Sensitivity of a hydraulic model to changes in channel erosion during extreme flooding

Recent research into flood modelling has primarily concentrated on the simulation of inundation flow without considering the influences of channel morphology. River channels are often represented by a simplified geometry that is implicitly assumed to remain unchanged during flood simulations. However, field evidence demonstrates that significant morphological changes can occur during floods to mobilise the boundary sediments. Despite this, the effect of channel morphology on model results has been largely unexplored. To address this issue, the impact of channel cross-section geometry and channel long-profile variability on flood dynamics is examined using an ensemble of a 1D-2D hydraulic model (LISFLOOD-FP) of the 1:2102 year recurrence interval floods in Cockermouth, UK, within an uncertainty framework. A series of hypothetical scenarios of channel morphology were constructed based on a simple velocity based model of critical entrainment. A Monte-Carlo simulation framework was used to quantify the effects of channel morphology together with variations in the channel and floodplain roughness coefficients, grain size characteristics, and critical shear stress on measures of flood inundation. The results showed that the bed elevation modifications generated by the simplistic equations reflected a good approximation of the observed patterns of spatial erosion despite its overestimation of erosion depths. The effect of uncertainty on channel long-profile variability only affected the local flood dynamics and did not significantly affect the friction sensitivity and flood inundation mapping. The results imply that hydraulic models generally do not need to account for within event morphodynamic changes of the type and magnitude modelled, as these have a negligible impact that is smaller than other uncertainties, e.g. boundary conditions. Instead morphodynamic change needs to happen over a series of events to become large enough to change the hydrodynamics of floods in supply limited gravel-bed rivers like the one used in this research.

Channel equalization for indoor lighting communications networks

We consider indoors communications networks using modulated LEDs to transmit the information packets. A generic indoor channel equalization formulation is proposed assuming the existence of both line of sight and diffuse emitters. The proposed approach is of relevance to emergent indoors distributed sensing modalities for which various lighting based network communications protocols are considered.

Oxygen-dependent hydroxylation by Factor Inhibiting HIF (FIH) regulates the TRPV3 ion channel

Factor Inhibiting HIF (FIH) is an oxygen-dependent asparaginyl hydroxylase that regulates the hypoxia-inducible factors (HIFs). Several proteins containing ankyrin repeat domains have been characterised as substrates of FIH, although there is little evidence for a functional consequence of hydroxylation on these substrates. This study demonstrates that the transient receptor potential vanilloid 3 (TRPV3) channel is hydroxylated by FIH on asparagine 242 within the cytoplasmic ankyrin repeat domain. Hypoxia, FIH inhibitors and mutation of asparagine 242 all potentiated TRPV3-mediated current, without altering TRPV3 protein levels, indicating that oxygen-dependent hydroxylation inhibits TRPV3 activity. This novel mechanism of channel regulation by oxygendependent asparaginyl hydroxylation is likely to extend to other ion channels.

Synaptic vesicle glycoprotein 2A modulates vesicular release and calcium channel function at peripheral sympathetic synapses

Synaptic vesicle glycoprotein (SV)2A is a transmembrane protein found in secretory vesicles and is critical for Ca2+-dependent exocytosis in central neurons, although its mechanism of action remains uncertain. Previous studies have proposed, variously, a role of SV2 in the maintenance and formation of the readily releasable pool (RRP) or in the regulation of Ca2+ responsiveness of primed vesicles. Such previous studies have typically used genetic approaches to ablate SV2 levels; here, we used a strategy involving small interference RNA (siRNA) injection to knockdown solely presynaptic SV2A levels in rat superior cervical ganglion (SCG) neuron synapses. Moreover, we investigated the effects of SV2A knockdown on voltage-dependent Ca2+ channel (VDCC) function in SCG neurons. Thus, we extended the studies of SV2A mechanisms by investigating the effects on vesicular transmitter release and VDCC function in peripheral sympathetic neurons. We first demonstrated an siRNA-mediated SV2A knockdown. We showed that this SV2A knockdown markedly affected presynaptic function, causing an attenuated RRP size, increased paired-pulse depression and delayed RRP recovery after stimulus-dependent depletion. We further demonstrated that the SV2A–siRNA-mediated effects on vesicular release were accompanied by a reduction in VDCC current density in isolated SCG neurons. Together, our data showed that SV2A is required for correct transmitter release at sympathetic neurons. Mechanistically, we demonstrated that presynaptic SV2A: (i) acted to direct normal synaptic transmission by maintaining RRP size, (ii) had a facilitatory role in recovery from synaptic depression, and that (iii) SV2A deficits were associated with aberrant Ca2+ current density, which may contribute to the secretory phenotype in sympathetic peripheral neurons.

Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Gaussian processes autoencoder for dimensionality reduction

Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing. The autoencoder is a powerful dimensionality reduction technique based on minimizing reconstruction error, and it has regained popularity because it has been efficiently used for greedy pretraining of deep neural networks. Compared to Neural Network (NN), the superiority of Gaussian Process (GP) has been shown in model inference, optimization and performance. GP has been successfully applied in nonlinear Dimensionality Reduction (DR) algorithms, such as Gaussian Process Latent Variable Model (GPLVM). In this paper we propose the Gaussian Processes Autoencoder Model (GPAM) for dimensionality reduction by extending the classic NN based autoencoder to GP based autoencoder. More interestingly, the novel model can also be viewed as back constrained GPLVM (BC-GPLVM) where the back constraint smooth function is represented by a GP. Experiments verify the performance of the newly proposed model.

On-line Gaussian mixture density estimator for adaptive minimum bit-error-rate beamforming receivers

We develop an on-line Gaussian mixture density estimator (OGMDE) in the complex-valued domain to facilitate adaptive minimum bit-error-rate (MBER) beamforming receiver for multiple antenna based space-division multiple access systems. Specifically, the novel OGMDE is proposed to adaptively model the probability density function of the beamformer’s output by tracking the incoming data sample by sample. With the aid of the proposed OGMDE, our adaptive beamformer is capable of updating the beamformer’s weights sample by sample to directly minimize the achievable bit error rate (BER). We show that this OGMDE based MBER beamformer outperforms the existing on-line MBER beamformer, known as the least BER beamformer, in terms of both the convergence speed and the achievable BER.

Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger scales the necessary information and model structures do not exist to take this approach. We therefore propose a fundamentally different approach where the structural uncertainty in channel geometry is represented using a simple parameterization, which could then be estimated through calibration or data assimilation. This paper first outlines the development of a computationally efficient numerical scheme to represent generalised channel shapes using a single parameter, which is then validated using a simple straight channel test case and shown to predict wetted perimeter to within 2% for the channels tested. An application to the River Severn, UK is also presented, along with an analysis of model sensitivity to channel shape, depth and friction. The channel shape parameter was shown to improve model simulations of river level, particularly for more physically plausible channel roughness and depth parameter ranges. Calibrating channel Manning’s coefficient in a rectangular channel provided similar water level simulation accuracy in terms of Nash-Sutcliffe efficiency to a model where friction and shape or depth were calibrated. However, the calibrated Manning coefficient in the rectangular channel model was ~2/3 greater than the likely physically realistic value for this reach and this erroneously slowed wave propagation times through the reach by several hours. Therefore, for large scale models applied in data sparse areas, calibrating channel depth and/or shape may be preferable to assuming a rectangular geometry and calibrating friction alone.

Quasi-sure existence of Gaussian rough paths and large deviation principles for capacities

We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated with a Gaussian process with long-time memory. As an application we establish a large deviation principle (LDP) for capacities for such Gaussian rough paths. Together with Lyons' universal limit theorem, our results yield immediately the corresponding results for pathwise solutions to stochastic differential equations driven by such Gaussian process in the sense of rough paths. Moreover, our LDP result implies the result of Yoshida on the LDP for capacities over the abstract Wiener space associated with such Gaussian process.

The Mesolithic-Neolithic transition in the Channel Islands: maritime and terrrestrial perspectives

This paper investigates the Mesolithic-Neolithic transition in the Channel Islands. It presents a new synthesis of all known evidence from the islands c. 5000-4300 BC, including several new excavations as well as find spot sites that have not previously been collated. It also summarises – in English – a large body of contemporary material from north-west France. The paper presents a new high-resolution sea level model for the region, shedding light on the formation of the Channel Islands from 9000-4000 BC. Through comparison with contemporary sites in mainland France, an argument is made suggesting that incoming migrants from the mainland and the small indigenous population of the islands were both involved in the transition. It is also argued that, as a result of the fact the Channel Islands witnessed a very different trajectory of change to that seen in Britain and Ireland c. 5000-3500 BC, this small group of islands has a great deal to tell us about the arrival of the Neolithic more widely.

The housing market channel of monetary policy transmission in the Euro area

Purpose – The purpose of this paper is to explore the role of the housing market in the monetary policy transmission to consumption among euro area member states. It has been argued that the housing market in one country is then important when its mortgage market is well developed. The countries in the euro area follow unitary monetary policy, however, their housing and mortgage markets show some heterogeneity, which may lead to different policy effects on aggregate consumption through the housing market. Design/methodology/approach – The housing market can act as a channel of monetary policy shocks to household consumption through changes in house prices and residential investment – the housing market channel. We estimate vector autoregressive models for each country and conduct a counterfactual analysis in order to disentangle the housing market channel and assess its importance across the euro area member states. Findings – We find little evidence for heterogeneity of the monetary policy transmission through house prices across the euro area countries. Housing market variations in the euro area seem to be better captured by changes in residential investment rather than by changes in house prices. As a result we do not find significantly large house price channels. For some of the countries however, we observe a monetary policy channel through residential investment. The existence of a housing channel may depend on institutional features of both the labour market or with institutional factors capturing the degree of household debt as is the LTV ratio. Originality/value – The study contributes to the existing literature by assessing whether a unitary monetary policy has a different impact on consumption across the euro area countries through their housing and mortgage markets. We disentangle monetary-policy-induced effects on consumption associated with variations on the housing markets due to either house price variations or residential investment changes. We show that the housing market can play a role in the monetary transmission mechanism even in countries with less developed mortgage markets through variations in residential investment.

Eddies and variability in the Mozambique Channel

Between 1995 and 2000, on average 4 eddies per year are observed from satellite altimetry to propagate southward through the Mozambique Channel, into the upstream Agulhas region. Further south, these eddies have been found to control the timing and frequenc yof Agulhas ring shedding. Within the Mozambique Channel, anomalous SSH amplitudes rise to 30 cm ; in agreement with in situ measured velocities. Comparison of an observed velocit ysection with GCM model results shows that the Mozambique Channel eddies in these models are too surface intensified. Also, the number of eddies formed in the models is in disagreement with our observational analysis. Moored current meter measurements observing the passage of three eddies in 2000 are extended to a 5-year time series b yreferencing the anomalous surface currents estimated from altimeter data to a s ynoptic LADCP velocit y measurement. The results show intermittent edd ypassage at the mooring location. A statistical analysis of SSH observations in different parts of the Mozambique Channel shows a southward decrease of the dominant frequency of the variability, going from 7 per year in the extension of the South Equatorial Current north of Madagascar to 4 per year south of Madagascar. The observations suggest that frequency reduction is related to the Rossb ywaves coming in from the east

High-precision measurements of the co-polar correlation coefficient: non-Gaussian errors and retrieval of the dispersion parameter µ in rainfall

The co-polar correlation coefficient (ρhv) has many applications, including hydrometeor classification, ground clutter and melting layer identification, interpretation of ice microphysics and the retrieval of rain drop size distributions (DSDs). However, we currently lack the quantitative error estimates that are necessary if these applications are to be fully exploited. Previous error estimates of ρhv rely on knowledge of the unknown "true" ρhv and implicitly assume a Gaussian probability distribution function of ρhv samples. We show that frequency distributions of ρhv estimates are in fact highly negatively skewed. A new variable: L = -log10(1 - ρhv) is defined, which does have Gaussian error statistics, and a standard deviation depending only on the number of independent radar pulses. This is verified using observations of spherical drizzle drops, allowing, for the first time, the construction of rigorous confidence intervals in estimates of ρhv. In addition, we demonstrate how the imperfect co-location of the horizontal and vertical polarisation sample volumes may be accounted for. The possibility of using L to estimate the dispersion parameter (µ) in the gamma drop size distribution is investigated. We find that including drop oscillations is essential for this application, otherwise there could be biases in retrieved µ of up to ~8. Preliminary results in rainfall are presented. In a convective rain case study, our estimates show µ to be substantially larger than 0 (an exponential DSD). In this particular rain event, rain rate would be overestimated by up to 50% if a simple exponential DSD is assumed.