990 resultados para high potentials


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Ce1-xSnxO2 (x = 0.1-0.5) solid solution and its Pd substituted analogue have been prepared by a single step solution combustion method using tin oxalate precursor. The compounds were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and H-2/temperature programmed redution (TPR) studies. The cubic fluorite structure remained intact up to 50% of Sri substitution in CeO2, and the compounds were stable up to 700 C. Oxygen storage capacity of Ce1-xSnxO2 was found to be much higher than that of Ce1-xZrxO2 due to accessible Ce4+/Ce3+ and Sn4+/Sn2+ redox couples at temperatures between 200 and 400 C. Pd 21 ions in Ce0.78Sn0.2Pd0.02O2-delta are highly ionic, and the lattice oxygen of this catalyst is highly labile, leading to low temperature CO to CO2 conversion. The rate of CO oxidation was 2 mu mol g(-1) s(-1) at 50 degrees C. NO reduction by CO with 70% N-2 selectivity was observed at similar to 200 degrees C and 100% N-2 selectivity below 260 degrees C with 1000-5000 ppm NO. Thus, Pd2+ ion substituted Ce1-xSnxO2 is a superior catalyst compared to Pd2+ ions in CeO2, Ce1-xZrxO2, and Ce1-xTixO2 for low temperature exhaust applications due to the involvement of the Sn2+/Sn4+ redox couple along with Pd2+/Pd-0 and Ce4+/Ce3+ couples.

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Non-Abelian quantum Hall states are characterized by the simultaneous appearance of charge and neutral gapless edge modes, with the structure of the latter being intricately related to the existence of bulk quasiparticle excitations obeying non-Abelian statistics. Here we propose a scenario for detecting the neutral modes by having two point contacts in series separated by a distance set by the thermal equilibration length of the charge mode. We show that by using the first point contact as a heating device, the excess charge noise measured at the second point contact carries a nontrivial signature of the presence of the neutral mode. We also obtain explicit expressions for the thermal conductance and corresponding Lorentz number for transport across a quantum point contact between two edges held at different temperatures and chemical potentials.

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This paper proposes a novel way of generating high voltage for electric discharge plasma in controlling NOx emission in diesel engine exhaust. A solar powered high frequency electric discharge topology has been suggested that will improve the size and specific energy density required when compared to the traditional repetitive pulse or 50 Hz AC energization. This methodology has been designed, fabricated and experimentally verified by conducting studies on real diesel engine exhaust.

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High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have implemented a Firewall with this architecture in reconflgurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results in both speed and area improvement when it is implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields. High throughput classification invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly in terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for the worst case packet size. The Firewall rule update involves only memory re-initialization in software without any hardware change.

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Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

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Objectives Funding for early career researchers in Australia's largest medical research funding scheme is determined by a competitive peer-review process using a panel of four reviewers. The purpose of this experiment was to appraise the reliability of funding by duplicating applications that were considered by separate grant review panels. Study Design and Methods Sixty duplicate applications were considered by two independent grant review panels that were awarding funding for Australia's National Health and Medical Research Council. Panel members were blinded to which applications were included in the experiment and to whether it was the original or duplicate application. Scores were compared across panels using Bland–Altman plots to determine measures of agreement, including whether agreement would have impacted on actual funding. Results Twenty-three percent of the applicants were funded by both panels and 60 percent were not funded by both, giving an overall agreement of 83 percent [95% confidence interval (CI): 73%, 92%]. The chance-adjusted agreement was 0.75 (95% CI: 0.58, 0.92). Conclusion There was a comparatively high level of agreement when compared with other types of funding schemes. Further experimental research could be used to determine if this higher agreement is due to nature of the application, the composition of the assessment panel, or the characteristics of the applicants.

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A series of dual-phase (DP) steels containing finely dispersed martensite with different volume fractions of martensite (V-m) were produced by intermediate quenching of a boron- and vanadium-containing microalloyed steel. The volume fraction of martensite was varied from 0.3 to 0.8 by changing the intercritical annealing temperature. The tensile and impact properties of these steels were studied and compared to those of step-quenched steels, which showed banded microstructures. The experimental results show that DP steels with finely dispersed microstructures have excellent mechanical properties, including high impact toughness values, with an optimum in properties obtained at similar to 0.55 V-m. A further increase in V-m was found to decrease the yield and tensile strengths as well as the impact properties. It was shown that models developed on the basis of a rule of mixtures are inadequate in capturing the tensile properties of DP steels with V-m > 0.55. Jaoul-Crussard analyses of the work-hardening behavior of the high-martensite volume fraction DP steels show three distinct stages of plastic deformation.

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Neural data are inevitably contaminated by noise. When such noisy data are subjected to statistical analysis, misleading conclusions can be reached. Here we attempt to address this problem by applying a state-space smoothing method, based on the combined use of the Kalman filter theory and the Expectation–Maximization algorithm, to denoise two datasets of local field potentials recorded from monkeys performing a visuomotor task. For the first dataset, it was found that the analysis of the high gamma band (60–90 Hz) neural activity in the prefrontal cortex is highly susceptible to the effect of noise, and denoising leads to markedly improved results that were physiologically interpretable. For the second dataset, Granger causality between primary motor and primary somatosensory cortices was not consistent across two monkeys and the effect of noise was suspected. After denoising, the discrepancy between the two subjects was significantly reduced.

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We propose an exactly solvable model for the two-state curve-crossing problem. Our model assumes the coupling to be a delta function. It is used to calculate the effect of curve crossing on the electronic absorption spectrum and the resonance Raman excitation profile.

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An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.

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High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have Implemented a Firewall with this architecture in reconfigurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using, our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results In both speed and area Improvement when It is Implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields.High throughput classification Invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly In terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware Implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for file worst case packet size. The Firewall rule update Involves only memory re-initialiization in software without any hardware change.

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Young females with mild hallux valgus (HV) have been identified as having an increased risk of first ray deformation. Little is known, however, about the biomechanical changes that might contribute to this increased risk. The purpose of this study was to compare kinetics changes during walking for mild HV subjects with high-heel-height shoes. Twelve female subjects (six with mild HV and six controls) participated in this study with heel height varying from 0 cm (barefoot) to 4.5 cm. Compared to healthy controls, patients had significantly higher peak pressure on the big toe area during barefoot walking. When the heel height increased, loading was transferred to medial side of the forefoot, and the big toe area suffered more impact compared to barefoot in mild HV. This study also demonstrated that the center of pressure (COP) inclines to medial side alteration after high-heeled shoes wearing. These findings indicate that mild HV people should be discouraged from wearing high-heeled shoes.

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Background and purpose: To prospectively evaluate differences in carotid plaque characteristics in symptomatic and asymptomatic patients using high resolution MRI. Methods: 20 symptomatic and 20 asymptomatic patients, with at least 50% carotid stenosis as determined by Doppler ultrasound, underwent preoperative in vivo multispectral MRI of the carotid arteries. Studies were analysed both qualitatively and quantitatively in a randomised manner by two experienced readers in consensus, blinded to clinical status, and plaques were classified according to the modified American Heart Association (AHA) criteria. Results: After exclusion of poor quality images, 109 MRI sections in 18 symptomatic and 19 asymptomatic patients were available for analysis. There were no significant differences in mean luminal stenosis severity (72.9% vs 67.6%; p = 0.09) or plaque burden (median plaque areas 50 mm2 vs 50 mm 2; p = 0.858) between the symptomatic and asymptomatic groups. However, symptomatic lesions had a higher incidence of ruptured fibrous caps (36.5% vs 8.7%; p = 0.004), haemorrhage or thrombus (46.5% vs 14.0%; p<0.001), large necrotic lipid cores (63.8% vs 28.0%; p = 0.002) and complicated type VI AHA lesions (61.5% vs 28.1%; p = 0.001) compared with asymptomatic lesions. The MRI findings of plaque haemorrhage or thrombus had an odds ratio of 5.25 (95% CI 2.08 to 13.24) while thin or ruptured fibrous cap (as opposed to a thick fibrous cap) had an odds ratio of 7.94 (95% CI 2.93 to 21.51) for prediction of symptomatic clinical status. Conclusions: There are significant differences in plaque characteristics between symptomatic and asymptomatic carotid atheroma and these can be detected in vivo by high resolution MRI.