Carboxydotrophic growth of Geobacter sulfurreducens

NARCIS (Netherlands)

Geelhoed, J.S.; Henstra, A.M.; Stams, A.J.M.

2016-01-01

This study shows that Geobacter sulfurreducens grows on carbon monoxide (CO) as electron donor with fumarate as electron acceptor. Geobacter sulfurreducens was tolerant to high CO levels, with up to 150 kPa in the headspace tested. During growth, hydrogen was detected in very slight amounts (∼5

Proteogenomic monitoring of Geobacter physiology during stimulated uranium bioremediation

Energy Technology Data Exchange (ETDEWEB)

Wilkins, M.J.; VerBerkmoes, N.C.; Williams, K.H.; Callister, S.J.; Mouser, P.J.; Elifantz, H.; N' Guessan, A.L.; Thomas, B.C.; Nicora, C.D.; Shah, M.B.; Lipton, M.S.; Lovley, D.R.; Hettich, R.L.; Long, P.E.; Banfield, J.F.; Abraham, P.

2009-08-01

Implementation of uranium bioremediation requires methods for monitoring the membership and activities of the subsurface microbial communities that are responsible for reduction of soluble U(VI) to insoluble U(IV). Here, we report a proteomics-based approach for simultaneously documenting the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, aquifer. Three planktonic Geobacter-dominated samples were obtained from two wells down-gradient of acetate addition. Over 2,500 proteins from each of these samples were identified by matching liquid chromatography-tandem mass spectrometry spectra to peptides predicted from seven isolate Geobacter genomes. Genome-specific peptides indicate early proliferation of multiple M21 and Geobacter bemidjiensis-like strains and later possible emergence of M21 and G. bemidjiensis-like strains more closely related to Geobacter lovleyi. Throughout biostimulation, the proteome is dominated by enzymes that convert acetate to acetyl-coenzyme A and pyruvate for central metabolism, while abundant peptides matching tricarboxylic acid cycle proteins and ATP synthase subunits were also detected, indicating the importance of energy generation during the period of rapid growth following the start of biostimulation. Evolving Geobacter strain composition may be linked to changes in protein abundance over the course of biostimulation and may reflect changes in metabolic functioning. Thus, metagenomics-independent community proteogenomics can be used to diagnose the status of the subsurface consortia upon which remediation biotechnology relies.

Electron shuttle-mediated biotransformation of hexahydro-1,3,5-trinitro-1,3,5-triazine adsorbed to granular activated carbon.

Science.gov (United States)

Millerick, Kayleigh; Drew, Scott R; Finneran, Kevin T

2013-08-06

Granular activated carbon (GAC) effectively removes hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) from groundwater but generates RDX-laden GAC that must be disposed of or regenerated. Batch reactors containing GAC to which RDX was preadsorbed were used in experiments to test the potential for adsorbed RDX reduction and daughter product formation using (i) chemically reduced anthrahydroquinone-2,6-disulfonate (AH2QDS), (ii) resting Geobacter metallireducens strain GS-15, and (iii) a combined system containing AQDS and GS-15. Approximately 97.0% of the adsorbed RDX was transformed in each of these experimental systems by 90 h. Chemically reduced AQDS (AH2QDS) transformed 99.2% of adsorbed RDX; formaldehyde was produced rapidly and was stoichiometric (3 mol HCHO per mol RDX). Geobacter metallireducens also reduced RDX with and without AQDS present. This is the first study to demonstrate biological transformation of RDX adsorbed to GAC. Formaldehyde increased and then decreased in biological systems, suggesting a previously unreported capacity for G. metallireducens to oxidize formaldehyde, which was confirmed with resting cell suspensions. These data suggest the masses of GAC waste currently produced by activated carbon at RDX remediation sites can be minimized, decreasing the carbon footprint of the treatment technology. Alternatively, this strategy may be used to develop a Bio-GAC system for ex situ RDX treatment.

Identification of geobacter populations in the uranium mill tailings Shiprock

International Nuclear Information System (INIS)

Radeva, G.; Selenska-Pobell, S.

2006-01-01

Geobacter - specific primers were used for construction of a 16S rDNA library for a water sample collected from uranium mill tailings near Shiprock (Sh853) in the USA . Most of the retrieved sequences were affiliated with different Geobacter species, however sequences related to other δ -Proteobacteria were identified as well. (authors)

Geobacter anodireducens sp. nov., an exoelectrogenic microbe in bioelectrochemical systems

KAUST Repository

Sun, D.

2014-07-22

© 2014 IUMS. A previously isolated exoelectrogenic bacterium, strain SD-1(T), was further characterized and identified as a representative of a novel species of the genus Geobacter. Strain SD-1(T) was Gram-negative, aerotolerant, anaerobic, non-spore-forming, non-fermentative and non-motile. Cells were short, curved rods (0.8-1.3 µm long and 0.3 µm in diameter). Growth of strain SD-1(T) was observed at 15-42 °C and pH 6.0-8.5, with optimal growth at 30-35 °C and pH 7. Analysis of 16S rRNA gene sequences indicated that the isolate was a member of the genus Geobacter, with the closest known relative being Geobacter sulfurreducens PCA(T) (98% similarity). Similar to other members of the genus Geobacter, strain SD-1(T) used soluble or insoluble Fe(III) as the sole electron acceptor coupled with the oxidation of acetate. However, SD-1(T) could not reduce fumarate as an electron acceptor with acetate oxidization, which is an important physiological trait for G. sulfurreducens. Moreover, SD-1(T) could grow in media containing as much as 3% NaCl, while G. sulfurreducens PCA(T) can tolerate just half this concentration, and this difference in salt tolerance was even more obvious when cultivated in bioelectrochemical systems. DNA-DNA hybridization analysis of strain SD-1(T) and its closest relative, G. sulfurreducens ATCC 51573(T), showed a relatedness of 61.6%. The DNA G+C content of strain SD-1(T) was 58.9 mol%. Thus, on the basis of these characteristics, strain SD-1(T) was not assigned to G. sulfurreducens, and was instead classified in the genus Geobacter as a representative of a novel species. The name Geobacter anodireducens sp. nov. is proposed, with the type strain SD-1(T) ( = CGMCC 1.12536(T) = KCTC 4672(T)).

Integrative analysis of Geobacter spp. and sulfate-reducing bacteria during uranium bioremediation

Directory of Open Access Journals (Sweden)

D. Lovley

2012-03-01

Full Text Available Enhancing microbial U(VI reduction with the addition of organic electron donors is a promising strategy for immobilizing uranium in contaminated groundwaters, but has yet to be optimized because of a poor understanding of the factors controlling the growth of various microbial communities during bioremediation. In previous field trials in which acetate was added to the subsurface, there were two distinct phases: an initial phase in which acetate-oxidizing, U(VI-reducing Geobacter predominated and U(VI was effectively reduced and a second phase in which acetate-oxidizing sulfate reducing bacteria (SRB predominated and U(VI reduction was poor. The interaction of Geobacter and SRB was investigated both in sediment incubations that mimicked in situ bioremediation and with in silico metabolic modeling. In sediment incubations, Geobacter grew quickly but then declined in numbers as the microbially reducible Fe(III was depleted whereas the SRB grow more slowly and reached dominance after 30–40 days. Modeling predicted a similar outcome. Additional modeling in which the relative initial percentages of the Geobacter and SRB were varied indicated that there was little to no competitive interaction between Geobacter and SRB when acetate was abundant. Further simulations suggested that the addition of Fe(III would revive the Geobacter, but have little to no effect on the SRB. This result was confirmed experimentally. The results demonstrate that it is possible to predict the impact of amendments on important components of the subsurface microbial community during groundwater bioremediation. The finding that Fe(III availability, rather than competition with SRB, is the key factor limiting the activity of Geobacter during in situ uranium bioremediation will aid in the design of improved uranium bioremediation strategies.

Conductive particles enable syntrophic acetate oxidation between Geobacter and Methanosarcina from coastal sediments

DEFF Research Database (Denmark)

Rotaru, Amelia-Elena; Calabrese, Federica; Stryhanyuk, Hryhoriy

2017-01-01

pressure and their survival depends on successful partnership. Here we demonstrate that conductive minerals facilitate a SAO partnership between Geobacter and Methanosarcina from the coastal sediments of the Bothnian Bay, Baltic Sea. Bothnian methanogenic sediments showed a high apparent isotopic...... fractionation (αc 1.07) characteristic of CO2-reductive methanogenesis. The native community was represented by electrogens such as Geobacter and methanogens like Methanosarcina. Upon the addition of conductive particles (activated carbon and magnetite), methanogenesis from acetate increased fourfold. Geobacter...... (96% related to G. psychrophilus) and Methanosarcina (99% related to M. subterranea) dominated the conductive particle-spiked SAO communities. Using NanoSIMS we demonstrated that during SAO, Geobacter incorporated 82% of the labeled acetate as compared to only 18% by Methanosarcina. At the same time...

Enrichment of Geobacter species in response to stimulation of Fe(III) reduction in sandy aquifer sediments

Science.gov (United States)

Snoeyenbos-West, O.L.; Nevin, K.P.; Anderson, R.T.; Lovely, D.R.

2000-01-01

Engineered stimulation of Fe(III) has been proposed as a strategy to enhance the immobilization of radioactive and toxic metals in metal-contaminated subsurface environments. Therefore, laboratory and field studies were conducted to determine which microbial populations would respond to stimulation of Fe(III) reduction in the sediments of sandy aquifers. In laboratory studies, the addition of either various organic electron donors or electron shuttle compounds stimulated Fe(III) reduction and resulted in Geobacter sequences becoming important constituents of the Bacterial 16S rDNA sequences that could be detected with PCR amplification and denaturing gradient gel electrophoresis (DGGE). Quantification of Geobacteraceae sequences with a PCR most-probable-number technique indicated that the extent to which numbers of Geobacter increased was related to the degree of stimulation of Fe(III) reduction. Geothrix species were also enriched in some instances, but were orders of magnitude less numerous than Geobacter species. Shewanella species were not detected, even when organic compounds known to be electron donors for Shewanella species were used to stimulate Fe(III) reduction in the sediments. Geobacter species were also enriched in two field experiments in which Fe(III) reduction was stimulated with the addition of benzoate or aromatic hydrocarbons. The apparent growth of Geobacter species concurrent with increased Fe(III) reduction suggests that Geobacter species were responsible for much of the Fe(III) reduction in all of the stimulation approaches evaluated in three geographically distinct aquifers. Therefore, strategies for subsurface remediation that involve enhancing the activity of indigenous Fe(III)-reducing populations in aquifers should consider the physiological properties of Geobacter species in their treatment design.

Syntrophic Growth via Quinone-Mediated Interspecies Electron Transfer

Directory of Open Access Journals (Sweden)

Jessica A Smith

2015-02-01

Full Text Available The mechanisms by which microbial species exchange electrons are of interest because interspecies electron transfer can expand the metabolic capabilities of microbial communities. Previous studies with the humic substance analog anthraquinone-2,6-disulfonate (AQDS suggested that quinone-mediated interspecies electron transfer (QUIET is feasible, but it was not determined if sufficient energy is available from QUIET to support the growth of both species. Furthermore, there have been no previous studies on the mechanisms for the oxidation of anthrahydroquinone-2,6-disulfonate (AHQDS. A co-culture of Geobacter metallireducens and Geobacter sulfurreducens metabolized ethanol with the reduction of fumarate much faster in the presence of AQDS, and there was an increase in cell protein. G. sulfurreducens was more abundant, consistent with G. sulfurreducens obtaining electrons from acetate that G. metallireducens produced from ethanol, as well as from AHQDS. Cocultures initiated with a citrate synthase-deficient strain of G. sulfurreducens that was unable to use acetate as an electron donor also metabolized ethanol with the reduction of fumarate and cell growth, but acetate accumulated over time. G. sulfurreducens and G. metallireducens were equally abundant in these co-cultures reflecting the inability of the citrate synthase-deficient strain of G. sulfurreducens to metabolize acetate. Evaluation of the mechanisms by which G. sulfurreducens accepts electrons from AHQDS demonstrated that a strain deficient in outer-surface c-type cytochromes that are required for AQDS reduction was as effective at QUIET as the wild-type strain. Deletion of additional genes previously implicated in extracellular electron transfer also had no impact on QUIET. These results demonstrate that QUIET can yield sufficient energy to support the growth of both syntrophic partners, but that the mechanisms by which electrons are derived from extracellular hydroquinones require

Maintenance of Geobacter-dominated biofilms in microbial fuel cells treating synthetic wastewater.

Science.gov (United States)

Commault, Audrey S; Lear, Gavin; Weld, Richard J

2015-12-01

Geobacter-dominated biofilms can be selected under stringent conditions that limit the growth of competing bacteria. However, in many practical applications, such stringent conditions cannot be maintained and the efficacy and stability of these artificial biofilms may be challenged. In this work, biofilms were selected on low-potential anodes (-0.36 V vs Ag/AgCl, i.e. -0.08 V vs SHE) in minimal acetate or ethanol media. Selection conditions were then relaxed by transferring the biofilms to synthetic wastewater supplemented with soil as a source of competing bacteria. We tracked community succession and functional changes in these biofilms. The Geobacter-dominated biofilms showed stability in their community composition and electrochemical properties, with Geobacter sp. being still electrically active after six weeks in synthetic wastewater with power densities of 100±19 mW·m(-2) (against 74±14 mW·m(-2) at week 0) for all treatments. After six weeks, the ethanol-selected biofilms, despite their high taxon richness and their efficiency at removing the chemical oxygen demand (0.8 g·L(-1) removed against the initial 1.3 g·L(-1) injected), were the least stable in terms of community structure. These findings have important implications for environmental microbial fuel cells based on Geobacter-dominated biofilms and suggest that they could be stable in challenging environments. Copyright © 2015 Elsevier B.V. All rights reserved.

Enhanced Uranium Immobilization and Reduction by Geobacter sulfurreducens Biofilms

Science.gov (United States)

Cologgi, Dena L.; Speers, Allison M.; Bullard, Blair A.; Kelly, Shelly D.

2014-01-01

Biofilms formed by dissimilatory metal reducers are of interest to develop permeable biobarriers for the immobilization of soluble contaminants such as uranium. Here we show that biofilms of the model uranium-reducing bacterium Geobacter sulfurreducens immobilized substantially more U(VI) than planktonic cells and did so for longer periods of time, reductively precipitating it to a mononuclear U(IV) phase involving carbon ligands. The biofilms also tolerated high and otherwise toxic concentrations (up to 5 mM) of uranium, consistent with a respiratory strategy that also protected the cells from uranium toxicity. The enhanced ability of the biofilms to immobilize uranium correlated only partially with the biofilm biomass and thickness and depended greatly on the area of the biofilm exposed to the soluble contaminant. In contrast, uranium reduction depended on the expression of Geobacter conductive pili and, to a lesser extent, on the presence of the c cytochrome OmcZ in the biofilm matrix. The results support a model in which the electroactive biofilm matrix immobilizes and reduces the uranium in the top stratum. This mechanism prevents the permeation and mineralization of uranium in the cell envelope, thereby preserving essential cellular functions and enhancing the catalytic capacity of Geobacter cells to reduce uranium. Hence, the biofilms provide cells with a physically and chemically protected environment for the sustained immobilization and reduction of uranium that is of interest for the development of improved strategies for the in situ bioremediation of environments impacted by uranium contamination. PMID:25128347

Promoting Interspecies Electron Transfer with Biochar

Science.gov (United States)

Chen, Shanshan; Rotaru, Amelia-Elena; Shrestha, Pravin Malla; Malvankar, Nikhil S.; Liu, Fanghua; Fan, Wei; Nevin, Kelly P.; Lovley, Derek R.

2014-01-01

Biochar, a charcoal-like product of the incomplete combustion of organic materials, is an increasingly popular soil amendment designed to improve soil fertility. We investigated the possibility that biochar could promote direct interspecies electron transfer (DIET) in a manner similar to that previously reported for granular activated carbon (GAC). Although the biochars investigated were 1000 times less conductive than GAC, they stimulated DIET in co-cultures of Geobacter metallireducens with Geobacter sulfurreducens or Methanosarcina barkeri in which ethanol was the electron donor. Cells were attached to the biochar, yet not in close contact, suggesting that electrons were likely conducted through the biochar, rather than biological electrical connections. The finding that biochar can stimulate DIET may be an important consideration when amending soils with biochar and can help explain why biochar may enhance methane production from organic wastes under anaerobic conditions. PMID:24846283

Charge transport in films of Geobacter sulfurreducens on graphite electrodes as a function of film thickness

KAUST Repository

Jana, Partha Sarathi; Katuri, Krishna; Kavanagh, Paul; Kumar, Amit Ravi Pradeep; Leech, Dó nal

2014-01-01

Harnessing, and understanding the mechanisms of growth and activity of, biofilms of electroactive bacteria (EAB) on solid electrodes is of increasing interest, for application to microbial fuel and electrolysis cells. Microbial electrochemical cell technology can be used to generate electricity, or higher value chemicals, from organic waste. The capability of biofilms of electroactive bacteria to transfer electrons to solid anodes is a key feature of this emerging technology, yet the electron transfer mechanism is not fully characterized as yet. Acetate oxidation current generated from biofilms of an EAB, Geobacter sulfurreducens, on graphite electrodes as a function of time does not correlate with film thickness. Values of film thickness, and the number and local concentration of electrically connected redox sites within Geobacter sulfurreducens biofilms as well as a charge transport diffusion co-efficient for the biofilm can be estimated from non-turnover voltammetry. The thicker biofilms, of 50 ± 9 μm, display higher charge transport diffusion co-efficient than that in thinner films, as increased film porosity of these films improves ion transport, required to maintain electro-neutrality upon electrolysis. This journal is © the Partner Organisations 2014.

Use of a Coculture To Enable Current Production by Geobacter sulfurreducens

KAUST Repository

Qu, Y.; Feng, Y.; Wang, X.; Logan, B. E.

2012-01-01

Microbial fuel cells often produce more electrical power with mixed cultures than with pure cultures. Here, we show that a coculture of a nonexoelectrogen (Escherichia coli) and Geobacter sulfurreducens improved system performance relative

Electricity-Assisted Biological Hydrogen Production from Acetate by Geobacter sulfurreducens

NARCIS (Netherlands)

Geelhoed, J.S.; Stams, A.J.M.

2011-01-01

Geobacter sulfurreducens is a well-known current-producing microorganism in microbial fuel cells, and is able to use acetate and hydrogen as electron donor. We studied the functionality of G. sulfurreducens as biocatalyst for hydrogen formation at the cathode of a microbial electrolysis cell (MEC).

The Complex Conductivity Signature of Geobacter Species in Geological Media

Science.gov (United States)

Brown, I.; Atekwana, E. A.; Sarkisova, S.; Achang, M.

2013-12-01

The Complex Conductivity (CC) technique is a promising biogeophysical approach for sensing microbially-induced changes in geological media because of its low-invasive character and sufficient sensitivity to enhanced microbial activity in the near subsurface. Geobacter species have been shown to play important roles in the bioremediation of groundwater contaminated with petroleum and landfill leachate. This capability is based on the ability of Geobacter species to reduce Fe(III) by transferring of electrons from the reduced equivalents to Fe(III) rich minerals through respiration chain and special metallic-like conductors - pili. Only the cultivation of Geobacter species on Fe(III) oxides specifically express pili biosynthesis. Moreover, mutants that cannot produce pili are unable to reduce Fe(III) oxides. However, little is known about the contribution of these molecular conductors (nanowires) to the generation of complex conductivity signatures in geological media. Here, we present the results about the modulation of CC signatures in geological media by Geobacter sulfurreducens (G.s.). Cultures of wild strain G.s. and its pilA(-) mutant were anaerobically cultivated in the presence of the pair of such donors and acceptors of electrons: acetate - fumarate, and acetate - magnetite under anaerobic conditions. Each culture was injected in CC sample holders filled either with N2-CO2 mix (planktonic variant) or with this gases mix and glass beads, d=1 mm, (porous medium variant). Both strains of G.s. proliferated well in a medium supplemented with acetate-fumarate. However, pilA(-) mutant did not multiply in a medium supplemented with ox-red pair yeast extract - magnetite. This observation confirmed that only wild pilA(+) strain is capable of the dissimilatory reduction of Fe(III) within magnetite molecule. The measurement of CC responses from planktonic culture of G.s. wild strain grown with acetate-fumarate did not show linear correlation with their magnitudes but

Geobacter daltonii sp. nov., an Fe(III)- and uranium(VI)-reducing bacterium isolated from a shallow subsurface exposed to mixed heavy metal and hydrocarbon contamination.

Science.gov (United States)

Prakash, Om; Gihring, Thomas M; Dalton, Dava D; Chin, Kuk-Jeong; Green, Stefan J; Akob, Denise M; Wanger, Greg; Kostka, Joel E

2010-03-01

An Fe(III)- and uranium(VI)-reducing bacterium, designated strain FRC-32(T), was isolated from a contaminated subsurface of the USA Department of Energy Oak Ridge Field Research Center (ORFRC) in Oak Ridge, Tennessee, where the sediments are exposed to mixed waste contamination of radionuclides and hydrocarbons. Analyses of both 16S rRNA gene and the Geobacteraceae-specific citrate synthase (gltA) mRNA gene sequences retrieved from ORFRC sediments indicated that this strain was abundant and active in ORFRC subsurface sediments undergoing uranium(VI) bioremediation. The organism belonged to the subsurface clade of the genus Geobacter and shared 92-98 % 16S rRNA gene and 75-81 % rpoB gene sequence similarities with other recognized species of the genus. In comparison to its closest relative, Geobacter uraniireducens Rf4(T), according to 16S rRNA gene sequence similarity, strain FRC-32(T) showed a DNA-DNA relatedness value of 21 %. Cells of strain FRC-32(T) were Gram-negative, non-spore-forming, curved rods, 1.0-1.5 microm long and 0.3-0.5 microm in diameter; the cells formed pink colonies in a semisolid cultivation medium, a characteristic feature of the genus Geobacter. The isolate was an obligate anaerobe, had temperature and pH optima for growth at 30 degrees C and pH 6.7-7.3, respectively, and could tolerate up to 0.7 % NaCl although growth was better in the absence of NaCl. Similar to other members of the Geobacter group, strain FRC-32(T) conserved energy for growth from the respiration of Fe(III)-oxyhydroxide coupled with the oxidation of acetate. Strain FRC-32(T) was metabolically versatile and, unlike its closest relative, G. uraniireducens, was capable of utilizing formate, butyrate and butanol as electron donors and soluble ferric iron (as ferric citrate) and elemental sulfur as electron acceptors. Growth on aromatic compounds including benzoate and toluene was predicted from preliminary genomic analyses and was confirmed through successive transfer with

Conjugated oligoelectrolyte represses hydrogen oxidation by Geobacter sulfurreducens in microbial electrolysis cells

KAUST Repository

Liu, Jia; Hou, Huijie; Chen, Xiaofen; Bazan, Guillermo C.; Kashima, Hiroyuki; Logan, Bruce

2015-01-01

© 2015 Elsevier B.V. A conjugated oligoelectrolyte (COE), which spontaneously aligns within cell membranes, was shown to completely inhibit H2 uptake by Geobacter sulfurreducens in microbial electrolysis cells. Coulombic efficiencies that were 490

Anode microbial communities produced by changing from microbial fuel cell to microbial electrolysis cell operation using two different wastewaters

KAUST Repository

Kiely, Patrick D.; Cusick, Roland; Call, Douglas F.; Selembo, Priscilla A.; Regan, John M.; Logan, Bruce E.

2011-01-01

Conditions in microbial fuel cells (MFCs) differ from those in microbial electrolysis cells (MECs) due to the intrusion of oxygen through the cathode and the release of H2 gas into solution. Based on 16S rRNA gene clone libraries, anode communities in reactors fed acetic acid decreased in species richness and diversity, and increased in numbers of Geobacter sulfurreducens, when reactors were shifted from MFCs to MECs. With a complex source of organic matter (potato wastewater), the proportion of Geobacteraceae remained constant when MFCs were converted into MECs, but the percentage of clones belonging to G. sulfurreducens decreased and the percentage of G. metallireducens clones increased. A dairy manure wastewater-fed MFC produced little power, and had more diverse microbial communities, but did not generate current in an MEC. These results show changes in Geobacter species in response to the MEC environment and that higher species diversity is not correlated with current. © 2010 Elsevier Ltd.

Development of a biomarker for Geobacter activity and strain composition: Proteogenomic analysis of the citrate synthase protein during bioremediation of U(VI)

Energy Technology Data Exchange (ETDEWEB)

Wilkins, M.J.; Callister, S.J.; Miletto, M.; Williams, K.H.; Nicora, C.D.; Lovley, D.R.; Long, P.E.; Lipton, M.S.

2010-02-15

Monitoring the activity of target microorganisms during stimulated bioremediation is a key problem for the development of effective remediation strategies. At the US Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, CO, the stimulation of Geobacter growth and activity via subsurface acetate addition leads to precipitation of U(VI) from groundwater as U(IV). Citrate synthase (gltA) is a key enzyme in Geobacter central metabolism that controls flux into the TCA cycle. Here, we utilize shotgun proteomic methods to demonstrate that the measurement of gltA peptides can be used to track Geobacter activity and strain evolution during in situ biostimulation. Abundances of conserved gltA peptides tracked Fe(III) reduction and changes in U(VI) concentrations during biostimulation, whereas changing patterns of unique peptide abundances between samples suggested sample-specific strain shifts within the Geobacter population. Abundances of unique peptides indicated potential differences at the strain level between Fe(III)-reducing populations stimulated during in situ biostimulation experiments conducted a year apart at the Rifle IFRC. These results offer a novel technique for the rapid screening of large numbers of proteomic samples for Geobacter species and will aid monitoring of subsurface bioremediation efforts that rely on metal reduction for desired outcomes.

Use of a Coculture To Enable Current Production by Geobacter sulfurreducens

KAUST Repository

Qu, Y.

2012-02-17

Microbial fuel cells often produce more electrical power with mixed cultures than with pure cultures. Here, we show that a coculture of a nonexoelectrogen (Escherichia coli) and Geobacter sulfurreducens improved system performance relative to that of a pure culture of the exoelectrogen due to the consumption of oxygen leaking into the reactor.

Flux analysis of central metabolic pathways in Geobactermetallireducens during reduction of solubleFe(III)-NTA

Energy Technology Data Exchange (ETDEWEB)

Tang, Yinjie J.; Chakraborty, Romy; Garcia-Martin, Hector; Chu,Jeannie; Hazen, Terry C.; Keasling, Jay D.

2007-01-01

We analyzed the carbon fluxes in the central metabolism ofGeobacter metallireducens strain GS-15 using 13C isotopomer modeling.Acetate labeled in the 1st or 2nd position was the sole carbon source,and Fe-NTA was the sole terminal electron acceptor. The measured labeledacetate uptake rate was 21 mmol/gdw/h in the exponential growth phase.The resulting isotope labeling pattern of amino acids allowed an accuratedetermination of the in vivo global metabolic reaction rates (fluxes)through the central metabolic pathways using a computational isotopomermodel. The tracer experiments showed that G. metallireducens containedcomplete biosynthesis pathways for essential metabolism, and this strainmight also have an unusual isoleucine biosynthesis route (usingacetyl-CoA and pyruvate as the precursors). The model indicated that over90 percent of the acetate was completely oxidized to CO2 via a completetricarboxylic acid (TCA) cycle while reducing iron. Pyruvate carboxylaseand phosphoenolpyruvate carboxykinase were present under theseconditions, but enzymes in the glyoxylate shunt and malic enzyme wereabsent. Gluconeogenesis and the pentose phosphate pathway were mainlyemployed for biosynthesis and accounted for less than 3 percent of totalcarbon consumption. The model also indicated surprisingly highreversibility in the reaction between oxoglutarate and succinate. Thisstep operates close to the thermodynamic equilibrium possibly becausesuccinate is synthesized via a transferase reaction, and the conversionof oxoglutarate to succinate is a rate limiting step for carbonmetabolism. These findings enable a better understanding of therelationship between genome annotation and extant metabolic pathways inG. metallireducens.

Set potential regulation reveals additional oxidation peaks of Geobacter sulfurreducens anodic biofilms

KAUST Repository

Zhu, Xiuping

2012-08-01

Higher current densities produced in microbial fuel cells and other bioelectrochemical systems are associated with the presence of various Geobacter species. A number of electron transfer components are involved in extracellular electron transfer by the model exoelectrogen, Geobacter sulfurreducens. It has previously been shown that 5 main oxidation peaks can be identified in cyclic voltammetry scans. It is shown here that 7 separate oxidation peaks emerged over relatively long periods of time when a larger range of set potentials was used to acclimate electroactive biofilms. The potentials of oxidation peaks obtained with G. sulfurreducens biofilms acclimated at 0.60 V (vs. Ag/AgCl) were different from those that developed at - 0.46 V, and both of their peaks were different from those obtained for biofilms incubated at - 0.30 V, 0 V, and 0.30 V. These results expand the known range of potentials for which G. sulfurreducens produces identifiable oxidation peaks that could be important for extracellular electron transfer. © 2012 Elsevier B.V.

High Biofilm Conductivity Maintained Despite Anode Potential Changes in a Geobacter-Enriched Biofilm

Science.gov (United States)

This study systematically assessed intracellular electron transfer (IET) and extracellular electron transfer (EET) kinetics with respect to anode potential (Eanode) in a mixed-culture biofilm anode enriched with Geobacter spp. High biofilm conductivity (0.96–1.24 mScm^-1) was mai...

Electron Transfer Strategies Regulate Carbonate Mineral and Micropore Formation

Science.gov (United States)

Zeng, Zhirui; Tice, Michael M.

2018-01-01

Some microbial carbonates are robust biosignatures due to their distinct morphologies and compositions. However, whether carbonates induced by microbial iron reduction have such features is unknown. Iron-reducing bacteria use various strategies to transfer electrons to iron oxide minerals (e.g., membrane-bound enzymes, soluble electron shuttles, nanowires, as well as different mechanisms for moving over or attaching to mineral surfaces). This diversity has the potential to create mineral biosignatures through manipulating the microenvironments in which carbonate precipitation occurs. We used Shewanella oneidensis MR-1, Geothrix fermentans, and Geobacter metallireducens GS-15, representing three different strategies, to reduce solid ferric hydroxide in order to evaluate their influence on carbonate and micropore formation (micro-size porosity in mineral rocks). Our results indicate that electron transfer strategies determined the morphology (rhombohedral, spherical, or long-chained) of precipitated calcium-rich siderite by controlling the level of carbonate saturation and the location of carbonate formation. Remarkably, electron transfer strategies also produced distinctive cell-shaped micropores in both carbonate and hydroxide minerals, thus producing suites of features that could potentially serve as biosignatures recording information about the sizes, shapes, and physiologies of iron-reducing organisms.

Production of gold nanoparticles by electrode-respiring Geobacter sulfurreducens biofilms

Energy Technology Data Exchange (ETDEWEB)

Tanzil, Abid H.; Sultana, Sujala T.; Saunders, Steven R.; Dohnalkova, Alice C.; Shi, Liang; Davenport, Emily; Ha, Phuc; Beyenal, Haluk

2016-12-01

Current chemical syntheses of nanoparticles (NP) has had limited success due to the relatively high environmental cost caused by the use of harsh chemicals requiring necessary purification and size-selective fractionation. Therefore, biological approaches have received recent attention for their potential to overcome these obstacles as a benign synthetic approach. The intrinsic nature of biomolecules present in microorganisms has intrigued researchers to design bottom-up approaches to biosynthesize metal nanoparticles using microorganisms. Most of the literature work has focused on NP synthesis using planktonic cells while the use of biofilms are limited. The goal of this work was to synthesize gold nanoparticles (AuNPs) using electrode respiring Geobacter sulfurreducens biofilms. We found that most of the AuNPs are generated in the extracellular matrix of Geobacter biofilms with an average particle size of 20 nm. The formation of AuNPs was verified using TEM, FTIR and EDX. We also found that the extracellular substances extracted from electrode respiring G. sulfurreducens biofilms can reduce Au3+ to AuNPs. It appears that reducing sugars were involved in bioreduction and synthesis of AuNPs and amine groups acted as the major biomolecules involved in binding. This is first demonstration of AuNPs formation from the extracellular matrix of electrode respiring biofilms.

Impact of natural organic matter coatings on the microbial reduction of iron oxides

Science.gov (United States)

Poggenburg, Christine; Mikutta, Robert; Schippers, Axel; Dohrmann, Reiner; Guggenberger, Georg

2018-03-01

Iron (Fe) oxyhydroxides are important constituents of the soil mineral phase known to stabilize organic matter (OM) under oxic conditions. In an anoxic milieu, however, these Fe-organic associations are exposed to microbial reduction, releasing OM into soil solution. At present, only few studies have addressed the influence of adsorbed natural OM (NOM) on the reductive dissolution of Fe oxyhydroxides. This study therefore examined the impact of both the composition and concentration of adsorbed NOM on microbial Fe reduction with regard to (i) electron shuttling, (ii) complexation of Fe(II,III), (iii) surface site coverage and/or pore blockage, and (iv) aggregation. Adsorption complexes with varying carbon loadings were synthesized using different Fe oxyhydroxides (ferrihydrite, lepidocrocite, goethite, hematite, magnetite) and NOM of different origin (extracellular polymeric substances from Bacillus subtilis, OM extracted from soil Oi and Oa horizons). The adsorption complexes were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), N2 gas adsorption, electrophoretic mobility and particle size measurements, and OM desorption. Incubation experiments under anaerobic conditions were conducted for 16 days comparing two different strains of dissimilatory Fe(III)-reducing bacteria (Shewanella putrefaciens, Geobacter metallireducens). Mineral transformation during reduction was assessed via XRD and FTIR. Microbial reduction of the pure Fe oxyhydroxides was controlled by the specific surface area (SSA) and solubility of the minerals. For Shewanella putrefaciens, the Fe reduction of adsorption complexes strongly correlated with the concentration of potentially usable electron-shuttling molecules for NOM concentrations <2 mg C L-1, whereas for Geobacter metallireducens, Fe reduction depended on the particle size and thus aggregation of the adsorption complexes. These diverging results suggest that

G eobacter sp. SD-1 with enhanced electrochemical activity in high-salt concentration solutions

KAUST Repository

Sun, Dan; Call, Douglas; Wang, Aijie; Cheng, Shaoan; Logan, Bruce E.

2014-01-01

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd. Summary: An isolate, designated strain SD-1, was obtained from a biofilm dominated by Geobacter sulfurreducens in a microbial fuel cell. The electrochemical activity of strain SD-1 was compared with type strains, G.sulfurreducensPCA and Geobacter metallireducensGS-15, and a mixed culture in microbial electrolysis cells. SD-1 produced a maximum current density of 290±29Am-3 in a high-concentration phosphate buffer solution (PBS-H, 200mM). This current density was significantly higher than that produced by the mixed culture (189±44Am-3) or the type strains (<70Am-3). In a highly saline water (SW; 50mM PBS and 650mM NaCl), current by SD-1 (158±4Am-3) was reduced by 28% compared with 50mM PBS (220±4Am-3), but it was still higher than that of the mixed culture (147±19Am-3), and strains PCA and GS-15 did not produce any current. Electrochemical tests showed that the improved performance of SD-1 was due to its lower charge transfer resistance and more negative potentials produced at higher current densities. These results show that the electrochemical activity of SD-1 was significantly different than other Geobacter strains and mixed cultures in terms of its salt tolerance.

G eobacter sp. SD-1 with enhanced electrochemical activity in high-salt concentration solutions

KAUST Repository

Sun, Dan

2014-07-16

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd. Summary: An isolate, designated strain SD-1, was obtained from a biofilm dominated by Geobacter sulfurreducens in a microbial fuel cell. The electrochemical activity of strain SD-1 was compared with type strains, G.sulfurreducensPCA and Geobacter metallireducensGS-15, and a mixed culture in microbial electrolysis cells. SD-1 produced a maximum current density of 290±29Am-3 in a high-concentration phosphate buffer solution (PBS-H, 200mM). This current density was significantly higher than that produced by the mixed culture (189±44Am-3) or the type strains (<70Am-3). In a highly saline water (SW; 50mM PBS and 650mM NaCl), current by SD-1 (158±4Am-3) was reduced by 28% compared with 50mM PBS (220±4Am-3), but it was still higher than that of the mixed culture (147±19Am-3), and strains PCA and GS-15 did not produce any current. Electrochemical tests showed that the improved performance of SD-1 was due to its lower charge transfer resistance and more negative potentials produced at higher current densities. These results show that the electrochemical activity of SD-1 was significantly different than other Geobacter strains and mixed cultures in terms of its salt tolerance.

Dicty_cDB: Contig-U16581-1 [Dicty_cDB

Lifescience Database Archive (English)

Full Text Available 915_913( CP000915 |pid:none) Francisella tularensis subsp. me... 174 1e-41 AP008232_642( AP008232 |pid:none) Sodalis glossini...( FM992690 |pid:none) Candida dubliniensis CD36 chromo... 227 9e-58 (Q9Y7F0) RecName: Full=Peroxiredoxin TSA...9( CP000148 |pid:none) Geobacter metallireducens GS-15... 199 3e-49 AY842247_1( AY842247 |pid:none) Leishmania amazonensi...2e-48 AE001363_758( AE001363 |pid:none) Chlamydophila pneumoniae CWL029,... 196 2e-48 CP001071_1298( CP001071 |pid:none) Akkermansi...none) Helicobacter pylori isolate HP52 a... 169 3e-40 CU468135_2542( CU468135 |pid:none) Erwinia tasmaniensi

Rational engineering of Geobacter sulfurreducens electron transfer components: a foundation for building improved Geobacter-based bioelectrochemical technologies

Directory of Open Access Journals (Sweden)

Joana M Dantas

2015-07-01

Full Text Available Multiheme cytochromes have been implicated in Geobacter sulfurreducens (Gs extracellular electron transfer (EET. These proteins are potential targets to improve EET and enhance bioremediation and electrical current production by Gs. However, the functional characterization of multiheme cytochromes is particularly complex due to the co-existence of several microstates in solution, connecting the fully reduced and fully oxidized states. Over the last decade, new strategies have been developed to characterize multiheme redox proteins functionally and structurally. These strategies were used to reveal the functional mechanism of Gs multiheme cytochromes and also to identify key residues in these proteins for EET. In previous studies, we set the foundations for enhancement of the EET abilities of Gs by characterizing a family of five triheme cytochromes (PpcA-E. These periplasmic cytochromes are implicated in electron transfer between the oxidative reactions of metabolism in the cytoplasm and the reduction of extracellular terminal electron acceptors at the cell’s outer surface. The results obtained suggested that PpcA can couple e-/H+ transfer, a property that might contribute to the proton electrochemical gradient across the cytoplasmic membrane for metabolic energy production. The structural and functional properties of PpcA were characterized in detail and used for rational design of a family of 23 single site PpcA mutants. In this review, we summarize the functional characterization of the native and mutant proteins. Mutants that retain the mechanistic features of PpcA and adopt preferential e-/H+ transfer pathways at lower reduction potential values compared to the wild-type protein were selected for in vivo studies as the best candidates to increase the electron transfer rate of Gs. For the first time Gs strains have been manipulated by the introduction of mutant forms of essential proteins with the aim to develop and improve

Microbial electrocatalysis with Geobacter sulfurreducens biofilm on stainless steel cathodes

OpenAIRE

Dumas, Claire; Basséguy, Régine; Bergel, Alain

2008-01-01

Stainless steel and graphite electrodes were individually addressed and polarized at−0.60V vs. Ag/AgCl in reactors filled with a growth medium that contained 25mM fumarate as the electron acceptor and no electron donor, in order to force the microbial cells to use the electrode as electron source. When the reactor was inoculated with Geobacter sulfurreducens, the current increased and stabilized at average values around 0.75Am−2 for graphite and 20.5Am−2 for stainless steel. Cyclic voltamm...

Lactate Oxidation Coupled to Iron or Electrode Reduction by Geobacter sulfurreducens PCA

KAUST Repository

Call, D. F.

2011-10-14

Geobacter sulfurreducens PCA completely oxidized lactate and reduced iron or an electrode, producing pyruvate and acetate intermediates. Compared to the current produced by Shewanella oneidensis MR-1, G. sulfurreducens PCA produced 10-times-higher current levels in lactate-fed microbial electrolysis cells. The kinetic and comparative analyses reported here suggest a prominent role of G. sulfurreducens strains in metaland electrode-reducing communities supplied with lactate. © 2011, American Society for Microbiology.

Lactate Oxidation Coupled to Iron or Electrode Reduction by Geobacter sulfurreducens PCA

KAUST Repository

Call, D. F.; Logan, B. E.

2011-01-01

Geobacter sulfurreducens PCA completely oxidized lactate and reduced iron or an electrode, producing pyruvate and acetate intermediates. Compared to the current produced by Shewanella oneidensis MR-1, G. sulfurreducens PCA produced 10-times-higher current levels in lactate-fed microbial electrolysis cells. The kinetic and comparative analyses reported here suggest a prominent role of G. sulfurreducens strains in metaland electrode-reducing communities supplied with lactate. © 2011, American Society for Microbiology.

Electron Transfer Strategies Regulate Carbonate Mineral and Micropore Formation.

Science.gov (United States)

Zeng, Zhirui; Tice, Michael M

2018-01-01

Some microbial carbonates are robust biosignatures due to their distinct morphologies and compositions. However, whether carbonates induced by microbial iron reduction have such features is unknown. Iron-reducing bacteria use various strategies to transfer electrons to iron oxide minerals (e.g., membrane-bound enzymes, soluble electron shuttles, nanowires, as well as different mechanisms for moving over or attaching to mineral surfaces). This diversity has the potential to create mineral biosignatures through manipulating the microenvironments in which carbonate precipitation occurs. We used Shewanella oneidensis MR-1, Geothrix fermentans, and Geobacter metallireducens GS-15, representing three different strategies, to reduce solid ferric hydroxide in order to evaluate their influence on carbonate and micropore formation (micro-size porosity in mineral rocks). Our results indicate that electron transfer strategies determined the morphology (rhombohedral, spherical, or long-chained) of precipitated calcium-rich siderite by controlling the level of carbonate saturation and the location of carbonate formation. Remarkably, electron transfer strategies also produced distinctive cell-shaped micropores in both carbonate and hydroxide minerals, thus producing suites of features that could potentially serve as biosignatures recording information about the sizes, shapes, and physiologies of iron-reducing organisms. Key Words: Microbial iron reduction-Micropore-Electron transfer strategies-Microbial carbonate. Astrobiology 18, 28-36.

Geobacter Dominates the Inner Layers of a Stratified Biofilm on a Fluidized Anode During Brewery Wastewater Treatment

Directory of Open Access Journals (Sweden)

Sara Tejedor-Sanz

2018-03-01

Full Text Available In this study, we designed a microbial electrochemical fluidized bed reactor (ME-FBR, with an electroconductive anodic bed made of activated carbon particles for treating a brewery wastewater. Under a batch operating mode, acetate and propionate consumption rates were 13-fold and 2.4-fold higher, respectively, when the fluidized anode was polarized (0.2 V with respect to open circuit conditions. Operating in a continuous mode, this system could effectively treat the brewery effluent at organic loading rates (OLR over 1.7 kg m-3NRV d-1 and with removal efficiencies of 95 ± 1.4% (hydraulic retention time of 1 day and an influent of 1.7 g-COD L-1. The coulombic efficiency values highly depended upon the OLR applied, and varied from a 56 ± 15% to 10 ± 1%. Fluorescence in situ hybridization (FISH analysis revealed a relative high abundance of Geobacter species (ca. 20%, and clearly showed a natural microbial stratification. Interestingly, the Geobacter cluster was highly enriched in the innermost layers of the biofilm (thickness of 10 μm, which were in contact with the electroconductive particles of bed, whereas the rest of bacteria were located in the outermost layers. To our knowledge, this is the first time that such a clear microbial stratification has been observed on an anode-respiring biofilm. Our results revealed the relevant role of Geobacter in switching between the electrode and other microbial communities performing metabolic reactions in the outermost environment of the biofilm.

Identification of Genes Involved in Biofilm Formation and Respiration via Mini-Himar Transposon Mutagenesis of Geobacter sulfurreducens▿ †

Science.gov (United States)

Rollefson, Janet B.; Levar, Caleb E.; Bond, Daniel R.

2009-01-01

Electron transfer from cells to metals and electrodes by the Fe(III)-reducing anaerobe Geobacter sulfurreducens requires proper expression of redox proteins and attachment mechanisms to interface bacteria with surfaces and neighboring cells. We hypothesized that transposon mutagenesis would complement targeted knockout studies in Geobacter spp. and identify novel genes involved in this process. Escherichia coli mating strains and plasmids were used to develop a conjugation protocol and deliver mini-Himar transposons, creating a library of over 8,000 mutants that was anaerobically arrayed and screened for a range of phenotypes, including auxotrophy for amino acids, inability to reduce Fe(III) citrate, and attachment to surfaces. Following protocol validation, mutants with strong phenotypes were further characterized in a three-electrode system to simultaneously quantify attachment, biofilm development, and respiratory parameters, revealing mutants defective in Fe(III) reduction but unaffected in electron transfer to electrodes (such as an insertion in GSU1330, a putative metal export protein) or defective in electrode reduction but demonstrating wild-type biofilm formation (due to an insertion upstream of the NHL domain protein GSU2505). An insertion in a putative ATP-dependent transporter (GSU1501) eliminated electrode colonization but not Fe(III) citrate reduction. A more complex phenotype was demonstrated by a mutant containing an insertion in a transglutaminase domain protein (GSU3361), which suddenly ceased to respire when biofilms reached approximately 50% of the wild-type levels. As most insertions were not in cytochromes but rather in transporters, two-component signaling proteins, and proteins of unknown function, this collection illustrates how biofilm formation and electron transfer are separate but complementary phenotypes, controlled by multiple loci not commonly studied in Geobacter spp. PMID:19395486

Genome-wide analysis of the RpoN regulon in Geobacter sulfurreducens

Directory of Open Access Journals (Sweden)

Núñez Cinthia

2009-07-01

Full Text Available Abstract Background The role of the RNA polymerase sigma factor RpoN in regulation of gene expression in Geobacter sulfurreducens was investigated to better understand transcriptional regulatory networks as part of an effort to develop regulatory modules for genome-scale in silico models, which can predict the physiological responses of Geobacter species during groundwater bioremediation or electricity production. Results An rpoN deletion mutant could not be obtained under all conditions tested. In order to investigate the regulon of the G. sulfurreducens RpoN, an RpoN over-expression strain was made in which an extra copy of the rpoN gene was under the control of a taclac promoter. Combining both the microarray transcriptome analysis and the computational prediction revealed that the G. sulfurreducens RpoN controls genes involved in a wide range of cellular functions. Most importantly, RpoN controls the expression of the dcuB gene encoding the fumarate/succinate exchanger, which is essential for cell growth with fumarate as the terminal electron acceptor in G. sulfurreducens. RpoN also controls genes, which encode enzymes for both pathways of ammonia assimilation that is predicted to be essential under all growth conditions in G. sulfurreducens. Other genes that were identified as part of the RpoN regulon using either the computational prediction or the microarray transcriptome analysis included genes involved in flagella biosynthesis, pili biosynthesis and genes involved in central metabolism enzymes and cytochromes involved in extracellular electron transfer to Fe(III, which are known to be important for growth in subsurface environment or electricity production in microbial fuel cells. The consensus sequence for the predicted RpoN-regulated promoter elements is TTGGCACGGTTTTTGCT. Conclusion The G. sulfurreducens RpoN is an essential sigma factor and a global regulator involved in a complex transcriptional network controlling a variety of

Functional Role of Infective Viral Particles on Metal Reduction

Energy Technology Data Exchange (ETDEWEB)

Coates, John D.

2014-04-01

A proposed strategy for the remediation of uranium (U) contaminated sites was based on the immobilization of U by reducing the oxidized soluble U, U(VI), to form a reduced insoluble end product, U(IV). Previous studies identified Geobacter sp., including G. sulfurreducens and G. metallireducens, as predominant U(VI)-reducing bacteria under acetate-oxidizing and U(VI)-reducing conditions. Examination of the finished genome sequence annotation of the canonical metal reducing species Geobacter sulfurreducens strain PCA and G. metallireduceans strain GS-15 as well as the draft genome sequence of G. uraniumreducens strain Rf4 identified phage related proteins. In addition, the completed genome for Anaeromyxobacter dehalogenans and the draft genome sequence of Desulfovibrio desulfuricans strain G20, two more model metal-reducing bacteria, also revealed phage related sequences. The presence of these gene sequences indicated that Geobacter spp., Anaeromyxobacter spp., and Desulfovibrio spp. are susceptible to viral infection. Furthermore, viral populations in soils and sedimentary environments in the order of 6.4×10{sup 6}–2.7×10{sup 10} VLP’s cm{sup -3} have been observed. In some cases, viral populations exceed bacterial populations in these environments suggesting that a relationship may exist between viruses and bacteria. Our preliminary screens of samples collected from the ESR FRC indicated that viral like particles were observed in significant numbers. The objective of this study was to investigate the potential functional role viruses play in metal reduction specifically Fe(III) and U(VI) reduction, the environmental parameters affecting viral infection of metal reducing bacteria, and the subsequent effects on U transport.

Final Report Systems Level Analysis of the Function and Adaptive Responses of Methanogenic Consortia

Energy Technology Data Exchange (ETDEWEB)

Lovley, Derek R. [Univ. of Massachusetts, Amherst, MA (United States)

2015-03-09

The purpose of this research was to determine whether the syntrophic microbial associations that are central to the functioning of methane-producing terrestrial wetlands can be predictively modeled with coupled multi-species genome-scale metabolic models. Such models are important because methane is an important greenhouse gas and there is a need to predictively model how the methane-producing microbial communities will respond to environmental perturbations, such as global climate change. The research discovered that the most prodigious methane-producing microorganisms on earth participate in a previously unrecognized form of energy exchange. The methane-producers Methanosaeta and Methanosarcina forge biological electrical connections with other microbes in order to obtain electrons to reduce carbon dioxide to methane. This direct interspecies electron transfer (DIET) was demonstrated in complex microbial communities as well as in defined co-cultures. For example, metatranscriptomic analysis of gene expression in both natural communities and defined co-cultures demonstrated that Methanosaeta species highly expressed genes for the enzymes for the reduction of carbon dioxide to methane. Furthermore, Methanosaeta’s electron-donating partners highly expressed genes for the biological electrical connections known as microbial nanowires. A series of studies involving transcriptomics, genome resequencing, and analysis of the metabolism of a series of strains with targeted gene deletions, further elucidated the mechanisms and energetics of DIET in methane-producing co-cultures, as well as in a co-culture of Geobacter metallireducens and Geobacter sulfurreducens, which provided a system for studying DIET with two genetically tractable partners. Genome-scale modeling of DIET in the G. metallireducens/G. sulfurreducens co-culture suggested that DIET provides more energy to the electron-donating partner that electron exchange via interspecies hydrogen transfer, but that the

MOLECULAR DOCKING AND DYNAMICS STUDIES ON THE PROTEIN-PROTEIN INTERACTIONS OF ELECTRICALLY ACTIVE PILIN NANOWIRES OF GEOBACTER SULFURREDUCENS.

Directory of Open Access Journals (Sweden)

D. Jeya Sundara Sharmila1 *

2017-06-01

Full Text Available Molecular interactions are key aspects in biological recognitions applicable in nano/micro systems. Bacterial nanowires are pilus filament based structures that can conduct electrons. The transport of electron is proposed to be facilitated by filamentous fibers made up of polymeric assemblies of proteins called pilin. Geobacter sulfurreducens is capable of delivering electrons through extracellular electron transport (EET by employing conductive nanowires, which are pilin proteins composed of type IV subunit PilA. Protein-protein interactions play an important role in the stabilization of the pilin nanowire assembly complex and it contains transmembrane (TM domain. In current study, protein-protein docking and multiple molecular dynamic (MD simulations were performed to understand the binding mode of pilin nanowires. The MD result explains the conformational behavior and folding of pilin nanowires in water environment in different time scale duration 20, 5, 5, 10 and 20ns (total of 60ns. Direct hydrogen bonds and water mediated hydrogen bonds that play a crucial role during the simulation were investigated. The conformational state, folding, end-toend distance profile and hydrogen bonding behavior had indicated that the Geobacter sulfurreducens pilin nanowires have electrical conductivity properties.

Quantifying Temporal Autocorrelations for the Expression of Geobacter species mRNA Gene Transcripts at Variable Ammonium Levels during in situ U(VI) Bioremediation

Science.gov (United States)

Mouser, P. J.

2010-12-01

In order to develop decision-making tools for the prediction and optimization of subsurface bioremediation strategies, we must be able to link the molecular-scale activity of microorganisms involved in remediation processes with biogeochemical processes observed at the field-scale. This requires the ability to quantify changes in the in situ metabolic condition of dominant microbes and associate these changes to fluctuations in nutrient levels throughout the bioremediation process. It also necessitates a need to understand the spatiotemporal variability of the molecular-scale information to develop meaningful parameters and constraint ranges in complex bio-physio-chemical models. The expression of three Geobacter species genes (ammonium transporter (amtB), nitrogen fixation (nifD), and a housekeeping gene (recA)) were tracked at two monitoring locations that differed significantly in ammonium (NH4+) concentrations during a field-scale experiment where acetate was injected into the subsurface to simulate Geobacteraceae in a uranium-contaminated aquifer. Analysis of amtB and nifD mRNA transcript levels indicated that NH4+ was the primary form of fixed nitrogen during bioremediation. Overall expression levels of amtB were on average 8-fold higher at NH4+ concentrations of 300 μM or more than at lower NH4+ levels (average 60 μM). The degree of temporal correlation in Geobacter species mRNA expression levels was calculated at both locations using autocorrelation methods that describe the relationship between sample semi-variance and time lag. At the monitoring location with lower NH4+, a temporal correlation lag of 8 days was observed for both amtB and nifD transcript patterns. At the location where higher NH4+ levels were observed, no discernable temporal correlation lag above the sampling frequency (approximately every 2 days) was observed for amtB or nifD transcript fluctuations. Autocorrelation trends in recA expression levels at both locations indicated that

From Nanowires to Biofilms: An Exploration of Novel Mechanisms of Uranium Transformation Mediated by Geobacter Bacteria

Energy Technology Data Exchange (ETDEWEB)

REGUERA, GEMMA [Michigan State University

2014-01-16

One promising strategy for the in situ bioremediation of radioactive groundwater contaminants that has been identified by the SBR Program is to stimulate the activity of dissimilatory metal-reducing microorganisms to reductively precipitate uranium and other soluble toxic metals. The reduction of U(VI) and other soluble contaminants by Geobacteraceae is directly dependent on the reduction of Fe(III) oxides, their natural electron acceptor, a process that requires the expression of Geobacter’s conductive pili (pilus nanowires). Expression of conductive pili by Geobacter cells leads to biofilm development on surfaces and to the formation of suspended biogranules, which may be physiological closer to biofilms than to planktonic cells. Biofilm development is often assumed in the subsurface, particularly at the matrix-well screen interface, but evidence of biofilms in the bulk aquifer matrix is scarce. Our preliminary results suggest, however, that biofilms develop in the subsurface and contribute to uranium transformations via sorption and reductive mechanisms. In this project we elucidated the mechanism(s) for uranium immobilization mediated by Geobacter biofilms and identified molecular markers to investigate if biofilm development is happening in the contaminated subsurface. The results provided novel insights needed in order to understand the metabolic potential and physiology of microorganisms with a known role in contaminant transformation in situ, thus having a significant positive impact in the SBR Program and providing novel concept to monitor, model, and predict biological behavior during in situ treatments.

Identification of the electron transfer flavoprotein as an upregulated enzyme in the benzoate utilization of Desulfotignum balticum.

Science.gov (United States)

Habe, Hiroshi; Kobuna, Akinori; Hosoda, Akifumi; Kosaka, Tomoyuki; Endoh, Takayuki; Tamura, Hiroto; Yamane, Hisakazu; Nojiri, Hideaki; Omori, Toshio; Watanabe, Kazuya

2009-07-01

Desulfotignum balticum utilizes benzoate coupled to sulfate reduction. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) analysis was conducted to detect proteins that increased more after growth on benzoate than on butyrate. A comparison of proteins on 2D gels showed that at least six proteins were expressed. The N-terminal sequences of three proteins exhibited significant identities with the alpha and beta subunits of electron transfer flavoprotein (ETF) from anaerobic aromatic-degraders. By sequence analysis of the fosmid clone insert (37,590 bp) containing the genes encoding the ETF subunits, we identified three genes, whose deduced amino acid sequences showed 58%, 74%, and 62% identity with those of Gmet_2267 (Fe-S oxidoreductase), Gmet_2266 (ETF beta subunit), and Gmet_2265 (ETF alpha subunit) respectively, which exist within the 300-kb genomic island of aromatic-degradation genes from Geobacter metallireducens GS-15. The genes encoding ETF subunits found in this study were upregulated in benzoate utilization.

Extracellular Palladium Nanoparticle Production using Geobacter sulfurreducens

KAUST Repository

Yates, Matthew D.

2013-09-03

Sustainable methods are needed to recycle precious metals and synthesize catalytic nanoparticles. Palladium nanoparticles can be produced via microbial reduction of soluble Pd(II) to Pd(0), but in previous tests using dissimilatory metal reducing bacteria (DMRB), the nanoparticles were closely associated with the cells, occupying potential reductive sites and eliminating the potential for cell reuse. The DMRB Geobacter sulfurreducens was shown here to reduce soluble Pd(II) to Pd(0) nanoparticles primarily outside the cell, reducing the toxicity of metal ions, and allowing nanoparticle recovery without cell destruction that has previously been observed using other microorganisms. Cultures reduced 50 ± 3 mg/L Pd(II) with 1% hydrogen gas (v/v headspace) in 6 h incubation tests [100 mg/L Pd(II) initially], compared to 8 ± 3 mg/L (10 mM acetate) without H2. Acetate was ineffective as an electron donor for palladium removal in the presence or absence of fumarate as an electron acceptor. TEM imaging verified that Pd(0) nanoparticles were predominantly in the EPS surrounding cells in H2-fed cultures, with only a small number of particles visible inside the cell. Separation of the cells and EPS by centrifugation allowed reuse of the cell suspensions and effective nanoparticle recovery. These results demonstrate effective palladium recovery and nanoparticle production using G. sulfurreducens cell suspensions and renewable substrates such as H2 gas. © 2013 American Chemical Society.

Role of U(VI) adsorption in U(VI) Reduction by Geobacter species

International Nuclear Information System (INIS)

Lovely, Derrick

2008-01-01

Previous work had suggested that Acholeplasma palmae has a higher capacity for uranium sorption than other bacteria studied. Sorption studies were performed with cells in suspension in various solutions containing uranium, and results were used to generate uranium-biosorption isotherms. Results from this study showed that the U(VI) sorption capacity of G. uraniireducens was relatively similar in simple solutions, such as sodium chloride or bicarbonate. However, this ability to sorb uranium significantly decreased in groundwater. This suggested that certain chemicals present in the groundwater were inhibiting the ability of cell components of Geobacter to adsorb uranium. It was hypothesized that uranium removal would also be diminished in the bicarbonate solution. However, this did not seem to be the case, as uranium was as easily removed in the bicarbonate solution as in the sodium chloride solution.

Reduction of low potential electron acceptors requires the CbcL inner membrane cytochrome of Geobacter sulfurreducens.

Science.gov (United States)

Zacharoff, Lori; Chan, Chi Ho; Bond, Daniel R

2016-02-01

The respiration of metals by the bacterium Geobacter sulfurreducens requires electrons generated by metabolism to pass from the interior of the cell to electron acceptors beyond the cell membranes. The G. sulfurreducens inner membrane multiheme c-type cytochrome ImcH is required for respiration to extracellular electron acceptors with redox potentials greater than -0.1 V vs. SHE, but ImcH is not essential for electron transfer to lower potential acceptors. In contrast, deletion of cbcL, encoding an inner membrane protein consisting of b-type and multiheme c-type cytochrome domains, severely affected reduction of low potential electron acceptors such as Fe(III)-oxides and electrodes poised at -0.1 V vs. SHE. Catalytic cyclic voltammetry of a ΔcbcL strain growing on poised electrodes revealed a 50 mV positive shift in driving force required for electron transfer out of the cell. In non-catalytic conditions, low-potential peaks present in wild type biofilms were absent in ∆cbcL mutants. Expression of cbcL in trans increased growth at low redox potential and restored features to cyclic voltammetry. This evidence supports a model where CbcL is a component of a second electron transfer pathway out of the G. sulfurreducens inner membrane that dominates when redox potential is at or below -0.1 V vs. SHE. Copyright © 2015. Published by Elsevier B.V.

Importance of c-Type cytochromes for U(VI reduction by Geobacter sulfurreducens

Directory of Open Access Journals (Sweden)

Leang Ching

2007-03-01

Full Text Available Abstract Background In order to study the mechanism of U(VI reduction, the effect of deleting c-type cytochrome genes on the capacity of Geobacter sulfurreducens to reduce U(VI with acetate serving as the electron donor was investigated. Results The ability of several c-type cytochrome deficient mutants to reduce U(VI was lower than that of the wild type strain. Elimination of two confirmed outer membrane cytochromes and two putative outer membrane cytochromes significantly decreased (ca. 50–60% the ability of G. sulfurreducens to reduce U(VI. Involvement in U(VI reduction did not appear to be a general property of outer membrane cytochromes, as elimination of two other confirmed outer membrane cytochromes, OmcB and OmcC, had very little impact on U(VI reduction. Among the periplasmic cytochromes, only MacA, proposed to transfer electrons from the inner membrane to the periplasm, appeared to play a significant role in U(VI reduction. A subpopulation of both wild type and U(VI reduction-impaired cells, 24–30%, accumulated amorphous uranium in the periplasm. Comparison of uranium-accumulating cells demonstrated a similar amount of periplasmic uranium accumulation in U(VI reduction-impaired and wild type G. sulfurreducens. Assessment of the ability of the various suspensions to reduce Fe(III revealed no correlation between the impact of cytochrome deletion on U(VI reduction and reduction of Fe(III hydroxide and chelated Fe(III. Conclusion This study indicates that c-type cytochromes are involved in U(VI reduction by Geobacter sulfurreducens. The data provide new evidence for extracellular uranium reduction by G. sulfurreducens but do not rule out the possibility of periplasmic uranium reduction. Occurrence of U(VI reduction at the cell surface is supported by the significant impact of elimination of outer membrane cytochromes on U(VI reduction and the lack of correlation between periplasmic uranium accumulation and the capacity for uranium

A method for high throughput bioelectrochemical research based on small scale microbial electrolysis cells

KAUST Repository

Call, Douglas F.

2011-07-01

There is great interest in studying exoelectrogenic microorganisms, but existing methods can require expensive electrochemical equipment and specialized reactors. We developed a simple system for conducting high throughput bioelectrochemical research using multiple inexpensive microbial electrolysis cells (MECs) built with commercially available materials and operated using a single power source. MECs were small crimp top serum bottles (5mL) with a graphite plate anode (92m 2/m 3) and a cathode of stainless steel (SS) mesh (86m 2/m 3), graphite plate, SS wire, or platinum wire. The highest volumetric current density (240A/m 3, applied potential of 0.7V) was obtained using a SS mesh cathode and a wastewater inoculum (acetate electron donor). Parallel operated MECs (single power source) did not lead to differences in performance compared to non-parallel operated MECs, which can allow for high throughput reactor operation (>1000 reactors) using a single power supply. The utility of this method for cultivating exoelectrogenic microorganisms was demonstrated through comparison of buffer effects on pure (Geobacter sulfurreducens and Geobacter metallireducens) and mixed cultures. Mixed cultures produced current densities equal to or higher than pure cultures in the different media, and current densities for all cultures were higher using a 50mM phosphate buffer than a 30mM bicarbonate buffer. Only the mixed culture was capable of sustained current generation with a 200mM phosphate buffer. These results demonstrate the usefulness of this inexpensive method for conducting in-depth examinations of pure and mixed exoelectrogenic cultures. © 2011 Elsevier B.V.

Iron and manganese in anaerobic respiration: environmental significance, physiology, and regulation

Science.gov (United States)

Nealson, K. H.; Saffarini, D.

1994-01-01

Dissimilatory iron and/or manganese reduction is known to occur in several organisms, including anaerobic sulfur-reducing organisms such as Geobacter metallireducens or Desulfuromonas acetoxidans, and facultative aerobes such as Shewanella putrefaciens. These bacteria couple both carbon oxidation and growth to the reduction of these metals, and inhibitor and competition experiments suggest that Mn(IV) and Fe(III) are efficient electron acceptors similar to nitrate in redox abilities and capable of out-competing electron acceptors of lower potential, such as sulfate (sulfate reduction) or CO2 (methanogenesis). Field studies of iron and/or manganese reduction suggest that organisms with such metabolic abilities play important roles in coupling the oxidation of organic carbon to metal reduction under anaerobic conditions. Because both iron and manganese oxides are solids or colloids, they tend to settle downward in aquatic environments, providing a physical mechanism for the movement of oxidizing potential into anoxic zones. The resulting biogeochemical metal cycles have a strong impact on many other elements including carbon, sulfur, phosphorous, and trace metals.

Salt removal using multiple microbial desalination cells under continuous flow conditions

KAUST Repository

Qu, Youpeng

2013-05-01

Four microbial desalination cells (MDCs) were hydraulically connected and operated under continuous flow conditions. The anode solution from the first MDC flowed into the cathode, and then on to the anode of the next reactor, which avoided pH imbalances that inhibit bacterial metabolism. The salt solution also moved through each desalination chamber in series. Increasing the hydraulic retention times (HRTs) of the salt solution from 1 to 2. days increased total NaCl removal from 76 ± 1% to 97 ± 1%, but coulombic efficiencies decreased from 49 ± 4% to 35 ± 1%. Total COD removals were similar at both HRTs (60 ± 2%, 2. days; 59 ± 2%, 1. day). Community analysis of the anode biofilms showed that bacteria most similar to the xylose fermenting bacterium Klebsiella ornithinolytica predominated in the anode communities, and sequences most similar to Geobacter metallireducens were identified in all MDCs except the first one. These results demonstrated successful operation of a series of hydraulically connected MDCs and good desalination rates. © 2013 Elsevier B.V..

Microbial electrocatalysis with Geobacter sulfurreducens biofilm on stainless steel cathodes

International Nuclear Information System (INIS)

Dumas, Claire; Basseguy, Regine; Bergel, Alain

2008-01-01

Stainless steel and graphite electrodes were individually addressed and polarized at -0.60 V vs. Ag/AgCl in reactors filled with a growth medium that contained 25 mM fumarate as the electron acceptor and no electron donor, in order to force the microbial cells to use the electrode as electron source. When the reactor was inoculated with Geobacter sulfurreducens, the current increased and stabilized at average values around 0.75 A m -2 for graphite and 20.5 A m -2 for stainless steel. Cyclic voltammetry performed at the end of the experiment indicated that the reduction started at around -0.30 V vs. Ag/AgCl on stainless steel. Removing the biofilm formed on the electrode surface made the current totally disappear, confirming that the G.sulfurreducens biofilm was fully responsible for the electrocatalysis of fumarate reduction. Similar current densities were recorded when the electrodes were polarized after being kept in open circuit for several days. The reasons for the bacteria presence and survival on non-connected stainless steel coupons were discussed. Chronoamperometry experiments performed at different potential values suggested that the biofilm-driven catalysis was controlled by electrochemical kinetics. The high current density obtained, quite close to the redox potential of the fumarate/succinate couple, presents stainless steel as a remarkable material to support biocathodes

Anode biofilm transcriptomics reveals outer surface components essential for high density current production in Geobacter sulfurreducens fuel cells.

Directory of Open Access Journals (Sweden)

Kelly P Nevin

Full Text Available The mechanisms by which Geobacter sulfurreducens transfers electrons through relatively thick (>50 microm biofilms to electrodes acting as a sole electron acceptor were investigated. Biofilms of Geobacter sulfurreducens were grown either in flow-through systems with graphite anodes as the electron acceptor or on the same graphite surface, but with fumarate as the sole electron acceptor. Fumarate-grown biofilms were not immediately capable of significant current production, suggesting substantial physiological differences from current-producing biofilms. Microarray analysis revealed 13 genes in current-harvesting biofilms that had significantly higher transcript levels. The greatest increases were for pilA, the gene immediately downstream of pilA, and the genes for two outer c-type membrane cytochromes, OmcB and OmcZ. Down-regulated genes included the genes for the outer-membrane c-type cytochromes, OmcS and OmcT. Results of quantitative RT-PCR of gene transcript levels during biofilm growth were consistent with microarray results. OmcZ and the outer-surface c-type cytochrome, OmcE, were more abundant and OmcS was less abundant in current-harvesting cells. Strains in which pilA, the gene immediately downstream from pilA, omcB, omcS, omcE, or omcZ was deleted demonstrated that only deletion of pilA or omcZ severely inhibited current production and biofilm formation in current-harvesting mode. In contrast, these gene deletions had no impact on biofilm formation on graphite surfaces when fumarate served as the electron acceptor. These results suggest that biofilms grown harvesting current are specifically poised for electron transfer to electrodes and that, in addition to pili, OmcZ is a key component in electron transfer through differentiated G. sulfurreducens biofilms to electrodes.

Investigating different mechanisms for biogenic selenite transformations: Geobacter sulfurreducens, Shewanella oneidensis and Veillonella atypica

Science.gov (United States)

Pearce, C.I.; Pattrick, R.A.D.; Law, N.; Charnock, J.M.; Coker, V.S.; Fellowes, J.W.; Oremland, R.S.; Lloyd, J.R.

2009-01-01

The metal-reducing bacteria Geobacter sulfurreducens, Shewanella oneidensis and Veillonella atypica, use different mechanisms to transform toxic, bioavailable sodium selenite to less toxic, non-mobile elemental selenium and then to selenide in anaerobic environments, offering the potential for in situ and ex situ bioremediation of contaminated soils, sediments, industrial effluents, and agricultural drainage waters. The products of these reductive transformations depend on both the organism involved and the reduction conditions employed, in terms of electron donor and exogenous extracellular redox mediator. The intermediary phase involves the precipitation of elemental selenium nanospheres and the potential role of proteins in the formation of these structures is discussed. The bionanomineral phases produced during these transformations, including both elemental selenium nanospheres and metal selenide nanoparticles, have catalytic, semiconducting and light-emitting properties, which may have unique applications in the realm of nanophotonics. This research offers the potential to combine remediation of contaminants with the development of environmentally friendly manufacturing pathways for novel bionanominerals. ?? 2009 Taylor & Francis.

Electrochemical and genomic analysis of novel electroactive isolates obtained via potentiostatic enrichment from tropical sediment

Science.gov (United States)

Doyle, Lucinda E.; Yung, Pui Yi; Mitra, Sumitra D.; Wuertz, Stefan; Williams, Rohan B. H.; Lauro, Federico M.; Marsili, Enrico

2017-07-01

Enrichment of electrochemically-active microorganisms (EAM) to date has mostly relied on microbial fuel cells fed with wastewater. This study aims to enrich novel EAM by exposing tropical sediment, not frequently reported in the literature, to sustained anodic potentials. Voltamperometric techniques and electrochemical impedance spectroscopy, performed over a wide range of potentials, characterise extracellular electron transfer (EET) over time. Applied potential is found to affect biofilm electrochemical signature. Geobacter metallireducens is heavily enriched on the electrodes, as determined by metagenomic and metatranscriptomic analysis, in the first report of the species in a lactate-fed system. Two novel isolates are grown in pure culture from the enrichment, identified by 16S rRNA gene sequencing as Aeromonas and Enterobacter, respectively. The names proposed are Aeromonas sp. CL-1 and Enterobacter sp. EA-1. Both isolates are capable of EET on carbon felt and screen-printed carbon electrodes without the addition of exogenous redox mediators. Enterobacter sp. EA-1 can also perform mediated electron transfer using the soluble redox mediator 2-hydroxy-1,4-naphthoquinone (HNQ). Both isolates are able to use acetate and lactate as electron donors. This work outlines a comprehensive methodology for characterising novel EAM from unconventional inocula.

Nonproteinogenic D-amino acids at millimolar concentrations are a toxin for anaerobic microorganisms relevant to early Earth and other anoxic planets.

Science.gov (United States)

Nixon, Sophie L; Cockell, Charles S

2015-03-01

The delivery of extraterrestrial organics to early Earth provided a potentially important source of carbon and energy for microbial life. Optically active organic compounds of extraterrestrial origin exist in racemic form, yet life on Earth has almost exclusively selected for L- over D-enantiomers of amino acids. Although D-enantiomers of proteinogenic amino acids are known to inhibit aerobic microorganisms, the role of concentrated nonproteinogenic meteoritic D-amino acids on anaerobic metabolisms relevant to early Earth and other anoxic planets such as Mars is unknown. Here, we test the inhibitory effect of D-enantiomers of two nonproteinogenic amino acids common to carbonaceous chondrites, norvaline and α-aminobutyric acid, on microbial iron reduction. Three pure strains (Geobacter bemidjiensis, Geobacter metallireducens, Geopsychrobacter electrodiphilus) and an iron-reducing enrichment culture were grown in the presence of 10 mM D-enantiomers of both amino acids. Further tests were conducted to assess the inhibitory effect of these D-amino acids at 1 and 0.1 mM. The presence of 10 mM D-norvaline and D-α-aminobutyric acid inhibited microbial iron reduction by all pure strains and the enrichment. G. bemidjiensis was not inhibited by either amino acid at 0.1 mM, but D-α-aminobutyric acid still inhibited at 1 mM. Calculations using published meteorite accumulation rates to the martian surface indicate D-α-aminobutyric acid may have reached inhibitory concentrations in little over 1000 years during peak infall. These data show that, on a young anoxic planet, the use of one enantiomer over another may render the nonbiological enantiomer an environmental toxin. Processes that generate racemic amino acids in the environment, such as meteoritic infall or impact synthesis, would have been toxic processes and could have been a selection pressure for the evolution of early racemases.

Computational and experimental analysis of redundancy in the central metabolism of Geobacter sulfurreducens.

Directory of Open Access Journals (Sweden)

Daniel Segura

2008-02-01

Full Text Available Previous model-based analysis of the metabolic network of Geobacter sulfurreducens suggested the existence of several redundant pathways. Here, we identified eight sets of redundant pathways that included redundancy for the assimilation of acetate, and for the conversion of pyruvate into acetyl-CoA. These equivalent pathways and two other sub-optimal pathways were studied using 5 single-gene deletion mutants in those pathways for the evaluation of the predictive capacity of the model. The growth phenotypes of these mutants were studied under 12 different conditions of electron donor and acceptor availability. The comparison of the model predictions with the resulting experimental phenotypes indicated that pyruvate ferredoxin oxidoreductase is the only activity able to convert pyruvate into acetyl-CoA. However, the results and the modeling showed that the two acetate activation pathways present are not only active, but needed due to the additional role of the acetyl-CoA transferase in the TCA cycle, probably reflecting the adaptation of these bacteria to acetate utilization. In other cases, the data reconciliation suggested additional capacity constraints that were confirmed with biochemical assays. The results demonstrate the need to experimentally verify the activity of key enzymes when developing in silico models of microbial physiology based on sequence-based reconstruction of metabolic networks.

Sediment studies of the biological factors controlling the reduction of U(VI)

International Nuclear Information System (INIS)

Lovley, Derek R.

2004-01-01

Studies were conducted primarily with sediments, both in laboratory incubations and in a field experiment, with supporting studies with pure cultures. To our knowledge the sediment studies were the first on microbial U(VI) reduction in actual uranium-contaminated subsurface sediments, under conditions that mimic those found in situ. Important findings included: (1) U(VI) reduction is a biotic process in subsurface sediments. (2) U(VI) reduction can be stimulated most effectively with the addition of acetate. Although it had been speculated that microbial U(VI) reduction might be capable of this type of environmental remediation ever since the discovery of microbial U(VI) reduction, this had not been previously demonstrated under environmentally relevant conditions. (3) U(VI) is reduced concurrently with Fe(III) and prior to sulfate reduction. U(VI) and Fe(III) reduction proceeded concurrently, accompanied by a dramatic enrichment in organisms in the Geobacteraceae. Sulfate-reducing microorganisms do not appear to be important components of the microbial community reducing U(VI) in these subsurface sediments. (4) Nitrate has important influences on U(VI) reduction. Nitrate inhibits the reduction of metals until nitrate is depleted. Fe(III)-reducing microorganisms such as Geobacter metallireducens and Desulfitobacterium species can oxidize Fe(II) with the reduction of nitrate which is an important consideration because our previous studies have demonstrated that freshly precipitated Fe(III) oxides can reoxidize U(IV) to U(VI). The discovery that G. metallireducens can ''run backwards'' and oxidize U(IV) when nitrate is present reveals another mechanism preventing precipitation of U(IV) in the presence of nitrate as well as potential novel strategy for removing uranium from the subsurface after a site has been remediated. (5) Importance of understanding Fe(III) forms available for microbial reduction. Fe(III) is orders of magnitude more abundant than U(VI) as an

Metabolic response of Geobacter sulfurreducens towards electron donor/acceptor variation

Directory of Open Access Journals (Sweden)

Lovley Derek R

2010-11-01

Full Text Available Abstract Background Geobacter sulfurreducens is capable of coupling the complete oxidation of organic compounds to iron reduction. The metabolic response of G. sulfurreducens towards variations in electron donors (acetate, hydrogen and acceptors (Fe(III, fumarate was investigated via 13C-based metabolic flux analysis. We examined the 13C-labeling patterns of proteinogenic amino acids obtained from G. sulfurreducens cultured with 13C-acetate. Results Using 13C-based metabolic flux analysis, we observed that donor and acceptor variations gave rise to differences in gluconeogenetic initiation, tricarboxylic acid cycle activity, and amino acid biosynthesis pathways. Culturing G. sulfurreducens cells with Fe(III as the electron acceptor and acetate as the electron donor resulted in pyruvate as the primary carbon source for gluconeogenesis. When fumarate was provided as the electron acceptor and acetate as the electron donor, the flux analysis suggested that fumarate served as both an electron acceptor and, in conjunction with acetate, a carbon source. Growth on fumarate and acetate resulted in the initiation of gluconeogenesis by phosphoenolpyruvate carboxykinase and a slightly elevated flux through the oxidative tricarboxylic acid cycle as compared to growth with Fe(III as the electron acceptor. In addition, the direction of net flux between acetyl-CoA and pyruvate was reversed during growth on fumarate relative to Fe(III, while growth in the presence of Fe(III and acetate which provided hydrogen as an electron donor, resulted in decreased flux through the tricarboxylic acid cycle. Conclusions We gained detailed insight into the metabolism of G. sulfurreducens cells under various electron donor/acceptor conditions using 13C-based metabolic flux analysis. Our results can be used for the development of G. sulfurreducens as a chassis for a variety of applications including bioremediation and renewable biofuel production.

Biochemical Mechanisms and Energy Strategies of Geobacter sulfurreducens for Long- Term Survival

Science.gov (United States)

Helmus, R. A.; Liermann, L. J.; Brantley, S. L.; Tien, M.

2008-12-01

Numerous species of bacteria have been observed to exhibit a growth advantage in stationary phase (GASP) phenotype, indicating that microorganisms starved of an energy source may adapt to allow for long-term survival. Understanding how Geobacter sulfurreducens persists using various metal forms as energy sources and whether a GASP phenotype develops during long-term growth are important for efficient application of this bacterium to sites requiring engineered bioremediation of soluble metals. Thus, we investigated the growth kinetics and survival of G. sulfurreducens. The growth rate of G. sulfurreducens was highest when cultured with soluble iron and generally higher on iron oxide than manganese oxide, suggesting that soluble metal forms are more readily utilized as energy sources by G. sulfurreducens. By monitoring the abundance of G. sulfurreducens in batch cultures for >6 months, distinct growth, stationary, and prolonged starvation phases were observed and a cell density of 105- 106 cells/mL persisted under long-term starvation conditions. The outgrowth of an aged G. sulfurreducens strain co-cultured with a young strain was monitored as a measure of the existence of the GASP phenotype. As the strains aged, the rpoS gene was cloned and sequenced at different stages of growth to identify mutations corresponding to a growth advantage. The results of these studies provide insight into the use of various metal forms for growth by G. sulfurreducens and its ability to persist when starved of energy sources.

Visible spectroelectrochemical characterization of Geobacter sulfurreducens biofilms on optically transparent indium tin oxide electrode

International Nuclear Information System (INIS)

Jain, Anand; Gazzola, Giulio; Panzera, Aurora; Zanoni, Michele; Marsili, Enrico

2011-01-01

We report visible spectroelectrochemical (SEC) characterization of cytochrome c 552 (cyt c 552 ) in viable Geobacter sulfurreducens biofilms on tin-doped indium oxide (ITO) electrodes poised at 0.24 V vs. SHE. G. sulfurreducens biofilms were grown in minimal medium with acetate as electron donor (turnover conditions), followed by 24 h incubation in electron donor-depleted medium (non-turnover conditions). The electronic absorption spectra of G. sulfurreducens biofilms showed the lowest energy absorption band in the reduced state at 552 nm, which indicated excess of cyt c 552 in the biofilm. The spectra under non-turnover conditions displayed gradual reduction of the cyt c 552 , following the step-wise decrease of electrode potential from 0.0 V to −0.6 V vs. standard calomel electrode (SCE). The spectral changes were fully reversible in both positive and negative direction of the scan potential, with average midpoint potential value of −0.42 V vs. SCE. Confocal microscopy analysis revealed that the thickness of biofilms under turnover conditions and non-turnover conditions was approximately 35 and 3.5 μm, respectively. This is the first study to observe the reversible redox conversion of cyt c 552 in viable G. sulfurreducens biofilms.

Electrochemical activities of Geobacter biofilms growing on electrodes with various potentials

International Nuclear Information System (INIS)

Li, Dao-Bo; Huang, Yu-Xi; Li, Jie; Li, Ling-Li; Tian, Li-Jiao; Yu, Han-Qing

2017-01-01

Highlights: • Dependence of current generation on potentials by G. sulfurreducens is complex with the optimum at +0.1 V. • Unfavorable spatial distribution of biological activity within the biofilm at high potentials limits the current generation. • Same cytochrome c species are used for electron transfer in the biofilms developed at all potentials. - Abstract: Exoelectrogenic bacteria (EEB) play a central role in bioenergy recovery, biogeochemistry of elements, and polluting remediation. The electrochemical activity of EEB biofilm on electrode was proven to be dependent on the electrode potential, but the mechanism behind such a phenomenon is unclear. In this work, Geobacter sulfurreducens biofilms were developed at potentials ranging from −0.1 V to +0.6 V vs. standard hydrogen electrode to explore the profiles of potential regulation on G. sulfurreducens biofilm development and the electrochemical activity. We found that elevating the developing potential could improve the current generation by G. sulfurreducens biofilm until +0.1 V. At higher potentials less current was generated, although more biomass was formed on the electrode. The same cytochrome c species were synthesized for electron transfer in all biofilms, independent of the developing potential. Electrochemical experimental results and redox-sensitive staining imagings proved that the biofilms developed at +0.2 V–+0.4 V had greater cytochrome c contents and reducing capacities than the others. Current generation at high potentials was likely to be limited by both the metabolic rate and the electron transfer kinetics. These findings are useful for tuning the electrochemical activity of biofilm in catalyzing redox processes or generating electricity, which is crucial for the environmental and electrochemical application of EEB.

High Resolution AFM and Single-Cell Resonance Raman Spectroscopy of Geobacter sulfurreducens Biofilms Early in Growth

Energy Technology Data Exchange (ETDEWEB)

Lebedev, Nikolai, E-mail: nikolai.lebedev@nrl.navy.mil; Strycharz-Glaven, Sarah M.; Tender, Leonard M., E-mail: nikolai.lebedev@nrl.navy.mil [Center for Biomolecular Science and Engineering, US Naval Research Laboratory, Washington, DC (United States)

2014-08-21

Atomic force microscopy and confocal resonance Raman microscopy (CRRM) of single-cells were used to study the transition of anode-grown Geobacter sulfurreducens biofilms from lag phase (initial period of low current) to exponential phase (subsequent period of rapidly increasing current). Results reveal that lag phase biofilms consist of lone cells and tightly packed single-cell thick clusters crisscrossed with extracellular linear structures that appears to be comprised of nodules approximately 20 nm in diameter aligned end to end. By early exponential phase, cell clusters expand laterally and a second layer of closely packed cells begins to form on top of the first. Abundance of c-type cytochromes (c-Cyt) is threefold greater in two-cell thick regions than in one-cell thick regions. The results indicate that early biofilm growth involves two transformations. The first is from lone cells to two-dimensionally associated cells during lag phase when current remains low. This is accompanied by formation of extracellular linear structures. The second is from two- to three-dimensionally associated cells during early exponential phase when current begins to increase rapidly. This is accompanied by a dramatic increase in c-Cyt abundance.

High Resolution AFM and Single-Cell Resonance Raman Spectroscopy of Geobacter sulfurreducens Biofilms Early in Growth

International Nuclear Information System (INIS)

Lebedev, Nikolai; Strycharz-Glaven, Sarah M.; Tender, Leonard M.

2014-01-01

Atomic force microscopy and confocal resonance Raman microscopy (CRRM) of single-cells were used to study the transition of anode-grown Geobacter sulfurreducens biofilms from lag phase (initial period of low current) to exponential phase (subsequent period of rapidly increasing current). Results reveal that lag phase biofilms consist of lone cells and tightly packed single-cell thick clusters crisscrossed with extracellular linear structures that appears to be comprised of nodules approximately 20 nm in diameter aligned end to end. By early exponential phase, cell clusters expand laterally and a second layer of closely packed cells begins to form on top of the first. Abundance of c-type cytochromes (c-Cyt) is threefold greater in two-cell thick regions than in one-cell thick regions. The results indicate that early biofilm growth involves two transformations. The first is from lone cells to two-dimensionally associated cells during lag phase when current remains low. This is accompanied by formation of extracellular linear structures. The second is from two- to three-dimensionally associated cells during early exponential phase when current begins to increase rapidly. This is accompanied by a dramatic increase in c-Cyt abundance.

MacA is a second cytochrome c peroxidase of Geobacter sulfurreducens.

Science.gov (United States)

Seidel, Julian; Hoffmann, Maren; Ellis, Katie E; Seidel, Antonia; Spatzal, Thomas; Gerhardt, Stefan; Elliott, Sean J; Einsle, Oliver

2012-04-03

The metal-reducing δ-proteobacterium Geobacter sulfurreducens produces a large number of c-type cytochromes, many of which have been implicated in the transfer of electrons to insoluble metal oxides. Among these, the dihemic MacA was assigned a central role. Here we have produced G. sulfurreducens MacA by recombinant expression in Escherichia coli and have solved its three-dimensional structure in three different oxidation states. Sequence comparisons group MacA into the family of diheme cytochrome c peroxidases, and the protein indeed showed hydrogen peroxide reductase activity with ABTS(-2) as an electron donor. The observed K(M) was 38.5 ± 3.7 μM H(2)O(2) and v(max) was 0.78 ± 0.03 μmol of H(2)O(2)·min(-1)·mg(-1), resulting in a turnover number k(cat) = 0.46 · s(-1). In contrast, no Fe(III) reductase activity was observed. MacA was found to display electrochemical properties similar to other bacterial diheme peroxidases, in addition to the ability to electrochemically mediate electron transfer to the soluble cytochrome PpcA. Differences in activity between CcpA and MacA can be rationalized with structural variations in one of the three loop regions, loop 2, that undergoes conformational changes during reductive activation of the enzyme. This loop is adjacent to the active site heme and forms an open loop structure rather than a more rigid helix as in CcpA. For the activation of the protein, the loop has to displace the distal ligand to the active site heme, H93, in loop 1. A H93G variant showed an unexpected formation of a helix in loop 2 and disorder in loop 1, while a M297H variant that altered the properties of the electron transfer heme abolished reductive activation.

Geobacter sulfurreducens adapts to low electrode potential for extracellular electron transfer

International Nuclear Information System (INIS)

Peng, Luo; Zhang, Xiao-Ting; Yin, Jie; Xu, Shuo-Yuan; Zhang, Yong; Xie, De-Ti; Li, Zhen-Lun

2016-01-01

Microbial extracellular electron transfer (EET) occurring in natural and engineering processes is attracting increasing interests. While a meaningful question for bioenergetics, microbial physiology and microbial electrochemical systems; less is known about the lower limit of electron acceptor reduction potential for EET. It is also unclear how microbes adapt to weak electron acceptors. This study evaluated Geobacter sulfurreducens biofilms grown with an electrode poised at −0.25 V vs. SHE. This potential was found to be sufficient for microbial metabolism and proliferation. The turnover cyclic voltammetries found that these biofilms had a half-saturation potential of −0.242 ± 0.004 V, in contrast to −0.151 ± 0.003 V for that of the biofilms grown under 0.2 V. For the biofilms grown under 0.2 V, differential pulse voltammetry showed that the metabolic current was mediated by interfacial cofactors with mid-point potential around −0.16 V performing single-electron electron transfer (ET). The major electron conduits for the biofilms respiring under −0.25 V had mid-point potentials of −0.22 V or −0.26 V, which appeared to perform two-electron ET. Under the non-turnover condition, both biofilms showed similar patterns in voltammograms and the low-potential conduits largely disappeared for the biofilms grown under −0.25 V. Transcriptome analysis identified 17 cytochrome-c genes significantly up-regulated for the biofilms grown under −0.25 V, together with many other genes linked to the ET system. It was also noted that, lowering the poised potential from −0.25 V to −0.28 V (the fuel standard oxidation potential) did not fully inhibit microbial respiration.

Mechanisms for Fe(III) oxide reduction in sedimentary environments

Science.gov (United States)

Nevin, Kelly P.; Lovely, Derek R.

2002-01-01

Although it was previously considered that Fe(III)-reducing microorganisms must come into direct contact with Fe(III) oxides in order to reduce them, recent studies have suggested that electron-shuttling compounds and/or Fe(III) chelators, either naturally present or produced by the Fe(III)-reducing microorganisms themselves, may alleviate the need for the Fe(III) reducers to establish direct contact with Fe(III) oxides. Studies with Shewanella alga strain BrY and Fe(III) oxides sequestered within microporous beads demonstrated for the first time that this organism releases a compound(s) that permits electron transfer to Fe(III) oxides which the organism cannot directly contact. Furthermore, as much as 450 w M dissolved Fe(III) was detected in cultures of S. alga growing in Fe(III) oxide medium, suggesting that this organism releases compounds that can solublize Fe(III) from Fe(III) oxide. These results contrast with previous studies, which demonstrated that Geobacter metallireducens does not produce electron-shuttles or Fe(III) chelators. Some freshwater aquatic sediments and groundwaters contained compounds, which could act as electron shuttles by accepting electrons from G. metallireducens and then transferring the electrons to Fe(III). However, other samples lacked significant electron-shuttling capacity. Spectroscopic studies indicated that the electron-shuttling capacity of the waters was not only associated with the presence of humic substances, but water extracts of walnut, oak, and maple leaves contained electron-shuttling compounds did not appear to be humic substances. Porewater from a freshwater aquatic sediment and groundwater from a petroleum-contaminated aquifer contained dissolved Fe(III) (4-16 w M), suggesting that soluble Fe(III) may be available as an electron acceptor in some sedimentary environments. These results demonstrate that in order to accurately model the mechanisms for Fe(III) reduction in sedimentary environments it will be necessary

Use of Novel Reinforced Cation Exchange Membranes for Microbial Fuel Cells

International Nuclear Information System (INIS)

Kamaraj, Sathish-Kumar; Romano, Sergio Mollá; Moreno, Vicente Compañ; Poggi-Varaldo, H.M.; Solorza-Feria, O.

2015-01-01

This work has been focused on the synthesis and characterization of different blended membranes SPEEK-35PVA (Water), SPEEK-35PVA (DMAc) prepared by casting and nanofiber-reinforced proton exchange membranes Nafion-PVA-15, Nafion-PVA-23 and SPEEK/PVA-PVB. The two first reinforced membranes were made up of Nafion® polymer deposited between polyvinyl alcohol (PVA) nanofibers. The last composite membrane is considered because the PVA is a hydrophilic polymer which forms homogeneous blends with SPEEK suitable to obtain high proton conductivity, while the hydrophobic PVB can produce blends in a phase separation morphology in which very low water uptake can be found. The synthesized membranes showed an outstanding stability, high proton conductivity, and enhanced mechanical and barrier properties. The membranes were characterized in single chamber microbial fuel cells (SCMFCs) using electrochemically enriched high sodic saline hybrid H-inocula (Geobacter metallireducen, Desulfurivibrio alkaliphilus, and Marinobacter adhaerens) as biocatalyst. The best performance was obtained with Nafion-PVA-15 membrane, which achieved a maximum power density of 1053 mW/m 3 at a cell voltage of 340 mV and displayed the lowest total internal resistance (Rint ≈ 522 Ω). This result is in agreement with the low oxygen permeability and the moderate conductivity found in this kind of membranes. These results are encouraging towards obtaining high concentrated sodic saline model wastewater exploiting MFCs

Optimization of culture conditions and electricity generation using Geobacter sulfurreducens in a dual-chambered microbial fuel-cell

Energy Technology Data Exchange (ETDEWEB)

Kim, Mi-Sun; Lee, Yu-jin [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-343 (Korea, Republic of)

2010-12-15

The promise of generating electricity from the oxidation of organic substances using metal-reducing bacteria is drawing attention as an alternate form of bio-technology with positive environmental implications. In this study, we examined various experimental factors to obtain the maximum power output in a dual-chamber mediator-less microbial fuel-cell (MFC) using Geobacter sulfurreducens and acetate as an electron donor in a semi-continuous mode. The G. sulfurreducens culture conditions were optimized in a nutrient buffer containing 20 mM of acetate and 50 mM of fumarate at pH 6.8 and 30 C. For use in the MFC system, electrodes were made with carbon paper (area: 11.5 cm{sup 2}) and spaced 1.5 cm apart. Once the MFC was inoculated with the pre-cultured G. sulfurreducens in the anode chamber and while air was continuously sparged to the cathode chamber, the cells produced electricity stably over 60 days with the regular addition of 20 mM acetate, generating the maximum power density of 7 mW/m{sup 2} with a 5000 and ohm; load. The current output was significantly increased, by 1.6 times after 20 days of incubation under the same experimental conditions, when the carbon-paper anode was coated with carbon nanotubes. (author)

Control of nanoparticle size, reactivity and magnetic properties during the bioproduction of magnetite by Geobacter sulfurreducens

Energy Technology Data Exchange (ETDEWEB)

Byrne, J. M.; Telling, N. D.; Coker, V. S.; Pattrick, R. A. D.; Laan, G. van der; Arenholz, E.; Tuna, F.; Lloyd, J. R.

2011-08-02

The bioproduction of nano-scale magnetite by Fe(III)-reducing bacteria offers a potentially tunable, environmentally benign route to magnetic nanoparticle synthesis. Here, we demonstrate that it is possible to control the size of magnetite nanoparticles produced by Geobacter sulfurreducens, by adjusting the total biomass introduced at the start of the process. The particles have a narrow size distribution and can be controlled within the range of 10-50 nm. X-ray diffraction analysis indicates that controlled production of a number of different biominerals is possible via this method including goethite, magnetite and siderite, but their formation is strongly dependent upon the rate of Fe(III) reduction and total concentration and rate of Fe(II) produced by the bacteria during the reduction process. Relative cation distributions within the structure of the nanoparticles has been investigated by X-ray magnetic circular dichroism and indicates the presence of a highly reduced surface layer which is not observed when magnetite is produced through abiotic methods. The enhanced Fe(II)-rich surface, combined with small particle size, has important environmental applications such as in the reductive bioremediation of organics, radionuclides and metals. In the case of Cr(VI), as a model high-valence toxic metal, optimised biogenic magnetite is able to reduce and sequester the toxic hexavalent chromium very efficiently in the less harmful trivalent form.

pH, redox potential and local biofilm potential microenvironments within Geobacter sulfurreducens biofilms and their roles in electron transfer.

Science.gov (United States)

Babauta, Jerome T; Nguyen, Hung Duc; Harrington, Timothy D; Renslow, Ryan; Beyenal, Haluk

2012-10-01

The limitation of pH inside electrode-respiring biofilms is a well-known concept. However, little is known about how pH and redox potential are affected by increasing current inside biofilms respiring on electrodes. Quantifying the variations in pH and redox potential with increasing current is needed to determine how electron transfer is tied to proton transfer within the biofilm. In this research, we quantified pH and redox potential variations in electrode-respiring Geobacter sulfurreducens biofilms as a function of respiration rates, measured as current. We also characterized pH and redox potential at the counter electrode. We concluded that (1) pH continued to decrease in the biofilm through different growth phases, showing that the pH is not always a limiting factor in a biofilm and (2) decreasing pH and increasing redox potential at the biofilm electrode were associated only with the biofilm, demonstrating that G. sulfurreducens biofilms respire in a unique internal environment. Redox potential inside the biofilm was also compared to the local biofilm potential measured by a graphite microelectrode, where the tip of the microelectrode was allowed to acclimatize inside the biofilm. Copyright © 2012 Wiley Periodicals, Inc.

Mechanisms for the reduction of actinide ions by Geobacter sulfurreducens

International Nuclear Information System (INIS)

Renshaw, J.C.; Livens, F.R.; May, I.; Lloyd, J.R.

2005-01-01

Full text of publication follows: Three of the most problematic radioactive contaminants are the actinide elements uranium, neptunium and plutonium. All three pose considerable long-term environmental risks. The most stable environmental oxidation states of uranium and neptunium are VI and V, respectively, as the di-oxo cations [UO 2 ] 2+ and [NpO 2 ] + ; both are highly soluble and so are relatively mobile and biologically available in the environment. In similar conditions, plutonium mainly exists as Pu(IV), which forms a highly insoluble hydrous oxide, although is also environmentally stable in the more soluble III, V and VI oxidation states. The bio-reduction of U(VI) by anaerobic subsurface microorganisms has been the focus of much recent interest. Both Fe(III)- and sulfate-reducing bacteria have been shown to reduce soluble [U VI O 2 ] 2+ to insoluble U IV O 2 , with c-type cytochromes involved in electron transfer to the actinide. Such transformations offer a strategy for the bio-remediation of uranium contaminated groundwater and a potential mechanism for the bio-deposition of uranium ores. The mechanism of U(VI). reduction has important implications for the potential microbial reduction of transuranic elements with environmentally stable lower oxidation states. Reduction of mobile 237 Np(V) to Np(IV) and subsequent precipitation may be advantageous whilst remobilization of immobile Pu(IV) as more soluble Pu(III) species could have important environmental implications. Conversely, selective reduction might allow targeting of particular radionuclide species. The model anaerobic bacterium Geobacter sulfurreducens is typical of those found in contaminated subsurface environments and has been shown to reduce soluble [U VI O 2 ] 2+ to insoluble U IV O 2 . In the course of this study we use X-ray absorption spectroscopy (XAS) to show that G. sulfurreducens reduces U(VI) by a one-electron reduction, forming an unstable [UO 2 ] + species which subsequently

A defined co-culture of Geobacter sulfurreducens and Escherichia coli in a membrane-less microbial fuel cell.

Science.gov (United States)

Bourdakos, Nicholas; Marsili, Enrico; Mahadevan, Radhakrishnan

2014-04-01

Wastewater-fed microbial fuel cells (MFCs) are a promising technology to treat low-organic carbon wastewater and recover part of the chemical energy in wastewater as electrical power. However, the interactions between electrochemically active and fermentative microorganisms cannot be easily studied in wastewater-fed MFCs because of their complex microbial communities. Defined co-culture MFCs provide a detailed understanding of such interactions. In this study, we characterize the extracellular metabolites in laboratory-scale membrane-less MFCs inoculated with Geobacter sulfurreducens and Escherichia coli co-culture and compare them with pure culture MFCs. G. sulfurreducens MFCs are sparged to maintain anaerobic conditions, while co-culture MFCs rely on E. coli for oxygen removal. G. sulfurreducens MFCs have a power output of 128 mW m(-2) , compared to 63 mW m(-2) from the co-culture MFCs. Analysis of metabolites shows that succinate production in co-culture MFCs decreases current production by G. sulfurreducens and that the removal of succinate is responsible for the increased current density in the late co-culture MFCs. Interestingly, pH adjustment is not required for co-culture MFCs but a base addition is necessary for E. coli MFCs and cultures in vials. Our results show that defined co-culture MFCs provide clear insights into metabolic interactions among bacteria while maintaining a low operational complexity. © 2013 Wiley Periodicals, Inc.

Fate of Cd during microbial Fe(III) mineral reduction by a novel and Cd-tolerant Geobacter species.

Science.gov (United States)

Muehe, E Marie; Obst, Martin; Hitchcock, Adam; Tyliszczak, Tolek; Behrens, Sebastian; Schröder, Christian; Byrne, James M; Michel, F Marc; Krämer, Ute; Kappler, Andreas

2013-12-17

Fe(III) (oxyhydr)oxides affect the mobility of contaminants in the environment by providing reactive surfaces for sorption. This includes the toxic metal cadmium (Cd), which prevails in agricultural soils and is taken up by crops. Fe(III)-reducing bacteria can mobilize such contaminants by Fe(III) mineral dissolution or immobilize them by sorption to or coprecipitation with secondary Fe minerals. To date, not much is known about the fate of Fe(III) mineral-associated Cd during microbial Fe(III) reduction. Here, we describe the isolation of a new Geobacter sp. strain Cd1 from a Cd-contaminated field site, where the strain accounts for 10(4) cells g(-1) dry soil. Strain Cd1 reduces the poorly crystalline Fe(III) oxyhydroxide ferrihydrite in the presence of at least up to 112 mg Cd L(-1). During initial microbial reduction of Cd-loaded ferrihydrite, sorbed Cd was mobilized. However, during continuous microbial Fe(III) reduction, Cd was immobilized by sorption to and/or coprecipitation within newly formed secondary minerals that contained Ca, Fe, and carbonate, implying the formation of an otavite-siderite-calcite (CdCO3-FeCO3-CaCO3) mixed mineral phase. Our data shows that microbially mediated turnover of Fe minerals affects the mobility of Cd in soils, potentially altering the dynamics of Cd uptake into food or phyto-remediating plants.

The genome of Pelobacter carbinolicus reveals surprising metabolic capabilities and physiological features

Energy Technology Data Exchange (ETDEWEB)

Aklujkar, Muktak [University of Massachusetts, Amherst; Haveman, Shelley [University of Massachusetts, Amherst; DiDonatoJr, Raymond [University of Massachusetts, Amherst; Chertkov, Olga [Los Alamos National Laboratory (LANL); Han, Cliff [Los Alamos National Laboratory (LANL); Land, Miriam L [ORNL; Brown, Peter [University of Massachusetts, Amherst; Lovley, Derek [University of Massachusetts, Amherst

2012-01-01

Background: The bacterium Pelobacter carbinolicus is able to grow by fermentation, syntrophic hydrogen/formate transfer, or electron transfer to sulfur from short-chain alcohols, hydrogen or formate; it does not oxidize acetate and is not known to ferment any sugars or grow autotrophically. The genome of P. carbinolicus was sequenced in order to understand its metabolic capabilities and physiological features in comparison with its relatives, acetate-oxidizing Geobacter species. Results: Pathways were predicted for catabolism of known substrates: 2,3-butanediol, acetoin, glycerol, 1,2-ethanediol, ethanolamine, choline and ethanol. Multiple isozymes of 2,3-butanediol dehydrogenase, ATP synthase and [FeFe]-hydrogenase were differentiated and assigned roles according to their structural properties and genomic contexts. The absence of asparagine synthetase and the presence of a mutant tRNA for asparagine encoded among RNA-active enzymes suggest that P. carbinolicus may make asparaginyl-tRNA in a novel way. Catabolic glutamate dehydrogenases were discovered, implying that the tricarboxylic acid (TCA) cycle can function catabolically. A phosphotransferase system for uptake of sugars was discovered, along with enzymes that function in 2,3-butanediol production. Pyruvate: ferredoxin/flavodoxin oxidoreductase was identified as a potential bottleneck in both the supply of oxaloacetate for oxidation of acetate by the TCA cycle and the connection of glycolysis to production of ethanol. The P. carbinolicus genome was found to encode autotransporters and various appendages, including three proteins with similarity to the geopilin of electroconductive nanowires. Conclusions: Several surprising metabolic capabilities and physiological features were predicted from the genome of P. carbinolicus, suggesting that it is more versatile than anticipated.

Abundance of the multiheme c-type cytochrome OmcB increases in outer biofilm layers of electrode-grown Geobacter sulfurreducens.

Directory of Open Access Journals (Sweden)

Camille S Stephen

Full Text Available When Geobacter sulfurreducens utilizes an electrode as its electron acceptor, cells embed themselves in a conductive biofilm tens of microns thick. While environmental conditions such as pH or redox potential have been shown to change close to the electrode, less is known about the response of G. sulfurreducens to growth in this biofilm environment. To investigate whether respiratory protein abundance varies with distance from the electrode, antibodies against an outer membrane multiheme cytochrome (OmcB and cytoplasmic acetate kinase (AckA were used to determine protein localization in slices spanning ∼25 µm-thick G. sulfurreducens biofilms growing on polished electrodes poised at +0.24 V (vs. Standard Hydrogen Electrode. Slices were immunogold labeled post-fixing, imaged via transmission electron microscopy, and digitally reassembled to create continuous images allowing subcellular location and abundance per cell to be quantified across an entire biofilm. OmcB was predominantly localized on cell membranes, and 3.6-fold more OmcB was detected on cells 10-20 µm distant from the electrode surface compared to inner layers (0-10 µm. In contrast, acetate kinase remained constant throughout the biofilm, and was always associated with the cell interior. This method for detecting proteins in intact conductive biofilms supports a model where the utilization of redox proteins changes with depth.

Contrasting Effects of Dissolved Organic Matter on Mercury Methylation by Geobacter sulfurreducens PCA and Desulfovibrio desulfuricans ND132.

Science.gov (United States)

Zhao, Linduo; Chen, Hongmei; Lu, Xia; Lin, Hui; Christensen, Geoff A; Pierce, Eric M; Gu, Baohua

2017-09-19

Natural dissolved organic matter (DOM) affects mercury (Hg) redox reactions and anaerobic microbial methylation in the environment. Several studies have shown that DOM can enhance Hg methylation, especially under sulfidic conditions, whereas others show that DOM inhibits Hg methylation due to strong Hg-DOM complexation. In this study, we investigated and compared the effects of DOM on Hg methylation by an iron-reducing bacterium Geobacter sulfurreducens PCA and a sulfate-reducing bacterium Desulfovibrio desulfuricans ND132 under nonsulfidic conditions. The methylation experiment was performed with washed cells either in the absence or presence of DOM or glutathione, both of which form strong complexes with Hg via thiol-functional groups. DOM was found to greatly inhibit Hg methylation by G. Sulfurreducens PCA but enhance Hg methylation by D. desulfuricans ND132 cells with increasing DOM concentration. These strain-dependent opposing effects of DOM were also observed with glutathione, suggesting that thiols in DOM likely played an essential role in affecting microbial Hg uptake and methylation. Additionally, DOM and glutathione greatly decreased Hg sorption by G. sulfurreducens PCA but showed little effect on D. desulfuricans ND132 cells, demonstrating that ND132 has a higher affinity to sorb or take up Hg than the PCA strain. These observations indicate that DOM effects on Hg methylation are bacterial strain specific, depend on the DOM:Hg ratio or site-specific conditions, and may thus offer new insights into the role of DOM in methylmercury production in the environment.

Biological Recovery of Platinum Complexes from Diluted Aqueous Streams by Axenic Cultures.

Directory of Open Access Journals (Sweden)

Synthia Maes

Full Text Available The widespread use of platinum in high-tech and catalytic applications has led to the production of diverse Pt loaded wastewaters. Effective recovery strategies are needed for the treatment of low concentrated waste streams to prevent pollution and to stimulate recovery of this precious resource. The biological recovery of five common environmental Pt-complexes was studied under acidic conditions; the chloro-complexes PtCl42- and PtCl62-, the amine-complex Pt(NH34Cl2 and the pharmaceutical complexes cisplatin and carboplatin. Five bacterial species were screened on their platinum recovery potential; the Gram-negative species Shewanella oneidensis MR-1, Cupriavidus metallidurans CH34, Geobacter metallireducens, and Pseudomonas stutzeri, and the Gram-positive species Bacillus toyonensis. Overall, PtCl42- and PtCl62- were completely recovered by all bacterial species while only S. oneidensis and C. metallidurans were able to recover cisplatin quantitatively (99%, all in the presence of H2 as electron donor at pH 2. Carboplatin was only partly recovered (max. 25% at pH 7, whereas no recovery was observed in the case of the Pt-tetraamine complex. Transmission electron microscopy (TEM revealed the presence of both intra- and extracellular platinum particles. Flow cytometry based microbial viability assessment demonstrated the decrease in number of intact bacterial cells during platinum reduction and indicated C. metallidurans to be the most resistant species. This study showed the effective and complete biological recovery of three common Pt-complexes, and estimated the fate and transport of the Pt-complexes in wastewater treatment plants and the natural environment.

Subsurface clade of Geobacteraceae that predominates in a diversity of Fe(III)-reducing subsurface environments

Science.gov (United States)

Holmes, Dawn E.; O'Neil, Regina A.; Vrionis, Helen A.; N'Guessan, Lucie A.; Ortiz-Bernad, Irene; Larrahondo, Maria J.; Adams, Lorrie A.; Ward, Joy A.; Nicoll , Julie S.; Nevin, Kelly P.; Chavan, Milind A.; Johnson, Jessica P.; Long, Philip E.; Lovely, Derek R.

2007-01-01

There are distinct differences in the physiology of Geobacter species available in pure culture. Therefore, to understand the ecology of Geobacter species in subsurface environments, it is important to know which species predominate. Clone libraries were assembled with 16S rRNA genes and transcripts amplified from three subsurface environments in which Geobacter species are known to be important members of the microbial community: (1) a uranium-contaminated aquifer located in Rifle, CO, USA undergoing in situ bioremediation; (2) an acetate-impacted aquifer that serves as an analog for the long-term acetate amendments proposed for in situ uranium bioremediation and (3) a petroleum-contaminated aquifer in which Geobacter species play a role in the oxidation of aromatic hydrocarbons coupled with the reduction of Fe(III). The majority of Geobacteraceae 16S rRNA sequences found in these environments clustered in a phylogenetically coherent subsurface clade, which also contains a number of Geobacter species isolated from subsurface environments. Concatamers constructed with 43 Geobacter genes amplified from these sites also clustered within this subsurface clade. 16S rRNA transcript and gene sequences in the sediments and groundwater at the Rifle site were highly similar, suggesting that sampling groundwater via monitoring wells can recover the most active Geobacter species. These results suggest that further study of Geobacter species in the subsurface clade is necessary to accurately model the behavior of Geobacter species during subsurface bioremediation of metal and organic contaminants.

A novel Geobacteraceae-specific outer membrane protein J (OmpJ is essential for electron transport to Fe (III and Mn (IV oxides in Geobacter sulfurreducens

Directory of Open Access Journals (Sweden)

Schiffer Marianne

2005-07-01

Full Text Available Abstract Background Metal reduction is thought to take place at or near the bacterial outer membrane and, thus, outer membrane proteins in the model dissimilatory metal-reducing organism Geobacter sulfurreducens are of interest to understand the mechanisms of Fe(III reduction in the Geobacter species that are the predominant Fe(III reducers in many environments. Previous studies have implicated periplasmic and outer membrane cytochromes in electron transfer to metals. Here we show that the most abundant outer membrane protein of G. sulfurreducens, OmpJ, is not a cytochrome yet it is required for metal respiration. Results When outer membrane proteins of G. sulfurreducens were separated via SDS-PAGE, one protein, designated OmpJ (outer membrane protein J, was particularly abundant. The encoding gene, which was identified from mass spectrometry analysis of peptide fragments, is present in other Geobacteraceae, but not in organisms outside this family. The predicted localization and structure of the OmpJ protein suggested that it was a porin. Deletion of the ompJ gene in G. sulfurreducens produced a strain that grew as well as the wild-type strain with fumarate as the electron acceptor but could not grow with metals, such as soluble or insoluble Fe (III and insoluble Mn (IV oxide, as the electron acceptor. The heme c content in the mutant strain was ca. 50% of the wild-type and there was a widespread loss of multiple cytochromes from soluble and membrane fractions. Transmission electron microscopy analyses of mutant cells revealed an unusually enlarged periplasm, which is likely to trigger extracytoplasmic stress response mechanisms leading to the degradation of periplasmic and/or outer membrane proteins, such as cytochromes, required for metal reduction. Thus, the loss of the capacity for extracellular electron transport in the mutant could be due to the missing c-type cytochromes, or some more direct, but as yet unknown, role of OmpJ in metal

STRUCTURE AND FUNCTION OF SUBSURFACE MICROBIAL COMMUNITIES AFFECTING RADIONUCLIDE TRANSPORT AND BIOIMMOBILIZATION

Energy Technology Data Exchange (ETDEWEB)

Joel E. Kostka; Lee Kerkhof; Kuk-Jeong Chin; Martin Keller; Joseph W. Stucki

2011-06-15

(comprising 50% to 100% of rRNA detected). (2) We demonstrated for the first time that the function of microbial communities can be quantified in subsurface sediments using messenger RNA assays (molecular proxies) under in situ conditions. (3) Active Geobacteraceae were identified and phylogenetically characterized from the cDNA of messenger RNA extracted from ORFRC subsurface sediment cores. Multiple clone sequences were retrieved from G. uraniireducens, G. daltonii, and G. metallireducens. (4) Results show that Geobacter strain FRC-32 is capable of growth on benzoate, toluene and benzene as the electron donor, thereby providing evidence that this strain is physiologically distinct from other described members of the subsurface Geobacter clade. (5) Fe(III)-reducing bacteria transform structural Fe in clay minerals from their layer edges rather than from their basal surfaces.

Functional environmental proteomics: elucidating the role of a c-type cytochrome abundant during uranium bioremediation.

Science.gov (United States)

Yun, Jiae; Malvankar, Nikhil S; Ueki, Toshiyuki; Lovley, Derek R

2016-02-01

Studies with pure cultures of dissimilatory metal-reducing microorganisms have demonstrated that outer-surface c-type cytochromes are important electron transfer agents for the reduction of metals, but previous environmental proteomic studies have typically not recovered cytochrome sequences from subsurface environments in which metal reduction is important. Gel-separation, heme-staining and mass spectrometry of proteins in groundwater from in situ uranium bioremediation experiments identified a putative c-type cytochrome, designated Geobacter subsurface c-type cytochrome A (GscA), encoded within the genome of strain M18, a Geobacter isolate previously recovered from the site. Homologs of GscA were identified in the genomes of other Geobacter isolates in the phylogenetic cluster known as subsurface clade 1, which predominates in a diversity of Fe(III)-reducing subsurface environments. Most of the gscA sequences recovered from groundwater genomic DNA clustered in a tight phylogenetic group closely related to strain M18. GscA was most abundant in groundwater samples in which Geobacter sp. predominated. Expression of gscA in a strain of Geobacter sulfurreducens that lacked the gene for the c-type cytochrome OmcS, thought to facilitate electron transfer from conductive pili to Fe(III) oxide, restored the capacity for Fe(III) oxide reduction. Atomic force microscopy provided evidence that GscA was associated with the pili. These results demonstrate that a c-type cytochrome with an apparent function similar to that of OmcS is abundant when Geobacter sp. are abundant in the subsurface, providing insight into the mechanisms for the growth of subsurface Geobacter sp. on Fe(III) oxide and suggesting an approach for functional analysis of other Geobacter proteins found in the subsurface.

In-Situ Survival Mechanisms of U and Tc Reducing Bacteria in Contaminated Sediments

International Nuclear Information System (INIS)

Krumholz, Lee R.

2005-01-01

periplasmic space and outer membrane associated proteins. Through blast search analysis, we also showed that 81 out of 94 proteins shown to be important in sediment survival have homologs in D. vulgaris, 70 have homologs in Geobacter metallireducens, and 69 have homologs in Geobacter sulfurreducens PCA. Some interesting proteins include ribonucleotide reductase and chemotaxis related proteins. Ribonucleotide reductase catalyzes the reductive synthesis of deoxyribonucleotides from their corresponding ribonucleotides, providing the precursors necessary for DNA synthesis. Two ribonucleotide reductase genes (nrdE, nrdD) were found to be essential for G20 survival in the sediment, but not essential for growth in the lactate-sulfate medium. Bacterial methyl-accepting chemotaxis proteins (MCP) respond to changes in the concentration of attractants and repellents in the environment

Novel processes for anaerobic sulfate production from elemental sulfur by sulfate-reducing bacteria

Science.gov (United States)

Lovley, D.R.; Phillips, E.J.P.

1994-01-01

Sulfate reducers and related organisms which had previously been found to reduce Fe(III) with H2 or organic electron donors oxidized S0 to sulfate when Mn(IV) was provided as an electron acceptor. Organisms catalyzing this reaction in washed cell suspensions included Desulfovibrio desulfuricans, Desulfomicrobium baculatum. Desulfobacterium autotrophicum, Desulfuromonas acetoxidans, and Geobacter metallireducens. These organisms produced little or no sulfate from S0 with Fe(III) as a potential electron acceptor or in the absence of an electron acceptor. In detailed studies with Desulfovibrio desulfuricans, the stoichiometry of sulfate and Mn(II) production was consistent with the reaction S0 + 3 MnO2 + 4H+ ???SO42- + 3Mn(II) + 2H2O. None of the organisms evaluated could be grown with S0 as the sole electron donor and Mn(IV) as the electron acceptor. In contrast to the other sulfate reducers evaluated, Desulfobulbus propionicus produced sulfate from S0 in the absence of an electron acceptor and Fe(III) oxide stimulated sulfate production. Sulfide also accumulated in the absence of Mn(IV) or Fe(III). The stoichiometry of sulfate and sulfide production indicated that Desulfobulbus propionicus disproportionates S0 as follows: 4S0 + 4H2O???SO42- + 3HS- + 5 H+. Growth of Desulfobulbus propionicus with S0 as the electron donor and Fe(III) as a sulfide sink and/or electron acceptor was very slow. The S0 oxidation coupled to Mn(IV) reduction described here provides a potential explanation for the Mn(IV)-dependent sulfate production that previous studies have observed in anoxic marine sediments. Desulfobulbus propionicus is the first example of a pure culture known to disproportionate S0.

Changes in phosphorylation of adenosine phosphate and redox state of nicotinamide-adenine dinucleotide (phosphate) in Geobacter sulfurreducens in response to electron acceptor and anode potential variation

KAUST Repository

Rose, Nicholas D.; Regan, John M.

2015-01-01

© 2015 Elsevier B.V. Geobacter sulfurreducens is one of the dominant bacterial species found in biofilms growing on anodes in bioelectrochemical systems. The intracellular concentrations of reduced and oxidized forms of nicotinamide-adenine dinucleotide (NADH and NAD⁺, respectively) and nicotinamide-adenine dinucleotide phosphate (NADPH and NADP⁺, respectively) as well as adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP) were measured in G. sulfurreducens using fumarate, Fe(III)-citrate, or anodes poised at different potentials (110, 10, -90, and -190mV (vs. SHE)) as the electron acceptor. The ratios of CNADH/CNAD+ (0.088±0.022) and CNADPH/CNADP+ (0.268±0.098) were similar under all anode potentials tested and with Fe(III)-citrate (reduced extracellularly). Both ratios significantly increased with fumarate as the electron acceptor (0.331±0.094 for NAD and 1.96±0.37 for NADP). The adenylate energy charge (the fraction of phosphorylation in intracellular adenosine phosphates) was maintained near 0.47 under almost all conditions. Anode-growing biofilms demonstrated a significantly higher molar ratio of ATP/ADP relative to suspended cultures grown on fumarate or Fe(III)-citrate. These results provide evidence that the cellular location of reduction and not the redox potential of the electron acceptor controls the intracellular redox potential in G. sulfurreducens and that biofilm growth alters adenylate phosphorylation.

Changes in phosphorylation of adenosine phosphate and redox state of nicotinamide-adenine dinucleotide (phosphate) in Geobacter sulfurreducens in response to electron acceptor and anode potential variation

KAUST Repository

Rose, Nicholas D.

2015-12-01

© 2015 Elsevier B.V. Geobacter sulfurreducens is one of the dominant bacterial species found in biofilms growing on anodes in bioelectrochemical systems. The intracellular concentrations of reduced and oxidized forms of nicotinamide-adenine dinucleotide (NADH and NAD⁺, respectively) and nicotinamide-adenine dinucleotide phosphate (NADPH and NADP⁺, respectively) as well as adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP) were measured in G. sulfurreducens using fumarate, Fe(III)-citrate, or anodes poised at different potentials (110, 10, -90, and -190mV (vs. SHE)) as the electron acceptor. The ratios of CNADH/CNAD+ (0.088±0.022) and CNADPH/CNADP+ (0.268±0.098) were similar under all anode potentials tested and with Fe(III)-citrate (reduced extracellularly). Both ratios significantly increased with fumarate as the electron acceptor (0.331±0.094 for NAD and 1.96±0.37 for NADP). The adenylate energy charge (the fraction of phosphorylation in intracellular adenosine phosphates) was maintained near 0.47 under almost all conditions. Anode-growing biofilms demonstrated a significantly higher molar ratio of ATP/ADP relative to suspended cultures grown on fumarate or Fe(III)-citrate. These results provide evidence that the cellular location of reduction and not the redox potential of the electron acceptor controls the intracellular redox potential in G. sulfurreducens and that biofilm growth alters adenylate phosphorylation.

ORF Alignment: NC_002939 [GENIUS II[Archive

Lifescience Database Archive (English)

Full Text Available NC_002939 gi|39996821 >1v7zA 3 252 1 232 3e-42 ... ref|NP_952772.1| creatinine amidoh...ydrolase [Geobacter sulfurreducens PCA] ... gb|AAR35099.1| creatinine amidohydrolase [Geobacter ...

NCBI nr-aa BLAST: CBRC-GACU-16-0048 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-GACU-16-0048 ref|YP_001231116.1| lipopolysaccharide biosynthesis protein [Geobacter uranium...reducens Rf4] gb|ABQ26543.1| lipopolysaccharide biosynthesis protein [Geobacter uraniumreducens Rf4] YP_001231116.1 0.14 18% ...

NCBI nr-aa BLAST: CBRC-XTRO-01-0152 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-XTRO-01-0152 ref|YP_001230889.1| inner-membrane translocator [Geobacter uranium...reducens Rf4] gb|ABQ26316.1| inner-membrane translocator [Geobacter uraniumreducens Rf4] YP_001230889.1 3e-34 36% ...

NCBI nr-aa BLAST: CBRC-LAFR-01-0322 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-LAFR-01-0322 ref|YP_001231537.1| carbon starvation protein CstA [Geobacter uranium...reducens Rf4] gb|ABQ26964.1| carbon starvation protein CstA [Geobacter uraniumreducens Rf4] YP_001231537.1 0.96 31% ...

Magnetite Compensates for the Lack of a Pilin-Associated c-Type Cytochrome in Extracellular Electron Exchange

DEFF Research Database (Denmark)

Liu, Fanghua; Rotaru, Amelia-Elena; Shrestha, Pravin

2015-01-01

investigation revealed that magnetite attached to the electrically conductive pili of Geobacter species in a manner reminiscent of the association of the multi-heme c-type cytochrome OmcS with the pili of Geobacter sulfurreducens. Magnetite conferred extracellular electron capabilities on an Omc...

NCBI nr-aa BLAST: CBRC-DMEL-04-0042 [SEVENS

Lifescience Database Archive (English)

Full Text Available ike protein [Geobacter uraniumreducens Rf4] gb|ABQ26219.1| Uncharacterized membrane-associated protein-like protein [Geobacter uraniumreducens Rf4] YP_001230792.1 4.3 28% ... ...CBRC-DMEL-04-0042 ref|YP_001230792.1| Uncharacterized membrane-associated protein-l

NCBI nr-aa BLAST: CBRC-DYAK-02-0022 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-DYAK-02-0022 ref|YP_001232964.1| ATP synthase F0, A subunit [Geobacter uranium...reducens Rf4] gb|ABQ28391.1| ATP synthase F0, A subunit [Geobacter uraniumreducens Rf4] YP_001232964.1 0.85 25% ...

Carboxydotrophic growth of

NARCIS (Netherlands)

Geelhoed, J.; Henstra, A.M.; Stams, A.J.M.

2016-01-01

This study shows that Geobacter sulfurreducensgrows on carbon monoxide (CO) as electron donor with fumarateas electron acceptor. Geobacter sulfurreducens wastolerant to high CO levels, with up to 150 kPa in the headspacetested. During growth, hydrogen was detected in very slightamounts (~5 Pa). In

NCBI nr-aa BLAST: CBRC-DNOV-01-1221 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-DNOV-01-1221 ref|YP_001230970.1| UBA/THIF-type NAD/FAD binding protein [Geobacter uranium...reducens Rf4] gb|ABQ26397.1| UBA/THIF-type NAD/FAD binding protein [Geobacter uraniumreducens Rf4] YP_001230970.1 3.9 50% ...

NCBI nr-aa BLAST: CBRC-BTAU-01-2822 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-BTAU-01-2822 ref|YP_001230511.1| lipolytic enzyme, G-D-S-L family [Geobacter uranium...reducens Rf4] gb|ABQ25938.1| lipolytic enzyme, G-D-S-L family [Geobacter uraniumreducens Rf4] YP_001230511.1 0.001 40% ...

NCBI nr-aa BLAST: CBRC-HSAP-11-0402 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-HSAP-11-0402 ref|YP_001232090.1| heavy metal efflux pump, CzcA family [Geobacter uranium...reducens Rf4] gb|ABQ27517.1| heavy metal efflux pump, CzcA family [Geobacter uraniumreducens Rf4] YP_001232090.1 1.2 30% ...

Influence of heterogeneous ammonium availability on bacterial community structure and the expression of nitrogen fixation and ammonium transporter genes during in situ bioremediation of uranium-contaminated groundwater

Energy Technology Data Exchange (ETDEWEB)

Mouser, P.J.; N' Guessan, A.L.; Elifantz, H.; Holmes, D.E.; Williams, K.H.; Wilkins, M.J.; Long, P.E.; Lovley, D.R.

2009-04-01

The impact of ammonium availability on microbial community structure and the physiological status and activity of Geobacter species during in situ bioremediation of uranium-contaminated groundwater was evaluated. Ammonium concentrations varied by as much as two orders of magnitude (<4 to 400 {micro}M) across the study site. Analysis of 16S rRNA gene sequences suggested that ammonium influenced the composition of the microbial community prior to acetate addition with Rhodoferax species predominating over Geobacter species at the site with the highest ammonium, and Dechloromonas species dominating at sites with lowest ammonium. However, once acetate was added, and dissimilatory metal reduction was stimulated, Geobacter species became the predominant organisms at all locations. Rates of U(VI) reduction appeared to be more related to the concentration of acetate that was delivered to each location rather than the amount of ammonium available in the groundwater. In situ mRNA transcript abundance of the nitrogen fixation gene, nifD, and the ammonium importer gene, amtB, in Geobacter species indicated that ammonium was the primary source of nitrogen during in situ uranium reduction, and that the abundance of amtB transcripts was inversely correlated to ammonium levels across all sites examined. These results suggest that nifD and amtB expression by subsurface Geobacter species are closely regulated in response to ammonium availability to ensure an adequate supply of nitrogen while conserving cell resources. Thus, quantifying nifD and amtB expression appears to be a useful approach for monitoring the nitrogen-related physiological status of Geobacter species in subsurface environments during bioremediation. This study also emphasizes the need for more detailed analysis of geochemical/physiological interactions at the field scale, in order to adequately model subsurface microbial processes.

Global Proteome Response to Deletion of Genes Related to Mercury Methylation and Dissimilatory Metal Reduction Reveals Changes in Respiratory Metabolism in Geobacter sulfurreducens PCA.

Science.gov (United States)

Qian, Chen; Johs, Alexander; Chen, Hongmei; Mann, Benjamin F; Lu, Xia; Abraham, Paul E; Hettich, Robert L; Gu, Baohua

2016-10-07

Geobacter sulfurreducens PCA can reduce, sorb, and methylate mercury (Hg); however, the underlying biochemical mechanisms of these processes and interdependent metabolic pathways remain unknown. In this study, shotgun proteomics was used to compare global proteome profiles between wild-type G. sulfurreducens PCA and two mutant strains: a ΔhgcAB mutant, which is deficient in two genes known to be essential for Hg methylation and a ΔomcBESTZ mutant, which is deficient in five outer membrane c-type cytochromes and thus impaired in its ability for dissimilatory metal ion reduction. We were able to delineate the global response of G. sulfurreducens PCA in both mutants and identify cellular networks and metabolic pathways that were affected by the loss of these genes. Deletion of hgcAB increased the relative abundances of proteins implicated in extracellular electron transfer, including most of the c-type cytochromes, PilA-C, and OmpB, and is consistent with a previously observed increase in Hg reduction in the ΔhgcAB mutant. Deletion of omcBESTZ was found to significantly increase relative abundances of various methyltransferases, suggesting that a loss of dissimilatory reduction capacity results in elevated activity among one-carbon (C1) metabolic pathways and thus increased methylation. We show that G. sulfurreducens PCA encodes only the folate branch of the acetyl-CoA pathway, and proteins associated with the folate branch were found at lower abundance in the ΔhgcAB mutant strain than the wild type. This observation supports the hypothesis that the function of HgcA and HgcB is linked to C1 metabolism through the folate branch of the acetyl-CoA pathway by providing methyl groups required for Hg methylation.

Online feature selection with streaming features.

Science.gov (United States)

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

Direct Involvement of ombB, omaB and omcB Genes in Extracellular Reduction of Fe(III by Geobacter sulfurreducens PCA

Directory of Open Access Journals (Sweden)

Yimo eLiu

2015-10-01

Full Text Available The tandem gene clusters orfR-ombB-omaB-omcB and orfS-ombC-omaC-omcC of the metal-reducing bacterium Geobacter sulfurreducens PCA are responsible for trans-outer membrane electron transfer during extracellular reduction of Fe(III-citrate and ferrihydrite [a poorly crystalline Fe(III oxide]. Each gene cluster encodes a putative transcriptional factor (OrfR/OrfS, a porin-like outer-membrane protein (OmbB/OmbC, a periplasmic c-type cytochrome (c-Cyt, OmaB/OmaC and an outer-membrane c-Cyt (OmcB/OmcC. The individual roles of OmbB, OmaB and OmcB in extracellular reduction of Fe(III, however, have remained either uninvestigated or controversial. Here, we showed that replacements of ombB, omaB, omcB and ombB-omaB with an antibiotic gene in the presence of ombC-omaC-omcC had no impact on reduction of Fe(III-citrate by G. sulfurreducens PCA. Disruption of ombB, omaB, omcB and ombB-omaB in the absence of ombC-omaC-omcC, however, severely impaired the bacterial ability to reduce Fe(III-citrate as well as ferrihydrite. These results unequivocally demonstrate an overlapping role of ombB-omaB-omcB and ombC-omaC-omcC in extracellular Fe(III reduction by G. sulfurreducens PCA. Involvement of both ombB-omaB-omcB and ombC-omaC-omcC in extracellular Fe(III reduction reflects the importance of these trans-outer membrane protein complexes in the physiology of this bacterium. Moreover, the kinetics of Fe(III-citrate and ferrihydrite reduction by these mutants in the absence of ombC-omaC-omcC were nearly identical, which suggests that absence of any protein subunit eliminates function of OmaB/OmbB/OmcB protein complex. Finally, orfS was found to have a negative impact on the extracellular reduction of Fe(III-citrate and ferrihydrite in G. sulfurreducens PCA probably by serving as a transcriptional repressor.

Application of a tetrazolium dye as an indicator of viability in anaerobic bacteria.

Science.gov (United States)

Bhupathiraju, V K; Hernandez, M; Landfear, D; Alvarez-Cohen, L

1999-09-01

The use of the redox dye 5-cyano-2,3,-ditolyl tetrazolium chloride (CTC) for evaluating the metabolic activity of aerobic bacteria has gained wide application in recent years. In this study, we examined the utility of CTC in capturing the metabolic activity of anaerobic bacteria. In addition, the factors contributing to abiotic reduction of CTC were also examined. CTC was used in conjunction with the fluorochrome 5-(4,6-dichlorotriazinyl) aminofluorescein (DTAF), that targets bacterial cell wall proteins, to quantitate the active fraction of total bacterial numbers. Facultative anaerobic bacteria, including Escherichia coli grown fermentatively, and Pseudomonas chlorophis, P. fluorescens, P. stutzeri, and P. pseudoalcalegenes subsp. pseudoalcalegenes grown under nitrate-reducing conditions, actively reduced CTC during all phases of growth. Greater than 95% of these cells accumulated intracellular CTC-formazan crystals during the exponential phase. Obligate anaerobic bacteria, including Syntrophus aciditrophicus grown fermentatively, Geobacter sulfurreducens grown with fumarate as the electron acceptor, Desulfovibrio desulfuricans subsp. desulfuricans and D. halophilus grown under sulfate-reducing conditions, Methanobacterium formicicum grown on formate, H2 and CO2, and Methanobacterium thermoautotrophicum grown autotrophically on H2 and CO2 all reduced CTC to intracellular CTC-formazan crystals. The optimal CTC concentration for all organisms examined was 5 mM. Anaerobic CTC incubations were not required for quantification of anaerobically grown cells. CTC-formazan production by all cultures examined was proportional to biomass production, and CTC reduction was observed even in the absence of added nutrients. CTC was reduced by culture fluids containing ferric citrate as electron acceptor following growth of either G. metallireducens or G. sulfurreducens. Abiotic reduction of CTC was observed in the presence of ascorbic acid, cysteine hydrochloride, dithiothreitol

Impact of fulvic acids on bio-methanogenic treatment of municipal solid waste incineration leachate.

Science.gov (United States)

Dang, Yan; Lei, Yuqing; Liu, Zhao; Xue, Yiting; Sun, Dezhi; Wang, Li-Ying; Holmes, Dawn E

2016-12-01

A considerable amount of leachate with high fulvic acid (FA) content is generated during the municipal solid waste (MSW) incineration process. This incineration leachate is usually processed by downstream bio-methanogenic treatment. However, few studies have examined the impact that these compounds have on methanogenesis and how they are degraded and transformed during the treatment process. In this study, a laboratory-scale expanded granular sludge bed (EGSB) reactor was operated with MSW incineration leachate containing various concentrations of FA (1500 mg/L to 8000 mg/L) provided as the influent. We found that FA degradation rates decreased from 86% to 72% when FA concentrations in the reactor were increased, and that molecular size, level of humification and aromatization of the residual FA macromolecules all increased after bio-methanogenic treatment. Increasing FA influent concentrations also inhibited growth of hydrogenotrophic methanogens from the genus Methanobacterium and syntrophic bacteria from the genus Syntrophomonas, which resulted in a decrease in methane production and a concomitant increase in CO 2 content in the biogas. Sequences most similar to species from the genus Anaerolinea went up as FA concentrations increased. Bacteria from this genus are capable of extracellular electron transfer and may be using FA as an electron acceptor for growth or as a shuttle for syntrophic exchange with other microorganisms in the reactor. In order to determine whether FA could serve as an electron shuttle to promote syntrophy in an anaerobic digester, co-cultures of Geobacter metallireducens and G. sulfurreducens were grown in the presence of FA from raw leachate or from residual bioreactor effluent. While raw FA stimulated electron transfer between these two bacteria, residual FA did not have any electron shuttling abilities, indicating that FA underwent a significant transformation during the bio-methanogenic treatment process. These results are

Influence of ammonium availability on expression of nifD and amtB genes during biostimulation of a U(VI) contaminated aquifer: implications for U(VI) removal and monitoring the metabolic state of Geobacteraceae

Energy Technology Data Exchange (ETDEWEB)

Mouser, Paula J.; N' Guessan, A. Lucie; Elifantz, Hila; Holmes, Dawn E.; Williams, Kenneth H; Wilkins, Michael J.; Long, Philip E.; Lovley, Derek R.

2009-03-25

The influence of ammonium availability on bacterial community structure and the physiological status of Geobacter species during in situ bioremediation of uranium-contaminated groundwater was evaluated. Ammonium concentrations varied by 2 orders of magnitude (<4 to 400 ?M) across the study site. Analysis of 16S rRNA sequences suggested that ammonium may have been one factor influencing the community composition prior to acetate amendment with Rhodoferax species predominating over Geobacter species with higher ammonium and Dechloromonas species dominating at the site with lowest ammonium. However, once acetate was added and dissimilatory metal reduction was stimulated, Geobacter species became the predominant organisms at all locations. Rates of U(VI) reduction appeared to be more related to acetate concentrations rather than ammonium levels. In situ mRNA transcript abundance of the nitrogen fixation gene, nifD, and the ammonium transporter gene, amtB, in Geobacter species indicated that ammonium was the primary source of nitrogen during uranium reduction. The abundance of amtB was inversely correlated to ammonium levels, whereas nifD transcript levels were similar across all sites examined. These results suggest that nifD and amtB expression are closely regulated in response to ammonium availability to ensure an adequate supply of nitrogen while conserving cell resources. Thus, quantifying nifD and amtB transcript expression appears to be a useful approach for monitoring the nitrogen-related physiological status of subsurface Geobacter species. This study also emphasizes the need for more detailed analysis of geochemical and physiological interactions at the field scale in order to adequately model subsurface microbial processes during bioremediation.

Potential for Methanosarcina to contribute to uranium reduction during acetate-promoted groundwater bioremediation

DEFF Research Database (Denmark)

Holmes, Dawn E; Orellana, Roberto; Giloteaux, Ludovic

2018-01-01

Previous studies of acetate-promoted bioremediation of uranium-contaminated aquifers focused on Geobacter because no other microorganisms that can couple the oxidation of acetate with U(VI) reduction had been detected in situ. Monitoring the levels of methyl CoM reductase subunit A (mcrA) transcr......Previous studies of acetate-promoted bioremediation of uranium-contaminated aquifers focused on Geobacter because no other microorganisms that can couple the oxidation of acetate with U(VI) reduction had been detected in situ. Monitoring the levels of methyl CoM reductase subunit A (mcr......(VI) reduction was observed in inactive controls. These results demonstrate that Methanosarcina species could play an important role in the long-term bioremediation of uranium-contaminated aquifers after depletion of Fe(III) oxides limits the growth of Geobacter species. The results also suggest...

Nitrate Enhanced Microbial Cr(VI) Reduction-Final Report

Energy Technology Data Exchange (ETDEWEB)

John F. Stolz

2011-06-15

A major challenge for the bioremediation of radionuclides (i.e., uranium, technetium) and metals (i.e., Cr(VI), Hg) is the co-occurrence of nitrate as it can inhibit metal transformation. Denitrification (nitrate reduction to dinitrogen gas) is considered the most important ecological process. For many metal and metalloid reducing bacteria, however, ammonia is the end product through respiratory nitrate reduction (RNRA). The focus of this work was to determine how RNRA impacts Cr(VI) transformation. The goal was to elucidate the specific mechanism(s) that limits Cr(VI) reduction in the presence of nitrate and to use this information to develop strategies that enhance Cr(VI) reduction (and thus detoxification). Our central hypothesis is that nitrate impacts the biotransformation of metals and metalloids in three ways 1) as a competitive alternative electron acceptor (inhibiting transformation), 2) as a co-metabolite (i.e., concomitant reduction, stimulating transformation), and 3) as an inducer of specific proteins and pathways involved in oxidation/reduction reactions (stimulating transformation). We have identified three model organisms, Geobacter metallireducens (mechanism 1), Sulfurospirillum barnesii, (mechasism 2), and Desulfovibrio desulfuricans (mechanisms 3). Our specific aims were to 1) investigate the role of Cr(VI) concentration on the kinetics of both growth and reduction of nitrate, nitrite, and Cr(VI) in these three organisms; 2) develop a profile of bacterial enzymes involved in nitrate transformation (e.g., oxidoreductases) using a proteomic approach; 3) investigate the function of periplasmic nitrite reductase (Nrf) as a chromate reductase; and 4) develop a strategy to maximize microbial chromium reduction in the presence of nitrate. We found that growth on nitrate by G. metallireducens was inhibited by Cr(VI). Over 240 proteins were identified by LC/MS-MS. Redox active proteins, outer membrane heavy metal efflux proteins, and chemotaxis sensory

A prototype feature system for feature retrieval using relationships

Science.gov (United States)

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Combining microbial cultures for efficient production of electricity from butyrate in a microbial electrochemical cell

Science.gov (United States)

Miceli, Joseph F.; Garcia-Peña, Ines; Parameswaran, Prathap; Torres, César I.; Krajmalnik-Brown, Rosa

2014-01-01

Butyrate is an important product of anaerobic fermentation; however, it is not directly used by characterized strains of the highly efficient anode respiring bacteria (ARB) Geobacter sulfurreducens in microbial electrochemical cells. By combining a butyrate-oxidizing community with a Geobacter rich culture, we generated a microbial community which outperformed many naturally derived communities found in the literature for current production from butyrate and rivaled the highest performing natural cultures in terms of current density (~11 A/m2) and Coulombic efficiency (~70%). Microbial community analyses support the shift in the microbial community from one lacking efficient ARB in the marine hydrothermal vent community to a community consisting of ~80% Geobacter in the anode biofilm. This demonstrates the successful production and adaptation of a novel microbial culture for generating electrical current from butyrate with high current density and high Coulombic efficiency, by combining two mixed micro bial cultures containing complementing biochemical pathways. PMID:25048958

Enhancing facial features by using clear facial features

Science.gov (United States)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

Spatial features register: toward standardization of spatial features

Science.gov (United States)

Cascio, Janette

1994-01-01

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

Directory of Open Access Journals (Sweden)

Ratri Enggar Pawening

2016-06-01

Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

Potential for Methanosarcina to contribute to uranium reduction during acetate-promoted groundwater bioremediation

DEFF Research Database (Denmark)

Holmes, Dawn E; Orellana, Roberto; Giloteaux, Ludovic

2017-01-01

Previous studies of in situ bioremediation of uranium-contaminated groundwater with acetate injections have focused on the role of Geobacter species in U(VI) reduction because of a lack of other abundant known U(VI)-reducing microorganisms. Monitoring the levels of methyl CoM reductase subunit...... an important role in the long-term bioremediation of uranium-contaminated aquifers after depletion of Fe(III) oxides limits the growth of Geobacter species. The results also suggest that Methanosarcina have the potential to influence uranium geochemistry in a diversity of anaerobic sedimentary environments....

Identifying significant environmental features using feature recognition.

Science.gov (United States)

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

Microbial Fe(III) Oxide Reduction in Chocolate Pots Hot Springs, Yellowstone National Park

Science.gov (United States)

Fortney, N. W.; Roden, E. E.; Boyd, E. S.; Converse, B. J.

2014-12-01

Previous work on dissimilatory iron reduction (DIR) in Yellowstone National Park (YNP) has focused on high temperature, low pH environments where soluble Fe(III) is utilized as an electron acceptor for respiration. Much less attention has been paid to DIR in lower temperature, circumneutral pH environments, where solid phase Fe(III) oxides are the dominant forms of Fe(III). This study explored the potential for DIR in the warm (ca. 40-50°C), circumneutral pH Chocolate Pots hot springs (CP) in YNP. Most probable number (MPN) enumerations and enrichment culture studies confirmed the presence of endogenous microbial communities that reduced native CP Fe(III) oxides. Enrichment cultures demonstrated sustained DIR coupled to acetate and lactate oxidation through repeated transfers over ca. 450 days. Pyrosequencing of 16S rRNA genes indicated that the dominant organisms in the enrichments were closely affiliated with the well known Fe(III) reducer Geobacter metallireducens. Additional taxa included relatives of sulfate reducing bacterial genera Desulfohalobium and Thermodesulfovibrio; however, amendment of enrichments with molybdate, an inhibitor of sulfate reduction, suggested that sulfate reduction was not a primary metabolic pathway involved in DIR in the cultures. A metagenomic analysis of enrichment cultures is underway in anticipation of identifying genes involved in DIR in the less well-characterized dominant organisms. Current studies are aimed at interrogating the in situ microbial community at CP. Core samples were collected along the flow path (Fig. 1) and subdivided into 1 cm depth intervals for geochemical and microbiological analysis. The presence of significant quantities of Fe(II) in the solids indicated that DIR is active in situ. A parallel study investigated in vitro microbial DIR in sediments collected from three of the coring sites. DNA was extracted from samples from both studies for 16S rRNA gene and metagenomic sequencing in order to obtain a

Diverse anaerobic Cr(VI) tolerant bacteria from Cr(VI)-contaminated 100H site at Hanford

Science.gov (United States)

Chakraborty, R.; Phan, R.; Lam, S.; Leung, C.; Brodie, E. L.; Hazen, T. C.

2007-12-01

Hexavalent Chromium [Cr(VI)] is a widespread contaminant found in soil, sediment, and ground water. Cr(VI) is more soluble, toxic, carcinogenic, and mutagenic compared to its reduced form Cr(III). In order to stimulate microbially mediated reduction of Cr(VI), a poly-lactate compound HRC was injected into the chromium contaminated aquifers at site 100H at Hanford. Based on the results of the bacterial community composition using high-density DNA microarray analysis of 16S rRNA gene products, we recently investigated the diversity of the dominant anaerobic culturable microbial population present at this site and their role in Cr(VI) reduction. Positive enrichments set up at 30°C using specific defined anaerobic media resulted in the isolation of an iron reducing isolate strain HAF, a sulfate reducing isolate strain HBLS and a nitrate reducing isolate, strain HLN among several others. Preliminary 16S rDNA sequence analysis identifies strain HAF as Geobacter metallireducens, strain HLN as Pseudomonas stutzeri and strain HBLS as a member of Desulfovibrio species. Strain HAF isolated with acetate as the electron donor utilized propionate, glycerol and pyruvate as alternative carbon sources, and reduced metals like Mn(IV) and Cr(VI). Growth was optimal at 37°C, pH of 6.5 and 0% salinity. Strain HLN isolated with lactate as electron donor utilized acetate, glycerol and pyruvate as alternative carbon sources, and reduced metals like Mn(IV) and Cr(VI). Optimal growth was observed at 37°C, at a pH of 7.5 and 0.3% salinity. Anaerobic active washed cell suspension of strain HLN reduced almost 95 micromolar Cr(VI) within 4 hours relative to controls. Further, with 100 micromolar Cr(VI) as the sole electron acceptor, cells of strain HLN grew to cell numbers of 4.05X 107/ml over a period of 24hrs after an initial lag, demonstrating direct enzymatic Cr(VI) reduction by this species. 10mM lactate served as the sole electron donor. These results demonstrate that Cr

6-Oxocyclohex-1-ene-1-carbonyl-coenzyme A hydrolases from obligately anaerobic bacteria: characterization and identification of its gene as a functional marker for aromatic compounds degrading anaerobes.

Science.gov (United States)

Kuntze, Kevin; Shinoda, Yoshifumi; Moutakki, Housna; McInerney, Michael J; Vogt, Carsten; Richnow, Hans-Hermann; Boll, Matthias

2008-06-01

In anaerobic bacteria, most aromatic growth substrates are channelled into the benzoyl-coenzyme A (CoA) degradation pathway where the aromatic ring is dearomatized and cleaved into an aliphatic thiol ester. The initial step of this pathway is catalysed by dearomatizing benzoyl-CoA reductases yielding the two electron-reduction product, cyclohexa-1,5-diene-1-carbonyl-CoA, to which water is subsequently added by a hydratase. The next two steps have so far only been studied in facultative anaerobes and comprise the oxidation of the 6-hydroxyl-group to 6-oxocyclohex-1-ene-1-carbonyl-CoA (6-OCH-CoA), the addition of water and hydrolytic ring cleavage yielding 3-hydroxypimelyl-CoA. In this work, two benzoate-induced genes from the obligately anaerobic bacteria, Geobacter metallireducens (bamA(Geo)) and Syntrophus aciditrophicus (bamA(Syn)), were heterologously expressed in Escherichia coli, purified and characterized as 6-OCH-CoA hydrolases. Both enzymes consisted of a single 43 kDa subunit. Some properties of the enzymes are presented and compared with homologues from facultative anaerobes. An alignment of the nucleotide sequences of bamA(Geo) and bamA(Syn) with the corresponding genes from facultative anaerobes identified highly conserved DNA regions, which enabled the discrimination of genes coding for 6-OCH-CoA hydrolases from those coding for related enzymes. A degenerate oligonucleotide primer pair was deduced from conserved regions and applied in polymerase chain reaction reactions. Using these primers, the expected DNA fragment of the 6-OCH-CoA hydrolase genes was specifically amplified from the DNA of nearly all known facultative and obligate anaerobes that use aromatic growth substrates. The only exception was the aromatic compound-degrading Rhodopseudomonas palustris, which uniquely uses a modified benzoyl-CoA degradation pathway. Using the oligonucleotide primers, the expected DNA fragment was also amplified in a toluene-degrading and a m

Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

Directory of Open Access Journals (Sweden)

Pachet François

2009-01-01

Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

Featureous: infrastructure for feature-centric analysis of object-oriented software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand how user-observable program features are implemented and how their implementations relate to each other. It is worthwhile to improve this situation, since feature-centric program...... understanding and modification are essential during software evolution and maintenance. In this paper, we present an infrastructure built on top of the NetBeans IDE called Featureous that allows for rapid construction of tools for feature-centric analysis of object-oriented software. Our infrastructure...... encompasses a lightweight feature location mechanism, a number of analytical views and an API allowing for addition of third-party extensions. To form a common conceptual framework for future feature-centric extensions, we propose to structure feature centric analysis along three dimensions: perspective...

Feature Article

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. Feature Article. Articles in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 80-85 Feature Article. What's New in Computers Windows 95 · Vijnan Shastri · More Details Fulltext PDF. Volume 1 Issue 1 January 1996 pp 86-89 Feature ...

Featureous: A Tool for Feature-Centric Analysis of Java Software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

Feature-centric comprehension of source code is necessary for incorporating user-requested modifications during software evolution and maintenance. However, such comprehension is difficult to achieve in case of large object-oriented programs due to the size, complexity, and implicit character...... of mappings between features and source code. To support programmers in overcoming these difficulties, we present a feature-centric analysis tool, Featureous. Our tool extends the NetBeans IDE with mechanisms for efficient location of feature implementations in legacy source code, and an extensive analysis...

ORF Alignment: NC_002939 [GENIUS II[Archive

Lifescience Database Archive (English)

Full Text Available Geobacter sulfurreducens PCA] ... Length = 81 ... Query: 1 ... MFVXXXXXXXXXXXXXXKGKRGIVKSILARARQDFNVSAAEVDL...QDVPDEAVLAFATVTG 60 ... MFV ... KGKRGIVKSILARARQDFNVSAAEVDLQDVPDEA...VLAFATVTG Sbjct: 1 ... MFVHSLCLHLHLPSHSLKGKRGIVKSILARARQDFNVSAAEVDLQDVPDEAVLAFATVTG 60 ...

ORF Alignment: NC_002939 [GENIUS II[Archive

Lifescience Database Archive (English)

Full Text Available GESSFNPLAINYNSNGTYDYGLMQINSSWEPALRK 79 ... ASAFCFEEAGNRYGISPQLLYAISKGESSFNPLAINYNSNGTYDYGLMQINSS...WEPALRK Sbjct: 1 ... ASAFCFEEAGNRYGISPQLLYAISKGESSFNPLAINYNSNGTYDYGLMQINSSWEPALRK 60 ... ...tein ... [Geobacter sulfurreducens PCA] ... Length = 101 ... Query: 20 ... ASAFCFEEAGNRYGISPQLLYAISK

Definitions of engineered safety features and related features for nuclear power plants

International Nuclear Information System (INIS)

1986-01-01

In light water moderated, light water cooled nuclear power plants, definitions are given of engineered safety features which are designed to suppress or prevent dispersion of radioactive materials due to damage etc. of fuel at the times of power plant failures, and of related features which are designed to actuate or operate the engineered safety features. Contents are the following: scope of engineered safety features and of related features; classification of engineered safety features (direct systems and indirect systems) and of related features (auxiliaries, emergency power supply, and protective means). (Mori, K.)

ORF Alignment: NC_002939 [GENIUS II[Archive

Lifescience Database Archive (English)

Full Text Available FliM ... [Geobacter sulfurreducens PCA] ... Length = 79 ... Query: 248 RLSKELLEAPLDVSVEVGGAVISLNDLLSLVPGDTIMLDTPCTSDLT...VKVGGVPKFTGMP 307 ... RLSKELLEAPLDVSVEVGGAVISLNDLLSLVPGDTIMLDTPCTSDLT...VKVGGVPKFTGMP Sbjct: 1 ... RLSKELLEAPLDVSVEVGGAVISLNDLLSLVPGDTIMLDTPCTSDLTVKVGGVPKFTGMP 60 ...

ORF Alignment: NC_002939 [GENIUS II[Archive

Lifescience Database Archive (English)

Full Text Available tein-alanine acetyltransferase [Geobacter ... sulfurreducens PCA] ... Length = 146 ... Query: 1 ... MNTADCP...TIMPMTEGDLDEVLQIESDSFPRPWTRDHFVAELASPRSFPVVARSPGGLIVG 60 ... MNTADCP...TIMPMTEGDLDEVLQIESDSFPRPWTRDHFVAELASPRSFPVVARSPGGLIVG Sbjct: 1 ... MNTADCPTIMPMTEGDLDEVLQIESDSFPRPWTRDHFVAEL

JCE Feature Columns

Science.gov (United States)

Holmes, Jon L.

1999-05-01

The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

Directory of Open Access Journals (Sweden)

Lijun Wang

2013-01-01

Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

Microbial Fuel Cells; Microbiele Fuel Cells

Energy Technology Data Exchange (ETDEWEB)

Louzada, K.

2012-03-15

Geobacter bacteria are able to transfer electrons to their environment and have a recovering effect on the environment. The US Office for Naval research (ONR) is conducting research on the application of bacteria in the development of natural batteries for under water applications such as lighting, chemical sensors, hydrophones and autonomous vehicles. [Dutch] Geobacter bacterien zijn in staat zijn om elektronen over te dragen aan hun omgeving en hebben een herstellende invloed op het milieu. Het US Office for Naval Research (ONR) voert onderzoek uit naar de toepassingen van de bacterien in de ontwikkeling van natuurlijke batterijen voor onderwater applicaties als verlichting, chemische sensoren, hydrofonen en autonome voertuigen.

Classification Influence of Features on Given Emotions and Its Application in Feature Selection

Science.gov (United States)

Xing, Yin; Chen, Chuang; Liu, Li-Long

2018-04-01

In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

OpenAIRE

Keong Chen Wong; Yusof Yusri

2017-01-01

This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

Unsupervised Feature Subset Selection

DEFF Research Database (Denmark)

Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose

2003-01-01

This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....

When do letter features migrate? A boundary condition for feature-integration theory.

Science.gov (United States)

Butler, B E; Mewhort, D J; Browse, R A

1991-01-01

Feature-integration theory postulates that a lapse of attention will allow letter features to change position and to recombine as illusory conjunctions (Treisman & Paterson, 1984). To study such errors, we used a set of uppercase letters known to yield illusory conjunctions in each of three tasks. The first, a bar-probe task, showed whole-character mislocations but not errors based on feature migration and recombination. The second, a two-alternative forced-choice detection task, allowed subjects to focus on the presence or absence of subletter features and showed illusory conjunctions based on feature migration and recombination. The third was also a two-alternative forced-choice detection task, but we manipulated the subjects' knowledge of the shape of the stimuli: In the case-certain condition, the stimuli were always in uppercase, but in the case-uncertain condition, the stimuli could appear in either upper- or lowercase. Subjects in the case-certain condition produced illusory conjunctions based on feature recombination, whereas subjects in the case-uncertain condition did not. The results suggest that when subjects can view the stimuli as feature groups, letter features regroup as illusory conjunctions; when subjects encode the stimuli as letters, whole items may be mislocated, but subletter features are not. Thus, illusory conjunctions reflect the subject's processing strategy, rather than the architecture of the visual system.

Featureous: an Integrated Approach to Location, Analysis and Modularization of Features in Java Applications

DEFF Research Database (Denmark)

Olszak, Andrzej

, it is essential that features are properly modularized within the structural organization of software systems. Nevertheless, in many object-oriented applications, features are not represented explicitly. Consequently, features typically end up scattered and tangled over multiple source code units......, such as architectural layers, packages and classes. This lack of modularization is known to make application features difficult to locate, to comprehend and to modify in isolation from one another. To overcome these problems, this thesis proposes Featureous, a novel approach to location, analysis and modularization...... quantitative and qualitative results suggest that Featureous succeeds at efficiently locating features in unfamiliar codebases, at aiding feature-oriented comprehension and modification, and at improving modularization of features using Java packages....

Innovations in individual feature history management - The significance of feature-based temporal model

Science.gov (United States)

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Dependency Parsing with Transformed Feature

Directory of Open Access Journals (Sweden)

Fuxiang Wu

2017-01-01

Full Text Available Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

Science.gov (United States)

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Language Features and Culture Features on Short Message

Institute of Scientific and Technical Information of China (English)

王佳

2013-01-01

Mobile phone is regarded as“the fifth media”after newspaper,radio,TV and the Internet.The mobile phone short message further highlights the importance of written signs in communication.“The thumb revolution”is eagerly anticipating one kind of trend by the hand replace of mouth,sound substitute for the quiet around us. My paper will analyze the language features and the culture features of mobile phone short messages which are written in Chinese and English.

Pulse electromagnetic fields enhance extracellular electron transfer in magnetic bioelectrochemical systems.

Science.gov (United States)

Zhou, Huihui; Liu, Bingfeng; Wang, Qisong; Sun, Jianmin; Xie, Guojun; Ren, Nanqi; Ren, Zhiyong Jason; Xing, Defeng

2017-01-01

Microbial extracellular electron transfer (EET) is essential in driving the microbial interspecies interaction and redox reactions in bioelectrochemical systems (BESs). Magnetite (Fe 3 O 4 ) and magnetic fields (MFs) were recently reported to promote microbial EET, but the mechanisms of MFs stimulation of EET and current generation in BESs are not known. This study investigates the behavior of current generation and EET in a state-of-the-art pulse electromagnetic field (PEMF)-assisted magnetic BES (PEMF-MBES), which was equipped with magnetic carbon particle (Fe 3 O 4 @N-mC)-coated electrodes. Illumina Miseq sequencing of 16S rRNA gene amplicons was also conducted to reveal the changes of microbial communities and interactions on the anode in response to magnetic field. PEMF had significant influences on current generation. When reactors were operated in microbial fuel cell (MFC) mode with pulse electromagnetic field (PEMF-MMFCs), power densities increased by 25.3-36.0% compared with no PEMF control MFCs (PEMF-OFF-MMFCs). More interestingly, when PEMF was removed, the power density dropped by 25.7%, while when PEMF was reintroduced, the value was restored to the previous level. Illumina sequencing of 16S rRNA gene amplicon and principal component analysis (PCA) based on operational taxonomic units (OTUs) indicate that PEMFs led to the shifts in microbial community and changes in species evenness that decreased biofilm microbial diversity. Geobacter spp. were found dominant in all anode biofilms, but the relative abundance in PEMF-MMFCs (86.1-90.0%) was higher than in PEMF-OFF-MMFCs (82.5-82.7%), indicating that the magnetic field enriched Geobacter on the anode. The current generation of Geobacter -inoculated microbial electrolysis cells (MECs) presented the same change regularity, the accordingly increase or decrease corresponding with switch of PEMF, which confirmed the reversible stimulation of PEMFs on microbial electron transfer. The pulse electromagnetic

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Directory of Open Access Journals (Sweden)

Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

Directory of Open Access Journals (Sweden)

Jin-Jia Wang

2015-01-01

Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

Coding of visual object features and feature conjunctions in the human brain.

Science.gov (United States)

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

An object-oriented feature-based design system face-based detection of feature interactions

International Nuclear Information System (INIS)

Ariffin Abdul Razak

1999-01-01

This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

Assessment of Bacterial Degradation of Aromatic Hydrocarbons in the Environment by Analysis of Stable Carbon Isotope Fractionation

International Nuclear Information System (INIS)

Meckenstock, Rainer U.; Morasch, Barbara; Kaestner, Matthias; Vieth, Andrea; Richnow, Hans Hermann

2002-01-01

13 C/ 12 C stable carbon isotope fractionation was used to assess biodegradation in contaminated aquifers with toluene as a model compound. Different strains of anaerobic bacteria (Thauera aromatica, Geobacter metallireducens, and the sulfate-reducing strain TRM1) showed consistent 13 C/ 12 C carbon isotope fractionation with fractionation factors between αC = 1.0017 and 1.0018. In contrast, three cultures of aerobic organisms, using different mono- and dioxygenase enzyme systems to initiate toluene degradation, showed variable isotope fractionation factors of αC = 1.0027 (Pseudomonasputida strain mt-2), αC = 1.0011 (Ralstonia picketii), andαC = 1.0004 (Pseudomonas putida strain F1). The great variability of isotope fractionation between different aerobic bacterial strains suggests that interpretation of isotope data in oxic habitats can only be qualitative. A soil column was run as a model system for contaminated aquifers with toluene as the carbon source and sulfate as the electron acceptor and samples were taken at different ports along the column. Microbial toluene degradation was calculated based on the 13 C/ 12 C isotope fractionation factors of the batch culture experiments together with the observed 13 C/ 12 C isotope shifts of the residual toluene fractions. The calculated percentage of biodegradation, B, correlated well with the decreasing toluene concentrations at the sampling ports and indicated the increasing extent of biodegradation along the column. The theoretical toluene concentrations as calculated based on the isotope values matched the measured concentrations at the different sampling ports indicating that the Rayleigh equation can be used to calculate biodegradation in quasi closed systems based on measured isotope shifts. A similar attempt was performed to assess toluene degradation in a contaminated, anoxic aquifer. A transect of groundwater wells was monitored along the main direction of the groundwater flow and revealed decreasing

Feature-Based Retinal Image Registration Using D-Saddle Feature

Directory of Open Access Journals (Sweden)

Roziana Ramli

2017-01-01

Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

Screening for Plant Features

NARCIS (Netherlands)

Heijden, van der G.W.A.M.; Polder, G.

2015-01-01

In this chapter, an overview of different plant features is given, from (sub)cellular to canopy level. A myriad of methods is available to measure these features using image analysis, and often, multiple methods can be used to measure the same feature. Several criteria are listed for choosing a

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Dissociation between Features and Feature Relations in Infant Memory: Effects of Memory Load.

Science.gov (United States)

Bhatt, Ramesh S.; Rovee-Collier, Carolyn

1997-01-01

Four experiments examined effects of the number of features and feature relations on learning and long-term memory in 3-month olds. Findings suggested that memory load size selectively constrained infants' long-term memory for relational information, suggesting that in infants, features and relations are psychologically distinct and that memory…

Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

Science.gov (United States)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

Doubly sparse factor models for unifying feature transformation and feature selection

International Nuclear Information System (INIS)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato; Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko

2010-01-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Doubly sparse factor models for unifying feature transformation and feature selection

Energy Technology Data Exchange (ETDEWEB)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato [ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama (Japan); Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko, E-mail: okada@k.u-tokyo.ac.j [Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan)

2010-06-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Feature Import Vector Machine: A General Classifier with Flexible Feature Selection.

Science.gov (United States)

Ghosh, Samiran; Wang, Yazhen

2015-02-01

The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifiers based on the training data in a high dimensional space by using all available dimensions. The SVM achieves huge data compression by selecting only few observations which lie close to the boundary of the classifier function. However when the number of observations are not very large (small n ) but the number of dimensions/features are large (large p ), then it is not necessary that all available features are of equal importance in the classification context. Possible selection of an useful fraction of the available features may result in huge data compression. In this paper we propose an algorithmic approach by means of which such an optimal set of features could be selected. In short, we reverse the traditional sequential observation selection strategy of SVM to that of sequential feature selection. To achieve this we have modified the solution proposed by Zhu and Hastie (2005) in the context of import vector machine (IVM), to select an optimal sub-dimensional model to build the final classifier with sufficient accuracy.

Rust dissolution and removal by iron-reducing bacteria: A potential rehabilitation of rusted equipment

International Nuclear Information System (INIS)

Starosvetsky, J.; Kamari, R.; Farber, Y.; Bilanović, D.; Armon, R.

2016-01-01

Highlights: • The present study demonstrated the high reductive capacity of both strains: the collection S. oneidensis and the wild strain Geobacter spp. (soil isolate). • The experimental strains were successful in Fe 3+ reduction for both states: soluble and crystalline (originally prepared from rust). • Rust dissolution can be improved by: addition of AFC at low concentration (0.2 g/l), increasing bacterial initial inoculum and rust reactive surface. • Both experimental IRB strains were able to completely remove previously formed rust on carbon steel coupons. • Additional results (not showed) revealed that culture S. oneidensis and the environmental isolate Geobacter spp., apparently have a different mechanism of iron reduction that requires further study. - Abstract: Iron reducing bacteria (IRB), to be used in rust dissolution and removal, have been isolated and enriched from different environmental sources. Comparative measurements revealed that a soil isolate (Geobacter sulfurreducens sp.) had the highest reductive activity equivalent to Shewanella oneidensis (strain CIP 106686, pure culture). Both reductive microorganisms can use Fe 3+ ions as electron acceptors from soluble as well as from crystalline sources. In nutrient medium containing soluble Fe 3+ , the highest reductive activity obtained for G. sulfurreducens sp. and S. oneidensis was 93 and 97% respectively. Successful removal of rust from carbon steel coupons has been achieved with both experimental bacteria.

Internal versus external features in triggering the brain waveforms for conjunction and feature faces in recognition.

Science.gov (United States)

Nie, Aiqing; Jiang, Jingguo; Fu, Qiao

2014-08-20

Previous research has found that conjunction faces (whose internal features, e.g. eyes, nose, and mouth, and external features, e.g. hairstyle and ears, are from separate studied faces) and feature faces (partial features of these are studied) can produce higher false alarms than both old and new faces (i.e. those that are exactly the same as the studied faces and those that have not been previously presented) in recognition. The event-related potentials (ERPs) that relate to conjunction and feature faces at recognition, however, have not been described as yet; in addition, the contributions of different facial features toward ERPs have not been differentiated. To address these issues, the present study compared the ERPs elicited by old faces, conjunction faces (the internal and the external features were from two studied faces), old internal feature faces (whose internal features were studied), and old external feature faces (whose external features were studied) with those of new faces separately. The results showed that old faces not only elicited an early familiarity-related FN400, but a more anterior distributed late old/new effect that reflected recollection. Conjunction faces evoked similar late brain waveforms as old internal feature faces, but not to old external feature faces. These results suggest that, at recognition, old faces hold higher familiarity than compound faces in the profiles of ERPs and internal facial features are more crucial than external ones in triggering the brain waveforms that are characterized as reflecting the result of familiarity.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

Science.gov (United States)

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those

Evaluating the Stability of Feature Selectors that Optimize Feature Subset Cardinality

Czech Academy of Sciences Publication Activity Database

Somol, Petr; Novovičová, Jana

2008-01-01

Roč. 2008, č. 5342 (2008), s. 956-966 ISSN 0302-9743. [Joint IAPR International Workshops SSPR 2008 and SPR 2008. Orlando , 04.12.2008-06.12.2008] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA ČR GA102/07/1594 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Feature selection * stability * relative weighted consistency measure * sequential search * floating search Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2008/RO/somol-evaluating the stability of feature selectors that optimize feature subset cardinality.pdf

RESEARCH ON FEATURE POINTS EXTRACTION METHOD FOR BINARY MULTISCALE AND ROTATION INVARIANT LOCAL FEATURE DESCRIPTOR

Directory of Open Access Journals (Sweden)

Hongwei Ying

2014-08-01

Full Text Available An extreme point of scale space extraction method for binary multiscale and rotation invariant local feature descriptor is studied in this paper in order to obtain a robust and fast method for local image feature descriptor. Classic local feature description algorithms often select neighborhood information of feature points which are extremes of image scale space, obtained by constructing the image pyramid using certain signal transform method. But build the image pyramid always consumes a large amount of computing and storage resources, is not conducive to the actual applications development. This paper presents a dual multiscale FAST algorithm, it does not need to build the image pyramid, but can extract feature points of scale extreme quickly. Feature points extracted by proposed method have the characteristic of multiscale and rotation Invariant and are fit to construct the local feature descriptor.

Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

Science.gov (United States)

Sloan, G. C.; Kraemer, K. E.; Goebel, J. H.; Price, S. D.

A study of spectra from the SWS on ISO of optically thin oxygen-rich dust shells shows that the strength of the 13 micron dust emission feature is correlated with the CO2 bands (13--17 microns) and dust emission features at 19.8 and 28.1 microns. SRb variables tend to show stronger 13 micron features than Mira variables, suggesting that the presence of the 13 micron and related features depends on pulsation mode and mass-loss rate. The absence of any correlation to dust emission features at 16.8 and 32 microns makes spinel an unlikely carrier. The most plausible carrier of the 13 micron feature remains crystalline alumina, and we suggest that the related dust features may be crystalline silicates. When dust forms in regions of low density, it may condense into crystalline grain structures.

Feature displacement interpolation

DEFF Research Database (Denmark)

Nielsen, Mads; Andresen, Per Rønsholt

1998-01-01

Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo disparity computation, flow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features...... often are very sparse, the interpolation model becomes crucial. We show that a maximum likelihood estimation based on the covariance properties (Kriging) show properties more expedient than methods such as Gaussian interpolation or Tikhonov regularizations, also including scale......-selection. The computational complexities are identical. We apply the maximum likelihood interpolation to growth analysis of the mandibular bone. Here, the features used are the crest-lines of the object surface....

Mid-Infrared Emission Features in the ISM: Feature-to-Features Flux Ratios

Science.gov (United States)

Lu, N. Y.

1998-01-01

Using a limited, but representative sample of sources in the ISM of our Galaxy with published spectra from the Infrared Space Observatory, we analyze flux ratios between the major mid-IR emission features (EFs) centered around 6.2, 7.7, 8.6 and 11.3 mu, respectively.

FEATUREOUS: AN INTEGRATED ENVIRONMENT FOR FEATURE-CENTRIC ANALYSIS AND MODIFICATION OF OBJECT-ORIENTED SOFTWARE

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand the implementations of user-observable program features and their respective interdependencies. As feature-centric program understanding and modification are essential during...... software maintenance and evolution, this situation needs to change. In this paper, we present Featureous, an integrated development environment built on top of the NetBeans IDE that facilitates feature-centric analysis of object-oriented software. Our integrated development environment encompasses...... a lightweight feature location mechanism, a number of reusable analytical views, and necessary APIs for supporting future extensions. The base of the integrated development environment is a conceptual framework comprising of three complementary dimensions of comprehension: perspective, abstraction...

Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

Energy Technology Data Exchange (ETDEWEB)

Pon, R K; Cardenas, A F; Buttler, D J

2007-09-19

The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifier with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.

Feature confirmation in object perception: Feature integration theory 26 years on from the Treisman Bartlett lecture.

Science.gov (United States)

Humphreys, Glyn W

2016-10-01

The Treisman Bartlett lecture, reported in the Quarterly Journal of Experimental Psychology in 1988, provided a major overview of the feature integration theory of attention. This has continued to be a dominant account of human visual attention to this day. The current paper provides a summary of the work reported in the lecture and an update on critical aspects of the theory as applied to visual object perception. The paper highlights the emergence of findings that pose significant challenges to the theory and which suggest that revisions are required that allow for (a) several rather than a single form of feature integration, (b) some forms of feature integration to operate preattentively, (c) stored knowledge about single objects and interactions between objects to modulate perceptual integration, (d) the application of feature-based inhibition to object files where visual features are specified, which generates feature-based spreading suppression and scene segmentation, and (e) a role for attention in feature confirmation rather than feature integration in visual selection. A feature confirmation account of attention in object perception is outlined.

Complex Topographic Feature Ontology Patterns

Science.gov (United States)

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

Science.gov (United States)

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

Science.gov (United States)

Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

2015-12-01

Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

Feature Selection by Reordering

Czech Academy of Sciences Publication Activity Database

Jiřina, Marcel; Jiřina jr., M.

2005-01-01

Roč. 2, č. 1 (2005), s. 155-161 ISSN 1738-6438 Institutional research plan: CEZ:AV0Z10300504 Keywords : feature selection * data reduction * ordering of features Subject RIV: BA - General Mathematics

DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

Directory of Open Access Journals (Sweden)

A. A. Vorobeva

2017-01-01

Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

Temporal Feature Integration for Music Organisation

DEFF Research Database (Denmark)

Meng, Anders

2006-01-01

This Ph.D. thesis focuses on temporal feature integration for music organisation. Temporal feature integration is the process of combining all the feature vectors of a given time-frame into a single new feature vector in order to capture relevant information in the frame. Several existing methods...... for handling sequences of features are formulated in the temporal feature integration framework. Two datasets for music genre classification have been considered as valid test-beds for music organisation. Human evaluations of these, have been obtained to access the subjectivity on the datasets. Temporal...... ranking' approach is proposed for ranking the short-time features at larger time-scales according to their discriminative power in a music genre classification task. The multivariate AR (MAR) model has been proposed for temporal feature integration. It effectively models local dynamical structure...

Feature Inference Learning and Eyetracking

Science.gov (United States)

Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

2009-01-01

Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

Set anode potentials affect the electron fluxes and microbial community structure in propionate-fed microbial electrolysis cells

KAUST Repository

Rao, Hari Ananda; Katuri, Krishna; Logan, Bruce E.; Saikaly, Pascal

2016-01-01

, but their relative abundance varied among the tested SAPs. Microbial community analysis implies that complete degradation of propionate in all the tested SAPs was facilitated by syntrophic interactions between fermenters and Geobacter at the anode and ferementers

Hypothesis testing for differentially correlated features.

Science.gov (United States)

Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

2016-10-01

In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Emergent interfaces for feature modularization

CERN Document Server

Ribeiro, Márcio; Brabrand, Claus

2014-01-01

Developers frequently introduce errors into software systems when they fail to recognise module dependencies. Using forty-three software families and Software Product Lines (SPLs), where the majority are commonly used in industrial practice, the authors reports on the feature modularization problem and provides a study of how often it may occur in practice. To solve the problem they present the concept of emergent feature modularization which aims to establish contracts between features to prevent developers from breaking other features when performing a maintenance task.

Writer identification using curvature-free features

NARCIS (Netherlands)

He, Sheng; Schomaker, Lambertus

2017-01-01

Feature engineering takes a very important role in writer identification which has been widely studied in the literature. Previous works have shown that the joint feature distribution of two properties can improve the performance. The joint feature distribution makes feature relationships explicit

Patterns of Dysmorphic Features in Schizophrenia

Science.gov (United States)

Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

2011-01-01

Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

Object feature extraction and recognition model

International Nuclear Information System (INIS)

Wan Min; Xiang Rujian; Wan Yongxing

2001-01-01

The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

Solar Features

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Collection includes a variety of solar feature datasets contributed by a number of national and private solar observatories located worldwide.

Search features of digital libraries

Directory of Open Access Journals (Sweden)

Alastair G. Smith

2000-01-01

Full Text Available Traditional on-line search services such as Dialog, DataStar and Lexis provide a wide range of search features (boolean and proximity operators, truncation, etc. This paper discusses the use of these features for effective searching, and argues that these features are required, regardless of advances in search engine technology. The literature on on-line searching is reviewed, identifying features that searchers find desirable for effective searching. A selective survey of current digital libraries available on the Web was undertaken, identifying which search features are present. The survey indicates that current digital libraries do not implement a wide range of search features. For instance: under half of the examples included controlled vocabulary, under half had proximity searching, only one enabled browsing of term indexes, and none of the digital libraries enable searchers to refine an initial search. Suggestions are made for enhancing the search effectiveness of digital libraries, for instance by: providing a full range of search operators, enabling browsing of search terms, enhancement of records with controlled vocabulary, enabling the refining of initial searches, etc.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

Science.gov (United States)

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

Science.gov (United States)

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

Volcanic features of Io

International Nuclear Information System (INIS)

Carr, M.H.; Masursky, H.; Strom, R.G.; Terrile, R.J.

1979-01-01

The volcanic features of Io as detected during the Voyager mission are discussed. The volcanic activity is apparently higher than on any other body in the Solar System. Its volcanic landforms are compared with features on Earth to indicate the type of volcanism present on Io. (U.K.)

Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality

Czech Academy of Sciences Publication Activity Database

Somol, Petr; Novovičová, Jana

2010-01-01

Roč. 32, č. 11 (2010), s. 1921-1939 ISSN 0162-8828 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593; GA ČR GA102/07/1594 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection * feature stability * stability measures * similarity measures * sequential search * individual ranking * feature subset-size optimization * high dimensionality * small sample size Subject RIV: BD - Theory of Information Impact factor: 5.027, year: 2010 http://library.utia.cas.cz/separaty/2010/RO/somol-0348726.pdf

Site Features

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times...

New features in MEDM

International Nuclear Information System (INIS)

Evans, K. Jr.

1999-01-01

MEDM, which is derived from Motif Editor and Display Manager, is the primary graphical interface to the EPICS control system. This paper describes new features that have been added to MEDM in the last two years. These features include new editing capabilities, a PV Info dialog box, a means of specifying limits and precision, a new implementation of the Cartesian Plot, new features for several objects, new capability for the Related Display, help, a user-configurable Execute Menu, reconfigured start-up options, and availability for Windows 95/98/NT. Over one hundred bugs have been fixed, and the program is quite stable and in extensive use

Tolerance-Based Feature Transforms

NARCIS (Netherlands)

Reniers, Dennie; Telea, Alexandru

2007-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

Science.gov (United States)

Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

Directory of Open Access Journals (Sweden)

Seyed Mostafa Mousavi Kahaki

Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

Crowding with conjunctions of simple features.

Science.gov (United States)

Põder, Endel; Wagemans, Johan

2007-11-20

Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.

Sensitivity to feature displacement in familiar and unfamiliar faces: beyond the internal/external feature distinction.

Science.gov (United States)

Brooks, Kevin R; Kemp, Richard I

2007-01-01

Previous studies of face recognition and of face matching have shown a general improvement for the processing of internal features as a face becomes more familiar to the participant. In this study, we used a psychophysical two-alternative forced-choice paradigm to investigate thresholds for the detection of a displacement of the eyes, nose, mouth, or ears for familiar and unfamiliar faces. No clear division between internal and external features was observed. Rather, for familiar (compared to unfamiliar) faces participants were more sensitive to displacements of internal features such as the eyes or the nose; yet, for our third internal feature-the mouth no such difference was observed. Despite large displacements, many subjects were unable to perform above chance when stimuli involved shifts in the position of the ears. These results are consistent with the proposal that familiarity effects may be mediated by the construction of a robust representation of a face, although the involvement of attention in the encoding of face stimuli cannot be ruled out. Furthermore, these effects are mediated by information from a spatial configuration of features, rather than by purely feature-based information.

Feature extraction for magnetic domain images of magneto-optical recording films using gradient feature segmentation

International Nuclear Information System (INIS)

Quanqing, Zhu.; Xinsai, Wang; Xuecheng, Zou; Haihua, Li; Xiaofei, Yang

2002-01-01

In this paper, we present a method to realize feature extraction on low contrast magnetic domain images of magneto-optical recording films. The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated. We describe these steps with particular emphasis on the gradient feature segmentation. The results show that this method has advantages over other traditional ones for feature extraction of low contrast images

Discrete Feature Model (DFM) User Documentation

Energy Technology Data Exchange (ETDEWEB)

Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

2008-06-15

This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this

Discrete Feature Model (DFM) User Documentation

International Nuclear Information System (INIS)

Geier, Joel

2008-06-01

This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this software, the

Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection.

Science.gov (United States)

Kipli, Kuryati; Kouzani, Abbas Z

2015-07-01

Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression. A feature selection (FS) algorithm called degree of contribution (DoC) is developed for selection of sMRI volumetric features. This algorithm uses an ensemble approach to determine the degree of contribution in detection of major depressive disorder. The DoC is the score of feature importance used for feature ranking. The algorithm involves four stages: feature ranking, subset generation, subset evaluation, and DoC analysis. The performance of DoC is evaluated on the Duke University Multi-site Imaging Research in the Analysis of Depression sMRI dataset. The dataset consists of 115 brain sMRI scans of 88 healthy controls and 27 depressed subjects. Forty-four sMRI volumetric features are used in the evaluation. The DoC score of forty-four features was determined as the accuracy threshold (Acc_Thresh) was varied. The DoC performance was compared with that of four existing FS algorithms. At all defined Acc_Threshs, DoC outperformed the four examined FS algorithms for the average classification score and the maximum classification score. DoC has a good ability to generate reduced-size subsets of important features that could yield high classification accuracy. Based on the DoC score, the most discriminant volumetric features are those from the left-brain region.

Flow-like Features On Europa

Science.gov (United States)

1997-01-01

This image shows features on Jupiter's moon Europa that may be 'flows' from ice volcanoes. It was taken by the Galileo spacecraft solid state imaging (CCD) system during its seventh orbit around Jupiter. North is to the top of the image. The sun illuminates the scene from the left, showing features with shapes similar to lava flows on Earth. Two such features can be seen in the northwest corner of the image. The southern feature appears to have flowed over a ridge along its western edge. Scientists use these types of relationships to determine which feature formed first. In this case, the ridge probably formed before the flow-like feature that covers it.The image, centered at 22.6 degrees north latitude and 106.7 degrees west longitude, covers an area of 180 by 215 kilometers (112 by 134 miles). The smallest distinguishable features in the image are about 1.1 kilometers (0.7 miles) across. This image was obtained on April 28, 1997, when Galileo was 27,590 kilometers (16,830 miles) from Europa.The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Feature Extraction

CERN Document Server

CERN. Geneva

2015-01-01

Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

Video genre classification using multimodal features

Science.gov (United States)

Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

2003-12-01

We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Science.gov (United States)

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

MRI features associated with acute appendicitis

NARCIS (Netherlands)

Leeuwenburgh, Marjolein M. N.; Jensch, Sebastiaan; Gratama, Jan W. C.; Spilt, Aart; Wiarda, Bart M.; van Es, H. Wouter; Cobben, Lodewijk P. J.; Bossuyt, Patrick M. M.; Boermeester, Marja A.; Stoker, Jaap; Bouma, Wim H.; Houdijk, Alexander P. J.; Richir, Milan C.; Stockmann, Hein B. A. C.; Wiezer, Marinus J.; Verhagen, Thijs

2014-01-01

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith,

Hong Kong English: phonological features

OpenAIRE

Irina-Ana Drobot

2008-01-01

The aim of the paper is to present phonological features of Hong Kong English, which is a variety of New English. I examine features of the sound system (vowel and consonantal systems), characteristics of stress, rhythm, intonation, and phonological processes of the English spoken by Hongkongers. The way in which the accent and characteristics of the Hong Kong variety of English differs from standard, RP English is pointed out. Influences of Chinese and Cantonese on the phonological features ...

Cascaded face alignment via intimacy definition feature

Science.gov (United States)

Li, Hailiang; Lam, Kin-Man; Chiu, Man-Yau; Wu, Kangheng; Lei, Zhibin

2017-09-01

Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement.

Extracellular Palladium Nanoparticle Production using Geobacter sulfurreducens

KAUST Repository

Yates, Matthew D.; Cusick, Roland D.; Logan, Bruce E.

2013-01-01

verified that Pd(0) nanoparticles were predominantly in the EPS surrounding cells in H2-fed cultures, with only a small number of particles visible inside the cell. Separation of the cells and EPS by centrifugation allowed reuse of the cell suspensions

Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

Directory of Open Access Journals (Sweden)

Li Yao

2016-01-01

Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

Temporal feature integration for music genre classification

DEFF Research Database (Denmark)

Meng, Anders; Ahrendt, Peter; Larsen, Jan

2007-01-01

, but they capture neither the temporal dynamics nor dependencies among the individual feature dimensions. Here, a multivariate autoregressive feature model is proposed to solve this problem for music genre classification. This model gives two different feature sets, the diagonal autoregressive (DAR......) and multivariate autoregressive (MAR) features which are compared against the baseline mean-variance as well as two other temporal feature integration techniques. Reproducibility in performance ranking of temporal feature integration methods were demonstrated using two data sets with five and eleven music genres...

Inflation and WMAP three year data. Features have a feature.

Energy Technology Data Exchange (ETDEWEB)

Covi, L.; Hamann, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Melchiorri, A. [INFN, Roma (Italy)]|[Rome-3 Univ. (Italy). Dipt. di Fisica; Slosar, A. [Ljubljana Univ. (Slovenia). Faculty of Mathematics and Physics; Sorbera, I. [Rome-3 Univ. (Italy). Dipt. di Fisica

2006-06-15

The new three year WMAP data seem to confirm the presence of non-standard large scale features in the Cosmic Microwave Anisotropies power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step in the inflaton potential. We show that a step in the potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. (Orig.)

Feature singletons attract spatial attention independently of feature priming.

Science.gov (United States)

Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

2017-08-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

MRI features associated with acute appendicitis

Energy Technology Data Exchange (ETDEWEB)

Leeuwenburgh, Marjolein M.N. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Academic Medical Center, Department of Radiology (G1-223.1), Amsterdam (Netherlands); Jensch, Sebastiaan [Sint Lucas Andreas Hospital, Department of Radiology, Amsterdam (Netherlands); Gratama, Jan W.C. [Gelre Hospitals, Department of Radiology, Apeldoorn (Netherlands); Spilt, Aart [Kennemer Gasthuis, Department of Radiology, Haarlem (Netherlands); Wiarda, Bart M. [Alkmaar Medical Center, Department of Radiology, Alkmaar (Netherlands); Es, H.W. van [Sint Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Cobben, Lodewijk P.J. [Haaglanden Medical Center, Department of Radiology, Leidschendam (Netherlands); Bossuyt, Patrick M.M. [University of Amsterdam, Department of Clinical Epidemiology, Academic Medical Center, Amsterdam (Netherlands); Boermeester, Marja A. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Stoker, Jaap [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Collaboration: on behalf of the OPTIMAP study group

2014-01-15

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

MRI features associated with acute appendicitis

International Nuclear Information System (INIS)

Leeuwenburgh, Marjolein M.N.; Jensch, Sebastiaan; Gratama, Jan W.C.; Spilt, Aart; Wiarda, Bart M.; Es, H.W. van; Cobben, Lodewijk P.J.; Bossuyt, Patrick M.M.; Boermeester, Marja A.; Stoker, Jaap

2014-01-01

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

Textural features for radar image analysis

Science.gov (United States)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

Convergent development of anodic bacterial communities in microbial fuel cells.

KAUST Repository

Yates, Matthew D

2012-05-10

Microbial fuel cells (MFCs) are often inoculated from a single wastewater source. The extent that the inoculum affects community development or power production is unknown. The stable anodic microbial communities in MFCs were examined using three inocula: a wastewater treatment plant sample known to produce consistent power densities, a second wastewater treatment plant sample, and an anaerobic bog sediment. The bog-inoculated MFCs initially produced higher power densities than the wastewater-inoculated MFCs, but after 20 cycles all MFCs on average converged to similar voltages (470±20 mV) and maximum power densities (590±170 mW m(-2)). The power output from replicate bog-inoculated MFCs was not significantly different, but one wastewater-inoculated MFC (UAJA3 (UAJA, University Area Joint Authority Wastewater Treatment Plant)) produced substantially less power. Denaturing gradient gel electrophoresis profiling showed a stable exoelectrogenic biofilm community in all samples after 11 cycles. After 16 cycles the predominance of Geobacter spp. in anode communities was identified using 16S rRNA gene clone libraries (58±10%), fluorescent in-situ hybridization (FISH) (63±6%) and pyrosequencing (81±4%). While the clone library analysis for the underperforming UAJA3 had a significantly lower percentage of Geobacter spp. sequences (36%), suggesting that a predominance of this microbe was needed for convergent power densities, the lower percentage of this species was not verified by FISH or pyrosequencing analyses. These results show that the predominance of Geobacter spp. in acetate-fed systems was consistent with good MFC performance and independent of the inoculum source.

Molecular analysis of phosphate limitation in Geobacteraceae during the bioremediation of a uranium-contaminated aquifer

Energy Technology Data Exchange (ETDEWEB)

N' Guessan, L.A.; Elifantz, H.; Nevin, K.P.; Mouser, P.J.; Methe, B.; Woodard, T. L.; Manley, K.; Williams, K. H.; Wilkins, M. J.; Larsen, J.T.; Long, P. E.; Lovley, D. R.

2009-09-01

Nutrient limitation is an environmental stress that may reduce the effectiveness of bioremediation strategies, especially when the contaminants are organic compounds or when organic compounds are added to promote microbial activities such as metal reduction. Genes indicative of phosphate-limitation were identified via microarray analysis of chemostat cultures of Geobacter sulfureducens. This analysis revealed that genes in the pst-pho operon, which is associated with a high affinity phosphate uptake system in other microorganisms, had significantly higher transcript abundance under phosphate-limiting conditions, with the genes pstB and phoU the most up-regulated. Quantitative PCR analysis of pstB and phoU transcript levels in G. sulfurreducens grown in chemostats demonstrated that the expression of these genes increased when phosphate was removed from the culture medium. Transcripts of pstB and phoU within the subsurface Geobacter species predominating during an in situ uranium bioremediation field experiment were more abundant than in chemostat cultures of G. sulfurreducens that were not limited for phosphate. Addition of phosphate to incubations of subsurface sediments did not stimulate dissimilatory metal reduction. The added phosphate was rapidly adsorbed onto the sediments. The results demonstrate that Geobacter species can effectively reduce U(VI) even when experiencing suboptimal phosphate concentrations and that increasing phosphate availability with phosphate additions is difficult to achieve due to the high reactivity of this compound. This transcript-based approach developed for diagnosing phosphate limitation should be applicable to assessing the potential need for additional phosphate in other bioremediation processes.

Conjunctive Coding of Complex Object Features

Science.gov (United States)

Erez, Jonathan; Cusack, Rhodri; Kendall, William; Barense, Morgan D.

2016-01-01

Critical to perceiving an object is the ability to bind its constituent features into a cohesive representation, yet the manner by which the visual system integrates object features to yield a unified percept remains unknown. Here, we present a novel application of multivoxel pattern analysis of neuroimaging data that allows a direct investigation of whether neural representations integrate object features into a whole that is different from the sum of its parts. We found that patterns of activity throughout the ventral visual stream (VVS), extending anteriorly into the perirhinal cortex (PRC), discriminated between the same features combined into different objects. Despite this sensitivity to the unique conjunctions of features comprising objects, activity in regions of the VVS, again extending into the PRC, was invariant to the viewpoints from which the conjunctions were presented. These results suggest that the manner in which our visual system processes complex objects depends on the explicit coding of the conjunctions of features comprising them. PMID:25921583

Hong Kong English: phonological features

Directory of Open Access Journals (Sweden)

Irina-Ana Drobot

2008-01-01

Full Text Available The aim of the paper is to present phonological features of Hong Kong English, which is a variety of New English. I examine features of the sound system (vowel and consonantal systems, characteristics of stress, rhythm, intonation, and phonological processes of the English spoken by Hongkongers. The way in which the accent and characteristics of the Hong Kong variety of English differs from standard, RP English is pointed out. Influences of Chinese and Cantonese on the phonological features of Hong Kong English are noticeable

Personality Features of Motorists

Directory of Open Access Journals (Sweden)

Andrej Justinek

1997-12-01

Full Text Available Justinek tries to answer the question whether or not motorists have specific personality features which predispose them for safe and well-mannered driving. A good driver should have sensory abilities which enable psycho-motor coordiation of a vehicle, intellectual and cognitive features that are important for solving problems in new, unknown situations, and emotional and motivational trails defining a driver's maturity. Justmek advocates the belief that in training future drivers greater attention should be paid to developing these features which are vital for safe driving and appropriate behaviour of drivers in traffic. He also suggests certain learning methods leading to development of the above­ mentioned personality traits. Justinek introduces the notion of the 'philosophy of driving' as an essential educational category in training future drivers.

Features for detecting smoke in laparoscopic videos

Directory of Open Access Journals (Sweden)

Jalal Nour Aldeen

2017-09-01

Full Text Available Video-based smoke detection in laparoscopic surgery has different potential applications, such as the automatic addressing of surgical events associated with the electrocauterization task and the development of automatic smoke removal. In the literature, video-based smoke detection has been studied widely for fire surveillance systems. Nevertheless, the proposed methods are insufficient for smoke detection in laparoscopic videos because they often depend on assumptions which rarely hold in laparoscopic surgery such as static camera. In this paper, ten visual features based on motion, texture and colour of smoke are proposed and evaluated for smoke detection in laparoscopic videos. These features are RGB channels, energy-based feature, texture features based on gray level co-occurrence matrix (GLCM, HSV colour space feature, features based on the detection of moving regions using optical flow and the smoke colour in HSV colour space. These features were tested on four laparoscopic cholecystectomy videos. Experimental observations show that each feature can provide valuable information in performing the smoke detection task. However, each feature has weaknesses to detect the presence of smoke in some cases. By combining all proposed features smoke with high and even low density can be identified robustly and the classification accuracy increases significantly.

Novel Features for Brain-Computer Interfaces

Science.gov (United States)

Woon, W. L.; Cichocki, A.

2007-01-01

While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which indicate that the proposed method is a potentially useful addition to current feature extraction techniques. PMID:18364991

Feature Binding in Zebrafish

Directory of Open Access Journals (Sweden)

P Neri

2012-07-01

Full Text Available Binding operations are primarily ascribed to cortex or similarly complex avian structures. My experiments show that the zebrafish, a lower vertebrate lacking cortex, supports visual feature binding of form and motion for the purpose of social behavior. These results challenge the notion that feature binding may require highly evolved neural structures and demonstrate that the nervous system of lower vertebrates can afford unexpectedly complex computations.

Ontology patterns for complex topographic feature yypes

Science.gov (United States)

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Assessment of Bacterial Degradation of Aromatic Hydrocarbons in the Environment by Analysis of Stable Carbon Isotope Fractionation

Energy Technology Data Exchange (ETDEWEB)

Meckenstock, Rainer U. [Eberhard-Karls University of Tuebingen, Center for Applied Geoscience (Germany)], E-mail: rainer.meckenstock@uni-tuebingen.de; Morasch, Barbara [University of Konstanz, Faculty of Biology (Germany); Kaestner, Matthias; Vieth, Andrea; Richnow, Hans Hermann [Center for Environmental Research, Department of Remediation Research (Germany)

2002-05-15

{sup 13}C/{sup 12}C stable carbon isotope fractionation was used to assess biodegradation in contaminated aquifers with toluene as a model compound. Different strains of anaerobic bacteria (Thauera aromatica, Geobacter metallireducens, and the sulfate-reducing strain TRM1) showed consistent {sup 13}C/{sup 12}C carbon isotope fractionation with fractionation factors between {alpha}C = 1.0017 and 1.0018. In contrast, three cultures of aerobic organisms, using different mono- and dioxygenase enzyme systems to initiate toluene degradation, showed variable isotope fractionation factors of {alpha}C = 1.0027 (Pseudomonasputida strain mt-2), {alpha}C = 1.0011 (Ralstonia picketii), and{alpha}C = 1.0004 (Pseudomonas putida strain F1). The great variability of isotope fractionation between different aerobic bacterial strains suggests that interpretation of isotope data in oxic habitats can only be qualitative. A soil column was run as a model system for contaminated aquifers with toluene as the carbon source and sulfate as the electron acceptor and samples were taken at different ports along the column. Microbial toluene degradation was calculated based on the {sup 13}C/{sup 12}C isotope fractionation factors of the batch culture experiments together with the observed {sup 13}C/{sup 12}C isotope shifts of the residual toluene fractions. The calculated percentage of biodegradation, B, correlated well with the decreasing toluene concentrations at the sampling ports and indicated the increasing extent of biodegradation along the column. The theoretical toluene concentrations as calculated based on the isotope values matched the measured concentrations at the different sampling ports indicating that the Rayleigh equation can be used to calculate biodegradation in quasi closed systems based on measured isotope shifts. A similar attempt was performed to assess toluene degradation in a contaminated, anoxic aquifer. A transect of groundwater wells was monitored along the main

Feature-level domain adaptation

DEFF Research Database (Denmark)

Kouw, Wouter M.; Van Der Maaten, Laurens J P; Krijthe, Jesse H.

2016-01-01

-level domain adaptation (flda), that models the dependence between the two domains by means of a feature-level transfer model that is trained to describe the transfer from source to target domain. Subsequently, we train a domain-adapted classifier by minimizing the expected loss under the resulting transfer...... modeled via a dropout distribution, which allows the classiffier to adapt to differences in the marginal probability of features in the source and the target domain. Our experiments on several real-world problems show that flda performs on par with state-of-the-art domainadaptation techniques.......Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, whilst test data is sampled from a target domain. This paper proposes and studies an approach, called feature...

Addressing scalability while feature requests persist. A look at NASA Worldview's new features and their implementation.

Science.gov (United States)

King, B. A.

2017-12-01

Worldview is a high-traffic web mapping application created using the JavaScript mapping library, OpenLayers. This presentation will primarily focus on three new features: A wrapping component that seamlessly shows satellite imagery over the dateline where most maps either stop or wrap the imagery of the same date. An animation feature that allows users to select date ranges over which they can animate. An A/B comparison feature that gives users the power to compare imagery between dates and layers. In response to an increasingly large codebase caused by ongoing feature requests, Worldview is transitioning to a smaller core codebase comprised of external reusable modules. When creating a module with the intention of having someone else reuse it for a different task, one inherently starts generating code that is easier to read and easier to maintain. This presentation will show demos of these features and cover development techniques used to create them.

Light field morphing using 2D features.

Science.gov (United States)

Wang, Lifeng; Lin, Stephen; Lee, Seungyong; Guo, Baining; Shum, Heung-Yeung

2005-01-01

We present a 2D feature-based technique for morphing 3D objects represented by light fields. Existing light field morphing methods require the user to specify corresponding 3D feature elements to guide morph computation. Since slight errors in 3D specification can lead to significant morphing artifacts, we propose a scheme based on 2D feature elements that is less sensitive to imprecise marking of features. First, 2D features are specified by the user in a number of key views in the source and target light fields. Then the two light fields are warped view by view as guided by the corresponding 2D features. Finally, the two warped light fields are blended together to yield the desired light field morph. Two key issues in light field morphing are feature specification and warping of light field rays. For feature specification, we introduce a user interface for delineating 2D features in key views of a light field, which are automatically interpolated to other views. For ray warping, we describe a 2D technique that accounts for visibility changes and present a comparison to the ideal morphing of light fields. Light field morphing based on 2D features makes it simple to incorporate previous image morphing techniques such as nonuniform blending, as well as to morph between an image and a light field.

Nonmotor Features in Atypical Parkinsonism.

Science.gov (United States)

Bhatia, Kailash P; Stamelou, Maria

2017-01-01

Atypical parkinsonism (AP) comprises mainly multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD), which are distinct pathological entities, presenting with a wide phenotypic spectrum. The classic syndromes are now called MSA-parkinsonism (MSA-P), MSA-cerebellar type (MSA-C), Richardson's syndrome, and corticobasal syndrome. Nonmotor features in AP have been recognized almost since the initial description of these disorders; however, research has been limited. Autonomic dysfunction is the most prominent nonmotor feature of MSA, but also gastrointestinal symptoms, sleep dysfunction, and pain, can be a feature. In PSP and CBD, the most prominent nonmotor symptoms comprise those deriving from the cognitive/neuropsychiatric domain. Apart from assisting the clinician in the differential diagnosis with Parkinson's disease, nonmotor features in AP have a big impact on quality of life and prognosis of AP and their treatment poses a major challenge for clinicians. © 2017 Elsevier Inc. All rights reserved.

Wilson’s disease: Atypical imaging features

Directory of Open Access Journals (Sweden)

Venugopalan Y Vishnu

2016-10-01

Full Text Available Wilson’s disease is a genetic movement disorder with characteristic clinical and imaging features. We report a 17- year-old boy who presented with sialorrhea, hypophonic speech, paraparesis with repeated falls and recurrent seizures along with cognitive decline. He had bilateral Kayser Flescher rings. Other than the typical features of Wilson’s disease in cranial MRI, there were extensive white matter signal abnormalities (T2 and FLAIR hyperintensities and gyriform contrast enhancement which are rare imaging features in Wilson's disease. A high index of suspicion is required to diagnose Wilson’s disease when atypical imaging features are present.

Multimodal Feature Learning for Video Captioning

Directory of Open Access Journals (Sweden)

Sujin Lee

2018-01-01

Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

Language identification using excitation source features

CERN Document Server

Rao, K Sreenivasa

2015-01-01

This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

Guilt by Association: The 13 Micron Dust Emission Feature and Its Correlation to Other Gas and Dust Features

Science.gov (United States)

Sloan, G. C.; Kraemer, Kathleen E.; Goebel, J. H.; Price, Stephan D.

2003-09-01

A study of all full-scan spectra of optically thin oxygen-rich circumstellar dust shells in the database produced by the Short Wavelength Spectrometer on ISO reveals that the strength of several infrared spectral features correlates with the strength of the 13 μm dust feature. These correlated features include dust features at 19.8 and 28.1 μm and the bands produced by warm carbon dioxide molecules (the strongest of which are at 13.9, 15.0, and 16.2 μm). The database does not provide any evidence for a correlation of the 13 μm feature with a dust feature at 32 μm, and it is more likely that a weak emission feature at 16.8 μm arises from carbon dioxide gas rather than dust. The correlated dust features at 13, 20, and 28 μm tend to be stronger with respect to the total dust emission in semiregular and irregular variables associated with the asymptotic giant branch than in Mira variables or supergiants. This family of dust features also tends to be stronger in systems with lower infrared excesses and thus lower mass-loss rates. We hypothesize that the dust features arise from crystalline forms of alumina (13 μm) and silicates (20 and 28 μm). Based on observations with the ISO, a European Space Agency (ESA) project with instruments funded by ESA member states (especially the Principal Investigator countries: France, Germany, the Netherlands, and the United Kingdom) and with the participation of the Institute of Space and Astronautical Science (ISAS) and the National Aeronautics and Space Administration (NASA).

Comparison of advanced mid-sized reactors regarding passive features, core damage frequencies and core melt retention features

International Nuclear Information System (INIS)

Wider, H.

2005-01-01

New Light Water Reactors, whose regular safety systems are complemented by passive safety systems, are ready for the market. The special aspect of passive safety features is their actuation and functioning independent of the operator. They add significantly to reduce the core damage frequency (CDF) since the operator continues to play its independent role in actuating the regular safety devices based on modern instrumentation and control (I and C). The latter also has passive features regarding the prevention of accidents. Two reactors with significant passive features that are presently offered on the market are the AP1000 PWR and the SWR 1000 BWR. Their passive features are compared and also their core damage frequencies (CDF). The latter are also compared with those of a VVER-1000. A further discussion about the two passive plants concerns their mitigating features for severe accidents. Regarding core-melt retention both rely on in-vessel cooling of the melt. The new VVER-1000 reactor, on the other hand features a validated ex-vessel concept. (author)

Controllable edge feature sharpening for dental applications.

Science.gov (United States)

Fan, Ran; Jin, Xiaogang

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Controllable Edge Feature Sharpening for Dental Applications

Directory of Open Access Journals (Sweden)

Ran Fan

2014-01-01

Full Text Available This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

DEFF Research Database (Denmark)

Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

2006-01-01

FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...

Glacial Features (Point) - Quad 168 (EPPING, NH)

Data.gov (United States)

University of New Hampshire — The Glacial Features (Point) layer describes point features associated with surficial geology. These glacial features include, but are not limited to, delta forsets,...

Microbial Activity Influences Electrical Conductivity of Biofilm Anode

Science.gov (United States)

This study assessed the conductivity of a Geobacter-enriched biofilm anode along with biofilm activity in a microbial electrochemical cell (MxC) equipped with two gold anodes (25 mM acetate medium), as different proton gradients were built throughout the biofilm. There was no pH ...

Partial Epilepsy with Auditory Features

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2004-07-01

Full Text Available The clinical characteristics of 53 sporadic (S cases of idiopathic partial epilepsy with auditory features (IPEAF were analyzed and compared to previously reported familial (F cases of autosomal dominant partial epilepsy with auditory features (ADPEAF in a study at the University of Bologna, Italy.

Feature Extraction Using Fractal Codes

NARCIS (Netherlands)

B.A.M. Schouten (Ben); P.M. de Zeeuw (Paul)

1999-01-01

htmlabstractFast and successful searching for an object in a multimedia database is a highly desirable functionality. Several approaches to content based retrieval for multimedia databases can be found in the literature [9,10,12,14,17]. The approach we consider is feature extraction. A feature can

Remodularizing Java programs for comprehension of features

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2009-01-01

. In absence of these mechanisms, feature implementations tend to be scattered and tangled in terms of object-oriented abstractions, making the code implementing features difficult to locate and comprehend. In this paper we present a semi-automatic method for feature-oriented remodularization of Java programs....... Our method uses execution traces to locate implementations of features, and Java packages to establish explicit feature modules. To evaluate usefulness of the approach, we present a case study where we apply our method to two real-world software systems. The obtained results indicate a significant...

Patch layout generation by detecting feature networks

KAUST Repository

Cao, Yuanhao

2015-02-01

The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines several key ingredients, including feature detection, feature filtering, feature curve extension, patch subdivision and boundary smoothing. Our framework is able to compute patch layouts through concave features as previous approaches, but also able to generate nice layouts through smoothing regions. We demonstrate the effectiveness of our framework by comparing with the state-of-the-art methods.

Feature coding for image representation and recognition

CERN Document Server

Huang, Yongzhen

2015-01-01

This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) D

Currency features for visually impaired people

Science.gov (United States)

Hyland, Sandra L.; Legge, Gordon E.; Shannon, Robert R.; Baer, Norbert S.

1996-03-01

The estimated 3.7 million Americans with low vision experience a uniquely difficult task in identifying the denominations of U.S. banknotes because the notes are remarkably uniform in size, color, and general design. The National Research Council's Committee on Currency Features Usable by the Visually Impaired assessed features that could be used by people who are visually disabled to distinguish currency from other documents and to denominate and authenticate banknotes using available technology. Variation of length and height, introduction of large numerals on a uniform, high-contrast background, use of different colors for each of the six denominations printed, and the introduction of overt denomination codes that could lead to development of effective, low-cost devices for examining banknotes were all deemed features available now. Issues affecting performance, including the science of visual and tactile perception, were addressed for these features, as well as for those features requiring additional research and development. In this group the committee included durable tactile features such as those printed with transparent ink, and the production of currency with holes to indicate denomination. Among long-range approaches considered were the development of technologically advanced devices and smart money.

Spatial distribution of bacterial communities on volumetric and planar anodes in single-chamber air-cathode microbial fuel cells

KAUST Repository

Vargas, Ignacio T.

2013-05-29

Pyrosequencing was used to characterize bacterial communities in air-cathode microbial fuel cells across a volumetric (graphite fiber brush) and a planar (carbon cloth) anode, where different physical and chemical gradients would be expected associated with the distance between anode location and the air cathode. As expected, the stable operational voltage and the coulombic efficiency (CE) were higher for the volumetric anode than the planar anode (0.57V and CE=22% vs. 0.51V and CE=12%). The genus Geobacter was the only known exoelectrogen among the observed dominant groups, comprising 57±4% of recovered sequences for the brush and 27±5% for the carbon-cloth anode. While the bacterial communities differed between the two anode materials, results showed that Geobacter spp. and other dominant bacterial groups were homogenously distributed across both planar and volumetric anodes. This lends support to previous community analysis interpretations based on a single biofilm sampling location in these systems. © 2013 Wiley Periodicals, Inc.

Correlation between microbial community and granule conductivity in anaerobic bioreactors for brewery wastewater treatment

DEFF Research Database (Denmark)

Shrestha, Pravin; Malvankar, Nikhil S.; Werner, Jeffrey

2014-01-01

Prior investigation of an upflow anaerobic sludge blanket (UASB) reactor treating brewery wastes suggested that direct interspecies electron transfer (DIET) significantly contributed to interspecies electron transfer to methanogens. To investigate DIET in granules further, the electrical conducti......Prior investigation of an upflow anaerobic sludge blanket (UASB) reactor treating brewery wastes suggested that direct interspecies electron transfer (DIET) significantly contributed to interspecies electron transfer to methanogens. To investigate DIET in granules further, the electrical...... conductivity and bacterial community composition of granules in fourteen samples from four different UASB reactors treating brewery wastes were investigated. All of the UASB granules were electrically conductive whereas control granules from ANAMMOX (ANaerobic AMMonium OXidation) reactors and microbial...... granules from an aerobic bioreactor designed for phosphate removal were not. There was a moderate correlation (r = 0.67) between the abundance of Geobacter species in the UASB granules and granule conductivity, suggesting that Geobacter contributed to granule conductivity. These results, coupled...

Fall Detection Using Smartphone Audio Features.

Science.gov (United States)

Cheffena, Michael

2016-07-01

An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

Flexible feature interface for multimedia sources

Science.gov (United States)

Coffland, Douglas R [Livermore, CA

2009-06-09

A flexible feature interface for multimedia sources system that includes a single interface for the addition of features and functions to multimedia sources and for accessing those features and functions from remote hosts. The interface utilizes the export statement: export "C" D11Export void FunctionName(int argc, char ** argv,char * result, SecureSession *ctrl) or the binary equivalent of the export statement.

Prostatic adenocarcinoma with glomeruloid features.

Science.gov (United States)

Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

1998-05-01

A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or

Feature extraction using fractal codes

NARCIS (Netherlands)

B.A.M. Ben Schouten; Paul M. de Zeeuw

1999-01-01

Fast and successful searching for an object in a multimedia database is a highly desirable functionality. Several approaches to content based retrieval for multimedia databases can be found in the literature [9,10,12,14,17]. The approach we consider is feature extraction. A feature can be seen as a

Iris recognition based on key image feature extraction.

Science.gov (United States)

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Vehicle barriers: emphasis on natural features

International Nuclear Information System (INIS)

Adams, K.G.; Roscoe, B.J.

1985-07-01

The recent increase in the use of car and truck bombs by terrorist organizations has led NRC to evaluate the adequacy of licensee security against such threats. As part of this evaluation, one of the factors is the effectiveness of terrain and vegetation in providing barriers against the vehicle entry. The effectiveness of natural features is presented in two contexts. First, certain natural features are presented. Second, the effectiveness of combinations of features is presented. In addition to the discussion of natural features, this report provides a discussion of methods to slow vehicles. Also included is an overview of man-made barrier systems, with particular attention to ditches. 17 refs., 49 figs

Contextual Multi-armed Bandits under Feature Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nam, Jun Hyun [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Mo, Sangwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Shin, Jinwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of)

2017-03-03

We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.

Unsupervised feature learning for autonomous rock image classification

Science.gov (United States)

Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

2017-09-01

Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Directory of Open Access Journals (Sweden)

Ahmed Majid Taha

2013-01-01

Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Science.gov (United States)

Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

2013-01-01

When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

Less common CT features of medulloblastoma

International Nuclear Information System (INIS)

Zee, C.S; Segall, H.D.; Miller, C.; Ahmad, J.; McComb, J.G.; Han, J.S.; Park, S.H.

1982-01-01

While many medulloblastomas have characteristic features on computed tomography (CT), a significant number have atypical features, including a cystic or necrotic component, calcification, hemorrhage, lack of contrast enhancement, and eccentric location, and/or direct supratentorial extension. Of 30 consecutive untreated cases reviewed by the authors, 14 (47%) had such findings. Failure to make the proper diagnosis will result in some cases if these features are not recognized as possible signs of medulloblastoma

Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

Science.gov (United States)

Wang, Rui; Zhu, Zhengdan; Zhang, Liang

2015-05-01

Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

Enrichment of specific protozoan populations during in situ bioremediation of uranium-contaminated groundwater

Energy Technology Data Exchange (ETDEWEB)

Holmes, Dawn; Giloteaux, L.; Williams, Kenneth H.; Wrighton, Kelly C.; Wilkins, Michael J.; Thompson, Courtney A.; Roper, Thomas J.; Long, Philip E.; Lovley, Derek

2013-07-28

The importance of bacteria in the anaerobic bioremediation of groundwater polluted with organic and/or metal contaminants is well-recognized and in some instances so well understood that modeling of the in situ metabolic activity of the relevant subsurface microorganisms in response to changes in subsurface geochemistry is feasible. However, a potentially significant factor influencing bacterial growth and activity in the subsurface that has not been adequately addressed is protozoan predation of the microorganisms responsible for bioremediation. In field experiments at a uranium-contaminated aquifer located in Rifle, CO, acetate amendments initially promoted the growth of metal-reducing Geobacter species followed by the growth of sulfate-reducers, as previously observed. Analysis of 18S rRNA gene sequences revealed a broad diversity of sequences closely related to known bacteriovorous protozoa in the groundwater prior to the addition of acetate. The bloom of Geobacter species was accompanied by a specific enrichment of sequences most closely related to the amoeboid flagellate, Breviata anathema, which at their peak accounted for over 80% of the sequences recovered. The abundance of Geobacter species declined following the rapid emergence of B. anathema. The subsequent growth of sulfate-reducing Peptococcaceae was accompanied by another specific enrichment of protozoa, but with sequences most similar to diplomonadid flagellates from the family Hexamitidae, which accounted for up to 100% of the sequences recovered during this phase of the bioremediation. These results suggest a prey-predator response with specific protozoa responding to increased availability of preferred prey bacteria. Thus, quantifying the influence of protozoan predation on the growth, activity, and composition of the subsurface bacterial community is essential for predictive modeling of in situ uranium bioremediation strategies.

Discriminative semi-supervised feature selection via manifold regularization.

Science.gov (United States)

Xu, Zenglin; King, Irwin; Lyu, Michael Rung-Tsong; Jin, Rong

2010-07-01

Feature selection has attracted a huge amount of interest in both research and application communities of data mining. We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number of labeled samples are usually insufficient for identifying the relevant features, the critical problem arising from semi-supervised feature selection is how to take advantage of the information underneath the unlabeled data. To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization. The proposed approach selects features through maximizing the classification margin between different classes and simultaneously exploiting the geometry of the probability distribution that generates both labeled and unlabeled data. In comparison with previous semi-supervised feature selection algorithms, our proposed semi-supervised feature selection method is an embedded feature selection method and is able to find more discriminative features. We formulate the proposed feature selection method into a convex-concave optimization problem, where the saddle point corresponds to the optimal solution. To find the optimal solution, the level method, a fairly recent optimization method, is employed. We also present a theoretic proof of the convergence rate for the application of the level method to our problem. Empirical evaluation on several benchmark data sets demonstrates the effectiveness of the proposed semi-supervised feature selection method.

Feature Evaluation for Building Facade Images - AN Empirical Study

Science.gov (United States)

Yang, M. Y.; Förstner, W.; Chai, D.

2012-08-01

The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

Schizophrenia classification using functional network features

Science.gov (United States)

Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

2012-03-01

This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

Hierarchical feature selection for erythema severity estimation

Science.gov (United States)

Wang, Li; Shi, Chenbo; Shu, Chang

2014-10-01

At present PASI system of scoring is used for evaluating erythema severity, which can help doctors to diagnose psoriasis [1-3]. The system relies on the subjective judge of doctors, where the accuracy and stability cannot be guaranteed [4]. This paper proposes a stable and precise algorithm for erythema severity estimation. Our contributions are twofold. On one hand, in order to extract the multi-scale redness of erythema, we design the hierarchical feature. Different from traditional methods, we not only utilize the color statistical features, but also divide the detect window into small window and extract hierarchical features. Further, a feature re-ranking step is introduced, which can guarantee that extracted features are irrelevant to each other. On the other hand, an adaptive boosting classifier is applied for further feature selection. During the step of training, the classifier will seek out the most valuable feature for evaluating erythema severity, due to its strong learning ability. Experimental results demonstrate the high precision and robustness of our algorithm. The accuracy is 80.1% on the dataset which comprise 116 patients' images with various kinds of erythema. Now our system has been applied for erythema medical efficacy evaluation in Union Hosp, China.

Discriminating Induced-Microearthquakes Using New Seismic Features

Science.gov (United States)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.

Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

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.

The Non-motor Features of Essential Tremor: A Primary Disease Feature or Just a Secondary Phenomenon?

Directory of Open Access Journals (Sweden)

Ketan Jhunjhunwala

2014-08-01

Full Text Available Essential tremor (ET is a pathologically heterogeneous neurodegenerative disorder with both motor and increasingly recognized non-motor features. It is debated whether the non-motor manifestations in ET result from widespread neurodegeneration or are merely secondary to impaired motor functions and decreased quality of life due to tremor. It is important to review these features to determine how to best treat the non-motor symptoms of patients and to understand the basic pathophysiology of the disease and develop appropriate pharmacotherapies. In this review, retrospective and prospective clinical studies were critically analyzed to identify possible correlations between the severities of non-motor features and tremor. We speculated that if such a correlation existed, the non-motor features were likely to be secondary to tremor. According to the current literature, the deficits in executive function, attention, concentration, and memory often observed in ET are likely to be a primary manifestation of the disease. It has also been documented that patients with ET often exhibit characteristic personality traits. However, it remains to be determined whether the other non-motor features often seen in ET, such as anxiety, depression, and sleep disturbances are primary or secondary to motor manifestations of ET and subsequent poor quality of life. Finally, there is evidence that patients with ET can also have impaired color vision, disturbances of olfaction, and hearing impairments, though there are few studies in these areas. Further investigations of large cohorts of patients with ET are required to understand the prevalence, nature, and true significance of the non-motor features in ET.

CT features of renal epithelioid angiomyolipomas

International Nuclear Information System (INIS)

Hu Xiaoyun; Fang Xiangming; Hu Chunhong; Chen Hongwei; Cui Lei; Bao Jian; Yao Xuanjun

2010-01-01

Objective: To explore the CT and pathological features of renal epithelioid angiomyolipoma (EAML). Methods: Clinical data and CT images from ten cases with EAML proved by surgery and pathology were retrospectively analyzed. All cases were performed with plain and contrast enhanced CT scans. Results: CT features: higher pre-contrasted density than kidney, bulging from kidney, absent of fat, markedly heterogeneous enhancement (quick wash-in and slow wash-out), big size without lobular sign, complete capsule with clear margin and mild necrostic area. Pathological features: diffuse sheets of epithelioid cells were found under microscopy with immunohistochemistrical findings including positivity for HMB-45 and negativity for EMA. Conclusion: Some specific CT features, which is correlated well with the pathological findings, provide helpful information in the primary diagnosis of EAML. (authors)

Feature Extraction in Radar Target Classification

Directory of Open Access Journals (Sweden)

Z. Kus

1999-09-01

Full Text Available This paper presents experimental results of extracting features in the Radar Target Classification process using the J frequency band pulse radar. The feature extraction is based on frequency analysis methods, the discrete-time Fourier Transform (DFT and Multiple Signal Characterisation (MUSIC, based on the detection of Doppler effect. The analysis has turned to the preference of DFT with implemented Hanning windowing function. We assumed to classify targets-vehicles into two classes, the wheeled vehicle and tracked vehicle. The results show that it is possible to classify them only while moving. The feature of the class results from a movement of moving parts of the vehicle. However, we have not found any feature to classify the wheeled and tracked vehicles while non-moving, although their engines are on.

Review of research in feature based design

NARCIS (Netherlands)

Salomons, O.W.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

1993-01-01

Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems

Genetic search feature selection for affective modeling

DEFF Research Database (Denmark)

Martínez, Héctor P.; Yannakakis, Georgios N.

2010-01-01

Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

Feature Scaling via Second-Order Cone Programming

Directory of Open Access Journals (Sweden)

Zhizheng Liang

2016-01-01

Full Text Available Feature scaling has attracted considerable attention during the past several decades because of its important role in feature selection. In this paper, a novel algorithm for learning scaling factors of features is proposed. It first assigns a nonnegative scaling factor to each feature of data and then adopts a generalized performance measure to learn the optimal scaling factors. It is of interest to note that the proposed model can be transformed into a convex optimization problem: second-order cone programming (SOCP. Thus the scaling factors of features in our method are globally optimal in some sense. Several experiments on simulated data, UCI data sets, and the gene data set are conducted to demonstrate that the proposed method is more effective than previous methods.

Quantification of the methane concentration using anaerobic oxidation of methane coupled to extracellular electron transfer

Science.gov (United States)

A biofilm anode acclimated with acetate, acetate+methane, and methane growth media for over three years produced a steady current density of 1.6-2.3 mA/m^2 in a microbial electrochemical cell (MxC) fed with methane as the sole electron donor. Geobacter was the dominant genus for...

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

Science.gov (United States)

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Integrated Phoneme Subspace Method for Speech Feature Extraction

Directory of Open Access Journals (Sweden)

Park Hyunsin

2009-01-01

Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.

Does Attention Serve to Integrate Features?

Science.gov (United States)

Navon, David; Treisman, Anne

1990-01-01

An article and two commentaries consider the attentional feature-integration theory proposed by A. Treisman and colleagues. Hypotheses about the encoding of conjunctions are reviewed. Whether or not data support perceptual feature-integration is argued. (SLD)

14 CFR 35.7 - Features and characteristics.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Features and characteristics. 35.7 Section... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have features or characteristics, revealed by any test or analysis or known to the applicant, that make it...

Finger vein recognition based on the hyperinformation feature

Science.gov (United States)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Multi-scale salient feature extraction on mesh models

KAUST Repository

Yang, Yongliang; Shen, ChaoHui

2012-01-01

We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

Passive Safety Features for Small Modular Reactors

International Nuclear Information System (INIS)

Ingersoll, Daniel T.

2010-01-01

The rapid growth in the size and complexity of commercial nuclear power plants in the 1970s spawned an interest in smaller, simpler designs that are inherently or intrinsically safe through the use of passive design features. Several designs were developed, but none were ever built, although some of their passive safety features were incorporated into large commercial plant designs that are being planned or built today. In recent years, several reactor vendors are actively redeveloping small modular reactor (SMR) designs with even greater use of passive features. Several designs incorporate the ultimate in passive safety they completely eliminate specific accident initiators from the design. Other design features help to reduce the likelihood of an accident or help to mitigate the accidents consequences, should one occur. While some passive safety features are common to most SMR designs, irrespective of the coolant technology, other features are specific to water, gas, or liquid-metal cooled SMR designs. The extensive use of passive safety features in SMRs promise to make these plants highly robust, protecting both the general public and the owner/investor. Once demonstrated, these plants should allow nuclear power to be used confidently for a broader range of customers and applications than will be possible with large plants alone.

Effective traffic features selection algorithm for cyber-attacks samples

Science.gov (United States)

Li, Yihong; Liu, Fangzheng; Du, Zhenyu

2018-05-01

By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

Prominent feature extraction for review analysis: an empirical study

Science.gov (United States)

Agarwal, Basant; Mittal, Namita

2016-05-01

Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

MCNP4A: Features and philosophy

International Nuclear Information System (INIS)

Hendricks, J.S.

1993-01-01

This paper describes MCNP, states its philosophy, introduces a number of new features becoming available with version MCNP4A, and answers a number of questions asked by participants in the workshop. MCNP is a general-purpose three-dimensional neutron, photon and electron transport code. Its philosophy is ''Quality, Value and New Features.'' Quality is exemplified by new software quality assurance practices and a program of benchmarking against experiments. Value includes a strong emphasis on documentation and code portability. New features are the third priority. MCNP4A is now available at Los Alamos. New features in MCNP4A include enhanced statistical analysis, distributed processor multitasking, new photon libraries, ENDF/B-VI capabilities, X-Windows graphics, dynamic memory allocation, expanded criticality output, periodic boundaries, plotting of particle tracks via SABRINA, and many other improvements. 23 refs

Interplay of a multiplicity of security features

Science.gov (United States)

Moser, Jean-Frederic

2000-04-01

The great variety of existing security features can cause difficulty in choosing the adequate set for a particular security document. Considering the cost/benefit aspects with respect to the overall protection performance requested, a choice has to be made, for example, between either few features of high-security value or numerous many, less- resistant features. Another choice is the high versus low complexity of one particular features. A study aimed at providing a decision basis is a challenging matter because it involves human factors. Attention, perception, physiology of seeing and habits - to name some of the factors - are intangibles and are subject to evaluations involving normally a great number of experiments, if they are to be representative. The opportunity was given for a case study with the introduction of new Swiss banknotes between 1995 and 1998, because the new banknotes represent a novelty in the sense of the multiplicity and interplay of its optical security features. We have analyzed 652 articles which appeared in the press media concerning the new banknotes, seeking especially for peoples' reaction towards the security features.

Feature Vector Construction Method for IRIS Recognition

Science.gov (United States)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Disruption of visual feature binding in working memory.

Science.gov (United States)

Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

2011-01-01

In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.

Feature-based Alignment of Volumetric Multi-modal Images

Science.gov (United States)

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Feature-Oriented Programming with Object Algebras

NARCIS (Netherlands)

B.C.d.S. Oliveira (Bruno); T. van der Storm (Tijs); A. Loh; W.R. Cook

2013-01-01

htmlabstractObject algebras are a new programming technique that enables a simple solution to basic extensibility and modularity issues in programming languages. While object algebras excel at defining modular features, the composition mechanisms for object algebras (and features) are still

Biometric feature extraction using local fractal auto-correlation

International Nuclear Information System (INIS)

Chen Xi; Zhang Jia-Shu

2014-01-01

Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

Image feature detectors and descriptors foundations and applications

CERN Document Server

Hassaballah, Mahmoud

2016-01-01

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition. .

Organization Features and School Performance

OpenAIRE

Atkins, Lois Major

2005-01-01

The purpose of this study was to determine the odds of school organization features predicting schools meeting district or state performance goals. The school organization features were organizational complexity, shared decision making, and leadership behavior. The dependent variable was school performance, operationally defined as a principalâ s yes response or no response to the question, â did your school meet district or state performance goals.â The independent variables representing...

Designing attractive gamification features for collaborative storytelling websites.

Science.gov (United States)

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

Discovering highly informative feature set over high dimensions

KAUST Repository

Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

2012-01-01

For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

Discovering highly informative feature set over high dimensions

KAUST Repository

Zhang, Chongsheng

2012-11-01

For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

Feature Selection for Chemical Sensor Arrays Using Mutual Information

Science.gov (United States)

Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

2014-01-01

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

The radiographic features of familial expansile osteolysis

International Nuclear Information System (INIS)

Crone, M.D.; Wallace, R.G.H.

1990-01-01

The radiographic features of a unique autosomal dominant bone dysplasia are presented. The features are classified as generalised and/or focal. Generalised features are either altered trabecular pattern or modelling abnormalities. Focal features comprise lytic areas which progressively enlarge, producing expansion of the bone and eventual disintegration due to fibrous and finally fatty replacement of the normal medulla. Almost 90% of these lesions occur in the appendicular skeleton. Clinically, hearing loss is the earliest manifestation of the disease, presenting sometimes as early as 4 years of age. Apical and cervical resorption of teeth is extremely common, resulting in premature loss of teeth. Radiologically, the differential diagnosis refers to Paget's disease, polyostotic fibrous dysplasia, and osteofibrous dysplasia. The progressive destruction of the bone is similar to massive osteolysis (Gorham's disease). The radiographic features in combination with the histopathology render the condition unique. (orig.)

Probabilistic Slow Features for Behavior Analysis

NARCIS (Netherlands)

Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitidis, Symeon; Pantic, Maja

A recently introduced latent feature learning technique for time-varying dynamic phenomena analysis is the so-called slow feature analysis (SFA). SFA is a deterministic component analysis technique for multidimensional sequences that, by minimizing the variance of the first-order time derivative

Learning slow features for behavior analysis

NARCIS (Netherlands)

Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitids, Symeon; Pantic, Maja

2013-01-01

A recently introduced latent feature learning technique for time varying dynamic phenomena analysis is the socalled Slow Feature Analysis (SFA). SFA is a deterministic component analysis technique for multi-dimensional sequences that by minimizing the variance of the first order time derivative

Aging, selective attention, and feature integration.

Science.gov (United States)

Plude, D J; Doussard-Roosevelt, J A

1989-03-01

This study used feature-integration theory as a means of determining the point in processing at which selective attention deficits originate. The theory posits an initial stage of processing in which features are registered in parallel and then a serial process in which features are conjoined to form complex stimuli. Performance of young and older adults on feature versus conjunction search is compared. Analyses of reaction times and error rates suggest that elderly adults in addition to young adults, can capitalize on the early parallel processing stage of visual information processing, and that age decrements in visual search arise as a result of the later, serial stage of processing. Analyses of a third, unconfounded, conjunction search condition reveal qualitatively similar modes of conjunction search in young and older adults. The contribution of age-related data limitations is found to be secondary to the contribution of age decrements in selective attention.

Behind every innovative solution lies an obscure feature

Directory of Open Access Journals (Sweden)

Lee Spector (Fellow ISGEC

2012-06-01

Full Text Available The Obscure Features Hypothesis (OFH for innovation states that a two-step process undergirds almost all innovative solutions: (1 notice an infrequently observed or new (i.e., obscure feature of the problem and (2 construct an interaction involving the obscure feature that produces the desired effects to solve the problem. The OFH leads to a systematic derivation of innovation-enhancing techniques by engaging in two tasks. First, we developed a 32-category system of the types of features possessable by a physical object or material. This Feature Type Taxonomy (FTT provides a panoramic view of the space of features and assists in searches for the obscure ones. Second, we are articulating the many cognitive reasons that obscure features are overlooked and are developing countering techniques for each known reason. We present the implications and techniques of the OFH, as well as indicate how software can assist innovators in the effective use of these innovation-enhancing techniques.

Mammographic feature enhancement by multiscale analysis

International Nuclear Information System (INIS)

Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

1994-01-01

This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

Laboratory simulation of infrared astrophysical features

International Nuclear Information System (INIS)

Rose, L.A.

1979-01-01

Laboratory infrared emission and absorption spectra have been taken of terrestrial silicates, meteorites and lunar soils in the form of micrometer and sub-micrometer grains. The emission spectra were taken in a way that imitates telescopic observations. The purpose was to see which materials best simulate the 10 μm astrophysical feature. The emission spectra of dunite, fayalite and Allende give a good fit to the 10 μm broadband emission feature of comets Bennett and Kohoutek. A study of the effect of grain size on the presence of the 10 μm emission features of dunite shows that for particles larger than 37 μm no feature is seen. The emission spectrum of the Murray meteorite, a Type 2 carbonaceous chondrite, is quite similar to the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Hydrous silicates or amorphous magnesium silicates in combination with high-temperature condensates, such as olivine or anorthite, would yield spectra that match the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Glassy olivine and glassy anorthite in approximately equal proportions would also give a spectrum that is a good fit to the cometary 10 μm feature. (Auth.)

Joint Feature Selection and Classification for Multilabel Learning.

Science.gov (United States)

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Automatic feature-based grouping during multiple object tracking.

Science.gov (United States)

Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

2013-12-01

Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

Spatiotemporal Features for Asynchronous Event-based Data

Directory of Open Access Journals (Sweden)

Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

Science.gov (United States)

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Critical feature analysis of a radiotherapy machine

International Nuclear Information System (INIS)

Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

2005-01-01

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

Analysing Feature Model Changes using FMDiff

NARCIS (Netherlands)

Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

2015-01-01

Evolving a large scale, highly variable sys- tems is a challenging task. For such a system, evolution operations often require to update consistently both their implementation and its feature model. In this con- text, the evolution of the feature model closely follows the evolution of the system.

Graphical matching rules for cardinality based service feature diagrams

Directory of Open Access Journals (Sweden)

Faiza Kanwal

2017-03-01

Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.

Robust emotion recognition using spectral and prosodic features

CERN Document Server

Rao, K Sreenivasa

2013-01-01

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

Video Scene Parsing with Predictive Feature Learning

OpenAIRE

Jin, Xiaojie; Li, Xin; Xiao, Huaxin; Shen, Xiaohui; Lin, Zhe; Yang, Jimei; Chen, Yunpeng; Dong, Jian; Liu, Luoqi; Jie, Zequn; Feng, Jiashi; Yan, Shuicheng

2016-01-01

In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we contribute two novel methods that constitute a unified parsing framework. (1) \\textbf{Predictive feature learning}} from nearly unlimited unlabeled video data. Different from existing methods learning features from single frame parsing, we learn spatiotemporal discriminative features by enforcing a parsing network to ...

Characters Feature Extraction Based on Neat Oracle Bone Rubbings

OpenAIRE

Lei Guo

2013-01-01

In order to recognize characters on the neat oracle bone rubbings, a new mesh point feature extraction algorithm was put forward in this paper by researching and improving of the existing coarse mesh feature extraction algorithm and the point feature extraction algorithm. Some improvements of this algorithm were as followings: point feature was introduced into the coarse mesh feature, the absolute address was converted to relative address, and point features have been changed grid and positio...

Speech recognition using articulatory and excitation source features

CERN Document Server

Rao, K Sreenivasa

2017-01-01

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

MRI features of placenta accreta

International Nuclear Information System (INIS)

Cao Manrui; Du Mu; Huang Yi; Liu Bingguang; Zhang Fangjing; Guo Jimin; Zhu Zhijun

2012-01-01

Objective: To investigate the MRI features of placenta accreta. Methods: From Apr 2009 to Jun 2011, 15 patients with placenta accrete received MRI examination. In them, placenta accreta was diagnosed based on clinical manifestations or postoperative histopathology. The MR features of placenta accreta in them (study group) were retrospectively analyzed and compared with those in 15 pregnant women without placenta accreta (control group) with Fisher exact test. Results: In the 15 patients with placenta accreta,uterine bulging and (or) a focal outward contour bulge was detected in 14 patients; heterogeneous signal intensity in the placenta was detected in 15 patients; dark intraplacental bands on T 2 -weighted images was detected in 15 patients; and increased subplacental vascularity was detected in 11 patients on T 1 - weighted images. In the study group, 14 patients showed at least three of the above four features, and in all of them uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images were detected; one patient showed heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity. In the control group,none patient had three of the above features.Uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity were detected in 3, 6, 3 and 4 patients (P=0.000, 0.001, 0.000 and 0.027), respectively. Conclusions: The main MRI features of placenta accreta are uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images Besides, increased subplacental vascularity also could provide useful information for the diagnosis of placenta accreta. (authors)

A study on feature analysis for musical instrument classification.

Science.gov (United States)

Deng, Jeremiah D; Simmermacher, Christian; Cranefield, Stephen

2008-04-01

In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.

Audio feature extraction using probability distribution function

Science.gov (United States)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Temporality of Features in Near-Death Experience Narratives

Directory of Open Access Journals (Sweden)

Charlotte Martial

2017-06-01

Full Text Available Background: After an occurrence of a Near-Death Experience (NDE, Near-Death Experiencers (NDErs usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area.Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives as well as the most frequently reported temporality sequences of features.Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32. A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features.Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs.Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

Feature Optimization for Long-Range Visual Homing in Changing Environments

Directory of Open Access Journals (Sweden)

Qidan Zhu

2014-02-01

Full Text Available This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

Gene expression correlates with process rates quantified for sulfate- and Fe(III-reducing bacteria in U(VI-contaminated sediments

Directory of Open Access Journals (Sweden)

Denise M Akob

2012-08-01

Full Text Available Though iron- and sulfate-reducing bacteria are well known for mediating uranium(VI reduction in contaminated subsurface environments, quantifying the in situ activity of the microbial groups responsible remains a challenge. The objective of this study was to demonstrate the use of quantitative molecular tools that target mRNA transcripts of key genes related to Fe(III and sulfate reduction pathways in order to monitor these processes during in situ U(VI remediation in the subsurface. Expression of the Geobacteraceae-specific citrate synthase gene (gltA and the dissimilatory (bisulfite reductase gene (dsrA, were correlated with the activity of iron- or sulfate-reducing microorganisms, respectively, under stimulated bioremediation conditions in microcosms of sediments sampled from the U.S. Department of Energy’s Oak Ridge Integrated Field Research Challenge (OR-IFRC site at Oak Ridge, Tennessee. In addition, Geobacteraceae-specific gltA and dsrA transcript levels were determined in parallel with the predominant electron acceptors present in moderately and highly contaminated subsurface sediments from the OR-IFRC. Phylogenetic analysis of the cDNA generated from dsrA mRNA, sulfate-reducing bacteria-specific 16S rRNA, and gltA mRNA identified activity of specific microbial groups. Active sulfate reducers were members of the Desulfovibrio, Desulfobacterium, and Desulfotomaculum genera. Members of the subsurface Geobacter clade, closely related to uranium-reducing Geobacter uraniireducens and Geobacter daltonii, were the metabolically-active iron-reducers in biostimulated microcosms and in situ core samples. Direct correlation of transcripts and process rates demonstrated evidence of competition between the functional guilds in subsurface sediments. We further showed that active populations of Fe(III-reducing bacteria and sulfate-reducing bacteria are present in OR-IFRC sediments and are good potential targets for in situ bioremediation.

Acoustic Features Influence Musical Choices Across Multiple Genres.

Science.gov (United States)

Barone, Michael D; Bansal, Jotthi; Woolhouse, Matthew H

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning.

Imaging features of kaposiform lymphangiomatosis

International Nuclear Information System (INIS)

Goyal, Pradeep; Alomari, Ahmad I.; Shaikh, Raja; Chaudry, Gulraiz; Kozakewich, Harry P.; Perez-Atayde, Antonio R.; Trenor, Cameron C.; Fishman, Steven J.; Greene, Arin K.

2016-01-01

Kaposiform lymphangiomatosis is a rare, aggressive lymphatic disorder. The imaging and presenting features of kaposiform lymphangiomatosis can overlap with those of central conducting lymphatic anomaly and generalized lymphatic anomaly. To analyze the imaging findings of kaposiform lymphangiomatosis disorder and highlight features most suggestive of this diagnosis. We retrospectively identified and characterized 20 children and young adults with histopathological diagnosis of kaposiform lymphangiomatosis and radiologic imaging referred to the vascular anomalies center between 1995 and 2015. The median age at onset was 6.5 years (range 3 months to 27 years). The most common presenting features were respiratory compromise (dyspnea, cough, chest pain; 55.5%), swelling/mass (25%), bleeding (15%) and fracture (5%). The thoracic cavity was involved in all patients; all patients had mediastinal involvement followed by lung parenchymal disease (90%) and pleural (85%) and pericardial (50%) effusions. The most common extra-thoracic sites of disease were the retroperitoneum (80%), bone (60%), abdominal viscera (55%) and muscles (45%). There was characteristic enhancing and infiltrative soft-tissue thickening in the mediastinum and retroperitoneum extending along the lymphatic distribution. Kaposiform lymphangiomatosis has overlapping imaging features with central conducting lymphatic anomaly and generalized lymphatic anomaly. Presence of mediastinal or retroperitoneal enhancing and infiltrative soft-tissue disease along the lymphatic distribution, hemorrhagic effusions and moderate thrombocytopenia (50-100,000/μl) should favor diagnosis of kaposiform lymphangiomatosis. (orig.)

Spectral features in the cosmic ray fluxes

Science.gov (United States)

Lipari, Paolo

2018-01-01

The cosmic ray energy distributions contain spectral features, that is narrow energy regions where the slope of the spectrum changes rapidly. The identification and study of these features is of great importance to understand the astrophysical mechanisms of acceleration and propagation that form the spectra. In first approximation a spectral feature is often described as a discontinuous change in slope, however very valuable information is also contained in its width, that is the length of the energy interval where the change in spectral index develops. In this work we discuss the best way to define and parameterize the width a spectral feature, and for illustration discuss some of the most prominent known structures.

A Novel Real-Time Feature Matching Scheme

Directory of Open Access Journals (Sweden)

Ying Liu

2014-02-01

Full Text Available Affine Scale Invariant Feature Transform (ASIFT can obtain fully affine invariance, however, its time cost reaches about twice that in Scale Invariant Feature Transform (SIFT. We propose an improved ASIFT algorithm based on feature points in scale space for real-time application. In order to detect the affine invariant feature point, we establish a second-order difference of Gaussian (DOG pyramid and replace the extreme detection in the DOG pyramid by zero detection in the proposed second-order DOG pyramid, which decreases the complexity of the scheme. Experimental results show that the proposed method has a big progress in the real-time performance compared to the traditional one, while preserving the fully affine invariance and precision.

Single-labelled music genre classification using content-based features

CSIR Research Space (South Africa)

Ajoodha, R

2015-11-01

Full Text Available In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these features into four groups: features extracted from the Fourier transform’s magnitude spectrum, features designed...

SIP-FS: a novel feature selection for data representation

Directory of Open Access Journals (Sweden)

Yiyou Guo

2018-02-01

Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

Integration of heterogeneous features for remote sensing scene classification

Science.gov (United States)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 – 4.9 % and 1.9 – 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 – 0.006 % and 0.002 – 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respectively. GRLVQ permits objective feature reduction by inclusion of all processing stages, but is not as accurate as SVM.

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM.

Tunable features of magnetoelectric transformers.

Science.gov (United States)

Dong, Shuxiang; Zhai, Junyi; Priya, Shashank; Li, Jie-Fang; Viehland, Dwight

2009-06-01

We have found that magnetostrictive FeBSiC alloy ribbons laminated with piezoelectric Pb(Zr,Ti)O(3) fiber can act as a tunable transformer when driven under resonant conditions. These composites were also found to exhibit the strongest resonant magnetoelectric voltage coefficient of 750 V/cm-Oe. The tunable features were achieved by applying small dc magnetic biases of -5 transformer features can be attributed to large changes in the piezomagnetic coefficient and permeability of the magnetostrictive phase under H(dc).

Enhanced feature integration in musicians

DEFF Research Database (Denmark)

Hansen, Niels Christian; Højlund, Andreas; Møller, Cecilie

the classical oddball control paradigm which used identical sounds. This novel finding supports the dependent processing hypothesis suggesting that musicians recruit overlapping neural resources facilitating more holistic representations of domain-relevant stimuli. These specialised refinements in predictive......Distinguishing and integrating features of sensory input is essential to human survival and no less paramount in music perception and cognition. Yet, little is known about training-induced plasticity of neural mechanisms for auditory feature integration. This study aimed to contrast the two...

Solving jigsaw puzzles using image features

DEFF Research Database (Denmark)

Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus

2008-01-01

In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm i...

FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

Directory of Open Access Journals (Sweden)

M. Y. Yang

2012-08-01

Full Text Available The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

Learning Transferable Features with Deep Adaptation Networks

OpenAIRE

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

2015-01-01

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

SIFT based algorithm for point feature tracking

Directory of Open Access Journals (Sweden)

Adrian BURLACU

2007-12-01

Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.

Mining Videos for Features that Drive Attention

Science.gov (United States)

2015-04-01

that can be added or removed from the final saliency computation. Examples of these features include intensity contrast, motion energy , color opponent...corresponding to the image. Each pixel in the feature map indicates the energy that the feature in question contributes at that location. In the standard...eye and head animation using a neurobio - logical model of visual attention. In: Bosacchi B, Fogel DB, Bezdek JC (eds) Proceedings of SPIE 48th annual

Radiographic features of periapical cysts and granulomas

OpenAIRE

Zain, R. B.; Roswati, N.; Ismail, K.

1989-01-01

Many studies have been reported on radiographic lesion sizes of periapical lesions. However no studies have been reported on prevalences of subjective radiographic features in these lesions except for the early assumption that a periapical cyst usually exhibit a radiopaque cortex. This study is conducted to evaluate the prevalences of several subjective radiographic features of periapical cysts and granulomas in the hope to identify features that maybe suggestive of either diagnosis. The resu...

PROBLEMATIC FEATURES OF THE POLITICAL DECISION MAKERS

OpenAIRE

Aleksey Sergeevih Voynov

2014-01-01

Purpose: identify the most important features in the process of making political decisions that affect the effectiveness of problem-solving situationsScientific novelty: as a result of the analysis identified the problematic features of major importance for the efficiency of the development and adoption of the most rational solution to a problem situation.Results: the analysis of the most significant features affecting the quality of decisions among them the interest of the person making deci...

Recognition of handwritten characters using local gradient feature descriptors

NARCIS (Netherlands)

Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

2015-01-01

Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors

MetaFIND: A feature analysis tool for metabolomics data

Directory of Open Access Journals (Sweden)

Cunningham Pádraig

2008-11-01

Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

Interactive music composition driven by feature evolution.

Science.gov (United States)

Kaliakatsos-Papakostas, Maximos A; Floros, Andreas; Vrahatis, Michael N

2016-01-01

Evolutionary music composition is a prominent technique for automatic music generation. The immense adaptation potential of evolutionary algorithms has allowed the realisation of systems that automatically produce music through feature and interactive-based composition approaches. Feature-based composition employs qualitatively descriptive music features as fitness landmarks. Interactive composition systems on the other hand, derive fitness directly from human ratings and/or selection. The paper at hand introduces a methodological framework that combines the merits of both evolutionary composition methodologies. To this end, a system is presented that is organised in two levels: the higher level of interaction and the lower level of composition. The higher level incorporates the particle swarm optimisation algorithm, along with a proposed variant and evolves musical features according to user ratings. The lower level realizes feature-based music composition with a genetic algorithm, according to the top level features. The aim of this work is not to validate the efficiency of the currently utilised setup in each level, but to examine the convergence behaviour of such a two-level technique in an objective manner. Therefore, an additional novelty in this work concerns the utilisation of artificial raters that guide the system through the space of musical features, allowing the exploration of its convergence characteristics: does the system converge to optimal melodies, is this convergence fast enough for potential human listeners and is the trajectory to convergence "interesting' and "creative" enough? The experimental results reveal that the proposed methodological framework represents a fruitful and robust, novel approach to interactive music composition.

Feature-aware natural texture synthesis

KAUST Repository

Wu, Fuzhang

2014-12-04

This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis quality can be affected adversely if the texture elements in an example display spatially varied patterns, such as perspective distortion, the composition of different sub-textures, and variations in global color pattern as a result of complex illumination. This issue is common in natural textures and is a fundamental challenge for previously developed methods. Thus, we address it from a feature point of view and propose a feature-aware approach to synthesize natural textures. The synthesis process is guided by a feature map that represents the visual characteristics of the input texture. Moreover, we present a novel adaptive initialization algorithm that can effectively avoid the repeat and verbatim copying artifacts. Our approach improves texture synthesis in many images that cannot be handled effectively with traditional technologies.

Histological image classification using biologically interpretable shape-based features

International Nuclear Information System (INIS)

Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

2013-01-01

Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

Grammar-based feature generation for time-series prediction

CERN Document Server

De Silva, Anthony Mihirana

2015-01-01

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

Treatment recommendations for DSM-5-defined mixed features.

Science.gov (United States)

Rosenblat, Joshua D; McIntyre, Roger S

2017-04-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) mixed features specifier provides a less restrictive definition of mixed mood states, compared to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR), including mood episodes that manifest with subthreshold symptoms of the opposite mood state. A limited number of studies have assessed the efficacy of treatments specifically for DSM-5-defined mixed features in mood disorders. As such, there is currently an inadequate amount of data to appropriately inform evidence-based treatment guidelines of DSM-5 defined mixed features. However, given the high prevalence and morbidity of mixed features, treatment recommendations based on the currently available evidence along with expert opinion may be of benefit. This article serves to provide these interim treatment recommendations while humbly acknowledging the limited amount of evidence currently available. Second-generation antipsychotics (SGAs) appear to have the greatest promise in the treatment of bipolar disorder (BD) with mixed features. Conventional mood stabilizing agents (ie, lithium and divalproex) may also be of benefit; however, they have been inadequately studied. In the treatment of major depressive disorder (MDD) with mixed features, the comparable efficacy of antidepressants versus other treatments, such as SGAs, remains unknown. As such, antidepressants remain first-line treatment of MDD with or without mixed features; however, there are significant safety concerns associated with antidepressant monotherapy when mixed features are present, which merits increased monitoring. Lurasidone is the only SGA monotherapy that has been shown to be efficacious specifically in the treatment of MDD with mixed features. Further research is needed to accurately determine the efficacy, safety, and tolerability of treatments specifically for mood episodes with mixed features to adequately inform

A feature dictionary supporting a multi-domain medical knowledge base.

Science.gov (United States)

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Online Feature Selection for Classifying Emphysema in HRCT Images

Directory of Open Access Journals (Sweden)

M. Prasad

2008-06-01

Full Text Available Feature subset selection, applied as a pre- processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. In the classic formulation of the feature selection problem, it is assumed that all the features are available at the beginning. However, in many real world problems, there are scenarios where not all features are present initially and must be integrated as they become available. In such scenarios, online feature selection provides an efficient way to sort through a large space of features. It is in this context that we introduce online feature selection for the classification of emphysema, a smoking related disease that appears as low attenuation regions in High Resolution Computer Tomography (HRCT images. The technique was successfully evaluated on 61 HRCT scans and compared with different online feature selection approaches, including hill climbing, best first search, grafting, and correlation-based feature selection. The results were also compared against ldensity maskr, a standard approach used for emphysema detection in medical image analysis.

Feature Selection via Chaotic Antlion Optimization.

Directory of Open Access Journals (Sweden)

Hossam M Zawbaa

Full Text Available Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting while minimizing the number of features used.We propose an optimization approach for the feature selection problem that considers a "chaotic" version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics.

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

Teaching World Music through Feature Films

Science.gov (United States)

Lum, Chee-Hoo

2009-01-01

When used effectively, feature films can bring a plethora of visual and aural stimulation to students and enhance their learning about world cultures. Feature films can take students to places, sights, and sounds that they have yet to experience. After watching these films, students might become new admirers or even keen followers of the subject…

Recent Development of the Two-Stroke Engine. II - Design Features. 2; Design Features

Science.gov (United States)

Zeman, J.

1945-01-01

Completing the first paper dealing with charging methods and arrangements, the present paper discusses the design forms of two-stroke engines. Features which largely influence piston running are: (a) The shape and surface condition of the sliding parts. (b) The cylinder and piston materials. (c) Heat conditions in the piston, and lubrication. There is little essential difference between four-stroke and two-stroke engines with ordinary pistons. In large engines, for example, are always found separately cast or welded frames in which the stresses are taken up by tie rods. Twin piston and timing piston engines often differ from this design. Examples can be found in many engines of German or foreign make. Their methods of operation will be dealt with in the third part of the present paper, which also includes the bibliography. The development of two-stroke engine design is, of course, mainly concerned with such features as are inherently difficult to master; that is, the piston barrel and the design of the gudgeon pin bearing. Designers of four-stroke engines now-a-days experience approximately the same difficulties, since heat stresses have increased to the point of influencing conditions in the piston barrel. Features which notably affect this are: (a) The material. (b) Prevailing heat conditions.

New features of the Helioviewer Project

Science.gov (United States)

Ireland, J.; Zahniy, S.; Nicula, B.; Mueller, D.; Felix, S.; Verstringe, F.; Bourgoignie, B.

2016-12-01

This year saw the release of major new upgrades to the capabilities of helioviewer.org and JHelioviewer. The helioviewer.org interface was completely re-designed, and now provides image and feature/event time-lines and data download capabilities. JHelioviewer introduced interactive time-series, the ability to query different servers for different data, and image reprojection. We introduce the new features of these software releases and give use cases. We will summarize our latest usage statistics, and discuss what's coming up next for the Helioviewer Project. We will also be soliciting bug reports, requests for new features and comments on the effectiveness of helioviewer.org and JHelioviewer. What would you like to see next from the Helioviewer Project?

Temporal resolution for the perception of features and conjunctions.

Science.gov (United States)

Bodelón, Clara; Fallah, Mazyar; Reynolds, John H

2007-01-24

The visual system decomposes stimuli into their constituent features, represented by neurons with different feature selectivities. How the signals carried by these feature-selective neurons are integrated into coherent object representations is unknown. To constrain the set of possible integrative mechanisms, we quantified the temporal resolution of perception for color, orientation, and conjunctions of these two features. We find that temporal resolution is measurably higher for each feature than for their conjunction, indicating that time is required to integrate features into a perceptual whole. This finding places temporal limits on the mechanisms that could mediate this form of perceptual integration.

Feature Binding and the Hebb Repetition Effect

OpenAIRE

Barrett, Maeve

2008-01-01

Previous studies have found no evidence that long-term learning of integrated objects and individual features benefit visual short term memory tasks (Logie, Brockmole, & Vandenbroucke, in press; Olson & Jiang, 2004; Treisman, 2006). These findings may have been due to stimulus interference as a restricted number of features were utilised in these studies to form objects in the stimulus arrays. In these studies, participants would have needed to break apart the features of several objects in a...

Optimized feature subsets for epileptic seizure prediction studies.

Science.gov (United States)

Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

2011-01-01

The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

Imaging features of thalassemia

Energy Technology Data Exchange (ETDEWEB)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B. [Dept. of Radiology, Istanbul Univ. (Turkey); Dincol, G. [Dept. of Internal Medicine, Istanbul Univ. (Turkey)

1999-07-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of {beta}-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Imaging features of thalassemia

International Nuclear Information System (INIS)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B.; Dincol, G.

1999-01-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of β-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

Science.gov (United States)

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods

Directory of Open Access Journals (Sweden)

Kaiyang Qu

2017-09-01

Full Text Available DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF, is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Hindi vowel classification using QCN-MFCC features

Directory of Open Access Journals (Sweden)

Shipra Mishra

2016-09-01

Full Text Available In presence of environmental noise, speakers tend to emphasize their vocal effort to improve the audibility of voice. This involuntary adjustment is known as Lombard effect (LE. Due to LE the signal to noise ratio of speech increases, but at the same time the loudness, pitch and duration of phonemes changes. Hence, accuracy of automatic speech recognition systems degrades. In this paper, the effect of unsupervised equalization of Lombard effect is investigated for Hindi vowel classification task using Hindi database designed at TIFR Mumbai, India. Proposed Quantile-based Dynamic Cepstral Normalization MFCC (QCN-MFCC along with baseline MFCC features have been used for vowel classification. Hidden Markov Model (HMM is used as classifier. It is observed that QCN-MFCC features have given a maximum improvement of 5.97% and 5% over MFCC features for context-dependent and context-independent cases respectively. It is also observed that QCN-MFCC features have given improvement of 13% and 11.5% over MFCC features for context-dependent and context-independent classification of mid vowels.

Breast Cancer Detection with Reduced Feature Set

Directory of Open Access Journals (Sweden)

Ahmet Mert

2015-01-01

Full Text Available This paper explores feature reduction properties of independent component analysis (ICA on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC dataset is reduced to one-dimensional feature vector computing an independent component (IC. The original data with 30 features and reduced one feature (IC are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN, artificial neural network (ANN, radial basis function neural network (RBFNN, and support vector machine (SVM. The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations and partitioning (20%–40% methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden’s index, discriminant power, and the receiver operating characteristic (ROC curve with its criterion values including area under curve (AUC and 95% confidential interval (CI. This represents an improvement in diagnostic decision support system, while reducing computational complexity.

Feature-based tolerancing for intelligent inspection process definition

International Nuclear Information System (INIS)

Brown, C.W.

1993-07-01

This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

Dynamic Features for Iris Recognition.

Science.gov (United States)

da Costa, R M; Gonzaga, A

2012-08-01

The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

Performance Evaluation of Feature Sets of Minutiae Quadruplets ...

African Journals Online (AJOL)

The features proposed in this paper are derived from minutiae quadruplets and are applicable in matching and indexing ngerprint images. In this work nineteen different possibilities of features were explored for indexing and the performances of some of the feature sets were mixed: some giving good performances on ...

Feature Selection for Audio Surveillance in Urban Environment

Directory of Open Access Journals (Sweden)

KIKTOVA Eva

2014-05-01

Full Text Available This paper presents the work leading to the acoustic event detection system, which is designed to recognize two types of acoustic events (shot and breaking glass in urban environment. For this purpose, a huge front-end processing was performed for the effective parametric representation of an input sound. MFCC features and features computed during their extraction (MELSPEC and FBANK, then MPEG-7 audio descriptors and other temporal and spectral characteristics were extracted. High dimensional feature sets were created and in the next phase reduced by the mutual information based selection algorithms. Hidden Markov Model based classifier was applied and evaluated by the Viterbi decoding algorithm. Thus very effective feature sets were identified and also the less important features were found.

Research on oral test modeling based on multi-feature fusion

Science.gov (United States)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

Directory of Open Access Journals (Sweden)

Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

Features of upbringing children in civil law

OpenAIRE

Лобжанідзе, Давид

2014-01-01

The paper analyzes the features of upbringing children in civil law, in particular under the Civil Code of Georgia. The author examines the concept of the family as a social phenomenon and its underlying principles. Attention is paid also to the court practice of upbringing children and determining the place of their residence. English abstract D. Lobzhanidze Features of upbringing children in civil law. The paper analyzes the features of upbringing children in civil law, in particular u...

Clinical features of radiation retinopathy

International Nuclear Information System (INIS)

Tabuchi, Shoko; Oda, Itsuo; Okawa, Tomohiko

1977-01-01

The clinical features of 25 cases with radiation retinopathy are described. Retinopathy was induced following therapeutic irradiation of paraobital malignancies with megavoltage Linac x-ray of 3,000 rads or more. Retinal vessels, particularly the proximal portion of retinal arteries, seemed to be the primary site of damage due to radiation. According to the type of lesion and dosage, fundus features simulated papillitis, retinal angiosclerosis, or hard exudates due to capillary obliteration. Acute obstruction of the central retinal artery and ischemic optic neuropathy could result from heavy irradiation of over 5,000 rads. (Evans, J.)

News and Features Updates from USA.gov

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General Services Administration — Stay on top of important government news and information with the USA.gov Updates: News and Features RSS feed. We'll update this feed when we add news and featured...

Realistic Free-Spins Features Increase Preference for Slot Machines.

Science.gov (United States)

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Abdominal cocoon: sonographic features.

Science.gov (United States)

Vijayaraghavan, S Boopathy; Palanivelu, Chinnusamy; Sendhilkumar, Karuppusamy; Parthasarathi, Ramakrishnan

2003-07-01

An abdominal cocoon is a rare condition in which the small bowel is encased in a membrane. The diagnosis is usually established at surgery. Here we describe the sonographic features of this condition.

Are Haar-like Rectangular Features for Biometric Recognition Reducible?

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2013-01-01

Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

Automatic processing of unattended object features by functional connectivity

Directory of Open Access Journals (Sweden)

Katja Martina Mayer

2013-05-01

Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.

TreeBASIS Feature Descriptor and Its Hardware Implementation

Directory of Open Access Journals (Sweden)

Spencer Fowers

2014-01-01

Full Text Available This paper presents a novel feature descriptor called TreeBASIS that provides improvements in descriptor size, computation time, matching speed, and accuracy. This new descriptor uses a binary vocabulary tree that is computed using basis dictionary images and a test set of feature region images. To facilitate real-time implementation, a feature region image is binary quantized and the resulting quantized vector is passed into the BASIS vocabulary tree. A Hamming distance is then computed between the feature region image and the effectively descriptive basis dictionary image at a node to determine the branch taken and the path the feature region image takes is saved as a descriptor. The TreeBASIS feature descriptor is an excellent candidate for hardware implementation because of its reduced descriptor size and the fact that descriptors can be created and features matched without the use of floating point operations. The TreeBASIS descriptor is more computationally and space efficient than other descriptors such as BASIS, SIFT, and SURF. Moreover, it can be computed entirely in hardware without the support of a CPU for additional software-based computations. Experimental results and a hardware implementation show that the TreeBASIS descriptor compares well with other descriptors for frame-to-frame homography computation while requiring fewer hardware resources.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

3-D FEATURE-BASED MATCHING BY RSTG APPROACH

Directory of Open Access Journals (Sweden)

J.-J. Jaw

2012-07-01

Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.

Parabolic features and the erosion rate on Venus

Science.gov (United States)

Strom, Robert G.

1993-01-01

The impact cratering record on Venus consists of 919 craters covering 98 percent of the surface. These craters are remarkably well preserved, and most show pristine structures including fresh ejecta blankets. Only 35 craters (3.8 percent) have had their ejecta blankets embayed by lava and most of these occur in the Atla-Beta Regio region; an area thought to be recently active. parabolic features are associated with 66 of the 919 craters. These craters range in size from 6 to 105 km diameter. The parabolic features are thought to be the result of the deposition of fine-grained ejecta by winds in the dense venusian atmosphere. The deposits cover about 9 percent of the surface and none appear to be embayed by younger volcanic materials. However, there appears to be a paucity of these deposits in the Atla-Beta Regio region, and this may be due to the more recent volcanism in this area of Venus. Since parabolic features are probably fine-grain, wind-deposited ejecta, then all impact craters on Venus probably had these deposits at some time in the past. The older deposits have probably been either eroded or buried by eolian processes. Therefore, the present population of these features is probably associated with the most recent impact craters on the planet. Furthermore, the size/frequency distribution of craters with parabolic features is virtually identical to that of the total crater population. This suggests that there has been little loss of small parabolic features compared to large ones, otherwise there should be a significant and systematic paucity of craters with parabolic features with decreasing size compared to the total crater population. Whatever is erasing the parabolic features apparently does so uniformly regardless of the areal extent of the deposit. The lifetime of parabolic features and the eolian erosion rate on Venus can be estimated from the average age of the surface and the present population of parabolic features.

Real-time hypothesis driven feature extraction on parallel processing architectures

DEFF Research Database (Denmark)

Granmo, O.-C.; Jensen, Finn Verner

2002-01-01

the problem of higher-order feature-content/feature-feature correlation, causally complexly interacting features are identified through Bayesian network d-separation analysis and combined into joint features. When used on a moderately complex object-tracking case, the technique is able to select...... extraction, which selectively extract relevant features one-by-one, have in some cases achieved real-time performance on single processing element architectures. In this paperwe propose a novel technique which combines the above two approaches. Features are selectively extracted in parallelizable sets...

Feature representation of RGB-D images using joint spatial-depth feature pooling

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2016-01-01

Recent development in depth imaging technology makes acquisition of depth information easier. With the additional depth cue, RGB-D cameras can provide effective support for many RGB-D perception tasks beyond traditional RGB information. However, current feature representation based on RGB-D image...

Dynamic binding of visual features by neuronal/stimulus synchrony.

Science.gov (United States)

Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Effective Feature Selection for Classification of Promoter Sequences.

Directory of Open Access Journals (Sweden)

Kouser K

Full Text Available Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine, KNN (K Nearest Neighbor and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

Feature-based RNN target recognition

Science.gov (United States)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Adversarial Feature Selection Against Evasion Attacks.

Science.gov (United States)

Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

2016-03-01

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

Neural Architecture for Feature Binding in Visual Working Memory.

Science.gov (United States)

Schneegans, Sebastian; Bays, Paul M

2017-04-05

Binding refers to the operation that groups different features together into objects. We propose a neural architecture for feature binding in visual working memory that employs populations of neurons with conjunction responses. We tested this model using cued recall tasks, in which subjects had to memorize object arrays composed of simple visual features (color, orientation, and location). After a brief delay, one feature of one item was given as a cue, and the observer had to report, on a continuous scale, one or two other features of the cued item. Binding failure in this task is associated with swap errors, in which observers report an item other than the one indicated by the cue. We observed that the probability of swapping two items strongly correlated with the items' similarity in the cue feature dimension, and found a strong correlation between swap errors occurring in spatial and nonspatial report. The neural model explains both swap errors and response variability as results of decoding noisy neural activity, and can account for the behavioral results in quantitative detail. We then used the model to compare alternative mechanisms for binding nonspatial features. We found the behavioral results fully consistent with a model in which nonspatial features are bound exclusively via their shared location, with no indication of direct binding between color and orientation. These results provide evidence for a special role of location in feature binding, and the model explains how this special role could be realized in the neural system. SIGNIFICANCE STATEMENT The problem of feature binding is of central importance in understanding the mechanisms of working memory. How do we remember not only that we saw a red and a round object, but that these features belong together to a single object rather than to different objects in our environment? Here we present evidence for a neural mechanism for feature binding in working memory, based on encoding of visual

Efficient Generation and Selection of Combined Features for Improved Classification

KAUST Repository

Shono, Ahmad N.

2014-05-01

This study contributes a methodology and associated toolkit developed to allow users to experiment with the use of combined features in classification problems. Methods are provided for efficiently generating combined features from an original feature set, for efficiently selecting the most discriminating of these generated combined features, and for efficiently performing a preliminary comparison of the classification results when using the original features exclusively against the results when using the selected combined features. The potential benefit of considering combined features in classification problems is demonstrated by applying the developed methodology and toolkit to three sample data sets where the discovery of combined features containing new discriminating information led to improved classification results.

Acetate availability and its influence on sustainable bioremediation of uranium-contaminated groundwater

International Nuclear Information System (INIS)

Williams, Kenneth H.; Long, Philip E.; Davis, James A.; Wilkins, Michael J.; N'Guessan, A. Lucie; Steefel, Carl I.; Yang, Li; Newcomer, Darrell R.; Spane, Frank A.; Kerkhof, L.; McGuinness, L.; Dayvault, Richard; Lovley, Derek

2011-01-01

Field biostimulation experiments at the U.S. Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, Colorado, have demonstrated that uranium concentrations in groundwater can be decreased to levels below the U.S. Environmental Protection Agency's (EPA) drinking water standard (0.126 (micro)M). During successive summer experiments - referred to as 'Winchester' (2007) and 'Big Rusty' (2008) - acetate was added to the aquifer to stimulate the activity of indigenous dissimilatory metal-reducing bacteria capable of reductively immobilizing uranium. The two experiments differed in the length of injection (31 vs. 110 days), the maximum concentration of acetate (5 vs. 30 mM), and the extent to which iron reduction ('Winchester') or sulfate reduction ('Big Rusty') was the predominant metabolic process. In both cases, rapid removal of U(VI) from groundwater occurred at calcium concentrations (6 mM) and carbonate alkalinities (8 meq/L) where Ca-UO2-CO3 ternary complexes constitute >90% of uranyl species in groundwater. Complete consumption of acetate and increased alkalinity (>30 meq/L) accompanying the onset of sulfate reduction corresponded to temporary increases in U(VI); however, by increasing acetate concentrations in excess of available sulfate (10 mM), low U(VI) concentrations (0.1-0.05 (micro)M) were achieved for extended periods of time (>140 days). Uniform delivery of acetate during 'Big Rusty' was impeded due to decreases in injection well permeability, likely resulting from biomass accumulation and carbonate and sulfide mineral precipitation. Such decreases were not observed during the short-duration 'Winchester' experiment. Terminal restriction fragment length polymorphism (TRFLP) analysis of 16S rRNA genes demonstrated that Geobacter sp. and Geobacter-like strains dominated the groundwater community profile during iron reduction, with 13C stable isotope probing (SIP) results confirming these strains were actively utilizing acetate to

Acetate availability and its influence on sustainable bioremediation of Uranium-contaminated groundwater

Science.gov (United States)

Williams, K.H.; Long, P.E.; Davis, J.A.; Wilkins, M.J.; N'Guessan, A. L.; Steefel, Carl; Yang, L.; Newcomer, D.; Spane, F.A.; Kerkhof, L.J.; Mcguinness, L.; Dayvault, R.; Lovley, D.R.

2011-01-01

Field biostimulation experiments at the U.S. Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, Colorado, have demonstrated that uranium concentrations in groundwater can be decreased to levels below the U.S. Environmental Protection Agency's (EPA) drinking water standard (0.126??M).During successive summer experiments - referred to as "Winchester" (2007) and "Big Rusty" (2008) - acetate was added to the aquifer to stimulate the activity of indigenous dissimilatory metal reducing bacteria capable of reductively immobilizing uranium. The two experiments differed in the length of injection (31 vs. 110 days), the maximum concentration of acetate (5 vs. 30 mM),and the extent to which iron reduction ("Winchester") or sulfate reduction("Big Rusty") was the predominant metabolic process. In both cases, rapid removal of U(VI) from groundwater occurred at calcium concentrations (6 mM) and carbonate alkalinities (8 meq/L) where Ca-UO2-CO3 ternary complexes constitute >90% of uranyl species in groundwater. Complete consumption of acetate and increased alkalinity (>30 meq/L) accompanying the onset of sulfate reduction corresponded to temporary increases in U(VI);however, by increasing acetate concentrations in excess of available sulfate (10 mM), low U(VI) concentrations (0.1-0.05 ??M) were achieved for extended periods of time (>140 days). Uniform delivery of acetate during "Big Rusty" was impeded due to decreases in injection well permeability, likely resulting from biomass accumulation and carbonate and sulfide mineral precipitation. Such decreases were not observed during the short-duration "Winchester" experiment. Terminal restriction fragment length polymorphism (TRFLP) analysis of 16S rRNA genes demonstrated that Geobacter sp. and Geobacter-like strains dominated the groundwater community profile during iron reduction, with 13C stable isotope probing (SIP) results confirming these strains were actively utilizing acetate to replicate their

Cherubism: Clinicoradiographic Features and Treatment

Directory of Open Access Journals (Sweden)

Luiz Antonio Guimarães Cabral

2010-04-01

Full Text Available Objectives: Cherubism is a congenital childhood disease of autosomal dominant inheritance. This disease is characterized by painless bilateral enlargement of the jaws, in which bone is replaced with fibrous tissue. The condition has sui generis clinical, radiographic and histological features, of which the clinician should be aware for a better differential diagnosis in the presence of a fibro-osseous lesion affecting the bones of the maxillomandibular complex. The purpose of present paper was to review the literature and to report the most important aspects of cherubism in order to facilitate the study of this disease.Material and Methods: Literature was reviewed about cherubism, emphasizing the relevant clinicoradiographic features and treatment. Literature was selected through a search of PubMed and Scielo electronic databases. The keywords used for search were adolescent, cherubism, cherubism/physiopathology, cherubism/treatment, cherubism/radiography. A manual search of the reference lists of the identified articles and the authors’ article files and recent reviews was conducted to identify additional publications. Those studies that described new features about cherubism were included in this review.Results: In total 44 literature sources were obtained and reviewed. Studies that described new features about cherubism physiopathology, diagnostics and treatment were reviewed.Conclusions: Despite the exceptions, cherubism is a clinically well-characterized disease. In cases of a suspicion of cherubism, radiographic examination is essential since the clinical presentation, the location and distribution of the lesions may define the diagnosis. Histopathological examination is complementary. Nowadays, genetic tests should be used for final diagnosis of cherubism.

Improving Music Genre Classification by Short-Time Feature Integration

DEFF Research Database (Denmark)

Meng, Anders; Ahrendt, Peter; Larsen, Jan

2005-01-01

Many different short-time features, using time windows in the size of 10-30 ms, have been proposed for music segmentation, retrieval and genre classification. However, often the available time frame of the music to make the actual decision or comparison (the decision time horizon) is in the range...... of seconds instead of milliseconds. The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration and late information fusion for music genre classification...

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

Face recognition algorithm using extended vector quantization histogram features.

Science.gov (United States)

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Uniform competency-based local feature extraction for remote sensing images

Science.gov (United States)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Prostate cancer multi-feature analysis using trans-rectal ultrasound images

International Nuclear Information System (INIS)

Mohamed, S S; Salama, M M A; Kamel, M; El-Saadany, E F; Rizkalla, K; Chin, J

2005-01-01

This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided into regions of interest (ROIs) by the Gabor multi-resolution analysis, a crucial stage, in which segmentation is achieved according to the frequency response of the image pixels. The pixels with a similar response to the same filter are grouped to form one ROI. Next, from each ROI two different statistical feature sets are constructed; the first set includes four grey level dependence matrix (GLDM) features and the second set consists of five grey level difference vector (GLDV) features. These constructed feature sets are then ranked by the mutual information feature selection (MIFS) algorithm. Here, the features that provide the maximum mutual information of each feature and class (cancerous and non-cancerous) and the minimum mutual information of the selected features are chosen, yeilding a reduced feature subset. The two constructed feature sets, GLDM and GLDV, as well as the reduced feature subset, are examined in terms of three different classifiers: the condensed k-nearest neighbour (CNN), the decision tree (DT) and the support vector machine (SVM). The accuracy classification results range from 87.5% to 93.75%, where the performance of the SVM and that of the DT are significantly better than the performance of the CNN. (note)

Including product features in process redesign

DEFF Research Database (Denmark)

Hvam, Lars; Hauksdóttir, Dagný; Mortensen, Niels Henrik

2017-01-01

do not take into account how the product features are applied throughout the process, which makes it difficult to obtain a comprehensive understanding of the activities in the processes and to generate significant improvements. The suggested approach models the product family using the so......This article suggests a visual modelling method for integrating models of product features with business process models for redesigning the business processes involving specifications of customer-tailored products and services. The current methods for redesigning these types of business processes......-called product variant master and the business process modelling notation for modelling the process flow. The product model is combined with the process map by identifying features used in each step of the process flow. Additionally, based on the information absorbed from the integrated model, the value stream...

Detection of fraudulent emails by employing advanced feature abundance

Directory of Open Access Journals (Sweden)

Sarwat Nizamani

2014-11-01

Full Text Available In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM (Nizamani et al., 2011 [1] which is authors’ previous cluster based classification model. The experiments have been performed on diverse feature sets and the different classification methods. The comparison of the results is also presented and the evaluation show that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection requires the better choice of feature set; while the choice of classification method is of less importance.

Salient Region Detection via Feature Combination and Discriminative Classifier

Directory of Open Access Journals (Sweden)

Deming Kong

2015-01-01

Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

Science.gov (United States)

Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

2012-01-01

Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

Mesoblastic nephroma: Pathological features

African Journals Online (AJOL)

N.M. El-Badawy

determined mainly by its histologic type, we found it worthwhile to elaborate more on the gross and microscopic features of ... behavior of mesoblastic nephroma is determined mainly by its his- .... However, it exhibits a nodular growth pattern at.

Genome-wide analyses of borderline personality features

NARCIS (Netherlands)

Lubke, G.H.; Laurin, C.; Amin, N.; Hottenga, J.J.; Willemsen, G.; Grootheest, G.; Abdellaoui, A.; Karssen, L.C.; Oostra, B.A.; van Duijn, C.M.; Penninx, B.W.J.H.; Boomsma, D.I.

2014-01-01

The heritability of borderline personality (BP) features has been established in multiple twin and family studies. Using data from the borderline subscale of the Personality Assessment Inventory Borderline Features Scale (PAI-BOR) collected in two Dutch cohorts (N=7125), the Netherlands Twin

Shapes and features of the primordial bispectrum

Energy Technology Data Exchange (ETDEWEB)

Gong, Jinn-Ouk [Asia Pacific Center for Theoretical Physics, Cheongam-ro 67, Pohang, 37673 (Korea, Republic of); Palma, Gonzalo A.; Sypsas, Spyros, E-mail: jinn-ouk.gong@apctp.org, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: s.sypsas@gmail.com [Departamento de Física, FCFM, Universidad de Chile, Blanco Encalada 2008, Santiago, 837.0415 Chile (Chile)

2017-05-01

If time-dependent disruptions from slow-roll occur during inflation, the correlation functions of the primordial curvature perturbation should have scale-dependent features, a case which is marginally supported from the cosmic microwave background (CMB) data. We offer a new approach to analyze the appearance of such features in the primordial bispectrum that yields new consistency relations and justifies the search of oscillating patterns modulated by orthogonal and local templates. Under the assumption of sharp features, we find that the cubic couplings of the curvature perturbation can be expressed in terms of the bispectrum in two specific momentum configurations, for example local and equilateral. This allows us to derive consistency relations among different bispectrum shapes, which in principle could be tested in future CMB surveys. Furthermore, based on the form of the consistency relations, we construct new two-parameter templates for features that include all the known shapes.

An Effective Combined Feature For Web Based Image Retrieval

Directory of Open Access Journals (Sweden)

H.M.R.B Herath

2015-08-01

Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

Adaptive feature selection using v-shaped binary particle swarm optimization.

Science.gov (United States)

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Feature-based morphometry: discovering group-related anatomical patterns.

Science.gov (United States)

Toews, Matthew; Wells, William; Collins, D Louis; Arbel, Tal

2010-02-01

This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). Copyright (c) 2009 Elsevier Inc. All rights reserved.

Physical model for the 2175 A interstellar extinction feature

International Nuclear Information System (INIS)

Hecht, J.H.

1986-01-01

Recent IUE observations have shown that the 2175 A interstellar extinction feature is constant in wavelength but varies in width. A model has been constructed to explain these results. It is proposed that the 2175 A feature will only be seen when there is extinction due to carbon grains which have lost their hydrogen. In particular, the feature is caused by a separate population of small (less than 50 A radius), hydrogen-free carbon grains. The variations in width would be due to differences in either their temperature, size distribution, or impurity content. All other carbon grains retain hydrogen, which causes the feature to be suppressed. If this model is correct, then it implies that the grains responsible for the unidentified IR emission features would not generally cause the 2175 A feature. 53 references

Consistency relations for sharp inflationary non-Gaussian features

Energy Technology Data Exchange (ETDEWEB)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris [Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Blanco Encalada 2008, Santiago (Chile); Soto, Alex, E-mail: sander.mooij@ing.uchile.cl, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: gpanotop@ing.uchile.cl, E-mail: gatogeno@gmail.com [Departamento de Física, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago (Chile)

2016-09-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

Consistency relations for sharp inflationary non-Gaussian features

International Nuclear Information System (INIS)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris; Soto, Alex

2016-01-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

Character feature integration of Chinese calligraphy and font

Science.gov (United States)

Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

2013-01-01

A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

Multistage feature extraction for accurate face alignment

NARCIS (Netherlands)

Zuo, F.; With, de P.H.N.

2004-01-01

We propose a novel multistage facial feature extraction approach using a combination of 'global' and 'local' techniques. At the first stage, we use template matching, based on an Edge-Orientation-Map for fast feature position estimation. Using this result, a statistical framework applying the Active

Second feature of the matter two-point function

Science.gov (United States)

Tansella, Vittorio

2018-05-01

We point out the existence of a second feature in the matter two-point function, besides the acoustic peak, due to the baryon-baryon correlation in the early Universe and positioned at twice the distance of the peak. We discuss how the existence of this feature is implied by the well-known heuristic argument that explains the baryon bump in the correlation function. A standard χ2 analysis to estimate the detection significance of the second feature is mimicked. We conclude that, for realistic values of the baryon density, a SKA-like galaxy survey will not be able to detect this feature with standard correlation function analysis.

Image fusion using sparse overcomplete feature dictionaries

Science.gov (United States)

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

Directory of Open Access Journals (Sweden)

Vibha Gupta

2018-02-01

Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

Slow feature analysis: unsupervised learning of invariances.

Science.gov (United States)

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Rotation invariant fast features for large-scale recognition

Science.gov (United States)

Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

2012-10-01

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

Features of MCNP6

International Nuclear Information System (INIS)

Goorley, T.; James, M.; Booth, T.; Brown, F.; Bull, J.; Cox, L.J.; Durkee, J.; Elson, J.; Fensin, M.; Forster, R.A.; Hendricks, J.; Hughes, H.G.; Johns, R.; Kiedrowski, B.; Martz, R.; Mashnik, S.; McKinney, G.; Pelowitz, D.; Prael, R.; Sweezy, J.

2016-01-01

Highlights: • MCNP6 is simply and accurately described as the merger of MCNP5 and MCNPX capabilities, but it is much more than the sum of these two computer codes. • MCNP6 is the result of six years of effort by the MCNP5 and MCNPX code development teams. • These groups of people, residing in Los Alamos National Laboratory’s X Computational Physics Division, Monte Carlo Codes Group (XCP-3) and Nuclear Engineering and Nonproliferation Division, Radiation Transport Modeling Team (NEN-5) respectively, have combined their code development efforts to produce the next evolution of MCNP. • While maintenance and major bug fixes will continue for MCNP5 1.60 and MCNPX 2.7.0 for upcoming years, new code development capabilities only will be developed and released in MCNP6. • In fact, the initial release of MCNP6 contains numerous new features not previously found in either code. • These new features are summarized in this document. • Packaged with MCNP6 is also the new production release of the ENDF/B-VII.1 nuclear data files usable by MCNP. • The high quality of the overall merged code, usefulness of these new features, along with the desire in the user community to start using the merged code, have led us to make the first MCNP6 production release: MCNP6 version 1. • High confidence in the MCNP6 code is based on its performance with the verification and validation test suites, comparisons to its predecessor codes, our automated nightly software debugger tests, the underlying high quality nuclear and atomic databases, and significant testing by many beta testers. - Abstract: MCNP6 can be described as the merger of MCNP5 and MCNPX capabilities, but it is much more than the sum of these two computer codes. MCNP6 is the result of six years of effort by the MCNP5 and MCNPX code development teams. These groups of people, residing in Los Alamos National Laboratory’s X Computational Physics Division, Monte Carlo Codes Group (XCP-3) and Nuclear Engineering and

Characterization of phenols biodegradation by compound specific stable isotope analysis

Science.gov (United States)

Wei, Xi; Gilevska, Tetyana; Wenzig, Felix; Hans, Richnow; Vogt, Carsten

2015-04-01

Biodegradation of phenol and alkylphenols has been described under both oxic and anoxic conditions. In the absence of molecular oxygen, the degradation of phenolic compounds is initiated by microorganisms through carboxylation, fumarate addition to the methyl moiety or anoxic hydroxylation of the methyl moiety. Comparatively, under aerobic condition, the initiation mechanisms are revealed to be monoxygenation or dihydroxylation for phenol and ring hydroxylation or methyl group oxidation for cresols. While several studies biochemically characterized the enzymes and reaction mechanisms in the relevant degradation pathways, isotope fractionation patterns were rarely reported possibly due to constraints in current analytical methods. In this study, the carbon isotope fractionation patterns upon the degradation of phenol and cresols by several strains were analyzed by using isotope ratio mass spectrometry connected with liquid chromatography (LC-IRMS). The corresponding enrichment factors for carbon (ƐC) have been obtained. Cresols degradation by various strains showed generally moderate carbon isotope fractionation patterns with notable differences. For p-cresol degradation, five strains were examined. The aerobic strain Acinetobacter calcoaceticus NCIMB8250 exploits ring hydroxylation by molecular oxygen as initial reaction, and a ƐC value of -1.4±0.2‰ was obtained. Pseudomonas pseudoalcaligenes NCIMB 9867, an aerobic strain initiating cresols degradation via oxygen-dependent side chain hydroxylation, yielded a ƐC value of -2.3±0.2‰. Under nitrate-reducing conditions, Geobacter metallireducens DSM 7210 and Azoarcus buckelii DSM 14744 attacks p-cresol at the side chain by monohydroxylation using water as oxygen source; the two strains produced ƐC values of -3.6±0.4‰ and -2±0.1‰, accordingly. The sulfate-reducing Desulfosarcina cetonica DSM 7267 activating cresols by fumarate addition to the methyl moiety yielded ƐC values of -1.9±0.2‰ for p

A performance evaluation of point pair features

DEFF Research Database (Denmark)

Kiforenko, Lilita; Drost, Bertram; Tombari, Federico

2018-01-01

have low resolution data, where local histogram features show a higher performance than PPFs. We also found that PPFs compared to most local histogram features degrade faster under disturbances such as occlusion and clutter, however, PPFs still remain more descriptive on an absolute scale. The main...

Feature Selection with the Boruta Package

OpenAIRE

Kursa, Miron B.; Rudnicki, Witold R.

2010-01-01

This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

Turkish Music Genre Classification using Audio and Lyrics Features

Directory of Open Access Journals (Sweden)

Önder ÇOBAN

2017-05-01

Full Text Available Music Information Retrieval (MIR has become a popular research area in recent years. In this context, researchers have developed music information systems to find solutions for such major problems as automatic playlist creation, hit song detection, and music genre or mood classification. Meta-data information, lyrics, or melodic content of music are used as feature resource in previous works. However, lyrics do not often used in MIR systems and the number of works in this field is not enough especially for Turkish. In this paper, firstly, we have extended our previously created Turkish MIR (TMIR dataset, which comprises of Turkish lyrics, by including the audio file of each song. Secondly, we have investigated the effect of using audio and textual features together or separately on automatic Music Genre Classification (MGC. We have extracted textual features from lyrics using different feature extraction models such as word2vec and traditional Bag of Words. We have conducted our experiments on Support Vector Machine (SVM algorithm and analysed the impact of feature selection and different feature groups on MGC. We have considered lyrics based MGC as a text classification task and also investigated the effect of term weighting method. Experimental results show that textual features can also be effective as well as audio features for Turkish MGC, especially when a supervised term weighting method is employed. We have achieved the highest success rate as 99,12\\% by using both audio and textual features together.

Feature selection gait-based gender classification under different circumstances

Science.gov (United States)

Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

2014-05-01

This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

Science.gov (United States)

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

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.

Hybrid feature selection for supporting lightweight intrusion detection systems

Science.gov (United States)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

Directory of Open Access Journals (Sweden)

R. Aishwarya

2013-01-01

Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

Reductio ad discrimen: Where features come from

Directory of Open Access Journals (Sweden)

Elizabeth Cowper

2015-04-01

Full Text Available This paper addresses two fundamental questions about the nature of formal features in phonology and morphosyntax: what is their expressive power, and where do they come from? To answer these questions, we begin with the most restrictive possible hypothesis (all features are privative, and are wholly dictated by Universal Grammar, with no room for cross-linguistic variation, and examine the extent to which empirical evidence from a variety of languages compels a retreat from this position. We argue that there is little to be gained by positing a universal set of specific features, and propose instead that the crucial contribution of UG is the language learner's ability to construct features by identifying correlations between contrasts at different levels of linguistic structure. This view resonates with current research on how the interaction between UG and external 'third factors' shapes the structure of language, while at the same time harking back to the Saussurean notion that contrast is the central function of linguistic representations.

Individual discriminative face recognition models based on subsets of features

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

2007-01-01

The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

Saliency image of feature building for image quality assessment

Science.gov (United States)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Boosting Discriminant Learners for Gait Recognition Using MPCA Features

Directory of Open Access Journals (Sweden)

Haiping Lu

2009-01-01

Full Text Available This paper proposes a boosted linear discriminant analysis (LDA solution on features extracted by the multilinear principal component analysis (MPCA to enhance gait recognition performance. Three-dimensional gait objects are projected in the MPCA space first to obtain low-dimensional tensorial features. Then, lower-dimensional vectorial features are obtained through discriminative feature selection. These feature vectors are then fed into an LDA-style booster, where several regularized and weakened LDA learners work together to produce a strong learner through a novel feature weighting and sampling process. The LDA learner employs a simple nearest-neighbor classifier with a weighted angle distance measure for classification. The experimental results on the NIST/USF “Gait Challenge” data-sets show that the proposed solution has successfully improved the gait recognition performance and outperformed several state-of-the-art gait recognition algorithms.

Detection of Fraudulent Emails by Employing Advanced Feature Abundance

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Glasdam, Mathies

2014-01-01

In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features...... are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM [1] which is authors' previous cluster based classification model. The experiments have been performed on diverse feature sets...... and the different classification methods. The comparison of the results is also presented and the evaluations shows that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection...

Cloud field classification based on textural features

Science.gov (United States)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

Energy Technology Data Exchange (ETDEWEB)

Mishra, Ajay; Li, Aigen [Department of Physics and Astronomy, University of Missouri, Columbia, MO 65211 (United States); Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn [Department of Astronomy, Beijing Normal University, Beijing 100875 (China)

2015-03-20

The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm, and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.

Multithreaded hybrid feature tracking for markerless augmented reality.

Science.gov (United States)

Lee, Taehee; Höllerer, Tobias

2009-01-01

We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

Science.gov (United States)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

Infants' Developing Sensitivity to Object Function: Attention to Features and Feature Correlations

Science.gov (United States)

Baumgartner, Heidi A.; Oakes, Lisa M.

2011-01-01

When learning object function, infants must detect relations among features--for example, that squeezing is associated with squeaking or that objects with wheels roll. Previously, Perone and Oakes (2006) found 10-month-old infants were sensitive to relations between object appearances and actions, but not to relations between appearances and…

A Study of Feature Extraction Using Divergence Analysis of Texture Features

Science.gov (United States)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Creating fair lineups for suspects with distinctive features

OpenAIRE

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

2009-01-01

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

Bread crumb classification using fractal and multifractal features

OpenAIRE

Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos

2017-01-01

Adequate image descriptors are fundamental in image classification and object recognition. Main requirements for image features are robustness and low dimensionality which would lead to low classification errors in a variety of situations and with a reasonable computational cost. In this context, the identification of materials poses a significant challenge, since typical (geometric and/or differential) feature extraction methods are not robust enough. Texture features based on Fourier or wav...

Sequence-based classification using discriminatory motif feature selection.

Directory of Open Access Journals (Sweden)

Hao Xiong

Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

Feature-Based Statistical Analysis of Combustion Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

Discrete-Feature Model Implementation of SDM-Site Forsmark

Energy Technology Data Exchange (ETDEWEB)

Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

2010-03-15

A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

Discrete-Feature Model Implementation of SDM-Site Forsmark

International Nuclear Information System (INIS)

Geier, Joel

2010-03-01

A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

A new approach for detecting local features

DEFF Research Database (Denmark)

Nguyen, Phuong Giang; Andersen, Hans Jørgen

2010-01-01

Local features up to now are often mentioned in the meaning of interest points. A patch around each point is formed to compute descriptors or feature vectors. Therefore, in order to satisfy different invariant imaging conditions such as scales and viewpoints, an input image is often represented i...

Meta-Level Runtime Feature Awareness for Java

DEFF Research Database (Denmark)

Olszak, Andrzej; Jensen, Martin Lykke Rytter; Jørgensen, Bo Nørregaard

2011-01-01

introduce the concept of runtime feature awareness that enables a running program to establish and make use of its own feature-code traceability links. We present an implementation of this idea, a dynamic-analysis Java library called JAwareness. JAwareness provides a meta-level architecture that can be non...

Constraint solving for direct manipulation of features

NARCIS (Netherlands)

Lourenco, D.; Oliveira, P.; Noort, A.; Bidarra, R.

2006-01-01

In current commercial feature modeling systems, support for direct manipulation of features is not commonly available. This is partly due to the strong reliance of such systems on constraints, but also to the lack of speed of current constraint solvers. In this paper, an approach to the optimization

Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

Directory of Open Access Journals (Sweden)

Dane Brown

2017-07-01

Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

Science.gov (United States)

Ding, L.; Li, H.; Hu, C.; Zhang, W.; Wang, S.

2018-04-01

In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

ALEXNET FEATURE EXTRACTION AND MULTI-KERNEL LEARNING FOR OBJECTORIENTED CLASSIFICATION

Directory of Open Access Journals (Sweden)

L. Ding

2018-04-01

Full Text Available In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

Stylistic Features of the Legal Discourse | Alabi | UJAH: Unizik ...

African Journals Online (AJOL)

Every profession, every occupation, for example architecture, journalism, medicine, sports, has its specialised language features. These features may be viewed at the phonological, semantic, syntactic, lexical and graphological levels, among others. The language features identified with certain professions are most of the ...

A keyword spotting model using perceptually significant energy features

Science.gov (United States)

Umakanthan, Padmalochini

The task of a keyword recognition system is to detect the presence of certain words in a conversation based on the linguistic information present in human speech. Such keyword spotting systems have applications in homeland security, telephone surveillance and human-computer interfacing. General procedure of a keyword spotting system involves feature generation and matching. In this work, new set of features that are based on the psycho-acoustic masking nature of human speech are proposed. After developing these features a time aligned pattern matching process was implemented to locate the words in a set of unknown words. A word boundary detection technique based on frame classification using the nonlinear characteristics of speech is also addressed in this work. Validation of this keyword spotting model was done using widely acclaimed Cepstral features. The experimental results indicate the viability of using these perceptually significant features as an augmented feature set in keyword spotting.

Feature Selection Criteria for Real Time EKF-SLAM Algorithm

Directory of Open Access Journals (Sweden)

Fernando Auat Cheein

2010-02-01

Full Text Available This paper presents a seletion procedure for environmet features for the correction stage of a SLAM (Simultaneous Localization and Mapping algorithm based on an Extended Kalman Filter (EKF. This approach decreases the computational time of the correction stage which allows for real and constant-time implementations of the SLAM. The selection procedure consists in chosing the features the SLAM system state covariance is more sensible to. The entire system is implemented on a mobile robot equipped with a range sensor laser. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing-time consumed by the SLAM with the feature selection procedure proposed are shown. A comparison between the feature selection approach proposed and the classical sequential EKF-SLAM along with an entropy feature selection approach is also performed.

Feature Selection with the Boruta Package

Directory of Open Access Journals (Sweden)

Miron B. Kursa

2010-10-01

Full Text Available This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

Quantitative Comparison of Tolerance-Based Feature Transforms

NARCIS (Netherlands)

Reniers, Dennie; Telea, Alexandru

2006-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary

W-transform method for feature-oriented multiresolution image retrieval

Energy Technology Data Exchange (ETDEWEB)

Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

1995-07-01

Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

Diffusion tensor image registration using hybrid connectivity and tensor features.