Neonatal control of sucking pressures

Human newborns appear to regulate sucking pressure when bottle feeding by employing, with similar precision, the same principle of control evidenced by adults in skilled behavior, such as reaching (Lee et al., 1998a). In particular, the present study of 12 full-term newborn infants indicated that the intraoral sucking pressures followed an internal dynamic prototype - an intrinsic tau-guide. The intrinsic tau-guide, a recent hypothesis of general tau theory is a time-varying quantity, tau(g), assumed to be generated within the nervous system. It corresponds to some quantity (e.g., electrical charge), chang ing with a constant second-order temporal derivative from a rest level to a goal level, in the sense that tau(g) equals tau of the gap between the quantity and its goal level at each time t. (tau of a gap is the rime-to-closure of the gap at the current closure-rate.) According to the hypoth esis, the infant senses tau(p), the tau of the gap between the current intraoral pressure and its goal level, and regulates intraoral pressure so that tau(p) and tau(g) remain coupled in a constant ratio, k; i.e., tau(p) = k tau(g). With k in the range 0-1, the tau-coupling would result in a bell-shaped rate of change pressure profile, as was, in fact, found. More specifically, the high mean r(2) values obtained when regressing tau(p) on tau(g), for both the increasing and decreasing suction periods of the infants' suck, supported a strong tau-coupling between tau(p) and tau(g). The mean k values were significantly higher In the Increasing suction period, indicating that the ending of the movement was more forceful, a finding which makes sense given the different functions of the two periods of the suck.

Bit error rate performance enhancement of a retrodirective array over a conventional fixed beam array in a dynamic multipath environment

In this paper, we provide experimental evidence to show that enhanced bit error rate (BER) performance is possible using a retrodirective array operating in a dynamically varying multipath environment. The operation of such a system will be compared to that obtained by a conventional nonretrodirective array. The ability of the array to recover amplitude shift keyed encoded data transmitted from a remote location whose position is not known a priori is described. In addition, its ability to retransmit data inserted at the retrodirective array back to a spatially remote beacon location whose position is also not known beforehand is also demonstrated. Comparison with an equivalent conventional fixed beam antenna array utilizing an identical radiating aperture arrangement to that of the retrodirective array are given. These show that the retrodirective array can effectively exploit the presence of time varying multipath in order to give significant reductions in BER over what can be otherwise achieved. Additionally, the retrodirective system is shown to be able to deliver low BER regardless of whether line of sight is present or absent.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Dynamic Density Forecasts for Multivariate Asset Returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.

Temporal characterization and in vitro comparison of cell survival following the delivery of 3D-conformal, intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT)

A phantom was designed and implemented for the delivery of treatment plans to cells in vitro. Single beam, 3D-conformal radiotherapy (3D-CRT) plans, inverse planned five-field intensity-modulated radiation therapy (IMRT), nine-field IMRT, single-arc volumetric modulated arc therapy (VMAT) and dual-arc VMAT plans were created on a CT scan of the phantom to deliver 3 Gy to the cell layer and verified using a Farmer chamber, 2D ionization chamber array and gafchromic film. Each plan was delivered to a 2D ionization chamber array to assess the temporal characteristics of the plan including delivery time and 'cell's eye view' for the central ionization chamber. The effective fraction time, defined as the percentage of the fraction time where any dose is delivered to each point examined, was also assessed across 120 ionization chambers. Each plan was delivered to human prostate cancer DU-145 cells and normal primary AGO-1522b fibroblast cells. Uniform beams were delivered to each cell line with the delivery time varying from 0.5 to 20.54 min. Effective fraction time was found to increase with a decreasing number of beams or arcs. For a uniform beam delivery, AGO-1552b cells exhibited a statistically significant trend towards increased survival with increased delivery time. This trend was not repeated when the different modulated clinical delivery methods were used. Less sensitive DU-145 cells did not exhibit a significant trend towards increased survival with increased delivery time for either the uniform or clinical deliveries. These results confirm that dose rate effects are most prevalent in more radiosensitive cells. Cell survival data generated from uniform beam deliveries over a range of dose rates and delivery times may not always be accurate in predicting response to more complex delivery techniques, such as IMRT and VMAT.

Approaching near-capacity on a multi-antenna channel using successive decoding and interference cancellation receivers

In this paper, we address the problem of designing multirate codes for a multiple-input and multiple-output (MIMO) system by restricting the receiver to be a successive decoding and interference cancellation type, when each of the antennas is encoded independently. Furthermore, it is assumed that the receiver knows the instantaneous fading channel states but the transmitter does not have access to them. It is well known that, in theory, minimum-mean-square error (MMSE) based successive decoding of multiple access (in multi-user communications) and MIMO channels achieves the total channel capacity. However, for this scheme to perform optimally, the optimal rates of each antenna (per-antenna rates) must be known at the transmitter. We show that the optimal per-antenna rates at the transmitter can be estimated using only the statistical characteristics of the MIMO channel in time-varying Rayleigh MIMO channel environments. Based on the results, multirate codes are designed using punctured turbo codes for a horizontal coded MIMO system. Simulation results show performances within about one to two dBs of MIMO channel capacity.

An integrated multi-sensor data fusion algorithm and autopilot iImplementation in an uninhabited surface craft

Unmanned surface vehicles (USVs) are able to accomplish difficult and challenging tasks both in civilian and defence sectors without endangering human lives. Their ability to work round the clock makes them well-suited for matters that demand immediate attention. These issues include but not limited to mines countermeasures, measuring the extent of an oil spill and locating the source of a chemical discharge. A number of USV programmes have emerged in the last decade for a variety of aforementioned purposes. Springer USV is one such research project highlighted in this paper. The intention herein is to report results emanating from data acquired from experiments on the Springer vessel whilst testing its advanced navigation, guidance and control (NGC) subsystems. The algorithms developed for these systems are based on soft-computing methodologies. A novel form of data fusion navigation algorithm has been developed and integrated with a modified optimal controller. Experimental results are presented and analysed for various scenarios including single and multiple waypoints tracking and fixed and time-varying reference bearings. It is demonstrated that the proposed NGC system provides promising results despite the presence of modelling uncertainty and external disturbances.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Speaker Recognition In Noisy Conditions With Limited Training Data

In this paper we present a novel method for performing speaker recognition with very limited training data and in the presence of background noise. Similarity-based speaker recognition is considered so that speaker models can be created with limited training speech data. The proposed similarity is a form of cosine similarity used as a distance measure between speech feature vectors. Each speech frame is modelled using subband features, and into this framework, multicondition training and optimal feature selection are introduced, making the system capable of performing speaker recognition in the presence of realistic, time-varying noise, which is unknown during training. Speaker identi?cation experiments were carried out using the SPIDRE database. The performance of the proposed new system for noise compensation is compared to that of an oracle model; the speaker identi?cation accuracy for clean speech by the new system trained with limited training data is compared to that of a GMM trained with several minutes of speech. Both comparisons have demonstrated the effectiveness of the new model. Finally, experiments were carried out to test the new model for speaker identi?cation given limited training data and with differing levels and types of realistic background noise. The results have demonstrated the robustness of the new system.

A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle

Previous research based on theoretical simulations has shown the potential of the wavelet transform to detect damage in a beam by analysing the time-deflection response due to a constant moving load. However, its application to identify damage from the response of a bridge to a vehicle raises a number of questions. Firstly, it may be difficult to record the difference in the deflection signal between a healthy and a slightly damaged structure to the required level of accuracy and high scanning frequencies in the field. Secondly, the bridge is going to have a road profile and it will be loaded by a sprung vehicle and time-varying forces rather than a constant load. Therefore, an algorithm based on a plot of wavelet coefficients versus time to detect damage (a singularity in the plot) appears to be very sensitive to noise. This paper addresses these questions by: (a) using the acceleration signal, instead of the deflection signal, (b) employing a vehicle-bridge finite element interaction model, and (c) developing a novel wavelet-based approach using wavelet energy content at each bridge section which proves to be more sensitive to damage than a wavelet coefficient line plot at a given scale as employed by others.

A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework

This paper proposes a new non-parametric method for estimating model-free, time-varying liquidity betas which builds on realized covariance and volatility theory. Working under a liquidity-adjusted CAPM framework we provide evidence that liquidity risk is a factor priced in the Greek stock market, mainly arising from the covariation of individual liquidity with local market liquidity, however, the level of liquidity seems to be an irrelevant variable in asset pricing. Our findings provide support to the notion that liquidity shocks transmitted across securities can cause market-wide effects and can have important implications for portfolio diversification strategies. ©2012 Elsevier B.V. All rights reserved.

Robust Audio-Visual Speech Recognition under Noisy Audio-Video Conditions

This paper presents the maximum weighted stream posterior (MWSP) model as a robust and efficient stream integration method for audio-visual speech recognition in environments, where the audio or video streams may be subjected to unknown and time-varying corruption. A significant advantage of MWSP is that it does not require any specific measurements of the signal in either stream to calculate appropriate stream weights during recognition, and as such it is modality-independent. This also means that MWSP complements and can be used alongside many of the other approaches that have been proposed in the literature for this problem. For evaluation we used the large XM2VTS database for speaker-independent audio-visual speech recognition. The extensive tests include both clean and corrupted utterances with corruption added in either/both the video and audio streams using a variety of types (e.g., MPEG-4 video compression) and levels of noise. The experiments show that this approach gives excellent performance in comparison to another well-known dynamic stream weighting approach and also compared to any fixed-weighted integration approach in both clean conditions or when noise is added to either stream. Furthermore, our experiments show that the MWSP approach dynamically selects suitable integration weights on a frame-by-frame basis according to the level of noise in the streams and also according to the naturally fluctuating relative reliability of the modalities even in clean conditions. The MWSP approach is shown to maintain robust recognition performance in all tested conditions, while requiring no prior knowledge about the type or level of noise.

Relations Between Political Violence and Child Adjustment: a four-wave test of the role of emotional insecurity about community

This study further explored the impact of sectarian violence and children's emotional insecurity about community on child maladjustment using a 4-wave longitudinal design. The study included 999 mother-child dyads in Belfast, Northern Ireland (482 boys, 517 girls). Across the 4 waves, child mean age was 12.19 (SD = 1.82), 13.24 (SD = 1.83), 13.61 (SD = 1.99), and 14.66 years (SD = 1.96), respectively. Building on previous studies of the role of emotional insecurity in child adjustment, the current study examines within-person change in emotional insecurity using latent growth curve analyses. The results showed that children's trajectories of emotional insecurity about community were related to risk for developing conduct and emotion problems. These findings controlled for earlier adjustment problems, age, and gender, and took into account the time-varying nature of experience with sectarian violence. Discussion considers the implications for children's emotional insecurity about community for relations between political violence and children's adjustment, including the significance of trajectories of emotional insecurity over time.

In vitro mesenchymal stem cell responses on laser-welded NiTi alloy

The biocompatibility of NiTi after laser welding was studied by examining the in vitro (mesenchymal stem cell) MSC responses at different sets of time varying from early (4 to 12 h) to intermediate phases (1 and 4 days) of cell culture. The effects of physical (surface roughness and topography) and chemical (surface Ti/Ni ratio) changes as a consequence of laser welding in different regions (WZ, HAZ, and BM) on the cell morphology and cell coverage were studied. The results in this research indicated that the morphology of MSCs was affected primarily by the topographical factors in the WZ: the well-defined and directional dendritic pattern and the presence of deeper grooves. The morphology of MSCs was not significantly modulated by surface roughness. Despite the possible initial Ni release in the medium during the cell culture, no toxic effect seemed to cause to MSCs as evidenced by the success of adhesion and spreading of the cells onto different regions in the laser weldment. The good biocompatibility of the NiTi laser weldment has been firstly reported in this study.