Hearing loss and a supportive tactile signal in a navigation system : effects on driving behavior and eye movements

An on-road study was conducted to evaluate a complementary tactile navigation signal on driving behaviour and eye movements for drivers with hearing loss (HL) compared to drivers with normal hearing (NH). 32 participants (16 HL and 16 NH) performed two preprogrammed navigation tasks. In one, participants received only visual information, while the other also included a vibration in the seat to guide them in the correct direction. SMI glasses were used for eye tracking, recording the point of gaze within the scene. Analysis was performed on predefined regions. A questionnaire examined participant's experience of the navigation systems. Hearing loss was associated with lower speed, higher satisfaction with the tactile signal and more glances in the rear view mirror. Additionally, tactile support led to less time spent viewing the navigation display.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Small signal stability analysis of power systems with high penetration of wind power

The integration of large amount of wind power into a power system imposes a new challenge for the secure and economic operation of the system. It is necessary to investigate the impacts of wind power generation on the dynamic behavior of the power system concerned. This paper investigates the impacts of large amount of wind power on small signal stability and the corresponding control strategies to mitigate the negative effects. The concepts of different types of wind turbine generators (WTGs) and the principles of the grid-connected structures of wind power generation systems are first briefly introduced. Then, the state-of-the-art of the studies on the impacts of WTGs on small signal stability as well as potential problems to be studied are clarified. Finally, the control strategies on WTGs to enhance power system damping characteristics are presented.

Impacts of different wind power generators on power system small signal and transient stability

With the ever-increasing penetration level of wind power, the impacts of wind power on the power system are becoming more and more significant. Hence, it is necessary to systematically examine its impacts on the small signal stability and transient stability in order to find out countermeasures. As such, a comprehensive study is carried out to compare the dynamic performances of power system respectively with three widely-used power generators. First, the dynamic models are described for three types of wind power generators, i. e. the squirrel cage induction generator (SCIG), doubly fed induction generator (DFIG) and permanent magnet generator (PMG). Then, the impacts of these wind power generators on the small signal stability and transient stability are compared with that of a substituted synchronous generator (SG) in the WSCC three-machine nine-bus system by the eigenvalue analysis and dynamic time-domain simulations. Simulation results show that the impacts of different wind power generators are different under small and large disturbances.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

Induction of epithelial-mesenchymal transition (EMT) in breast cancer cells is calcium signal dependent

Signals from the tumor microenvironment trigger cancer cells to adopt an invasive phenotype through epithelial-mesenchymal transition (EMT). Relatively little is known regarding key signal transduction pathways that serve as cytosolic bridges between cell surface receptors and nuclear transcription factors to induce EMT. A better understanding of these early EMT events may identify potential targets for the control of metastasis. One rapid intracellular signaling pathway that has not yet been explored during EMT induction is calcium. Here we show that stimuli used to induce EMT produce a transient increase in cytosolic calcium levels in human breast cancer cells. Attenuation of the calcium signal by intracellular calcium chelation significantly reduced epidermal growth factor (EGF)- and hypoxia-induced EMT. Intracellular calcium chelation also inhibited EGF-induced activation of signal transducer and activator of transcription 3 (STAT3), while preserving other signal transduction pathways such as Akt and extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation. To identify calcium-permeable channels that may regulate EMT induction in breast cancer cells, we performed a targeted siRNA-based screen. We found that transient receptor potential-melastatin-like 7 (TRPM7) channel expression regulated EGF-induced STAT3 phosphorylation and expression of the EMT marker vimentin. Although intracellular calcium chelation almost completely blocked the induction of many EMT markers, including vimentin, Twist and N-cadherin, the effect of TRPM7 silencing was specific for vimentin protein expression and STAT3 phosphorylation. These results indicate that TRPM7 is a partial regulator of EMT in breast cancer cells, and that other calcium-permeable ion channels are also involved in calcium-dependent EMT induction. In summary, this work establishes an important role for the intracellular calcium signal in the induction of EMT in human breast cancer cells. Manipulation of calcium-signaling pathways controlling EMT induction in cancer cells may therefore be an important therapeutic strategy for preventing metastases.

Sphingosine-1-phosphate, a novel second messenger involved in cell growth regulation and signal transduction, affects growth and invasiveness of human breast cancer cells

This review will focus on the role of sphingosine and its phosphorylated derivative sphingosine-1-phosphate (SPP) in cell growth regulation and signal transduction. We will show that many of the effects attributed to sphingosine in quiescent Swiss 3T3 fibroblasts are mediated via its conversion to SPP. We propose that SPP has appropriate properties to function as an intracellular second messenger based on the following: it elicits diverse cellular responses; it is rapidly produced from sphingosine by a specific kinase and rapidly degraded by a specific lyase; its concentration is low in quiescent cells but increases rapidly and transiently in response to the growth factors, fetal calf serum (FCS) and platelet derived growth factor (PDGF); it releases Ca2+ from internal sources in an InsP3-independent manner; and finally, it may link sphingolipid signaling pathways to cellular ras-mediated signaling pathways by elevating phosphatidic acid levels. The effects of this novel second messenger on growth, differentiation and invasion of human breast cancer cells will be discussed. © 1994 Kluwer Academic Publishers.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

Catalytic probes with nanostructured surface for gas/discharge diagnostics : a study of a probe signal behaviour

Catalytic probes are used for plasma diagnostics in order to quantify the density of neutral atoms. The probe response primarily depends on the probe material and its surface morphology. Here we report on the design, operation and modelling of the response of niobium pentoxide sensors with a flat and nanowire (NW) surfaces. These sensors were used to detect neutral oxygen atoms in the afterglow region of an inductively coupled rf discharge in oxygen. A very different response of the flat-surface and NW probes to the varying densities of oxygen atoms was explained by modelling heat conduction and taking into account the associated temperature gradients. It was found that the nanostructure probe can measure in a broader range than the flat oxide probe due to an increase in the surface to volume ratio, and the presence of nanostructures which act as a thermal barrier against sensor overheating. These results can be used for the development of the new generation of catalytic probes for gas/discharge diagnostics in a range of industrial and environmental applications.

Stop-signal task difficulty and the right inferior frontal gyrus

The stop-signal paradigm is increasingly being used as a probe of response inhibition in basic and clinical neuroimaging research. The critical feature of this task is that a cued response is countermanded by a secondary ‘stop-signal’ stimulus offset from the first by a ‘stop-signal delay’. Here we explored the role of task difficulty in the stop-signal task with the hypothesis that what is critical for successful inhibition is the time available for stopping, that we define as the difference between stop-signal onset and the expected response time (approximated by reaction time from previous trial). We also used functional magnetic resonance imaging (fMRI) to examine how the time available for stopping affects activity in the putative right inferior frontal gyrus and presupplementary motor area (right IFG-preSMA) network that is known to support stopping. While undergoing fMRI scanning, participants performed a stop-signal variant where the time available for stopping was kept approximately constant across participants, which enabled us to compare how the time available for stopping affected stop-signal task difficulty both within and between subjects. Importantly, all behavioural and neuroimaging data were consistent with previous findings. We found that the time available for stopping distinguished successful from unsuccessful inhibition trials, was independent of stop-signal delay, and affected successful inhibition depending upon individual SSRT. We also found that right IFG and adjacent anterior insula were more strongly activated during more difficult stopping. These findings may have critical implications for stop-signal studies that compare different patient or other groups using fixed stop-signal delays.

Stop-signal response inhibition in schizophrenia : Behavioural, event-related potential and functional neuroimaging data

Inhibitory control deficits are well documented in schizophrenia, supported by impairment in an established measure of response inhibition, the stop-signal reaction time (SSRT). We investigated the neural basis of this impairment by comparing schizophrenia patients and controls matched for age, sex and education on behavioural, functional magnetic resonance imaging (fMRI) and event-related potential (ERP) indices of stop-signal task performance. Compared to controls, patients exhibited slower SSRT and reduced right inferior frontal gyrus (rIFG) activation, but rIFG activation correlated with SSRT in both groups. Go stimulus and stop-signal ERP components (N1/P3) were smaller in patients, but the peak latencies of stop-signal N1 and P3 were also delayed in patients, indicating impairment early in stop-signal processing. Additionally, response-locked lateralised readiness potentials indicated response preparation was prolonged in patients. An inability to engage rIFG may predicate slowed inhibition in patients, however multiple spatiotemporal irregularities in the networks underpinning stop-signal task performance may contribute to this deficit.