Positionally controlled growth of cells using a cytophobic fluorinated polymer

This paper presents a novel method for cell positioning on a substrate which combines the optical quality of glass and the cell-repelling property of fluoropolymers. The process employs plasma lithography, which utilizes the high-resolution patterning of photolithography along with the versatility of the plasma polymerization. When mammalian cells were grown over these substrates, they avoided the fluoropolymer regions and grew almost exclusively within the exposed glass areas (windows). The patterned surface reproduces the initial design of the mask, offering the possibility to control cell distances and interactions with a versatile arrangement whilst keeping the optical quality of glass for microscopy observation, in particular, when a pristine substrate in needed. This approach opens up possibilities for analysis of biological processes, such as studying cell interactions, with the integration of optical or electrical sensors.     

Tuning natural modes of vibration by prestress in the design of a harmonic gong

Prestresses are purposefully added to an object to improve its performance, such as tuning a guitar string by adding tension. This paper reports how the normal modes of a sheet metal component can be tuned through the prestresses generated by cold-forging small dimples. Finite element analysis showed that the frequencies of specific mode shapes were differentially affected by the location of residual stress fields due to dimple formation in relation to modal stress fields. The frequencies of overtones were most sensitive to the depth of the dimples located near the maxima of modal stresses. Using this approach a series of musical gongs were designed with up to the first five overtones tuned to within 5% of the harmonic series. The balance of harmonic and inharmonic overtones in these gongs that are well resolved by the human cochlea may constitute a set of recognizable musical timbres with sufficient harmonicity to produce an unambiguous pitch for most listeners. Since many other mechanical properties of sheet metal components are affected by residual stresses this manufacturing technique may have broader application in design engineering.     

Explicit Geometric Integration of Polynomial Vector Fields

We present a unified framework in which to study splitting methods for polynomial vector fields in R ⁿ . The vector field is to be represented as a sum of shears, each of which can be integrated exactly, and each of which is a function of k<n variables. Each shear must also inherit the structure of the original vector field: we consider Hamiltonian, Poisson, and volume-preserving cases. Each case then leads to the problem of finding an optimal distribution of points on an appropriate homogeneous space, generally the Grassmannians of k-planes or (in the Hamiltonian case) isotropic k-planes in R ⁿ . These optimization problems have the same structure as those of constructing optimal experimental designs in statistics.     

Constant time gradient HSQC–iDOSY: practical aspects

An improved constant time gradient HSQC–iDOSY pulse sequence is presented, and the corresponding form of the Stejskal–Tanner equation is derived. The pulse sequence is particularly well suited to the problem of analysing mixtures of chemically cognate species, where the high spectral resolution afforded by ¹H? ¹³C correlation methods is needed for DOSY experiments to give good diffusion resolution. Its use is illustrated for a mixture of rutin and its aglycone quercetin. Copyright © 2009 John Wiley & Sons, Ltd.     

AC and DC percolative conductivity of single wall carbon nanotube polymer composites

The equations needed to correctly interpret both AC and DC conductivity results of single wall carbon nanotube (SWNT) polymer composites and the scaling of these results onto a single master curve are presented. Brief discussions on the factors that determine the critical volume fraction (?_c) and the percolation exponent (t) are also given. The results for a series of SWNT–polyimide composites are presented and the parameters obtained from fitting these results are discussed. The critical volume fraction for electrical percolation of the present composite was about 0.0005. Results obtained from previous work on SWNT (MWNT)–polymer composites and other percolation systems and the modeling (interpretation) of these results are also discussed and compared. © 2005 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 43: 3273–3287, 2005     

A neurocognitive model of recognition and pitch segregation

This paper describes a neurocognitive model of pitch segregation in which it is proposed that recognition mechanisms initiate early in auditory processing pathways so that long-term memory templates may be employed to segregate and integrate auditory features. In this model neural representations of pitch height are primed by the location and pattern of excitation across auditory filter channels in relation to long-term memory templates for common stimuli. Since waveform driven pitch mechanisms may produce information at multiple frequencies for tonal stimuli, pitch priming was assumed to include competitive inhibition that would allow only one pitch estimation at any time. Consequently concurrent pitch information must be relayed to short-term memory via a parallel mechanism that employs pitch information contained in the long-term memory template of the chord. Pure tones, harmonic complexes and two pitch chords of harmonic complexes were correctly classified by the correlation of templates comprising auditory nerve excitation and off-frequency inhibition with the excitation patterns of stimuli. The model then replicated behavioral data for pitch matching of concurrent vowels. Comparison of model outputs to the behavioral data suggests that inability to recognize a stimulus was associated with poor pitch segregation due to the use of inappropriate pitch priming strategies.     

A very fast algorithm for matrix factorization

We present a very fast algorithm for general matrix factorization of a data matrix for use in the statistical analysis of high-dimensional data via latent factors. Such data are prevalent across many application areas and generate an ever-increasing demand for methods of dimension reduction in order to undertake the statistical analysis of interest. Our algorithm uses a gradient-based approach which can be used with an arbitrary loss function provided the latter is differentiable. The speed and effectiveness of our algorithm for dimension reduction is demonstrated in the context of supervised classification of some real high-dimensional data sets from the bioinformatics literature.