988 resultados para Mode selection


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Indium tin-oxide (ITO) and polycrystalline boron-doped diamond (BDD) have been examined in detail using the scanning electrochemical microscopy technique in feedback mode. For the interrogation of electrodes made from these materials, the choice of mediator has been varied. Using Ru(CN) 4− 6 (aq), ferrocene methanol (FcMeOH), Fe(CN) 3− 6 (aq) and Ru(NH 3) 3+ 6 (aq), approach curve experiments have been performed, and for purposes of comparison, calculations of the apparent heterogeneous electron transfer rates (k app) have been made using these data. In general, it would appear that values of k app are affected mainly by the position of the mediator reversible potential relative to the relevant semiconductor band edge (associated with majority carriers). For both the ITO (n type) and BDD (p type) electrodes, charge transfer is impeded and values are very low when using FcMeOH and Fe(CN) 3− 6 (aq) as mediators, and the use of Ru(NH 3) 3+ 6(aq) results in the largest value of k app. With ITO, the surface is chemically homogeneous and no variation is observed for any given mediator. Data is also presented where the potential of the ITO electrode is fixed using a ratio of the mediators Fe(CN) 3− 6(aq) and Fe(CN) 4− 6(aq). In stark contrast, the BDD electrode is quite the opposite and a range of k app values are observed for all mediators depending on the position on the surface. Both electrode surfaces are very flat and very smooth, and hence, for BDD, variations in feedback current imply a variation in the electrochemical activity. A comparison of the feedback current where the substrate is biased and unbiased shows a surprising degree of proportionality.

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The charge transfer-mediated surface enhanced Raman scattering (SERS) of crystal violet (CV) molecules that were chemically conjugated between partially polarized silver nanoparticles and optically smooth gold and silver substrates has been studied under off-resonant conditions. Tyrosine molecules were used as a reducing agent to convert silver ions into silver nanoparticles where oxidised tyrosine caps the silver nanoparticle surface with its semiquinone group. This binding through the quinone group facilitates charge transfer and results in partially oxidised silver. This establishes a chemical link between the silver nanoparticles and the CV molecules, where the positively charged central carbon of CV molecules can bind to the terminal carboxylate anion of the oxidised tyrosine molecules. After drop casting Ag nanoparticles bound with CV molecules it was found that the free terminal amine groups tend to bind with the underlying substrates. Significantly, only those CV molecules that were chemically conjugated between the partially polarised silver nanoparticles and the underlying gold or silver substrates were found to show SERS under off-resonant conditions. The importance of partial charge transfer at the nanoparticle/capping agent interface and the resultant conjugation of CV molecules to off resonant SERS effects was confirmed by using gold nanoparticles prepared in a similar manner. In this case the capping agent binds to the nanoparticle through the amine group which does not facilitate charge transfer from the gold nanoparticle and under these conditions SERS enhancement in the sandwich configuration was not observed.

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Nowadays, most of the infrastructure development projects undertaken are complex in nature. Practically, public clients who do not have a good understanding of the design and management may suffer severe losses, especially for infrastructure projects. There is a need for luring the right consultant to secure client's investment in infrastructure developments. Throughout the project life cycle, consultants play vital role from the inception to completion stage of a project. A few studies in Malaysia show that infrastructure projects involving irrigation and drainage have experience problems such as poor workmanship, delay and cost overrun due to the consultant's inability or the client incompetence of recruiting consultants in time. This highlights the need of aided decision making and an efficient system to select the best consultant by using Decision Support System (DSS). On the other hand, recent trends reveal that most DSS in construction only concentrate on decision model development. These models are impractical and unused as they are complicated or difficult for laymen such as project managers to utilize. Thus, this research attempts to develop an efficient DSS for consultant selection namely consultDeSS. Driven by the motivation and research aims, this study deployed Design Science Research Methodology (DSRM) dominant with a combination of case studies at the Malaysian Department of Irrigation and Drainage (DID). Two real projects involving irrigation and drainage infrastructure were used to design, implement and evaluate the artefact. The 3-tier consultDeSS was revised after the evaluation and the design was significantly improved based on user feedback. By developing desirable tools that fit client's needs will enhance the productivity and minimize conflict within groups and organisations. The tool is more usable and efficient compared to previous studies in construction. Thus, this research has demonstrated a purposeful artefact with a practical and valid structured development approach that is applicable in a variety of problems in construction discipline.

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Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

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Mobile teledermatoscopy (MTD) for the early detection of skin cancer uses smartphones with dermatoscope attachments to magnify, capture, and transfer images remotely.1 Using the asymmetry–color variation (AC) rule, consumers achieve dermoscopy sensitivity of 92.9% to 94.0% and specificity of 62.0% to 64.2% for melanoma.2 This pilot randomized trial assessed lesions of concern selected by consumers at high risk of melanoma using MTD plus the AC rule (intervention, n = 10) or the AC rule alone (control, n = 12) during skin self-examination (SSE). Also measured were lesion location patterns, lesions overlooked by participants, provisional clinical diagnoses, likelihood of malignant tumor, and participant pressure to excise lesions.

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In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.

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Plants transformed with Agrobacterium frequently contain T-DNA concatamers with direct-repeat (d/r) or inverted-repeat (i/r) transgene integrations, and these repetitive T-DNA insertions are often associated with transgene silencing. To facilitate the selection of transgenic lines with simple T-DNA insertions, we constructed a binary vector (pSIV) based on the principle of hairpin RNA (hpRNA)-induced gene silencing. The vector is designed so that any transformed cells that contain more than one insertion per locus should generate hpRNA against the selective marker gene, leading to its silencing. These cells should, therefore, be sensitive to the selective agent and less likely to regenerate. Results from Arabidopsis and tobacco transformation showed that pSIV gave considerably fewer transgenic lines with repetitive insertions than did a conventional T-DNA vector (pCON). Furthermore, the transgene was more stably expressed in the pSIV plants than in the pCON plants. Rescue of plant DNA flanking sequences from pSIV plants was significantly more frequent than from pCON plants, suggesting that pSIV is potentially useful for T-DNA tagging. Our results revealed a perfect correlation between the presence of tail-to-tail inverted repeats and transgene silencing, supporting the view that read-through hpRNA transcript derived from i/r T-DNA insertions is a primary inducer of transgene silencing in plants. © CSIRO 2005.

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Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

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Ureaplasmas are the microorganisms most frequently isolated from the amniotic fluid of pregnant women and can cause chronic intrauterine infections. These tiny bacteria are thought to undergo rapid evolution and exhibit a hypermutatable phenotype; however, little is known about how ureaplasmas respond to selective pressures in utero. Using an ovine model of chronic intra-amniotic infection, we investigated if exposure of ureaplasmas to sub-inhibitory concentrations of erythromycin could induce phenotypic or genetic indicators of macrolide resistance. At 55 days gestation, 12 pregnant ewes received an intra-amniotic injection of a non-clonal, clinical U. parvum strain, followed by: (i) erythromycin treatment (IM, 30 mg/kg/day, n=6); or (ii) saline (IM, n=6) at 100 days gestation. Fetuses were then delivered surgically at 125 days gestation. Despite injecting the same inoculum into all ewes, significant differences between amniotic fluid and chorioamnion ureaplasmas were detected following chronic intra-amniotic infection. Numerous polymorphisms were observed in domain V of the 23S rRNA gene of ureaplasmas isolated from the chorioamnion (but not the amniotic fluid), resulting in a mosaic-like sequence. Chorioamnion isolates also harboured the macrolide resistance genes erm(B) and msr(D) and were associated with variable roxithromycin minimum inhibitory concentrations. Remarkably, this variability occurred independently of exposure of ureaplasmas to erythromycin, suggesting that low-level erythromycin exposure does not induce ureaplasmal macrolide resistance in utero. Rather, the significant differences observed between amniotic fluid and chorioamnion ureaplasmas suggest that different anatomical sites may select for ureaplasma sub-types within non-clonal, clinical strains. This may have implications for the treatment of intrauterine ureaplasma infections.

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The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

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Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

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Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

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Background: Self-selection-whether individuals inclined to walk more seek to live in walkable environments-must be accounted for when studying built environment influences on walking. The way neighborhoods are marketed to future residents has the potential to sway residential location choice, and may consequently affect measures of self-selection related to location preferences. We assessed how walking opportunities are promoted to potential buyers, by examining walkability attributes in marketing materials for housing developments. Methods: A content analysis of marketing materials for 32 new housing developments in Perth, Australia was undertaken, to assess how walking was promoted in the text and pictures. Housing developments designed to be pedestrian-friendly (LDs) were compared with conventional developments (CDs). Results: Compared with CDs, LD marketing materials had significantly more references to 'public transport,' small home sites,' walkable parks/open space,' ease of cycling,' safe environment,' and 'boardwalks.' Other walkability attributes approached significance. Conclusion: Findings suggest the way neighborhoods are marketed may contribute to self-reported reasons for choosing particular neighborhoods, especially when attributes are not present at the time of purchase. The marketing of housing developments may be an important factor to consider when measuring self-selection, and its influence on the built environment and walking relationship.