Dietary intake and food sources of added sugar in the Australian population

Previous studies in Australian children/adolescents and adults examining added sugar (AS) intake were based on now out-of-date national surveys. We aimed to examine the AS and free sugar (FS) intakes and the main food sources of AS among Australians, using plausible dietary data collected by a multiple-pass, 24-h recall, from the 2011-12 Australian Health Survey respondents (n 8202). AS and FS intakes were estimated using a previously published method, and as defined by the WHO, respectively. Food groups contributing to the AS intake were described and compared by age group and sex by one-way ANOVA. Linear regression was used to test for trends across age groups. Usual intake of FS (as percentage energy (%EFS)) was computed using a published method and compared with the WHO cut-off of <10 %EFS. The mean AS intake of the participants was 60·3 (sd 52·6) g/d. Sugar-sweetened beverages accounted for the greatest proportion of the AS intake of the Australian population (21·4 (sd 30·1) %), followed by sugar and sweet spreads (16·3 (sd 24·5) %) and cakes, biscuits, pastries and batter-based products (15·7 (sd 24·4) %). More than half of the study population exceeded the WHO's cut-off for FS, especially children and adolescents. Overall, 80-90 % of the daily AS intake came from high-sugar energy-dense and/or nutrient-poor foods. To conclude, the majority of Australian adults and children exceed the WHO recommendation for FS intake. Efforts to reduce AS intake should focus on energy-dense and/or nutrient-poor foods.postprin

Statistical physics-based reconstruction in compressed sensing

Compressed sensing is triggering a major evolution in signal acquisition. It consists in sampling a sparse signal at low rate and later using computational power for its exact reconstruction, so that only the necessary information is measured. Currently used reconstruction techniques are, however, limited to acquisition rates larger than the true density of the signal. We design a new procedure which is able to reconstruct exactly the signal with a number of measurements that approaches the theoretical limit in the limit of large systems. It is based on the joint use of three essential ingredients: a probabilistic approach to signal reconstruction, a message-passing algorithm adapted from belief propagation, and a careful design of the measurement matrix inspired from the theory of crystal nucleation. The performance of this new algorithm is analyzed by statistical physics methods. The obtained improvement is confirmed by numerical studies of several cases.Comment: 20 pages, 8 figures, 3 tables. Related codes and data are available at http://aspics.krzakala.or

Chance long-distance or human-mediated dispersal? How Acacia s.l. farnesiana attained its pan-tropical distribution

Acacia s.l. farnesiana, which originates from Mesoamerica, is the most widely distributed Acacia s.l. species across the tropics. It is assumed that the plant was transferred across the Atlantic to southern Europe by Spanish explorers, and then spread across the Old World tropics through a combination of chance long-distance and human-mediated dispersal. Our study uses genetic analysis and information from historical sources to test the relative roles of chance and human-mediated dispersal in its distribution. The results confirm the Mesoamerican origins of the plant and show three patterns of human- mediated dispersal. Samples from Spain showed greater genetic diversity than those from other Old World tropics, suggesting more instances of transatlantic introductions from the Americas to that country than to other parts of Africa and Asia. Individuals from the Philippines matched a population from South Central Mexico and were likely to have been direct, trans-Pacific introductions. Australian samples were genetically unique, indicating that the arrival of the species in the continent was independent of these European colonial activities. This suggests the possibility of pre-European human- mediated dispersal across the Pacific Ocean. These significant findings raise new questions for biogeographic studies that assume chance or transoceanic dispersal 2 for disjunct plant distributions

Quantum phase retrieval of a Rydberg wave packet using a half-cycle pulse

A terahertz half-cycle pulse was used to retrieve information stored as quantum phase in an $N$-state Rydberg atom data register. The register was prepared as a wave packet with one state phase-reversed from the others (the "marked bit"). A half-cycle pulse then drove a significant portion of the electron probability into the flipped state via multimode interference.Comment: accepted by PR

Are Steadily Moving Crystals Unstable?

We study the dynamics of small fluctuations about the uniform state of a crystal moving through a dissipative medium, e.g. a sedimenting colloidal crystal or a moving flux lattice, using a set of continuum equations for the displacement fields, and a one-dimensional driven lattice-gas model for the coupled concentration and tilt fields. For the colloidal crystal we predict a continuous nonequilibrium phase transition to a clumped state above a critical Peclet number.Comment: 4 pages, revtex, 2 .eps figures, uses epsf.sty; To be published in Phys. Rev. Lett. This version is substantially rewritten but the essential content is the same as befor

Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in [arXiv:1109.4424] a strategy that allows compressed sensing to be performed at acquisition rates approaching to the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation max- imization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distribution of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.Comment: 42 pages, 37 figures, 3 appendixe

A typical reconstruction limit of compressed sensing based on Lp-norm minimization

We consider the problem of reconstructing an $N$-dimensional continuous vector \bx from $P$ constraints which are generated by its linear transformation under the assumption that the number of non-zero elements of \bx is typically limited to $\rho N$ ($0\le \rho \le 1$). Problems of this type can be solved by minimizing a cost function with respect to the $L_p$-norm ||\bx||_p=\lim_{\epsilon \to +0}\sum_{i=1}^N |x_i|^{p+\epsilon}, subject to the constraints under an appropriate condition. For several $p$, we assess a typical case limit $\alpha_c(\rho)$, which represents a critical relation between $\alpha=P/N$ and $\rho$ for successfully reconstructing the original vector by minimization for typical situations in the limit $N,P \to \infty$ with keeping $\alpha$ finite, utilizing the replica method. For $p=1$, $\alpha_c(\rho)$ is considerably smaller than its worst case counterpart, which has been rigorously derived by existing literature of information theory.Comment: 12 pages, 2 figure