Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

Magnetic Resonance Materials in Physics, Biology and Medicine - Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI....     

Injectable Cardiac Cell Microdroplets for Tissue Regeneration

One of the strategies for heart regeneration includes cell delivery to the defected heart. However, most of the injected cells do not form quick cell–cell or cell–matrix interactions, therefore, their ability to engraft at the desired site and improve heart function is poor. Here, the use of a microfluidic system is reported for generating personalized hydrogel‐based cellular microdroplets for cardiac cell delivery. To evaluate the system's limitations, a mathematical model of oxygen diffusion and consumption within the droplet is developed. Following, the microfluidic system's parameters are optimized and cardiac cells from neonatal rats or induced pluripotent stem cells are encapsulated. The morphology and cardiac specific markers are assessed and cell function within the droplets is analyzed. Finally, the cellular droplets are injected to mouse gastrocnemius muscle to validate cell retention, survival, and maturation within the host tissue. These results demonstrate the potential of this approach to generate personalized cellular microtissues, which can be injected to distinct regions in the body for treating damaged tissues.     

Mass production of nanofibre assemblies by electrostatic spinning

Electrospinning is a well‐established and intensively investigated methodology, and is currently the only known technique that can fabricate continuous nanofibres. The major challenge associated with electrospinning is its production rate, compared with that of conventional fibre spinning. However, the understanding of the scale‐up possibility of the electrospinning process is still in its infancy. Substantial up‐scaling of electrospinning may pave the way for applications of nanofibre assemblies (i.e. yarns) not accessible otherwise in conventional textile processes, such as weaving, knitting and braiding. Here we summarize recent advances regarding the enhancement of electrospinning throughput with special emphasis on multiple jets from multi‐needles and the free surface of polymer solutions. Copyright © 2009 Society of Chemical Industry     

FIR system identification using fourth-order cumulants withapplication to channel equalization

Three algorithms for finite impulse response (FIR) system identification from output measurements, using fourth-order cumulants, are described. The impulse response is assumed to be complex, and the input is a complex independent and identically distributed (i.i.d) non-Gaussian sequence. The algorithms are based on a certain low-rank matrix constructed from the output cumulants. An application of the algorithms to blind equalization of digital communication channels is discussed and illustrated by some examples     

The generalized Gabor scheme of image representation in biologicaland machine vision

A scheme suitable for visual information representation in a combined frequency-position space is investigated through image decomposition into a finite set of two-dimensional Gabor elementary functions (GEF). The scheme is generalized to account for the position-dependent Gabor-sampling rate, oversampling, logarithmic frequency scaling and phase-quantization characteristic of the visual system. Comparison of reconstructed signal highlights the advantages of the generalized Gabor scheme in coding typical bandlimited images. It is shown that there exists a tradeoff between the number of frequency components used per position and the number of such clusters (sampling rate) utilized along the spatial coordinate     

Optimal ARMA parameter estimation based on the sample covariancesfor data with missing observations

The problem of spectral estimation through the autoregressive moving-average (ARMA) modeling of stationary processes with missing observations is considered. A class of estimators based on the sample covariances is presented, and an asymptotically optimal estimator in this class is proposed. The proposed algorithm is based on a nonlinear-least-squares fit of the sample covariances computed from the data to the true covariances of the assumed ARMA model. The statistical properties of the algorithm are explored and used to show that it is asymptotically optimal, in the sense of achieving the smallest possible asymptotic variance. The performance of the algorithm is illustrated by some numerical examples     

Direction finding algorithms based on high-order statistics

Two direction finding algorithms are presented for nonGaussian signals, which are based on the fourth-order cumulants of the data received by the array. The first algorithm is similar to MUSIC, while the second is asymptotically minimum variance in a certain sense. The first algorithm requires singular value decomposition of the cumulant matrix, while the second is based on nonlinear minimization of a certain cost function. The performance of the minimum variance algorithm can be assessed by analytical means, at least for the case of discrete probability distributions of the source signals and spatially uncorrelated Gaussian noise. The numerical experiments performed seem to confirm the insensitivity of these algorithms to the (Gaussian) noise parameters     

Efficient construction of canonical ladder forms for vector autoregressive processes

The paper treats the problem of constructing canonical ladder realizations for vector autoregressive (AR) processes specified by their characteristic matrix polynomials. The difficulty of this problem is rooted in the fact that the backward matrix polynomial corresponding to a given vector AR process is a nontrivial function of the forward matrix polynomial. The construction calls for solving a discrete Lyapunov equation in block-controller form. Two efficient procedures for solving this equation are presented, both requiring a number of operations that is proportional to at most the square of the model order. Applications of the new procedures to stability, tests, simulation of AR processes, and model reduction are described.