Surface modification of activated polymeric matrices by dendritic attachments

Aware of the growing interest in materials that exhibit specific physiochemical properties and potential applications, we focused our work on modifying commercial agarose with polyfunctional dendrons capable of molecular recognition through hydrogen bonding. 2,6‐Di(acylamino)pyridine moieties within the internal superstructure of dendritic macromolecules have been reported to be capable of forming H‐bonded complexes with imide groups, such as barbituric acid and its derivatives. We report the synthesis of new dendrons possessing multiple 2,6‐di(acylamino)pyridinyl sites, each capable of molecular recognition, and the development of new polymeric supports of an activated agarose matrix by surface modification. From comparative studies of the beads modified by different dendrons, we found improved results in those dendritic supports possessing 2,6‐di(acylamino)pyridinyl moieties, except when their juxtaposition between the groups promoted inner H bonds. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 2779–2786, 2000     

Stereocontrolled Routes to Bridged Ethers by Tandem Cyclizations

Ring contraction of a 3,4-epoxyalcohol, then lactolization and electrophilic attack are the steps in the domino cyclization protocol for the formation of 8-oxabicyclo[3.2.1]octane systems [Eq. (a)].     

Novel surface treatments for glass fillers

Glass fillers were suface modified by direct formation of a silicon-carbon non-hydrolyzable linkage between glass and coupling agent. The grafted silane monolayer was evaluated by infrared spectroscopy. Samples were subjected to hydrolytic conditions to compare their surface treatment stability with traditional surface treatment hydrolytic stability. Composite specimens were fabricated and their mechanical properties were compared with traditional aminopropylsilane coupling agent treatment.     

Materials Research with X-ray Micro-beams at the Advanced Photon Source

X-ray scattering has had a rich and prominent place in the history of materials research. For samples that are large single crystals, X-ray diffraction provides very detailed, high-quality information about the atomic structure of almost every kind. However, most engineering materials are not a large single crystal, but mixtures of materials or a poly-crystalline material. Still, X-ray diffraction using X-ray beams significantly larger than the structures being investigated has produced much excellent information. Examples of this are powder diffraction, texture analysis, strain analysis, etc. While these types of analyses have been very useful in providing a microscopic understanding, they do not provide the microscopic information that we really want. What we really want to have is this useful X-ray diffraction information for every volume element in our sample; not just the diffraction information about small volume elements, but all of the volume elements, exactly where they are in our sample, and how each one diffracts. This detailed spatial and structural information is what is needed for a full understanding of the source of the properties that we find in engineering materials.     

Improvement of modified analytic embedded atom method potentials for noble metals and Cu

The modified analytic embedded atom model (EAM) potentials considering farther neighbor atoms are improved for the noble metals (Ag, Au, Pt, Pd, Rh) and Cu. We not only adopt an end processing function and an enhanced smooth continuous condition for the pair potential, but also adjust the model parameters of multi-body potential by fitting a cohesive energy, a mono-vacancy formation energy, the Rose equation curve for the cohesive energy as a function of lattice parameter, a structure energy difference, elastic parameters and an equilibrium condition of crystal. The calculation results of structure energy differences misfit the experiment data for the noble metals and Cu in the unimproved EAM, because anyone of these differences have not been considered in the calculation of its model parameters. After the modification, the model showed better simulation results for the noble metals and Cu.     

Controlled Stripping of Polyelectrolyte Multilayers by Quaternary Ammonium Surfactants

The quartz crystal microbalance with dissipation technique (QCM‐D) and atomic force microscopy (AFM) have been employed to study the interaction of N‐tetradecyl trimethyl ammonium bromide (TdTmAB) with polyelectrolyte multilayers containing poly(sodium 4‐styrene sulfonate) (PSS) as the polyanion and either poly(allylamine hydrochloride) (PAH) or poly(diallyl dimethyl ammonium chloride) (PDADMAC) as the polycations. The multilayers were exposed to aqueous solutions of TdTmAB. This resulted in a selective removal of PDADMAC PSS layers while layers with PAH as polycation remained stable. It is suggested that PDADMAC/PSS multilayers can be employed as strippable protecting layers.

     

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.