Determination of the boiling point distribution of sulfur compounds in light cycle oil using GC with a flame photometric detector and pyrolyzer

A method has been developed to determine the boiling point distribution of sulfur compounds in light cycle oils (LCO'S). The method chosen for this analysis was GC with a flame photometric detector (FPD) and pyrolyzer. Tests were carried out to evaluate the recovery efficiency, repeatability, and accuracy of the method. Repeatabilities within 2% were obtained. The recovery of benzothiophenes and dibenzothiophenes was close to 100%; this was important because these are the major sulfur components in LCO's. No hydrocarbon or solvent interferences were observed with the use of the pyrolyzer, even for a 95% solvent level. Comparison with results from other techniques showed that the method accurately determined the levels of sulfur compounds in the LCO boiling point range.     

A study into the effect of subtle structural details and disorder on the terahertz spectrum of crystalline benzoic acid

The phonon modes of crystalline benzoic acid have been investigated using terahertz time-domain spectroscopy, rigid molecule atom-atom model potential and plane-wave density functional theory lattice dynamics calculations. The simulation results show good agreement with the measured terahertz spectra and an assignment of the terahertz absorption features of benzoic acid is made with the help of both computational methods. Focussing on the strongest interactions in the crystal, we describe each vibration in terms of distortions of the benzoic acid hydrogen bonded dimers that are present in the crystal structure. The terahertz spectrum is also shown to be highly sensitive to the location of the carboxylic acid hydrogen atoms in the cyclic hydrogen-bonded dimers and we have systematically explored the influence of the observed disorder in the hydrogen atom positions on the lattice dynamics.     

Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

Prisoner's dilemma and clusters on small‐world networks

The structure of interaction plays an important role in the outcome of evolutionary games. This study investigates the evolution of stochastic strategies of the prisoner's dilemma played on structures ranging from lattices to small world networks. Strategies and payoffs are analyzed as a function of the network characteristics of the node they are playing on. Nodes with lattice‐like neighborhoods tend to perform better than the nodes modified during the rewiring process of the construction of the small‐world network. © 2007 Wiley Periodicals, Inc. Complexity 12:22–36, 2006     

High spatial and angular resolution diffusion-weighted imaging reveals forniceal damage related to memory impairment

Introduction

Diffusion tensor imaging (DTI) measures in patients with multiple sclerosis (MS), particularly those measures associated with a specific white matter pathway, have consistently shown correlations with function. This study sought to investigate correlations between DTI measures in the fornix and common cognitive deficits in MS patients, including episodic memory, working memory and attention.

Materials and Methods

Patients with MS and group age- and sex-matched controls underwent high-resolution diffusion scanning (1-mm isotropic voxels) and cognitive testing. Manually drawn forniceal regions of interest were applied to individual maps of tensor-derived measures, and mean values of transverse diffusivity (TD), mean diffusivity (MD), longitudinal diffusivity (LD) and fractional anisotropy (FA) were calculated.

Results

In 40 patients with MS [mean age±S.D.= 42.55±9.1 years; Expanded Disability Status Scale (EDSS)=2.0±1.2; Multiple Sclerosis Functional Composite (MSFC) score=0.38±0.46] and 20 healthy controls (mean age±S.D.= 41.35±9.7 years; EDSS=0.0±0; MSFC score=0.74±0.24), we found that FA, MD and TD values in the fornix were significantly different between groups (P< .03), and patient performance on the Brief Visuospatial Memory Test-Revised (BVMT-R) was correlated with DTI measures (P< .03).

Discussion

These results are consistent with findings of axonal degeneration in MS and support the use of DTI as an indicator of disease progression.     

Salicylaldehyde based oxazolidines as catalysts for the asymmetric addition of diethylzinc to aldehydes

A series of oxazolidines have been prepared by condensation of N‐isopropyl norephedrine with a variety of salicylaldehyde derivatives. Despite the stereochemical relationship of (1R,2S)‐norephedrine with (1R,2S)‐ephedrine, the resultant oxazolidines 12‐14 were determined to have a stronger stereochemical relationship with (1S,2S)‐pseudoephedrine based oxazolidines. The resultant oxazolidines were used as catalytic ligands in the addition of diethylzinc to several aldehydes. It was determined that the oxazolidine derivative 12 gave the highest yield and a moderate enantioselectivity.     

Incorporation and controlled release of silyl ether prodrugs from PRINT nanoparticles

Asymmetric bifunctional silyl ether (ABS) prodrugs of chemotherapeutics were synthesized and incorporated within 200 nm × 200 nm particles. ABS prodrugs of gemcitabine were selected as model compounds because of the difficulty to encapsulate a water-soluble drug within a hydrogel. The resulting drug delivery systems were degraded under acidic conditions and were found to release only the parent or active drug. Furthermore, changing the steric bulk of the alkyl substituents on the silicon atom could regulate the rate of drug release and, therefore, the intracellular toxicity of the gemcitabine-loaded particles. This yielded a family of novel nanoparticles that could be tuned to release drug over the course of hours, days, or months.     

Numerical simulation of microwave thawing using a coupled solver approach

Thawing of a frozen food product in a domestic microwave oven is numerically simulated using a coupled solver approach. The approach consists of a dedicated electromagnetic FDTD solver and a closely coupled UFVM multi-physics package. Two overlapping numerical meshes are defined; the food material and container were meshed for heat transfer and phase change solution, whilst the microwave oven cavity and waveguide were meshed for the microwave irradiation. The two solution domains were linked using a cross-mapping routine. This approach allowed the rotation of the food load to be captured. Power densities obtained on the structured FDTD mesh were interpolated onto the UFVM mesh for each timestep/turntable position. The UFVM solver utilised the power density data to advance the temperature and phase distribution solution. The temperature-dependant dielectric and thermo-physical properties of the food load were updated prior to revising the electromagnetic solution. Changes in thermal/electric properties associated with the phase transition were fully accounted for as well as heat losses from product to cavity. Two scenarios were investigated: a centric and eccentric placement on the turntable. Developing temperature fields predicted by the numerical solution are validated against experimentally obtained data. Presented results indicate the feasibility of fully coupled simulations of the microwave heating of a frozen product. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)