WorldWideScience

Sample records for macleodii deep ecotype

  1. Why close a bacterial genome? The plasmid of Alteromonas macleodii HOT1A3 is a vector for inter-specific transfer of a flexible genomic island

    Directory of Open Access Journals (Sweden)

    Eduard eFadeev

    2016-03-01

    Full Text Available Genome sequencing is rapidly becoming a staple technique in environmental and clinical microbiology, yet computational challenges still remain, leading to many draft genomes which are typically fragmented into many contigs. We sequenced and completely assembled the genome of a marine heterotrophic bacterium, Alteromonas macleodii HOT1A3, and compared its full genome to several draft genomes obtained using different reference-based and de-novo methods. In general, the de-novo assemblies clearly outperformed the reference-based or hybrid ones, covering>99% of the genes and representing essentially all of the gene functions. However, only the fully closed genome (~4.5Mbp allowed us to identify the presence of a large, 148 kbp plasmid, pAM1A3. While HOT1A3 belongs to Alteromonas macleodii, typically found in surface waters (surface ecotype, this plasmid consists of an almost complete flexible genomic island, containing many genes involved in metal resistance previously identified in the genomes of Alteromonas mediterranea (deep ecotype. Indeed, similar to A. mediterranea, A. macleodii HOT1A3 grows at concentrations of zinc, mercury and copper that are inhibitory for other A. macleodii strains. The presence of a plasmid encoding almost an entire flexible genomic island suggests that wholesale genomic exchange between heterotrophic marine bacteria belonging to related but ecologically different populations is not uncommon.

  2. Switchgrass ecotypes alter microbial contribution to deep-soil C

    Science.gov (United States)

    Roosendaal, Damaris; Stewart, Catherine E.; Denef, Karolien; Follett, Ronald F.; Pruessner, Elizabeth; Comas, Louise H.; Varvel, Gary E.; Saathoff, Aaron; Palmer, Nathan; Sarath, Gautam; Jin, Virginia L.; Schmer, Marty; Soundararajan, Madhavan

    2016-05-01

    Switchgrass (Panicum virgatum L.) is a C4, perennial grass that is being developed as a bioenergy crop for the United States. While aboveground biomass production is well documented for switchgrass ecotypes (lowland, upland), little is known about the impact of plant belowground productivity on microbial communities down deep in the soil profiles. Microbial dynamics in deeper soils are likely to exert considerable control on ecosystem services, including C and nutrient cycles, due to their involvement in such processes as soil formation and ecosystem biogeochemistry. Differences in root biomass and rooting characteristics of switchgrass ecotypes could lead to distinct differences in belowground microbial biomass and microbial community composition. We quantified root abundance and root architecture and the associated microbial abundance, composition, and rhizodeposit C uptake for two switchgrass ecotypes using stable-isotope probing of microbial phospholipid fatty acids (PLFAs) after 13CO2 pulse-chase labeling. Kanlow, a lowland ecotype with thicker roots, had greater plant biomass above- and belowground (g m-2), greater root mass density (mg cm-3), and lower specific root length (m g-1) compared to Summer, an upland ecotype with finer root architecture. The relative abundance of bacterial biomarkers dominated microbial PLFA profiles for soils under both Kanlow and Summer (55.4 and 53.5 %, respectively; P = 0.0367), with differences attributable to a greater relative abundance of Gram-negative bacteria in soils under Kanlow (18.1 %) compared to soils under Summer (16.3 %; P = 0.0455). The two ecotypes also had distinctly different microbial communities process rhizodeposit C: greater relative atom % 13C excess in Gram-negative bacteria (44.1 ± 2.3 %) under the thicker roots of Kanlow and greater relative atom % 13C excess in saprotrophic fungi under the thinner roots of Summer (48.5 ± 2.2 %). For bioenergy production systems, variation between switchgrass

  3. Antioxidant and hepatoprotective activity of Cordia macleodii leaves

    Science.gov (United States)

    Qureshi, Naseem N.; Kuchekar, Bhanudansh S.; Logade, Nadeem A.; Haleem, Majid A.

    2009-01-01

    This investigation was undertaken to evaluate ethanolic extract of Cordia macleodii leaves for possible antioxidant and hepatoprotective potential. Antioxidant activity of the extracts was evaluated by four established, in vitro methods viz. 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging method, nitric oxide (NO) radical scavenging method, iron chelation method and reducing power method. The extract demonstrated a significant dose dependent antioxidant activity comparable with ascorbic acid. The extract was also evaluated for hepatoprotective activity by carbon tetrachloride (CCl4) induced liver damage model in rats. CCl4 produced a significant increase in levels of serum glutamate pyruvate transaminase (GPT), serum glutamate oxaloacetate transaminase (GOT), Alkaline Phosphatase (ALP) and total bilirubin. Pretreatment of the rats with ethanolic extract of C. macleodii (100, 200 and 400 mg/kg po) inhibited the increase in levels of GPT, GOT, ALP and total bilirubin and the inhibition was comparable with Silymarin (100 mg/kg po). The present study revealed that C. macleodii leaves have significant radical scavenging and hepatoprotective activities. PMID:23960714

  4. Antivenom potential of ethanolic extract of Cordia macleodii bark against Naja venom

    OpenAIRE

    Pranay Soni; Surendra H. Bodakhe

    2014-01-01

    Objective: To evaluate the antivenom potential of ethanolic extract of bark of Cordia macleodii against Naja venom induced pharmacological effects such as lethality, hemorrhagic lesion, necrotizing lesion, edema, cardiotoxicity and neurotoxicity. Methods: Wistar strain rats were challenged with Naja venom and treated with the ethanolic extract of Cordia macleodii bark. The effectiveness of the extract to neutralize the lethalities of Naja venom was investigated as recommended by WHO. Re...

  5. Antivenom potential of ethanolic extract of Cordia macleodii bark against Naja venom.

    Science.gov (United States)

    Soni, Pranay; Bodakhe, Surendra H

    2014-05-01

    To evaluate the antivenom potential of ethanolic extract of bark of Cordia macleodii against Naja venom induced pharmacological effects such as lethality, hemorrhagic lesion, necrotizing lesion, edema, cardiotoxicity and neurotoxicity. Wistar strain rats were challenged with Naja venom and treated with the ethanolic extract of Cordia macleodii bark. The effectiveness of the extract to neutralize the lethalities of Naja venom was investigated as recommended by WHO. At the dose of 400 and 800 mg/kg ethanolic extract of Cordia macleodii bark significantly inhibited the Naja venom induced lethality, hemorrhagic lesion, necrotizing lesion and edema in rats. Ethanolic extract of Cordia macleodii bark was effective in neutralizing the coagulant and defibrinogenating activity of Naja venom. The cardiotoxic effects in isolated frog heart and neurotoxic activity studies on frog rectus abdominus muscle were also antagonized by ethanolic extract of Cordia macleodii bark. It is concluded that the protective effect of extract of Cordia macleodii against Naja venom poisoning may be mediated by the cardiotonic, proteolysin neutralization, anti-inflammatory, antiserotonic and antihistaminic activity. It is possible that the protective effect may also be due to precipitation of active venom constituents.

  6. Adaptation to copper stress influences biofilm formation in Alteromonas macleodii.

    Science.gov (United States)

    Cusick, Kathleen D; Dale, Jason R; Fitzgerald, Lisa A; Little, Brenda J; Biffinger, Justin C

    2017-07-01

    An Alteromonas macleodii strain was isolated from copper-containing coupons incubated in surface seawater (Key West, FL, USA). In addition to the original isolate, a copper-adapted mutant was created and maintained with 0.78 mM Cu 2+ . Biofilm formation was compared between the two strains under copper-amended and low-nutrient conditions. Biofilm formation was significantly increased in the original isolate under copper amendment, while biofilm formation was significantly higher in the mutant under low-nutrient conditions. Biofilm expression profiles of diguanylate cyclase (DGC) genes, as well as genes involved in secretion, differed between the strains. Comparative genomic analysis demonstrated that both strains possessed a large number of gene attachment harboring cyclic di-GMP synthesis and/or degradation domains. One of the DGC genes, induced at very high levels in the mutant, possessed a degradation domain in the original isolate that was lacking in the mutant. The genetic and transcriptional mechanisms contributing to biofilm formation are discussed.

  7. Antivenom potential of ethanolic extract of Cordia macleodii bark against Naja venom

    Directory of Open Access Journals (Sweden)

    Pranay Soni

    2014-05-01

    Conclusions: It is concluded that the protective effect of extract of Cordia macleodii against Naja venom poisoning may be mediated by the cardiotonic, proteolysin neutralization, anti-inflammatory, antiserotonic and antihistaminic activity. It is possible that the protective effect may also be due to precipitation of active venom constituents.

  8. Pharmacognostic evaluation of leaf of Cordia macleodii Hook., An ethnomedicinally important plant.

    Science.gov (United States)

    Bhide, Bhargav; Pillai, A P G; Shukla, V J; Acharya, R N

    2011-04-01

    Plants of ethnomedicinal importance have contributed for the development of many new pharmacologically effective molecules/chemical entities to modern medicine. India, the country having one of the richest biodiversity of its flora in its forest, with numerous tribal inhabitants, is able to contribute a lot from ethnomedicine to the ailing humanity. Cordia macleodii Hook. (Boraginaceae), an ethnomedicinal plant has been highlighted for its wound healing, aphrodisiac and hepatoprotective activities. It is a medium-sized tree, known as Panki/Shikari by the tribals, rarely found in the forests of Orissa, Chhattisgarh and Madhya Pradesh. So far, the plant has been studied neither for its pharmacognostical characters nor for its pharmacological actions except its hepatoprotective activity. Hence, it has been selected for a detailed investigation which includes pharmacognostic study of its leaf to find out the diagnostic characters and preliminary physicochemical analysis. Results of the study will help in identifying the plant pharmacognostically. Presence of alkaloids, glycosides and tannins were found during the study.

  9. Genetic variation between ecotypic populations of Chloris ...

    African Journals Online (AJOL)

    Genetic variation between ecotypic populations of Chloris roxburghiana grass detected through RAPD analysis. ... frequency indicated that the four populations of C. roxburghiana were genetically distinct, probably as a result of variation in soil fertility, geographical isolation and socio-ecological history of the study sites.

  10. Evaluation of Freeze Tolerance in Lancelot Plantain (Plantago lanceolata L. Ecotypes under Controlled Conditions

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    M. Janalizadeh

    2016-02-01

    Full Text Available Introduction Lancelot Plantain (Ribwort, narrow-leaf or English plantain is a deep-rooted, short-lived perennial herb from Plantaginaceae family which has been used for various medicinal purposes for centuries, especially in Europe and only more recently has been proposed as a forage plant. The leaf of plantain is highly palatable for grazing animals, providing mineral-rich forage. Recently two productive upright cultivars of plantain have been bred and introduced, Grasslands Lancelot and the more erect winter active Ceres Tonic. Plantain grows moderately in winter but its main growth periods beings in spring and autumn with opportunistic summer growth. Although it reveals suitable winter survival in natural conditions, but there is not a lot of information about cold tolerance of this plant. So it is important to recognize the freeze tolerance of narrow leaf plantain for successful planting and utilization in cold regions such as Mashhad in Khorasan Razavi Province (Northeast of Iran. Determining LT50 point or critical temperature for survival of plant is the most reliable and simple method for evaluating cold tolerance of plants. Another reliable method for freeze tolerance of plants is estimation of temperature at which 50 % of dry matter reduces (RDMT50. This experiment was carried out to evaluate freeze tolerance of five ecotypes of Lancelot plantain according to the LT50su and RDMT50 indices. Materials and Methods In order to evaluate freeze tolerance of Lancelot plantain, a factorial experiment based on completely randomized design with three replications was carried out under controlled conditions at college of agriculture, Ferdowsi University of Mashhad. Five ecotypes of Lancelot plantain (Bojnourd, Kalat, Mashhad, Ghayen and Birjand after three months growth and hardening in natural environment were transferred to a Thermo gradient freezer on January 20th, 2012 and exposed to eight freezing temperatures (Zero, -3, -6, -9, -12, -15, -18

  11. Morphological features of indigenous chicken ecotype populations of Kenya

    NARCIS (Netherlands)

    Ngeno, K.; Waaij, van der E.H.; Kahi, A.K.; Arendonk, van J.A.M.

    2014-01-01

    This study characterized indigenous chicken (IC) ecotypes morphologically. Five IC ecotypes studied were Kakamega (KK), Siaya (BN), West Pokot (WP), Narok (NR) and Bomet (BM). Data on morphological features were collected from 1 580 chickens and 151 for zoometric measurements. Descriptive

  12. The evaluation of four Eragrostis curvula ecotypes with grazing sheep.

    African Journals Online (AJOL)

    There were no significant differences in the dry matter production and chemical composition of the clipped samples of the ecotypes. Keywords: afrikaans; chemical composition; dry matter production; ecotypes; eragrostis curvula; grazing; live mass; live mass gains; open rotational grazing system; production; sheep; south ...

  13. Varied growth response of cogongrass ecotypes to elevated CO2

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    G. Brett Runion

    2016-01-01

    Full Text Available Cogongrass [Imperata cylindrica (L. P. Beauv] is an invasive C4 perennial grass which is listed as one of the top ten worst weeds in the world and is a major problem in the Southeast US. Five cogongrass ecotypes (Florida, Hybrid, Louisiana, Mobile, and North Alabama collected across the Southeast and a red-tip ornamental variety were container grown for six months in open top chambers under ambient and elevated (ambient plus 200 ppm atmospheric CO2. Elevated CO2 increased average dry weight (13% which is typical for grasses. Elevated CO2 increased height growth and both nitrogen and water use efficiencies, but lowered tissue nitrogen concentration; again, these are typical plant responses to elevated CO2. The hybrid ecotype tended to exhibit the greatest growth (followed by Louisiana, North Alabama, and Florida ecotypes while the red-tip and Mobile ecotypes were smallest. Interactions of CO2 with ecotype generally showed that the hybrid, Louisiana, Florida, and/or North Alabama ecotypes showed a positive response to CO2 while the Mobile and red-tip ecotypes did not. Cogongrass is a problematic invasive weed in the southeastern U.S. and some ecotypes may become more so as atmospheric CO2 continues to rise.

  14. Extracellular polysaccharide production by a novel osmotolerant marine strain of Alteromonas macleodii and its application towards biomineralization of silver.

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    Ananya Mehta

    Full Text Available The present study demonstrates exopolysaccharide production by an osmotolerant marine isolate and also describes further application of the purified polysaccharide for production of colloidal suspension of silver nanoparticles with narrow size distribution. Phylogenetic analysis based on 16S r RNA gene sequencing revealed close affinity of the isolate to Alteromonas macleodii. Unlike earlier reports, where glucose was used as the carbon source, lactose was found to be the most suitable substrate for polysaccharide production. The strain was capable of producing 23.4 gl(-1 exopolysaccharide with a productivity of 7.8 gl(-1 day(-1 when 15% (w/v lactose was used as carbon source. Furthermore, the purified polysaccharide was able to produce spherical shaped silver nanoparticles of around 70 nm size as characterized by Uv-vis spectroscopy, Dynamic light scattering and Transmission electron microscopy. These observations suggested possible commercial potential of the isolated strain for production of a polysaccharide which has the capability of synthesizing biocompatible metal nanoparticle.

  15. Genetic diversity of indigenous chicken ecotypes in Jordan

    African Journals Online (AJOL)

    Jane

    2010-10-11

    Oct 11, 2010 ... DNA polymorphism of 4 indigenous chicken ecotypes was assessed in Jordan using random amplified ... Such technology is random amplified polymorphic DNA. (RAPD) ..... ping from genetics lab for animal and plant at MU.

  16. Genetic structure among the local chicken ecotypes of Tanzania ...

    African Journals Online (AJOL)

    A study was conducted to evaluate the genetic structure of local chicken ecotypes of Tanzania using 20 polymorphic microsatellite DNA markers. A standard PCR was followed by manual genotyping (6% native polyacrylamide gel visualized by silver staining). Phylogenetic analysis of 13 individuals from each of the nine ...

  17. Asymmetric impacts of two herbivore ecotypes on similar host plants

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    Ecotypes may arise following allopatric separation from source populations. The simultaneous transfer of an exotic plant to a novel environment, along with its stenophagous herbivore, may complicate more traditional patterns of divergence from the plant and insect source populations. We evaluated ...

  18. Varied growth response of cogongrass ecotypes to elevated CO2

    Science.gov (United States)

    Cogongrass [Imperata cylindrica (L.) P. Beauv] is an invasive C4 perennial grass which is listed as one of the top ten worst weeds in the world and is a major problem in the Southeast US. Five cogongrass ecotypes (Florida, Hybrid, Louisiana, Mobile, and North Alabama) collected across the Southeast ...

  19. Genetic variations between two ecotypes of Egyptian clover by inter ...

    African Journals Online (AJOL)

    Aghomotsegin

    2015-06-10

    Jun 10, 2015 ... Four Egyptian clover (Trifolium alexandrinum L) cultivars representing two ecotypes were used in the present study. Fahl cultivar is prevalent in whole Egypt and is good for single cut as it has poor regeneration ability, whereas Serw1, Giza6 and Gemmiza1 give 5-6 cuts of good fodder. Techniques based ...

  20. The molecular dimension of microbial species: 1. Ecological distinctions among, and homogeneity within, putative ecotypes of Synechococcus inhabiting the cyanobacterial mat of Mushroom Spring, Yellowstone National Park

    DEFF Research Database (Denmark)

    Becraft, Eric D.; Wood, Jason M.; Rusch, Douglas B.

    2015-01-01

    Based on the Stable Ecotype Model, evolution leads to the divergence of ecologically distinct populations (e.g., with different niches and/or behaviors) of ecologically interchangeable membership. In this study, pyrosequencing was used to provide deep sequence coverage of Synechococcus psaA genes...... the PEs are ecologically distinct, the members of each ecotype are ecologically homogeneous. PEs responded differently to experimental perturbations of temperature and light, but the genetic variation within each PE was maintained as the relative abundances of PEs changed, further indicating that each...

  1. Accumulation and tolerance of lead in two contrasting ecotypes of Dianthus carthusianorum.

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    Wójcik, Małgorzata; Tukiendorf, Anna

    2014-04-01

    Dianthus carthusianorum is one of the dominant plant species colonising the Zn-Pb waste deposits in Bolesław, Southern Poland. It differs in terms of morphology and genetics from ecotypes inhabiting non-metal-polluted areas. The response of waste-heap (metallicolous, M) and reference (nonmetallicolous, NM) ecotypes of D. carthusianorum to Pb in hydroponics was investigated and compared in this study. The plants of the M ecotype were more tolerant to Pb than these of the NM ecotype in spite of accumulation of higher concentrations of Pb. In both ecotypes, about 70-78% of Pb was retained in roots. In non Pb-treated plants, a higher glutathione (GSH) level was found in the M ecotype. After the Pb exposure, the GSH level decreased and was similar in both ecotypes. Lead treatment induced synthesis of phytochelatins (PCs) only in the plant roots, with significantly higher concentrations thereof detected in the NM ecotype. Malate and citrate concentrations were higher in the M ecotype; however, they did not change significantly upon any Pb treatment in either ecotype. The results indicated that neither PCs nor organic acids were responsible for the enhanced Pb tolerance of the waste-heap plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Cadmium Induced Changes of Proline in Two Ecotypes of Thlaspi Caerulescens

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    Zemanová V.

    2013-04-01

    Full Text Available A Thlaspi caerulescens (J. & C. PRESL was used to study the effect of cadmium on the content of free amino acids and ability accumulation of Cd in ecotypes of this plant species. In pot experiment two ecotypes T. caerulescens were used: Ganges ecotype from France and Mežica ecotype from Slovenia. The plants were grown in soil (chernozem – Suchdol spiked with NPK and three different concentration of Cd: 30, 60 and 90 mg/kg. The content of Cd was measured in the above-ground biomass and roots using ICP-OES. Accumulation of Cd was higher in the Mežica ecotype in contrast to the low Cd-accumulating the Ganges ecotype. Analyses of free amino acids contents were measured by GC-MS method. The content of free amino acids in above-ground biomass of the Mežica ecotype declined progressively with increasing concentrations of Cd. Opposite trend was observed in roots of this ecotype. The increase of free amino acids contents in above-ground biomass and roots of the Ganges ecotype were detected. The results of specific amino acids free proline showed increased content in plant biomass with increasing Cd contamination of soil. A statistically significant increase was observed between control plants (0 mg/kg Cd and variant Cd3 (90 mg/kg Cd for both ecotypes. The statistically significant decrease of free proline was observed in the Mežica ecotype roots. Opposite trend was observed in roots of Ganges ecotype - increasing trend of free proline content. These results indicate a correlation between content of Cd and content of free proline in different parts of the plant. We can speculate that the mechanism of Cd hyperaccumulation and metabolism of free proline are not identical in ecotypes of this species.

  3. Ecotypic variation in population dynamics of reintroduced bighorn sheep

    Science.gov (United States)

    Bleich, Vernon C.; Sargeant, Glen A.; Wiedmann, Brett P.

    2018-01-01

    Selection of bighorn sheep (Ovis canadensis) for translocation historically has been motivated by preservation of subspecific purity rather than by adaptation of source stocks to similar environments. Our objective was to estimate cause‐specific, annual, and age‐specific mortality of introduced bighorn sheep that originated at low elevations in southern British Columbia, Canada (BC ecotype), or in the Missouri River Breaks region of central Montana, USA (MT ecotype). In North Dakota, USA, mortality was similar and typically low for adult female bighorn sheep from Montana (0.09 ± 0.029 [SE]) and British Columbia (0.08 ± 0.017) during 2000–2016. Median life expectancy was 11 years for females that reached adulthood (2 yrs old); however, mortality accelerated with age and reached 86% by age 16. Mortalities resulted primarily from low rates of predation, disease, accidents, and unknown natural causes (<0.04 [upper 90% CI]). Similar survival rates of female bighorn sheep from female bighorn sheep from British Columbia and Montana, coupled with greater recruitment of bighorn sheep from Montana, resulted in a greater projected rate of increase for the MT ecotype (λ = 1.21) than for the BC ecotype (1.02), and a more youthful age structure. These results support translocation of bighorn sheep from areas that are environmentally similar to areas that will be stocked. Potential benefits include more rapid population growth, greater resilience to and more rapid recovery from density‐independent losses, an increased possibility that rapidly growing populations will expand into adjacent habitat, increased hunter opportunity, increased connectivity among herds, and a more complete restoration of ecosystem processes.

  4. Ecotypic variation in population dynamics of reintroduced bighorn sheep

    Science.gov (United States)

    Bleich, Vernon C.; Sargeant, Glen A.; Wiedmann, Brett P.

    2018-01-01

    Selection of bighorn sheep (Ovis canadensis) for translocation historically has been motivated by preservation of subspecific purity rather than by adaptation of source stocks to similar environments. Our objective was to estimate cause‐specific, annual, and age‐specific mortality of introduced bighorn sheep that originated at low elevations in southern British Columbia, Canada (BC ecotype), or in the Missouri River Breaks region of central Montana, USA (MT ecotype). In North Dakota, USA, mortality was similar and typically low for adult female bighorn sheep from Montana (0.09 ± 0.029 [SE]) and British Columbia (0.08 ± 0.017) during 2000–2016. Median life expectancy was 11 years for females that reached adulthood (2 yrs old); however, mortality accelerated with age and reached 86% by age 16. Mortalities resulted primarily from low rates of predation, disease, accidents, and unknown natural causes (recruitment of bighorn sheep from Montana, resulted in a greater projected rate of increase for the MT ecotype (λ = 1.21) than for the BC ecotype (1.02), and a more youthful age structure. These results support translocation of bighorn sheep from areas that are environmentally similar to areas that will be stocked. Potential benefits include more rapid population growth, greater resilience to and more rapid recovery from density‐independent losses, an increased possibility that rapidly growing populations will expand into adjacent habitat, increased hunter opportunity, increased connectivity among herds, and a more complete restoration of ecosystem processes.

  5. Distribution and diversity of Prochlorococcus ecotypes in the Red Sea.

    Science.gov (United States)

    Shibl, Ahmed A; Thompson, Luke R; Ngugi, David K; Stingl, Ulrich

    2014-07-01

    Photosynthetic prokaryotes of the genus Prochlorococcus play a major role in global primary production in the world's oligotrophic oceans. A recent study on pelagic bacterioplankton communities in the northern and central Red Sea indicated that the predominant cyanobacterial 16S rRNA gene sequence types were from Prochlorococcus cells belonging to a high-light-adapted ecotype (HL II). In this study, we analyzed microdiversity of Prochlorococcus sp. at multiple depths within and below the euphotic zone in the northern, central, and southern regions of the Red Sea, as well as in surface waters in the same locations, but in a different season. Prochlorococcus dominated the communities in clone libraries of the amplified 16S-23S rRNA internal transcribed spacer (ITS) region. Almost no differences were found between samples from coastal or open-water sites, but a high diversity of Prochlorococcus ecotypes was detected at 100-meter depth in the water column. In addition, an unusual dominance of HL II-related sequences was observed in deeper waters. Our results indicate that the Red Sea harbors diverse Prochlorococcus lineages, but no novel ecotypes, despite its unusual physicochemical properties. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  6. Distribution and diversity of Prochlorococcus ecotypes in the Red Sea

    KAUST Repository

    Shibl, Ahmed A.

    2014-06-19

    Photosynthetic prokaryotes of the genus Prochlorococcus play a major role in global primary production in the world\\'s oligotrophic oceans. A recent study on pelagic bacterioplankton communities in the northern and central Red Sea indicated that the predominant cyanobacterial 16S rRNA gene sequence types were from Prochlorococcus cells belonging to a high-light-adapted ecotype (HL II). In this study, we analyzed microdiversity of Prochlorococcus sp. at multiple depths within and below the euphotic zone in the northern, central, and southern regions of the Red Sea, as well as in surface waters in the same locations, but in a different season. Prochlorococcus dominated the communities in clone libraries of the amplified 16S-23S rRNA internal transcribed spacer (ITS) region. Almost no differences were found between samples from coastal or open-water sites, but a high diversity of Prochlorococcus ecotypes was detected at 100-meter depth in the water column. In addition, an unusual dominance of HL II-related sequences was observed in deeper waters. Our results indicate that the Red Sea harbors diverse Prochlorococcus lineages, but no novel ecotypes, despite its unusual physicochemical properties. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  7. Distribution and diversity of Prochlorococcus ecotypes in the Red Sea

    KAUST Repository

    Shibl, Ahmed A.; Thompson, Luke R.; Ngugi, David; Stingl, Ulrich

    2014-01-01

    Photosynthetic prokaryotes of the genus Prochlorococcus play a major role in global primary production in the world's oligotrophic oceans. A recent study on pelagic bacterioplankton communities in the northern and central Red Sea indicated that the predominant cyanobacterial 16S rRNA gene sequence types were from Prochlorococcus cells belonging to a high-light-adapted ecotype (HL II). In this study, we analyzed microdiversity of Prochlorococcus sp. at multiple depths within and below the euphotic zone in the northern, central, and southern regions of the Red Sea, as well as in surface waters in the same locations, but in a different season. Prochlorococcus dominated the communities in clone libraries of the amplified 16S-23S rRNA internal transcribed spacer (ITS) region. Almost no differences were found between samples from coastal or open-water sites, but a high diversity of Prochlorococcus ecotypes was detected at 100-meter depth in the water column. In addition, an unusual dominance of HL II-related sequences was observed in deeper waters. Our results indicate that the Red Sea harbors diverse Prochlorococcus lineages, but no novel ecotypes, despite its unusual physicochemical properties. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  8. Acclimation of Swedish and Italian ecotypes of Arabidopsis thaliana to light intensity.

    Science.gov (United States)

    Stewart, Jared J; Polutchko, Stephanie K; Adams, William W; Demmig-Adams, Barbara

    2017-11-01

    This study addressed whether ecotypes of Arabidopsis thaliana from Sweden and Italy exhibited differences in foliar acclimation to high versus low growth light intensity, and compared CO 2 uptake under growth conditions with light- and CO 2 -saturated intrinsic photosynthetic capacity and leaf morphological and vascular features. Differential responses between ecotypes occurred mainly at the scale of leaf architecture, with thicker leaves with higher intrinsic photosynthetic capacities and chlorophyll contents per leaf area, but no difference in photosynthetic capacity on a chlorophyll basis, in high light-grown leaves of the Swedish versus the Italian ecotype. Greater intrinsic photosynthetic capacity per leaf area in the Swedish ecotype was accompanied by a greater capacity of vascular infrastructure for sugar and water transport, but this was not associated with greater CO 2 uptake rates under growth conditions. The Swedish ecotype with its thick leaves is thus constructed for high intrinsic photosynthetic and vascular flux capacity even under growth chamber conditions that may not permit full utilization of this potential. Conversely, the Swedish ecotype was less tolerant of low growth light intensity than the Italian ecotype, with smaller rosette areas and lesser aboveground biomass accumulation in low light-grown plants. Foliar vein density and stomatal density were both enhanced by high growth light intensity with no significant difference between ecotypes, and the ratio of water to sugar conduits was also similar between the two ecotypes during light acclimation. These findings add to the understanding of the foliar vasculature's role in plant photosynthetic acclimation and adaptation.

  9. Comparison of the spaceflight transcriptome of four commonly used Arabidopsis thaliana ecotypes

    Data.gov (United States)

    National Aeronautics and Space Administration — This experiment compared the spaceflight transcriptomes of four commonly used natural variants (ecotypes) of Arabidopsis thaliana using RNAseq. In nature Arabidopsis...

  10. Application of otolith shape analysis in identifying different ecotypes of Coilia ectenes in the Yangtze Basin, China

    Digital Repository Service at National Institute of Oceanography (India)

    Radhakrishnan, K.V.; Li, Y.; Jayalakshmy, K.V.; Liu, M.; Murphy, B.R.; Xie, S.

    The variability in otolith shape of the tapertail anchovy Coilia ectenes was investigated as a tool for identifying its different ecotypes. The outlines of 350 sagittal otoliths of known ecotypes collected from seven sampling areas, covering most...

  11. Differences in thermal acclimation of chloroplast functioning in two ecotypes of Valonia utricularis (Chlorophyta)

    NARCIS (Netherlands)

    Eggert, A.; van Hasselt, P.R; Breeman, Arno

    Chloroplast functioning in two temperature ecotypes of the tropical to warm-temperate green macrophyte Valonia ultricularis was monitored by measuring chlorophyll a fluorescence parameters. One ecotype from the Mediterranean Sea is, with respect to growth and survival, more cold-adapted and

  12. Molecular Characterizations of Kenyan Brachiaria Grass Ecotypes with Microsatellite (SSR Markers

    Directory of Open Access Journals (Sweden)

    Naftali Ondabu

    2017-02-01

    Full Text Available Brachiaria grass is an emerging forage option for livestock production in Kenya. Kenya lies within the center of diversity for Brachiaria species, thus a high genetic variation in natural populations of Brachiaria is expected. Overgrazing and clearing of natural vegetation for crop production and nonagricultural uses and climate change continue to threaten the natural biodiversity. In this study, we collected 79 Brachiaria ecotypes from different parts of Kenya and examined them for genetic variations and their relatedness with 8 commercial varieties. A total of 120 different alleles were detected by 22 markers in the 79 ecotypes. Markers were highly informative in differentiating ecotypes with average diversity and polymorphic information content of 0.623 and 0.583, respectively. Five subpopulations: International Livestock Research Institute (ILRI, Kitui, Kisii, Alupe, and Kiminini differed in sample size, number of alleles, number of private alleles, diversity index, and percentage polymorphic loci. The contribution of within‐the‐individual difference to total genetic variation of Kenyan ecotype population was 81%, and the fixation index (FST = 0.021 and number of migrant per generation (Nm = 11.58 showed low genetic differentiation among the populations. The genetic distance was highest between Alupe and Kisii populations (0.510 and the lowest between ILRI and Kiminini populations (0.307. The unweighted neighborjoining (NJ tree showed test ecotypes grouped into three major clusters: ILRI ecotypes were present in all clusters; Kisii and Alupe ecotypes and improved varieties grouped in clusters I and II; and ecotypes from Kitui and Kiminini grouped in cluster I. This study confirms higher genetic diversity in Kenyan ecotypes than eight commercial varieties (Basilisk, Humidicola, Llanero, Marandú, MG4, Mulato II, Piatá and Xaraés that represent three species and one three‐way cross‐hybrid Mulato II. There is a need for further

  13. Distribution of Prochlorococcus Ecotypes in the Red Sea Basin Based on Analyses of rpoC1 Sequences

    KAUST Repository

    Shibl, Ahmed A.; Haroon, Mohamed; Ngugi, David; Thompson, Luke R.; Stingl, Ulrich

    2016-01-01

    The marine picocyanobacteria Prochlorococcus represent a significant fraction of the global pelagic bacterioplankton community. Specifically, in the surface waters of the Red Sea, they account for around 91% of the phylum Cyanobacteria. Previous work suggested a widespread presence of high-light (HL)-adapted ecotypes in the Red Sea with the occurrence of low-light (LL)-adapted ecotypes at intermediate depths in the water column. To obtain a more comprehensive dataset over a wider biogeographical scope, we used a 454-pyrosequencing approach to analyze the diversity of the Prochlorococcus rpoC1 gene from a total of 113 samples at various depths (up to 500 m) from 45 stations spanning the Red Sea basin from north to south. In addition, we analyzed 45 metagenomes from eight stations using hidden Markov models based on a set of reference Prochlorococcus genomes to (1) estimate the relative abundance of Prochlorococcus based on 16S rRNA gene sequences, and (2) identify and classify rpoC1 sequences as an assessment of the community structure of Prochlorococcus in the northern, central and southern regions of the basin without amplification bias. Analyses of metagenomic data indicated that Prochlorococcus occurs at a relative abundance of around 9% in samples from surface waters (25, 50, 75 m), 3% in intermediate waters (100 m) and around 0.5% in deep-water samples (200–500 m). Results based on rpoC1 sequences using both methods showed that HL II cells dominate surface waters and were also present in deep-water samples. Prochlorococcus communities in intermediate waters (100 m) showed a higher diversity and co-occurrence of low-light and high-light ecotypes. Prochlorococcus communities at each depth range (surface, intermediate, deep sea) did not change significantly over the sampled transects spanning most of the Saudi waters in the Red Sea. Statistical analyses of rpoC1 sequences from metagenomes indicated that the vertical distribution of Prochlorococcus in the water

  14. Distribution of Prochlorococcus Ecotypes in the Red Sea Basin Based on Analyses of rpoC1 Sequences

    KAUST Repository

    Shibl, Ahmed A.

    2016-06-25

    The marine picocyanobacteria Prochlorococcus represent a significant fraction of the global pelagic bacterioplankton community. Specifically, in the surface waters of the Red Sea, they account for around 91% of the phylum Cyanobacteria. Previous work suggested a widespread presence of high-light (HL)-adapted ecotypes in the Red Sea with the occurrence of low-light (LL)-adapted ecotypes at intermediate depths in the water column. To obtain a more comprehensive dataset over a wider biogeographical scope, we used a 454-pyrosequencing approach to analyze the diversity of the Prochlorococcus rpoC1 gene from a total of 113 samples at various depths (up to 500 m) from 45 stations spanning the Red Sea basin from north to south. In addition, we analyzed 45 metagenomes from eight stations using hidden Markov models based on a set of reference Prochlorococcus genomes to (1) estimate the relative abundance of Prochlorococcus based on 16S rRNA gene sequences, and (2) identify and classify rpoC1 sequences as an assessment of the community structure of Prochlorococcus in the northern, central and southern regions of the basin without amplification bias. Analyses of metagenomic data indicated that Prochlorococcus occurs at a relative abundance of around 9% in samples from surface waters (25, 50, 75 m), 3% in intermediate waters (100 m) and around 0.5% in deep-water samples (200–500 m). Results based on rpoC1 sequences using both methods showed that HL II cells dominate surface waters and were also present in deep-water samples. Prochlorococcus communities in intermediate waters (100 m) showed a higher diversity and co-occurrence of low-light and high-light ecotypes. Prochlorococcus communities at each depth range (surface, intermediate, deep sea) did not change significantly over the sampled transects spanning most of the Saudi waters in the Red Sea. Statistical analyses of rpoC1 sequences from metagenomes indicated that the vertical distribution of Prochlorococcus in the water

  15. Genetic Diversity Analysis of Iranian Jujube Ecotypes (Ziziphus spp. Using RAPD Molecular Marker

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    S Abbasi

    2012-12-01

    Full Text Available Jujube (Ziziphus jujuba Mill. is a valuable medicinal plant which is important in Iranian traditional medicines. Although the regional plants such as jujube play an important role in our economy, but they are forgotten in research and technology. Considering the economic and medicinal importance of jujube, the first step in breeding programs is determination of the genetic diversity among the individuals. 34 ecotypes of jujube, which have been collected from eight provinces of Iran, were used in this study. The genetic relationships of Iranian jujube ecotypes were analyzed using Random Amplified Polymorphic DNA (RAPD marker. Six out of 15 random decamer primers applied for RAPD analysis, showed an informative polymorphism. According to clustering analysis using UPGMA's methods, the ecotypes were classified into two major groups at the 0.81 level of genetic similarity. The highest value of similarity coefficient (0.92 was detected between Mazandaran and Golestan ecotypes and the most genetic diversity was observed in ecotypes of Khorasan-Jonoubi. The affinity of Khorasan-Jonoubi and Esfahan ecotypes indicated a possible common origin for the variation in these areas. Results indicated that RAPD analysis could be successfully used for the estimation of genetic diversity among Ziziphus ecotypes and it can be useful for further investigations.

  16. Reproductive, morphological, and phytochemical responses of Arabidopsis thaliana ecotypes to enhanced UV-B radiation

    Energy Technology Data Exchange (ETDEWEB)

    Trumbull, V.L.; McCloud, E.S.; Paige, K.N. (Univ. of Illinois, Urbana, IL (United States))

    1994-06-01

    Two ecotypes of Arabidopsis thaliana, collected from Libya and Norway, were grown in the greenhouse under. UV-B doses of 0 and 10.5 kJ m[sup [minus]2] UV-B[sub BE]. The high UV-B dose simulated midsummer ambient conditions over Libya and a 40% reduction in stratospheric ozone over Norway. The Libyan ectotype, which originated from latitudes where solar UV-B is high, showed no UV-B induced damage to plant growth. However the Norwegian ecotype, which originated from latitudes where solar UV-B is low, showed a significant reduction in plant height, inflorescence weight, and rosette weight in response to enhanced UV-B. Although fruit and seed number for both ecotypes were unaffected by enhanced UV-B radiation the germination success of the seeds harvested from the irradiated Norwegian plants were significantly reduced. The two ecotypes also differed with respect to their accumulation of kaempferol, a putative UV-B protective filter. The Libyan ecotype increased kaempferol concentration by 38% over the 0 kJ treatment whereas the Norwegian ecotype increased by only 15%. These data suggest that, for these ecotypes, variation in UV-B sensitivity may be explained by the differential induction of UV-absorbing leaf pigments.

  17. The eastern migratory caribou: the role of genetic introgression in ecotype evolution.

    Science.gov (United States)

    Klütsch, Cornelya F C; Manseau, Micheline; Trim, Vicki; Polfus, Jean; Wilson, Paul J

    2016-02-01

    Understanding the evolutionary history of contemporary animal groups is essential for conservation and management of endangered species like caribou (Rangifer tarandus). In central Canada, the ranges of two caribou subspecies (barren-ground/woodland caribou) and two woodland caribou ecotypes (boreal/eastern migratory) overlap. Our objectives were to reconstruct the evolutionary history of the eastern migratory ecotype and to assess the potential role of introgression in ecotype evolution. STRUCTURE analyses identified five higher order groups (i.e. three boreal caribou populations, eastern migratory ecotype and barren-ground). The evolutionary history of the eastern migratory ecotype was best explained by an early genetic introgression from barren-ground into a woodland caribou lineage during the Late Pleistocene and subsequent divergence of the eastern migratory ecotype during the Holocene. These results are consistent with the retreat of the Laurentide ice sheet and the colonization of the Hudson Bay coastal areas subsequent to the establishment of forest tundra vegetation approximately 7000 years ago. This historical reconstruction of the eastern migratory ecotype further supports its current classification as a conservation unit, specifically a Designatable Unit, under Canada's Species at Risk Act. These findings have implications for other sub-specific contact zones for caribou and other North American species in conservation unit delineation.

  18. Variable but persistent coexistence of Prochlorococcus ecotypes along temperature gradients in the ocean's surface mixed layer.

    Science.gov (United States)

    Chandler, Jeremy W; Lin, Yajuan; Gainer, P Jackson; Post, Anton F; Johnson, Zackary I; Zinser, Erik R

    2016-04-01

    The vast majority of the phytoplankton communities in surface mixed layer of the oligotrophic ocean are numerically dominated by one of two ecotypes of Prochlorococcus, eMIT9312 or eMED4. In this study, we surveyed large latitudinal transects in the Atlantic and Pacific Ocean to determine if these ecotypes discretely partition the surface mixed layer niche, or if populations exist as a continuum along key environmental gradients, particularly temperature. Transitions of dominance occurred at approximately 19-21°C, with the eMED4 ecotype dominating the colder, and eMIT9312 ecotype dominating the warmer regions. Within these zones of regional dominance, however, the minority ecotype was not competed to extinction. Rather, a robust log-linear relationship between ecotype ratio and temperature characterized this stabilized coexistence: for every 2.5°C increase in temperature, the eMIT9312:eMED4 ratio increased by an order of magnitude. This relationship was observed in both quantitative polymerase chain reaction and in pyrosequencing assays. Water column stratification also contributed to the ecotype ratio along the basin-scale transects, but to a lesser extent. Finally, instances where the ratio of the eMED4 and eMIT9312 abundances did not correlate well with temperature were identified. Such occurrences are likely due to changes in water temperatures outpacing changes in community structure. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

  19. Evaluation of Freezing Tolerance of Three Ajowan (Trachyspermum ammi (Linn. Sprague Ecotypes in Controlled Conditions

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    Z Boroumand Rezazadeh

    2013-08-01

    Full Text Available Ajowan is one of the endemic plants in Khorasan province, and there is a little information on its tolerance to cold stress. In order to study freezing tolerance of ajowan, an experiment was conducted in faculty of agriculture, Ferdowsi University of Mashhad, based on factorial-completely randomized design with three replications and three ecotypes of ajowan (Neishabour, Birjand and Torbat-e-Heidarieh were imposed on eight freezing temperatures (0 (control, -1.5, -3, -4.5, -6,-7.5, -9 and -10.5 °C. Plants were grown in natural environment till 4-5 leaf stage, then for freezing treatments transferred to thermo-gradient freezer. The cell membrane stability was evaluated by electrolyte leakage index (EL and temperature for killing 50% of samples according to the electrolyte leakage (LT50el was determined. Furthermore, survival percentage, leaf number and dry weight, temperature for killing 50% of samples according to survival (LT50su and reduced dry matter temperature 50 (RDMT50 were determined after three weeks recovery in the glasshouse. Response of ajowan ecotypes for electrolyte leakage was different and birjand ecotype had the lowest %EL, whereas the slope of %EL in mentioned ecotype was lower than two other ecotypes. However there were no significant differences among ajowan ecotypes on LT50su. Decreasing temperature to -7.5 °C reduced survival percentage of Neishabour and Torbat-e-Heidarieh ecotypes to lower than 20 percent, whiles in this temperature Birjand’s survival percentage was about 60 percent. It seems that Birjand ecotype with the lowest electrolyte leakage, the highest survival and dry matter and the lowest LT50su was more tolerant than two other ecotypes.

  20. Growth performance and stomatal behavior in relation to ecotypic adaptations in cynodon dactylon (L.) pers

    International Nuclear Information System (INIS)

    Tufail, A.; Ahmad, F.; Hameed, M.; Ahmad, R.

    2017-01-01

    Evolution has great ecological significance in terms of plant morphological and stomatal characteristics that must have been genetically fixed during the long evolutionary period. Impact of environmental conditions on growth and stomatal features of twelve ecotypes of Cynodon dactylon that were collected from ecologically different habitats in the Punjab, Pakistan were evaluated. The collected ecotypes Derawar Fort-saline desert (DF-SD), Muzaffar garh-River bank (M-RB), Khabbeki Lake-hyper saline (KL-HS), Ucchali Lake-hyper saline (UL-HS), Kalar Kahar Lake-saline (KKL-S), Treemu-saline wetland (T-SW), Sahianwala-saline wetland (S-SW), Sahianwala-hyper saline (S-HS), Pakka Anna-hyper saline (PA-HS), Pakka Anna-reclaimed field (PA-RF), Botanic Garden-non saline (BG-NS) and Gatwala-saline semiarid (G-SSA) were grown in controlled environments at University of Agriculture, Faisalabad till their acclimatization to evaluate genetically fixed characteristics. After 6-month growth in soil, the plants were transferred to half-strength Hoagland's nutrient medium. There was a huge variation in all morphological characteristics recorded during the investigation, which were due to environmental heterogeniety to which these ecotypes were originally adapted. An exclusive feature of the DF-SD ecotypes is the long and numerous roots, and tillering capacity that surpassed all other ecotypes. Leaves per plant were also exceptionally high that may improve the photosymthetic efficiency of the plant. It showed a good potential of overall growth and biomass production. The robust growth was also recorded in the KKL-S ecotypes, and this can be related to the complete dominance of these two ecotypes in their respective habitats. Small stomata were recorded in the three ecotypes (DF-SD, KL-HS and PA-HS), which are of great ecological significance. Stomatal shape, however, is different in different ecotypes, but its contribution towards stress tolerance is still to be investigated. (author)

  1. Phenotypic plasticity in response to the social environment: effects of density and sex ratio on mating behaviour following ecotype divergence.

    Directory of Open Access Journals (Sweden)

    Kristina Karlsson

    Full Text Available The ability to express phenotypically plastic responses to environmental cues might be adaptive in changing environments. We studied phenotypic plasticity in mating behaviour as a response to population density and adult sex ratio in a freshwater isopod (Asellus aquaticus. A. aquaticus has recently diverged into two distinct ecotypes, inhabiting different lake habitats (reed Phragmites australis and stonewort Chara tomentosa, respectively. In field surveys, we found that these habitats differ markedly in isopod population densities and adult sex ratios. These spatially and temporally demographic differences are likely to affect mating behaviour. We performed behavioural experiments using animals from both the ancestral ecotype ("reed" isopods and from the novel ecotype ("stonewort" isopods population. We found that neither ecotype adjusted their behaviour in response to population density. However, the reed ecotype had a higher intrinsic mating propensity across densities. In contrast to the effects of density, we found ecotype differences in plasticity in response to sex ratio. The stonewort ecotype show pronounced phenotypic plasticity in mating propensity to adult sex ratio, whereas the reed ecotype showed a more canalised behaviour with respect to this demographic factor. We suggest that the lower overall mating propensity and the phenotypic plasticity in response to sex ratio have evolved in the novel stonewort ecotype following invasion of the novel habitat. Plasticity in mating behaviour may in turn have effects on the direction and intensity of sexual selection in the stonewort habitat, which may fuel further ecotype divergence.

  2. Microsatellite based genetic diversity study in indigenous chicken ecotypes of Karnataka

    Directory of Open Access Journals (Sweden)

    B. H. Rudresh

    2015-08-01

    Full Text Available Aim: The current study was the first of its kind taken upon indigenous ecotypes of the Karnataka in order to unravel the diversity details at 20 chicken microsatellite regions. Materials and Methods: 210 indigenous chicken belonging to six districts of Bangalore and Mysore division formed the target sample for the present study. The genomic deoxyribonucleic acid was isolated by phenol chloroform isoamyl alcohol method. A panel of 20 microsatellite regions, including 14 recommended by FAO and six identified from published scientific literature became the targeted chicken genomic region. 27-33 samples were successfully genotyped in each of the six ecotypes through simplex or multiplex polymerase chain reactions, polyacrylamide gel electrophoresis and silver staining for the selected microsatellite panel. Results: The chickens of Ramanagara and Chamrajnagara were most distant with a Nei’s genetic distance value of 0.22. The chickens of Bangalore rural and Mysore were least distant with a value of 0.056. The Ramanagara and Chamrajnagara pair had Nei’s genetic identity value of 0.802, which is least among all pairs of ecotypes. There were five main nodes from which the six ecotypes evolved on the basis 20 microsatellite markers used in this study. This study indicates that the four ecotypes Ramnagara, Bangalore Rural, Chickaballapura and Mysore are genetically identical due to their common ancestral evolution while, Mandya and Chamrajnagara ecotypes formed a relatively different cluster due to a separate common ancestral chicken population and less number of generations since drifting from bifurcation node. Conclusion: Twenty microsatellite markers based genetic diversity study on six indigenous ecotypes indicated lower genetic distances as well as lower FST values compared to the distinguished breeds reported. There were two main clusters, which differentiated into six ecotypes. They may differentiate into more distinct varieties if bred in

  3. Identification and Selection for Salt Tolerance in Alfalfa (Medicago sativa L. Ecotypes via Physiological Traits

    Directory of Open Access Journals (Sweden)

    Hassan MONIRIFAR

    2009-12-01

    Full Text Available Salt stress is a serious environmental problem throughout the world which may be partially relieved by breeding cultivars that can tolerate salt stress. Plant breeding may provide a relatively cost effective short-term solution to the salinity problem by producing cultivars able to remain productive at low to moderate levels of salinity. Five alfalfa cultivars, �Seyah-Roud�, �Ahar-Hourand�, �Oskou�, �Malekan� and �Sefida-Khan� were assessed for salt tolerance at mature plant stage. A greenhouse screening system was used to evaluate individual alfalfa plants grown in perlit medium, and irrigated with water containing different amounts of NaCl. Three salt levels were achieved by adding 0, 100 and 200 mM NaCl to Hoagland nutrient solution, respectively. Forage yield, sodium and potassium contents and K/Na ratio was determined. Also, leaf samples were analyzed for proline and chlorophyll contents. The ecotypes Seyha-Roud and �Sefida-Khan� had comparatively less sodium contents than �Oskou�, �Ahar-Hourand� and �Malekan� ecotypes, also potassium content increased under saline condition. Forage yield of different alfalfa ecotypes was significantly influenced by the salinity. The ecotypes �Malekan�, Ahar- Hourand and �Oskou� were successful in maintaining forage yield under salinity stress. Sodium contents increased due to salinity in all alfalfa ecotypes however ecotypes �Ahar-Hourand� and �Malekan� maintained the highest leaf Na concentration. They showed higher content of K than other ecotypes but had lower K/Na ratio. It was concluded that, two ecotypes �Malekan� and �Ahar-Hourand� were better.

  4. A comparison of the phenolic profile and antioxidant activity of different Cichorium spinosum L. ecotypes.

    Science.gov (United States)

    Petropoulos, Spyridon A; Fernandes, Ângela; Barros, Lillian; Ferreira, Isabel Cfr

    2018-01-01

    Wild greens are considered a rich source of phenolic compounds and antioxidants and an essential part of the so-called Mediterranean diet. In the present study, Cichorium spinosum L. ecotypes, cultivated or collected in situ from wild plants from the eastern Mediterranean, were evaluated regarding their phenolic composition and antioxidant activity. Significant differences were observed among the various studied ecotypes regarding their phenolic compound content and profile, especially between wild and cultivated ecotypes, as well as the phenolic acid content between commercial products and cultivated plants. The antioxidant activity also varied among the various studied ecotypes and growing conditions, with commercial products having the highest antioxidant activity, whereas wild ecotypes showed lower antioxidant activity. Cichorium spinosum leaves are a rich source of chicoric and 5-O-caffeoylquinic acid, while significant differences in total phenolic acids, flavonoids and phenolic compound content and in antioxidant activity were observed among the studied ecotypes, as well as between the tested growing conditions. According to the results of the present study, further valorization of C. spinosum species has great potential, since it could be used as a new alternative species in the food industry. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  5. Quantification of caffeic acid content in 4 species of mullein (Verbascum sp. ecotypes from southwest Iran

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    F. Jamshidi kia

    2017-11-01

    Full Text Available Background and objectives: The Verbascum genus is the largest genus of Scrophulariaceae family which has extensive natural habitat in southwest of Iran. Phenolic acids are one of the most important chemical compounds that have different biological activities including anti-inflammatory, antibacterial, antiviral, anti-tumor and antioxidant. Therefore, this study was conducted with the aim of caffeic acid quantification of 4 species of Verbascum sp. ecotypes from southwest Iran. Methods: Nine ecotypes of the 4 species (V. macrophyllus, V. pseudo- digitalis, V. sinatum, V. songaricum were collected from the southwest of Iran. Quantification of caffeic acid contentusing reversed-phase high-performance liquid chromatography (RP-HPLC with UV PDA 2800 detector, a C18 column with dimensions of 250×4.6 mm was performed. Results: The results showed that Verbascum sp. contained caffeic acid compound and there was a difference among species and ecotypes. The results showed the highest and lowest content of caffeic acid obtained from the V. sinatum species and ecotype Sepidan (7.76 μg/mg extract and V. songaricum species and ecotype Farokhshahr (0.54 μg/mg extract, respectively. Conclusion: The results revealed a high level of variation in caffeic acid among Verbascum sp. which was affected by habitat and climatic. The pattern of habitats of suitable ecotypes superior in terms of composition to should be selected and used for breeding and cropping mullein.

  6. Assessment of total flavonoid content and antioxidant activity of Mullein (Verbascum songaricum ecotypes

    Directory of Open Access Journals (Sweden)

    2017-11-01

    Full Text Available Background and objectives: The Mullein genus is the largest genus of Scrophulariaceae family which has extensive natural habitat in southwest of Iran. Mullein contains compounds such as phenolic compounds, mucilage, saponins and anthocyanin. The aim of this study was to evaluate the total flavonoid content and antioxidant activity of mullein ecotypes in Iran. Methods: Six ecotypes of the Verbascum songaricum were evaluated. Determination of total flavonoid content was performed bythealuminium chloride colourimetric method. The antioxidant activity of the flower extracts was measured using the DPPH method. Results: The results showed that total flavonoid content and antioxidant activity were different among ecotypes.  The highest and lowest amounts of total flavonoidwas obtained  from Shermard ecotype (13.42 mg rutin /g DW and Klar ecotypes(10.10 mg rutin /g DW, respectively. The highest amounts of antioxidant activity were obtained from the Shermard ecotype (IC50 246.35 μg/mL. The correlation analysis showed that a significant relation between flavonoid, antioxidant activity and habitat elevation. Conclusion: Total flavonoid content and antioxidant activity of the samples were affected by habitat climatic.  The present data indicated that the highest antioxidant activity may be due to higher flavonoid content and the habitat elevation was effective on the flavonoid content. Due to the high amounts of flavonoid and antioxidant activity of mullein extract, it seems to be a good herbal option as an antioxidant in complementary therapies.

  7. The role of ecotypic variation and the environment on biomass and nitrogen in a dominant prairie grass.

    Science.gov (United States)

    Mendola, Meredith L; Baer, Sara G; Johnson, Loretta C; Maricle, Brian R

    2015-09-01

    Knowledge of the relative strength of evolution and the environment on a phenotype is required to predict species responses to environmental change and decide where to source plant material for ecological restoration. This information is critically needed for dominant species that largely determine the productivity of the central U.S. grassland. We established a reciprocal common garden experiment across a longitudinal gradient to test whether ecotypic variation interacts with the environment to affect growth and nitrogen (N) storage in a dominant grass. We predicted plant growth would increase from west to east, corresponding with increasing precipitation, but differentially among ecotypes due to local adaptation in all ecotypes and a greater range of growth response in ecotypes originating from west to east. We quantified aboveground biomass, root biomass, belowground net primary production (BNPP), root C:N ratio, and N storage in roots of three ecotypes of Andropogon gerardii collected from and reciprocally planted in central Kansas, eastern Kansas, and s6uthern Illinois. Only the ecotype from the most mesic region (southern Illinois) exhibited more growth from west to east. There was evidence for local adaptation in the southern Illinois ecotype by means of the local vs. foreign contrast within a site and the home vs. away contrast when growth in southern Illinois was compared to the most distant 'site in central Kansas. Root biomass of the eastern Kansas ecotype was higher at home than at either away site. The ecotype from the driest region, central Kansas, exhibited the least response across the environmental gradient, resulting in a positive relationship between the range of biomass response and precipitation in ecotype region of origin. Across all sites, ecotypes varied in root C:N ratio (highest in the driest-origin ecotype) and N storage in roots (highest in the most mesic-origin ecotype). The low and limited range of biomass, higher C:N ratio of roots

  8. Search for possible latitudinal ecotypes in Dumontia contorta (Rhodophyta)

    Science.gov (United States)

    Rietema, H.; van den Hoek, C.

    1984-09-01

    Effects of daylength and temperature on the formation of erect fronds (macrothalli) from crusts (microthalli) of Dumontia contorta (S. G. Gmel.) Rupr. from three localities in Nova Scotia and one locality in Southern Iceland were investigated and compared to such effects shown by strains from three different East Atlantic localities (Isle of Man; Zeeland, S. W. Netherlands; and Roscoff, Brittany, France). Although these strains showed small differences in their temperature-daylength responses, these could not be interpreted as latitudinal adaptations, and consequently no latitudinal ecotypes could be found for Dumontia contorta in the N. Atlantic Ocean. Upright fronds are formed at a broad temperature range of about 4°-18°C and at daylengths ≤ 13 h. Only in the southernmost part of its distribution area can high autumnal temperatures be expected to block the reappearance of upright fronds after passage of the critical daylength in September. In the larger part of the distribution area even summer temperatures are not high enough to block formation of uprights and here apparently only short daylengths initiate the reappearance of young upright fronds in autumn. The consequences of these aspects of the life history regulation for the geographic distribution are discussed.

  9. Replaying Evolution to Test the Cause of Extinction of One Ecotype in an Experimentally Evolved Population.

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    Caroline B Turner

    Full Text Available In a long-term evolution experiment with Escherichia coli, bacteria in one of twelve populations evolved the ability to consume citrate, a previously unexploited resource in a glucose-limited medium. This innovation led to the frequency-dependent coexistence of citrate-consuming (Cit+ and non-consuming (Cit- ecotypes, with Cit-bacteria persisting on the exogenously supplied glucose as well as other carbon molecules released by the Cit+ bacteria. After more than 10,000 generations of coexistence, however, the Cit-lineage went extinct; cells with the Cit-phenotype dropped to levels below detection, and the Cit-clade could not be detected by molecular assays based on its unique genotype. We hypothesized that this extinction was a deterministic outcome of evolutionary change within the population, specifically the appearance of a more-fit Cit+ ecotype that competitively excluded the Cit-ecotype. We tested this hypothesis by re-evolving the population from a frozen population sample taken within 500 generations of the extinction and from another sample taken several thousand generations earlier, in each case for 500 generations and with 20-fold replication. To our surprise, the Cit-type did not go extinct in any of these replays, and Cit-cells also persisted in a single replicate that was propagated for 2,500 generations. Even more unexpectedly, we showed that the Cit-ecotype could reinvade the Cit+ population after its extinction. Taken together, these results indicate that the extinction of the Cit-ecotype was not a deterministic outcome driven by competitive exclusion by the Cit+ ecotype. The extinction also cannot be explained by demographic stochasticity alone, as the population size of the Cit-ecotype should have been many thousands of cells even during the daily transfer events. Instead, we infer that the extinction must have been caused by a rare chance event in which some aspect of the experimental conditions was inadvertently perturbed.

  10. Evaluation of Fall Planting Dates of Cumin (Cuminum cyminum L. Ecotypes in Mashhad Conditions

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    Z Khorasani

    2012-07-01

    Full Text Available In order to study the effects of fall planting dates on yield and yield components of six cumin (Cuminum cyminum L. ecotypes an experiment was arranged in a randomized complete block design as a split-plot with three replications during 2007-08 growing season at the Agricultural Research Station of Ferdowsi University of Mashhad. Three planting dates (18 Oct. (first, 8 Nov. (second and 29 Dec. (third and six cumin ecotypes (Torbat heydarieh, Khaf, Sabzevar, Ghaen, Ghoochan and RZ19 were allocated to main and sub plots, respectively. Results showed that the effects of planting dates, ecotypes and interaction effects of planting dates and cumin ecotypes were significant for yield components (winter survival percentage, number of umbel per plant, number of seeds per umbel and 1000-seed weight and seed yield and biological yield. There was a reduction on yield components (number of umbel per plant, number of seeds per umbel and 1000-seed weight, seed yield and biological yield due to delay planting date from 18 Oct. to 29 Dec. The highest winter survival percentage was achieved on the third planting date. The highest and lowest amount for all of the traits, were achieved in Ghaen and RZ19 ecotypes, respectively. According to the useful results and for the deployment of cumin fall planting in other locations of province, continuation of this study to recommended.

  11. Effect of Irrigation Intervals on Some Morphophysiological Traits of Basil (Ocimum basilicum L. Ecotypes

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    M Goldani

    2012-10-01

    Full Text Available In order to determine the effect of different irrigation intervals on some morphophysiological traits of basil (Ocimum basilicum L., an experiment was conducted as factorial based on randomized complete block design with three replications under greenhouse conditions during 2010. Treatments included five irrigation intervals with 4, 8, 12, 16 and 20 days intervals and two ecotypes of basil (green and purple. The results showed that by increasing irrigation interval plant height, spike number, spike weight and shoot dry weight between irrigation intervals decreased. Purple basil was more tolerant than basil green ecotype to drought stress. Interaction between irrigation intervals and ecotypes showed that the best treatment related to four days irrigation interval and purple basil ecotype. The effect of irrigation intervals on root area, root diameter mean, total length, root volume and dry weight of root was significant. In all irrigation intervals, purple basil had better performance compared to green ecotype. The results showed that by increasing in irrigation interval decreased root surface area, but increased total root length. It was concluded that increasing irrigation interval up to 12 days decreased shoot and root surface areas. Increasing irrigation interval decreased chlorophyll- a, b and increased prolin amino acid content of basil leaf.

  12. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

  13. Preliminary Evaluation of Yield and Yield Components of Some Khorasanian Sesame Ecotypes (Sesamum indicum L.

    Directory of Open Access Journals (Sweden)

    A. Nezami

    2014-09-01

    Full Text Available In most region of Khorasan, sesame ecotypes have been planted for many years, but there is little information about seed yield and yield components of them. Therefore a field experimental was conducted to investigation of yield parameters of 14 sesame ecotypes (MSC1, MSC2, MSC3, MSC4, MSC5, MSC6, MSC7, MSC8, MSC9, MSC10, MSC11, MSC12, MSC13 and MSC14 in randomized complete block design with three replications at experimental station, Collage of Agriculture, Ferdowsi University of Mashhad during 2009. Results showed that there were significant difference (P

  14. Phytostabilization potential of two ecotypes of Vetiveria zizanioides in cadmium-contaminated soils: greenhouse and field experiments.

    Science.gov (United States)

    Phusantisampan, Theerawut; Meeinkuirt, Weeradej; Saengwilai, Patompong; Pichtel, John; Chaiyarat, Rattanawat

    2016-10-01

    Soil contamination by cadmium (Cd) poses a serious environmental and public health concern. Phytoremediation, i.e., the use of plants to remove contaminants from soil, has been proposed for treatment of Cd-contaminated ecosystems. In this study, we demonstrated the potential of Vetiveria zizanioides, commonly known as vetiver, to serve as an effective phytoremediation agent. Two ecotypes, i.e., India and Sri Lanka, were grown in greenhouse pots and in the field. Soils were amended with cow manure, pig manure, bat manure, and an organic fertilizer. Among all amendments, pig manure performed best in both greenhouse and field studies in terms of increasing total V. zizanioides biomass production in both ecotypes. In both greenhouse and in the field, tissue of the Sri Lanka ecotype had higher Cd concentrations than did the India ecotype. In the greenhouse, the presence of Cd did not affect total biomass production or root dry weight. The Sri Lanka ecotype had 2.7 times greater adventitious root numbers and 3.6 times greater Cd accumulation in roots than did the India ecotype. In the field study, the Sri Lanka ecotype offers potential as an excluder species, as it accumulated Cd primarily in roots, with translocation factor values 1 for all experiments except for the pig manure amendment. In addition, the highest Cd concentration in the Sri Lanka ecotype root (71.3 mg kg(-1)) was consistent with highest Cd uptake (10.4 mg plant(-1)) in the cow manure treatment. The India ecotype contained lower root Cd concentrations, and Cd accumulation was slightly higher in shoots compared to roots, with translocation factor (TF) values >1. The India ecotype was therefore not considered as an excluder in the Cd-contaminated soil. With the use of excluder species combined with application of organic amendments, soil contamination by Cd may be treated by alternative remediation methods such as phytostabilization.

  15. Screening of sesame ecotypes (Sesamum indicum L. for salinity tolerance under field conditions: 1-Phenological and morphological characteristics

    Directory of Open Access Journals (Sweden)

    F. Fazeli Kakhki

    2016-05-01

    Full Text Available Salinity is one of the most restrictions in plant growth in dry and semi dry land which effects production of many crops such as sesame. In order to study the phenology and morphology characteristics of 43 ecotypes and line of sesame (Sesamum indicum L. under salinity of irrigation water (5.2 dS.m-1 a field experiment was conducted at research farm of center of excellence for special crops, Ferdowsi University of Mashhad, Iran, during growing season of 2009-2010 based on a randomized complete block design with three replications. Results showed that four sesame ecotypes could not emerge, 14 sesame ecotypes had appropriate emergence but died before reproductive stage and only 58 % of sesame ecotypes could alive until maturity. There was significant difference between sesame ecotypes for phenological stages and were varied from 64 to 81 days for vegetative and 60 to 65 days for reproductive stages. Plant height, number and length of branches also were different between sesame ecotypes. The highest and the lowest plant height were observed in MSC43 and MSC12 ecotypes, respectively. Number of branches per plant was from 1 to 8 and length of branches in 32 percent of ecotypes was more than 100 cm. There was a considerable correlation between seed weight in plant with reproductive growth (r=0.38** and plant height (r=0.25. In addition different response of sesame ecotypes to saline water and also better morphological indices in some sesame ecotypes may be show the tolerance of these accessions to salinity. More studies may be useful for selection of sesame salt tolerance resources.

  16. Sensitivity of two ecotypes of Arabidopsis Thaliana (Cvi and Te) towards UV-B irradiation

    International Nuclear Information System (INIS)

    Velichkova, M.; Stanoeva, D.; Popova, A.

    2013-01-01

    he susceptibility of Arabidopsis thaliana towards the detrimental effect of UV-B irradiation was investigated using two ecotypes, Cvi and Te. The effect of UV-B treatment on primary photosynthetic reactions - energy interaction between the main pigment-protein complexes and oxygen evolution, was evaluated at low (4 0 C) and at room (22 0 C) temperature. UV-B-induced alterations of investigated photosynthetic reactions are better expressed at 22 0 C than at 4 0 C for Cvi. For Te ecotype the energy interaction was suppressed to higher extent at 22 0 C, while oxygen evolving activity was affected similarly at both temperatures. At low and room temperature, the energy interaction in the complex PSII-core antenna is affected stronger by UV-B treatment than the energy distribution between both photosystems, as revealed by fluorescence ratios of 77 K spectra. The results presented indicate that the Arabidopsis thaliana ecotype Cvi (Cape Verde Islands) is less affected by UV-B irradiation in respect to the investigated primary photosynthetic reactions than the ecotype Te (Finland)

  17. METABOLISM OF [14C]GA19 AND [14C]GA53 BY ECOTYPES OF ...

    African Journals Online (AJOL)

    ADMIN

    hand, metabolism of [14C]GA53 was very limited in all day-length treatments and during both, day and night periods. ... compounds which are formed by covalent coupling of GAs to .... For each ecotype day-time and night-time metabolism of ...

  18. Cross-cultural and cross-ecotype production of a killer whale `excitement' call suggests universality

    Science.gov (United States)

    Rehn, Nicola; Filatova, Olga A.; Durban, John W.; Foote, Andrew D.

    2011-01-01

    Facial and vocal expressions of emotion have been found in a number of social mammal species and are thought to have evolved to aid social communication. There has been much debate about whether such signals are culturally inherited or are truly biologically innate. Evidence for the innateness of such signals can come from cross-cultural studies. Previous studies have identified a vocalisation (the V4 or `excitement' call) associated with high arousal behaviours in a population of killer whales in British Columbia, Canada. In this study, we compared recordings from three different socially and reproductively isolated ecotypes of killer whales, including five vocal clans of one ecotype, each clan having discrete culturally transmitted vocal traditions. The V4 call was found in recordings of each ecotype and each vocal clan. Nine independent observers reproduced our classification of the V4 call from each population with high inter-observer agreement. Our results suggest the V4 call may be universal in Pacific killer whale populations and that transmission of this call is independent of cultural tradition or ecotype. We argue that such universality is more consistent with an innate vocalisation than one acquired through social learning and may be linked to its apparent function of motivational expression.

  19. Hybrid Sterility over Tens of Meters Between Ecotypes Adapted to Serpentine and Non-Serpentine Soils

    Science.gov (United States)

    Leonie Moyle; Levine Mia; Stanton Maureen; Jessica Wright

    2012-01-01

    The development of hybrid sterility is an important step in the process of speciation, however the role of adaptive evolution in triggering these postzygotic barriers is poorly understood. We show that, in the California endemic plant Collinsia sparsiflora ecotypic adaptation to two distinct soil types is associated with the expression of...

  20. Seasonal adaptations to day length in ecotypes of Diorhabda spp. (Coleoptera: Chrysomelidae) inform selection of agents against saltcedars (Tamarix spp.).

    Science.gov (United States)

    Dalin, Peter; Bean, Daniel W; Dudley, Tom L; Carney, Vanessa A; Eberts, Debra; Gardner, Kevin T; Hebertson, Elizabeth; Jones, Erin N; Kazmer, David J; Michels, G J; O'Meara, Scott A; Thompson, David C

    2010-10-01

    Seasonal adaptations to daylength often limit the effective range of insects used in biological control of weeds. The leaf beetle Diorhabda carinulata (Desbrochers) was introduced into North America from Fukang, China (latitude 44° N) to control saltcedars (Tamarix spp.), but failed to establish south of 38° N latitude because of a mismatched critical daylength response for diapause induction. The daylength response caused beetles to enter diapause too early in the season to survive the duration of winter at southern latitudes. Using climate chambers, we characterized the critical daylength response for diapause induction (CDL) in three ecotypes of Diorhabda beetles originating from 36, 38, and 43° N latitudes in Eurasia. In a field experiment, the timing of reproductive diapause and voltinism were compared among ecotypes by rearing the insects on plants in the field. CDL declined with latitude of origin among Diorhabda ecotypes. Moreover, CDL in southern (42° N latitude) ecotypes, however, CDL was relatively insensitive to temperature. The southern ecotypes produced up to four generations when reared on plants in the field at sites south of 38° N, whereas northern ecotypes produced only one or two generations. The study reveals latitudinal variation in how Diorhabda ecotypes respond to daylength for diapause induction and how these responses affect insect voltinism across the introduced range.

  1. Photosynthetic pigments and stomatal conductance in ecotypes of copoazu (Theobroma grandi orum Willd. Ex. Spreng K. Schum..

    Directory of Open Access Journals (Sweden)

    Juan Carlos Suárez-Salazar

    2016-12-01

    Full Text Available The objective of this work was to evaluate the variability of photosynthetic pigment content and daily stomatal conductance was evaluated in relation to environmental variables in Copoazú (Theobroma grandi orum ecotypes. The ecotypes used were part of the germoplasm bank of the University of the Amazon (Colombia. The study was carried out during the year 2015. Four leaves of the average stratum of four plants were collected for each ecotype, to extract and read at different levels of absorbance and determine the content of photosynthetic pigments. During the hours of 04:00 a.m. to 6:00 p.m., the stomatal conductance (gs was monitored for environmental variables (relative humidity, air temperature, radiation and vapor pressure de cit (VPD. An analysis of variance was made using the Tukey test, correlations and regressions were made between gs and environmental variables. The contents of chlorophyll a, b, total and carotenoids among ecotypes were different (P<0.0001, the ecotype UA-31 presented the highest values, contrasting with the ecotype UA-37. Concerning gs, the interaction ecotype*hour showed signi cant differences (P<0.0001 .The ecotypes that presented the highest values of gs were UA-67 and UA-039, (P<0.0001, radiation (-0.91, P<0.0001 and DPV (-0.94; P<0.0001 0.0001.The results suggest that ecotypes UA-039 and UA-31 were the most suitable in terms of gaseous exchange and content of photosynthetic pigments.

  2. Metabolism of [ 14 C]GA 19 and [ 14 C]GA 53 by ecotypes of Betula ...

    African Journals Online (AJOL)

    Continuing with this line of research, we studied the metabolism of 14C-labelled GA19 and GA53. [14C]GA19 and [14C] A53 were applied to the apices of the northern ecotype (67º N) and to the leaves of the southern ecotype (64º N) of Betula pendula Roth. under different photoperiods and at different times in order to ...

  3. Ecotypes as a concept for exploring responses to climate change in fish assemblages

    DEFF Research Database (Denmark)

    Engelhard, George H.; Ellis, Jim R.; Payne, Mark

    2011-01-01

    How do species-rich fish assemblages respond to climate change or to other anthropogenic or environmental drivers? To explore this, a categorization concept is presented whereby species are assigned with respect to six ecotype classifications, according to biogeography, horizontal and vertical...... or combinations of them. The post-1989 warm biological regime appears to have favoured pelagic species more than demersal species. These community-level patterns agree with the expected responses of ecotypes to climate change and also with anticipated vulnerability to fishing pressure....... habitat preference, trophic guild, trophic level, or body size. These classification schemes are termed ecotypology, and the system is applied to fish in the North Sea using International Bottom Trawl Survey data. Over the period 1977–2008, there were changes in the North Sea fish community that can...

  4. Adaptive Epigenetic Differentiation between Upland and Lowland Rice Ecotypes Revealed by Methylation-Sensitive Amplified Polymorphism

    OpenAIRE

    Xia, Hui; Huang, Weixia; Xiong, Jie; Tao, Tao; Zheng, Xiaoguo; Wei, Haibin; Yue, Yunxia; Chen, Liang; Luo, Lijun

    2016-01-01

    The stress-induced epimutations could be inherited over generations and play important roles in plant adaption to stressful environments. Upland rice has been domesticated in water-limited environments for thousands of years and accumulated drought-induced epimutations of DNA methylation, making it epigenetically differentiated from lowland rice. To study the epigenetic differentiation between upland and lowland rice ecotypes on their drought-resistances, the epigenetic variation was investig...

  5. Scaling-up permafrost thermal measurements in western Alaska using an ecotype approach

    Directory of Open Access Journals (Sweden)

    W. L. Cable

    2016-10-01

    Full Text Available Permafrost temperatures are increasing in Alaska due to climate change and in some cases permafrost is thawing and degrading. In areas where degradation has already occurred the effects can be dramatic, resulting in changing ecosystems, carbon release, and damage to infrastructure. However, in many areas we lack baseline data, such as subsurface temperatures, needed to assess future changes and potential risk areas. Besides climate, the physical properties of the vegetation cover and subsurface material have a major influence on the thermal state of permafrost. These properties are often directly related to the type of ecosystem overlaying permafrost. In this paper we demonstrate that classifying the landscape into general ecotypes is an effective way to scale up permafrost thermal data collected from field monitoring sites. Additionally, we find that within some ecotypes the absence of a moss layer is indicative of the absence of near-surface permafrost. As a proof of concept, we used the ground temperature data collected from the field sites to recode an ecotype land cover map into a map of mean annual ground temperature ranges at 1 m depth based on analysis and clustering of observed thermal regimes. The map should be useful for decision making with respect to land use and understanding how the landscape might change under future climate scenarios.

  6. Agronomic behaviour of some Cynodon dactylon ecotypes for turfgrass use in the Mediterranean climate

    Directory of Open Access Journals (Sweden)

    Roberto Viggiani

    2015-02-01

    Full Text Available In Italy, the expansion of turfgrasses is limited by the lack of suitable species for cultivation in the Mediterranean climate. With this view, Mi.Te.A.Med. (Turfgrass improvement in the Mediterranean climate research project was developed with the main purpose to find out and agronomically characterise native turfgrass species of Southern and Central Italy and to compare them with some commercial cultivars. During the first step of the research, 11 sites from 6 regions of Southern and Central Italy were identified. In these sites 24 ecotypes of Cynodon dactylon L. (Pers. were collected and their habitus, phenology plus some biometric parameters have been determined. During the two years of research both botanic and agronomic characterisation of the collected C. dactylon ecotypes and their comparison with 3 commercial cultivars (Panama, Transcontinental and Yukon was carried out. In the first year the colour loss interval was assessed. In the second year, colour index was measured by an electronic colorimeter, weekly growth rate was measured by a turfmeter, turf quality and ground cover percentage were assessed by visual estimate. Some native accessions showed behaviour similar to commercial cultivars while an ecotype from the Abruzzo region showed better results compared to the commercial cultivars for several quality indices.

  7. Genetic diversity among Korean bermudagrass (Cynodon spp.) ecotypes characterized by morphological, cytological and molecular approaches.

    Science.gov (United States)

    Kang, Si-Yong; Lee, Geung-Joo; Lim, Ki Byung; Lee, Hye Jung; Park, In Sook; Chung, Sung Jin; Kim, Jin-Baek; Kim, Dong Sub; Rhee, Hye Kyung

    2008-04-30

    The genus Cynodon comprises ten species. The objective of this study was to evaluate the genetic diversity of Korean bermudagrasses at the morphological, cytological and molecular levels. Morphological parameters, the nuclear DNA content and ploidy levels were observed in 43 bermudagrass ecotypes. AFLP markers were evaluated to define the genetic diversity, and chromosome counts were made to confirm the inferred cytotypes. Nuclear DNA contents were in the ranges 1.42-1.56, 1.94-2.19, 2.54, and 2.77-2.85 pg/2C for the triploid, tetraploid, pentaploid, and hexaploid accessions, respectively. The inferred cytotypes were triploid (2n = 3x = 27), tetraploid (2n = 4x = 36), pentaploid (2n = 5x = 45), and hexaploid (2n = 6x = 54), but the majority of the collections were tetraploid (81%). Mitotic chromosome counts verified the corresponding ploidy levels. The fast growing fine-textured ecotypes had lower ploidy levels, while the pentaploids and hexaploids were coarse types. The genetic similarity ranged from 0.42 to 0.94 with an average of 0.64. UPGMA cluster analysis and principle coordinate analysis separated the ecotypes into 6 distinct groups. The genetic similarity suggests natural hybridization between the different cytotypes, which could be useful resources for future breeding and genetic studies.

  8. Study on homologous series of induced early mutants in Indica rice Ⅱ. the relationship between the homologous series of early mutants induced and the ecotype in Indica rice

    International Nuclear Information System (INIS)

    Chen Xiulan; Yang Hefeng; He Zhentian; Han Yuepeng; Liu Xueyu

    2001-01-01

    The induced mutation in light sensitivity of the Indica rice leads to induction of the homologous series of early mutants along with the variation of ecological character and the ecoclimate. The induction of mutants was closely related to the ecotype of Indica rice, the homologous series of early mutants in different level were derived from the different ecotype of the Indica rice, otherwise, the similar homologous series of early mutants were derived from the same ecotypic variety. The induction of the early ecotypic variety derived from the homologous series of early mutants provides the basis and possibility for accelerating the development of the new cultivars. (authors)

  9. Effects of environmental biomass-producing factors on Cd uptake in two Swedish ecotypes of Pinus sylvestris

    Energy Technology Data Exchange (ETDEWEB)

    Ekvall, Lars; Greger, Maria

    2003-03-01

    Cadmium uptake in Scots pine seedlings was mainly regulated by biomass production. - A factorial design was used to study direct effects of external biomass-producing factors such as light, temperature and photoperiod on cadmium (Cd) uptake and indirect effects, via change in biomass production in two ecotypes of Scots pine (Pinus silvestris). The aim was to find out if the external factors affect the Cd uptake directly or via change in biomass production, and if the effect differs between ecotypes. Seedlings were grown under 10 combinations of external factors, i.e. temperature (15 and 20 deg. C), light intensity (50 and 200 {mu}mol photons m{sup -2} s{sup -1}), photoperiod (18 h light/8 h darkness and continuous light) and external Cd concentration (totally 1.88 and 7.50 {mu}mol). The treatment lasted for 18 days and Cd concentrations in roots and shoots were determined by AAS. The results showed that an increased biomass production increased the total Cd uptake but had a dilution effect on the Cd concentration, especially in the root tissues. The external factors tested did not have any direct effects on the Cd uptake, only in the case of Cd translocation to the shoot did the higher temperature show a direct increase, but only in the southern ecotype. The two ecotypes reacted differently in Cd uptake and translocation to the external factors studied. The relative Cd uptake increased with increasing photoperiod in the northern but not in the southern ecotype. The southern ecotype decreased the Cd concentration in the shoot with increased light intensity caused by a dilution effect due to extensive shoot growth of this ecotype. The conclusion is that the uptake in pine seedlings is mainly regulated via biomass production, and not directly by light and temperature and that resulting plant Cd contents to a certain extent depend on plant origin.

  10. Effects of environmental biomass-producing factors on Cd uptake in two Swedish ecotypes of Pinus sylvestris

    International Nuclear Information System (INIS)

    Ekvall, Lars; Greger, Maria

    2003-01-01

    Cadmium uptake in Scots pine seedlings was mainly regulated by biomass production. - A factorial design was used to study direct effects of external biomass-producing factors such as light, temperature and photoperiod on cadmium (Cd) uptake and indirect effects, via change in biomass production in two ecotypes of Scots pine (Pinus silvestris). The aim was to find out if the external factors affect the Cd uptake directly or via change in biomass production, and if the effect differs between ecotypes. Seedlings were grown under 10 combinations of external factors, i.e. temperature (15 and 20 deg. C), light intensity (50 and 200 μmol photons m -2 s -1 ), photoperiod (18 h light/8 h darkness and continuous light) and external Cd concentration (totally 1.88 and 7.50 μmol). The treatment lasted for 18 days and Cd concentrations in roots and shoots were determined by AAS. The results showed that an increased biomass production increased the total Cd uptake but had a dilution effect on the Cd concentration, especially in the root tissues. The external factors tested did not have any direct effects on the Cd uptake, only in the case of Cd translocation to the shoot did the higher temperature show a direct increase, but only in the southern ecotype. The two ecotypes reacted differently in Cd uptake and translocation to the external factors studied. The relative Cd uptake increased with increasing photoperiod in the northern but not in the southern ecotype. The southern ecotype decreased the Cd concentration in the shoot with increased light intensity caused by a dilution effect due to extensive shoot growth of this ecotype. The conclusion is that the uptake in pine seedlings is mainly regulated via biomass production, and not directly by light and temperature and that resulting plant Cd contents to a certain extent depend on plant origin

  11. Study of Ecotype and Sowing Date Interaction in Cumin (Cuminum cyminum L. using Different Univariate Stability Parameters

    Directory of Open Access Journals (Sweden)

    J Ghanbari

    2017-06-01

    Full Text Available Introduction Cumin is one of the most important medicinal plants in Iran and today, it is in the second level of popularity between spices in the world after black pepper. Cumin is an aromatic plant used as flavoring and seasoning agent in foods. Cumin seeds have been found to possess significant biological and have been used for treatment of toothache, dyspepsia, diarrhoea, epilepsy and jaundice. Knowledge of GEI is advantageous to have a cultivar that gives consistently high yield in a broad range of environments and to increase efficiency of breeding program and selection of best genotypes. A genotype that has stable trait expression across environments contributes little to GEI and its performance should be more predictable from the main several statistical methods have been proposed for stability analysis, with the aim of explaining the information contained in the GEI. Regression technique was proposed by Finlay and Wilkinson (1963 and was improved by Eberhart and Russell (1966. Generally, genotype stability was estimated by the slope of and deviation from the regression line for each of the genotypes. This is a popular method in stability analysis and has been applied in many crops. Non-parametric methods (rank mean (R, standard deviation rank (SDR and yield index ratio (YIR, environmental variance (S2i and genotypic variation coefficient (CVi Wricke's ecovalence and Shukla's stability variance (Shukla, 1972 have been used to determine genotype-by-environment interaction in many studies. This study was aimed to evaluate the ecotype × sowing date interaction in cumin and to evaluation of genotypic response of cumin to different sowing dates using univariate stability parameters. Materials and Methods In order to study of ecotype × sowing date interaction, different cumin ecotypes: Semnan, Fars, Yazd, Golestan, Khorasan-Razavi, Khorasan-Shomali, Khorasan-Jonoubi, Isfahan and Kerman in 5 different sowing dates (26th December, 10th January

  12. Variable response of three Trifolium repens ecotypes to soil flooding by seawater.

    Science.gov (United States)

    White, Anissia C; Colmer, Timothy D; Cawthray, Greg R; Hanley, Mick E

    2014-08-01

    Despite concerns about the impact of rising sea levels and storm surge events on coastal ecosystems, there is remarkably little information on the response of terrestrial coastal plant species to seawater inundation. The aim of this study was to elucidate responses of a glycophyte (white clover, Trifolium repens) to short-duration soil flooding by seawater and recovery following leaching of salts. Using plants cultivated from parent ecotypes collected from a natural soil salinity gradient, the impact of short-duration seawater soil flooding (8 or 24 h) on short-term changes in leaf salt ion and organic solute concentrations was examined, together with longer term impacts on plant growth (stolon elongation) and flowering. There was substantial Cl(-) and Na(+) accumulation in leaves, especially for plants subjected to 24 h soil flooding with seawater, but no consistent variation linked to parent plant provenance. Proline and sucrose concentrations also increased in plants following seawater flooding of the soil. Plant growth and flowering were reduced by longer soil immersion times (seawater flooding followed by drainage and freshwater inputs), but plants originating from more saline soil responded less negatively than those from lower salinity soil. The accumulation of proline and sucrose indicates a potential for solute accumulation as a response to the osmotic imbalance caused by salt ions, while variation in growth and flowering responses between ecotypes points to a natural adaptive capacity for tolerance of short-duration seawater soil flooding in T. repens. Consequently, it is suggested that selection for tolerant ecotypes is possible should the predicted increase in frequency of storm surge flooding events occur. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Ecotype variability in growth and secondary metabolite profile in Moringa oleifera: impact of sulfur and water availability.

    Science.gov (United States)

    Förster, Nadja; Ulrichs, Christian; Schreiner, Monika; Arndt, Nick; Schmidt, Reinhard; Mewis, Inga

    2015-03-25

    Moringa oleifera is widely cultivated in plantations in the tropics and subtropics. Previous cultivation studies with M. oleifera focused primarily only on leaf yield. In the present study, the content of potentially health-promoting secondary metabolites (glucosinolates, phenolic acids, and flavonoids) were also investigated. Six different ecotypes were grown under similar environmental conditions to identify phenotypic differences that can be traced back to the genotype. The ecotypes TOT4880 (origin USA) and TOT7267 (origin India) were identified as having the best growth performance and highest secondary metabolite production, making them an ideal health-promoting food crop. Furthermore, optimal cultivation conditions-exemplarily on sulfur fertilization and water availability-for achieving high leaf and secondary metabolite yields were investigated for M. oleifera. In general, plant biomass and height decreased under water deficiency compared to normal cultivation conditions, whereas the glucosinolate content increased. The effects depended to a great extent on the ecotype.

  14. The Effect of Plant Density on Photosynthesis and Growth Indices of Henna (Lowsonia inermis L. Ecotypes

    Directory of Open Access Journals (Sweden)

    A Pasandi Pour

    2018-05-01

    Full Text Available Introduction One of the most important factors to obtain the maximum performance or yield in every climatic condition and for each plant varieties is determining the optimum plant density. Henna (Lowsonia inermis L. is a perennial plant with high value in terms of having medicinal properties and industrial applications. The dye which is derived from green leaves of henna is used for decorating the body with intricate designs and the principle coloring matter is lawsone, 2-hydroxy-1, 4-naphthoqunone. The main purpose of this study was to evaluate the agro-physiological reaction of different henna ecotypes to different planting densities in Kerman weather conditions. Materials and Methods The study was carried out as a factorial experiment based on complete randomized block design with three replications in Shahid Bahonar University in 2015. The experiment consisted of four plant densities (25, 33, 50 and 100 plants m-2 and three ecotypes (Shahdad, Roodbar and Bam. Due to its small seeds and germination problems the planting method used was transplanting. In this study, growth indices such as leaf area index (LAI, crop growth rate (CGR, relative growth rate (RGR, leaf area ratio (LAR, specific leaf area (SLA, specific leaf weight (SLW, leaf area duration (LAD and biomass duration (BMD were calculated. The net photosynthesis, stomatal conductance and transpiration rate were measured in the middle of growing period by photosynthesis meter (CI-340 model, CID Bio- Science companies, USA. At the end, the results were analyzed using the SAS v. 9.1 and MSTATC software’s and diagrams were drawn by Excel software. Results and Discussion The results showed that the studied ecotypes were significantly different in terms of CGR, RGR and stomatal conductance. The highest average of CGR belonged to Shahdad ecotype while there was no significant difference between Roodbar and Bam ecotypes in this case. Shahdad ecotype with the RGR of 0.018 g.g.day had the

  15. Identifying the transition to the maturation zone in three ecotypes of Arabidopsis thaliana roots.

    Science.gov (United States)

    Cajero Sánchez, Wendy; García-Ponce, Berenice; Sánchez, María de la Paz; Álvarez-Buylla, Elena R; Garay-Arroyo, Adriana

    2018-01-01

    The Arabidopsis thaliana (hereafter Arabidopsis) root has become a useful model for studying how organ morphogenesis emerge from the coordination and balance of cell proliferation and differentiation, as both processes may be observed and quantified in the root at different stages of development. Hence, being able to objectively identify and delimit the different stages of root development has been very important. Up to now, three different zones along the longitudinal axis of the primary root of Arabidopsis, have been identified: the root apical meristematic zone (RAM) with two domains [the proliferative (PD) and the transition domain (TD)], the elongation zone (EZ) and the maturation zone (MZ). We previously reported a method to quantify the length of the cells of the meristematic and the elongation zone, as well as the boundaries or transitions between the root domains along the growing part of the Arabidopsis root. In this study, we provide a more accurate criterion to identify the MZ. Traditionally, the transition between the EZ to the MZ has been established by the emergence of the first root-hair bulge in the epidermis, because this emergence coincides with cell maturation in this cell type. But we have found here that after the emergence of the first root-hair bulge some cells continue to elongate and we have confirmed this in three different Arabidopsis ecotypes. We established the limit between the EZ and the MZ by looking for the closest cortical cell with a longer length than the average cell length of 10 cells after the cortical cell closest to the epidermal cell with the first root-hair bulge in these three ecotypes. In Col-0 and Ws this cell is four cells above the one with the root hair bulge and, in the Ler ecotype, this cell is five cells above. To unambiguously identifying the site at which cells stop elongating and attain their final length and fate at the MZ, we propose to calculate the length of completely elongated cortical cells counting 10

  16. Comparative Mapping of Seed Dormancy Loci Between Tropical and Temperate Ecotypes of Weedy Rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Lihua Zhang

    2017-08-01

    Full Text Available Genotypic variation at multiple loci for seed dormancy (SD contributes to plant adaptation to diverse ecosystems. Weedy rice (Oryza sativa was used as a model to address the similarity of SD genes between distinct ecotypes. A total of 12 quantitative trait loci (QTL for SD were identified in one primary and two advanced backcross (BC populations derived from a temperate ecotype of weedy rice (34.3°N Lat.. Nine (75% of the 12 loci were mapped to the same positions as those identified from a tropical ecotype of weedy rice (7.1°N Lat.. The high similarity suggested that the majority of SD genes were conserved during the ecotype differentiation. These common loci are largely those collocated/linked with the awn, hull color, pericarp color, or plant height loci. Phenotypic correlations observed in the populations support the notion that indirect selections for the wild-type morphological characteristics, together with direct selections for germination time, were major factors influencing allelic distributions of SD genes across ecotypes. Indirect selections for crop-mimic traits (e.g., plant height and flowering time could also alter allelic frequencies for some SD genes in agroecosystems. In addition, 3 of the 12 loci were collocated with segregation distortion loci, indicating that some gametophyte development genes could also influence the genetic equilibria of SD loci in hybrid populations. The SD genes with a major effect on germination across ecotypes could be used as silencing targets to develop transgene mitigation (TM strategies to reduce the risk of gene flow from genetically modified crops into weed/wild relatives.

  17. Problems with the claim of ecotype and taxon status of the wolf in the Great Lakes region

    Science.gov (United States)

    Cronin, Matthew A.; Mech, L. David

    2009-01-01

    Koblmuller et al. (2009) analysed molecular genetic data of the wolf in the Great Lakes (GL) region of the USA and concluded that the animal was a unique ecotype of grey wolf and that genetic data supported the population as a discrete wolf taxon. However, some of the literature that the researchers used to support their position actually did not, and additional confusion arises from indefinite use of terminology. Herein, we discuss the problems with designation of a wolf population as a taxon or ecotype without proper definition and assessment of criteria.

  18. Ecotype evolution in Glossina palpalis subspecies, major vectors of sleeping sickness.

    Directory of Open Access Journals (Sweden)

    Thierry De Meeûs

    2015-03-01

    Full Text Available The role of environmental factors in driving adaptive trajectories of living organisms is still being debated. This is even more important to understand when dealing with important neglected diseases and their vectors.In this paper, we analysed genetic divergence, computed from seven microsatellite loci, of 614 tsetse flies (Glossina palpalis gambiensis and Glossina palpalis palpalis, major vectors of animal and human trypanosomes from 28 sites of West and Central Africa. We found that the two subspecies are so divergent that they deserve the species status. Controlling for geographic and time distances that separate these samples, which have a significant effect, we found that G. p. gambiensis from different landscapes (Niayes of Senegal, savannah and coastal environments were significantly genetically different and thus represent different ecotypes or subspecies. We also confirm that G. p. palpalis from Ivory Coast, Cameroon and DRC are strongly divergent.These results provide an opportunity to examine whether new tsetse fly ecotypes might display different behaviour, dispersal patterns, host preferences and vectorial capacities. This work also urges a revision of taxonomic status of Glossina palpalis subspecies and highlights again how fast ecological divergence can be, especially in host-parasite-vector systems.

  19. Evaluation of the defensive behavior of two honeybee ecotypes using a laboratory test

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    Cecilia Andere

    2002-01-01

    Full Text Available Honeybee defensive behavior is a useful selection criterion, especially in areas with Africanized honeybees (Apis mellifera L. In all genetic improvement programs the selected characters must be measured with precision, and because of this we evaluated a metabolic method for testing honeybee defensive behavior in the laboratory for its usefulness in distinguishing between honeybee ecotypes and selecting honeybees based on their level of defensive responses. Ten honeybee colonies were used, five having been produced by feral queens from a subtropical region supposedly colonized by Africanized honeybees and five by queens from a temperate region apparently colonized by European honeybees. We evaluate honeybee defensive behavior using a metabolic test based on oxygen consumption after stimulation with an alarm pheromone, measuring the time to the first response, time to maximum oxygen consumption, duration of activity, oxygen consumption at first response, maximum oxygen consumption and total oxygen consumption, colonies being ranked according to the values obtained for each variable. Significant (p < 0.05 differences were detected between ecotypes for each variable but for all variables the highest rankings were obtained for colonies of subtropical origin, which had faster and more intense responses. All variables were highly associated (p < 0.05. Total oxygen consumption was the best indicator of metabolic activity for defensive behavior because it combined oxygen consumption and the length of the response. This laboratory method may be useful for evaluating the defensive behavior of honey bees in genetic programs designed to select less defensive bees.

  20. Allele-specific physical interactions regulate the heterotic traits in hybrids of Arabidopsis thaliana ecotypes

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    Babita Singh

    2017-10-01

    Full Text Available Heterosis is an important phenomenon for the breeding in agricultural crops as it influences yield related traits such as biomass yield, seed number and weight, adaptive and reproductive traits. However, the level of heterosis greatly varies for different traits and different genotypes. The present study focuses on identification of physical interactions between alleles and their role in transcriptional regulation in heterotic plants. Here, we used two Arabidopsis ecotypes; Col-0 and C24 as parent for crosses. We performed crossing between these ecotypes and screened the F1 hybrids on the basis of different SSR markers. Further, we used Hi-C to capture intra- and inter-chromosomal physical interactions between alleles on genome-wide level. Then, we identified allele-specific chromatin interactions and constructed genome-wide allele-specific contact maps at different resolutions for the entire chromosome. We also performed RNA-seq of hybrids and their parents. RNA-seq analysis identified several differentially expressed genes and non-additively expressed genes in hybrids with respect to their parents. Further, to understand the biological significance of these chromatin interactions, we annotated these interactions and correlated with the transcriptome data. Thus, our study provides alleles-specific chromatin interactions in genome-wide fashion which play a crucial role in regulation of different genes that may be important for heterosis.

  1. Establishment of an Indirect Genetic Transformation Method for Arabidopsis thaliana ecotype Bangladesh

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    Bulbul AHMED

    2011-11-01

    Full Text Available Arabidopsis thaliana is a small flowering plant belonging to the Brassicaceae family, which is adopted as a model plant for genetic research. Agrobacterium tumifaciensmediated transformation method for A. thaliana ecotype Bangladesh was established. Leaf discs of A. thaliana were incubated with A. tumefaciens strain LBA4404 containing chimeric nos. nptII. nos and intron-GUS genes. Following inoculation and co-cultivation, leaf discs were cultured on selection medium containing 50 mg/l kanamycin + 50 mg/l cefotaxime + 1.5 mg/l NAA and kanamycin resistant shoots were induced from the leaf discs after two weeks. Shoot regeneration was achieved after transferring the tissues onto fresh medium of the same combination. Finally, the shoots were rooted on MS medium containing 50 mg/l kanamycin. Incorporation and expression of the transgenes were confirmed by PCR analysis. Using this protocol, transgenic A. thaliana plants can be obtained and indicates that genomic transformation in higher plants is possible through insertion of desired gene. Although Agrobacterium mediated genetic transformation is established for A. thaliana, this study was the conducted to transform A. thaliana ecotype Bangladesh.

  2. Effect of Freezing on Spermatozoa from Tigaie Rams Belonging to the Mountain Ecotype

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    Vasile Miclea

    2011-05-01

    Full Text Available Our aim was to study the influence of freezing on the viability and frequency of abnormalities in frozen ram spermatozoa. Sperm was collected form 20 rams belonging to the mountain ecotype of the Tigaie breed using the artificial vagina technique and volume and motility were assessed. Afterward it was diluted with Tryladil (1:4 supplemented with 20% egg yolk and heated at 37°C. Subsequently the temperature decreased at a rate of 0.2°C/minute until reaching 4°C and an equilibration time of 2 hours followed. During this time the diluted sperm was packaged in 0.25 ml straws. After sealing these were kept 6 cm above liquid nitrogen level for 13 minutes (- 120°C and then plunged into nitrogen. Volume, motility and concentration were assessed before freezing. After thawing sperm morphology was assessed using Hancock’s method and at the same time the endurance (at 10, 30 and 60 minutes and HOST tests were performed. The highest motility (0.40 was graded at 30 minutes. It could be correlated with the increased percentage of HOST positive spermatozoa, 27.78%. The percentage of abnormal spermatozoa was also high (47.89%, 38.44% of them having acrosome flaws. Cryopreservation has a negative effect on the characteristics of sperm cells from Tigaie rams belonging to the mountain ecotype.

  3. Co-occurring Synechococcus ecotypes occupy four major oceanic regimes defined by temperature, macronutrients and iron.

    Science.gov (United States)

    Sohm, Jill A; Ahlgren, Nathan A; Thomson, Zachary J; Williams, Cheryl; Moffett, James W; Saito, Mak A; Webb, Eric A; Rocap, Gabrielle

    2016-02-01

    Marine picocyanobacteria, comprised of the genera Synechococcus and Prochlorococcus, are the most abundant and widespread primary producers in the ocean. More than 20 genetically distinct clades of marine Synechococcus have been identified, but their physiology and biogeography are not as thoroughly characterized as those of Prochlorococcus. Using clade-specific qPCR primers, we measured the abundance of 10 Synechococcus clades at 92 locations in surface waters of the Atlantic and Pacific Oceans. We found that Synechococcus partition the ocean into four distinct regimes distinguished by temperature, macronutrients and iron availability. Clades I and IV were prevalent in colder, mesotrophic waters; clades II, III and X dominated in the warm, oligotrophic open ocean; clades CRD1 and CRD2 were restricted to sites with low iron availability; and clades XV and XVI were only found in transitional waters at the edges of the other biomes. Overall, clade II was the most ubiquitous clade investigated and was the dominant clade in the largest biome, the oligotrophic open ocean. Co-occurring clades that occupy the same regime belong to distinct evolutionary lineages within Synechococcus, indicating that multiple ecotypes have evolved independently to occupy similar niches and represent examples of parallel evolution. We speculate that parallel evolution of ecotypes may be a common feature of diverse marine microbial communities that contributes to functional redundancy and the potential for resiliency.

  4. In vitro regeneration of Amazonian pineapple (Ananas comosus plants ecotype Gobernadora

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    Héctor Alexander Blanco Flores

    2017-01-01

    Full Text Available There are a number of pineapple (Ananas comosus cultivars and ecotypes of local commercial importance in Venezuela, among them the Amazonian ones, cultivated mainly by the aboriginal Piaroa, are of relevance. They sow the propagules, which restricts the availability of material for large-scale cultivation. This limitation was approached by plant tissue culture for in vitro propagation of Amazonian pineapple plants, Gobernadora ecotype, through somatic embryogenesis (ES and adventitious organogenesis (OA. Basal and intermediate sections of leaves were tested. Only the leaf base sections (FBS were morphogenically induced. The highest number of vitroplants (1.58 plants / explant was obtained from the embryogenic callus induced in MS medium with Picloram 10 mg.L-1 + Thidiazuron 2 mg.L-1, transferred to MS medium without hormones. In the organogenic process, the highest number of plants/explants (5 was obtained directly in MS with naphthaleneacetic acid 5 mg.L-1 + benzylaminopurine 0.25 mg.L-1, transferred to MS. The latter being the best in vitro culture system due to its productivity and for being a method that minimizes somaclonal variation.

  5. Lack of Ecotypic Differentiation: Plant Response to Elevation, Population Origin, and Wind in the Luquillo Mountains, Puerto Rico

    Science.gov (United States)

    Ned Fetcher; Roberto A. Cordero; Janice Voltzow

    2000-01-01

    How important is ecotypic differentiation along elevational gradients in the tropics? Reciprocal transplants of two shrubs, Clibadium erosum (Asteraceae) and Psychotria berteriana (Rubiaceae), and a palm, Prestoea acuminata var. montana (Palmaceae), were used to test for the effect of environment and population origin on growth and physiology in the Luquillo...

  6. Kompetisi Antara Ekotipe Echinochloa Crus-galli Pada Beberapa Tingkat Populasi Dengan Padi Sawah (Competition of Echinochloa Crus-galli Ecotypes at Several Populations Against Lowland Rice)

    OpenAIRE

    Guntoro, Dwi; Chozin, Muhamad Achmad; Santosa, Edi; Tjitrosemito, Soekisman; Burhan, Abdul Harris

    2009-01-01

    Echinochloa crus-galli is a major weed in paddy field that reduces rice yield. The objective of the research was to study the effect of E. crus-galli ecotypes and populations on rice growth and production. The research was conducted in a green house using split plot design with three replications. The main plot consisted of three E. crus-galli ecotypes i.e ecotype from Karawang, Cikampek, and Sukabumi. E. crus-galli population as sub plot consisted of 0, 1, 2, 3, and 4 E. crus-galli per po...

  7. Association between minor loading vein architecture and light- and CO2-saturated rates of photosynthetic oxygen evolution among Arabidopsis thaliana ecotypes from different latitudes

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    Christopher M Cohu

    2013-07-01

    Full Text Available Through microscopic analysis of veins and assessment of light- and CO2-saturated rates of photosynthetic oxygen evolution, we investigated the relationship between minor loading vein anatomy and photosynthesis of mature leaves in three ecotypes of Arabidopsis thaliana grown under four different combinations of temperature and photon flux density (PFD. All three ecotypes exhibited greater numbers and cross-sectional area of phloem cells as well as higher photosynthesis rates in response to higher PFD and especially lower temperature. The Swedish ecotype exhibited the strongest response to these conditions, the Italian ecotype the weakest response, and the Col-0 ecotype exhibited an intermediate response. Among all three ecotypes, strong linear relationships were found between light- and CO2-saturated rates of photosynthetic oxygen evolution and the number and area of either sieve elements or of companion and phloem parenchyma cells in foliar minor loading veins, with the Swedish ecotype showing the highest number of cells in minor loading veins (and largest minor veins coupled with unprecedented high rates of photosynthesis. Linear, albeit less significant, relationships were also observed between number and cross-sectional area of tracheids per minor loading vein versus light- and CO2-saturated rates of photosynthetic oxygen evolution. We suggest that sugar distribution infrastructure in the phloem is co-regulated with other features that set the upper limit for photosynthesis. The apparent genetic differences among Arabidopsis ecotypes should allow for future identification of the gene(s involved in augmenting sugar-loading and -transporting phloem cells and maximal rates of photosynthesis.

  8. Effects of Irrigation Levels on Growth Characteristics and Yield of Four Ecotypes of Sesame (Sesamum indicum L.

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    A Koocheki

    2015-09-01

    Full Text Available In order to study the effects of irrigation levels on growth criteria, yield components and seed yield of four ecotypes of sesame (Sesamum indicum L., a field experiment was conducted as factorial based on a randomized complete block design with three replications at the Agricultural Research Station, Ferdowsi University of Mashhad, during growing season 2010-2011. Three irrigation levels (2000, 3000 and 4000 m3 ha-1 and four ecotypes (Darab, Sabzevar, Kashmar and Kalat were allocated as treatments. Criteria such as leaf are index (LAI, dry matter (DM accumulation, yield components (branch number, capsule number, seed number and 1000-seed weight, biological yield and seed yield of sesame were measured, accordingly. Results indicated that the simple effects of irrigation levels and ecotypes were significant (p≤0.05 on yield and yield components of sesame. Interaction between irrigation levels and ecotypes for yield components, biological yield and seed yield were significant (p≤0.01. By increasing water level from 2000 to 4000 m3 ha-1 enhanced branch number, capsule number, seed number and 1000-seed weight up to 57, 55 and 36%, respectively. Seed yield of Kalat was higher than Darab, Sabzevar and Kashmar with 1, 7 and 11%, respectively. By enhancing irrigation from 2000 to 4000 m3.ha-1 seed yield of Darab, Sabzevar and Kashmar and Kalat increased with 15, 67T 62 and 34%, respectively. There was a positive and significant relationship between yield and yield components. The highest correlation coefficient was observed for 1000-seed weight (r=0.87**.

  9. A Proteome Translocation Response to Complex Desert Stress Environments in Perennial Phragmites Sympatric Ecotypes with Contrasting Water Availability.

    Science.gov (United States)

    Li, Li; Chen, Xiaodan; Shi, Lu; Wang, Chuanjing; Fu, Bing; Qiu, Tianhang; Cui, Suxia

    2017-01-01

    After a long-term adaptation to desert environment, the perennial aquatic plant Phragmites communis has evolved a desert-dune ecotype. The desert-dune ecotype (DR) of Phragmites communis showed significant differences in water activity and protein distribution compared to its sympatric swamp ecotype (SR). Many proteins that were located in the soluble fraction of SR translocated to the insoluble fraction of DR, suggesting that membrane-associated proteins were greatly reinforced in DR. The unknown phenomenon in plant stress physiology was defined as a proteome translocation response. Quantitative 2D-DIGE technology highlighted these 'bound' proteins in DR. Fifty-eight kinds of proteins were identified as candidates of the translocated proteome in Phragmites . The majority were chloroplast proteins. Unexpectedly, Rubisco was the most abundant protein sequestered by DR. Rubisco activase, various chaperons and 2-cysteine peroxiredoxin were major components in the translocation response. Conformational change was assumed to be the main reason for the Rubisco translocation due to no primary sequence difference between DR and SR. The addition of reductant in extraction process partially reversed the translocation response, implying that intracellular redox status plays a role in the translocation response of the proteome. The finding emphasizes the realistic significance of the membrane-association of biomolecule for plant long-term adaptation to complex stress conditions.

  10. 'Fagiolo a Formella', an Italian lima bean ecotype: biochemical and nutritional characterisation of dry and processed seeds.

    Science.gov (United States)

    Piergiovanni, Angela R; Sparvoli, Francesca; Zaccardelli, Massimo

    2012-08-30

    An ecotype of the lima bean, named 'fagiolo a Formella', which, to the best of our knowledge, is the only example of an Italian lima bean (Phaseolus lunatus L.) ecotype, is cultivated in the Campania region of southern Italy. Physical, nutritional and processing traits of dry seeds were evaluated for two consecutive growing seasons (2009 and 2010). The canning quality was also investigated, but only for the harvest of 2010. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis of total seed proteins allowed the attribution of 'fagiolo a Formella' to the Mesoamerican gene pool and Sieva morphotype. Seeds have a trapezoid shape, white coat and 100-seed weight greater than 42 g. Yield, protein, trypsin inhibitor and phytic acid values were found comparable with those reported for lima bean varieties cultivated in sub-tropical areas. Moreover, we found that this ecotype is devoid of lectin. The good adaptation to growing environment is indicated by the fact that 'fagiolo a Formella' seed quality is comparable to that of lima beans grown in America. Overall the canning quality was found satisfactory and canning significantly destroys the main anti-nutritional compounds present in dry seeds. Copyright © 2012 Society of Chemical Industry.

  11. Effects of cadmium on ultrastructure and antioxidative defense system in hyperaccumulator and non-hyperaccumulator ecotypes of Sedum alfredii Hance

    International Nuclear Information System (INIS)

    Jin Xiaofen; Yang Xiaoe; Islam, Ejazul; Liu Dan; Mahmood, Qaisar

    2008-01-01

    Plant growth, ultrastructural and antioxidant adaptations and glutathione biosynthesis in Cd-hyperaccumulating ecotype Sedum alfredii Hance (HE) countering high Cd environment were investigated and compared with its non Cd-hyperaccumulating ecotype (NHE). Cadmium exposure resulted in significant ultrastructural changes in root meristem and leaf mesophyll cells of S. alfredii, but damage was more pronounced in NHE even when Cd concentrations were one-tenth of those applied to HE. Cadmium stress damaged chloroplasts causing imbalanced lamellae formation coupled with early leaf senescence. Histochemical results revealed that glutathione (GSH) biosynthesis inhibition led to overproduction of hydrogen peroxide (H 2 O 2 ) and superoxide radical (O 2 · - ) in HE but not in NHE. Differences were noted in both HE and NHE for catalase (CAT), guaiacol peroxidase (GPX), ascorbate peroxidase (APX) and glutathione reductase (GR) activities under various Cd stress levels. No relationship was found between antioxidative defense capacity including activities of superoxide dismutase (SOD), CAT, GPX, APX and GR as well as ascorbic acid (AsA) contents and Cd tolerance in the two ecotypes of S. alfredii. The GSH biosynthesis induction in root and shoot exposed to elevated Cd conditions may be involved in Cd tolerance and hyperaccumulation in HE of S. alfredii H

  12. Switchgrass Cultivar/Ecotype Selection and Management for Biofuels in the Upper Southeast USA

    Science.gov (United States)

    Parrish, David J.; Wolf, Dale D.

    2014-01-01

    Switchgrass (Panicum virgatum L.), a perennial warm-season grass indigenous to the eastern USA, has potential as a biofuels feedstock. The objective of this study was to investigate the performance of upland and lowland switchgrass cultivars under different environments and management treatments. Four cultivars of switchgrass were evaluated from 2000 to 2001 under two management regimes in plots established in 1992 at eight locations in the upper southeastern USA. Two management treatments included 1) a single annual harvest (in late October to early November) and a single application of 50 kg N/ha/yr and 2) two annual harvests (in midsummer and November) and a split application of 100 kg N/ha/yr. Biomass yields averaged 15 Mg/ha/yr and ranged from 10 to 22 Mg/ha/yr across cultivars, managements, locations, and years. There was no yield advantage in taking two harvests of the lowland cultivars (Alamo and Kanlow). When harvested twice, upland cultivars (Cave-in-Rock and Shelter) provided yields equivalent to the lowland ecotypes. Tiller density was 36% lower in stands cutting only once per year, but the stands appeared vigorous after nine years of such management. Lowland cultivars and a one-cutting management (after the tops have senesced) using low rates of applied N (50 kg/ha) are recommended. PMID:25105170

  13. Identification of ecotype-specific marker genes for categorization of beer-spoiling Lactobacillus brevis.

    Science.gov (United States)

    Behr, Jürgen; Geissler, Andreas J; Preissler, Patrick; Ehrenreich, Armin; Angelov, Angel; Vogel, Rudi F

    2015-10-01

    The tolerance to hop compounds, which is mainly associated with inhibition of bacterial growth in beer, is a multi-factorial trait. Any approaches to predict the physiological differences between beer-spoiling and non-spoiling strains on the basis of a single marker gene are limited. We identified ecotype-specific genes related to the ability to grow in Pilsner beer via comparative genome sequencing. The genome sequences of four different strains of Lactobacillus brevis were compared, including newly established genomes of two highly hop tolerant beer isolates, one strain isolated from faeces and one published genome of a silage isolate. Gene fragments exclusively occurring in beer-spoiling strains as well as sequences only occurring in non-spoiling strains were identified. Comparative genomic arrays were established and hybridized with a set of L. brevis strains, which are characterized by their ability to spoil beer. As result, a set of 33 and 4 oligonucleotide probes could be established specifically detecting beer-spoilers and non-spoilers, respectively. The detection of more than one of these marker sequences according to a genetic barcode enables scoring of L. brevis for their beer-spoiling potential and can thus assist in risk evaluation in brewing industry. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Induction of cell death by graphene in Arabidopsis thaliana (Columbia ecotype) T87 cell suspensions

    International Nuclear Information System (INIS)

    Begum, Parvin; Fugetsu, Bunshi

    2013-01-01

    Highlights: • This study was set up to explore potential influence of graphene on T87 cells. • Fragmented nuclei, membrane damage, mitochondrial dysfunction were observed. • ROS increased, ROS are key mediators in the cell death signaling pathway. • Translocation of graphene into cells and an endocytosis-like structure was observed. • Graphene entering into the cells by endocytosis. -- Abstract: The toxicity of graphene on suspensions of Arabidopsis thaliana (Columbia ecotype) T87 cells was investigated by examining the morphology, mitochondrial dysfunction, reactive oxygen species generation (ROS), and translocation of graphene as the toxicological endpoints. The cells were grown in Jouanneau and Péaud-Lenoel (JPL) media and exposed to graphene at concentrations 0–80 mg/L. Morphological changes were observed by scanning electron microscope and the adverse effects such as fragmented nuclei, membrane damage, mitochondrial dysfunction was observed with fluorescence microscopy by staining with Hoechst 33342/propidium iodide and succinate dehydrogenase (mitochondrial bioenergetic enzyme). Analysis of intracellular ROS by 2′,7′-dichlorofluorescein diacetate demonstrated that graphene induced a 3.3-fold increase in ROS, suggesting that ROS are key mediators in the cell death signaling pathway. Transmission electron microscopy verified the translocation of graphene into cells and an endocytosis-like structure was observed which suggested graphene entering into the cells by endocytosis. In conclusion, our results show that graphene induced cell death in T87 cells through mitochondrial damage mediated by ROS

  15. Resistance of a Local Ecotype of Castanea sativa to Dryocosmus kuriphilus (Hymenoptera: Cynipidae in Southern Italy

    Directory of Open Access Journals (Sweden)

    Francesco Nugnes

    2018-02-01

    Full Text Available The cynipid Dryocosmus kuriphilus is the most impactful invasive pest of Castanea sativa copse woods and orchards currently reported from many European countries. A low impact solution for the containment of this pest could be the use of resistant trees. We examined the resistance of the red salernitan ecotype (RSE of C. sativa to D. kuriphilus and carried out a morphological characterization of this ecotype’s plants and fruits. From November 2015 to May 2017 we observed and recorded the percentage of infested buds, healthy leaves and shoots on about 50 chestnut trees, together with the number, size, and position of galls, and the number of eggs laid by the gall wasps into the buds and the number of larvae inside the galls. We showed a progressive mortality of cynipid larvae up to the starting point of galls development when almost total larval mortality was recorded. This suggests that RSE trees have a moderate resistance to D. kuriphilus; however, resistance acts at different levels, resulting in fewer eggs being deposited, a low number of larvae reaching the complete development, and a low number of galls on the branches. Moreover, the galls on resistant trees are smaller than the susceptible ones, so the larvae are more exposed to parasitization.

  16. Identifying Differences in Abiotic Stress Gene Networks between Lowland and Upland Ecotypes of Switchgrass (DE-SC0008338)

    Energy Technology Data Exchange (ETDEWEB)

    Childs, Kevin [Michigan State Univ., East Lansing, MI (United States); Buell, Robin [Michigan State Univ., East Lansing, MI (United States); Zhao, Bingyu [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Zhang, Xunzhong [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2016-11-10

    Switchgrass (Panicum virgatum) is a warm-season C4 grass that is a target lignocellulosic biofuel species for use in the United States due to its local adaption capabilities and high biomass accumulation. Two ecotypes of switchgrass have been described. Members of the lowland ecotype are taller, have narrower leaf blades and generate more biomass compared to individuals from the upland ecotype. Additionally, lowland plants are generally found in the southern United States while upland switchgrass is more typically present in the northern United States. These differences are important as it is envisioned that switchgrass for biofuel production will typically be grown on marginal lands in the northern United States to supplement and diversify farmers' traditional crop incomes. While lowland switchgrass is more productive, it has poor winter survivability in northern latitudes where upland switchgrass is expected to be grown for biofuel use. Abiotic stresses likely to be encountered by switchgrass include drought and salinity. Despite initially being described as preferring wetter environments, members of the lowland ecotype have been characterized as being more drought tolerant than plants of the upland ecotype. Nonetheless, direct trials have indicated that variation for drought tolerance exists in both ecotypes, but prior to this project, only a relatively small number of switchgrass lines had been tested for drought responses. Similarly, switchgrass cultivars have not been widely tested for salt tolerance, but a few studies have shown that even mild salt stress can inhibit growth. The effects of drought and salt stress on plant growth are complex. Both drought and salinity affect the osmotic potential of plant cells and negatively affect plant growth due to reduced water potential and reduced photosynthesis that results from lower stomatal conductance of CO2. Plants respond to drought and salt stress by activating genes that directly attempt to

  17. Adaptive Epigenetic Differentiation between Upland and Lowland Rice Ecotypes Revealed by Methylation-Sensitive Amplified Polymorphism.

    Directory of Open Access Journals (Sweden)

    Hui Xia

    Full Text Available The stress-induced epimutations could be inherited over generations and play important roles in plant adaption to stressful environments. Upland rice has been domesticated in water-limited environments for thousands of years and accumulated drought-induced epimutations of DNA methylation, making it epigenetically differentiated from lowland rice. To study the epigenetic differentiation between upland and lowland rice ecotypes on their drought-resistances, the epigenetic variation was investigated in 180 rice landraces under both normal and osmotic conditions via methylation-sensitive amplified polymorphism (MSAP technique. Great alterations (52.9~54.3% of total individual-locus combinations of DNA methylation are recorded when rice encountering the osmotic stress. Although the general level of epigenetic differentiation was very low, considerable level of ΦST (0.134~0.187 was detected on the highly divergent epiloci (HDE. The HDE detected in normal condition tended to stay at low levels in upland rice, particularly the ones de-methylated in responses to osmotic stress. Three out of four selected HDE genes differentially expressed between upland and lowland rice under normal or stressed conditions. Moreover, once a gene at HDE was up-/down-regulated in responses to the osmotic stress, its expression under the normal condition was higher/lower in upland rice. This result suggested expressions of genes at the HDE in upland rice might be more adaptive to the osmotic stress. The epigenetic divergence and its influence on the gene expression should contribute to the higher drought-resistance in upland rice as it is domesticated in the water-limited environment.

  18. Adaptive Epigenetic Differentiation between Upland and Lowland Rice Ecotypes Revealed by Methylation-Sensitive Amplified Polymorphism.

    Science.gov (United States)

    Xia, Hui; Huang, Weixia; Xiong, Jie; Tao, Tao; Zheng, Xiaoguo; Wei, Haibin; Yue, Yunxia; Chen, Liang; Luo, Lijun

    2016-01-01

    The stress-induced epimutations could be inherited over generations and play important roles in plant adaption to stressful environments. Upland rice has been domesticated in water-limited environments for thousands of years and accumulated drought-induced epimutations of DNA methylation, making it epigenetically differentiated from lowland rice. To study the epigenetic differentiation between upland and lowland rice ecotypes on their drought-resistances, the epigenetic variation was investigated in 180 rice landraces under both normal and osmotic conditions via methylation-sensitive amplified polymorphism (MSAP) technique. Great alterations (52.9~54.3% of total individual-locus combinations) of DNA methylation are recorded when rice encountering the osmotic stress. Although the general level of epigenetic differentiation was very low, considerable level of ΦST (0.134~0.187) was detected on the highly divergent epiloci (HDE). The HDE detected in normal condition tended to stay at low levels in upland rice, particularly the ones de-methylated in responses to osmotic stress. Three out of four selected HDE genes differentially expressed between upland and lowland rice under normal or stressed conditions. Moreover, once a gene at HDE was up-/down-regulated in responses to the osmotic stress, its expression under the normal condition was higher/lower in upland rice. This result suggested expressions of genes at the HDE in upland rice might be more adaptive to the osmotic stress. The epigenetic divergence and its influence on the gene expression should contribute to the higher drought-resistance in upland rice as it is domesticated in the water-limited environment.

  19. Backcasting the decline of a vulnerable Great Plains reproductive ecotype: identifying threats and conservation priorities

    Science.gov (United States)

    Worthington, Thomas A.; Brewer, Shannon K.; Grabowski, Timothy B.; Mueller, Julia

    2014-01-01

    Conservation efforts for threatened or endangered species are challenging because the multi-scale factors that relate to their decline or inhibit their recovery are often unknown. To further exacerbate matters, the perceptions associated with the mechanisms of species decline are often viewed myopically rather than across the entire species range. We used over 80 years of fish presence data collected from the Great Plains and associated ecoregions of the United States, to investigate the relative influence of changing environmental factors on the historic and current truncated distributions of the Arkansas River shiner Notropis girardi. Arkansas River shiner represent a threatened reproductive ecotype considered especially well adapted to the harsh environmental extremes of the Great Plains. Historic (n = 163 records) and current (n = 47 records) species distribution models were constructed using a vector-based approach in MaxEnt by splitting the available data at a time when Arkansas River shiner dramatically declined. Discharge and stream order were significant predictors in both models; however, the shape of the relationship between the predictors and species presence varied between time periods. Drift distance (river fragment length available for ichthyoplankton downstream drift before meeting a barrier) was a more important predictor in the current model and indicated river segments 375–780 km had the highest probability of species presence. Performance for the historic and current models was high (area under the curve; AUC > 0.95); however, forecasting and backcasting to alternative time periods suggested less predictive power. Our results identify fragments that could be considered refuges for endemic plains fish species and we highlight significant environmental factors (e.g., discharge) that could be manipulated to aid recovery.

  20. Genetic and Developmental Basis for Increased Leaf Thickness in the Arabidopsis Cvi Ecotype

    Directory of Open Access Journals (Sweden)

    Viktoriya Coneva

    2018-03-01

    Full Text Available Leaf thickness is a quantitative trait that is associated with the ability of plants to occupy dry, high irradiance environments. Despite its importance, leaf thickness has been difficult to measure reproducibly, which has impeded progress in understanding its genetic basis, and the associated anatomical mechanisms that pattern it. Here, we used a custom-built dual confocal profilometer device to measure leaf thickness in the Arabidopsis Ler × Cvi recombinant inbred line population and found statistical support for four quantitative trait loci (QTL associated with this trait. We used publically available data for a suite of traits relating to flowering time and growth responses to light quality and show that three of the four leaf thickness QTL coincide with QTL for at least one of these traits. Using time course photography, we quantified the relative growth rate and the pace of rosette leaf initiation in the Ler and Cvi ecotypes. We found that Cvi rosettes grow slower than Ler, both in terms of the rate of leaf initiation and the overall rate of biomass accumulation. Collectively, these data suggest that leaf thickness is tightly linked with physiological status and may present a tradeoff between the ability to withstand stress and rapid vegetative growth. To understand the anatomical basis of leaf thickness, we compared cross-sections of Cvi and Ler leaves and show that Cvi palisade mesophyll cells elongate anisotropically contributing to leaf thickness. Flow cytometry of whole leaves show that endopolyploidy accompanies thicker leaves in Cvi. Overall, our data suggest that mechanistically, an altered schedule of cellular events affecting endopolyploidy and increasing palisade mesophyll cell length contribute to increase of leaf thickness in Cvi. Ultimately, knowledge of the genetic basis and developmental trajectory leaf thickness will inform the mechanisms by which natural selection acts to produce variation in this adaptive trait.

  1. Effect of Drought Stress on Growth and Morphological Characteristics of Two Garlic (Allium sativum L. Ecotypes in Different Planting Densities

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    shiva akbari

    2017-10-01

    Full Text Available Introduction Plants may be exposed to various stresses and water deficit is the most important limiting factor of growth and yield in many parts of the world and Iran. Stress induced growth decrement can be because of cell development decrease due to decrement of turgor pressure and meiosis and photosynthesis decrease due to stomata closure. Determination of desired planting density is one of the success factors of plant growth and production. Garlic (Allium sativum has been an important medicinal plant over centuries in human life. According to the importance of medicinal plants and studying the effects of drought stress on them, the goal of this research is to investigate the effect of drought stress and planting density on growth and morphological characteristics of two ecotypes of garlic and determining the preferable ecotype and density from the perspective of these traits. Materials and methods This experiment was performed in 2012 in a farm in south east of Semnan. It was conducted on a split-plot factorial arrangement based on randomized complete blocks design with three replications. Three levels of drought stress with 60, 80 and 100 percent of crop evapotranspiration (ETc were the main plot factors and factorial combination of three planting density (30, 40 and 50 plants.m-2 and two ecotypes of Tabas and Toroud were the levels of sub plot factors. To estimate water requirement of garlic, daily measured meteorology parameters of Semnan synoptic station were used and water requirement was calculated based on FAO-56 instructions. From mid-January, the sampling of leaf area, bulb and leaf fresh and dry weight was started with destructive method every other week and continued until middle of Jun. three plant were selected randomly from each plot in each turn. From middle of May, height and number of leaves were measured. Leaf area measurement was done by leaf area meter (Delta-T. To estimate growth indices, dry weight of aerial and

  2. Description of some characteristics of flowers and seeds of Arabidopsis thaliana - ecotype landsberg erecta and mutant NW4

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    Leszek Trząski

    2014-01-01

    Full Text Available Flowers and seeds of Landsberg erecta (Ler ecotype and NW4 mutant were studied by light microscopy and scanning electron microscopy to reveal characteristic features of their structure. The NW4 mutant flowers differ from Ler mainly in presence of two bract-like sepals with complicated vasculature and a variable number of secondary flowers. In the two outer whorls of NW4 flower, variable number of transformed stamen-, petal-, sepal- and style-like elements also occur. The NW4 mutant seeds are characterized by the absence of mucilage around the surface and a deviating seed coat morphology.

  3. Which plant trait explains the variations in relative growth rate and its response to elevated carbon dioxide concentration among Arabidopsis thaliana ecotypes derived from a variety of habitats?

    Science.gov (United States)

    Oguchi, Riichi; Ozaki, Hiroshi; Hanada, Kousuke; Hikosaka, Kouki

    2016-03-01

    Elevated atmospheric carbon dioxide (CO2) concentration ([CO2]) enhances plant growth, but this enhancement varies considerably. It is still uncertain which plant traits are quantitatively related to the variation in plant growth. To identify the traits responsible, we developed a growth analysis model that included primary parameters associated with morphology, nitrogen (N) use, and leaf and root activities. We analysed the vegetative growth of 44 ecotypes of Arabidopsis thaliana L. grown at ambient and elevated [CO2] (800 μmol mol(-1)). The 44 ecotypes were selected such that they were derived from various altitudes and latitudes. Relative growth rate (RGR; growth rate per unit plant mass) and its response to [CO2] varied by 1.5- and 1.7-fold among ecotypes, respectively. The variation in RGR at both [CO2]s was mainly explained by the variation in leaf N productivity (LNP; growth rate per leaf N),which was strongly related to photosynthetic N use efficiency (PNUE). The variation in the response of RGR to [CO2] was also explained by the variation in the response of LNP to [CO2]. Genomic analyses indicated that there was no phylogenetic constraint on inter-ecotype variation in the CO2 response of RGR or LNP. We conclude that the significant variation in plant growth and its response to [CO2] among ecotypes reflects the variation in N use for photosynthesis among ecotypes, and that the response of PNUE to CO2 is an important target for predicting and/or breeding plants that have high growth rates at elevated [CO2].

  4. Evaluation of Effect of Chemical and Organic Fertilizers on Growth Characteristics, Yield and Yield components of three Sesame Ecotypes (Sesamum indicum L.

    Directory of Open Access Journals (Sweden)

    M Goldani

    2014-07-01

    Full Text Available Using organic fertilizers is cause increase soil fertility, improving crop growth and production. For this purpose a greenhouse experiment was carried out in factorial arrangement based on a completely randomized design with three replications during 2011 year. First factor included: three sesame ecotype (MSC3, MSC6, MSC7 and second factor was 6 fertilizer treatments that included: Incorporation manure and chemical fertilizer (216 g manure and 1 gram chemical fertilizer NPK, Chemical fertilizer (2 g NPK, Vermicompost (192 g, Manure ( 228 g, Compost Sulfur granules (192 g per vase and Control (without any manure or fertilizer. Results indicated that different manure treatments had significant effect on morphological and yield components traits, as the most number and length branch per plant was obtained from incorporation manure and chemical fertilizer treatment. Appling incorporation manure and chemical fertilizer treatment had the most biomass in MSC3 ecotype that in comparison of control treatment was increased almost 73 percent. Consuming incorporation manure and chemical fertilizer treatment in MSC3 ecotype was also obtained the most capsule per plant (21.2, number seed per capsule (54.4, 100-seed weight (0.257 g and seed per plant with (1.95 g. The least seed weight per plant with 0.450 g was observed in MSC7 ecotype from application of control treatment. Response of three sesame ecotype (MSC3, MSC6, MSC7 to applied vermin-compost manure was similar; as the amount of seed weight per plant was increased more than 1 g per plant in all these ecotypes and in others fertilizer treatments was not observed this trend. There was significant positive correlation between seed weight per plant and number of capsule per plant (r=0.83**, height (r=0.68** and biomass (r=0.51**. The results showed that incorporation manure and chemical fertilizer was improved on growth and yield characteristics of sesame plant.

  5. Morphological and physiological divergences within Quercus ilex support the existence of different ecotypes depending on climatic dryness.

    Science.gov (United States)

    Peguero-Pina, José Javier; Sancho-Knapik, Domingo; Barrón, Eduardo; Camarero, Julio Jesús; Vilagrosa, Alberto; Gil-Pelegrín, Eustaquio

    2014-08-01

    Several studies show apparently contradictory findings about the functional convergence within the Mediterranean woody flora. In this context, this study evaluates the variability of functional traits within holm oak (Quercus ilex) to elucidate whether provenances corresponding to different morphotypes represent different ecotypes locally adapted to the prevaling stress levels. Several morphological and physiological traits were measured at leaf and shoot levels in 9-year-old seedlings of seven Q. ilex provenances including all recognized morphotypes. Plants were grown in a common garden for 9 years under the same environmental conditions to avoid possible biases due to site-specific characteristics. Leaf morphometry clearly separates holm oak provenances into 'ilex' (more elongated leaves with low vein density) and 'rotundifolia' (short and rounded leaves with high vein density) morphotypes. Moreover, these morphotypes represent two consistent and very contrasting functional types in response to dry climates, mainly in terms of leaf area, major vein density, leaf specific conductivity, resistance to drought-induced cavitation and turgor loss point. The 'ilex' and 'rotundifolia' morphotypes correspond to different ecotypes as inferred from their contrasting functional traits. To the best of our knowledge, this is the first time that the combined use of morphological and physiological traits has provided support for the concept of these two holm oak morphotypes being regarded as two different species. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Corticosterone and pace of life in two life-history ecotypes of the garter snake Thamnophis elegans.

    Science.gov (United States)

    Palacios, Maria G; Sparkman, Amanda M; Bronikowski, Anne M

    2012-02-01

    Glucocorticoids are main candidates for mediating life-history trade-offs by regulating the balance between current reproduction and survival. It has been proposed that slow-living organisms should show higher stress-induced glucocorticoid levels that favor self-maintenance rather than current reproduction when compared to fast-living organisms. We tested this hypothesis in replicate populations of two ecotypes of the garter snake (Thamnophis elegans) that exhibit slow and fast pace of life strategies. We subjected free-ranging snakes to a capture-restraint protocol and compared the stress-induced corticosterone levels between slow- and fast-living snakes. We also used a five-year dataset to assess whether baseline corticosterone levels followed the same pattern as stress-induced levels in relation to pace of life. In accordance with the hypothesis, slow-living snakes showed higher stress-induced corticosterone levels than fast-living snakes. Baseline corticosterone levels showed a similar pattern with ecotype, although differences depended on the year of study. Overall, however, levels of glucocorticoids are higher in slow-living than fast-living snakes, which should favor self-maintenance and survival at the expense of current reproduction. The results of the present study are the first to relate glucocorticoid levels and pace of life in a reptilian system and contribute to our understanding of the physiological mechanisms involved in life-history evolution. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. The Amazonian Floodplains, an ecotype with challenging questions on volatile organic compound (VOC) emissions

    Science.gov (United States)

    Kesselmeier, J.

    2012-12-01

    based on short-term experiments is risky being transferred to an ecotype which is governed under natural conditions by long term flooding. Furthermore, contrasting such experiments with usually young trees (saplings or a few years old) nothing is known about the emission behavior of adult trees under field conditions.

  8. Factors influencing elk recruitment across ecotypes in the Western United States

    Science.gov (United States)

    Lukacs, Paul M.; Mitchell, Michael S.; Hebblewhite, Mark; Johnson, Bruce K.; Johnson, Heather; Kauffman, Matthew J.; Proffitt, Kelly M.; Zager, Peter; Brodie, Jedediah; Hersey, Kent R.; Holland, A. Andrew; Hurley, Mark; McCorquodale, Scott; Middleton, Arthur; Nordhagen, Matthew; Nowak, J. Joshua; Walsh, Daniel P.; White, P.J.

    2018-01-01

    Ungulates are key components in ecosystems and economically important for sport and subsistence harvest. Yet the relative importance of the effects of weather conditions, forage productivity, and carnivores on ungulates are not well understood. We examined changes in elk (Cervus canadensis) recruitment (indexed as age ratios) across 7 states and 3 ecotypes in the northwestern United States during 1989–2010, while considering the effects of predator richness, forage productivity, and precipitation. We found a broad‐scale, long‐term decrease in elk recruitment of 0.48 juveniles/100 adult females/year. Weather conditions (indexed as summer and winter precipitation) showed small, but measurable, influences on recruitment. Forage productivity on summer and winter ranges (indexed by normalized difference vegetation index [NDVI] metrics) had the strongest effect on elk recruitment relative to other factors. Relationships between forage productivity and recruitment varied seasonally and regionally. The productivity of winter habitat was more important in southern parts of the study area, whereas annual variation in productivity of summer habitat had more influence on recruitment in northern areas. Elk recruitment varied by up to 15 juveniles/100 adult females across the range of variation in forage productivity. Areas with more species of large carnivores had relatively low elk recruitment, presumably because of increased predation. Wolves (Canis lupus) were associated with a decrease of 5 juveniles/100 adult females, whereas grizzly bears (Ursus arctos) were associated with an additional decrease of 7 juveniles/100 adult females. Carnivore species can have a critical influence on ungulate recruitment because their influence rivals large ranges of variation in environmental conditions. A more pressing concern, however, stems from persistent broad‐scale decreases in recruitment across the distribution of elk in the northwestern United States, irrespective of

  9. Evaluation of Genetic Diversity in Collection from Iranian Jujube Ecotypes (Ziziphus spp. using ISSR-molecular Marker

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    hajar shayesteh

    2018-02-01

    Full Text Available Introduction Jujube (Zizyphus jujuba Mill. as a valuable medicinal plant and adapted to different climatic conditions is widespread in many parts of Iran. Nowadays, beside the export of its fruit, jujube is also used as an herbal medicine to treat the diseases, so it has a high economic value. Study on genetic diversity is the first step to identify and preservation of germplasm. It is also considered as the basic principles of plant breeding. DNA markers seem to be the best way in determination of the genetic diversity. Inter simple sequence repeats (ISSR markers are highly polymorphic and combine most benefits of Simple Sequence Repeats (SSRs and amplified fragment length polymorphism (AFLP to the generality of random amplified polymorphic DNA (RAPD. Materials and Methods In order to study of the genetic diversity among 31 ecotypes collected from eight Jujube-rich provinces, including South Khorasan, Razavi Khorasan, Mazandaran, Golestan, Qom, Isfahan, Lorestan and Fars. Genomic DNA was extracted by CTAB method and polymerase chain reaction (PCR was performed with 13 ISSR primers in which six most efficient primers were selected. Cluster analysis based on Dice similarity coefficient and Unweighed Pair Group Method with Arithmetic Mean (UPGMA was carried out and POPGENe.3.2 software was used to determine the similarity of populations with each other. Results and Discussion 84 loci were amplified and 70 of them (83% revealed a proper polymorphism with the size between 200 and 2000 base pair. The average number of amplified and polymorphic bands per primer was 14 and 11.6 respectively. Primers with di-nucleotide repeats produced more polymorphic bands than ones with tri-nucleotide repeats. It seems that this is due to a higher frequency of sequences containing di-nucleotide repeats in intergenic regions and higher possibility of mutation revealed in more diversity in comparison to gene coding regions. Anchored primers with 1 or 2 nucleotides at

  10. Diverse, rare microbial taxa responded to the Deepwater Horizon deep-sea hydrocarbon plume.

    Science.gov (United States)

    Kleindienst, Sara; Grim, Sharon; Sogin, Mitchell; Bracco, Annalisa; Crespo-Medina, Melitza; Joye, Samantha B

    2016-02-01

    The Deepwater Horizon (DWH) oil well blowout generated an enormous plume of dispersed hydrocarbons that substantially altered the Gulf of Mexico's deep-sea microbial community. A significant enrichment of distinct microbial populations was observed, yet, little is known about the abundance and richness of specific microbial ecotypes involved in gas, oil and dispersant biodegradation in the wake of oil spills. Here, we document a previously unrecognized diversity of closely related taxa affiliating with Cycloclasticus, Colwellia and Oceanospirillaceae and describe their spatio-temporal distribution in the Gulf's deepwater, in close proximity to the discharge site and at increasing distance from it, before, during and after the discharge. A highly sensitive, computational method (oligotyping) applied to a data set generated from 454-tag pyrosequencing of bacterial 16S ribosomal RNA gene V4-V6 regions, enabled the detection of population dynamics at the sub-operational taxonomic unit level (0.2% sequence similarity). The biogeochemical signature of the deep-sea samples was assessed via total cell counts, concentrations of short-chain alkanes (C1-C5), nutrients, (colored) dissolved organic and inorganic carbon, as well as methane oxidation rates. Statistical analysis elucidated environmental factors that shaped ecologically relevant dynamics of oligotypes, which likely represent distinct ecotypes. Major hydrocarbon degraders, adapted to the slow-diffusive natural hydrocarbon seepage in the Gulf of Mexico, appeared unable to cope with the conditions encountered during the DWH spill or were outcompeted. In contrast, diverse, rare taxa increased rapidly in abundance, underscoring the importance of specialized sub-populations and potential ecotypes during massive deep-sea oil discharges and perhaps other large-scale perturbations.

  11. 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

  12. Impact of nitrogen source and supply level on growth, yield and nutritional value of two contrasting ecotypes of Cichorium spinosum L. grown hydroponically.

    Science.gov (United States)

    Chatzigianni, Martina; Alkhaled, Bara'a; Livieratos, Ioannis; Stamatakis, Aristidis; Ntatsi, Georgia; Savvas, Dimitrios

    2018-03-01

    In the present study, two contrasting stamnagathi (Cichorium spinosum L.) ecotypes originating either from a mountainous or from a seaside habitat were grown hydroponically and supplied with a nutrient solution differing in the total-N level (4 or 16 mmol L -1 ) and the N source (NH 4 + -N/total-N: 0.05, 0.25 or 0.50). The aim was to search for genotypic differences in nitrogen nutrition. At commercial maturity, the dry weight of mountainous plants was higher than that of seaside plants. The shoot mineral concentrations were higher in seaside plants than in mountainous plants in both harvests. The leaf nitrate concentration was influenced by the levels of both total-N and NH 4 + -N/total-N at both harvests, whereas plants with a seaside origin exhibited higher nitrate concentrations than those originating from a mountainous site in all total-N and NH 4 + -N/total-N treatments. The two stamnagathi ecotypes differed considerably in their responses to nitrogen nutrition and tissue nitrate content. The mountainous ecotype was superior in terms of growth, tissue nitrate concentration and antioxidant capacity, whereas the seaside ecotype accumulated more nutrient microcations in leaves. A low total-N concentration (up to 4 mmol L -1 ) combined with a high NH 4 + -N/total-N ratio (up to 0.05) could minimize tissue NO 3 - concentrations without compromising yield. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  13. 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...

  14. The Effect of Drought Stress and Plant Density on Biochemical and Physiological Characteristics of Two Garlic (Allium sativum L. Ecotypes

    Directory of Open Access Journals (Sweden)

    Sh Akbari

    2017-03-01

    Full Text Available Introduction Drought stress is the most important growth limiting factor for crop production. Sugar accumulation under drought stress strengthens and stabilizes cell membranes and maintains the water absorption and turgid property. Under stress conditions, proline will also maintain the turgor pressure and decreased the damages caused to plant membrane. Although proline concentrations may have undesirable effects on plant growth, because of deflecting photosynthetic resources to the processes that are not involved in plant growth. Chloroplasts and its pigments are also affected by drought stress. Density is one of the factors that has a significant impact on plant growth. Garlic is one of the edible plants which has generated considerable interest throughout human history because of its pharmaceutical properties. This study aimed to determine the effects of drought stress and plant density on some biochemical and physiological treats of two garlic ecotypes and determining the more resistant ecotype. Materials and Methods The study was carried out in 2011-2012 in a farm land at the south east of Semnan city. The experimental layout was a split-plot factorial with a randomized complete block design in three replications. The treatments were comprised of three factors: irrigation regimes (60%, 80% and 100% of estimated crop evapotranspiration (ETC that were assigned as the main plot and the factorial combination of 3 levels of planting density (30, 40 and 50 plants. m-2 and two ecotypes (Tabas and Toroud made up the sub-plots. The water requirement was calculated based on FAO-56 crop water requirements instruction. FAO-56 Penman-Monteith equation was used to calculate evapotranspiration. To calculate the content of soluble sugar, proline and leaves pigment, the samples were collected in a random way from the youngest fully expended leaves one month before the final harvest. Relative water content was estimated by measuring dry weight, fresh weight

  15. Characterization of biochemical traits of dog rose (Rosa canina L.) ecotypes in the central part of Iran.

    Science.gov (United States)

    Javanmard, Milad; Asadi-Gharneh, Hossein Ali; Nikneshan, Pejman

    2018-07-01

    Dog rose (Rosa canina L.) is a wild native species in Iran, with a significant genetic diversity. This plant serves as a rich source of vitamin C, anthocyanins, phenolic contents and carotenoids. Rose hips have been used in several food products, as well as perfumery and cosmetics industries. In this research, we investigate biochemical characteristics of five dog rose ecotypes (Kopehjamshid, Zarneh, Miyankish, Aghcheh and Sadeghiyeh), that were collected from the central part of Iran (Isfahan province). Amounts of vitamin C, total carotenoids, total phenolic contents, total anthocyanins, macro and micro minerals were measured. Seed oil are extracted by soxhlet method and analysed by gas chromatography. The macro and micro minerals levels in the fruit vary significantly among these regions. The results of this study demonstrate that dog rose have great diversity and can be used in breeding programmes in order to increase nutrient values as a food resource additive.

  16. Different NaCl-Induced Calcium Signatures in the Arabidopsis thaliana Ecotypes Col-0 and C24

    KAUST Repository

    Schmö ckel, Sandra M.; Garcia, Alexandre F.; Berger, Bettina; Tester, Mark A.; Webb, Alex A. R.; Roy, Stuart J.

    2015-01-01

    A common feature of stress signalling pathways are alterations in the concentration of cytosolic free calcium ([Ca2+]cyt), which allow the specific and rapid transmission of stress signals through a plant after exposure to a stress, such as salinity. Here, we used an aequorin based bioluminescence assay to compare the NaCl-induced changes in [Ca2+]cyt of the Arabidopsis ecotypes Col-0 and C24. We show that C24 lacks the NaCl specific component of the [Ca2+]cyt signature compared to Col-0. This phenotypic variation could be exploited as a screening methodology for the identification of yet unknown components in the early stages of the salt signalling pathway.

  17. Different NaCl-Induced Calcium Signatures in the Arabidopsis thaliana Ecotypes Col-0 and C24

    KAUST Repository

    Schmöckel, Sandra M.

    2015-02-27

    A common feature of stress signalling pathways are alterations in the concentration of cytosolic free calcium ([Ca2+]cyt), which allow the specific and rapid transmission of stress signals through a plant after exposure to a stress, such as salinity. Here, we used an aequorin based bioluminescence assay to compare the NaCl-induced changes in [Ca2+]cyt of the Arabidopsis ecotypes Col-0 and C24. We show that C24 lacks the NaCl specific component of the [Ca2+]cyt signature compared to Col-0. This phenotypic variation could be exploited as a screening methodology for the identification of yet unknown components in the early stages of the salt signalling pathway.

  18. A compatible interaction of Alternaria brassicicola with Arabidopsis thaliana ecotype DiG: evidence for a specific transcriptional signature

    Directory of Open Access Journals (Sweden)

    Gepstein Shimon

    2009-03-01

    Full Text Available Abstract Background The interaction of Arabidopsis with Alternaria brassicicola provides a model for disease caused by necrotrophs, but a drawback has been the lack of a compatible pathosystem. Infection of most ecotypes, including the widely-studied line Col-0, with this pathogen generally leads to a lesion that does not expand beyond the inoculated area. This study examines an ecotype, Dijon G (DiG, which is considered sensitive to A. brassicicola. Results We show that the interaction has the characteristics of a compatible one, with expanding rather than limited lesions. To ask whether DiG is merely more sensitive to the pathogen or, rather, interacts in distinct manner, we identified genes whose regulation differs between Col-0 and DiG challenged with A. brassicicola. Suppression subtractive hybridization was used to identify differentially expressed genes, and their expression was verified using semi-quantitative PCR. We also tested a set of known defense-related genes for differential regulation in the two plant-pathogen interactions. Several known pathogenesis-related (PR genes are up-regulated in both interactions. PR1, and a monooxygenase gene identified in this study, MO1, are preferentially up-regulated in the compatible interaction. In contrast, GLIP1, which encodes a secreted lipase, and DIOX1, a pathogen-response related dioxygenase, are preferentially up-regulated in the incompatible interaction. Conclusion The results show that DiG is not only more susceptible, but demonstrate that its interaction with A. brassicicola has a specific transcriptional signature.

  19. Tissue-Specific Accumulation of Sulfur Compounds and Saponins in Different Parts of Garlic Cloves from Purple and White Ecotypes.

    Science.gov (United States)

    Diretto, Gianfranco; Rubio-Moraga, Angela; Argandoña, Javier; Castillo, Purificación; Gómez-Gómez, Lourdes; Ahrazem, Oussama

    2017-08-20

    This study set out to determine the distribution of sulfur compounds and saponin metabolites in different parts of garlic cloves. Three fractions from purple and white garlic ecotypes were obtained: the tunic (SS), internal (IS) and external (ES) parts of the clove. Liquid Chromatography coupled to High Resolution Mass spectrometry (LC-HRMS), together with bioinformatics including Principal Component Analysis (PCA), Hierarchical Clustering (HCL) and correlation network analyses were carried out. Results showed that the distribution of these metabolites in the different parts of garlic bulbs was different for the purple and the white ecotypes, with the main difference being a slightly higher number of sulfur compounds in purple garlic. The SS fraction in purple garlic had a higher content of sulfur metabolites, while the ES in white garlic was more enriched by these compounds. The correlation network indicated that diallyl disulfide was the most relevant metabolite with regards to sulfur compound metabolism in garlic. The total number of saponins was almost 40-fold higher in purple garlic than in the white variety, with ES having the highest content. Interestingly, five saponins including desgalactotigonin-rhamnose, proto-desgalactotigonin, proto-desgalactotigonin-rhamnose, voghieroside D1, sativoside B1-rhamnose and sativoside R1 were exclusive to the purple variety. Data obtained from saponin analyses revealed a very different network between white and purple garlic, thus suggesting a very robust and tight coregulation of saponin metabolism in garlic. Findings in this study point to the possibility of using tunics from purple garlic in the food and medical industries, since it contains many functional compounds which can be exploited as ingredients.

  20. Effect of Irrigation CutOff on Flowering Stage and Foliar Application of Spermidine on Some Quantitative and Qualitative Characteristics of Various Ecotypes of Cumin

    Directory of Open Access Journals (Sweden)

    Sarah Bakhtari

    2017-02-01

    Full Text Available Introduction: Medicinal plants play major roles in human health. . Cumin (Cuminum cyminum L. is an annual plant that commonly cultivated in arid and semiarid regions of Iran. The crop has a wide range of uses including medicinal, cosmetic and food industry. Cumin occupies about 26% of the total area devoted to medicinal plants in Iran. However, cumin is seriously affected by the Fusarium wilt and blight diseases. The diseases usually increase under warm and wet conditions. It was demonstrated that the peak of the disease incidence is occurring at the flowering stage and irrigation cutoff at this time may be reduced the diseases density. Materials and methods: In order to evaluate the effects of irrigation cutoff in flowering stage and foliar application of spermidine on some characteristics of various ecotype of cumin, an experiment was conducted in a split-split-plot arrangement in randomized complete block design with three replications at the research farm of Shahid Bahonar University of Kerman at 2014. The experimental treatments were irrigation in two levels (complete irrigation and cutoff the irrigation in flowering stage assigned to main plots, foliar application of spermidine in three levels (0, 1 and 2 Mm as a subplot and cumin ecotypes in three levels (Kerman, Khorasan and Esfahan that was randomized in sub-subplot. Plots size under the trial was 4 m × 3 m so as to get 50 cm inter row spacing in six rows. The ideal density of the crops was considered as 120 plant m-2. As soon as the seeds were sown, irrigation was applied every 10 days. Foliar application of spermidine was done at three stages (after thinning, before flowering stage and in the middle of flowering stage. No herbicides and chemical fertilizers were applied during the expriments. Results and discussion: In this study the number of branches, umbels per plant, 1000-seed weight, seed yield per plant and hectare, harvest index, essential oil percentage and yield, infected

  1. Comparison of synthetic chelators and low molecular weight organic acids in enhancing phytoextraction of heavy metals by two ecotypes of Sedum alfredii Hance.

    Science.gov (United States)

    Liu, Dan; Islam, Ejazul; Li, Tingqiang; Yang, Xiaoe; Jin, Xiaofen; Mahmood, Qaisar

    2008-05-01

    Lab scale and pot experiments were conducted to compare the effects of synthetic chelators and low molecular weight organic acids (LMWOA) on the phytoextraction of multi-contaminated soils by two ecotypes of Sedum alfredii Hance. Through lab scale experiments, the treatment dosage of 5 and 10 mM for synthetic chelators and LMWOA, respectively, and the treatment time of 10 days were selected for pot experiment. In pot experiment, the hyperaccumulating ecotype (HE) was found more tolerant to the metal toxicity compared with the non-hyperaccumulating ecotype (NHE). EDTA for Pb, EDDS for Cu, and DTPA for Cu and Cd were found more effective to enhance heavy metal accumulation in the shoots of S. alfredii Hance. Compared with synthetic chelators, the phytoextraction ability of LMWOA was lesser. Considering the strong post-harvest effects of synthetic chelators, it is suggested that higher dosage of LMWOA could be practiced during phytoextraction, and some additional measures could also be taken to lower the potential environmental risks of synthetic chelators in the future studies.

  2. RAPD-PCR and real-time PCR HRM based genetic variation evaluations of Urtica dioica parts, ecotypes and evaluations of morphotypes in Turkey.

    Science.gov (United States)

    Uzonur, Irem; Akdeniz, Gamze; Katmer, Zeynep; Ersoy, Seyda Karaman

    2013-01-01

    Urtica dioica is an ethnobotanically and medicinally important Complementary and Alternative Medicine (CAM) plant worldwide and in Turkey; 90 % of herbal CAM applications depend on it in Turkey. It has a wide range of habitats in nearly all continents. It is found in all three phytogeographical regions in Turkey (Euro-Siberian, Irano-Turanian, Mediterranean) with high adaptivity to heterogeneous geographies such as climate, soil types and altitudes. This fact in relation to the assessment of chemical constituents of the plant and combining with further genetic and morphological variation data can assist and enhance the works for the utility and reliability of CAM applications in effect and activity of this plant species. In this work we have made some preliminary experiments with novel approaches to reveal the ecotypes and genetic variation of mighty ecotypes of Urtica dioica from different phytogeographical regions of Turkey (Euro-Siberian and Mediterranean). The ecotypes have heterogeneity in both its parts (leaf, stem, root) as revealed by Random Amplified Polymorphic DNA-Polymerase Chain Reaction (RAPD-PCR) using random primers and High-resolution Melt (HRM) analysis using Urtica dioica specific primers and universal chloroplast DNA (cpDNA) primers and morphological traits such as phenolic contents and antioxidant capacities of plants' leaf infusions as used in medicinal applications in Turkey. This work will contribute a lot for the development of molecular markers to detect the genetic variation and heterogeneity of Urtica dioica to further relate with expected phenotypes that are most useful and relevant in CAM applications.

  3. Seed longevity of red rice ecotypes buried in soil Longevidade de sementes de arroz-vermelho enterradas no solo

    Directory of Open Access Journals (Sweden)

    J.A. Noldin

    2006-12-01

    Full Text Available Red rice is a troublesome weed in irrigated rice production and is spread through contaminated commercial rice seed and machinery. Seed dormancy is a major trait for red rice. Studies were carried out at two locations to determine red rice seed longevity in the soil of several ecotypes from four US states. Five months after burial near Beaumont, Texas only three ecotypes had viable seed (O arroz-vermelho constitui-se na principal planta daninha infestante de lavouras de arroz irrigado e a sua disseminação ocorre, principalmente, pelo uso de sementes comerciais contaminadas e equipamentos agrícolas. A ocorrência de dormência nas sementes é uma das principais características que dificultam o controle do arroz-vermelho em lavouras. O objetivo deste trabalho foi estimar a longevidade no solo de ecótipos de arroz-vermelho provenientes de diferentes áreas de produção de arroz nos Estados Unidos. O estudo foi conduzido em dois locais: Beaumont e College Station, no estado do Texas (TX. Para sementes enterradas a 5 cm de profundidade em Beaumont, apenas três ecótipos apresentaram sementes viáveis (<1%. No entanto, quando as sementes foram enterradas em maior profundidade (25 cm, nove ecótipos tinham sementes viáveis após 2 anos. Trinta e seis meses após o enterrio, cinco ecótipos apresentavam sementes com alguma viabilidade, mas todos inferiores a 1%. Sementes de arroz-vermelho produzidas e enterradas em College Station na profundidade de 12 cm, um dia após a colheita, apresentaram maior longevidade que aquelas mantidas na superfície do solo. Após 17 meses, um dos ecótipos de arroz-preto (TX 4, enterrado a 12 cm, foi o que apresentou maior percentual de viabilidade (2%. Nos dois experimentos, observou-se que os cultivares comerciais, Lemont e Mars, não apresentaram sementes viáveis após cinco meses, independentemente da localização no solo. Os resultados deste estudo sugerem que em áreas com arroz-vermelho deve-se evitar o

  4. 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....

  5. 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

  6. Non-destructive flavour evaluation of red onion (Allium cepa L.) ecotypes: an electronic-nose-based approach.

    Science.gov (United States)

    Russo, Mariateresa; di Sanzo, Rosa; Cefaly, Vittoria; Carabetta, Sonia; Serra, Demetrio; Fuda, Salvatore

    2013-11-15

    This work reports preliminary results on the potential of a metal oxide sensor (MOS)-based electronic nose, as a non-destructive method to discriminate three "Tropea Red Onion" PGI ecotypes (TrT, TrMC and TrA) from each other and the common red onion (RO), which is usually used to counterfeit. The signals from the sensor array were processed using a canonical discriminant function analysis (DFA) pattern recognition technique. The DFA on onion samples showed a clear separation among the four onion groups with an overall correct classification rate (CR) of 97.5%. Onion flavour is closely linked to pungency and thus to the pyruvic acid content. The e-nose analysis results are in good agreement with pyruvic acid analysis. This work demonstrated that artificial olfactory systems have potential for use as an innovative, rapid and specific non-destructive technique, and may provide a method to protect food products against counterfeiting. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Otolith morphology and hearing abilities in cave- and surface-dwelling ecotypes of the Atlantic molly, Poecilia mexicana (Teleostei: Poeciliidae)

    Science.gov (United States)

    Schulz-Mirbach, Tanja; Ladich, Friedrich; Riesch, Rüdiger; Plath, Martin

    2010-01-01

    Cave fish have rarely been investigated with regard to their inner ear morphology, hearing abilities, and acoustic communication. Based on a previous study that revealed morphological differences in the saccular otolith between a cave and two surface populations of Poecilia mexicana, we checked for additional differences in utricular and lagenar otoliths and tested whether different populations have similar hearing sensitivities. We found pronounced differences in the shape of all three otoliths. Otoliths of the saccule and lagena from cave fish differed from those of surface fish in the features of the face oriented towards the sensory epithelium. In addition, otoliths of the utricle and lagena were significantly heavier in cave fish. Auditory sensitivities were measured between 100 and 1500 Hz, utilizing the auditory evoked potential recording technique. We found similar hearing abilities in cave and surface fish, with greatest sensitivity between 200 and 300 Hz. An acoustic survey revealed that neither ecotype produced species-specific sounds. Our data indicate that cave dwelling altered the otolith morphology in Atlantic mollies, probably due to metabolic differences. Different otolith morphology, however, did not affect general auditory sensitivity or acoustic behavior. PMID:20430090

  8. 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.

  9. Cold-acclimation limits low temperature induced photoinhibition by promoting a higher photochemical quantum yield and a more effective PSII restoration in darkness in the Antarctic rather than the Andean ecotype of Colobanthus quitensis Kunt Bartl (Cariophyllaceae

    Directory of Open Access Journals (Sweden)

    Bascuñán-Godoy Luisa

    2012-07-01

    Full Text Available Abstract Background Ecotypes of Colobanthus quitensis Kunt Bartl (Cariophyllaceae from Andes Mountains and Maritime Antarctic grow under contrasting photoinhibitory conditions, reaching differential cold tolerance upon cold acclimation. Photoinhibition depends on the extent of photodamage and recovery capability. We propose that cold acclimation increases resistance to low-temperature-induced photoinhibition, limiting photodamage and promoting recovery under cold. Therefore, the Antarctic ecotype (cold hardiest should be less photoinhibited and have better recovery from low-temperature-induced photoinhibition than the Andean ecotype. Both ecotypes were exposed to cold induced photoinhibitory treatment (PhT. Photoinhibition and recovery of photosystem II (PSII was followed by fluorescence, CO2 exchange, and immunoblotting analyses. Results The same reduction (25% in maximum PSII efficiency (Fv/Fm was observed in both cold-acclimated (CA and non-acclimated (NA plants under PhT. A full recovery was observed in CA plants of both ecotypes under dark conditions, but CA Antarctic plants recover faster than the Andean ecotype. Under PhT, CA plants maintain their quantum yield of PSII, while NA plants reduced it strongly (50% and 73% for Andean and Antarctic plants respectively. Cold acclimation induced the maintenance of PsaA and Cyt b6/f and reduced a 41% the excitation pressure in Antarctic plants, exhibiting the lowest level under PhT. xCold acclimation decreased significantly NPQs in both ecotypes, and reduced chlorophylls and D1 degradation in Andean plants under PhT. NA and CA plants were able to fully restore their normal photosynthesis, while CA Antarctic plants reached 50% higher photosynthetic rates after recovery, which was associated to electron fluxes maintenance under photoinhibitory conditions. Conclusions Cold acclimation has a greater importance on the recovery process than on limiting photodamage. Cold acclimation determined the

  10. The Effect of Irrigation Cut-off in Flowering Stage and Foliar Application of Spermidine on Essential Oil Quantity and Quality of Three Ecotypes of Cumin

    Directory of Open Access Journals (Sweden)

    Sarah Bakhtari

    2017-08-01

    Full Text Available Introduction Cumin (Cuminum cyminum L. is an annual plant that commonly cultivated in arid and semiarid regions of Iran. The crop has a wide range of uses including medicinal, cosmetic and food industry. Cumin occupies about 26% of total area devoted to medicinal plants in Iran. However, cumin is seriously affected by the Fusarium wilt and blight diseases. The diseases usually increase under warm and wet conditions. Control of the diseases incidence is a crucial factor for cumin production. Limited control of the diseases is provided by seed pre-sowing with certain fungicides such as benlate. Soil fumigation with methyle bromide can provide a control measure against the disease but may be limited application value for large scale production systems in the open field. In addition, methyle bromide is considered an ozone-depleting compound and has potential risk on the living environment and human health. Considering the environmental limitations of chemical fungicides, it seems appropriate to search for a supplemental control strategy .It was demonstrated that peak of the diseases incidence is occurred at flowering stage and irrigation cut-off in this time may be reduced the diseases density. Materials and methods This experiment was conducted in a split-split-plot arrangement in randomized complete block design with three replications in research farm of Shahid Bahonar University of Kerman at 2014. The experimental treatments were irrigation (complete irrigation and cut-off the irrigation in flowering stage assigned to main plots, foliar application of spermidine (0, 1 and 2 Mm as subplot and cumin ecotypes (Kerman, Khorasan and Esfahan that was randomized in sub-subplot. The seedbed preparation was made based on common practices at the location. Plots size under the trial was 4 m×3 m so as to get 50 cm inter row spacing in six rows. The ideal density of the crops was considered as 120 plant.m-2. As soon as the seeds were sown, irrigation

  11. Ecotypic differentiation between urban and rural populations of the grasshopper Chorthippus brunneus relative to climate and habitat fragmentation.

    Science.gov (United States)

    San Martin Y Gomez, Gilles; Van Dyck, Hans

    2012-05-01

    Urbanization alters environmental conditions in multiple ways and offers an ecological or evolutionary challenge for organisms to cope with. Urban areas typically have a warmer climate and strongly fragmented herbaceous vegetation; the urban landscape matrix is often assumed to be hostile for many organisms. Here, we addressed the issue of evolutionary differentiation between urban and rural populations of an ectotherm insect, the grasshopper Chorthippus brunneus. We compared mobility-related morphology and climate-related life history traits measured on the first generation offspring of grasshoppers from urban and rural populations reared in a common garden laboratory experiment. We predicted (1) the urban phenotype to be more mobile (i.e., lower mass allocation to the abdomen, longer relative femur and wing lengths) than the rural phenotype; (2) the urban phenotype to be more warm adapted (e.g., higher female body mass); and (3) further evidence of local adaptation in the form of significant interaction effects between landscape of origin and breeding temperature. Both males and females of urban origin had significantly longer relative femur and wing lengths and lower mass allocation to the abdomen (i.e., higher investment in thorax and flight muscles) relative to individuals of rural origin. The results were overall significant but small (2-4%). Body mass and larval growth rate were much higher (+10%) in females of urban origin. For the life history traits, we did not find evidence for significant interaction effects between the landscape of origin and the two breeding temperatures. Our results point to ecotypic differentiation with urbanization for mobility-related morphology and climate-related life history traits. We argue that the warmer urban environment has an indirect effect through longer growth season rather than direct effects on the development.

  12. From prediction to function using evolutionary genomics: human-specific ecotypes of Lactobacillus reuteri have diverse probiotic functions.

    Science.gov (United States)

    Spinler, Jennifer K; Sontakke, Amrita; Hollister, Emily B; Venable, Susan F; Oh, Phaik Lyn; Balderas, Miriam A; Saulnier, Delphine M A; Mistretta, Toni-Ann; Devaraj, Sridevi; Walter, Jens; Versalovic, James; Highlander, Sarah K

    2014-06-19

    The vertebrate gut symbiont Lactobacillus reuteri has diversified into separate clades reflecting host origin. Strains show evidence of host adaptation, but how host-microbe coevolution influences microbial-derived effects on hosts is poorly understood. Emphasizing human-derived strains of L. reuteri, we combined comparative genomic analyses with functional assays to examine variations in host interaction among genetically distinct ecotypes. Within clade II or VI, the genomes of human-derived L. reuteri strains are highly conserved in gene content and at the nucleotide level. Nevertheless, they share only 70-90% of total gene content, indicating differences in functional capacity. Human-associated lineages are distinguished by genes related to bacteriophages, vitamin biosynthesis, antimicrobial production, and immunomodulation. Differential production of reuterin, histamine, and folate by 23 clade II and VI strains was demonstrated. These strains also differed with respect to their ability to modulate human cytokine production (tumor necrosis factor, monocyte chemoattractant protein-1, interleukin [IL]-1β, IL-5, IL-7, IL-12, and IL-13) by myeloid cells. Microarray analysis of representative clade II and clade VI strains revealed global regulation of genes within the reuterin, vitamin B12, folate, and arginine catabolism gene clusters by the AraC family transcriptional regulator, PocR. Thus, human-derived L. reuteri clade II and VI strains are genetically distinct and their differences affect their functional repertoires and probiotic features. These findings highlight the biological impact of microbe:host coevolution and illustrate the functional significance of subspecies differences in the human microbiome. Consideration of host origin and functional differences at the subspecies level may have major impacts on probiotic strain selection and considerations of microbial ecology in mammalian species. © The Author(s) 2014. Published by Oxford University Press on

  13. Effect of Drought Stress on Leaf Water Status, Electrolyte Leakage, Photosynthesis Parameters and Chlorophyll Fluorescence of Two Kochia Ecotypes (Kochia scoparia Irrigated With Saline Water

    Directory of Open Access Journals (Sweden)

    A Masoumi

    2012-12-01

    Full Text Available Rainfall deficiency and the development of salinity in Iran are the most important factors for using new salt and drought-resistant plants instead of conventional crops. Kochia species have recently attracted the attention of researchers as a forage and fodder crop in marginal lands worldwide due to its drought and salt tolerant characteristics. This field experiment was performed at the Salinity Research Station of Ferdowsi University of Mashhad, Iran, in a split plot based on randomized complete block design with three replications in 2008. Drought stress, including four levels (control, no irrigation in vegetative stage, no irrigation at reproductive stage and no irrigation at maturity stage for four weeks, and two Kochia ecotypes (Birjand and Borujerd were allocated as main and sub plots, respectively. Relative water content, electrolyte leakage, photosynthesis parameters and chlorophyll fluorescence were assayed every two week from late vegetative stage. Results showed that drought stress decreased significantly measured parameters in plants under stress, in all stages. Plants completely recovered after eliminating stress and rewatering and recovered plants did not show significant difference with control. Electrolyte leaking and chlorophyll fluorescence showed the lowest change among the measured parameters. It can emphasize that resistant to stress conditions in this plant and cell wall is not damaged at this level of stress situation. Birjand ecotype from the arid region, revealed a better response than Borujerd ecotype to drought stress. Probably it returns to initial adaptation of Birjand. In general this plant can recover after severe drought stress well. It is possible to introduce this plant as a new fodder in arid and saline conditions.

  14. Microbiome and ecotypic adaption of Holcus lanatus (L.) to extremes of its soil pH range, investigated through transcriptome sequencing.

    Science.gov (United States)

    Young, Ellen; Carey, Manus; Meharg, Andrew A; Meharg, Caroline

    2018-03-20

    Plants can adapt to edaphic stress, such as nutrient deficiency, toxicity and biotic challenges, by controlled transcriptomic responses, including microbiome interactions. Traditionally studied in model plant species with controlled microbiota inoculation treatments, molecular plant-microbiome interactions can be functionally investigated via RNA-Seq. Complex, natural plant-microbiome studies are limited, typically focusing on microbial rRNA and omitting functional microbiome investigations, presenting a fundamental knowledge gap. Here, root and shoot meta-transcriptome analyses, in tandem with shoot elemental content and root staining, were employed to investigate transcriptome responses in the wild grass Holcus lanatus and its associated natural multi-species eukaryotic microbiome. A full factorial reciprocal soil transplant experiment was employed, using plant ecotypes from two widely contrasting natural habitats, acid bog and limestone quarry soil, to investigate naturally occurring, and ecologically meaningful, edaphically driven molecular plant-microbiome interactions. Arbuscular mycorrhizal (AM) and non-AM fungal colonization was detected in roots in both soils. Staining showed greater levels of non-AM fungi, and transcriptomics indicated a predominance of Ascomycota-annotated genes. Roots in acid bog soil were dominated by Phialocephala-annotated transcripts, a putative growth-promoting endophyte, potentially involved in N nutrition and ion homeostasis. Limestone roots in acid bog soil had greater expression of other Ascomycete genera and Oomycetes and lower expression of Phialocephala-annotated transcripts compared to acid ecotype roots, which corresponded with reduced induction of pathogen defense processes, particularly lignin biosynthesis in limestone ecotypes. Ascomycota dominated in shoots and limestone soil roots, but Phialocephala-annotated transcripts were insignificant, and no single Ascomycete genus dominated. Fusarium-annotated transcripts were

  15. Carbon source utilization patterns of Bacillus simplex ecotypes do not reflect their adaptation to ecologically divergent slopes in 'Evolution Canyon', Israel.

    Science.gov (United States)

    Sikorski, Johannes; Pukall, Rüdiger; Stackebrandt, Erko

    2008-10-01

    The 'Evolution Canyons' I and II in Israel are model habitats to study adaptation and speciation of bacteria in the environment. These canyons represent similar ecological replicates, separated by 40 km, with a strongly sun-exposed and hot 'African' south-facing slope (SFS) vs. a cooler and mesic-lush 'European' north-facing slope (NFS). Previously, among 131 Bacillus simplex isolates, distinct genetic lineages (ecotypes), each specific for either SFS or NFS, were identified, suggesting a temperature-driven slope-specific adaptation. Here, we asked whether the ecological heterogeneity of SFS vs. NFS also affected carbon utilization abilities, as determined using the Biolog assay. Contrary to expectation, a correlation between substrate utilization patterns and the ecological origin of strains was not found. Rather, the patterns split according to the two major phylogenetic lineages each of which contain SFS and NFS ecotypes. We conclude that traits related to the general energy metabolism, as far as assessed here, are neither shaped by the major abiotic features of 'Evolution Canyon', namely solar radiation, temperature, and drought, nor by the soil characteristics. We further conclude that some traits diverge rather neutrally from each other, whereas other, more environmentally related traits are shaped by natural selection and show evolutionary convergence.

  16. 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...

  17. Assessment of Qualitative and Quantitative Characters of Two Persian Clover Ecotypes Inoculated by Rhizobium leguminosarum biovartrifoli and Pesudomonas putida Bacteria

    Directory of Open Access Journals (Sweden)

    R Azamei

    2016-02-01

    Full Text Available Introduction Over the past decades, world attitude has changed towards the reduction of environmental pollutants. Harmful effects of synthetic fertilizers on environment have been identified. Bio-fertilizers are not harmful to the environment, but also they have favorable effects on plant growth processes. Soil biotechnology can be defined as the study of soil organisms and their metabolic processes which may have positive effects on plant yields. The main goal of this study is to asess the biotechnology fertilizers beneficial effects on soil organisms and their subsequently to maximize the yield. It is also our desire conside the soil quality, hygiene and environmental protection along this process. Among the strain of nitrogen-fixing bacteria, symbiotic bacteria such as rhizobium bacteria are important and essential in planning the sustainable farming systems. Several studies have shown that crop varieties which inoculated with rhizobium and pseudomonas were superior in yield production and performance. Material and Methods An experiment was designed as factorial performed in randomized complete block design (RCBD with three replications in Agricultural Research Center of Golpayegan (Isfahan during 2010 – 2011. the purpose of this study was to evaluate the effects of inoculation of two ecotypes of Persian clover by various strains of Rhizobium leguminosarum. Biovar trifoli bacteria accompanied with plant growth promoting rhizobacteria (PGPR Pseudomonas putida was employed to find certain qualitative and quantitative characteristics of clover yield, The main plots included two local ecotypes of Persian clover; Arak Haft Chin (V1 and Isfahan Haft Chin (V2, the subplots included inoculation by two strain of Rhizobium; Rb-3, Rb-13 and one strain of Pseudomonas; PS -168.4 cuts were performed during the experiment and 60 kg/ha seed was used for cultivation based on local knowledge. According to recommendations of the Institute of Soil and Water

  18. The molecular dimension of microbial species: 3. Comparative genomics of Synechococcus strains with different light responses and in situ diel transcription patterns of associated ecotypes in the Mushroom Spring microbial mat

    Directory of Open Access Journals (Sweden)

    Millie T. Olsen

    2015-06-01

    Full Text Available Genomes were obtained for three closely related strains of Synechococcus that are representative of putative ecotypes that predominate at different depths in the 1 mm-thick, upper-green layer in the 60°C mat of Mushroom Spring, Yellowstone National Park, and exhibit different light adaptation and acclimation responses. The genomes were compared to the published genome of a previously obtained, closely related strain from a neighboring spring, and differences in both gene content and orthologous gene alleles between high-light-adapted and low-light-adapted strains were identified. Evidence of genetic differences that relate to adaptation to light intensity and/or quality, CO2 uptake, nitrogen metabolism, organic carbon metabolism, and uptake of other nutrients were found between strains of the different putative ecotypes. In situ diel transcription patterns of genes, including genes unique to either low-light-adapted or high-light-adapted strains and different alleles of an orthologous photosystem gene, revealed that expression is fine-tuned to the different light environments experienced by ecotypes prevalent at various depths in the mat. This study suggests that strains of closely related putative ecotypes have different genomic adaptations that enable them to inhabit distinct ecological niches while living in close proximity within a microbial community.

  19. The Effects of Drought Stress on Yield, Yield Components and Anti-oxidant of Two Garlic (Allium sativum L. Ecotypes with Different Planting Densities

    Directory of Open Access Journals (Sweden)

    shiva akbari

    2016-07-01

    Full Text Available Introduction Drought stress reduces plant growth by affecting various physiological and biochemical processes, such as photosynthesis, respiration, translocation, ion uptake, carbohydrates, nutrient metabolism and growth promoters. Garlic (Allium sativum L. is an annual bulb crop that has been cultivated since ancient times and was used as a spice and condiment for many centuries. Garlic is an important plant because of its pharmaceutical properties. The optimum yield of this bulb crop depends on well-managed irrigation, fertilization and cultivation practices. In the final and middle stages of growth, garlic is sensitive to water stress and low irrigation is unsuitable in these stages. This experiment was established to study the influence of drought stress and planting density on yield and its components and the non-enzymatic anti-oxidant content of two different garlic ecotypes. Materials and methods This study was conducted in 2011-2012 in a farmland at the south east of Semnan city. The experimental layout was a split-plot factorial with a randomized complete block design with three replications. The treatments were comprised of three factors: irrigation rates (60%, 80% and 100% of estimated crop evapotranspiration (ETC as the main plot and the factorial combination of three levels of planting density (30, 40 and 50 plants.m-2 and two ecotypes (Tabas and Toroud as the sub-plots. To estimate the crop water requirement, different meteorological parameters were collected from Semnan weather station and were used based on FAO-56 water irrigation calculation instructions. After harvesting, ten garlic plants were sampled randomly in each plot and bulb yield components were measured. To calculate the leaves anti-oxidant content, DPPH method was used. The statistical significances of mean values were assessed by analysis of variance and LSD tests at p≤0.05. All calculations were performed using SAS and Mstat-C softwares. Results and discussion

  20. 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...

  1. Effect of Organic and Chemical Fertilizers on Yield and Essential Oil of Two Ecotypes of Savory (Satureja hortensis L. under Normal and Drought Stress Conditions

    Directory of Open Access Journals (Sweden)

    O Akrami nejad

    2016-02-01

    Full Text Available Introduction Savory (Satureja hortensis L. is an annual and aromatic plant from Labiatae family, which has plenty of essential oil and is important in medicinal, food, health and beauty industries (6. In comparison with chemical fertilizers, organic fertilizers especially manure have lots of organic material sources, and can be used as nutrients, especially Nitrogen, Phosphor and Potassium. Organic fertilizers also keeps more water in the soil (14. Water deficit is one of the most important boundaries of production in arid and semi-arid regions. Drought stress reduces water content, limits plant growth and changes some physiological and metabolic activities (31. This experiment was conducted as there is a global interest for production of medicinal plants with sustainable agriculture system, and with low input and shortage of information about Savory reaction to fertilization in drought stress condition. The objective of this research was to compare the effects of chemical fertilizers and different organic fertilizers on quantitative and qualitative characteristics of two ecotypes of savory under drought stress condition. Materials and Methods In order to study the effects of organic and mineral (N, P and K fertilizers on quantitative and qualitative characteristics of savory in drought stress condition, two separate split plot designs with three replications were carried out in 2012-2013 year, at the research field of Shahid Bahonar University of Kerman, Iran. In each design fertilizers including cow manure (30 ton per hectare, poultry manure (10 ton per hectare, chemical fertilizers (used equally with macro elements existing in both poultry and cow manure and control (no fertilizer were used as main factor. Kerman and Khuzestan ecotypes were sub-factor. One of the experiments was irrigated to 100% and the other to 50% of field capacity. Two experiments were analyzed as a combined design. The important characteristics of Savory such as plant

  2. 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)

  3. 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...

  4. 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.

  5. 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 ...

  6. 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 ...

  7. Nickel-tolerant ectomycorrhizal Pisolithus albus ultramafic ecotype isolated from nickel mines in New Caledonia strongly enhance growth of the host plant Eucalyptus globulus at toxic nickel concentrations.

    Science.gov (United States)

    Jourand, Philippe; Ducousso, Marc; Reid, Robert; Majorel, Clarisse; Richert, Clément; Riss, Jennifer; Lebrun, Michel

    2010-10-01

    Ectomycorrhizal (ECM) Pisolithus albus (Cooke & Massee), belonging to the ultramafic ecotype isolated in nickel-rich serpentine soils from New Caledonia (a tropical hotspot of biodiversity) and showing in vitro adaptive nickel tolerance, were inoculated to Eucalyptus globulus Labill used as a Myrtaceae plant-host model to study ectomycorrhizal symbiosis. Plants were then exposed to a nickel (Ni) dose-response experiment with increased Ni treatments up to 60 mg kg( - )(1) soil as extractable Ni content in serpentine soils. Results showed that plants inoculated with ultramafic ECM P. albus were able to tolerate high and toxic concentrations of Ni (up to 60 μg g( - )(1)) while uninoculated controls were not. At the highest Ni concentration tested, root growth was more than 20-fold higher and shoot growth more than 30-fold higher in ECM plants compared with control plants. The improved growth in ECM plants was associated with a 2.4-fold reduction in root Ni concentration but a massive 60-fold reduction in transfer of Ni from root to shoots. In vitro, P. albus strains could withstand high Ni concentrations but accumulated very little Ni in its tissue. The lower Ni uptake by mycorrhizal plants could not be explained by increased release of metal-complexing chelates since these were 5- to 12-fold lower in mycorrhizal plants at high Ni concentrations. It is proposed that the fungal sheath covering the plant roots acts as an effective barrier to limit transfer of Ni from soil into the root tissue. The degree of tolerance conferred by the ultramafic P. albus isolates to growth of the host tree species is considerably greater than previously reported for other ECM. The primary mechanisms underlying this improved growth were identified as reduced Ni uptake into the roots and markedly reduced transfer from root to shoot in mycorrhizal plants. The fact that these positive responses were observed at Ni concentrations commonly observed in serpentinic soils suggests that

  8. 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....

  9. Diversity of Mat-Forming Fungi in Relation to Soil Properties, Disturbance, and Forest Ecotype at Crater Lake National Park, Oregon, USA

    Directory of Open Access Journals (Sweden)

    James M. Trappe

    2012-04-01

    Full Text Available In forest ecosystems, fungal mats are functionally important in nutrient and water uptake in litter and wood decomposition processes, in carbon resource allocation, soil weathering and in cycling of soil resources. Fungal mats can occur abundantly in forests and are widely distributed globally. We sampled ponderosa pine/white fir and mountain hemlock/noble fir communities at Crater Lake National Park for mat-forming soil fungi. Fungus collections were identified by DNA sequencing. Thirty-eight mat-forming genotypes were identified; members of the five most common genera (Gautieria, Lepiota, Piloderma, Ramaria, and Rhizopogon comprised 67% of all collections. The mycorrhizal genera Alpova and Lactarius are newly identified as ectomycorrhizal mat-forming taxa, as are the saprotrophic genera Flavoscypha, Gastropila, Lepiota and Xenasmatella. Twelve typical mat forms are illustrated, representing both ectomycorrhizal and saprotrophic fungi that were found. Abundance of fungal mats was correlated with higher soil carbon to nitrogen ratios, fine woody debris and needle litter mass in both forest ecotypes. Definitions of fungal mats are discussed, along with some of the challenges in defining what comprises a fungal “mat”.

  10. A field reciprocal transplant experiment reveals asymmetric costs of migration between lake and river ecotypes of three-spined sticklebacks (Gasterosteus aculeatus).

    Science.gov (United States)

    Kaufmann, J; Lenz, T L; Kalbe, M; Milinski, M; Eizaguirre, C

    2017-05-01

    Theory of local adaptation predicts that nonadapted migrants will suffer increased costs compared to local residents. Ultimately this process can result in the reduction of gene flow and culminate in speciation. Here, we experimentally investigated the relative fitness of migrants in foreign habitats, focusing on diverging lake and river ecotypes of three-spined sticklebacks. A reciprocal transplant experiment performed in the field revealed asymmetric costs of migration: whereas mortality of river fish was increased under lake conditions, lake migrants suffered from reduced growth relative to river residents. Selection against migrants thus involved different traits in each habitat but generally contributed to bidirectional reduction in gene flow. Focusing particularly on the parasitic environments, migrant fish differed from resident fish in the parasite community they harboured. This pattern correlated with both cellular phenotypes of innate immunity as well as with allelic variation at the genes of the major histocompatibility complex. In addition to showing the costs of migration in three-spined sticklebacks, this study highlights the role of asymmetric selection particularly from parasitism in genotype sorting and in the emergence of local adaptation. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  11. Comparative study of growth traits and haematological parameters of Anak and Nigerian heavy ecotype chickens fed with graded levels of mango seed kernel (Mangifera indica) meal.

    Science.gov (United States)

    Mbunwen, Ndofor-Foleng Harriet; Ngongeh, Lucas Atehmengo; Okolie, Peter Nzeribe; Okoli, Emeka Linus

    2015-08-01

    One hundred fifty Anak and 120 Nigerian heavy local ecotype (NHLE) chickens were used to study the effects of feeding graded levels of mango seed kernel meal (MKM) replacing maize diet on growth traits and haematological parameters. A 2 × 5 factorial arrangement was employed: two breeds and five diets. The birds were randomly allocated to five finisher diets formulated such that MKM replaced maize at 0, 10, 20, 30 and 40% (T1, T2, T3, T4 and T5) inclusion levels, respectively. The effect of breed and dietary treatments on growth performance and blood characteristics were determined. The results showed a significant (P  0.05) when the breeds and treatments were compared. It was concluded that inclusion of dietary MKM below 30% could replace maize in the diets of Anak and NHLE growing chickens without adverse effect on growth performance and blood constituents. This work suggests that genetic differences exist in growth traits of these breeds of chickens. This advantage could be useful in breed improvement programmes and better feeding managements of the NHLE and Anak chickens.

  12. Comparative efficacy of pour-on and subcutaneous injection of ivermectin on Melophagus ovinus (L.) in Darab ecotype goats of Southern Iran.

    Science.gov (United States)

    Jafari Shoorijeh, S; Noori, A; Tamadon, A

    2007-09-01

    The efficacy of ivermectin was evaluated against Melophagus ovinus in Darab ecotype goats of Iran. Twenty-four healthy Iranian crossbreed male goats were randomly divided into three equal groups (n = 8). An experimental infestation was induced in all animals of the three groups with 100 M. ovinus on the body of each animal. Groups 1 and 2 were treated with 1% ivermectin solution at a dosage of 0.5 mg/kg of body weight applied as a pour-on along the dorsal midline and 0.2 mg/kg subcutaneously, respectively; while group 3 was kept as control group. Seven days after infestation ivermectin was administered then the goats were observed for a period of 7 days. Body surface of each goat of three groups was inspected daily and decreases in M. ovinus were recorded. The rate of elimination in keds was assessed on the basis of decrease in keds count on the skin and hairs. The results revealed that complete absence of keds were observed in 6 and 7 days post-treatment with injection and pour-on routes, respectively. The results of present study showed that subcutaneous injection of ivermectin more rapidly eliminated M. ovinus than pour-on route. Both routes were 100% effective against this parasite in the goats. Ivermectin can be a drug of choice against M. ovinus in long-hair Iranian goats due to its high efficacy, easy applicability and wide safety margin.

  13. 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.

  14. 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 ...

  15. 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.

  16. 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

  17. 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...

  18. 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...

  19. 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.

  20. 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

  1. 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...

  2. 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.

  3. Comprehensive genomic analyses of the OM43 clade including a novel species from Red Sea indicate ecotype differentiation among marine methylotrophs

    KAUST Repository

    Jimenez Infante, Francy M.

    2015-12-11

    The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs playing important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (designated here as MBRS-H7) from the ultra-oligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species, which forms a distinct cluster together with isolate KB13 from Hawaii (H-RS cluster) that is separate from that represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S–23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low chlorophyll and/or high temperature provinces for the H-RS cluster, but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of H-RS include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely the existence of the NADH:quinone oxidoreductase NUO system in the H-RS and the non-homologous NQR system in HTCC2181, which might have implications on their overall energetic yields.

  4. Comprehensive genomic analyses of the OM43 clade including a novel species from Red Sea indicate ecotype differentiation among marine methylotrophs

    KAUST Repository

    Jimenez Infante, Francy M.; Ngugi, David; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan; Blom, Jochen; Bajic, Vladimir B.; Stingl, Ulrich

    2015-01-01

    The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs playing important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (designated here as MBRS-H7) from the ultra-oligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species, which forms a distinct cluster together with isolate KB13 from Hawaii (H-RS cluster) that is separate from that represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S–23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low chlorophyll and/or high temperature provinces for the H-RS cluster, but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of H-RS include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely the existence of the NADH:quinone oxidoreductase NUO system in the H-RS and the non-homologous NQR system in HTCC2181, which might have implications on their overall energetic yields.

  5. Comprehensive Genomic Analyses of the OM43 Clade, Including a Novel Species from the Red Sea, Indicate Ecotype Differentiation among Marine Methylotrophs

    Science.gov (United States)

    Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan Anthony; Blom, Jochen; Bajic, Vladimir B.

    2015-01-01

    The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs that play important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (here designated MBRS-H7) from the ultraoligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species that forms a distinct cluster together with isolate KB13 from Hawaii (Hawaii-Red Sea [H-RS] cluster) that is separate from the cluster represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S-23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low-chlorophyll and/or high-temperature provinces for the H-RS cluster but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of the H-RS cluster include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely, the existence of the NADH:quinone oxidoreductase complex I (NUO) system in the H-RS cluster and the nonhomologous NADH:quinone oxidoreductase (NQR) system in the HTCC2181 cluster, which might have implications for their overall energetic yields. PMID:26655752

  6. 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...

  7. Contribution of Bicarbonate Assimilation to Carbon Pool Dynamics in the Deep Mediterranean Sea and Cultivation of Actively Nitrifying and CO2-Fixing Bathypelagic Prokaryotic Consortia.

    Science.gov (United States)

    La Cono, Violetta; Ruggeri, Gioachino; Azzaro, Maurizio; Crisafi, Francesca; Decembrini, Franco; Denaro, Renata; La Spada, Gina; Maimone, Giovanna; Monticelli, Luis S; Smedile, Francesco; Giuliano, Laura; Yakimov, Michail M

    2018-01-01

    Covering two-thirds of our planet, the global deep ocean plays a central role in supporting life on Earth. Among other processes, this biggest ecosystem buffers the rise of atmospheric CO 2 . Despite carbon sequestration in the deep ocean has been known for a long time, microbial activity in the meso- and bathypelagic realm via the " assimilation of bicarbonate in the dark " (ABD) has only recently been described in more details. Based on recent findings, this process seems primarily the result of chemosynthetic and anaplerotic reactions driven by different groups of deep-sea prokaryoplankton. We quantified bicarbonate assimilation in relation to total prokaryotic abundance, prokaryotic heterotrophic production and respiration in the meso- and bathypelagic Mediterranean Sea. The measured ABD values, ranging from 133 to 370 μg C m -3 d -1 , were among the highest ones reported worldwide for similar depths, likely due to the elevated temperature of the deep Mediterranean Sea (13-14°C also at abyssal depths). Integrated over the dark water column (≥200 m depth), bicarbonate assimilation in the deep-sea ranged from 396 to 873 mg C m -2 d -1 . This quantity of produced de novo organic carbon amounts to about 85-424% of the phytoplankton primary production and covers up to 62% of deep-sea prokaryotic total carbon demand. Hence, the ABD process in the meso- and bathypelagic Mediterranean Sea might substantially contribute to the inorganic and organic pool and significantly sustain the deep-sea microbial food web. To elucidate the ABD key-players, we established three actively nitrifying and CO 2 -fixing prokaryotic enrichments. Consortia were characterized by the co-occurrence of chemolithoautotrophic Thaumarchaeota and chemoheterotrophic proteobacteria. One of the enrichments, originated from Ionian bathypelagic waters (3,000 m depth) and supplemented with low concentrations of ammonia, was dominated by the Thaumarchaeota "low-ammonia-concentration" deep-sea ecotype

  8. 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....

  9. 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...

  10. 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.

  11. 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

  12. The efficiency of Arabidopsis thaliana floral dip transformation is determined not only by the Agrobacterium strain used but also by the physiology and the ecotype of the dipped plant.

    Science.gov (United States)

    Ghedira, Rim; De Buck, Sylvie; Nolf, Jonah; Depicker, Ann

    2013-07-01

    To evaluate the chromosomal background of different Agrobacterium strains on floral dip transformation frequency, eight wild-type Agrobacterium strains, provided by Laboratorium voor Microbiologie Gent (LMG) and classified in different genomic groups, were compared with the commonly used Agrobacterium strains C58C1 Rif(r) (pMP90) and LBA4404 in Arabidopsis thaliana Columbia (Col-0) and C24 ecotypes. The C58C1 Rif(r) chromosomal background in combination with the pMP90 virulence plasmid showed high Col-0 floral dip transformation frequencies (0.76 to 1.57%). LMG201, which is genetically close to the Agrobacterium C58 strain, with the same virulence plasmid showed comparable or even higher transformation frequencies (1.22 to 2.28%), whereas the LBA4404 strain displayed reproducibly lower transformation frequencies (Agrobacterium chromosomal backgrounds had transformation frequencies between those of the C58C1 Rif(r) (pMP90) and LBA4404 reference strains. None of the strains could transform the C24 ecotype with a frequency higher than 0.1%. Strikingly, all Arabidopsis Col-0 floral dip transformation experiments showed a high transformation variability from plant to plant (even more than 50-fold) within and across the performed biological repeats for all analyzed Agrobacterium strains. Therefore, the physiology of the plant and, probably, the availability of competent flowers to be transformed determine, to a large extent, floral dip transformation frequencies.

  13. Changes in endogenous abscisic acid levels during dormancy release and maintenance of mature seeds: studies with the Cape Verde Islands ecotype, the dormant model of Arabidopsis thaliana.

    Science.gov (United States)

    Ali-Rachedi, Sonia; Bouinot, Denise; Wagner, Marie-Hélène; Bonnet, Magda; Sotta, Bruno; Grappin, Philippe; Jullien, Marc

    2004-07-01

    Mature seeds of the Cape Verde Islands (Cvi) ecotype of Arabidopsis thaliana (L.) Heynh. show a very marked dormancy. Dormant (D) seeds completely fail to germinate in conditions that are favourable for germination whereas non-dormant (ND) seeds germinate easily. Cvi seed dormancy is alleviated by after-ripening, stratification, and also by nitrate or fluridone treatment. Addition of gibberellins to D seeds does not suppress dormancy efficiently, suggesting that gibberellins are not directly involved in the breaking of dormancy. Dormancy expression of Cvi seeds is strongly dependent on temperature: D seeds do not germinate at warm temperatures (20-27 degrees C) but do so easily at a low temperature (13 degrees C) or when a fluridone treatment is given to D seeds sown at high temperature. To investigate the role of abscisic acid (ABA) in dormancy release and maintenance, we measured the ABA content in both ND and D seeds imbibed using various dormancy-breaking conditions. It was found that dry D seeds contained higher amounts of ABA than dry ND after-ripened seeds. During early imbibition in standard conditions, there was a decrease in ABA content in both seeds, the rate of which was slower in D seeds. Three days after sowing, the ABA content in D seeds increased specifically and then remained at a high level. When imbibed with fluridone, nitrate or stratified, the ABA content of D seeds decreased and reached a level very near to that of ND seeds. In contrast, gibberellic acid (GA3) treatment caused a transient increase in ABA content. When D seeds were sown at low optimal temperature their ABA content also decreased to the level observed in ND seeds. The present study indicates that Cvi D and ND seeds can be easily distinguished by their ability to synthesize ABA following imbibition. Treatments used here to break dormancy reduced the ABA level in imbibed D seeds to the level observed in ND seeds, with the exception of GA3 treatment, which was active in promoting

  14. Ecotypic and allozyme variation of Capsella bursa-pastoris and C. rubella (Brassicaceae along latitude and altitude gradients on the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    Hoffrogge, Raimund

    1999-12-01

    Full Text Available Life-history traits (onset of flowering, leaf number, rosette diameter, plant height, branching number, fruit dimensions, seed number of Capsella species from the Iberian Península associated with colotúzing ability were compared in a random block field experiment. Data were evaluated by a principal component analysis. Allozymes (AAT, LAP, GDH and leaf types were recorded. C. bursa-pastoris plants originating from low and high elevations of the summer dry Mediterranean climatic zone (Sierra Nevada were early flowering, whereas those originating from the Pyrenees with an alpine climate were late. In C. bursa-pastoris the "rhomboidea" leaf type was very frequent, whereas in C. rubella it was the "heteris" leaf type. There was a change of leaf type frequencies along geographical clines which is explained by adaptive components of the leaf shape. The allozymes displayed a geographical distribuüon pattem and in C. bursa-pastoris a certain multilocus genotype appeared to be a molecular marker for an early flowering ecotype(inicio de la floración, número de hojas, diámetro de la roseta, altura de la planta, número de ramas, dimensiones del fruto y número de semillas de plantas de Capsella procedentes de la Península Ibérica mediante un experimento de bloques aleatorios en el campo. Los datos se evaluaron con un análisis de componentes principales. También se registraron el tipo de hojas y el perfil aloenzimático de las plantas. Las plantas de Capsella bursa-pastoris procedentes de altitudes altas y bajas de la zona climática Mediterránea de verano seco (Sierra Nevada mostraron ser de floración temprana, mientras que las plantas de los Pirineos, con un clima alpino, presentaron una floración tardía. En C. bursa-pastoris el tipo de hoja "rhomboidea" resultó ser el más frecuente, en tanto que en C. rubella lo fue el tipo "heteris". Se observó un cambio en las frecuencias de los tipos de hojas a lo largo de una clina geográfica, lo

  15. 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

  16. 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.

  17. 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...

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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…

  3. 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...

  4. [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.

  5. 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

  6. 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...

  7. 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)

  8. 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...

  9. 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.

  10. 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

  11. 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.)

  12. 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.)

  13. [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.

  14. 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

  15. 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...

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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...

  2. 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.

  3. 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 ...

  4. 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

  5. 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

  6. Significance of the identification in the Horn of Africa of an exceptionally deep branching Mycobacterium tuberculosis clade.

    Directory of Open Access Journals (Sweden)

    Yann Blouin

    Full Text Available Molecular and phylogeographic studies have led to the definition within the Mycobacterium tuberculosis complex (MTBC of a number of geotypes and ecotypes showing a preferential geographic location or host preference. The MTBC is thought to have emerged in Africa, most likely the Horn of Africa, and to have spread worldwide with human migrations. Under this assumption, there is a possibility that unknown deep branching lineages are present in this region. We genotyped by spoligotyping and multiple locus variable number of tandem repeats (VNTR analysis (MLVA 435 MTBC isolates recovered from patients. Four hundred and eleven isolates were collected in the Republic of Djibouti over a 12 year period, with the other 24 isolates originating from neighbouring countries. All major M. tuberculosis lineages were identified, with only two M. africanum and one M. bovis isolates. Upon comparison with typing data of worldwide origin we observed that several isolates showed clustering characteristics compatible with new deep branching. Whole genome sequencing (WGS of seven isolates and comparison with available WGS data from 38 genomes distributed in the different lineages confirms the identification of ancestral nodes for several clades and most importantly of one new lineage, here referred to as lineage 7. Investigation of specific deletions confirms the novelty of this lineage, and analysis of its precise phylogenetic position indicates that the other three superlineages constituting the MTBC emerged independently but within a relatively short timeframe from the Horn of Africa. The availability of such strains compared to the predominant lineages and sharing very ancient ancestry will open new avenues for identifying some of the genetic factors responsible for the success of the modern lineages. Additional deep branching lineages may be readily and efficiently identified by large-scale MLVA screening of isolates from sub-Saharan African countries followed by

  7. 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…

  8. 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.

  9. 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.

  10. 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...

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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...

  19. 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

  20. 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...

  1. 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 ...

  2. Contribution of Bicarbonate Assimilation to Carbon Pool Dynamics in the Deep Mediterranean Sea and Cultivation of Actively Nitrifying and CO2-Fixing Bathypelagic Prokaryotic Consortia

    Science.gov (United States)

    La Cono, Violetta; Ruggeri, Gioachino; Azzaro, Maurizio; Crisafi, Francesca; Decembrini, Franco; Denaro, Renata; La Spada, Gina; Maimone, Giovanna; Monticelli, Luis S.; Smedile, Francesco; Giuliano, Laura; Yakimov, Michail M.

    2018-01-01

    Covering two-thirds of our planet, the global deep ocean plays a central role in supporting life on Earth. Among other processes, this biggest ecosystem buffers the rise of atmospheric CO2. Despite carbon sequestration in the deep ocean has been known for a long time, microbial activity in the meso- and bathypelagic realm via the “assimilation of bicarbonate in the dark” (ABD) has only recently been described in more details. Based on recent findings, this process seems primarily the result of chemosynthetic and anaplerotic reactions driven by different groups of deep-sea prokaryoplankton. We quantified bicarbonate assimilation in relation to total prokaryotic abundance, prokaryotic heterotrophic production and respiration in the meso- and bathypelagic Mediterranean Sea. The measured ABD values, ranging from 133 to 370 μg C m−3 d−1, were among the highest ones reported worldwide for similar depths, likely due to the elevated temperature of the deep Mediterranean Sea (13–14°C also at abyssal depths). Integrated over the dark water column (≥200 m depth), bicarbonate assimilation in the deep-sea ranged from 396 to 873 mg C m−2 d−1. This quantity of produced de novo organic carbon amounts to about 85–424% of the phytoplankton primary production and covers up to 62% of deep-sea prokaryotic total carbon demand. Hence, the ABD process in the meso- and bathypelagic Mediterranean Sea might substantially contribute to the inorganic and organic pool and significantly sustain the deep-sea microbial food web. To elucidate the ABD key-players, we established three actively nitrifying and CO2-fixing prokaryotic enrichments. Consortia were characterized by the co-occurrence of chemolithoautotrophic Thaumarchaeota and chemoheterotrophic proteobacteria. One of the enrichments, originated from Ionian bathypelagic waters (3,000 m depth) and supplemented with low concentrations of ammonia, was dominated by the Thaumarchaeota “low-ammonia-concentration” deep

  3. 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.

  4. 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.

  5. 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.

  6. Accelerating Deep Learning with Shrinkage and Recall

    OpenAIRE

    Zheng, Shuai; Vishnu, Abhinav; Ding, Chris

    2016-01-01

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

  7. What Really is Deep Learning Doing?

    OpenAIRE

    Xiong, Chuyu

    2017-01-01

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

  8. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

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

  9. Deep Learning in Drug Discovery.

    Science.gov (United States)

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

    2016-01-01

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

  10. Eric Davidson and deep time.

    Science.gov (United States)

    Erwin, Douglas H

    2017-10-13

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

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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 ...

  20. 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.

  1. 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.

  2. 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)

  3. 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,

  4. 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,

  5. 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

  6. 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.

  7. 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.

  8. 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…

  9. 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...

  10. 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.

  11. Organophosphorus acid anhydrolase from Alteromonas macleodii: structural study and functional relationship to prolidases

    Czech Academy of Sciences Publication Activity Database

    Štěpánková, Andrea; Dušková, Jarmila; Skálová, Tereza; Hašek, Jindřich; Koval, Tomáš; Ostergaard, L. H.; Dohnálek, Jan

    2013-01-01

    Roč. 69, č. 4 (2013), s. 346-354 ISSN 1744-3091 R&D Projects: GA ČR GA310/09/1407; GA ČR GA305/07/1073; GA MŠk EE2.3.30.0029 Institutional research plan: CEZ:AV0Z40500505 Institutional support: RVO:61389013 Keywords : organophosphorus acid anhydrolase * prolidases * bifunctional Subject RIV: CE - Biochemistry Impact factor: 0.568, year: 2013

  12. 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...

  13. 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.

  14. 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...

  15. 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...

  16. 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.

  17. 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...

  18. 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.

  19. 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...

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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...

  14. 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.

  15. 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...

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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...

  1. 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...

  2. 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

  3. 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

  4. 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

  5. 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...

  6. 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.)

  7. 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.

  8. 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.

  9. 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 ...

  10. 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 ...

  11. 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

  12. Ecotype diversification of an abundant Roseobacter lineage.

    Science.gov (United States)

    Sun, Ying; Zhang, Yao; Hollibaugh, James T; Luo, Haiwei

    2017-04-01

    The Roseobacter DC5-80-3 cluster (also known as the RCA clade) is among the most abundant bacterial lineages in temperate and polar oceans. Previous studies revealed two phylotypes within this cluster that are distinctly distributed in the Antarctic and other ocean provinces. Here, we report a nearly complete genome co-assembly of three closely related single cells co-occurring in the Antarctic, and compare it to the available genomes of the other phylotype from ocean regions where iron is more accessible but phosphorus and nitrogen are less. The Antarctic phylotype exclusively contains an operon structure consisting of a dicitrate transporter fecBCDE and an upstream regulator likely for iron uptake, whereas the other phylotype consistently carry a high-affinity phosphate pst transporter and the phoB-phoR regulatory system, a high-affinity ammonium amtB transporter, urea and taurine utilization systems. Moreover, the Antarctic phylotype uses proteorhodopsin to acquire light, whereas the other uses bacteriochlorophyll-a and the sulfur-oxidizing sox cluster for energy acquisition. This is potentially an iron-saving strategy for the Antarctic phylotype because only the latter two pathways have iron-requiring cytochromes. Therefore, the two DC5-80-3 phylotypes, while diverging by only 1.1% in their 16S rRNA genes, have evolved systematic differences in metabolism to support their distinct ecologies. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

  13. 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)

  14. 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

  15. 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)

  16. 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.

  17. 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)

  18. 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

  19. 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.

  20. 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...

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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....

  6. 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.

  7. 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.

  8. Nutritional Aspects of Six Quinoa (Chenopodium quinoa Willd. Ecotypes from three Geographical Areas of Chile Aspectos Nutricionales de Seis Ecotipos de Quínoa (Chenopodium quinoa Willd. de Tres Zonas Geográficas de Chile

    Directory of Open Access Journals (Sweden)

    Margarita Miranda

    2012-06-01

    Full Text Available This study explored the diversity of the quinoa crop in Chile from a nutritional perspective. Nutritional properties, minerals, vitamins, and saponin content were assessed in seeds of six Chilean quinoa (Chenopodium quinoa Willd. ecotypes grown in three main production areas with distinctive climatic and edaphic conditions: Ancovinto and Cancosa in the North-Altiplano or High Plateau, Cáhuil and Faro in the central coastal area, and Regalona and Villarrica in the south of the country. There were significant differences (P La diversidad en el cultivo de la quinoa (Chenopodium quinoa Willd. de Chile fue explorada desde una perspectiva nutricional. En este contexto las propiedades nutricionales como también los contenidos de minerales, vitaminas y saponina fueron evaluados en las semillas de seis ecotipos chilenos de quínoa, cultivados en las tres principales zonas de producción con condiciones edafoclimáticas distintas: Ancovinto y Cancosa del altiplano del norte, Cáhuil y Faro de la zona costera central y, Regalona y Villarrica en el sur del país. Hubo diferencias significativas (P < 0.05 en todas las propiedades nutricionales de las semillas de todas las zonas. El ecotipo Villarrica tenia el mayor contenido de proteína (16.10 g 100 g-1 MS y de vitamina E y C (4.644 ± 0.240 y 23.065 ± 1.119 mg 100 g-1 MS, respectivamente. El mayor contenido de vitamina B1 (0.648 ± 0.006 mg 100 g-1 MS y B3 (1.569 ± 0.026 mg 100 g-1 MS fue encontrado en el ecotipo Regalona, y el mayor contenido de vitamina B2 (0.081 ± 0.002 mg 100 g-1 MS en el ecotipo Ancovinto. El K fue el mineral más abundante con un valor de 2325.56 mg 100 g-1 MS en el ecotipo Cancosa. El contenido de saponina fluctuó entre 0.84 g 100 g-1 MS en el ecotipo Villarrica y 3.91 g 100 g-1 MS en el ecotipo Cáhuil. Hubo diferencias significativas entre los ecotipos chilenos de quínoa cultivados bajo diferentes condiciones climáticas. No obstante, las semillas de quinoa de cualquier

  9. 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.

  10. 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.

  11. 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

  12. WFIRST: Science from Deep Field Surveys

    Science.gov (United States)

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

    2018-01-01

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

  13. Deep Learning and Its Applications in Biomedicine.

    Science.gov (United States)

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

    2018-02-01

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

  14. The deep lymphatic anatomy of the hand.

    Science.gov (United States)

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

    2018-04-03

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

  15. 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.

  16. 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...

  17. 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...

  18. 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

  19. 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).

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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'

  6. 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.

  7. 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.

  8. 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

  9. 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...

  10. 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.

  11. 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...

  12. 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...

  13. 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.

  14. 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,...

  15. 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

  16. 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.

  17. 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

  18. 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,...

  19. 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

  20. 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

  1. 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.

  2. 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...

  3. 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...

  4. 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...

  5. 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

  6. 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

  7. 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 ...

  8. 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...

  9. 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.

  10. 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...

  11. 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...

  12. 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...

  13. 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

  14. 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...

  15. 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...

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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).

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.)

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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).

  6. 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.

  7. 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)

  8. 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.

  9. 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...

  10. 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...

  11. 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

  12. 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

  13. 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

  14. 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...

  15. 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.

  16. 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

  17. 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 ...

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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/ .

  4. 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.

  5. 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...

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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...

  12. 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.

  13. 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...

  14. 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, $\

  15. 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.)

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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...

  2. 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.)

  3. 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.

  4. 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)

  5. 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

  6. 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…

  7. 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,

  8. 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.

  9. 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

  10. 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

  11. 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)

  12. 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

  13. 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…

  14. 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…

  15. 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.

  16. 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...

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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...

  6. 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...

  7. 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...

  8. 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)

  9. 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...

  10. 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...

  11. 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,

  12. 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.

  13. 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

  14. 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

  15. 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...

  16. 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...

  17. 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 ...

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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....

  5. 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.

  6. 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).

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. 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).

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.)

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. A Moessbauer study of deep sea sediments

    International Nuclear Information System (INIS)

    Minai, Y.; Tominaga, T.; Furuta, T.; Kobayashi, K.

    1981-01-01

    In order to determine the chemical states of iron in deep sea sediments, Moessbauer spectra of the sediments collected from various areas of the Pacific have been measured. The Moessbauer spectra were composed of paramagnetic ferric, high-spin ferrous, and magnetic components. The correlation of their relative abundance to the sampling location and the kind of sediments may afford clues to infer the origin of each iron-bearing phase. (author)

  9. Deep inelastic collisions viewed as Brownian motion

    International Nuclear Information System (INIS)

    Gross, D.H.E.; Freie Univ. Berlin

    1980-01-01

    Non-equilibrium transport processes like Brownian motion, are studied since perhaps 100 years and one should ask why does one not use these theories to explain deep inelastic collision data. These theories have reached a high standard of sophistication, experience, and precision that I believe them to be very usefull for our problem. I will try to sketch a possible form of an advanced theory of Brownian motion that seems to be suitable for low energy heavy ion collisions. (orig./FKS)

  10. Deep electroproduction of exotic hybrid mesons

    International Nuclear Information System (INIS)

    Anikin, I.V.; Pire, B.; Szymanowski, L.; Teryaev, O.V.; Wallon, S.

    2004-01-01

    We evaluate the leading order amplitude for the deep exclusive electroproduction of an exotic hybrid meson in the Bjorken regime. We show that, contrarily to naive expectation, this amplitude factorizes at the twist 2 level and thus scales like usual meson electroproduction when the virtual photon and the hybrid meson are longitudinally polarized. Exotic hybrid mesons may thus be studied in electroproduction experiments at JLAB, HERA (HERMES) or CERN (Compass)

  11. Deep primary production in coastal pelagic systems

    DEFF Research Database (Denmark)

    Lyngsgaard, Maren Moltke; Richardson, Katherine; Markager, Stiig

    2014-01-01

    produced. The primary production (PP) occurring below the surface layer, i.e. in the pycnocline-bottom layer (PBL), is shown to contribute significantly to total PP. Oxygen concentrations in the PBL are shown to correlate significantly with the deep primary production (DPP) as well as with salinity...... that eutrophication effects may include changes in the structure of planktonic food webs and element cycling in the water column, both brought about through an altered vertical distribution of PP....

  12. Environmental studies for deep seabed mining

    Digital Repository Service at National Institute of Oceanography (India)

    Sharma, R.

    tests of prototype mining systems and components in the Pacific Ocean in the seventies (DOMES, 1976). The subsequent progress in the development of mining technology for deep-sea minerals has been slow since 1980 due to unfavorable metal market... assume instead, because commercial system size and type are likely different depending upon the use of nodule elements and can vary with metal market situation. 2. How do we generalize the test parameters from the tow-sled collector and miner...

  13. Deep vein thrombosis: diagnosis, treatment, and prevention

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, W.P.; Youngswick, F.D.

    Deep vein thrombosis (DVT) is a dangerous complication that may present after elective foot surgery. Because of the frequency with which DVT occurs in the elderly patient, as well as in the podiatric surgical population, the podiatrist should be acquainted with this entity. A review of the diagnosis, treatment, prevention, and the role of podiatry in the management of DVT is discussed in this paper.

  14. Deep Learning with Dynamic Computation Graphs

    OpenAIRE

    Looks, Moshe; Herreshoff, Marcello; Hutchins, DeLesley; Norvig, Peter

    2017-01-01

    Neural networks that compute over graph structures are a natural fit for problems in a variety of domains, including natural language (parse trees) and cheminformatics (molecular graphs). However, since the computation graph has a different shape and size for every input, such networks do not directly support batched training or inference. They are also difficult to implement in popular deep learning libraries, which are based on static data-flow graphs. We introduce a technique called dynami...

  15. Critical study of high efficiency deep grinding

    OpenAIRE

    Johnstone, lain

    2002-01-01

    The recent years, the aerospace industry in particular has embraced and actively pursued the development of stronger high performance materials, namely nickel based superalloys and hardwearing steels. This has resulted in a need for a more efficient method of machining, and this need was answered with the advent of High Efficiency Deep Grinding (HEDG). This relatively new process using Cubic Boron Nitride (CBN) electroplated grinding wheels has been investigated through experim...

  16. Young Children in Deep Poverty. Fact Sheet

    Science.gov (United States)

    Ekono, Mercedes; Jiang, Yang; Smith, Sheila

    2016-01-01

    A U.S. family of three living in deep poverty survives on an annual income below $9,276, or less than $9.00 a day per family member. The struggle to raise children on such a meager income is not a rare circumstance among U.S. families, especially those with young children. Currently, 11 percent of young children (0-9 years) live in households with…

  17. Deuteron structure in the deep inelastic regime

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Canal, C.A.; Tarutina, T. [Universidad Nacional de La Plata, IFLP/CONICET y Departamento de Fisica, La Plata (Argentina); Vento, V. [Universidad de Valencia-CSIC, Departamento de Fisica Teorica-IFIC, Burjassot (Valencia) (Spain)

    2017-06-15

    We study nuclear effects in the deuteron in the deep inelastic regime using the newest available data. We put special emphasis on their Q{sup 2} dependence. The study is carried out using a scheme which parameterizes, in a simple manner, these effects by changing the proton and neutron stucture functions in medium. The result of our analysis is compared with other recent proposals. We conclude that precise EMC ratios cannot be obtained without considering the nuclear effects in the deuteron. (orig.)

  18. Deep Inelastic Scattering at the Amplitude Level

    International Nuclear Information System (INIS)

    Brodsky, Stanley J.

    2005-01-01

    The deep inelastic lepton scattering and deeply virtual Compton scattering cross sections can be interpreted in terms of the fundamental wavefunctions defined by the light-front Fock expansion, thus allowing tests of QCD at the amplitude level. The AdS/CFT correspondence between gauge theory and string theory provides remarkable new insights into QCD, including a model for hadronic wavefunctions which display conformal scaling at short distances and color confinement at large distances

  19. Mean associated multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

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

    1982-01-01

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

  20. Microplastic pollution in deep-sea sediments

    International Nuclear Information System (INIS)

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

    2013-01-01

    Microplastics are small plastic particles ( 3 was observed. •The depths from where these microplastics were recovered range from 1176 to 4843 m. •The sizes of the particles range from 75 to 161 μm at their largest cross-section. -- Here, we demonstrate that microplastics have invaded the marine environment to an extent that they appear to even be present in the remote deep sea