Aligned Bioelectronic Polypyrrole/Collagen Constructs for Peripheral Nerve Interfacing

Electrical stimulation has shown promise in clinical studies to treat nerve injuries. This work is aimed to create an aligned bioelectronic construct that can be used to bridge a nerve gap, directly interfacing with the damaged nerve tissue to provide growth support. The conductive three-dimensional bioelectronic scaffolds described herein are composite materials, comprised of conductive polypyrrole (PPy) nanoparticles embedded in an aligned collagen hydrogel. The bioelectronic constructs are seeded with dorsal root ganglion derived primary rat neurons and electrically stimulated in vitro. The PPy loaded constructs support a 1.7-fold increase in neurite length in comparison to control collagen constructs. Furthermore, upon electrical stimulation of the PPy-collagen construct, a 1.8-fold increase in neurite length is shown. This work illustrates the potential of bioelectronic constructs in neural tissue engineering and lays the groundwork for the development of novel bioelectronic materials for neural interfacing applications

Ethnic In-Group Favoritism Among Minority and Majority Groups: Testing the Self-Esteem Hypothesis Among Preadolescents

The self-esteem hypothesis in intergroup relations, as proposed by social identity theory (SIT), states that successful intergroup discrimination enhances momentary collective self-esteem. This hypothesis is a source of continuing controversy. Furthermore, although SIT is increasingly used to account for children’s group attitudes, few studies have examined the hypothesis among children. In addition, the hypothesis’s generality makes it important to study among children from different ethnic groups. The present study, conducted among Dutch and Turkish preadolescents, examined momentary collective self-feelings as a consequence of ethnic group evaluations. The results tended to support the self-esteem hypothesis. In-group favoritism was found to have a self-enhancing effect among participants high in ethnic identification. This result was found for ethnic majority (Dutch) and minority (Turkish) participants.

Necessary and sufficient conditions of solution uniqueness in ℓ1\ell_1 minimization

This paper shows that the solutions to various convex $\ell_1$ minimization problems are \emph{unique} if and only if a common set of conditions are satisfied. This result applies broadly to the basis pursuit model, basis pursuit denoising model, Lasso model, as well as other $\ell_1$ models that either minimize $f(Ax-b)$ or impose the constraint $f(Ax-b)\leq\sigma$, where $f$ is a strictly convex function. For these models, this paper proves that, given a solution $x^*$ and defining I=\supp(x^*) and s=\sign(x^*_I), $x^*$ is the unique solution if and only if $A_I$ has full column rank and there exists $y$ such that $A_I^Ty=s$ and $|a_i^Ty|_\infty<1$ for $i\not\in I$. This condition is previously known to be sufficient for the basis pursuit model to have a unique solution supported on $I$. Indeed, it is also necessary, and applies to a variety of other $\ell_1$ models. The paper also discusses ways to recognize unique solutions and verify the uniqueness conditions numerically.Comment: 6 pages; revised version; submitte

Balance in single-limb stance after surgically treated ankle fractures: a 14-month follow-up

BACKGROUND: The maintenance of postural control is fundamental for different types of physical activity. This can be measured by having subjects stand on one leg on a force plate. Many studies assessing standing balance have previously been carried out in patients with ankle ligament injuries but not in patients with ankle fractures. The aim of this study was to evaluate whether patients operated on because of an ankle fracture had impaired postural control compared to an uninjured age- and gender-matched control group. METHODS: Fifty-four individuals (patients) operated on because of an ankle fracture were examined 14 months postoperatively. Muscle strength, ankle mobility, and single-limb stance on a force-platform were measured. Average speed of centre of pressure movements and number of movements exceeding 10 mm from the mean value of centre of pressure were registered in the frontal and sagittal planes on a force-platform. Fifty-four age- and gender-matched uninjured individuals (controls) were examined in the single-limb stance test only. The paired Student t-test was used for comparisons between patients' injured and uninjured legs and between side-matched legs within the controls. The independent Student t-test was used for comparisons between patients and controls. The Chi-square test, and when applicable, Fisher's exact test were used for comparisons between groups. Multiple logistic regression was performed to identify factors associated with belonging to the group unable to complete the single-limb stance test on the force-platform. RESULTS: Fourteen of the 54 patients (26%) did not manage to complete the single-limb stance test on the force-platform, whereas all controls managed this (p < 0.001). Age over 45 years was the only factor significantly associated with not managing the test. When not adjusted for age, decreased strength in the ankle plantar flexors and dorsiflexors was significantly associated with not managing the test. In the 40 patients who managed to complete the single-limb stance test no differences were found between the results of patients' injured leg and the side-matched leg of the controls regarding average speed and the number of centre of pressure movements. CONCLUSION: One in four patients operated on because of an ankle fracture had impaired postural control compared to an age- and gender-matched control group. Age over 45 years and decreased strength in the ankle plantar flexors and dorsiflexors were found to be associated with decreased balance performance. Further, longitudinal studies are required to evaluate whether muscle and balance training in the rehabilitation phase may improve postural control

Restricted Isometries for Partial Random Circulant Matrices

In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse and compressible signals. Many recovery algorithms are known to succeed when the restricted isometry constants of the sampling matrix are small. Many potential applications of compressed sensing involve a data-acquisition process that proceeds by convolution with a random pulse followed by (nonrandom) subsampling. At present, the theoretical analysis of this measurement technique is lacking. This paper demonstrates that the $s$th order restricted isometry constant is small when the number $m$ of samples satisfies $m \gtrsim (s \log n)^{3/2}$, where $n$ is the length of the pulse. This bound improves on previous estimates, which exhibit quadratic scaling

Compressive Inverse Scattering I. High Frequency SIMO Measurements

Inverse scattering from discrete targets with the single-input-multiple-output (SIMO), multiple-input-single-output (MISO) or multiple-input-multiple-output (MIMO) measurements is analyzed by compressed sensing theory with and without the Born approximation. High frequency analysis of (probabilistic) recoverability by the $L^1$-based minimization/regularization principles is presented. In the absence of noise, it is shown that the $L^1$-based solution can recover exactly the target of sparsity up to the dimension of the data either with the MIMO measurement for the Born scattering or with the SIMO/MISO measurement for the exact scattering. The stability with respect to noisy data is proved for weak or widely separated scatterers. Reciprocity between the SIMO and MISO measurements is analyzed. Finally a coherence bound (and the resulting recoverability) is proved for diffraction tomography with high-frequency, few-view and limited-angle SIMO/MISO measurements.Comment: A new section on diffraction tomography added; typos fixed; new figures adde

Precision Tests of the Standard Model

30 páginas, 11 figuras, 11 tablas.-- Comunicación presentada al 25º Winter Meeting on Fundamental Physics celebrado del 3 al 8 de MArzo de 1997 en Formigal (España).Precision measurements of electroweak observables provide stringent tests of the Standard Model structure and an accurate determination of its parameters. An overview of the present experimental status is presented.This work has been supported in part by CICYT (Spain) under grant No. AEN-96-1718.Peer reviewe

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Efficient Sparse Coding in Early Sensory Processing: Lessons from Signal Recovery

Sensory representations are not only sparse, but often overcomplete: coding units significantly outnumber the input units. For models of neural coding this overcompleteness poses a computational challenge for shaping the signal processing channels as well as for using the large and sparse representations in an efficient way. We argue that higher level overcompleteness becomes computationally tractable by imposing sparsity on synaptic activity and we also show that such structural sparsity can be facilitated by statistics based decomposition of the stimuli into typical and atypical parts prior to sparse coding. Typical parts represent large-scale correlations, thus they can be significantly compressed. Atypical parts, on the other hand, represent local features and are the subjects of actual sparse coding. When applied on natural images, our decomposition based sparse coding model can efficiently form overcomplete codes and both center-surround and oriented filters are obtained similar to those observed in the retina and the primary visual cortex, respectively. Therefore we hypothesize that the proposed computational architecture can be seen as a coherent functional model of the first stages of sensory coding in early vision