Polymorphisms of the estrogen receptor alpha (ESR1) gene and the risk of Alzheimer's disease in a southern Chinese community

Background: Alzheimer's disease (AD) is a neurodegenerative disease with a higher prevalence in women. Expression of estrogen receptor 1 (ESR1) gene has been identified throughout the brain. Owing to the putative neuroprotective effects of estrogen, estro

The biology, ecology, distribution and conservation of some surviving native non-cichlid fish species of Lakes Victoria, Kyoga and Nabugabo

Prior to introduction of non-native fish species into Lakes Victor i a, Kyoga and Nabugabo, the three lakes suppor ted diverse fish fauna representing 13 families consisting of six cichlid genera and fifteen non-cichlid genera. There were about 50 non-cichlid species and over 300 cichlids consisting of mainly haplochromines (Graham 1929, worthington 1929, Greenwood 1960). Many of the species were commercially and scientifically important and provided a rich variety of protein source to choose from. Following introduction of the Nile perch and several tilapiines species, most of the native species were drastically reduced and some have apparently disappeared. The few remaining species appear to be restricted in distribution due to the presence of the Nile perch. They are mainly confined to refugia such as marginal macrophytes, rocky outcrops and small satellite lakes which are separated from the areas of introduction by swamps

Assessment of computational fluid dynamics and experimental data for shock boundary-layer interactions

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop, numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric, and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and, in general, it was difficult to discern clear trends in the data. For the Reynolds-averaged Navier-Stokes (RANS) methods, the choice of turbulence model appeared to be the largest factor in solution accuracy. Scale-resolving methods, such as large-eddy simulation (LES), hybrid RANS/LES, and direct numerical simulation, produced error levels similar to RANS methods but provided superior predictions of normal stresses. Copyright © 2012 by Daniella E. Raveh and Michael Iovnovich.

Probabilistic amplitude and frequency demodulation

A number of recent scientific and engineering problems require signals to be decomposed into a product of a slowly varying positive envelope and a quickly varying carrier whose instantaneous frequency also varies slowly over time. Although signal processing provides algorithms for so-called amplitude-and frequency-demodulation (AFD), there are well known problems with all of the existing methods. Motivated by the fact that AFD is ill-posed, we approach the problem using probabilistic inference. The new approach, called probabilistic amplitude and frequency demodulation (PAFD), models instantaneous frequency using an auto-regressive generalization of the von Mises distribution, and the envelopes using Gaussian auto-regressive dynamics with a positivity constraint. A novel form of expectation propagation is used for inference. We demonstrate that although PAFD is computationally demanding, it outperforms previous approaches on synthetic and real signals in clean, noisy and missing data settings.

State-space inference and learning with Gaussian processes

State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. Copyright 2010 by the authors.

Robust filtering and smoothing with gaussian processes

We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of system identification is more robust than finding point estimates of a parametric function representation. Our principled filtering/smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail. © 2011 IEEE.

Development of a servo-hydraulic earthquake actuator for the Cambridge Turner beam centrifuge

Dynamic centrifuge modelling has been carried out at Cambridge since the late 1970s. Over this period, three different mechanical earthquake actuators were developed. In this paper the development of a new servo-hydraulic earthquake actuator is described. The basic design principles are explained along with the need to carry out these designs to match the existing services and systems of the 35 year old Turner beam centrifuge at Cambridge. In addition, some of the features of the Turner beam centrifuge are exploited in the design of this new earthquake actuator. The paper also explains the mechanical fabrication of the actuator and the control systems that were developed in order to generate real earthquake motions. Finally, the performance of this new servo-hydraulic earthquake actuator is presented and assessed based on a wide range of earthquake input motions.

Decomposing signals into a sum of amplitude and frequency modulated sinusoids using probabilistic inference

There are many methods for decomposing signals into a sum of amplitude and frequency modulated sinusoids. In this paper we take a new estimation based approach. Identifying the problem as ill-posed, we show how to regularize the solution by imposing soft constraints on the amplitude and phase variables of the sinusoids. Estimation proceeds using a version of Kalman smoothing. We evaluate the method on synthetic and natural, clean and noisy signals, showing that it outperforms previous decompositions, but at a higher computational cost. © 2012 IEEE.

Thermal stratification produced by plumes and jets in enclosed spaces

The airflow and thermal stratification produced by a localised heat source located at floor level in a closed room is of considerable practical interest and is commonly referred to as a 'filling box'. In rooms with low aspect ratios H/R ≲ 1 (room height H to characteristic horizontal dimension R) the thermal plume spreads laterally on reaching the ceiling and a descending horizontal 'front' forms separating a stably stratified, warm upper region from cooler air below. The stratification is well predicted for H/R ≲ 1 by the original filling box model of Baines and Turner (J. Fluid. Mech. 37 (1968) 51). This model represents a somewhat idealised situation of a plume rising from a point source of buoyancy alone-in particular the momentum flux at the source is zero. In practical situations, real sources of heating and cooling in a ventilation system often include initial fluxes of both buoyancy and momentum, e.g. where a heating system vents warm air into a space. This paper describes laboratory experiments to determine the dependence of the 'front' formation and stratification on the source momentum and buoyancy fluxes of a single source, and on the location and relative strengths of two sources from which momentum and buoyancy fluxes were supplied separately. For a single source with a non-zero input of momentum, the rate of descent of the front is more rapid than for the case of zero source momentum flux and increases with increasing momentum input. Increasing the source momentum flux effectively increases the height of the enclosure, and leads to enhanced overturning motions and finally to complete mixing for highly momentum-driven flows. Stratified flows may be maintained by reducing the aspect ratio of the enclosure. At these low aspect ratios different long-time behaviour is observed depending on the nature of the heat input. A constant heat flux always produces a stratified interior at large times. On the other hand, a constant temperature supply ultimately produces a well-mixed space at the supply temperature. For separate sources of momentum and buoyancy, the developing stratification is shown to be strongly dependent on the separation of the sources and their relative strengths. Even at small separation distances the stratification initially exhibits horizontal inhomogeneity with localised regions of warm fluid (from the buoyancy source) and cool fluid. This inhomogeneity is less pronounced as the strength of one source is increased relative to the other. Regardless of the strengths of the sources, a constant buoyancy flux source dominates after sufficiently large times, although the strength of the momentum source determines whether the enclosure is initially well mixed (strong momentum source) or stably stratified (weak momentum source). © 2001 Elsevier Science Ltd. All rights reserved.

On sparsity and overcompleteness in image models

Computational models of visual cortex, and in particular those based on sparse coding, have enjoyed much recent attention. Despite this currency, the question of how sparse or how over-complete a sparse representation should be, has gone without principled answer. Here, we use Bayesian model-selection methods to address these questions for a sparse-coding model based on a Student-t prior. Having validated our methods on toy data, we find that natural images are indeed best modelled by extremely sparse distributions; although for the Student-t prior, the associated optimal basis size is only modestly over-complete.

Generation and evolution of magma beneath the East Pacific Rise: Constraints from U-series disequilibrium and plagioclase-hosted melt inclusions

Mid-ocean ridge basalt (MORB) samples from the East Pacific Rise (EPR 12 degrees 50'N) were analyzed for U-series isotopes and compositions of plagioclase-hosted melt inclusions. The Ra-226 and Th-230 excesses are negatively correlated; the Ra-226 excess is positively correlated with Mg# and Sm/Nd, and is negatively correlated with La/Sm and Fe-8; the Th-230 excess is positively correlated with Fe-8 and La/Sm and is negatively correlated with Mg# and Sm/Nd. Interpretation of these correlations is critical for understanding the magmatic process. There are two models (the dynamic model and the "two-porosity" model) for interpreting these correlations, however, some crucial parameters used in these models are not ascertained. We propose instead a model to explain the U-series isotopic compositions based on the control of melt density variation. For melting either peridotite or the "marble-cake" mantle, the FeOt content, Th-230 excess and La/Sm ratio increases and Sm/Nd decreases with increasing pressure. A deep melt will evolve to a higher density and lower Mg# than a shallow melt, the former corresponds to a long residence time, which lowers the Ra-226 excess significantly. This model is supported by the existence of low Ra-226 excesses and high Th-230 excesses in MORBs having a high Fe-8 content and high density. The positive correlation of Ra-226 excess and magma liquidus temperature implies that the shallow melt is cooled less than the deep melt due to its low density and short residence time. The correlations among Fe-8, Ti-8 and Ca-8/Al-8 in plagioclase-hosted melt inclusions further prove that MORBs are formed from melts having a negative correlation in melting depths and degrees. The negative correlation of Ra-226 excess vs. chemical diversity index (standard deviation of Fe-8, Ti-8 and Ca-8/Al-8) of the melt inclusions is in accordance with the influence of a density-controlled magma residence time. We conclude that the magma density variation exerts significant control on residence time and U-series isotopic compositions. (c) 2010 Elsevier B.V. All rights reserved.

Physical mechanism and numerical simulations of surface layer temperature inversion in tropical ocean

The one-dimensional Kraus-Turner mixed layer model improved by Liu is developed to consider the effect of salinity and the equations of temperature and salinity under the mixed layer. On this basis, the processes of growth and death of surface layer temperature inversion is numerically simulated under different environmental parameters. At the same time, the physical mechanism is preliminarily discussed combining the observations at the station of TOGA-COARE 0 degrees N, 156 degrees E. The results indicate that temperature inversion sensitively depends on the mixed layer depth, sea surface wind speed and solar shortwave radiation, etc., and appropriately meteorological and hydrological conditions often lead to the similarly periodical occurrence of this inversion phenomenon.