121 resultados para correlation decoding


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Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. 

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This study describes the preclinical development of a matrix-type silicone elastomer vaginal ring device designed to provide controlled release of UC781, a non-nucleoside re- verse transcriptase inhibitor. Testing of both human- and macaque-sized rings in a sink condition in vitro release model demonstrated continuous UC781 release in quantities consid- ered sufficient to maintain vaginal fluid concentrations at levels 82–860-fold higher than the in vitro IC50 (2.0 to 10.4 nM) and therefore potentially protect against mucosal trans- mission of HIV. The 100-mg UC781 rings were well tolerated in pig-tailed macaques, did not induce local inflammation as determined by cytokine analysis and maintained median con- centrations in vaginal fluids of UC781 in the range of 0.27 to 5.18 mM during the course of the 28-day study. Analysis of residual UC781 content in rings after completion of both the in vitro release and macaque pharmacokinetic studies revealed that 57 and 5 mg of UC781 was released, respectively. The pharmacokinetic analysis of a 100-mg UC781 vaginal ring in pig-tailed macaques showed poor in vivo–in vitro correlation, attributed to the very poor solubility of UC781 in vaginal fluid and resulting in a dissolution-controlled drug release mecha- nism rather than the expected diffusion-controlled mechanism.

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Reversible work extraction from identical quantum systems via collective operations was shown to be possible even without producing entanglement among the sub-parts. Here, we show that implementing such global operations necessarily imply the creation of quantum correlations, as measured by quantum discord. We also reanalyze the conditions under which global transformations outperform local gates as far as maximal work extraction is considered by deriving a necessary and sufficient condition that is based on classical correlations.

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Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

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The statistical properties of the multivariate GammaGamma (ΓΓ) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (PDF), cumulative distribution function (CDF) and moment generation function of the multivariate ΓΓ distribution with arbitrary correlation. Furthermore, we present novel approximating expressions for the PDF and CDF of the su m of ΓΓ random variables with arbitrary correlation. Based on this statistical analysis, we investigate the performance of radio frequency and optical wireless communication systems. It is noteworthy that the presented expressions include several previous results in the literature as special cases.

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A novel digital image correlation (DIC) technique has been developed to track changes in textile yarn orientations during shear characterisation experiments, requiring only low-cost digital imaging equipment. Fabric shear angles and effective yarn strains are calculated and visualised using this new DIC technique for bias extension testing of an aerospace grade, carbon-fibre reinforcement material with a plain weave architecture. The DIC results are validated by direct measurement, and the use of a wide bias extension sample is evaluated against a more commonly used narrow sample. Wide samples exhibit a shear angle range 25% greater than narrow samples and peak loads which are 10 times higher. This is primarily due to excessive yarn slippage in the narrow samples; hence, the wide sample configuration is recommended for characterisation of shear properties which are required for accurate modelling of textile draping.

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A resazurin (Rz) based photocatalyst indicator ink is used to test the activity of a commercial self-cleaning glass, using UV–vis spectroscopy and digital photography to monitor the photocatalyst-driven change in colour of the ink. UV–vis spectroscopy allows the change in film absorbance, ΔAbs, to be monitored as a function of irradiation time, whereas digital photography is used to monitor the concomitant change in the red component of the RGB values, i.e. ΔRGB (red). Initial work reveals the variation in ΔAbst and ΔRGB (red)t as a function of irradiation time, t, are linearly correlated. The rates of change of these parameters are also linearly correlated to the rates of oxidative destruction of stearic acid on self-cleaning glass under different irradiances. This work demonstrates that a measure of photocatalyst activity of self-cleaning glass, i.e. the time taken to change the colour of an Rz photocatalyst indicator ink, can be obtained using inexpensive digital photography, as alternative to more expensive lab-based techniques, such as UV–vis spectrophotometry.

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Purpose Previously, it has been reported that molecular mobility determines the rate of molecular approach to crystal surfaces, while entropy relates to the probability of that approaching molecule having the desirable configuration for further growth of the existing crystal; and the free energy dictates the probability of that molecule not returning to the liquid phase1. If we plot the crystal growth rate and viscosity of a supercooled liquid in a log-log format, the relationship between the two is linear, indicating the influence viscosity has upon crystal growth rate. However, such approximation has been derived from pure drug compounds and it is apparent that further understanding of crystallization from drug-polymer solid dispersion is required in order to stabilise drugs embedded within amorphous polymeric solid dispersions. Methods Mixtures of felodipine and polymer (HPMCAS-HF, PVPK15 and Soluplus®) at specified compositions were prepared using a Restch MM200 ball mill. To examine crystal growth within amorphous solid dispersions, samples were prepared by melting 5-10 mg of ball milled mixture at 150°C for 3-5 minutes on a glass slip pre-cleaned with methanol and acetone. All prepared samples were confirmed to be crystal free by visual observation using a polarised light microscope (Olympus BX50). Prepared samples were stored at 0% RH (P2O5), inside desiccators, maintained in ovens at 80°C. For the dynamic viscosity measurement, approximately 100-200mg ball milled mixture was heated on the base plate of a rotational rheometer at 150°C for 5 minutes and the top plate was lowered to a defined gap to form a good contact with the material. The sandwiched amorphous material was heated to 80°C and the viscosity was measured. Results The equation was used to probe the correlation of viscosity to crystal growth rate. In comparison to the value of xi in log-log equation reported from pure drug compound, a value of 1.63 was obtained for FD-polymer solid dispersions irrespective of the polymer involved. &#8733 Conclusion The high xi value suggests stronger viscosity dependence may exist for amorphous FD once incorporated with amorphous polymer.

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High Efficiency Video Coding (HEVC) is the most recent video codec coming after currently most popular H.264/MPEG4 codecs and has promising compression capabilities. It is conjectured that it will be a substitute for current video compression standards. However, to the best knowledge of the authors, none of the current video steganalysis methods designed or tested with HEVC video. In this paper, pixel domain steganography applied on HEVC video is targeted for the first time. Also, its the first paper that employs accordion unfolding transformation, which merges temporal and spatial correlation, in pixel domain video steganalysis. With help of the transformation, temporal correlation is incorporated into the system. Its demonstrated for three different feature sets that integrating temporal dependency substantially increased the detection accuracy.

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The activity levels of stars are influenced by several stellar properties, such as stellar rotation, spectral type, and the presence of stellar companions. Analogous to binaries, planetary companions are also thought to be able to cause higher activity levels in their host stars, although at lower levels. Especially in X-rays, such influences are hard to detect because coronae of cool stars exhibit a considerable amount of intrinsic variability. Recently, a correlation between the mass of close-in exoplanets and their host star's X-ray luminosity has been detected, based on archival X-ray data from the ROSAT All-Sky Survey. This finding has been interpreted as evidence for star-planet interactions. We show in our analysis that this correlation is caused by selection effects due to the flux limit of the X-ray data used and due to the intrinsic planet detectability of the radial velocity method, and thus does not trace possible planet-induced effects. We also show that the correlation is not present in a corresponding complete sample derived from combined XMM-Newton and ROSAT data.