973 resultados para Data-fusion


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Thermodynamic properties of bread dough (fusion enthalpy, apparent specific heat, initial freezing point and unfreezable water) were measured at temperatures from -40 degrees C to 35 degrees C using differential scanning calorimetry. The initial freezing point was also calculated based on the water activity of dough. The apparent specific heat varied as a function of temperature: specific heat in the freezing region varied from (1.7-23.1) J g(-1) degrees C(-1), and was constant at temperatures above freezing (2.7 J g(-1) degrees C(-1)). Unfreezable water content varied from (0.174-0.182) g/g of total product. Values of heat capacity as a function of temperature were correlated using thermodynamic models. A modification for low-moisture foodstuffs (such as bread dough) was successfully applied to the experimental data. (C) 2010 Elsevier Ltd. All rights reserved.

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Recent structural studies of proteins mediating membrane fusion reveal intriguing similarities between diverse viral and mammalian systems. Particularly striking is the close similarity between the transmembrane envelope glycoproteins from the retrovirus HTLV-1 and the filovirus Ebola. These similarities suggest similar mechanisms of membrane fusion. The model that fits most currently available data suggests fusion activation in viral systems is driven by a symmetrical conformational change triggered by an activation event such as receptor binding or a pH change. The mammalian vesicle fusion mediated by the SNARE protein complex most likely occurs by a similar mechanism but without symmetry constraints.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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This paper presents a numerical study of fluidized-bed coating on thin plates using an orthogonal collocation technique. Inclusion of the latent heat of fusion term in the boundary conditions of the mathematical model accounts for the fact that some polymer powders used in coating may be partially crystalline. Predictions of coating thickness on flat plates were made with actual polymers used in fluidized-bed coating. Reasonably good agreement between numerical predictions of the coating thickness and experimental coating data of Richart was obtained for steel panels preheated to 316 degreesC. A good agreement was also obtained between numerical predictions and our coating thickness data for nylon-11 and polyethylene powders. Predicted coating thickness for polyethylene powder on flat plates were obtained with values of heat transfer coefficient closer to those obtained from our experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

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Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.

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In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.

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Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

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A search for a charged Higgs boson, H±, decaying to a W± boson and a Z boson is presented. The search is based on 20.3 fb−1 of proton-proton collision data at a center-of-mass energy of 8 TeV recorded with the ATLAS detector at the LHC. The H± boson is assumed to be produced via vector-boson fusion and the decays W±→qq′¯ and Z→e+e−/μ+μ− are considered. The search is performed in a range of charged Higgs boson masses from 200 to 1000 GeV. No evidence for the production of an H± boson is observed. Upper limits of 31--1020 fb at 95% CL are placed on the cross section for vector-boson fusion production of an H± boson times its branching fraction to W±Z. The limits are compared with predictions from the Georgi-Machacek Higgs Triplet Model.

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Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

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The specific interactions of the pairs laminin binding protein (LBP)-purified tick-borne encephalitis viral surface protein E and certain recombinant fragments of this protein, as well as West Nile viral surface protein E and certain recombinant fragments of that protein, are studied by combined methods of single-molecule dynamic force spectroscopy (SMDFS), enzyme immunoassay and optical surface waves-based biosensor measurements. The experiments were performed at neutral pH (7.4) and acid pH (5.3) conditions. The data obtained confirm the role of LBP as a cell receptor for two typical viral species of the Flavivirus genus. A comparison of these data with similar data obtained for another cell receptor of this family, namely human αVβ3 integrin, reveals that both these receptors are very important. Studying the specific interaction between the cell receptors in question and specially prepared monoclonal antibodies against them, we could show that both interaction sites involved in the process of virus-cell interaction remain intact at pH 5.3. At the same time, for these acid conditions characteristic for an endosome during flavivirus-cell membrane fusion, SMDFS data reveal the existence of a force-induced (effective already for forces as small as 30-70 pN) sharp globule-coil transition for LBP and LBP-fragments of protein E complexes. We argue that this conformational transformation, being an analog of abrupt first-order phase transition and having similarity with the famous Rayleigh hydrodynamic instability, might be indispensable for the flavivirus-cell membrane fusion process. Copyright © 2014 John Wiley & Sons, Ltd.

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UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon–intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua–UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua–UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua–UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua–UEV protein confers new biological properties to this regulator of variant polyubiquitination.[Kua cDNAs isolated by RT-PCR and described in this paper have been deposited in the GenBank data library under accession nos. AF1155120 (H. sapiens) and AF152361 (D. melanogaster). Genomic clones containing UEV genes: S. cerevisiae, YGL087c (accession no. Z72609); S. pombe, c338 (accession no. AL023781); P. falciparum, MAL3P2 (accession no. AL034558); A. thaliana, F26F24 (accession no. AC005292); C. elegans, F39B2 (accession no. Z92834); D. melanogaster, AC014908; and H. sapiens, 1185N5 (accession no. AL034423). Accession numbers for Kua cDNAs in GenBank dbEST: M. musculus, AA7853; T. cruzi, AI612534. Other Kua-containing sequences: A. thaliana genomic clones F10M23 (accession no. AL035440), F19K23 (accession no. AC000375), and T20K9 (accession no. AC004786).

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Intracellular membrane fusion proceeds via distinct stages of membrane docking, hemifusion and fusion pore opening and depends on interacting families of Rab, SNARE and SM proteins. Trans-SNARE complexes dock the membranes in close apposition. Efficient fusion requires further SNARE-associated proteins. They might increase the number of trans-SNARE complexes or the fusogenic potential of a single SNARE complex. We investigated the contributions of the SM protein Vps33 to hemifusion and pore opening between yeast vacuoles. Mutations in Vps33 that weaken its interactions with the SNARE complex allowed normal trans-SNARE pairing and lipid mixing but retarded content mixing. Deleting the H(abc) domain of the vacuolar t-SNARE Vam3, which interacts with Vps33, had the same effect. This suggests that SM proteins promote fusion pore opening by enhancing the fusogenic activity of a SNARE complex. They should thus be considered integral parts of the fusion machinery.

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The biological properties of wild-type A75/17 and cell culture-adapted Onderstepoort canine distemper virus differ markedly. To learn more about the molecular basis for these differences, we have isolated and sequenced the protein-coding regions of the attachment and fusion proteins of wild-type canine distemper virus strain A75/17. In the attachment protein, a total of 57 amino acid differences were observed between the Onderstepoort strain and strain A75/17, and these were distributed evenly over the entire protein. Interestingly, the attachment protein of strain A75/17 contained an extension of three amino acids at the C terminus. Expression studies showed that the attachment protein of strain A75/17 had a higher apparent molecular mass than the attachment protein of the Onderstepoort strain, in both the presence and absence of tunicamycin. In the fusion protein, 60 amino acid differences were observed between the two strains, of which 44 were clustered in the much smaller F2 portion of the molecule. Significantly, the AUG that has been proposed as a translation initiation codon in the Onderstepoort strain is an AUA codon in strain A75/17. Detailed mutation analyses showed that both the first and second AUGs of strain A75/17 are the major translation initiation sites of the fusion protein. Similar analyses demonstrated that, also in the Onderstepoort strain, the first two AUGs are the translation initiation codons which contribute most to the generation of precursor molecules yielding the mature form of the fusion protein.

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The bacterial insertion sequence IS21 contains two genes, istA and istB, which are organized as an operon. IS21 spontaneously forms tandem repeats designated (IS21)2. Plasmids carrying (IS21)2 react efficiently with other replicons, producing cointegrates via a cut-and-paste mechanism. Here we show that transposition of a single IS21 element (simple insertion) and cointegrate formation involving (IS21)2 result from two distinct non-replicative pathways, which are essentially due to two differentiated IstA proteins, transposase and cointegrase. In Escherichia coli, transposase was characterized as the full-length, 46 kDa product of the istA gene, whereas the 45 kDa cointegrase was expressed, in-frame, from a natural internal translation start of istA. The istB gene, which could be experimentally disconnected from istA, provided a helper protein that strongly stimulated the transposase and cointegrase-driven reactions. Site-directed mutagenesis was used to express either cointegrase or transposase from the istA gene. Cointegrase promoted replicon fusion at high frequencies by acting on IS21 ends which were linked by 2, 3, or 4 bp junction sequences in (IS21)2. By contrast, cointegrase poorly catalyzed simple insertion of IS21 elements. Transposase had intermediate, uniform activity in both pathways. The ability of transposase to synapse two widely spaced IS21 ends may reside in the eight N-terminal amino acid residues which are absent from cointegrase. Given the 2 or 3 bp spacing in naturally occurring IS21 tandems and the specialization of cointegrase, the fulminant spread of IS21 via cointegration can now be understood.