When the five giants of post war reconstruction meet the four pillars of welfare reform-young people lose out, again

This paper discusses proposed changes to the Australian welfare state in the Welfare Review chaired by Patrick McClure and launched by Kevin Andrews, Minister for Social Services in the Abbott government, in a recent address to the Sydney Institute. Andrews cited the Beveridge Report of 1942, referring to Lord William Beveridge as the “godfather of the British post-war welfare state”, commending him for putting forward a plan for a welfare state providing a minimal level of support, constituting a bare safety net, rather than “stifling civil society and personal responsibility” through generous provision. In line with a key TASA conference theme of challenging institutions and identifying social and political change at local and global levels, this paper examines both the Beveridge Report and the McClure Report, identifying key issues and themes of relevance to current times in Australia.

Separable spatiotemporal priors for convex reconstruction of time-varying 3D point clouds

Reconstructing 3D motion data is highly under-constrained due to several common sources of data loss during measurement, such as projection, occlusion, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariances. We relate the marginals of the distribution to the shape, trajectory, and shape-trajectory models of prior art. When the marginal shape distribution is not available from training data, we show how placing a hierarchical prior over shapes results in a convex MAP solution in terms of the trace-norm. The matrix normal distribution, fit to a single sequence, outperforms state-of-the-art methods at reconstructing 3D motion data in the presence of significant data loss, while providing covariance estimates of the imputed points.

Nanopatterning by solid-state dewetting on reconstructed ceramic surfaces

We demonstrate ordered array formation of Au nanoparticles by controlled solid-state dewetting of a metal film on stepped alumina substrates. In situ transmission electron microscopy studies reveal that the dewetting process starts with nucleation of ordered dry regions on the substrate. The chemical potential difference between concave and convex surface regions induces anisotropic metal diffusion leading to the formation of nanowires in the valleys. The nanowires fragment due to Rayleigh instability forming arrays of metal nanoparticles on the substrate. The length scale of reconstruction relative to the starting film thickness is an important parameter in controlling the spatial order of the nanoparticles.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography

The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

Composite MR image reconstruction and unaliasing for general trajectories using neural networks

In rapid parallel magnetic resonance imaging, the problem of image reconstruction is challenging. Here, a novel image reconstruction technique for data acquired along any general trajectory in neural network framework, called ``Composite Reconstruction And Unaliasing using Neural Networks'' (CRAUNN), is proposed. CRAUNN is based on the observation that the nature of aliasing remains unchanged whether the undersampled acquisition contains only low frequencies or includes high frequencies too. Here, the transformation needed to reconstruct the alias-free image from the aliased coil images is learnt, using acquisitions consisting of densely sampled low frequencies. Neural networks are made use of as machine learning tools to learn the transformation, in order to obtain the desired alias-free image for actual acquisitions containing sparsely sampled low as well as high frequencies. CRAUNN operates in the image domain and does not require explicit coil sensitivity estimation. It is also independent of the sampling trajectory used, and could be applied to arbitrary trajectories as well. As a pilot trial, the technique is first applied to Cartesian trajectory-sampled data. Experiments performed using radial and spiral trajectories on real and synthetic data, illustrate the performance of the method. The reconstruction errors depend on the acceleration factor as well as the sampling trajectory. It is found that higher acceleration factors can be obtained when radial trajectories are used. Comparisons against existing techniques are presented. CRAUNN has been found to perform on par with the state-of-the-art techniques. Acceleration factors of up to 4, 6 and 4 are achieved in Cartesian, radial and spiral cases, respectively. (C) 2010 Elsevier Inc. All rights reserved.

Advances in Image Reconstruction Methods for Real-Time Magnetic Resonance Thermometry

Magnetic Resonance Imaging (MRI) has been widely used in cancer treatment planning, which takes the advantage of high-resolution and high-contrast provided by it. The raw data collected in the MRI can also be used to obtain the temperature maps and has been explored for performing MR thermometry. This review article describes the methods that are used in performing MR thermometry, with an emphasis on reconstruction methods that are useful to obtain these temperature maps in real-time for large region of interest. This article also proposes a prior-image constrained reconstruction method for temperature reconstruction in MR thermometry, and a systematic comparison using ex-vivo tissue experiments with state of the art reconstruction method is presented.

B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy). A comparative study of the proposed technique with the state-of-art maximum likelihood (ML) and maximum-a-posteriori (MAP) with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED. (C) 2015 Author(s).

Geometric documentation and reconstruction of the church of the Monastery of San Prudencio (La Rioja, Spain)

[EN] Data contained in this record come from the following accademic activity (from which it is possible to locate additional records related with the Monastery):

Dimorfismo sexual e polimorfismo no gênero Ptychoderes Schoenherr, 1823 (Coleoptera Anthribidae, Anthribinae, Ptychoderini)

O dimorfismo sexual exibido por machos polifênicos em algumas espécies do gênero Ptychoderes envolve variação no rostro, antena e ventritos. A existência de polifenismo pode ser um importante componente no processo evolutivo por meio de novidades morfológicas e comportamentais. O objetivo desse estudo foi determinar a variação em caracteres morfométricos, polifenismo em machos, variação de estruturas com conhecido dimorfismo sexual, possíveis padrões alométricos e testar estas inferências para Ptychoderes através do mapeamento do dimorfismo sexual e de machos em uma reconstrução filogenética de Ptychoderes usando Mesquite 2.04. Foram medidas 23 variáveis morfométricas em 510 espécimes com as seguintes análises realizadas: análises de cluster, analises de componentes principais (PCA), analise de variáveis canônicas (AVC), análise de regressão por eixo maior reduzido (RMA). Cada tipo de dimorfismo foi mapeado em uma filogenia prévia como dois estados separados usando parcimônia. Para todas as espécies o dimorfismo sexual apresentou diferenças significativas entre os sexos com relação aos segmentos antenais (II- X).O compriemtno do rosto e ventrito V foram confirmados como indicativos de dimorfismo sexual (exceto em P. jordani). A única espécie em que não ocorreu machos polifenicos foi P. depressus. Nas outras espécies machos grandes e pequenos diferem significantemente para muitas variáveis com similaridades e diferenças. Na ACP, o primeiro componente (PC1) apresentou alta porcentagem de variância nos dados de todas as espécies; apresentou loadings de mesmo sinal sugerindo diferenças relacionadas ao tamanho para as espécies P. jordani, P. depressus, P. virgatus, P. mixtus e P. callosus e para as espécies P. viridanus, P. antiquus, P. elongates e P. nebulosus apresentou loadings positivos e negativos sugerindo diferenças relacionadas a forma (alometria). O PC2 apresentou loadings positivos e negativos para todas as espécies, um provável componente alométricos. A AVC confirmou os grupos: machos grandes, machos pequenos e fêmeas quando estes ocorreram. Nós encontramos diferentes padrões alométricos para todas as espécies com diferenças e semelhanças entre as espécies. Todos esses resultados confirmam a hipótese de polifenismo em machos e dimorfismo sexual para Ptychhoderes. A análise dos padrões alométricos para o dimorfismo sexual revelou alometria positiva para o comprimento do rostro (CR1) em machos e fêmeas, com os ventritos apenas em machos. Padrões alométricos positivos relacionados ao polifenismo nos antenômeros foram confirmados para os machos grandes e pequenos de quase todas as espécies exceto em P. nebulosus. O ancestral de clados na filogenia de Ptychoderes foi inferido para machos polifênicos (exceto P. depressus) com variáveis no rostro, antenas e ventritos indicativas de dimorfismo sexual com alometria positiva. Estes padrões poderiam estar ligados com o comportamento de proteção das fêemeas realizados por machos grandes durante a oviposição.

Parity-dependent State Engineering and Tomography in the ultrastrong coupling regime

Reaching the strong coupling regime of light-matter interaction has led to an impressive development in fundamental quantum physics and applications to quantum information processing. Latests advances in different quantum technologies, like superconducting circuits or semiconductor quantum wells, show that the ultrastrong coupling regime (USC) can also be achieved, where novel physical phenomena and potential computational benefits have been predicted. Nevertheless, the lack of effective decoupling mechanism in this regime has so far hindered control and measurement processes. Here, we propose a method based on parity symmetry conservation that allows for the generation and reconstruction of arbitrary states in the ultrastrong coupling regime of light-matter interactions. Our protocol requires minimal external resources by making use of the coupling between the USC system and an ancillary two-level quantum system.

Fourier analysis and gabor filtering for texture analysis and local reconstruction of general shapes

Since the pioneering work of Gibson in 1950, Shape- From-Texture has been considered by researchers as a hard problem, mainly due to restrictive assumptions which often limit its applicability. We assume a very general stochastic homogeneity and perspective camera model, for both deterministic and stochastic textures. A multi-scale distortion is efficiently estimated with a previously presented method based on Fourier analysis and Gabor filters. The novel 3D reconstruction method that we propose applies to general shapes, and includes non-developable and extensive surfaces. Our algorithm is accurate, robust and compares favorably to the present state of the art of Shape-From- Texture. Results show its application to non-invasively study shape changes with laid-on textures, while rendering and retexturing of cloth is suggested for future work. © 2009 IEEE.

Free energy surface reconstruction from umbrella samples using Gaussian process regression

We demonstrate how the Gaussian process regression approach can be used to efficiently reconstruct free energy surfaces from umbrella sampling simulations. By making a prior assumption of smoothness and taking account of the sampling noise in a consistent fashion, we achieve a significant improvement in accuracy over the state of the art in two or more dimensions or, equivalently, a significant cost reduction to obtain the free energy surface within a prescribed tolerance in both regimes of spatially sparse data and short sampling trajectories. Stemming from its Bayesian interpretation the method provides meaningful error bars without significant additional computation. A software implementation is made available on www.libatoms.org.

Network reconstruction using knock-out and over-expression data

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. © 2013 EUCA.

Effect of reconstruction beam polarization on the kinetics of anisotropic gratings in bacteriorhodopsin

Anisotropic gratings are recorded on bacteriorhodopsin films by two parallelly polarized beams, and the effect of the polarization orientation of the reconstructing beam on the diffraction efficiency kinetics is studied. A theoretical model for the diffraction efficiency kinetics of the anisotropic grating is developed by combining Jones-matrix and photochromic two-state theory. It is found that the polarization azimuth of the reconstructing beam produces a cosine modulation on the kinetics of the diffraction efficiency, being positive at the peak efficiency and negative for steady state. By adding auxiliary violet light during grating formation, the saturation of the grating can be restrained. As a result, the negative cosine modulation for the steady-state diffraction efficiency changes to a positive one. In addition, the steady-state diffraction efficiency is increased appreciably for all reconstructing polarization orientations. (c) 2008 Optical Society of America.