851 resultados para Nondegenerate Parametric Amplification


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In the present study we utilised functional magnetic resonance imaging (fMRI) to examine cerebral activation during performance of a classic motor task in which response suppression load was parametrically varied. Linear increases in activity were observed in a distributed network of regions across both cerebral hemispheres, although with more extensive involvement of the right prefrontal cortex. Activated regions included prefrontal, parietal and occipitotemporal cortices. Decreasing activation was similarly observed in a distributed network of regions. These response forms are discussed in terms of an increasing requirement for visual cue discrimination and suppression/selection of motor responses, and a decreasing probability of the occurrence of non-target stimuli and attenuation of a prepotent tendency to respond. The results support recent proposals for a dominant role for the right-hemisphere in performance of motor response suppression tasks that emphasise the importance of the right prefrontal cortex.

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Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

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In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. After a pilot run of ABC, the likelihood-free parametric bootstrap approach requires very few model simulations to produce an approximate posterior, which can be a useful approximation in its own right. An alternative is to use this approximation as a proposal distribution in ABC algorithms to make them more efficient. In this paper, the parametric bootstrap approximation is used to form the initial importance distribution for the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. The new approach is illustrated through a simulation study of the univariate g-and- k quantile distribution, and is used to infer parameter values of a stochastic model describing expanding melanoma cell colonies.

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An innovative cement-based soft-hard-soft (SHS) multi-layer composite has been developed for protective infrastructures. Such composite consists of three layers including asphalt concrete (AC), high strength concrete (HSC), and engineered cementitious composites (ECC). A three dimensional benchmark numerical model for this SHS composite as pavement under blast load was established using LSDYNA and validated by field blast test. Parametric studies were carried out to investigate the influence of a few key parameters including thickness and strength of HSC and ECC layers, interface properties, soil conditions on the blast resistance of the composite. The outcomes of this study also enabled the establishment of a damage pattern chart for protective pavement design and rapid repair after blast load. Efficient methods to further improve the blast resistance of the SHS multi-layer pavement system were also recommended.

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Eleven new human polyomaviruses have been recently discovered, yet for most of these viruses, little is known of their biology and clinical impact. Rolling circle amplification (RCA) is an ideal method for the amplification of the circular polyomavirus genome due to its high fidelity amplification of circular DNA. In this study, a modified RCA method was developed to selectively amplify a range of polyomavirus genomes. Initial evaluation showed a multiplexed temperature-graded reaction profile gave the best yield and sensitivity in amplifying BK polyomavirus in a background of human DNA, with up to 1 × 10(8)-fold increases in viral genomes from as little as 10 genome copies per reaction. Furthermore, the method proved to be more sensitive and provided a 200-fold greater yield than that of random hexamers based standard RCA. Application of the method to other novel human polyomaviruses showed successful amplification of TSPyV, HPyV6, HPyV7, and STLPyV from low-viral load positive clinical samples, with viral genome enrichment ranging from 1 × 10(8) up to 1 × 10(10). This directed RCA method can be applied to selectively amplify other low-copy polyomaviral genomes from a background of competing non-specific DNA, and is a useful tool in further research into the rapidly expanding Polyomaviridae family.

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Results of photoelastic investigations on single edge-notch tension specimens of varying notch angle and crack length are reported. The experimental results of Mode I stress intensity factors are compared with analytical results.

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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Twelve microsatellite DNA markers were isolated in the spot-tail shark (Carcharhinus sorrah) and nine were isolated in Australian black-tip shark (Carcharhinus tilstoni). These loci plus 18 others developed for sharks from the genera Negaprion, Ginglymostoma, Carcharodon and Isurus were tested for amplification success on four species of Carcharhinus (including C. sorrah and C. tilstoni) and four other species representing three diverse families. Cross-amplification was most common within families. Five loci were subsequently tested for polymorphism on 50 C. sorrah and 60 C. tilstoni. The number of alleles per locus was two to 24 and the average heterozygosity was 0.54 (range 0.16-0.87) for C. sorrah and 0.64 (range 0.44-0.78) for C. tilstoni. These loci may be useful tools for genetic analyses of the Carcharhinidae.

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Obesity has long been linked with prostate cancer progression, although the underlying mechanism is still largely unknown. Here, we report that adipocytes promote the enrichment of prostate cancer stem cells (CSCs) through a vicious cycle of autocrine amplification. In the presence of adipocytes, prostate cancer cells actively secrete the peptide hormone cholecystokinin (CCK), which not only stimulates prostate CSC self-renewal, but also induces cathepsin B (CTSB) production of the adipocytes. In return, CTSB facilitates further CCK secretion by the cancer cells. More importantly, inactivation of CCK receptor not only suppresses CTSB secretion by the adipocytes, but also synergizes the inhibitory effect of CTSB inhibitor on adipocyte-promoted prostate CSC self-renewal. In summary, we have uncovered a novel mechanism underlying the mutual interplay between adipocytes and prostate CSCs, which may help explaining the role of adipocytes in prostate cancer progression and provide opportunities for effective intervention.

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Genetic variation among 29 isolates of Fusarium oxysporum f.sp. zingiberi (Foz) collected from diseased ginger rhizome in production regions throughout Queensland was analysed using DNA amplification fingerprinting (DAF). Eight isolates of other Fusarium species and/or formae speciales were included for comparative analysis. Within the Foz isolates, three haplotypes were identified based on 17 polymorphic bands generated with five primers. Two groups showed very little genetic variation (98.6% similarity), whereas the third single isolate was quite distinct in terms of its molecular profile (77.2% similarity). Genetic similarity among the Fusarium solani, F. oxysporum f.sp. lycopersici and F. oxysporum f.sp. cubense races 1, 3 and 4 isolates compared well with the published literature.

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Typhoid fever is becoming an ever increasing threat in the developing countries. We have improved considerably upon the existing PCR-based diagnosis method by designing primers against a region that is unique to Salmonella enterica subsp. enterica serovar Typhi and Salmonella enterica subsp. enterica serovar Paratyphi A, corresponding to the STY0312 gene in S. Typhi and its homolog SPA2476 in S. Paratyphi A. An additional set of primers amplify another region in S. Typhi CT18 and S. Typhi Ty2 corresponding to the region between genes STY0313 to STY0316 but which is absent in S. Paratyphi A. The possibility of a false-negative result arising due to mutation in hypervariable genes has been reduced by targeting a gene unique to typhoidal Salmonella serovars as a diagnostic marker. The amplified region has been tested for genomic stability by amplifying the region from clinical isolates of patients from various geographical locations in India, thereby showing that this region is potentially stable. These set of primers can also differentiate between S. Typhi CT18, S. Typhi Ty2, and S. Paratyphi A, which have stable deletions in this specific locus. The PCR assay designed in this study has a sensitivity of 95% compared to the Widal test which has a sensitivity of only 63%. As observed, in certain cases, the PCR assay was more sensitive than the blood culture test was, as the PCR-based detection could also detect dead bacteria.

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Genotyping in DNA pools reduces the cost and the time required to complete large genotyping projects. The aim of the present study was to evaluate pooling as part of a strategy for fine mapping in regions of significant linkage. Thirty-nine single nucleotide polymorphisms (SNPs) were analyzed in two genomic DNA pools of 384 individuals each and results compared with data after typing all individuals used in the pools. There were no significant differences using data from either 2 or 8 heterozygous individuals to correct frequency estimates for unequal allelic amplification. After correction, the mean difference between estimates from the genomic pool and individual allele frequencies was .033. A major limitation of the use of DNA pools is the time and effort required to carefully adjust the concentration of each individual DNA sample before mixing aliquots. Pools were also constructed by combining DNA after Multiple Displacement Amplification (MDA). The MDA pools gave similar results to pools constructed after careful DNA quantitation (mean difference from individual genotyping .040) and MDA provides a rapid method to generate pools suitable for some applications. Pools provide a rapid and cost-effective screen to eliminate SNPs that are not polymorphic in a test population and can detect minor allele frequencies as low as 1% in the pooled samples. With current levels of accuracy, pooling is best suited to an initial screen in the SNP validation process that can provide high-throughput comparisons between cases and controls to prioritize SNPs for subsequent individual genotyping.

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We describe a novel approach to treatment planning for focal brachytherapy utilizing a biologically based inverse optimization algorithm and biological imaging to target an ablative dose at known regions of significant tumour burden and a lower, therapeutic dose to low risk regions.

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In der vorliegenden Arbeit wird die Methode der parametrischen Differentiation angewendet, um ein System nichtlinearer Gleichungen zu lösen, das zwei- und dreidimensionale freie, konvektive Grenzschichströmungen bzw. eine zweidimensionale magnetohydrodynamische Grenzschichtströmung beherrscht. Der Hauptvorteil dieser Methode besteht darin, daß die nichlinearen Gleichungen auf lineare reduziert werden und die Nichtlinearität auf ein System von Gleichungen erster Ordnung beschränkt wird, das, verglichen mit den ursprünglichen Nichtlinearen Gleichungen, viel leichter gelöst werden kann. Ein anderer Vorzug der Methode ist, daß sie es ermöglicht, die Lösung von einer bekannten, zu einem bestimmten Parameterwert gehörigen Lösung aus durch schrittweises Vorgehen die Lösung für den gesamten Parameterbereich zu erhalten. Die mit dieser Methode gewonnenen Ergebnisse stimmen gut mit den entsprechenden, mit anderen numerischen Verfahren erzielten überein.