A Soluble Fluorescent Binding Assay Reveals PIP2 Antagonism of TREK-1 Channels

Directory of Open Access Journals (Sweden)

Cerrone Cabanos

2017-08-01

Full Text Available Lipid regulation of ion channels by low-abundance signaling lipids phosphatidylinositol 4,5-bisphosphate (PIP2 and phosphatidic acid (PA has emerged as a central cellular mechanism for controlling ion channels and the excitability of nerves. A lack of robust assays suitable for facile detection of a lipid bound to a channel has hampered the probing of the lipid binding sites and measuring the pharmacology of putative lipid agonists for ion channels. Here, we show a fluorescent PIP2 competition assay for detergent-purified potassium channels, including TWIK-1-related K+-channel (TREK-1. Anionic lipids PA and phosphatidylglycerol (PG bind dose dependently (9.1 and 96 μM, respectively and agonize the channel. Our assay shows PIP2 binds with high affinity (0.87 μM but surprisingly can directly antagonize TREK-1 in liposomes. We propose a model for TREK-1 lipid regulation where PIP2 can compete with PA and PG agonism based on the affinity of the lipid for a site within the channel.

Mars Trek: An Interactive Web Portal for Current and Future Missions to Mars

Science.gov (United States)

Law, E.; Day, B.

2017-09-01

NASA's Mars Trek (https://marstrek.jpl.nasa.gov) provides a web-based Portal and a suite of interactive visualization and analysis tools to enable mission planners, lunar scientists, and engineers to access mapped data products from past and current missions to Mars. During the past year, the capabilities and data served by Mars Trek have been significantly expanded beyond its original design as a public outreach tool. At the request of NASA's Science Mission Directorate and Human Exploration Operations Mission Directorate, Mars Trek's technology and capabilities are now being extended to support site selection and analysis activities for the first human missions to Mars.

Mars Trek: An Interactive Web Portal for Current and Future Missions to Mars

Science.gov (United States)

Law, E.; Day, B.

2017-01-01

NASA's Mars Trek (https://marstrek.jpl.nasa.gov) provides a web-based Portal and a suite of interactive visualization and analysis tools to enable mission planners, lunar scientists, and engineers to access mapped data products from past and current missions to Mars. During the past year, the capabilities and data served by Mars Trek have been significantly expanded beyond its original design as a public outreach tool. At the request of NASA's Science Mission Directorate and Human Exploration Operations Mission Directorate, Mars Trek's technology and capabilities are now being extended to support site selection and analysis activities for the first human missions to Mars.

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.

Star Trek, Global Capitalism, and Immaterial Labor

NARCIS (Netherlands)

Hassler-Forest, Dan

2016-01-01

As one of the most expansive storyworlds in sf, Star Trek appears to offer an imaginary representation of a post-capitalist utopia. But in the context of global capitalism the franchise’s superficial post-capitalism translates all too easily into a neoliberal fantasy of post-industrial labour and

Changes in balance and joint position sense during a 12-day high altitude trek: The British Services Dhaulagiri medical research expedition.

Directory of Open Access Journals (Sweden)

Sarah B Clarke

Full Text Available Postural control and joint position sense are essential for safely undertaking leisure and professional activities, particularly at high altitude. We tested whether exposure to a 12-day trek with a gradual ascent to high altitude impairs postural control and joint position sense. This was a repeated measures observational study of 12 military service personnel (28±4 years. Postural control (sway velocity measured by a portable force platform during standing balance, a Sharpened Romberg Test and knee joint position sense were measured, in England (113m elevation and at 3 research camps (3619m, 4600m and 5140m on a 12-day high altitude trek in the Dhaulagiri region of Nepal. Pulse oximetry, and Lake Louise scores were also recorded on the morning and evening of each trek day. Data were compared between altitudes and relationships between pulse oximetry, Lake Louise score, and sway velocity were explored. Total sway velocity during standing balance with eyes open (p = 0.003, d = 1.9 and during Sharpened Romberg test with eyes open (p = 0.007, d = 1.6 was significantly greater at altitudes of 3619m and 5140m when compared with sea level. Anterior-posterior sway velocity during standing balance with eyes open was also significantly greater at altitudes of 3619m and 5140m when compared with sea level (p = 0.001, d = 1.9. Knee joint position sense was not altered at higher altitudes. There were no significant correlations between Lake Louise scores, pulse oximetry and postural sway. Despite a gradual ascent profile, exposure to 3619 m was associated with impairments in postural control without impairment in knee joint position sense. Importantly, these impairments did not worsen at higher altitudes of 4600 m or 5140 m. The present findings should be considered during future trekking expeditions when developing training strategies targeted to manage impairments in postural control that occur with increasing altitude.

Changes in balance and joint position sense during a 12-day high altitude trek: The British Services Dhaulagiri medical research expedition.

Science.gov (United States)

Clarke, Sarah B; Deighton, Kevin; Newman, Caroline; Nicholson, Gareth; Gallagher, Liam; Boos, Christopher J; Mellor, Adrian; Woods, David R; O'Hara, John P

2018-01-01

Postural control and joint position sense are essential for safely undertaking leisure and professional activities, particularly at high altitude. We tested whether exposure to a 12-day trek with a gradual ascent to high altitude impairs postural control and joint position sense. This was a repeated measures observational study of 12 military service personnel (28±4 years). Postural control (sway velocity measured by a portable force platform) during standing balance, a Sharpened Romberg Test and knee joint position sense were measured, in England (113m elevation) and at 3 research camps (3619m, 4600m and 5140m) on a 12-day high altitude trek in the Dhaulagiri region of Nepal. Pulse oximetry, and Lake Louise scores were also recorded on the morning and evening of each trek day. Data were compared between altitudes and relationships between pulse oximetry, Lake Louise score, and sway velocity were explored. Total sway velocity during standing balance with eyes open (p = 0.003, d = 1.9) and during Sharpened Romberg test with eyes open (p = 0.007, d = 1.6) was significantly greater at altitudes of 3619m and 5140m when compared with sea level. Anterior-posterior sway velocity during standing balance with eyes open was also significantly greater at altitudes of 3619m and 5140m when compared with sea level (p = 0.001, d = 1.9). Knee joint position sense was not altered at higher altitudes. There were no significant correlations between Lake Louise scores, pulse oximetry and postural sway. Despite a gradual ascent profile, exposure to 3619 m was associated with impairments in postural control without impairment in knee joint position sense. Importantly, these impairments did not worsen at higher altitudes of 4600 m or 5140 m. The present findings should be considered during future trekking expeditions when developing training strategies targeted to manage impairments in postural control that occur with increasing altitude.

Solar System Treks: Interactive Web Portals or STEM, Exploration and Beyond

Science.gov (United States)

Law, E.; Day, B. H.; Viotti, M.

2017-12-01

NASA's Solar System Treks project produces a suite of online visualization and analysis tools for lunar and planetary mapping and modeling. These portals offer great benefits for education and public outreach, providing access to data from a wide range of instruments aboard a variety of past and current missions. As a component of NASA's STEM Activation Infrastructure, they are available as resources for NASA STEM programs, and to the greater STEM community. As new missions are planned to a variety of planetary bodies, these tools facilitate public understanding of the missions and engage the public in the process of identifying and selecting where these missions will land. There are currently three web portals in the program: Moon Trek (https://moontrek.jpl.nasa.gov), Mars Trek (https://marstrek.jpl.nasa.gov), and Vesta Trek (https://vestatrek.jpl.nasa.gov). A new release of Mars Trek includes new tools and data products focusing on human landing site selection. Backed by evidence-based cognitive and computer science findings, an additional version is available for educational and public audiences in support of earning along novice-to-expert pathways, enabling authentic, real-world interaction with planetary data. Portals for additional planetary bodies are planned. As web-based toolsets, the portals do not require users to purchase or install any software beyond current web browsers. The portals provide analysis tools for measurement and study of planetary terrain. They allow data to be layered and adjusted to optimize visualization. Visualizations are easily stored and shared. The portals provide 3D visualization and give users the ability to mark terrain for generation of STL/OBJ files that can be directed to 3D printers. Such 3D prints are valuable tools in museums, public exhibits, and classrooms - especially for the visually impaired. The program supports additional clients, web services, and APIs facilitating dissemination of planetary data to external

Veganism In Star Trek : A Comic Reformatting Of Plant-Based Space Exploration

OpenAIRE

Tamminen, Tiariia

2017-01-01

My thesis revolves around collecting references to veganism and animal rights in five different science fiction TV series of the Star Trek franchise. I especially concentrate on how the character creation, setting and spoken lines express development and implementation of food technology and ethics. My objective is to show how our relationship to food and animal rights is presented in the main canon of the Star Trek franchise in terms of exploration in space. I will express this further t...

Kinetic properties and adrenergic control of TREK-2-like channels in rat medial prefrontal cortex (mPFC) pyramidal neurons.

Science.gov (United States)

Ładno, W; Gawlak, M; Szulczyk, P; Nurowska, E

2017-06-15

TREK-2-like channels were identified on the basis of electrophysiological and pharmacological tests performed on freshly isolated and enzymatically/mechanically dispersed pyramidal neurons of the rat medial prefrontal cortex (mPFC). Single-channel currents were recorded in cell-attached configuration and the impact of adrenergic receptors (α 1 , α 2 , β) stimulation on spontaneously appearing TREK-2-like channel activity was tested. The obtained results indicate that noradrenaline decreases the mean open probability of TREK-2-like channel currents by activation of β 1 but not of α 1 - and α 2 -adrenergic receptors. Mean open time and channel conductance were not affected. The system of intracellular signaling pathways depends on the activation of protein kinase A. We also show that adrenergic control of TREK-2-like channel currents by adrenergic receptors was similar in pyramidal neurons isolated from young, adolescent, and adult rats. Immunofluorescent confocal scans of mPFC slices confirmed the presence of the TREK-2 protein, which was abundant in layer V pyramidal neurons. The role of TREK-2-like channel control by adrenergic receptors is discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Spadin, a sortilin-derived peptide, targeting rodent TREK-1 channels: a new concept in the antidepressant drug design.

Directory of Open Access Journals (Sweden)

Jean Mazella

2010-04-01

Full Text Available Current antidepressant treatments are inadequate for many individuals, and when they are effective, they require several weeks of administration before a therapeutic effect can be observed. Improving the treatment of depression is challenging. Recently, the two-pore domain potassium channel TREK-1 has been identified as a new target in depression, and its antagonists might become effective antidepressants. In mice, deletion of the TREK-1 gene results in a depression-resistant phenotype that mimics antidepressant treatments. Here, we validate in mice the antidepressant effects of spadin, a secreted peptide derived from the propeptide generated by the maturation of the neurotensin receptor 3 (NTSR3/Sortilin and acting through TREK-1 inhibition. NTSR3/Sortilin interacted with the TREK-1 channel, as shown by immunoprecipitation of TREK-1 and NTSR3/Sortilin from COS-7 cells and cortical neurons co-expressing both proteins. TREK-1 and NTSR3/Sortilin were colocalized in mouse cortical neurons. Spadin bound specifically to TREK-1 with an affinity of 10 nM. Electrophysiological studies showed that spadin efficiently blocked the TREK-1 activity in COS-7 cells, cultured hippocampal pyramidal neurons, and CA3 hippocampal neurons in brain slices. Spadin also induced in vivo an increase of the 5-HT neuron firing rate in the Dorsal Raphe Nucleus. In five behavioral tests predicting an antidepressant response, spadin-treated mice showed a resistance to depression as found in TREK-1 deficient mice. More importantly, an intravenous 4-d treatment with spadin not only induced a strong antidepressant effect but also enhanced hippocampal phosphorylation of CREB protein and neurogenesis, considered to be key markers of antidepressant action after chronic treatment with selective serotonin reuptake inhibitors. This work also shows the development of a reliable method for dosing the propeptide in serum of mice by using AlphaScreen technology. These findings point out

Closeout Report - Search for Time Reversal Symmetry Violation with TREK at J-PARC

Energy Technology Data Exchange (ETDEWEB)

Kohl, Michael [Hampton Univ., VA (United States)

2015-04-15

academic positions. Two former graduate students of the group have graduated and received their PhD degrees in nuclear physics (Dr. Anusha Liyanage and Dr. Ozgur Ates). In particular, this award has enabled Dr. Kohl to pursue the TREK project (Time Reversal Experiment with Kaons) at J-PARC, which he has been leading and advancing as International Spokesperson. Originally proposed as a search for time reversal symmetry violation [6], the project has evolved into a precision test of lepton flavor universality in the Standard Model along with sensitive searches for physics beyond the Standard Model through a possible discovery of new particles such as a sterile neutrino or a neutral gauge boson from the hidden sector in the mass region up to 300 MeV/c2 [7]. Experiment TREK/E36, first proposed in 2010, has been mounted between November 2014 and April 2015, and commissioning with beam has been started in April 2015, with production running anticipated in early summer and late fall 2015. It uses the apparatus from the previous KEK/E-246 experiment with partial upgrades to measure the ratio of decay widths of leptonic two-body decays of the charged kaon to µν and eν, respectively, which is highly sensitive to the ratio of electromagnetic charged lepton couplings and possible new physics processes that could differentiate between μ and e, hence breaking lepton flavor universality of the Standard Model. Through the searches for neutral massive particles, TREK/E36 can severely constrain any new physics scenarios designed to explain the proton radius puzzle [12, 13].

The Role of the Two-Pore Domain Potassium Channel TREK-1 in the Therapeutic Effects of Escitalopram in a Rat Model of Poststroke Depression.

Science.gov (United States)

Lin, Dai-Hua; Zhang, Xiang-Rong; Ye, Dong-Qing; Xi, Guang-Jun; Hui, Jiao-Jie; Liu, Shan-Shan; Li, Lin-Jiang; Zhang, Zhi-Jun

2015-06-01

Poststroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. TREK-1, a two-pore-domain potassium channel, has been implicated in the pathogenesis of stroke and depression. The aim of this study was to investigate whether TREK-1 plays a role in the therapeutic effects of the selective serotonin reuptake inhibitor (SSRI) escitalopram in a rat PSD model. The whole-cell patch-clamp technique was performed to assess the effect of escitalopram on recombinant TREK-1 currents in HEK293 cells. The expression of TREK-1 mRNA and protein was measured in the hippocampus and prefrontal cortex (PFC), and neural stem cell (NSC) proliferation was detected in the hippocampal dentate gyrus (DG) in PSD rats after 3 weeks of escitalopram administration. Escitalopram reversibly inhibited TREK-1 currents in a concentration-dependent manner. Chronic treatment with escitalopram significantly reversed the reductions in weight gain, locomotor activity, and sucrose preference in PSD rats. The expressions of TREK-1 mRNA and protein were significantly increased in hippocampal CA1, CA3, DG, and PFC in PSD rats, with the exception of TREK-1 mRNA in hippocampal CA1. NSC proliferation was significantly decreased in hippocampal DG of PSD rats. Escitalopram significantly reversed the regional increases of TREK-1 expression and the reduction of hippocampal NSC proliferation in PSD rats. TREK-1 plays an important role in the therapeutic effects of the SSRI escitalopram in PSD model, making TREK-1 an attractive candidate molecule for further understanding the pathophysiology and treatment of PSD. © 2015 John Wiley & Sons Ltd.

The Mathematics of "Star Trek"--An Honors Colloquium

Science.gov (United States)

Karls, Michael A.

2011-01-01

After the success of a course on cryptography for a general audience, based on Simon Singh's "The Code Book" [49], I decided to try again and create a mathematics course for a general audience based on "The Physics of Star Trek" by Lawrence Krauss [32]. This article looks at the challenges of designing a physics-based mathematics course "from…

Identification of critical amino acids in the proximal C-terminal of TREK-2 K+ channel for activation by acidic pHi and ATP-dependent inhibition.

Science.gov (United States)

Woo, Joohan; Jun, Young Keul; Zhang, Yin-Hua; Nam, Joo Hyun; Shin, Dong Hoon; Kim, Sung Joon

2018-02-01

TWIK-related two-pore domain K + channels (TREKs) are regulated by intracellular pH (pH i ) and Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P 2 ). Previously, Glu 306 in proximal C-terminal (pCt) of mouse TREK-1 was identified as the pH i -sensing residue. The direction of PI(4,5)P 2 sensitivity is controversial, and we have recently shown that TREKs are inhibited by intracellular ATP via endogenous PI(4,5)P 2 formation. Here we investigate the anionic and cationic residues of pCt for the pH i and ATP-sensitivity in human TREK-2 (hTREK-2). In inside-out patch clamp recordings (I TREK-2,i-o ), acidic pH i -induced activation was absent in E332A and was partly attenuated in E335A. Neutralization of cationic Lys (K330A) also eliminated the acidic pH i sensitivity of I TREK-2,i-o . Unlike the inhibition of wild-type (WT) I TREK-2,i-o by intracellular ATP, neither E332A nor K330A was sensitive to ATP. Nevertheless, exogenous PI(4,5)P 2 (10 μM) abolished I TREK-2 i-o in all the above mutants as well as in WT, indicating unspecific inhibition by exogenous PI(4,5)P 2 . In whole-cell recordings of TREK-2 (I TREK-2,w-c ), K330A and E332A showed higher or fully active basal activity, showing attenuated or insignificant activation by 2-APB, arachidonic acid, or acidic pH e 6.9. I TREK-1,w-c of WT is largely suppressed by pH e 6.9, and the inhibition is slightly attenuated in K312A and E315A. The results show concerted roles of the oppositely charged Lys and Glu in pCt for the ATP-dependent low basal activity and pH i sensitivity.

Fluoxetine protection in decompression sickness in mice is enhanced by blocking TREK-1 potassium channel with the spadin antidepressant.

Directory of Open Access Journals (Sweden)

Nicolas eVallée

2016-02-01

Full Text Available In mice, disseminated coagulation, inflammation and ischemia induce neurological damages that can lead to the death. These symptoms result from circulating bubbles generated by a pathogenic decompression. An acute fluoxetine treatment or the presence of the TREK-1 potassium channel increased the survival rate when mice are subjected to an experimental dive/decompression protocol. This is a paradox because fluoxetine is a blocker of TREK-1 channels. First, we studied the effects of an acute dose of fluoxetine (50mg/kg in wild-type (WT and TREK-1 deficient mice (Knockout homozygous KO and heterozygous HET. Then, we combined the same fluoxetine treatment with a five-day treatment by spadin, in order to specifically block TREK-1 activity (KO-like mice. KO and KO-like mice could be regarded as antidepressed models.167 mice (45 WTcont 46 WTflux 30 HETflux and 46 KOflux constituting the flux-pool and 113 supplementary mice (27 KO-like 24 WTflux2 24 KO-likeflux 21 WTcont2 17 WTno dive constituting the spad-pool were included in this study. Only 7% of KO-TREK-1 treated with fluoxetine (KOflux and 4% of mice treated with both spadin and fluoxetine (KO-likeflux died from decompression sickness (DCS symptoms. These values are much lower than those of WT control (62% or KO-like mice (41%. After the decompression protocol, mice showed a significant consumption of their circulating platelets and leukocytes.Spadin antidepressed mice were more likely to declare DCS. Nevertheless, which had both blocked TREK-1 channel and were treated with fluoxetine were better protected against DCS. We conclude that the protective effect of such an acute dose of fluoxetine is enhanced when TREK-1 is inhibited. We confirmed that antidepressed models may have worse DCS outcomes, but a concomitant fluoxetine treatment not only decreases DCS severity but increases the survival rate.

BARTHESOVA ANALIZA MITOLOGIJE V STAR TREK FILMIH

OpenAIRE

Arcet, Nik

2016-01-01

Temeljni princip magistrske naloge je identificirati in analizirati različne mite v Star Trek filmih, s pomočjo literarne teorije. V nalogi so uporabljene primerjalne, korelacijske in deskriptivne metode raziskovalnega dela. Primarni teoretični vir je zbirka esejev imenovana Mitologije, avtorja Rolanda Barthesa. Teoretični principi opisani v esejih, so bili implicirani v vseh dvanajst znanstveno fantastičnih filmov. Miti so bili analizirani skozi dejanja protagonistov oziroma antagonistov, sk...

Trek and ECCO: Abundance measurements of ultraheavy galactic cosmic rays

International Nuclear Information System (INIS)

Westphal, Andrew J.

2000-01-01

Using the Trek detector, we have measured the abundances of the heaviest elements (with Z>70) in the galactic cosmic rays with sufficient charge resolution to resolve the even-Z elements. We find that the abundance of Pb compared to Pt is ∼3 times lower than the value expected from the most widely-held class of models of the origin of galactic cosmic ray nuclei, that is, origination in a partially ionized medium with solar-like composition. The low abundance of Pb is, however, consistent with the interstellar gas and dust model of Meyer, Drury and Ellison, and with a source enriched in r-process material, proposed by Binns et al. A high-resolution, high-statistics measurement of the abundances of the individual actinides would distinguish between these models. This is the goal of ECCO, the Extremely Heavy Cosmic-ray Composition Observer, which we plan to deploy on the International Space Station

Cardiac response to hypobaric hypoxia: persistent changes in cardiac mass, function, and energy metabolism after a trek to Mt. Everest Base Camp

NARCIS (Netherlands)

Holloway, Cameron J.; Montgomery, Hugh E.; Murray, Andrew J.; Cochlin, Lowri E.; Codreanu, Ion; Hopwood, Naomi; Johnson, Andrew W.; Rider, Oliver J.; Levett, Denny Z. H.; Tyler, Damian J.; Francis, Jane M.; Neubauer, Stefan; Grocott, Michael P. W.; Clarke, Kieran; Grocott, Mike; Montgomery, Hugh; Levett, Denny; Martin, Daniel; Wilson, Mark; Windsor, Jeremy; Luery, Helen; Murray, Andrew; Stroud, Mike; Khosravi, Maryam; Wandrag, Liesl; Holloway, Cameron; Edwards, Lindsay; Ince, Can; Mythen, Monty; Jonas, Max; Imray, Chris; Newman, Stan; Stygal, Jan; Doyle, Patrick; Rodway, George; Howard, David; McMorrow, Roger; Ahuja, Vijay; Aref-Adib, Golnar; Burnham, Richard Dick; Chisholm, Amber; Coates, David; Cook, Debbie; Dhillon, Sundeep; Dougall, Christina; Duncan, Polly; Edsell, Mark; Evans, Lynn; Gardiner, Paul Bugs; Gunning, Paul

2011-01-01

We postulated that changes in cardiac high-energy phosphate metabolism may underlie the myocardial dysfunction caused by hypobaric hypoxia. Healthy volunteers (n=14) were studied immediately before, and within 4 d of return from, a 17-d trek to Mt. Everest Base Camp (5300 m). (31)P magnetic

Popular Imagination and Identity Politics: Reading the Future in "Star Trek: The Next Generation."

Science.gov (United States)

Ott, Brian L.; Aoki, Eric

2001-01-01

Analyzes the television series "Star Trek: The Next Generation." Theorizes the relationship between collective visions of the future and the identity politics of the present. Argues that "The Next Generation" invites audiences to participate in a shared sense of the future that constrains human agency and (re)produces the…

The Great Trek as exodus in J.D. Kestell's and N. Hofmeyr's De ...

African Journals Online (AJOL)

Voor die einde van die negentiende eeu en selfs daarna was die Groot Trek van die agtiendertiger en -veertiger jare 'n herhaaldelike tema in historiese romans. In talle van die romans wat in Nederlands en Afrikaans geskryf is, en in 'n mindere mate ook die wat in Engels verskyn het, is die dapperheid van die Voortrekkers ...

De trek van kruiden van volgroeid wortelmateriaal : handleiding van A tot Z in beknopte vorm

NARCIS (Netherlands)

Wijk, van C.A.P.

2005-01-01

Deze teelthandleiding richt zich op de trek van vooral dragon, krulpeterselie, rucola en munt, uitgaande van wortelmateriaal dat in de vollegrond wordt geteeld. Deze forcering richt zich zowel op aanbod van kruiden in potjes als de meermalige oogst van het gesneden product in een kas of een

Starry white trek: Science fiction and racial discourse

Directory of Open Access Journals (Sweden)

Krstić Predrag

2012-01-01

Full Text Available This article demonstrates that the science fiction’s visions of the future are not exempt from problems of rasism even when openly opposed it. Film and TV Star Trek production is commonly regarded as a significant example of courageous and effective intervention of mass culture on the widespread racial prejudices legitimized by the public policy. Subsequent interpretations, however, in its ‘emancipatory text’ finds smuggled recurrences of the same racial discourse against which it acted, whether it concerns other ‘races’ on Earth or space aliens. A fair interpretation would have to conclude that the white male norm requires effort of its ‘deconstruction’ that would be more extensive then involvement in the program the non-white characters - if we do not want to extend his exclusive and discriminatory rule, in mitigated or disguised form, to the galaxy.

STEM Engagement with NASA's Solar System Treks Portals for Lunar and Planetary Mapping and Modeling

Science.gov (United States)

Law, E. S.; Day, B. H.

2018-01-01

This presentation will provide an overview of the uses and capabilities of NASA's Solar System Treks family of online mapping and modeling portals. While also designed to support mission planning and scientific research, this presentation will focus on the Science, Technology, Engineering, and Math (STEM) engagement and public outreach capabilities of these web based suites of data visualization and analysis tools.

“To boldly go where no series has gone before”. Star Trek - The Original Series in Italia: il linguaggio della tecno-scienza, il doppiaggio, il fandom

Directory of Open Access Journals (Sweden)

Giulia Iannuzzi

2014-12-01

Full Text Available This essay consists of a critical analysis of the Italian dubbing of Star Trek. The Original Series (1966-1969, which was partially translated and shown on Italian television between 1979 and 1981. The study of the dubbing is approached considering translation as a complex cultural phenomenon (drawing on studies such as Even-Zohar and Venuti's, and using the case of Star Trek also as an example of broader phenomena and dynamics, namely the presence of American science fiction series on Italian television, and the difficult relationship in Italy between humanistic and scientific cultures (here, Pierpaolo Antonello's contributions are the milestones, to which the essay attributes the noticeable simplification and flattening the techno-scientific language undergoes during translation in the Star Trek episodes considered. This general tendency to simplify (and even remove technical and scientific terminology in the Italian version can be explained by two main factors: the idea that Italian viewers are less well educated scientifically than Americans, and limited investment (in terms of both financial and professional resources, on the part of the TV channel and dubbing company (TMC and ADC. Both these aspects reveal a perception of a television series as merely a commodity product, typical of the years preceding the current new golden age of American series, but still not unknown in contemporary Italy (as has been shown in other cases, by studies such those by Buonomo, Izzo and Scarpino, and Ranzato. The analysis of the Italian dubbing of Star Trek in the present essay is accompanied by a preliminary overview of the translation and airing of American science fiction series in Italy between the 1950s and the 1970s, and by a survey of the fortunes of these series across different media over the same period. Star Trek, at the center of one the biggest and most profitable contemporary cultural franchises, and one of the most well organized fandoms

pH-sensitive K+ channel TREK-1 is a novel target in pancreatic cancer

DEFF Research Database (Denmark)

Sauter, Daniel Rafael Peter; Sørensen, Christiane Elisabeth; Rapedius, Markus

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and new therapeutic targets are urgently needed. One of the hallmarks of cancer is changed pH-homeostasis and potentially pH-sensors may play an important role in cancer cell behavior. Two-pore potassium channels (K2P) are p...... proliferation and migration indicating that hyperpolarization of Vm attenuates cancer cell behavior. TREK-1 may therefore be a promising novel target for PDAC therapy....

TREK-1 Channel Expression in Smooth Muscle as a Target for Regulating Murine Intestinal Contractility: Therapeutic Implications for Motility Disorders

Directory of Open Access Journals (Sweden)

Ruolin Ma

2018-03-01

Full Text Available Gastrointestinal (GI motility disorders such as irritable bowel syndrome (IBS can occur when coordinated smooth muscle contractility is disrupted. Potassium (K+ channels regulate GI smooth muscle tone and are key to GI tract relaxation, but their molecular and functional phenotypes are poorly described. Here we define the expression and functional roles of mechano-gated K2P channels in mouse ileum and colon. Expression and distribution of the K2P channel family were investigated using quantitative RT-PCR (qPCR, immunohistochemistry and confocal microscopy. The contribution of mechano-gated K2P channels to mouse intestinal muscle tension was studied pharmacologically using organ bath. Multiple K2P gene transcripts were detected in mouse ileum and colon whole tissue preparations. Immunohistochemistry confirmed TREK-1 expression was smooth muscle specific in both ileum and colon, whereas TREK-2 and TRAAK channels were detected in enteric neurons but not smooth muscle. In organ bath, mechano-gated K2P channel activators (Riluzole, BL-1249, flufenamic acid, and cinnamyl 1-3,4-dihydroxy-alpha-cyanocinnamate induced relaxation of KCl and CCh pre-contracted ileum and colon tissues and reduced the amplitude of spontaneous contractions. These data reveal the specific expression of mechano-gated K2P channels in mouse ileum and colon tissues and highlight TREK-1, a smooth muscle specific K2P channel in GI tract, as a potential therapeutic target for combating motility pathologies arising from hyper-contractility.

Solid waste management in Indian Himalayan tourists' treks: a case study in and around the Valley of Flowers and Hemkund Sahib

International Nuclear Information System (INIS)

Kuniyal, Jagdish C.; Jain, Arun P.; Shannigrahi, Ardhendu S.

2003-01-01

Solid waste generation in sensitive tourist areas of the Indian Himalayan region is approaching that of some metro cities of the country. The present study showed ∼288 g waste generation visitor -1 day -1 compared with the nation-wide average of 350 g capita -1 day -1 . About 29 metric tonnes (MT) solid waste is generated along a distance of about 19-km trek (a stretch of land or distance between two or more places covered by a walk) during a 4-month tourist season every year. Treks and trek stalls are the two major places where the visitors generate solid waste. Waste estimated from stalls accounted for about 51% by weight of the total waste generation in the trekking region. The native villagers generally construct stalls every year to meet the requirement of visitors going to Valley of Flowers (VOF) and Hemkund Sahib. The average annual results of 2 years (or equivalent to the average of one, 4-month tourist season for the region) showed non-biodegradable waste (NBW) to be 96.3% by weight whereas biodegradable waste (BW) amounted to merely 3.7%. From management point of view of the government, 96% NBW could easily be reused and recycled. Nevertheless, the need is to manage this waste by bringing it from the trekking areas to the road head (Govind Ghat) first and then to transport it to adjacent recycling centers. Cold drink glass bottles (68%), plastic (26%) and metal (2%) were the major items contributing to non-biodegradable waste. The remaining organic waste could be used as feedstock for composting. A well coordinated effort of public participation is necessary at all the levels for managing waste. There is a need to educate the visitors to instill in them the habit of considering discarded waste as potentially valuable and manageable

Turning the Star Trek Dream into Reality by Understanding Matter & Antimatter

Science.gov (United States)

Hansen, Norm

2002-04-01

People are going to learn all about matter and antimatter. Where matter and antimatter comes from. Where antimatter exists within our solar system. What the Periodic Table of Matter-AntiMatter Elements looks like. What each of the 109 antimatter element's nuclear, physical, and chemical characteristics are. How much energy is produced from matter and antimatter. And what needs to be done to turn the Star Trek Dream into Reality. The Milky Way Galaxy is composed of matter and antimatter. At the center of the galaxy, there are two black holes. One black hole is composed of matter; and the other is antimatter. The black holes are ejecting matter and antimatter into space forming a halo and spiral arms of matter & antimatter stars. The sun is one of the billions of stars that are composed of matter. There are a similar number of antimatter stars. Our Solar System contains the sun, earth, planets, and asteroids that are composed of matter, and comets that are composed of antimatter. When galactic antimatter enters our solar system, the antimatter is called comets. Astronomers have observed hundred of comets orbiting the sun and are finding new comets every year. During the last century, mass destruction has resulted when antimatter collided with Jupiter and Earth. How Humanity deals with the opportunities and dangers of antimatter will determine our destiny. Mankind has known about comets destructive power for thousands of years going back to the days of antiquity. Did comets have anything to do with the disappearance of Atlantis over twelve thousand years ago? We may never know; but is there a similar situation about to take place? Scientists have been studying antimatter by producing, storing, and colliding small quantities at national laboratories for several decades. Symmetry exists between matter and antimatter. Science and Technology provides unlimited opportunities to benefit humanity. Antimatter can be used, as a natural source of energy, to bring every country

Deep Trek Re-configurable Processor for Data Acquisition (RPDA)

Energy Technology Data Exchange (ETDEWEB)

Bruce Ohme; Michael Johnson

2009-06-30

This report summarizes technical progress achieved during the cooperative research agreement between Honeywell and U.S. Department of Energy to develop a high-temperature Re-configurable Processor for Data Acquisition (RPDA). The RPDA development has incorporated multiple high-temperature (225C) electronic components within a compact co-fired ceramic Multi-Chip-Module (MCM) package. This assembly is suitable for use in down-hole oil and gas applications. The RPDA module is programmable to support a wide range of functionality. Specifically this project has demonstrated functional integrity of the RPDA package and internal components, as well as functional integrity of the RPDA configured to operate as a Multi-Channel Data Acquisition Controller. This report reviews the design considerations, electrical hardware design, MCM package design, considerations for manufacturing assembly, test and screening, and results from prototype assembly and characterization testing.

High-Redshift Radio Galaxies from Deep Fields

Indian Academy of Sciences (India)

2016-01-27

Jan 27, 2016 ... High-Redshift Radio Galaxies from Deep Fields ... Here we present results from the deep 150 MHz observations of LBDS-Lynx field, which has been imaged at 327, ... Articles are also visible in Web of Science immediately.

Effect of leucine supplementation on fat free mass with prolonged hypoxic exposure during a 13-day trek to Everest Base Camp: a double-blind randomized study.

Science.gov (United States)

Wing-Gaia, Stacie L; Gershenoff, Dana C; Drummond, Micah J; Askew, E Wayne

2014-03-01

Loss of body weight and fat-free mass (FFM) are commonly noted with prolonged exposure to hypobaric hypoxia. Recent evidence suggests protein supplementation, specifically leucine, may potentially attenuate loss of FFM in subcaloric conditions during normoxia. The purpose of this study was to determine if leucine supplementation would prevent the loss of FFM in subcaloric conditions during prolonged hypoxia. Eighteen physically active male (n = 10) and female (n = 8) trekkers completed a 13-day trek in Nepal to Everest Base Camp with a mean altitude of 4140 m (range 2810-5364 m). In this double-blind study, participants were randomized to ingest either leucine (LEU) (7 g leucine, 93 kcal, 14.5 g whey-based protein) or an isocaloric isonitrogenous control (CON) (0.3 g LEU, 93 kcal, 11.3 g collagen protein) twice daily prior to meals. Body weight, body composition, and circumferences of bicep, thigh, and calf were measured pre- and post-trek. There was a significant time effect for body weight (-2.2% ± 1.7%), FFM (-1.7% ± 1.5%), fat mass (-4.0% ± 6.9%), and circumferences (p FFM (CON -2.1 ± 1.5%; LEU -1.2 ± 1.6%), fat mass (CON -2.9% ± 5.9%; LEU -5.4% ± 8.1%), or circumferences. Although a significant loss of body weight, FFM, and fat mass was noted in 13 days of high altitude exposure, FFM loss was not attenuated by leucine. Future studies are needed to determine if leucine attenuates loss of FFM with longer duration high altitude exposure.

Time-REferenced data Kriging (TREK): mapping hydrological statistics given their time of reference

Science.gov (United States)

Porcheron, Delphine; Leblois, Etienne; Sauquet, Eric

2016-04-01

A major issue in water sciences is to predict runoff parameters at ungauged sites. Estimates can be obtained by various methods. Among them, geostatistical approaches provide interpolation methods that consequently use explicit assumptions on the variable of interest. Geostatistical techniques have been applied to precipitation and temperature fields and later extended to estimate runoff features considered as basin-support variates along the river network (e.g. Gottschalk, 1993; Sauquet et al., 2000; Skoien et al., 2006; Gottschalk et al., 2011). To obtain robust estimations, the first step is to collect a relevant dataset. Sauquet et al. (2000) and Sauquet (2006) suggest including a large number of catchments with long and common observation periods to ensure both reliability and temporal consistency in runoff estimates. However most observation networks evolve with time. Several choices are thus possible to define an optimal reference period maximizing either spatial or temporal overlap. However, the constraints usually lead to discard a significant number of stations. Time-REferenced data Kriging method (TREK) has been developed to overcome this issue. Here is proposed a method of geostatistical estimation considering the temporal support over which a hydrological statistic has been estimated. This allows attenuating the loss of data previously caused by the application of a strict reference period. The time reference remains for the targeted map itself. The weights depend on the observation period of the data included in the dataset and how near this is to the target period. In this presentation, the concepts of TREK will be introduced and thereafter illustrated to map mean annual runoff in France. References Gottschalk, L., 1993, Correlation and covariance of runoff. Stochastic Hydrology and Hydraulics 7(2), 85-101. Sauquet, E., Gottschalk, L. and Leblois, E., 2000, Mapping average annual runoff: a hierarchical approach applying a stochastic interpolation

Defense AT and L. Volume 37, Number 5

Science.gov (United States)

2008-10-01

of the television show Star Trek : Deep Space Nine will immediately recognize the recurring theme of “The Rules of Acquisition.” In the Star Trek ... NASA Titan propellant, and successfully transporting and detonating the first 81,000-pound, first-stage Trident missile motor for the Navy Helping...MANPRINT program. National Aeronautics and Space Administration ( NASA )’s Commercial Technology Office (CTO) http://technology.grc.nasa.gov Promotes

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

Science.gov (United States)

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

2017-04-18

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

Deep shaft high rate aerobic digestion: laboratory and pilot plant performance

Energy Technology Data Exchange (ETDEWEB)

Tran, F; Gannon, D

1981-01-01

The Deep Shaft is essentially an air-lift reactor, sunk deep in the ground (100-160 m); the resulting high hydrostatic pressure together with very efficient mixing in the shaft provide extremely high O transfer efficiencies (O.T.E.) of less than or equal to 90% vs. 4-20% in other aerators. This high O.T.E. suggests real potential for Deep-Shaft technology in the aerobic digestion of sludges and animal wastes: with conventional aerobic digesters an O.T.E. over 8% is extremely difficult to achieve. Laboratory and pilot plant Deep-Shaft aerobic digester studies carried out at Eco-Research's Pointe Claire, Quebec laboratories, and at the Paris, Ontario pilot Deep-Shaft digester are described.

Localized Electron Trap Modification as a Result of Space Weather Exposure in Highly Disordered Insulating Materials

Science.gov (United States)

2017-03-06

produced by Trek Inc. Trek probe model 370 is capable of -3 to 3kV and has an extremely fast, 50µs/kV response to changing surface potentials. Trek probe...This motor can move a Trek 370 surface potential probe (± 3 kV range) and a Faraday cup mounted at opposite ends of a propeller-shaped bracket...Spacecraft Charging, in Reference Publication, 1995, NASA . 35. Horowitz, G., Organic field-effect transistors, Advanced Materials, 1998, 10(5), pp. 365

Deep borehole disposal of high-level radioactive waste.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Freeze, Geoffrey A.; Brady, Patrick Vane; Swift, Peter N.; Rechard, Robert Paul; Arnold, Bill Walter; Kanney, Joseph F.; Bauer, Stephen J.

2009-07-01

Preliminary evaluation of deep borehole disposal of high-level radioactive waste and spent nuclear fuel indicates the potential for excellent long-term safety performance at costs competitive with mined repositories. Significant fluid flow through basement rock is prevented, in part, by low permeabilities, poorly connected transport pathways, and overburden self-sealing. Deep fluids also resist vertical movement because they are density stratified. Thermal hydrologic calculations estimate the thermal pulse from emplaced waste to be small (less than 20 C at 10 meters from the borehole, for less than a few hundred years), and to result in maximum total vertical fluid movement of {approx}100 m. Reducing conditions will sharply limit solubilities of most dose-critical radionuclides at depth, and high ionic strengths of deep fluids will prevent colloidal transport. For the bounding analysis of this report, waste is envisioned to be emplaced as fuel assemblies stacked inside drill casing that are lowered, and emplaced using off-the-shelf oilfield and geothermal drilling techniques, into the lower 1-2 km portion of a vertical borehole {approx}45 cm in diameter and 3-5 km deep, followed by borehole sealing. Deep borehole disposal of radioactive waste in the United States would require modifications to the Nuclear Waste Policy Act and to applicable regulatory standards for long-term performance set by the US Environmental Protection Agency (40 CFR part 191) and US Nuclear Regulatory Commission (10 CFR part 60). The performance analysis described here is based on the assumption that long-term standards for deep borehole disposal would be identical in the key regards to those prescribed for existing repositories (40 CFR part 197 and 10 CFR part 63).

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...

Social network analysis of character interaction in the Stargate and Star Trek television series

Science.gov (United States)

Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

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

Science.gov (United States)

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

2016-04-15

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

Preliminary analyses of the deep geoenvironmental characteristics for the deep borehole disposal of high-level radioactive waste in Korea

Energy Technology Data Exchange (ETDEWEB)

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

2016-06-15

Spent fuels from nuclear power plants, as well as high-level radioactive waste from the recycling of spent fuels, should be safely isolated from human environment for an extremely long time. Recently, meaningful studies on the development of deep borehole radioactive waste disposal system in 3-5 km depth have been carried out in USA and some countries in Europe, due to great advance in deep borehole drilling technology. In this paper, domestic deep geoenvironmental characteristics are preliminarily investigated to analyze the applicability of deep borehole disposal technology in Korea. To do this, state-of-the art technologies in USA and some countries in Europe are reviewed, and geological and geothermal data from the deep boreholes for geothermal usage are analyzed. Based on the results on the crystalline rock depth, the geothermal gradient and the spent fuel types generated in Korea, a preliminary deep borehole concept including disposal canister and sealing system, is suggested.

Preliminary analyses of the deep geoenvironmental characteristics for the deep borehole disposal of high-level radioactive waste in Korea

International Nuclear Information System (INIS)

Lee, Jong Youl; Lee, Min Soo; Choi, Heui Joo; Kim, Geon Young; Kim, Kyung Su

2016-01-01

Spent fuels from nuclear power plants, as well as high-level radioactive waste from the recycling of spent fuels, should be safely isolated from human environment for an extremely long time. Recently, meaningful studies on the development of deep borehole radioactive waste disposal system in 3-5 km depth have been carried out in USA and some countries in Europe, due to great advance in deep borehole drilling technology. In this paper, domestic deep geoenvironmental characteristics are preliminarily investigated to analyze the applicability of deep borehole disposal technology in Korea. To do this, state-of-the art technologies in USA and some countries in Europe are reviewed, and geological and geothermal data from the deep boreholes for geothermal usage are analyzed. Based on the results on the crystalline rock depth, the geothermal gradient and the spent fuel types generated in Korea, a preliminary deep borehole concept including disposal canister and sealing system, is suggested

Changes in appetite, energy intake, body composition, and circulating ghrelin constituents during an incremental trekking ascent to high altitude.

Science.gov (United States)

Matu, Jamie; O'Hara, John; Hill, Neil; Clarke, Sarah; Boos, Christopher; Newman, Caroline; Holdsworth, David; Ispoglou, Theocharis; Duckworth, Lauren; Woods, David; Mellor, Adrian; Deighton, Kevin

2017-09-01

Circulating acylated ghrelin concentrations are associated with altitude-induced anorexia in laboratory environments, but have never been measured at terrestrial altitude. This study examined time course changes in appetite, energy intake, body composition, and ghrelin constituents during a high-altitude trek. Twelve participants [age: 28(4) years, BMI 23.0(2.1) kg m -2 ] completed a 14-day trek in the Himalayas. Energy intake, appetite perceptions, body composition, and circulating acylated, des-acylated, and total ghrelin concentrations were assessed at baseline (113 m, 12 days prior to departure) and at three fixed research camps during the trek (3619 m, day 7; 4600 m, day 10; 5140 m, day 12). Relative to baseline, energy intake was lower at 3619 m (P = 0.038) and 5140 m (P = 0.016) and tended to be lower at 4600 m (P = 0.056). Appetite perceptions were lower at 5140 m (P = 0.027) compared with baseline. Acylated ghrelin concentrations were lower at 3619 m (P = 0.046) and 4600 m (P = 0.038), and tended to be lower at 5140 m (P = 0.070), compared with baseline. Des-acylated ghrelin concentrations did not significantly change during the trek (P = 0.177). Total ghrelin concentrations decreased from baseline to 4600 m (P = 0.045). Skinfold thickness was lower at all points during the trek compared with baseline (P ≤ 0.001) and calf girth decreased incrementally during the trek (P = 0.010). Changes in plasma acylated and total ghrelin concentrations may contribute to the suppression of appetite and energy intake at altitude, but differences in the time course of these responses suggest that additional factors are also involved. Interventions are required to maintain appetite and energy balance during trekking at terrestrial altitudes.

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...

The influence of deep cryogenic treatment on the properties of high-vanadium alloy steel

Energy Technology Data Exchange (ETDEWEB)

Li, Haizhi [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Tong, Weiping, E-mail: wptong@mail.neu.edu.cn [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Cui, Junjun [State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819 (China); Zhang, Hui [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Chen, Liqing [State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819 (China); Zuo, Liang [Key Laboratory for Anisotropy and Texture of Materials (Ministry of Education), School of Materials and Metallurgy, Northeastern University, Shenyang 110819 (China)

2016-04-26

Deep cryogenic treatment can improve the mechanical properties of many metallic materials, but there are few reports of the effect of deep cryogenic treatment on high-vanadium alloy steel. The main objective of this work is to investigate the effect of deep cryogenic treatment on the microstructure, hardness, impact toughness and abrasive wear resistance of high-vanadium alloy steel. The results show that large amounts of small secondary carbide precipitation after deep cryogenic treatment and microcracks were detected and occurred preferentially at carbide/matrix interfaces; except for the hardness, the mechanical properties increased compared to those of the conventional treatment sample. By increasing the deep cryogenic processing time and cycle number, impact toughness and abrasive wear resistance can be further improved, the carbide contents continuously increase, and the hardness decreases.

High-Resolution Ultrasound-Switchable Fluorescence Imaging in Centimeter-Deep Tissue Phantoms with High Signal-To-Noise Ratio and High Sensitivity via Novel Contrast Agents.

Science.gov (United States)

Cheng, Bingbing; Bandi, Venugopal; Wei, Ming-Yuan; Pei, Yanbo; D'Souza, Francis; Nguyen, Kytai T; Hong, Yi; Yuan, Baohong

2016-01-01

For many years, investigators have sought after high-resolution fluorescence imaging in centimeter-deep tissue because many interesting in vivo phenomena-such as the presence of immune system cells, tumor angiogenesis, and metastasis-may be located deep in tissue. Previously, we developed a new imaging technique to achieve high spatial resolution in sub-centimeter deep tissue phantoms named continuous-wave ultrasound-switchable fluorescence (CW-USF). The principle is to use a focused ultrasound wave to externally and locally switch on and off the fluorophore emission from a small volume (close to ultrasound focal volume). By making improvements in three aspects of this technique: excellent near-infrared USF contrast agents, a sensitive frequency-domain USF imaging system, and an effective signal processing algorithm, for the first time this study has achieved high spatial resolution (~ 900 μm) in 3-centimeter-deep tissue phantoms with high signal-to-noise ratio (SNR) and high sensitivity (3.4 picomoles of fluorophore in a volume of 68 nanoliters can be detected). We have achieved these results in both tissue-mimic phantoms and porcine muscle tissues. We have also demonstrated multi-color USF to image and distinguish two fluorophores with different wavelengths, which might be very useful for simultaneously imaging of multiple targets and observing their interactions in the future. This work has opened the door for future studies of high-resolution centimeter-deep tissue fluorescence imaging.

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics

KAUST Repository

Ghoneim, Mohamed T.; Hussain, Muhammad Mustafa

2017-01-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible

High Power Uplink Amplifier for Deep Space Communications, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Critical to the success of delivering on the promise of deep space optical communications is the creation of a stable and reliable high power multichannel optical...

High Power Uplink Amplifier for Deep Space Communications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Critical to the success of delivering on the promise of deep space optical communications is the creation of a stable and reliable high power multichannel optical...

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics

KAUST Repository

Ghoneim, Mohamed T.

2017-02-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible, stretchable, and reconfigurable) electronic systems.

Research of narrow pulse width, high repetition rate, high output power fiber lasers for deep space exploration

Science.gov (United States)

Tang, Yan-feng; Li, Hong-zuo; Wang, Yan; Hao, Zi-qiang; Xiao, Dong-Ya

2013-08-01

As human beings expand the research in unknown areas constantly, the deep space exploration has become a hot research topic all over the world. According to the long distance and large amount of information transmission characteristics of deep space exploration, the space laser communication is the preferred mode because it has the advantages of concentrated energy, good security, and large information capacity and interference immunity. In a variety of laser source, fibre-optical pulse laser has become an important communication source in deep space laser communication system because of its small size, light weight and large power. For fiber lasers, to solve the contradiction between the high repetition rate and the peak value power is an important scientific problem. General Q technology is difficult to obtain a shorter pulse widths, This paper presents a DFB semiconductor laser integrated with Electro-absorption modulator to realize the narrow pulse width, high repetition rate of the seed source, and then using a two-cascaded high gain fiber amplifier as amplification mean, to realize the fibre-optical pulse laser with pulse width 3ns, pulse frequency 200kHz and peak power 1kW. According to the space laser atmospheric transmission window, the wavelength selects for 1.06um. It is adopted that full fibre technology to make seed source and amplification, pumping source and amplification of free-space coupled into fiber-coupled way. It can overcome that fibre lasers are vulnerable to changes in external conditions such as vibration, temperature drift and other factors affect, improving long-term stability. The fiber lasers can be modulated by PPM mode, to realize high rate modulation, because of its peak power, high transmission rate, narrow pulse width, high frequency stability, all technical indexes meet the requirements of the exploration of deep space communication technology.

Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing

Directory of Open Access Journals (Sweden)

Lei Wang

2013-01-01

Full Text Available The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and width of shallow recess. The results indicate that the load capacity, drag torque increases as the depth of shallow recess is shallower and the width ratio (half angle of deep recess versus half angle of shallow recess is smaller. In contrast, the flow rate decreases as the depth of shallow recess is shallower and the width ratio is smaller. Nevertheless, the appropriate design of the depth and width of shallow recess might well induce the performance of high-speed deep/shallow recessed hybrid bearing.

Should the U.S. proceed to consider licensing deep geological disposal of high-level nuclear waste

International Nuclear Information System (INIS)

Curtiss, J.R.

1993-01-01

The United States, as well as other countries facing the question of how to handle high-level nuclear waste, has decided that the most appropriate means of disposal is in a deep geologic repository. In recent years, the Radioactive Waste Management Committee of the Nuclear Energy Agency has developed several position papers on the technical achievability of deep geologic disposal, thus demonstrating the serious consideration of deep geologic disposal in the international community. The Committee has not, as yet, formally endorsed disposal in a deep geologic repository as the preferred method of handling high-level nuclear waste. The United States, on the other hand, has studied the various methods of disposing of high-level nuclear waste, and has determined that deep geologic disposal is the method that should be developed. The purpose of this paper is to present a review of the United States' decision on selecting deep geologic disposal as the preferred method of addressing the high-level waste problem. It presents a short history of the steps taken by the U.S. in determining what method to use, discusses the NRC's waste Confidence Decision, and provides information on other issues in the U.S. program such as reconsideration of the final disposal standard and the growing inventory of spent fuel in storage

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.

Highly efficient deep-blue organic light emitting diode with a carbazole based fluorescent emitter

Science.gov (United States)

Sahoo, Snehasis; Dubey, Deepak Kumar; Singh, Meenu; Joseph, Vellaichamy; Thomas, K. R. Justin; Jou, Jwo-Huei

2018-04-01

High efficiency deep-blue emission is essential to realize energy-saving, high-quality display and lighting applications. We demonstrate here a deep-blue organic light emitting diode using a novel carbazole based fluorescent emitter 7-[4-(diphenylamino)phenyl]-9-(2-ethylhexyl)-9H-carbazole-2-carbonitrile (JV234). The solution processed resultant device shows a maximum luminance above 1,750 cd m-2 and CIE coordinates (0.15,0.06) with a 1.3 lm W-1 power efficiency, 2.0 cd A-1 current efficiency, and 4.1% external quantum efficiency at 100 cd m-2. The resulting deep-blue emission enables a greater than 100% color saturation. The high efficiency may be attributed to the effective host-to-guest energy transfer, suitable device architecture facilitating balanced carrier injection and low doping concentration preventing efficiency roll-off caused by concentration quenching.

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics.

Science.gov (United States)

Ghoneim, Mohamed Tarek; Hussain, Muhammad Mustafa

2017-04-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible, stretchable, and reconfigurable) electronic systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DEEP SPACE: High Resolution VR Platform for Multi-user Interactive Narratives

Science.gov (United States)

Kuka, Daniela; Elias, Oliver; Martins, Ronald; Lindinger, Christopher; Pramböck, Andreas; Jalsovec, Andreas; Maresch, Pascal; Hörtner, Horst; Brandl, Peter

DEEP SPACE is a large-scale platform for interactive, stereoscopic and high resolution content. The spatial and the system design of DEEP SPACE are facing constraints of CAVETM-like systems in respect to multi-user interactive storytelling. To be used as research platform and as public exhibition space for many people, DEEP SPACE is capable to process interactive, stereoscopic applications on two projection walls with a size of 16 by 9 meters and a resolution of four times 1080p (4K) each. The processed applications are ranging from Virtual Reality (VR)-environments to 3D-movies to computationally intensive 2D-productions. In this paper, we are describing DEEP SPACE as an experimental VR platform for multi-user interactive storytelling. We are focusing on the system design relevant for the platform, including the integration of the Apple iPod Touch technology as VR control, and a special case study that is demonstrating the research efforts in the field of multi-user interactive storytelling. The described case study, entitled "Papyrate's Island", provides a prototypical scenario of how physical drawings may impact on digital narratives. In this special case, DEEP SPACE helps us to explore the hypothesis that drawing, a primordial human creative skill, gives us access to entirely new creative possibilities in the domain of interactive storytelling.

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

Science.gov (United States)

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

2016-10-01

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

Cryogenic Impinging Jets Subjected to High Frequency Transverse Acoustic Forcing in a High Pressure Environment

Science.gov (United States)

2016-07-27

generated by a Fluke 292 arbitrary waveform generator. The signal generator was then fed to two Trek PZD2000A high- voltage amplifiers that drove two...Processes of Impinging Jet Injectors,” NASA Propulsion Engineering Research Center, vol. 2, N94-23042, 1993, pp.69-74. 8 Li, R., and Ashgriz...Instability,” NASA SP-194, 1972 V. Appendix A Figure A1. Instantaneous images of an acoustic cycle for the PAN 5 condition. A large group of

Reference design and operations for deep borehole disposal of high-level radioactive waste

International Nuclear Information System (INIS)

Herrick, Courtney Grant; Brady, Patrick Vane; Pye, Steven; Arnold, Bill Walter; Finger, John Travis; Bauer, Stephen J.

2011-01-01

A reference design and operational procedures for the disposal of high-level radioactive waste in deep boreholes have been developed and documented. The design and operations are feasible with currently available technology and meet existing safety and anticipated regulatory requirements. Objectives of the reference design include providing a baseline for more detailed technical analyses of system performance and serving as a basis for comparing design alternatives. Numerous factors suggest that deep borehole disposal of high-level radioactive waste is inherently safe. Several lines of evidence indicate that groundwater at depths of several kilometers in continental crystalline basement rocks has long residence times and low velocity. High salinity fluids have limited potential for vertical flow because of density stratification and prevent colloidal transport of radionuclides. Geochemically reducing conditions in the deep subsurface limit the solubility and enhance the retardation of key radionuclides. A non-technical advantage that the deep borehole concept may offer over a repository concept is that of facilitating incremental construction and loading at multiple perhaps regional locations. The disposal borehole would be drilled to a depth of 5,000 m using a telescoping design and would be logged and tested prior to waste emplacement. Waste canisters would be constructed of carbon steel, sealed by welds, and connected into canister strings with high-strength connections. Waste canister strings of about 200 m length would be emplaced in the lower 2,000 m of the fully cased borehole and be separated by bridge and cement plugs. Sealing of the upper part of the borehole would be done with a series of compacted bentonite seals, cement plugs, cement seals, cement plus crushed rock backfill, and bridge plugs. Elements of the reference design meet technical requirements defined in the study. Testing and operational safety assurance requirements are also defined. Overall

Reference design and operations for deep borehole disposal of high-level radioactive waste.

Energy Technology Data Exchange (ETDEWEB)

Herrick, Courtney Grant; Brady, Patrick Vane; Pye, Steven; Arnold, Bill Walter; Finger, John Travis; Bauer, Stephen J.

2011-10-01

A reference design and operational procedures for the disposal of high-level radioactive waste in deep boreholes have been developed and documented. The design and operations are feasible with currently available technology and meet existing safety and anticipated regulatory requirements. Objectives of the reference design include providing a baseline for more detailed technical analyses of system performance and serving as a basis for comparing design alternatives. Numerous factors suggest that deep borehole disposal of high-level radioactive waste is inherently safe. Several lines of evidence indicate that groundwater at depths of several kilometers in continental crystalline basement rocks has long residence times and low velocity. High salinity fluids have limited potential for vertical flow because of density stratification and prevent colloidal transport of radionuclides. Geochemically reducing conditions in the deep subsurface limit the solubility and enhance the retardation of key radionuclides. A non-technical advantage that the deep borehole concept may offer over a repository concept is that of facilitating incremental construction and loading at multiple perhaps regional locations. The disposal borehole would be drilled to a depth of 5,000 m using a telescoping design and would be logged and tested prior to waste emplacement. Waste canisters would be constructed of carbon steel, sealed by welds, and connected into canister strings with high-strength connections. Waste canister strings of about 200 m length would be emplaced in the lower 2,000 m of the fully cased borehole and be separated by bridge and cement plugs. Sealing of the upper part of the borehole would be done with a series of compacted bentonite seals, cement plugs, cement seals, cement plus crushed rock backfill, and bridge plugs. Elements of the reference design meet technical requirements defined in the study. Testing and operational safety assurance requirements are also defined. Overall

High-throughput verification of transcriptional starting sites by Deep-RACE

DEFF Research Database (Denmark)

Olivarius, Signe; Plessy, Charles; Carninci, Piero

2009-01-01

We present a high-throughput method for investigating the transcriptional starting sites of genes of interest, which we named Deep-RACE (Deep–rapid amplification of cDNA ends). Taking advantage of the latest sequencing technology, it allows the parallel analysis of multiple genes and is free...

Deep Reactive Ion Etching for High Aspect Ratio Microelectromechanical Components

DEFF Research Database (Denmark)

Jensen, Søren; Yalcinkaya, Arda Deniz; Jacobsen, S.

2004-01-01

A deep reactive ion etch (DRIE) process for fabrication of high aspect ratio trenches has been developed. Trenches with aspect ratios exceeding 20 and vertical sidewalls with low roughness have been demonstrated. The process has successfully been used in the fabrication of silicon-on-insulator (SOI...

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

Science.gov (United States)

Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

2017-02-01

The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

Social stakes of the reversibility in the deep storage of high level radioactive wastes

International Nuclear Information System (INIS)

Heriard-Dubreuil, G.; Schieber, C.; Schneider, T.

1998-06-01

This document proposes a study of the conditions which surrounded the reversibility introduction in high activity wastes deep storage at an international scale, as well as a reflexion on the social stakes associated there. In France, the law of december 30, 1991 concerning the research on the radioactive wastes prescribes '' the study of possibilities retrieval or non retrieval storage in deep geological deposits''. The analysis of the reversibility associated social stakes emphasizes the necessity to prevent irreversible consequences, to take care to the choices reversibility, to preserve the future generations autonomy. Thus to elaborate a more satisfactory solution between deep disposal and surface storage, a deep storage, capable of gradually evolution, concept is defined. (A.L.B.)

Dimethylurea/citric acid as a highly efficient deep eutectic solvent

Indian Academy of Sciences (India)

Dimethylurea/citric acid deep eutectic solvent was used as a dual catalyst and a green reaction medium for the efficient synthesis of bis(indolyl)methanes, quinolines and aryl-4, 5-diphenyl-1H-imidazoles. Ease of recovery and reusability of DES with high activity makes this method efficient and eco-friendly.

Inclusive quasielastic and deep inelastic electron scattering at high energies

International Nuclear Information System (INIS)

Day, D.B.

1990-01-01

With high electron energies a kinematic regime can be reached where it will be possible to separate quasielastic and deep inelastic scattering. We present a short description of these processes which dominate the inclusive spectrum. Using the highest momentum transfer data available to guide our estimates, we give the kinematic requirements and the cross sections expected. These results indicate that inclusive scattering at high q has a yet unfilled potential. 18 refs., 13 figs

Southern Ocean Circulation: a High Resolution Examination of the Last Deglaciation from Deep-Sea Corals

Science.gov (United States)

Robinson, L. F.; Li, T.; Chen, T.; Burke, A.; Pegrum Haram, A.; Stewart, J.; Rae, J. W. B.; van de Flierdt, T.; Struve, T.; Wilson, D. J.

2017-12-01

Two decades ago it was first noted that the skeletal remains of deep-sea corals had the potential to provide absolutely dated archives of past ocean conditions. In the intervening twenty years this field has developed to the point where strategic collections and high throughput dating techniques now allow high resolution, well dated records of past deep sea behaviour to be produced. Likewise, efforts to improve understanding of biomineralisation and growth rates are leading to refinements in proxy tools useful for examining circulation, nutrient and carbon cycling, temperature and weathering processes. Deep-sea corals are particularly valuable archives in high latitude regions where radiocarbon-based age models are susceptible to large changes in surface reservoir ages. In this presentation we show new high resolution multiproxy records of the Southern Ocean (Drake Passage) made on U-Th dated corals spanning the last glacial cycle. With more than seventeen hundred reconnaissance ages, and around 200 precise isotope dilution U-Th ages, subtle changes in ocean behaviour can be identified during times of abrupt climate change. The geochemical signature of corals from the deepest sites, closest to modern day Lower Circumpolar Deep Waters, typically show a gradual shift from glacial to Holocene values during deglaciation, likely related to ventilation of the deep ocean. By contrast for the samples collected shallower in the water column (within sites currently bathed by Upper Circumpolar Deep Waters and Antarctic Intermediate and Mode Waters) the evidence points to a more complicated picture. Vertical zonation in the geochemical data suggests that periods of stratification are interspersed with mixing events within the upper 1500m of the water column. At the same time comparison to U-Th dated records from the low latitude Pacific and Atlantic points to an important role for the Southern Ocean in feeding the intermediate waters of both ocean basins throughout the

Deep geologic storage of high level radioactive wastes: conceptual generic designs

International Nuclear Information System (INIS)

1995-01-01

This report summarizes the studies on deep geologic storage of radioactive wastes and specially for the high-level radioactive wastes. The study is focussed to the geotechnical assessment and generic-conceptual designs. Methodology analysis, geotechnical feasibility, costs and operation are studied

High-level radioactive waste disposal in the deep ocean

International Nuclear Information System (INIS)

Hill, H.W.

1977-01-01

A joint programme has begun between the Fisheries Laboratory, Lowestoft and the Institute of Oceanographic Sciences, Wormley to study the dispersion of radioactivity in the deep ocean arising from the possible dumping of high level waste on the sea bed in vitrified-glass form which would permit slow leakage over a long term scale. The programme consists firstly of the development of a simple diffusion/advection model for the dispersion of radioactivity in a closed and finite ocean, which overcomes many of the criticisms of the earlier model proposed by Webb and Morley. Preliminary results from this new model are comparable to those of the Webb-Morley model for radio isotopes with half-lives of 10-300 years but are considerably more restrictive outside this range, particularly for those which are much longer-lived. The second part of the programme, towards which the emphasis is directed, concerns the field programme planned to measure the advection and diffusion parameters in the deeper layers of the ocean to provide realistic input parameters to the model and increase our fundamental understanding of the environment in which the radioactive materials may be released. The first cruises of the programme will take place in late 1976 and involve deep current meter deployments and float dispersion experiments around the present NEA dump site with some sediment sampling, so that adsorption experiments can be started on typical deep sea sediments. The programme will expand the number of long-term deep moored stations over the next five years and include further float experiments, CTD profiling, and other physical oceanography. In the second half of the 5-year programme, attempts will be made to measure diffusion parameters in the deeper layers of the ocean using radioactive tracers

Highly efficient deep ultraviolet generation by sum-frequency mixing ...

Indian Academy of Sciences (India)

Generation of deep ultraviolet radiation at 210 nm by Type-I third harmonic generation is achieved in a pair of BBO crystals with conversion efficiency as high as 36%. The fundamental source is the dye laser radiation pumped by the second harmonic of a Q-switched Nd : YAG laser. A walk-off compensated configuration ...

High levels of natural radionuclides in a deep-sea infaunal xenophyophore

Energy Technology Data Exchange (ETDEWEB)

Swinbanks, D D; Shirayama, Y

1986-03-27

The paper concerns the high levels of natural radionuclides in a deep-sea infaunal xenophyophore from the Izu-Ogasawara Trench. Measured /sup 210/Po activities and barium contents of various parts of Occultammina profunda and the surrounding sediment are given, together with their estimated /sup 210/Pb and /sup 226/Ra activities. The data suggest that xenophyphores are probably subject to unusually high levels of natural radiation.

Deep Boreholes Seals Subjected to High P, T conditions – Preliminary Experimental Studies

Energy Technology Data Exchange (ETDEWEB)

Caporuscio, Florie Andre [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Norskog, Katherine Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Maner, James Lavada [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-01-18

The objective of this planned experimental work is to evaluate physio-chemical processes for ‘seal’ components and materials relevant to deep borehole disposal. These evaluations will encompass multi-laboratory efforts for the development of seals concepts and application of Thermal-Mechanical-Chemical (TMC) modeling work to assess barrier material interactions with subsurface fluids, their stability at high temperatures, and the implications of these processes to the evaluation of thermal limits. Deep borehole experimental work will constrain the Pressure, Temperature (P, T) conditions which “seal” material will experience in deep borehole crystalline rock repositories. The rocks of interest to this study include the silicic (granitic gneiss) end members. The experiments will systematically add components to capture discrete changes in both water and EBS component chemistries.

Where no guideline has gone before: retrospective analysis of resuscitation in the 24th century.

Science.gov (United States)

Hörburger, David; Haslinger, Julia; Bickel, Hubert; Graf, Nikolaus; Schober, Andreas; Testori, Christoph; Weiser, Christoph; Sterz, Fritz; Haugk, Moritz

2014-12-01

Evaluation of the treatment, epidemiology and outcome of cardiac arrest in the television franchise Star Trek. Retrospective cohort study of prospective events. Screening of all episodes of Star Trek: The Next Generation, Star Trek: Deep Space Nine and Star Trek: Voyager for cardiac arrest events. Documentation was performed according to the Utstein guidelines for cardiac arrest documentation. All adult, single person cardiac arrests were included. Patients were excluded if cardiac arrest occurred during mass casualties, if the victims were annihilated by energy weapons or were murdered and nobody besides the assassin could provide first aid. Epidemiological data, treatment and outcome of cardiac arrest victims in the 24th century were studied. Ninety-six cardiac arrests were included. Twenty-three individuals were female (24%). Cardiac arrest was witnessed in 91 cases (95%), trauma was the leading cause (n = 38; 40%). Resuscitation was initiated in 17 cases (18%) and 12 patients (13%) had return of spontaneous circulation. Favorable neurological outcome and long-term survival was documented in nine patients (9%). Technically diagnosed cardiac arrest was associated with higher rates of favorable neurological outcome and long-term survival. Neurological outcome and survival did not depend on cardiac arrest location. Cardiac arrest remains a critical event in the 24th century. We observed a change of etiology from cardiac toward traumatic origin. Quick access to medical help and new prognostic tools were established to treat cardiac arrest.

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

KAUST Repository

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

2013-01-01

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

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

KAUST Repository

Bougouffa, Salim

2013-03-29

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

High efficacy with deep nurse-administered propofol sedation for advanced gastroenterologic endoscopic procedures

DEFF Research Database (Denmark)

Jensen, Jeppe Thue; Hornslet, Pernille; Konge, Lars

2016-01-01

was requested eight times (0.4 %). One patient was intubated due to suspected aspiration. CONCLUSIONS: Intermittent deep NAPS for advanced endoscopies in selected patients provided an almost 100 % success rate. However, the rate of hypoxia, hypotension and respiratory support was high compared with previously......BACKGROUND AND STUDY AIMS: Whereas data on moderate nurse-administered propofol sedation (NAPS) efficacy and safety for standard endoscopy is abundant, few reports on the use of deep sedation by endoscopy nurses during advanced endoscopy, such as Endoscopic Retrograde Cholangiopancreatography (ERCP......) and Endoscopic Ultrasound (EUS) are available and potential benefits or hazards remain unclear. The aims of this study were to investigate the efficacy of intermittent deep sedation with propofol for a large cohort of advanced endoscopies and to provide data on the safety. PATIENTS AND METHODS: All available...

Final LDRD report : science-based solutions to achieve high-performance deep-UV laser diodes.

Energy Technology Data Exchange (ETDEWEB)

Armstrong, Andrew M.; Miller, Mary A.; Crawford, Mary Hagerott; Alessi, Leonard J.; Smith, Michael L.; Henry, Tanya A.; Westlake, Karl R.; Cross, Karen Charlene; Allerman, Andrew Alan; Lee, Stephen Roger

2011-12-01

We present the results of a three year LDRD project that has focused on overcoming major materials roadblocks to achieving AlGaN-based deep-UV laser diodes. We describe our growth approach to achieving AlGaN templates with greater than ten times reduction of threading dislocations which resulted in greater than seven times enhancement of AlGaN quantum well photoluminescence and 15 times increase in electroluminescence from LED test structures. We describe the application of deep-level optical spectroscopy to AlGaN epilayers to quantify deep level energies and densities and further correlate defect properties with AlGaN luminescence efficiency. We further review our development of p-type short period superlattice structures as an approach to mitigate the high acceptor activation energies in AlGaN alloys. Finally, we describe our laser diode fabrication process, highlighting the development of highly vertical and smooth etched laser facets, as well as characterization of resulting laser heterostructures.

High-speed railway real-time localization auxiliary method based on deep neural network

Science.gov (United States)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments

KAUST Repository

Wang, Yong; Yang, Jiang Ke; Lee, On On; Li, Tie Gang; Al-Suwailem, Abdulaziz M.; Danchin, Antoine; Qian, Pei-Yuan

2011-01-01

The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers) of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed. © 2011 Wang et al.

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments

KAUST Repository

Wang, Yong

2011-12-21

The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers) of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed. © 2011 Wang et al.

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments.

Directory of Open Access Journals (Sweden)

Yong Wang

Full Text Available The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed.

High temperature annealing effects on deep-level defects in a high purity semi-insulating 4H-SiC substrate

Energy Technology Data Exchange (ETDEWEB)

Iwamoto, Naoya, E-mail: naoya.iwamoto@smn.uio.no; Azarov, Alexander; Svensson, Bengt G. [Department of Physics, Center for Materials Science and Nanotechnology, University of Oslo, P.O. Box 1048 Blindern, N-0316 Oslo (Norway); Ohshima, Takeshi [Japan Atomic Energy Agency, 1233 Watanuki, Takasaki, 370-1292 Gunma (Japan); Moe, Anne Marie M. [Washington Mills AS, N-7300 Orkanger (Norway)

2015-07-28

Effects of high-temperature annealing on deep-level defects in a high-purity semi-insulating 4H silicon carbide substrate have been studied by employing current-voltage, capacitance-voltage, junction spectroscopy, and chemical impurity analysis measurements. Secondary ion mass spectrometry data reveal that the substrate contains boron with concentration in the mid 10{sup 15 }cm{sup −3} range, while other impurities including nitrogen, aluminum, titanium, vanadium and chromium are below their detection limits (typically ∼10{sup 14 }cm{sup −3}). Schottky barrier diodes fabricated on substrates annealed at 1400–1700 °C exhibit metal/p-type semiconductor behavior with a current rectification of up to 8 orders of magnitude at bias voltages of ±3 V. With increasing annealing temperature, the series resistance of the Schottky barrier diodes decreases, and the net acceptor concentration in the substrates increases approaching the chemical boron content. Admittance spectroscopy results unveil the presence of shallow boron acceptors and deep-level defects with levels in lower half of the bandgap. After the 1400 °C annealing, the boron acceptor still remains strongly compensated at room temperature by deep donor-like levels located close to mid-gap. However, the latter decrease in concentration with increasing annealing temperature and after 1700 °C, the boron acceptor is essentially uncompensated. Hence, the deep donors are decisive for the semi-insulating properties of the substrates, and their thermal evolution limits the thermal budget for device processing. The origin of the deep donors is not well-established, but substantial evidence supporting an assignment to carbon vacancies is presented.

Superconducting Nanowire Single Photon Detectors for High-Data-Rate Deep-Space Optical Communication

Data.gov (United States)

National Aeronautics and Space Administration — High data rate deep space optical communication (DSOC) links for manned and unmanned space exploration have been identified by NASA as a critical future capability,...

Fusion of shallow and deep features for classification of high-resolution remote sensing images

Science.gov (United States)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

Deep eutectic solvents for highly efficient separations in oil and gas industries

NARCIS (Netherlands)

Warrag, S.E.E.; Peters, C.J.; Kroon, M.C.

2017-01-01

Deep eutectic solvents (DESs) have captured a great scientific attention as a new, ‘green’ and sustainable class of tailor-made solvents. DESs share many properties with ionic liquids (ILs) including low vapor pressure, wide liquid range, thermal stability, low flammability, and high solvation

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

Directory of Open Access Journals (Sweden)

Yunlong Yu

2018-01-01

Full Text Available One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

Science.gov (United States)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging

Numerical investigation of high level nuclear waste disposal in deep anisotropic geologic repositories

KAUST Repository

Salama, Amgad; El Amin, Mohamed F.; Sun, Shuyu

2015-01-01

One of the techniques that have been proposed to dispose high level nuclear waste (HLW) has been to bury them in deep geologic formations, which offer relatively enough space to accommodate the large volume of HLW accumulated over the years since

MBARI Mapping AUV: A High-Resolution Deep Ocean Seafloor Mapping Capability

Science.gov (United States)

Caress, D. W.; Kirkwood, W. J.; Thomas, H.; McEwen, R.; Henthorn, R.; McGill, P.; Thompson, D.; Sibenac, M.; Jensen, S.; Shane, F.; Hamilton, A.

2005-05-01

The Monterey Bay Aquarium Research Institute (MBARI) is developing an autonomous seafloor mapping capability for deep ocean science applications. The MBARI Mapping AUV is a 0.53 m (21 in) diameter, 5.1 m (16.7 ft) long, Dorado-class vehicle designed to carry four mapping sonars. The primary sensor is a 200 kHz multibeam sonar producing swath bathymetry and sidescan. In addition, the vehicle carries 100 kHz and 410 kHz chirp sidescan sonars, and a 2-16 kHz sweep chirp subbottom profiler. Navigation and attitude data are obtained from an inertial navigation system (INS) incorporating a ring laser gyro and a 300 kHz Doppler velocity log (DVL). The vehicle also includes acoustic modem, ultra-short baseline navigation, and long-baseline navigation systems. The Mapping AUV is powered by 6 kWhr of Li-polymer batteries, providing expected mission duration of 12 hours at a typical speed of 1.5 m/s. All components of the vehicle are rated to 6000 m depth, allowing MBARI to conduct high-resolution mapping of the deep-ocean seafloor. The sonar package is also be mountable on ROV Ventana, allowing surveys at altitudes less than 20 m at topographically challenging sites. The vehicle was assembled and extensively tested during 2004; this year we are commencing operations for MBARI science projects while continuing the process of testing and integrating the complete suite of sensors and systems. MBARI is beginning to use this capability to observe the changing morphology of dynamic systems such as submarine canyons and active slumps, to map deep-water benthic habitats at resolutions comparable to ROV and submersible observations, to provide basemaps for ROV dives, and to provide high resolution bathymetry and subbottom profiles as part of a variety of projects requiring knowledge of the seafloor. We will present initial results from surveys in and around Monterey Canyon, including high resolution repeat surveys of four sites along the canyon axis.

Structure functions and parton distributions in deep inelastic lepton-hadron scattering at high energies

International Nuclear Information System (INIS)

Bluemlein, J.

1993-08-01

The possibilities to measure structure functions, to extract parton distributions, and to measure α s and Λ QCD in current and future high energy deep inelastic scattering experiments are reviewed. A comparison is given for experiments at HERA, an ep option at LEP xLHC, and a high energy neutrino experiment. (orig.)

Effectiveness of deep cleaning followed by hydrogen peroxide decontamination during high Clostridium difficile infection incidence.

Science.gov (United States)

Best, E L; Parnell, P; Thirkell, G; Verity, P; Copland, M; Else, P; Denton, M; Hobson, R P; Wilcox, M H

2014-05-01

Clostridium difficile infection (CDI) remains an infection control challenge, especially when environmental spore contamination and suboptimal cleaning may increase transmission risk. To substantiate the long-term effectiveness throughout a stroke rehabilitation unit (SRU) of deep cleaning and hydrogen peroxide decontamination (HPD), following a high incidence of CDI. Extensive environmental sampling (342 sites on each occasion) for C. difficile using sponge wipes was performed: before and after deep cleaning with detergent/chlorine agent; immediately following HPD; and on two further occasions, 19 days and 20 weeks following HPD. C. difficile isolates underwent polymerase chain reaction ribotyping and multi-locus variable repeat analysis (MLVA). C. difficile was recovered from 10.8%, 6.1%, 0.9%, 0% and 3.5% of sites at baseline, following deep cleaning, immediately after HPD, and 19 days and 20 weeks after HPD, respectively. C. difficile ribotypes recovered after deep cleaning matched those from CDI cases in the SRU during the previous 10 months. Similarly, 10/12 of the positive sites identified at 20 weeks post-HPD harboured the same C. difficile ribotype (002) and MLVA pattern as the isolate from the first post-HPD CDI case. CDI incidence [number of cases on SRU per 10 months (January-October 2011)] declined from 20 before to seven after the intervention. HPD, after deep cleaning with a detergent/chlorine agent, was highly effective for removing environmental C. difficile contamination. Long-term follow-up demonstrated that a CDI symptomatic patient can rapidly recontaminate the immediate environment. Determining a role for HPD should include long-term cost-effectiveness evaluations. Copyright © 2014 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

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

Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning

Science.gov (United States)

Sagun, Levent

This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would

Offline High pH Reversed-Phase Peptide Fractionation for Deep Phosphoproteome Coverage

DEFF Research Database (Denmark)

Batth, Tanveer S; Olsen, Jesper V

2016-01-01

Protein phosphorylation, a process in which kinases modify serines, threonines, and tyrosines with phosphoryl groups is of major importance in eukaryotic biology. Protein phosphorylation events are key initiators of signaling responses which determine cellular outcomes after environmental...... and metabolic stimuli, and are thus highly regulated. Therefore, studying the mechanism of regulation by phosphorylation, and pinpointing the exact site of phosphorylation on proteins is of high importance. This protocol describes in detail a phosphoproteomics workflow for ultra-deep coverage by fractionating...

miRBase: annotating high confidence microRNAs using deep sequencing data.

Science.gov (United States)

Kozomara, Ana; Griffiths-Jones, Sam

2014-01-01

We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.

Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

Directory of Open Access Journals (Sweden)

Yongyang Xu

2018-01-01

Full Text Available Very high resolution (VHR remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.

Medium Deep High Temperature Heat Storage

Science.gov (United States)

Bär, Kristian; Rühaak, Wolfram; Schulte, Daniel; Welsch, Bastian; Chauhan, Swarup; Homuth, Sebastian; Sass, Ingo

2015-04-01

Heating of buildings requires more than 25 % of the total end energy consumption in Germany. Shallow geothermal systems for indirect use as well as shallow geothermal heat storage systems like aquifer thermal energy storage (ATES) or borehole thermal energy storage (BTES) typically provide low exergy heat. The temperature levels and ranges typically require a coupling with heat pumps. By storing hot water from solar panels or thermal power stations with temperatures of up to 110 °C a medium deep high temperature heat storage (MDHTS) can be operated on relatively high temperature levels of more than 45 °C. Storage depths of 500 m to 1,500 m below surface avoid conflicts with groundwater use for drinking water or other purposes. Permeability is typically also decreasing with greater depth; especially in the crystalline basement therefore conduction becomes the dominant heat transport process. Solar-thermal charging of a MDHTS is a very beneficial option for supplying heat in urban and rural systems. Feasibility and design criteria of different system configurations (depth, distance and number of BHE) are discussed. One system is designed to store and supply heat (300 kW) for an office building. The required boreholes are located in granodioritic bedrock. Resulting from this setup several challenges have to be addressed. The drilling and completion has to be planned carefully under consideration of the geological and tectonical situation at the specific site.

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

Science.gov (United States)

Wei, Lu; Zhu, Xinxin; Chen, Zhixing; Min, Wei

2014-02-01

Two-photon excited fluorescence microscopy (TPFM) offers the highest penetration depth with subcellular resolution in light microscopy, due to its unique advantage of nonlinear excitation. However, a fundamental imaging-depth limit, accompanied by a vanishing signal-to-background contrast, still exists for TPFM when imaging deep into scattering samples. Formally, the focusing depth, at which the in-focus signal and the out-of-focus background are equal to each other, is defined as the fundamental imaging-depth limit. To go beyond this imaging-depth limit of TPFM, we report a new class of super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging, including multiphoton activation and imaging (MPAI) harnessing novel photo-activatable fluorophores, stimulated emission reduced fluorescence (SERF) microscopy by adding a weak laser beam for stimulated emission, and two-photon induced focal saturation imaging with preferential depletion of ground-state fluorophores at focus. The resulting image contrasts all exhibit a higher-order (third- or fourth- order) nonlinear signal dependence on laser intensity than that in the standard TPFM. Both the physical principles and the imaging demonstrations will be provided for each super-nonlinear microscopy. In all these techniques, the created super-nonlinearity significantly enhances the imaging contrast and concurrently extends the imaging depth-limit of TPFM. Conceptually different from conventional multiphoton processes mediated by virtual states, our strategy constitutes a new class of fluorescence microscopy where high-order nonlinearity is mediated by real population transfer.

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

Science.gov (United States)

Pang, Bo; Becker, Frank

2017-04-28

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

Precision-cut liver slices to investigate responsiveness of deep-sea fish to contaminants at high pressure.

Science.gov (United States)

Lemaire, Benjamin; Debier, Cathy; Calderon, Pedro Buc; Thomé, Jean Pierre; Stegeman, John; Mork, Jarle; Rees, Jean François

2012-09-18

While deep-sea fish accumulate high levels of persistent organic pollutants (POPs), the toxicity associated with this contamination remains unknown. Indeed, the recurrent collection of moribund individuals precludes experimental studies to investigate POP effects in this fauna. We show that precision-cut liver slices (PCLS), an in vitro tool commonly used in human and rodent toxicology, can overcome such limitation. This technology was applied to individuals of the deep-sea grenadier Coryphaenoides rupestris directly upon retrieval from 530-m depth in Trondheimsfjord (Norway). PCLS remained viable and functional for 15 h when maintained in an appropriate culture media at 4 °C. This allowed experimental exposure of liver slices to the model POP 3-methylcholanthrene (3-MC; 25 μM) at levels of hydrostatic pressure mimicking shallow (0.1 megapascal or MPa) and deep-sea (5-15 MPa; representative of 500-1500 m depth) environments. As in shallow water fish, 3-MC induced the transcription of the detoxification enzyme cytochrome P4501A (CYP1A; a biomarker of exposure to POPs). This induction was diminished at elevated pressure, suggesting a limited responsiveness of C. rupestris toward POPs in its native environment. This very first in vitro toxicological investigation on a deep-sea fish opens the route for understanding pollutants effects in this highly exposed fauna.

High-speed rupture during the initiation of the 2015 Bonin Islands deep earthquake

Science.gov (United States)

Zhan, Z.; Ye, L.; Shearer, P. M.; Lay, T.; Kanamori, H.

2015-12-01

Among the long-standing questions on how deep earthquakes rupture, the nucleation phase of large deep events is one of the most puzzling parts. Resolving the rupture properties of the initiation phase is difficult to achieve with far-field data because of the need for accurate corrections for structural effects on the waveforms (e.g., attenuation, scattering, and site effects) and alignment errors. Here, taking the 2015 Mw 7.9 Bonin Islands earthquake (depth = 678 km) as an example, we jointly invert its far-field P waves at multiple stations for the average rupture speed during the first second of the event. We use waveforms from a closely located aftershock as empirical Green's functions, and correct for possible differences in focal mechanisms and waveform misalignments with an iterative approach. We find that the average initial rupture speed is over 5 km/s, significantly higher than the average rupture speed of 3 km/s later in the event. This contrast suggests that rupture speeds of deep earthquakes can be highly variable during individual events and may define different stages of rupture, potentially with different mechanisms.

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.

Deep Borehole Disposal as an Alternative Concept to Deep Geological Disposal

Energy Technology Data Exchange (ETDEWEB)

Lee, Jongyoul; Lee, Minsoo; Choi, Heuijoo; Kim, Kyungsu [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

In this paper, the general concept and key technologies for deep borehole disposal of spent fuels or HLW, as an alternative method to the mined geological disposal method, were reviewed. After then an analysis on the distance between boreholes for the disposal of HLW was carried out. Based on the results, a disposal area were calculated approximately and compared with that of mined geological disposal. These results will be used as an input for the analyses of applicability for DBD in Korea. The disposal safety of this system has been demonstrated with underground research laboratory and some advanced countries such as Finland and Sweden are implementing their disposal project on commercial stage. However, if the spent fuels or the high-level radioactive wastes can be disposed of in the depth of 3-5 km and more stable rock formation, it has several advantages. Therefore, as an alternative disposal concept to the mined deep geological disposal concept (DGD), very deep borehole disposal (DBD) technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general concept of deep borehole disposal for spent fuels or high level radioactive wastes was reviewed. And the key technologies, such as drilling technology of large diameter borehole, packaging and emplacement technology, sealing technology and performance/safety analyses technologies, and their challenges in development of deep borehole disposal system were analyzed. Also, very preliminary deep borehole disposal concept including disposal canister concept was developed according to the nuclear environment in Korea.

Deep Borehole Disposal as an Alternative Concept to Deep Geological Disposal

International Nuclear Information System (INIS)

Lee, Jongyoul; Lee, Minsoo; Choi, Heuijoo; Kim, Kyungsu

2016-01-01

In this paper, the general concept and key technologies for deep borehole disposal of spent fuels or HLW, as an alternative method to the mined geological disposal method, were reviewed. After then an analysis on the distance between boreholes for the disposal of HLW was carried out. Based on the results, a disposal area were calculated approximately and compared with that of mined geological disposal. These results will be used as an input for the analyses of applicability for DBD in Korea. The disposal safety of this system has been demonstrated with underground research laboratory and some advanced countries such as Finland and Sweden are implementing their disposal project on commercial stage. However, if the spent fuels or the high-level radioactive wastes can be disposed of in the depth of 3-5 km and more stable rock formation, it has several advantages. Therefore, as an alternative disposal concept to the mined deep geological disposal concept (DGD), very deep borehole disposal (DBD) technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general concept of deep borehole disposal for spent fuels or high level radioactive wastes was reviewed. And the key technologies, such as drilling technology of large diameter borehole, packaging and emplacement technology, sealing technology and performance/safety analyses technologies, and their challenges in development of deep borehole disposal system were analyzed. Also, very preliminary deep borehole disposal concept including disposal canister concept was developed according to the nuclear environment in Korea

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.

New High Pressure Phase of CaCO3: Implication for the Deep Diamond Formation

Science.gov (United States)

Mao, Z.; Li, X.; Zhang, Z.; Lin, J. F.; Ni, H.; Prakapenka, V.

2017-12-01

Surface carbon can be transported to the Earth's deep interior through sinking subduction slabs. Carbonates, including CaCO3, MgCO3 and MgCa(CO3)2, are important carbon carriers for the deep carbon cycle. Experimental studies on the phase stability of carbonates with coexisting mantle minerals at relevant pressure and temperature conditions are thus important for understanding the deep carbon cycle. In particular, recent petrological studies have revealed the evidence for the transportation of CaCO3 to the depth at least of the top lower mantle by analyzing the diamond inclusions. Yet the phase stability of CaCO3 at relevant pressure and temperature conditions of the top lower mantle is still unclear. Previous single-crystal study has shown that CaCO3 transforms from the CaCO3-III structure to CaCO3-VI at 15 GPa and 300 K. The CaCO3-VI is stable at least up to 40 GPa at 300 K. At high temperatures, CaCO3 in the aragonite structure will directly transform into the post-aragonite structure at 40 GPa. However, a recent theoretical study predicted a new phase of CaCO3 with a space group of P21/c between 32 and 48 GPa which is different from previous experimental results. In this study, we have investigated the phase stability of CaCO3 at high pressure-temperature conditions using synchrotron X-ray diffraction in laser-heated diamond anvil cells. We report the discovery of a new phase of CaCO3 at relevant pressure-temperature conditions of the top lower mantle which is consistent with previous theoretical predictions. This new phase is an important carrier for the transportation of carbon to the Earth's lower mantle and crucial for growing deep diamonds in the region.

High energy deep inelastic scattering in perturbative quantum chromodynamics

International Nuclear Information System (INIS)

Wallon, S.

1996-01-01

In this PhD thesis, we deal with high energy Deep Inelastic Scattering in Perturbative Quantum Chromodynamics (QCD). In this work, two main topics are emphasized: The first one deals with dynamics based on perturbative renormalization group, and on perturbative Regge approaches. We discuss the applicability of these predictions, the possibility of distinguishing them in the HERA experiments, and their unification. We prove that the perturbative Regge dynamic can be successfully applied to describe the HERA data. Different observables are proposed for distinguishing these two approaches. We show that these two predictions can be unified in a system of equations. In the second one, unitarization and saturation problems in high energy QCD are discussed. In the multi-Regge approach, equivalent to the integrable one-dimensional XXX Heisenberg spin chain, we develop methods in order to solve this system, based on the Functional Bethe Ansatz. In the dipole model context, we propose a new formulation of unitarity and saturation effects, using Wilson loops. (author)

Deep Reactive Ion Etching (DRIE) of High Aspect Ratio SiC Microstructures using a Time-Multiplexed Etch-Passivate Process

Science.gov (United States)

Evans, Laura J.; Beheim, Glenn M.

2006-01-01

High aspect ratio silicon carbide (SiC) microstructures are needed for microengines and other harsh environment micro-electro-mechanical systems (MEMS). Previously, deep reactive ion etching (DRIE) of low aspect ratio (AR less than or = 1) deep (greater than 100 micron) trenches in SiC has been reported. However, existing DRIE processes for SiC are not well-suited for definition of high aspect ratio features because such simple etch-only processes provide insufficient control over sidewall roughness and slope. Therefore, we have investigated the use of a time-multiplexed etch-passivate (TMEP) process, which alternates etching with polymer passivation of the etch sidewalls. An optimized TMEP process was used to etch high aspect ratio (AR greater than 5) deep (less than 100 micron) trenches in 6H-SiC. Power MEMS structures (micro turbine blades) in 6H-SiC were also fabricated.

Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

Directory of Open Access Journals (Sweden)

Rui Guo

2018-03-01

Full Text Available Considering the classification of high spatial resolution remote sensing imagery, this paper presents a novel classification method for such imagery using deep neural networks. Deep learning methods, such as a fully convolutional network (FCN model, achieve state-of-the-art performance in natural image semantic segmentation when provided with large-scale datasets and respective labels. To use data efficiently in the training stage, we first pre-segment training images and their labels into small patches as supplements of training data using graph-based segmentation and the selective search method. Subsequently, FCN with atrous convolution is used to perform pixel-wise classification. In the testing stage, post-processing with fully connected conditional random fields (CRFs is used to refine results. Extensive experiments based on the Vaihingen dataset demonstrate that our method performs better than the reference state-of-the-art networks when applied to high-resolution remote sensing imagery classification.

submitter Accelerating high-energy physics exploration with deep learning

CERN Document Server

Ojika, Dave; Gordon-Ross, Ann; Carnes, Andrew; Gleyzer, Sergei

2017-01-01

In this work, we present our approach to using deep learning for identification of rarely produced physics particles (such as the Higgs Boson) out of a majority of uninteresting, background or noise-dominated data. A fast and efficient system to eliminate uninteresting data would result in much less data being stored, thus significantly reducing processing time and storage requirements. In this paper, we present a generalized preliminary version of our approach to motivate research interest in advancing the state-of-the-art in deep learning networks for other applications that can benefit from learning systems.

Plan of deep underground construction for investigations on high-level radioactive waste storage

International Nuclear Information System (INIS)

Mayanovskij, M.S.

1996-01-01

The program of studies of the Japanese PNC corporation on construction of deep underground storage for high-level radioactive wastes is presented. The program is intended for 20 years. The total construction costs equal about 20 billion yen. The total cost of the project is equal to 60 billion yen. The underground part is planned to reach 1000 m depth

High-Efficiency, High-Power Laser Transmitter for Deep-Space Communication, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — There is demand for vastly improved deep space satellite communications links. As data rates dramatically increase due to new sensor technologies and the desire to...

Estimating the Economic Impacts of a Small-Scale Sport Tourism Event: The Case of the Italo-Swiss Mountain Trail CollonTrek

Directory of Open Access Journals (Sweden)

Stefano Duglio

2017-02-01

Full Text Available Evidence from several studies shows that small-scale sport events may have more positive repercussions for the host community than major ones in terms of both economic and social impacts. This study estimates the economic impacts on a small community derived from athletes’ expenditure at a specific small-scale sport tourism event, the Italo-Swiss mountain endurance trail CollonTrek. Even if this kind of event is considered a minor sport event, generating very limited economic activity, this study supports the hypothesis that the funds invested by the public administration are compensated for by revenue generated during the trail. In fact, according to the three analyzed scenarios (Conservative, Average and Liberal, for each euro invested by the public administration, an economic return between €17.62 and €18.92 has been estimated, and between €5.64 and €6.9 (32%–36.47% represent the direct economic return for the local community. Furthermore, in addition to the direct economic benefits, in accordance with the feedback from a sample of participants at the event (n = 180, this kind of event has positive implications in terms of future tourism for the host valley, pointing out how this kind of tourist activities has positive repercussions in terms of economic and social sustainability.

Expedition 'Idraren Draren'.

Science.gov (United States)

Yeoman, L P

1990-01-01

In May 1990 a team of 12 personnel from the Royal Naval Medical Service flew to Marrakech and were then transported by truck to the village of Imlil to commence a 12-day trek into the High Atlas Mountains with the primary aim of ascending the summit of Mount Toubkal and encircling the Toubkal Massif. It was then the intention to get off the tourist tracks and to experience life among the Berber tribes, and to trek part of the high Atlas range.

Development of in situ Brillouin spectroscopy at high pressure and high temperature with synchrotron radiation and infrared laser heating system: Application to the Earth's deep interior

Science.gov (United States)

Murakami, Motohiko; Asahara, Yuki; Ohishi, Yasuo; Hirao, Naohisa; Hirose, Kei

2009-05-01

Seismic wave velocity profiles in the Earth provide one of the strongest constraints on structure, mineralogy and elastic properties of the Earth's deep interior. Accurate sound velocity data of deep Earth materials under relevant high-pressure and high-temperature conditions, therefore, are essential for interpretation of seismic data. Such information can be directly obtained from Brillouin scattering measurement. Here we describe an in situ Brillouin scattering system for measurements at high pressure and high temperature using a laser heated diamond anvil cell and synchrotron radiation for sample characterization. The system has been used with single-crystal and polycrystalline materials, and with glass and fluid phase. It provided high quality sound velocity and elastic data with X-ray diffraction data at high pressure and/or high temperature. Those combined techniques can potentially offer the essential information for resolving many remaining issues in mineral physics.

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

Science.gov (United States)

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

2018-02-01

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

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

Science.gov (United States)

Yang, Jian-Hua; Qu, Liang-Hu

2012-01-01

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

High temperature tensile properties and deep drawing of fully green composites

Directory of Open Access Journals (Sweden)

2009-01-01

Full Text Available In recent years, research and development of materials using biomass sources are much expected to construct a sustainable society. The so-called green composite consisting of natural fibers and biodegradable resin, is one of the most promising materials in developing biomass products. In this study, especially, we focus on the tensile deformation behavior of the green composites reinforced with ramie woven fabrics at high temperature. The results show that the fracture strain at high temperatures increases larger than that of room temperature, and initial deformation resistance of the composites seen at room temperature does not appear at high temperatures. Thus, several conditions to cause more deformability of the green composites were found. Finally, in order to utilize such deformability, Lankford-values of the green composites were clarified, and deep drawing was carried out for sheet materials made of the green composites.

Dual-wavelength photo-Hall effect spectroscopy of deep levels in high resistive CdZnTe with negative differential photoconductivity

Science.gov (United States)

Musiienko, A.; Grill, R.; Moravec, P.; Korcsmáros, G.; Rejhon, M.; Pekárek, J.; Elhadidy, H.; Šedivý, L.; Vasylchenko, I.

2018-04-01

Photo-Hall effect spectroscopy was used in the study of deep levels in high resistive CdZnTe. The monochromator excitation in the photon energy range 0.65-1.77 eV was complemented by a laser diode high-intensity excitation at selected photon energies. A single sample characterized by multiple unusual features like negative differential photoconductivity and anomalous depression of electron mobility was chosen for the detailed study involving measurements at both the steady and dynamic regimes. We revealed that the Hall mobility and photoconductivity can be both enhanced and suppressed by an additional illumination at certain photon energies. The anomalous mobility decrease was explained by an excitation of the inhomogeneously distributed deep level at the energy Ev + 1.0 eV, thus enhancing potential non-uniformities. The appearance of negative differential photoconductivity was interpreted by an intensified electron occupancy of that level by a direct valence band-to-level excitation. Modified Shockley-Read-Hall theory was used for fitting experimental results by a model comprising five deep levels. Properties of the deep levels and their impact on the device performance were deduced.

Charged particle production in high Q deep-inelastic scattering at HERA

Science.gov (United States)

H1 Collaboration; Aaron, F. D.; Aktas, A.; Alexa, C.; Andreev, V.; Antunovic, B.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Backovic, S.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Beckingham, M.; Begzsuren, K.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, N.; Bizot, J. C.; Boenig, M.-O.; Boudry, V.; Bozovic-Jelisavcic, I.; Bracinik, J.; Brandt, G.; Brinkmann, M.; Brisson, V.; Bruncko, D.; Büsser, F. W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A. J.; Avila, K. B. Cantun; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Cholewa, A.; Contreras, J. G.; Coughlan, J. A.; Cozzika, G.; Cvach, J.; Dainton, J. B.; Daum, K.; Deak, M.; de Boer, Y.; Delcourt, B.; Del Degan, M.; Delvax, J.; de Roeck, A.; de Wolf, E. A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eliseev, A.; Elsen, E.; Essenov, S.; Falkiewicz, A.; Faulkner, P. J. W.; Favart, L.; Fedotov, A.; Felst, R.; Feltesse, J.; Ferencei, J.; Finke, L.; Fleischer, M.; Fomenko, A.; Franke, G.; Frisson, T.; Gabathuler, E.; Gayler, J.; Ghazaryan, S.; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Gouzevitch, M.; Grab, C.; Greenshaw, T.; Gregori, M.; Grell, B. R.; Grindhammer, G.; Habib, S.; Haidt, D.; Hansson, M.; Heinzelmann, G.; Helebrant, C.; Henderson, R. C. W.; Henschel, H.; Herrera, G.; Hildebrandt, M.; Hiller, K. H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Jacquet, M.; Janssen, M. E.; Janssen, X.; Jemanov, V.; Jönsson, L.; Johnson, D. P.; Jung, A. W.; Jung, H.; Kapichine, M.; Katzy, J.; Kenyon, I. R.; Kiesling, C.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knutsson, A.; Korbel, V.; Kostka, P.; Kraemer, M.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Krüger, K.; Landon, M. P. J.; Lange, W.; Laštovička-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Li, G.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; List, J.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lytkin, L.; Makankine, A.; Malinovski, E.; Marage, P.; Marti, Ll.; Martisikova, M.; Martyn, H.-U.; Maxfield, S. J.; Mehta, A.; Meier, K.; Meyer, A. B.; Meyer, H.; Meyer, H.; Meyer, J.; Michels, V.; Mikocki, S.; Milcewicz-Mika, I.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J. V.; Mozer, M. U.; Müller, K.; Murín, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, P. R.; Niebuhr, C.; Nikiforov, A.; Nowak, G.; Nowak, K.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J. E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Pandurovic, M.; Papadopoulou, Th.; Pascaud, C.; Patel, G. D.; Peng, H.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Picuric, I.; Piec, S.; Pitzl, D.; Plačakytė, R.; Polifka, R.; Povh, B.; Preda, T.; Prideaux, P.; Radescu, V.; Rahmat, A. J.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salek, D.; Salvaire, F.; Sankey, D. P. C.; Sauter, M.; Sauvan, E.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schöning, A.; Schultz-Coulon, H.-C.; Sefkow, F.; Shaw-West, R. N.; Sheviakov, I.; Shtarkov, L. N.; Sloan, T.; Smiljanic, I.; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, A.; Staykova, Z.; Steder, M.; Stella, B.; Stiewe, J.; Straumann, U.; Sunar, D.; Sykora, T.; Tchoulakov, V.; Thompson, G.; Thompson, P. D.; Toll, T.; Tomasz, F.; Tran, T. H.; Traynor, D.; Trinh, T. N.; Truöl, P.; Tsakov, I.; Tseepeldorj, B.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, K.; Utkin, D.; Valkárová, A.; Vallée, C.; van Mechelen, P.; Trevino, A. Vargas; Vazdik, Y.; Vinokurova, S.; Volchinski, V.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Wessels, M.; Wissing, Ch.; Wolf, R.; Wünsch, E.; Xella, S.; Yeganov, V.; Žáček, J.; Zálešák, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y. C.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.

2007-10-01

The average charged track multiplicity and the normalised distribution of the scaled momentum, x, of charged final state hadrons are measured in deep-inelastic ep scattering at high Q in the Breit frame of reference. The analysis covers the range of photon virtuality 100

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.

Study of the earth's deep interior and crystallography. X-ray and neutron diffraction experiments under high pressures

International Nuclear Information System (INIS)

Yagi, Takehiko

2014-01-01

History of the study of the Earth's deep interior was reviewed. In order to understand Earth's deep interior from the view point of materials science, X-ray diffraction under high pressure and high temperature played very important role. Use of synchrotron radiation dramatically advanced this experimental technique and it is now possible to make precise X-ray study under the P-T conditions corresponding even to the center of the Earth. In order to clarify the behavior of light elements such as hydrogen, however, studies using neutron diffraction are also required. A new neutron beam line dedicated for high-pressure science is constructed at J-PARC and is now ready for use. (author)

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...

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.

Charge deep-level transient spectroscopy study of high-energy-electron-beam-irradiated hydrogenated amorphous silicon

NARCIS (Netherlands)

Klaver, A.; Nádaždy, V.; Zeman, M.; Swaaiij, R.A.C.M.M.

2006-01-01

We present a study of changes in the defect density of states in hydrogenated amorphous silicon (a-Si:H) due to high-energy electron irradiation using charged deep-level transient spectroscopy. It was found that defect states near the conduction band were removed, while in other band gap regions the

Prediction of pressure between packers of staged fracturing pipe strings in high-pressure deep wells and its application

Directory of Open Access Journals (Sweden)

Fuxiang Zhang

2015-03-01

Full Text Available Addressing to the deteriorated load conditions of working string and packers caused by annular pressure drop between packers during the staged stimulation of high-pressure deep well, one 2D temperature field transient prediction model for borehole under injecting conditions which considers such influences as friction heat, convection heat exchange was set up, based on energy conservation principle and borehole heat transfer theory. By means of analyzing the influences of borehole temperature and pressure changes on the annular volume between packers, and in combination with borehole temperature transient prediction model, annular fluid PVT equations of state, radial deformation model of tubing and formation transient seepage equation, a typical high-pressure deep well inter-packer annular pressure prediction model was established. Taking a high-pressure gas well in Tarim Oilfield for example, the inter-packer annular pressure prediction was conducted, on which, the mechanical analysis on packers and working strings was carried out. The analysis results show that although the pipe string is safe in the viewpoint of conventional design methods, it is still susceptible to failure after the annular pressure drop between packers was taken into consideration. Such factor should be fully considered in the design of staged stimulation pipe strings, and this prediction model provides new thoughts for the optimal design of high-pressure deep well staged stimulation pipe strings.

Droplet Combustion and Non-Reactive Shear-Coaxial Jets with Transverse Acoustic Excitation

Science.gov (United States)

2012-06-01

for this. Recent studies at UCLA and at NASA Glenn Research Center by Dattarajan et al. [20, 21] have focused on methanol droplet combustion...via Trek PZD2000A high-voltage amplifiers, to each piezo-siren. The waveform generators output signals were locked in frequency. However, their phase...1.3. Verify the wire on Channel 1 of the Tenma oscilloscope (Model No. 72-6800) comes from the output voltage monitor on the Trek -1 amplifier

Le rôle majeur du canal potassique TREK-1 dans la protection neuronale induite par les oméga-3

Directory of Open Access Journals (Sweden)

Heurteaux Catherine

2005-01-01

Full Text Available The nutritional interest of polyunsaturated fatty acids from omega-3, that are mainly present in vegetal and fish oils is now validated by the scientific community. Their beneficial effects have first been reported in coronary heart diseases. Many neurological and chronic diseases are often related to deficiencies in omega-3 and omega-6 and their derivatives. Polyunsaturated fatty acids from omega-3 family are essential to brain growth and neuronal preserving (foetuses, children, old people as well as visual and cognitive functions. They are recently considered as factors of improvement in some mental diseases. Today, polyunsaturated fatty acids could play a key role in the prevention and/or or the treatment of cerebral diseases. With the development of in vitro and in vivo experimental models, it is now possible to demonstrate the omega-3-induced neuronal protection against major pathologies such as epileptic seizures and cerebral ischemia. The molecular mechanism of neuronal protection induced by omega-3 is now clarified. The omega-3 target would be a potassium channel, TREK-1, which belongs to the new family of 2-P domain potassium channels (K-2P. The discovery of the physiopathological role of these K-2P channels can represent an important therapeutical challenge not only in cerebrovascular diseases, but also in psychiatry.

Inclusive gluon production in deep inelastic scattering at high parton density

International Nuclear Information System (INIS)

Kovchegov, Yuri V.; Tuchin, Kirill

2002-01-01

We calculate the cross section of single inclusive gluon production in deep inelastic scattering at very high energies in the saturation regime, where the parton densities inside hadrons and nuclei are large and the evolution of structure functions with energy is nonlinear. The expression we obtain for the inclusive gluon production cross section is generated by this nonlinear evolution. We analyze the rapidity distribution of the produced gluons as well as their transverse momentum spectrum given by the derived expression for the inclusive cross section. We propose an ansatz for the multiplicity distribution of gluons produced in nuclear collisions which includes the effects of nonlinear evolution in both colliding nuclei

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.

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.

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.

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

Deep Drawing Behavior of CoCrFeMnNi High-Entropy Alloys

Science.gov (United States)

Bae, Jae Wung; Moon, Jongun; Jang, Min Ji; Ahn, Dong-Hyun; Joo, Soo-Hyun; Jung, Jaimyun; Yim, Dami; Kim, Hyoung Seop

2017-09-01

Herein, the deep drawability and deep drawing behavior of an equiatomic CoCrFeMnNi HEA and its microstructure and texture evolution are first studied for future applications. The CoCrFeMnNi HEA is successfully drawn to a limit drawing ratio (LDR) of 2.14, while the planar anisotropy of the drawn cup specimen is negligible. The moderate combination of strain hardening exponent and strain rate sensitivity and the formation of deformation twins in the edge region play important roles in successful deep drawing. In the meanwhile, the texture evolution of CoCrFeMnNi HEA has similarities with conventional fcc metals.

Building with materials from demolition projects

NARCIS (Netherlands)

Moonen, S.P.G.; Hermans, K.; Shu-Ming, xx; Che-Ming Chiang, xx; Chun-Ta Tzeng, xx; Kuang-Sheng Liu, xx; Nien-Tsu Chen, xx; Yi-Pin Lin, xx; Emmitt, S.

2013-01-01

Students of Eindhoven University of Technology have developed a sustainable and innovative hikers’ cabin, called "Trek-In" for SNK, a Dutch coordinating organization of natural campsites. By now, three Trek-Ins are in commercial use, while SNK intends to exploit over 100 Trek-Ins in the coming

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

Defense AT and L, Volume 40, Number 1, January - February 2011

Science.gov (United States)

2011-01-01

making the trip. I should have known better. Over the River and Through the Traffic Making the trek across the unnamed river was no mean feat in an...lines of Star Trek ) or “the ulti- mate high ground” (from Department of Defense and Air Force space doctrine documents) appeal to the adventurous...systems came into being and evolved over the last 50-plus years as NASA , DoD, and commercial space launch customers brought individual requirements

Droplet Combustion and Non-Reactive Shear-Coaxial Jets with and without Transverse Acoustic Excitation

Science.gov (United States)

2012-01-01

node, there is no droplet deflection, but there is limited evidence for this. Recent studies at UCLA and at NASA Glenn Research Center by Dattarajan et...generator supplied continuous sine wave signals, which were amplified via Trek PZD2000A high-voltage amplifiers, to each piezo-siren. The waveform...1.3. Verify the wire on Channel 1 of the Tenma oscilloscope (Model No. 72-6800) comes from the output voltage monitor on the Trek -1 amplifier and the

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...

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

Directory of Open Access Journals (Sweden)

A. Vereshchaka

2016-11-01

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

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.

Deep Echo State Network (DeepESN): A Brief Survey

OpenAIRE

Gallicchio, Claudio; Micheli, Alessio

2017-01-01

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

Deep 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...

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

Science.gov (United States)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Easy fabrication of high quality nickel mold for deep polymer microfluidic channels

International Nuclear Information System (INIS)

Wong, Ten It; Tan, Christina Yuan Ling; Zhou, Xiaodong; Limantoro, Julian; Fong, Kin Phang; Quan, Chenggen; Sun, Ling Ling

2016-01-01

Mass fabrication of disposable microfluidic chips with hot embossing is a key technology for microfluidic chip based biosensors. In this work, we develop a new method of fabricating high quality and highly durable nickel molds for hot embossing polymer chips. The process involves the addition of a thick, patterned layer of negative photoresist AZ-125nxT to a 4″ silicon wafer, followed by nickel electroplating and delamination of the nickel mold. Our investigations found that compared to a pillar mask, a hole mask can minimize the diffraction effect in photolithography of a thick photoresist, reduce the adhesion of the AZ-125nxT to the photomask in photolithography, and facilitate clean development of the photoresist patterns. By optimizing the hot embossing and chip bonding parameters, microfluidic chips with deep channels are achieved. (paper)

A deep learning and novelty detection framework for rapid phenotyping in high-content screening

Science.gov (United States)

Sommer, Christoph; Hoefler, Rudolf; Samwer, Matthias; Gerlich, Daniel W.

2017-01-01

Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with CellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates that CellCognition Explorer enables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening. PMID:28954863

Propagation of Measurement-While-Drilling Mud Pulse during High Temperature Deep Well Drilling Operations

OpenAIRE

Li, Hongtao; Meng, Yingfeng; Li, Gao; Wei, Na; Liu, Jiajie; Ma, Xiao; Duan, Mubai; Gu, Siman; Zhu, Kuanliang; Xu, Xiaofeng

2013-01-01

Signal attenuates while Measurement-While-Drilling (MWD) mud pulse is transmited in drill string during high temperature deep well drilling. In this work, an analytical model for the propagation of mud pulse was presented. The model consists of continuity, momentum, and state equations with analytical solutions based on the linear perturbation analysis. The model can predict the wave speed and attenuation coefficient of mud pulse. The calculated results were compared with the experimental dat...

High power deep UV-LEDs for analytical optical instrumentation

Czech Academy of Sciences Publication Activity Database

Li, Y.; Dvořák, Miloš; Nesterenko, P. N.; Nuchtavorn, N.; Macka, M.

2018-01-01

Roč. 255, č. 2 (2018), s. 1238-1243 ISSN 0925-4005 Institutional support: RVO:68081715 Keywords : deep UV Light emitting diodes (LEDs) * optical detection * portable analytical instrumentation Subject RIV: CB - Analytical Chemistry, Separation OBOR OECD: Analytical chemistry Impact factor: 5.401, year: 2016

Statistics of Deep Convection in the Congo Basin Derived From High-Resolution Simulations.

Science.gov (United States)

White, B.; Stier, P.; Kipling, Z.; Gryspeerdt, E.; Taylor, S.

2016-12-01

Convection transports moisture, momentum, heat and aerosols through the troposphere, and so the temporal variability of convection is a major driver of global weather and climate. The Congo basin is home to some of the most intense convective activity on the planet and is under strong seasonal influence of biomass burning aerosol. However, deep convection in the Congo basin remains under studied compared to other regions of tropical storm systems, especially when compared to the neighbouring, relatively well-understood West African climate system. We use the WRF model to perform a high-resolution, cloud-system resolving simulation to investigate convective storm systems in the Congo. Our setup pushes the boundaries of current computational resources, using a 1 km grid length over a domain covering millions of square kilometres and for a time period of one month. This allows us to draw statistical conclusions on the nature of the simulated storm systems. Comparing data from satellite observations and the model enables us to quantify the diurnal variability of deep convection in the Congo basin. This approach allows us to evaluate our simulations despite the lack of in-situ observational data. This provides a more comprehensive analysis of the diurnal cycle than has previously been shown. Further, we show that high-resolution convection-permitting simulations performed over near-seasonal timescales can be used in conjunction with satellite observations as an effective tool to evaluate new convection parameterisations.

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.

All-photonic drying and sintering process via flash white light combined with deep-UV and near-infrared irradiation for highly conductive copper nano-ink

Science.gov (United States)

Hwang, Hyun-Jun; Oh, Kyung-Hwan; Kim, Hak-Sung

2016-01-01

We developed an ultra-high speed photonic sintering method involving flash white light (FWL) combined with near infrared (NIR) and deep UV light irradiation to produce highly conductive copper nano-ink film. Flash white light irradiation energy and the power of NIR/deep UV were optimized to obtain high conductivity Cu films. Several microscopic and spectroscopic characterization techniques such as scanning electron microscopy (SEM), a x-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy were employed to characterize the Cu nano-films. Optimally sintered Cu nano-ink films produced using a deep UV-assisted flash white light sintering technique had the lowest resistivity (7.62 μΩ·cm), which was only 4.5-fold higher than that of bulk Cu film (1.68 μΩ•cm). PMID:26806215

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...

Iris Transponder-Communications and Navigation for Deep Space

Science.gov (United States)

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

2014-01-01

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

Numerical and Experimental Study on Manufacture of a Novel High-Capacity Engine Oil Pan Subjected to Hydro-Mechanical Deep Drawing

Science.gov (United States)

Chen, D. Y.; Xu, Y.; Zhang, S. H.; El-Aty, A. Abd; Ma, Y.

2017-09-01

The oil pan is equipped at the bottom of engine crankcase of the automobile to prevent impurity and collect the lubrication oil from the surfaces of the engine which is helpful for heat dissipation and oxidation prevention. The present study aims at manufacturing a novel high-capacity engine oil pan, which is considered as a complex shaped component with features of thin wall, large size and asymmetric deep cavity through both numerical and experimental methods. The result indicated that it is difficult to form the current part through the common deep drawing process. Accordingly, the hydro-mechanical deep drawing technology was conducted, which consisted of two steps, previous local drawing and the final integral deep drawing with hydraulic pressure. The finite element analysis (FEA) was carried out to investigate the influence of initial blank dimension and the key process parameters such as loading path, draw-bead force and fillet radius on the formability of the sheet blank. Compared with the common deep drawing, the limit drawing ratio by hydro-mechanical deep drawing can be increased from 2.34 to 2.77, while the reduction in blank wall thickness can be controlled in the range of 28%. The formability is greatly improved without any defects such as crack and wrinkle by means of parameters optimisation. The results gained from simulation keep a reasonable agreement with that obtained from experiment trials.

Deep ice and salty oceans of icy worlds, how high pressures influence their thermodynamics and provide constrains on extraterrestrial habitability

Science.gov (United States)

Journaux, B.; Brown, J. M.; Bollengier, O.; Abramson, E.

2017-12-01

As in Earth arctic and Antarctic regions, suspected extraterrestrial deep oceans in icy worlds (i.e. icy moons and water-rich exoplanets) chemistry and thermodynamic state will strongly depend on their equilibrium with H2O ice and present solutes. Na-Mg-Cl-SO4 salt species are currently the main suspected ionic solutes to be present in deep oceans based on remote sensing, magnetic field measurements, cryovolcanism ice grains chemical analysis and chondritic material aqueous alteration chemical models. Unlike on our planet, deep extraterrestrial ocean might also be interacting at depth with high pressure ices (e.g. III, V, VI, VI, X) which have different behavior compared to ice Ih. Unfortunately, the pressures and temperatures inside these hydrospheres differ significantly from the one found in Earth aqueous environments, so most of our current thermodynamic databases do not cover the range of conditions relevant for modeling realistically large icy worlds interiors. Recent experimental results have shown that the presence of solutes, and more particularly salts, in equilibrium with high pressure ices have large effects on the stability, buoyancy and chemistry of all the phases present at these extreme conditions. High pressure in-situ measurements using diamond anvil cell apparatus were operated both at the University of washington and at the European Synchrotron Radiation Facility on aqueous systems phase diagrams with Na-Mg-Cl-SO4 species, salt incorporation in high pressure ices and density inversions between the solid and the fluids. These results suggest a more complex picture of the interior structure, dynamic and chemical evolution of large icy worlds hydrospheres when solutes are taken into account, compared to current models mainly using pure water. Based on our in-situ experimental measurements, we propose the existence of new liquid environments at greater depths and the possibility of solid state transport of solute through the high pressure ices

High resolution shadow mask patterning in deep holes and its application to an electrical wafer feed-through

NARCIS (Netherlands)

Burger, G.J.; Burger, G.J.; Smulders, E.J.T.; Berenschot, Johan W.; Lammerink, Theodorus S.J.; Fluitman, J.H.J.; Imai, S.

1995-01-01

This paper presents a technique to pattern materials in deep holes and/or on non-planar substrate surfaces. A rather old technique, E-beam evaporation of metals through a shadow mask, is used [1]. The realisation of high resolution shadow masks using micromachining techniques is described. Further,

Effects of heat from high-level waste on performance of deep geological repository components

International Nuclear Information System (INIS)

1984-11-01

This report discusses the effects of heat on the deep geological repository systems and its different components. The report is focussed specifically on effects due to thermal energy release solely from high-level waste or spent fuel. It reviews the experimental data and theoretical models of the effects of heat both on the behaviour of engineered and natural barriers. A summary of the current status of research and repository development including underground test facilities is presented

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

Science.gov (United States)

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Interpretation of the deep cracking phenomenon of tungsten monoblock targets observed in high-heat-flux fatigue tests at 20 MW/m"2

International Nuclear Information System (INIS)

Li, Muyuan; You, Jeong-Ha

2015-01-01

Highlights: • A theoretical interpretation is presented for deep crack of W monoblocks at 20 MW/m"2. • A consecutive process of crack initiation and growth was modeled in two stages. • The lifetime to crack initiation and the driving force of fracture are assessed. • Numerical predictions in this study agree well with the experimental findings. - Abstract: The HHF qualification tests conducted on the ITER divertor target prototypes showed that the tungsten monoblock armor suffered from deep cracking due to fatigue, when the applied high-heat-flux load approaches 20 MW/m"2. In spite of the critical implication of the deep cracking of armor on the structural integrity of a whole target component, no rigorous interpretation has been given to date. In this paper, a theoretical interpretation of the observed deep cracking feature is presented. A two-stage modeling approach is employed where deep cracking is thought to be a consecutive process of crack initiation and crack growth, which is assumed to be caused by plastic fatigue and brittle facture, respectively. The fatigue lifetime to crack initiation on the armor surface and the crack tip load of brittle fracture are assessed as a function of crack length and heat flux loads. The potential mechanisms of deep cracking are discussed for a typical slow transient high-heat-flux load cycle. It is shown that the quantitative predictions delivered in this study agree well with the observed findings offering insight into the nature of tungsten armor failure.

Charged Particle Production in High Q2 Deep-Inelastic Scattering at HERA

CERN Document Server

Aaron, F.D.; Alexa, C.; Andreev, V.; Antunovic, B.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Backovic, S.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Beckingham, M.; Begzsuren, K.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, N.; Bizot, J.C.; Boenig, M.-O.; Boudry, V.; Bozovic-Jelisavcic, I.; Bracinik, J.; Brandt, G.; Brinkmann, M.; Brisson, V.; Bruncko, D.; Busser, F.W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A.J.; Cantun Avila, K.B.; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Cholewa, A.; Contreras, J.G.; Coughlan, J.A.; Cozzika, G.; Cvach, J.; Dainton, J.B.; Daum, K.; Deak, M.; de Boer, Y.; Delcourt, B.; Del Degan, M.; Delvax, J.; De Roeck, A.; De Wolf, E.A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, Guenter; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eliseev, A.; Elsen, E.; Essenov, S.; Falkiewicz, A.; Faulkner, P.J.W.; Favart, L.; Fedotov, A.; Felst, R.; Feltesse, J.; Ferencei, J.; Finke, L.; Fleischer, M.; Fomenko, A.; Franke, G.; Frisson, T.; Gabathuler, E.; Gayler, J.; Ghazaryan, Samvel; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Gouzevitch, M.; Grab, C.; Greenshaw, T.; Grell, B.R.; Grindhammer, G.; Habib, S.; Haidt, D.; Hansson, M.; Heinzelmann, G.; Helebrant, C.; Henderson, R.C.W.; Henschel, H.; Herrera, G.; Hildebrandt, M.; Hiller, K.H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Jacquet, M.; Janssen, M.E.; Janssen, X.; Jemanov, V.; Jonsson, L.; Johnson, D.P.; Jung, Andreas Werner; Jung, H.; Kapichine, M.; Katzy, J.; Kenyon, I.R.; Kiesling, Christian M.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knutsson, A.; Korbel, V.; Kostka, P.; Kraemer, M.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Kruger, K.; Landon, M.P.J.; Lange, W.; Lastovicka-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Li, G.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; List, J.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lytkin, L.; Makankine, A.; Malinovski, E.; Marage, P.; Marti, Ll.; Martisikova, M.; Martyn, H.-U.; Maxfield, S.J.; Mehta, A.; Meier, K.; Meyer, A.B.; Meyer, H.; Meyer, J.; Michels, V.; Mikocki, S.; Milcewicz-Mika, I.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J.V.; Mozer, Matthias Ulrich; Muller, K.; Murin, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, Paul R.; Niebuhr, C.; Nikiforov, A.; Nowak, G.; Nowak, K.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J.E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Pandurovic, M.; Papadopoulou, Th.; Pascaud, C.; Patel, G.D.; Peng, H.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Picuric, I.; Piec, S.; Pitzl, D.; Placakyte, R.; Polifka, R.; Povh, B.; Preda, T.; Prideaux, P.; Radescu, V.; Rahmat, A.J.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salek, D.; Salvaire, F.; Sankey, D.P.C.; Sauter, M.; Sauvan, E.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schoning, A.; Schultz-Coulon, H.-C.; Sefkow, F.; Shaw-West, R.N.; Sheviakov, I.; Shtarkov, L.N.; Sloan, T.; Smiljanic, Ivan; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, Arnd E.; Staykova, Z.; Steder, M.; Stella, B.; Stiewe, J.; Straumann, U.; Sunar, D.; Sykora, T.; Tchoulakov, V.; Thompson, G.; Thompson, P.D.; Toll, T.; Tomasz, F.; Tran, T.H.; Traynor, D.; Trinh, T.N.; Truol, P.; Tsakov, I.; Tseepeldorj, B.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, K.; Utkin, D.; Valkarova, A.; Vallee, C.; Van Mechelen, P.; Vargas Trevino, A.; Vazdik, Y.; Vinokurova, S.; Volchinski, V.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Wessels, M.; Wissing, Ch.; Wolf, R.; Wunsch, E.; Xella, S.; Yeganov, V.; Zacek, J.; Zalesak, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y.C.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.

2007-01-01

The average charged track multiplicity and the normalised distribution of the scaled momentum, $\\xp$, of charged final state hadrons are measured in deep-inelastic $\\ep$ scattering at high $Q^2$ in the Breit frame of reference. The analysis covers the range of photon virtuality $100 < Q^2 < 20 000 \\GeV^{2}$. Compared with previous results presented by HERA experiments this analysis has a significantly higher statistical precision and extends the phase space to higher $Q^{2}$ and to the full range of $\\xp$. The results are compared with $e^+e^-$ annihilation data and with various calculations based on perturbative QCD using different models of the hadronisation process.

Charged particle production in high Q2 deep-inelastic scattering at HERA

Science.gov (United States)

Aaron, F. D.; Aktas, A.; Alexa, C.; Andreev, V.; Antunovic, B.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Backovic, S.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Beckingham, M.; Begzsuren, K.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, N.; Bizot, J. C.; Boenig, M.-O.; Boudry, V.; Bozovic-Jelisavcic, I.; Bracinik, J.; Brandt, G.; Brinkmann, M.; Brisson, V.; Bruncko, D.; Büsser, F. W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A. J.; Avila, K. B. Cantun; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Cholewa, A.; Contreras, J. G.; Coughlan, J. A.; Cozzika, G.; Cvach, J.; Dainton, J. B.; Daum, K.; Deak, M.; de Boer, Y.; Delcourt, B.; Del Degan, M.; Delvax, J.; De Roeck, A.; De Wolf, E. A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eliseev, A.; Elsen, E.; Essenov, S.; Falkiewicz, A.; Faulkner, P. J. W.; Favart, L.; Fedotov, A.; Felst, R.; Feltesse, J.; Ferencei, J.; Finke, L.; Fleischer, M.; Fomenko, A.; Franke, G.; Frisson, T.; Gabathuler, E.; Gayler, J.; Ghazaryan, S.; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Gouzevitch, M.; Grab, C.; Greenshaw, T.; Gregori, M.; Grell, B. R.; Grindhammer, G.; Habib, S.; Haidt, D.; Hansson, M.; Heinzelmann, G.; Helebrant, C.; Henderson, R. C. W.; Henschel, H.; Herrera, G.; Hildebrandt, M.; Hiller, K. H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Jacquet, M.; Janssen, M. E.; Janssen, X.; Jemanov, V.; Jönsson, L.; Johnson, D. P.; Jung, A. W.; Jung, H.; Kapichine, M.; Katzy, J.; Kenyon, I. R.; Kiesling, C.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knutsson, A.; Korbel, V.; Kostka, P.; Kraemer, M.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Krüger, K.; Landon, M. P. J.; Lange, W.; Laštovička-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Li, G.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; List, J.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lytkin, L.; Makankine, A.; Malinovski, E.; Marage, P.; Marti, Ll.; Martisikova, M.; Martyn, H.-U.; Maxfield, S. J.; Mehta, A.; Meier, K.; Meyer, A. B.; Meyer, H.; Meyer, H.; Meyer, J.; Michels, V.; Mikocki, S.; Milcewicz-Mika, I.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J. V.; Mozer, M. U.; Müller, K.; Murín, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, P. R.; Niebuhr, C.; Nikiforov, A.; Nowak, G.; Nowak, K.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J. E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Pandurovic, M.; Papadopoulou, Th.; Pascaud, C.; Patel, G. D.; Peng, H.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Picuric, I.; Piec, S.; Pitzl, D.; Plačakytė, R.; Polifka, R.; Povh, B.; Preda, T.; Prideaux, P.; Radescu, V.; Rahmat, A. J.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salek, D.; Salvaire, F.; Sankey, D. P. C.; Sauter, M.; Sauvan, E.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schöning, A.; Schultz-Coulon, H.-C.; Sefkow, F.; Shaw-West, R. N.; Sheviakov, I.; Shtarkov, L. N.; Sloan, T.; Smiljanic, I.; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, A.; Staykova, Z.; Steder, M.; Stella, B.; Stiewe, J.; Straumann, U.; Sunar, D.; Sykora, T.; Tchoulakov, V.; Thompson, G.; Thompson, P. D.; Toll, T.; Tomasz, F.; Tran, T. H.; Traynor, D.; Trinh, T. N.; Truöl, P.; Tsakov, I.; Tseepeldorj, B.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, K.; Utkin, D.; Valkárová, A.; Vallée, C.; Van Mechelen, P.; Trevino, A. Vargas; Vazdik, Y.; Vinokurova, S.; Volchinski, V.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Wessels, M.; Wissing, Ch.; Wolf, R.; Wünsch, E.; Xella, S.; Yeganov, V.; Žáček, J.; Zálešák, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y. C.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.; H1 Collaboration

2007-10-01

The average charged track multiplicity and the normalised distribution of the scaled momentum, xp, of charged final state hadrons are measured in deep-inelastic ep scattering at high Q2 in the Breit frame of reference. The analysis covers the range of photon virtuality 100

Technologies in deep and ultra-deep well drilling: Present status, challenges and future trend in the 13th Five-Year Plan period (2016–2020

Directory of Open Access Journals (Sweden)

Haige Wang

2017-09-01

Full Text Available During the 12th Five-Year Plan period (2011–2015, CNPC independently developed a series of new drilling equipment, tools and chemical materials for deep and ultra-deep wells, including six packages of key drilling equipment: rigs for wells up to 8000 m deep, quadruple-joint-stand rigs, automatic pipe handling devices for rigs for wells being 5000/7000 m deep, managed pressure drilling systems & equipment, gas/fuel alternative combustion engine units, and air/gas/underbalanced drilling systems; seven sets of key drilling tools: automatic vertical well drilling tools, downhole turbine tools, high-performance PDC bits, hybrid bits, bit jet pulsation devices, no-drilling-surprise monitoring system, & casing running devices for top drive; and five kinds of drilling fluids and cementing slurries: high temperature and high density water-based drilling fluids, oil-based drilling fluids, high temperature and large temperature difference cementing slurry, and ductile cement slurry system. These new development technologies have played an important role in supporting China's oil and gas exploration and development business. During the following 13th Five-Year Plan period (2016–2020, there are still many challenges to the drilling of deep and ultra-deep wells, such as high temperatures, high pressures, narrow pressure window, wellbore integrity and so on, as well as the enormous pressure on cost reduction and efficiency improvement. Therefore, the future development trend will be focused on the development of efficient and mobile rigs, high-performance drill bits and auxiliary tools, techniques for wellbore integrity and downhole broadband telemetry, etc. In conclusion, this study will help improve the ability and level of drilling ultra-deep wells and provide support for oil and gas exploration and development services in China. Keywords: Deep well, Ultra-deep well, Drilling techniques, Progress, Challenge, Strategy, CNPC

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

Science.gov (United States)

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

2004-08-01

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

Radial transport of high-energy oxygen ions into the deep inner magnetosphere observed by Van Allen Probes

Science.gov (United States)

Mitani, K.; Seki, K.; Keika, K.; Gkioulidou, M.; Lanzerotti, L. J.; Mitchell, D. G.; Kletzing, C.

2017-12-01

It is known that proton is main contributor of the ring current and oxygen ions can make significant contribution during major magnetic storms. Ions are supplied to the ring current by radial transport from the plasma sheet. Convective transport of lower-energy protons and diffusive transport of higher-energy protons were reported to contribute to the storm-time and quiet-time ring current respectively [e.g., Gkioulidou et al., 2016]. However, supply mechanisms of the oxygen ions are not clear. To characterize the supply of oxygen ions to the ring current during magnetic storms, we studied the properties of energetic proton and oxygen ion phase space densities (PSDs) for specific magnetic moment (μ) during the April 23-25, 2013, geomagnetic storm observed by the Van Allen Probes mission. We here report on radial transport of high-energy (μ ≥ 0.5 keV/nT) oxygen ions into the deep inner magnetosphere during the late main phase of the magnetic storm. Since protons show little change during this period, this oxygen radial transport is inferred to cause the development of the late main phase. Enhancement of poloidal magnetic fluctuations is simultaneously observed. We estimated azimuthal mode number ≤5 by using cross wavelet analysis with ground-based observation of IMAGE ground magnetometers. The fluctuations can resonate with drift and bounce motions of the oxygen ions. The results suggest that combination of the drift and drift-bounce resonances is responsible for the radial transport of high-energy oxygen ions into the deep inner magnetosphere. We also report on the radial transport of the high-energy oxygen ions into the deep inner magnetosphere during other magnetic storms.

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 ...

Exploration in the Deep water Niger Delta: Technical to Business Perspectives

International Nuclear Information System (INIS)

Feeley, M.H.

2002-01-01

Prolific source rocks, high quality deep water reservoirs and a high technical success rate in finding hydrocarbons make the Nigeria deep water one of the top exploration opportunities in the world. Several major discoveries have resulted from exploration on blocks awarded in 1993. Enthusiastic participation by industry in the 2000 Tender Round clearly indicates the continuing appeal of deep water exploration in Nigeria.Commercially, challenges still exist in the Nigerian deep water. Industry has spent more than $2 Billion USD on exploration and appraisal, yet only a handful of developments are moving forward to development. First oil from the deep water is not expected until 2004, 11 years after acreage award and 8 years after discovery. Tougher economic terms, OPEC quota constraints, an abundance of deep water gas, lengthy approval processes and high up-front bonus and exploration costs challenge the economic returns on deep water gas, lengthy approval processes and high up-front bonus and exploration costs challenge the economic returns on deep water investments. Will deep water exploration, development and production deliver the financial returns industry expected when it signed up for the blocks 10 years ago? What are the indications for the 2000 Tender Round blocks?A good explorer learns form experience. What can be learned technically and commercially by looking back over the results of the last 10 years of exploration in Nigeria's deep water? A perspective is provided on the successes, the failures and the challenges to be overcome in realizing the commercial potential of the basin

Sensitivity of on-resistance and threshold voltage to buffer-related deep level defects in AlGaN/GaN high electron mobility transistors

International Nuclear Information System (INIS)

Armstrong, Andrew M; Allerman, Andrew A; Baca, Albert G; Sanchez, Carlos A

2013-01-01

The influence of deep levels defects located in highly resistive GaN:C buffers on the on-resistance (R ON ) and threshold voltage (V th ) of AlGaN/GaN high electron mobility transistors (HEMTs) power devices was studied by a combined photocapacitance deep level optical spectroscopy (C-DLOS) and photoconductance deep level optical spectroscopy (G-DLOS) methodology as a function of electrical stress. Two carbon-related deep levels at 1.8 and 2.85 eV below the conduction band energy minimum were identified from C-DLOS measurements under the gate electrode. It was found that buffer-related defects under the gate shifted V th positively by approximately 10%, corresponding to a net areal density of occupied defects of 8 × 10 12 cm −2 . The effect of on-state drain stress and off-state gate stress on buffer deep level occupancy and R ON was also investigated via G-DLOS. It was found that the same carbon-related deep levels observed under the gate were also active in the access region. Off-state gate stress produced significantly more trapping and degradation of R ON (∼140%) compared to on-state drain stress (∼75%). Greater sensitivity of R ON to gate stress was explained by a more sharply peaked lateral distribution of occupied deep levels between the gate and drain compared to drain stress. The overall greater sensitivity of R ON compared to V th to buffer defects suggests that electron trapping is significantly greater in the access region compared to under the gate, likely due to the larger electric fields in the latter region. (invited paper)

Deep Arm/Ear-ECG Image Learning for Highly Wearable Biometric Human Identification.

Science.gov (United States)

Zhang, Qingxue; Zhou, Dian

2018-01-01

In this study, to advance smart health applications which have increasing security/privacy requirements, we propose a novel highly wearable ECG-based user identification system, empowered by both non-standard convenient ECG lead configurations and deep learning techniques. Specifically, to achieve a super wearability, we suggest situating all the ECG electrodes on the left upper-arm, or behind the ears, and successfully obtain weak but distinguishable ECG waveforms. Afterwards, to identify individuals from weak ECG, we further present a two-stage framework, including ECG imaging and deep feature learning/identification. In the former stage, the ECG heartbeats are projected to a 2D state space, to reveal heartbeats' trajectory behaviors and produce 2D images by a split-then-hit method. In the second stage, a convolutional neural network is introduced to automatically learn the intricate patterns directly from the ECG image representations without heavy feature engineering, and then perform user identification. Experimental results on two acquired datasets using our wearable prototype, show a promising identification rate of 98.4% (single-arm-ECG) and 91.1% (ear-ECG), respectively. To the best of our knowledge, it is the first study on the feasibility of using single-arm-ECG/ear-ECG for user identification purpose, which is expected to contribute to pervasive ECG-based user identification in smart health applications.

Analytical investigation of high temperature 1 kW solid oxide fuel cell system feasibility in methane hydrate recovery and deep ocean power generation

International Nuclear Information System (INIS)

Azizi, Mohammad Ali; Brouwer, Jacob; Dunn-Rankin, Derek

2016-01-01

Highlights: • A dynamic Solid Oxide Fuel Cell (SOFC) model was developed. • Hydrate bed methane dissociation model was integrated with the SOFC model. • SOFC operated steadily for 120 days at high pressure deep ocean environment. • Burning some of the dissociated gas for SMR heat leads to more net methane produced. • Higher SOFC fuel utilization produces higher integrated system efficiency. - Abstract: Methane hydrates are potential valuable energy resources. However, finding an efficient method for methane gas recovery from hydrate sediments is still a challenge. New challenges arise from increasing environmental protection. This is due in part to the technical difficulties involved in the efficient dissociation of methane hydrates at high pressures. In this study, a new approach is proposed to produce valuable products of: 1. Net methane gas recovery from the methane hydrate sediment, and 2. Deep ocean power generation. We have taken the first steps toward utilization of a fuel cell system in methane gas recovery from deep ocean hydrate sediments. An integrated high pressure and high temperature solid oxide fuel cell (SOFC) and steam methane reformer (SMR) system is analyzed for this application and the recoverable amount of methane from deep ocean sediments is measured. System analysis is accomplished for two major cases regarding system performance: 1. Energy for SMR is provided by the burning part of the methane gas dissociated from the hydrate sediment. 2. Energy for SMR is provided through heat exchange with fuel cell effluent gases. We found that the total production of methane gas is higher in the first case compared to the second case. The net power generated by the fuel cell system is estimated for all cases. The primary goal of this study is to evaluate the feasibility of integrated electrochemical devices to accomplish energy efficient dissociation of methane hydrate gases in deep ocean sediments. Concepts for use of electrochemical devices

Ductility and performance assessment of high strength self compacting concrete (HSSCC) deep beams: An experimental investigation

International Nuclear Information System (INIS)

Mohammadhassani, Mohammad; Jumaat, Mohd Zamin; Jameel, Mohammed; Badiee, Hamid; Arumugam, Arul M.S.

2012-01-01

Highlights: ► Ductility decreased with increase in tensile reinforcement ratio. ► The width of the load point and the support point influences premature failure. ► Load–deflection relationship is linear till 85% of the ultimate load. ► The absorbed energy increases with the increase of tensile reinforcement ratios. - Abstract: The behavior of deep beams is significantly different from that of normal beams. Because of their proportions, deep beams are likely to have strength controlled by shear. This paper discusses the results of eight simply supported high strength self compacting concrete (HSSCC) deep beams having variation in ratio of web reinforcement and tensile reinforcement. The deflection at two points along the beam length, web strains, tensile bars strains and the strain at concrete surface are recorded. The results show that the strain distribution at the section height of mid span is nonlinear. Ductility decreased with increase in tensile reinforcement ratio. The effect of width of load point and the support point is more important than the effect of tensile reinforcement ratio in preventing premature failure. Load–deflection graphs confirm linear relationship up to 85% of the ultimate load for HSSCC over-reinforcement web sections. The absorbed energy index increases with the increase in tensile reinforcement ratios.

[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.

Detecting atrial fibrillation by deep convolutional neural networks.

Science.gov (United States)

Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

2018-02-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Erbium-doped fiber lasers as deep-sea hydrophones

International Nuclear Information System (INIS)

Bagnoli, P.E.; Beverini, N.; Bouhadef, B.; Castorina, E.; Falchini, E.; Falciai, R.; Flaminio, V.; Maccioni, E.; Morganti, M.; Sorrentino, F.; Stefani, F.; Trono, C.

2006-01-01

The present work describes the development of a hydrophone prototype for deep-sea acoustic detection. The base-sensitive element is a single-mode erbium-doped fiber laser. The high sensitivity of these sensors makes them particularly suitable for a wide range of deep-sea acoustic applications, including geological and marine mammals surveys and above all as acoustic detectors in under-water telescopes for high-energy neutrinos

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...

High-throughput sequencing and analysis of the gill tissue transcriptome from the deep-sea hydrothermal vent mussel Bathymodiolus azoricus

Directory of Open Access Journals (Sweden)

Gomes Paula

2010-10-01

Full Text Available Abstract Background Bathymodiolus azoricus is a deep-sea hydrothermal vent mussel found in association with large faunal communities living in chemosynthetic environments at the bottom of the sea floor near the Azores Islands. Investigation of the exceptional physiological reactions that vent mussels have adopted in their habitat, including responses to environmental microbes, remains a difficult challenge for deep-sea biologists. In an attempt to reveal genes potentially involved in the deep-sea mussel innate immunity we carried out a high-throughput sequence analysis of freshly collected B. azoricus transcriptome using gills tissues as the primary source of immune transcripts given its strategic role in filtering the surrounding waterborne potentially infectious microorganisms. Additionally, a substantial EST data set was produced and from which a comprehensive collection of genes coding for putative proteins was organized in a dedicated database, "DeepSeaVent" the first deep-sea vent animal transcriptome database based on the 454 pyrosequencing technology. Results A normalized cDNA library from gills tissue was sequenced in a full 454 GS-FLX run, producing 778,996 sequencing reads. Assembly of the high quality reads resulted in 75,407 contigs of which 3,071 were singletons. A total of 39,425 transcripts were conceptually translated into amino-sequences of which 22,023 matched known proteins in the NCBI non-redundant protein database, 15,839 revealed conserved protein domains through InterPro functional classification and 9,584 were assigned with Gene Ontology terms. Queries conducted within the database enabled the identification of genes putatively involved in immune and inflammatory reactions which had not been previously evidenced in the vent mussel. Their physical counterpart was confirmed by semi-quantitative quantitative Reverse-Transcription-Polymerase Chain Reactions (RT-PCR and their RNA transcription level by quantitative PCR (q

Applying a punch with microridges in multistage deep drawing processes.

Science.gov (United States)

Lin, Bor-Tsuen; Yang, Cheng-Yu

2016-01-01

The developers of high aspect ratio components aim to minimize the processing stages in deep drawing processes. This study elucidates the application of microridge punches in multistage deep drawing processes. A microridge punch improves drawing performance, thereby reducing the number of stages required in deep forming processes. As an example, the original eight-stage deep forming process for a copper cylindrical cup with a high aspect ratio was analyzed by finite element simulation. Microridge punch designs were introduced in Stages 4 and 7 to replace the original punches. In addition, Stages 3 and 6 were eliminated. Finally, these changes were verified through experiments. The results showed that the microridge punches reduced the number of deep drawing stages yielding similar thickness difference percentages. Further, the numerical and experimental results demonstrated good consistency in the thickness distribution.

Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks

Science.gov (United States)

Ubbens, Jordan R.; Stavness, Ian

2017-01-01

Plant phenomics has received increasing interest in recent years in an attempt to bridge the genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput phenotyping capabilities to keep up with an increasing amount of data from high-dimensional imaging sensors and the desire to measure more complex phenotypic traits (Knecht et al., 2016). In this paper, we introduce an open-source deep learning tool called Deep Plant Phenomics. This tool provides pre-trained neural networks for several common plant phenotyping tasks, as well as an easy platform that can be used by plant scientists to train models for their own phenotyping applications. We report performance results on three plant phenotyping benchmarks from the literature, including state of the art performance on leaf counting, as well as the first published results for the mutant classification and age regression tasks for Arabidopsis thaliana. PMID:28736569

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

International Nuclear Information System (INIS)

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

2004-01-01

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

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.

A Study on the Fracture Control of Rock Bolts in High Ground Pressure Roadways of Deep Mines

Directory of Open Access Journals (Sweden)

Wen Jinglin

2015-01-01

Full Text Available According to the frequent fractures of rock bolts in high ground pressure roadways of deep mines, this paper analyzes the mechanism of fractures and concludes that high ground pressure and material de-fects are main reasons for the fracture of rock bolts. The basic idea of fracture control of rock bolts in high ground pressure roadways of deep mines is to increase the yield load and the limit load of rock bolt materials and reduce the actual load of rock bolts. There are four ways of controlling rock bolt fracture: increasing the rock bolt diameter, strengthening bolt materials, weakening support rigidity and the implementation of double supporting. With the roadway support of the 2302 working face of a coal mine as the project background, this paper carries out a study on the effect of two schemes, increasing the rock bolt diameter and the double supporting technique through methods of theoretical analysis, numerical simulation and so on. It determines the most reasonable diam-eter of rock bolts and the best delay distance of secondary support. Practices indicate that rock bolt fracture can be effectively controlled through the double supporting technique, which strengthens the roof and two sides through the first supporting technique and strengthens side angles through the secondary supporting technique.

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.

Ductility and performance assessment of high strength self compacting concrete (HSSCC) deep beams: An experimental investigation

Energy Technology Data Exchange (ETDEWEB)

Mohammadhassani, Mohammad, E-mail: mmh356@yahoo.com [Department of Civil Engineering, University of Malaya, Kuala Lumpur (Malaysia); Jumaat, Mohd Zamin; Jameel, Mohammed [Department of Civil Engineering, University of Malaya, Kuala Lumpur (Malaysia); Badiee, Hamid [Department of Civil Engineering, University of Kerman (Iran, Islamic Republic of); Arumugam, Arul M.S. [Department of Civil Engineering, University of Malaya, Kuala Lumpur (Malaysia)

2012-09-15

Highlights: Black-Right-Pointing-Pointer Ductility decreased with increase in tensile reinforcement ratio. Black-Right-Pointing-Pointer The width of the load point and the support point influences premature failure. Black-Right-Pointing-Pointer Load-deflection relationship is linear till 85% of the ultimate load. Black-Right-Pointing-Pointer The absorbed energy increases with the increase of tensile reinforcement ratios. - Abstract: The behavior of deep beams is significantly different from that of normal beams. Because of their proportions, deep beams are likely to have strength controlled by shear. This paper discusses the results of eight simply supported high strength self compacting concrete (HSSCC) deep beams having variation in ratio of web reinforcement and tensile reinforcement. The deflection at two points along the beam length, web strains, tensile bars strains and the strain at concrete surface are recorded. The results show that the strain distribution at the section height of mid span is nonlinear. Ductility decreased with increase in tensile reinforcement ratio. The effect of width of load point and the support point is more important than the effect of tensile reinforcement ratio in preventing premature failure. Load-deflection graphs confirm linear relationship up to 85% of the ultimate load for HSSCC over-reinforcement web sections. The absorbed energy index increases with the increase in tensile reinforcement ratios.

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

Science.gov (United States)

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

2017-11-01

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

Culturable prokaryotic diversity of deep, gas hydrate sediments: first use of a continuous high-pressure, anaerobic, enrichment and isolation system for subseafloor sediments (DeepIsoBUG)

OpenAIRE

Parkes, R John; Sellek, Gerard; Webster, Gordon; Martin, Derek; Anders, Erik; Weightman, Andrew J; Sass, Henrik

2009-01-01

Deep subseafloor sediments may contain depressurization-sensitive, anaerobic, piezophilic prokaryotes. To test this we developed the DeepIsoBUG system, which when coupled with the HYACINTH pressure-retaining drilling and core storage system and the PRESS core cutting and processing system, enables deep sediments to be handled without depressurization (up to 25 MPa) and anaerobic prokaryotic enrichments and isolation to be conducted up to 100 MPa. Here, we describe the system and its first use...

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

Average multiplications in deep inelastic processes and their interpretation

International Nuclear Information System (INIS)

Kiselev, A.V.; Petrov, V.A.

1983-01-01

Inclusive production of hadrons in deep inelastic proceseseus is considered. It is shown that at high energies the jet evolution in deep inelastic processes is mainly of nonperturbative character. With the increase of a final hadron state energy the leading contribution to an average multiplicity comes from a parton subprocess due to production of massive quark and gluon jets and their further fragmentation as diquark contribution becomes less and less essential. The ratio of the total average multiplicity in deep inelastic processes to the average multiplicity in e + e - -annihilation at high energies tends to unity

Distributed deep learning networks among institutions for medical imaging.

Science.gov (United States)

Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

2018-03-29

Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

Highly efficient and simplified phosphorescence white organic light-emitting diodes based on synthesized deep-blue host and orange emitter

Energy Technology Data Exchange (ETDEWEB)

Koo, Ja Ryong; Lee, Seok Jae; Hyung, Gun Woo; Kim, Bo Young; Lee, Dong Hyung [Department of Information Display, Hongik University, Seoul 121-791 (Korea, Republic of); Kim, Woo Young [Department of Green Energy and Semiconductor Engineering, Hoseo University, Asan 336-795 (Korea, Republic of); Lee, Kum Hee [Department of Chemistry, Sungkyunkwan University, Suwon 440-746 (Korea, Republic of); Yoon, Seung Soo, E-mail: ssyoon@skku.edu [Department of Chemistry, Sungkyunkwan University, Suwon 440-746 (Korea, Republic of); Kim, Young Kwan, E-mail: kimyk@hongik.ac.kr [Department of Information Display, Hongik University, Seoul 121-791 (Korea, Republic of)

2013-10-01

The authors have demonstrated a highly efficient and stable phosphorescent white organic light-emitting diode (WOLED), which has been achieved by doping only one orange phosphorescent emitter, Bis(5-benzoyl-2-(4-fluorophenyl)pyridinato-C,N)iridium(III) acetylacetonate into an appropriate deep blue phosphorescent host, 4,4'-bis(4-(triphenylsilyl)phenyl)-1,1'-binaphthyl as an emitting layer (EML). The WOLED has been achieved by effective confinement of triplet excitons to emit a warm white color. The optimized WOLED, with a simple structure as a hole transporting layer-EML-electron transporting layer, showed a maximum luminous efficiency of 22.38 cd/A, a maximum power efficiency of 12.01 lm/W, a maximum external quantum efficiency of 7.32%, and CIEx,y coordinates of (0.38,0.42) at 500 cd/m{sup 2}, respectively. - Highlights: • Highly efficient phosphorescent white organic light-emitting diode (WOLED) • Single emitting layer consists of synthesized deep blue host and orange emitter • The WOLED with high EL efficiencies due to efficient triplet exciton confinement.

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.

Investigation of deep levels in GaInNAs

International Nuclear Information System (INIS)

Abulfotuh, F.; Balcioglu, A.; Friedman, D.; Geisz, J.; Kurtz, S.

1999-01-01

This paper presents and discusses the first Deep-Level transient spectroscopy (DLTS) data obtained from measurements carried out on both Schottky barriers and homojunction devices of GaInNAs. The effect of N and In doping on the electrical properties of the GaNInAs devices, which results in structural defects and interface states, has been investigated. Moreover, the location and densities of deep levels related to the presence of N, In, and N+In are identified and correlated with the device performance. The data confirmed that the presence of N alone creates a high density of shallow hole traps related to the N atom and structural defects in the device. Doping by In, if present alone, also creates low-density deep traps (related to the In atom and structural defects) and extremely deep interface states. On the other hand, the co-presence of In and N eliminates both the interface states and levels related to structural defects. However, the device still has a high density of the shallow and deep traps that are responsible for the photocurrent loss in the GaNInAs device, together with the possible short diffusion length. copyright 1999 American Institute of Physics

Investigation of Deep Levels in GaInNas

International Nuclear Information System (INIS)

Balcioglu, A.; Friedman, D.; Abulfotuh, F.; Geisz, J.; Kurtz, S.

1998-01-01

This paper presents and discusses the first Deep-Level transient spectroscopy (DLTS) data obtained from measurements carried out on both Schottky barriers and homojunction devices of GaInNAs. The effect of N and In doping on the electrical properties of the GaNInAs devices, which results in structural defects and interface states, has been investigated. Moreover, the location and densities of deep levels related to the presence of N, In, and N+In are identified and correlated with the device performance. The data confirmed that the presence of N alone creates a high density of shallow hole traps related to the N atom and structural defects in the device. Doping by In, if present alone, also creates low-density deep traps (related to the In atom and structural defects) and extremely deep interface states. On the other hand, the co-presence of In and N eliminates both the interface states and levels related to structural defects. However, the device still has a high density of the shallow and deep traps that are responsible for the photocurrent loss in the GaNInAs device, together with the possible short diffusion length

DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

Science.gov (United States)

Wachinger, Christian; Reuter, Martin; Klein, Tassilo

2018-04-15

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

Deep 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...

Neuromodulation of Attentional Control in Major Depression: A Pilot DeepTMS Study

Directory of Open Access Journals (Sweden)

Jodie Naim-Feil

2016-01-01

Full Text Available While Major Depressive Disorder (MDD is primarily characterized by mood disturbances, impaired attentional control is increasingly identified as a critical feature of depression. Deep transcranial magnetic stimulation (deepTMS, a noninvasive neuromodulatory technique, can modulate neural activity and induce neuroplasticity changes in brain regions recruited by attentional processes. This study examined whether acute and long-term high-frequency repetitive deepTMS to the dorsolateral prefrontal cortex (DLPFC can attenuate attentional deficits associated with MDD. Twenty-one MDD patients and 26 matched control subjects (CS were administered the Beck Depression Inventory and the Sustained Attention to Response Task (SART at baseline. MDD patients were readministered the SART and depressive assessments following a single session (n=21 and after 4 weeks (n=13 of high-frequency (20 Hz repetitive deepTMS applied to the DLPFC. To control for the practice effect, CS (n=26 were readministered the SART a further two times. The MDD group exhibited deficits in sustained attention and cognitive inhibition. Both acute and long-term high-frequency repetitive frontal deepTMS ameliorated sustained attention deficits in the MDD group. Improvement after acute deepTMS was related to attentional recovery after long-term deepTMS. Longer-term improvement in sustained attention was not related to antidepressant effects of deepTMS treatment.

Neuromodulation of Attentional Control in Major Depression: A Pilot DeepTMS Study.

Science.gov (United States)

Naim-Feil, Jodie; Bradshaw, John L; Sheppard, Dianne M; Rosenberg, Oded; Levkovitz, Yechiel; Dannon, Pinhas; Fitzgerald, Paul B; Isserles, Moshe; Zangen, Abraham

2016-01-01

While Major Depressive Disorder (MDD) is primarily characterized by mood disturbances, impaired attentional control is increasingly identified as a critical feature of depression. Deep transcranial magnetic stimulation (deepTMS), a noninvasive neuromodulatory technique, can modulate neural activity and induce neuroplasticity changes in brain regions recruited by attentional processes. This study examined whether acute and long-term high-frequency repetitive deepTMS to the dorsolateral prefrontal cortex (DLPFC) can attenuate attentional deficits associated with MDD. Twenty-one MDD patients and 26 matched control subjects (CS) were administered the Beck Depression Inventory and the Sustained Attention to Response Task (SART) at baseline. MDD patients were readministered the SART and depressive assessments following a single session (n = 21) and after 4 weeks (n = 13) of high-frequency (20 Hz) repetitive deepTMS applied to the DLPFC. To control for the practice effect, CS (n = 26) were readministered the SART a further two times. The MDD group exhibited deficits in sustained attention and cognitive inhibition. Both acute and long-term high-frequency repetitive frontal deepTMS ameliorated sustained attention deficits in the MDD group. Improvement after acute deepTMS was related to attentional recovery after long-term deepTMS. Longer-term improvement in sustained attention was not related to antidepressant effects of deepTMS treatment.

Extraction of Urban Water Bodies from High-Resolution Remote-Sensing Imagery Using Deep Learning

Directory of Open Access Journals (Sweden)

Yang Chen

2018-05-01

Full Text Available Accurate information on urban surface water is important for assessing the role it plays in urban ecosystem services in the context of human survival and climate change. The precise extraction of urban water bodies from images is of great significance for urban planning and socioeconomic development. In this paper, a novel deep-learning architecture is proposed for the extraction of urban water bodies from high-resolution remote sensing (HRRS imagery. First, an adaptive simple linear iterative clustering algorithm is applied for segmentation of the remote-sensing image into high-quality superpixels. Then, a new convolutional neural network (CNN architecture is designed that can extract useful high-level features of water bodies from input data in a complex urban background and mark the superpixel as one of two classes: an including water or no-water pixel. Finally, a high-resolution image of water-extracted superpixels is generated. Experimental results show that the proposed method achieved higher accuracy for water extraction from the high-resolution remote-sensing images than traditional approaches, and the average overall accuracy is 99.14%.

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...

Text feature extraction based on deep learning: a review.

Science.gov (United States)

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

2017-01-01

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

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

High Temperature Reactor (HTR) Deep Burn Core and Fuel Analysis: Design Selection for the Prismatic Block Reactor

Energy Technology Data Exchange (ETDEWEB)

Francesco Venneri; Chang-Keun Jo; Jae-Man Noh; Yonghee Kim; Claudio Filippone; Jonghwa Chang; Chris Hamilton; Young-Min Kim; Ji-Su Jun; Moon-Sung Cho; Hong-Sik Lim; MIchael A. Pope; Abderrafi M. Ougouag; Vincent Descotes; Brian Boer

2010-09-01

The Deep Burn (DB) Project is a U.S. Department of Energy sponsored feasibility study of Transuranic Management using high burnup fuel in the high temperature helium cooled reactor (HTR). The DB Project consists of seven tasks: project management, core and fuel analysis, spent fuel management, fuel cycle integration, TRU fuel modeling, TRU fuel qualification, and HTR fuel recycle. In the Phase II of the Project, we conducted nuclear analysis of TRU destruction/utilization in the HTR prismatic block design (Task 2.1), deep burn fuel/TRISO microanalysis (Task 2.3), and synergy with fast reactors (Task 4.2). The Task 2.1 covers the core physics design, thermo-hydraulic CFD analysis, and the thermofluid and safety analysis (low pressure conduction cooling, LPCC) of the HTR prismatic block design. The Task 2.3 covers the analysis of the structural behavior of TRISO fuel containing TRU at very high burnup level, i.e. exceeding 50% of FIMA. The Task 4.2 includes the self-cleaning HTR based on recycle of HTR-generated TRU in the same HTR. Chapter IV contains the design and analysis results of the 600MWth DB-HTR core physics with the cycle length, the average discharged burnup, heavy metal and plutonium consumptions, radial and axial power distributions, temperature reactivity coefficients. Also, it contains the analysis results of the 450MWth DB-HTR core physics and the analysis of the decay heat of a TRU loaded DB-HTR core. The evaluation of the hot spot fuel temperature of the fuel block in the DB-HTR (Deep-Burn High Temperature Reactor) core under full operating power conditions are described in Chapter V. The investigated designs are the 600MWth and 460MWth DB-HTRs. In Chapter VI, the thermo-fluid and safety of the 600MWth DB-HTRs has been analyzed to investigate a thermal-fluid design performance at the steady state and a passive safety performance during an LPCC event. Chapter VII describes the analysis results of the TRISO fuel microanalysis of the 600MWth and 450

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

Directory of Open Access Journals (Sweden)

Tanel Pärnamaa

2017-05-01

Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

Science.gov (United States)

Pärnamaa, Tanel; Parts, Leopold

2017-05-05

High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.

A deep learning / neuroevolution hybrid for visual control

DEFF Research Database (Denmark)

Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

2017-01-01

This paper presents a deep learning / neuroevolution hybrid approach called DLNE, which allows FPS bots to learn to aim & shoot based only on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature...... representations, while the evolving network takes those features as inputs to infer actions. The results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution....

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Radio-active waste disposal and deep-sea biology

International Nuclear Information System (INIS)

Rice, A.L.

1978-01-01

The deep-sea has been widely thought of as a remote, sparsely populated, and biologically inactive environment, well suited to receive the noxious products of nuclear fission processes. Much of what is known of abyssal biology tends to support this view, but there are a few disquieting contra-indications. The realisation, in recent years, that many animal groups show a previously unsuspected high species diversity in the deep-sea emphasized the paucity of our knowledge of this environment. More dramatically, the discovery of a large, active, and highly mobile abysso-bentho-pelagic fauna changed the whole concept of abyssal life. Finally, while there is little evidence for the existence of vertical migration patterns linking the deep-sea bottom communities with those of the overlying water layers, there are similarly too few negative results for the possibility of such transport mechanisms to be dismissed. In summary, biological knowledge of the abyss is insufficient to answer the questions raised in connection with deep-sea dumping, but in the absence of adequate answers it might be dangerous to ignore the questions

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...

Dual effects of fluoxetine on mouse early embryonic development

International Nuclear Information System (INIS)

Kim, Chang-Woon; Choe, Changyong; Kim, Eun-Jin; Lee, Jae-Ik; Yoon, Sook-Young; Cho, Young-Woo; Han, Sunkyu; Tak, Hyun-Min; Han, Jaehee; Kang, Dawon

2012-01-01

Fluoxetine, a selective serotonin reuptake inhibitor, regulates a variety of physiological processes, such as cell proliferation and apoptosis, in mammalian cells. Little is known about the role of fluoxetine in early embryonic development. This study was undertaken to investigate the effect of fluoxetine during mouse early embryonic development. Late two-cell stage embryos (2-cells) were cultured in the presence of various concentrations of fluoxetine (1 to 50 μM) for different durations. When late 2-cells were incubated with 5 μM fluoxetine for 6 h, the percentage that developed into blastocysts increased compared to the control value. However, late 2-cells exposed to fluoxetine (5 μM) over 24 h showed a reduction in blastocyst formation. The addition of fluoxetine (5 μM) together with KN93 or KN62 (calcium/calmodulin-dependent protein kinase II (CaMKII) inhibitors) failed to increase blastocyst formation. Fluoxetine treatment inhibited TREK-1 and TREK-2, members of the two-pore domain K + channel family expressed in mouse embryos, activities, indicating that fluoxetine-induced membrane depolarization in late 2-cells might have resulted from TREK inhibition. In addition, long-term exposure to fluoxetine altered the TREK mRNA expression levels. Furthermore, injection of siRNA targeting TREKs significantly decreased blastocyst formation by ∼ 30% compared to injection of scrambled siRNA. Long-term exposure of fluoxetine had no effect on blastocyst formation of TREK deficient embryos. These results indicate that low-dose and short-term exposures of late 2-cells to fluoxetine probably increase blastocyst formation through activation of CaMKII-dependent signal transduction pathways, whereas long-term exposure decreases mouse early embryonic development through inhibition of TREK channel gating. Highlights: ► Short-term exposure of 2-cells to fluoxetine enhances mouse blastocyst formation. ► The enhancive effect of fluoxetine is resulted from CaMKII activation

Dual effects of fluoxetine on mouse early embryonic development

Energy Technology Data Exchange (ETDEWEB)

Kim, Chang-Woon [Department of Physiology and Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju 660-751 (Korea, Republic of); Department of Obstetrics and Gynecology, Samsung Changwon Hospital, Sungkyunkwan University, Changwon 630-723 (Korea, Republic of); Choe, Changyong [National Institute of Animal Science, RDA, Cheonan 330-801 (Korea, Republic of); Kim, Eun-Jin [Department of Physiology and Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju 660-751 (Korea, Republic of); Lee, Jae-Ik [Department of Obstetrics and Gynecology, Gyeongsang National University Hospital, Jinju 660-702 (Korea, Republic of); Yoon, Sook-Young [Fertility Center of CHA Gangnam Medical Center, CHA University, Seoul 135-081 (Korea, Republic of); Cho, Young-Woo; Han, Sunkyu; Tak, Hyun-Min; Han, Jaehee [Department of Physiology and Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju 660-751 (Korea, Republic of); Kang, Dawon, E-mail: dawon@gnu.ac.kr [Department of Physiology and Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju 660-751 (Korea, Republic of)

2012-11-15

Fluoxetine, a selective serotonin reuptake inhibitor, regulates a variety of physiological processes, such as cell proliferation and apoptosis, in mammalian cells. Little is known about the role of fluoxetine in early embryonic development. This study was undertaken to investigate the effect of fluoxetine during mouse early embryonic development. Late two-cell stage embryos (2-cells) were cultured in the presence of various concentrations of fluoxetine (1 to 50 μM) for different durations. When late 2-cells were incubated with 5 μM fluoxetine for 6 h, the percentage that developed into blastocysts increased compared to the control value. However, late 2-cells exposed to fluoxetine (5 μM) over 24 h showed a reduction in blastocyst formation. The addition of fluoxetine (5 μM) together with KN93 or KN62 (calcium/calmodulin-dependent protein kinase II (CaMKII) inhibitors) failed to increase blastocyst formation. Fluoxetine treatment inhibited TREK-1 and TREK-2, members of the two-pore domain K{sup +} channel family expressed in mouse embryos, activities, indicating that fluoxetine-induced membrane depolarization in late 2-cells might have resulted from TREK inhibition. In addition, long-term exposure to fluoxetine altered the TREK mRNA expression levels. Furthermore, injection of siRNA targeting TREKs significantly decreased blastocyst formation by ∼ 30% compared to injection of scrambled siRNA. Long-term exposure of fluoxetine had no effect on blastocyst formation of TREK deficient embryos. These results indicate that low-dose and short-term exposures of late 2-cells to fluoxetine probably increase blastocyst formation through activation of CaMKII-dependent signal transduction pathways, whereas long-term exposure decreases mouse early embryonic development through inhibition of TREK channel gating. Highlights: ► Short-term exposure of 2-cells to fluoxetine enhances mouse blastocyst formation. ► The enhancive effect of fluoxetine is resulted from Ca

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...

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.

Comparison of Conventional Deep Drawing, Hydromechanical Deep-Drawing and High Pressure Sheet Metal Forming by Numerical Experiments

International Nuclear Information System (INIS)

Oender, I. Erkan; Tekkaya, A. Erman

2005-01-01

Increasing use of new technologies in automotive and aircraft applications requires intensive research and developments on sheet metal forming processes. This study focuses on the assessment of sheet hydroforming, hydro-mechanical deep drawing and conventional deep-drawing processes by performing a systematic analysis by numerical simulations. Circular, elliptic, rectangular and square cross-section cups have been selected for the geometry spectrum. Within the range of each cross section, depth, drawing ratio and fillet radii have been altered systematically. St14 stainless steel has been used as the material throughout the study. The deformation behavior has been described by an elasto-plastic material model and all numerical simulations have been carried out by using a dynamic-explicit commercial finite element code. During the analyses each workpiece is produced by the three competing processes. The analyses results such as sheet thickness distribution, necking, forming of radii etc., are used for assessing the success of each forming process alternative. The analyses revealed that depending on the workpiece geometry and dimensional properties certain processes are preferable for obtaining satisfactory products. The process windows for each process have been established based on the analyzed parameters of the three different product geometries. This data is expected to be useful for selecting the appropriate production process for a given workpiece geometry

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...

A critical study of high efficiency deep grinding

International Nuclear Information System (INIS)

Johnstone, Iain

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 experimental and theoretical means applied to two widely used materials, M50 bearing steel and IN718 nickel based superalloy. It has been shown that this grinding method using a stiff grinding centre such as the Edgetek 5-axis machine is a viable process. Using a number of experimental designs, produced results which were analysed using a variety of methods including visual assessment, sub-surface microscopy and surface analysis using a Scanning Electron Microscope (SEM), residual stress measurement using X-Ray Diffraction (XRD) techniques, Barkhausen Noise Amplitude (BNA) measurements, surface roughness and Vickers micro-hardness appraisal. It has been shown that the fundamentals of the HEDG process have been understood through experimental as well as theoretical means and that through the various thermal models used, grinding temperatures can be predicted to give more control over this dynamic process. The main contributions to knowledge are made up of a number of elements within the grinding environment, the most important being the demonstration of the HEDG effect, explanation of the phenomenon and the ability to model the process. It has also been shown that grinding is a dynamic process and factors such as wheel wear will result in a continuous change in the optimum grinding conditions for a given material and wheel combination. With the significance of these factors recognised, they can be accounted for within an industrial adaptive control scenario with the process engineer confident of a

L-shaped fiber-chip grating couplers with high directionality and low reflectivity fabricated with deep-UV lithography.

Science.gov (United States)

Benedikovic, Daniel; Alonso-Ramos, Carlos; Pérez-Galacho, Diego; Guerber, Sylvain; Vakarin, Vladyslav; Marcaud, Guillaume; Le Roux, Xavier; Cassan, Eric; Marris-Morini, Delphine; Cheben, Pavel; Boeuf, Frédéric; Baudot, Charles; Vivien, Laurent

2017-09-01

Grating couplers enable position-friendly interfacing of silicon chips by optical fibers. The conventional coupler designs call upon comparatively complex architectures to afford efficient light coupling to sub-micron silicon-on-insulator (SOI) waveguides. Conversely, the blazing effect in double-etched gratings provides high coupling efficiency with reduced fabrication intricacy. In this Letter, we demonstrate for the first time, to the best of our knowledge, the realization of an ultra-directional L-shaped grating coupler, seamlessly fabricated by using 193 nm deep-ultraviolet (deep-UV) lithography. We also include a subwavelength index engineered waveguide-to-grating transition that provides an eight-fold reduction of the grating reflectivity, down to 1% (-20  dB). A measured coupling efficiency of -2.7  dB (54%) is achieved, with a bandwidth of 62 nm. These results open promising prospects for the implementation of efficient, robust, and cost-effective coupling interfaces for sub-micrometric SOI waveguides, as desired for large-volume applications in silicon photonics.

Development of an assessment methodology for the disposal of high-level radioactive waste into deep ocean sediments

International Nuclear Information System (INIS)

Murray, C.N.; Stanners, D.A.

1982-01-01

This paper presents the results of a theoretical study concerning the option of disposal of vitrified high activity waste (HAW) into deep ocean sediments. The development of a preliminary methodology is presented which concerns the assessment of the possible effects of a release of radioactivity on the ecosystem and eventually on man. As the long-term hazard is considered basically to be due to transuranic elements (and daughter products) the period studied for the assessment is from 10 3 to 10 6 years. A simple ecosystem model is developed so that the transfer of activity between different compartments of the systems, e.g. the sediment column, sediment-water interface, deep sea water column, can be estimated. A critical pathway analysis is made for an imaginary critical group in order to complete the assessment. A sensitivity analysis is undertaken using the computed minimum-maximum credible values for the different parameters used in the calculations in order to obtain a minimum-maximum dose range for a critical group. (Auth.)

Deep-blue efficient OLED based on NPB with little efficiency roll-off under high current density

Science.gov (United States)

Liu, Jian

2017-03-01

NPB usually is used as a hole-transport layer in OLED. In fact, it is a standard pure blue-emission material. However, its light-emitting efficiency in OLED is low due to emissive nature of organic material. Herein, a deep-blue OLDE based on NPB was fabricated. The light-emitting efficiency of the device demonstrates a moderate value, and efficiency roll-off is little under high current density. The device demonstrates that the electroplex's emission decreases with increasing electric field intensity.

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.

Feasibility of disposal of high-level radioactive waste into the seabed. Volume 6: Deep-sea biology, biological processes and radiobiology

International Nuclear Information System (INIS)

Pentreath, R.J.; Hargrave, B.T.; Roe, H.S.J.; Sibuet, M.

1988-01-01

One of the options suggested for disposal of high-level radioactive waste resulting from the generation of nuclear power is burial beneath the deep ocean floor in geologically stable sediment formations which have no economic value. The 8-volume series provides an assessment of the technical feasibility and radiological safety of this disposal concept based on the results obtained by ten years of co-operation and information exchange among the Member countries participating in the NEA Seabed Working Group. This report summarizes the biological description of selected sites, the means by which radionuclides could result in human exposure via seafood pathways, and the doses likely to be received by, and effects on, the deep-sea fauna

Deep learning with convolutional neural network in radiology.

Science.gov (United States)

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

2018-04-01

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

Deep reversible storage. Design options for the storage in deep geological formation - High-medium activity, long living wastes 2009 milestone

International Nuclear Information System (INIS)

2010-09-01

This report aims at presenting a synthesis of currently studied solutions for the different components of the project of deep geological radioactive waste storage centre. For each of these elements, the report indicates the main operational objectives to be taken into account in relationship with safety functions or with reversibility. It identifies the currently proposed design options, presents the technical solutions (with sometime several possibilities), indicates industrial references (in the nuclear sector, in underground works) and comments results of technological tests performed by the ANDRA. After a description of functionalities and of the overall organisation of storage components, the different following elements and aspects are addressed: surface installations, underground architecture, parcel transfer between the surface and storage cells, storage container for medium-activity long-life (MAVL) waste, storage cell for medium-activity long-life waste, handling of MAVL parcels in storage cells, storage container for high-activity (HA) waste, storage cell for HA waste, handling of HA parcels in storage cells, and works for site closing

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

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.

Deep-Burn High Temperature Reactor - TRU Utilization and Nuclear Waste Management

International Nuclear Information System (INIS)

Tsvetkov, Pavel V.

2013-01-01

Summary of our historical and ongoing efforts: • We have a long history of R and Ds supporting DB-HTRs. Our R and Ds carry V and V and are consistent with ongoing benchmark efforts. • We are looking at DB-HTR configurations based on HTTR block and GA block (NGNP). Both offer advantages. • MAs as a Fuel lead to the designs of Ultra-Long Life VHTRs, which may be focused on Deep Burn or autonomy (not HLW management). • Our role in the Deep Burn Project R and D package was focused on 3D optimization and related software development. • Scenario studies towards an Environmentally Benign Sustainable and Secure Energy Source (integration of DB-HTRs within a fuel cycle) demonstrate advantages of DB-HTRs. • Advanced sensing and 3D mapping are of importance to DB-HTRs. • Fission product management in HTRs is a viable supplementary option in addition to their potential TRU management role in advanced fuel cycle scenarios

Viral infections as controlling factors for the deep biosphere? (Invited)

Science.gov (United States)

Engelen, B.; Engelhardt, T.; Sahlberg, M.; Cypionka, H.

2009-12-01

The marine deep biosphere represents the largest biotope on Earth. Throughout the last years, we have obtained interesting insights into its microbial community composition. However, one component that was completely overlooked so far is the viral inventory of deep-subsurface sediments. While viral infections were identified to have a major impact on the benthic microflora of deep-sea surface sediments (Danavaro et al. 2008), no studies were performed on deep-biosphere samples, so far. As grazers probably play only a minor role in anoxic and highly compressed deep sediments, viruses might be the main “predators” for indigenous microorganisms. Furthermore, the release of cell components, called “the viral shunt”, could have a major impact on the deep biosphere in providing labile organic compounds to non-infected microorganisms in these generally nutrient depleted sediments. However, direct counting of viruses in sediments is highly challenging due to the small size of viruses and the high background of small particles. Even molecular surveys using “universal” PCR primers that target phage-specific genes fail due to the vast phage diversity. One solution for this problem is the lysogenic viral life cycle as many bacteriophages integrate their DNA into the host genome. It is estimated that up to 70% of cultivated bacteria contain prophages within their genome. Therefore, culture collections (Batzke et al. 2007) represent an archive of the viral composition within the respective habitat. These prophages can be induced to become free phage particles in stimulation experiments in which the host cells are set under certain stress situations such as a treatment with UV exposure or DNA-damaging antibiotics. The study of the viral component within the deep biosphere offers to answer the following questions: To which extent are deep-biosphere populations controlled by viral infections? What is the inter- and intra-specific diversity and the host-specific viral

Highly Sensitive Photon Counting Detectors for Deep Space Optical Communications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — A new type of a photon-counting photodetector is proposed to advance the state-of the-art in deep space optical communications technology. The proposed detector...

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.

High Acidification Rate of Norwegian Sea Revealed by Boron Isotopes in the Deep-Sea Coral Madrepora Oculata

Science.gov (United States)

Gonzalez, C.; Douville, E.; Hall-Spencer, J.; Montagna, P.; Louvat, P.; Gaillardet, J.; Frank, N.; Bordier, L.; Juillet-Leclerc, A.

2012-12-01

Ocean acidification and global warming due to the increase of anthropogenic CO2 are major threats for marine calcifying organisms, such as deep-sea corals, particularly in high-latitude regions. In order to evaluate the current anthropogenic perturbation and to properly assess the impacts and responses of calcifiers to previous changes in pH it is critical to investigate past changes of the seawater carbonate system. Unfortunately, current instrumental records of oceanic pH are limited, covering only a few decades. Scleractinian coral skeletons record chemical parameters of the seawater in which they grow. However, pH variability over multidecadal timescales remains largely unknown in intermediate and deep seawater masses. Here we present a study that highlights the potential of deep-sea-corals to overcome the lack of long-term pH records and that emphasizes a rapid acidification of high latitude subsurface waters of Norwegian Sea during the past decades. We have reconstructed seawater pH and temperature from a well dated deep-sea coral specimen Madrepora oculata collected alive from Røst reef in Norwegian Sea (67°N, 9°E, 340 m depth). This large branching framework forming coral species grew its skeleton over more than four decades determined using AMS 14C and 210Pb dating (Sabatier et al. 2012). B-isotopes and Li/Mg ratios yield an acidification rate of about -0.0030±0.0008 pH-unit.year-1 and a warming of 0.3°C during the past four decades (1967-2007). Overall our reconstruction technique agrees well with previous pH calculations (Hönisch et al., 2007 vs. Trotter et al., 2011 and McCulloch et al., 2012, i.e. the iterative method), but additional corrections are here applied using stable isotope correlations (O, C, B) to properly address kinetic fractionation of boron isotopes used for pH reconstruction. The resulting pH curve strongly anti-correlates with the annual NAO index, which further strengthens our evidence for the ocean acidification rate

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.

LUMINOUS AND HIGH STELLAR MASS CANDIDATE GALAXIES AT z ≈ 8 DISCOVERED IN THE COSMIC ASSEMBLY NEAR-INFRARED DEEP EXTRAGALACTIC LEGACY SURVEY

International Nuclear Information System (INIS)

Yan Haojing; Finkelstein, Steven L.; Huang, Kuang-Han; Ryan, Russell E.; Ferguson, Henry C.; Koekemoer, Anton M.; Grogin, Norman A.; Dickinson, Mark; Newman, Jeffrey A.; Somerville, Rachel S.; Davé, Romeel; Faber, S. M.; Papovich, Casey; Guo Yicheng; Giavalisco, Mauro; Lee, Kyoung-soo; Reddy, Naveen; Siana, Brian D.; Cooray, Asantha R.; Hathi, Nimish P.

2012-01-01

One key goal of the Hubble Space Telescope Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey is to track galaxy evolution back to z ≈ 8. Its two-tiered ''wide and deep'' strategy bridges significant gaps in existing near-infrared surveys. Here we report on z ≈ 8 galaxy candidates selected as F105W-band dropouts in one of its deep fields, which covers 50.1 arcmin 2 to 4 ks depth in each of three near-infrared bands in the Great Observatories Origins Deep Survey southern field. Two of our candidates have J 1 mag brighter than any previously known F105W-dropouts. We derive constraints on the bright end of the rest-frame ultraviolet luminosity function of galaxies at z ≈ 8, and show that the number density of such very bright objects is higher than expected from the previous Schechter luminosity function estimates at this redshift. Another two candidates are securely detected in Spitzer Infrared Array Camera images, which are the first such individual detections at z ≈ 8. Their derived stellar masses are on the order of a few × 10 9 M ☉ , from which we obtain the first measurement of the high-mass end of the galaxy stellar mass function at z ≈ 8. The high number density of very luminous and very massive galaxies at z ≈ 8, if real, could imply a large stellar-to-halo mass ratio and an efficient conversion of baryons to stars at such an early time.

Extracting Databases from Dark Data with DeepDive.

Science.gov (United States)

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

2016-01-01

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

Maximization of Transuranic Deep-Burn in High Temperature Gas-Cooled Reactor

International Nuclear Information System (INIS)

Kim, Yong Hee; Kim, K. S.; Hong, S. G.; Shim, H. J.; Jo, C. K.; Lee, S. W.

2008-03-01

An optimization study of a single-pass transuranic (TRU) deep burn (DB) has been performed for a block-type modular helium reactor (MHR) proposed. A high-burnup TRU feed vector from light water reactors is considered. For three dimensional equilibrium cores, the performance analysis is done by using the Monte Carlo code McCARD. The core optimization is performed from the viewpoints of the core configuration, fuel management, TRISO fuel specification, and neutron spectrum. With regard to core configuration, two annular cores are investigated in terms of the neutron economy. A conventional radial shuffling scheme of fuel blocks is compared with an axial-only block-shuffling strategy in terms of the fuel bum up and core power distributions. The impact of the kernel size of the TRISO fuel is evaluated, and a diluted kernel, instead of a conventional concentrated kernel, is introduced to maximize the TRU burnup by reducing the self-shielding effects of the TRISO particles. In addition, it is shown that the core power distribution can be effectively controlled by a zoning of the packing fraction of the TRISO fuels. We also have shown that a long-cycle DB-MHR core can be designed by using a two- or three-batch fuel-reloading scheme, at the expense of only a marginal decrease of the TRU discharge bum up. Preliminary safety characteristics of a DBMHR core have been investigated in terms of the temperature coefficients and effective delayed neutron fraction. It has been found that, depending on the fuel management scheme and fuel specifications, the TRU burnup in an optimized DB-MHR core can be over 60% in a single-pass irradiation campaign. In addition, the equilibrium cycle mass balance analyses were also performed for 12 fuel cycles and the impact of TRU deep-bum on the repository was evaluated as well. Additionally, an SFR (Sodium Fast Reactor) fed with DB-MHR spent fuel were designed and characterized

Development of Thermal Radiation Experiments Kit Based on Data Logger for Physics Learning Media

Science.gov (United States)

Permana, H.; Iswanto, B. H.

2018-04-01

Thermal Radiation Experiments Kit (TREK) based on data logger for physics learning media was developed. TREK will be used as a learning medium on the subject of Temperature and Heat to explain the concept of emissivity of a material in grade XI so that it can add variations of experiments which are commonly done such as thermal expansion, transfer of thermal energy (conduction, convection, and radiation), and specific heat capacity. DHT11 sensor is used to measure temperature and microcontroller Arduino-uno used as data logger. The object tested are in the form of coated glass thin films and aluminum with different colors. TREK comes with a user manual and student worksheet (LKS) to make it easier for teachers and students to use. TREK was developed using the ADDIE Development Model (Analyze, Design, Development, Implementation, and Evaluation). And validated by experts, physics teachers, and students. Validation instrument is a questionnaire with a five-item Likert response scale with reviewed aspect coverage: appropriate content and concepts, design, and user friendly. The results showed that TREK was excellent (experts 88.13%, science teachers 95.68%, and students 85.77%).

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...

Hydro-mechanical deep drawing of rolled magnesium sheets

Energy Technology Data Exchange (ETDEWEB)

Bach, F.W.; Rodman, M.; Rossberg, A. [Hannover Univ., Garbsen (Germany). Inst. of Materials Science; Behrens, B.A.; Vogt, O. [Hannover Univ., Garbsen (DE). Inst. of Metal Forming and Metal Forming Machine Tools (IFUM)

2005-12-01

Magnesium sheets offer high specific properties which make them very attractive in modern light weight constructions. The main obstacles for a wider usage are their high production costs, the poor corrosion properties and the limited ductility. Until today, forming processes have to be conducted at temperatures well above T=220 C. In the first place, this is a cost factor. Moreover, technical aspects, such as grain growth or the limited use of lubrication speak against high temperatures. The first aim of the presented research work is to increase the ductility at lower temperatures by alloy modification and by an adapted rolling technology. The key factor to reach isotropic mechanical properties and increased limit drawing ratios in deep drawing tools, is to achieve fine, homogeneous microstructures. This can be done by cross rolling at moderate temperatures. The heat treatment has to be adapted accordingly. In a second stage, hydro-mechanical deep drawing experiments were carried out at elevated temperature. The results show that the forming behaviour of the tested Mg-alloys is considerably improved compared to conventional deep drawing. (orig.)

A fuel performance analysis for a 450 MWth deep burn-high temperature reactor

International Nuclear Information System (INIS)

Kim, Young Min; Jo, Chang Keun; Jun, Ji Su; Cho, Moon Sung; Venneri, Francesco

2011-01-01

Highlights: → We have checked, through a fuel performance analysis, if a 450 MW th high temperature reactor was safe for the deep burn of a TRU fuel. → During a core heat-up event, the fuel temperature was below 1600 deg. C and the maximum gas pressure in the void of coated fuel particle was about 90 MPa. → At elevated temperatures of the accident event, the failure fraction of coated fuel particles resulted from the mechanical failure and the thermal decomposition of the SiC barrier was 3.30 x 10 -3 . - Abstract: A performance analysis for a 450 MW th deep burn-high temperature reactor (DB-HTR) fuel was performed using COPA, a fuel performance analysis code of Korea Atomic Energy Research Institute (KAERI). The code computes gas pressure buildup in the void volume of a tri-isotropic coated fuel particle (TRISO), temperature distribution in a DB-HTR fuel, thermo-mechanical stress in a coated fuel particle (CFP), failure fractions of a batch of CFPs, and fission product (FP) releases into the coolant. The 350 μm DB-HTR kernel is composed of 30% UO 2 + 70% (5% NpO 2 + 95% PuO 1.8 ) mixed with 0.6 moles of silicon carbide (SiC) per mole of heavy metal. The DB-HTR is operated at the constant temperature and power of 858 deg. C and 39.02 mW per CFP for 1395 effective full power days (EFPD) and is subjected to a core heat-up event for 250 h during which the maximum coolant temperature reaches 1548.70 deg. C. Within the normal operating temperature, the fuel showed good thermal and mechanical integrity. At elevated temperatures of the accident event, the failure fraction of CFPs resulted from the mechanical failure (MF) and the thermal decomposition (TD) of the SiC barrier is 3.30 x 10 -3 .

The dynamics of biogeographic ranges in the deep sea.

Science.gov (United States)

McClain, Craig R; Hardy, Sarah Mincks

2010-12-07

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

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

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 ...

Jumbo Space Environment Simulation and Spacecraft Charging Chamber Characterization

Science.gov (United States)

2015-04-09

probes for Jumbo. Both probes are produced by Trek Inc. Trek probe model 370 is capable of -3 to 3kV and has an extremely fast, 50µs/kV response to...changing surface potentials. Trek probe 341B is capable of -20 to 20kV with a 200 µs/kV response time. During our charging experiments the probe sits...unlimited. 12 REFERENCES [1] R. D. Leach and M. B. Alexander, "Failures and anomalies attributed to spacecraft charging," NASA RP-1375, Marshall Space

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

Directory of Open Access Journals (Sweden)

Peter Christiansen

2016-11-01

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

Deep Charging Evaluation of Satellite Power and Communication System Components

Science.gov (United States)

Schneider, T. A.; Vaughn, J. A.; Chu, B.; Wong, F.; Gardiner, G.; Wright, K. H.; Phillips, B.

2016-01-01

Deep charging, in contrast to surface charging, focuses on electron penetration deep into insulating materials applied over conductors. A classic example of this scenario is an insulated wire. Deep charging can pose a threat to material integrity, and to sensitive electronics, when it gives rise to an electrostatic discharge or arc. With the advent of Electric Orbit Raising, which requires spiraling through Earth's radiation belts, satellites are subjected to high energy electron environments which they normally would not encounter. Beyond Earth orbit, missions to Jupiter and Saturn face deep charging concerns due to the high energy radiation environments. While predictions can be made about charging in insulating materials, it is difficult to extend those predictions to complicated geometries, such as the case of an insulating coating around a small wire, or a non-uniform silicone grouting on a bus bar. Therefore, to conclusively determine the susceptibility of a system to arcs from deep charging, experimental investigations must be carried out. This paper will describe the evaluation carried out by NASA's Marshall Space Flight Center on subscale flight-like samples developed by Space Systems/Loral, LLC. Specifically, deep charging evaluations of solar array wire coupons, a photovoltaic cell coupon, and a coaxial microwave transmission cable, will be discussed. The results of each evaluation will be benchmarked against control sample tests, as well as typical power system levels, to show no significant deep charging threat existed for this set of samples under the conditions tested.

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.

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

DEFF Research Database (Denmark)

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

2009-01-01

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

Periodic arrays of deep nanopores made in silicon with reactive ion etching and deep UV lithography

International Nuclear Information System (INIS)

Woldering, Leon A; Tjerkstra, R Willem; Vos, Willem L; Jansen, Henri V; Setija, Irwan D

2008-01-01

We report on the fabrication of periodic arrays of deep nanopores with high aspect ratios in crystalline silicon. The radii and pitches of the pores were defined in a chromium mask by means of deep UV scan and step technology. The pores were etched with a reactive ion etching process with SF 6 , optimized for the formation of deep nanopores. We have realized structures with pitches between 440 and 750 nm, pore diameters between 310 and 515 nm, and depth to diameter aspect ratios up to 16. To the best of our knowledge, this is the highest aspect ratio ever reported for arrays of nanopores in silicon made with a reactive ion etching process. Our experimental results show that the etching rate of the nanopores is aspect-ratio-dependent, and is mostly influenced by the angular distribution of the etching ions. Furthermore we show both experimentally and theoretically that, for sub-micrometer structures, reducing the sidewall erosion is the best way to maximize the aspect ratio of the pores. Our structures have potential applications in chemical sensors, in the control of liquid wetting of surfaces, and as capacitors in high-frequency electronics. We demonstrate by means of optical reflectivity that our high-quality structures are very well suited as photonic crystals. Since the process studied is compatible with existing CMOS semiconductor fabrication, it allows for the incorporation of the etched arrays in silicon chips

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.

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.

Deep seismic profiling of the continents and their margins

DEFF Research Database (Denmark)

Ito, T.; Iwasaki, T.; Thybo, Hans

2009-01-01

, in many applications, the methods are used up-to their limits at the present technological state. Therefore, development of methods has high priority in the seismic community. This volume provides an overview of recent development of deep seismic techniques and their application to the imaging and probing......Application of deep seismic methods to studies of the crust and lithospheric mantle receives considerable interest and the methods are constantly refined and new methods are developed, which allows the extension of studies to new subjects and regions. Deep seismic methods are applied to a long...

Structure and Stability of High-Pressure Dolomite with Implications for the Earth's Deep Carbon Cycle

Science.gov (United States)

Solomatova, N. V.; Asimow, P. D.

2014-12-01

Carbon is subducted into the mantle primarily in the form of metasomatically calcium-enriched basaltic rock, calcified serpentinites and carbonaceous ooze. The fate of these carbonates in subduction zones is not well understood. End-member CaMg(CO3)2 dolomite typically breaks down into two carbonates at 2-7 GPa, which may further decompose to oxides and CO2-bearing fluid. However, high-pressure X-ray diffraction experiments have recently shown that the presence of iron may be sufficient to stabilize dolomite I to high pressures, allowing the transformation to dolomite II at 17 GPa and subsequently to dolomite III at 35 GPa [1][2]. Such phases may be a principal host for deeply subducted carbon. The structure and equation of state of these high-pressure phases is debated and the effect of varying concentrations of iron is unknown, creating a need for theoretical calculations. Here we compare calculated dolomite structures to experimentally observed phases. Using the Vienna ab-initio simulation package (VASP) interfaced with a genetic algorithm that predicts crystal structures (USPEX), a monoclinic phase with space group 5 ("dolomite sg5") was found for pure end-member dolomite. Dolomite sg5 has a lower energy than reported dolomite structures and an equation of state that resembles that of dolomite III. It is possible that dolomite sg5 is not achieved experimentally due to a large energy barrier and a correspondingly large required volume drop, resulting in the transformation to metastable dolomite II. Due to the complex energy landscape for candidate high-pressure dolomite structures, it is likely that several competing polymorphs exist. Determining the behavior of high-pressure Ca-Mg-Fe(-Mn) dolomite phases in subduction environments is critical for our understanding of the Earth's deep carbon cycle and supercell calculations with Fe substitution are in progress. [1] Mao, Z., Armentrout, M., Rainey, E., Manning, C. E., Dera, P., Prakapenka, V. B., and Kavner, A

Challenging oil bioremediation at deep-sea hydrostatic pressure

Directory of Open Access Journals (Sweden)

Alberto Scoma

2016-08-01

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

Opportunities and Challenges in Deep Mining: A Brief Review

Directory of Open Access Journals (Sweden)

Pathegama G. Ranjith

2017-08-01

Full Text Available Mineral consumption is increasing rapidly as more consumers enter the market for minerals and as the global standard of living increases. As a result, underground mining continues to progress to deeper levels in order to tackle the mineral supply crisis in the 21st century. However, deep mining occurs in a very technical and challenging environment, in which significant innovative solutions and best practice are required and additional safety standards must be implemented in order to overcome the challenges and reap huge economic gains. These challenges include the catastrophic events that are often met in deep mining engineering: rockbursts, gas outbursts, high in situ and redistributed stresses, large deformation, squeezing and creeping rocks, and high temperature. This review paper presents the current global status of deep mining and highlights some of the newest technological achievements and opportunities associated with rock mechanics and geotechnical engineering in deep mining. Of the various technical achievements, unmanned working-faces and unmanned mines based on fully automated mining and mineral extraction processes have become important fields in the 21st century.

Sacrificial structures for deep reactive ion etching of high-aspect ratio kinoform silicon x-ray lenses

DEFF Research Database (Denmark)

Stöhr, Frederik; Michael-Lindhard, Jonas; Hübner, Jörg

2015-01-01

This article describes the realization of complex high-aspect ratio silicon structures with feature dimensions from 100 lm to 100nm by deep reactive ion etching using the Bosch process. As the exact shape of the sidewall profiles can be crucial for the proper functioning of a device, the authors...... of the sacrificial structures was accomplished by thermal oxidation and subsequent selective wet etching. The effects of the dimensions and relative placement of sacrificial walls and pillars on the etching result were determined through systematic experiments. The authors applied this process for exact sidewall...

Validation of a high-power, time-resolved, near-infrared spectroscopy system for measurement of superficial and deep muscle deoxygenation during exercise.

Science.gov (United States)

Koga, Shunsaku; Barstow, Thomas J; Okushima, Dai; Rossiter, Harry B; Kondo, Narihiko; Ohmae, Etsuko; Poole, David C

2015-06-01

Near-infrared assessment of skeletal muscle is restricted to superficial tissues due to power limitations of spectroscopic systems. We reasoned that understanding of muscle deoxygenation may be improved by simultaneously interrogating deeper tissues. To achieve this, we modified a high-power (∼8 mW), time-resolved, near-infrared spectroscopy system to increase depth penetration. Precision was first validated using a homogenous optical phantom over a range of inter-optode spacings (OS). Coefficients of variation from 10 measurements were minimal (0.5-1.9%) for absorption (μa), reduced scattering, simulated total hemoglobin, and simulated O2 saturation. Second, a dual-layer phantom was constructed to assess depth sensitivity, and the thickness of the superficial layer was varied. With a superficial layer thickness of 1, 2, 3, and 4 cm (μa = 0.149 cm(-1)), the proportional contribution of the deep layer (μa = 0.250 cm(-1)) to total μa was 80.1, 26.9, 3.7, and 0.0%, respectively (at 6-cm OS), validating penetration to ∼3 cm. Implementation of an additional superficial phantom to simulate adipose tissue further reduced depth sensitivity. Finally, superficial and deep muscle spectroscopy was performed in six participants during heavy-intensity cycle exercise. Compared with the superficial rectus femoris, peak deoxygenation of the deep rectus femoris (including the superficial intermedius in some) was not significantly different (deoxyhemoglobin and deoxymyoglobin concentration: 81.3 ± 20.8 vs. 78.3 ± 13.6 μM, P > 0.05), but deoxygenation kinetics were significantly slower (mean response time: 37 ± 10 vs. 65 ± 9 s, P ≤ 0.05). These data validate a high-power, time-resolved, near-infrared spectroscopy system with large OS for measuring the deoxygenation of deep tissues and reveal temporal and spatial disparities in muscle deoxygenation responses to exercise. Copyright © 2015 the American Physiological Society.

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 ...

Formas particulares de comunicação em blogs nerd/geek: expressões linguísticas relacionadas às produções das franquias Star Wars e Star Trek

Directory of Open Access Journals (Sweden)

Angela Dillmann Nunes Bicca

2014-11-01

Full Text Available Diversos blogs produzidos por integrantes de grupos culturais juvenis nerd/geek têm posto em circulação expressões linguísticas que assumem significados particulares para essas ‘tribos urbanas’, orquestrando os processos por meio dos quais suas identidades têm sido discursivamente produzidas. Nesta perspectiva, partindo das discussões promovidas pelos estudos culturais de vertente pós-estruturalista, e compreendendo os blogs como espaços de produção de saber, atentamos para os modos como expressões advindas das séries de filmes Star Wars e Star Trek são requeridas nos blogs para criar modos particulares de comunicação nerd/geek. Para desenvolver as análises, selecionamos sete blogs disponíveis na Internet, dentre um conjunto de 97 examinados nos meses de setembro e outubro de 2013. Excertos retirados dos blogs foram discutidos a partir do conceito de representação cultural, indicando que expressões, tais como ‘padawan’, ‘que a força esteja com vocês’ e ‘vida longa e prospera’, designam, respectivamente, sujeitos aprendizes e formas de despedida em situações nas quais um grande desafio está por ser assumido.

Deep-sea Hexactinellida (Porifera) of the Weddell Sea

Science.gov (United States)

Janussen, Dorte; Tabachnick, Konstantin R.; Tendal, Ole S.

2004-07-01

New Hexactinellida from the deep Weddel Sea are described. This moderately diverse hexactinellid fauna includes 14 species belonging to 12 genera, of which five species and one subgenus are new to science: Periphragella antarctica n. sp., Holascus pseudostellatus n. sp., Caulophacus (Caulophacus) discohexactinus n. sp., C. ( Caulodiscus) brandti n. sp., C. ( Oxydiscus) weddelli n. sp., and C. ( Oxydiscus) n. subgen. So far, 20 hexactinellid species have been reported from the deep Weddell Sea, 15 are known from the northern part and 10 only from here, while 10 came from the southern area, and five of these only from there. However, this apparent high "endemism" of Antarctic hexactinellid sponges is most likely the result of severe undersampling of the deep-sea fauna. We find no reason to believe that a division between an oceanic and a more continental group of species exists. The current poor database indicates that a substantial part of the deep hexactinellid fauna of the Weddell Sea is shared with other deep-sea regions, but it does not indicate a special biogeographic relationship with any other ocean.

Deep Packet/Flow Analysis using GPUs

Energy Technology Data Exchange (ETDEWEB)

Gong, Qian [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Wu, Wenji [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); DeMar, Phil [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

2017-11-12

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

The effects of deep level traps on the electrical properties of semi-insulating CdZnTe

Energy Technology Data Exchange (ETDEWEB)

Zha, Gangqiang; Yang, Jian; Xu, Lingyan; Feng, Tao; Wang, Ning; Jie, Wanqi [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an (China)

2014-01-28

Deep level traps have considerable effects on the electrical properties and radiation detection performance of high resistivity CdZnTe. A deep-trap model for high resistivity CdZnTe was proposed in this paper. The high resistivity mechanism and the electrical properties were analyzed based on this model. High resistivity CdZnTe with high trap ionization energy E{sub t} can withstand high bias voltages. The leakage current is dependent on both the deep traps and the shallow impurities. The performance of a CdZnTe radiation detector will deteriorate at low temperatures, and the way in which sub-bandgap light excitation could improve the low temperature performance can be explained using the deep trap model.

DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

Science.gov (United States)

Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

2018-01-01

Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

Deep 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 ...

Constraining the source location of the 30 May 2015 (Mw 7.9) Bonin deep-focus earthquake using seismogram envelopes of high-frequency P waveforms: Occurrence of deep-focus earthquake at the bottom of a subducting slab

Science.gov (United States)

Takemura, Shunsuke; Maeda, Takuto; Furumura, Takashi; Obara, Kazushige

2016-05-01

In this study, the source location of the 30 May 2015 (Mw 7.9) deep-focus Bonin earthquake was constrained using P wave seismograms recorded across Japan. We focus on propagation characteristics of high-frequency P wave. Deep-focus intraslab earthquakes typically show spindle-shaped seismogram envelopes with peak delays of several seconds and subsequent long-duration coda waves; however, both the main shock and aftershock of the 2015 Bonin event exhibited pulse-like P wave propagations with high apparent velocities (~12.2 km/s). Such P wave propagation features were reproduced by finite-difference method simulations of seismic wave propagation in the case of slab-bottom source. The pulse-like P wave seismogram envelopes observed from the 2015 Bonin earthquake show that its source was located at the bottom of the Pacific slab at a depth of ~680 km, rather than within its middle or upper regions.

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.

Convective transport of highly plasma protein bound drugs facilitates direct penetration into deep tissues after topical application

Science.gov (United States)

Dancik, Yuri; Anissimov, Yuri G; Jepps, Owen G; Roberts, Michael S

2012-01-01

AIMS To relate the varying dermal, subcutaneous and muscle microdialysate concentrations found in man after topical application to the nature of the drug applied and to the underlying physiology. METHODS We developed a physiologically based pharmacokinetic model in which transport to deeper tissues was determined by tissue diffusion, blood, lymphatic and intersitial flow transport and drug properties. The model was applied to interpret published human microdialysis data, estimated in vitro dermal diffusion and protein binding affinity of drugs that have been previously applied topically in vivo and measured in deep cutaneous tissues over time. RESULTS Deeper tissue microdialysis concentrations for various drugs in vivo vary widely. Here, we show that carriage by the blood to the deeper tissues below topical application sites facilitates the transport of highly plasma protein bound drugs that penetrate the skin, leading to rapid and significant concentrations in those tissues. Hence, the fractional concentration for the highly plasma protein bound diclofenac in deeper tissues is 0.79 times that in a probe 4.5 mm below a superficial probe whereas the corresponding fractional concentration for the poorly protein bound nicotine is 0.02. Their corresponding estimated in vivo lag times for appearance of the drugs in the deeper probes were 1.1 min for diclofenac and 30 min for nicotine. CONCLUSIONS Poorly plasma protein bound drugs are mainly transported to deeper tissues after topical application by tissue diffusion whereas the transport of highly plasma protein bound drugs is additionally facilitated by convective blood, lymphatic and interstitial transport to deep tissues. PMID:21999217

Effect of swift heavy ion irradiation on deep levels in Au /n-Si (100) Schottky diode studied by deep level transient spectroscopy

Science.gov (United States)

Kumar, Sandeep; Katharria, Y. S.; Kumar, Sugam; Kanjilal, D.

2007-12-01

In situ deep level transient spectroscopy has been applied to investigate the influence of 100MeV Si7+ ion irradiation on the deep levels present in Au/n-Si (100) Schottky structure in a wide fluence range from 5×109to1×1012ions cm-2. The swift heavy ion irradiation introduces a deep level at Ec-0.32eV. It is found that initially, trap level concentration of the energy level at Ec-0.40eV increases with irradiation up to a fluence value of 1×1010cm-2 while the deep level concentration decreases as irradiation fluence increases beyond the fluence value of 5×1010cm-2. These results are discussed, taking into account the role of energy transfer mechanism of high energy ions in material.

Direct observation and measurements of neutron induced deep levels responsible for N{sub eff} changes in high resistivity silicon detectors using TCT

Energy Technology Data Exchange (ETDEWEB)

Li, Z.; Li, C.J. [Brookhaven National Lab., Upton, NY (United States); Eremin, V.; Verbitskaya, E. [AN SSSR, Leningrad (Russian Federation). Fiziko-Tekhnicheskij Inst.

1996-03-01

Neutron induced deep levels responsible for changes of space charge concentration {ital N{sub eff}} in high resistivity silicon detectors have been observed directly using the transient current technique (TCT). It has been observed by TCT that the absolute value and sign of {ital N{sub eff}} experience changes due to the trapping of non- equilibrium free carriers generated near the surface (about 5 micrometers depth into the silicon) by short wavelength laser pulses in fully depleted detectors. Electron trapping causes {ital N{sub eff}} to change toward negative direction (or more acceptor-like space charges) and hole trapping causes {ital N{sub eff}} to change toward positive direction (or more donor-like space charges). The specific temperature associated with these {ital N{sub eff}} changes are those of the frozen-up temperatures for carrier emission of the corresponding deep levels. The carrier capture cross sections of various deep levels have been measured directly using different free carrier injection schemes. 10 refs., 12 figs., 3 tabs.

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

CERN Document Server

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

2014-01-01

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

Bacterial diversity and biogeography in deep-sea sediments of the South Atlantic Ocean

DEFF Research Database (Denmark)

Schauer, Regina; Bienhold, Christina; Ramette, Alban

2010-01-01

in 1051 sequences. Phylotypes affiliated with Gammaproteobacteria, Deltaproteobacteria and Acidobacteria were present in all three basins. The distribution of these shared phylotypes seemed to be influenced neither by the Walvis Ridge nor by different deep water masses, suggesting a high dispersal......Microbial biogeographic patterns in the deep sea depend on the ability of microorganisms to disperse. One possible limitation to microbial dispersal may be the Walvis Ridge that separates the Antarctic Lower Circumpolar Deep Water from the North Atlantic Deep Water. We examined bacterial...... communities in three basins of the eastern South Atlantic Ocean to determine diversity and biogeography of bacterial communities in deep-sea surface sediments. The analysis of 16S ribosomal RNA (rRNA) gene clone libraries in each basin revealed a high diversity, representing 521 phylotypes with 98% identity...

Deep-well injection of radioactive waste in Russia

International Nuclear Information System (INIS)

Hoek, J.

1998-01-01

In the Russian federation, deep borehole injection of liquid radioactive waste has been established practice since at least 1963. The liquid is injected into sandy or other formations with high porosity, which are isolated by water-tight layers. This technique has also been used elsewhere for toxic liquid waste and residues from mining operations. Deep-well injection of radioactive waste is not currently used in any of the European Commission (EC) countries. In this paper the results of a EC-funded study were presented. The study is entitled 'Measurements, modelling of migration and possible radiological consequences at deep well injection sites for liquid radioactive waste in Russia', COSU-CT94-0099-UK. The study was carried out jointly by AEA Technology, CAG and the Research Institute for Nuclear Reactors (NIIAR) at Dimitrovgrad. Many scientists have contributed to the results reported here. The aims of the study are: Provision of extensive information on the deep-well injection repositories and their use in the former Soviet Union; Provision of a methodology to assess safety aspects of deep-well injection of liquid radioactive waste in deep geological formations; This will allow evaluation of proposals to use deep-well injection techniques in other regions; Support for Russian regulatory bodies through evaluation of the suitability of the sites, including estimates of the maximum amount of waste that can be safely stored in them; and Provision of a methodology to assess the use of deep-well injection repositories as an alternative disposal technique for EC countries. 7 refs

AHPCRC (Army High Performance Computing Research Center) Bulletin. Volume 1, Issue 2

Science.gov (United States)

2011-01-01

area and the researchers working on these projects. Also inside: news from the AHPCRC consortium partners at Morgan State University and the NASA ...Computing Research Center is provided by the supercomputing and research facilities at Stanford University and at the NASA Ames Research Center at...atomic and molecular level, he said. He noted that “every general would like to have” a Star Trek -like holodeck, where holographic avatars could

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

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

DEFF Research Database (Denmark)

Valen, Eivind; Pascarella, Giovanni; Chalk, Alistair

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Pantenburg, F.J. E-mail: pantenburg@imt.fzk.de; Mohr, J

2001-07-21

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

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

Science.gov (United States)

Pantenburg, F. J.; Mohr, J.

2001-07-01

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

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

International Nuclear Information System (INIS)

Pantenburg, F.J.; Mohr, J.

2001-01-01

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

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

CERN Document Server

Pantenburg, F J

2001-01-01

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

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...

Deep learning—Accelerating Next Generation Performance Analysis Systems?

Directory of Open Access Journals (Sweden)

Heike Brock

2018-02-01

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

Disposition of excess fissile materials in deep boreholes

International Nuclear Information System (INIS)

Halsey, W.G.; Danker, W.; Morley, R.

1995-09-01

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. Plutonium utilization options have in common the generation of high-level radioactive waste which will be disposed of in a mined geologic disposal system to be developed for spent reactor fuel and defense high level waste. Other final disposition forms, such as plutonium metal, plutonium oxide and plutonium immobilized without high-level radiation sources may be better suited to placement in a custom facility. This paper discusses a leading candidate for such a facility; deep (several kilometer) borehole disposition. The deep borehole disposition concept involves placing excess plutonium deep into old stable rock formations with little free water present. The safety argument centers around ancient groundwater indicating lack of migration, and thus no expected communication with the accessible environment until the plutonium has decayed

Volume fracturing of deep shale gas horizontal wells

Directory of Open Access Journals (Sweden)

Tingxue Jiang

2017-03-01

Full Text Available Deep shale gas reservoirs buried underground with depth being more than 3500 m are characterized by high in-situ stress, large horizontal stress difference, complex distribution of bedding and natural cracks, and strong rock plasticity. Thus, during hydraulic fracturing, these reservoirs often reveal difficult fracture extension, low fracture complexity, low stimulated reservoir volume (SRV, low conductivity and fast decline, which hinder greatly the economic and effective development of deep shale gas. In this paper, a specific and feasible technique of volume fracturing of deep shale gas horizontal wells is presented. In addition to planar perforation, multi-scale fracturing, full-scale fracture filling, and control over extension of high-angle natural fractures, some supporting techniques are proposed, including multi-stage alternate injection (of acid fluid, slick water and gel and the mixed- and small-grained proppant to be injected with variable viscosity and displacement. These techniques help to increase the effective stimulated reservoir volume (ESRV for deep gas production. Some of the techniques have been successfully used in the fracturing of deep shale gas horizontal wells in Yongchuan, Weiyuan and southern Jiaoshiba blocks in the Sichuan Basin. As a result, Wells YY1HF and WY1HF yielded initially 14.1 × 104 m3/d and 17.5 × 104 m3/d after fracturing. The volume fracturing of deep shale gas horizontal well is meaningful in achieving the productivity of 50 × 108 m3 gas from the interval of 3500–4000 m in Phase II development of Fuling and also in commercial production of huge shale gas resources at a vertical depth of less than 6000 m.

Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing

OpenAIRE

Lei Wang; Shuyun Jiang

2013-01-01

The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and widt...

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.

AN EFFICIENT METHOD FOR DEEP WEB CRAWLER BASED ON ACCURACY -A REVIEW

OpenAIRE

Pranali Zade1, Dr.S.W.Mohod2

2018-01-01

As deep web grows at a very fast pace, there has been increased interest in techniques that help efficiently locate deep-web interfaces. However, due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. We propose a three-stage framework, for efficient harvesting deep web interfaces. Project experimental results on a set of representative domains show the agility and accuracy of our proposed crawler framew...

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

Mathematical modelling of heat production in deep geological repository of high-level nuclear waste

International Nuclear Information System (INIS)

Kovanda, O.

2017-01-01

Waste produced by nuclear industry requires special handling. Currently, there is a research taking place, focused at possibilities of nuclear waste storage in deep geological repositories, hosted in stable geological environment. The high-level nuclear waste produces significant amount of heat for a long time, which can affect either environment outside of or within the repository in a negative way. Therefore to reduce risks, it is desirable to know the principles of such heat production, which can be achieved using mathematical modeling. This thesis comes up with a general model of heat production-time dependency, dependable on initial composition of the waste. To be able to model real situations, output of this thesis needs to be utilized in an IT solution. (authors)

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

Science.gov (United States)

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

2017-12-01

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

Development of deep silicon plasma etching for 3D integration technology

Directory of Open Access Journals (Sweden)

Golishnikov А. А.

2014-02-01

Full Text Available Plasma etch process for thought-silicon via (TSV formation is one of the most important technological operations in the field of metal connections creation between stacked circuits in 3D assemble technology. TSV formation strongly depends on parameters such as Si-wafer thickness, aspect ratio, type of metallization material, etc. The authors investigate deep silicon plasma etch process for formation of TSV with controllable profile. The influence of process parameters on plasma etch rate, silicon etch selectivity to photoresist and the structure profile are researched in this paper. Technology with etch and passivation steps alternation was used as a method of deep silicon plasma etching. Experimental tool «Platrane-100» with high-density plasma reactor based on high-frequency ion source with transformer coupled plasma was used for deep silicon plasma etching. As actuation gases for deep silicon etching were chosen the following gases: SF6 was used for the etch stage and CHF3 was applied on the polymerization stage. As a result of research, the deep plasma etch process has been developed with the following parameters: silicon etch rate 6 µm/min, selectivity to photoresist 60 and structure profile 90±2°. This process provides formation of TSV 370 µm deep and about 120 µm in diameter.

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.

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.)

The National Deep-Sea Coral and Sponge Database: A Comprehensive Resource for United States Deep-Sea Coral and Sponge Records

Science.gov (United States)

Dornback, M.; Hourigan, T.; Etnoyer, P.; McGuinn, R.; Cross, S. L.

2014-12-01

Research on deep-sea corals has expanded rapidly over the last two decades, as scientists began to realize their value as long-lived structural components of high biodiversity habitats and archives of environmental information. The NOAA Deep Sea Coral Research and Technology Program's National Database for Deep-Sea Corals and Sponges is a comprehensive resource for georeferenced data on these organisms in U.S. waters. The National Database currently includes more than 220,000 deep-sea coral records representing approximately 880 unique species. Database records from museum archives, commercial and scientific bycatch, and from journal publications provide baseline information with relatively coarse spatial resolution dating back as far as 1842. These data are complemented by modern, in-situ submersible observations with high spatial resolution, from surveys conducted by NOAA and NOAA partners. Management of high volumes of modern high-resolution observational data can be challenging. NOAA is working with our data partners to incorporate this occurrence data into the National Database, along with images and associated information related to geoposition, time, biology, taxonomy, environment, provenance, and accuracy. NOAA is also working to link associated datasets collected by our program's research, to properly archive them to the NOAA National Data Centers, to build a robust metadata record, and to establish a standard protocol to simplify the process. Access to the National Database is provided through an online mapping portal. The map displays point based records from the database. Records can be refined by taxon, region, time, and depth. The queries and extent used to view the map can also be used to download subsets of the database. The database, map, and website is already in use by NOAA, regional fishery management councils, and regional ocean planning bodies, but we envision it as a model that can expand to accommodate data on a global scale.

High Temperature Logging and Monitoring Instruments to Explore and Drill Deep into Hot Oceanic Crust.

Science.gov (United States)

Denchik, N.; Pezard, P. A.; Ragnar, A.; Jean-Luc, D.; Jan, H.

2014-12-01

Drilling an entire section of the oceanic crust and through the Moho has been a goal of the scientific community for more than half of a century. On the basis of ODP and IODP experience and data, this will require instruments and strategies working at temperature far above 200°C (reached, for example, at the bottom of DSDP/ODP Hole 504B), and possibly beyond 300°C. Concerning logging and monitoring instruments, progress were made over the past ten years in the context of the HiTI ("High Temperature Instruments") project funded by the european community for deep drilling in hot Icelandic geothermal holes where supercritical conditions and a highly corrosive environment are expected at depth (with temperatures above 374 °C and pressures exceeding 22 MPa). For example, a slickline tool (memory tool) tolerating up to 400°C and wireline tools up to 300°C were developed and tested in Icelandic high-temperature geothermal fields. The temperature limitation of logging tools was defined to comply with the present limitation in wireline cables (320°C). As part of this new set of downhole tools, temperature, pressure, fluid flow and casing collar location might be measured up to 400°C from a single multisensor tool. Natural gamma radiation spectrum, borehole wall ultrasonic images signal, and fiber optic cables (using distributed temperature sensing methods) were also developed for wireline deployment up to 300°C and tested in the field. A wireline, dual laterolog electrical resistivity tool was also developed but could not be field tested as part of HiTI. This new set of tools constitutes a basis for the deep exploration of the oceanic crust in the future. In addition, new strategies including the real-time integration of drilling parameters with modeling of the thermo-mechanical status of the borehole could be developed, using time-lapse logging of temperature (for heat flow determination) and borehole wall images (for hole stability and in-situ stress determination

High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.

Science.gov (United States)

Stegmayer, Georgina; Yones, Cristian; Kamenetzky, Laura; Milone, Diego H

2017-01-01

The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high class-imbalance classification problem. The classical way of approaching it has been training a binary classifier in a supervised manner, using well-known pre-miRNAs as positive class and artificially defining the negative class. However, although the selection of positive labeled examples is straightforward, it is very difficult to build a set of negative examples in order to obtain a good set of training samples for a supervised method. In this work, we propose a novel and effective way of approaching this problem using machine learning, without the definition of negative examples. The proposal is based on clustering unlabeled sequences of a genome together with well-known miRNA precursors for the organism under study, which allows for the quick identification of the best candidates to miRNA as those sequences clustered with known precursors. Furthermore, we propose a deep model to overcome the problem of having very few positive class labels. They are always maintained in the deep levels as positive class while less likely pre-miRNA sequences are filtered level after level. Our approach has been compared with other methods for pre-miRNAs prediction in several species, showing effective predictivity of novel miRNAs. Additionally, we will show that our approach has a lower training time and allows for a better graphical navegability and interpretation of the results. A web-demo interface to try deepSOM is available at http://fich.unl.edu.ar/sinc/web-demo/deepsom/.

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.

The effects of illumination on deep levels observed in as-grown and low-energy electron irradiated high-purity semi-insulating 4H-SiC

Science.gov (United States)

Alfieri, G.; Knoll, L.; Kranz, L.; Sundaramoorthy, V.

2018-05-01

High-purity semi-insulating 4H-SiC can find a variety of applications, ranging from power electronics to quantum computing applications. However, data on the electronic properties of deep levels in this material are scarce. For this reason, we present a deep level transient spectroscopy study on HPSI 4H-SiC substrates, both as-grown and irradiated with low-energy electrons (to displace only C-atoms). Our investigation reveals the presence of four deep levels with activation energies in the 0.4-0.9 eV range. The concentrations of three of these levels increase by at least one order of magnitude after irradiation. Furthermore, we analyzed the behavior of these traps under sub- and above-band gap illumination. The nature of the traps is discussed in the light of the present data and results reported in the literature.

Optimization of lining design in deep clays

International Nuclear Information System (INIS)

Rousset, G.; Bublitz, D.

1989-01-01

The main features of the mechanical behaviour of deep clay are time dependent effects and also the existence of a long term cohesion which may be taken into account for dimensioning galleries. In this text, a lining optimization test is presented. It concerns a gallery driven in deep clay, 230 m. deep, at Mol (Belgium). We show that sliding rib lining gives both: - an optimal tunnel face advance speed, a minimal closure of the gallery wall before setting the lining and therefore less likelihood of failure developing inside the rock mass. - limitation of the length of the non-lined part of the gallery. The chosen process allows on one hand the preservation of the rock mass integrity, and, on the other, use of the confinement effect to allow closure under high average stress conditions; this process can be considered as an optimal application of the convergence-confinement method. An important set of measurement devices is then presented along with results obtained for one year's operation. We show in particular that stress distribution in the lining is homogeneous and that the sliding limit can be measured with high precision

High precision time calibration of the Permian-Triassic boundary mass extinction event in a deep marine context

Science.gov (United States)

Baresel, Björn; Bucher, Hugo; Brosse, Morgane; Bagherpour, Borhan; Schaltegger, Urs

2015-04-01

To construct a revised and high resolution calibrated time scale for the Permian-Triassic boundary (PTB) we use (1) high-precision U-Pb zircon age determinations of a unique succession of volcanic ash layers interbedded with deep water fossiliferous sediments in the Nanpanjiang Basin (South China) combined with (2) accurate quantitative biochronology based on ammonoids, conodonts, radiolarians, and foraminifera and (3) tracers of marine bioproductivity (carbon isotopes) across the PTB. The unprecedented precision of the single grain chemical abrasion isotope-dilution thermal ionization mass spectrometry (CA-ID-TIMS) dating technique at sub-per mil level (radio-isotopic calibration of the PTB at the groups of processes. Using these alignments allows (1) positioning the PTB in different depositional setting and (2) solving the age contradictions generated by the misleading use of the first occurrence (FO) of the conodont Hindeodus parvus, whose diachronous first occurrences are arbitrarily used for placing the base of the Triassic. This new age framework provides the basis for a combined calibration of chemostratigraphic records with high-resolution biochronozones of the Late Permian and Early Triassic. Here, we present new single grain U-Pb zircon data of volcanic ash layers from two deep marine sections (Dongpan and Penglaitan) revealing stratigraphic consistent dates over several volcanic ash layers bracketing the PTB. These analyses define weighted mean 206Pb/238U ages of 251.956±0.033 Ma (Dongpan) and 252.062±0.043 Ma (Penglaitan) for the last Permian ash bed. By calibration with detailed litho- and biostratigraphy new U-Pb ages of 251.953±0.038 Ma (Dongpan) and 251.907±0.033 Ma (Penglaitan) are established for the onset of the Triassic.

Key Factors to Determine the Borehole Spacing in a Deep Borehole Disposal for HLW

International Nuclear Information System (INIS)

Lee, Jongyoul; Choi, Heuijoo; Lee, Minsoo; Kim, Geonyoung; Kim, Kyeongsoo

2015-01-01

Deep fluids also resist vertical movement because they are density stratified and reducing conditions will sharply limit solubility of most dose critical radionuclides at the depth. Finally, high ionic strengths of deep fluids will prevent colloidal transport. 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 concept for deep borehole disposal of spent fuels or high level radioactive wastes which has been developed by some countries according to the rapid advance in the development of drilling technology, as an alternative method to the deep geological disposal method, was reviewed. After then an analysis on key factors for the distance between boreholes for the disposal of HLW was carried out. In this paper, the general concept for deep borehole disposal of spent fuels or HLW wastes, as an alternative method to the deep geological disposal method, were reviewed. After then an analysis on key factors for the determining the distance between boreholes for the disposal of HLW was carried out. These results can be used for the development of the HLW deep borehole disposal system

Key Factors to Determine the Borehole Spacing in a Deep Borehole Disposal for HLW

Energy Technology Data Exchange (ETDEWEB)

Lee, Jongyoul; Choi, Heuijoo; Lee, Minsoo; Kim, Geonyoung; Kim, Kyeongsoo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

Deep fluids also resist vertical movement because they are density stratified and reducing conditions will sharply limit solubility of most dose critical radionuclides at the depth. Finally, high ionic strengths of deep fluids will prevent colloidal transport. 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 concept for deep borehole disposal of spent fuels or high level radioactive wastes which has been developed by some countries according to the rapid advance in the development of drilling technology, as an alternative method to the deep geological disposal method, was reviewed. After then an analysis on key factors for the distance between boreholes for the disposal of HLW was carried out. In this paper, the general concept for deep borehole disposal of spent fuels or HLW wastes, as an alternative method to the deep geological disposal method, were reviewed. After then an analysis on key factors for the determining the distance between boreholes for the disposal of HLW was carried out. These results can be used for the development of the HLW deep borehole disposal system.

A poor sealing Scenario for Deep disposal of high level waste

International Nuclear Information System (INIS)

Weetjens, E.

2005-01-01

Especially for geological disposal options in clay, the safety of the repository relies chiefly on the performance of the host formation as the main barrier. Understandably, scenarios in which this clay barrier is somehow bypassed earn great concern in PA (Performance Assessment) studies. The Poor Sealing Scenario is one of those scenarios that have been recently studied by the PA section of the Waste and Disposal department in the framework of the Belgian programme on deep disposal of high-level radwaste in Boom Clay. This scenario hypothesises that at least one disposal gallery and an access shaft have been poorly sealed off, providing a preferential pathway for RNs (radionuclides). The scenario further assumes a severe climate change, which would invert the presently downward hydraulic gradient, such that the potential impact would be maximal. The main objective is assessing the contribution from two transport processes to the overall radionuclide migration from a spent fuel repository towards the Neogene aquifer. The processes considered are advective transport through the poorly sealed repository and diffusive transport through the host formation. In addition, we would like to identify the most influential parameters with respect to repository design and performance

Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function.

Science.gov (United States)

Cardenas, Carlos E; McCarroll, Rachel E; Court, Laurence E; Elgohari, Baher A; Elhalawani, Hesham; Fuller, Clifton D; Kamal, Mona J; Meheissen, Mohamed A M; Mohamed, Abdallah S R; Rao, Arvind; Williams, Bowman; Wong, Andrew; Yang, Jinzhong; Aristophanous, Michalis

2018-06-01

Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin expansions to auto-delineate high-risk CTVs, very little work has been performed to provide patient- and disease-specific high-risk CTVs. The aim of the present study was to develop a deep neural network for the auto-delineation of high-risk CTVs. Fifty-two oropharyngeal cancer patients were selected for the present study. All patients were treated at The University of Texas MD Anderson Cancer Center from January 2006 to August 2010 and had previously contoured gross tumor volumes and CTVs. We developed a deep learning algorithm using deep auto-encoders to identify physician contouring patterns at our institution. These models use distance map information from surrounding anatomic structures and the gross tumor volume as input parameters and conduct voxel-based classification to identify voxels that are part of the high-risk CTV. In addition, we developed a novel probability threshold selection function, based on the Dice similarity coefficient (DSC), to improve the generalization of the predicted volumes. The DSC-based function is implemented during an inner cross-validation loop, and probability thresholds are selected a priori during model parameter optimization. We performed a volumetric comparison between the predicted and manually contoured volumes to assess our model. The predicted volumes had a median DSC value of 0.81 (range 0.62-0.90), median mean surface distance of 2.8 mm (range 1.6-5.5), and median 95th Hausdorff distance of 7.5 mm (range 4.7-17.9) when comparing our predicted high-risk CTVs with the physician manual contours. These predicted high-risk CTVs provided close agreement to the ground-truth compared with current interobserver variability. The predicted contours could be implemented clinically, with only

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.

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....

De novo transcriptome assembly and positive selection analysis of an individual deep-sea fish.

Science.gov (United States)

Lan, Yi; Sun, Jin; Xu, Ting; Chen, Chong; Tian, Renmao; Qiu, Jian-Wen; Qian, Pei-Yuan

2018-05-24

High hydrostatic pressure and low temperatures make the deep sea a harsh environment for life forms. Actin organization and microtubules assembly, which are essential for intracellular transport and cell motility, can be disrupted by high hydrostatic pressure. High hydrostatic pressure can also damage DNA. Nucleic acids exposed to low temperatures can form secondary structures that hinder genetic information processing. To study how deep-sea creatures adapt to such a hostile environment, one of the most straightforward ways is to sequence and compare their genes with those of their shallow-water relatives. We captured an individual of the fish species Aldrovandia affinis, which is a typical deep-sea inhabitant, from the Okinawa Trough at a depth of 1550 m using a remotely operated vehicle (ROV). We sequenced its transcriptome and analyzed its molecular adaptation. We obtained 27,633 protein coding sequences using an Illumina platform and compared them with those of several shallow-water fish species. Analysis of 4918 single-copy orthologs identified 138 positively selected genes in A. affinis, including genes involved in microtubule regulation. Particularly, functional domains related to cold shock as well as DNA repair are exposed to positive selection pressure in both deep-sea fish and hadal amphipod. Overall, we have identified a set of positively selected genes related to cytoskeleton structures, DNA repair and genetic information processing, which shed light on molecular adaptation to the deep sea. These results suggest that amino acid substitutions of these positively selected genes may contribute crucially to the adaptation of deep-sea animals. Additionally, we provide a high-quality transcriptome of a deep-sea fish for future deep-sea studies.

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

OpenAIRE

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

2013-01-01

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with ?deep-sea? and ?cold-water? corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20?C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the ...

High-Performance solar-blind flexible Deep-UV photodetectors based on quantum dots synthesized by femtosecond-laser ablation

KAUST Repository

Mitra, Somak

2018-03-31

High-performance deep ultraviolet (DUV) photodetectors operating at ambient conditions with < 280nm detection wavelengths are in high demand because of their potential applications in diverse fields. We demonstrate for the first time, high-performance flexible DUV photodetectors operating at ambient conditions based on quantum dots (QDs) synthesized by femtosecond-laser ablation in liquid (FLAL) technique. Our method is facile without complex chemical procedures, which allows large-scale cost-effective devices. This synthesis method is demonstrated to produce highly stable and reproducible ZnO QDs from zinc nitride target (Zn3N2) without any material degradation due to water and oxygen molecule species, allowing photodetectors operate at ambient conditions. Carbon-doped ZnO QD-based photodetector is capable of detecting efficiently in the DUV spectral region, down to 224nm, and exhibits high photo responsivity and stability. As fast response of DUV photodetector remains significant parameter for high-speed communication; we show fast-response QD-based DUV photodetector. Such surfactant-free synthesis by FLAL can lead to commercially available high-performance low-cost optoelectronic devices based on nanostructures for large scale applications.

Synthesis of gold nanoflowers using deep eutectic solvent with high surface enhanced Raman scattering properties

Science.gov (United States)

Aghakhani Mahyari, Farzaneh; Tohidi, Maryam; Safavi, Afsaneh

2016-09-01

A facile, seed-less and one-pot method was developed for synthesis of gold nanoflowers with multiple tips through reduction of HAuCl4 with deep eutectic solvent at room temperature. This solvent is eco-friendly, low-cost, non-toxic and biodegradable and can act as both reducing and shape-controlling agent. In this protocol, highly branched and stable gold nanoflowers were obtained without using any capping agent. The obtained products were characterized by different techniques including, field emission scanning electron microscopy, transmission electron microscopy, x-ray diffraction and UV-vis spectroscopy. The as-prepared gold nanoflowers exhibit efficient surface-enhanced Raman scattering (SERS) properties which can be used as excellent substrates for SERS.

Final disposal of high-level radioactive waste in deep boreholes. An evaluation based on recent research on the bedrock at great depths

International Nuclear Information System (INIS)

Aahaell, Karl-Inge

2006-05-01

New knowledge in hydrogeology and boring technology have opened the possibility to use deep boreholes as a repository for the Swedish high-level radioactive wastes. The determining property is that the repository can be housed in the stable bedrock at levels where the ground water has no contact with the biosphere and disposal and sealing can take place without disturbing the ground water stratification outside the disposal area. An advantage compared to a shallow repository of KBS-3 type, that is now being planned in Sweden, is that a borehole repository is likely to be technologically more robust, since the concept 'deep boreholes' seems to admit such a deep disposal that the entire disposal area would be surrounded by stable density-layered ground water, while a KBS-3 repository would be surrounded by moving ground water in contact with level close to the surface. This hydrological difference is of great importance for the safety in scenarios with leaching of radioactive substances. A deep repository is also less vulnerable for effects from natural events such as glaciation and earthquakes as well as from technological mishaps and terrorist actions. A crucial factor is, however, that the radioactive waste can be disposed of, in a secure way, at the intended depth, which will require new research and technology development

A reconsideration on deep sea bed disposal of high level radiological wastes. A post-Fukushima reflection on sustainable nuclear energy in Japan

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu

2013-01-01

The ultimate disposal of high-level radioactive waste (HLW) is a common issue among all nuclear developing countries. However, this becomes especially a hard issue for sustainable nuclear energy in Japan after Fukushima Daiichi accident. In this paper, the difficulty of realizing underground HLW disposal in Japanese islands is first discussed from socio-political aspects. Then, revival of old idea of deep seabed disposal of HLW in Pacific Ocean is proposed as an alternative way of HLW disposal. Although this old idea had been abandoned in the past for the reason that it would violate London Convention which prohibits dumping radioactive wastes in public sea, the author will stress the merit of seabed disposal of HLW deep in Pacific Ocean not only from the view point of more safe and ultimate way of disposing HLWs (both vitrified and spent fuel) than by underground disposal, but also the emergence of new marine project by synergetic collaboration of rare-earth resource exploration from the deep sea floor in Pacific Ocean. (author)

Application of Ga-Al discrimination plots in identification of high strength granitic host rocks for deep geological repository of high level radioactive waste

International Nuclear Information System (INIS)

Bajpai, R.K.; Narayan, P.K.; Trivedi, R.K.; Purohit, M.K.

2010-01-01

The permanent disposal of vitrified high level wastes and in some cases even spent fuel, is being planned in specifically designed and built deep geological repository located in the depth range of 500-600m in appropriate host rock at carefully selected sites. Such facilities are expected to provide very long term isolation and confinement to the disposed waste by means of long term mechanical stability of such structures that results from very high strength and homogeneity of the chosen rock, geochemical compatible environment around the disposed waste and general lack of groundwater. In Indian geological repository development programme, granites have been selected as target host rock and large scale characterization studies have been undertaken to develop database of mineralogy, petrology, geochemistry and rock mechanical characteristics. The paper proposes a new approach for demarcation of high strength homogeneous granite rocks from within an area of about 100 square kilometres wherein a cocktail of granites of different origins with varying rock mass characteristics co exists. The study area is characterised by the presence of A, S and I type granites toughly intermixed. The S type granites are derived from sedimentary parent material and therefore carry relics of parent fabric and at times undigested material with resultant reduction in their strength and increased inhomogeneity. On the other hand I type varieties are derived from igneous parents and are more homogeneous with sufficient strength. The A type granites are emplaced as molten mass in a complete non-tectonic setting with resultant homogeneous compositions, absence of tectonic fabric and very high strength. Besides they are silica rich with less vulnerability to alterations with time. Thus A type granites are most suited for construction of Deep Geological Repository. For developing a geochemical approach for establishing relation between chemical compositions and rock strength parameters, a

) A Feasibility Study for High Resolution 3D Seismic In The Deep Offshore Nigeria

International Nuclear Information System (INIS)

Enuma, C.; Hope, R.; Mila, F.; Maurel, L.

2003-01-01

The conventional Exploration 3D seismic in the Deep Offshore Nigeria is typically acquired with 4000m-6000m cable length at 6-8 depth and with flip-flop shooting, providing a shot point interval of 50m. the average resulting frequency content is typically between 10-60hz which is adequate for exploration interpretation. It has become common in the last few years. E.g. in Angola and the Gulf of Mexico, to re-acquire High Resolution 3D seismic, after a discovery, to improve definition of turbidite systems and accuracy of reservoir geometry for optimized delineation drilling. This feasibility study which was carried out in three different steps was due to the question on whether HR-Seismic should be acquired over TotalFinaElf AKPO discovery for optimized delineation drilling

The Livermore Brain: Massive Deep Learning Networks Enabled by High Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Chen, Barry Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-11-29

The proliferation of inexpensive sensor technologies like the ubiquitous digital image sensors has resulted in the collection and sharing of vast amounts of unsorted and unexploited raw data. Companies and governments who are able to collect and make sense of large datasets to help them make better decisions more rapidly will have a competitive advantage in the information era. Machine Learning technologies play a critical role for automating the data understanding process; however, to be maximally effective, useful intermediate representations of the data are required. These representations or “features” are transformations of the raw data into a form where patterns are more easily recognized. Recent breakthroughs in Deep Learning have made it possible to learn these features from large amounts of labeled data. The focus of this project is to develop and extend Deep Learning algorithms for learning features from vast amounts of unlabeled data and to develop the HPC neural network training platform to support the training of massive network models. This LDRD project succeeded in developing new unsupervised feature learning algorithms for images and video and created a scalable neural network training toolkit for HPC. Additionally, this LDRD helped create the world’s largest freely-available image and video dataset supporting open multimedia research and used this dataset for training our deep neural networks. This research helped LLNL capture several work-for-others (WFO) projects, attract new talent, and establish collaborations with leading academic and commercial partners. Finally, this project demonstrated the successful training of the largest unsupervised image neural network using HPC resources and helped establish LLNL leadership at the intersection of Machine Learning and HPC research.

Pressure measurements and high speed visualizations of the cavitation phenomena at deep part load condition in a Francis turbine

International Nuclear Information System (INIS)

Yamamoto, K; Müller, A; Favrel, A; Landry, C; Avellan, F

2014-01-01

In a hydraulic power plant, it is essential to provide a reliable, sustainable and flexible energy supply. In recent years, in order to cover the variations of the renewable electricity production, hydraulic power plants are demanded to operate with more extended operating range. Under these off-design conditions, a hydraulic turbine is subject to cavitating swirl flow at the runner outlet. It is well-known that the helically/symmetrically shaped cavitation develops at the runner outlet in part load/full load condition, and it gives severe damage to the hydraulic systems under certain conditions. Although there have been many studies about partial and full load conditions, contributions reporting the deep part load condition are limited, and the cavitation behaviour at this condition is not yet understood. This study aims to unveil the cavitation phenomena at deep part load condition by high speed visualizations focusing on the draft tube cone as well as the runner blade channel, and pressure fluctuations associated with the phenomena were also investigated

Chemical stability of copper-canisters in deep repository

International Nuclear Information System (INIS)

Ahonen, L.

1995-12-01

The spent fuel from Finnish nuclear reactors is planned to be encapsulated in thick-walled copper-iron canisters and placed deep into the bedrock. The copper wall of the canister provides a long-time shield against corrosion, preventing the high-level nuclear fuel from contact with ground water. In the report, stability of metallic copper and its possible corrosion reactions in the conditions of deep bedrock are evaluated by means of thermo-dynamic calculations. (90 refs., 28 figs., 11 tabs.)

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.

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.

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

Science.gov (United States)

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

2013-10-03

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

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

KAUST Repository

Roder, Cornelia

2013-10-03

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

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.

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

Science.gov (United States)

Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei

2017-09-01

Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

Deep tissue optical imaging of upconverting nanoparticles enabled by exploiting higher intrinsic quantum yield through use of millisecond single pulse excitation with high peak power

DEFF Research Database (Denmark)

Liu, Haichun; Xu, Can T.; Dumlupinar, Gökhan

2013-01-01

We have accomplished deep tissue optical imaging of upconverting nanoparticles at 800 nm, using millisecond single pulse excitation with high peak power. This is achieved by carefully choosing the pulse parameters, derived from time-resolved rate-equation analysis, which result in higher intrinsic...... quantum yield that is utilized by upconverting nanoparticles for generating this near infrared upconversion emission. The pulsed excitation approach thus promises previously unreachable imaging depths and shorter data acquisition times compared with continuous wave excitation, while simultaneously keeping...... therapy and remote activation of biomolecules in deep tissues....

Effects of thermal-hydraulic feedback on burnup modeling of the deep burn modular high temperature reactor (DB-MHR)

International Nuclear Information System (INIS)

Bei, Yea; Wen, Wua; Di, Yuna; Stubbins, J.F.; Venneri, F.

2007-01-01

The Deep-Burn concept investigates the use of commercial high temperature gas-cooled reactors such as modular helium reactors (DB-MHR) to transmute spent fuel from light water reactors (LWRs). An essential feature of this technology is the fabrication of spent fuel into TRISO particles with full transuranic composition to achieve very extensive destruction levels (deep-burn) in a one-pass fuel cycle. Due to the strong temperature influence on the cross sections of transuranics, the coupling between temperature and neutronics is very important to be able to simulate realistic operations of the deep burn reactor. In this study, detailed simulations of the DB-MHR operation are performed with a Monte Carlo code system (MCNP-5 + ORIGEN-2.2 + MONTEBURNS-2 for neutronics calculations), POKE code (General Atomics, for thermohydraulics calculations) and NJOY-99 code (for processing nuclear data libraries), called MHRBURNS. Resulting power densities of fuel blocks (from neutronics calculations) are provided as input to the POKE code, which in turn, calculates new temperature distributions. The temperature distributions obtained from POKE are used to update the MCNP input, and NJOY is called to process new nuclear cross sections based on appropriate temperatures. These steps are repeated to calculate the entire burnup performance of the system. In this preliminary study only the feedback on graphite temperature is taken into account. It is observed that the temperature feedback results show a 200 K higher temperature and thus a slight difference in 237 Np and 239 Pu destruction rates, although the overall burnup rates remain the same

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

Science.gov (United States)

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

Deep Learning Questions Can Help Selection of High Ability Candidates for Universities

Science.gov (United States)

Mellanby, Jane; Cortina-Borja, Mario; Stein, John

2009-01-01

Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates' "deep learning" approach since this assesses the motivation and creative thinking…

Bidirectional Nonnegative Deep Model and Its Optimization in Learning

Directory of Open Access Journals (Sweden)

Xianhua Zeng

2016-01-01

Full Text Available Nonnegative matrix factorization (NMF has been successfully applied in signal processing as a simple two-layer nonnegative neural network. Projective NMF (PNMF with fewer parameters was proposed, which projects a high-dimensional nonnegative data onto a lower-dimensional nonnegative subspace. Although PNMF overcomes the problem of out-of-sample of NMF, it does not consider the nonlinear characteristic of data and is only a kind of narrow signal decomposition method. In this paper, we combine the PNMF with deep learning and nonlinear fitting to propose a bidirectional nonnegative deep learning (BNDL model and its optimization learning algorithm, which can obtain nonlinear multilayer deep nonnegative feature representation. Experiments show that the proposed model can not only solve the problem of out-of-sample of NMF but also learn hierarchical nonnegative feature representations with better clustering performance than classical NMF, PNMF, and Deep Semi-NMF algorithms.

Fabrications and application of single crystalline GaN for high-performance deep UV photodetectors

Energy Technology Data Exchange (ETDEWEB)

Velazquez, R.; Rivera, M.; Feng, P., E-mail: p.feng@upr.edu [Department of Physics, College of Natural Sciences, University of Puerto Rico, San Juan, 00936-8377, PR/USA (Puerto Rico); Aldalbahi, A. [Department of Chemistry, College of Science, King Saud University, Riyadh 11451 (Saudi Arabia)

2016-08-15

High-quality single crystalline Gallium Nitride (GaN) semiconductor has been synthesized using molecule beam epitaxy (MBE) technique for development of high-performance deep ultraviolet (UV) photodetectors. Thickness of the films was estimated by using surface profile meter and scanning electron microscope. Electronic states and elemental composition of the films were obtained using Raman scattering spectroscopy. The orientation, crystal structure and phase purity of the films were examined using a Siemens x-ray diffractometer radiation. The surface microstructure was studied using high resolution scanning electron microscopy (SEM). Two types of metal pairs: Al-Al, Al-Cu or Cu-Cu were used for interdigital electrodes on GaN film in order to examine the Schottky properties of the GaN based photodetector. The characterizations of the fabricated prototype include the stability, responsivity, response and recovery times. Typical time dependent photoresponsivity by switching different UV light source on and off five times for each 240 seconds at a bias of 2V, respectively, have been obtained. The detector appears to be highly sensitive to various UV wavelengths of light with very stable baseline and repeatability. The obtained photoresponsivity was up to 354 mA/W at the bias 2V. Higher photoresponsivity could be obtained if higher bias was applied but it would unavoidably result in a higher dark current. Thermal effect on the fabricated GaN based prototype was discussed.

Large-Scale Genotyping-by-Sequencing Indicates High Levels of Gene Flow in the Deep-Sea Octocoral Swiftia simplex (Nutting 1909 on the West Coast of the United States.

Directory of Open Access Journals (Sweden)

Meredith V Everett

Full Text Available Deep-sea corals are a critical component of habitat in the deep-sea, existing as regional hotspots for biodiversity, and are associated with increased assemblages of fish, including commercially important species. Because sampling these species is so difficult, little is known about the connectivity and life history of deep-sea octocoral populations. This study evaluates the genetic connectivity among 23 individuals of the deep-sea octocoral Swiftia simplex collected from Eastern Pacific waters along the west coast of the United States. We utilized high-throughput restriction-site associated DNA (RAD-tag sequencing to develop the first molecular genetic resource for the deep-sea octocoral, Swiftia simplex. Using this technique we discovered thousands of putative genome-wide SNPs in this species, and after quality control, successfully genotyped 1,145 SNPs across individuals sampled from California to Washington. These SNPs were used to assess putative population structure across the region. A STRUCTURE analysis as well as a principal coordinates analysis both failed to detect any population differentiation across all geographic areas in these collections. Additionally, after assigning individuals to putative population groups geographically, no significant FST values could be detected (FST for the full data set 0.0056, and no significant isolation by distance could be detected (p = 0.999. Taken together, these results indicate a high degree of connectivity and potential panmixia in S. simplex along this portion of the continental shelf.

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

Science.gov (United States)

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

2017-12-01

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

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

DLNE: A hybridization of deep learning and neuroevolution for visual control

DEFF Research Database (Denmark)

Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

2017-01-01

This paper investigates the potential of combining deep learning and neuroevolution to create a bot for a simple first person shooter (FPS) game capable of aiming and shooting based on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition...... on evolution, and (3) how well they allow the deep network and evolved network to interface with each other. Overall, the results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks...... and translating raw pixels to compact feature representations, while the evolving network takes those features as inputs to infer actions. Two types of feature representations are evaluated in terms of (1) how precise they allow the deep network to recognize the position of the enemy, (2) their effect...

Deep neural networks to enable real-time multimessenger astrophysics

Science.gov (United States)

George, Daniel; Huerta, E. A.

2018-02-01

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

Surface Improvement of Shafts by Turn-Assisted Deep Cold Rolling Process

Directory of Open Access Journals (Sweden)

Prabhu Raghavendra

2016-01-01

Full Text Available It is well recognized that mechanical surface enhancement methods can significantly improve the characteristics of highly-stressed metallic components. Deep cold rolling is one of such technique which is particularly attractive since it is possible to generate, near the surface, deep compressive residual stresses and work hardened layers while retaining a relatively smooth surface finish. In this paper, the effect of turn-assisted deep cold rolling on AISI 4140 steel is examined, with emphasis on the residual stress state. Based on the X-ray diffraction measurements, it is found that turn-assisted deep cold rolling can be quite effective in retarding the initiation and initial propagation of fatigue cracks in AISI 4140 steel.

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/ .

Single-mode pumped high air-fill fraction photonic crystal fiber taper for high-power deep-blue supercontinuum sources

DEFF Research Database (Denmark)

Sørensen, Simon Toft; Larsen, Casper; Jakobsen, Christian

2014-01-01

Dispersion control with axially nonuniform photonic crystal fibers (PCFs) permits supercontinuum (SC) generation into the deep-blue from an ytterbium pump laser. In this Letter, we exploit the full degrees of freedom afforded by PCFs to fabricate a fiber with longitudinally increasing air-fill fr...

Development of Deep-tow Autonomous Cable Seismic (ACS) for Seafloor Massive Sulfides (SMSs) Exploration.

Science.gov (United States)

Asakawa, Eiichi; Murakami, Fumitoshi; Tsukahara, Hitoshi; Saito, Shutaro; Lee, Sangkyun; Tara, Kenji; Kato, Masafumi; Jamali Hondori, Ehsan; Sumi, Tomonori; Kadoshima, Kazuyuki; Kose, Masami

2017-04-01

Within the EEZ of Japan, numerous surveys exploring ocean floor resources have been conducted. The exploration targets are gas hydrates, mineral resources (manganese, cobalt or rare earth) and especially seafloor massive sulphide (SMS) deposits. These resources exist in shallow subsurface areas in deep waters (>1500m). For seismic explorations very high resolution images are required. These cannot be effectively obtained with conventional marine seismic techniques. Therefore we have been developing autonomous seismic survey systems which record the data close to the seafloor to preserve high frequency seismic energy. Very high sampling rate (10kHz) and high accurate synchronization between recording systems and shot time are necessary. We adopted Cs-base atomic clock considering its power consumption. At first, we developed a Vertical Cable Seismic (VCS) system that uses hydrophone arrays moored vertically from the ocean bottom to record close to the target area. This system has been successfully applied to SMS exploration. Specifically it fixed over known sites to assess the amount of reserves with the resultant 3D volume. Based on the success of VCS, we modified the VCS system to use as a more efficient deep-tow seismic survey system. Although there are other examples of deep-tow seismic systems, signal transmission cables present challenges in deep waters. We use our autonomous recording system to avoid these problems. Combining a high frequency piezoelectric source (Sub Bottom Profiler:SBP) that automatically shots with a constant interval, we achieve the high resolution deep-tow seismic without data transmission/power cable to the board. Although the data cannot be monitored in real-time, the towing system becomes very simple. We have carried out survey trial, which showed the systems utility as a high-resolution deep-tow seismic survey system. Furthermore, the frequency ranges of deep-towed source (SBP) and surface towed sparker are 700-2300Hz and 10-200Hz

High-Power, Solid-State, Deep Ultraviolet Laser Generation

Directory of Open Access Journals (Sweden)

Hongwen Xuan

2018-02-01

Full Text Available At present, deep ultraviolet (DUV lasers at the wavelength of fourth harmonics of 1 μm (266 nm/258 nm and at the wavelength of 193 nm are widely utilized in science and industry. We review the generation of these DUV lasers by nonlinear frequency conversion processes using solid-state/fiber lasers as the fundamental frequency. A DUV laser at 258 nm by fourth harmonics generation (FHG could achieve an average power of 10 W with a beam quality of M2 < 1.5. Moreover, 1 W of average power at 193 nm was obtained by sum-frequency generation (SFG. A new concept of 193-nm DUV laser generation by use of the diamond Raman laser is also introduced. A proof-of-principle experiment of the diamond Raman laser is reported with the conversion efficiency of 23% from the pump to the second Stokes wavelength, which implies the potential to generate a higher power 193 nm DUV laser in the future.

Global diversity and biogeography of deep-sea pelagic prokaryotes

KAUST Repository

Salazar, Guillem

2015-08-07

The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean\\'s microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (∼3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

Global diversity and biogeography of deep-sea pelagic prokaryotes

KAUST Repository

Salazar, Guillem; Cornejo-Castillo, Francisco M.; Bení tez-Barrios, Veró nica; Fraile-Nuez, Eugenio; Á lvarez-Salgado, X. Antó n; Duarte, Carlos M.; Gasol, Josep M.; Acinas, Silvia G.

2015-01-01

The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean's microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (∼3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

Advanced Microgrid Concepts and Technologies Workshop

Science.gov (United States)

2013-04-01

Prognostics for Microgrid Components—Abhinav Saxena, NASA Ames Research Center...but very expensive; companies: Trek , Omron, SMC, Plessey Semiconductors, Quasar Federal Systems) o Field meters (chopper or rotating vane technology...still relatively expensive and low precision; companies: Monroe, Trek , AlphaLab, Campbell Scientific) • Why do we need anything beyond what is

Influence of deep RIE tolerances on comb-drive actuator performance

International Nuclear Information System (INIS)

Chen, Bangtao; Miao, Jianmin

2007-01-01

This paper analyses the various etching tolerances and profiles of comb-drive microstructures by using deep reactive ion etching (RIE) and studies their influence on the actuator's performance. The comb-drive actuators studied in this paper are fabricated with the silicon-on-glass (SOG) wafer process using deep RIE and wafer bonding, which present very high-aspect-ratio and high-strength microstructures. However, the deep RIE process generates some tolerances and varies the dimension and profile of comb fingers and flexures due to the process limitations. We have analysed the different etching tolerances and studied their influence on the actuator's performance, in terms of the electrostatic force, flexure stiffness, actuator's displacement, air damping and quality factor of the actuator. The analysis shows that the comb fingers with a positive slope profile generated a larger electrostatic force, and the flexures with a negative profile induced the loss of the actuator's stiffness. The combination of these two profiles leads to a great increase in the actuator's displacement and decrease in the quality factor. The measured results of the SOG fabricated actuators have demonstrated the influence of deep RIE tolerance on the actuator's performance

Construction of System for Seismic Observation in Deep Borehole (SODB) - Development of Multi-depth, High-temperature/pressure resistance seismometer

International Nuclear Information System (INIS)

Mamada, Yutaka

2014-01-01

The development of a high quality system for seismic observation in deep boreholes, the installation process at the NIIT site, and the data sharing plan for this observation were explained. The key points of the development were high temperature resistance (150 degrees Celsius), high pressure resistance (30 MPa), and a high dynamic/wide frequency range seismometer which allows for observation of micro-tremor to strong motions as well as a cascade-connection-type borehole seismometer, which allows multiple probes to be set at several depths in a single borehole. The developed system consists of broadband (0.1-50 Hz) and high dynamic range (up to 1000 gal) seismometer with electronic parts on the ground and only the pendulum part in the borehole (it became a servo-type seismometer). Durability and maintenance may be issues in the future. (author)

Support technology of deep roadway under high stress and its application

Institute of Scientific and Technical Information of China (English)

Cao Rihong; Cao Ping; Lin Hang

2016-01-01

Roadway instability has been a major concern in the fields of mining engineering. This paper aims to provide practical and efficient strategy to support the roadways under high in-situ stress. A case study on the stability of deep roadways was carried out in an underground mine in Gansu province, China. Currently,the surrounding rock strata is extremely fractured, which results in a series of engineering disasters, such as side wall collapse and severe floor heave in the past decades. Aiming to solve these problems, an improved support method was proposed, which includes optimal bolt parameters and arrangement, floor beam layout by grooving, and full length grouting. Based on the modeling results by FLAC3D, the new support method is much better than the current one in terms of preventing the large deformation of surrounding rock and restricting the development of plastic zones. For implementation and verification, field experiments, along with deformation monitoring, were conducted in the 958 level roadway of Mining II areas. The results show that the improved support can significantly reduce surrounding rock deformation, avoid frequent repair, and maintain the long-term stability of the roadway. Compared to the original support, the new support method can greatly save investment of mines, and has good application value and popularization value.

Deep water characteristics and circulation in the South China Sea

Science.gov (United States)

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

2018-04-01

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

Rapid and Deep Proteomes by Faster Sequencing on a Benchtop Quadrupole Ultra-High-Field Orbitrap Mass Spectrometer

DEFF Research Database (Denmark)

Kelstrup, Christian D; Jersie-Christensen, Rosa R; Batth, Tanveer Singh

2014-01-01

per second or up to 600 new peptides sequenced per gradient minute. We identify 4400 proteins from one microgram of HeLa digest using a one hour gradient, which is an approximately 30% improvement compared to previous instrumentation. In addition, we show very deep proteome coverage can be achieved...... in less than 24 hours of analysis time by offline high pH reversed-phase peptide fractionation from which we identify more than 140,000 unique peptide sequences. This is comparable to state-of-the-art multi-day, multi-enzyme efforts. Finally the acquisition methods are evaluated for single...

Deep sea mega-geomorphology: Progress and problems

Science.gov (United States)

Bryan, W. B.

1985-01-01

Historically, marine geologists have always worked with mega-scale morphology. This is a consequence both of the scale of the ocean basins and of the low resolution of the observational remote sensing tools available until very recently. In fact, studies of deep sea morphology have suffered from a serious gap in observational scale. Traditional wide-beam echo sounding gave images on a scale of miles, while deep sea photography has been limited to scales of a few tens of meters. Recent development of modern narrow-beam echo sounding coupled with computer-controlled swath mapping systems, and development of high-resolution deep-towed side-scan sonar, are rapidly filling in the scale gap. These technologies also can resolve morphologic detail on a scale of a few meters or less. As has also been true in planetary imaging projects, the ability to observe phenomena over a range of scales has proved very effective in both defining processes and in placing them in proper context.

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.

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

Guidelines for the operation and closure of deep geological repositories for the disposal of high level and alpha bearing wastes

International Nuclear Information System (INIS)

1991-10-01

The operation and closure of a deep geological repository for the disposal of high level and alpha bearing wastes is a long term project involving many disciplines. This unique combination of nuclear operations in a deep underground location will require careful planning by the operating organization. The basic purpose of the operation stage of the deep repository is to ensure the safe disposal of the radioactive wastes. The purpose of the closure stage is to ensure that the wastes are safely isolated from the biosphere, and that the surface region can be returned to normal use. During these two stages of operation and closure, it is essential that both workers and the public are safely protected from radiation hazards, and that workers are protected from the hazards of working underground. For these periods of the repository, it is essential to carry out monitoring for purposes of radiological protection, and to continue testing and investigations to provide data for repository performance confirmation and for final safety assessment. Over the lengthy stages of operation and closure, there will be substantial feedback of experience and generation of site data. These will lead both to improved quality of operation and a better understanding of the site characteristics, thereby enhancing the confidence in the ability of the repository system to isolate the waste and protect future generations. 15 refs

Chronicles of the deep : ageing deep-sea corals in New Zealand waters

International Nuclear Information System (INIS)

Tracey, D.; Neil, H.; Gordon, D.; O'Shea, S.

2003-01-01

How old is a coral? Finding the answer requires some rather complex steps. We need to understand: the source of carbonate; the effects of climatic events; how to interpret growth zones; the effect of 14 C and biological processes such as feeding and reproduction; and how to overcome the lack of deep-sea environmental data records. We also need to find out where on the coral we should be sampling to get the best estimates of age. At the moment we know little about how deep-sea corals deposit their calcite, but we will be exploring this further so that we can have greater confidence in our age estimates. To confirm and validate age and growth, it will be necessary to use a combination of some of the the possible methods for ageing coral. In addition to ageing the corals, this work should yield a high-resolution record of ocean temperature during the past 100 years by using stable-isotope signatures preserved in the corals' carbonate skeletons. (author). 4 figs

Combination Treatment of Deep Sea Water and Fucoidan Attenuates High Glucose-Induced Insulin-Resistance in HepG2 Hepatocytes

OpenAIRE

Shan He; Wei-Bing Peng; Hong-Lei Zhou

2018-01-01

Insulin resistance (IR) plays a central role in the development of several metabolic diseases, which leads to increased morbidity and mortality rates, in addition to soaring health-care costs. Deep sea water (DSW) and fucoidans (FPS) have drawn much attention in recent years because of their potential medical and pharmaceutical applications. This study investigated the effects and mechanisms of combination treatment of DSW and FPS in improving IR in HepG2 hepatocytes induced by a high glucose...

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.

A Fuel Microanalysis for a Deep Burn-High Temperature Reactor

International Nuclear Information System (INIS)

Kim, Young Min; Jo, Chang Keun; Jun, Ji Su; Cho, Moon Sung

2010-08-01

The microanalysis for a deep burn-high temperature reactor (DB-HTR) covers the gas pressure buildup in a coated fuel particle (CFP), the thermo-mechanical behavior of a CFP, the failure probabilities of CFPs, the thermal analysis for a fuel element and a CFP, and the fission product transport into a coolant. The fuel performance analysis code of KAERI, COPA, is used in the microanalysis. The considered fuel materials are 0.2% UO 2 + 99.8% (5% NpO 2 + 95% PuO 1.8 ) mixed with 0.6 moles of silicon carbide (SiC) per mole of heavy metal and 30% UO 2 + 70% (5% NpO 2 + 95% PuO 1.8 ) mixed with 0.6 moles SiC per mole of heavy metal. Two thermal powers, 600 and 450 MW th , are taken into account. It was assumed that the DB-HTR was operated at constant temperature and power for normal operation and then was subjected to a low pressure conduction cooling (LPCC) accident for 250 hours. All the fuels of the DB-HTRs had good mechanical and thermal integrity during normal operation. But in the LPCC accident, whole particle failure occurred in the 600 MW DB-HTRs and the failure fractions in the 450 MW DB-HTRs are below 0.03. In order to secure the integrity of CFPs during the LPCC accident, it is necessary to reduce the excessive temperatures and the gas pressure in a CFP

Reversible deep storage: reversibility options for storage in deep geological formations

International Nuclear Information System (INIS)

2009-01-01

This report describes the definition approach to reversibility conditions, presents the main characteristics of high-activity and intermediate-activity long-lived wastes, describes the storage in deep geological formations (safety functions, general description of the storage centre), discusses the design options for the different types of wastes (container, storage module, handling processes, phenomenological analysis, monitoring arrangements) and the decision process in support reversibility (steering of the storage process, progressive development and step-by-step closing), and reports and discusses the researches concerning the memory of the storage site

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.

Process optimization of a deep trench isolation structure for high voltage SOI devices

International Nuclear Information System (INIS)

Zhu Kuiying; Qian Qinsong; Zhu Jing; Sun Weifeng

2010-01-01

The process reasons for weak point formation of the deep trench on SOI wafers have been analyzed in detail. An optimized trench process is also proposed. It is found that there are two main reasons: one is over-etching laterally of the silicon on the surface of the buried oxide caused by a fringe effect; and the other is the slow growth rate of the isolation oxide in the concave silicon corner of the trench bottom. In order to improve the isolation performance of the deep trench, two feasible ways for optimizing the trench process are proposed. The improved process thickens the isolation oxide and rounds sharp silicon corners at their weak points, increasing the applied voltage by 15-20 V at the same leakage current. The proposed new trench isolation process has been verified in the foundry's 0.5-μm HV SOI technology. (semiconductor devices)

Out of their depth? Isolated deep populations of the cosmopolitan coral Desmophyllum dianthus may be highly vulnerable to environmental change.

Directory of Open Access Journals (Sweden)

Karen J Miller

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

Out of their depth? Isolated deep populations of the cosmopolitan coral Desmophyllum dianthus may be highly vulnerable to environmental change.

Science.gov (United States)

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

2011-01-01

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

Multicenter evaluation of the Sepsityper™ extraction kit and MALDI-TOF MS for direct identification of positive blood culture isolates using the BD BACTEC™ FX and VersaTREK(®) diagnostic blood culture systems.

Science.gov (United States)

Schieffer, K M; Tan, K E; Stamper, P D; Somogyi, A; Andrea, S B; Wakefield, T; Romagnoli, M; Chapin, K C; Wolk, D M; Carroll, K C

2014-04-01

(i) Evaluation of delayed time to blood culture extraction by the Sepsityper kit and impact of shipping pellets off-site for MALDI-TOF MS analysis. (ii) Comparison of Sepsityper and laboratory-developed extraction methods from a literature review. Using two blood culture systems (BD BACTEC and VersaTREK), we extracted 411 positive blood cultures using the Sepsityper kit to mimic a potential protocol for institutions without a MALDI-TOF MS. Extracted pellets were shipped and analysed on the Bruker UltraflexIII. Successful extraction of 358 (87·1%) samples was determined by the presence of detectable proteins. MALDI-TOF MS correctly identified 332 (80·8%) samples. Delayed time to extraction did not affect Sepsityper extraction or MALDI-TOF MS accuracy. The extracted pellets remain stable and provide accurate results by MALDI-TOF MS when shipped at room temperature to off-site reference laboratories. This is the first study to show that institutions without a MALDI-TOF MS can take advantage of this innovative technology by shipping a volume of blood to an off-site laboratory for extraction and MALDI-TOF MS analysis. We also performed a literature review to compare various extraction methods. © 2014 The Society for Applied Microbiology.

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

Science.gov (United States)

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

2017-12-05

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

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

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

Science.gov (United States)

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

Deep imitation learning for 3D navigation tasks.

Science.gov (United States)

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

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

Science.gov (United States)

Purkey, S. G.; Llovel, W.

2017-12-01

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

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.

2017-03-13

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it\\'s time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.; Khan, Ayaz H.

2017-01-01

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it's time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Double seismic zone for deep earthquakes in the izu-bonin subduction zone.

Science.gov (United States)

Iidaka, T; Furukawa, Y

1994-02-25

A double seismic zone for deep earthquakes was found in the Izu-Bonin region. An analysis of SP-converted phases confirms that the deep seismic zone consists of two layers separated by approximately 20 kilometers. Numerical modeling of the thermal structure implies that the hypocenters are located along isotherms of 500 degrees to 550 degrees C, which is consistent with the hypothesis that deep earthquakes result from the phase transition of metastable olivine to a high-pressure phase in the subducting slab.

SyPRID sampler: A large-volume, high-resolution, autonomous, deep-ocean precision plankton sampling system

Science.gov (United States)

Billings, Andrew; Kaiser, Carl; Young, Craig M.; Hiebert, Laurel S.; Cole, Eli; Wagner, Jamie K. S.; Van Dover, Cindy Lee

2017-03-01

The current standard for large-volume (thousands of cubic meters) zooplankton sampling in the deep sea is the MOCNESS, a system of multiple opening-closing nets, typically lowered to within 50 m of the seabed and towed obliquely to the surface to obtain low-spatial-resolution samples that integrate across 10 s of meters of water depth. The SyPRID (Sentry Precision Robotic Impeller Driven) sampler is an innovative, deep-rated (6000 m) plankton sampler that partners with the Sentry Autonomous Underwater Vehicle (AUV) to obtain paired, large-volume plankton samples at specified depths and survey lines to within 1.5 m of the seabed and with simultaneous collection of sensor data. SyPRID uses a perforated Ultra-High-Molecular-Weight (UHMW) plastic tube to support a fine mesh net within an outer carbon composite tube (tube-within-a-tube design), with an axial flow pump located aft of the capture filter. The pump facilitates flow through the system and reduces or possibly eliminates the bow wave at the mouth opening. The cod end, a hollow truncated cone, is also made of UHMW plastic and includes a collection volume designed to provide an area where zooplankton can collect, out of the high flow region. SyPRID attaches as a saddle-pack to the Sentry vehicle. Sentry itself is configured with a flight control system that enables autonomous survey paths to low altitudes. In its verification deployment at the Blake Ridge Seep (2160 m) on the US Atlantic Margin, SyPRID was operated for 6 h at an altitude of 5 m. It recovered plankton samples, including delicate living larvae, from the near-bottom stratum that is seldom sampled by a typical MOCNESS tow. The prototype SyPRID and its next generations will enable studies of plankton or other particulate distributions associated with localized physico-chemical strata in the water column or above patchy habitats on the seafloor.

Initial observations of cell-mediated drug delivery to the deep lung.

Science.gov (United States)

Kumar, Arun; Glaum, Mark; El-Badri, Nagwa; Mohapatra, Shyam; Haller, Edward; Park, Seungjoo; Patrick, Leslie; Nattkemper, Leigh; Vo, Dawn; Cameron, Don F

2011-01-01

Using current methodologies, drug delivery to small airways, terminal bronchioles, and alveoli (deep lung) is inefficient, especially to the lower lungs. Urgent lung pathologies such as acute respiratory distress syndrome (ARDS) and post-lung transplantation complications are difficult to treat, in part due to the methodological limitations in targeting the deep lung with high efficiency drug distribution to the site of pathology. To overcome drug delivery limitations inhibiting the optimization of deep lung therapy, isolated rat Sertoli cells preloaded with chitosan nanoparticles were use to obtain a high-density distribution and concentration (92%) of the nanoparticles in the lungs of mice by way of the peripheral venous vasculature rather than the more commonly used pulmonary route. Additionally, Sertoli cells were preloaded with chitosan nanoparticles coupled with the anti-inflammatory compound curcumin and then injected intravenously into control or experimental mice with deep lung inflammation. By 24 h postinjection, most of the curcumin load (∼90%) delivered in the injected Sertoli cells was present and distributed throughout the lungs, including the perialveloar sac area in the lower lungs. This was based on the high-density, positive quantification of both nanoparticles and curcumin in the lungs. There was a marked positive therapeutic effect achieved 24 h following curcumin treatment delivered by this Sertoli cell nanoparticle protocol (SNAP). Results identify a novel and efficient protocol for targeted delivery of drugs to the deep lung mediated by extratesticular Sertoli cells. Utilization of SNAP delivery may optimize drug therapy for conditions such as ARDS, status asthmaticus, pulmonary hypertension, lung cancer, and complications following lung transplantation where the use of high concentrations of anti-inflammatory drugs is desirable, but often limited by risks of systemic drug toxicity.

Finite Element Analysis and Optimization for the Multi-stage Deep Drawing of Molybdenum Sheet

International Nuclear Information System (INIS)

Kim, Heung-Kyu; Hong, Seok Kwan; Kang, Jeong Jin; Heo, Young-moo; Lee, Jong-Kil; Jeon, Byung-Hee

2005-01-01

Molybdenum, a bcc refractory metal with a melting point of about 2600 deg. C, has a high heat and electrical conductivity. In addition, it remains strong mechanically at high temperatures as well as at low temperatures. Therefore it is a technologically very important material for the applications operating at high temperatures. However, a multi-stage process is required due to the low drawability for making a deep drawn part from the molybdenum sheet. In this study, a multi-stage deep drawing process for a molybdenum circular cup was designed by combining the drawing with the ironing, which was effective for the low drawability materials. A parametric study by FE analysis for the multi-stage deep drawing was conducted for evaluation of the design variables effect. Based on the FE analysis result, the multi-stage deep drawing process was parameterized by the design variables, and an optimum process design was obtained by the process optimization based on the FE simulation at each stage

Extending the Lunar Mapping and Modeling Portal - New Capabilities and New Worlds

Science.gov (United States)

Day, B. H.; Law, E.; Arevalo, E.; Bui, B.; Chang, G.; Dodge, K.; Kim, R. M.; Malhotra, S.; Sadaqathullah, S.

2015-12-01

NASA's Lunar Mapping and Modeling Portal (LMMP) provides a web-based Portal and a suite of interactive visualization and analysis tools to enable mission planners, lunar scientists, and engineers to access mapped lunar data products from past and current lunar missions (http://lmmp.nasa.gov). During the past year, the capabilities and data served by LMMP have been significantly expanded. New interfaces are providing improved ways to access and visualize data. Many of the recent enhancements to LMMP have been specifically in response to the requirements of NASA's proposed Resource Prospector lunar rover, and as such, provide an excellent example of the application of LMMP to mission planning. At the request of NASA's Science Mission Directorate, LMMP's technology and capabilities are now being extended to additional planetary bodies. New portals for Vesta and Mars are the first of these new products to be released. On March 31, 2015, the LMMP team released Vesta Trek (http://vestatrek.jpl.nasa.gov), a web-based application applying LMMP technology to visualizations of the asteroid Vesta. Data gathered from multiple instruments aboard Dawn have been compiled into Vesta Trek's user-friendly set of tools, enabling users to study the asteroid's features. With an initial release on July 1, 2015, Mars Trek replicates the functionality of Vesta Trek for the surface of Mars. While the entire surface of Mars is covered, higher levels of resolution and greater numbers of data products are provided for special areas of interest. Early releases focus on past, current, and future robotic sites of operation. Future releases will add many new data products and analysis tools as Mars Trek has been selected for use in site selection for the Mars 2020 rover and in identifying potential human landing sites on Mars. Other destinations will follow soon. The user community is invited to provide suggestions and requests as the development team continues to expand the capabilities of LMMP

The Deep Space Gateway Lightning Mapper (DLM) — Monitoring Global Change and Thunderstorm Processes through Observations of Earth's High-Latitude Lightning from Cis-Lunar Orbit

Science.gov (United States)

Lang, T. J.; Blakeslee, R. J.; Cecil, D. J.; Christian, H. J.; Gatlin, P. N.; Goodman, S. J.; Koshak, W. J.; Petersen, W. A.; Quick, M.; Schultz, C. J.; Tatum, P. F.

2018-02-01

We propose the Deep Space Gateway Lightning Mapper (DLM) instrument. The primary goal of the DLM is to optically monitor Earth's high-latitude (50° and poleward) total lightning not observed by current and planned spaceborne lightning mappers.

Current Status of Deep Geological Repository Development

International Nuclear Information System (INIS)

Budnitz, R J

2005-01-01

This talk provided an overview of the current status of deep-geological-repository development worldwide. Its principal observation is that a broad consensus exists internationally that deep-geological disposal is the only long-term solution for disposition of highly radioactive nuclear waste. Also, it is now clear that the institutional and political aspects are as important as the technical aspects in achieving overall progress. Different nations have taken different approaches to overall management of their highly radioactive wastes. Some have begun active programs to develop a deep repository for permanent disposal: the most active such programs are in the United States, Sweden, and Finland. Other countries (including France and Russia) are still deciding on whether to proceed quickly to develop such a repository, while still others (including the UK, China, Japan) have affirmatively decided to delay repository development for a long time, typically for a generation of two. In recent years, a major conclusion has been reached around the world that there is very high confidence that deep repositories can be built, operated, and closed safely and can meet whatever safety requirements are imposed by the regulatory agencies. This confidence, which has emerged in the last few years, is based on extensive work around the world in understanding how repositories behave, including both the engineering aspects and the natural-setting aspects, and how they interact together. The construction of repositories is now understood to be technically feasible, and no major barriers have been identified that would stand in the way of a successful project. Another major conclusion around the world is that the overall cost of a deep repository is not as high as some had predicted or feared. While the actual cost will not be known in detail until the costs are incurred, the general consensus is that the total life-cycle cost will not exceed a few percent of the value of the

Comparative Analysis of Single and Dual Irradiation Pass of Deep Burn High Temperature Reactor Scenario

International Nuclear Information System (INIS)

Jeong, Chang Joon; Jo, Chang Keun; Noh, Jae Man

2012-01-01

A concept of a deep-burn (DB) of trans uranic (TRU) elements in a high temperature reactor (HTR) has been proposed and studied with a single irradiation pass. However, there is still a significant amount of TRU after burn in an HTR. Therefore, it is necessary to burn more TRU in a fast reactor (FR) with repeated reprocessing such as a pyro-process. In this study, the fuel cycle calculations are performed and the results are compared for a singlepass DB-HHR scenario and a dual-pass sodium-cooled fast reactor (SFR) scenario. For the analysis, front-end and back-end parameters are compared. The calculations were performed by the DANESS (Dynamic Analysis of Nuclear Energy System Strategies), which is an integrated system dynamic fuel cycle analysis code

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

Science.gov (United States)

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

2017-11-13

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

Status and prospects of exploration and exploitation key technologies of the deep petroleum resources in onshore China

Directory of Open Access Journals (Sweden)

Genshun Yao

2018-02-01

Full Text Available In recent years, China's deep oil and gas exploration and exploitation have developed rapidly. Technological advancements have played an important role in the rapid exploration and highly efficient development. Aimed at the complex engineering geological environment of deep oil and gas in China, this paper has combined the four technological systems that have made significant progress, mainly including: (1 seismic imaging and reservoir prediction techniques for deep–burial complex structures, includign “2W1S” technique (wide-band, wide azimuth, and small bin, RTM (Reverse Time Migration, integrated modeling technology for complex structures and variable velocity mapping technique, improving structural interpretation accuracy, ensuring high precision ofimaging, and prediction for deep geological bodies; (2 deep speed raising and efficiency drilling technology series, which significantly improved the drilling speed, in turn reduced the drilling cost and drilling risk; (3 development of a deep high-temperature and high-pressure logging technology series, which provided a guarantee for the accurate identification of reservoir properties and fluid properties; (4 the efficient development technology for deep reservoirs, especially the development and maturity of the reconstruction volume technology, improve the production of single well and the benefit of deep oil and gas development. This paper further points out the improvement direction of the four major technology series of deep oil based on the analysis of the current development of the four major technological systems. Moreover, the development of applicability and economy for technical system is the key to realize high efficiency and low-cost exploration and development of deep oil and gas. Keywords: Deep oil & gas, Exploration and exploitation technologies, Seismic, Logging, Drilling, Petroleum reservoir stimulation

Uncovering the mechanism(s) of deep brain stimulation

International Nuclear Information System (INIS)

Li Gang; Yu Chao; Lin Ling; Lu, Stephen C-Y

2005-01-01

Deep brain stimulators, often called 'pacemakers for the brain', are implantable devices which continuously deliver impulse stimulation to specific targeted nuclei of deep brain structure, namely deep brain stimulation (DBS). To date, deep brain stimulation (DBS) is the most effective clinical technique for the treatment of several medically refractory movement disorders (e.g., Parkinson's disease, essential tremor, and dystonia). In addition, new clinical applications of DBS for other neurologic and psychiatric disorders (e.g., epilepsy and obsessive-compulsive disorder) have been put forward. Although DBS has been effective in the treatment of movement disorders and is rapidly being explored for the treatment of other neurologic disorders, the scientific understanding of its mechanisms of action remains unclear and continues to be debated in the scientific community. Optimization of DBS technology for present and future therapeutic applications will depend on identification of the therapeutic mechanism(s) of action. The goal of this review is to address our present knowledge of the effects of high-frequency stimulation within the central nervous system and comment on the functional implications of this knowledge for uncovering the mechanism(s) of DBS

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.

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,

Deep learning for computational chemistry

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-08

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

Deep 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.

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...

High-pressure hydrogen respiration in hydrothermal vent samples from the deep biosphere

Science.gov (United States)

Morgan-Smith, D.; Schrenk, M. O.

2013-12-01

Cultivation of organisms from the deep biosphere has met with many challenges, chief among them the ability to replicate this extreme environment in a laboratory setting. The maintenance of in situ pressure levels, carbon sources, and gas concentrations are important, intertwined factors which may all affect the growth of subsurface microorganisms. Hydrogen in particular is of great importance in hydrothermal systems, but in situ hydrogen concentrations are largely disregarded in attempts to culture from these sites. Using modified Hungate-type culture tubes (Bowles et al. 2011) within pressure-retaining vessels, which allow for the dissolution of higher concentrations of gas than is possible with other culturing methods, we have incubated hydrothermal chimney and hydrothermally-altered rock samples from the Lost City and Mid-Cayman Rise hydrothermal vent fields. Hydrogen concentrations up to 15 mmol/kg have been reported from Lost City (Kelley et al. 2005), but data are not yet available from the recently-discovered Mid-Cayman site, and the elevated concentration of 30 mmol/kg is being used in all incubations. We are using a variety of media types to enrich for various metabolic pathways including iron and sulfur reduction under anoxic or microaerophilic conditions. Incubations are being carried out at atmospheric (0.1 MPa), in situ (9, 23, or 50 MPa, depending on site), and elevated (50 MPa) pressure levels. Microbial cell concentrations, taxonomic diversity, and metabolic activities are being monitored during the course of these experiments. These experiments will provide insight into the relationships between microbial activities, pressure, and gas concentrations typical of deep biosphere environments. Results will inform further culturing studies from both fresh and archived samples. References cited: Bowles, M.W., Samarkin, V.A., Joye, S.B. 2011. Improved measurement of microbial activity in deep-sea sediments at in situ pressure and methane concentration

Study on the flotation technology for deep-cleaning of coal slime

Energy Technology Data Exchange (ETDEWEB)

Fu Xiao-heng; Shan Xiao-yun; Jiang He-jin; Li Xiang-li [China University of Mining and Technology, Beijing (China). School of Chemical and Environmental Engineering

2006-07-01

The paper introduced the basic principle and special features of deep-cleaning of coal slime by flotation, first, separating the slime by conventional flotation to give a relatively low ash concentrate, a tailing containing an ash as high as possible, followed by flocculation-flotation to recover additional low ash concentrate. The regressive release flotation test and microphoto indicated that the middling consists mainly of intergrowth particles of coal and minerals. Comparison between deep-cleaning and conventional flotation results denoted that, at approximately same concentrate ash, its yield by deep-cleaning was 46.06 percent point higher, and at similar yield, its concentrate ash, 1.78 percent point lower. The performance by deep-cleaning is even better than that by regressive release flotation test. 4 refs., 2 figs., 6 tabs.

Deep surface rolling for fatigue life enhancement of laser clad aircraft aluminium alloy

Energy Technology Data Exchange (ETDEWEB)

Zhuang, W., E-mail: wyman.zhuang@dsto.defence.gov.au [Aerospace Division, Defence Science and Technology Organisation, 506 Lorimer Street, Fishermans Bend, Victoria 3207 (Australia); Liu, Q.; Djugum, R.; Sharp, P.K. [Aerospace Division, Defence Science and Technology Organisation, 506 Lorimer Street, Fishermans Bend, Victoria 3207 (Australia); Paradowska, A. [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW 2232 (Australia)

2014-11-30

Highlights: • Deep surface rolling as a post-repair enhancement technology was applied to the laser cladded 7075-T651 aluminium alloy specimens that simulated corrosion damage blend-out repair. • The residual stresses induced by the deep surface rolling process were measured. • The deep surface rolling process can introduce deep and high magnitude compressive residual stresses beyond the laser clad and substrate interface. • Spectrum fatigue test showed the fatigue life was significantly increased by deep surface rolling. - Abstract: Deep surface rolling can introduce deep compressive residual stresses into the surface of aircraft metallic structure to extend its fatigue life. To develop cost-effective aircraft structural repair technologies such as laser cladding, deep surface rolling was considered as an advanced post-repair surface enhancement technology. In this study, aluminium alloy 7075-T651 specimens with a blend-out region were first repaired using laser cladding technology. The surface of the laser cladding region was then treated by deep surface rolling. Fatigue testing was subsequently conducted for the laser clad, deep surface rolled and post-heat treated laser clad specimens. It was found that deep surface rolling can significantly improve the fatigue life in comparison with the laser clad baseline repair. In addition, three dimensional residual stresses were measured using neutron diffraction techniques. The results demonstrate that beneficial compressive residual stresses induced by deep surface rolling can reach considerable depths (more than 1.0 mm) below the laser clad surface.

Deep surface rolling for fatigue life enhancement of laser clad aircraft aluminium alloy

International Nuclear Information System (INIS)

Zhuang, W.; Liu, Q.; Djugum, R.; Sharp, P.K.; Paradowska, A.

2014-01-01

Highlights: • Deep surface rolling as a post-repair enhancement technology was applied to the laser cladded 7075-T651 aluminium alloy specimens that simulated corrosion damage blend-out repair. • The residual stresses induced by the deep surface rolling process were measured. • The deep surface rolling process can introduce deep and high magnitude compressive residual stresses beyond the laser clad and substrate interface. • Spectrum fatigue test showed the fatigue life was significantly increased by deep surface rolling. - Abstract: Deep surface rolling can introduce deep compressive residual stresses into the surface of aircraft metallic structure to extend its fatigue life. To develop cost-effective aircraft structural repair technologies such as laser cladding, deep surface rolling was considered as an advanced post-repair surface enhancement technology. In this study, aluminium alloy 7075-T651 specimens with a blend-out region were first repaired using laser cladding technology. The surface of the laser cladding region was then treated by deep surface rolling. Fatigue testing was subsequently conducted for the laser clad, deep surface rolled and post-heat treated laser clad specimens. It was found that deep surface rolling can significantly improve the fatigue life in comparison with the laser clad baseline repair. In addition, three dimensional residual stresses were measured using neutron diffraction techniques. The results demonstrate that beneficial compressive residual stresses induced by deep surface rolling can reach considerable depths (more than 1.0 mm) below the laser clad surface

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)

Characterization of irradiation induced deep and shallow impurities

Science.gov (United States)

Treberspurg, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Krammer, Manfred; Valentan, Manfred

2013-12-01

Silicon Detectors close to the interaction point of the High Luminosity Large Hardron Collider (HL-LHC) have to withstand a harsh irradiation environment. In order to evaluate the behaviour of shallow and deep defects, induced by neutron irradiation, spreading resistance resistivity measurements and capacitance voltage measurements have been performed. These measurements, deliver information about the profile of shallow impurities after irradiation as well as indications of deep defects in the Space Charge Region (SCR) and the Electrical Neutral Bulk (ENB). By considering the theoretical background of the measurement both kinds of defects can be investigated independently from each other.

Characterization of irradiation induced deep and shallow impurities

Energy Technology Data Exchange (ETDEWEB)

Treberspurg, Wolfgang, E-mail: wolfgang.treberspurg@oeaw.ac.at; Bergauer, Thomas; Dragicevic, Marko; Krammer, Manfred; Valentan, Manfred

2013-12-21

Silicon Detectors close to the interaction point of the High Luminosity Large Hardron Collider (HL-LHC) have to withstand a harsh irradiation environment. In order to evaluate the behaviour of shallow and deep defects, induced by neutron irradiation, spreading resistance resistivity measurements and capacitance voltage measurements have been performed. These measurements, deliver information about the profile of shallow impurities after irradiation as well as indications of deep defects in the Space Charge Region (SCR) and the Electrical Neutral Bulk (ENB). By considering the theoretical background of the measurement both kinds of defects can be investigated independently from each other.

Characterization of irradiation induced deep and shallow impurities

International Nuclear Information System (INIS)

Treberspurg, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Krammer, Manfred; Valentan, Manfred

2013-01-01

Silicon Detectors close to the interaction point of the High Luminosity Large Hardron Collider (HL-LHC) have to withstand a harsh irradiation environment. In order to evaluate the behaviour of shallow and deep defects, induced by neutron irradiation, spreading resistance resistivity measurements and capacitance voltage measurements have been performed. These measurements, deliver information about the profile of shallow impurities after irradiation as well as indications of deep defects in the Space Charge Region (SCR) and the Electrical Neutral Bulk (ENB). By considering the theoretical background of the measurement both kinds of defects can be investigated independently from each other

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

Science.gov (United States)

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

2016-07-08

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

Feasibility of disposal of high-level radioactive waste into the seabed. volume 7: Review of laboratory investigations of radionuclide migration through deep-sea sediments

International Nuclear Information System (INIS)

Brush, L.H.

1988-01-01

One of the options suggested for disposal of high-level radioactive waste resulting from the generation of nuclear power is burial beneath the deep ocean floor in geologically stable sediment formations which have no economic value. The 8-volume series provides an assessment of the technical feasibility and radiological safety of this disposal concept based on the results obtained by ten years of co-operation and information exchange among the Member countries participating in the NEA Seabed Working Group. This volume contains a review of the laboratory investigations of radionuclide migration through deep-sea sediments. In addition, it discusses the data selected for the radiological assessment, on the basis of both field and laboratory studies

High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

Science.gov (United States)

Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

2017-09-01

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

Testing deep-sea biodiversity paradigms on abyssal nematode genera and Acantholaimus species

Science.gov (United States)

Lins, Lidia; da Silva, Maria Cristina; Neres, Patrícia; Esteves, André Morgado; Vanreusel, Ann

2018-02-01

Biodiversity patterns in the deep sea have been extensively studied in the last decades. In this study, we investigated whether reputable concepts in deep-sea ecology also explain diversity and distribution patterns of nematode genera and species in the abyss. Among them, three paradigms were tackled: (1) the deep sea is a highly diverse environment at a local scale, while on a regional and even larger geographical scale, species and genus turnover is limited; (2) the biodiversity of deep-sea nematode communities changes with the nature and amount of organic matter input from the surface; and (3) patch-mosaic dynamics of the deep-sea environment drive local diversity. To test these hypotheses, diversity and density of nematode assemblages and of species of the genus Acantholaimus were studied along two abyssal E-W transects. These two transects were situated in the Southern Ocean ( 50°S) and the North Atlantic ( 10°N). Four different hierarchical scales were used to compare biodiversity: at the scale of cores, between stations from the same region, and between regions. Results revealed that the deep sea harbours a high diversity at a local scale (alpha diversity), but that turnover can be shaped by different environmental drivers. Therefore, these results question the second part of the paradigm about limited species turnover in the deep sea. Higher surface primary productivity was correlated with greater nematode densities, whereas diversity responses to the augmentation of surface productivity showed no trend. Areas subjected to a constant and low food input revealed similar nematode communities to other oligotrophic abyssal areas, while stations under high productivity were characterized by different dominant genera and Acantholaimus species, and by a generally low local diversity. Our results corroborate the species-energy hypothesis, where productivity can set a limit to the richness of an ecosystem. Finally, we observed no correlation between sediment

Support technology of deep roadway under high stress and its application

Institute of Scientific and Technical Information of China (English)

Cao Rihong; Cao Ping; Lin Hang

2016-01-01

Roadway instability has been a major concern in the fields of mining engineering. This paper aims to pro-vide practical and efficient strategy to support the roadways under high in-situ stress. A case study on the stability of deep roadways was carried out in an underground mine in Gansu province, China. Currently, the surrounding rock strata is extremely fractured, which results in a series of engineering disasters, such as side wall collapse and severe floor heave in the past decades. Aiming to solve these problems, an improved support method was proposed, which includes optimal bolt parameters and arrangement, floor beam layout by grooving, and full length grouting. Based on the modeling results by FLAC3D, the new support method is much better than the current one in terms of preventing the large deformation of sur-rounding rock and restricting the development of plastic zones. For implementation and verification, field experiments, along with deformation monitoring, were conducted in the 958 level roadway of Mining II areas. The results show that the improved support can significantly reduce surrounding rock deforma-tion, avoid frequent repair, and maintain the long-term stability of the roadway. Compared to the original support, the new support method can greatly save investment of mines, and has good application value and popularization value.

High mitochondrial mutation rates estimated from deep-rooting Costa Rican pedigrees

Science.gov (United States)

Madrigal, Lorena; Melendez-Obando, Mauricio; Villegas-Palma, Ramon; Barrantes, Ramiro; Raventos, Henrieta; Pereira, Reynaldo; Luiselli, Donata; Pettener, Davide; Barbujani, Guido

2012-01-01

Estimates of mutation rates for the noncoding hypervariable Region I (HVR-I) of mitochondrial DNA (mtDNA) vary widely, depending on whether they are inferred from phylogenies (assuming that molecular evolution is clock-like) or directly from pedigrees. All pedigree-based studies so far were conducted on populations of European origin. In this paper we analyzed 19 deep-rooting pedigrees in a population of mixed origin in Costa Rica. We calculated two estimates of the HVR-I mutation rate, one considering all apparent mutations, and one disregarding changes at sites known to be mutational hot spots and eliminating genealogy branches which might be suspected to include errors, or unrecognized adoptions along the female lines. At the end of this procedure, we still observed a mutation rate equal to 1.24 × 10−6, per site per year, i.e., at least three-fold as high as estimates derived from phylogenies. Our results confirm that mutation rates observed in pedigrees are much higher than estimated assuming a neutral model of long-term HVRI evolution. We argue that, until the cause of these discrepancies will be fully understood, both lower estimates (i.e., those derived from phylogenetic comparisons) and higher, direct estimates such as those obtained in this study, should be considered when modeling evolutionary and demographic processes. PMID:22460349

High Frequency Deep Brain Stimulation and Neural Rhythms in Parkinson's Disease.

Science.gov (United States)

Blumenfeld, Zack; Brontë-Stewart, Helen

2015-12-01

High frequency (HF) deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD). It effectively treats the cardinal motor signs of PD, including tremor, bradykinesia, and rigidity. The most common neural target is the subthalamic nucleus, located within the basal ganglia, the region most acutely affected by PD pathology. Using chronically-implanted DBS electrodes, researchers have been able to record underlying neural rhythms from several nodes in the PD network as well as perturb it using DBS to measure the ensuing neural and behavioral effects, both acutely and over time. In this review, we provide an overview of the PD neural network, focusing on the pathophysiological signals that have been recorded from PD patients as well as the mechanisms underlying the therapeutic benefits of HF DBS. We then discuss evidence for the relationship between specific neural oscillations and symptoms of PD, including the aberrant relationships potentially underlying functional connectivity in PD as well as the use of different frequencies of stimulation to more specifically target certain symptoms. Finally, we briefly describe several current areas of investigation and how the ability to record neural data in ecologically-valid settings may allow researchers to explore the relationship between brain and behavior in an unprecedented manner, culminating in the future automation of neurostimulation therapy for the treatment of a variety of neuropsychiatric diseases.

An introduction to deep submicron CMOS for vertex applications

CERN Document Server

Campbell, M; Cantatore, E; Faccio, F; Heijne, Erik H M; Jarron, P; Santiard, Jean-Claude; Snoeys, W; Wyllie, K

2001-01-01

Microelectronics has become a key enabling technology in the development of tracking detectors for High Energy Physics. Deep submicron CMOS is likely to be extensively used in all future tracking systems. Radiation tolerance in the Mrad region has been achieved and complete readout chips comprising many millions of transistors now exist. The choice of technology is dictated by market forces but the adoption of deep submicron CMOS for tracking applications still poses some challenges. The techniques used are reviewed and some of the future challenges are discussed.

Studies of the reproductive biology of deep-sea megabenthos

International Nuclear Information System (INIS)

Tyler, P.A.

1987-07-01

The final report describes the general biology and ecology of the 15 holothurians, 3 asteroids, 2 zoanthids and 1 crustacea species studied in Reports I-XIII, the sampling methods used and the station data. A summary of the histological, histochemical and biochemical results for the species examined is given. The data suggest that the reproductive processes in the deep-sea species examined are highly unlikely to be part of a pathway for the transfer of radionuclides from the deep-sea back to man. (author)

Highly Efficient Solution-Processed Deep-Red Organic Light-Emitting Diodes Based on an Exciplex Host Composed of a Hole Transporter and a Bipolar Host.

Science.gov (United States)

Huang, Manli; Jiang, Bei; Xie, Guohua; Yang, Chuluo

2017-10-19

With the aim to achieve highly efficient deep-red emission, we introduced an exciplex forming cohost, 4,4',4″-tris(3-methylphenylphenylamino)triphenylamine (m-MTDATA): 2,5-bis(2-(9H-carbazol-9-yl)phenyl)-1,3,4-oxadiazole (o-CzOXD) (1:1). Due to the efficient triplet up-conversion processes upon the exciplex forming cohost, excellent performances of the devices were achieved with deep-red emission. Using the heteroleptic iridium complexes as the guest dopants, the solution-processed deep-red phosphorescent organic light-emitting diodes (PhOLEDs) with the iridium(III) bis(6-(4-(tert-butyl)phenyl)phenanthridine)acetylacetonate [(TP-BQ) 2 Ir(acac)]-based phosphorescent emitter exhibited an electroluminescent peak at 656 nm and a maximum external quantum efficiency (EQE) of 11.9%, which is 6.6 times that of the device based on the guest emitter doped in the polymer-based cohost. The unique exciplex with a typical hole transporter and a bipolar material is ideal and universal for hosting the red PhOLEDs and tremendously improves the device performances.

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

PERFORMANCE OF HIGH SCHOOL FOOTBALL PLAYERS ON CLINICAL MEASURES OF DEEP CERVICAL FLEXOR ENDURANCE AND CERVICAL ACTIVE RANGE OF MOTION: IS HISTORY OF CONCUSSION A FACTOR?

Science.gov (United States)

Smith, Laura; Ruediger, Thomas; Alsalaheen, Bara; Bean, Ryan

2016-04-01

More than one million adolescent athletes participated in organized high school sanctioned football during the 2014-15 season. These athletes are at risk for sustaining concussion. Although cervical spine active range of motion (AROM) and deep neck flexor endurance may serve a preventative role in concussion, and widespread clinical use of measurements of these variables, reference values are not available for this population. Cost effective, clinically relevant methods for measuring neck endurance are also well established for adolescent athletes. The purpose of this study was to report reference values for deep cervical flexor endurance and cervical AROM in adolescent football players and examine whether differences in these measures exist in high school football players with and without a history of concussion. Concussion history, cervical AROM, and deep neck flexor endurance were measured in 122 high school football players. Reference values were calculated for AROM and endurance measures; association were examined between various descriptive variables and concussion. No statistically significant differences were found between athletes with a history of concussion and those without. A modest inverse correlation was seen between body mass and AROM in the sagittal and transverse planes. The results of this study indicate that the participants with larger body mass had less cervical AROM in some directions. While cervical AROM and endurance measurements may not be adequate to identify adolescents with a history of previous concussions among high school football players. However, if a concussion is sustained, these measures can offer a baseline to examine whether cervical AROM is affected as compared to healthy adolescents. 2c.

A Programmable High-Voltage Compliance Neural Stimulator for Deep Brain Stimulation in Vivo

Directory of Open Access Journals (Sweden)

Cihun-Siyong Alex Gong

2015-05-01

Full Text Available Deep brain stimulation (DBS is one of the most effective therapies for movement and other disorders. The DBS neurosurgical procedure involves the implantation of a DBS device and a battery-operated neurotransmitter, which delivers electrical impulses to treatment targets through implanted electrodes. The DBS modulates the neuronal activities in the brain nucleus for improving physiological responses as long as an electric discharge above the stimulation threshold can be achieved. In an effort to improve the performance of an implanted DBS device, the device size, implementation cost, and power efficiency are among the most important DBS device design aspects. This study aims to present preliminary research results of an efficient stimulator, with emphasis on conversion efficiency. The prototype stimulator features high-voltage compliance, implemented with only a standard semiconductor process, without the use of extra masks in the foundry through our proposed circuit structure. The results of animal experiments, including evaluation of evoked responses induced by thalamic electrical stimuli with our fabricated chip, were shown to demonstrate the proof of concept of our design.

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

Electronic structure properties of deep defects in hBN

Science.gov (United States)

Dev, Pratibha; Prdm Collaboration

In recent years, the search for room-temperature solid-state qubit (quantum bit) candidates has revived interest in the study of deep-defect centers in semiconductors. The charged NV-center in diamond is the best known amongst these defects. However, as a host material, diamond poses several challenges and so, increasingly, there is an interest in exploring deep defects in alternative semiconductors such as hBN. The layered structure of hBN makes it a scalable platform for quantum applications, as there is a greater potential for controlling the location of the deep defect in the 2D-matrix through careful experiments. Using density functional theory-based methods, we have studied the electronic and structural properties of several deep defects in hBN. Native defects within hBN layers are shown to have high spin ground states that should survive even at room temperature, making them interesting solid-state qubit candidates in a 2D matrix. Partnership for Reduced Dimensional Material (PRDM) is part of the NSF sponsored Partnerships for Research and Education in Materials (PREM).

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

Key technologies for well drilling and completion in ultra-deep sour gas reservoirs, Yuanba Gasfield, Sichuan Basin

Directory of Open Access Journals (Sweden)

Jiaxiang Xia

2016-12-01

Full Text Available The Yuanba Gasfield is a large gas field discovered by Sinopec in the Sichuan Basin in recent years, and another main exploration area for natural gas reserves and production increase after the Puguang Gasfield. The ultra-deep sour gas reservoir in the Yuanba Gasfield is characterized by complicated geologic structure, deep reservoirs and complex drilled formation, especially in the continental deep strata which are highly abrasive with low ROP (rate of penetration and long drilling period. After many years of drilling practice and technical research, the following six key drilling and completion technologies for this type reservoir are established by introducing new tools and technologies, developing specialized drill bits and optimizing drilling design. They are: casing program optimization technology for ROP increasing and safe well completion; gas drilling technology for shallow continental strata and high-efficiency drilling technology for deep high-abrasion continental strata; drilling fluid support technologies of gas–liquid conversion, ultra-deep highly-deviated wells and horizontal-well lubrication and drag reduction, hole stability control and sour gas contamination prevention; well cementing technologies for gas medium, deep-well long cementing intervals and ultra-high pressure small space; horizontal-well trajectory control technologies for measuring instrument, downhole motor optimization and bottom hole assembly design; and liner completion modes and completion string optimization technologies suitable for this gas reservoir. Field application shows that these key technologies are contributive to ROP increase and efficiency improvement of 7000 m deep horizontal wells and to significant operational cycle shortening.

Improved process robustness by using closed loop control in deep drawing applications

Science.gov (United States)

Barthau, M.; Liewald, M.; Christian, Held

2017-09-01

The production of irregular shaped deep-drawing parts with high quality requirements, which are common in today’s automotive production, permanently challenges production processes. High requirements on lightweight construction of passenger car bodies following European regulations until 2020 have been massively increasing the use of high strength steels substantially for years and are also leading to bigger challenges in sheet metal part production. Of course, the more and more complex shapes of today’s car body shells also intensify the issue due to modern and future design criteria. The metal forming technology tries to meet these challenges by developing a highly sophisticated layout of deep drawing dies that consider part quality requirements, process robustness and controlled material flow during the deep or stretch drawing process phase. A new method for controlling material flow using a closed loop system was developed at the IFU Stuttgart. In contrast to previous approaches, this new method allows a control intervention during the deep-drawing stroke. The blank holder force around the outline of the drawn part is used as control variable. The closed loop is designed as trajectory follow up with feed forward control. The used command variable is the part-wall stress that is measured with a piezo-electric measuring pin. In this paper the used control loop will be described in detail. The experimental tool that was built for testing the new control approach is explained here with its features. A method for gaining the follow up trajectories from simulation will also be presented. Furthermore, experimental results considering the robustness of the deep drawing process and the gain in process performance with developed control loop will be shown. Finally, a new procedure for the industrial application of the new control method of deep drawing will be presented by using a new kind of active element to influence the local blank holder pressure onto part

Voederbomen in trek

NARCIS (Netherlands)

Eekeren, van N.J.M.; Luske, B.L.; Vonk, M.; Anssems, E.

2015-01-01

Bladeren en twijgen van bomen en struiken hebben potentie in het rantsoen van koeien, geiten en schapen, omdat ze een aanvullende bron zijn van eiwit, mineralen en sporenelementen. Daarnaast bevatten veel bomen secundaire plantenstoffen die een positief effect kunnen hebben op de vertering en de

Boosted Jet Tagging with Jet-Images and Deep Neural Networks

International Nuclear Information System (INIS)

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

2016-01-01

Building on the jet-image based representation of high energy jets, we develop computer vision based techniques for jet tagging through the use of deep neural networks. Jet-images enabled the connection between jet substructure and tagging with the fields of computer vision and image processing. We show how applying such techniques using deep neural networks can improve the performance to identify highly boosted W bosons with respect to state-of-the-art substructure methods. In addition, we explore new ways to extract and visualize the discriminating features of different classes of jets, adding a new capability to understand the physics within jets and to design more powerful jet tagging methods

Method for manufacturing nuclear radiation detector with deep diffused junction

International Nuclear Information System (INIS)

Hall, R.N.

1977-01-01

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

The structural integrity of high level waste containers for deep disposal

International Nuclear Information System (INIS)

Keer, T.J.; Martindale, N.J.; Haijtink, B.

1990-01-01

Most countries with a nuclear power program are developing plans to dispose of high level waste in deep geological repositories. These facilities are typically in the range 500-1000m below ground. Although long term safety analyses mainly rely on the isolation function of the geological barrier, for the medium term (between 500 and 1000 years) a barrier such as a container (overpack) may play an important role. This paper addresses the mechanical/structural behavior of these structures under extreme geological pressures. The work described in the paper was conducted within the COMPAS project (Container Mechanical Performance Assessment) funded by the Commission of the European Communities and the United Kingdom Department of the Environment. The work was aimed at predicting the modes of failure and failure pressures which characterize the heavy, thick walled mild steel containers which might be considered for the disposal of vitrified waste. The work involved a considerable amount of analytical work, using 3-D non-linear finite element techniques, coupled with a large parallel program of experimental work. The experimental work consisted of a number of scale model tests in which the response of the containers was examined under external pressures as high as 120MPa. Extensive strain-gauge instrumentation was used to record the behavior of the models as they were driven to collapse. A number of comparative computer calculations were carried out by organizations from various European countries. Correlations were established between experimental and analytical data and guidelines regarding the choice of suitable software were established. The work concluded with a full 3-D simulation of the behavior of a container under long-term disposal conditions. In this analysis, non-linearities due to geological effects and material/geometry effects in the container were properly accounted for. 6 refs., 9 figs., 4 tabs

Containers and overpacks for high-level radioactive waste in deep geological disposal. Conditions: French Corrosion Programme

International Nuclear Information System (INIS)

Crusset, D.; Plas, F.; Santarini, G.

2003-01-01

Within the framework of the act of French law dated 31 December, 1991, ANDRA (National Radioactive Waste Management Agency) is responsible for conducting the feasibility study on disposal of reversible and irreversible high-level or long-life radioactive waste in deep geological formations. Consequently, ANDRA is carrying out research on corrosion of the metallic materials envisaged for the possible construction of overpacks for vitrified waste packages or containers for spent nuclear fuel. Low-alloy or unalloyed steels and the passive alloys (Fe-Ni-Cr-Mo) constitute the two families of materials studied and ANDRA has set up a research programme in partnership with other research organisations. The 'broad outlines' of the programme, which includes experimental and modelling operations, are presented. (authors)

DeepGait: A Learning Deep Convolutional Representation for View-Invariant Gait Recognition Using Joint Bayesian

Directory of Open Access Journals (Sweden)

Chao Li

2017-02-01

Full Text Available Human gait, as a soft biometric, helps to recognize people through their walking. To further improve the recognition performance, we propose a novel video sensor-based gait representation, DeepGait, using deep convolutional features and introduce Joint Bayesian to model view variance. DeepGait is generated by using a pre-trained “very deep” network “D-Net” (VGG-D without any fine-tuning. For non-view setting, DeepGait outperforms hand-crafted representations (e.g., Gait Energy Image, Frequency-Domain Feature and Gait Flow Image, etc.. Furthermore, for cross-view setting, 256-dimensional DeepGait after PCA significantly outperforms the state-of-the-art methods on the OU-ISR large population (OULP dataset. The OULP dataset, which includes 4007 subjects, makes our result reliable in a statistically reliable way.

Winnie Rust

African Journals Online (AJOL)

Owner

Om te trek is om jou kortstondig in 'n liminale staat te bevind. Nóg by jou vertrekpunt, nóg by jou uiteindelike bestemming, sonder die geborgenheid wat hierdie twee vaste plekke kwansuis bied. In 'n hele aantal opsigte is Trek van Winnie Rust 'n beskrywing van verskil- lende liminale state. Dit is egter nie 'n reisverhaal met ...

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...

Standard high-resolution pelvic MRI vs. low-resolution pelvic MRI in the evaluation of deep infiltrating endometriosis

International Nuclear Information System (INIS)

Scardapane, Arnaldo; Lorusso, Filomenamila; Ferrante, Annunziata; Stabile Ianora, Amato Antonio; Angelelli, Giuseppe; Scioscia, Marco

2014-01-01

To compare the capabilities of standard pelvic MRI with low-resolution pelvic MRI using fast breath-hold sequences to evaluate deep infiltrating endometriosis (DIE). Sixty-eight consecutive women with suspected DIE were studied with pelvic MRI. A double-acquisition protocol was carried out in each case. High-resolution (HR)-MRI consisted of axial, sagittal, and coronal TSE T2W images, axial TSE T1W, and axial THRIVE. Low-resolution (LR)-MRI was acquired using fast single shot (SSH) T2 and T1 images. Two radiologists with 10 and 2 years of experience reviewed HR and LR images in two separate sessions. The presence of endometriotic lesions of the uterosacral ligament (USL), rectovaginal septum (RVS), pouch of Douglas (POD), and rectal wall was noted. The accuracies of LR-MRI and HR-MRI were compared with the laparoscopic and histopathological findings. Average acquisition times were 24 minutes for HR-MRI and 7 minutes for LR-MRI. The more experienced radiologist achieved higher accuracy with both HR-MRI and LR-MRI. The values of sensitivity, specificity, PPV, NPV, and accuracy did not significantly change between HR and LR images or interobserver agreement for all of the considered anatomic sites. LR-MRI performs as well as HR-MRI and is a valuable tool for the detection of deep endometriosis extension. (orig.)

Standard high-resolution pelvic MRI vs. low-resolution pelvic MRI in the evaluation of deep infiltrating endometriosis

Energy Technology Data Exchange (ETDEWEB)

Scardapane, Arnaldo; Lorusso, Filomenamila; Ferrante, Annunziata; Stabile Ianora, Amato Antonio; Angelelli, Giuseppe [University Hospital ' ' Policlinico' ' of Bari, Interdisciplinary Department of Medicine, Bari (Italy); Scioscia, Marco [Sacro Cuore Don Calabria General Hospital, Department of Obstetrics and Gynecology, Negrar, Verona (Italy)

2014-10-15

To compare the capabilities of standard pelvic MRI with low-resolution pelvic MRI using fast breath-hold sequences to evaluate deep infiltrating endometriosis (DIE). Sixty-eight consecutive women with suspected DIE were studied with pelvic MRI. A double-acquisition protocol was carried out in each case. High-resolution (HR)-MRI consisted of axial, sagittal, and coronal TSE T2W images, axial TSE T1W, and axial THRIVE. Low-resolution (LR)-MRI was acquired using fast single shot (SSH) T2 and T1 images. Two radiologists with 10 and 2 years of experience reviewed HR and LR images in two separate sessions. The presence of endometriotic lesions of the uterosacral ligament (USL), rectovaginal septum (RVS), pouch of Douglas (POD), and rectal wall was noted. The accuracies of LR-MRI and HR-MRI were compared with the laparoscopic and histopathological findings. Average acquisition times were 24 minutes for HR-MRI and 7 minutes for LR-MRI. The more experienced radiologist achieved higher accuracy with both HR-MRI and LR-MRI. The values of sensitivity, specificity, PPV, NPV, and accuracy did not significantly change between HR and LR images or interobserver agreement for all of the considered anatomic sites. LR-MRI performs as well as HR-MRI and is a valuable tool for the detection of deep endometriosis extension. (orig.)

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

Classification of radiolarian images with hand-crafted and deep features

Science.gov (United States)

Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

2017-12-01

Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

AlGaN-based deep-ultraviolet light-emitting diodes grown on high-quality AlN template using MOVPE

KAUST Repository

Yan, Jianchang; Wang, Junxi; Zhang, Yun; Cong, Peipei; Sun, Lili; Tian, Yingdong; Zhao, Chao; Li, Jinmin

2015-01-01

In this article, we report the growth of high-quality AlN film using metal-organic vapor phase epitaxy. Three layers of middle-temperature (MT) AlN were introduced during the high-temperature (HT) AlN growth. During the MT-AlN layer growth, aluminum and nitrogen sources were closed for 6 seconds after every 5-nm MT-AlN, while H2 carrier gas was always on. The threading dislocation density in an AlN epi-layer on a sapphire substrate was reduced by almost half. AlGaN-based deep-ultraviolet light-emitting diodes were further fabricated based on the AlN/sapphire template. At 20 mA driving current, the emitted peak wavelength is 284.5 nm and the light output power exceeds 3 mW.

AlGaN-based deep-ultraviolet light-emitting diodes grown on high-quality AlN template using MOVPE

KAUST Repository

Yan, Jianchang

2015-03-01

In this article, we report the growth of high-quality AlN film using metal-organic vapor phase epitaxy. Three layers of middle-temperature (MT) AlN were introduced during the high-temperature (HT) AlN growth. During the MT-AlN layer growth, aluminum and nitrogen sources were closed for 6 seconds after every 5-nm MT-AlN, while H2 carrier gas was always on. The threading dislocation density in an AlN epi-layer on a sapphire substrate was reduced by almost half. AlGaN-based deep-ultraviolet light-emitting diodes were further fabricated based on the AlN/sapphire template. At 20 mA driving current, the emitted peak wavelength is 284.5 nm and the light output power exceeds 3 mW.

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.

High-resolution and Deep Crustal Imaging Across The North Sicily Continental Margin (southern Tyrrhenian Sea)

Science.gov (United States)

Agate, M.; Bertotti, G.; Catalano, R.; Pepe, F.; Sulli, A.

Three multichannel seismic reflection profiles across the North Sicily continental mar- gin have been reprocessed and interpreted. Data consist of an unpublished high pene- tration seismic profile (deep crust Italian CROP Project) and a high-resolution seismic line. These lines run in the NNE-SSW direction, from the Sicilian continental shelf to the Tyrrhenian abyssal plain (Marsili area), and are tied by a third, high penetration seismic line MS104 crossing the Sisifo High. The North Sicily continental margin represents the inner sector of the Sicilian-Maghrebian chain that is collapsed as con- sequence of extensional tectonics. The chain is formed by a tectonic wedge (12-15 km thick. It includes basinal Meso-Cenozoic carbonate units overthrusting carbonate platform rock units (Catalano et al., 2000). Presently, main culmination (e.g. Monte Solunto) and a number of tectonic depressions (e.g. Cefalù basin), filled by >1000 m thick Plio-Pleistocene sedimentary wedge, are observed along the investigated tran- sect. Seismic attributes and reflector pattern depicts a complex crustal structure. Be- tween the coast and the M. Solunto high, a transparent to diffractive band (assigned to the upper crust) is recognised above low frequency reflective layers (occurring be- tween 9 and 11 s/TWT) that dips towards the North. Their bottom can be correlated to the seismological (African?) Moho discontinuity which is (26 km deep in the Sicilian shelf (Scarascia et al., 1994). Beneath the Monte Solunto ridge, strongly deformed re- flectors occurring between 8 to 9.5 s/TWT (European lower crust?) overly the African (?) lower crust. The resulting geometry suggests underplating of the African crust respect to the European crust (?). The already deformed crustal edifice is dissected by a number of N-dipping normal faults that open extensional basins and are associ- ated with crustal thinning. The Plio-Pleistocene fill of the Cefalù basin can be subdi- vided into three subunits by

DEEP SPITZER OBSERVATIONS OF INFRARED-FAINT RADIO SOURCES: HIGH-REDSHIFT RADIO-LOUD ACTIVE GALACTIC NUCLEI?

International Nuclear Information System (INIS)

Norris, Ray P.; Mao, Minnie; Afonso, Jose; Cava, Antonio; Farrah, Duncan; Oliver, Seb; Huynh, Minh T.; Mauduit, Jean-Christophe; Surace, Jason; Ivison, R. J.; Jarvis, Matt; Lacy, Mark; Maraston, Claudia; Middelberg, Enno; Seymour, Nick

2011-01-01

Infrared-faint radio sources (IFRSs) are a rare class of objects which are relatively bright at radio wavelengths but very faint at infrared and optical wavelengths. Here we present sensitive near-infrared observations of a sample of these sources taken as part of the Spitzer Extragalactic Representative Volume Survey. Nearly all the IFRSs are undetected at a level of ∼1 μJy in these new deep observations, and even the detections are consistent with confusion with unrelated galaxies. A stacked image implies that the median flux density is S 3.6μm ∼ 0.2 μJy or less, giving extreme values of the radio-infrared flux density ratio. Comparison of these objects with known classes of object suggests that the majority are probably high-redshift radio-loud galaxies, possibly suffering from significant dust extinction.

Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Fan Hu

2015-11-01

Full Text Available Learning efficient image representations is at the core of the scene classification task of remote sensing imagery. The existing methods for solving the scene classification task, based on either feature coding approaches with low-level hand-engineered features or unsupervised feature learning, can only generate mid-level image features with limited representative ability, which essentially prevents them from achieving better performance. Recently, the deep convolutional neural networks (CNNs, which are hierarchical architectures trained on large-scale datasets, have shown astounding performance in object recognition and detection. However, it is still not clear how to use these deep convolutional neural networks for high-resolution remote sensing (HRRS scene classification. In this paper, we investigate how to transfer features from these successfully pre-trained CNNs for HRRS scene classification. We propose two scenarios for generating image features via extracting CNN features from different layers. In the first scenario, the activation vectors extracted from fully-connected layers are regarded as the final image features; in the second scenario, we extract dense features from the last convolutional layer at multiple scales and then encode the dense features into global image features through commonly used feature coding approaches. Extensive experiments on two public scene classification datasets demonstrate that the image features obtained by the two proposed scenarios, even with a simple linear classifier, can result in remarkable performance and improve the state-of-the-art by a significant margin. The results reveal that the features from pre-trained CNNs generalize well to HRRS datasets and are more expressive than the low- and mid-level features. Moreover, we tentatively combine features extracted from different CNN models for better performance.

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

Science.gov (United States)

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

2017-10-01

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

Study of microorganisms present in deep geologic formations

International Nuclear Information System (INIS)

Camus, H.; Lion, R.; Bianchi, A.; Garcin, J.

1987-01-01

This work has been executed in the scope of the studies on high activity radioactive wastes storage in deep geological environments. The authors make reference to an as complete as possible literature on the existence of microorganisms in those environments or under similar conditions. Then they describe the equipment and methods they have implemented to perform their study of the populations present in three deep-reaching drill-holes in Auriat (France), Mol (Belgique) and Troon (Great Britain). The results of the study exhibit the presence of a certain biological activity, well adapted to that particular life environment. Strains appear to be very varied from the taxonomic point of view and seemingly show an important potential of mineral alteration when provided with an adequate source of energy. Complementary studies, using advanced techniques such as those employed during the work forming the basis of this paper, seem necessary for a more accurate evaluation of long-term risks of perturbation of a deep storage site [fr

Highlights of electron-proton deep inelastic scattering at HERA

International Nuclear Information System (INIS)

Feltesse, J.

1996-02-01

Salient results on deep inelastic scattering from the H1 and ZEUS collaborations are reviewed. These include preliminary measurements of the proton structure function F 2 extending to new regimes at both high Q 2 and low Q 2 and x, studies of the hadronic final states and discussion on QCD interpretations of low x data. New determination of α s from jet rates in deep inelastic scattering based on 1994 data are presented. A consistent picture of the gluon density in the proton at low x from a variety of processes is obtained. (author)

Deep Learning and its Applications in the Natural Sciences

CERN Multimedia

CERN. Geneva

2015-01-01

Starting from a brief historical perspective on scientific discovery, this talk will review some of the theory and open problems of deep learning and describe how to design efficient feedforward and recursive deep learning architectures for applications in the natural sciences. In particular, the focus will be on multiple particle problems at different scales: in biology (e.g. prediction of protein structures), chemistry (e.g. prediction of molecular properties and reactions), and high-energy physics (e.g. detection of exotic particles, jet substructure and tagging, "dark matter and dark knowledge")

Acoustic emission localization on ship hull structures using a deep learning approach

DEFF Research Database (Denmark)

Georgoulas, George; Kappatos, Vassilios; Nikolakopoulos, George

2016-01-01

In this paper, deep belief networks were used for localization of acoustic emission events on ship hull structures. In order to avoid complex and time consuming implementations, the proposed approach uses a simple feature extraction module, which significantly reduces the extremely high dimension......In this paper, deep belief networks were used for localization of acoustic emission events on ship hull structures. In order to avoid complex and time consuming implementations, the proposed approach uses a simple feature extraction module, which significantly reduces the extremely high...

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

Coaxial nuclear radiation detector with deep junction and radial field gradient

International Nuclear Information System (INIS)

Hall, R.N.

1979-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

Complete genome sequence of the highly Mn(II) tolerant Staphylococcus sp. AntiMn-1 isolated from deep-sea sediment in the Clarion-Clipperton Zone.

Science.gov (United States)

Wang, Xing; Lin, Danqiu; Jing, Xiaohuan; Zhu, Sidong; Yang, Jifang; Chen, Jigang

2018-01-20

Staphylococcus sp. AntiMn-1 is a deep-sea bacterium inhabiting seafloor sediment in the Clarion-Clipperton Zone (CCZ) that is highly tolerant to Mn(II) and displays efficient Mn(II) oxidation. Herein, we present the assembly and annotation of its genome. Copyright © 2017 Elsevier B.V. All rights reserved.

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.