Injectable hydrogels with high fixed charge density and swelling pressure for nucleus pulposus repair:biomimetic glycosaminoglycan analogues

The load-bearing biomechanical role of the intervertebral disc is governed by the composition and organization of its major macromolecular components, collagen and aggrecan. The major function of aggrecan is to maintain tissue hydration, and hence disc height, under the high loads imposed by muscle activity and body weight. Key to this role is the high negative fixed charge of its glycosaminoglycan side chains, which impart a high osmotic pressure to the tissue, thus regulating and maintaining tissue hydration and hence disc height under load. In degenerate discs, aggrecan degrades and is lost from the disc, particularly centrally from the nucleus pulposus. This loss of fixed charge results in reduced hydration and loss of disc height; such changes are closely associated with low back pain. The present authors developed biomimetic glycosaminoglycan analogues based on sulphonate-containing polymers. These biomimetics are deliverable via injection into the disc where they polymerize in situ, forming a non-degradable, nuclear "implant" aimed at restoring disc height to degenerate discs, thereby relieving back pain. In vitro, these glycosaminoglycan analogues possess appropriate fixed charge density, hydration and osmotic responsiveness, thereby displaying the capacity to restore disc height and function. Preliminary biomechanical tests using a degenerate explant model showed that the implant adapts to the space into which it is injected and restores stiffness. These hydrogels mimic the role taken by glycosaminoglycans in vivo and, unlike other hydrogels, provide an intrinsic swelling pressure, which can maintain disc hydration and height under the high and variable compressive loads encountered in vivo. © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Using interior point algorithms for the solution of linear programs with special structural features

Linear Programming (LP) is a powerful decision making tool extensively used in various economic and engineering activities. In the early stages the success of LP was mainly due to the efficiency of the simplex method. After the appearance of Karmarkar's paper, the focus of most research was shifted to the field of interior point methods. The present work is concerned with investigating and efficiently implementing the latest techniques in this field taking sparsity into account. The performance of these implementations on different classes of LP problems is reported here. The preconditional conjugate gradient method is one of the most powerful tools for the solution of the least square problem, present in every iteration of all interior point methods. The effect of using different preconditioners on a range of problems with various condition numbers is presented. Decomposition algorithms has been one of the main fields of research in linear programming over the last few years. After reviewing the latest decomposition techniques, three promising methods were chosen the implemented. Sparsity is again a consideration and suggestions have been included to allow improvements when solving problems with these methods. Finally, experimental results on randomly generated data are reported and compared with an interior point method. The efficient implementation of the decomposition methods considered in this study requires the solution of quadratic subproblems. A review of recent work on algorithms for convex quadratic was performed. The most promising algorithms are discussed and implemented taking sparsity into account. The related performance of these algorithms on randomly generated separable and non-separable problems is also reported.

Compositional semantics of dataflow networks with query-driven communication of exact values

We develop and study the concept of dataflow process networks as used for exampleby Kahn to suit exact computation over data types related to real numbers, such as continuous functions and geometrical solids. Furthermore, we consider communicating these exact objectsamong processes using protocols of a query-answer nature as introduced in our earlier work. This enables processes to provide valid approximations with certain accuracy and focusing on certainlocality as demanded by the receiving processes through queries. We define domain-theoretical denotational semantics of our networks in two ways: (1) directly, i. e. by viewing the whole network as a composite process and applying the process semantics introduced in our earlier work; and (2) compositionally, i. e. by a fixed-point construction similarto that used by Kahn from the denotational semantics of individual processes in the network. The direct semantics closely corresponds to the operational semantics of the network (i. e. it iscorrect) but very difficult to study for concrete networks. The compositional semantics enablescompositional analysis of concrete networks, assuming it is correct. We prove that the compositional semantics is a safe approximation of the direct semantics. Wealso provide a method that can be used in many cases to establish that the two semantics fully coincide, i. e. safety is not achieved through inactivity or meaningless answers. The results are extended to cover recursively-defined infinite networks as well as nested finitenetworks. A robust prototype implementation of our model is available.

Control of pattern formation by time-delay feedback with global and local contributions

We consider the suppression of spatiotemporal chaos in the complex GinzburgLandau equation by a combined global and local time-delay feedback. Feedback terms are implemented as a control scheme, i.e., they are proportional to the difference between the time-delayed state of the system and its current state. We perform a linear stability analysis of uniform oscillations with respect to space-dependent perturbations and compare with numerical simulations. Similarly, for the fixed-point solution that corresponds to amplitude death in the spatially extended system, a linear stability analysis with respect to space-dependent perturbations is performed and complemented by numerical simulations. © 2010 Elsevier B.V. All rights reserved.

Incorporating curvature information into on-line learning

We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

Is subclinical thyroid dysfunction in the elderly associated with depression or cognitive dysfunction?

Background: Widespread use of automated sensitive assays for thyroid hormones and thyroid-stimulating hormone (TSH) has increased identification of mild thyroid dysfunction, especially in elderly patients. The clinical significance of this dysfunction, however, remains uncertain, and associations with cognitive impairment, depression, and anxiety are unconfirmed. Objective: To determine the association between mild thyroid dysfunction and cognition, depression, and anxiety in elderly persons. Design: Cross-sectional study. Associations were explored through mixed-model analyses. Setting: Primary care practices in central England. Patients: 5865 patients 65 years of age or older with no known thyroid disease who were recruited from primary care registers. Measurements: Serum TSH and free thyroxine (T4) were measured. Depression and anxiety were assessed by using the Hospital Anxiety and Depression Scale (HADS), and cognitive functioning was established by using the Middlesex Elderly Assessment of Mental State and the Folstein Mini-Mental State Examination. Comorbid conditions, medication use, and sociodemographic profiles were recorded. Results: 295 patients met the criteria for subclinical thyroid dysfunction (127 were hyperthyroid, and 168 were hypothyroid). After confounding variables were controlled for, statistically significant associations were seen between anxiety (HADS score) and TSH level (P = 0.013) and between cognition and both TSH and free T4 levels. The magnitude of these associations lacked clinical relevance: A 50-mIU/L increase in the TSH level was associated with a 1-point reduction in the HADS anxiety score, and a 1-point increase in the Mini-Mental State Examination score was associated with an increase of 50 mIU/L in the TSH level or 25 pmol/L in the free T4 level. Limitations: Because of the low participation rate, low prevalence of subclinical thyroid dysfunction, and other unidentified recruitment biases, participants may not be representative of the elderly population. Conclusions: After the confounding effects of comorbid conditions and use of medication were controlled for, subclinical thyroid dysfunction was not associated with depression, anxiety, or cognition. © 2006 American College of Physicians.

Dynamic behaviour of rotary mechanical seals

This thesis covers both experimental and computer investigations into the dynamic behaviour of mechanical seals. The literature survey shows no investigations on the effect of vibration on mechanical seals of the type common in the various process industries. Typical seal designs are discussed. A form of Reynolds' equation has been developed that permits the calculation of stiffnesses and damping coefficients for the fluid film. The dynamics of the mechanical seal floating ring have been investigated using approximate formulae, and it has been shown that the floating ring will behave as a rigid body. Some elements, such as the radial damping due to the fluid film, are small and may be neglected. The equations of motion of the floating ring have been developed utilising the significant elements, and a solution technique described. The stiffness and damping coefficients of nitrile rubber o-rings have been obtained. These show a wide variation, with a constant stiffness up to 60 Hz. The importance of the effect of temperature on the properties is discussed. An unsuccessful test rig is described in the appendices. The dynamic behaviour of a mechanical seal has been investigated experimentally, including the effect of changes of speed, sealed pressure and seal geometry. The results, as expected, show that high vibration levels result in both high leakage and seal temperatures. Computer programs have been developed to solve Reynolds' Equation and the equations of motion. Two solution techniques for this latter program were developed, the unsuccesful technique is described in the appendices. Some stability problems were encountered, but despite these the solution shows good agreement with some of the experimental conditions. Possible reasons for the discrepancies are discussed. Various suggestions for future work in this field are given. These include the combining of the programs and more extensive experimental and computer modelling.

Palette-colouring: a belief propagation approach

We consider a variation of the prototype combinatorial optimization problem known as graph colouring. Our optimization goal is to colour the vertices of a graph with a fixed number of colours, in a way to maximize the number of different colours present in the set of nearest neighbours of each given vertex. This problem, which we pictorially call palette-colouring, has been recently addressed as a basic example of a problem arising in the context of distributed data storage. Even though it has not been proved to be NP-complete, random search algorithms find the problem hard to solve. Heuristics based on a naive belief propagation algorithm are observed to work quite well in certain conditions. In this paper, we build upon the mentioned result, working out the correct belief propagation algorithm, which needs to take into account the many-body nature of the constraints present in this problem. This method improves the naive belief propagation approach at the cost of increased computational effort. We also investigate the emergence of a satisfiable-to-unsatisfiable 'phase transition' as a function of the vertex mean degree, for different ensembles of sparse random graphs in the large size ('thermodynamic') limit.

Effects of electric charge on osmotic flow across periodically arranged circular cylinders

An electrostatic model is developed for osmotic flow across a layer consisting of identical circular cylinders with a fixed surface charge, aligned parallel to each other so as to form an ordered hexagonal arrangement. The expression of the osmotic reflection coefficient is derived for spherical solutes with a fixed surface charge suspended in an electrolyte, based on low-Reynolds-number hydrodynamics and a continuum, point-charge description of the electric double layers. The repulsive electrostatic interaction between the surface charges with the same sign on the solute and the cylinders is shown to increase the exclusion region of solute from the cylinder surface, which enhances the osmotic flow. Applying the present model to the study of osmotic flow across the endothelial surface glycocalyx of capillary walls has revealed that this electrostatic model could account well for the reflection coefficients measured for charged macromolecules, such as albumin, in the physiological range of charge density and ion concentration.

Fast reconstruction of harmonic functions from Cauchy data using integral equation techniques

We consider the problem of stable determination of a harmonic function from knowledge of the solution and its normal derivative on a part of the boundary of the (bounded) solution domain. The alternating method is a procedure to generate an approximation to the harmonic function from such Cauchy data and we investigate a numerical implementation of this procedure based on Fredholm integral equations and Nyström discretization schemes, which makes it possible to perform a large number of iterations (millions) with minor computational cost (seconds) and high accuracy. Moreover, the original problem is rewritten as a fixed point equation on the boundary, and various other direct regularization techniques are discussed to solve that equation. We also discuss how knowledge of the smoothness of the data can be used to further improve the accuracy. Numerical examples are presented showing that accurate approximations of both the solution and its normal derivative can be obtained with much less computational time than in previous works.

Spectrum-, pulsewidth-, and wavelengthswitchable all-fiber mode-locked Yb laser with fiber based birefringent filter

We examined methods of controlling the pulse duration, spectral width and wavelength of the output from an all-fiber Yb laser mode-locked by carbon nanotubes. It is shown that a segment of polarization maintaining (PM) fiber inserted into a standard single mode fiber based laser cavity can function as a spectral selective filter. Adjustment of the length of the PM fiber from 1 to 2 m led to a corresponding variation in the pulse duration from 2 to 3.8 ps, the spectral bandwidth of the laser output changes from 0.15 to 1.26 nm. Laser output wavelength detuning within up to 5 nm was demonstrated with a fixed length of the PM fiber by adjustment of the polarization controller. © 2012 Optical Society of America.

Raman fiber lasers with a random distributed feedback based on Rayleigh scattering

We demonstrate lasing based on a random distributed feedback due to the Raman amplified Rayleigh backscattering in different types of cavities with and without conventional point-action reflectors. Quasistationary generation of a narrowband spectrum is achieved despite the random nature of the feedback. The generated spectrum is localized at the reflection or gain spectral maxima in schemes with and without point reflectors, respectively. The length limit for a conventional cavity and the minimal pump power required for the lasing based purely on a random distributed feedback are determined. © 2010 The American Physical Society.