Bayesian estimation for selective trace gas detection

We present a Bayesian estimation analysis for a particular trace gas detection technique with species separation provided by differential diffusion. The proposed method collects a sample containing multiple gas species into a common volume, and then allows it to diffuse across a linear array of optical absorption detectors, using, for example, high-finesse Fabry-Perot cavities. The estimation procedure assumes that all gas parameters (e.g. diffusion constants, optical cross sections) are known except for the number population of each species, which are determined from the time-of-flight absorption profiles in each detector

Self-organized criticality in the intermediate phase of rigidity percolation

Experimental results for covalent glasses have highlighted the existence of a new self-organized phase due to the tendency of glass networks to minimize internal stress. Recently, we have shown that an equilibrated self-organized two-dimensional lattice-based model also possesses an intermediate phase in which a percolating rigid cluster exists with a probability between zero and one, depending on the average coordination of the network. In this paper, we study the properties of this intermediate phase in more detail. We find that microscopic perturbations, such as the addition or removal of a single bond, can affect the rigidity of macroscopic regions of the network, in particular, creating or destroying percolation. This, together with a power-law distribution of rigid cluster sizes, suggests that the system is maintained in a critical state on the rigid/floppy boundary throughout the intermediate phase, a behavior similar to self-organized criticality, but, remarkably, in a thermodynamically equilibrated state. The distinction between percolating and non-percolating networks appears physically meaningless, even though the percolating cluster, when it exists, takes up a finite fraction of the network. We point out both similarities and differences between the intermediate phase and the critical point of ordinary percolation models without self-organization. Our results are consistent with an interpretation of recent experiments on the pressure dependence of Raman frequencies in chalcogenide glasses in terms of network homogeneity.Comment: 20 pages, 18 figure

Microstructure and magnetization of doped Y-Ba-Ca-O materials prepared by melt quench and post annealing method

Y-Ba-Cu-O bulk materials prepared using the melt quench and post annealing method were shown to have very high maximum as well as remanent magnetization. Studies were carried out on materials prepared using this method which deviate from the Y:Ba:Cu = 1:2:3 stoichiometry. In one series of materials, only the stoichiometry was changed, in particular by introducing an excess of yttrium. In other cases, dopants including several rare earths were introduced. Effects of variations in composition on microstructure and phase evolution are discussed, as well as effects on the magnetic susceptibility and on the magnetization. The results show that doped materials can exhibit improvements in magnetic properties. Furthermore, the use of dopants sheds light on the role of defect sites in flux pinning

Rigidity analysis of HIV-1 protease

We present a rigidity analysis on a large number of X-ray crystal structures of the enzyme HIV-1 protease using the 'pebble game' algorithm of the software FIRST. We find that although the rigidity profile remains similar across a comprehensive set of high resolution structures, the profile changes significantly in the presence of an inhibitor. Our study shows that the action of the inhibitors is to restrict the flexibility of the beta-hairpin flaps which allow access to the active site. The results are discussed in the context of full molecular dynamics simulations as well as data from NMR experiments.Comment: 4 pages, 3 figures. Conference proceedings for CMMP conference 2010 which was held at the University of Warwic

Elastin is Localised to the Interfascicular Matrix of Energy Storing Tendons and Becomes Increasingly Disorganised With Ageing

Tendon is composed of fascicles bound together by the interfascicular matrix (IFM). Energy storing tendons are more elastic and extensible than positional tendons; behaviour provided by specialisation of the IFM to enable repeated interfascicular sliding and recoil. With ageing, the IFM becomes stiffer and less fatigue resistant, potentially explaining why older tendons become more injury-prone. Recent data indicates enrichment of elastin within the IFM, but this has yet to be quantified. We hypothesised that elastin is more prevalent in energy storing than positional tendons, and is mainly localised to the IFM. Further, we hypothesised that elastin becomes disorganised and fragmented, and decreases in amount with ageing, especially in energy storing tendons. Biochemical analyses and immunohistochemical techniques were used to determine elastin content and organisation, in young and old equine energy storing and positional tendons. Supporting the hypothesis, elastin localises to the IFM of energy storing tendons, reducing in quantity and becoming more disorganised with ageing. These changes may contribute to the increased injury risk in aged energy storing tendons. Full understanding of the processes leading to loss of elastin and its disorganisation with ageing may aid in the development of treatments to prevent age related tendinopathy

Data-Driven Stochastic Optimal Control Using Kernel Gradients

We present an empirical, gradient-based method for solving data-driven stochastic optimal control problems using the theory of kernel embeddings of distributions. By embedding the integral operator of a stochastic kernel in a reproducing kernel Hilbert space, we can compute an empirical approximation of stochastic optimal control problems, which can then be solved efficiently using the properties of the RKHS. Existing approaches typically rely upon finite control spaces or optimize over policies with finite support to enable optimization. In contrast, our approach uses kernel-based gradients computed using observed data to approximate the cost surface of the optimal control problem, which can then be optimized using gradient descent. We apply our technique to the area of data-driven stochastic optimal control, and demonstrate our proposed approach on a linear regulation problem for comparison and on a nonlinear target tracking problem

Gas permeation through a polymer network

We study the diffusion of gas molecules through a two-dimensional network of polymers with the help of Monte Carlo simulations. The polymers are modeled as non-interacting random walks on the bonds of a two-dimensional square lattice, while the gas particles occupy the lattice cells. When a particle attempts to jump to a nearest-neighbor empty cell, it has to overcome an energy barrier which is determined by the number of polymer segments on the bond separating the two cells. We investigate the gas current $J$ as a function of the mean segment density $\rho$, the polymer length $\ell$ and the probability $q^{m}$ for hopping across $m$ segments. Whereas $J$ decreases monotonically with $\rho$ for fixed $\ell$, its behavior for fixed $\rho$ and increasing $\ell$ depends strongly on $q$. For small, non-zero $q$, $J$ appears to increase slowly with $\ell$. In contrast, for $q=0$, it is dominated by the underlying percolation problem and can be non-monotonic. We provide heuristic arguments to put these interesting phenomena into context.Comment: Dedicated to Lothar Schaefer on the occasion of his 60th birthday. 11 pages, 3 figure

A bio-inspired image coder with temporal scalability

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.Comment: 12 pages; Advanced Concepts for Intelligent Vision Systems (ACIVS 2011

Mind the Gap

Mind the Gap sought to improve the metacognition and academic attainment of pupils in Year 4. There were two aspects to the intervention. The first involved training teachers in how to embed metacognitive approaches in their work, and how to continue to effectively and strategically involve parents. This training took place over a day and was provided by a consultant. The second component focused on parental engagement and offered families the opportunity to participate in a series of facilitated workshops where children and parents work together to create an animated film. Sessions were coordinated by a practitioner who helped participants to think about how they are learning, create learning goals and reflect on their progress; to be metacognitive about the learning process they were engaged in together. The families were offered 2 hours of workshops per week for 5 weeks (10 hours in total). The project targeted schools in four areas of England: Birmingham, Devon, London and Manchester. It was delivered by the Campaign for Learning, with assessments carried out by Durham University. Delivery started in September 2012 and finished in October 2013. The project was evaluated using a randomised controlled trial, which compared the interventions to a ‘business-as-usual’ control group. It is important to note that it was eligibility for the animation course, not participation, that was randomised, so the results must be regarded as estimating the effect of being offered the animation course (alone or in combination with teacher training, as appropriate) rather than participating in it

Atomistic modeling of amorphous silicon carbide: An approximate first-principles study in constrained solution space

Localized basis ab initio molecular dynamics simulation within the density functional framework has been used to generate realistic configurations of amorphous silicon carbide (a-SiC). Our approach consists of constructing a set of smart initial configurations that conform essential geometrical and structural aspects of the materials obtained from experimental data, which is subsequently driven via first-principles force-field to obtain the best solution in a reduced solution space. A combination of a priori information (primarily structural and topological) along with the ab-initio optimization of the total energy makes it possible to model large system size (1000 atoms) without compromising the quantum mechanical accuracy of the force-field to describe the complex bonding chemistry of Si and C. The structural, electronic and the vibrational properties of the models have been studied and compared to existing theoretical models and available data from experiments. We demonstrate that the approach is capable of producing large, realistic configurations of a-SiC from first-principles simulation that display excellent structural and electronic properties of a-SiC. Our study reveals the presence of predominant short-range order in the material originating from heteronuclear Si-C bonds with coordination defect concentration as small as 5% and the chemical disorder parameter of about 8%.Comment: 16 pages, 7 figure