Morphology development in polyethylene/polystyrene blends: the influence of processing conditions and interfacial modification

The influence of processing conditions and interfacial modification on the morphology evolution and the composition range within which fully co‐continuous high density polyethylene/polystyrene blend structures can exist during blending in a single screw extruder was studied. Blends ranging from pure A to pure B component, with and without compatibilizer, were prepared under two different shear rates. It was found that high shear rates displaced the breakdown–coalescence balance of the dispersed nodules to the side of coalescence, narrowing the percolation domain and the critical composition for full co‐continuity decreased with increasing shear rates. The addition of a tri‐block compatibilizer induced the percolation threshold of the polystyrene phase to begin at lower percentages of polyethylene but the phase inversion point did not change. The experimental results are discussed in the light of various theoretical models. Copyright © 2005 Society of Chemical Industry     

A fast PNN design algorithm for entropy-constrained residual vectorquantization

A clustering algorithm based on the pairwise nearest-neighbor (PNN) algorithm developed by Equitz (1989), is introduced for the design of entropy-constrained residual vector quantizers. The algorithm designs residual vector quantization codebooks by merging the pair of stage clusters that minimizes the increase in overall distortion subject to a given decrease in entropy. Image coding experiments show that the clustering design algorithm typically results in more than a 200:1 reduction in design time relative to the standard iterative entropy-constrained residual vector quantization algorithm while introducing only small additional distortion. Multipath searching over the sequence of merges is also investigated and shown experimentally to slightly improve rate-distortion performance. The proposed algorithm can be used alone or can he followed by the iterative algorithm to improve the reproduction quality at the same bit rate.     

Iterative scheme for MS image pansharpening based on the combination of multi-resolution decompositions

Image pansharpening in the remote-sensing domain may be defined as the technique of extracting high-resolution details from the panchromatic (PAN) image and injecting them into the multispectral (MS) one in a way to preserve the spectral signature and improve the spatial resolution. In this article, the authors propose an image fusion framework that tries to derive sharpened MS image such that: (i) when decimated taking into account the imagery system Modulation Transfer Function (MTF), it equals the original MS image; (ii) when decomposed using discrete wavelet transform (DWT), its geometrical details are those of the PAN image weighted by the compatibility PAN/MS. Indeed, MS sharpening is carried out in two steps. First, pre-pansharpened MS image is obtained using inverse DWT taking as approximations those of the upsampled original MS image and as details those of PAN (to reduce spectral distortion, PAN detail injection is performed proportionally to the similarity PAN/MS). Second, to satisfy (i) and to remove the PAN-MS disagreement, an iteration algorithm (alternatively corrects approximations and details) has been proposed. The proposed approach is designed in two versions inspired by the Generalized Laplacian Pyramid (GLP) and the Gram–Schmidt (GS) transformation, respectively.

To validate our approach, Pléiades-1A, Geoeye-1, and Landsat Enhanced Thematic Mapper Plus (ETM+) images are tested. The results of qualitative and quantitative scores are presented and discussed. Compared to well-known techniques, our approach shows generally better results, particularly the one based on GLP formalism.     

Fatty acid accumulation in the different fractions of the developing corn kernel

In the food industry, the use of the oil is determined by the composition of fatty acids, and this is highly dependent on its natural origin. The fatty acid composition of whole corn kernel was determined in three varieties of corn (Astro, GH2547, and Local). Linoleic acid was the predominant fatty acid in the oil of Astro and Local at all collection dates, whereas it was the major fatty acid in the oil of GH2547 only between 40 and 60 days after pollination (DAP). The fatty acid accumulation in the endosperm, pericarp and germ fractions of the corn kernel during maturation was determined. The accumulation pattern of oil content was different in these three kernel fractions. The highest levels of oil content in the endosperm (2.2%), germ (34.3%) and pericarp (10.8%) fractions were detected at 20, 40 and 30 (DAP), respectively. The fatty acid accumulation patterns were different amongst the analysed kernel parts, indicating a numerous differences between the three corn kernel parts. Throughout the sampling periods, the endosperm fraction was distinguished by the highest and the lowest levels of oleic and linoleic acids, respectively. At all stages of kernel development, the pericarp fraction had the highest levels of total polyunsaturated fatty acids, which has numerous healthy applications. These results may be useful in the understanding of the potential source of the beneficial unsaturated fatty acids amongst the different fractions of the corn kernel during maturation.     

Multireference object pose retrieval with volume feedback

Pose retrieval of a rigid object from monocular video sequences or images is addressed. Initially, the object pose is estimated in each image assuming flat depth maps. Shape-from-silhouette is then applied to make a 3-D model (volume), which is used for a new round of pose estimations, this time by a model-based method that gives better estimates. Before repeating this process by building a new volume, pose estimates are adjusted to reduce error by maximizing a novel quality factor for shape-from-silhouette volume reconstruction. The feedback loop is terminated when pose estimates do not change much, as compared with those produced by the previous iteration. Based on a theoretical study of the proposed system, a test of convergence to a given set of poses is devised. Reliable performance of the system is also proved by several experiments on both synthetic and real image sequences. No model is assumed for the object and no feature point is detected or tracked as there is no problematic feature matching or correspondence. Our method can be used for 3-D object tracking in video, 3-D modeling, and volume reconstruction from video.     

Fast and high performance image subsampling using feedforwardneural networks

We introduce a fast and high performance image subsampling method using feedforward artificial neural networks (FANNs). Our method employs a pattern matching technique to extract local edge information within the image, in order to select the FANN desired output values during the supervised training stage. Subjective and objective evaluations of experimental results using still images and video frames show that our method, while less computationally intensive, outperforms the standard lowpass filtering and subsampling method.     

A comparison of predictive measures of problem difficulty inevolutionary algorithms

This paper studies a number of predictive measures of problem difficulty, among which epistasis variance and fitness distance correlation are the most widely known. Our approach is based on comparing the reference class of a measure to a number of known easy function classes. First, we generalize the reference classes of fitness distance correlation and epistasis variance, and construct a new predictive measure that is insensitive to nonlinear fitness scaling. We then investigate the relations between the reference classes of the measures and a number of intuitively easy classes. We also point out the need to further identify which functions are easy for a given class of evolutionary algorithms in order to design more efficient hardness indicators for them. We finally restrict attention to the genetic algorithm (GA), and consider both GA-easy and GA-hard fitness functions, and give experimental evidence that the values of the measures, based on random samples, can be completely unreliable and entirely uncorrelated to the convergence quality and convergence speed of GA instances using either proportional or ranking selection     

NARP-HPLC/MS and silver cationization fingerprinting of triacylglycerols in wild and cultivar Tunisian peanut kernels

A simple strategy to identify triacylglycerols (TAGs) in wild and cultivar peanuts was performed using on line coupling of non-aqueous reversed phase chromatography-electrospray ionization–mass spectrometry (NARP-LC-ESI–MS) with silver nitrate (AgNO₃) as a post-column additive. The combination of the structural information given by MS with chromatographic retention laws led to the determination of the structure of TAGs in wild and cultivar peanut oil. In addition, by using the MS⁵ method, the regio-specificity of the TAGs was determined. It was also demonstrated that in Tunisian peanut oil, the saturates have a preference for the sn-1/sn-3 position for the arachidonic and behenic acids. In the wild variety fatty acids with odd numbers of carbons were found and more TAGs were identified in comparison to the cultivar peanut oil.     

The nonstationary strain filter in elastography: Part II. Lateral and elevational decorrelation

The nonstationary evolution of the strain filter due to lateral and elevational motion of the tissue scatterers across the ultrasound beam is analyzed for the 1-D cross-correlation-based strain estimator. The effective correlation coefficient that includes the contributions due to lateral and elevational signal decorrelation is used to derate the upper bound of the signal-to-noise ratio in the elastogram (SNRe) predicted by the ideal strain filter. In the case of an elastically homogeneous target, if the transducer is on the axis of symmetry of such target in the elevational direction, the motion of the scatterers out the imaging plane is minimized. In addition, the ultrasound beam along the elevational direction is broader, allowing scatterers to stay longer within the beam during tissue compression. Under these conditions, lateral signal decorrelation becomes the primary contributor to the nonstationary behavior of the strain filter. Both the elastographic SNRe and the dynamic range are reduced, with an increase in lateral decorrelation. Finite element simulations and phantom experiments are presented in this paper to corroborate the theoretical strain filter. The nonstationary behavior of the strain filter is reduced by confining the tissue in the lateral direction (minimizing motion of tissue scatterers), thereby improving the quality of the elastogram.     

Generalized S transform

The generalized S transform (GST), a family of reversible integer-to-integer transforms inspired by the S transform, is proposed. This family of transforms is then studied in detail by considering topics such as GST parameter calculation, the effects of using different rounding operators in the GST, and the relationship between the GST and the lifting scheme. Some examples of specific transforms in the GST family are also given. In particular, a new transform in this family is introduced, and its practical utility is demonstrated.