953 resultados para Active Noise Control
Resumo:
Hypercoiling polymers can be suited for application to living systems because they are similar in structure to the protein-based lipid assemblies found at fluid interfaces within the body. This leads to a range of exciting possibilities, not only in membrane transport applications but also in biosensors, drug delivery and mechanistic studies of biological membrane function. This study is focused in the study of the stability and suitability of nanostructures made of a hypercoiling polymer for drug delivery applications. The polymer poly (styrene-maleic acid) (PSMA) was combined with the phospholipid dimyristoylphosphatidylcholine (DMPC) to form amphiphilic nanostructures. The stability and suitability of these polymer-phospholipid nanocarriers for hydrophobic and hydrophilic molecules load and release was analyzed by several techniques. It was found that several of the studied molecules had a substantial effect on the surface charge and stability of the nanocarrier. It was also demonstrated that two types of nanocarriers, chemically modified and unmodified, were able to control the release of the molecules, especially in the case of hydrophobic compounds. In addition, as the hydrophobicity increased the release slowed down. These clear nanocarriers have the potential to behave very favorably at interfaces such as the tear lipid film were transparency is a requirement, giving a new way of controlled drug release in the eye.
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Synchronous, time-resolved DRIFTS/MS/XAS cycling studies of the vapor-phase selective aerobic oxidation of crotyl alcohol over nanoparticulate Pd have revealed surface oxide as the desired catalytically active phase, with dynamic, reaction-induced Pd redox processes controlling selective versus combustion pathways.
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This paper is concerned with synchronization of complex stochastic dynamical networks in the presence of noise and functional uncertainty. A probabilistic control method for adaptive synchronization is presented. All required probabilistic models of the network are assumed to be unknown therefore estimated to be dependent on the connectivity strength, the state and control values. Robustness of the probabilistic controller is proved via the Liapunov method. Furthermore, based on the residual error of the network states we introduce the definition of stochastic pinning controllability. A coupled map lattice with spatiotemporal chaos is taken as an example to illustrate all theoretical developments. The theoretical derivation is complemented by its validation on two representative examples.
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In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the probabilistic models of both the forward and inverse dynamics are estimated such that they are dependent on the state and the control input. The optimal control strategy is then derived which minimizes uncertainty of the closed loop system. In the absence of reliable plant models, the proposed control algorithm incorporates uncertainties in model parameters, observations, and latent processes. The local stability of the closed loop system has been established. The efficacy of the control algorithm is demonstrated on two nonlinear stochastic control examples with additive and multiplicative noise.
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Baker and Meese (2012) (B&M) provided an empirically driven criticism of the use of two-dimensional (2D) pixel noise in equivalent noise (EN) experiments. Their main objection was that in addition to injecting variability into the contrast detecting mechanisms, 2D noise also invokes gain control processes from a widely tuned contrast gain pool (e.g., Foley, 1994). B&M also developed a zero-dimensional (0D) noise paradigm in which all of the variance is concentrated in the mechanisms involved in the detection process. They showed that this form of noise conformed much more closely to expectations than did a 2D variant.
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Cyclooxygenase 2 (COX2), a key regulatory enzyme of the prostaglandin/eicosanoid pathway, is an important target for anti-inflammatory therapy. It is highly induced by pro-inflammatory cytokines in a Nuclear factor kappa B (NFκB)-dependent manner. However, the mechanisms determining the amplitude and dynamics of this important pro-inflammatory event are poorly understood. Furthermore, there is significant difference between human and mouse COX2 expression in response to the inflammatory stimulus tumor necrosis factor alpha (TNFα). Here, we report the presence of a molecular logic AND gate composed of two NFκB response elements (NREs) which controls the expression of human COX2 in a switch-like manner. Combining quantitative kinetic modeling and thermostatistical analysis followed by experimental validation in iterative cycles, we show that the human COX2 expression machinery regulated by NFκB displays features of a logic AND gate. We propose that this provides a digital, noise-filtering mechanism for a tighter control of expression in response to TNFα, such that a threshold level of NFκB activation is required before the promoter becomes active and initiates transcription. This NFκB-regulated AND gate is absent in the mouse COX2 promoter, most likely contributing to its differential graded response in promoter activity and protein expression to TNFα. Our data suggest that the NFκB-regulated AND gate acts as a novel mechanism for controlling the expression of human COX2 to TNFα, and its absence in the mouse COX2 provides the foundation for further studies on understanding species-specific differential gene regulation.
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Competing approaches exist, which allow control of phase noise and frequency tuning in mode-locked lasers, but no judgement of pros and cons based on a comparative analysis was presented yet. Here, we compare results of hybrid mode-locking, hybrid mode-locking with optical injection seeding, and sideband optical injection seeding performed on the same quantum dot laser under identical bias conditions. We achieved the lowest integrated jitter of 121 fs and a record large radio-frequency (RF) tuning range of 342 MHz with sideband injection seeding of the passively mode-locked laser. The combination of hybrid mode-locking together with optical injection-locking resulted in 240 fs integrated jitter and a RF tuning range of 167 MHz. Using conventional hybrid mode-locking, the integrated jitter and the RF tuning range were 620 fs and 10 MHz, respectively. © 2014 AIP Publishing LLC.
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Signal processing is an important topic in technological research today. In the areas of nonlinear dynamics search, the endeavor to control or order chaos is an issue that has received increasing attention over the last few years. Increasing interest in neural networks composed of simple processing elements (neurons) has led to widespread use of such networks to control dynamic systems learning. This paper presents backpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodic orbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading to more efficient system control. The procedure can be applied to every point of the basin, no matter how far away from the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using a backpropagation neural network as a filter to separate and control both signals at the same time. The neural network provides more effective control, overcoming the problems that arise with control feedback methods. Control is more effective because it can be applied to the system at any point, even if it is moving away from the target state, which prevents waiting times. Also control can be applied even if there is little information about the system and remains stable longer even in the presence of random dynamic noise.
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Chaos control is a concept that recently acquiring more attention among the research community, concerning the fields of engineering, physics, chemistry, biology and mathematic. This paper presents a method to simultaneous control of deterministic chaos in several nonlinear dynamical systems. A radial basis function networks (RBFNs) has been used to control chaotic trajectories in the equilibrium points. Such neural network improves results, avoiding those problems that appear in other control methods, being also efficient dealing with a relatively small random dynamical noise.
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Theoretical developments on pinning control of complex dynamical networks have mainly focused on the deterministic versions of the model dynamics. However, the dynamical behavior of most real networks is often affected by stochastic noise components. In this paper the pinning control of a stochastic version of the coupled map lattice network with spatiotemporal characteristics is studied. The control of these complex dynamical networks have functional uncertainty which should be considered when calculating stabilizing control signals. Two feedback control methods are considered: the conventional feedback control and modified stochastic feedback control. It is shown that the typically-used conventional control method suffers from the ignorance of model uncertainty leading to a reduction and potentially a collapse in the control efficiency. Numerical verification of the main result is provided for a chaotic coupled map lattice network. © 2011 IEEE.
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High-volume capacitance is required to buffer the power difference between the input and output ports in single-phase grid-connected photovoltaic inverters, which become an obstacle to high system efficiency and long device lifetime. Furthermore, total harmonic distortion becomes serious when the system runs into low power level. In this study, a comprehensive analysis is introduced for two-stage topology with the consideration of active power, DC-link (DCL) voltage, ripple and capacitance. This study proposed a comprehensive DCL voltage control strategy to minimise the DCL capacitance while maintaining a normal system operation. Furthermore, the proposed control strategy is flexible to be integrated with the pulse-skipping control that significantly improves the power quality at light power conditions. Since the proposed control strategy needs to vary DCL voltage, an active protection scheme is also introduced to prevent any voltage violation across the DCL. The proposed control strategy is evaluated by both simulation and experiments, whose results confirm the system effectiveness.
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This study investigated the effects of sound reduction on physiological variables in premature infants in neonatal intensive care. Ten premature infants born between 27 and 36 weeks gestation wore a specially designed earmuff cap for a 45-minute rest period. Heart rate, respiration rate, oxygen saturation level and behavioral state were measured and compared to a similar 45-minute control period without the earmuff cap. Subjects showed a significant decrease (p =.050) in mean respiration rate, and a significant increase (p $<$.02) in mean oxygen saturation level with the earmuff cap on. No significant differences were found in heart rate between the experimental condition and the control condition. Behavioral state was documented only as a potentially confounding variable, however a significant decrease (p $<$.05) in the time spent awake and a significant increase (p $<$.05) in the time spent in quiet sleep rather than active sleep occurred with the earmuff cap on. Findings suggest that noise reduction may be a viable means of increasing respiratory efficiency and the amount and quality of sleep in premature infants in neonatal intensive care.
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The use of canines as a method of detection of explosives is well established worldwide and those applying this technology range from police forces and law enforcement to humanitarian agencies in the developing world. Despite the recent surge in publication of novel instrumental sensors for explosives detection, canines are still regarded by many to be the most effective real-time field method of explosives detection. However, unlike instrumental methods, currently it is difficult to determine detection levels, perform calibration of the canines' ability or produce scientifically valid quality control checks. Accordingly, amongst increasingly strict requirements regarding forensic evidence admission such as Frye and Daubert, there is a need for better scientific understanding of the process of canine detection. ^ When translated to the field of canine detection, just like any instrumental technique, peer reviewed publication of the reliability, success and error rates, is required for admissibility. Commonly training is focussed towards high explosives such as TNT and Composition 4, and the low explosives such as Black and Smokeless Powders are added often only for completeness. ^ Headspace analyses of explosive samples, performed by Solid Phase Microextraction (SPME) paired with Gas Chromatography - Mass Spectrometry (GC-MS), and Gas Chromatography - Electron Capture Detection (GC-ECD) was conducted, highlighting common odour chemicals. The odour chemicals detected were then presented to previously trained and certified explosives detection canines, and the activity/inactivity of the odour determined through field trials and experiments. ^ It was demonstrated that TNT and cast explosives share a common odour signature, and the same may be said for plasticized explosives such as Composition C-4 and Deta Sheet. Conversely, smokeless powders were demonstrated not to share common odours. An evaluation of the effectiveness of commercially available pseudo aids reported limited success. The implications of the explosive odour studies upon canine training then led to the development of novel inert training aids based upon the active odours determined. ^
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Structural vibration control is of great importance. Current active and passive vibration control strategies usually employ individual elements to fulfill this task, such as viscoelastic patches for providing damping, transducers for picking up signals and actuators for inputting actuating forces. The goal of this dissertation work is to design, manufacture, investigate and apply a new type of multifunctional composite material for structural vibration control. This new composite, which is based on multi-walled carbon nanotube (MWCNT) film, is potentially to function as free layer damping treatment and strain sensor simultaneously. That is, the new material integrates the transducer and the damping patch into one element. The multifunctional composite was prepared by sandwiching the MWCNT film between two adhesive layers. Static sensing test indicated that the MWCNT film sensor resistance changes almost linearly with the applied load. Sensor sensitivity factors were comparable to those of the foil strain gauges. Dynamic test indicated that the MWCNT film sensor can outperform the foil strain gage in high frequency ranges. Temperature test indicated the MWCNT sensor had good temperature stability over the range of 237 K-363 K. The Young’s modulus and shear modulus of the MWCNT film composite were acquired by nanoindentation test and direct shear test, respectively. A free vibration damping test indicated that the MWCNT composite sensor can also provide good damping without adding excessive weight to the base structure. A new model for sandwich structural vibration control was then proposed. In this new configuration, a cantilever beam covered with MWCNT composite on top and one layer of shape memory alloy (SMA) on the bottom was used to illustrate this concept. The MWCNT composite simultaneously serves as free layer damping and strain sensor, and the SMA acts as actuator. Simple on-off controller was designed for controlling the temperature of the SMA so as to control the SMA recovery stress as input and the system stiffness. Both free and forced vibrations were analyzed. Simulation work showed that this new configuration for sandwich structural vibration control was successful especially for low frequency system.
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Automation of managed pressure drilling (MPD) enhances the safety and increases efficiency of drilling and that drives the development of controllers and observers for MPD. The objective is to maintain the bottom hole pressure (BHP) within the pressure window formed by the reservoir pressure and fracture pressure and also to reject kicks. Practical MPD automation solutions must address the nonlinearities and uncertainties caused by the variations in mud flow rate, choke opening, friction factor, mud density, etc. It is also desired that if pressure constraints are violated the controller must take appropriate actions to reject the ensuing kick. The objectives are addressed by developing two controllers: a gain switching robust controller and a nonlinear model predictive controller (NMPC). The robust gain switching controller is designed using H1 loop shaping technique, which was implemented using high gain bumpless transfer and 2D look up table. Six candidate controllers were designed in such a way they preserve robustness and performance for different choke openings and flow rates. It is demonstrated that uniform performance is maintained under different operating conditions and the controllers are able to reject kicks using pressure control and maintain BHP during drill pipe extension. The NMPC was designed to regulate the BHP and contain the outlet flow rate within certain tunable threshold. The important feature of that controller is that it can reject kicks without requiring any switching and thus there is no scope for shattering due to switching between pressure and flow control. That is achieved by exploiting the constraint handling capability of NMPC. Active set method was used for computing control inputs. It is demonstrated that NMPC is able to contain kicks and maintain BHP during drill pipe extension.