359 resultados para signal-flow graphs
Resumo:
The gonadotropin hypothesis proposes that elevated serum gonadotropin levels may increase the risk of epithelial ovarian cancer (EOC). We have studied the effect of treating EOC cell lines (OV207 and OVCAR-3) with FSH or LH. Both gonadotropins activated the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase 1/2 (ERK1/2) pathway and increased cell migration that was inhibited by the MAPK 1 inhibitor PD98059. Both extra- and intracellular calcium ion signalling were implicated in gonadotropin-induced ERK1/2 activation as treatment with either the calcium chelator EGTA or an inhibitor of intracellular calcium release, dantrolene, inhibited gonadotropin-induced ERK1/2 activation. Verapamil was also inhibitory, indicating that gonadotropins activate calcium influx via L-type voltage-dependent calcium channels. The cAMP/protein kinase A (PKA) pathway was not involved in the mediation of gonadotropin action in these cells as gonadotropins did not increase intracellular cAMP formation and inhibition of PKA did not affect gonadotropin-induced phosphorylation of ERK1/2. Activation of ERK1/2 was inhibited by the protein kinase C (PKC) inhibitor GF 109203X as well as by the PKCδ inhibitor rottlerin, and downregulation of PKCδ was inhibited by small interfering RNA (siRNA), highlighting the importance of PKCδ in the gonadotropin signalling cascade. Furthermore, in addition to inhibition by PD98059, gonadotropin-induced ovarian cancer cell migration was also inhibited by verapamil, GF 109203X and rottlerin. Similarly, gonadotropin-induced proliferation was inhibited by PD98059, verapamil, GF 109203X and PKCδ siRNA. Taken together, these results demonstrate that gonadotropins induce both ovarian cancer cell migration and proliferation by activation of ERK1/2 signalling in a calcium- and PKCδ-dependent manner.
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This paper describes the design and implementation of a unique undergraduate program in signal processing at the Queensland University of Technology (QUT). The criteria that influenced the choice of the subjects and the laboratories developed to support them are presented. A recently established Signal Processing Research Centre (SPRC) has played an important role in the development of the signal processing teaching program. The SPRC also provides training opportunities for postgraduate studies and research.
Resumo:
The School of Electrical and Electronic Systems Engineering at Queensland University of Technology, Brisbane, Australia (QUT), offers three bachelor degree courses in electrical and computer engineering. In all its courses there is a strong emphasis on signal processing. A newly established Signal Processing Research Centre (SPRC) has played an important role in the development of the signal processing units in these courses. This paper describes the unique design of the undergraduate program in signal processing at QUT, the laboratories developed to support it, and the criteria that influenced the design.
Resumo:
The School of Electrical and Electronic Systems Engineering of Queensland University of Technology (like many other universities around the world) has recognised the importance of complementing the teaching of signal processing with computer based experiments. A laboratory has been developed to provide a "hands-on" approach to the teaching of signal processing techniques. The motivation for the development of this laboratory was the cliche "What I hear I remember but what I do I understand." The laboratory has been named as the "Signal Computing and Real-time DSP Laboratory" and provides practical training to approximately 150 final year undergraduate students each year. The paper describes the novel features of the laboratory, techniques used in the laboratory based teaching, interesting aspects of the experiments that have been developed and student evaluation of the teaching techniques
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Diesel engine fuel injector faults can lead to reduced power, increased fuel consumption and greater exhaust emission levels and if left unchecked, can eventually lead to premature engine failure. This paper provides an overview of the Diesel, or compression ignition combustion process, and of the two basic fuel injector nozzle designs used in Diesel engines, namely, the pintle-type and hole-type nozzles. Also described are some common faults associated with these two types of fuel injector nozzles and the techniques previously used to experimentally simulate these faults. This paper also presents a recent experimental campaign undertaken using two different diesel engines whereby various fuel injector nozzle faults were induced into the engines. The first series of tests was undertaken using a turbo-charged 5.9 litre; Cummins Diesel engine whist the second series of tests was undertaken using a naturally aspirated 4 cylinder, 2.216 litre, Perkins Diesel engine. Data corresponding to different injector fault conditions was captured using in-cylinder pressure, and acoustic emission transducers along with both crank-angle encoder and top-dead centre reference signals. Using averaged in-cylinder pressure signals, it was possible to qualify the severity of the faults whilst averaged acoustic emission signals were in turn, used as the basis for wavelets decomposition. Initial observations from this signal decomposition are also presented and discussed.
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Acoustic emission has been found effective in offering earlier fault detection and improving identification capabilities of faults. However, the sensors are inherently uncalibrated. This paper presents a source to sensor paths calibration technique which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time domain, time-frequency domain, and the root mean square (RMS) energy. The results reveal how the RMS energy of a source propagates to the adjacent sensors. The findings lead to allocate the source and estimate its inferences to the adjacent sensor, and finally help to diagnose the small size diesel engines by minimising the crosstalk from multiple cylinders.
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Travel time is an important network performance measure and it quantifies congestion in a manner easily understood by all transport users. In urban networks, travel time estimation is challenging due to number of reasons such as, fluctuations in traffic flow due to traffic signals, significant flow to/from mid link sinks/sources, etc. The classical analytical procedure utilizes cumulative plots at upstream and downstream locations for estimating travel time between the two locations. In this paper, we discuss about the issues and challenges with classical analytical procedure such as its vulnerability to non conservation of flow between the two locations. The complexity with respect to exit movement specific travel time is discussed. Recently, we have developed a methodology utilising classical procedure to estimate average travel time and its statistic on urban links (Bhaskar, Chung et al. 2010). Where, detector, signal and probe vehicle data is fused. In this paper we extend the methodology for route travel time estimation and test its performance using simulation. The originality is defining cumulative plots for each exit turning movement utilising historical database which is self updated after each estimation. The performance is also compared with a method solely based on probe (Probe-only). The performance of the proposed methodology has been found insensitive to different route flow, with average accuracy of more than 94% given a probe per estimation interval which is more than 5% increment in accuracy with respect to Probe-only method.
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The purpose of the present study was to compare the effects of cold water immersion (CWI) and active recovery (ACT) on resting limb blood flow, rectal temperature and repeated cycling performance in the heat. Ten subjects completed two testing sessions separated by 1 week; each trial consisted of an initial all-out 35-min exercise bout, one of two 15-min recovery interventions (randomised: CWI or ACT), followed by a 40-min passive recovery period before repeating the 35-min exercise bout. Performance was measured as the change in total work completed during the exercise bouts. Resting limb blood flow, heart rate, rectal temperature and blood lactate were recorded throughout the testing sessions. There was a significant decline in performance after ACT (mean (SD) −1.81% (1.05%)) compared with CWI where performance remained unchanged (0.10% (0.71%)). Rectal temperature was reduced after CWI (36.8°C (1.0°C)) compared with ACT (38.3°C (0.4°C)), as was blood flow to the arms (CWI 3.64 (1.47) ml/100 ml/min; ACT 16.85 (3.57) ml/100 ml/min) and legs (CW 4.83 (2.49) ml/100 ml/min; ACT 4.83 (2.49) ml/100 ml/min). Leg blood flow at the end of the second exercise bout was not different between the active (15.25 (4.33) ml/100 ml/min) and cold trials (14.99 (4.96) ml/100 ml/min), whereas rectal temperature (CWI 38.1°C (0.3°C); ACT 38.8°C (0.2°C)) and arm blood flow (CWI 20.55 (3.78) ml/100 ml/min; ACT 23.83 (5.32) ml/100 ml/min) remained depressed until the end of the cold trial. These findings indicate that CWI is an effective intervention for maintaining repeat cycling performance in the heat and this performance benefit is associated with alterations in core temperature and limb blood flow.
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Background: High-flow nasal cannulae (HFNC) create positive oropharyngeal airway pressure but it is unclear how their use affects lung volume. Electrical impedance tomography (EIT) allows assessment of changes in lung volume by measuring changes in lung impedance. Primary objectives were to investigate the effects of HFNC on airway pressure (Paw) and end-expiratory lung volume (EELV), and to identify any correlation between the two. Secondary objectives were to investigate the effects of HFNC on respiratory rate (RR), dyspnoea, tidal volume and oxygenation; and the interaction between body mass index (BMI) and EELV. Methods: Twenty patients prescribed HFNC post-cardiac surgery were investigated. Impedance measures, Paw, PaO2/FiO2 ratio, RR and modified Borg scores were recorded first on low flow oxygen (nasal cannula or Hudson face mask) and then on HFNC. Results: A strong and significant correlation existed between Paw and end-expiratory lung impedance (EELI) (r=0.7, p<0.001). Compared with low flow oxygen, HFNC significantly increased EELI by 25.6% (95% CI 24.3, 26.9) and Paw by 3.0 cmH2O (95% CI 2.4, 3.7). RR reduced by 3.4 breaths per minute (95% CI 1.7, 5.2) with HFNC use, tidal impedance variation increased by 10.5% (95% CI 6.1, 18.3) and PaO2/FiO2 ratio improved by 30.6 mmHg (95% CI 17.9, 43.3). HFNC improved subjective dyspnoea scoring (p=0.023). Increases in EELI were significantly influenced by BMI, with larger increases associated with higher BMIs (p<0.001). Conclusions: This study suggests that HFNC improve dyspnoea and oxygenation by increasing both EELV and tidal volume, and are most beneficial in patients with higher BMIs.
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The phase of an analytic signal constructed from the autocorrelation function of a signal contains significant information about the shape of the signal. Using Bedrosian's (1963) theorem for the Hilbert transform it is proved that this phase is robust to multiplicative noise if the signal is baseband and the spectra of the signal and the noise do not overlap. Higher-order spectral features are interpreted in this context and shown to extract nonlinear phase information while retaining robustness. The significance of the result is that prior knowledge of the spectra is not required.