The shape parameter of Liposomes and DNA-lipid complexes determined by viscometry utilizing small sample volumes

A minicapillary viscometer utilizing <0.5 ml of sample at a volume fraction of <0.1% is described. The calculated a/b of DPPC/DPPG multilamellar liposome was 1.14 as prolate ellipsoids and a/b of dioleoylpropyltrimethyl ammonium methylsulfate-DNA complex at a charge ratio of 4: 1 (+/-) was 3.7 as prolate ellipsoids or 4.9 as oblate ellipsoids. The deviation of shape from perfect sphere is thus expressed quantitatively in more than two significant figures. In these measurement, the necessary amount of DNA is <0.5 mg.

Study of remote sensing based parameter uncertainty in Production Efficiency Models

The remote sensing based Production Efficiency Models (PEMs), springs from the concept of "Light Use Efficiency" and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy.

Effect of chain-length dependence of interaction parameter on spinodals for polydisperse polymer blends

The chain-length dependence of the Flory-Huggins (FH) interaction parameter is introduced into the FH lattice theory for polydisperse polymer-blend systems. The spinodals are calculated for the model polymer blends with different chain lengths and distributions. It is found that all the related variables r(n), r(w), r(z), and chain-length distribution, have effects on the spinodals for polydisperse polymer blends.

Effects of molecular weight and interaction parameter on the glass transition temperature of polystyrene mixtures and its blends with polystyrene/poly(2,6-dimethyl-p-phenylene oxide)

The glass transition temperature (T-g) of mixtures of polystyrene (PS) with different molecular weight and of blends of poly(2,6-dimethyl-p-phenylene oxide) (PPO) and polystyrene with different molecular weight (DMWPS) was studied by a DSC method. For the whole range of composition, the curves of T-g vs composition obtained by experiment were compared with predictions from the Fox, Gordon-Taylor, Couchman and Lu-Weiss, equations. It was found that the experimental results were not in agreement with those from the Fox, Gordon-TayIor and Couchman equations for the binary mixtures of DMWPS, where the interaction parameter chi was approximately zero. However, for the blends PPO/DMWPS (chi < 0), with an increase of molecular weight of PS, it was shown that the experimental results fitted well with those obtained from the Couchman, Gordon-Taylor and Fox equations, respectively. Furthermore, the Gordon-Taylor equation was nearly identical to the Lu-Weiss equation when \chi\ was not very large. Further, the dependence of the change of heat capacity associated with the glass transition (Delta C-p) on the molecular weight of PS was investigated and an empirical equation was presented. (C) 1997 Elsevier Science Ltd.

Genetic parameter estimates for growth traits at early stage of Pacific abalone, Haliotis discus hannai Ino

Heritability and genetic and phenotypic correlations were estimated for juvenile growth traits of Pacific abalone Haliotis discus hannai Ino. The estimates were calculated from shell length and shell width measurements on progeny resulting from 12 half-sib families and 36 full-sib families obtained using artificial fertilization of mating three females to each male. The measurements were taken at 10, 20 and 30 d after fertilization. It was found that heritability estimates based on sire component ranged from 0.23 to 0.36 for shell length and 0.21 to 0.32 for shell width. Heritability estimates from dam component were larger than those from sire component at three ages, indicating presence of maternal effects, non-additive genetic effects and common environmental effects. Phenotypic correlations were significant at three ages (P < 0.05), with values of 0.92, 0.93 and 0.92, respectively. Genetic correlations from the paternal half-sib correlation analysis were highly positive at three ages, with values of 0.50, 0.78 and 0.81, respectively. The results suggest that selective breeding is an effective approach to improving growth traits of Pacific abalone stocks.

Optimization and parameter study for chiral separation by capillary electrophoresis

Orthogonal design and uniform design were used for the optimization of separation of enantiomers using 2,6-di-O-methyl-beta-cyclodextrin (DM-beta-CD) as a chiral selector by capillary zone electrophoresis, The concentration of DM-beta-CD, buffer pH, running voltage, and capillary temperature were selected as variable parameters, their different effects on peak resolution were studied by the design methods. It was concluded that orthogonal design offers a rapid and efficient means for testing the importance of individual parameters and for determining the optimum operating conditions. However, for a large number of both factors and levels, uniform design is more efficient, The effect of addition of methanol and citric acid buffer on the separation of enantiomers was also examined.

Fast Pose Estimation with Parameter Sensitive Hashing

Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensional problems such as pose estimation, the number of required examples and the computational complexity rapidly becme prohibitively high. We introduce a new algorithm that learns a set of hashing functions that efficiently index examples relevant to a particular estimation task. Our algorithm extends a recently developed method for locality-sensitive hashing, which finds approximate neighbors in time sublinear in the number of examples. This method depends critically on the choice of hash functions; we show how to find the set of hash functions that are optimally relevant to a particular estimation problem. Experiments demonstrate that the resulting algorithm, which we call Parameter-Sensitive Hashing, can rapidly and accurately estimate the articulated pose of human figures from a large database of example images.

Parameter sensitivity in simulations of snowmelt

Essery, RLH & P, Etchevers, (2004). Parameter sensitivity in simulations of snowmelt. Journal of Geophysical Research, 109, doi:10. 1029/2004JD005036.

Parameter Sensitive Detectors

Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and then train separate classifiers for each portion. However, with continuous spaces the partitions tend to be arbitrary since there are no natural boundaries (for example, consider the continuous range of human body poses). In this paper, a new formulation is proposed, where the detectors themselves are associated with continuous parameters, and reside in a parameterized function space. There are two advantages of this strategy. First, a-priori partitioning of the parameter space is not needed; the detectors themselves are in a parameterized space. Second, the underlying parameters for object variations can be learned from training data in an unsupervised manner. In profile face detection experiments, at a fixed false alarm number of 90, our method attains a detection rate of 75% vs. 70% for the method of Viola-Jones. In hand shape detection, at a false positive rate of 0.1%, our method achieves a detection rate of 99.5% vs. 98% for partition based methods. In pedestrian detection, our method reduces the miss detection rate by a factor of three at a false positive rate of 1%, compared with the method of Dalal-Triggs.

Computing a Uniform Scaling Parameter for 3D Registration of Lung Surfaces

A difficulty in lung image registration is accounting for changes in the size of the lungs due to inspiration. We propose two methods for computing a uniform scale parameter for use in lung image registration that account for size change. A scaled rigid-body transformation allows analysis of corresponding lung CT scans taken at different times and can serve as a good low-order transformation to initialize non-rigid registration approaches. Two different features are used to compute the scale parameter. The first method uses lung surfaces. The second uses lung volumes. Both approaches are computationally inexpensive and improve the alignment of lung images over rigid registration. The two methods produce different scale parameters and may highlight different functional information about the lungs.

Nonlinear parameter retrieval from three- and four-wave mixing in metamaterials

We present a generalized nonlinear susceptibility retrieval method for metamaterials based on transfer matrices and valid in the nondepleted pump approximation. We construct a general formalism to describe the transfer matrix method for nonlinear media and apply it to the processes of three- and four-wave mixing. The accuracy of this approach is verified via finite element simulations. The method is then reversed to give a set of equations for retrieving the nonlinear susceptibility. Finally, we apply the proposed retrieval operation to a three-wave mixing transmission experiment performed on a varactor loaded split ring resonator metamaterial sample and find quantitative agreement with an analytical effective medium theory model. © 2010 The American Physical Society.

The FUELCON meta-architecture, II: alternatives for parameter prediction

We continue the discussion of the decision points in the FUELCON metaarchitecture. Having discussed the relation of the original expert system to its sequel projects in terms of an AND/OR tree, we consider one further domain for a neural component: parameter prediction downstream of the core reload candidate pattern generator, thus, a replacement for the NOXER simulator currently in use in the project.