.gov (United States)

    Browman, Alexander S; Destin, Mesmin; Molden, Daniel C

    2017-12-01

    Research on self-regulation has traditionally emphasized that people's thoughts and actions are guided by either (a) domain-general motivations that emerge from a cumulative history of life experiences, or (b) situation-specific motivations that emerge in immediate response to the incentives present in a particular context. However, more recent studies have illustrated the importance of understanding the interplay between such domain-general and situation-specific motivations across the types of contexts people regularly encounter. The present research, therefore, expands existing perspectives on self-regulation by investigating how people's identities -the internalized roles, relationships, and social group memberships that define who they are-systemically guide when and how different domain-general motivations are activated within specific types of situations. Using the motivational framework described by regulatory focus theory (Higgins, 1997), Studies 1 and 2 demonstrate that people indeed have distinct, identity-specific motivations that uniquely influence their current self-regulation when such identities are active. Studies 3-5 then begin to explore how identity-specific motivations are situated within people's larger self-concept. Studies 3a and 3b demonstrate that the less compatible people's specific identities, the more distinct are the motivations connected to those identities. Studies 4-5 then provide some initial, suggestive evidence that identity-specific motivations are not a separate, superordinate feature of people's identities that then alter how they pursue any subordinate, identity-relevant traits, but instead that such motivations emerge from the cumulative motivational significance of the subordinate traits to which the identities themselves become attached. Implications for understanding the role of the self-concept in self-regulation are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Distinctiveness of Encoding and Memory for Learning Tasks.

    Science.gov (United States)

    Glover, John A.; And Others

    1982-01-01

    A distinctiveness of encoding hypothesis, as applied to the facilitative effects that higher order objectives have on readers' prose recall, was evaluated in three experiments. Results suggest that distinctiveness of encoding may offer a theoretical basis for the effects of adjunct aids as well as a guide to their construction. (Author/GK)

  9. Equivalent drawbead performance in deep drawing simulations

    NARCIS (Netherlands)

    Meinders, Vincent T.; Geijselaers, Hubertus J.M.; Huetink, Han

    1999-01-01

    Drawbeads are applied in the deep drawing process to improve the control of the material flow during the forming operation. In simulations of the deep drawing process these drawbeads can be replaced by an equivalent drawbead model. In this paper the usage of an equivalent drawbead model in the

  10. Is deep dreaming the new collage?

    Science.gov (United States)

    Boden, Margaret A.

    2017-10-01

    Deep dreaming (DD) can combine and transform images in surprising ways. But, being based in deep learning (DL), it is not analytically understood. Collage is an art form that is constrained along various dimensions. DD will not be able to generate collages until DL can be guided in a disciplined fashion.

  11. Deep web search: an overview and roadmap

    NARCIS (Netherlands)

    Tjin-Kam-Jet, Kien; Trieschnigg, Rudolf Berend; Hiemstra, Djoerd

    2011-01-01

    We review the state-of-the-art in deep web search and propose a novel classification scheme to better compare deep web search systems. The current binary classification (surfacing versus virtual integration) hides a number of implicit decisions that must be made by a developer. We make these

  12. 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

  13. Development of Hydro-Mechanical Deep Drawing

    DEFF Research Database (Denmark)

    Zhang, Shi-Hong; Danckert, Joachim

    1998-01-01

    The hydro-mechanical deep-drawing process is reviewed in this article. The process principles and features are introduced and the developments of the hydro-mechanical deep-drawing process in process performances, in theory and in numerical simulation are described. The applications are summarized....... Some other related hydraulic forming processes are also dealt with as a comparison....

  14. Stable architectures for deep neural networks

    Science.gov (United States)

    Haber, Eldad; Ruthotto, Lars

    2018-01-01

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

  15. Temperature impacts on deep-sea biodiversity.

    Science.gov (United States)

    Yasuhara, Moriaki; Danovaro, Roberto

    2016-05-01

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

  16. Deep-Earth Equilibration between Molten Iron and Solid Silicates

    Science.gov (United States)

    Brennan, M.; Zurkowski, C. C.; Chidester, B.; Campbell, A.

    2017-12-01

    Elemental partitioning between iron-rich metals and silicate minerals influences the properties of Earth's deep interior, and is ultimately responsible for the nature of the core-mantle boundary. These interactions between molten iron and solid silicates were influential during planetary accretion, and persist today between the mantle and liquid outer core. Here we report the results of diamond anvil cell experiments at lower mantle conditions (40 GPa, >2500 K) aimed at examining systems containing a mixture of metals (iron or Fe-16Si alloy) and silicates (peridotite). The experiments were conducted at pressure-temperature conditions above the metallic liquidus but below the silicate solidus, and the recovered samples were analyzed by FIB/SEM with EDS to record the compositions of the coexisting phases. Each sample formed a three-phase equilibrium between bridgmanite, Fe-rich metallic melt, and an oxide. In one experiment, using pure Fe, the quenched metal contained 6 weight percent O, and the coexisting oxide was ferropericlase. The second experiment, using Fe-Si alloy, was highly reducing; its metal contained 10 wt% Si, and the coexisting mineral was stishovite. The distinct mineralogies of the two experiments derived from their different starting metals. These results imply that metallic composition is an important factor in determining the products of mixed phase iron-silicate reactions. The properties of deep-Earth interfaces such as the core-mantle boundary could be strongly affected by their metallic components.

  17. Shallow and Deep Groundwater Contributions to Ephemeral Streamflow Generation

    Science.gov (United States)

    Zimmer, M. A.; McGlynn, B. L.

    2016-12-01

    Our understanding of streamflow generation processes in low relief, humid landscapes is limited. To address this, we utilized an ephemeral-to-intermittent drainage network in the Piedmont region of the United States to gain new understanding about the drivers of ephemeral streamflow generation, stream-groundwater interactions, and longitudinal expansion and contraction of the stream network. We used hydrometric and chemical data collected within zero through second order catchments to characterize streamflow and overland, shallow soil, and deep subsurface flow across landscape positions. Results showed bi-directionality in stream-groundwater gradients that were dependent on catchment storage state. This led to annual groundwater recharge magnitudes that were similar to annual streamflow. Perched shallow and deep water table contributions shifted dominance with changes in catchment storage state, producing distinct stream hydrograph recession constants. Active channel length versus runoff followed a consistent relationship independent of storage state, but exhibited varying discharge-solute hysteresis directions. Together, our results suggest that temporary streams can act as both important groundwater recharge and discharge locations across the landscape, especially in this region where ephemeral drainage densities are among the highest recorded. Our results also highlight that the internal catchment dynamics that generate temporary streams play an important role in dictating biogeochemical fluxes at the landscape scale.

  18. Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status.

    Science.gov (United States)

    Korfiatis, Panagiotis; Kline, Timothy L; Lachance, Daniel H; Parney, Ian F; Buckner, Jan C; Erickson, Bradley J

    2017-10-01

    Predicting methylation of the O6-methylguanine methyltransferase (MGMT) gene status utilizing MRI imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare three different residual deep neural network (ResNet) architectures to evaluate their ability in predicting MGMT methylation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture was the best performing model, achieving an accuracy of 94.90% (+/- 3.92%) for the test set (classification of a slice as no tumor, methylated MGMT, or non-methylated). ResNet34 (34 layers) achieved 80.72% (+/- 13.61%) while ResNet18 (18 layers) accuracy was 76.75% (+/- 20.67%). ResNet50 performance was statistically significantly better than both ResNet18 and ResNet34 architectures (p deep neural architectures can be used to predict molecular biomarkers from routine medical images.

  19. 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.

  20. Photobiology of the deep twilight zone and beyond

    Science.gov (United States)

    Waterman, Talbot H.

    1997-02-01

    Photobiology in the twilight zone of the deep sea depends on faint light of two, or possibly three, origins: sunlight, bioluminescence and some visible radiation near the bottom associated with hydrothermal vents. The deep twilight zone also contains two quite distinct ecosystems: the vast open ocean pelagic regime far from the shore and the bottom as well as the far less expansive benthic regime with quite different characteristic animals that live on, in or near the sea bo10 Most of the whole ocean's benthic regime with a mean depth over 3000m is well below the twilight zone, which eliminates sunlight as a light source there. Many of the most familiar deepsea animals with their spectacular arrays of dennal light organs and remarkable eyes are from the pelagic 19, 25 The less familiar benthic fishes and crustaceans sometimes have curious internal light organs powered by bacteria13 and occasional incredibly modified eyes.30 With the exception of those on the fishing rods of most female deepsea anglerfish, where the light is produced by symbiotic bacteria, all the numerous light organs of pelagic deepsea fishes are generally believed to manage their own chemiluminescence independent of luminous bacteria.17

  1. Hidden cycle of dissolved organic carbon in the deep ocean.

    Science.gov (United States)

    Follett, Christopher L; Repeta, Daniel J; Rothman, Daniel H; Xu, Li; Santinelli, Chiara

    2014-11-25

    Marine dissolved organic carbon (DOC) is a large (660 Pg C) reactive carbon reservoir that mediates the oceanic microbial food web and interacts with climate on both short and long timescales. Carbon isotopic content provides information on the DOC source via δ(13)C and age via Δ(14)C. Bulk isotope measurements suggest a microbially sourced DOC reservoir with two distinct components of differing radiocarbon age. However, such measurements cannot determine internal dynamics and fluxes. Here we analyze serial oxidation experiments to quantify the isotopic diversity of DOC at an oligotrophic site in the central Pacific Ocean. Our results show diversity in both stable and radio isotopes at all depths, confirming DOC cycling hidden within bulk analyses. We confirm the presence of isotopically enriched, modern DOC cocycling with an isotopically depleted older fraction in the upper ocean. However, our results show that up to 30% of the deep DOC reservoir is modern and supported by a 1 Pg/y carbon flux, which is 10 times higher than inferred from bulk isotope measurements. Isotopically depleted material turns over at an apparent time scale of 30,000 y, which is far slower than indicated by bulk isotope measurements. These results are consistent with global DOC measurements and explain both the fluctuations in deep DOC concentration and the anomalous radiocarbon values of DOC in the Southern Ocean. Collectively these results provide an unprecedented view of the ways in which DOC moves through the marine carbon cycle.

  2. Deep-sea Lebensspuren of the Australian continental margins

    Science.gov (United States)

    Przeslawski, Rachel; Dundas, Kate; Radke, Lynda; Anderson, Tara J.

    Much of the deep sea comprises soft-sediment habitats dominated by comparatively low abundances of species-rich macrofauna and meiofauna. Although often not observed, these animals bioturbate the sediment during feeding and burrowing, leaving signs of their activities called Lebensspuren ('life traces'). In this study, we use still images to quantify Lebensspuren from the eastern (1921 images, 13 stations, 1300-2200 m depth) and western (1008 images, 11 stations, 1500-4400 m depth) Australian margins using a univariate measure of trace richness and a multivariate measure of Lebensspuren assemblages. A total of 46 Lebensspuren types were identified, including those matching named trace fossils and modern Lebensspuren found elsewhere in the world. Most traces could be associated with waste, crawling, dwellings, organism tests, feeding, or resting, but the origin of 15% of trace types remains unknown. Assemblages were significantly different between the two regions and depth profiles, with five Lebensspuren types accounting for over 95% of the differentiation (ovoid pinnate trace, crater row, spider trace, matchstick trace, mesh trace). Lebensspuren richness showed no strong relationships with depth, total organic carbon, or mud, although there was a positive correlation to chlorin index (i.e., organic freshness) in the eastern margin, with richness increasing with organic freshness. Lebensspuren richness was not related to epifauna either, indicating that epifauna may not be the primary source of Lebensspuren. Despite the abundance and distinctiveness of several traces both in the current and previous studies (e.g., ovoid pinnate, mesh, spider), their origin and distribution remains a mystery. We discuss this and several other considerations in the identification and quantification of Lebensspuren. This study represents the first comprehensive catalogue of deep-sea Lebensspuren in Australian waters and highlights the potential of Lebensspuren as valuable and often

  3. A Novel Algorithm for the Generation of Distinct Kinematic Chain

    Science.gov (United States)

    Medapati, Sreenivasa Reddy; Kuchibhotla, Mallikarjuna Rao; Annambhotla, Balaji Srinivasa Rao

    2016-07-01

    Generation of distinct kinematic chains is an important topic in the design of mechanisms for various industrial applications i.e., robotic manipulator, tractor, crane etc. Many researchers have intently focused on this area and explained various processes of generating distinct kinematic chains which are laborious and complex. It is desirable to enumerate the kinematic chains systematically to know the inherent characteristics of a chain related to its structure so that all the distinct chains can be analyzed in depth, prior to the selection of a chain for a purpose. This paper proposes a novel and simple method with set of rules defined to eliminate isomorphic kinematic chains generating distinct kinematic chains. Also, this method simplifies the process of generating distinct kinematic chains even at higher levels i.e., 10-link, 11-link with single and multiple degree of freedom.

  4. Tagging like Humans: Diverse and Distinct Image Annotation

    KAUST Repository

    Wu, Baoyuan

    2018-03-31

    In this work we propose a new automatic image annotation model, dubbed {\\\\bf diverse and distinct image annotation} (D2IA). The generative model D2IA is inspired by the ensemble of human annotations, which create semantically relevant, yet distinct and diverse tags. In D2IA, we generate a relevant and distinct tag subset, in which the tags are relevant to the image contents and semantically distinct to each other, using sequential sampling from a determinantal point process (DPP) model. Multiple such tag subsets that cover diverse semantic aspects or diverse semantic levels of the image contents are generated by randomly perturbing the DPP sampling process. We leverage a generative adversarial network (GAN) model to train D2IA. Extensive experiments including quantitative and qualitative comparisons, as well as human subject studies, on two benchmark datasets demonstrate that the proposed model can produce more diverse and distinct tags than the state-of-the-arts.

  5. Towards deep learning with segregated dendrites.

    Science.gov (United States)

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

    2017-12-05

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

  6. Effects of hydrostatic pressure on yeasts isolated from deep-sea hydrothermal vents.

    Science.gov (United States)

    Burgaud, Gaëtan; Hué, Nguyen Thi Minh; Arzur, Danielle; Coton, Monika; Perrier-Cornet, Jean-Marie; Jebbar, Mohamed; Barbier, Georges

    2015-11-01

    Hydrostatic pressure plays a significant role in the distribution of life in the biosphere. Knowledge of deep-sea piezotolerant and (hyper)piezophilic bacteria and archaea diversity has been well documented, along with their specific adaptations to cope with high hydrostatic pressure (HHP). Recent investigations of deep-sea microbial community compositions have shown unexpected micro-eukaryotic communities, mainly dominated by fungi. Molecular methods such as next-generation sequencing have been used for SSU rRNA gene sequencing to reveal fungal taxa. Currently, a difficult but fascinating challenge for marine mycologists is to create deep-sea marine fungus culture collections and assess their ability to cope with pressure. Indeed, although there is no universal genetic marker for piezoresistance, physiological analyses provide concrete relevant data for estimating their adaptations and understanding the role of fungal communities in the abyss. The present study investigated morphological and physiological responses of fungi to HHP using a collection of deep-sea yeasts as a model. The aim was to determine whether deep-sea yeasts were able to tolerate different HHP and if they were metabolically active. Here we report an unexpected taxonomic-based dichotomic response to pressure with piezosensitve ascomycetes and piezotolerant basidiomycetes, and distinct morphological switches triggered by pressure for certain strains. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  7. Implicit and explicit processing in deep dyslexia: Semantic blocking as a test for failure of inhibition in the phonological output lexicon.

    Science.gov (United States)

    Colangelo, Annette; Buchanan, Lori

    2006-12-01

    The failure of inhibition hypothesis posits a theoretical distinction between implicit and explicit access in deep dyslexia. Specifically, the effects of failure of inhibition are assumed only in conditions that have an explicit selection requirement in the context of production (i.e., aloud reading). In contrast, the failure of inhibition hypothesis proposes that implicit processing and explicit access to semantic information without production demands are intact in deep dyslexia. Evidence for intact implicit and explicit access requires that performance in deep dyslexia parallels that observed in neurologically intact participants on tasks based on implicit and explicit processes. In other words, deep dyslexics should produce normal effects in conditions with implicit task demands (i.e., lexical decision) and on tasks based on explicit access without production (i.e., forced choice semantic decisions) because failure of inhibition does not impact the availability of lexical information, only explicit retrieval in the context of production. This research examined the distinction between implicit and explicit processes in deep dyslexia using semantic blocking in lexical decision and forced choice semantic decisions as a test for the failure of inhibition hypothesis. The results of the semantic blocking paradigm support the distinction between implicit and explicit processing and provide evidence for failure of inhibition as an explanation for semantic errors in deep dyslexia.

  8. 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.

  9. Deep learning classification in asteroseismology

    Science.gov (United States)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2017-08-01

    In the power spectra of oscillating red giants, there are visually distinct features defining stars ascending the red giant branch from those that have commenced helium core burning. We train a 1D convolutional neural network by supervised learning to automatically learn these visual features from images of folded oscillation spectra. By training and testing on Kepler red giants, we achieve an accuracy of up to 99 per cent in separating helium-burning red giants from those ascending the red giant branch. The convolutional neural network additionally shows capability in accurately predicting the evolutionary states of 5379 previously unclassified Kepler red giants, by which we now have greatly increased the number of classified stars.

  10. 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

  11. Pineal organs of deep-sea fish: photopigments and structure.

    Science.gov (United States)

    Bowmaker, James K; Wagner, Hans-Joachim

    2004-06-01

    We have examined the morphology and photopigments of the pineal organs from a number of mesopelagic fish, including representatives of the hatchet fish (Sternoptychidae), scaly dragon-fish (Chauliodontidae) and bristlemouths (Gonostomidae). Although these fish were caught at depths of between 500 and 1000 m, the morphological organisation of their pineal organs is remarkably similar to that of surface-dwelling fish. Photoreceptor inner and outer segments protrude into the lumen of the pineal vesicle, and the outer segment is composed of a stack of up to 20 curved disks that form a cap-like cover over the inner segment. In all species, the pineal photopigment was spectrally distinct from the retinal rod pigment, with lambdamax displaced to longer wavelengths, between approximately 485 and 503 nm. We also investigated the pineal organ of the deep demersal eel, Synaphobranchus kaupi, caught at depths below 2000 m, which possesses a rod visual pigment with lambdamax at 478 nm, but the pineal pigment has lambdamax at approximately 515 nm. In one species of hatchet fish, Argyropelecus affinis, two spectral classes of pinealocyte were identified, both spectrally distinct from the retinal rod photopigment.

  12. WFIRST: Science from Deep Field Surveys

    Science.gov (United States)

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

    2018-01-01

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

  13. 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.

  14. The deep lymphatic anatomy of the hand.

    Science.gov (United States)

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

    2018-04-03

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

  15. Many-Objective Distinct Candidates Optimization using Differential Evolution

    DEFF Research Database (Denmark)

    Justesen, Peter; Ursem, Rasmus Kjær

    2010-01-01

    for each objective. The Many-Objective Distinct Candidates Optimization using Differential Evolution (MODCODE) algorithm takes a novel approach by focusing search using a user-defined number of subpopulations each returning a distinct optimal solution within the preferred region of interest. In this paper......, we present the novel MODCODE algorithm incorporating the ROD measure to measure and control candidate distinctiveness. MODCODE is tested against GDE3 on three real world centrifugal pump design problems supplied by Grundfos. Our algorithm outperforms GDE3 on all problems with respect to all...

  16. Creating fair lineups for suspects with distinctive features.

    Science.gov (United States)

    Zarkadi, Theodora; Wade, Kimberley A; Stewart, Neil

    2009-12-01

    In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineups--without increasing the incorrect identification of foils in target-absent lineups--than did concealment. This pattern, and only this pattern, is predicted by the hybrid-similarity model of recognition.

  17. Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

    Directory of Open Access Journals (Sweden)

    E. Ramirez-Llodra

    2010-09-01

    Full Text Available The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna.

    Investigations of deep-sea habitats and their fauna began in the late 19th century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 28 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st century. However, for most of these habitats the global area covered is unknown or has been only very roughly estimated; an even smaller – indeed, minimal – proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation thus shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps. Here, chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold

  18. 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.

  19. Deep Generative Models for Molecular Science

    DEFF Research Database (Denmark)

    Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole

    2018-01-01

    Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...

  20. Harnessing the Deep Web: Present and Future

    OpenAIRE

    Madhavan, Jayant; Afanasiev, Loredana; Antova, Lyublena; Halevy, Alon

    2009-01-01

    Over the past few years, we have built a system that has exposed large volumes of Deep-Web content to Google.com users. The content that our system exposes contributes to more than 1000 search queries per-second and spans over 50 languages and hundreds of domains. The Deep Web has long been acknowledged to be a major source of structured data on the web, and hence accessing Deep-Web content has long been a problem of interest in the data management community. In this paper, we report on where...

  1. Desalination Economic Evaluation Program (DEEP). User's manual

    International Nuclear Information System (INIS)

    2000-01-01

    DEEP (formerly named ''Co-generation and Desalination Economic Evaluation'' Spreadsheet, CDEE) has been developed originally by General Atomics under contract, and has been used in the IAEA's feasibility studies. For further confidence in the software, it was validated in March 1998. After that, a user friendly version has been issued under the name of DEEP at the end of 1998. DEEP output includes the levelised cost of water and power, a breakdown of cost components, energy consumption and net saleable power for each selected option. Specific power plants can be modelled by adjustment of input data including design power, power cycle parameters and costs

  2. Zooplankton at deep Red Sea brine pools

    KAUST Repository

    Kaartvedt, Stein

    2016-03-02

    The deep-sea anoxic brines of the Red Sea comprise unique, complex and extreme habitats. These environments are too harsh for metazoans, while the brine–seawater interface harbors dense microbial populations. We investigated the adjacent pelagic fauna at two brine pools using net tows, video records from a remotely operated vehicle and submerged echosounders. Waters just above the brine pool of Atlantis II Deep (2000 m depth) appeared depleted of macrofauna. In contrast, the fauna appeared to be enriched at the Kebrit Deep brine–seawater interface (1466 m).

  3. Geometrical constraint on the localization of deep water formation

    Science.gov (United States)

    Ferreira, D.; Marshall, J.

    2008-12-01

    That deep water formation occurs in the North Atlantic and not North Pacific is one of the most notable features of the present climate. In an effort to build a system able to mimic such basic aspects of climate using a minimal description, we study here the influence of ocean geometry on the localization of deep water formation. Using the MIT GCM, two idealized configurations of an ocean-atmosphere-sea ice climate system are studied: Drake and Double-Drake. In Drake, one narrow barrier extends from the North Pole to 35°S while, in Double-Drake, two such barriers set 90° apart join at the North Pole to delimit a Small and a Large basin. Despite the different continental configurations, the two climates are strikingly similar in the zonal average (almost identical heat and fresh water transports, and meridional overturning circulation). However, regional circulations in the Small and Large basins exhibit distinctive Atlantic-like and Pacific-like characteristics: the Small basin is warmer and saltier than the Large one, concentrates dense water formation and deep overturning circulation and achieve the largest fraction of the northward ocean heat transport. We show that the warmer temperature and higher evaporation over the Small basin is not its distinguishing factor. Rather, it is the width of the basin in relation to the zonal fetch of the precipitation pattern. This generates a deficit/excess of precipitation over the Small/Large basin: a fraction of the moisture evaporated from the Small basin is transported zonally and rains out over the Large basin. This creates a salt contrast between the 2 basins, leading to the localization of deep convection in the salty Small basin. Finally, given on the broad similarities between the Double-Drake and real World, we suggest that many gross features that define the present climate are a consequence of 2 asymmetries: a meridional asymmetry (a zonally unblocked southern/blocked northern ocean) and a zonal one (a small and

  4. 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

  5. Comet Dust After Deep Impact

    Science.gov (United States)

    Wooden, Diane H.; Harker, David E.; Woodward, Charles E.

    2006-01-01

    When the Deep Impact Mission hit Jupiter Family comet 9P/Tempel 1, an ejecta crater was formed and an pocket of volatile gases and ices from 10-30 m below the surface was exposed (A Hearn et aI. 2005). This resulted in a gas geyser that persisted for a few hours (Sugita et al, 2005). The gas geyser pushed dust grains into the coma (Sugita et a1. 2005), as well as ice grains (Schulz et al. 2006). The smaller of the dust grains were submicron in radii (0-25.3 micron), and were primarily composed of highly refractory minerals including amorphous (non-graphitic) carbon, and silicate minerals including amorphous (disordered) olivine (Fe,Mg)2SiO4 and pyroxene (Fe,Mg)SiO3 and crystalline Mg-rich olivine. The smaller grains moved faster, as expected from the size-dependent velocity law produced by gas-drag on grains. The mineralogy evolved with time: progressively larger grains persisted in the near nuclear region, having been imparted with slower velocities, and the mineralogies of these larger grains appeared simpler and without crystals. The smaller 0.2-0.3 micron grains reached the coma in about 1.5 hours (1 arc sec = 740 km), were more diverse in mineralogy than the larger grains and contained crystals, and appeared to travel through the coma together. No smaller grains appeared at larger coma distances later (with slower velocities), implying that if grain fragmentation occurred, it happened within the gas acceleration zone. These results of the high spatial resolution spectroscopy (GEMINI+Michelle: Harker et 4. 2005, 2006; Subaru+COMICS: Sugita et al. 2005) revealed that the grains released from the interior were different from the nominally active areas of this comet by their: (a) crystalline content, (b) smaller size, (c) more diverse mineralogy. The temporal changes in the spectra, recorded by GEMIM+Michelle every 7 minutes, indicated that the dust mineralogy is inhomogeneous and, unexpectedly, the portion of the size distribution dominated by smaller grains has

  6. Anisotropy in the deep Earth

    Science.gov (United States)

    Romanowicz, Barbara; Wenk, Hans-Rudolf

    2017-08-01

    Seismic anisotropy has been found in many regions of the Earth's interior. Its presence in the Earth's crust has been known since the 19th century, and is due in part to the alignment of anisotropic crystals in rocks, and in part to patterns in the distribution of fractures and pores. In the upper mantle, seismic anisotropy was discovered 50 years ago, and can be attributed for the most part, to the alignment of intrinsically anisotropic olivine crystals during large scale deformation associated with convection. There is some indication for anisotropy in the transition zone, particularly in the vicinity of subducted slabs. Here we focus on the deep Earth - the lower mantle and core, where anisotropy is not yet mapped in detail, nor is there consensus on its origin. Most of the lower mantle appears largely isotropic, except in the last 200-300 km, in the D″ region, where evidence for seismic anisotropy has been accumulating since the late 1980s, mostly from shear wave splitting measurements. Recently, a picture has been emerging, where strong anisotropy is associated with high shear velocities at the edges of the large low shear velocity provinces (LLSVPs) in the central Pacific and under Africa. These observations are consistent with being due to the presence of highly anisotropic MgSiO3 post-perovskite crystals, aligned during the deformation of slabs impinging on the core-mantle boundary, and upwelling flow within the LLSVPs. We also discuss mineral physics aspects such as ultrahigh pressure deformation experiments, first principles calculations to obtain information about elastic properties, and derivation of dislocation activity based on bonding characteristics. Polycrystal plasticity simulations can predict anisotropy but models are still highly idealized and neglect the complex microstructure of polyphase aggregates with strong and weak components. A promising direction for future progress in understanding the origin of seismic anisotropy in the deep mantle

  7. The rhetorician's craft, distinctions in science, and political morality

    Science.gov (United States)

    Sadler, John Z

    2006-01-01

    In his response to Szasz' Secular Humanism and Scientific Psychiatry, the author considers the use of rhetorical devices in Szasz' work, Szasz' avoidance of acknowledging psychiatry's scientific distinctions, and Szaszian libertarianism versus liberalism. PMID:16759356

  8. Education and Training: Is There Any Longer a Useful Distinction?

    Science.gov (United States)

    Hager, Paul; Laurent, John

    1990-01-01

    Although education and training were distinct concepts when Taylorism dominated the workplace, it is no longer appropriate to separate them. Today's highly competitive environment requires the education of a flexible, multiskilled workforce, not training for narrowly defined employment tasks. (SK)

  9. The rhetorician's craft, distinctions in science, and political morality

    OpenAIRE

    Sadler, John Z

    2006-01-01

    Abstract In his response to Szasz' Secular Humanism and Scientific Psychiatry, the author considers the use of rhetorical devices in Szasz' work, Szasz' avoidance of acknowledging psychiatry's scientific distinctions, and Szaszian libertarianism versus liberalism.

  10. The rhetorician's craft, distinctions in science, and political morality

    Directory of Open Access Journals (Sweden)

    Sadler John Z

    2006-05-01

    Full Text Available Abstract In his response to Szasz' Secular Humanism and Scientific Psychiatry, the author considers the use of rhetorical devices in Szasz' work, Szasz' avoidance of acknowledging psychiatry's scientific distinctions, and Szaszian libertarianism versus liberalism.

  11. Tagging like Humans: Diverse and Distinct Image Annotation

    KAUST Repository

    Wu, Baoyuan; Chen, Weidong; Sun, Peng; Liu, Wei; Ghanem, Bernard; Lyu, Siwei

    2018-01-01

    including quantitative and qualitative comparisons, as well as human subject studies, on two benchmark datasets demonstrate that the proposed model can produce more diverse and distinct tags than the state-of-the-arts.

  12. Identification of distinct phenotypes of locally advanced pancreatic adenocarcinoma.

    LENUS (Irish Health Repository)

    Teo, Minyuen

    2013-03-01

    A significant number of pancreatic ductal adenocarcinoma present as locally advanced disease. Optimal treatment remains controversial. We sought to analyze the clinical course of locally advanced pancreatic adenocarcinoma (LAPC) in order to identify potential distinct clinical phenotypes.

  13. Fetterman-House: A Process Use Distinction and a Theory.

    Science.gov (United States)

    Fetterman, David

    2003-01-01

    Discusses the concept of process use as an important distinction between the evaluation theories of E. House and D. Fetterman, thus helping to explain the discordant results of C. Christie for these two theories. (SLD)

  14. 29 CFR 549.3 - Distinction between plan and trust.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 3 2010-07-01 2010-07-01 false Distinction between plan and trust. 549.3 Section 549.3 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR REGULATIONS REQUIREMENTS OF A âBONA FIDE PROFIT-SHARING PLAN OR TRUSTâ § 549.3 Distinction between plan and trust. As used in this part: (a) Profit-sharing plan...

  15. An Adult Developmental Approach to Perceived Facial Attractiveness and Distinctiveness

    OpenAIRE

    Natalie C. Ebner; Natalie C. Ebner; Natalie C. Ebner; Joerg Luedicke; Manuel C. Voelkle; Manuel C. Voelkle; Michaela Riediger; Michaela Riediger; Tian Lin; Ulman Lindenberger; Ulman Lindenberger

    2018-01-01

    Attractiveness and distinctiveness constitute facial features with high biological and social relevance. Bringing a developmental perspective to research on social-cognitive face perception, we used a large set of faces taken from the FACES Lifespan Database to examine effects of face and perceiver characteristics on subjective evaluations of attractiveness and distinctiveness in young (20–31 years), middle-aged (44–55 years), and older (70–81 years) men and women. We report novel findings su...

  16. DeepDive: Declarative Knowledge Base Construction.

    Science.gov (United States)

    De Sa, Christopher; Ratner, Alex; Ré, Christopher; Shin, Jaeho; Wang, Feiran; Wu, Sen; Zhang, Ce

    2016-03-01

    The dark data extraction or knowledge base construction (KBC) problem is to populate a SQL database with information from unstructured data sources including emails, webpages, and pdf reports. KBC is a long-standing problem in industry and research that encompasses problems of data extraction, cleaning, and integration. We describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems. The key idea in DeepDive is that statistical inference and machine learning are key tools to attack classical data problems in extraction, cleaning, and integration in a unified and more effective manner. DeepDive programs are declarative in that one cannot write probabilistic inference algorithms; instead, one interacts by defining features or rules about the domain. A key reason for this design choice is to enable domain experts to build their own KBC systems. We present the applications, abstractions, and techniques of DeepDive employed to accelerate construction of KBC systems.

  17. Variational inference & deep learning : A new synthesis

    NARCIS (Netherlands)

    Kingma, D.P.

    2017-01-01

    In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.

  18. Pathways to deep decarbonization - 2015 report

    International Nuclear Information System (INIS)

    Ribera, Teresa; Colombier, Michel; Waisman, Henri; Bataille, Chris; Pierfederici, Roberta; Sachs, Jeffrey; Schmidt-Traub, Guido; Williams, Jim; Segafredo, Laura; Hamburg Coplan, Jill; Pharabod, Ivan; Oury, Christian

    2015-12-01

    In September 2015, the Deep Decarbonization Pathways Project published the Executive Summary of the Pathways to Deep Decarbonization: 2015 Synthesis Report. The full 2015 Synthesis Report was launched in Paris on December 3, 2015, at a technical workshop with the Mitigation Action Plans and Scenarios (MAPS) program. The Deep Decarbonization Pathways Project (DDPP) is a collaborative initiative to understand and show how individual countries can transition to a low-carbon economy and how the world can meet the internationally agreed target of limiting the increase in global mean surface temperature to less than 2 degrees Celsius (deg. C). Achieving the 2 deg. C limit will require that global net emissions of greenhouse gases (GHG) approach zero by the second half of the century. In turn, this will require a profound transformation of energy systems by mid-century through steep declines in carbon intensity in all sectors of the economy, a transition we call 'deep decarbonization'

  19. Variational inference & deep learning: A new synthesis

    OpenAIRE

    Kingma, D.P.

    2017-01-01

    In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.

  20. DNA Replication Profiling Using Deep Sequencing.

    Science.gov (United States)

    Saayman, Xanita; Ramos-Pérez, Cristina; Brown, Grant W

    2018-01-01

    Profiling of DNA replication during progression through S phase allows a quantitative snap-shot of replication origin usage and DNA replication fork progression. We present a method for using deep sequencing data to profile DNA replication in S. cerevisiae.

  1. DAPs: Deep Action Proposals for Action Understanding

    KAUST Repository

    Escorcia, Victor; Caba Heilbron, Fabian; Niebles, Juan Carlos; Ghanem, Bernard

    2016-01-01

    action proposals from long videos. We show how to take advantage of the vast capacity of deep learning models and memory cells to retrieve from untrimmed videos temporal segments, which are likely to contain actions. A comprehensive evaluation indicates

  2. Evaluation of static resistance of deep foundations.

    Science.gov (United States)

    2017-05-01

    The focus of this research was to evaluate and improve Florida Department of Transportation (FDOT) FB-Deep software prediction of nominal resistance of H-piles, prestressed concrete piles in limestone, large diameter (> 36) open steel and concrete...

  3. The deep ocean under climate change.

    Science.gov (United States)

    Levin, Lisa A; Le Bris, Nadine

    2015-11-13

    The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems. Copyright © 2015, American Association for the Advancement of Science.

  4. Deep gold mine fracture zone behaviour

    CSIR Research Space (South Africa)

    Napier, JAL

    1998-12-01

    Full Text Available The investigation of the behaviour of the fracture zone surrounding deep level gold mine stopes is detailed in three main sections of this report. Section 2 outlines the ongoing study of fundamental fracture process and their numerical...

  5. Deep Ultraviolet Macroporous Silicon Filters, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal describes a novel method to make deep and far UV optical filters from macroporous silicon. This type of filter consists of an array of...

  6. Toolkits and Libraries for Deep Learning.

    Science.gov (United States)

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy; Philbrick, Kenneth

    2017-08-01

    Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. In the medical imaging domain, example tasks include organ segmentation, lesion detection, and tumor classification. The most popular network architecture for deep learning for images is the convolutional neural network (CNN). Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting of those features to make predictions for new data. In this paper, we will describe some of the libraries and tools that are available to aid in the construction and efficient execution of deep learning as applied to medical images.

  7. Deep-Sea Soft Coral Habitat Suitability

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Deep-sea corals, also known as cold water corals, create complex communities that provide habitat for a variety of invertebrate and fish species, such as grouper,...

  8. Photon diffractive dissociation in deep inelastic scattering

    International Nuclear Information System (INIS)

    Ryskin, M.G.

    1990-01-01

    The new ep-collider HERA gives us the possibility to study the diffractive dissociation of virtual photon in deep inelastic ep-collision. The process of photon dissociation in deep inelastic scattering is the most direct way to measure the value of triple-pomeron vertex G 3P . It was shown that the value of the correct bare vertex G 3P may more than 4 times exceeds its effective value measuring in the triple-reggeon region and reaches the value of about 40-50% of the elastic pp-pomeron vertex. On the contrary in deep inelastic processes the perpendicular momenta q t of the secondary particles are large enough. Thus in deep inelastic reactions one can measure the absolute value of G 3P vertex in the most direct way and compare its value and q t dependence with the leading log QCD predictions

  9. Applications of Deep Learning in Biomedicine.

    Science.gov (United States)

    Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

    2016-05-02

    Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

  10. Mean associative multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

    Dzhaparidze, G.Sh.; Kiselev, A.V.; Petrov, V.A.

    1981-01-01

    The associative hadron multiplicities in deep inelastic and Drell--Yan processes are studied. In particular the mean multiplicities in different hard processes in QCD are found to be determined by the mean multiplicity in parton jet [ru

  11. Deep-Sea Stony Coral Habitat Suitability

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Deep-sea corals, also known as cold water corals, create complex communities that provide habitat for a variety of invertebrate and fish species, such as grouper,...

  12. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information

  13. Leading particle in deep inelastic scattering

    International Nuclear Information System (INIS)

    Petrov, V.A.

    1984-01-01

    The leading particle effect in deep inelastic scattering is considered. The change of the characteris cs shape of the leading particle inclusive spectrum with Q 2 is estimated to be rather significant at very high Q 2

  14. Progress in deep-UV photoresists

    Indian Academy of Sciences (India)

    Unknown

    This paper reviews the recent development and challenges of deep-UV photoresists and their ... small amount of acid, when exposed to light by photo- chemical ... anomalous insoluble skin and linewidth shift when the. PEB was delayed.

  15. Methods in mooring deep sea sediment traps

    Digital Repository Service at National Institute of Oceanography (India)

    Venkatesan, R.; Fernando, V.; Rajaraman, V.S.; Janakiraman, G.

    The experience gained during the process of deployment and retrieval of nearly 39 sets of deep sea sediment trap moorings on various ships like FS Sonne, ORV Sagarkanya and DSV Nand Rachit are outlined. The various problems encountered...

  16. Deep Water Horizon (HB1006, EK60)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monitor and measure the biological, chemical, and physical environment in the area of the oil spill from the deep water horizon oil rig in the Gulf of Mexico. A wide...

  17. Deep Time Iterations: Familiarity, Horizons, and Pattern among Finland's Nuclear Waste Safety Experts

    Science.gov (United States)

    Ialenti, Vincent Francis

    This ethnography reconsiders nuclear waste risk's deep time horizons' often-sensationalized aesthetics of horror, sublimity, and awe. It does so by tracking how Finland's nuclear energy and waste experts made visions of distant future Finlands appear more intelligible through mundane corporate, regulatory, financial, and technoscientific practices. Each chapter unpacks how informants iterated and reiterated traces of the very familiar to establish shared grounds of continuity for moving forward in time. Chapter 1 explores how Finland's energy sector's "mankala" cooperative corporate form was iterated and reiterated to give shape to political and financial time horizons. Chapter 2 explores how workplace role distinctions between recruit/retiree and junior/senior were iterated and reiterated to reckon nuclear personnel successions' intergenerational horizons. Chapter 3 explores how input/output and part/whole distinctions were iterated and reiterated to help model distant future worlds in a portfolio of "Safety Case" evidence made to demonstrate the Olkiluoto repository's safety to Finnish nuclear regulator STUK. Chapter 4 explores how Safety Case experts iterated and reiterated memories of a deceased predecessor figure in everyday engagements with deep time. What emerges are three insights about how futures attain discernible features--insights about the "continuity," "thinkability," and "extensibility" of expert thought--that, I argue, can help twenty-first century experts better navigate not only deep time, but also unknown futures of nuclear technologies, planetary environment, and expertise itself.

  18. Biodiversity loss from deep-sea mining

    OpenAIRE

    C. L. Van Dover; J. A. Ardron; E. Escobar; M. Gianni; K. M. Gjerde; A. Jaeckel; D. O. B. Jones; L. A. Levin; H. Niner; L. Pendleton; C. R. Smith; T. Thiele; P. J. Turner; L. Watling; P. P. E. Weaver

    2017-01-01

    The emerging deep-sea mining industry is seen by some to be an engine for economic development in the maritime sector. The International Seabed Authority (ISA) – the body that regulates mining activities on the seabed beyond national jurisdiction – must also protect the marine environment from harmful effects that arise from mining. The ISA is currently drafting a regulatory framework for deep-sea mining that includes measures for environmental protection. Responsible mining increasingly stri...

  19. DEEP VADOSE ZONE TREATABILITY TEST PLAN

    International Nuclear Information System (INIS)

    Chronister, G.B.; Truex, M.J.

    2009-01-01

    (sm b ullet) Treatability test plan published in 2008 (sm b ullet) Outlines technology treatability activities for evaluating application of in situ technologies and surface barriers to deep vadose zone contamination (technetium and uranium) (sm b ullet) Key elements - Desiccation testing - Testing of gas-delivered reactants for in situ treatment of uranium - Evaluating surface barrier application to deep vadose zone - Evaluating in situ grouting and soil flushing

  20. Deep inelastic inclusive weak and electromagnetic interactions

    International Nuclear Information System (INIS)

    Adler, S.L.

    1976-01-01

    The theory of deep inelastic inclusive interactions is reviewed, emphasizing applications to electromagnetic and weak charged current processes. The following reactions are considered: e + N → e + X, ν + N → μ - + X, anti ν + N → μ + + X where X denotes a summation over all final state hadrons and the ν's are muon neutrinos. After a discussion of scaling, the quark-parton model is invoked to explain the principle experimental features of deep inelastic inclusive reactions

  1. 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 ...

  2. Deep Learning for Video Game Playing

    OpenAIRE

    Justesen, Niels; Bontrager, Philip; Togelius, Julian; Risi, Sebastian

    2017-01-01

    In this article, we review recent Deep Learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces...

  3. Life Support for Deep Space and Mars

    Science.gov (United States)

    Jones, Harry W.; Hodgson, Edward W.; Kliss, Mark H.

    2014-01-01

    How should life support for deep space be developed? The International Space Station (ISS) life support system is the operational result of many decades of research and development. Long duration deep space missions such as Mars have been expected to use matured and upgraded versions of ISS life support. Deep space life support must use the knowledge base incorporated in ISS but it must also meet much more difficult requirements. The primary new requirement is that life support in deep space must be considerably more reliable than on ISS or anywhere in the Earth-Moon system, where emergency resupply and a quick return are possible. Due to the great distance from Earth and the long duration of deep space missions, if life support systems fail, the traditional approaches for emergency supply of oxygen and water, emergency supply of parts, and crew return to Earth or escape to a safe haven are likely infeasible. The Orbital Replacement Unit (ORU) maintenance approach used by ISS is unsuitable for deep space with ORU's as large and complex as those originally provided in ISS designs because it minimizes opportunities for commonality of spares, requires replacement of many functional parts with each failure, and results in substantial launch mass and volume penalties. It has become impractical even for ISS after the shuttle era, resulting in the need for ad hoc repair activity at lower assembly levels with consequent crew time penalties and extended repair timelines. Less complex, more robust technical approaches may be needed to meet the difficult deep space requirements for reliability, maintainability, and reparability. Developing an entirely new life support system would neglect what has been achieved. The suggested approach is use the ISS life support technologies as a platform to build on and to continue to improve ISS subsystems while also developing new subsystems where needed to meet deep space requirements.

  4. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  5. Predicting Process Behaviour using Deep Learning

    OpenAIRE

    Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter

    2016-01-01

    Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...

  6. A Deep Learning Approach to Drone Monitoring

    OpenAIRE

    Chen, Yueru; Aggarwal, Pranav; Choi, Jongmoo; Kuo, C. -C. Jay

    2017-01-01

    A drone monitoring system that integrates deep-learning-based detection and tracking modules is proposed in this work. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone images. To address this issue, we develop a model-based drone augmentation technique that automatically generates drone images with a bounding box label on drone's location. To track a small flying drone, we utilize the residual information between consecutive i...

  7. Bank of Weight Filters for Deep CNNs

    Science.gov (United States)

    2016-11-22

    very large even on the best available hardware . In some studies in transfer learning it has been observed that the network learnt on one task can be...CNNs. Keywords: CNN, deep learning , neural networks, transfer learning , bank of weigh filters, BWF 1. Introduction Object recognition is an important...of CNNs (or, in general, of deep neural networks) is that feature generation part is fused with the classifier part and both parts are learned together

  8. Leveraging multiple datasets for deep leaf counting

    OpenAIRE

    Dobrescu, Andrei; Giuffrida, Mario Valerio; Tsaftaris, Sotirios A

    2017-01-01

    The number of leaves a plant has is one of the key traits (phenotypes) describing its development and growth. Here, we propose an automated, deep learning based approach for counting leaves in model rosette plants. While state-of-the-art results on leaf counting with deep learning methods have recently been reported, they obtain the count as a result of leaf segmentation and thus require per-leaf (instance) segmentation to train the models (a rather strong annotation). Instead, our method tre...

  9. Expert Knowledge, Distinctiveness, and Levels of Processing in Language Learning

    Science.gov (United States)

    Bird, Steve

    2012-01-01

    The foreign language vocabulary learning research literature often attributes strong mnemonic potency to the cognitive processing of meaning when learning words. Routinely cited as support for this idea are experiments by Craik and Tulving (C&T) demonstrating superior recognition and recall of studied words following semantic tasks ("deep"…

  10. DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters

    OpenAIRE

    Kim, Hanjoo; Park, Jaehong; Jang, Jaehee; Yoon, Sungroh

    2016-01-01

    The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operation...

  11. Contemporary deep recurrent learning for recognition

    Science.gov (United States)

    Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

    2017-05-01

    Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

  12. Diabetic retinopathy screening using deep neural network.

    Science.gov (United States)

    Ramachandran, Nishanthan; Hong, Sheng Chiong; Sime, Mary J; Wilson, Graham A

    2017-09-07

    There is a burgeoning interest in the use of deep neural network in diabetic retinal screening. To determine whether a deep neural network could satisfactorily detect diabetic retinopathy that requires referral to an ophthalmologist from a local diabetic retinal screening programme and an international database. Retrospective audit. Diabetic retinal photos from Otago database photographed during October 2016 (485 photos), and 1200 photos from Messidor international database. Receiver operating characteristic curve to illustrate the ability of a deep neural network to identify referable diabetic retinopathy (moderate or worse diabetic retinopathy or exudates within one disc diameter of the fovea). Area under the receiver operating characteristic curve, sensitivity and specificity. For detecting referable diabetic retinopathy, the deep neural network had an area under receiver operating characteristic curve of 0.901 (95% confidence interval 0.807-0.995), with 84.6% sensitivity and 79.7% specificity for Otago and 0.980 (95% confidence interval 0.973-0.986), with 96.0% sensitivity and 90.0% specificity for Messidor. This study has shown that a deep neural network can detect referable diabetic retinopathy with sensitivities and specificities close to or better than 80% from both an international and a domestic (New Zealand) database. We believe that deep neural networks can be integrated into community screening once they can successfully detect both diabetic retinopathy and diabetic macular oedema. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

  13. Deep-water fisheries at the Atlantic Frontier

    Science.gov (United States)

    Gordon, J. D. M.

    2001-05-01

    The deep sea is often thought of as a cold, dark and uniform environment with a low-fish biomass, much of which is highly adapted for life in a food-poor environment. While this might be true of the pelagic fish living in the water column, it is certainly not true of the demersal fish which live on or close to the bottom on the continental slopes around the British Isles (the Atlantic Frontier). These fish are currently being commercially exploited. There is growing evidence to support the view that success of the demersal fish assemblages depends on the pelagic or benthopelagic food sources that impinge both vertically and horizontally onto the slope. There are several quite separate and distinct deep-water fisheries on the Atlantic Frontier. It is a physical barrier, the Wyville-Thomson Ridge, which results in the most significant division of the fisheries. The Ridge, which has a minimum depth of about 500 m, separates the warmer deep Atlantic waters from the much colder Norwegian Sea water and as a result, the deep-water fisheries to the west of the Hebrides and around the offshore banks are quite different from those of the Faroe-Shetland Channel (West of Shetland). The fisheries to the West of the Hebrides can be further divided by the fishing method used into bottom trawl, semipelagic trawl and longline. The bottom-trawl fisheries extend from the shelf-slope break down to about 1700 m and the target species varies with depth. The smallest vessels in the fleet fish on the upper slope, where an important target species is the anglerfish or monkfish ( Lophius spp.). On the mid-slope the main target species are blue ling ( Molva dypterygia) and roundnose grenadier ( Coryphaenoides rupestris), with bycatches of black scabbardfish ( Aphanopus carbo) and deep-water sharks. On the lower slope orange roughy ( Hoplostethus atlanticus) is an important target species. The major semipelagic trawl fishery is a seasonal fishery on spawning aggregations of blue whiting

  14. Search for and characterization of microorganisms in deep geological compartments

    International Nuclear Information System (INIS)

    Barsotti, Vanessa

    2011-01-01

    and 260 g.l -1 ) on the metabolic activity of anaerobic prokaryotes. In order to identify effects of parameters on microbial activities, a complete factorial plan was constructed from the metabolic activities measured for eight halophile and thermo-tolerant bacterial strains exposed to 30 distinct temperature, pressure and salinity conditions. All the strains issued from deep environments were at the least piezo-tolerant and capable of maintaining their activity under hydrostatic pressures. The fermenting (Thermovirga lienii and Halothermothrix orenii) and thiosulfate reducing strains (Petrotoga mexicana and Thermiosipho japonicus) were particularly well adapted, from a metabolic point of view, to high pressures; indeed the highest activities were measured under pressure. Also, several strains (such as Petrotoga mexicana) showed an increased resistance to high temperatures under pressure. However, resistance to an increase in salinity was variable for each strain under the different temperature and pressure conditions. This suggests that the resistance mechanisms for osmotic pressure also enable resistance to high temperatures and hydrostatic pressures.This work underlines that the microbiological characterization of deep terrestrial ecosystems must not be limited to the search and analyses of the existing diversity. Moreover, such upstream studies of the metabolic activities of subsurface bacterial strains in deep terrestrial conditions are a necessary beginning towards understanding the role of microbial communities in extreme environments. (author) [fr

  15. Some Challenges of Deep Mining†

    Directory of Open Access Journals (Sweden)

    Charles Fairhurst

    2017-08-01

    Full Text Available An increased global supply of minerals is essential to meet the needs and expectations of a rapidly rising world population. This implies extraction from greater depths. Autonomous mining systems, developed through sustained R&D by equipment suppliers, reduce miner exposure to hostile work environments and increase safety. This places increased focus on “ground control” and on rock mechanics to define the depth to which minerals may be extracted economically. Although significant efforts have been made since the end of World War II to apply mechanics to mine design, there have been both technological and organizational obstacles. Rock in situ is a more complex engineering material than is typically encountered in most other engineering disciplines. Mining engineering has relied heavily on empirical procedures in design for thousands of years. These are no longer adequate to address the challenges of the 21st century, as mines venture to increasingly greater depths. The development of the synthetic rock mass (SRM in 2008 provides researchers with the ability to analyze the deformational behavior of rock masses that are anisotropic and discontinuous—attributes that were described as the defining characteristics of in situ rock by Leopold Müller, the president and founder of the International Society for Rock Mechanics (ISRM, in 1966. Recent developments in the numerical modeling of large-scale mining operations (e.g., caving using the SRM reveal unanticipated deformational behavior of the rock. The application of massive parallelization and cloud computational techniques offers major opportunities: for example, to assess uncertainties in numerical predictions; to establish the mechanics basis for the empirical rules now used in rock engineering and their validity for the prediction of rock mass behavior beyond current experience; and to use the discrete element method (DEM in the optimization of deep mine design. For the first time, mining

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

    Science.gov (United States)

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

    2017-03-01

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

  17. Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

    Science.gov (United States)

    Dai, Guoxian; Xie, Jin; Fang, Yi

    2018-07-01

    How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

  18. Sea-level and deep-sea-temperature variability over the past 5.3 million years.

    Science.gov (United States)

    Rohling, E J; Foster, G L; Grant, K M; Marino, G; Roberts, A P; Tamisiea, M E; Williams, F

    2014-04-24

    Ice volume (and hence sea level) and deep-sea temperature are key measures of global climate change. Sea level has been documented using several independent methods over the past 0.5 million years (Myr). Older periods, however, lack such independent validation; all existing records are related to deep-sea oxygen isotope (δ(18)O) data that are influenced by processes unrelated to sea level. For deep-sea temperature, only one continuous high-resolution (Mg/Ca-based) record exists, with related sea-level estimates, spanning the past 1.5 Myr. Here we present a novel sea-level reconstruction, with associated estimates of deep-sea temperature, which independently validates the previous 0-1.5 Myr reconstruction and extends it back to 5.3 Myr ago. We find that deep-sea temperature and sea level generally decreased through time, but distinctly out of synchrony, which is remarkable given the importance of ice-albedo feedbacks on the radiative forcing of climate. In particular, we observe a large temporal offset during the onset of Plio-Pleistocene ice ages, between a marked cooling step at 2.73 Myr ago and the first major glaciation at 2.15 Myr ago. Last, we tentatively infer that ice sheets may have grown largest during glacials with more modest reductions in deep-sea temperature.

  19. Zonation of Microbial Communities by a Hydrothermal Mound in the Atlantis II Deep (the Red Sea)

    KAUST Repository

    Wang, Yong; Li, Jiang Tao; He, Li Sheng; Yang, Bo; Gao, Zhao Ming; Cao, Hui Luo; Batang, Zenon B.; Al-Suwailem, Abdulaziz M.; Qian, Pei-Yuan

    2015-01-01

    In deep-sea geothermal rift zones, the dispersal of hydrothermal fluids of moderately-high temperatures typically forms subseafloor mounds. Major mineral components of the crust covering the mound are barite and metal sulfides. As a result of the continental rifting along the Red Sea, metalliferous sediments accumulate on the seafloor of the Atlantis II Deep. In the present study, a barite crust was identified in a sediment core from the Atlantis II Deep, indicating the formation of a hydrothermal mound at the sampling site. Here, we examined how such a dense barite crust could affect the local environment and the distribution of microbial inhabitants. Our results demonstrate distinctive features of mineral components and microbial communities in the sediment layers separated by the barite crust. Within the mound, archaea accounted for 65% of the community. In contrast, the sediments above the barite boundary were overwhelmed by bacteria. The composition of microbial communities under the mound was similar to that in the sediments of the nearby Discovery Deep and marine cold seeps. This work reveals the zonation of microbial communities after the formation of the hydrothermal mound in the subsurface sediments of the rift basin.

  20. Going Deeper or Flatter: Connecting Deep Mapping, Flat Ontologies and the Democratizing of Knowledge

    Directory of Open Access Journals (Sweden)

    Selina Springett

    2015-10-01

    Full Text Available The concept of “deep mapping”, as an approach to place, has been deployed as both a descriptor of a specific suite of creative works and as a set of aesthetic practices. While its definition has been amorphous and adaptive, a number of distinct, yet related, manifestations identify as, or have been identified by, the term. In recent times, it has garnered attention beyond literary discourse, particularly within the “spatial” turn of representation in the humanities and as a result of expanded platforms of data presentation. This paper takes a brief look at the practice of “deep mapping”, considering it as a consciously performative act and tracing a number of its various manifestations. It explores how deep mapping is a reflection of epistemological trends in ontological practices of connectivity and the “flattening” of knowledge systems. In particular those put forward by post structural and cultural theorists, such as Bruno Latour, Gilles Deleuze, and Felix Guattari, as well as by theorists who associate with speculative realism. The concept of deep mapping as an aesthetic, methodological, and ideological tool, enables an approach to place that democratizes knowledge by crossing temporal, spatial, and disciplinary boundaries.

  1. Zonation of Microbial Communities by a Hydrothermal Mound in the Atlantis II Deep (the Red Sea)

    KAUST Repository

    Wang, Yong

    2015-10-20

    In deep-sea geothermal rift zones, the dispersal of hydrothermal fluids of moderately-high temperatures typically forms subseafloor mounds. Major mineral components of the crust covering the mound are barite and metal sulfides. As a result of the continental rifting along the Red Sea, metalliferous sediments accumulate on the seafloor of the Atlantis II Deep. In the present study, a barite crust was identified in a sediment core from the Atlantis II Deep, indicating the formation of a hydrothermal mound at the sampling site. Here, we examined how such a dense barite crust could affect the local environment and the distribution of microbial inhabitants. Our results demonstrate distinctive features of mineral components and microbial communities in the sediment layers separated by the barite crust. Within the mound, archaea accounted for 65% of the community. In contrast, the sediments above the barite boundary were overwhelmed by bacteria. The composition of microbial communities under the mound was similar to that in the sediments of the nearby Discovery Deep and marine cold seeps. This work reveals the zonation of microbial communities after the formation of the hydrothermal mound in the subsurface sediments of the rift basin.

  2. Zonation of Microbial Communities by a Hydrothermal Mound in the Atlantis II Deep (the Red Sea.

    Directory of Open Access Journals (Sweden)

    Yong Wang

    Full Text Available In deep-sea geothermal rift zones, the dispersal of hydrothermal fluids of moderately-high temperatures typically forms subseafloor mounds. Major mineral components of the crust covering the mound are barite and metal sulfides. As a result of the continental rifting along the Red Sea, metalliferous sediments accumulate on the seafloor of the Atlantis II Deep. In the present study, a barite crust was identified in a sediment core from the Atlantis II Deep, indicating the formation of a hydrothermal mound at the sampling site. Here, we examined how such a dense barite crust could affect the local environment and the distribution of microbial inhabitants. Our results demonstrate distinctive features of mineral components and microbial communities in the sediment layers separated by the barite crust. Within the mound, archaea accounted for 65% of the community. In contrast, the sediments above the barite boundary were overwhelmed by bacteria. The composition of microbial communities under the mound was similar to that in the sediments of the nearby Discovery Deep and marine cold seeps. This work reveals the zonation of microbial communities after the formation of the hydrothermal mound in the subsurface sediments of the rift basin.

  3. Applying Deep Learning in Medical Images: The Case of Bone Age Estimation.

    Science.gov (United States)

    Lee, Jang Hyung; Kim, Kwang Gi

    2018-01-01

    A diagnostic need often arises to estimate bone age from X-ray images of the hand of a subject during the growth period. Together with measured physical height, such information may be used as indicators for the height growth prognosis of the subject. We present a way to apply the deep learning technique to medical image analysis using hand bone age estimation as an example. Age estimation was formulated as a regression problem with hand X-ray images as input and estimated age as output. A set of hand X-ray images was used to form a training set with which a regression model was trained. An image preprocessing procedure is described which reduces image variations across data instances that are unrelated to age-wise variation. The use of Caffe, a deep learning tool is demonstrated. A rather simple deep learning network was adopted and trained for tutorial purpose. A test set distinct from the training set was formed to assess the validity of the approach. The measured mean absolute difference value was 18.9 months, and the concordance correlation coefficient was 0.78. It is shown that the proposed deep learning-based neural network can be used to estimate a subject's age from hand X-ray images, which eliminates the need for tedious atlas look-ups in clinical environments and should improve the time and cost efficiency of the estimation process.

  4. Garthambrus, a new genus of deep water parthenopid crabs (Crustacea: Decapoda: Brachyura) from the Indo-Pacific, with description of a new species from the Seychelles

    NARCIS (Netherlands)

    Ng, P.K.L.

    1996-01-01

    A new genus of parthenopid crab, Garthambrus gen. nov., characterised by a broad carapace with strongly raised branchial and gastric regions, distinctive rostrum, sub-cylindrical ambulatory meri and a long distal segment of the second male pleopod, is established for six deep water species from

  5. Ultra Deep Wave Equation Imaging and Illumination

    Energy Technology Data Exchange (ETDEWEB)

    Alexander M. Popovici; Sergey Fomel; Paul Sava; Sean Crawley; Yining Li; Cristian Lupascu

    2006-09-30

    In this project we developed and tested a novel technology, designed to enhance seismic resolution and imaging of ultra-deep complex geologic structures by using state-of-the-art wave-equation depth migration and wave-equation velocity model building technology for deeper data penetration and recovery, steeper dip and ultra-deep structure imaging, accurate velocity estimation for imaging and pore pressure prediction and accurate illumination and amplitude processing for extending the AVO prediction window. Ultra-deep wave-equation imaging provides greater resolution and accuracy under complex geologic structures where energy multipathing occurs, than what can be accomplished today with standard imaging technology. The objective of the research effort was to examine the feasibility of imaging ultra-deep structures onshore and offshore, by using (1) wave-equation migration, (2) angle-gathers velocity model building, and (3) wave-equation illumination and amplitude compensation. The effort consisted of answering critical technical questions that determine the feasibility of the proposed methodology, testing the theory on synthetic data, and finally applying the technology for imaging ultra-deep real data. Some of the questions answered by this research addressed: (1) the handling of true amplitudes in the downward continuation and imaging algorithm and the preservation of the amplitude with offset or amplitude with angle information required for AVO studies, (2) the effect of several imaging conditions on amplitudes, (3) non-elastic attenuation and approaches for recovering the amplitude and frequency, (4) the effect of aperture and illumination on imaging steep dips and on discriminating the velocities in the ultra-deep structures. All these effects were incorporated in the final imaging step of a real data set acquired specifically to address ultra-deep imaging issues, with large offsets (12,500 m) and long recording time (20 s).

  6. Distinctions, Affiliations, and Professional Knowledge in Financial Reform Commissions

    DEFF Research Database (Denmark)

    Seabrooke, Leonard; Tsingou, Eleni

    the different stresses in reports with and without clear mandates, and the role of important members of the policy community in promoting particular reform ideas. The article finds that differences in ideas emerging from the financial reform expert groups reflect nested power relationships in the commissioning...... the reports. Fractal distinctions, such as between ‘behavior’ or ‘system’ as a reform focus, allow us to locate the object of regulation within expert groups, experts’ professional context, and the politics behind the commissioning of work. Analyzing fractal distinctions provides a useful way to understand...... of work, constituent audiences, and reform priorities among governing institutions, rather than distinct ‘European’ and ‘American’ ideas....

  7. Distinctions, Affiliations, and Professional Knowledge in Financial Reform Expert Groups

    DEFF Research Database (Denmark)

    Seabrooke, Leonard; Tsingou, Eleni

    2014-01-01

    to understand the different stresses in reports with and without clear mandates, and the role of important members of the policy community in promoting particular reform ideas. The contribution finds that differences in ideas emerging from the financial reform expert groups reflect nested power relationships...... the reports. Fractal distinctions, such as between ‘behaviour’ or ‘system’ as a reform focus, allow us to locate the object of regulation within expert groups, the experts' professional context and the politics behind the commissioning of work. Analysing fractal distinctions provides a useful way...... in the commissioning of work, constituent audiences and reform priorities among governing institutions, rather than distinct ‘European’ and ‘American’ ideas....

  8. Liquidity spillover in international stock markets through distinct time scales.

    Science.gov (United States)

    Righi, Marcelo Brutti; Vieira, Kelmara Mendes

    2014-01-01

    This paper identifies liquidity spillovers through different time scales based on a wavelet multiscaling method. We decompose daily data from U.S., British, Brazilian and Hong Kong stock markets indices in order to calculate the scale correlation between their illiquidities. The sample is divided in order to consider non-crisis, sub-prime crisis and Eurozone crisis. We find that there are changes in correlations of distinct scales and different periods. Association in finest scales is smaller than in coarse scales. There is a rise on associations in periods of crisis. In frequencies, there is predominance for significant distinctions involving the coarsest scale, while for crises periods there is predominance for distinctions on the finest scale.

  9. The deep-subsurface sulfate reducer Desulfotomaculum kuznetsovii employs two methanol-degrading pathways.

    Science.gov (United States)

    Sousa, Diana Z; Visser, Michael; van Gelder, Antonie H; Boeren, Sjef; Pieterse, Mervin M; Pinkse, Martijn W H; Verhaert, Peter D E M; Vogt, Carsten; Franke, Steffi; Kümmel, Steffen; Stams, Alfons J M

    2018-01-16

    Methanol is generally metabolized through a pathway initiated by a cobalamine-containing methanol methyltransferase by anaerobic methylotrophs (such as methanogens and acetogens), or through oxidation to formaldehyde using a methanol dehydrogenase by aerobes. Methanol is an important substrate in deep-subsurface environments, where thermophilic sulfate-reducing bacteria of the genus Desulfotomaculum have key roles. Here, we study the methanol metabolism of Desulfotomaculum kuznetsovii strain 17 T , isolated from a 3000-m deep geothermal water reservoir. We use proteomics to analyze cells grown with methanol and sulfate in the presence and absence of cobalt and vitamin B12. The results indicate the presence of two methanol-degrading pathways in D. kuznetsovii, a cobalt-dependent methanol methyltransferase and a cobalt-independent methanol dehydrogenase, which is further confirmed by stable isotope fractionation. This is the first report of a microorganism utilizing two distinct methanol conversion pathways. We hypothesize that this gives D. kuznetsovii a competitive advantage in its natural environment.

  10. Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

    Directory of Open Access Journals (Sweden)

    YiNan Zhang

    2017-01-01

    Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

  11. Deep convolutional networks for pancreas segmentation in CT imaging

    Science.gov (United States)

    Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

    2015-03-01

    Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

  12. DeepPVP: phenotype-based prioritization of causative variants using deep learning

    KAUST Repository

    Boudellioua, Imene; Kulmanov, Maxat; Schofield, Paul N; Gkoutos, Georgios V; Hoehndorf, Robert

    2018-01-01

    phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well

  13. What History Tells Us about the Distinct Nature of Chemistry.

    Science.gov (United States)

    Chang, Hasok

    2017-11-01

    Attention to the history of chemistry can help us recognise the characteristics of chemistry that have helped to maintain it as a separate scientific discipline with a unique identity. Three such features are highlighted in this paper. First, chemistry has maintained a distinct type of theoretical thinking, independent from that of physics even in the era of quantum chemistry. Second, chemical research has always been shaped by its ineliminable practical relevance and usefulness. Third, the lived experience of chemistry, spanning the laboratory, the classroom and everyday life, is distinctive in its multidimensional sensuousness. Furthermore, I argue that the combination of these three features makes chemistry an exemplary science.

  14. Revitalizing the “civic” and “ethnic” distinction

    DEFF Research Database (Denmark)

    Larsen, Christian Albrekt

    2017-01-01

    This article describes how contemporary publics think about the nation along Kohn’s classic distinction between “civic” and “ethnic” nationalism. The article makes three contributes to the existing literature. Firstly, it introduces a new statistical tool, multi-classification-analysis, to establ......This article describes how contemporary publics think about the nation along Kohn’s classic distinction between “civic” and “ethnic” nationalism. The article makes three contributes to the existing literature. Firstly, it introduces a new statistical tool, multi...

  15. Grammar-Lexicon Distinction in a Neurocognitive Context

    DEFF Research Database (Denmark)

    Ishkhanyan, Byurakn

    hypotheses and testing them through using various methods. The grammar-lexicon distinction and working memory are thus central topics of this thesis. The results suggest a potential for a successful integration of the two theories. The findings further provide evidence for Boye & Harder’s (2012......) understanding of the grammar-lexicon distinction, and for the involvement of working memory in language production, as the REF-model would predict. As a starting point for integrating the two theories, the present thesis gives directions for future research on the neurocognitive underpinning of language and its...... relation to working memory....

  16. Genomic and Phylogenetic Characterization of Luminous Bacteria Symbiotic with the Deep-Sea Fish Chlorophthalmus albatrossis (Aulopiformes: Chlorophthalmidae)

    OpenAIRE

    Dunlap, Paul V.; Ast, Jennifer C.

    2005-01-01

    Bacteria forming light-organ symbiosis with deep-sea chlorophthalmid fishes (Aulopiformes: Chlorophthalmidae) are considered to belong to the species Photobacterium phosphoreum. The identification of these bacteria as P. phosphoreum, however, was based exclusively on phenotypic traits, which may not discriminate between phenetically similar but evolutionarily distinct luminous bacteria. Therefore, to test the species identification of chlorophthalmid symbionts, we carried out a genomotypic (r...

  17. 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

  18. Molecular analysis of deep subsurface bacteria

    International Nuclear Information System (INIS)

    Jimenez Baez, L.E.

    1989-09-01

    Deep sediments samples from site C10a, in Appleton, and sites, P24, P28, and P29, at the Savannah River Site (SRS), near Aiken, South Carolina were studied to determine their microbial community composition, DNA homology and mol %G+C. Different geological formations with great variability in hydrogeological parameters were found across the depth profile. Phenotypic identification of deep subsurface bacteria underestimated the bacterial diversity at the three SRS sites, since bacteria with the same phenotype have different DNA composition and less than 70% DNA homology. Total DNA hybridization and mol %G+C analysis of deep sediment bacterial isolates suggested that each formation is comprised of different microbial communities. Depositional environment was more important than site and geological formation on the DNA relatedness between deep subsurface bacteria, since more 70% of bacteria with 20% or more of DNA homology came from the same depositional environments. Based on phenotypic and genotypic tests Pseudomonas spp. and Acinetobacter spp.-like bacteria were identified in 85 million years old sediments. This suggests that these microbial communities might have been adapted during a long period of time to the environmental conditions of the deep subsurface

  19. 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.

  20. Training Deep Spiking Neural Networks Using Backpropagation.

    Science.gov (United States)

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

    2016-01-01

    Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

  1. Deep Ocean Contribution to Sea Level Rise

    Science.gov (United States)

    Chang, L.; Sun, W.; Tang, H.; Wang, Q.

    2017-12-01

    The ocean temperature and salinity change in the upper 2000m can be detected by Argo floats, so we can know the steric height change of the ocean. But the ocean layers above 2000m represent only 50% of the total ocean volume. Although the temperature and salinity change are small compared to the upper ocean, the deep ocean contribution to sea level might be significant because of its large volume. There has been some research on the deep ocean rely on the very sparse situ observation and are limited to decadal and longer-term rates of change. The available observational data in the deep ocean are too spares to determine the temporal variability, and the long-term changes may have a bias. We will use the Argo date and combine the situ data and topographic data to estimate the temperature and salinity of the sea water below 2000m, so we can obtain a monthly data. We will analyze the seasonal and annual change of the steric height change due to the deep ocean between 2005 and 2016. And we will evaluate the result combination the present-day satellite and in situ observing systems. The deep ocean contribution can be inferred indirectly as the difference between the altimetry minus GRACE and Argo-based steric sea level.

  2. 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.

  3. Localized deep levels in AlxGa1−xN epitaxial films with various Al compositions

    International Nuclear Information System (INIS)

    Shi Li-Yang; Shen Bo; Wang Ping; Yan Jian-Chang; Wang Jun-Xi

    2014-01-01

    By using high-temperature deep-level transient spectroscopy (HT-DLTS) and other electrical measurement techniques, localized deep levels in n-type Al x Ga 1−x N epitaxial films with various Al compositions (x = 0, 0.14, 0.24, 0.33, and 0.43) have been investigated. It is found that there are three distinct deep levels in Al x Ga 1−x N films, whose level position with respect to the conduction band increases as Al composition increases. The dominant defect level with the activation energy deeper than 1.0 eV below the conduction band closely follows the Fermi level stabilization energy, indicating that its origin may be related to the defect complex, including the anti-site defects and divacancies in Al x Ga 1−x N films. (condensed matter: structural, mechanical, and thermal properties)

  4. DeepPVP: phenotype-based prioritization of causative variants using deep learning

    KAUST Repository

    Boudellioua, Imene

    2018-05-02

    Background: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient\\'s phenotype. Results: We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy.

  5. Deep learning in TMVA Benchmarking Benchmarking TMVA DNN Integration of a Deep Autoencoder

    CERN Document Server

    Huwiler, Marc

    2017-01-01

    The TMVA library in ROOT is dedicated to multivariate analysis, and in partic- ular oers numerous machine learning algorithms in a standardized framework. It is widely used in High Energy Physics for data analysis, mainly to perform regression and classication. To keep up to date with the state of the art in deep learning, a new deep learning module was being developed this summer, oering deep neural net- work, convolutional neural network, and autoencoder. TMVA did not have yet any autoencoder method, and the present project consists in implementing the TMVA autoencoder class based on the deep learning module. It also includes some bench- marking performed on the actual deep neural network implementation, in comparison to the Keras framework with Tensorflow and Theano backend.

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

    Science.gov (United States)

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

    2018-02-26

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

  7. Parallel prefrontal pathways reach distinct excitatory and inhibitory systems in memory-related rhinal cortices.

    Science.gov (United States)

    Bunce, Jamie G; Zikopoulos, Basilis; Feinberg, Marcia; Barbas, Helen

    2013-12-15

    To investigate how prefrontal cortices impinge on medial temporal cortices we labeled pathways from the anterior cingulate cortex (ACC) and posterior orbitofrontal cortex (pOFC) in rhesus monkeys to compare their relationship with excitatory and inhibitory systems in rhinal cortices. The ACC pathway terminated mostly in areas 28 and 35 with a high proportion of large terminals, whereas the pOFC pathway terminated mostly through small terminals in area 36 and sparsely in areas 28 and 35. Both pathways terminated in all layers. Simultaneous labeling of pathways and distinct neurochemical classes of inhibitory neurons, followed by analyses of appositions of presynaptic and postsynaptic fluorescent signal, or synapses, showed overall predominant association with spines of putative excitatory neurons, but also significant interactions with presumed inhibitory neurons labeled for calretinin, calbindin, or parvalbumin. In the upper layers of areas 28 and 35 the ACC pathway was associated with dendrites of neurons labeled with calretinin, which are thought to disinhibit neighboring excitatory neurons, suggesting facilitated hippocampal access. In contrast, in area 36 pOFC axons were associated with dendrites of calbindin neurons, which are poised to reduce noise and enhance signal. In the deep layers, both pathways innervated mostly dendrites of parvalbumin neurons, which strongly inhibit neighboring excitatory neurons, suggesting gating of hippocampal output to other cortices. These findings suggest that the ACC, associated with attention and context, and the pOFC, associated with emotional valuation, have distinct contributions to memory in rhinal cortices, in processes that are disrupted in psychiatric diseases. Copyright © 2013 Wiley Periodicals, Inc.

  8. Deep Learning in Open Source Learning Streams

    DEFF Research Database (Denmark)

    Kjærgaard, Thomas

    2016-01-01

    This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...

  9. Deep learning in medical imaging: General overview

    Energy Technology Data Exchange (ETDEWEB)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)

    2017-08-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  10. Deep-seated sarcomas of the penis

    Directory of Open Access Journals (Sweden)

    Alberto A. Antunes

    2005-06-01

    Full Text Available Mesenchymal neoplasias represent 5% of tumors affecting the penis. Due to the rarity of such tumors, there is no agreement concerning the best method for staging and managing these patients. Sarcomas of the penis can be classified as deep-seated if they derive from the structures forming the spongy body and the cavernous bodies. Superficial lesions are usually low-grade and show a small tendency towards distant metastasis. In contrast, deep-seated lesions usually show behavior that is more aggressive and have poorer prognosis. The authors report 3 cases of deep-seated primary sarcomas of the penis and review the literature on this rare and aggressive neoplasia.

  11. Strategic Technologies for Deep Space Transport

    Science.gov (United States)

    Litchford, Ronald J.

    2016-01-01

    Deep space transportation capability for science and exploration is fundamentally limited by available propulsion technologies. Traditional chemical systems are performance plateaued and require enormous Initial Mass in Low Earth Orbit (IMLEO) whereas solar electric propulsion systems are power limited and unable to execute rapid transits. Nuclear based propulsion and alternative energetic methods, on the other hand, represent potential avenues, perhaps the only viable avenues, to high specific power space transport evincing reduced trip time, reduced IMLEO, and expanded deep space reach. Here, key deep space transport mission capability objectives are reviewed in relation to STMD technology portfolio needs, and the advanced propulsion technology solution landscape is examined including open questions, technical challenges, and developmental prospects. Options for potential future investment across the full compliment of STMD programs are presented based on an informed awareness of complimentary activities in industry, academia, OGAs, and NASA mission directorates.

  12. Deep learning in medical imaging: General overview

    International Nuclear Information System (INIS)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging

  13. Deep learning for SAR image formation

    Science.gov (United States)

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  14. 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.)

  15. In Brief: Deep-sea observatory

    Science.gov (United States)

    Showstack, Randy

    2008-11-01

    The first deep-sea ocean observatory offshore of the continental United States has begun operating in the waters off central California. The remotely operated Monterey Accelerated Research System (MARS) will allow scientists to monitor the deep sea continuously. Among the first devices to be hooked up to the observatory are instruments to monitor earthquakes, videotape deep-sea animals, and study the effects of acidification on seafloor animals. ``Some day we may look back at the first packets of data streaming in from the MARS observatory as the equivalent of those first words spoken by Alexander Graham Bell: `Watson, come here, I need you!','' commented Marcia McNutt, president and CEO of the Monterey Bay Aquarium Research Institute, which coordinated construction of the observatory. For more information, see http://www.mbari.org/news/news_releases/2008/mars-live/mars-live.html.

  16. 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.

  17. Deep Learning in Medical Imaging: General Overview

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging. PMID:28670152

  18. 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.

  19. Pathways to deep decarbonization - Interim 2014 Report

    International Nuclear Information System (INIS)

    2014-01-01

    The interim 2014 report by the Deep Decarbonization Pathways Project (DDPP), coordinated and published by IDDRI and the Sustainable Development Solutions Network (SDSN), presents preliminary findings of the pathways developed by the DDPP Country Research Teams with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C. The DDPP is a knowledge network comprising 15 Country Research Teams and several Partner Organizations who develop and share methods, assumptions, and findings related to deep decarbonization. Each DDPP Country Research Team has developed an illustrative road-map for the transition to a low-carbon economy, with the intent of taking into account national socio-economic conditions, development aspirations, infrastructure stocks, resource endowments, and other relevant factors. The interim 2014 report focuses on technically feasible pathways to deep decarbonization

  20. Excess plutonium disposition: The deep borehole option

    International Nuclear Information System (INIS)

    Ferguson, K.L.

    1994-01-01

    This report reviews the current status of technologies required for the disposition of plutonium in Very Deep Holes (VDH). It is in response to a recent National Academy of Sciences (NAS) report which addressed the management of excess weapons plutonium and recommended three approaches to the ultimate disposition of excess plutonium: (1) fabrication and use as a fuel in existing or modified reactors in a once-through cycle, (2) vitrification with high-level radioactive waste for repository disposition, (3) burial in deep boreholes. As indicated in the NAS report, substantial effort would be required to address the broad range of issues related to deep bore-hole emplacement. Subjects reviewed in this report include geology and hydrology, design and engineering, safety and licensing, policy decisions that can impact the viability of the concept, and applicable international programs. Key technical areas that would require attention should decisions be made to further develop the borehole emplacement option are identified

  1. Deep Learning in Medical Imaging: General Overview.

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae; Seo, Joon Beom; Kim, Namkug

    2017-01-01

    The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  2. Jetting from impact of a spherical drop with a deep layer

    Science.gov (United States)

    Zhang, Li; Toole, Jameson; Fazzaa, Kamel; Deegan, Robert; Deegan Group Team; X-Ray Science Division, Advanced Photon Source Collaboration

    2011-11-01

    We performed an experimental study of jets during the impact of a spherical drop with a deep layer of same liquid. Using high speed optical and X-ray imaging, we observe two types of jets: the so-called ejecta sheet which emerges almost immediately after impact and the lamella which emerges later. For high Reynolds number the two jets are distinct, while for low Reynolds number the two jets combine into a single continuous jet. We also measured the emergence time, speed, and position of the ejecta sheet and found simple scaling relations for these quantities.

  3. The ‘French exception’: the right to continuous deep sedation at the end of life

    Science.gov (United States)

    Horn, Ruth

    2018-01-01

    In 2016, a law came into force in France granting terminally ill patients the right to continuous deep sedation (CDS) until death. This right was proposed as an alternative to euthanasia and presented as the ‘French response’ to problems at the end of life. The law draws a distinction between CDS and euthanasia and other forms of sympton control at the end of life. France is the first country in the world to legislate on CDS. This short report describes the particular context and underlying social values that led to this piece of legislation, and explores its meaning in the wider French context. PMID:29056584

  4. Stable isotope geochemistry of deep sea cherts

    Energy Technology Data Exchange (ETDEWEB)

    Kolodny, Y; Epstein, S [California Inst. of Tech., Pasadena (USA). Div. of Geological Sciences

    1976-10-01

    Seventy four samples of DSDP (Deep Sea Drilling Project) recovered cherts of Jurassic to Miocene age from varying locations, and 27 samples of on-land exposed cherts were analyzed for the isotopic composition of their oxygen and hydrogen. These studies were accompanied by mineralogical analyses and some isotopic analyses of the coexisting carbonates. delta/sup 18/0 of chert ranges between 27 and 39 parts per thousand relative to SMOW, delta/sup 18/0 of porcellanite - between 30 and 42 parts per thousand. The consistent enrichment of opal-CT in porcellanites in /sup 18/0 with respect to coexisting microcrystalline quartz in chert is probably a reflection of a different temperature (depth) of diagenesis of the two phases. delta/sup 18/0 of deep sea cherts generally decrease with increasing age, indicating an overall cooling of the ocean bottom during the last 150 m.y. A comparison of this trend with that recorded by benthonic foraminifera (Douglas et al., Initial Reports of the Deep Sea Drilling Project; 32:509(1975)) indicates the possibility of delta/sup 18/0 in deep sea cherts not being frozen in until several tens of millions of years after deposition. Cherts of any Age show a spread of delta/sup 18/0 values, increasing diagenesis being reflected in a lowering of delta/sup 18/0. Drusy quartz has the lowest delta/sup 18/0 values. On land exposed cherts are consistently depleted in /sup 18/0 in comparison to their deep sea time equivalent cherts. Water extracted from deep sea cherts ranges between 0.5 and 1.4 wt%. deltaD of this water ranges between -78 and -95 parts per thousand and is not a function of delta/sup 18/0 of the cherts (or the temperature of their formation).

  5. Neural correlates of the food/non-food visual distinction.

    Science.gov (United States)

    Tsourides, Kleovoulos; Shariat, Shahriar; Nejati, Hossein; Gandhi, Tapan K; Cardinaux, Annie; Simons, Christopher T; Cheung, Ngai-Man; Pavlovic, Vladimir; Sinha, Pawan

    2016-03-01

    An evolutionarily ancient skill we possess is the ability to distinguish between food and non-food. Our goal here is to identify the neural correlates of visually driven 'edible-inedible' perceptual distinction. We also investigate correlates of the finer-grained likability assessment. Our stimuli depicted food or non-food items with sub-classes of appealing or unappealing exemplars. Using data-classification techniques drawn from machine-learning, as well as evoked-response analyses, we sought to determine whether these four classes of stimuli could be distinguished based on the patterns of brain activity they elicited. Subjects viewed 200 images while in a MEG scanner. Our analyses yielded two successes and a surprising failure. The food/non-food distinction had a robust neural counterpart and emerged as early as 85 ms post-stimulus onset. The likable/non-likable distinction too was evident in the neural signals when food and non-food stimuli were grouped together, or when only the non-food stimuli were included in the analyses. However, we were unable to identify any neural correlates of this distinction when limiting the analyses only to food stimuli. Taken together, these positive and negative results further our understanding of the substrates of a set of ecologically important judgments and have clinical implications for conditions like eating-disorders and anhedonia. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Magnetic mirror fusion systems: Characteristics and distinctive features

    International Nuclear Information System (INIS)

    Post, R.F.

    1987-01-01

    A tutorial account is given of the main characteristics and distinctive features of conceptual magnetic fusion systems employing the magnetic mirror principle. These features are related to the potential advantages that mirror-based fusion systems may exhibit for the generation of economic fusion power

  7. Visual Distinctiveness and the Development of Children's False Memories

    Science.gov (United States)

    Howe, Mark L.

    2008-01-01

    Distinctiveness effects in children's (5-, 7-, and 11-year-olds) false memory illusions were examined using visual materials. In Experiment 1, developmental trends (increasing false memories with age) were obtained using Deese-Roediger-McDermott lists presented as words and color photographs but not line drawings. In Experiment 2, when items were…

  8. Effectiveness, Improvement and Educational Change: A Distinctively Canadian Approach?

    Science.gov (United States)

    Hargreaves, Andy; Fink, Dean

    1998-01-01

    A distinctive Canadian school of thought on educational change is inclined to synthesize diverse bodies of work and integrate nonrational and emotional dimensions with rational and technically effective ones in a socially critical way. Highlights the Canadian perspective through discussions about complex systems, contexts of change, critical…

  9. Distinct patterns of epigenetic marks and transcription factor binding ...

    Indian Academy of Sciences (India)

    Distinct patterns of epigenetic marks and transcription factor binding sites across promoters of sense-intronic long noncoding RNAs. Sourav Ghosh, Satish Sati, Shantanu Sengupta and Vinod Scaria. J. Genet. 94, 17–25. Gencode V9 lncRNA gene : 11004. Known lncRNA : 1175. Novel lncRNA : 5898. Putative lncRNA :.

  10. Genetic Determinism and the Innate-Acquired Distinction in Medicine

    Science.gov (United States)

    2009-01-01

    This article illustrates in which sense genetic determinism is still part of the contemporary interactionist consensus in medicine. Three dimensions of this consensus are discussed: kinds of causes, a continuum of traits ranging from monogenetic diseases to car accidents, and different kinds of determination due to different norms of reaction. On this basis, this article explicates in which sense the interactionist consensus presupposes the innate–acquired distinction. After a descriptive Part 1, Part 2 reviews why the innate–acquired distinction is under attack in contemporary philosophy of biology. Three arguments are then presented to provide a limited and pragmatic defense of the distinction: an epistemic, a conceptual, and a historical argument. If interpreted in a certain manner, and if the pragmatic goals of prevention and treatment (ideally specifying what medicine and health care is all about) are taken into account, then the innate–acquired distinction can be a useful epistemic tool. It can help, first, to understand that genetic determination does not mean fatalism, and, second, to maintain a system of checks and balances in the continuing nature–nurture debates. PMID:20234831

  11. Amnesia, rehearsal, and temporal distinctiveness models of recall.

    Science.gov (United States)

    Brown, Gordon D A; Della Sala, Sergio; Foster, Jonathan K; Vousden, Janet I

    2007-04-01

    Classical amnesia involves selective memory impairment for temporally distant items in free recall (impaired primacy) together with relative preservation of memory for recency items. This abnormal serial position curve is traditionally taken as evidence for a distinction between different memory processes, with amnesia being associated with selectively impaired long-term memory. However recent accounts of normal serial position curves have emphasized the importance of rehearsal processes in giving rise to primacy effects and have suggested that a single temporal distinctiveness mechanism can account for both primacy and recency effects when rehearsal is considered. Here we explore the pattern of strategic rehearsal in a patient with very severe amnesia. When the patient's rehearsal pattern is taken into account, a temporal distinctiveness model can account for the serial position curve in both amnesic and control free recall. The results are taken as consistent with temporal distinctiveness models of free recall, and they motivate an emphasis on rehearsal patterns in understanding amnesic deficits in free recall.

  12. Are there distinctive indigenous methods of inquiry? | Le Grange ...

    African Journals Online (AJOL)

    This article explores whether there are methods that might be referred to as being distinctly indigenous. In doing so the nature of method is examined and it is concluded that method is not universal and neutral, but rather situated and performative. The upshot of this is that research methods can be transformed and that ...

  13. Blurring Boundaries : Carnap, Quine, and the Internal-External Distinction

    NARCIS (Netherlands)

    Verhaegh, Sander

    Quine is routinely perceived as saving metaphysics from Carnapian positivism. Where Carnap rejects metaphysical existence claims as meaningless, Quine is taken to restore their intelligibility by dismantling the former's internal-external distinction. The problem with this picture, however, is that

  14. 48 CFR 307.7001 - Distinction between acquisition and assistance.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Distinction between acquisition and assistance. 307.7001 Section 307.7001 Federal Acquisition Regulations System HEALTH AND HUMAN... barter, of property or services for the direct benefit or use of the Government; or (2) Government...

  15. MAGDM linear-programming models with distinct uncertain preference structures.

    Science.gov (United States)

    Xu, Zeshui S; Chen, Jian

    2008-10-01

    Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

  16. Differential Recruitment of Distinct Amygdalar Nuclei across Appetitive Associative Learning

    Science.gov (United States)

    Cole, Sindy; Powell, Daniel J.; Petrovich, Gorica D.

    2013-01-01

    The amygdala is important for reward-associated learning, but how distinct cell groups within this heterogeneous structure are recruited during appetitive learning is unclear. Here we used Fos induction to map the functional amygdalar circuitry recruited during early and late training sessions of Pavlovian appetitive conditioning. We found that a…

  17. An Objective Approach to Identify Spectral Distinctiveness for Hearing Impairment

    Directory of Open Access Journals (Sweden)

    Yeou-Jiunn Chen

    2013-01-01

    Full Text Available To facilitate the process of developing speech perception, speech-language pathologists have to teach a subject with hearing loss the differences between two syllables by manually enhancing acoustic cues of speech. However, this process is time consuming and difficult. Thus, this study proposes an objective approach to automatically identify the regions of spectral distinctiveness between two syllables, which is used for speech-perception training. To accurately represent the characteristics of speech, mel-frequency cepstrum coefficients are selected as analytical parameters. The mismatch between two syllables in time domain is handled by dynamic time warping. Further, a filter bank is adopted to estimate the components in different frequency bands, which are also represented as mel-frequency cepstrum coefficients. The spectral distinctiveness in different frequency bands is then easily estimated by using Euclidean metrics. Finally, a morphological gradient operator is applied to automatically identify the regions of spectral distinctiveness. To evaluate the proposed approach, the identified regions are manipulated and then the manipulated syllables are measured by a close-set based speech-perception test. The experimental results demonstrated that the identified regions of spectral distinctiveness are very useful in speech perception, which indeed can help speech-language pathologists in speech-perception training.

  18. Distinctiveness and Bidirectional Effects in Input Enhancement for Vocabulary Learning

    Science.gov (United States)

    Barcroft, Joe

    2003-01-01

    This study examined input enhancement and second language (L2) vocabulary learning while exploring the role of "distinctiveness," the degree to which an item in the input diverges from the form in which other items in the input are presented, with regard to the nature and direction of the effects of enhancement. In this study,…

  19. BMP signalling differentially regulates distinct haematopoietic stem cell types

    NARCIS (Netherlands)

    M. Crisan (Mihaela); P. Solaimani Kartalaei (Parham); C.S. Vink (Chris); T. Yamada-Inagawa (Tomoko); K. Bollerot (Karine); W.F.J. van IJcken (Wilfred); R. Van Der Linden (Reinier); S.C. de Sousa Lopes (Susana Chuva); R. Monteiro (Rui); C.L. Mummery (Christine); E.A. Dzierzak (Elaine)

    2015-01-01

    textabstractAdult haematopoiesis is the outcome of distinct haematopoietic stem cell (HSC) subtypes with self-renewable repopulating ability, but with different haematopoietic cell lineage outputs. The molecular basis for this heterogeneity is largely unknown. BMP signalling regulates HSCs as they

  20. Deep Space Detection of Oriented Ice Crystals

    Science.gov (United States)

    Marshak, A.; Varnai, T.; Kostinski, A. B.

    2017-12-01

    The deep space climate observatory (DSCOVR) spacecraft resides at the first Lagrangian point about one million miles from Earth. A polychromatic imaging camera onboard delivers nearly hourly observations of the entire sun-lit face of the Earth. Many images contain unexpected bright flashes of light over both ocean and land. We constructed a yearlong time series of flash latitudes, scattering angles and oxygen absorption to demonstrate conclusively that the flashes over land are specular reflections off tiny ice crystals floating in the air nearly horizontally. Such deep space detection of tropospheric ice can be used to constrain the likelihood of oriented crystals and their contribution to Earth albedo.

  1. A clinical study on deep neck abscess

    International Nuclear Information System (INIS)

    Ota, Yumi; Ogawa, Yoshiko; Takemura, Teiji; Sawada, Toru

    2007-01-01

    Although various effective antibiotics have been synthesized, deep neck abscess is still a serious and life-threatening infection. It is important to diagnose promptly and treat adequately, and contrast-enhanced CT is useful and indispensable for diagnosis. We reviewed our patients with deep neck abscess, and analyzed the location by reviewing CT images, and discussed the treatment. Surgical drainage is a fundamental treatment for abscess but if it exists in only one area such as the parotid gland space, it can be cured with needle aspiration and suitable antibiotics. (author)

  2. Approximate Inference and Deep Generative Models

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I'll review a few standard methods for approximate inference and introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models. Finally, I'll demonstrate several important application of these models to density estimation, missing data imputation, data compression and planning.

  3. Deep Belief Nets for Topic Modeling

    DEFF Research Database (Denmark)

    Maaløe, Lars; Arngren, Morten; Winther, Ole

    2015-01-01

    -formative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To solve the digital publishing recommender problem we compare two approaches: latent Dirichlet allocation (LDA) and deep be-lief nets (DBN) that both find low-dimensional latent representations for documents....... Efficient retrieval can be carried out in the latent representation. We work both on public benchmarks and digital media content provided by Issuu, an on-line publishing platform. This article also comes with a newly developed deep belief nets toolbox for topic modeling tailored towards performance...

  4. Un paseo por la Deep Web

    OpenAIRE

    Ortega Castillo, Carlos

    2018-01-01

    Este documento busca presentar una mirada técnica e inclusiva a algunas de las tecnologías de interconexión desarrolladas en la DeepWeb, primero desde un punto de vista teórico y después con una breve introducción práctica. La desmitificación de los procesos desarrollados bajo la DeepWeb, brinda herramientas a los usuarios para esclarecer y construir nuevos paradigmas de sociedad, conocimiento y tecnología que aporten al desarrollo responsable de este tipo de redes y contribuyan al crecimi...

  5. Deep fracturation of granitic rock mass

    International Nuclear Information System (INIS)

    Bles, J.L.; Blanchin, R.; Bonijoly, D.; Dutartre, P.; Feybesse, J.L.; Gros, Y.; Landry, J.; Martin, P.

    1986-01-01

    This documentary study realized with the financial support of the European Communities and the CEA aims at the utilization of available data for the understanding of the evolution of natural fractures in granitic rocks from the surface to deep underground, in various feasibility studies dealing with radioactive wastes disposal. The Mont Blanc road tunnel, the EDF Arc-Isere gallerie, the Auriat deep borehole and the Pyrenean rock mass of Bassies are studied. In this study are more particularly analyzed the relationship between small fractures and large faults, evolution with depth of fracture density and direction, consequences of rock decompression and relationship between fracturation and groundwater [fr

  6. Gamma-rays from deep inelastic collisions

    International Nuclear Information System (INIS)

    Stephens, F.S.

    1979-01-01

    The γ-rays associated with deep inelastic collisions can give information about the magnitude and orientation of the angular momentum transferred in these events. In this review, special emphasis is placed on understanding the origin and nature of these γ-rays in order to avoid some of the ambiguities that can arise. The experimental information coming from these γ-ray studies is reviewed, and compared briefly with that obtained by other methods and also with the expectations from current models for deep inelastic collisions. 15 figures

  7. Fractal measures in a deep penetration problem

    International Nuclear Information System (INIS)

    Murthy, K.P.N.; Indira, R.; John, T.M.

    1993-01-01

    In the Monte Carlo simulation of a deep penetration problem the parameter, say b in the importance function must be assigned a value b' such that variance is minimum. If b b' the sample mean is still not reliable; but the sample fluctuations would be small and misleading, though the actual fluctuations are quite large. This is because the distribution of transmission has a tail which becomes prominent when b > b'. Considering a model deep penetration problem, and employing exact enumeration techniques, it is shown that in the limit of large biasing the long tailed distribution to the transmission is multifractal. (author). 5 refs., 3 figs

  8. La deep web : el mercado negro global

    OpenAIRE

    Gay Fernández, José

    2015-01-01

    La deep web es un espacio oculto de internet donde la primera garantía es el anonimato. En líneas generales, la deep web contiene todo aquello que los buscadores convencionales no pueden localizar. Esta garantía sirve para albergar una vasta red de servicios ilegales, como el narcotráfico, la trata de blancas, la contratación de sicarios, la compra-venta de pasaportes y cuentas bancarias, o la pornografía infantil, entre otros muchos. Pero el anonimato también posibilita que activ...

  9. 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.

  10. Nuclear structure in deep-inelastic reactions

    International Nuclear Information System (INIS)

    Rehm, K.E.

    1986-01-01

    The paper concentrates on recent deep inelastic experiments conducted at Argonne National Laboratory and the nuclear structure effects evident in reactions between super heavy nuclei. Experiments indicate that these reactions evolve gradually from simple transfer processes which have been studied extensively for lighter nuclei such as 16 O, suggesting a theoretical approach connecting the one-step DWBA theory to the multistep statistical models of nuclear reactions. This transition between quasi-elastic and deep inelastic reactions is achieved by a simple random walk model. Some typical examples of nuclear structure effects are shown. 24 refs., 9 figs

  11. Deep Learning For Sequential Pattern Recognition

    OpenAIRE

    Safari, Pooyan

    2013-01-01

    Projecte realitzat en el marc d’un programa de mobilitat amb la Technische Universität München (TUM) In recent years, deep learning has opened a new research line in pattern recognition tasks. It has been hypothesized that this kind of learning would capture more abstract patterns concealed in data. It is motivated by the new findings both in biological aspects of the brain and hardware developments which have made the parallel processing possible. Deep learning methods come along with ...

  12. 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

  13. An Adult Developmental Approach to Perceived Facial Attractiveness and Distinctiveness

    Directory of Open Access Journals (Sweden)

    Natalie C. Ebner

    2018-05-01

    Full Text Available Attractiveness and distinctiveness constitute facial features with high biological and social relevance. Bringing a developmental perspective to research on social-cognitive face perception, we used a large set of faces taken from the FACES Lifespan Database to examine effects of face and perceiver characteristics on subjective evaluations of attractiveness and distinctiveness in young (20–31 years, middle-aged (44–55 years, and older (70–81 years men and women. We report novel findings supporting variations by face and perceiver age, in interaction with gender and emotion: although older and middle-aged compared to young perceivers generally rated faces of all ages as more attractive, young perceivers gave relatively higher attractiveness ratings to young compared to middle-aged and older faces. Controlling for variations in attractiveness, older compared to young faces were viewed as more distinctive by young and middle-aged perceivers. Age affected attractiveness more negatively for female than male faces. Furthermore, happy faces were rated as most attractive, while disgusted faces were rated as least attractive, particularly so by middle-aged and older perceivers and for young and female faces. Perceivers largely agreed on distinctiveness ratings for neutral and happy emotions, but older and middle-aged compared to young perceivers rated faces displaying negative emotions as more distinctive. These findings underscore the importance of a lifespan perspective on perception of facial characteristics and suggest possible effects of age on goal-directed perception, social motivation, and in-group bias. This publication makes available picture-specific normative data for experimental stimulus selection.

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

    Science.gov (United States)

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

    2018-04-01

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

  15. 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.

  16. DeepBipolar: Identifying genomic mutations for bipolar disorder via deep learning.

    Science.gov (United States)

    Laksshman, Sundaram; Bhat, Rajendra Rana; Viswanath, Vivek; Li, Xiaolin

    2017-09-01

    Bipolar disorder, also known as manic depression, is a brain disorder that affects the brain structure of a patient. It results in extreme mood swings, severe states of depression, and overexcitement simultaneously. It is estimated that roughly 3% of the population of the United States (about 5.3 million adults) suffers from bipolar disorder. Recent research efforts like the Twin studies have demonstrated a high heritability factor for the disorder, making genomics a viable alternative for detecting and treating bipolar disorder, in addition to the conventional lengthy and costly postsymptom clinical diagnosis. Motivated by this study, leveraging several emerging deep learning algorithms, we design an end-to-end deep learning architecture (called DeepBipolar) to predict bipolar disorder based on limited genomic data. DeepBipolar adopts the Deep Convolutional Neural Network (DCNN) architecture that automatically extracts features from genotype information to predict the bipolar phenotype. We participated in the Critical Assessment of Genome Interpretation (CAGI) bipolar disorder challenge and DeepBipolar was considered the most successful by the independent assessor. In this work, we thoroughly evaluate the performance of DeepBipolar and analyze the type of signals we believe could have affected the classifier in distinguishing the case samples from the control set. © 2017 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2016-09-01

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

  18. Determination of deep-level impurities and their effects on the small-single and LF noise properties of ion-implanted GaAs MESFETs

    International Nuclear Information System (INIS)

    Sriram, S.; Kim, B.; Ghosh, P.K.; Das, M.B.; Pennsylvania State Univ., University Park; Pennsylvania State Univ., University Park

    1982-01-01

    A large number of deep levels, with energies ranging from Esub(c)-0.19eV to Esub(c)-0.9eV, have been identified and characterized using ion-implanted MESFET's on undoped and Cr-doped LEC-grown semi-insulating GaAs substrates. Measurement techniques used include deep level transient (DLTS) and steady state spectroscopic (DLSS) methods. Large capture cross-section values are obtained for levels below Esub(c)-0.5eV, possibly due to high electric field. Spectral densities of LF noise with distinct bulges have been shown to be related to deep levels. In some samples, natural deep level related oscillations have been observed and their ionization energies have been determined. (author)

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

    Science.gov (United States)

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

    2016-12-05

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

  20. 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.

  1. Fine-grained leukocyte classification with deep residual learning for microscopic images.

    Science.gov (United States)

    Qin, Feiwei; Gao, Nannan; Peng, Yong; Wu, Zizhao; Shen, Shuying; Grudtsin, Artur

    2018-08-01

    Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories. Based on deep learning theory, a systematic study is conducted on finer leukocyte classification in this paper. A deep residual neural network based leukocyte classifier is constructed at first, which can imitate the domain expert's cell recognition process, and extract salient features robustly and automatically. Then the deep neural network classifier's topology is adjusted according to the prior knowledge of white blood cell test. After that the microscopic image dataset with almost one hundred thousand labeled leukocytes belonging to 40 categories is built, and combined training strategies are adopted to make the designed classifier has good generalization ability. The proposed deep residual neural network based classifier was tested on microscopic image dataset with 40 leukocyte categories. It achieves top-1 accuracy of 77.80%, top-5 accuracy of 98.75% during the training procedure. The average accuracy on the test set is nearly 76.84%. This paper presents a fine-grained leukocyte classification method for microscopic images, based on deep residual learning theory and medical domain knowledge. Experimental results validate the feasibility and effectiveness of our approach. Extended experiments support that the fine-grained leukocyte classifier could be used in real medical applications, assist doctors in diagnosing diseases, reduce human power significantly. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Neuronal pathology in deep grey matter structures: a multimodal imaging analysis combining PET and MRI

    Energy Technology Data Exchange (ETDEWEB)

    Bosque-Freeman, L.; Leroy, C.; Galanaud, D.; Sureau, F.; Assouad, R.; Tourbah, A.; Papeix, C.; Comtat, C.; Trebossen, R.; Lubetzki, C.; Delforge, J.; Bottlaender, M.; Stankoff, B. [Serv. Hosp. Frederic Joliot, Orsay (France)

    2009-07-01

    Objective: To assess neuronal damage in deep gray matter structures by positron emission tomography (PET) using [{sup 11}C]-flumazenil (FMZ), a specific central benzodiazepine receptor antagonist, and [{sup 18}F]-fluorodeoxyglucose (FDG), which reflects neuronal metabolism. To compare results obtained by PET and those with multimodal magnetic resonance imaging (MRI). Background: It is now accepted that neuronal injury plays a crucial role in the occurrence and progression of neurological disability in multiple sclerosis (MS). To date, available MRI techniques do not specifically assess neuronal damage, but early abnormalities, such as iron deposition or atrophy, have been described in deep gray matter structures. Whether those MRI modifications correspond to neuronal damage remains to be further investigated. Materials and methods: Nine healthy volunteers were compared to 10 progressive and 9 relapsing remitting (RR) MS patients. Each subject performed two PET examinations with [{sup 11}C]-FMZ and [{sup 18}F]-FDG, on a high resolution research tomograph dedicated to brain imaging (Siemens Medical Solution, spatial resolution of 2.5 mm). Deep gray matter regions were manually segmented on T1-weighted MR images with the mutual information algorithm (www.brainvisa.info), and co-registered with PET images. A multimodal MRI including T1 pre and post gadolinium, T2-proton density sequences, magnetization transfer, diffusion tensor, and protonic spectroscopy was also performed for each subject. Results: On PET with [{sup 11}C]-FMZ, there was a pronounced decrease in receptor density for RR patients in all deep gray matter structures investigated, whereas the density was unchanged or even increased in the same regions for progressive patients. Whether the different patterns between RR and progressive patients reflect distinct pathogenic mechanisms is currently investigated by comparing PET and multimodal MRI results. Conclusion: Combination of PET and multimodal MR imaging

  3. Abrupt pre-Bølling-Allerød warming and circulation changes in the deep ocean.

    Science.gov (United States)

    Thiagarajan, Nivedita; Subhas, Adam V; Southon, John R; Eiler, John M; Adkins, Jess F

    2014-07-03

    Several large and rapid changes in atmospheric temperature and the partial pressure of carbon dioxide in the atmosphere--probably linked to changes in deep ocean circulation--occurred during the last deglaciation. The abrupt temperature rise in the Northern Hemisphere and the restart of the Atlantic meridional overturning circulation at the start of the Bølling-Allerød interstadial, 14,700 years ago, are among the most dramatic deglacial events, but their underlying physical causes are not known. Here we show that the release of heat from warm waters in the deep North Atlantic Ocean probably triggered the Bølling-Allerød warming and reinvigoration of the Atlantic meridional overturning circulation. Our results are based on coupled radiocarbon and uranium-series dates, along with clumped isotope temperature estimates, from water column profiles of fossil deep-sea corals in a limited area of the western North Atlantic. We find that during Heinrich stadial 1 (the cool period immediately before the Bølling-Allerød interstadial), the deep ocean was about three degrees Celsius warmer than shallower waters above. This reversal of the ocean's usual thermal stratification pre-dates the Bølling-Allerød warming and must have been associated with increased salinity at depth to preserve the static stability of the water column. The depleted radiocarbon content of the warm and salty water mass implies a long-term disconnect from rapid surface exchanges, and, although uncertainties remain, is most consistent with a Southern Ocean source. The Heinrich stadial 1 ocean profile is distinct from the modern water column, that for the Last Glacial Maximum and that for the Younger Dryas, suggesting that the patterns we observe are a unique feature of the deglacial climate system. Our observations indicate that the deep ocean influenced dramatic Northern Hemisphere warming by storing heat at depth that preconditioned the system for a subsequent abrupt overturning event during the

  4. Directed networks' different link formation mechanisms causing degree distribution distinction

    Science.gov (United States)

    Behfar, Stefan Kambiz; Turkina, Ekaterina; Cohendet, Patrick; Burger-Helmchen, Thierry

    2016-11-01

    Within undirected networks, scientists have shown much interest in presenting power-law features. For instance, Barabási and Albert (1999) claimed that a common property of many large networks is that vertex connectivity follows scale-free power-law distribution, and in another study Barabási et al. (2002) showed power law evolution in the social network of scientific collaboration. At the same time, Jiang et al. (2011) discussed deviation from power-law distribution; others indicated that size effect (Bagrow et al., 2008), information filtering mechanism (Mossa et al., 2002), and birth and death process (Shi et al., 2005) could account for this deviation. Within directed networks, many authors have considered that outlinks follow a similar mechanism of creation as inlinks' (Faloutsos et al., 1999; Krapivsky et al., 2001; Tanimoto, 2009) with link creation rate being the linear function of node degree, resulting in a power-law shape for both indegree and outdegree distribution. Some other authors have made an assumption that directed networks, such as scientific collaboration or citation, behave as undirected, resulting in a power-law degree distribution accordingly (Barabási et al., 2002). At the same time, we claim (1) Outlinks feature different degree distributions than inlinks; where different link formation mechanisms cause the distribution distinctions, (2) in/outdegree distribution distinction holds for different levels of system decomposition; therefore this distribution distinction is a property of directed networks. First, we emphasize in/outlink formation mechanisms as causal factors for distinction between indegree and outdegree distributions (where this distinction has already been noticed in Barker et al. (2010) and Baxter et al. (2006)) within a sample network of OSS projects as well as Java software corpus as a network. Second, we analyze whether this distribution distinction holds for different levels of system decomposition: open

  5. Deep sedation during pneumatic reduction of intussusception.

    Science.gov (United States)

    Ilivitzki, Anat; Shtark, Luda Glozman; Arish, Karin; Engel, Ahuva

    2012-05-01

    Pneumatic reduction of intussusception under fluoroscopic guidance is a routine procedure. The unsedated child may resist the procedure, which may lengthen its duration and increase the radiation dose. We use deep sedation during the procedure to overcome these difficulties. The purpose of this study was to summarize our experience with deep sedation during fluoroscopic reduction of intussusception and assess the added value and complication rate of deep sedation. All children with intussusception who underwent pneumatic reduction in our hospital between January 2004 and June 2011 were included in this retrospective study. Anesthetists sedated the children using propofol. The fluoroscopic studies, ultrasound (US) studies and the childrens' charts were reviewed. One hundred thirty-one attempted reductions were performed in 119 children, of which 121 (92%) were successful and 10 (8%) failed. Two perforations (1.5%) occurred during attempted reduction. Average fluoroscopic time was 1.5 minutes. No complication to sedation was recorded. Deep sedation with propofol did not add any complication to the pneumatic reduction. The fluoroscopic time was short. The success rate of reduction was high,raising the possibility that sedation is beneficial, possibly by smooth muscle relaxation.

  6. Evaluation of Deep Discount Fare Strategies

    Science.gov (United States)

    1995-08-01

    This report evaluates the success of a fare pricing strategy known as deep discounting, that entails the bulk sale of transit tickets or tokens to customers at a significant discount compared to the full fare single ticket price. This market-driven s...

  7. Parity violation in deep inelastic scattering

    Energy Technology Data Exchange (ETDEWEB)

    Souder, P. [Syracuse Univ., NY (United States)

    1994-04-01

    AA beam of polarized electrons at CEBAF with an energy of 8 GeV or more will be useful for performing precision measurements of parity violation in deep inelastic scattering. Possible applications include precision tests of the Standard Model, model-independent measurements of parton distribution functions, and studies of quark correlations.

  8. Into the depths of deep eutectic solvents

    NARCIS (Netherlands)

    Rodriguez, N.; Alves da Rocha, M.A.; Kroon, M.C.

    2015-01-01

    Ionic liquids (ILs) have been successfully tested in a wide range of applications; however, their high price and complicated synthesis make them infeasible for large scale implementation. A decade ago, a new generation of solvents so called deep eutectic solvents (DESs) was reported for the first

  9. Modern problems of deep processing of coal

    International Nuclear Information System (INIS)

    Ismagilov, Z.R.

    2013-01-01

    Present article is devoted to modern problems of deep processing of coal. The history and development of new Institute of Coal Chemistry and Material Sciences of Siberian Branch of Russian Academy of Science was described. The aims and purposes of new institute were discussed.

  10. Case Studies and Monitoring of Deep Excavations

    NARCIS (Netherlands)

    Korff, M.

    2017-01-01

    Several case histories from Dutch underground deep excavation projects are presented in this paper, including the lessons learned and the learning processes involved. The focus of the paper is on how the learning takes places and how it is documented. It is necessary to learn in a systematic and

  11. Performance of deep geothermal energy systems

    Science.gov (United States)

    Manikonda, Nikhil

    Geothermal energy is an important source of clean and renewable energy. This project deals with the study of deep geothermal power plants for the generation of electricity. The design involves the extraction of heat from the Earth and its conversion into electricity. This is performed by allowing fluid deep into the Earth where it gets heated due to the surrounding rock. The fluid gets vaporized and returns to the surface in a heat pipe. Finally, the energy of the fluid is converted into electricity using turbine or organic rankine cycle (ORC). The main feature of the system is the employment of side channels to increase the amount of thermal energy extracted. A finite difference computer model is developed to solve the heat transport equation. The numerical model was employed to evaluate the performance of the design. The major goal was to optimize the output power as a function of parameters such as thermal diffusivity of the rock, depth of the main well, number and length of lateral channels. The sustainable lifetime of the system for a target output power of 2 MW has been calculated for deep geothermal systems with drilling depths of 8000 and 10000 meters, and a financial analysis has been performed to evaluate the economic feasibility of the system for a practical range of geothermal parameters. Results show promising an outlook for deep geothermal systems for practical applications.

  12. Fingerprint Minutiae Extraction using Deep Learning

    CSIR Research Space (South Africa)

    Darlow, Luke Nicholas

    2017-10-01

    Full Text Available components, such as image enhancement. We pose minutiae extraction as a machine learning problem and propose a deep neural network – MENet, for Minutiae Extraction Network – to learn a data-driven representation of minutiae points. By using the existing...

  13. Evolutionary Scheduler for the Deep Space Network

    Science.gov (United States)

    Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert

    2010-01-01

    A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

  14. Deep Water Coral (HB1402, EK60)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The cruise will survey and collect samples of deep-sea corals and related marine life in the canyons in the northern Gulf of Maine in U.S. and Canadian waters. The...

  15. Particle Production in Deep Inelastic Muon Scattering

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, John James [MIT

    1991-01-01

    The E665 spectrometer at Fermila.b measured Deep-Inelastic Scattering of 490 GeV /c muons off several targets: Hydrogen, Deuterium, and Xenon. Events were selected from the Xenon and Deuterium targets, with a range of energy exchange, $\

  16. Influence functionals in deep inelastic reactions

    International Nuclear Information System (INIS)

    Avishai, Y.

    1978-01-01

    It is suggested that the concept of influence functionals introduced by Feynman and Vernon could be applied to the study of deep inelastic reactions among heavy ions if the coupling between the relative motion and the internal degrees of freedom has a separable form as suggested by Hofmann and Siemens. (Auth.)

  17. 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.

  18. 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.

  19. Pre-cementation of deep shaft

    Science.gov (United States)

    Heinz, W. F.

    1988-12-01

    Pre-cementation or pre-grouting of deep shafts in South Africa is an established technique to improve safety and reduce water ingress during shaft sinking. The recent completion of several pre-cementation projects for shafts deeper than 1000m has once again highlighted the effectiveness of pre-grouting of shafts utilizing deep slimline boreholes and incorporating wireline technique for drilling and conventional deep borehole grouting techniques for pre-cementation. Pre-cementation of deep shaft will: (i) Increase the safety of shaft sinking operation (ii) Minimize water and gas inflow during shaft sinking (iii) Minimize the time lost due to additional grouting operations during sinking of the shaft and hence minimize costly delays and standing time of shaft sinking crews and equipment. (iv) Provide detailed information of the geology of the proposed shaft site. Informations on anomalies, dykes, faults as well as reef (gold bearing conglomerates) intersections can be obtained from the evaluation of cores of the pre-cementation boreholes. (v) Provide improved rock strength for excavations in the immediate vicinity of the shaft area. The paper describes pre-cementation techniques recently applied successfully from surface and some conclusions drawn for further considerations.

  20. Should deep seabed mining be allowed?

    NARCIS (Netherlands)

    Kim, Rak

    2017-01-01

    Abstract Commercial interest in deep sea minerals in the area beyond the limits of national jurisdiction has rapidly increased in recent years. The International Seabed Authority has already given out 26 exploration contracts and it is currently in the process of developing the Mining Code for

  1. Dust Measurements Onboard the Deep Space Gateway

    Science.gov (United States)

    Horanyi, M.; Kempf, S.; Malaspina, D.; Poppe, A.; Srama, R.; Sternovsky, Z.; Szalay, J.

    2018-02-01

    A dust instrument onboard the Deep Space Gateway will revolutionize our understanding of the dust environment at 1 AU, help our understanding of the evolution of the solar system, and improve dust hazard models for the safety of crewed and robotic missions.

  2. A quantitative lubricant test for deep drawing

    DEFF Research Database (Denmark)

    Olsson, David Dam; Bay, Niels; Andreasen, Jan L.

    2010-01-01

    A tribological test for deep drawing has been developed by which the performance of lubricants may be evaluated quantitatively measuring the maximum backstroke force on the punch owing to friction between tool and workpiece surface. The forming force is found not to give useful information...

  3. Deep underground disposal facility and the public

    International Nuclear Information System (INIS)

    Sumberova, V.

    1997-01-01

    Factors arousing public anxiety in relation to the deep burial of radioactive wastes are highlighted based on Czech and foreign analyses, and guidelines are presented to minimize public opposition when planning a geologic disposal site in the Czech Republic. (P.A.)

  4. Emotional arousal and memory after deep encoding.

    Science.gov (United States)

    Leventon, Jacqueline S; Camacho, Gabriela L; Ramos Rojas, Maria D; Ruedas, Angelica

    2018-05-22

    Emotion often enhances long-term memory. One mechanism for this enhancement is heightened arousal during encoding. However, reducing arousal, via emotion regulation (ER) instructions, has not been associated with reduced memory. In fact, the opposite pattern has been observed: stronger memory for emotional stimuli encoded with an ER instruction to reduce arousal. This pattern may be due to deeper encoding required by ER instructions. In the current research, we examine the effects of emotional arousal and deep-encoding on memory across three studies. In Study 1, adult participants completed a writing task (deep-encoding) for encoding negative, neutral, and positive picture stimuli, whereby half the emotion stimuli had the ER instruction to reduce the emotion. Memory was strong across conditions, and no memory enhancement was observed for any condition. In Study 2, adult participants completed the same writing task as Study 1, as well as a shallow-encoding task for one-third of negative, neutral, and positive trials. Memory was strongest for deep vs. shallow encoding trials, with no effects of emotion or ER instruction. In Study 3, adult participants completed a shallow-encoding task for negative, neutral, and positive stimuli, with findings indicating enhanced memory for negative emotional stimuli. Findings suggest that deep encoding must be acknowledged as a source of memory enhancement when examining manipulations of emotion-related arousal. Copyright © 2018. Published by Elsevier B.V.

  5. 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)

  6. Regulatory issues for deep borehole plutonium disposition

    International Nuclear Information System (INIS)

    Halsey, W.G.

    1995-03-01

    As a result of recent changes throughout the world, a substantial inventory of excess separated plutonium is expected to result from dismantlement of US nuclear weapons. The safe and secure management and eventual disposition of this plutonium, and of a similar inventory in Russia, is a high priority. A variety of options (both interim and permanent) are under consideration to manage this material. The permanent solutions can be categorized into two broad groups: direct disposal and utilization. The deep borehole disposition concept involves placing excess plutonium deep into old stable rock formations with little free water present. Issues of concern include the regulatory, statutory and policy status of such a facility, the availability of sites with desirable characteristics and the technologies required for drilling deep holes, characterizing them, emplacing excess plutonium and sealing the holes. This white paper discusses the regulatory issues. Regulatory issues concerning construction, operation and decommissioning of the surface facility do not appear to be controversial, with existing regulations providing adequate coverage. It is in the areas of siting, licensing and long term environmental protection that current regulations may be inappropriate. This is because many current regulations are by intent or by default specific to waste forms, facilities or missions significantly different from deep borehole disposition of excess weapons usable fissile material. It is expected that custom regulations can be evolved in the context of this mission

  7. Deep Reflection on My Pedagogical Transformations

    Science.gov (United States)

    Suzawa, Gilbert S.

    2014-01-01

    This retrospective essay contains my reflection on the deep concept of ambiguity (uncertainty) and a concomitant epistemological theory that all of our human knowledge is ultimately self-referential in nature. This new epistemological perspective is subsequently utilized as a platform for gaining insights into my experiences in conjunction with…

  8. 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,

  9. Top Tagging by Deep Learning Algorithm

    CERN Document Server

    Akil, Ali

    2015-01-01

    In this report I will show the application of a deep learning algorithm on a Monte Carlo simulation sample to test its performance in tagging hadronic decays of boosted top quarks and compare what we get with the results of the application of some other algorithms.

  10. Semantic Tagging with Deep Residual Networks

    NARCIS (Netherlands)

    Bjerva, Johannes; Plank, Barbara; Bos, Johan

    2016-01-01

    We propose a novel semantic tagging task, semtagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations and includes a novel residual bypass architecture. We evaluate

  11. Priapulus from the deep sea (Vermes, Priapulida)

    NARCIS (Netherlands)

    Land, van der J.

    1972-01-01

    INTRODUCTION The species of the genus Priapulus occur in rather cold water. Hence, their shallow-water distribution is restricted to northern and southern waters (fig. 1); there are only a few isolated records from sub-tropical localities. However, in deep water the genus apparently has a world-wide

  12. Gamma-rays from deep inelastic collisions

    International Nuclear Information System (INIS)

    Stephens, F.S.

    1981-01-01

    My objective in this talk is to consider the question: 'What can be learned about deep inelastic collisions (DIC) from studying the associated gamma-rays'. First, I discuss the origin and nature of the gamma-rays from DIC, then the kinds of information gamma-ray spectra contain, and finally come to the combination of these two subjects. (orig./HSI)

  13. Deep Support Vector Machines for Regression Problems

    NARCIS (Netherlands)

    Wiering, Marco; Schutten, Marten; Millea, Adrian; Meijster, Arnold; Schomaker, Lambertus

    2013-01-01

    In this paper we describe a novel extension of the support vector machine, called the deep support vector machine (DSVM). The original SVM has a single layer with kernel functions and is therefore a shallow model. The DSVM can use an arbitrary number of layers, in which lower-level layers contain

  14. Using Cooperative Structures to Promote Deep Learning

    Science.gov (United States)

    Millis, Barbara J.

    2014-01-01

    The author explores concrete ways to help students learn more and have fun doing it while they support each other's learning. The article specifically shows the relationships between cooperative learning and deep learning. Readers will become familiar with the tenets of cooperative learning and its power to enhance learning--even more so when…

  15. Stimulating Deep Learning Using Active Learning Techniques

    Science.gov (United States)

    Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin

    2016-01-01

    When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…

  16. 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.

  17. Pathways to deep decarbonization in India

    DEFF Research Database (Denmark)

    Shukla, P.; Dhar, Subash; Pathak, Minal

    This report is a part of the global Deep Decarbonisation Pathways (DDP) Project. The analysis consider two development scenarios for India and assess alternate roadmaps for transiting to a low carbon economy consistent with the globally agreed 2°C stabilization target. The report does not conside...

  18. Pressure induced deep tissue injury explained

    NARCIS (Netherlands)

    Oomens, C.W.J.; Bader, D.L.; Loerakker, S.; Baaijens, F.P.T.

    The paper describes the current views on the cause of a sub-class of pressure ulcers known as pressure induced deep tissue injury (DTI). A multi-scale approach was adopted using model systems ranging from single cells in culture, tissue engineered muscle to animal studies with small animals. This

  19. Deep inelastic scattering near the Coulomb barrier

    International Nuclear Information System (INIS)

    Gehring, J.; Back, B.; Chan, K.

    1995-01-01

    Deep inelastic scattering was recently observed in heavy ion reactions at incident energies near and below the Coulomb barrier. Traditional models of this process are based on frictional forces and are designed to predict the features of deep inelastic processes at energies above the barrier. They cannot be applied at energies below the barrier where the nuclear overlap is small and friction is negligible. The presence of deep inelastic scattering at these energies requires a different explanation. The first observation of deep inelastic scattering near the barrier was in the systems 124,112 Sn + 58,64 Ni by Wolfs et al. We previously extended these measurements to the system 136 Xe + 64 Ni and currently measured the system 124 Xe + 58 Ni. We obtained better statistics, better mass and energy resolution, and more complete angular coverage in the Xe + Ni measurements. The cross sections and angular distributions are similar in all of the Sn + Ni and Xe + Ni systems. The data are currently being analyzed and compared with new theoretical calculations. They will be part of the thesis of J. Gehring

  20. Mean associated multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

    Dzhaparidze, G.Sh.; Kiselev, A.V.; Petrov, V.A.

    1982-01-01

    A formula is derived for the mean hadron multiplicity in the target fragmentation range of deep inelastic scattering processes. It is shown that in the high-x region the ratio of the mean multiplicities in the current fragmentation region and in the target fragmentation region tends to unity at high energies. The mean multiplicity for the Drell-Yan process is considered

  1. Deep inelastic scattering near the Coulomb barrier

    Energy Technology Data Exchange (ETDEWEB)

    Gehring, J.; Back, B.; Chan, K. [and others

    1995-08-01

    Deep inelastic scattering was recently observed in heavy ion reactions at incident energies near and below the Coulomb barrier. Traditional models of this process are based on frictional forces and are designed to predict the features of deep inelastic processes at energies above the barrier. They cannot be applied at energies below the barrier where the nuclear overlap is small and friction is negligible. The presence of deep inelastic scattering at these energies requires a different explanation. The first observation of deep inelastic scattering near the barrier was in the systems {sup 124,112}Sn + {sup 58,64}Ni by Wolfs et al. We previously extended these measurements to the system {sup 136}Xe + {sup 64}Ni and currently measured the system {sup 124}Xe + {sup 58}Ni. We obtained better statistics, better mass and energy resolution, and more complete angular coverage in the Xe + Ni measurements. The cross sections and angular distributions are similar in all of the Sn + Ni and Xe + Ni systems. The data are currently being analyzed and compared with new theoretical calculations. They will be part of the thesis of J. Gehring.

  2. Predicting galling behaviour in deep drawing processes

    NARCIS (Netherlands)

    van der Linde, G.

    2011-01-01

    Deep drawing is a sheet metal forming process which is widely used in, for example, the automotive industry. With this process it is possible to form complex shaped parts of sheet metal and it is suitable for products that have to be produced in large numbers. The tools for this process are required

  3. Deep Belief Networks for dimensionality reduction

    NARCIS (Netherlands)

    Noulas, A.K.; Kröse, B.J.A.

    2008-01-01

    Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art

  4. Authenticity and autonomy in deep-brain stimulation.

    Science.gov (United States)

    Wardrope, Alistair

    2014-08-01

    Felicitas Kraemer draws on the experiences of patients undergoing deep-brain stimulation (DBS) to propose two distinct and potentially conflicting principles of respect: for an individual's autonomy (interpreted as mental competence), and for their authenticity. I argue instead that, according to commonly-invoked justifications of respect for autonomy, authenticity is itself in part constitutive of an analysis of autonomy worthy of respect; Kraemer's argument thus highlights the shortcomings of practical applications of respect for autonomy that emphasise competence while neglecting other important dimensions of autonomy such as authenticity, since it shows that competence alone cannot be interpreted as a reliable indicator of an individual's capacity for exercising autonomy. I draw from relational accounts to suggest how respect for a more expansive conception of autonomy might be interpreted for individuals undergoing DBS and in general. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Hydration of high-silica glasses in the deep sea

    International Nuclear Information System (INIS)

    Federman, A.N.

    1986-01-01

    Natural analogs of nuclear waste glasses are important because they provide information of the one variable that is not controllable in the laboratory - long intervals of time in the actual environment of storage. Some natural glasses have persisted for millions of years in deep-sea sediments in the form of disseminated particles and distinct tephra layers, while other apparently similar specimens have been completely altered to clay assemblages relatively quickly. Geologists have reached no firm conclusions as to why these differences exist, and more research is certainly warranted. These glasses vary in age, composition, and in the in-situ conditions they have experienced. They may provide important information for two different aspects of nuclear waste glass research: First, the chemical composition and especially the water content of these glasses as a function of time may give an understanding of the mechanisms and rates of diffusion in glasses in the natural environment. Second, the apparent differing durability of these glasses in different environmental conditions may suggest the optimal characteristics of a nuclear waste glass depository

  6. 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.

  7. DRREP: deep ridge regressed epitope predictor.

    Science.gov (United States)

    Sher, Gene; Zhi, Degui; Zhang, Shaojie

    2017-10-03

    The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

  8. Distinction of Fly Artifacts from Human Blood using Immunodetection.

    Science.gov (United States)

    Rivers, David B; Acca, Gillian; Fink, Marc; Brogan, Rebecca; Chen, Dorothy; Schoeffield, Andrew

    2018-02-21

    Insect stains produced by necrophagous flies are indistinguishable morphologically from human bloodstains. At present, no diagnostic tests exist to overcome this deficiency. As the first step toward developing a chemical test to recognize fly artifacts, polyclonal antisera were generated in rats against three distinct antigenic sequences of fly cathepsin D-like proteinase, an enzyme that is structurally distinct in cyclorrhaphous Diptera from other animals. The resulting rat antisera bound to artifacts produced by Protophormia terraenovae and synthetic peptides used to generate the polyclonal antisera, but not with any type of mammalian blood tested in immunoassays. Among the three antisera, anti-md3 serum displayed the highest reactivity for fly stains, demonstrated cross-reactivity for all synthetic peptides representing antigenic sequences of the mature fly enzyme, and bound artifacts originating from the fly digestive tract. Further work is needed to determine whether the antisera are suitable for non-laboratory conditions. © 2018 American Academy of Forensic Sciences.

  9. Morphological distinctiveness of Javan Tupaia hypochrysa (Scandentia, Tupaiidae)

    Science.gov (United States)

    Sargis, Eric J.; Woodman, Neal; Morningstar, Natalie C.; Reese, Aspen T.; Olson, Link E.

    2013-01-01

    The common treeshrew, Tupaia glis, represents a species complex with a complicated taxonomic history. It is distributed mostly south of the Isthmus of Kra on the Malay Peninsula and surrounding islands. In our recent revision of a portion of this species complex, we did not fully assess the population from Java (T. “glis” hypochrysa) because of our limited sample. Herein, we revisit this taxon using multivariate analyses in comparisons with T. glis, T. chrysogaster of the Mentawai Islands, and T. ferruginea from Sumatra. Analyses of both the manus and skull of Javan T. “glis” hypochrysa show it to be most similar to T. chrysogaster and distinct from both T. glis and T. ferruginea. Yet, the Javan population and T. chrysogaster have different mammae counts, supporting recognition of T. hypochrysa as a distinct species. The change in taxonomic status of T. hypochrysa has conservation implications for both T. glis and this Javan endemic.

  10. Neonatal lethal dwarfism with distinct skeletal malformations - a separate entity?

    Energy Technology Data Exchange (ETDEWEB)

    Rosendahl, K.; Maurseth, K.; Olsen, Oe.E. [Dept. of Paediatric Radiology, Haukeland University Hospital, Bergen (Norway); Halvorsen, O.J. [Dept. of Pathology, Haukeland University Hospital, Bergen (Norway); Gjelland, K. [Dept. of Gynaecology, Haukeland University Hospital, Bergen (Norway); Engebretsen, L. [Dept. of Genetics, Haukeland University Hospital, Bergen (Norway)

    2001-09-01

    We describe a case of neonatal lethal dwarfism characterised by short trunk, short, stick-like tubular bones, deficient ossification of the axial skeleton and broad, sclerotic horizontal ribs. Two similar cases have previously been reported as examples of the Neu-Laxova syndrome. However, the radiological findings of the Neu-Laxova syndrome, as reported in 16 out of 40 documented cases, show a heterogeneous pattern of minor features, which differ distinctively from those found in the previous two cases and by us. A literature research did not reveal similar cases, and we therefore suggest that our case, together with the two previous cases, may represent a new distinctive form of neonatal lethal dwarfism. (orig.)

  11. Neonatal lethal dwarfism with distinct skeletal malformations - a separate entity?

    International Nuclear Information System (INIS)

    Rosendahl, K.; Maurseth, K.; Olsen, Oe.E.; Halvorsen, O.J.; Gjelland, K.; Engebretsen, L.

    2001-01-01

    We describe a case of neonatal lethal dwarfism characterised by short trunk, short, stick-like tubular bones, deficient ossification of the axial skeleton and broad, sclerotic horizontal ribs. Two similar cases have previously been reported as examples of the Neu-Laxova syndrome. However, the radiological findings of the Neu-Laxova syndrome, as reported in 16 out of 40 documented cases, show a heterogeneous pattern of minor features, which differ distinctively from those found in the previous two cases and by us. A literature research did not reveal similar cases, and we therefore suggest that our case, together with the two previous cases, may represent a new distinctive form of neonatal lethal dwarfism. (orig.)

  12. Distinctive safety aspects of the CANDU-PHW reactor design

    International Nuclear Information System (INIS)

    Kugler, G.

    1980-01-01

    Two lectures are presented in this report. They were prepared in response to a request from IAEA to provide information on the 'Special characteristics of the safety analysis of heavy water reactors' to delegates from member states attending the Interregional Training Course on Safety Analysis Review, held at Karlsruhe, November 19 to December 20, 1979. The CANDU-PHW reactor is used as a model for discussion. The first lecture describes the distinctive features of the CANDU reactor and how they impact on reactor safety. In the second lecture the Canadian safety philosophy, the safety design objective, and other selected topics on reactor safety analysis are discussed. The material in this report was selected with a view to assisting those not familiar with the CANDU heavy water reactor design in evaluating the distinctive safety aspects of these reactors. (auth)

  13. A distinct bacterial dysbiosis associated skin inflammation in ovine footrot

    Science.gov (United States)

    Maboni, Grazieli; Blanchard, Adam; Frosth, Sara; Stewart, Ceri; Emes, Richard; Tötemeyer, Sabine

    2017-03-01

    Ovine footrot is a highly prevalent bacterial disease caused by Dichelobacter nodosus and characterised by the separation of the hoof horn from the underlying skin. The role of innate immune molecules and other bacterial communities in the development of footrot lesions remains unclear. This study shows a significant association between the high expression of IL1β and high D. nodosus load in footrot samples. Investigation of the microbial population identified distinct bacterial populations in the different disease stages and also depending on the level of inflammation. Treponema (34%), Mycoplasma (29%) and Porphyromonas (15%) were the most abundant genera associated with high levels of inflammation in footrot. In contrast, Acinetobacter (25%), Corynebacteria (17%) and Flavobacterium (17%) were the most abundant genera associated with high levels of inflammation in healthy feet. This demonstrates for the first time there is a distinct microbial community associated with footrot and high cytokine expression.

  14. The emotional memory effect: differential processing or item distinctiveness?

    Science.gov (United States)

    Schmidt, Stephen R; Saari, Bonnie

    2007-12-01

    A color-naming task was followed by incidental free recall to investigate how emotional words affect attention and memory. We compared taboo, nonthreatening negative-affect, and neutral words across three experiments. As compared with neutral words, taboo words led to longer color-naming times and better memory in both within- and between-subjects designs. Color naming of negative-emotion nontaboo words was slower than color naming of neutral words only during block presentation and at relatively short interstimulus intervals (ISIs). The nontaboo emotion words were remembered better than neutral words following blocked and random presentation and at both long and short ISIs, but only in mixed-list designs. Our results support multifactor theories of the effects of emotion on attention and memory. As compared with neutral words, threatening stimuli received increased attention, poststimulus elaboration, and benefit from item distinctiveness, whereas nonthreatening emotional stimuli benefited only from increased item distinctiveness.

  15. Pseudomonas aeruginosa diversity in distinct paediatric patient groups

    DEFF Research Database (Denmark)

    Tramper-Stranders, G.A.; Ent, C.K. van der; Wolfs, T.F.

    2008-01-01

    the other groups. A group of clonal isolates was observed among patients from the CF-chronic and CF-1 groups. These or different clonal isolates were not encountered among the three other patient groups. No characteristic resistance pattern could be identified among isolates from the distinct patient groups......Pseudomonas aeruginosa is a pathogen that often infects patients who are either immunocompromised or have local defects in host defences. It is known that cystic fibrosis (CF) patients are sometimes infected with certain clonal isolates. It is not clear whether these clonal isolates also infect non......-CF patients and whether clonality of isolates occurs in other patient groups. The aim of this study was to investigate P. aeruginosa diversity and the occurrence of clones within five distinct paediatric patient groups susceptible to P. aeruginosa infection. P. aeruginosa isolates were cultured from 157...

  16. Two distinct forms of functional lateralization in the human brain

    Science.gov (United States)

    Gotts, Stephen J.; Jo, Hang Joon; Wallace, Gregory L.; Saad, Ziad S.; Cox, Robert W.; Martin, Alex

    2013-01-01

    The hemispheric lateralization of certain faculties in the human brain has long been held to be beneficial for functioning. However, quantitative relationships between the degree of lateralization in particular brain regions and the level of functioning have yet to be established. Here we demonstrate that two distinct forms of functional lateralization are present in the left vs. the right cerebral hemisphere, with the left hemisphere showing a preference to interact more exclusively with itself, particularly for cortical regions involved in language and fine motor coordination. In contrast, right-hemisphere cortical regions involved in visuospatial and attentional processing interact in a more integrative fashion with both hemispheres. The degree of lateralization present in these distinct systems selectively predicted behavioral measures of verbal and visuospatial ability, providing direct evidence that lateralization is associated with enhanced cognitive ability. PMID:23959883

  17. New approach to equipment quality evaluation method with distinct functions

    Directory of Open Access Journals (Sweden)

    Milisavljević Vladimir M.

    2016-01-01

    Full Text Available The paper presents new approach for improving method for quality evaluation and selection of equipment (devices and machinery by applying distinct functions. Quality evaluation and selection of devices and machinery is a multi-criteria problem which involves the consideration of numerous parameters of various origins. Original selection method with distinct functions is based on technical parameters with arbitrary evaluation of each parameter importance (weighting. Improvement of this method, presented in this paper, addresses the issue of weighting of parameters by using Delphi Method. Finally, two case studies are provided, which included quality evaluation of standard boilers for heating and evaluation of load-haul-dump (LHD machines, to demonstrate applicability of this approach. Analytical Hierarchical Process (AHP is used as a control method.

  18. Recognition of distinctive patterns of gallium-67 distribution in sarcoidosis

    International Nuclear Information System (INIS)

    Sulavik, S.B.; Spencer, R.P.; Weed, D.A.; Shapiro, H.R.; Shiue, S.T.; Castriotta, R.J.

    1990-01-01

    Assessment of gallium-67 ( 67 Ga) uptake in the salivary and lacrimal glands and intrathoracic lymph nodes was made in 605 consecutive patients including 65 with sarcoidosis. A distinctive intrathoracic lymph node 67 Ga uptake pattern, resembling the Greek letter lambda, was observed only in sarcoidosis (72%). Symmetrical lacrimal gland and parotid gland 67 Ga uptake (panda appearance) was noted in 79% of sarcoidosis patients. A simultaneous lambda and panda pattern (62%) or a panda appearance with radiographic bilateral, symmetrical, hilar lymphadenopathy (6%) was present only in sarcoidosis patients. The presence of either of these patterns was particularly prevalent in roentgen Stages I (80%) or II (74%). We conclude that simultaneous (a) lambda and panda images, or (b) a panda image with bilateral symmetrical hilar lymphadenopathy on chest X-ray represent distinctive patterns which are highly specific for sarcoidosis, and may obviate the need for invasive diagnostic procedures

  19. The influence of context on distinct facial expressions of disgust.

    Science.gov (United States)

    Reschke, Peter J; Walle, Eric A; Knothe, Jennifer M; Lopez, Lukas D

    2018-06-11

    Face perception is susceptible to contextual influence and perceived physical similarities between emotion cues. However, studies often use structurally homogeneous facial expressions, making it difficult to explore how within-emotion variability in facial configuration affects emotion perception. This study examined the influence of context on the emotional perception of categorically identical, yet physically distinct, facial expressions of disgust. Participants categorized two perceptually distinct disgust facial expressions, "closed" (i.e., scrunched nose, closed mouth) and "open" (i.e., scrunched nose, open mouth, protruding tongue), that were embedded in contexts comprising emotion postures and scenes. Results demonstrated that the effect of nonfacial elements was significantly stronger for "open" disgust facial expressions than "closed" disgust facial expressions. These findings provide support that physical similarity within discrete categories of facial expressions is mutable and plays an important role in affective face perception. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Ethical distinctions between different kinds of plant breeding

    DEFF Research Database (Denmark)

    Myskja, B.K.; Schouten, H.J.; Gjerris, Mickey

    2015-01-01

    The article discusses whether there are ethically significant distinctions between different forms of plant breeding. We distinguish different forms of plant breeding according to the kind of technology and degree of human intervention compared to plant reproduction occurring in nature. According...... differences between plant breeding methods. The framework can contribute to an improved dialogue between the scientific community and the wider public by making the scepticism towards GM-technology more intelligible....