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Sample records for mgcl2-dominated deep hypersaline

  1. Microbial ecology of deep-sea hypersaline anoxic basins

    KAUST Repository

    Merlino, Giuseppe

    2018-05-09

    Deep hypersaline anoxic basins (DHABs) are unique water bodies occurring within fractures at the bottom of the sea, where the dissolution of anciently buried evaporites created dense anoxic brines that are separated by a chemocline/pycnocline from the overlying oxygenated deep-seawater column. DHABs have been described in the Gulf of Mexico, the Mediterranean Sea, the Black Sea and the Red Sea. They are characterized by prolonged historical separation of the brines from the upper water column due to lack of mixing and by extreme conditions of salinity, anoxia, and relatively high hydrostatic pressure and temperatures. Due to these combined selection factors, unique microbial assemblages thrive in these polyextreme ecosystems. The topological localization of the different taxa in the brine-seawater transition zone coupled with the metabolic interactions and niche adaptations determine the metabolic functioning and biogeochemistry of DHABs. In particular, inherent metabolic strategies accompanied by genetic adaptations have provided insights on how prokaryotic communities can adapt to salt-saturated condition. Here, we review the current knowledge on the diversity, genomics, metabolisms and ecology of prokaryotes in DHABs.

  2. An Updated View of the Microbial Diversity in Deep Hypersaline Anoxic Basins

    KAUST Repository

    Mapelli, Francesca

    2017-03-02

    Deep hypersaline anoxic basins (DHABs) are marine extreme habitats, firstly discovered in the 1970s of the last century, located in several oceanographic regions, including the Mediterranean and Red Sea and the Gulf of Mexico. These basins are filled with brines that do not mix with the overlying seawater, due to a density difference. Brine and seawater result separated by a thick interface acting as a trap for particulate and cells. Some microbiological studies focused on seawater-brine interfaces of DHABs, showing that microbial populations are differentially distributed according to the gradient of salinity, oxygen, and nutrients occurring in such transition zones. Moreover, DHABs’ brines were intensively studied showing that specific bacterial, archaeal, and eukaryotic populations thrive there. In the last few years, cultivation and “omics”-based approaches have been used with samples collected from DHABs around the world, allowing clarifying metabolic processes of paramount ecological importance and pointing out the high biotechnological potential of the inhabiting extremophiles.

  3. Ecology of Hypersaline Microorganisms

    Digital Repository Service at National Institute of Oceanography (India)

    Kerkar, S.

    of ancient seas. Deep Sea brines are relatively stable as a result of their higher density as reported in the Red Sea and Gulf of Mexico (MacDonald et al, 1990). Preliminary studies have suggested that microbial activity occurs in some Deep Sea hypersaline... partially characterized extreme halophile called ?Halobacterium sp GN101? (GN = Guerrero Negro, Mexico) (Ebert and Goebel, 1985). Hal R1 activity is typical with first activity detected during the transition from exponential to stationary phase...

  4. Testing the Role of Microbial Ecology, Redox-Mediated Deep Water Production and Hypersalinity on TEX86: Lipids and 16s Sequences from Archaea and Bacteria in the Water Column and Sediments of Orca Basin

    Science.gov (United States)

    Warren, C.; Romero, I.; Ellis, G.; Goddard, E.; Krishnan, S.; Nigro, L. M.; Super, J. R.; Zhang, Y.; Zhuang, G.; Hollander, D. J.; Pagani, M.

    2014-12-01

    Mesophilic marine archaea and bacteria are known to substantially contribute to the oceanic microbial biomass and play critical roles in global carbon, nitrogen and nutrient cycles. The Orca Basin, a 2400 meter deep bathymetric depression on the continental slope of the north-central Gulf of Mexico, is an ideal environment to examine how redox-dependent biochemical processes control the input and cycling of bacterial and archaea-derived lipid compounds from formation in near-surface water, through secondary recycling processes operating at the redox-transition in the water column, to sedimentary diagenetic processes operating in oxic to anoxic zones within the basin. The lowermost 180 meters of the Orca Basin is characterized by an anoxic, hypersaline brine that is separated from the overlying oxic seawater by a well-defined redox sequence associated with a systematic increasing in salinity from 35 - 250‰. While surface water conditions are viewed as normal marine with a seasonally productive water column, the sub-oxic to anoxic transition zones within the deep-water column and the sediment spans over 200 m allowing the unique opportunity for discrete sampling of resident organisms and lipids. Here we present 16s rRNA sequence data of Bacteria and Archaea collected parallel to GDGT lipid profiles and in situ environmental measurements from the sediment and overlying water column in the intermediate zone of the basin, where movements of chemical transition zones are preserved. We evaluated GDGTs and corresponding taxa across the surface water, chlorophyll maximum, thermocline, and the deep redox boundary, including oxygenation, denitrification, manganese, iron and sulfate reduction zones, to determine if GDGTs are being produced under these conditions and how surface-derived GDGT lipids and the TEX86 signal may be altered. The results have implications for the application of the TEX86 paleotemperature proxy.

  5. Biodegradation of petroleum hydrocarbons in hypersaline environments

    Directory of Open Access Journals (Sweden)

    Luiz Fernando Martins

    2012-09-01

    Full Text Available Literature on hydrocarbon degradation in extreme hypersaline media presents studies that point to a negative effect of salinity increase on hydrocarbonoclastic activity, while several others report an opposite tendency. Based on information available in the literature, we present a discussion on the reasons that justify these contrary results. Despite the fact that microbial ability to metabolize hydrocarbons is found in extreme hypersaline media, indeed some factors are critical for the occurrence of hydrocarbon degradation in such environments. How these factors affect hydrocarbon degradation and their implications for the assessment of hydrocarbon biodegradation in hypersaline environments are presented in this review.

  6. Pressure retarded osmosis from hypersaline sources - A review

    DEFF Research Database (Denmark)

    Bajraktari, Niada; Hélix-Nielsen, Claus; Madsen, Henrik T.

    2017-01-01

    for commercialization. The scope of this paper is to review the existing knowledge on the use of hypersaline waters in the salinity gradient process, pressure retarded osmosis. Although only few papers have had the specific aim of investigating hypersaline waters, concentrated solutions have been used in many papers...

  7. Investigations of Methane Production in Hypersaline Environments

    Science.gov (United States)

    Bebout, Brad M.

    2015-01-01

    The recent reports of methane in the atmosphere of Mars, as well as the findings of hypersaline paleo-environments on that planet, have underscored the need to evaluate the importance of biological (as opposed to geological) trace gas production and consumption. Methane in the atmosphere of Mars may be an indication of life but might also be a consequence of geologic activity and/or the thermal alteration of ancient organic matter. Hypersaline environments have now been reported to be extremely likely in several locations in our solar system, including: Mars, Europa, and Enceladus. Modern hypersaline microbial mat communities, (thought to be analogous to those present on the early Earth at a period of time when Mars was experiencing very similar environmental conditions), have been shown to produce methane. However, very little is known about the physical and/or biological controls imposed upon the rates at which methane, and other important trace gases, are produced and consumed in these environments. We describe here the results of our investigations of methane production in hypersaline environments, including field sites in Chile, Baja California Mexico, California, USA and the United Arab Emirates. We have measured high concentrations of methane in bubbles of gas produced both in the sediments underlying microbial mats, as well as in areas not colonized by microbial mats in the Guerrero Negro hypersaline ecosystem, Baja California Mexico, in Chile, and in salt ponds on the San Francisco Bay. The carbon isotopic (d13C) composition of the methane in the bubbles exhibited an extremely wide range of values, (ca. -75 per mille ca. -25 per mille). The hydrogen isotopic composition of the methane (d2H) ranged from -60 to -30per mille and -450 to -350per mille. These isotopic values are outside of the range of values normally considered to be biogenic, however incubations of the sediments in contact with these gas bubbles reveals that the methane is indeed being

  8. Diversity of Heterotrophic Protists from Extremely Hypersaline Habitats.

    Science.gov (United States)

    Park, Jong Soo; Simpson, Alastair G B

    2015-09-01

    Heterotrophic protists (protozoa) are a diverse but understudied component of the biota of extremely hypersaline environments, with few data on molecular diversity within halophile 'species', and almost nothing known of their biogeographic distribution. We have garnered SSU rRNA gene sequences for several clades of halophilic protozoa from enrichments from waters of >12.5% salinity from Australia, North America, and Europe (6 geographic sites, 25 distinct samples). The small stramenopile Halocafeteria was found at all sites, but phylogenies did not show clear geographic clustering. The ciliate Trimyema was recorded from 6 non-European samples. Phylogenies confirmed a monophyletic halophilic Trimyema group that included possible south-eastern Australian, Western Australian and North American clusters. Several halophilic Heterolobosea were detected, demonstrating that Pleurostomum contains at least three relatively distinct clades, and increasing known continental ranges for Tulamoeba peronaphora and Euplaesiobystra hypersalinica. The unclassified flagellate Palustrimonas, found in one Australian sample, proves to be a novel deep-branching alveolate. These results are consistent with a global distribution of halophilic protozoa groups (∼ morphospecies), but the Trimyema case suggests that is worth testing whether larger forms exhibit biogeographic phylogenetic substructure. The molecular detection/characterization of halophilic protozoa is still far from complete at the clade level, let alone the 'species level'. Copyright © 2015 Elsevier GmbH. All rights reserved.

  9. Microbial stratification and microbially catalyzed processes along a hypersaline chemocline

    Science.gov (United States)

    Hyde, A.; Joye, S. B.; Teske, A.

    2017-12-01

    Orca Basin is the largest deep hypersaline anoxic basin in the world, covering over 400 km2. Located at the bottom of the Gulf of Mexico, this body of water reaches depths of 200 meters and is 8 times denser (and more saline) than the overlying seawater. The sharp pycnocline prevents any significant vertical mixing and serves as a particle trap for sinking organic matter. These rapid changes in salinity, oxygen, organic matter, and other geochemical parameters present unique conditions for the microbial communities present. We collected samples in 10m intervals throughout the chemocline. After filtering the water, we used high-throughput bacterial and archaeal 16S rRNA gene sequencing to characterize the changing microbial community along the Orca Basin chemocline. The results reveal a dominance of microbial taxa whose biogeochemical function is entirely unknown. We then used metagenomic sequencing and reconstructed genomes for select samples, revealing the potential dominant metabolic processes in the Orca Basin chemocline. Understanding how these unique geochemical conditions shape microbial communities and metabolic capabilities will have implications for the ocean's biogeochemical cycles and the consequences of expanding oxygen minimum zones.

  10. High-Quality Draft Single-Cell Genome Sequence Belonging to the Archaeal Candidate Division SA1, Isolated from Nereus Deep in the Red Sea

    KAUST Repository

    Ngugi, David

    2018-05-09

    Candidate division SA1 encompasses a phylogenetically coherent archaeal group ubiquitous in deep hypersaline anoxic brines around the globe. Recently, the genome sequences of two cultivated representatives from hypersaline soda lake sediments were published. Here, we present a single-cell genome sequence from Nereus Deep in the Red Sea that represents a putatively novel family within SA1.

  11. High-Quality Draft Single-Cell Genome Sequence Belonging to the Archaeal Candidate Division SA1, Isolated from Nereus Deep in the Red Sea

    KAUST Repository

    Ngugi, David; Stingl, Ulrich

    2018-01-01

    Candidate division SA1 encompasses a phylogenetically coherent archaeal group ubiquitous in deep hypersaline anoxic brines around the globe. Recently, the genome sequences of two cultivated representatives from hypersaline soda lake sediments were published. Here, we present a single-cell genome sequence from Nereus Deep in the Red Sea that represents a putatively novel family within SA1.

  12. Discovery of anaerobic lithoheterotrophic haloarchaea, ubiquitous in hypersaline habitats

    NARCIS (Netherlands)

    Sorokin, D.Y.; Messina, E.; Smedile, F; Roman, P.; Sinninghe Damsté, J.S.; Ciordia, S.; Mena, M.C.; Ferrer, M.; Golyshin, P.N.; Kublanov, I.V.; Samarov, N.I.; Toshchakov, S.V.; La Cono, V.; Yakimov, M.M.

    2017-01-01

    Hypersaline anoxic habitats harbour numerous novel uncultured archaea whose metabolic and ecological roles remain to be elucidated. Until recently, it was believed that energy generation via dissimilatory reduction of sulfur compounds is not functional at salt saturation conditions. Recent discovery

  13. Microbial ecology of deep-sea hypersaline anoxic basins

    KAUST Repository

    Merlino, Giuseppe; Barozzi, Alan; Michoud, Gregoire; Ngugi, David; Daffonchio, Daniele

    2018-01-01

    of mixing and by extreme conditions of salinity, anoxia, and relatively high hydrostatic pressure and temperatures. Due to these combined selection factors, unique microbial assemblages thrive in these polyextreme ecosystems. The topological localization

  14. A deep sea community at the Kebrit brine pool in the Red Sea

    KAUST Repository

    Vestheim, Hege; Kaartvedt, Stein

    2015-01-01

    Approximately 25 deep sea brine pools occur along the mid axis of the Red Sea. These hypersaline, anoxic, and acidic environments have previously been reported to host diverse microbial communities. We visited the Kebrit brine pool in April 2013

  15. Evolution of genomic diversity and sex at extreme environments: Fungal life under hypersaline Dead Sea stress

    Science.gov (United States)

    Kis-Papo, Tamar; Kirzhner, Valery; Wasser, Solomon P.; Nevo, Eviatar

    2003-01-01

    We have found that genomic diversity is generally positively correlated with abiotic and biotic stress levels (1–3). However, beyond a high-threshold level of stress, the diversity declines to a few adapted genotypes. The Dead Sea is the harshest planetary hypersaline environment (340 g·liter–1 total dissolved salts, ≈10 times sea water). Hence, the Dead Sea is an excellent natural laboratory for testing the “rise and fall” pattern of genetic diversity with stress proposed in this article. Here, we examined genomic diversity of the ascomycete fungus Aspergillus versicolor from saline, nonsaline, and hypersaline Dead Sea environments. We screened the coding and noncoding genomes of A. versicolor isolates by using >600 AFLP (amplified fragment length polymorphism) markers (equal to loci). Genomic diversity was positively correlated with stress, culminating in the Dead Sea surface but dropped drastically in 50- to 280-m-deep seawater. The genomic diversity pattern paralleled the pattern of sexual reproduction of fungal species across the same southward gradient of increasing stress in Israel. This parallel may suggest that diversity and sex are intertwined intimately according to the rise and fall pattern and adaptively selected by natural selection in fungal genome evolution. Future large-scale verification in micromycetes will define further the trajectories of diversity and sex in the rise and fall pattern. PMID:14645702

  16. Biodiversity of the Hypersaline Urmia Lake National Park (NW Iran

    Directory of Open Access Journals (Sweden)

    Alireza Asem

    2014-02-01

    Full Text Available Urmia Lake, with a surface area between 4000 to 6000 km2, is a hypersaline lake located in northwest Iran. It is the saltiest large lake in the world that supports life. Urmia Lake National Park is the home of an almost endemic crustacean species known as the brine shrimp, Artemia urmiana. Other forms of life include several species of algae, bacteria, microfungi, plants, birds, reptiles, amphibians and mammals. As a consequence of this unique biodiversity, this lake has been selected as one of the 59 biosphere reserves by UNESCO. This paper provides a comprehensive species checklist that needs to be updated by additional research in the future.

  17. Differences in lateral gene transfer in hypersaline versus thermal environments.

    Science.gov (United States)

    Rhodes, Matthew E; Spear, John R; Oren, Aharon; House, Christopher H

    2011-07-08

    The role of lateral gene transfer (LGT) in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these "long distance" LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles. We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei) and a halophilic class of Archaea (Halobacteria). We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles. Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. Furthermore, most hypersaline environments, as topographical minima, are natural collectors of cellular debris. Thus halophiles would in theory be exposed to a greater diversity and quantity of extracellular DNA than thermophiles.

  18. Lipid Biomarkers for a Hypersaline Microbial Mat Community

    Science.gov (United States)

    Jahnke, Linda L.; Embaye, Tsege; Turk, Kendra A.

    2003-01-01

    The use of lipid biomarkers and their carbon isotopic compositions are valuable tools for establishing links to ancient microbial ecosystems. As witnessed by the stromatolite record, benthic microbial mats grew in shallow water lagoonal environments where microorganisms had virtually no competition apart from the harsh conditions of hypersalinity, desiccation and intense light. Today, the modern counterparts of these microbial ecosystems find appropriate niches in only a few places where extremes eliminate eukaryotic grazers. Answers to many outstanding questions about the evolution of microorganisms and their environments on early Earth are best answered through study of these extant analogs. Lipids associated with various groups of bacteria can be valuable biomarkers for identification of specific groups of microorganisms both in ancient organic-rich sedimentary rocks (geolipids) and contemporary microbial communities (membrane lipids). Use of compound specific isotope analysis adds additional refinement to the identification of biomarker source, so that it is possible to take advantage of the 3C-depletions associated with various functional groups of organisms (i.e. autotrophs, heterotrophs, methanotrophs, methanogens) responsible for the cycling of carbon within a microbial community. Our recent work has focused on a set of hypersaline evaporation ponds at Guerrero Negro, Baja California Sur, Mexico which support the abundant growth of Microcoleus-dominated microbial mats. Specific biomarkers for diatoms, cyanobacteria, archaea, green nonsulfur (GNS), sulfate reducing, and methanotrophic bacteria have been identified. Analyses of the ester-bound fatty acids indicate a highly diverse microbial community, dominated by photosynthetic organisms at the surface.

  19. Cyanobacterial diversity and halotolerance in a variable hypersaline environment.

    Science.gov (United States)

    Kirkwood, Andrea E; Buchheim, Julie A; Buchheim, Mark A; Henley, William J

    2008-04-01

    The Great Salt Plains (GSP) in north-central Oklahoma, USA is an expansive salt flat (approximately 65 km(2)) that is part of the federally protected Salt Plains National Wildlife Refuge. The GSP serves as an ideal environment to study the microbial diversity of a terrestrial, hypersaline system that experiences wide fluctuations in freshwater influx and diel temperature. Our study assessed cyanobacterial diversity at the GSP by focusing on the taxonomic and physiological diversity of GSP isolates, and the 16S rRNA phylogenetic diversity of isolates and environmental clones from three sites (north, central, and south). Taxonomic diversity of isolates was limited to a few genera (mostly Phormidium and Geitlerinema), but physiological diversity based on halotolerance ranges was strikingly more diverse, even between strains of the same phylotype. The phylogenetic tree revealed diversity that spanned a number of cyanobacterial lineages, although diversity at each site was dominated by only a few phylotypes. Unlike other hypersaline systems, a number of environmental clones from the GSP were members of the heterocystous lineage. Although a number of cyanobacterial isolates were close matches with prevalent environmental clones, it is not certain if these clones reflect the same halotolerance ranges of their matching isolates. This caveat is based on the notable disparities we found between strains of the same phylotype and their inherent halotolerance. Our findings support the hypothesis that variable or poikilotrophic environments promote diversification, and in particular, select for variation in ecotype more than phylotype.

  20. Diversity of halophilic archaea from six hypersaline environments in Turkey.

    Science.gov (United States)

    Ozcan, Birgul; Ozcengiz, Gulay; Coleri, Arzu; Cokmus, Cumhur

    2007-06-01

    The diversity of archaeal strains from six hypersaline environments in Turkey was analyzed by comparing their phenotypic characteristics and 16S rDNA sequences. Thirty-three isolates were characterized in terms of their phenotypic properties including morphological and biochemical characteristics, susceptibility to different antibiotics, and total lipid and plasmid contents, and finally compared by 16S rDNA gene sequences. The results showed that all isolates belong to the family Halobacteriaceae. Phylogenetic analyses using approximately 1,388 bp comparisions of 16S rDNA sequences demonstrated that all isolates clustered closely to species belonging to 9 genera, namely Halorubrum (8 isolates), Natrinema (5 isolates), Haloarcula (4 isolates), Natronococcus (4 isolates), Natrialba (4 isolates), Haloferax (3 isolates), Haloterrigena (3 isolates), Halalkalicoccus (1 isolate), and Halomicrobium (1 isolate). The results revealed a high diversity among the isolated halophilic strains and indicated that some of these strains constitute new taxa of extremely halophilic archaea.

  1. Cooling, cryporitectant and hypersaline sensitivity of Penaeid shrimp embryos and nauplii larvae

    NARCIS (Netherlands)

    Alfaro Montoya, J.; Komen, J.; Huisman, E.A.

    2001-01-01

    The sensitivity of embryos of the penaeid shrimp, Trachypenaeus byrdi, to cooling, cryoprotectant exposure (dimethyl sulfoxide : DMSO, sucrose, methanol and glycerol), and hypersaline treatment was assessed in order to gain basic knowledge for cryopreservation procedures. In addition, cooling and

  2. Differences in lateral gene transfer in hypersaline versus thermal environments

    Directory of Open Access Journals (Sweden)

    House Christopher H

    2011-07-01

    Full Text Available Abstract Background The role of lateral gene transfer (LGT in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these "long distance" LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles. Results We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei and a halophilic class of Archaea (Halobacteria. We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles. Conclusions Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. Furthermore, most hypersaline environments, as topographical minima, are natural collectors of cellular debris. Thus halophiles would in theory be exposed to a greater diversity and quantity of extracellular DNA than thermophiles.

  3. Community Structure and Activity of a Highly Dynamic and Nutrient-Limited Hypersaline Microbial Mat in Um Alhool Sabkha, Qatar

    KAUST Repository

    Al-Thani, Roda

    2014-03-21

    The Um Alhool area in Qatar is a dynamic evaporative ecosystem that receives seawater from below as it is surrounded by sand dunes. We investigated the chemical composition, the microbial activity and biodiversity of the four main layers (L1–L4) in the photosynthetic mats. Chlorophyll a (Chl a) concentration and distribution (measured by HPLC and hyperspectral imaging, respectively), the phycocyanin distribution (scanned with hyperspectral imaging), oxygenic photosynthesis (determined by microsensor), and the abundance of photosynthetic microorganisms (from 16S and 18S rRNA sequencing) decreased with depth in the euphotic layer (L1). Incident irradiance exponentially attenuated in the same zone reaching 1% at 1.7-mm depth. Proteobacteria dominated all layers of the mat (24%–42% of the identified bacteria). Anoxygenic photosynthetic bacteria (dominated by Chloroflexus) were most abundant in the third red layer of the mat (L3), evidenced by the spectral signature of Bacteriochlorophyll as well as by sequencing. The deep, black layer (L4) was dominated by sulfate reducing bacteria belonging to the Deltaproteobacteria, which were responsible for high sulfate reduction rates (measured using 35S tracer). Members of Halobacteria were the dominant Archaea in all layers of the mat (92%–97%), whereas Nematodes were the main Eukaryotes (up to 87%). Primary productivity rates of Um Alhool mat were similar to those of other hypersaline microbial mats. However, sulfate reduction rates were relatively low, indicating that oxygenic respiration contributes more to organic material degradation than sulfate reduction, because of bioturbation. Although Um Alhool hypersaline mat is a nutrient-limited ecosystem, it is interestingly dynamic and phylogenetically highly diverse. All its components work in a highly efficient and synchronized way to compensate for the lack of nutrient supply provided during regular inundation periods.

  4. Archaeal Communities in a Heterogeneous Hypersaline-Alkaline Soil

    Directory of Open Access Journals (Sweden)

    Yendi E. Navarro-Noya

    2015-01-01

    Full Text Available In this study the archaeal communities in extreme saline-alkaline soils of the former lake Texcoco, Mexico, with electrolytic conductivities (EC ranging from 0.7 to 157.2 dS/m and pH from 8.5 to 10.5 were explored. Archaeal communities in the 0.7 dS/m pH 8.5 soil had the lowest alpha diversity values and were dominated by a limited number of phylotypes belonging to the mesophilic Candidatus Nitrososphaera. Diversity and species richness were higher in the soils with EC between 9.0 and 157.2 dS/m. The majority of OTUs detected in the hypersaline soil were members of the Halobacteriaceae family. Novel phylogenetic branches in the Halobacteriales class were detected in the soil, and more abundantly in soil with the higher pH (10.5, indicating that unknown and uncharacterized Archaea can be found in this soil. Thirteen different genera of the Halobacteriaceae family were identified and were distributed differently between the soils. Halobiforma, Halostagnicola, Haloterrigena, and Natronomonas were found in all soil samples. Methanogenic archaea were found only in soil with pH between 10.0 and 10.3. Retrieved methanogenic archaea belonged to the Methanosarcinales and Methanomicrobiales orders. The comparison of the archaeal community structures considering phylogenetic information (UniFrac distances clearly clustered the communities by pH.

  5. Field observations of hypersaline runoff through a shallow estuary

    Science.gov (United States)

    Hosseini, Seyed Taleb; Siadatmousavi, Seyed Mostafa

    2018-03-01

    This study investigates a rare situation at the Mond River Estuary in the Persian Gulf, in which the classical estuarine density gradient coincides with hypersaline runoff entering from saline soils upstream of the estuary after severe precipitation. This builds a unique estuarine setting, where two salt water masses, one originating from the coastal ocean and the other being discharged from upstream confine a range of almost freshwater in the middle of estuary. This "freshwater lens estuary" (FLE) situation includes two saltwater sources with opposing senses of estuarine circulation. Therefore, the tidal damping by the strong river flood can occur, especially during neap tide when high Unsteadiness number (∼0.04) signified ebb oriented condition which was induced by straining residual lateral circulation near the FLE mouth. Transition from well-mixed to weak strain induced periodic stratification regimes indicated the importance of the spring-neap tidal variations. Close to the mouth, a 13.66-day periodic tidal asymmetry from the triad K1-O1-M2 (ebb-dominance during spring tide and flood-dominance in neap tide) was overcome by higher harmonics.

  6. Mechanisms of fenthion activation in rainbow trout (Oncorhynchus mykiss) acclimated to hypersaline environments

    International Nuclear Information System (INIS)

    Lavado, Ramon; Rimoldi, John M.; Schlenk, Daniel

    2009-01-01

    Previous studies in rainbow trout have shown that acclimation to hypersaline environments enhances the toxicity to thioether organophosphate and carbamate pesticides. In order to determine the role of biotransformation in this process, the metabolism of the thioether organophosphate biocide, fenthion was evaluated in microsomes from gills, liver and olfactory tissues in rainbow trout (Oncorhynchus mykiss) acclimated to freshwater and 17 per mille salinity. Hypersalinity acclimation increased the formation of fenoxon and fenoxon sulfoxide from fenthion in liver microsomes from rainbow trout, but not in gills or in olfactory tissues. NADPH-dependent and independent hydrolysis was observed in all tissues, but only NADPH-dependent fenthion cleavage was differentially modulated by hypersalinity in liver (inhibited) and gills (induced). Enantiomers of fenthion sulfoxide (65% and 35% R- and S-fenthion sulfoxide, respectively) were formed in liver and gills. The predominant pathway of fenthion activation in freshwater appears to be initiated through initial formation of fenoxon which may be subsequently converted to the most toxic metabolite fenoxon R-sulfoxide. However, in hypersaline conditions both fenoxon and fenthion sulfoxide formation may precede fenoxon sulfoxide formation. Stereochemical evaluation of sulfoxide formation, cytochrome P450 inhibition studies with ketoconazole and immunoblots indicated that CYP3A27 was primarily involved in the enhancement of fenthion activation in hypersaline-acclimated fish with limited contribution of FMO to initial sulfoxidation

  7. Early diagenetic processes and sulphur speciation in pore waters and sediments of the hypersaline Tyro and Bannock basins, eastern Mediterranean

    NARCIS (Netherlands)

    Henneke, E.

    1993-01-01

    Anoxic hypersaline basins have been found in two different tectonic environments in the eastern Mediterranean. Within the Tyro area (the western Strabo Trench) there are three pull apart basins: the Tyro Basin, presently filled with anoxic hypersaline bottomwater, and the Poseidon and Kretheus

  8. Microbial fuel cells in saline and hypersaline environments: Advancements, challenges and future perspectives.

    Science.gov (United States)

    Grattieri, Matteo; Minteer, Shelley D

    2018-04-01

    This review is aimed to report the possibility to utilize microbial fuel cells for the treatment of saline and hypersaline solutions. An introduction to the issues related with the biological treatment of saline and hypersaline wastewater is reported, discussing the limitation that characterizes classical aerobic and anaerobic digestions. The microbial fuel cell (MFC) technology, and the possibility to be applied in the presence of high salinity, is discussed before reviewing the most recent advancements in the development of MFCs operating in saline and hypersaline conditions, with their different and interesting applications. Specifically, the research performed in the last 5years will be the main focus of this review. Finally, the future perspectives for this technology, together with the most urgent research needs, are presented. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Geo- and biogeochemical processes in a heliothermal hypersaline lake

    Science.gov (United States)

    Zachara, John M.; Moran, James J.; Resch, Charles T.; Lindemann, Stephen R.; Felmy, Andrew R.; Bowden, Mark E.; Cory, Alexandra B.; Fredrickson, James K.

    2016-05-01

    Water chemical variations were investigated over three annual hydrologic cycles in hypersaline, heliothermal, meromictic Hot Lake in north-central Washington State, USA. The lake contains diverse biota with dramatic zonation related to salinity and redox state. Water samples were collected at 10-cm depth intervals through the shallow lake (2.4 m) during 2012-2014, with comprehensive monitoring performed in 2013. Inorganic salt species, dissolved carbon forms (DOC, DIC), oxygen, sulfide, and methane were analyzed in lake water samples. Depth sonde measurements of pH and temperature were also performed to track their seasonal variations. A bathymetric survey of the lake was conducted to enable lake water volume and solute inventory calculations. Sediment cores were collected at low water and analyzed by X-ray diffraction to investigate sediment mineralogy. The primary dissolved salt in Hot Lake water was Mg2+-SO42- whereas sediments were dominated by gypsum (CaSO4·2H2O). Lake water concentrations increased with depth, reaching saturation with epsomite (MgSO4·7H2O) that was exposed at lake bottom. At maximum volume in spring, Hot Lake exhibited a relatively dilute mixolimnion; a lower saline metalimnion with stratified oxygenic and anoxygenic photosynthetic microbiological communities; and a stable, hypersaline monimolimnion, separated from above layers by a chemocline, containing high levels of sulfide and methane. The thickness of the mixolimnion regulates a heliothermal effect that creates temperatures in excess of 60 °C in the underlying metalimnion and monimolimnion. The mixolimnion was dynamic in volume and actively mixed. It displayed large pH variations, in-situ calcium carbonate precipitation, and large evaporative volume losses. The depletion of this layer by fall allowed deeper mixing into the metalimnion, more rapid heat exchange, and lower winter lake temperatures. Solubility calculations indicate seasonal biogenic and thermogenic aragonite

  10. Geo- and Biogeochemical Processes in a Heliothermal Hypersaline Lake

    Energy Technology Data Exchange (ETDEWEB)

    Zachara, John M.; Moran, James J.; Resch, Charles T.; Lindemann, Stephen R.; Felmy, Andrew R.; Bowden, Mark E.; Cory, Alexandra B.; Fredrickson, Jim K.

    2016-03-17

    Water chemical variations were investigated over three annual hydrologic cycles in hypersaline, heliothermal, meromictic Hot Lake in north-central Washington State, USA. The lake, originally studied by Anderson (1958), contains diverse biota with dramatic zonation related to salinity and redox state. Water samples were collected at 10 cm depth intervals through the shallow lake (2.4 m) at a consistent location during 2012-2014, with comprehensive monitoring performed in 2013. Inorganic salt species, total dissolved solids (TDS), dissolved carbon forms (DOC, DIC), oxygen, sulfide, and methane were analyzed in lake water samples. Depth sonde measurements of pH and temperature were also performed to track their seasonal variations. A bathymetric survey of the lake was conducted to enable lake water volume and solute inventory calculations. Sediment cores were collected at low water and analyzed by x-ray diffraction to investigate sediment mineralogy. The primary dissolved salt in Hot Lake water was Mg2+-SO42- while sediments were dominated by gypsum (CaSO4•2H2O). Lake water concentrations increased with depth to reach saturation with epsomite that was exposed at lake bottom. At maximum volume in spring, Hot Lake exhibited a relatively dilute mixolimnion containing phyto- and zooplankton; a lower saline metalimnion with stratified oxygenic and anoxygenic photosynthetic microbiologic communities; and a stable, hypersaline monimolimnion, separated from above layers by a chemocline, containing high levels of sulfide and methane. The thickness of the mixolimnion regulates a heliothermal effect which creates temperatures in excess of 60 oC in the underlying metalimnion and monimolimnion. The mixolimnion was dynamic and actively mixed. It displayed large pH variations, in-situ calcium carbonate precipitation, and large evaporative volume losses. The depletion of this ephemeral layer by fall allowed deeper mixing into the volume-stable lower mixolimnion, more rapid heat

  11. Diversity and stratification of archaea in a hypersaline microbial mat.

    Science.gov (United States)

    Robertson, Charles E; Spear, John R; Harris, J Kirk; Pace, Norman R

    2009-04-01

    The Guerrero Negro (GN) hypersaline microbial mats have become one focus for biogeochemical studies of stratified ecosystems. The GN mats are found beneath several of a series of ponds of increasing salinity that make up a solar saltern fed from Pacific Ocean water pumped from the Laguna Ojo de Liebre near GN, Baja California Sur, Mexico. Molecular surveys of the laminated photosynthetic microbial mat below the fourth pond in the series identified an enormous diversity of bacteria in the mat, but archaea have received little attention. To determine the bulk contribution of archaeal phylotypes to the pond 4 study site, we determined the phylogenetic distribution of archaeal rRNA gene sequences in PCR libraries based on nominally universal primers. The ratios of bacterial/archaeal/eukaryotic rRNA genes, 90%/9%/1%, suggest that the archaeal contribution to the metabolic activities of the mat may be significant. To explore the distribution of archaea in the mat, sequences derived using archaeon-specific PCR primers were surveyed in 10 strata of the 6-cm-thick mat. The diversity of archaea overall was substantial albeit less than the diversity observed previously for bacteria. Archaeal diversity, mainly euryarchaeotes, was highest in the uppermost 2 to 3 mm of the mat and decreased rapidly with depth, where crenarchaeotes dominated. Only 3% of the sequences were specifically related to known organisms including methanogens. While some mat archaeal clades corresponded with known chemical gradients, others did not, which is likely explained by heretofore-unrecognized gradients. Some clades did not segregate by depth in the mat, indicating broad metabolic repertoires, undersampling, or both.

  12. Hypersaline waters - a potential source of foodborne toxigenic aspergilli and penicillia

    DEFF Research Database (Denmark)

    Butinar, Lorena; Frisvad, Jens Christian; Gunde-Cimerman, Nina

    2011-01-01

    Previous studies of hypersaline environments have revealed the dominant presence of melanized yeast-like fungi and related Cladosporium spp. In this study, we focused on the genera Aspergillus and Penicillium and their teleomorphic forms. From oligotrophic and eutrophic hypersaline waters around...... herbariorum, as they were quite evenly distributed among the sampled sites, and Aspergillus candidus, which was abundant, but more locally distributed. These species and their byproducts can accumulate downstream following evaporation of brine, and they can become entrapped in the salt crystals. Consequently...

  13. Dynamics of Molecular Hydrogen in Hypersaline Microbial Mars

    Science.gov (United States)

    Hoehler, Tori M.; Bebout, Brad M.; Visscher, Pieter T.; DesMarais, David J.; DeVincenzi, Donald L. (Technical Monitor)

    2000-01-01

    Early Earth microbial communities that centered around the anaerobic decomposition of organic molecular hydrogen as a carrier of electrons, regulator of energy metabolism, and facilitator of syntroph'c microbial interactions. The advent of oxygenic photosynthetic organisms added a highly dynamic and potentially dominant term to the hydrogen economy of these communities. We have examined the daily variations of hydrogen concentrations in cyanobacteria-dominated microbial mats from hypersaline ponds in Baja California Sur, Mexico. These mats bring together phototrophic and anaerobic bacteria (along with virtually all other trophic groups) in a spatially ordered and chemically dynamic matrix that provides a good analog for early Earth microbial ecosystems. Hydrogen concentrations in the photic zone of the mat can be three orders of magnitude or more higher than in the photic zone, which are, in turn, an order of magnitude higher than in the unconsolidated sediments underlying the mat community. Within the photic zone, hydrogen concentrations can fluctuate dramatically during the diel (24 hour day-night) cycle, ranging from less than 0.001% during the day to nearly 10% at night. The resultant nighttime flux of hydrogen from the mat to the environment was up to 17% of the daytime oxygen flux. The daily pattern observed is highly dependent on cyanobacterial species composition within the mat, with Lyngbya-dominated systems having a much greater dynamic range than those dominated by Microcoleus; this may relate largely to differing degrees of nitrogen-fixing and fermentative activity in the two mats. The greatest H2 concentrations and fluxes were observed in the absence of oxygen, suggesting an important potential feedback control in the context of the evolution of atmospheric composition. The impact of adding this highly dynamic photosynthetic term to the hydrogen economy of early microbial ecosystems must have been substantial. From an evolutionary standpoint, the H2

  14. Uranium Geochemistry in Hypersaline Soda Lakes in Eastern Mongolia

    Science.gov (United States)

    Linhoff, B. S.; Bennett, P.; Puntsag, T.

    2007-12-01

    Extremely high concentrations of uranium were discovered in water samples from hypersaline soda lakes in eastern Mongolia. The origin and fate of uranium in these lakes was examined using geochemical analyses and modeling, using samples collected from five lakes, six wells and one stream. Samples were analyzed for strontium and uranium isotopes, cations and trace metals, anions, alkalinity, and unstable field parameters. The lakes are small, shallow (chlorine to bromine ratios implying groundwater discharges to lake water and is subsequently evaporated. Evaporation is intense with lake waters having average chlorine concentrations 300 times that of well waters. Uranium in well samples is higher than typical for shallow groundwaters (7-101ppb) suggesting discharging groundwater as a probable source of uranium in lake water. Concentrations of uranium in lake water ranges from 57-14,900ppb making these lakes possibly the highest naturally occurring uranium concentration reported. Lake water alkalinity is strongly correlated to uranium abundance suggesting uranium is complexed with carbonate as the aqueous species UO2CO3. Consequently, the extremely high alkalinity of the most alkaline lake (pH = 9.8, 1288.8 meq alk/L) also has the highest uranium concentrations. Stable strontium isotopes were used to assess the degree of water rock interactions and the presence of 90Sr was checked for to test the possibility of input of nuclear fallout. 90Sr was not detected in lake water samples suggesting the high uranium is of natural origins. A large difference in the 87Sr/86Sr ratio was found between groundwater and lake water samples. Groundwater samples displayed large variation in the 87Sr/86Sr ratio (0.70612-0.709776) whereas lake water samples averaged a high radiogenic ratio (0.709432). The large variation in the strontium isotopes in groundwater samples suggests varying degrees of water rock interactions, however the least radiogenic samples likely are derived from

  15. Do copepods inhabit hypersaline waters worldwide? A short review and discussion

    Science.gov (United States)

    Anufriieva, Elena V.

    2015-11-01

    A small number of copepod species have adapted to an existence in the extreme habitat of hypersaline water. 13 copepod species have been recorded in the hypersaline waters of Crimea (the largest peninsula in the Black Sea with over 50 hypersaline lakes). Summarizing our own and literature data, the author concludes that the Crimean extreme environment is not an exception: copepod species dwell in hypersaline waters worldwide. There are at least 26 copepod species around the world living at salinity above 100; among them 12 species are found at salinity higher than 200. In the Crimea Cletocamptus retrogressus is found at salinity 360×10-3 (with a density of 1 320 individuals/m3) and Arctodiaptomus salinus at salinity 300×10-3 (with a density of 343 individuals/m3). Those species are probably the most halotolerant copepod species in the world. High halotolerance of osmoconforming copepods may be explained by exoosmolyte consumption, mainly with food. High tolerance to many factors in adults, availability of resting stages, and an opportunity of long-distance transportation of resting stages by birds and/or winds are responsible for the wide geographic distribution of these halophilic copepods.

  16. Sulfidogenesis in hypersaline chloride-sulfate lakes of Kulunda Steppe (Altai, Russia)

    NARCIS (Netherlands)

    Sorokin, D.Y.; Zacharova, E.E.; Pimenov, N.V.; Tourova, T.P.; Panteleeva, A.N.; Muyzer, G.

    2012-01-01

    The activity and culturable diversity of sulfidogens were investigated in anoxic sediments of four hypersaline lakes with pH 7.6-8.2 in the Kulunda Steppe (Altai, Russia). Sulfate reduction rates were low, varying from 0.1 to 6.0 nmol HS−/(cm3 h) with a maximum in the top 10 cm layer. Potential

  17. A remarkable paradox: Freshwater algae (Botryococcus braunii) in an ancient hypersaline euxinic ecosytem

    NARCIS (Netherlands)

    Sinninghe Damsté, J.S.; Grice, K.; Schouten, S.; Nissenbaum, A.; Charrach, J.

    1998-01-01

    Two relatively immature hypersaline sediments of Miocene/Pliocene age from the Sdom Formation, Dead Sea, Israel were studied using both GC-MS and irm-GCMS analyses. A novel series of extractable organosulfur compounds (OSC) derived from functionalised lipids of freshwater Botryococcus braunii algae

  18. A Modeling Comparison of Methanogenesis from Noncompetitive vs Competitive Substrates in a Simulated Hypersaline Microbial Mat

    Science.gov (United States)

    Decker, K. L.; Potter, C.; Hoehler, T.

    2005-12-01

    The well-documented assumption about methanogens that co-occur in hypersaline mat communities with sulfate-reducing bacteria (SRB) is that they rely entirely on non-competitive substrates for methanogenesis. The reason for this is that during sulfate reduction, sulfur-reducing bacteria efficiently utilize H2, leaving a concentration too low for methanogenesis. Early results from recent work on a hypersaline microbial mat from salt evaporation ponds of Guerrero Negro, Baja, Mexico cast doubt that methanogenesis only occurs via non-competitive substrates, because it shows an excess of H2 in the mat rather than a paucity. We explore the use of our simulation model of the microbial biogeochemistry of a hypersaline mat (named MBGC) to compare methane production rates in a 1 cm thick mat when the methanogens use competitive substrates versus noncompetitive substrates. In the `non-competitive substrate' version of the model, methanogens rely exclusively on methylated amines that are accumulated as compatible solutes in cyanobacteria and released after lysis. In contrast, the `competitive substrate' models examine methanogen use of substrates (such as H2 + acetate) with different SRB population sizes (from absent to low). The comparison of these models of methane and sulfide biogeochemistry of a hypersaline mat has both ecological and geobiological significance, as one hypothesis of Archean microbial mats is that they existed in a low sulfate environment.

  19. Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines

    NARCIS (Netherlands)

    Vavourakis, Charlotte D.; Ghai, Rohit; Rodriguez-Valera, Francisco; Sorokin, Dimitry Y.; Tringe, Susannah G.; Hugenholtz, Philip; Muyzer, Gerard

    2016-01-01

    Soda lakes are salt lakes with a naturally alkaline pH due to evaporative concentration of sodium carbonates in the absence of major divalent cations. Hypersaline soda brines harbor microbial communities with a high species- and strain-level archaeal diversity and a large proportion of still

  20. Metagenomic Insights into the Uncultured Diversity and Physiology of Microbes in Four Hypersaline Soda Lake Brines

    NARCIS (Netherlands)

    Vavourakis, C.D.; Ghai, R.; Rodriguez-valera, F.; Sorokin, D.Y.; Tringe, S.G.; Hugenholtz, P.; Muyzer, G.

    2016-01-01

    Soda lakes are salt lakes with a naturally alkaline pH due to evaporative concentration of sodium carbonates in the absence of major divalent cations. Hypersaline soda brines harbor microbial communities with a high species- and strain-level archaeal diversity and a large proportion of still

  1. An Updated View of the Microbial Diversity in Deep Hypersaline Anoxic Basins

    KAUST Repository

    Mapelli, Francesca; Barozzi, Alan; Michoud, Gregoire; Merlino, Giuseppe; Crotti, Elena; Borin, Sara; Daffonchio, Daniele

    2017-01-01

    bacterial, archaeal, and eukaryotic populations thrive there. In the last few years, cultivation and “omics”-based approaches have been used with samples collected from DHABs around the world, allowing clarifying metabolic processes of paramount ecological

  2. Brackish to hypersaline lake dolostones of the Mississippian

    Science.gov (United States)

    Bennett, Carys; Kearsey, Timothy; Davies, Sarah; Millward, David; Marshall, John

    2016-04-01

    , and 9% of all dolostone beds in the Norham Core are pedogenically altered. The isotopic composition of dolomite beds is δ18O -3.6‰ to -1.7‰ and δ13C -2.6‰ to 1.6‰ which is consistent with a brackish as opposed to marine origin. The dolostones are categorised by their sedimentary composition: Facies 1: Cemented siltstone and sandstone; Facies 2: Homogeneous micrite to micro-crystaline dolomite, within a clay matrix; Facies 3: Bedded dolomite and siltstone; Facies 4: Mixed calcite and dolomite; Facies 5: Dolomite with gypsum and anhydrite. Formation processes are diverse, and include diagenetic cementation (Facies 1), deposition in saline (brackish) lakes (Facies 2), deposition in saline lakes with clastic sediment input (Facies 3), lagoonal to shallow-marine carbonate deposition (Facies 4), and hypersaline lake to sabkha environments (Facies 5). 60% of the beds are facies 2 or 3 and their sedimentology, fauna, ichnofauna and isotopic composition indicate a brackish-water origin. Other Mississippian dolostones from around the world also contain a fairly restricted fauna and have been interpreted as brackish water deposits. The mechanism of dolomite formation under these conditions is discussed. These dolostones provided extensive coastal lakes that may have been an important habitat for tetrapods and other transitional groups during the Mississippian.

  3. Geophysical Investigations of Hypersaline Subglacial Water Systems in the Canadian Arctic: A Planetary Analog

    Science.gov (United States)

    Rutishauser, A.; Sharp, M. J.; Blankenship, D. D.; Skidmore, M. L.; Grima, C.; Schroeder, D. M.; Greenbaum, J. S.; Dowdeswell, J. A.; Young, D. A.

    2017-12-01

    Robotic exploration and remote sensing of the solar system have identified the presence of liquid water beneath ice on several planetary bodies, with evidence for elevated salinity in certain cases. Subglacial water systems beneath Earth's glaciers and ice sheets may provide terrestrial analogs for microbial habitats in such extreme environments, especially those with higher salinity. Geological data suggest that several ice caps and glaciers in the eastern Canadian High Arctic are partially underlain by evaporite-rich sedimentary rocks, and subglacial weathering of these rocks is potentially conducive to the formation of hypersaline subglacial waters. Here, we combine airborne geophysical data with geological constraints to identify and characterize hypersaline subglacial water systems beneath ice caps in Canada's Queen Elizabeth Islands. High relative bedrock reflectivity and specularity anomalies that are apparent in radio-echo sounding data indicate multiple locations where subglacial water is present in areas where modeled ice temperatures at the glacier bed are well below the pressure melting point. This suggests that these water systems are hypersaline, with solute concentrations that significantly depress the freezing point of water. From combined interpretations of geological and airborne-magnetic data, we define the geological context within which these systems have developed, and identify possible solute-sources for the inferred brine-rich water systems. We also derive subglacial hydraulic potential gradients using airborne laser altimetry and ice thickness data, and apply water routing models to derive subglacial drainage pathways. These allow us to identify marine-terminating glaciers where outflow of the brine-rich waters may be anticipated. These hypersaline subglacial water systems beneath Canadian Arctic ice caps and glaciers may represent robust microbial habitats, and potential analogs for brines that may exist beneath ice masses on planetary

  4. A case for the protection of saline and hypersaline environments: a microbiological perspective.

    Science.gov (United States)

    Paul, Varun G; Mormile, Melanie R

    2017-08-01

    Saline and hypersaline environments are known for their unique geochemical properties, microbial populations and aesthetic appeal. Microbial activities and a spectrum of diversity seen in hypersaline environments are distinct with many novel species being identified and reported on a regular basis. Many distinguishing characteristics about the adaptation, morphology, evolutionary history, and potential environmental and biotechnological applications of these organisms are continually investigated. An abundance of interdisciplinary activities and opportunities exist to explore and understand the importance of these environments that potentially hold promising solutions for current and future global issues. Therefore, it is critical to conserve these unique environments and limit the damage inflicted by anthropogenic influences. Increased salinization due to water diversions, undesired freshening, extensive mineral extraction, sewage effluents, pollution due to agricultural runoff and industrial processes, urbanization, and global climate change are factors negatively affecting hypersaline lakes and their surrounding environments. If these harmful effects continue to proceed at the current or even accelerated rates, irrevocable consequences for these environments will occur, resulting in the loss of potential opportunities to gain new knowledge of the biogeochemistry as well as beneficial microbial populations closely associated with these unique and interesting environments. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Trophic ecology and food consumption of fishes in a hypersaline tropical lagoon.

    Science.gov (United States)

    Almeida-Silva, P H; Tubino, R A; Zambrano, L C; Hunder, D A; Garritano, S R; Monteiro-Neto, C

    2015-06-01

    This study evaluated the trophic ecology (diet composition, trophic strategy, similarities and overlap between species, feeding period and food consumption) of six benthivorous fish species in Araruama Lagoon, the largest hypersaline tropical lagoon on the east coast of South America, with an area of 210 km(2) and an average salinity of 52. The burrfish Chilomycterus spinosus fed on Anomalocardia flexuosa shell deposits, ingesting associated fauna. The caitipa mojarra Diapterus rhombeus differed from all other species, having not only the highest proportions of algae and Nematoda, but also feeding on polychaete tentacles. The two mojarras Eucinostomus spp. showed similar trophic strategies, feeding mostly on Polychaeta. The corocoro grunt Orthopristis ruber also fed mainly on Polychaeta, but differed from Eucinostomus spp. in secondary items. The whitemouth croacker Micropogonias furnieri fed mainly on small Crustacea at night, showing a high number of secondary prey items with low frequencies and high prey-specific abundance. The daily food consumption (g food g(-1) fish mass) for Eucinostomus argenteus was 0·012 and was 0·031 and 0·027 for M. furnieri in two different sampling events. The diet similarities between Araruama Lagoon and other brackish and marine environments indicate that hypersalinity is not a predominant factor shaping the trophic ecology of fishes in this lagoon. The stability of hypersaline conditions, without a pronounced gradient, may explain the presence of several euryhaline fishes and invertebrates well adapted to this condition, resulting in a complex food web. © 2015 The Fisheries Society of the British Isles.

  6. Organismal and spatial partitioning of energy and macronutrient transformations within a hypersaline mat

    Energy Technology Data Exchange (ETDEWEB)

    Mobberley, Jennifer M.; Lindemann, Stephen R.; Bernstein, Hans C.; Moran, James J.; Renslow, Ryan S.; Babauta, Jerome; Hu, Dehong; Beyenal, Haluk; Nelson, William C.

    2017-03-21

    Phototrophic mat communities are model ecosystems for studying energy cycling and elemental transformations because complete biogeochemical cycles occur over millimeter-to-centimeter scales. Characterization of energy and nutrient capture within hypersaline phototrophic mats has focused on specific processes and organisms, however little is known about community-wide distribution of and linkages between these processes. To investigate energy and macronutrient capture and flow through a structured community, the spatial and organismal distribution of metabolic functions within a compact hypersaline mat community from Hot Lake have been broadly elucidated through species-resolved metagenomics and geochemical, microbial diversity, and metabolic gradient measurements. Draft reconstructed genomes of abundant organisms revealed three dominant cyanobacterial populations differentially distributed across the top layers of the mat suggesting niche separation along light and oxygen gradients. Many organisms contained diverse functional profiles, allowing for metabolic response to changing conditions within the mat. Organisms with partial nitrogen and sulfur metabolisms were widespread indicating dependence upon metabolite exchange. In addition, changes in community spatial structure were observed over the diel. These results indicate that organisms within the mat community have adapted to the temporally dynamic environmental gradients in this hypersaline mat through metabolic flexibility and fluid syntrophic interactions, including shifts in spatial arrangements.

  7. Identification and characterization of bacteria in a selenium-contaminated hypersaline evaporation pond.

    Science.gov (United States)

    de Souza, M P; Amini, A; Dojka, M A; Pickering, I J; Dawson, S C; Pace, N R; Terry , N

    2001-09-01

    Solar evaporation ponds are commonly used to reduce the volume of seleniferous agricultural drainage water in the San Joaquin Valley, Calif. These hypersaline ponds pose an environmental health hazard because they are heavily contaminated with selenium (Se), mainly in the form of selenate. Se in the ponds may be removed by microbial Se volatilization, a bioremediation process whereby toxic, bioavailable selenate is converted to relatively nontoxic dimethylselenide gas. In order to identify microbes that may be used for Se bioremediation, a 16S ribosomal DNA phylogenetic analysis of an aerobic hypersaline pond in the San Joaquin Valley showed that a previously unaffiliated group of uncultured bacteria (belonging to the order Cytophagales) was dominant, followed by a group of cultured gamma-Proteobacteria which was closely related to Halomonas species. Se K-edge X-ray absorption spectroscopy of selenate-treated bacterial isolates showed that they accumulated a mixture of predominantly selenate and a selenomethionine-like species, consistent with the idea that selenate was assimilated via the S assimilation pathway. One of these bacterial isolates (Halomonas-like strain MPD-51) was the best candidate for the bioremediation of hypersaline evaporation ponds contaminated with high Se concentrations because it tolerated 2 M selenate and 32.5% NaCl, grew rapidly in media containing selenate, and accumulated and volatilized Se at high rates (1.65 microg of Se g of protein(-1) x h(-1)), compared to other cultured bacterial isolates.

  8. [New isolation methods and phylogenetic diversity of actinobacteria from hypersaline beach in Aksu].

    Science.gov (United States)

    Zhang, Yao; Xia, Zhanfeng; Cao, Xinbo; Li, Jun; Zhang, Lili

    2013-08-04

    We explored 4 new methods to improve the isolation of actinobacterial resources from high salt areas. Optimized media based on 4 new strategies were used for isolating actinobacteria from hypersaline beaches. Glycerin-arginine, trehalose-creatine, glycerol-asparticacid, mannitol-casein, casein-mannitol, mannitol-alanine, chitosan-asparagineand GAUZE' No. 1 were used as basic media. New isolation strategy includes 4 methods: ten-fold dilution culture, simulation of the original environment, actinobacterial culture guided by uncultured molecular technology detected, and reference of actinobacterial media for brackish marine environment. The 16S rRNA genes of the isolates were amplified with bacterial universal primers. The results of 16S rRNA gene sequences were compared with sequences obtained from GenBank databases. We constructed phylogenetic tree with the neighbor-joining method. No actinobacterial strains were isolated by 8 media of control group, while 403 strains were isolated by new strategies. The isolates by new methods were members of 14 genera (Streptomyces, Streptomonospora, Saccharomonospora, Plantactinospora, Nocardia, Amycolatopsis, Glycomyces, Micromonospora, Nocardiopsis, Isoptericola, Nonomuraea, Thermobifida, Actinopolyspora, Actinomadura) of 10 families in 8 suborders. The most abundant and diverse isolates were the two suborders of Streptomycineae (69.96%) and Streptosporangineaesuborder (9.68%) within the phylum Actinobacteria, including 9 potential novel species. New isolation methods significantly improved the actinobacterial culturability of hypersaline areas, and obtained many potential novel species, which provided a new and more effective way to isolate actinobacteria resources in hypersaline environments.

  9. Hydrology and Salt Balance in a Large, Hypersaline Coastal Lagoon: Lagoa de Araruama, Brazil

    Science.gov (United States)

    Kjerfve, Björn; Schettini, C. A. F.; Knoppers, Bastiaan; Lessa, Guilherme; Ferreira, H. O.

    1996-06-01

    Lagoa de Araruama in the state of Rio de Janeiro, Brazil, is a hypersaline coastal lagoon as a result of semi-arid climate conditions, a small drainage basin and a choked entrance channel. The lagoon has been continuously hypersaline for at least 4·5 centuries, but the mean salinity has varied substantially. It has recently decreased from 57 to 52 as indicated by density (salinity) measurements between 1965 and 1990. Analysis of more than 20 years of salinity time series data, in addition to monthly lagoon cruises to measure the spatial salinity distribution, indicate that the lagoon salinity largely fluctuates in response to the difference between evaporation and precipitation. The major factor explaining the long-term trend of decreasing salinity in the lagoon is the constant pumping of 1 m 3s -1of freshwater to the communities surrounding the lagoon from an adjacent watershed, and subsequent discharge of this water into Lagoa de Araruama. The net salt budget is primarily a balance between the advective import of salt from the coastal ocean and eddy diffusive export of salt to the ocean, although the extensive mining of salt from the lagoon during past decades is also a small but significant contribution to the salt budget. The flushing half-life is proposed as a useful time scale of water exchange, is calculated based on a combination of hydrological and tidal processes, and is excellent for comparison of lagoons and assessing water quality changes. The flushing half-life measures 83·5 days for Lagoa de Araruama, considerably longer than for most other coastal lagoons. The proposed dredging of a second ocean channel to Lagoa de Araruama is probably not a good idea. It is likely to accelerate the decrease of lagoon salinity and somewhat improve the lagoon water exchange. At the same time, this will eliminate the apparent buffering capacity provided by the hypersaline environment, and thus may potentially cause water quality problems.

  10. Prokaryotic diversity in one of the largest hypersaline coastal lagoons in the world.

    Science.gov (United States)

    Clementino, M M; Vieira, R P; Cardoso, A M; Nascimento, A P A; Silveira, C B; Riva, T C; Gonzalez, A S M; Paranhos, R; Albano, R M; Ventosa, A; Martins, O B

    2008-07-01

    Araruama Lagoon is an environment characterized by high salt concentrations. The low raining and high evaporation rates in this region favored the development of many salty ponds around the lagoon. In order to reveal the microbial composition of this system, we performed a 16S rRNA gene survey. Among archaea, most clones were related to uncultured environmental Euryarchaeota. In lagoon water, we found some clones related to Methanomicrobia and Methanothermococcus groups, while in the saline pond water members related to the genus Haloarcula were detected. Bacterial community was dominated by clones related to Gamma-proteobacteria, Actinobacteria, and Synechococcus in lagoon water, while Salinibacter ruber relatives dominated in saline pond. We also detected the presence of Alpha-proteobacteria, Pseudomonas-like bacteria and Verrucomicrobia. Only representatives of the genus Ralstonia were cosmopolitan, being observed in both systems. The detection of a substantial number of clones related to uncultured archaea and bacteria suggest that the hypersaline waters of Araruama harbor a pool of novel prokaryotic phylotypes, distinct from those observed in other similar systems. We also observed clones related to halophilic genera of cyanobacteria that are specific for each habitat studied. Additionally, two bacterioplankton molecular markers with ecological relevance were analyzed, one is linked to nitrogen fixation (nifH) and the other is linked to carbon fixation by bacterial photosynthesis, the protochlorophyllide genes, revealing a specific genetic distribution in this ecosystem. This is the first study of the biogeography and community structure of microbial assemblages in Brazilian tropical hypersaline environments. This work is directed towards a better understanding of the free-living prokaryotic diversity adapted to life in hypersaline waters.

  11. Anaerobic oxidation of methane by sulfate in hypersaline groundwater of the Dead Sea aquifer

    Science.gov (United States)

    Avrahamov, N; Antler, G; Yechieli, Y; Gavrieli, I; Joye, S B; Saxton, M; Turchyn, A V; Sivan, O

    2014-01-01

    Geochemical and microbial evidence points to anaerobic oxidation of methane (AOM) likely coupled with bacterial sulfate reduction in the hypersaline groundwater of the Dead Sea (DS) alluvial aquifer. Groundwater was sampled from nine boreholes drilled along the Arugot alluvial fan next to the DS. The groundwater samples were highly saline (up to 6300 mm chlorine), anoxic, and contained methane. A mass balance calculation demonstrates that the very low δ13CDIC in this groundwater is due to anaerobic methane oxidation. Sulfate depletion coincident with isotope enrichment of sulfur and oxygen isotopes in the sulfate suggests that sulfate reduction is associated with this AOM. DNA extraction and 16S amplicon sequencing were used to explore the microbial community present and were found to be microbial composition indicative of bacterial sulfate reducers associated with anaerobic methanotrophic archaea (ANME) driving AOM. The net sulfate reduction seems to be primarily controlled by the salinity and the available methane and is substantially lower as salinity increases (2.5 mm sulfate removal at 3000 mm chlorine but only 0.5 mm sulfate removal at 6300 mm chlorine). Low overall sulfur isotope fractionation observed (34ε = 17 ± 3.5‰) hints at high rates of sulfate reduction, as has been previously suggested for sulfate reduction coupled with methane oxidation. The new results demonstrate the presence of sulfate-driven AOM in terrestrial hypersaline systems and expand our understanding of how microbial life is sustained under the challenging conditions of an extremely hypersaline environment. PMID:25039851

  12. [Number of bacteria and features of their activity in hypersaline reservoirs of the Crimea].

    Science.gov (United States)

    Dobrynin, E G

    1979-01-01

    The incidence of bacteria, their biomass production, and heterotrophic assimilation of CO2 by bacterioplankton were studied in the Crimean hypersaline water reservoirs from May to October of 1974. The total incidence of bacteria in the natural brine of these reservoirs varied from 20 to 70 x 10(6) cells per 1 ml. Such a high bacterial number may be caused by the combined action of water evaporation which increased the concentration of bacterial cells and active growth of microflora. Low values of bacterial production and heterotrophic CO2 assimilation should be attributed to weak activity of microflora in the reservoirs.

  13. On the origins of hypersaline groundwater in the Nile Delta Aquifer

    Science.gov (United States)

    van Engelen, Joeri; Oude Essink, Gualbert H. P.; Kooi, Henk; Bierkens, Marc F. P.

    2017-04-01

    The fresh groundwater resources in the Nile Delta, Egypt, are of eminent socio-economic importance. These resources are under major stress due to population growth, the anticipated sea level rise and increased groundwater extraction rates, making fresh water availability the most challenging issue in this area. Up till now, numerous groundwater studies mainly focused on sea water intrusion on the top 100m of the groundwater system and assumed salinities not exceeding that of Mediterranean sea water, as there was no knowledge on groundwater in the deeper coastal parts of the Quaternary Nile Delta aquifer (that ranges up to 1000m depth). Recently, however, the Egyptian Research Institute for Groundwater (RIGW) collected salinity measurements and found a widespread occurrence of "hypersaline" groundwater: groundwater with salinities largely exceeding that of sea water at 600m depth (Nofal et al., 2015). This hypersaline groundwater greatly influences flow patterns and the fresh water potential of the aquifer. This research focuses on the origins of the hypersaline groundwater and the possible processes causing its transport. We consider all relevant salinization processes in the Nile Delta aquifer, over a time domain of up to 2.5 million years, which is the time span in which the aquifer got deposited. The following hypotheses were investigated with a combination of analytical solutions and numerical modelling: upward salt transport due to a) molecular diffusion, b) thermal buoyancy, c) consolidation-induced advection and dispersion, or downward transport due to d) composition buoyancy (salt inversion). We conclude that hypotheses a) and b) can be rejected, but c) and d) are both possible with the available information. An enhanced chemical analysis is suggested for further research, to determine the origins of this hypersaline water. This information in combination with the conclusions drawn in this research will give more insight in the potential amount of non

  14. Brain Transcriptome Profiling Analysis of Nile Tilapia (Oreochromis niloticus Under Long-Term Hypersaline Stress

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2018-03-01

    Full Text Available The fish brain plays an important role in controlling growth, development, reproduction, and adaptation to environmental change. However, few studies stem from the perspective of whole transcriptome change in a fish brain and its response to long-term hypersaline stress. This study compares the differential transcriptomic responses of juvenile Nile tilapia (Oreochromis niloticus maintained for 8 weeks in brackish water (16 practical salinity units, psu and in freshwater. Fish brains from each treatment were collected for RNA-seq analysis to identify potential genes and pathways responding to hypersaline stress. A total of 27,089 genes were annotated, and 391 genes were expressed differently in the salinity treatment. Ten pathways containing 40 differentially expressed genes were identified in the tilapia brain. Antigen processing and presentation and phagosome were the two principally affected pathways in the immune system. Thirty-one of 40 genes were involved in various expressions associated with environmental information processing pathways such as neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, the Jak-STAT signaling pathway, cell adhesion molecules (CAMs, and the PI3K-Akt signaling pathway, which are the upstream pathways for modulation of immunity and osmoregulation. The most-changed genes (>5-fold were all down-regulated, including four growth hormone/prolactin gene families, i.e., prolactin precursor (−10.62, prolactin-1 (−11, somatotropin (−10.15, somatolactin-like (−6.18, and two other genes [thyrotropin subunit beta (−7.73 and gonadotropin subunit beta-2 (−5.06] that stimulated prolactin release in tilapia. The downregulation pattern of these genes corroborates the decrease in tilapia immunity with increasing salinity and reveals an adaptive mechanism of tilapia to long-term hypersaline stress. Ovarian steroidogenesis, isoquinoline alkaloid biosynthesis, and phenylalanine metabolism are the

  15. PHYLOGENETIC ANALYSIS AND AUTECOLOGY OF SPORE-FORMING BACTERIA FROM HYPERSALINE ENVIRONMENTS.

    Science.gov (United States)

    Gladka, G V; Romanovskaya, V A; Tashyreva, H O; Tashyrev, O B

    2015-01-01

    Multi-resistant to extreme factors spore-forming bacteria of Bacillus genus are isolated from hypersaline environments of the Crimea (Ukraine) and the Dead Sea (Israel). Phylogenetic analysis showed distinction of dominating extremophilic culturable species in studied regions. In Crimean environments they are B. mojavensis and B. simplex, in the Dead Sea ecosystem--B. subtilis subsp. spizizenii, B. subtilis subsp. subtilis, B. licheniformis and B. simplex. Isolates are simultaneously halotolerant and resistant to UV radiation. Strains isolated from the Dead Sea and the Crimea environments were resistant to UV: LD90 and LD99.99 made 100-170 J/m2 and 750-1500 J/m2 respectively. Spores showed higher UV-resistance (LD99.99-2500 J/m2) than the vegetative cells. However the number of spores made 0.02-0.007% of the whole cell population, and should not significantly affect the UV LD99.99 value. Isolates of both environments were halotolerant in the range of 0.1-10% NaCl and thermotolerant in the range of 20-50 °C, and didn't grow at 15 °C. Survival strategy of spore-forming bacteria from hypersaline environments under high UV radiation level can be performed by spore formation which minimize cell damage as well as efficient DNA-repair systems that remove damages.

  16. Diversity of virus-host systems in hypersaline Lake Retba, Senegal.

    Science.gov (United States)

    Sime-Ngando, Télesphore; Lucas, Soizick; Robin, Agnès; Tucker, Kimberly Pause; Colombet, Jonathan; Bettarel, Yvan; Desmond, Elie; Gribaldo, Simonetta; Forterre, Patrick; Breitbart, Mya; Prangishvili, David

    2011-08-01

    Remarkable morphological diversity of virus-like particles was observed by transmission electron microscopy in a hypersaline water sample from Lake Retba, Senegal. The majority of particles morphologically resembled hyperthermophilic archaeal DNA viruses isolated from extreme geothermal environments. Some hypersaline viral morphotypes have not been previously observed in nature, and less than 1% of observed particles had a head-and-tail morphology, which is typical for bacterial DNA viruses. Culture-independent analysis of the microbial diversity in the sample suggested the dominance of extremely halophilic archaea. Few of the 16S sequences corresponded to known archeal genera (Haloquadratum, Halorubrum and Natronomonas), whereas the majority represented novel archaeal clades. Three sequences corresponded to a new basal lineage of the haloarchaea. Bacteria belonged to four major phyla, consistent with the known diversity in saline environments. Metagenomic sequencing of DNA from the purified virus-like particles revealed very few similarities to the NCBI non-redundant database at either the nucleotide or amino acid level. Some of the identifiable virus sequences were most similar to previously described haloarchaeal viruses, but no sequence similarities were found to archaeal viruses from extreme geothermal environments. A large proportion of the sequences had similarity to previously sequenced viral metagenomes from solar salterns. © 2010 Society for Applied Microbiology and Blackwell Publishing Ltd.

  17. Nutrient budgets and trophic state in a hypersaline coastal lagoon: Lagoa de Araruama, Brazil

    Science.gov (United States)

    Souza, Marcelo F. L.; Kjerfve, Björn; Knoppers, Bastiaan; Landim de Souza, Weber F.; Damasceno, Raimundo N.

    2003-08-01

    Lagoa de Araruama in the state of Rio de Janeiro, Brazil, is a hypersaline lagoon with salinity varying spatially from 45 to 56. We collected water samples during monthly cruises throughout the lagoon, and along the streams feeding the system, from April 1991 to March 1992. Nutrients and other water quality parameters exhibited great spatial and temporal variations. Mass balance calculations indicate large amounts of anthropogenic nutrient inputs. The data indicate that the lagoon currently is oligotrophic but is in a state of transition to become a mesotrophic system. Molar dissolved inorganic nitrogen:dissolved inorganic phosphorus (DIN/DIP) varied between 2.2:1 and 659:1 with a volume-weighted average of 22:1. The high DIN/DIP ratio contrasts with that found in nearby lagoons, suggesting that phytoplankton primary production is limited by phosphorus in Lagoa de Araruama. The major loss of DIP is apparently driven by biological assimilation and diagenic reactions in the sediments. Calculations indicate that the lagoon is slightly net autotrophic at +0.9 mol C m -2 yr -1. This suggests that the biomass of the primary producers is restricted by phosphorus availability. Phosphorus retention in the sediment and the hypersaline state of the lagoon prevent changes in autotrophic communities and the formation of eutrophic conditions.

  18. Viruses Occur Incorporated in Biogenic High-Mg Calcite from Hypersaline Microbial Mats

    Science.gov (United States)

    De Wit, Rutger; Gautret, Pascale; Bettarel, Yvan; Roques, Cécile; Marlière, Christian; Ramonda, Michel; Nguyen Thanh, Thuy; Tran Quang, Huy; Bouvier, Thierry

    2015-01-01

    Using three different microscopy techniques (epifluorescence, electronic and atomic force microscopy), we showed that high-Mg calcite grains in calcifying microbial mats from the hypersaline lake “La Salada de Chiprana”, Spain, contain viruses with a diameter of 50–80 nm. Energy-dispersive X-ray spectrometer analysis revealed that they contain nitrogen and phosphorus in a molar ratio of ~9, which is typical for viruses. Nucleic acid staining revealed that they contain DNA or RNA. As characteristic for hypersaline environments, the concentrations of free and attached viruses were high (>1010 viruses per g of mat). In addition, we showed that acid treatment (dissolution of calcite) resulted in release of viruses into suspension and estimated that there were ~15 × 109 viruses per g of calcite. We suggest that virus-mineral interactions are one of the possible ways for the formation of nano-sized structures often described as “nanobacteria” and that viruses may play a role in initiating calcification. PMID:26115121

  19. Hypersalinity Acclimation Increases the Toxicity of the Insecticide Phorate in Coho Salmon (Oncorhynchus kisutch)

    Science.gov (United States)

    Lavado, Ramon; Maryoung, Lindley A.; Schlenk, Daniel

    2012-01-01

    Previous studies in euryhaline fish have shown that acclimation to hypersaline environments enhances the toxicity of thioether organophosphate and carbamate pesticides. To better understand the potential mechanism of enhanced toxicity, the effects of the organophosphate insecticide phorate were evaluated in coho salmon (Oncorhynchus kisutch) maintained in freshwater (salinity-dependent manner. In contrast, formation of phorate-oxon (gill; olfactory tissues), phorate sulfone (liver), and phorate-oxon sulfoxide (liver; olfactory tissues) was significantly enhanced in fish acclimated to higher salinities. From previous studies, it was expected that phorate and phorate sulfoxide would be less potent AChE inhibitors than phorate-oxon, with phorate-oxon sulfoxide being the most potent of the compounds tested. This trend was confirmed in this study. In summary, these results suggest that differential expression and/or catalytic activities of Phase I enzymes may be involved to enhance phorate oxidative metabolism and subsequent toxicity of phorate to coho salmon under hypersaline conditions. The outcome may be enhanced fish susceptibility to anticholineterase oxon sulfoxides. PMID:21488666

  20. Halo(natronoarchaea isolated from hypersaline lakes utilize cellulose and chitin as growth substrates

    Directory of Open Access Journals (Sweden)

    Dimitry Y Sorokin

    2015-09-01

    Full Text Available Until recently, extremely halophilic euryarchaeota were considered mostly as aerobic heterotrophs utilizing simple organic compounds as growth substrates. Almost nothing is known on the ability of these prokaryotes to utilize complex polysaccharides as cellulose, xylan and chitin. Although few haloarchaeal cellulases and chitinases were recently characterized, the analysis of currently available haloarchaeal genomes deciphered numerous genes encoding glycosidases (GHs of various families including endoglucanases and chitinases. However, all these haloarchaea were isolated and cultivated on simple substrates and their ability to grow on polysaccharides in situ or in vitro is unknown. This study examines several halo(natronoarchaeal strains from geographically distant hypersaline lakes for the ability to grow on insoluble polymers as a sole growth substrate in salt-saturated mineral media. Some of them belonged to known taxa, while other represented novel phylogenetic lineages within the class Halobacteria. All isolates produced extracellular extremely salt tolerant cellulases or chitinases, either cell-free or cell-bound. Obtained results demonstrate a presence of diverse population of haloarchaeal cellulo/chitinotrophs in hypersaline habitats indicating that euryarchaea participate in aerobic mineralization of recalcitrant organic polymers in salt-saturated environments.

  1. Two fixed ratio dilutions for soil salinity monitoring in hypersaline wetlands.

    Directory of Open Access Journals (Sweden)

    Juan Herrero

    Full Text Available Highly soluble salts are undesirable in agriculture because they reduce yields or the quality of most cash crops and can leak to surface or sub-surface waters. In some cases salinity can be associated with unique history, rarity, or special habitats protected by environmental laws. Yet in considering the measurement of soil salinity for long-term monitoring purposes, adequate methods are required. Both saturated paste extracts, intended for agriculture, and direct surface and/or porewater salinity measurement, used in inundated wetlands, are unsuited for hypersaline wetlands that often are only occasionally inundated. For these cases, we propose the use of 1:5 soil/water (weight/weight extracts as the standard for expressing the electrical conductivity (EC of such soils and for further salt determinations. We also propose checking for ion-pairing with a 1:10 or more diluted extract in hypersaline soils. As an illustration, we apply the two-dilutions approach to a set of 359 soil samples from saline wetlands ranging in ECe from 2.3 dS m(-1 to 183.0 dS m(-1. This easy procedure will be useful in survey campaigns and in the monitoring of soil salt content.

  2. Two fixed ratio dilutions for soil salinity monitoring in hypersaline wetlands.

    Science.gov (United States)

    Herrero, Juan; Weindorf, David C; Castañeda, Carmen

    2015-01-01

    Highly soluble salts are undesirable in agriculture because they reduce yields or the quality of most cash crops and can leak to surface or sub-surface waters. In some cases salinity can be associated with unique history, rarity, or special habitats protected by environmental laws. Yet in considering the measurement of soil salinity for long-term monitoring purposes, adequate methods are required. Both saturated paste extracts, intended for agriculture, and direct surface and/or porewater salinity measurement, used in inundated wetlands, are unsuited for hypersaline wetlands that often are only occasionally inundated. For these cases, we propose the use of 1:5 soil/water (weight/weight) extracts as the standard for expressing the electrical conductivity (EC) of such soils and for further salt determinations. We also propose checking for ion-pairing with a 1:10 or more diluted extract in hypersaline soils. As an illustration, we apply the two-dilutions approach to a set of 359 soil samples from saline wetlands ranging in ECe from 2.3 dS m(-1) to 183.0 dS m(-1). This easy procedure will be useful in survey campaigns and in the monitoring of soil salt content.

  3. Sulphur-containing compounds in sulphur-rich crude oils from hypersaline lake sediments and their geochemical implications

    NARCIS (Netherlands)

    Sinninghe Damsté, J.S.; Guoying, S.; Jiamo, F.; Brassell, S.C.; Gowar, A.P.; Eglinton, G.; Leeuw, J.W. de; Schenck, P.A.

    1987-01-01

    Three sulphur-rich commercial crude oils have been studied, which contain sulphur as high as up to 4 —12 %. These samples were collected from Tertiary hypersaline lake sediments of the Jianghan Basin, Hubei Province at different depths, but above the oil generation threshold (2200m). FPD-GC and

  4. Functional-Structural Analysis of Nitrogen-Cycle Bacteria in a Hypersaline Mat from the Omani Desert

    DEFF Research Database (Denmark)

    Abed, Raeid M M; de Beer, Dirk; Stief, Peter

    2015-01-01

    to sequences from the Rhizobiales group. Sequences of the nosZ gene were the most diverse and clustered with sequences from various genera. Our results demonstrate that the hypersaline mat from Oman harbors nitrifying and denitrifying bacteria with the potential to perform respective processes at detectable...

  5. Wind effects on prey availability: How northward migrating waders use brackish and hypersaline lagoons in the Sivash, Ukraine

    NARCIS (Netherlands)

    Verkuil, Yvonne I.; Koolhaas, Anita; Van Der Winden, Jan

    1993-01-01

    Large numbers of waders migrating northward in spring use the Sivash, a large system of shallow, brackish and hypersaline lagoons in the Black Sea and Azov Sea region (Ukraine). The bottoms of these lagoons are often uncovered by the wind. Hence, for waders the time and space available for feeding

  6. SAR Imagery Applied to the Monitoring of Hyper-Saline Deposits: Death Valley Example (CA)

    Science.gov (United States)

    Lasne, Yannick; Paillou, Philippe; Freeman, Anthony; Chapman, Bruce

    2009-01-01

    The present study aims at understanding the influence of salinity on the dielectric constant of soils and then on the backscattering coeff cients recorded by airborne/spaceborne SAR systems. Based on dielectric measurements performed over hyper-saline deposits in Death Valley (CA), as well as laboratory electromagnetic characterization of salts and water mixtures, we used the dielectric constants as input parameters of analytical IEM simulations to model both the amplitude and phase behaviors of SAR signal at C, and L-bands. Our analytical simulations allow to reproduce specif c copolar signatures recorded in SAR data, corresponding to the Cottonball Basin saltpan. We also propose the copolar backscattering ratio and phase difference as indicators of moistened and salt-affected soils. More precisely, we show that these copolar indicators should allow to monitor the seasonal variations of the dielectric properties of saline deposits.

  7. Use of an Acoustic Doppler Current Profiler (ADCP) to Measure Hypersaline Bidirectional Discharge

    Science.gov (United States)

    Johnson, K.K.; Loving, B.L.; ,

    2002-01-01

    The U.S. Geological Survey measures the exchange of flow between the north and south parts of Great Salt Lake, Utah, as part of a monitoring program. Turbidity and bidirectional flow through the breach in the causeway that divides the lake into two parts makes it difficult to measure discharge with conventional streamflow techniques. An acoustic Doppler current profiler (ADCP) can be used to more accurately define the angles of flow and the location of the interface between the layers of flow. Because of the high salinity levels measured in Great Salt Lake (60-280 parts per thousand), special methods had to be developed to adjust ADCP-computed discharges for the increased speed of sound in hypersaline waters and for water entrained at the interface between flow layers.

  8. Exploiting the aerobic endospore-forming bacterial diversity in saline and hypersaline environments for biosurfactant production.

    Science.gov (United States)

    de Almeida Couto, Camila Rattes; Alvarez, Vanessa Marques; Marques, Joana Montezano; de Azevedo Jurelevicius, Diogo; Seldin, Lucy

    2015-10-28

    Biosurfactants are surface-active biomolecules with great applicability in the food, pharmaceutical and oil industries. Endospore-forming bacteria, which survive for long periods in harsh environments, are described as biosurfactant producers. Although the ubiquity of endospore-forming bacteria in saline and hypersaline environments is well known, studies on the diversity of the endospore-forming and biosurfactant-producing bacterial genera/species in these habitats are underrepresented. In this study, the structure of endospore-forming bacterial communities in sediment/mud samples from Vermelha Lagoon, Massambaba, Dois Rios and Abraão Beaches (saline environments), as well as the Praia Seca salterns (hypersaline environments) was determined via denaturing gradient gel electrophoresis. Bacterial strains were isolated from these environmental samples and further identified using 16S rRNA gene sequencing. Strains presenting emulsification values higher than 30 % were grouped via BOX-PCR, and the culture supernatants of representative strains were subjected to high temperatures and to the presence of up to 20 % NaCl to test their emulsifying activities in these extreme conditions. Mass spectrometry analysis was used to demonstrate the presence of surfactin. A diverse endospore-forming bacterial community was observed in all environments. The 110 bacterial strains isolated from these environmental samples were molecularly identified as belonging to the genera Bacillus, Thalassobacillus, Halobacillus, Paenibacillus, Fictibacillus and Paenisporosarcina. Fifty-two strains showed emulsification values of at least 30%, and they were grouped into 18 BOX groups. The stability of the emulsification values varied when the culture supernatants of representative strains were subjected to high temperatures and to the presence of up to 20% NaCl. The presence of surfactin was demonstrated in one of the most promising strains. The environments studied can harbor endospore

  9. Environmental drivers of the benthic macroinvertebrates community in a hypersaline estuary (Northeastern Brazil

    Directory of Open Access Journals (Sweden)

    Carlinda Railly Ferreira Medeiros

    Full Text Available Abstract Introduction The estuarine community of benthic macroinvertebrates spatially varies in response to changes in environmental variables in these ecosystems. Understanding this variability helps our understanding the mechanisms structuring these communities. Aim Assess the structural aspects of the benthic macroinvertebrate community in a hypersaline estuary, and to relate to environmental variables that influence the community structure along the estuary. Methods The study was conducted at Tubarão river estuary in May 2015. We sampled two estuarine areas (upper and lower, and in each zone were sampled six points composed of two replicas, one sampled in sandy bottom and the other in muddy bottom. Samples of benthic macroinvertebrates and estuarine environmental variables were collected. Environmental drivers of the benthic macroinvertebrate community were determined by Distance-based Linear Models analysis. The contribution of individual species to the dissimilarity between the areas and substrate types were determined by analysis of the percentage of similarity. Results The composition of benthic macroinvertebrate community differed between the upper and lower areas, although it was similar between the muddy and sandy bottoms. The variation in the benthic community between areas was mainly related to the influence of salinity in the upper area. In the lower area, the variation of the macroinvertebrates was related to salinity, associated with other variables in the sandy (temperature, turbidity and dissolved oxygen and muddy (temperature, total dissolved solids and dissolved oxygen substrates. Taxa which contributed most to the dissimilarity between the upper and lower areas were Nereididae (17.89%, Anomalocardia brasiliana (15% and Cirratulidae (10.43%. Conclusions Salinity was the main driver of the structural aspects of the benthic macroinvertebrate community in the upper area of the estuary, although in the lower area a set of

  10. Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

    International Nuclear Information System (INIS)

    Pendashteh, Ali Reza; Fakhru'l-Razi, A.; Chaibakhsh, Naz; Abdullah, Luqman Chuah; Madaeni, Sayed Siavash; Abidin, Zurina Zainal

    2011-01-01

    Highlights: → Hypersaline oily wastewater was treated in a membrane bioreactor. → The effects of salinity and organic loading rate were evaluated. → The system was modeled by neural network and optimized by genetic algorithm. → The model prediction agrees well with experimental values. → The model can be used to obtain effluent characteristics less than discharge limits. - Abstract: A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m 3 day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O and G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m 3 day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.

  11. Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Pendashteh, Ali Reza [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Environmental Research Institute, Iranian Academic Center for Education, Culture and Research (ACECR), Rasht (Iran, Islamic Republic of); Fakhru' l-Razi, A., E-mail: fakhrul@eng.upm.edu.my [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Chaibakhsh, Naz [Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Abdullah, Luqman Chuah [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Madaeni, Sayed Siavash [Chemical Engineering Department, Razi University, Kermanshah (Iran, Islamic Republic of); Abidin, Zurina Zainal [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia)

    2011-08-30

    Highlights: {yields} Hypersaline oily wastewater was treated in a membrane bioreactor. {yields} The effects of salinity and organic loading rate were evaluated. {yields} The system was modeled by neural network and optimized by genetic algorithm. {yields} The model prediction agrees well with experimental values. {yields} The model can be used to obtain effluent characteristics less than discharge limits. - Abstract: A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m{sup 3} day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O and G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m{sup 3} day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.

  12. A microbial oasis in the hypersaline Atacama subsurface discovered by a life detector chip: implications for the search for life on Mars.

    Science.gov (United States)

    Parro, Victor; de Diego-Castilla, Graciela; Moreno-Paz, Mercedes; Blanco, Yolanda; Cruz-Gil, Patricia; Rodríguez-Manfredi, José A; Fernández-Remolar, David; Gómez, Felipe; Gómez, Manuel J; Rivas, Luis A; Demergasso, Cecilia; Echeverría, Alex; Urtuvia, Viviana N; Ruiz-Bermejo, Marta; García-Villadangos, Miriam; Postigo, Marina; Sánchez-Román, Mónica; Chong-Díaz, Guillermo; Gómez-Elvira, Javier

    2011-12-01

    The Atacama Desert has long been considered a good Mars analogue for testing instrumentation for planetary exploration, but very few data (if any) have been reported about the geomicrobiology of its salt-rich subsurface. We performed a Mars analogue drilling campaign next to the Salar Grande (Atacama, Chile) in July 2009, and several cores and powder samples from up to 5 m deep were analyzed in situ with LDChip300 (a Life Detector Chip containing 300 antibodies). Here, we show the discovery of a hypersaline subsurface microbial habitat associated with halite-, nitrate-, and perchlorate-containing salts at 2 m deep. LDChip300 detected bacteria, archaea, and other biological material (DNA, exopolysaccharides, some peptides) from the analysis of less than 0.5 g of ground core sample. The results were supported by oligonucleotide microarray hybridization in the field and finally confirmed by molecular phylogenetic analysis and direct visualization of microbial cells bound to halite crystals in the laboratory. Geochemical analyses revealed a habitat with abundant hygroscopic salts like halite (up to 260 g kg(-1)) and perchlorate (41.13 μg g(-1) maximum), which allow deliquescence events at low relative humidity. Thin liquid water films would permit microbes to proliferate by using detected organic acids like acetate (19.14 μg g(-1)) or formate (76.06 μg g(-1)) as electron donors, and sulfate (15875 μg g(-1)), nitrate (13490 μg g(-1)), or perchlorate as acceptors. Our results correlate with the discovery of similar hygroscopic salts and possible deliquescence processes on Mars, and open new search strategies for subsurface martian biota. The performance demonstrated by our LDChip300 validates this technology for planetary exploration, particularly for the search for life on Mars.

  13. Total- and methyl-mercury concentrations and methylation rates across the freshwater to hypersaline continuum of the Great Salt Lake, Utah, USA

    Science.gov (United States)

    Johnson, William P.; Swanson, Neil; Black, Brooks; Rudd, Abigail; Carling, Gregory; Fernandez, Diego P.; Luft, John; Van Leeuwen, Jim; Marvin-DiPasquale, Mark C.

    2015-01-01

    We examined mercury (Hg) speciation in water and sediment of the Great Salt Lake and surrounding wetlands, a locale spanning fresh to hypersaline and oxic to anoxic conditions, in order to test the hypothesis that spatial and temporal variations in Hg concentration and methylation rates correspond to observed spatial and temporal trends in Hg burdens previously reported in biota. Water column, sediment, and pore water concentrations of methylmercury (MeHg) and total mercury (THg), as well as related aquatic chemical parameters were examined. Inorganic Hg(II)-methylation rates were determined in selected water column and sediment subsamples spiked with inorganic divalent mercury (204Hg(II)). Net production of Me204Hg was expressed as apparent first-order rate constants for methylation (kmeth), which were also expanded to MeHg production potential (MPP) rates via combination with tin reducible ‘reactive’ Hg(II) (Hg(II)R) as a proxy for bioavailable Hg(II). Notable findings include: 1) elevated Hg concentrations previously reported in birds and brine flies were spatially proximal to the measured highest MeHg concentrations, the latter occurring in the anoxic deep brine layer (DBL) of the Great Salt Lake; 2) timing of reduced Hg(II)-methylation rates in the DBL (according to both kmeth and MPP) coincides with reduced Hg burdens among aquatic invertebrates (brine shrimp and brine flies) that act as potential vectors of Hg propagation to the terrestrial ecosystem; 3) values ofkmeth were found to fall within the range reported by other studies; and 4) MPP rates were on the lower end of the range reported in methodologically comparable studies, suggesting the possibility that elevated MeHg in the anoxic deep brine layer results from its accumulation and persistence in this quasi-isolated environment, due to the absence of light (restricting abiotic photo demethylation) and/or minimal microbiological demethylation.

  14. Focused transhepatic electroporation mediated by hypersaline infusion through the portal vein in rat model. Preliminary results on differential conductivity

    Directory of Open Access Journals (Sweden)

    Pañella Clara

    2017-11-01

    Full Text Available Spread hepatic tumours are not suitable for treatment either by surgery or conventional ablation methods. The aim of this study was to evaluate feasibility and safety of selectively increasing the healthy hepatic conductivity by the hypersaline infusion (HI through the portal vein. We hypothesize this will allow simultaneous safe treatment of all nodules by irreversible electroporation (IRE when applied in a transhepatic fashion.

  15. Oil-bioremediation potential of two hydrocarbonoclastic, diazotrophic Marinobacter strains from hypersaline areas along the Arabian Gulf coasts.

    Science.gov (United States)

    Al-Mailem, D M; Eliyas, M; Radwan, S S

    2013-05-01

    Two halophilic, hydrocarbonoclastics bacteria, Marinobacter sedimentarum and M. flavimaris, with diazotrophic potential occured in hypersaline waters and soils in southern and northern coasts of Kuwait. Their numbers were in the magnitude of 10(3) colony forming units g(-1). The ambient salinity in the hypersaline environments was between 3.2 and 3.5 M NaCl. The partial 16S rRNA gene sequences of the two strains showed, respectively, 99 and 100% similarities to the sequences in the GenBank. The two strains failed to grow in the absence of NaCl, exhibited best growth and hydrocarbon biodegradation in the presence of 1 to 1.5 M NaCl, and still grew and maintained their hydrocarbonoclastic activity at salinities up to 5 M NaCl. Both species utilized Tween 80, a wide range of individual aliphatic hydrocarbons (C9-C40) and the aromatics benzene, biphenyl, phenanthrene, anthracene and naphthalene as sole sources of carbon and energy. Experimental evidence was provided for their nitrogen-fixation potential. The two halophilic Marinobacter strains successfully mineralized crude oil in nutrient media as well as in hypersaline soil and water microcosms without the use of any nitrogen fertilizers.

  16. Cyclic heliothermal behaviour of the shallow, hypersaline Lake Hayward, Western Australia

    Science.gov (United States)

    Turner, Jeffrey V.; Rosen, Michael R.; Coshell, Lee; Woodbury, Robert J.

    2018-01-01

    Lake Hayward is one of only about 30 hypersaline lakes worldwide that is meromictic and heliothermal and as such behaves as a natural salt gradient solar pond. Lake Hayward acts as a local groundwater sink, resulting in seasonally variable hypersaline lake water with total dissolved solids (TDS) in the upper layer (mixolimnion) ranging between 56 kg m−3 and 207 kg m−3 and the deeper layer (monimolimnion) from 153 kg m−3 to 211 kg m−3. This is up to six times the salinity of seawater and thus has the highest salinity of all eleven lakes in the Yalgorup National Park lake system. A program of continuously recorded water temperature profiles has shown that salinity stratification initiated by direct rainfall onto the lake’s surface and local runoff into the lake results in the onset of heliothermal conditions within hours of rainfall onset.The lake alternates between being fully mixed and becoming thermally and chemically stratified several times during the annual cycle, with the longest extended periods of heliothermal behaviour lasting 23 and 22 weeks in the winters of 1992 and 1993 respectively. The objective was to quantify the heat budgets of the cyclical heliothermal behaviour of Lake Hayward.During the period of temperature profile logging, the maximum recorded temperature of the monimolimnion was 42.6 °C at which time the temperature of the mixolimnion was 29.4 °C.The heat budget of two closed heliothermal cycles initiated by two rainfall events of 50 mm and 52 mm in 1993 were analysed. The cycles prevailed for 11 and 20 days respectively and the heat budget showed net heat accumulations of 34.2 MJ m−3 and 15.4 MJ m−3, respectively. The corresponding efficiencies of lake heat gain to incident solar energy were 0.17 and 0.18 respectively. Typically, artificial salinity gradient solar ponds (SGSP) have a solar radiation capture efficiencies ranging from 0.10 up to 0.30. Results from Lake Hayward have

  17. Cyclic heliothermal behaviour of the shallow, hypersaline Lake Hayward, Western Australia

    Science.gov (United States)

    Turner, Jeffrey V.; Rosen, Michael R.; Coshell, Lee; Woodbury, Robert J.

    2018-05-01

    Lake Hayward is one of only about 30 hypersaline lakes worldwide that is meromictic and heliothermal and as such behaves as a natural salt gradient solar pond. Lake Hayward acts as a local groundwater sink, resulting in seasonally variable hypersaline lake water with total dissolved solids (TDS) in the upper layer (mixolimnion) ranging between 56 kg m-3 and 207 kg m-3 and the deeper layer (monimolimnion) from 153 kg m-3 to 211 kg m-3. This is up to six times the salinity of seawater and thus has the highest salinity of all eleven lakes in the Yalgorup National Park lake system. A program of continuously recorded water temperature profiles has shown that salinity stratification initiated by direct rainfall onto the lake's surface and local runoff into the lake results in the onset of heliothermal conditions within hours of rainfall onset. The lake alternates between being fully mixed and becoming thermally and chemically stratified several times during the annual cycle, with the longest extended periods of heliothermal behaviour lasting 23 and 22 weeks in the winters of 1992 and 1993 respectively. The objective was to quantify the heat budgets of the cyclical heliothermal behaviour of Lake Hayward. During the period of temperature profile logging, the maximum recorded temperature of the monimolimnion was 42.6 °C at which time the temperature of the mixolimnion was 29.4 °C. The heat budget of two closed heliothermal cycles initiated by two rainfall events of 50 mm and 52 mm in 1993 were analysed. The cycles prevailed for 11 and 20 days respectively and the heat budget showed net heat accumulations of 34.2 MJ m-3 and 15.4 MJ m-3, respectively. The corresponding efficiencies of lake heat gain to incident solar energy were 0.17 and 0.18 respectively. Typically, artificial salinity gradient solar ponds (SGSP) have a solar radiation capture efficiencies ranging from 0.10 up to 0.30. Results from Lake Hayward have implications for comparative biogeochemistry and its

  18. Egg banks in hypersaline lakes of the South-East Europe

    Science.gov (United States)

    Moscatello, Salvatore; Belmonte, Genuario

    2009-01-01

    The cyst banks of 6 coastal hypersaline lakes of South-East Europe have been investigated. The study concerned the bottom sediments of Khersonesskoe and Koyashskoe lakes in the Crimea (Ukraine), Nartë saltworks (Albania), Vecchia Salina at Torre Colimena (Apulia, Italy), Pantano Grande and Pantano Roveto at Vendicari (Sicily, Italy). A total of 19 cyst types were recognised. The cyst banks of lakes were found to be well separated in the representation derived from a statistical multivariate data analysis. For all the lakes examined a comparison was possible between the resting community in sediments (cyst bank) and the active one in the water. The cyst banks contained more species than those recorded over a multi-year sampling effort in the water column. The study of cyst hatching, performed on 5 cyst types under lab conditions, demonstrated that cysts do not hatch under the same conditions. Furthermore, each cyst type shows a wide range of preferential hatching conditions, which allow us to confirm the ecological generalism of salt lake species. PMID:19292906

  19. Quantitative Proteomics Reveals Membrane Protein-Mediated Hypersaline Sensitivity and Adaptation in Halophilic Nocardiopsis xinjiangensis.

    Science.gov (United States)

    Zhang, Yao; Li, Yanchang; Zhang, Yongguang; Wang, Zhiqiang; Zhao, Mingzhi; Su, Na; Zhang, Tao; Chen, Lingsheng; Wei, Wei; Luo, Jing; Zhou, Yanxia; Xu, Yongru; Xu, Ping; Li, Wenjun; Tao, Yong

    2016-01-04

    The genus Nocardiopsis is one of the most dominant Actinobacteria that survives in hypersaline environments. However, the adaptation mechanisms for halophilism are still unclear. Here, we performed isobaric tags for relative and absolute quantification based quantitative proteomics to investigate the functions of the membrane proteome after salt stress. A total of 683 membrane proteins were identified and quantified, of which 126 membrane proteins displayed salt-induced changes in abundance. Intriguingly, bioinformatics analyses indicated that these differential proteins showed two expression patterns, which were further validated by phenotypic changes and functional differences. The majority of ABC transporters, secondary active transporters, cell motility proteins, and signal transduction kinases were up-regulated with increasing salt concentration, whereas cell differentiation, small molecular transporter (ions and amino acids), and secondary metabolism proteins were significantly up-regulated at optimum salinity, but down-regulated or unchanged at higher salinity. The small molecule transporters and cell differentiation-related proteins acted as sensing proteins that played a more important biological role at optimum salinity. However, the ABC transporters for compatible solutes, Na(+)-dependent transporters, and cell motility proteins acted as adaptive proteins that actively counteracted higher salinity stress. Overall, regulation of membrane proteins may provide a major protection strategy against hyperosmotic stress.

  20. Temporal acclimation of Microchloropsis gaditana CCMP526 in response to hypersalinity.

    Science.gov (United States)

    Karthikaichamy, Anbarasu; Deore, Pranali; Srivastava, Sanjeeva; Coppel, Ross; Bulach, Dieter; Beardall, John; Noronha, Santosh

    2018-04-01

    Evaporation from culture ponds and raceways can subject algae to hypersalinity stress, and this is exacerbated by global warming. We investigated the effect of salinity on a marine microalga, Microchloropsis gaditana, which is of industrial significance because of its high lipid-accumulating capability. Both short-term (hours) and medium-term (days) effects of salinity were studied across various salinities (37.5, 55, 70 and 100 PSU). Salinity above 55 PSU suppressed cell growth and specific growth rate was significantly reduced at 100 PSU. Photosynthesis (F v /F m , rETR max and I k ) was severely affected at high salinity conditions. Total carbohydrate per cell increased ∼1.7-fold after 24 h, which is consistent with previous findings that salinity induces osmolyte production to counter osmotic shock. In addition, accumulation of lipid increased by ∼4.6-fold in response to salinity. Our findings indicate a possible mechanism of acclimation to salinity, opening up new frontiers for osmolytes in pharmacological and cosmetics applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Potential for plant growth promotion of rhizobacteria associated with Salicornia growing in Tunisian hypersaline soils.

    Science.gov (United States)

    Mapelli, Francesca; Marasco, Ramona; Rolli, Eleonora; Barbato, Marta; Cherif, Hanene; Guesmi, Amel; Ouzari, Imen; Daffonchio, Daniele; Borin, Sara

    2013-01-01

    Soil salinity and drought are among the environmental stresses that most severely affect plant growth and production around the world. In this study the rhizospheres of Salicornia plants and bulk soils were collected from Sebkhet and Chott hypersaline ecosystems in Tunisia. Depiction of bacterial microbiome composition by Denaturing Gradient Gel Electrophoresis unveiled the occurrence of a high bacterial diversity associated with Salicornia root system. A large collection of 475 halophilic and halotolerant bacteria was established from Salicornia rhizosphere and the surrounding bulk soil, and the bacteria were characterized for the resistance to temperature, osmotic and saline stresses, and plant growth promotion (PGP) features. Twenty Halomonas strains showed resistance to a wide set of abiotic stresses and were able to perform different PGP activities in vitro at 5% NaCl, including ammonia and indole-3-acetic acid production, phosphate solubilisation, and potential nitrogen fixation. By using a gfp-labelled strain it was possible to demonstrate that Halomonas is capable of successfully colonising Salicornia roots in the laboratory conditions. Our results indicated that the culturable halophilic/halotolerant bacteria inhabiting salty and arid ecosystems have a potential to contribute to promoting plant growth under the harsh salinity and drought conditions. These halophilic/halotolerant strains could be exploited in biofertilizer formulates to sustain crop production in degraded and arid lands.

  2. Primary and heterotrophic productivity relate to multikingdom diversity in a hypersaline mat

    Energy Technology Data Exchange (ETDEWEB)

    Bernstein, Hans C.; Brislawn, Colin J.; Dana, Karl; Flores-Wentz, Tobias; Cory, Alexandra B.; Fansler, Sarah J.; Fredrickson, James K.; Moran, James J.

    2017-10-01

    Benthic microbial ecosystems are widespread yet knowledge gaps still remain on the relationships between the diversity of species across kingdoms and productivity. Here, we ask two fundamental questions: 1) How does species diversity relate to the rates of primary and heterotrophic productivity? 2) How do diel variations in light-energy inputs influence productivity and microbiome diversity? To answer these questions, microbial mats from a magnesium sulfate hypersaline Lake were used to establish microcosms. Both the number and relatedness between bacterial and eukaryotic taxa in the microbiome were assayed via amplicon based sequencing of 16S and 18S rRNA genes over two diel cycles. These results correlated with biomass productivity obtained from substrate-specific 13C stable isotope incorporation that enabled comparisons between primary and heterotrophic productivity. Both bacterial and eukaryotic species richness and evenness were related only to the rates of 13C labeled glucose and acetate biomass incorporation. Interestingly, measures of these heterotrophic relationships changed from positive and negative correlations depending on carbon derived from glucose and acetate, respectively. Bacterial and eukaryotic diversity of this ecosystem is also controlled, in part, energy constraints imposed by changing irradiance over a diel cycle.

  3. Electricity generation by anaerobic bacteria and anoxic sediments from hypersaline soda lakes

    Science.gov (United States)

    Miller, L.G.; Oremland, R.S.

    2008-01-01

    Anaerobic bacteria and anoxic sediments from soda lakes produced electricity in microbial fuel cells (MFCs). No electricity was generated in the absence of bacterial metabolism. Arsenate respiring bacteria isolated from moderately hypersaline Mono Lake (Bacillus selenitireducens), and salt-saturated Searles Lake, CA (strain SLAS-1) oxidized lactate using arsenate as the electron acceptor. However, these cultures grew equally well without added arsenate using the MFC anode as their electron acceptor, and in the process oxidized lactate more efficiently. The decrease in electricity generation by consumption of added alternative electron acceptors (i.e. arsenate) which competed with the anode for available electrons proved to be a useful indicator of microbial activity and hence life in the fuel cells. Shaken sediment slurries from these two lakes also generated electricity, with or without added lactate. Hydrogen added to sediment slurries was consumed but did not stimulate electricity production. Finally, electricity was generated in statically incubated "intact" sediment cores from these lakes. More power was produced in sediment from Mono Lake than from Searles Lake, however microbial fuel cells could detect low levels of metabolism operating under moderate and extreme conditions of salt stress. ?? 2008 US Government.

  4. Potential for Plant Growth Promotion of Rhizobacteria Associated with Salicornia Growing in Tunisian Hypersaline Soils

    Directory of Open Access Journals (Sweden)

    Francesca Mapelli

    2013-01-01

    Full Text Available Soil salinity and drought are among the environmental stresses that most severely affect plant growth and production around the world. In this study the rhizospheres of Salicornia plants and bulk soils were collected from Sebkhet and Chott hypersaline ecosystems in Tunisia. Depiction of bacterial microbiome composition by Denaturing Gradient Gel Electrophoresis unveiled the occurrence of a high bacterial diversity associated with Salicornia root system. A large collection of 475 halophilic and halotolerant bacteria was established from Salicornia rhizosphere and the surrounding bulk soil, and the bacteria were characterized for the resistance to temperature, osmotic and saline stresses, and plant growth promotion (PGP features. Twenty Halomonas strains showed resistance to a wide set of abiotic stresses and were able to perform different PGP activities in vitro at 5% NaCl, including ammonia and indole-3-acetic acid production, phosphate solubilisation, and potential nitrogen fixation. By using a gfp-labelled strain it was possible to demonstrate that Halomonas is capable of successfully colonising Salicornia roots in the laboratory conditions. Our results indicated that the culturable halophilic/halotolerant bacteria inhabiting salty and arid ecosystems have a potential to contribute to promoting plant growth under the harsh salinity and drought conditions. These halophilic/halotolerant strains could be exploited in biofertilizer formulates to sustain crop production in degraded and arid lands.

  5. Wind effects on prey availability: How northward migrating waders use brackish and hypersaline lagoons in the sivash, Ukraine

    Science.gov (United States)

    Verkuil, Yvonne; Koolhaas, Anita; Van Der Winden, Jan

    Large numbers of waders migrating northward in spring use the Sivash, a large system of shallow, brackish and hypersaline lagoons in the Black Sea and Azov Sea region (Ukraine). The bottoms of these lagoons are often uncovered by the wind. Hence, for waders the time and space available for feeding depend on wind conditions. In hypersaline lagoons the benthic and pelagic fauna was very poor, consisting mainly of chironomid larvae (0.19 g AFDM·m -2) and brine shrimps Artemia salina, respectively. Brine shrimp abundance was correlated with salinity, wind force, wind direction and water depth. Dunlin Calidris alpina and curlew sandpiper Calidris ferruginea were the only species feeding on brine shrimp. As brine shrimp densities are higher in deeper water, smaller waders such as broad-billed sandpipers Limicola falcinellus are too short-legged to reach exploitable densities of brine shrimp. In brackish lagoons the benthic and pelagic fauna was rich, consisting of polychaetes, bivalves, gastropods, chironomid larvae, isopods and amphipods (8.9 to 30.5 g AFDM·m -2), but there were no brine shrimps. Prey biomass increased with the distance from the coast, being highest on the site that was most frequently inundated. Dunlin, broad-billed sandpiper and grey plover Pluvialis squatarola were the most abundant birds in the brackish lagoon. Due to the effects of wind-tides only a small area was usually available as a feeding site. Gammarus insensibilis was the alternative prey resource in the water layer, and their density varied with wind direction in the same way as brine shrimp. Curlew sandpipers and dunlins in the hypersaline lagoons and broad-billed sandpipers in the brackish lagoons often changed feeding sites, probably following the variation in prey availability. Only because of the large size and variety of lagoons are waders in the Sivash always able to find good feeding sites.

  6. Exploration of microbial diversity and community structure of Lonar Lake: the only hypersaline meteorite crater lake within basalt rock

    Directory of Open Access Journals (Sweden)

    Dhiraj ePaul

    2016-01-01

    Full Text Available Lonar Lake is a hypersaline and hyperalkaline soda lake and the only meteorite impact crater in the world created in the basalt rocks. Although culture-dependent studies have been reported, the comprehensive understanding of microbial community composition and structure of Lonar Lake remain obscure. In the present study, microbial community structure associated with Lonar Lake sediment and water samples was investigated using high throughput sequencing. Microbial diversity analysis revealed the existence of diverse, yet near consistent community composition. The predominance of bacterial phyla Proteobacteria (30% followed by Actinobacteria (24%, Firmicutes (11% and Cyanobacteria (5% was observed. Bacterial phylum Bacteroidetes (1.12%, BD1-5 (0.5%, Nitrospirae (0.41% and Verrucomicrobia (0.28% were detected as relatively minor populations in Lonar Lake ecosystem. Within Proteobacteria, Gammaproteobacteria represented the most abundant population (21-47% among all the sediments and as a minor population in water samples. Bacterial members Proteobacteria and Firmicutes were present significantly higher (p≥0.05 in sediment samples, whereas members of Actinobacteria, Candidate_division_TM7 and Cyanobacteria (p≥0.05 were significantly abundant in water samples. It was noted that compared to other hypersaline soda lakes, Lonar Lake samples formed one distinct cluster, suggesting a different microbial community composition and structure. The present study reports for the first time the different composition of indigenous microbial communities between the sediment and water samples of Lonar Lake. Having better insight of community structure of this Lake ecosystem could be useful in understanding the microbial role in the geochemical cycle for future functional exploration of the unique hypersaline Lonar Lake.

  7. Microbial diversity of the hypersaline and lithium-rich Salar de Uyuni, Bolivia.

    Science.gov (United States)

    Haferburg, Götz; Gröning, Janosch A D; Schmidt, Nadja; Kummer, Nicolai-Alexeji; Erquicia, Juan Carlos; Schlömann, Michael

    2017-06-01

    Salar de Uyuni, situated in the Southwest of the Bolivian Altiplano, is the largest salt flat on Earth. Brines of this athalassohaline hypersaline environment are rich in lithium and boron. Due to the ever- increasing commodity demand, the industrial exploitation of brines for metal recovery from the world's biggest lithium reservoir is likely to increase substantially in the near future. Studies on the composition of halophilic microbial communities in brines of the salar have not been published yet. Here we report for the first time on the prokaryotic diversity of four brine habitats across the salar. The brine is characterized by salinity values between 132 and 177 PSU, slightly acidic to near-neutral pH and lithium and boron concentrations of up to 2.0 and 1.4g/L, respectively. Community analysis was performed after sequencing the V3-V4 region of the 16S rRNA genes employing the Illumina MiSeq technology. The mothur software package was used for sequence processing and data analysis. Metagenomic analysis revealed the occurrence of an exclusively archaeal community comprising 26 halobacterial genera including only recently identified genera like Halapricum, Halorubellus and Salinarchaeum. Despite the high diversity of the halobacteria-dominated community in sample P3 (Shannon-Weaver index H'=3.12 at 3% OTU cutoff) almost 40% of the Halobacteriaceae-assigned sequences could not be classified on the genus level under stringent filtering conditions. Even if the limited taxonomic resolution of the V3-V4 region for halobacteria is considered, it seems likely to discover new, hitherto undescribed genera of the family halobacteriaceae in this particular habitat of Salar de Uyuni in future. Copyright © 2017 Elsevier GmbH. All rights reserved.

  8. Assessment of the trophic state of a hypersaline-carbonatic environment: Vermelha Lagoon (Brazil.

    Directory of Open Access Journals (Sweden)

    Lazaro Laut

    Full Text Available Vermelha Lagoon is a hypersaline shallow transitional ecosystem in the state of Rio de Janeiro (Brazil. This lagoon is located in the protected area of Massambaba, between the cities of Araruama and Saquarema (Brazil, and displays two quite uncommon particularities: it exhibits carbonate sedimentation and displays the development of Holocene stromatolites. Due to both particularities, the salt industry and property speculation have been, increasingly, generating anthropic pressures on this ecosystem. This study aims to apply a multiproxy approach to evaluate the trophic state of Vermelha Lagoon based on physicochemical parameters and geochemical data for the quantification and qualification of organic matter (OM, namely total organic carbon (TOC, total sulfur (TS, total phosphorus (TP and biopolymeric carbon (BPC, including carbohydrates (CHO, lipids (LIP and proteins (PTN. The CHO/TOC ratio values suggest that OM supplied to the sediment is of autochthonous origin and results, essentially, from microbial activity. The cluster analyses allowed the identification of four regions in Vermelha Lagoon. The Region I included stations located in shallow areas of the eastern sector of Vermelha lagoon affected by the impact of the artificial channel of connection with Araruama Lagoon. The Region II, under the influence of salt pans, is characterized by the highest values of BPC, namely CHO promoted by microbiological activity. The Region III include stations spread through the lagoon with high values of dissolved oxygen and lower values of TP. Stromatolites and microbial mattes growth was observed in some stations of this sector. Region IV, where the highest values of TOC and TS were found, represents depocenters of organic matter, located in general in depressed areas. Results of this work evidences that the Vermelha Lagoon is an eutrophic but alkaline and well oxygenated environment (at both water column and surface sediment where the autotrophic

  9. Rapid instrument prototyping with open source hardware and software: Application to water quality in hypersaline estuaries.

    Science.gov (United States)

    Loose, B.; O'Shea, R.

    2016-02-01

    We describe the design and deployment of a water quality sonde that utilizes mobile phone networks for near-real time data telemetry. The REOL or Realtime Estuary Ocean Logger has the unique and valuable capability of logging data internally and simultaneously relaying the information to a webserver using a cellular modem. The internal circuitry consists of a GSM cellular modem, a microcontroller, and an SD card for data storage - these components are low cost, and backed up with circuit diagrams and programming libraries that are published under open source license. This configuration is versatile and is capable of reading instrument output from a broad spectrum of devices, including serial, TTL, analog voltage (0 - 5V), and analog current (typically 4-20 mA). We find the greatest challenges lie in development of smart software that is capable of handling the conditions brought on by this harsh environment. We have programmed the sonde to first determine whether it is submerged by water, and record the temperature on the electronics before deciding whether to telemeter measurements over the cellular network. The Google App EngineTM provides an interactive visualization platform. We have tested the REOL with a variety of water quality sensors. In the configuration described here, we use a thermistor, depth gauge and torroidal conductivity sensor to measure water temperature, water level and conductivity up to 200 mS/cm. The latter is necessary for studies in hypersaline estuaries, where porewater salinity can exceed 100 g/kg. We present data from two estuaries in West Africa and from a longer-term deployment in the Narragansett Bay, Rhode Island.

  10. Fermentation couples Chloroflexi and sulfate-reducing bacteria to Cyanobacteria in hypersaline microbial mats

    Directory of Open Access Journals (Sweden)

    Jackson Z Lee

    2014-02-01

    Full Text Available Past studies of hydrogen cycling in hypersaline microbial mats have shown an active nighttime cycle, with production largely from Cyanobacteria and consumption from sulfate-reducing bacteria (SRB. However, the mechanisms and magnitude of hydrogen cycling have not been extensively studied. Two mats types near Guerrero Negro, Mexico -- permanently submerged Microcoleus microbial mats (GN-S, and intertidal Lyngbya microbial mats (GN-I -- were used in microcosm diel manipulation experiments with 3-(3,4-dichlorophenyl-1,1-dimethylurea (DCMU, molybdate, ammonium addition, and physical disruption to understand the processes responsible for hydrogen cycling between mat microbes. Across microcosms, H2 production occurred under dark anoxic conditions with simultaneous production of a suite of organic acids. H2 production was not significantly affected by inhibition of nitrogen fixation, but rather appears to result from constitutive fermentation of photosynthetic storage products by oxygenic phototrophs. Comparison to accumulated glycogen and to CO2 flux indicated that, in the GN-I mat, fermentation released almost all of the carbon fixed via photosynthesis during the preceding day, primarily as organic acids. Across mats, although oxygenic and anoxygenic phototrophs were detected, cyanobacterial [NiFe]-hydrogenase transcripts predominated. Molybdate inhibition experiments indicated that SRBs from a wide distribution of dsrA phylotypes were responsible for H2 consumption. Incubation with 13C-acetate and nanoSIMS (secondary ion mass-spectrometry indicated higher uptake in both Chloroflexi and SRBs relative to other filamentous bacteria. These manipulations and diel incubations confirm that Cyanobacteria were the main fermenters in Guerrero Negro mats and that the net flux of nighttime fermentation byproducts (not only hydrogen was largely regulated by the interplay between Cyanobacteria, SRBs, and Chloroflexi.

  11. Responses of the Mediterranean seagrass Posidonia oceanica to hypersaline stress duration and recovery.

    Science.gov (United States)

    Marín-Guirao, Lázaro; Sandoval-Gil, Jose Miguel; Bernardeau-Esteller, Jaime; Ruíz, Juan Manuel; Sánchez-Lizaso, Jose Luis

    2013-03-01

    We studied the hypersaline stress responses of the Mediterranean seagrass Posidonia oceanica to determine if the species was tolerant to salinity increases that occur in coastal waters by the desalination industry. Water relations, amino acids, carbohydrates, ions, photosynthesis, respiration, chlorophyll a fluorescence, leaf growth and morphology, and plant mortality were analysed after exposing the mesocosm P. oceanica to a salinity level of 43 for one and three months followed by a month for recovery. One-month saline-stressed plants exhibited sub-lethal effects, including a leaf cell turgor pressure reduction, loss of ionic equilibrium and decreased leaf growth. There were also changes in photoprotective mechanisms, increased concentrations of organic osmolytes in leaves and reduced leaf ageing. All these dysfunctions recovered after removing the stress. After the longer exposure of three months, stress symptoms were much more acute and plants showed an excessive ionic exclusion capacity, increased leaf cell turgor, reduced plant carbon balance, increased leaf aging and leaf decay and increased plant mortality, which indicated that the plant had entered a stage of severe physiological stress. In addition, the long-term saline-stressed plants were not able to recover, still showing sustained injury after the one-month recovery period as reflected by unbalanced leaf ionic content, persistently impaired photosynthesis, decline in internal carbon resources and decreased leaf growth that resulted in undersized plants. In conclusion, P. oceanica was not able to acclimate to the saline conditions tested since it could not reach a new physiological equilibrium or recover after a chronic exposure of 3 months. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Methane as a biomarker in the search for extraterrestrial life: Lessons learned from Mars analog hypersaline environments

    Science.gov (United States)

    Bebout, B.; Tazaz, A.; Kelley, C. A.; Poole, J. A.; Davila, A.; Chanton, J.

    2010-12-01

    Methane released from discrete regions on Mars, together with previous reports of methane determined with ground-based telescopes, has revived the possibility of past or even extant life near the surface on Mars, since 90% of the methane on Earth has a biological origin. This intriguing possibility is supported by the abundant evidence of large bodies of liquid water, and therefore of conditions conducive to the origin of life, early in the planet's history. The detection and analysis of methane is at the core of NASA’s strategies to search for life in the solar system, and on extrasolar planets. Because methane is also produced abiotically, it is important to generate criteria to unambiguously assess biogenicity. The stable carbon and hydrogen isotopic signature of methane, as well as its ratio to other low molecular weight hydrocarbons (the methane/(ethane + propane) ratio: C1/(C2 + C3)), has been suggested to be diagnostic for biogenic methane. We report measurements of the concentrations and stable isotopic signature of methane from hypersaline environments. We focus on hypersaline environments because spectrometers orbiting Mars have detected widespread chloride bearing deposits resembling salt flats. Other evaporitic minerals, e.g., sulfates, are also abundant in several regions, including those studied by the Mars Exploration Rovers. The presence of evaporitic minerals, together with the known evolution of the Martian climate, from warmer and wetter to cold and hyper-arid, suggest that evaporitic and hypersaline environments were common in the past. Hypersaline environments examined to date include salt ponds located in Baja California, the San Francisco Bay, and the Atacama Desert. Methane was found in gas produced both in the sediments, and in gypsum- and halite-hosted (endolithic) microbial communities. Maximum methane concentrations were as high as 40% by volume. The methane carbon isotopic (δ13C) composition showed a wide range of values, from about

  13. Salt resistance genes revealed by functional metagenomics from brines and moderate-salinity rhizosphere within a hypersaline environment

    Directory of Open Access Journals (Sweden)

    Salvador eMirete

    2015-10-01

    Full Text Available Hypersaline environments are considered one of the most extreme habitats on earth and microorganisms have developed diverse molecular mechanisms of adaptation to withstand these conditions. The present study was aimed at identifying novel genes involved in salt resistance from the microbial communities of brines and the rhizosphere from the Es Trenc saltern (Mallorca, Spain. The microbial diversity assessed by pyrosequencing of 16S rRNA gene libraries revealed the presence of communities that are typical in such environments. Metagenomic libraries from brine and rhizosphere samples, were transferred to the osmosensitive strain Escherichia coli MKH13, and screened for salt resistance. As a result, eleven genes that conferred salt resistance were identified, some encoding for well known proteins previously related to osmoadaptation as a glycerol and a proton pump, whereas others encoded for proteins not previously related to this function in microorganisms as DNA/RNA helicases, an endonuclease III (Nth and hypothetical proteins of unknown function. Furthermore, four of the retrieved genes were cloned and expressed in Bacillus subtilis and they also exhibited salt resistance in this bacterium, broadening the spectrum of bacterial species where these genes can operate. This is the first report of salt resistance genes recovered from metagenomes of a hypersaline environment.

  14. 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

  15. 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...

  16. Diversity, distribution, and morphological deformities among living Foraminifera in hypersaline Salwa Bay, Saudi Arabia

    Science.gov (United States)

    Olalekan Amao, Abduljamiu; Kaminski, Michael

    2016-04-01

    The Arabian Gulf is considered a naturally stressed environment due to extremes of salinity and summer temperatures. Anthropogenic influences such as rapid urbanisation projects, maritime transport, and large numbers of desalination plants and oil-related activities compounds the problem. Foraminifera are known to be resilient under such stressful conditions. The purpose of our study is to document the foraminiferal diversity and abundance in the hypersaline Salwa Bay area, near the Saudi Arabian-Qatar Border. We expect the foraminiferal fauna in Salwa Bay to be adapted to extremes in salinity, and we wish to document any species that might be endemic or uniquely adapted to the area. Shannon-Wiener index, relative abundance, species richness, and the percentage of morphological deformities were determined for samples collected from the bay. Salwa Bay is the most saline extension of the Arabian Gulf with high salinity, water temperature and evaporation rate, which is attributed to slow flushing rates, coral reef barriers and higher residency time of the water. Environmental parameters measured at the time of collection were depth (10-110 cm), salinity (52.6-53.0) total dissolved solids (48.8-49.4 g/l), and temperature (27-27.6°C). The foraminiferal assemblages in Salwa Bay are dominated by porcelaneous foraminifera, which include Peneroplis pertusus, Peneroplis planatus, Coscinospira hemprichii and Coscinospira acicularis. The most common species across the sampled transect is Peneroplis pertusus. Hyaline species were also found, but agglutinated foraminifera are absent. Diversity in Salwa Bay is lower compared with localities that have "normal" salinity, and many of the foraminifera display conspicuous morphological deformities. Approximately 55% of the assemblage exhibits mild to severe deformities such as fusion of two adults or double tests, protuberance on the spiral side, abnormal arrangement of the chambers, abnormal shape of the proloculus and modification

  17. Lanthanide behavior in hypersaline evaporation ponds at Guerrero Negro, Baja California, Mexico - an environment with halophiles

    Science.gov (United States)

    Choumiline, K.; López-Cortés, A.; Grajeda-Muñoz, M.; Shumilin, E.; Sapozhnikov, D.

    2013-12-01

    Lanthanides are known, in some cases, to be sensitive to changes in water column or sediment chemistry, a fact that allows them to be used as environmental fingerprints. Nevertheless, the behavior of these elements in hypersaline environments is insufficiently understood, especially in those colonized by bacteria, archaea and eukarya halophiles. Extreme environments like the mentioned exist in the artificially-controlled ponds of the 'Exportadora de Sal' salt-producing enterprise located in Guerrero Negro (Baja California, Mexico). Sediment cores from various ponds were collected, subsampled and measured by ICP-MS and INAA. This allowed differencing the behavior of lanthanides and trace elements under a water column salinity gradient along the evaporation sequence of ponds. Sediment profiles (30 mm long), obtained in Pond 5, dominated by Ca and Mg precipitation and at the same time rich in organic matter due to bacterial mat presence, showed highs and lows of the shale-normalized patterns along different in-core depths. Two groups of elements could be distinguished with similar trends: set A (La, Ce, Pr and Nd) and set B (Sm, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu). The first 'group A' had two prominent peaks at 15 mm and around 22 mm, whereas the 'group B' showed only slight increase at 15 mm and none at 22 mm. Microscopic analyses of prokaryotic cells of a stratified mat in Pond 5 (collected in 2004) showed filamentous bacteria and cyanobacteria with a cell abundance and morphotype richness maxima of prokaryotic cells in a chemocline from 3 mm to 7 mm depth which co-exists nine morphotypes of aerobic and anaerobic prokaryotes Microcoleus chthonoplastes, Leptolyngbya, Cyanothece, Geitlerinema, Spirulina, Chloroflexus, Beggiatoa, Chromatium and Thioploca. Below the 7 mm depth, oxygenic photosynthesis depletes and sulfur reducing compounds increase. The highs of the shale-normalized lanthanide contents of the 'group A' (at 15 mm depth) seem to correlate with the

  18. Biological Characterization of Microenvironments in a Hypersaline Cold Spring Mars Analog

    Directory of Open Access Journals (Sweden)

    Haley M. Sapers

    2017-12-01

    Full Text Available While many habitable niches on Earth are characterized by permanently cold conditions, little is known about the spatial structure of seasonal communities and the importance of substrate-cell associations in terrestrial cyroenvironments. Here we use the 16S rRNA gene as a marker for genetic diversity to compare two visually distinct but spatially integrated surface microbial mats on Axel Heiberg Island, Canadian high arctic, proximal to a perennial saline spring. This is the first study to describe the bacterial diversity in microbial mats on Axel Heiberg Island. The hypersaline springs on Axel Heiberg represent a unique analog to putative subsurface aquifers on Mars. The Martian subsurface represents the longest-lived potentially habitable environment on Mars and a better understanding of the microbial communities on Earth that thrive in analog conditions will help direct future life detection missions. The microbial mats sampled on Axel Heiberg are only visible during the summer months in seasonal flood plains formed by melt water and run-off from the proximal spring. Targeted-amplicon sequencing revealed that not only does the bacterial composition of the two mat communities differ substantially from the sediment community of the proximal cold spring, but that the mat communities are distinct from any other microbial community in proximity to the Arctic springs studied to date. All samples are dominated by Gammaproteobacteria: Thiotichales is dominant within the spring samples while Alteromonadales comprises a significant component of the mat communities. The two mat samples differ in their Thiotichales:Alteromonadales ratio and contribution of Bacteroidetes to overall diversity. The red mats have a greater proportion of Alteromonadales and Bacteroidetes reads. The distinct bacterial composition of the mat bacterial communities suggests that the spring communities are not sourced from the surface, and that seasonal melt events create

  19. Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines

    Directory of Open Access Journals (Sweden)

    Charlotte Dafni Vavourakis

    2016-02-01

    Full Text Available Soda lakes are salt lakes with a naturally alkaline pH due to evaporative concentration of sodium carbonates in the absence of major divalent cations. Hypersaline soda brines harbor microbial communities with a high species- and strain-level archaeal diversity and a large proportion of still uncultured poly-extremophiles compared to neutral brines of similar salinities. We present the first ‘metagenomic snapshots’ of microbial communities thriving in the brines of four shallow soda lakes from the Kulunda Steppe (Altai, Russia covering a salinity range from 170 to 400 g/L. Both amplicon sequencing of 16S rRNA fragments and direct metagenomic sequencing showed that the top-level taxa abundance was linked to the ambient salinity: Bacteroidetes, Alpha- and Gammaproteobacteria were dominant below a salinity of 250 g/L, Euryarchaeota at higher salinities. Within these taxa, amplicon sequences related to Halorubrum, Natrinema, Gracilimonas, purple non-sulfur bacteria (Rhizobiales, Rhodobacter and Rhodobaca and chemolithotrophic sulfur oxidizers (Thioalkalivibrio were highly abundant. Twenty-four draft population genomes from novel members and ecotypes within the Nanohaloarchaea, Halobacteria and Bacteroidetes were reconstructed to explore their metabolic features, environmental abundance and strategies for osmotic adaptation. The Halobacteria- and Bacteroidetes-related draft genomes belong to putative aerobic heterotrophs, likely with the capacity to ferment sugars in the absence of oxygen. Members from both taxonomic groups are likely involved in primary organic carbon degradation, since some of the reconstructed genomes encode the ability to hydrolyze recalcitrant substrates, such as cellulose and chitin. Putative sodium-pumping rhodopsins were found in both a Flavobacteriaceae- and a Chitinophagaceae-related draft genome. The predicted proteomes of both the latter and a Rhodothermaceae-related draft genome were indicative of a

  20. Anaerobic halo- alkaliphilic bacterial community of athalassic, hypersaline Mono lake and Owens Lake in California

    Science.gov (United States)

    Pikuta, Elena V.; Detkova, Ekaterina N.; Bej, Asim K.; Marsic, Damien; Hoover, Richard B.

    2003-02-01

    The bacterial diversity of microbial extremophiles from the meromictic, hypersaline Mono Lake and a small evaporite pool in Owens Lake of California was studied. In spite of these regions had differing mineral background and different concentrations of NaCl in water they contain the same halo- alkaliphiles anaerobic bacterial community. Three new species of bacteria were detected in this community: primary anaerobe, dissipotrophic saccharolytic spirochete Spirochaeta americana strain AspG1T, primary anaerobe which is proteolytic Tindallia californiensis strain APOT, and secondary anaerobe, hydrogen using Desulfonatronum thiodismutans strain MLF1T, which is sulfate- reducer with chemo-litho-autotrophic metabolism. All of these bacteria are obligate alkaliphiles and dependent upon Na+ ions and CO32- ions in growth mediums. It is interesting that closest relationships for two of these species were isolates from samples of equatorial African soda Magadi lake: Spirochaeta americana AspG1T has 99.4% similarity on 16S rDNA- analyses with Spirochaeta alkalica Z- 7491T, and Tindallia californiensis APOT has 99.1% similarity with Tindallia magadiensis Z-7934T. But result of DNA-DNA- hybridization demonstrated less then 50% similarity between Spirochaeta americana AspG1T and Spirochaeta alkalica Z-7491T. Percent of homology between Tindallia californiensis APOT and Tindallia magadiensis Z-7934T is only 55%. The sulfate-reducer from the alkalic anaerobic community of Magadi lake Desulfonatronovibrio hydrogenovorans Z-7935T was phylogenetically distant from this sulfate-reducer in Mono lake, but genetically closer (99.7% similarity) to the sulfate-reducer, isolated from Central Asian alkalic lake Khadyn in Siberia Desulfonatronum lacustre Z-7951T. The study of key enzymes (hydrogenase and CO- hydrogenase) in Tindallia californiensis APOT and Desulfonatronum thiodismutans MLF1T showed the presence of high activity of both the enzymes in first and only hydrogenase in second

  1. Desulfonatronovibrio halophilus sp. nov., a novel moderately halophilic sulfate-reducing bacterium from hypersaline chloride-sulfate lakes in Central Asia

    NARCIS (Netherlands)

    Sorokin, D.Y.; Tourova, T.P.; Abbas, B.; Suhacheva, M.V.; Muyzer, G.

    2012-01-01

    Four strains of lithotrophic sulfate-reducing bacteria (SRB) have been enriched and isolated from anoxic sediments of hypersaline chloride-sulfate lakes in the Kulunda Steppe (Altai, Russia) at 2 M NaCl and pH 7.5. According to the 16S rRNA gene sequence analysis, the isolates were closely related

  2. Desulfonatronovibrio halophilus sp. nov., a novel moderately halophilic sulfate-reducing bacterium from hypersaline chloride–sulfate lakes in Central Asia

    NARCIS (Netherlands)

    Sorokin, D.Y.; Tourova, T.P.; Abbas, B.; Suhacheva, M.V.; Muyzer, G.

    2012-01-01

    Four strains of lithotrophic sulfate-reducing bacteria (SRB) have been enriched and isolated from anoxic sediments of hypersaline chloride–sulfate lakes in the Kulunda Steppe (Altai, Russia) at 2 M NaCl and pH 7.5. According to the 16S rRNA gene sequence analysis, the isolates were closely related

  3. Structural and functional analysis of a microbial mat ecosystem from a unique permanent hypersaline inland lake: ‘La Salada de Chiprana’ (NE Spain)

    DEFF Research Database (Denmark)

    Jonkers, Henk M.; Ludwig, Rebecca; De Wit, Rutger

    2003-01-01

    The benthic microbial mat community of the only permanent hypersaline natural inland lake of Western Europe, ‘La Salada de Chiprana’, northeastern Spain, was structurally and functionally analyzed. The ionic composition of the lake water is characterized by high concentrations of magnesium...

  4. Expression of Key Ion Transporters in the Gill and Esophageal-Gastrointestinal Tract of Euryhaline Mozambique Tilapia Oreochromis mossambicus Acclimated to Fresh Water, Seawater and Hypersaline Water

    Science.gov (United States)

    Li, Zhengjun; Lui, Eei Yin; Wilson, Jonathan M.; Ip, Yuen Kwong; Lin, Qingsong; Lam, Toong Jin; Lam, Siew Hong

    2014-01-01

    The ability of euryhaline Mozambique tilapia to tolerate extreme environmental salinities makes it an excellent model for investigating iono-regulation. This study aimed to characterize and fill important information gap of the expression levels of key ion transporters for Na+ and Cl− in the gill and esophageal-gastrointestinal tract of Mozambique tilapia acclimated to freshwater (0 ppt), seawater (30 ppt) and hypersaline (70 ppt) environments. Among the seven genes studied, it was found that nkcc2, nkcc1a, cftr, nka-α1 and nka-α3, were more responsive to salinity challenge than nkcc1b and ncc within the investigated tissues. The ncc expression was restricted to gills of freshwater-acclimated fish while nkcc2 expression was restricted to intestinal segments irrespective of salinity challenge. Among the tissues investigated, gill and posterior intestine were found to be highly responsive to salinity changes, followed by anterior and middle intestine. Both esophagus and stomach displayed significant up-regulation of nka-α1 and nka-α3, but not nkcc isoforms and cftr, in hypersaline-acclimated fish suggesting a response to hypersalinity challenge and involvement of other forms of transporters in iono-regulation. Changes in gene expression levels were partly corroborated by immunohistochemical localization of transport proteins. Apical expression of Ncc was found in Nka-immunoreactive cells in freshwater-acclimated gills while Nkcc co-localized with Nka-immunoreactive cells expressing Cftr apically in seawater- and hypersaline-acclimated gills. In the intestine, Nkcc-stained apical brush border was found in Nka-immunoreactive cells at greater levels under hypersaline conditions. These findings provided new insights into the responsiveness of these genes and tissues under hypersalinity challenge, specifically the posterior intestine being vital for salt absorption and iono-osmoregulation in the Mozambique tilapia; its ability to survive in hypersalinity may be in

  5. Functional Role of Native and Invasive Filter-Feeders, and the Effect of Parasites: Learning from Hypersaline Ecosystems.

    Science.gov (United States)

    Sánchez, Marta I; Paredes, Irene; Lebouvier, Marion; Green, Andy J

    2016-01-01

    Filter-feeding organisms are often keystone species with a major influence on the dynamics of aquatic ecosystems. Studies of filtering rates in such taxa are therefore vital in order to understand ecosystem functioning and the impact of natural and anthropogenic stressors such as parasites, climate warming and invasive species. Brine shrimps Artemia spp. are the dominant grazers in hypersaline systems and are a good example of such keystone taxa. Hypersaline ecosystems are relatively simplified environments compared with much more complex freshwater and marine ecosystems, making them suitable model systems to address these questions. The aim of this study was to compare feeding rates at different salinities and temperatures between clonal A. parthenogenetica (native to Eurasia and Africa) and the invasive American brine shrimp A. franciscana, which is excluding native Artemia from many localities. We considered how differences observed in laboratory experiments upscale at the ecosystem level across both spatial and temporal scales (as indicated by chlorophyll-a concentration and turbidity). In laboratory experiments, feeding rates increased at higher temperatures and salinities in both Artemia species and sexes, whilst A. franciscana consistently fed at higher rates. A field study of temporal dynamics revealed significantly higher concentrations of chlorophyll-a in sites occupied by A. parthenogenetica, supporting our experimental findings. Artemia parthenogenetica density and biomass were negatively correlated with chlorophyll-a concentration at the spatial scale. We also tested the effect of cestode parasites, which are highly prevalent in native Artemia but much rarer in the invasive species. The cestodes Flamingolepis liguloides and Anomotaenia tringae decreased feeding rates in native Artemia, whilst Confluaria podicipina had no significant effect. Total parasite prevalence was positively correlated with turbidity. Overall, parasites are likely to reduce

  6. Isotopic composition of methane and inferred methanogenic substrates along a salinity gradient in a hypersaline microbial mat system.

    Science.gov (United States)

    Potter, Elyn G; Bebout, Brad M; Kelley, Cheryl A

    2009-05-01

    The importance of hypersaline environments over geological time, the discovery of similar habitats on Mars, and the importance of methane as a biosignature gas combine to compel an understanding of the factors important in controlling methane released from hypersaline microbial mat environments. To further this understanding, changes in stable carbon isotopes of methane and possible methanogenic substrates in microbial mat communities were investigated as a function of salinity here on Earth. Microbial mats were sampled from four different field sites located within salterns in Baja California Sur, Mexico. Salinities ranged from 50 to 106 parts per thousand (ppt). Pore water and microbial mat samples were analyzed for the carbon isotopic composition of dissolved methane, dissolved inorganic carbon (DIC), and mat material (particulate organic carbon or POC). The POC delta(13)C values ranged from -6.7 to -13.5 per thousand, and DIC delta(13)C values ranged from -1.4 to -9.6 per thousand. These values were similar to previously reported values. The delta(13)C values of methane ranged from -49.6 to -74.1 per thousand; the methane most enriched in (13)C was obtained from the highest salinity area. The apparent fractionation factors between methane and DIC, and between methane and POC, within the mats were also determined and were found to change with salinity. The apparent fractionation factors ranged from 1.042 to 1.077 when calculated using DIC and from 1.038 to 1.068 when calculated using POC. The highest-salinity area showed the least fractionation, the moderate-salinity area showed the highest fractionation, and the lower-salinity sites showed fractionations that were intermediate. These differences in fractionation are most likely due to changes in the dominant methanogenic pathways and substrates used at the different sites because of salinity differences.

  7. Constraints on evaporation and dilution of terminal, hypersaline lakes under negative water balance: The Dead Sea, Israel

    Science.gov (United States)

    Zilberman, Tami; Gavrieli, Ittai; Yechieli, Yoseph; Gertman, Isaac; Katz, Amitai

    2017-11-01

    The response of hypersaline terminal lakes to negative water balance was investigated by studying brines evaporating to extreme salinities in sinkholes along the western coast of the Dead Sea and during on-site evaporation experiments of the Dead Sea brine. Density and temperature were determined in the field and all samples were analyzed for their major and a few minor solutes. The activity of H2O (aH2O) in the brines was calculated, and the degree of evaporation (DE) was established using Sr2+as a conservative solute. The relations between density and water activity were obtained by polynomial regression, and the relation between the lake's volume and level was established using Hall's (1996) hypsographic model for the Dead Sea basin. Relating the results to the modern, long-term relative humidity (RH) over the basin shows that (a) The lowermost attainable level of a terminal lake undergoing evaporation with no inflow is dictated by the median RH; this level represents equilibrium between the brine's aH2O and RH; (b) Small, saline water bodies with high surface to volume ratios (A/V), such as the hypersaline brines in the sinkholes, are very sensitive to short term changes in RH; in these, the brines' aH2O closely follows the seasonal changes; (c) the level decline of the Dead Sea due to evaporation under present climatic conditions and assuming no inflow to the lake may continue down to 516-537 m below mean sea level (bmsl), corresponding to a water activity range of 0.46-0.39 in its brine, in equilibrium with the overlying relative air humidity; this suggests that the lake level cannot drop more than ∼100 m from its present level; and (d) The maximum RH values that existed over the precursor lake of the Dead Sea (Lake Lisan) during geologically reconstructed minima levels can be similarly calculated.

  8. Macro and Microelements Drive Diversity and Composition of Prokaryotic and Fungal Communities in Hypersaline Sediments and Saline-Alkaline Soils.

    Science.gov (United States)

    Liu, Kaihui; Ding, Xiaowei; Tang, Xiaofei; Wang, Jianjun; Li, Wenjun; Yan, Qingyun; Liu, Zhenghua

    2018-01-01

    Understanding the effects of environmental factors on microbial communities is critical for microbial ecology, but it remains challenging. In this study, we examined the diversity (alpha diversity) and community compositions (beta diversity) of prokaryotes and fungi in hypersaline sediments and salinized soils from northern China. Environmental variables were highly correlated, but they differed significantly between the sediments and saline soils. The compositions of prokaryotic and fungal communities in the hypersaline sediments were different from those in adjacent saline-alkaline soils, indicating a habitat-specific microbial distribution pattern. The macroelements (S, P, K, Mg, and Fe) and Ca were, respectively, correlated closely with the alpha diversity of prokaryotes and fungi, while the macronutrients (e.g., Na, S, P, and Ca) were correlated with the prokaryotic and fungal beta-diversity ( P ≤ 0.05). And, the nine microelements (e.g., Al, Ba, Co, Hg, and Mn) and micronutrients (Ba, Cd, and Sr) individually shaped the alpha diversity of prokaryotes and fungi, while the six microelements (e.g., As, Ba, Cr, and Ge) and only the trace elements (Cr and Cu), respectively, influenced the beta diversity of prokaryotes and fungi ( P analysis (VPA) showed that environmental variables jointly explained 55.49% and 32.27% of the total variation for the prokaryotic and fungal communities, respectively. Together, our findings demonstrate that the diversity and community composition of the prokaryotes and fungi were driven by different macro and microelements in saline habitats, and that geochemical elements could more widely regulate the diversity and community composition of prokaryotes than these of fungi.

  9. Macro and Microelements Drive Diversity and Composition of Prokaryotic and Fungal Communities in Hypersaline Sediments and Saline–Alkaline Soils

    Science.gov (United States)

    Liu, Kaihui; Ding, Xiaowei; Tang, Xiaofei; Wang, Jianjun; Li, Wenjun; Yan, Qingyun; Liu, Zhenghua

    2018-01-01

    Understanding the effects of environmental factors on microbial communities is critical for microbial ecology, but it remains challenging. In this study, we examined the diversity (alpha diversity) and community compositions (beta diversity) of prokaryotes and fungi in hypersaline sediments and salinized soils from northern China. Environmental variables were highly correlated, but they differed significantly between the sediments and saline soils. The compositions of prokaryotic and fungal communities in the hypersaline sediments were different from those in adjacent saline–alkaline soils, indicating a habitat-specific microbial distribution pattern. The macroelements (S, P, K, Mg, and Fe) and Ca were, respectively, correlated closely with the alpha diversity of prokaryotes and fungi, while the macronutrients (e.g., Na, S, P, and Ca) were correlated with the prokaryotic and fungal beta-diversity (P ≤ 0.05). And, the nine microelements (e.g., Al, Ba, Co, Hg, and Mn) and micronutrients (Ba, Cd, and Sr) individually shaped the alpha diversity of prokaryotes and fungi, while the six microelements (e.g., As, Ba, Cr, and Ge) and only the trace elements (Cr and Cu), respectively, influenced the beta diversity of prokaryotes and fungi (P analysis (VPA) showed that environmental variables jointly explained 55.49% and 32.27% of the total variation for the prokaryotic and fungal communities, respectively. Together, our findings demonstrate that the diversity and community composition of the prokaryotes and fungi were driven by different macro and microelements in saline habitats, and that geochemical elements could more widely regulate the diversity and community composition of prokaryotes than these of fungi. PMID:29535703

  10. Hypersalinity reduces the risk of cyanide toxicosis to insectivorous bats interacting with wastewater impoundments at gold mines.

    Science.gov (United States)

    Griffiths, Stephen R; Donato, David B; Lumsden, Linda F; Coulson, Graeme

    2014-01-01

    Wildlife and livestock that ingest bioavailable cyanide compounds in gold mining tailings dams are known to experience cyanide toxicosis. Elevated levels of salinity in open impoundments have been shown to prevent wildlife cyanide toxicosis by reducing drinking and foraging. This finding appears to be consistent for diurnal wildlife interacting with open impoundments, however the risks to nocturnal wildlife of cyanide exposure are unknown. We investigated the activity of insectivorous bats in the airspace above both fresh (potable to wildlife) and saline water bodies at two gold mines in the goldfields of Western Australian. During this study, cyanide-bearing solutions stored in open impoundments at both mine sites were hypersaline (range=57,000-295,000 mg/L total dissolved solids (TDS)), well above known physiological tolerance of any terrestrial vertebrate. Bats used the airspace above each water body monitored, but were more active at fresh than saline water bodies. In addition, considerably more terminal echolocation buzz calls were recorded in the airspace above fresh than saline water bodies at both mine sites. However, it was not possible to determine whether these buzz calls corresponded to foraging or drinking bouts. No drinking bouts were observed in 33 h of thermal video footage recorded at one hypersaline tailings dam, suggesting that this water is not used for drinking. There is no information on salinity tolerances of bats, but it could be assumed that bats would not tolerate salinity in drinking water at concentrations greater than those documented as toxic for saline-adapted terrestrial wildlife. Therefore, when managing wastewater impoundments at gold mines to avoid wildlife mortalities, adopting a precautionary principle, bats are unlikely to drink solutions at salinity levels ≥50,000 mg/L TDS. © 2013 Published by Elsevier Inc.

  11. Focused Transhepatic Electroporation Mediated by Hypersaline Infusion through the Portal Vein in Rat Model. Preliminary Results on Differential Conductivity.

    Science.gov (United States)

    Pañella, Clara; Castellví, Quim; Moll, Xavier; Quesada, Rita; Villanueva, Alberto; Iglesias, Mar; Naranjo, Dolores; Sánchez-Velázquez, Patricia; Andaluz, Anna; Grande, Luís; Ivorra, Antoni; Burdío, Fernando

    2017-12-01

    Spread hepatic tumours are not suitable for treatment either by surgery or conventional ablation methods. The aim of this study was to evaluate feasibility and safety of selectively increasing the healthy hepatic conductivity by the hypersaline infusion (HI) through the portal vein. We hypothesize this will allow simultaneous safe treatment of all nodules by irreversible electroporation (IRE) when applied in a transhepatic fashion. Sprague Dawley (Group A, n = 10) and Athymic rats with implanted hepatic tumour (Group B, n = 8) were employed. HI was performed (NaCl 20%, 3.8 mL/Kg) by trans-splenic puncture. Deionized serum (40 mL/Kg) and furosemide (2 mL/Kg) were simultaneously infused through the jugular vein to compensate hypernatremia. Changes in conductivity were monitored in the hepatic and tumour tissue. The period in which hepatic conductivity was higher than tumour conductivity was defined as the therapeutic window (TW). Animals were monitored during 1-month follow-up. The animals were sacrificed and selective samples were used for histological analysis. The overall survival rate was 82.4% after the HI protocol. The mean maximum hepatic conductivity after HI was 2.7 and 3.5 times higher than the baseline value, in group A and B, respectively. The mean maximum hepatic conductivity after HI was 1.4 times higher than tumour tissue in group B creating a TW to implement selective IRE. HI through the portal vein is safe when the hypersaline overload is compensated with deionized serum and it may provide a TW for focused IRE treatment on tumour nodules.

  12. A deep sea community at the Kebrit brine pool in the Red Sea

    KAUST Repository

    Vestheim, Hege

    2015-02-26

    Approximately 25 deep sea brine pools occur along the mid axis of the Red Sea. These hypersaline, anoxic, and acidic environments have previously been reported to host diverse microbial communities. We visited the Kebrit brine pool in April 2013 and found macrofauna present just above the brine–seawater interface (~1465 m). In particular, inactive sulfur chimneys had associated epifauna of sea anemones, sabellid type polychaetes, and hydroids, and infauna consisting of capitellid polychaetes, gastropods of the genus Laeviphitus (fam. Elachisinidae), and top snails of the family Cocculinidae. The deep Red Sea generally is regarded as extremely poor in benthos. We hypothesize that the periphery along the Kebrit holds increased biomass and biodiversity that are sustained by prokaryotes associated with the brine pool or co-occurring seeps.

  13. Screening of polyhydroxyalkanoate-producing bacteria and PhaC-encoding genes in two hypersaline microbial mats from Guerrero Negro, Baja California Sur, Mexico

    Directory of Open Access Journals (Sweden)

    Carolina A. Martínez-Gutiérrez

    2018-05-01

    Full Text Available Hypersaline microbial mats develop through seasonal and diel fluctuations, as well as under several physicochemical variables. Hence, resident microorganisms commonly employ strategies such as the synthesis of polyhydroxyalkanoates (PHAs in order to resist changing and stressful conditions. However, the knowledge of bacterial PHA production in hypersaline microbial mats has been limited to date, particularly in regard to medium-chain length PHAs (mcl-PHAs, which have biotechnological applications due to their plastic properties. The aim of this study was to obtain evidence for PHA production in two hypersaline microbial mats of Guerrero Negro, Mexico by searching for PHA granules and PHA synthase genes in isolated bacterial strains and environmental samples. Six PHA-producing strains were identified by 16S rRNA gene sequencing; three of them corresponded to a Halomonas sp. In addition, Paracoccus sp., Planomicrobium sp. and Staphylococcus sp. were also identified as PHA producers. Presumptive PHA granules and PHA synthases genes were detected in both sampling sites. Moreover, phylogenetic analysis showed that most of the phylotypes were distantly related to putative PhaC synthases class I sequences belonging to members of the classes Alphaproteobacteria and Gammaproteobacteria distributed within eight families, with higher abundances corresponding mainly to Rhodobacteraceae and Rhodospirillaceae. This analysis also showed that PhaC synthases class II sequences were closely related to those of Pseudomonas putida, suggesting the presence of this group, which is probably involved in the production of mcl-PHA in the mats. According to our state of knowledge, this study reports for the first time the occurrence of phaC and phaC1 sequences in hypersaline microbial mats, suggesting that these ecosystems may be a novel source for the isolation of short- and medium-chain length PHA producers.

  14. 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....

  15. 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

  16. Controls on the pH of hyper-saline lakes - A lesson from the Dead Sea

    Science.gov (United States)

    Golan, Rotem; Gavrieli, Ittai; Ganor, Jiwchar; Lazar, Boaz

    2016-01-01

    The pH of aqueous environments is determined by the dominant buffer systems of the water, defined operationally as total alkalinity (TA). The major buffer systems in the modern ocean are carbonic and boric acids of which the species bicarbonate, carbonate and borate make up about 77%, 19% and 4% of the TA, respectively. During the course of seawater evaporation (e.g. lagoons) the residual brine loses considerable portion of the dissolved inorganic carbon (DIC) and carbonate alkalinity (CA) already at the early stages of evaporation. DIC and CA decrease due to massive precipitation of CaCO3, while total boron (TB) increases conservatively, turning borate to the dominant alkalinity species in marine derived brines. In the present work we assess the apparent dissociation constant value of boric acid (KB‧) in saline and hypersaline waters, using the Dead Sea (DS) as a case study. We explain the DS low pH (∼6.3) and the effect of the boric and carbonic acid pK‧-s on the behavior of the brine's buffer system, including the pH increase that results from brine dilution. The KB‧ in DS was estimated from TB, TA, DIC and pH data measured in this study and early empirical data on artificial DS brines containing just carbonic acid. The KB‧ value was corroborated by Pitzer ion interaction model calculations using PHREEQC thermodynamic code applied to the chemical composition of the DS. Our results show that KB‧ increases considerably with the brine's ionic strength, reaching in the DS to a factor of 100 higher than in ;mean; seawater. Based on theoretical calculations and analyses of other natural brines it is suggested that brines' composition is a major factor in determining the KB‧ value and in turn the pH of such brines. We show that the higher the proportion of divalent cations in the brine the higher the dissociation constants of the weak acids (presumably due to formation of complexes). The low pH of the Dead Sea is accordingly explained by its extremely

  17. 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.

  18. Biosynthesis and characterization of polyhydroxyalkanoates produced by an extreme halophilic bacterium, Halomonas nitroreducens, isolated from hypersaline ponds.

    Science.gov (United States)

    Cervantes-Uc, J M; Catzin, J; Vargas, I; Herrera-Kao, W; Moguel, F; Ramirez, E; Rincón-Arriaga, S; Lizama-Uc, G

    2014-10-01

    Morphological, biochemical and genotypic characterization of a halophilic bacterium isolated from hypersaline ponds located at Las Coloradas (Río Lagartos, Yucatán, Mexico). Characterization of polymer produced by this strain was also performed. Twenty strains were isolated from water samples of salt ponds and selected based on both morphological features and their PHA storage capacity, which were determined by SEM and staining methods with Nile red and Nile blue, respectively; strains were also analysed by the fluorescence imaging technique. Among them, JCCOL25.8 strain showed the highest production of PHA's reason why phenotypic and genotypic characterization was performed; this strain was identified as Halomonas nitroreducens. Polymer produced by this strain was characterized by FTIR, DSC, GPC and EDX spectroscopy. Results indicated that the biosynthesized polymer was polyhydroxybutyrate (PHB) which had a melting peak at 170°C and a crystallinity percentage of about 36%. Based on phenotypic and genotypic aspects, JCCOL25.8 strain was identified as H. nitroreducens and it was capable to accumulate PHB. To our knowledge, there is only one study published on the biosynthesis of PHA's by H. nitroreducens strains, although the characterization of the obtained polymer was not reported. © 2014 The Society for Applied Microbiology.

  19. Phylogenetic analysis of a microbialite-forming microbial mat from a hypersaline lake of the Kiritimati atoll, Central Pacific.

    Science.gov (United States)

    Schneider, Dominik; Arp, Gernot; Reimer, Andreas; Reitner, Joachim; Daniel, Rolf

    2013-01-01

    On the Kiritimati atoll, several lakes exhibit microbial mat-formation under different hydrochemical conditions. Some of these lakes trigger microbialite formation such as Lake 21, which is an evaporitic, hypersaline lake (salinity of approximately 170‰). Lake 21 is completely covered with a thick multilayered microbial mat. This mat is associated with the formation of decimeter-thick highly porous microbialites, which are composed of aragonite and gypsum crystals. We assessed the bacterial and archaeal community composition and its alteration along the vertical stratification by large-scale analysis of 16S rRNA gene sequences of the nine different mat layers. The surface layers are dominated by aerobic, phototrophic, and halotolerant microbes. The bacterial community of these layers harbored Cyanobacteria (Halothece cluster), which were accompanied with known phototrophic members of the Bacteroidetes and Alphaproteobacteria. In deeper anaerobic layers more diverse communities than in the upper layers were present. The deeper layers were dominated by Spirochaetes, sulfate-reducing bacteria (Deltaproteobacteria), Chloroflexi (Anaerolineae and Caldilineae), purple non-sulfur bacteria (Alphaproteobacteria), purple sulfur bacteria (Chromatiales), anaerobic Bacteroidetes (Marinilabiacae), Nitrospirae (OPB95), Planctomycetes and several candidate divisions. The archaeal community, including numerous uncultured taxonomic lineages, generally changed from Euryarchaeota (mainly Halobacteria and Thermoplasmata) to uncultured members of the Thaumarchaeota (mainly Marine Benthic Group B) with increasing depth.

  20. Phylogenetic analysis of a microbialite-forming microbial mat from a hypersaline lake of the Kiritimati atoll, Central Pacific.

    Directory of Open Access Journals (Sweden)

    Dominik Schneider

    Full Text Available On the Kiritimati atoll, several lakes exhibit microbial mat-formation under different hydrochemical conditions. Some of these lakes trigger microbialite formation such as Lake 21, which is an evaporitic, hypersaline lake (salinity of approximately 170‰. Lake 21 is completely covered with a thick multilayered microbial mat. This mat is associated with the formation of decimeter-thick highly porous microbialites, which are composed of aragonite and gypsum crystals. We assessed the bacterial and archaeal community composition and its alteration along the vertical stratification by large-scale analysis of 16S rRNA gene sequences of the nine different mat layers. The surface layers are dominated by aerobic, phototrophic, and halotolerant microbes. The bacterial community of these layers harbored Cyanobacteria (Halothece cluster, which were accompanied with known phototrophic members of the Bacteroidetes and Alphaproteobacteria. In deeper anaerobic layers more diverse communities than in the upper layers were present. The deeper layers were dominated by Spirochaetes, sulfate-reducing bacteria (Deltaproteobacteria, Chloroflexi (Anaerolineae and Caldilineae, purple non-sulfur bacteria (Alphaproteobacteria, purple sulfur bacteria (Chromatiales, anaerobic Bacteroidetes (Marinilabiacae, Nitrospirae (OPB95, Planctomycetes and several candidate divisions. The archaeal community, including numerous uncultured taxonomic lineages, generally changed from Euryarchaeota (mainly Halobacteria and Thermoplasmata to uncultured members of the Thaumarchaeota (mainly Marine Benthic Group B with increasing depth.

  1. The effects of salinity on nitrification using halophilic nitrifiers in a Sequencing Batch Reactor treating hypersaline wastewater.

    Science.gov (United States)

    Cui, You-Wei; Zhang, Hong-Yu; Ding, Jie-Ran; Peng, Yong-Zhen

    2016-04-25

    With annual increases in the generation and use of saline wastewater, the need to avoid environmental problems such as eutrophication is critical. A previous study identified ways to start up a halophilic sludge domesticated from estuarine sediments to remove nitrogen from wastewater with a salinity of 30 g/L. This investigation expands that work to explore the impact of salinity on nitrogen removal. This study demonstrated that the mixed halophilic consortia removed nitrogen from wastewater with a salinity of 30-85 g/L. A kinetic analysis showed that halophilic nitrifiers selected based on hypersalinity were characterized by low Ks, μmax and specific ammonium oxidization rates. This explains the decrease in ammonium removal efficiency in the high salinity operational phases. Salinity inhibited ammonia oxidizing bacteria (AOB) activity, as well as the number of dominant AOB, but did not significantly affect the AOB dominant species. Three most dominant AOB lineages in the halophilic sludge were Nitrosomonas marina, Nitrosomonas europaea, and Nitrosococcus mobilis. Nitrosomonas europaea and Nitrosococcus mobilis were mainly affected by salinity, while nitrite accumulation and ammonia loading played the key role in determining the abundance of Nitrosococcus mobilis and Nitrosococcus europaea. The study contributes insights about shifts in halophilic nitrifying bacterial populations.

  2. Egg production and hatching success of Paracartia grani (Copepoda, Calanoida, Acartiidae) in two hypersaline ponds of a Tunisian Solar Saltern

    Science.gov (United States)

    Annabi-Trabelsi, Neila; Rebai, Rayda Kobbi; Ali, Mohammad; Subrahmanyam, M. N. V.; Belmonte, Genuario; Ayadi, Habib

    2018-04-01

    Reproductive traits of Paracartia grani [percentage of spawning females, egg production rate (EPR), and hatching success (HS)] were investigated for the first time at high salinities (39-121 psu) to examine the impact of such a particular situation. The study was done in two hypersaline ponds [A1 (39-46 psu) and C31 (70-121 psu)] in Sfax Solar Saltern, central-eastern coast of Tunisia. These ponds also differed in terms of the composition and concentrations of nutritional parameters. The EPR differed significantly between the ponds (ANOVA, F = 29.45, p eggs female- 1 day- 1 (7 December 2009) and 14 ± 1 eggs female- 1 day- 1 (19 January 2010) with an average of 13.3 ± 0.44 eggs female- 1 day- 1. HS after 48 h of incubation were significantly higher than those after 24 h. The mean values of HS after 48 h were 42.72 ± 2.58% at pond A1 and 41.67 ± 3.92% at pond C31. The two peaks of HS (after 48 h) were observed at 15 °C in pond A1 (21 December 2009, 45.18% nauplii eggs- 1) and in C31 (4 January 2010, 48.78%) at the same temperature. This study confirms that a broad salinity tolerance allows P. grani to settle itself in environments, which are normally hostile to the development of other Acartiidae.

  3. Carbonate microbialites and hardgrounds from Manito Lake, an alkaline, hypersaline lake in the northern Great Plains of Canada

    Science.gov (United States)

    Last, Fawn M.; Last, William M.; Halden, Norman M.

    2010-03-01

    Manito Lake is a large, perennial, Na-SO 4 dominated saline to hypersaline lake located in the northern Great Plains of western Canada. Significant water level decrease over the past several decades has led to reduction in volume and surface area, as well as an increase in salinity. The salinity has increased from 10 ppt to about 50 ppt TDS. This decrease in water level has exposed large areas of nearshore microbialites. These organogenic structures range in size from several cm to over a meter and often form large bioherms several meters high. They have various external morphologies, vary in mineralogical composition, and show a variety of internal fabrics from finely laminated to massive. In addition to microbiolities and bioherms, the littoral zone of Manito Lake contains a variety of carbonate hardgrounds, pavements, and cemented clastic sediments. Dolomite and aragonite are the most common minerals found in these shoreline structures, however, calcite after ikaite, monohydrocalcite, magnesian calcite, and hydromagnesite are also present. The dolomite is nonstoichiometric and calcium-rich; the magnesian calcite has about 17 mol% MgCO 3. AMS radiocarbon dating of paired organic matter and endogenic carbonate material confirms little or no reservoir affect. Although there is abundant evidence for modern carbonate mineral precipitation and microbialite formation, most of the larger microbialites formed between about 2300 and 1000 cal BP, whereas the hardgrounds, cements, and laminated crusts formed about 1000-500 cal BP.

  4. Exploring Archaeal Communities And Genomes Across Five Deep-Sea Brine Lakes Of The Red Sea With A Focus On Methanogens

    KAUST Repository

    Guan, Yue

    2015-12-15

    The deep-sea hypersaline lakes in the Red Sea are among the most challenging, extreme, and unusual environments on the planet Earth. Despite their harshness to life, they are inhabited by diverse and novel members of prokaryotes. Methanogenesis was proposed as one of the main metabolic pathways that drive microbial colonization in similar habitats. However, not much is known about the identities of the methane-producing microbes in the Red Sea, let alone the way in which they could adapt to such poly extreme environments. Combining a range of microbial community assessment, cultivation and omics (genomics, transcriptomics, and single amplified genomics) approaches, this dissertation seeks to fill these gaps in our knowledge by studying archaeal composition, particularly methanogens, their genomic capacities and transcriptomic characteristics in order to elucidate their diversity, function, and adaptation to the deep-sea brines of the Red Sea. Although typical methanogens are not abundant in the samples collected from brine pool habitats of the Red Sea, the pilot cultivation experiment has revealed novel halophilic methanogenic species of the domain Archaea. Their physiological traits as well as their genomic and transcriptomic features unveil an interesting genetic and functional adaptive capacity that allows them to thrive in the unique deep-sea hypersaline environments in the Red Sea.

  5. 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.

  6. 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.

  7. The comparative osmoregulatory ability of two water beetle genera whose species span the fresh-hypersaline gradient in inland waters (Coleoptera: Dytiscidae, Hydrophilidae.

    Directory of Open Access Journals (Sweden)

    Susana Pallarés

    Full Text Available A better knowledge of the physiological basis of salinity tolerance is essential to understanding the ecology and evolutionary history of organisms that have colonized inland saline waters. Coleoptera are amongst the most diverse macroinvertebrates in inland waters, including saline habitats; however, the osmoregulatory strategies they employ to deal with osmotic stress remain unexplored. Survival and haemolymph osmotic concentration at different salinities were examined in adults of eight aquatic beetle species which inhabit different parts of the fresh-hypersaline gradient. Studied species belong to two unrelated genera which have invaded saline waters independently from freshwater ancestors; Nebrioporus (Dytiscidae and Enochrus (Hydrophilidae. Their osmoregulatory strategy (osmoconformity or osmoregulation was identified and osmotic capacity (the osmotic gradient between the animal's haemolymph and the external medium was compared between species pairs co-habiting similar salinities in nature. We show that osmoregulatory capacity, rather than osmoconformity, has evolved independently in these different lineages. All species hyperegulated their haemolymph osmotic concentration in diluted waters; those living in fresh or low-salinity waters were unable to hyporegulate and survive in hyperosmotic media (> 340 mosmol kg(-1. In contrast, the species which inhabit the hypo-hypersaline habitats were effective hyporegulators, maintaining their haemolymph osmolality within narrow limits (ca. 300 mosmol kg(-1 across a wide range of external concentrations. The hypersaline species N. ceresyi and E. jesusarribasi tolerated conductivities up to 140 and 180 mS cm(-1, respectively, and maintained osmotic gradients over 3500 mosmol kg(-1, comparable to those of the most effective insect osmoregulators known to date. Syntopic species of both genera showed similar osmotic capacities and in general, osmotic responses correlated well with upper salinity levels

  8. Application of factor analysis and electrical resistivity to understand groundwater contributions to coastal embayments in semi-arid and hypersaline coastal settings

    International Nuclear Information System (INIS)

    Bighash, Paniz; Murgulet, Dorina

    2015-01-01

    Groundwater contributions and sources of salinity to Oso Bay in south Texas were investigated using multivariate statistical analysis of geochemical data and multitemporal electrical resistivity tomography surveys. Both analysis of geochemical data and subsurface imaging techniques identified two commonalities for the investigated system: 1) hypersaline water occurs near the groundwater/surface water interface during wet conditions creating reverse hydraulic gradients due to density effects. The development and downward movement of these fluids as continuous plumes deflect fresher groundwater discharge downward and laterally away from the surface; and 2) more pronounced upwelling of fresher groundwater occurs during drought periods when density inversions are more defined and are expected to overcome dispersion and diffusion processes and create sufficiently large-enough unstable gradients that induce density-difference convection. Salinity mass-balance models derived from time-difference resistivity tomograph and in-situ salinity data reaffirm these findings indicating that groundwater upwelling is more prominent during dry to wet conditions in 2013 (~ 545.5 m 3 /d) and is less pronounced during wet to dry conditions in 2012 (~ 262.7 m 3 /d) for the 224 m 2 area surveyed. Findings show that the highly saline nature of water in this area and changes in salinity regimes can be attributed to a combination of factors, namely: surface outflows, evapoconcentration, recirculation of hypersaline groundwaters, and potential trapped oil field brines. Increased drought conditions will likely exacerbate the rate at which salinity levels are increasing in bays and estuaries in semi-arid regions where both hypersaline groundwater discharge and high evaporation rates occur simultaneously. - Highlights: • Study of salinity regimes in relation to groundwater in a coastal semiarid setting • Factor analysis defined dominant factors influencing water quality variations.

  9. Sedimentology, Mineralogy, Morphology, and Characterization of Purple Non-Sulfur Bacteria Communities from Modern Hypersaline Microbial Mats in Puerto Rico and the Virgin Islands

    Science.gov (United States)

    Rodriguez Colon, B. J.; Rivera-Lopez, E. O.; Ramirez-Martinez, W. R.; Rios-Velazquez, C.; Perez-Valentin, K. A.

    2017-12-01

    Microbial mats are organosedimentary structures which house complex guilds of microbial communities, held together by a gelatinous exopolymeric substance (EPS). This biofilm contributes to the formation of laminations by binding and trapping sediments, as well as in-situ organomineralization. Microbial mats commonly thrive in extreme habitats, such as the hypersaline environments, which have been studied throughout several coastal regions in the Caribbean. This project aims to study the morphology, sedimentology, and mineralogy of five different modern hypersaline microbial mats from Puerto Rico and Anegada that have not yet been studied, to assess their differences/similarities. At the same time, we intent to isolate and characterize purple non-sulfur bacteria (PNSB), which is an anoxyphototrophic microorganism that contributes to the pink pigmentation observed in the second layer of a typical microbial mat. Different layers within each mat were separated, dissected and dissolved to remove all organic material. The resulting sediment was then analyzed mineralogically using X-ray diffraction, and used to make petrographic thin sections. To isolate PNSB candidates, serial dilutions followed by filtration were performed to extracted sections from the pink layer of each mat. The samples were planted in Petri dishes with marine media and placed in Anaerobic Jars. Colonies Descriptions, Gram stain and molecular analysis using 16S rDNA gene was performed. Preliminary results show a diversity of mat morphologies throughout the ponds, similar to what has been observed in other hypersaline ponds and marshes in the Caribbean. Sedimentary analysis shows that the mats from Puerto Rico have similar allochthonous material (e.g. Halimeda sp. fragments). Microcodium fabrics, conoform structures, and hemispheroidal morphologies were observed as well. In Anegada, lithified microbialites were observed in the Red Pond location. Mineralogically, all samples were similar except for the

  10. Denitrification in a hypersaline lake–aquifer system (Pétrola Basin, Central Spain): The role of recent organic matter and Cretaceous organic rich sediments

    International Nuclear Information System (INIS)

    Gómez-Alday, J.J.; Carrey, R.; Valiente, N.; Otero, N.; Soler, A.; Ayora, C.; Sanz, D.

    2014-01-01

    Agricultural regions in semi-arid to arid climates with associated saline wetlands are one of the most vulnerable environments to nitrate pollution. The Pétrola Basin was declared vulnerable to NO 3 − pollution by the Regional Government in 1998, and the hypersaline lake was classified as a heavily modified body of water. The study assessed groundwater NO 3 − through the use of multi-isotopic tracers (δ 15 N, δ 34 S, δ 13 C, δ 18 O) coupled to hydrochemistry in the aquifer connected to the eutrophic lake. Hydrogeologically, the basin shows two main flow components: regional groundwater flow from recharge areas (Zone 1) to the lake (Zone 2), and a density-driven flow from surface water to the underlying aquifer (Zone 3). In Zones 1 and 2, δ 15 N NO 3 and δ 18 O NO 3 suggest that NO 3 − from slightly volatilized ammonium synthetic fertilizers is only partially denitrified. The natural attenuation of NO 3 − can occur by heterotrophic reactions. However, autotrophic reactions cannot be ruled out. In Zone 3, the freshwater–saltwater interface (down to 12–16 m below the ground surface) is a reactive zone for NO 3 − attenuation. Tritium data suggest that the absence of NO 3 − in the deepest zones of the aquifer under the lake can be attributed to a regional groundwater flow with long residence time. In hypersaline lakes the geometry of the density-driven flow can play an important role in the transport of chemical species that can be related to denitrification processes. - Highlights: • Denitrification comes about in a hypersaline lake–aquifer system. • Nitrate in the basin is derived from synthetic fertilizers slightly volatilized. • Organic carbon oxidation is likely to be the main electron donor in denitrification. • Density driven flow transports organic carbon to deeper zones of the aquifer

  11. Application of factor analysis and electrical resistivity to understand groundwater contributions to coastal embayments in semi-arid and hypersaline coastal settings

    Energy Technology Data Exchange (ETDEWEB)

    Bighash, Paniz, E-mail: Bighash.p@gmail.com; Murgulet, Dorina

    2015-11-01

    Groundwater contributions and sources of salinity to Oso Bay in south Texas were investigated using multivariate statistical analysis of geochemical data and multitemporal electrical resistivity tomography surveys. Both analysis of geochemical data and subsurface imaging techniques identified two commonalities for the investigated system: 1) hypersaline water occurs near the groundwater/surface water interface during wet conditions creating reverse hydraulic gradients due to density effects. The development and downward movement of these fluids as continuous plumes deflect fresher groundwater discharge downward and laterally away from the surface; and 2) more pronounced upwelling of fresher groundwater occurs during drought periods when density inversions are more defined and are expected to overcome dispersion and diffusion processes and create sufficiently large-enough unstable gradients that induce density-difference convection. Salinity mass-balance models derived from time-difference resistivity tomograph and in-situ salinity data reaffirm these findings indicating that groundwater upwelling is more prominent during dry to wet conditions in 2013 (~ 545.5 m{sup 3}/d) and is less pronounced during wet to dry conditions in 2012 (~ 262.7 m{sup 3}/d) for the 224 m{sup 2} area surveyed. Findings show that the highly saline nature of water in this area and changes in salinity regimes can be attributed to a combination of factors, namely: surface outflows, evapoconcentration, recirculation of hypersaline groundwaters, and potential trapped oil field brines. Increased drought conditions will likely exacerbate the rate at which salinity levels are increasing in bays and estuaries in semi-arid regions where both hypersaline groundwater discharge and high evaporation rates occur simultaneously. - Highlights: • Study of salinity regimes in relation to groundwater in a coastal semiarid setting • Factor analysis defined dominant factors influencing water quality

  12. Application of factor analysis and electrical resistivity to understand groundwater contributions to coastal embayments in semi-arid and hypersaline coastal settings.

    Science.gov (United States)

    Bighash, Paniz; Murgulet, Dorina

    2015-11-01

    Groundwater contributions and sources of salinity to Oso Bay in south Texas were investigated using multivariate statistical analysis of geochemical data and multitemporal electrical resistivity tomography surveys. Both analysis of geochemical data and subsurface imaging techniques identified two commonalities for the investigated system: 1) hypersaline water occurs near the groundwater/surface water interface during wet conditions creating reverse hydraulic gradients due to density effects. The development and downward movement of these fluids as continuous plumes deflect fresher groundwater discharge downward and laterally away from the surface; and 2) more pronounced upwelling of fresher groundwater occurs during drought periods when density inversions are more defined and are expected to overcome dispersion and diffusion processes and create sufficiently large-enough unstable gradients that induce density-difference convection. Salinity mass-balance models derived from time-difference resistivity tomograph and in-situ salinity data reaffirm these findings indicating that groundwater upwelling is more prominent during dry to wet conditions in 2013 (~545.5m(3)/d) and is less pronounced during wet to dry conditions in 2012 (~262.7 m(3)/d) for the 224 m(2) area surveyed. Findings show that the highly saline nature of water in this area and changes in salinity regimes can be attributed to a combination of factors, namely: surface outflows, evapoconcentration, recirculation of hypersaline groundwaters, and potential trapped oil field brines. Increased drought conditions will likely exacerbate the rate at which salinity levels are increasing in bays and estuaries in semi-arid regions where both hypersaline groundwater discharge and high evaporation rates occur simultaneously. Published by Elsevier B.V.

  13. Isolation and characterization of Halomonas sp. strain C2SS100, a hydrocarbon-degrading bacterium under hypersaline conditions.

    Science.gov (United States)

    Mnif, S; Chamkha, M; Sayadi, S

    2009-09-01

    To isolate and characterize an efficient hydrocarbon-degrading bacterium under hypersaline conditions, from a Tunisian off-shore oil field. Production water collected from 'Sercina' petroleum reservoir, located near the Kerkennah island, Tunisia, was used for the screening of halotolerant or halophilic bacteria able to degrade crude oil. Bacterial strain C2SS100 was isolated after enrichment on crude oil, in the presence of 100 g l(-1) NaCl and at 37 degrees C. This strain was aerobic, Gram-negative, rod-shaped, motile, oxidase + and catalase +. Phenotypic characters and phylogenetic analysis based on the 16S rRNA gene of the isolate C2SS100 showed that it was related to members of the Halomonas genus. The degradation of several compounds present in crude oil was confirmed by GC-MS analysis. The use of refined petroleum products such as diesel fuel and lubricating oil as sole carbon source, under the same conditions of temperature and salinity, showed that significant amounts of these heterogenic compounds could be degraded. Strain C2SS100 was able to degrade hexadecane (C16). During growth on hexadecane, cells surface hydrophobicity and emulsifying activity increased indicating the production of biosurfactant by strain C2SS100. A halotolerant bacterial strain Halomonas sp. C2SS100 was isolated from production water of an oil field, after enrichment on crude oil. This strain is able to degrade hydrocarbons efficiently. The mode of hydrocarbon uptake is realized by the production of a biosurfactant which enhances the solubility of hydrocarbons and renders them more accessible for biodegradation. The biodegradation potential of the Halomonas sp. strain C2SS100 gives it an advantage for possibly application on bioremediation of water, hydrocarbon-contaminated sites under high-salinity level.

  14. Cyanobacterial Diversity in Microbial Mats from the Hypersaline Lagoon System of Araruama, Brazil: An In-depth Polyphasic Study

    Directory of Open Access Journals (Sweden)

    Vitor M. C. Ramos

    2017-06-01

    Full Text Available Microbial mats are complex, micro-scale ecosystems that can be found in a wide range of environments. In the top layer of photosynthetic mats from hypersaline environments, a large diversity of cyanobacteria typically predominates. With the aim of strengthening the knowledge on the cyanobacterial diversity present in the coastal lagoon system of Araruama (state of Rio de Janeiro, Brazil, we have characterized three mat samples by means of a polyphasic approach. We have used morphological and molecular data obtained by culture-dependent and -independent methods. Moreover, we have compared different classification methodologies and discussed the outcomes, challenges, and pitfalls of these methods. Overall, we show that Araruama's lagoons harbor a high cyanobacterial diversity. Thirty-six unique morphospecies could be differentiated, which increases by more than 15% the number of morphospecies and genera already reported for the entire Araruama system. Morphology-based data were compared with the 16S rRNA gene phylogeny derived from isolate sequences and environmental sequences obtained by PCR-DGGE and pyrosequencing. Most of the 48 phylotypes could be associated with the observed morphospecies at the order level. More than one third of the sequences demonstrated to be closely affiliated (best BLAST hit results of ≥99% with cyanobacteria from ecologically similar habitats. Some sequences had no close relatives in the public databases, including one from an isolate, being placed as “loner” sequences within different orders. This hints at hidden cyanobacterial diversity in the mats of the Araruama system, while reinforcing the relevance of using complementary approaches to study cyanobacterial diversity.

  15. Cyanobacterial Diversity in Microbial Mats from the Hypersaline Lagoon System of Araruama, Brazil: An In-depth Polyphasic Study.

    Science.gov (United States)

    Ramos, Vitor M C; Castelo-Branco, Raquel; Leão, Pedro N; Martins, Joana; Carvalhal-Gomes, Sinda; Sobrinho da Silva, Frederico; Mendonça Filho, João G; Vasconcelos, Vitor M

    2017-01-01

    Microbial mats are complex, micro-scale ecosystems that can be found in a wide range of environments. In the top layer of photosynthetic mats from hypersaline environments, a large diversity of cyanobacteria typically predominates. With the aim of strengthening the knowledge on the cyanobacterial diversity present in the coastal lagoon system of Araruama (state of Rio de Janeiro, Brazil), we have characterized three mat samples by means of a polyphasic approach. We have used morphological and molecular data obtained by culture-dependent and -independent methods. Moreover, we have compared different classification methodologies and discussed the outcomes, challenges, and pitfalls of these methods. Overall, we show that Araruama's lagoons harbor a high cyanobacterial diversity. Thirty-six unique morphospecies could be differentiated, which increases by more than 15% the number of morphospecies and genera already reported for the entire Araruama system. Morphology-based data were compared with the 16S rRNA gene phylogeny derived from isolate sequences and environmental sequences obtained by PCR-DGGE and pyrosequencing. Most of the 48 phylotypes could be associated with the observed morphospecies at the order level. More than one third of the sequences demonstrated to be closely affiliated (best BLAST hit results of ≥99%) with cyanobacteria from ecologically similar habitats. Some sequences had no close relatives in the public databases, including one from an isolate, being placed as "loner" sequences within different orders. This hints at hidden cyanobacterial diversity in the mats of the Araruama system, while reinforcing the relevance of using complementary approaches to study cyanobacterial diversity.

  16. Methylohalobius crimeensis gen. nov., sp. nov., a moderately halophilic, methanotrophic bacterium isolated from hypersaline lakes of Crimea.

    Science.gov (United States)

    Heyer, Jürgen; Berger, Ursula; Hardt, Martin; Dunfield, Peter F

    2005-09-01

    A novel genus and species are proposed for two strains of methanotrophic bacteria isolated from hypersaline lakes in the Crimean Peninsula of Ukraine. Strains 10Ki(T) and 4Kr are moderate halophiles that grow optimally at 1-1.5 M (5.8-8.7%, w/v) NaCl and tolerate NaCl concentrations from 0.2 M up to 2.5 M (1.2-15%). This optimum and upper limit are the highest for any methanotrophic bacterium known to date. The strains are Gram-negative, aerobic, non-pigmented, motile, coccoid to spindle-shaped bacteria that grow on methane or methanol only and utilize the ribulose monophosphate pathway for carbon assimilation. They are neutrophilic (growth occurs only in the range pH 6.5-7.5) and mesophilic (optimum growth occurs at 30 degrees C). On the basis of 16S rRNA gene sequence phylogeny, strains 10Ki(T) and 4Kr represent a type I methanotroph within the 'Gammaproteobacteria'. However, the 16S rRNA gene sequence displays <91.5 % identity to any public-domain sequence. The most closely related methanotrophic bacterium is the thermophilic strain HB. The DNA G+C content is 58.7 mol%. The major phospholipid fatty acids are 18:1omega7 (52-61%), 16:0 (22-23%) and 16:1omega7 (14-20%). The dominance of 18:1 over 16:0 and 16:1 fatty acids is unique among known type I methanotrophs. The data suggest that strains 10Ki(T) and 4Kr should be considered as belonging to a novel genus and species of type I methanotrophic bacteria, for which the name Methylohalobius crimeensis gen. nov., sp. nov. is proposed. Strain 10Ki(T) (=DSM 16011(T)=ATCC BAA-967(T)) is the type strain.

  17. Association of a new type of gliding, filamentous, purple phototrophic bacterium inside bundles of Microcoleus chthonoplastes in hypersaline cyanobacterial mats

    Science.gov (United States)

    D'Amelio, E. D.; Cohen, Y.; Des Marais, D. J.

    1987-01-01

    An unidentified filamentous purple bacterium, probably belonging to a new genus or even a new family, is found in close association with the filamentous, mat-forming cyanobacterium Microcoleus chthonoplastes in a hypersaline pond at Guerrero Negro, Baja California Sur, Mexico, and in Solar Lake, Sinai, Egypt. This organism is a gliding, segmented trichome, 0.8-0.9 micrometer wide. It contains intracytoplasmic stacked lamellae which are perpendicular and obliquely oriented to the cell wall, similar to those described for the purple sulfur bacteria Ectothiorhodospira. These bacteria are found inside the cyanobacterial bundle, enclosed by the cyanobacterial sheath. Detailed transmission electron microscopical analyses carried out in horizontal sections of the upper 1.5 mm of the cyanobacterial mat show this cyanobacterial-purple bacterial association at depths of 300-1200 micrometers, corresponding to the zone below that of maximal oxygenic photosynthesis. Sharp gradients of oxygen and sulfide are established during the day at this microzone in the two cyanobacterial mats studied. The close association, the distribution pattern of this association and preliminary physiological experiments suggest a co-metabolism of sulfur by the two-membered community. This probable new genus of purple bacteria may also grow photoheterotrophically using organic carbon excreted by the cyanobacterium. Since the chemical gradients in the entire photic zone fluctuate widely in a diurnal cycle, both types of metabolism probably take place. During the morning and afternoon, sulfide migrates up to the photic zone allowing photoautotrophic metabolism with sulfide as the electron donor. During the day the photic zone is highly oxygenated and the purple bacteria may either use oxidized species of sulfur such as elemental sulfur and thiosulfate in the photoautotrophic mode or grow photoheterotrophically using organic carbon excreted by M. chthonoplastes. The new type of filamentous purple sulfur

  18. Microbial diversity in sediment ecosystems (evaporites domes, microbial mats and crusts of hypersaline Laguna Tebenquiche, Salar de Atacama, Chile

    Directory of Open Access Journals (Sweden)

    Ana Beatriz Fernandez

    2016-08-01

    Full Text Available We combined nucleic acid-based molecular methods, biogeochemical measurements and physicochemical characteristics to investigate microbial sedimentary ecosystems of Laguna Tebenquiche, Atacama Desert, Chile. Molecular diversity and biogeochemistry of hypersaline microbial mats, rhizome-associated concretions and an endoevaporite were compared with: The V4 hypervariable region of the 16S rRNA gene was amplified by pyrosequencing to analyze the total microbial diversity (i.e., bacteria and archaea in bulk samples and, in addition, in detail on a millimeter scale in one microbial mat and in one evaporite. Archaea were more abundant than bacteria. Euryarchaeota was one of the most abundant phyla in all samples, and particularly dominant (97% of total diversity in the most lithified ecosystem, the evaporite. Most of the euryarchaeal OTUs could be assigned to the class Halobacteria or anaerobic and methanogenic archaea. Planctomycetes potentially also play a key role in mats and rhizome-associated concretions, notably the aerobic organoheterotroph members of the class Phycisphaerae. In addition to cyanobacteria, members of Chromatiales and possibly the candidate family Chlorotrichaceae contributed to photosynthetic carbon fixation. Other abundant uncultured taxa such as the candidate division MSBL1, the uncultured MBGB and the phylum Acetothermia potentially play an important metabolic role in these ecosystems. Lithifying microbial mats contained calcium carbonate precipitates, whereas endoevoporites consisted of gypsum and halite. Biogeochemical measurements revealed that based on depth profiles of O2 and sulfide, metabolic activities were much higher in the non-lithifying mat (peaking in the least lithified systems than in lithifying mats with the lowest activity in endoevaporites. This trend in decreasing microbial activity reflects the increase in salinity, which may play an important role in the biodiversity.

  19. Salinivibrio costicola GL6, a Novel Isolated Strain for Biotransformation of Caffeine to Theobromine Under Hypersaline Conditions.

    Science.gov (United States)

    Ashengroph, Morahem

    2017-01-01

    The present study has been conducted towards isolation of moderately halophilic bacteria capable of transforming caffeine into theobromine. A total of 45 caffeine-degrading moderate halophiles were enriched from hypersaline lakes and examined for the biotransformation of caffeine to theobromine by thin-layer chromatography (TLC) and high-performance liquid chromatography analyses. Strain GL6, giving the highest yield of theobromine, was isolated from the Hoz Soltan Lake, 20 % w/v salinity, central Iran, and identified as Salinivibrio costicola based on morphological and biochemical features as well as its 16S rRNA gene sequence analysis (GeneBank Accession No. KT378066) and DNA-DNA relatedness. The biotransformation of caffeine with strain GL6 leads to the formation of two metabolites, identified as theobromine and paraxanthine, but the yield of paraxanthine was much lower. Further study on the production of theobromine from caffeine under resting cell experiment was carried out subsequently. The optimal yield of theobromine (56 %) was obtained after a 32-h incubation using 5 mM of caffeine and 15 g l -1 (wet weight) of biomass in 0.1 M saline phosphate buffer (pH 7.0 and 10 % w/v NaCl) under agitation 180 rpm at 30 °C. The biotransformed theobromine was purified by preparative TLC and subjected to FTIR and mass spectroscopy for chemical identification. This is the first evidence for biotransformation of caffeine into theobromine by strains of the genus Salinivibrio.

  20. Archaeal and bacterial communities respond differently to environmental gradients in anoxic sediments of a California hypersaline lake, the Salton Sea.

    Science.gov (United States)

    Swan, Brandon K; Ehrhardt, Christopher J; Reifel, Kristen M; Moreno, Lilliana I; Valentine, David L

    2010-02-01

    Sulfidic, anoxic sediments of the moderately hypersaline Salton Sea contain gradients in salinity and carbon that potentially structure the sedimentary microbial community. We investigated the abundance, community structure, and diversity of Bacteria and Archaea along these gradients to further distinguish the ecologies of these domains outside their established physiological range. Quantitative PCR was used to enumerate 16S rRNA gene abundances of Bacteria, Archaea, and Crenarchaeota. Community structure and diversity were evaluated by terminal restriction fragment length polymorphism (T-RFLP), quantitative analysis of gene (16S rRNA) frequencies of dominant microorganisms, and cloning and sequencing of 16S rRNA. Archaea were numerically dominant at all depths and exhibited a lesser response to environmental gradients than that of Bacteria. The relative abundance of Crenarchaeota was low (0.4 to 22%) at all depths but increased with decreased carbon content and increased salinity. Salinity structured the bacterial community but exerted no significant control on archaeal community structure, which was weakly correlated with total carbon. Partial sequencing of archaeal 16S rRNA genes retrieved from three sediment depths revealed diverse communities of Euryarchaeota and Crenarchaeota, many of which were affiliated with groups previously described from marine sediments. The abundance of these groups across all depths suggests that many putative marine archaeal groups can tolerate elevated salinity (5.0 to 11.8% [wt/vol]) and persist under the anaerobic conditions present in Salton Sea sediments. The differential response of archaeal and bacterial communities to salinity and carbon patterns is consistent with the hypothesis that adaptations to energy stress and availability distinguish the ecologies of these domains.

  1. 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...

  2. Evidence of in situ microbial activity and sulphidogenesis in perennially sub-0 °C and hypersaline sediments of a high Arctic permafrost spring.

    Science.gov (United States)

    Lamarche-Gagnon, Guillaume; Comery, Raven; Greer, Charles W; Whyte, Lyle G

    2015-01-01

    The lost hammer (LH) spring perennially discharges subzero hypersaline reducing brines through thick layers of permafrost and is the only known terrestrial methane seep in frozen settings on Earth. The present study aimed to identify active microbial communities that populate the sediments of the spring outlet, and verify whether such communities vary seasonally and spatially. Microcosm experiments revealed that the biological reduction of sulfur compounds (SR) with hydrogen (e.g., sulfate reduction) was potentially carried out under combined hypersaline and subzero conditions, down to -20 °C, the coldest temperature ever recorded for SR. Pyrosequencing analyses of both 16S rRNA (i.e., cDNA) and 16S rRNA genes (i.e., DNA) of sediments retrieved in late winter and summer indicated fairly stable bacterial and archaeal communities at the phylum level. Potentially active bacterial and archaeal communities were dominated by clades related to the T78 Chloroflexi group and Halobacteria species, respectively. The present study indicated that SR, hydrogenotrophy (possibly coupled to autotrophy), and short-chain alkane degradation (other than methane), most likely represent important, previously unaccounted for, metabolic processes carried out by LH microbial communities. Overall, the obtained findings provided additional evidence that the LH system hosts active communities of anaerobic, halophilic, and cryophilic microorganisms despite the extreme conditions in situ.

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

    Directory of Open Access Journals (Sweden)

    Roberto Danovaro

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

  4. Alloactinosynnema iranicum sp. nov., a rare actinomycete isolated from a hypersaline wetland, and emended description of the genus Alloactinosynnema.

    Science.gov (United States)

    Nikou, Mahdi Moshtaghi; Ramezani, Mohaddaseh; Amoozegar, Mohammad Ali; Fazeli, Seyed Abolhassan Shahzadeh; Schumann, Peter; Spröer, Cathrin; Sánchez-Porro, Cristina; Ventosa, Antonio

    2014-04-01

    A Gram-staining-positive actinobacterial strain, Chem10(T), was isolated from soil around Inche-Broun hypersaline wetland in the north of Iran. Strain Chem10(T) was strictly aerobic, and catalase- and oxidase-positive. The isolate grew with 0-3 % NaCl, at 20-40 °C and at pH 6.0-8.0. The optimum temperature and pH for growth were 30 °C and pH 7.0, respectively. The cell wall of strain Chem10(T) contained meso-diaminopimelic acid as diamino acid and galactose, ribose and arabinose as whole-cell sugars. The polar lipid pattern contained diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine. Strain Chem10(T) synthesized cellular fatty acids of the straight-chain saturated and mono-unsaturated, and iso- and anteiso-branched types C14 : 0, C16 : 0, iso-C16 : 1, anteiso-C17 : 0, iso-C16 : 0, iso-C14 : 0 and iso-C15 : 0, and the major respiratory quinone was MK-9(H4). The G+C content of the genomic DNA was 70.7 mol%. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain Chem10(T) belonged to the family Pseudonocardiaceae and showed the closest phylogenetic similarity to Alloactinosynnema album KCTC 19294(T) (98.3 %) and Actinokineospora cibodasensis DSM 45658(T) (97.9 %). DNA-DNA relatedness values between the novel strain and strains Alloactinosynnema album KCTC 19294(T) and Actinokineospora cibodasensis DSM 45658(T) were only 52 % and 23 %, respectively. On the basis of phylogenetic analysis, phenotypic characteristics and DNA-DNA hybridization data, a novel species of the genus Alloactinosynnema is proposed, Alloactinosynnema iranicum sp. nov. The type strain is Chem10(T) ( = IBRC-M 10403(T) = CECT 8209(T)). In addition, an emended description of the genus Alloactinosynnema is proposed.

  5. 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...

  6. Denitrification in a hypersaline lake–aquifer system (Pétrola Basin, Central Spain): The role of recent organic matter and Cretaceous organic rich sediments

    Energy Technology Data Exchange (ETDEWEB)

    Gómez-Alday, J.J., E-mail: JuanJose.Gomez@uclm.es [Hydrogeology Group, Institute for Regional Development (IDR), University of Castilla–La Mancha (UCLM), Campus Universitario s/n, 02071 Albacete (Spain); Carrey, R., E-mail: raulcarrey@ub.edu [Grup d’Mineralogia Aplicada i Medi Ambient, Dep. Cristallografia, Mineralogia i Dipòsits Minerals, Facultat de Geologia, Universitat de Barcelona, C/ Martí i Franquès s/n, 08028, Barcelona (Spain); Valiente, N., E-mail: Nicolas.Valiente@uclm.es [Hydrogeology Group, Institute for Regional Development (IDR), University of Castilla–La Mancha (UCLM), Campus Universitario s/n, 02071 Albacete (Spain); Otero, N., E-mail: notero@ub.edu [Grup d’Mineralogia Aplicada i Medi Ambient, Dep. Cristallografia, Mineralogia i Dipòsits Minerals, Facultat de Geologia, Universitat de Barcelona, C/ Martí i Franquès s/n, 08028, Barcelona (Spain); Soler, A., E-mail: albertsolergil@ub.edu [Grup d’Mineralogia Aplicada i Medi Ambient, Dep. Cristallografia, Mineralogia i Dipòsits Minerals, Facultat de Geologia, Universitat de Barcelona, C/ Martí i Franquès s/n, 08028, Barcelona (Spain); Ayora, C., E-mail: cayora1@gmail.com [Grup d' Hidrologia Subterrània (GHS), Institut de Diagnóstic Ambiental i Estudis de l' Aigua (IDAEA-CSIC), C/Jordi Girona 18, 08028 Barcelona (Spain); Sanz, D. [Hydrogeology Group, Institute for Regional Development (IDR), University of Castilla–La Mancha (UCLM), Campus Universitario s/n, 02071 Albacete (Spain); and others

    2014-11-01

    Agricultural regions in semi-arid to arid climates with associated saline wetlands are one of the most vulnerable environments to nitrate pollution. The Pétrola Basin was declared vulnerable to NO{sub 3}{sup −} pollution by the Regional Government in 1998, and the hypersaline lake was classified as a heavily modified body of water. The study assessed groundwater NO{sub 3}{sup −} through the use of multi-isotopic tracers (δ{sup 15}N, δ{sup 34}S, δ{sup 13}C, δ{sup 18}O) coupled to hydrochemistry in the aquifer connected to the eutrophic lake. Hydrogeologically, the basin shows two main flow components: regional groundwater flow from recharge areas (Zone 1) to the lake (Zone 2), and a density-driven flow from surface water to the underlying aquifer (Zone 3). In Zones 1 and 2, δ{sup 15}N{sub NO{sub 3}} and δ{sup 18}O{sub NO{sub 3}} suggest that NO{sub 3}{sup −} from slightly volatilized ammonium synthetic fertilizers is only partially denitrified. The natural attenuation of NO{sub 3}{sup −} can occur by heterotrophic reactions. However, autotrophic reactions cannot be ruled out. In Zone 3, the freshwater–saltwater interface (down to 12–16 m below the ground surface) is a reactive zone for NO{sub 3}{sup −} attenuation. Tritium data suggest that the absence of NO{sub 3}{sup −} in the deepest zones of the aquifer under the lake can be attributed to a regional groundwater flow with long residence time. In hypersaline lakes the geometry of the density-driven flow can play an important role in the transport of chemical species that can be related to denitrification processes. - Highlights: • Denitrification comes about in a hypersaline lake–aquifer system. • Nitrate in the basin is derived from synthetic fertilizers slightly volatilized. • Organic carbon oxidation is likely to be the main electron donor in denitrification. • Density driven flow transports organic carbon to deeper zones of the aquifer.

  7. Determination of biological and physicochemical parameters of Artemia franciscana strains in hypersaline environments for aquaculture in the Colombian Caribbean.

    Science.gov (United States)

    Camargo, William N; Durán, Gabriel C; Rada, Orlando C; Hernández, Licet C; Linero, Juan-Carlos G; Muelle, Igor M; Sorgeloos, Patrick

    2005-10-26

    Artemia (Crustacea, Anostraca), also known as brine shrimp, are typical inhabitants of extreme environments. These hypersaline environments vary considerably in their physicochemical composition, and even their climatic conditions and elevation. Several thalassohaline (marine) environments along the Colombian Caribbean coast were surveyed in order to contribute to the knowledge of brine shrimp biotopes in South America by determining some vital biological and physicochemical parameters for Artemia survival. Additionally, cyst quality tests, biometrical and essential fatty acids analysis were performed to evaluate the economic viability of some of these strains for the aquaculture industry. In addition to the three locations (Galerazamba, Manaure, and Pozos Colorados) reported in the literature three decades ago in the Colombian Caribbean, six new locations were registered (Salina Cero, Kangaru, Tayrona, Bahía Hondita, Warrego and Pusheo). All habitats sampled showed that chloride was the prevailing anion, as expected, because of their thalassohaline origin. There were significant differences in cyst diameter grouping strains in the following manner according to this parameter: 1) San Francisco Bay (SFB-Control, USA), 2) Galerazamba and Tayrona, 3) Kangarú, 4) Manaure, and 5) Salina Cero and Pozos Colorados. Chorion thickness values were smaller in Tayrona, followed by Salina Cero, Galerazamba, Manaure, SFB, Kangarú and Pozos Colorados. There were significant differences in naupliar size, grouping strains as follows (smallest to largest): 1) Galerazamba, 2) Manaure, 3) SFB, Kangarú, and Salina Cero, 4) Pozos Colorados, and 5) Tayrona. Overall, cyst quality analysis conducted on samples from Manaure, Galerazamba, and Salina Cero revealed that all sites exhibited a relatively high number of cysts.g-1. Essential fatty acids (EFA) analysis performed on nauplii from cyst samples from Manaure, Galerazamba, Salina Cero and Tayrona revealed that cysts from all sites

  8. X-ray microtomography characterization of carbonate microbialites from a hypersaline coastal lagoon in the Rio de Janeiro State—Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Machado, A.S., E-mail: alemachado@lin.ufrj.br [Laboratório de Geologia Sedimentar—IGEO, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil); Laboratório de Instrumentação Nuclear—COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil); Dal Bó, P.F.F. [Laboratório de Geologia Sedimentar—IGEO, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil); Lima, I. [Laboratório de Instrumentação Nuclear—COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil); Borghi, L. [Laboratório de Geologia Sedimentar—IGEO, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil); Lopes, R. [Laboratório de Instrumentação Nuclear—COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil)

    2015-06-01

    The objective of the present study is to apply the micro-CT technique to assess recent microbialite samples from a hypersaline coastal lagoon in the Rio de Janeiro State. The study comprises structural assessment, mineralogical characterization and porosity distribution of each sample. Micro-CT is increasingly present in geological reservoir analyses, and has advantages over other laboratory techniques since it is non-invasive and allows 2D/3D visualization of inner structures without previous preparation method, such as slabbing, polishing, thinning or impregnation. This technique renders structural analyses which can be spatially resolved to a scale of micrometers. Results show that micro-CT technique is also adequate for the characterization of carbonate microbialites, providing excellent high resolution 3D images, that enabled to distinguish different mineralogies and porosity distribution beyond it is inner structure.

  9. X-ray microtomography characterization of carbonate microbialites from a hypersaline coastal lagoon in the Rio de Janeiro State—Brazil

    International Nuclear Information System (INIS)

    Machado, A.S.; Dal Bó, P.F.F.; Lima, I.; Borghi, L.; Lopes, R.

    2015-01-01

    The objective of the present study is to apply the micro-CT technique to assess recent microbialite samples from a hypersaline coastal lagoon in the Rio de Janeiro State. The study comprises structural assessment, mineralogical characterization and porosity distribution of each sample. Micro-CT is increasingly present in geological reservoir analyses, and has advantages over other laboratory techniques since it is non-invasive and allows 2D/3D visualization of inner structures without previous preparation method, such as slabbing, polishing, thinning or impregnation. This technique renders structural analyses which can be spatially resolved to a scale of micrometers. Results show that micro-CT technique is also adequate for the characterization of carbonate microbialites, providing excellent high resolution 3D images, that enabled to distinguish different mineralogies and porosity distribution beyond it is inner structure

  10. 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)

  11. 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...

  12. 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.

  13. The Deep-Sea Polyextremophile Halobacteroides lacunaris TB21 Rough-Type LPS: Structure and Inhibitory Activity towards Toxic LPS

    Science.gov (United States)

    Di Lorenzo, Flaviana; Palmigiano, Angelo; Paciello, Ida; Pallach, Mateusz; Garozzo, Domenico; Bernardini, Maria-Lina; La Cono, Violetta; Yakimov, Michail M.; Molinaro, Antonio; Silipo, Alba

    2017-01-01

    The structural characterization of the lipopolysaccharide (LPS) from extremophiles has important implications in several biomedical and therapeutic applications. The polyextremophile Gram-negative bacterium Halobacteroides lacunaris TB21, isolated from one of the most extreme habitats on our planet, the deep-sea hypersaline anoxic basin Thetis, represents a fascinating microorganism to investigate in terms of its LPS component. Here we report the elucidation of the full structure of the R-type LPS isolated from H. lacunaris TB21 that was attained through a multi-technique approach comprising chemical analyses, NMR spectroscopy, and Matrix-Assisted Laser Desorption Ionization (MALDI) mass spectrometry. Furthermore, cellular immunology studies were executed on the pure R-LPS revealing a very interesting effect on human innate immunity as an inhibitor of the toxic Escherichia coli LPS. PMID:28653982

  14. 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 ...

  15. 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 ...

  16. Microbial investigations of deep geological compartments

    International Nuclear Information System (INIS)

    Barsotti, V.; Sergeant, C.; Vesvres, M.H.; Joulian, C.; Coulon, S.; Le Marrec, C.; Garrido, F.

    2010-01-01

    Document available in extended abstract form only. Deep sedimentary rocks are now considered to contain a significant part of the total bacterial population, but are microbiologically unexplored. The drilling down to the base of the Triassic (1980 meters deep) in the geological formations of the eastern Paris Basin performed by ANDRA (EST433) in 2008 provides us a good opportunity to explore the deep biosphere. We conditioned and sub-sampled on the coring site, in as aseptic conditions as possible, the nine cores: two in the Callovo-Oxfordian clay, two in the Dogger, five in the Triassic compartments. In addition to storage at atmospheric pressure, a portion of the five Triassic samples was placed in a 190 bars pressurized bars chamber to investigate the influence of the conservation pressure factor on the found microflora. In parallel, in order to evaluate a potential bacterial contamination of the core by the drilling fluids, samples of mud just before each sample drilling were taken and analysed. The microbial exploration we started can be divided in two parts: - A cultural approach in different culture media for six metabolic groups to try to find microbial cells still viable. This type of experiment is difficult because of the small proportion of cultivable species, especially in these extreme environmental samples. - A molecular approach by direct extraction of genomic DNA from the geological samples to explore a larger biodiversity. Here, the limits are the difficulties to extract DNA from these low biomass containing rocks. The five Triassic samples were partly crushed in powder and inoculated in the six culture media with four NaCl concentrations, because this type of rock is known as saline or hyper-saline, and incubated at three temperatures: 30 deg. C, 55 deg. C under agitation and 70 deg. C. First results will be presented. The direct extraction of DNA needs a complete method optimisation to adapt existent procedures (using commercial kit and classical

  17. 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....

  18. 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.

  19. 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 ...

  20. The effects of the pyrethroid insecticide, bifenthrin, on steroid hormone levels and gonadal development of steelhead (Oncorhynchus mykiss) under hypersaline conditions.

    Science.gov (United States)

    Forsgren, Kristy L; Riar, Navneet; Schlenk, Daniel

    2013-06-01

    The San Francisco Bay Estuary and Sacramento-San Joaquin Delta (Bay-Delta) is an important breeding and nursery ground for fish. Of particular interest are salmonids that migrate through fresh and saltwater areas polluted with various contaminants including bifenthrin, a widely used pyrethroid insecticide. Male steelhead (Oncorhynchus mykiss) exposed to bifenthrin (0.1 and 1.5μg/L) for two weeks had a lower gonadosomatic index (GSI) in freshwater but were not affected by concurrent bifenthrin exposure and saltwater acclimation. Plasma estradiol-17β (E2) levels and ovarian follicle diameter of fish exposed to bifenthrin (0.1 and 1.5μg/L) in freshwater significantly increased. Under hypersaline conditions, fish exposed to bifenthrin had significantly reduced E2 levels and smaller follicles, and unhealthy ovarian follicles were observed. Given the occurrence of bifenthrin in surface waters of the Bay Delta, understanding the impact of bifenthrin on wildlife is necessary for improving risk assessments of pyrethroids in this important ecosystem. Copyright © 2013 Elsevier Inc. All rights reserved.

  1. Evidence for marine origin and microbial-viral habitability of sub-zero hypersaline aqueous inclusions within permafrost near Barrow, Alaska.

    Science.gov (United States)

    Colangelo-Lillis, J; Eicken, H; Carpenter, S D; Deming, J W

    2016-05-01

    Cryopegs are sub-surface hypersaline brines at sub-zero temperatures within permafrost; their global extent and distribution are unknown. The permafrost barrier to surface and groundwater advection maintains these brines as semi-isolated systems over geological time. A cryopeg 7 m below ground near Barrow, Alaska, was sampled for geochemical and microbiological analysis. Sub-surface brines (in situtemperature of -6 °C, salinity of 115 ppt), and an associated sediment-infused ice wedge (melt salinity of 0.04 ppt) were sampled using sterile technique. Major ionic concentrations in the brine corresponded more closely to other (Siberian) cryopegs than to Standard seawater or the ice wedge. Ionic ratios and stable isotope analysis of water conformed to a marine or brackish origin with subsequent Rayleigh fractionation. The brine contained ∼1000× more bacteria than surrounding ice, relatively high viral numbers suggestive of infection and reproduction, and an unusually high ratio of particulate to dissolved extracellular polysaccharide substances. A viral metagenome indicated a high frequency of temperate viruses and limited viral diversity compared to surface environments, with closest similarity to low water activity environments. Interpretations of the results underscore the isolation of these underexplored microbial ecosystems from past and present oceans. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  2. Electrochemical evaluation of Ti/TiO{sub 2}-polyaniline anodes for microbial fuel cells using hypersaline microbial consortia for synthetic-wastewater treatment

    Energy Technology Data Exchange (ETDEWEB)

    Benetton, X.D.; Navarro-Avila, S.G. [Univ. Autonoma de Yucatan, Yucatan (Mexico). Biotecnologia y Bioingenieria; Carrera-Figueiras, C. [Univ. Autonoma de Yucatan, Yucatan (Mexico). Quimica Fundamental y Aplicada

    2010-07-01

    This paper described the development of a titanium (Ti/TiO{sub 2}) polyaniline composite electrode. The electrode was designed for use with a microbial fuel cell (MFC) that generated electricity through the microbial biodegradation of organic compounds. A modified NBAF medium was used with a 20 mM acetate as an electron donor and 53 mM fumarate as an electron acceptor for a period of 96 hours at 37 degrees C. Strains were cultured under strict anaerobic conditions. Two microbial cultures were used: (1) pure cultures of Geobacter sulfur-reducens; and (2) an uncharacterized stable microbial consortia isolated from hypersaline swamp sediments. The anodes were made with an emeraldine form of PANI deposited over Ti/TiO{sub 2} electrodes. Electrochemical impedance spectroscopy (EIS) monitoring was used to determine the open circuit potential of the MFC. Negative real impedances were obtained and reproduced in all systems studied with the Ti/TiO{sub 2}-PANI anodes. The highest power density was obtained using the Geobacter sulfur-reducens culture. Further research is needed to study the mechanisms that contribute to the occurrence of negative real impedances. 23 refs., 1 tab., 5 figs.

  3. 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.

  4. 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

  5. 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...

  6. 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...

  7. 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.

  8. 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

  9. 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...

  10. 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.

  11. 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...

  12. Inputs and internal cycling of nitrogen to a causeway influenced, hypersaline lake, Great Salt Lake, Utah, USA

    Science.gov (United States)

    Naftz, David L.

    2017-01-01

    Nitrogen inputs to Great Salt Lake (GSL), located in the western USA, were quantified relative to the resident nitrogen mass in order to better determine numeric nutrient criteria that may be considered at some point in the future. Total dissolved nitrogen inputs from four surface-water sources entering GSL were modeled during the 5-year study period (2010–2014) and ranged from 1.90 × 106 to 5.56 × 106 kg/year. The railroad causeway breach was a significant conduit for the export of dissolved nitrogen from Gilbert to Gunnison Bay, and in 2011 and 2012, net losses of total nitrogen mass from Gilbert Bay via the Causeway breach were 9.59 × 105 and 1.51 × 106 kg. Atmospheric deposition (wet + dry) was a significant source of nitrogen to Gilbert Bay, exceeding the dissolved nitrogen load contributed via the Farmington Bay causeway surface-water input by >100,000 kg during 2 years of the study. Closure of two railroad causeway culverts in 2012 and 2013 likely initiated a decreasing trend in the volume of the higher density Deep Brine Layer and associated declines in total dissolved nitrogen mass contained in this layer. The large dissolved nitrogen pool in Gilbert Bay relative to the amount of nitrogen contributed by surface-water inflow sources is consistent with the terminal nature of GSL and the predominance of internal nutrient cycling. The opening of the new railroad causeway breach in 2016 will likely facilitate more efficient bidirectional flow between Gilbert and Gunnison Bays, resulting in potentially substantial changes in nutrient pools within GSL.

  13. Molluscs associated with the macroalgae of the genus Gracilaria (Rhodophyta): importance of algal fronds as microhabitat in a hypersaline mangrove in Northeastern Brazil.

    Science.gov (United States)

    Queiroz, R N M; Dias, T L P

    2014-08-01

    The fronds of marine macroalgae play an important role in coastal ecosystems because the algae banks are utilized as a microhabitat by different taxa, including molluscs, one of the most abundant and diverse animals of marine ecosystems. In this study, we characterized the malacofauna associated with the macroalgae Gracilaria domingensis (Kützing) Sonder ex Dickie 1874 and Gracilaria cuneata Areschoug 1854 of a hypersaline mangrove on the northern coast of the state of Rio Grande do Norte, Northeastern Brazil. The first alga dominates in the rainy season and it is substituted by second one in the dry period. A total of 1,490 molluscs were surveyed, representing 56 species in 29 families: 1,081 were associated with G. domingensis and 409 with G. cuneata, the latter showing the greater diversity (H'=1.25). Columbellidae, Neritidae, Pyramidellidae and Cerithiidae were among the most representative families in the number of species and individuals. The micromolluscs were dominant in the algal microhabitat, constituting 74.63% of the malacofauna recorded. The columbellid Parvanachis obesa (C. B. Adams, 1845) was the dominant species followed by the neritid Neritina virginea (Linnaeus, 1758) in both algae. In spite of the annual alternated succession of the algae species, at least 15 mollusc species are common for these algae. Furthermore, juveniles of P. obesa were recorded in both seasons, indicating a continuous reproduction. Possible reasons for difference in abundance, diversity and dominance of molluscs living on these algae are discussed. Both species of substrate-algae represent an important microhabitat for refuge, feeding and the reproduction of small-sized mollusc species during rainy and dry seasons.

  14. Molluscs associated with the macroalgae of the genus Gracilaria (Rhodophyta: importance of algal fronds as microhabitat in a hypersaline mangrove in Northeastern Brazil

    Directory of Open Access Journals (Sweden)

    RNM Queiroz

    Full Text Available The fronds of marine macroalgae play an important role in coastal ecosystems because the algae banks are utilized as a microhabitat by different taxa, including molluscs, one of the most abundant and diverse animals of marine ecosystems. In this study, we characterized the malacofauna associated with the macroalgae Gracilaria domingensis (Kützing Sonder ex Dickie 1874 and Gracilaria cuneata Areschoug 1854 of a hypersaline mangrove on the northern coast of the state of Rio Grande do Norte, Northeastern Brazil. The first alga dominates in the rainy season and it is substituted by second one in the dry period. A total of 1,490 molluscs were surveyed, representing 56 species in 29 families: 1,081 were associated with G. domingensis and 409 with G. cuneata, the latter showing the greater diversity (H′=1.25. Columbellidae, Neritidae, Pyramidellidae and Cerithiidae were among the most representative families in the number of species and individuals. The micromolluscs were dominant in the algal microhabitat, constituting 74.63% of the malacofauna recorded. The columbellid Parvanachis obesa(C. B. Adams, 1845 was the dominant species followed by the neritid Neritina virginea (Linnaeus, 1758 in both algae. In spite of the annual alternated succession of the algae species, at least 15 mollusc species are common for these algae. Furthermore, juveniles of P. obesa were recorded in both seasons, indicating a continuous reproduction. Possible reasons for difference in abundance, diversity and dominance of molluscs living on these algae are discussed. Both species of substrate-algae represent an important microhabitat for refuge, feeding and the reproduction of small-sized mollusc species during rainy and dry seasons.

  15. 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....

  16. 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...

  17. 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.

  18. 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

  19. Benthic protists and fungi of Mediterranean deep hypsersaline anoxic basin redoxcline sediments.

    Science.gov (United States)

    Bernhard, Joan M; Kormas, Konstantinos; Pachiadaki, Maria G; Rocke, Emma; Beaudoin, David J; Morrison, Colin; Visscher, Pieter T; Cobban, Alec; Starczak, Victoria R; Edgcomb, Virginia P

    2014-01-01

    Some of the most extreme marine habitats known are the Mediterranean deep hypersaline anoxic basins (DHABs; water depth ∼3500 m). Brines of DHABs are nearly saturated with salt, leading many to suspect they are uninhabitable for eukaryotes. While diverse bacterial and protistan communities are reported from some DHAB water-column haloclines and brines, the existence and activity of benthic DHAB protists have rarely been explored. Here, we report findings regarding protists and fungi recovered from sediments of three DHAB (Discovery, Urania, L' Atalante) haloclines, and compare these to communities from sediments underlying normoxic waters of typical Mediterranean salinity. Halocline sediments, where the redoxcline impinges the seafloor, were studied from all three DHABs. Microscopic cell counts suggested that halocline sediments supported denser protist populations than those in adjacent control sediments. Pyrosequencing analysis based on ribosomal RNA detected eukaryotic ribotypes in the halocline sediments from each of the three DHABs, most of which were fungi. Sequences affiliated with Ustilaginomycotina Basidiomycota were the most abundant eukaryotic signatures detected. Benthic communities in these DHABs appeared to differ, as expected, due to differing brine chemistries. Microscopy indicated that only a low proportion of protists appeared to bear associated putative symbionts. In a considerable number of cases, when prokaryotes were associated with a protist, DAPI staining did not reveal presence of any nuclei, suggesting that at least some protists were carcasses inhabited by prokaryotic scavengers.

  20. 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

  1. 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.

  2. 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...

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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…

  8. 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...

  9. [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.

  10. Complete genome sequence and description of Salinispira pacifica gen. nov., sp. nov., a novel spirochaete isolated form a hypersaline microbial mat.

    Science.gov (United States)

    Ben Hania, Wajdi; Joseph, Manon; Schumann, Peter; Bunk, Boyke; Fiebig, Anne; Spröer, Cathrin; Klenk, Hans-Peter; Fardeau, Marie-Laure; Spring, Stefan

    2015-01-01

    During a study of the anaerobic microbial community of a lithifying hypersaline microbial mat of Lake 21 on the Kiritimati atoll (Kiribati Republic, Central Pacific) strain L21-RPul-D2(T) was isolated. The closest phylogenetic neighbor was Spirochaeta africana Z-7692(T) that shared a 16S rRNA gene sequence identity value of 90% with the novel strain and thus was only distantly related. A comprehensive polyphasic study including determination of the complete genome sequence was initiated to characterize the novel isolate. Cells of strain L21-RPul-D2(T) had a size of 0.2 - 0.25 × 8-9 μm, were helical, motile, stained Gram-negative and produced an orange carotenoid-like pigment. Optimal conditions for growth were 35°C, a salinity of 50 g/l NaCl and a pH around 7.0. Preferred substrates for growth were carbohydrates and a few carboxylic acids. The novel strain had an obligate fermentative metabolism and produced ethanol, acetate, lactate, hydrogen and carbon dioxide during growth on glucose. Strain L21-RPul-D2(T) was aerotolerant, but oxygen did not stimulate growth. Major cellular fatty acids were C14:0, iso-C15:0, C16:0 and C18:0. The major polar lipids were an unidentified aminolipid, phosphatidylglycerol, an unidentified phospholipid and two unidentified glycolipids. Whole-cell hydrolysates contained L-ornithine as diagnostic diamino acid of the cell wall peptidoglycan. The complete genome sequence was determined and annotated. The genome comprised one circular chromosome with a size of 3.78 Mbp that contained 3450 protein-coding genes and 50 RNA genes, including 2 operons of ribosomal RNA genes. The DNA G + C content was determined from the genome sequence as 51.9 mol%. There were no predicted genes encoding cytochromes or enzymes responsible for the biosynthesis of respiratory lipoquinones. Based on significant differences to the uncultured type species of the genus Spirochaeta, S. plicatilis, as well as to any other phylogenetically related

  11. Structural and functional analysis of a microbial mat ecosystem from a unique permanent hypersaline inland lake: 'La Salada de Chiprana' (NE Spain).

    Science.gov (United States)

    Jonkers, Henk M; Ludwig, Rebecca; Wit, Rutger; Pringault, Olivier; Muyzer, Gerard; Niemann, Helge; Finke, Niko; Beer, Dirk

    2003-05-01

    The benthic microbial mat community of the only permanent hypersaline natural inland lake of Western Europe, 'La Salada de Chiprana', northeastern Spain, was structurally and functionally analyzed. The ionic composition of the lake water is characterized by high concentrations of magnesium and sulfate, which were respectively 0.35 and 0.5 M at the time of sampling while the total salinity was 78 g l(-1). Community composition was analyzed by microscopy, high-performance liquid chromatography (HPLC) pigment analyses and by studying culturable bacteria from different functional groups. Therefore, denaturing gradient gel electrophoresis (DGGE) was applied on most probable number (MPN) dilution cultures. Microscopy revealed that a thin layer of Chloroflexus-like bacteria overlaid various cyanobacteria-dominated layers each characterized by different morphotypes. DGGE analysis of MPN dilution cultures from distinct mat layers showed that various phylotypes of anoxygenic phototrophic, aerobic heterotrophic, colorless sulfur-, and sulfate-reducing bacteria were present. The mats were furthermore functionally studied and attention was focussed on the relationship between oxygenic primary production and the flow of carbon through the microbial community. Microsensor techniques, porewater and sediment photopigment analysis were applied in order to estimate oxygenic photosynthetic rates, daily dynamics of (in)organic carbon porewater concentration and migration behavior of phototrophs. Chiprana microbial mats produced dissolved organic carbon (DOC) both during the day and night. It was estimated that 14% of the mats gross photosynthetic production and 49% of the mats net photosynthetic production diffused out of the mat in the form of low molecular mass fatty acids, although these compounds made up only 2% of the total DOC pool. The high flux of dissolved fatty acids from the microbial mat to the water column may explain why in this system Chloroflexus-like bacteria

  12. Spatial variability in photosynthetic and heterotrophic activity drives localized δ13C org fluctuations and carbonate precipitation in hypersaline microbial mats.

    Science.gov (United States)

    Houghton, J; Fike, D; Druschel, G; Orphan, V; Hoehler, T M; Des Marais, D J

    2014-11-01

    Modern laminated photosynthetic microbial mats are ideal environments to study how microbial activity creates and modifies carbon and sulfur isotopic signatures prior to lithification. Laminated microbial mats from a hypersaline lagoon (Guerrero Negro, Baja California, Mexico) maintained in a flume in a greenhouse at NASA Ames Research Center were sampled for δ(13) C of organic material and carbonate to assess the impact of carbon fixation (e.g., photosynthesis) and decomposition (e.g., bacterial respiration) on δ(13) C signatures. In the photic zone, the δ(13) C org signature records a complex relationship between the activities of cyanobacteria under variable conditions of CO2 limitation with a significant contribution from green sulfur bacteria using the reductive TCA cycle for carbon fixation. Carbonate is present in some layers of the mat, associated with high concentrations of bacteriochlorophyll e (characteristic of green sulfur bacteria) and exhibits δ(13) C signatures similar to DIC in the overlying water column (-2.0‰), with small but variable decreases consistent with localized heterotrophic activity from sulfate-reducing bacteria (SRB). Model results indicate respiration rates in the upper 12 mm of the mat alter in situ pH and HCO3- concentrations to create both phototrophic CO2 limitation and carbonate supersaturation, leading to local precipitation of carbonate minerals. The measured activity of SRB with depth suggests they variably contribute to decomposition in the mat dependent on organic substrate concentrations. Millimeter-scale variability in the δ(13) C org signature beneath the photic zone in the mat is a result of shifting dominance between cyanobacteria and green sulfur bacteria with the aggregate signature overprinted by heterotrophic reworking by SRB and methanogens. These observations highlight the impact of sedimentary microbial processes on δ(13) C org signatures; these processes need to be considered when attempting to relate

  13. 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

  14. 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...

  15. 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)

  16. 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...

  17. 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.

  18. 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

  19. 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.)

  20. 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.)

  1. [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.

  2. 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

  3. 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...

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  11. 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 ...

  12. 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

  13. 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

  14. Diversity of methanogens and sulfate-reducing bacteria in the interfaces of five deep-sea anoxic brines of the Red Sea

    KAUST Repository

    Guan, Yue

    2015-11-01

    Oceanic deep hypersaline anoxic basins (DHABs) are characterized by drastic changes in physico-chemical conditions in the transition from overlaying seawater to brine body. Brine-seawater interfaces (BSIs) of several DHABs across the Mediterranean Sea have been shown to possess methanogenic and sulfate-reducing activities, yet no systematic studies have been conducted to address the potential functional diversity of methanogenic and sulfate-reducing communities in the Red Sea DHABs. Here, we evaluated the relative abundance of Bacteria and Archaea using quantitative PCR and conducted phylogenetic analyses of nearly full-length 16S rRNA genes as well as functional marker genes encoding the alpha subunits of methyl-coenzyme M reductase (mcrA) and dissimilatory sulfite reductase (dsrA). Bacteria predominated over Archaea in most locations, the majority of which were affiliated with Deltaproteobacteria, while Thaumarchaeota were the most prevalent Archaea in all sampled locations. The upper convective layers of Atlantis II Deep, which bear increasingly harsh environmental conditions, were dominated by members of the class Thermoplasmata (Marine Benthic Group E and Mediterranean Sea Brine Lakes Group 1). Our study revealed unique microbial compositions, the presence of niche-specific groups, and collectively, a higher diversity of sulfate-reducing communities compared to methanogenic communities in all five studied locations. © 2015 Institut Pasteur.

  15. Diversity of methanogens and sulfate-reducing bacteria in the interfaces of five deep-sea anoxic brines of the Red Sea

    KAUST Repository

    Guan, Yue; Hikmawan, Tyas; Antunes, Andre; Ngugi, David; Stingl, Ulrich

    2015-01-01

    Oceanic deep hypersaline anoxic basins (DHABs) are characterized by drastic changes in physico-chemical conditions in the transition from overlaying seawater to brine body. Brine-seawater interfaces (BSIs) of several DHABs across the Mediterranean Sea have been shown to possess methanogenic and sulfate-reducing activities, yet no systematic studies have been conducted to address the potential functional diversity of methanogenic and sulfate-reducing communities in the Red Sea DHABs. Here, we evaluated the relative abundance of Bacteria and Archaea using quantitative PCR and conducted phylogenetic analyses of nearly full-length 16S rRNA genes as well as functional marker genes encoding the alpha subunits of methyl-coenzyme M reductase (mcrA) and dissimilatory sulfite reductase (dsrA). Bacteria predominated over Archaea in most locations, the majority of which were affiliated with Deltaproteobacteria, while Thaumarchaeota were the most prevalent Archaea in all sampled locations. The upper convective layers of Atlantis II Deep, which bear increasingly harsh environmental conditions, were dominated by members of the class Thermoplasmata (Marine Benthic Group E and Mediterranean Sea Brine Lakes Group 1). Our study revealed unique microbial compositions, the presence of niche-specific groups, and collectively, a higher diversity of sulfate-reducing communities compared to methanogenic communities in all five studied locations. © 2015 Institut Pasteur.

  16. 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…

  17. 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.

  18. 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.

  19. 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...

  20. 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

  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. Fungal diversity in deep-sea sediments revealed by culture-dependent and culture-independent approaches

    Digital Repository Service at National Institute of Oceanography (India)

    Singh, P.; Raghukumar, C.; Meena, R.M.; Verma, P.; Shouche, Y.

    dog. Journal of Clinical Microbiology 41: 1722-1725. Gunde-Cimerman N, Zalar P, Hoog Gsde, Plemenitas A, 2000. Hypersaline waters in salterns: natural ecological niches for halophilic black yeasts. FEMS Microbiology Ecology 32: 235–340. Gupta SM...

  6. 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

  7. 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.

  8. 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...

  9. 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

  10. 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...

  11. 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 ...

  12. 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.

  13. 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.

  14. 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.

  15. Relevance of a Hypersaline Sodium-Rich Naturally Sparkling Mineral Water to the Protection against Metabolic Syndrome Induction in Fructose-Fed Sprague-Dawley Rats: A Biochemical, Metabolic, and Redox Approach

    Directory of Open Access Journals (Sweden)

    Cidália Dionísio Pereira

    2014-01-01

    Full Text Available The Metabolic Syndrome increases the risk for atherosclerotic cardiovascular disease and type 2 Diabetes Mellitus. Increased fructose consumption and/or mineral deficiency have been associated with Metabolic Syndrome development. This study aimed to investigate the effects of 8 weeks consumption of a hypersaline sodium-rich naturally sparkling mineral water on 10% fructose-fed Sprague-Dawley rats (Metabolic Syndrome animal model. The ingestion of the mineral water (rich in sodium bicarbonate and with higher potassium, calcium, and magnesium content than the tap water used as control reduced/prevented not only the fructose-induced increase of heart rate, plasma triacylglycerols, insulin and leptin levels, hepatic catalase activity, and organ weight to body weight ratios (for liver and both kidneys but also the decrease of hepatic glutathione peroxidase activity and oxidized glutathione content. This mineral-rich water seems to have potential to prevent Metabolic Syndrome induction by fructose. We hypothesize that its regular intake in the context of modern diets, which have a general acidic character interfering with mineral homeostasis and are poor in micronutrients, namely potassium, calcium, and magnesium, could add surplus value and attenuate imbalances, thus contributing to metabolic and redox health and, consequently, decreasing the risk for atherosclerotic cardiovascular disease.

  16. 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...

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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 ...

  10. 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.

  11. 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.

  12. 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)

  13. 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,

  14. 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,

  15. 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

  16. 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.

  17. 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.

  18. 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…

  19. 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...

  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. 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...

  2. 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.

  3. 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...

  4. 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...

  5. 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.

  6. Linking the Modern and Recent Record of Cabo Frio Upwelling with Local Climate and Biogeochemical Processes in Hypersaline Coastal Lagoons, Região dos Lagos, Rio de Janeiro, Brazil

    Science.gov (United States)

    McKenzie, J. A.; Nascimento, G. S.; Albuquerque, A. L.; Belem, A. L.; Carreira, R.; Eglinton, T. I.; Vasconcelos, C.

    2015-12-01

    A unique marine and lagoonal system along the coast east of Rio de Janeiro is being investigated to understand the impact of climatic variability on the South Atlantic carbon cycle and biomineralisation processes involved in carbonate precipitation in the hypersaline coastal lagoons. The region is dominated by a semi-arid microclimate attributed to the local coastal upwelling phenomenon near Cabo Frio. The intensity of the upwelling affects the hydrology of the annual water and biogeochemical cycles in the lagoons, as well as biogeochemical signals of environmental change recorded in both onshore and offshore sediments. Preliminary results of δ18O and δD values of water samples collected monthly in Lagoa Vermelha and Brejo do Espinho from 2011 to 2014 show lower values for waters corresponding to the wet season, reflecting increased input of meteoric water. The higher values for waters collected during the dry season reflect the greater amount of evaporation with increased seasonal aridity. Radiocarbon dating of Holocene marine and lagoonal cores indicates that Mg-carbonate precipitation in the lagoons is associated with high evaporation. Modern field observations for the last 3 years suggest that the amount of carbonate precipitation is correlated with evaporitic conditions associated with the upwelling phenomenon. A calibration study of hydrogen isotopic fractionation in the modern lagoons is underway to define a relationship between δDlipid of suspended particles and δDwater of associated water. This isotopic relationship will be applied to material obtained in cores from the lagoons. Offshore cores will be studied using well-tested paleotemperature proxies to evaluate the intensity of the upwelling during the Holocene. In summary, linking the coastal upwelling with the lagoonal hydrology has the potential to furnish important insights about the relationship between the local climate and paleoceanographic circulation associated with the regional carbon cycle.

  7. 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...

  8. 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.

  9. 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...

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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...

  4. 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.

  5. 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...

  6. Deep microbial life in the Altmark natural gas reservoir: baseline characterization prior CO2 injection

    Science.gov (United States)

    Morozova, Daria; Shaheed, Mina; Vieth, Andrea; Krüger, Martin; Kock, Dagmar; Würdemann, Hilke

    2010-05-01

    Within the framework of the CLEAN project (CO2 Largescale Enhanced gas recovery in the Altmark Natural gas field) technical basics with special emphasis on process monitoring are explored by injecting CO2 into a gas reservoir. Our study focuses on the investigation of the in-situ microbial community of the Rotliegend natural gas reservoir in the Altmark, located south of the city Salzwedel, Germany. In order to characterize the microbial life in the extreme habitat we aim to localize and identify microbes including their metabolism influencing the creation and dissolution of minerals. The ability of microorganisms to speed up dissolution and formation of minerals might result in changes of the local permeability and the long-term safety of CO2 storage. However, geology, structure and chemistry of the reservoir rock and the cap rock as well as interaction with saline formation water and natural gases and the injected CO2 affect the microbial community composition and activity. The reservoir located at the depth of about 3500m, is characterised by high salinity fluid and temperatures up to 127° C. It represents an extreme environment for microbial life and therefore the main focus is on hyperthermophilic, halophilic anaerobic microorganisms. In consequence of the injection of large amounts of CO2 in the course of a commercial EGR (Enhanced Gas Recovery) the environmental conditions (e.g. pH, temperature, pressure and solubility of minerals) for the autochthonous microorganisms will change. Genetic profiling of amplified 16S rRNA genes are applied for detecting structural changes in the community by using PCR- SSCP (PCR-Single-Strand-Conformation Polymorphism) and DGGE (Denaturing Gradient Gel Electrophoresis). First results of the baseline survey indicate the presence of microorganisms similar to representatives from other saline, hot, anoxic, deep environments. However, due to the hypersaline and hyperthermophilic reservoir conditions, cell numbers are low, so that

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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...

  12. A new cement slurry modified with chitosan/alginate interpenetrating networks and hydroxyapatite: structural characteristics after long-term contact with hyper-saline produced water from oil well operations

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Ivory Marcos Gomes dos; Santos, Danilo Oliveira; Cestari, Antonio Reinaldo, E-mail: ivorymarcos@hotmail.com, E-mail: danilo.quimico@yahoo.com.br, E-mail: rcestari@gmail.com [Universidade Federal de Sergipe (UFS), Sao Cristovao, SE (Brazil). Departamento de Ciencia dos Materiais; Ribeiro, Joenesson Filip Santos, E-mail: joenesson.joe@hotmail.com [Universidade Federal de Sergipe (UFS), Sao Cristovao, SE (Brazil). Lab, Materiais e Calorimetria; Alves, Jose do Patrocinio Hora; Ferreira, Angelica Baganha, E-mail: jphalves@uol.com.br, E-mail: angelica.bferreira@itps.se.gov.br [Instituto Tecnologico e de Pesquisas do Estado de Sergipe (ITPS), Aracaju, SE (Brazil)

    2017-01-15

    Oil is an important source of energy, mainly in developing countries. Important research has been conducted to find cementing procedures that guarantee safe and cost-effective oil exploration below pre-salt layers. This work aimed to make a new cement paste with cement, seawater, silica, biopolymers (chitosan and sodium alginate) and hydroxyapatite (HA), found in nature. For comparison purposes, slurry without additives was prepared and characterized. The HA used was extracted from fish scales (Cynoscion acoupa) in optimized condition NaOH concentration, temperature and reaction time. Both slurry were prepared with ratios water/cement (w/c) and silica/cement (s/c) equal to 0.50 and 0.35, respectively. The new cement slurry was obtained with proportions of 5% of each biopolymer and HA with respect to the total weight of the cement. In the immersion tests, specimens were immersed in samples of hyper production of saline water by 35°C for 15 days. Thereafter, they were washed, dried and its surface layers were scraped. Before, the resulting materials were characterized. The values of the ratios Ca/Si of new cement slurry (3.38 ± 0.06) were superior compared to standard (2.58 ± 0.05). The new slurry had high thermal stability and low amounts of small crystallite-type portlandite (35.70 nm). Conversely, a slurry standard formed larger crystals of about 50.3 nm. Significantly, after continuous long-term contact of both slurries with hyper-saline produced water from oil well fields operations, in comparison with standard slurry structural characteristics, the new slurry has practically maintained its pristine chemical structure, as well as has shown crystallite-type particles of NaCl and Friedel’s/Kuzel’s salts with lower proportion. The presence of the biopolymers and HA has driven the improved the self-healing properties observed in the new cement slurry. In this first study, the new slurry has shown adequate characteristics to contribute to cost effective and

  13. Rates and cycles of microbial sulfate reduction in the hyper-saline Dead Sea over the last 200 kyrs from sedimentary d34S and d18O(SO4)

    Science.gov (United States)

    Torfstein, Adi; Turchyn, Alexandra V.

    2017-08-01

    We report the d34S and d18O(SO4) values measured in gypsum, pyrite, and elemental sulfur through a 456-m thick sediment core from the center of the Dead Sea, representing the last 200 kyrs, as well as from the exposed glacial outcrops of the Masada M1 section located on the margins of the modern Dead Sea. The results are used to explore and quantify the evolution of sulfur microbial metabolism in the Dead Sea and to reconstruct the lake’s water column configuration during the late Quaternary. Layers and laminae of primary gypsum, the main sulfur-bearing mineral in the sedimentary column, display the highest d34S and d18O(SO4) in the range of 13-28‰ and 13-30‰, respectively. Within this group, gypsum layers deposited during interglacials have lower d34S and d18O(SO4) relative to those associated with glacial or deglacial stages. The reduced sulfur phases, including chromium reducible sulfur, and secondary gypsum crystals are characterized by extremely low d34S in the range of -27 to +7‰. The d18O(SO4) of the secondary gypsum in the M1 outcrop ranges from 8 to 14‰. The relationship between d34S and d18O(SO4) of primary gypsum suggests that the rate of microbial sulfate reduction was lower during glacial relative to interglacial times. This suggests that the freshening of the lake during glacial wet intervals, and the subsequent rise in sulfate concentrations, slowed the rate of microbial metabolism. Alternatively, this could imply that sulfate-driven anaerobic methane oxidation, the dominant sulfur microbial metabolism today, is a feature of the hypersalinity in the modern Dead Sea. Sedimentary sulfides are quantitatively oxidized during epigenetic exposure, retaining the lower d34S signature; the d18O(SO4) of this secondary gypsum is controlled by oxygen atoms derived equally from atmospheric oxygen and from water, which is likely a unique feature in this hyperarid environment.

  14. A new cement slurry modified with chitosan/alginate interpenetrating networks and hydroxyapatite: structural characteristics after long-term contact with hyper-saline produced water from oil well operations

    International Nuclear Information System (INIS)

    Santos, Ivory Marcos Gomes dos; Santos, Danilo Oliveira; Cestari, Antonio Reinaldo

    2017-01-01

    Oil is an important source of energy, mainly in developing countries. Important research has been conducted to find cementing procedures that guarantee safe and cost-effective oil exploration below pre-salt layers. This work aimed to make a new cement paste with cement, seawater, silica, biopolymers (chitosan and sodium alginate) and hydroxyapatite (HA), found in nature. For comparison purposes, slurry without additives was prepared and characterized. The HA used was extracted from fish scales (Cynoscion acoupa) in optimized condition NaOH concentration, temperature and reaction time. Both slurry were prepared with ratios water/cement (w/c) and silica/cement (s/c) equal to 0.50 and 0.35, respectively. The new cement slurry was obtained with proportions of 5% of each biopolymer and HA with respect to the total weight of the cement. In the immersion tests, specimens were immersed in samples of hyper production of saline water by 35°C for 15 days. Thereafter, they were washed, dried and its surface layers were scraped. Before, the resulting materials were characterized. The values of the ratios Ca/Si of new cement slurry (3.38 ± 0.06) were superior compared to standard (2.58 ± 0.05). The new slurry had high thermal stability and low amounts of small crystallite-type portlandite (35.70 nm). Conversely, a slurry standard formed larger crystals of about 50.3 nm. Significantly, after continuous long-term contact of both slurries with hyper-saline produced water from oil well fields operations, in comparison with standard slurry structural characteristics, the new slurry has practically maintained its pristine chemical structure, as well as has shown crystallite-type particles of NaCl and Friedel’s/Kuzel’s salts with lower proportion. The presence of the biopolymers and HA has driven the improved the self-healing properties observed in the new cement slurry. In this first study, the new slurry has shown adequate characteristics to contribute to cost effective and

  15. 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...

  16. 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

  17. 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

  18. 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

  19. 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...

  20. 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.)

  1. 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.

  2. 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.

  3. 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 ...

  4. 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 ...

  5. 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

  6. 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)

  7. 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

  8. 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)

  9. 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.

  10. 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)

  11. 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

  12. 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.

  13. 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...

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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....

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Characterization of the deep microbial life in the Altmark natural gas reservoir

    Science.gov (United States)

    Morozova, D.; Alawi, M.; Vieth-Hillebrand, A.; Kock, D.; Krüger, M.; Wuerdemann, H.; Shaheed, M.

    2010-12-01

    ., Adicdovorax sp., Ralstonia sp., Pseudomonas sp.), thiosulfate-oxidising bacteria (Diaphorobacter sp.) and biocorrosive thermophilic microorganisms, which have not previously been cultivated. Furthermore, several uncultivated microorganisms were found, that were similar to representatives from other saline, hot, anoxic, deep environments. However, due to the hypersaline and hyperthermophilic reservoir conditions, cell numbers are low, so that the quantification of those microorganisms as well as the determination of microbial activity was not yet possible. Microbial monitoring methods have to be further developed to study microbial activities under these extreme conditions to access their influence on the EGR technique and on enhancing the long term safety of the process by fixation of carbon dioxide by precipitation of carbonates. We thank GDF SUEZ for providing the data for the Rotliegend reservoir, sample material and supporting sampling campaigns. The CLEAN project is funded by the German Federal Ministry of Education and Research (BMBF) in the framework of the GEOTECHNOLOGIEN Program.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. 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

  12. 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).

  13. 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

  14. 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

  15. 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

  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. 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...

  18. 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

  19. 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

  20. 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 ...

  1. 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...

  2. 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.

  3. 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...

  4. 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...

  5. 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...

  6. 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

  7. 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...

  8. 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...

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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).

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.)

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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

  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; 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.

  18. 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).

  19. 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.

  20. 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)

  1. 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.

  2. 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...

  3. 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...

  4. 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

  5. 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

  6. 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

  7. 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...

  8. 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.

  9. 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

  10. 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 ...

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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/ .

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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...

  5. 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.

  6. 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...

  7. 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, $\

  8. 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.)

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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...

  15. 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.)

  16. 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.

  17. 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)

  18. 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

  19. 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…

  20. 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,

  1. 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.

  2. 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

  3. 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

  4. 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)

  5. 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

  6. 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…

  7. 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…

  8. 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.

  9. 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...

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

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

    Science.gov (United States)

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

    2018-02-01

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

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

    OpenAIRE

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

    2016-01-01

    Background 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. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

  19. Deep Galaxy: Classification of Galaxies based on Deep Convolutional Neural Networks

    OpenAIRE

    Khalifa, Nour Eldeen M.; Taha, Mohamed Hamed N.; Hassanien, Aboul Ella; Selim, I. M.

    2017-01-01

    In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep galaxies architecture consists of 8 layers, one main convolutional layer for features extraction with 96 filters, followed by two principles fully connected layers for classification. It is trained over 1356 images and achieved 97.272% in testing accuracy. A c...

  20. Combining shallow and deep processing for a robust, fast, deep-linguistic dependency parser

    OpenAIRE

    Schneider, G

    2004-01-01

    This paper describes Pro3Gres, a fast, robust, broad-coverage parser that delivers deep-linguistic grammatical relation structures as output, which are closer to predicate-argument structures and more informative than pure constituency structures. The parser stays as shallow as is possible for each task, combining shallow and deep-linguistic methods by integrating chunking and by expressing the majority of long-distance dependencies in a context-free way. It combines statistical and rule-base...

  1. New optimized drill pipe size for deep-water, extended reach and ultra-deep drilling

    Energy Technology Data Exchange (ETDEWEB)

    Jellison, Michael J.; Delgado, Ivanni [Grant Prideco, Inc., Hoston, TX (United States); Falcao, Jose Luiz; Sato, Ademar Takashi [PETROBRAS, Rio de Janeiro, RJ (Brazil); Moura, Carlos Amsler [Comercial Perfuradora Delba Baiana Ltda., Rio de Janeiro, RJ (Brazil)

    2004-07-01

    A new drill pipe size, 5-7/8 in. OD, represents enabling technology for Extended Reach Drilling (ERD), deep water and other deep well applications. Most world-class ERD and deep water wells have traditionally been drilled with 5-1/2 in. drill pipe or a combination of 6-5/8 in. and 5-1/2 in. drill pipe. The hydraulic performance of 5-1/2 in. drill pipe can be a major limitation in substantial ERD and deep water wells resulting in poor cuttings removal, slower penetration rates, diminished control over well trajectory and more tendency for drill pipe sticking. The 5-7/8 in. drill pipe provides a significant improvement in hydraulic efficiency compared to 5-1/2 in. drill pipe and does not suffer from the disadvantages associated with use of 6-5/8 in. drill pipe. It represents a drill pipe assembly that is optimized dimensionally and on a performance basis for casing and bit programs that are commonly used for ERD, deep water and ultra-deep wells. The paper discusses the engineering philosophy behind 5-7/8 in. drill pipe, the design challenges associated with development of the product and reviews the features and capabilities of the second-generation double-shoulder connection. The paper provides drilling case history information on significant projects where the pipe has been used and details results achieved with the pipe. (author)

  2. Deep-Sea Corals: A New Oceanic Archive

    National Research Council Canada - National Science Library

    Adkins, Jess

    1998-01-01

    Deep-sea corals are an extraordinary new archive of deep ocean behavior. The species Desmophyllum cristagalli is a solitary coral composed of uranium rich, density banded aragonite that I have calibrated for several paleoclimate tracers...

  3. The development of deep learning in synthetic aperture radar imagery

    CSIR Research Space (South Africa)

    Schwegmann, Colin P

    2017-05-01

    Full Text Available sensing techniques but comes at the price of additional complexities. To adequately cope with these, researchers have begun to employ advanced machine learning techniques known as deep learning to Synthetic Aperture Radar data. Deep learning represents...

  4. Minimally invasive trans-portal resection of deep intracranial lesions.

    NARCIS (Netherlands)

    Raza, S.M.; Recinos, P.F.; Avendano, J.; Adams, H.; Jallo, G.I.; Quinones-Hinojosa, A.

    2011-01-01

    BACKGROUND: The surgical management of deep intra-axial lesions still requires microsurgical approaches that utilize retraction of deep white matter to obtain adequate visualization. We report our experience with a new tubular retractor system, designed specifically for intracranial applications,

  5. Extreme Longevity in Proteinaceous Deep-Sea Corals

    Energy Technology Data Exchange (ETDEWEB)

    Roark, E B; Guilderson, T P; Dunbar, R B; Fallon, S J; Mucciarone, D A

    2009-02-09

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

  6. Assessing Deep Sea Communities Through Seabed Imagery

    Science.gov (United States)

    Matkin, A. G.; Cross, K.; Milititsky, M.

    2016-02-01

    The deep sea still remains virtually unexplored. Human activity, such as oil and gas exploration and deep sea mining, is expanding further into the deep sea, increasing the need to survey and map extensive areas of this habitat in order to assess ecosystem health and value. The technology needed to explore this remote environment has been advancing. Seabed imagery can cover extensive areas of the seafloor and investigate areas where sampling with traditional coring methodologies is just not possible (e.g. cold water coral reefs). Remotely operated vehicles (ROVs) are an expensive option, so drop or towed camera systems can provide a more viable and affordable alternative, while still allowing for real-time control. Assessment of seabed imagery in terms of presence, abundance and density of particular species can be conducted by bringing together a variety of analytical tools for a holistic approach. Sixteen deep sea transects located offshore West Africa were investigated with a towed digital video telemetry system (DTS). Both digital stills and video footage were acquired. An extensive data set was obtained from over 13,000 usable photographs, allowing for characterisation of the different habitats present in terms of community composition and abundance. All observed fauna were identified to the lowest taxonomic level and enumerated when possible, with densities derived after the seabed area was calculated for each suitable photograph. This methodology allowed for consistent assessment of the different habitat types present, overcoming constraints, such as specific taxa that cannot be enumerated, such as sponges, corals or bryozoans, the presence of mobile and sessile species, or the level of taxonomic detail. Although this methodology will not enable a full characterisation of a deep sea community, in terms of species composition for instance, itt will allow a robust assessment of large areas of the deep sea in terms of sensitive habitats present and community

  7. Microbiological characterization of deep geological compartments

    International Nuclear Information System (INIS)

    Barsotti, V.; Sergeant, C.; Vesvres, M.H.; Coulon, S.; Joulian, C.; Garrido, F.; Ollivier, B.

    2012-01-01

    Document available in extended abstract form only. Microbial life in deep sediments and Earth's crust is now acknowledged by the scientific world. The deep subsurface biosphere contributes significantly to fundamental biogeochemical processes. However, despite great advances in geo-microbiological studies, deep terrestrial ecosystems are microbiologically poorly understood, mainly due to their inaccessibility. The drilling down to the base of the Triassic (1980 meters deep) in the geological formations of the eastern Paris Basin performed by ANDRA (EST433) in 2008 provides us a good opportunity to explore the deep biosphere. We conditioned the samples on the coring site, in as aseptic conditions as possible. In addition to storage at atmospheric pressure, a portion of the four Triassic samples was placed in a 190 bars pressurized chamber to investigate the influence of the conservation pressure factor on the found microflora. In parallel, in order to evaluate a potential bacterial contamination of the cores by the drilling fluids, samples of mud just before each sample drilling were taken and analyzed. The microbial exploration can be divided in two parts: - A cultural approach in different culture media for metabolic groups as methanogens, fermenters and sulphate reducing bacteria to stimulate their growth and to isolate microbial cells still viable. - A molecular approach by direct extraction of genomic DNA from the geological samples to explore a larger biodiversity. The limits are here the difficulties to extract DNA from these low biomass containing rocks. After comparison and optimization of several DNA extraction methods, the bacterial diversity present in rock cores was analyzed using DGGE (Denaturating Gel Gradient Electrophoresis) and cloning. The detailed results of all these investigations will be presented: - Despite all 400 cultural conditions experimented (with various media, salinities, temperatures, conservation pressure, agitation), no viable and

  8. Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

    OpenAIRE

    Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

    2016-01-01

    A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

  9. 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...

  10. Benchmarking State-of-the-Art Deep Learning Software Tools

    OpenAIRE

    Shi, Shaohuai; Wang, Qiang; Xu, Pengfei; Chu, Xiaowen

    2016-01-01

    Deep learning has been shown as a successful machine learning method for a variety of tasks, and its popularity results in numerous open-source deep learning software tools. Training a deep network is usually a very time-consuming process. To address the computational challenge in deep learning, many tools exploit hardware features such as multi-core CPUs and many-core GPUs to shorten the training time. However, different tools exhibit different features and running performance when training ...

  11. Deep Complementary Bottleneck Features for Visual Speech Recognition

    NARCIS (Netherlands)

    Petridis, Stavros; Pantic, Maja

    Deep bottleneck features (DBNFs) have been used successfully in the past for acoustic speech recognition from audio. However, research on extracting DBNFs for visual speech recognition is very limited. In this work, we present an approach to extract deep bottleneck visual features based on deep

  12. Automatic Segmentation and Deep Learning of Bird Sounds

    NARCIS (Netherlands)

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

    2015-01-01

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

  13. An Ensemble of Deep Support Vector Machines for Image Categorization

    NARCIS (Netherlands)

    Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

    2009-01-01

    This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next

  14. Deep brain stimulation as a functional scalpel.

    Science.gov (United States)

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

    2006-01-01

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

  15. Preliminary results from NOAMP deep drifting floats

    International Nuclear Information System (INIS)

    Ollitrault, M.

    1989-01-01

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

  16. Ion transport in deep-sea sediments

    International Nuclear Information System (INIS)

    Heath, G.R.

    1979-01-01

    Initial assessment of the ability of deep-sea clays to contain nuclear waste is optimistic. Yet, the investigators have no delusions about the complexity of the natural geochemical system and the perturbations that may result from emplacement of thermally-hot waste cannisters. Even though they may never be able to predict the exact nature of all these perturbations, containment of the nuclides by the waste form/cannister system until most of the heat has decayed, and burial of the waste to a sufficient depth that the altered zone can be treated as a black box source of dissolved nuclides to the enclosing unperturbed sediment, encourage them to believe that ion migration in the deep seabed can be modeled accurately and that our preliminary estimates of migration rates are likely to be reasonably realistic

  17. Deep learning for automated drivetrain fault detection

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2018-01-01

    A novel data-driven deep-learning system for large-scale wind turbine drivetrain monitoring applications is presented. It uses convolutional neural network processing on complex vibration signal inputs. The system is demonstrated to learn successfully from the actions of human diagnostic experts...... the fleet-wide diagnostic model performance. The analysis also explores the time dependence of the diagnostic performance, providing a detailed view of the timeliness and accuracy of the diagnostic outputs across the different architectures. Deep architectures are shown to outperform the human analyst...... as well as shallow-learning architectures, and the results demonstrate that when applied in a large-scale monitoring system, machine intelligence is now able to handle some of the most challenging diagnostic tasks related to wind turbines....

  18. Jet-images — deep learning edition

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Luke de [Institute for Computational and Mathematical Engineering, Stanford University,Huang Building 475 Via Ortega, Stanford, CA 94305 (United States); Kagan, Michael [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Mackey, Lester [Department of Statistics, Stanford University,390 Serra Mall, Stanford, CA 94305 (United States); Nachman, Benjamin; Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States)

    2016-07-13

    Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. This interplay between physically-motivated feature driven tools and supervised learning algorithms is general and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.

  19. JGR special issue on Deep Earthquakes

    Science.gov (United States)

    The editor and associate editors of the Journal of Geophysical Research—Solid Earth and Planets invite the submission of manuscripts for a special issue on the topic “Deep- and Intermediate-Focus Earthquakes, Phase Transitions, and the Mechanics of Deep Subduction.”Manuscripts should be submitted to JGR Editor Gerald Schubert (Department of Earth and Space Sciences, University of California, Los Angeles, Los Angeles, CA 90024) before July 1, 1986, in accordance with the usual rules for manuscript submission. Submitted papers will undergo the normal JGR review procedure. For more information, contact either Schubert or the special guest associate editor, Cliff Frohlich (Institute for Geophysics, University of Texas at Austin, 4920 North IH-35, Austin, TX 78751; telephone: 512-451-6223).

  20. Ensemble Network Architecture for Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Xi-liang Chen

    2018-01-01

    Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

  1. DCMDN: Deep Convolutional Mixture Density Network

    Science.gov (United States)

    D'Isanto, Antonio; Polsterer, Kai Lars

    2017-09-01

    Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

  2. An Introduction to Deep Learning with Keras

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Keras is a modular, powerful and intuitive open-source Deep Learning library built on Theano and TensorFlow. Thanks to its minimalist, user-friendly interface, it has become one of the most popular packages to build, train and test neural networks, for both beginners and experts. In this tutorial, we will start with an introduction of the basics of neural networks and will work through fully functioning examples, with an eye towards deployment strategies within the context of CERN. Fundamental steps and parameters in Deep Learning will be presented both from a conceptual and a practical standpoint, by looking at the way Keras implements them and exposes them to the users. Please visit the [Keras website][1] prior to the workshop for installation instructions and feel free to reach out for any issue. [1]: http://keras.io/#installation

  3. Deep space test bed for radiation studies

    International Nuclear Information System (INIS)

    Adams, James H.; Adcock, Leonard; Apple, Jeffery; Christl, Mark; Cleveand, William; Cox, Mark; Dietz, Kurt; Ferguson, Cynthia; Fountain, Walt; Ghita, Bogdan; Kuznetsov, Evgeny; Milton, Martha; Myers, Jeremy; O'Brien, Sue; Seaquist, Jim; Smith, Edward A.; Smith, Guy; Warden, Lance; Watts, John

    2007-01-01

    The Deep Space Test-Bed (DSTB) Facility is designed to investigate the effects of galactic cosmic rays on crews and systems during missions to the Moon or Mars. To gain access to the interplanetary ionizing radiation environment the DSTB uses high-altitude polar balloon flights. The DSTB provides a platform for measurements to validate the radiation transport codes that are used by NASA to calculate the radiation environment within crewed space systems. It is also designed to support other exploration related investigations such as measuring the shielding effectiveness of candidate spacecraft and habitat materials, testing new radiation monitoring instrumentation, flight avionics and investigating the biological effects of deep space radiation. We describe the work completed thus far in the development of the DSTB and its current status

  4. Nanostructured Deep Carbon: A Wealth of Possibilities

    Science.gov (United States)

    Navrotsky, A.

    2012-12-01

    The materials science community has been investigating novel forms of carbon including C60 buckyballs, nanodiamond, graphene, carbon "onion" structures with a mixture of sp2 and sp3 bonding , and multicomponent nanostructured Si-O-C-N polymer derived ceramics. Though such materials are generally viewed as metastable, recently measured energetics of several materials suggest that this may not always be the case in multicomponent systems. Finely disseminated carbon phases, including nanodiamonds, have been found in rocks from a variety of deep earth settings. The question then is whether some of the more exotic forms of carbon can also exist in the deep earth or other planetary interiors. This presentation discusses thermodynamic constraints related to surface and interface energies, nanodomain structures, and compositional effects on the possible existence of complex carbon, carbide and oxycarbide nanomaterials at high pressure.

  5. Randomized Clinical Trials on Deep Carious Lesions

    DEFF Research Database (Denmark)

    Bjørndal, Lars; Fransson, Helena; Bruun, Gitte

    2017-01-01

    nonselective carious removal to hard dentin with or without pulp exposure. The aim of this article was to report the 5-y outcome on these previously treated patients having radiographically well-defined carious lesions extending into the pulpal quarter of the dentin but with a well-defined radiodense zone...... pulp exposures per se were included as failures. Pulp exposure rate was significantly lower in the stepwise carious removal group (21.2% vs. 35.5%; P = 0.014). Irrespective of pulp exposure status, the difference (13.3%) was still significant when sustained pulp vitality without apical radiolucency......) in deep carious lesions in adults. In conclusion, the stepwise carious removal group had a significantly higher proportion of pulps with sustained vitality without apical radiolucency versus nonselective carious removal of deep carious lesions in adult teeth at 5-y follow-up (ClinicalTrials.gov NCT...

  6. Gas Classification Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-01

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

  7. Recanalization after acute deep vein thrombosis

    Directory of Open Access Journals (Sweden)

    Gustavo Mucoucah Sampaio Brandao

    2013-12-01

    Full Text Available The process of recanalization of the veins of the lower limbs after an episode of acute deep venous thrombosis is part of the natural evolution of the remodeling of the venous thrombus in patients on anticoagulation with heparin and vitamin K inhibitors. This remodeling involves the complex process of adhesion of thrombus to the wall of the vein, the inflammatory response of the vessel wall leading to organization and subsequent contraction of the thrombus, neovascularization and spontaneous lysis of areas within the thrombus. The occurrence of spontaneous arterial flow in recanalized thrombosed veins has been described as secondary to neovascularization and is characterized by the development of flow patterns characteristic of arteriovenous fistulae that can be identified by color duplex scanning. In this review, we discuss some controversial aspects of the natural history of deep vein thrombosis to provide a better understanding of its course and its impact on venous disease.

  8. Learning with hierarchical-deep models.

    Science.gov (United States)

    Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

    2013-08-01

    We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

  9. Gas Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-08

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

  10. Computational ghost imaging using deep learning

    Science.gov (United States)

    Shimobaba, Tomoyoshi; Endo, Yutaka; Nishitsuji, Takashi; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Shiraki, Atsushi; Ito, Tomoyoshi

    2018-04-01

    Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (or reflected) by an object. Although CGI can obtain two- or three-dimensional images with a single or a few bucket detectors, the quality of the reconstructed images is reduced by noise due to the reconstruction of images from random patterns. In this study, we improve the quality of CGI images using deep learning. A deep neural network is used to automatically learn the features of noise-contaminated CGI images. After training, the network is able to predict low-noise images from new noise-contaminated CGI images.

  11. Jet-images — deep learning edition

    International Nuclear Information System (INIS)

    Oliveira, Luke de; Kagan, Michael; Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel

    2016-01-01

    Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. This interplay between physically-motivated feature driven tools and supervised learning algorithms is general and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.

  12. On deep inelastic lepton-nuclear interactions

    International Nuclear Information System (INIS)

    Garsevanishvili, V.R.; Darbaidze, Ya.Z.; Menteshashvili, Z.R.; Ehsakiya, Sh.M.

    1981-01-01

    The problem of building relativistic theory of nuclear reactions by way of involving relativistic methods, developed in the elementary particle theory, becomes rather actual at the time being. The paper presents some results of investigations into deep inelastic lepton-nuclear processes lA → l'(A-1)x, with the spectator nucleus-fragment in the finite state. To describe the reactions lA → l'(A-1)x (where l=an electron, muan, neutrino, antineutrino), the use is made of the self-similarity principle and multiparticle quasipotential formalism in the ''light front'' variables. The expressions are obtained for the differential cross-sections of lepton-nuclear processes and for the structure functions of deep inelastic scattering of neutrinos (antineutrinos) and charged leptons by nuclei

  13. DAPs: Deep Action Proposals for Action Understanding

    KAUST Repository

    Escorcia, Victor

    2016-09-17

    Object proposals have contributed significantly to recent advances in object understanding in images. Inspired by the success of this approach, we introduce Deep Action Proposals (DAPs), an effective and efficient algorithm for generating temporal 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 that our approach outperforms previous work on a large scale action benchmark, runs at 134 FPS making it practical for large-scale scenarios, and exhibits an appealing ability to generalize, i.e. to retrieve good quality temporal proposals of actions unseen in training.

  14. pathways to deep decarbonization - 2014 report

    International Nuclear Information System (INIS)

    Sachs, Jeffrey; Guerin, Emmanuel; Mas, Carl; Schmidt-Traub, Guido; Tubiana, Laurence; Waisman, Henri; Colombier, Michel; Bulger, Claire; Sulakshana, Elana; Zhang, Kathy; Barthelemy, Pierre; Spinazze, Lena; Pharabod, Ivan

    2014-09-01

    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. 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.' Successfully transition to a low-carbon economy will require unprecedented global cooperation, including a global cooperative effort to accelerate the development and diffusion of some key low carbon technologies. As underscored throughout this report, the results of the DDPP analyses remain preliminary and incomplete. The DDPP proceeds in two phases. This 2014 report describes the DDPP's approach to deep decarbonization at the country level and presents preliminary findings on technically feasible pathways to deep decarbonization, utilizing technology assumptions and timelines provided by the DDPP Secretariat. At this stage we have not yet considered the economic and social costs and benefits of deep decarbonization, which will be the topic for the next report. The DDPP is issuing this 2014 report to the UN Secretary-General Ban Ki-moon in support of the Climate Leaders' Summit at the United Nations on September 23, 2014. This 2014 report by the Deep Decarbonization Pathway Project (DDPP) summarizes preliminary findings of the technical pathways developed by the DDPP Country Research Partners with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C., without, at this stage, consideration of economic and social costs and benefits. The DDPP is a knowledge

  15. Deep soft tissue leiomyoma of the thigh

    International Nuclear Information System (INIS)

    Watson, G.M.T.; Saifuddin, A.; Sandison, A.

    1999-01-01

    A case of ossified leiomyoma of the deep soft tissues of the left thigh is presented. The radiographic appearance suggested a low-grade chondrosarcoma. MRI of the lesion showed signal characteristics similar to muscle on both T1- and T2-weighted spin echo sequences with linear areas of high signal intensity on T1-weighted images consistent with medullary fat in metaplastic bone. Histopathological examination of the resected specimen revealed a benign ossified soft tissue leiomyoma. (orig.)

  16. Blind source deconvolution for deep Earth seismology

    Science.gov (United States)

    Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

    2007-12-01

    We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

  17. Tephrostratigraphy the DEEP site record, Lake Ohrid

    Science.gov (United States)

    Leicher, N.; Zanchetta, G.; Sulpizio, R.; Giaccio, B.; Wagner, B.; Francke, A.

    2016-12-01

    In the central Mediterranean region, tephrostratigraphy has been proofed to be a suitable and powerful tool for dating and correlating marine and terrestrial records. However, for the period older 200 ka, tephrostratigraphy is incomplete and restricted to some Italian continental basins (e.g. Sulmona, Acerno, Mercure), and continuous records downwind of the Italian volcanoes are rare. Lake Ohrid (Macedonia/Albania) in the eastern Mediterranean region fits this requisite and is assumed to be the oldest continuously existing lake of Europe. A continous record (DEEP) was recovered within the scope of the ICDP deep-drilling campaign SCOPSCO (Scientific Collaboration on Past Speciation Conditions in Lake Ohrid). In the uppermost 450 meters of the record, covering more than 1.2 Myrs of Italian volcanism, 54 tephra layers were identified during core-opening and description. A first tephrostratigraphic record was established for the uppermost 248 m ( 637 ka). Major element analyses (EDS/WDS) were carried out on juvenile glass fragments and 15 out of 35 tephra layers have been identified and correlated with known and dated eruptions of Italian volcanoes. Existing 40Ar/39Ar ages were re-calculated by using the same flux standard and used as first order tie points to develop a robust chronology for the DEEP site succession. Between 248 and 450 m of the DEEP site record, another 19 tephra horizons were identified and are subject of ongoing work. These deposits, once correlated with known and dated tephra, will hopefully enable dating this part of the succession, likely supported by major paleomagnetic events, such as the Brunhes-Matuyama boundary, or the Cobb-Mountain or the Jaramillo excursions. This makes the Lake Ohrid record a unique continuous, distal record of Italian volcanic activity, which is candidate to become the template for the central Mediterranean tephrostratigraphy, especially for the hitherto poorly known and explored lower Middle Pleistocene period.

  18. Uncertain Photometric Redshifts with Deep Learning Methods

    Science.gov (United States)

    D'Isanto, A.

    2017-06-01

    The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a method for determining accurate multi-modal photo-z probability density functions (PDFs) using Mixture Density Networks (MDN) and Deep Convolutional Networks (DCN). A comparison with a Random Forest (RF) is performed.

  19. Brucellosis associated with deep vein thrombosis.

    Science.gov (United States)

    Tolaj, Ilir; Mehmeti, Murat; Ramadani, Hamdi; Tolaj, Jasmina; Dedushi, Kreshnike; Fejza, Hajrullah

    2014-11-19

    Over the past 10 years more than 700 cases of brucellosis have been reported in Kosovo, which is heavily oriented towards agriculture and animal husbandry. Here, brucellosis is still endemic and represents an uncontrolled public health problem. Human brucellosis may present with a broad spectrum of clinical manifestations; among them, vascular complications are uncommon. Hereby we describe the case of a 37-year-old male patient with brucellosis complicated by deep vein thrombosis on his left leg.

  20. Gene expression inference with deep learning.

    Science.gov (United States)

    Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

    2016-06-15

    Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.