Interaction of metal salts with cytoskeletal motor protein systems

Interactions of chemicals with the microtubular network of cells may lead to genotoxicity. Micronuclei (MN) might be caused by interaction of metals with tubulin and/or kinesin. The genotoxic effects of inorganic lead and mercury salts were studied using the MN assay and the CREST analysis in V79 Chinese hamster fibroblasts. Effects on the functional activity of motor protein systems were examined by measurement of tubulin assembly and kinesin-driven motility. Lead and mercury salts induced MN dose-dependently. The no-effect-concentration for MN induction was 1.1 μM PbCl2, 0.05 μM Pb(OAc)2 and 0.01 μM HgCl2. The in vitro results obtained for PbCl2 correspond to reported MN induction in workers occupationally exposed to lead, starting at 1.2 μM Hg(II) (Vaglenov et al., 2001, Environ. Health Perspect. 109, 295-298). The CREST Analysis indicate aneugenic effects of Pb(II) and aneugenic and additionally clastogenic effects of Hg(II). Lead (chloride, acetate, and nitrate) and mercury (chloride and nitrate) interfered dose-dependently with tubulin assembly in vitro. The no-effect-concentration for lead salts in this assay was 10 μM. Inhibition of tubulin assembly by mercury started at 2 μM. The gliding velocity of microtubules along immobilised kinesin molecules was affected by 25 μM Pb(NO3)2 and 0.1 μM HgCl2 in a dose-dependent manner. Our data support the hypothesis that lead and mercury genotoxicity may result, at least in part, via disturbance of chromosome segregation via interaction with cytoskeletal proteins.

Observing the mother-infant feeding interaction

Early parenting is critical to effective attachment and a range of positive developmental outcomes for children. Feeding is a key task of early parenting and increasing evidence indicates that early feeding practices are important for the development of self-regulation of intake and food preferences which in turn are predictors of later obesity risk. However, relatively little is known about the mother-infant interaction at the transition to solids among typically developing children. This study aimed to describe parenting strategies used by mothers at the transition from milk feeding to solid food. Twenty mother-infant dyads were video-taped during a feeding interaction and data was analysed to describe maternal use of parenting strategies. It was predicted that positive feeding strategies would be correlated with lower levels of Infant Food Refusal (IFR), higher maternal sensitivity, and better overall parenting scores. The opposite was predicted for negative feeding strategies. It was found that positive strategy use and general parenting scores were significantly correlated in the predicted direction, however maternal instruction, aversive contact and ineffective strategy use were significantly correlated with and predictive of IFR. Additionally, it was hypothesised that maternal strategy use would deteriorate towards the end of the interaction, and this hypothesis was partially supported: significantly more negative strategy use was observed in the last third of the interaction, whilst positive strategy use remained consistent through the feeding interaction. The findings have important implications for early feeding parent education and intervention programs.

Faster parameter estimation using risk-sensitive filters

In this paper, we propose a risk-sensitive approach to parameter estimation for hidden Markov models (HMMs). The parameter estimation approach considered exploits estimation of various functions of the state, based on model estimates. We propose certain practical suboptimal risk-sensitive filters to estimate the various functions of the state during transients, rather than optimal risk-neutral filters as in earlier studies. The estimates are asymptotically optimal, if asymptotically risk neutral, and can give significantly improved transient performance, which is a very desirable objective for certain engineering applications. To demonstrate the improvement in estimation simulation studies are presented that compare parameter estimation based on risk-sensitive filters with estimation based on risk-neutral filters.

Short-data recursive HMM parameter estimation for rapid vision-based aircraft heading estimation

Rapid recursive estimation of hidden Markov Model (HMM) parameters is important in applications that place an emphasis on the early availability of reasonable estimates (e.g. for change detection) rather than the provision of longer-term asymptotic properties (such as convergence, convergence rate, and consistency). In the context of vision- based aircraft (image-plane) heading estimation, this paper suggests and evaluates the short-data estimation properties of 3 recursive HMM parameter estimation techniques (a recursive maximum likelihood estimator, an online EM HMM estimator, and a relative entropy based estimator). On both simulated and real data, our studies illustrate the feasibility of rapid recursive heading estimation, but also demonstrate the need for careful step-size design of HMM recursive estimation techniques when these techniques are intended for use in applications where short-data behaviour is paramount.

Comparison of the gate drive parameter space for driving power MOSFETs using conventional and cascode configurations

Conventional voltage driven gate drive circuits utilise a resistor to control the switching speed of power MOS-FETs. The gate resistance is adjusted to provide controlled rate of change of load current and voltage. The cascode gate drive configuration has been proposed as an alternative to the conventional resistor-fed gate drive circuit. While cascode drive is broadly understood in the literature the switching characteristics of this topology are not well documented. This paper explores, through both simulation and experimentation, the gate drive parameter space of the cascode gate drive configuration and provides a comparison to the switching characteristics of conventional gate drive.

Spatially varying ground motion effects on seismic response of adjacent structures considering soil-structure interaction

Spatial variation of seismic ground motions is caused by incoherence effect, wave passage, and local site conditions. This study focuses on the effects of spatial variation of earthquake ground motion on the responses of adjacent reinforced concrete (RC) frame structures. The adjacent buildings are modeled considering soil-structure interaction (SSI) so that the buildings can be interacted with each other under uniform and non-uniform ground motions. Three different site classes are used to model the soil layers of SSI system. Based on fast Fourier transformation (FFT), spatially correlated non-uniform ground motions are generated compatible with known power spectrum density function (PSDF) at different locations. Numerical analyses are carried out to investigate the displacement responses and the absolute maximum base shear forces of adjacent structures subjected to spatially varying ground motions. The results are presented in terms of related parameters affecting the structural response using three different types of soil site classes. The responses of adjacent structures have changed remarkably due to spatial variation of ground motions. The effect can be significant on rock site rather than clay site.

Soil–pile interaction of pile embedded in deep-layered marine sediment under seismic excitation

This paper investigates the soil–pile interaction of a pile embedded in a deep multi-layered soil under seismic excitation considering both kinematic and inertial interaction effects. A comprehensive three-dimensional finite element model is developed and validated using existing results in the literature. The response of the pile in the deep multi-layered soil profile is investigated with respect to pile head response, deflection modes and maximum deflections along the pile. Results show that the pile exhibits complex deflection patterns and that the pile response is influenced by the properties of both the soil profile and the seismic excitation. It is also evident that kinematic interaction effects have a greater influence on the pile response than the inertial interaction effects.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Interaction of erythrocyte eicosapentaenoic acid and physical activity predicts reduced risk of mild cognitive impairment

Objectives To evaluate relationships between self-reported physical activity, proportions of long-chain omega-3 polyunsaturated fatty acids (LCn3) in erythrocyte content (percentage of total fatty acids) and risk of mild cognitive impairment (MCI) in older adults. Method A cross-sectional study was conducted. Community-dwelling male and female (n = 84) participants over the age of 65 years with and without MCI were tested for erythrocyte proportions of the LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Physical activity was measured using a validated questionnaire. Results The interaction between erythrocyte EPA, but not DHA, and increased physical activity was associated with increased odds of a non-MCI classification. Conclusion An interaction between physical activity and erythrocyte EPA content (percentage of fatty acids) significantly predicted MCI status in older adults. Randomised control trials are needed to examine the potential for supplementation with EPA in combination with increased physical activity to mitigate the risk of MCI in ageing adults.