994 resultados para ULTRASOUND-ENHANCED THROMBOLYSIS


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Ability to control the properties of single-wall nanotubes produced in the arc discharge is important for many practical applications. Our experiments suggest that the length and purity of single-wall nanotubes significantly increase when the magnetic field is applied to the arc discharge. A model of a single wall carbon nanotube interaction and growth in the thermal plasma was developed which considers several important effects such as anode ablation that supplies the carbon plasma in an anodic arc discharge technique, and the momentum, charge and energy transfer processes between nanotube and plasma. The numerical simulations based on Monte-Carlo technique were performed, which explain an increase of the nanotubes produced in the magnetic field - enhanced arc discharge.

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The results of 1D simulation of nanoparticle dynamics in the areas adjacent to nanostructured carbon-based films exposed to chemically active complex plasma of CH4 + H2 + Ar gas mixtures are presented. The nanoparticle-loaded near-substrate (including sheath and presheath) areas of a low-frequency (0.5 MHz) inductively coupled plasma facility for the PECVD growth of the ordered carbon-based nanotip structures are considered. The conditions allowing one to predict the size of particles that can pass through the plasma sheath and softly land onto the surface are formulated. The possibility of soft nano-cluster deposition without any additional acceleration common for some existing nano-cluster deposition schemes is demonstrated. The effect of the substrate heating power and the average atomic mass of neutral species is studied numerically and verified experimentally.

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This paper reports on the efficient deposition of hydrogenated diamond-like carbon (DLC) film in a plasma reactor that features both the capacitively and inductively coupled operation regimes. The hydrogenated DLC films have been prepared on silicon wafers using a low-frequency (500 kHz) inductively coupled plasma (ICP) chemical vapor deposition (CVD) system. At low RF powers, the system operates as an asymmetric capacitively coupled plasma source, and the film deposition process is undertaken in the electrostatic (E) discharge regime. Above the mode transition threshold, the high-density inductively coupled plasma is produced in the electromagnetic (H) discharge regime. It has been shown that the deposition rate and hardness of the DLC film are much higher in the H-mode deposition regime. For a 2.66-Pa H-mode CH4 + Ar gas mixture discharge, the deposited DLC film exhibits a mechanical hardness of 18 GPa, Young's modulus of 170 GPa, and compressive stress of 1.3 GPa.

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Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

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Graphene has received great interest from researchers all over the world owing to its unique properties. Much of the excitement surrounding graphene is due to its remarkable properties and inherent quantum effects. These effects and properties make it a desirable material for the fabrication of new devices. Graphene has a plethora of potential uses including gas and molecular sensors, electronics, spintronics and optics [1-7]. Interestingly, some of these properties have been known about since before the material was even isolated due to a considerable amount of theoretical work and simulations. The material was to some extent a condensed matter modelers "toy" as it was used as a benchmark 2D material Graphene had been used for a long time as the fundamental building block of many other carbon structures...

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We present a theoretical model describing a plasma-assisted growth of carbon nanofibers (CNFs), which involves two competing channels of carbon incorporation into stacked graphene sheets: via surface diffusion and through the bulk of the catalyst particle (on the top of the nanofiber), accounting for a range of ion- and radical-assisted processes on the catalyst surface. Using this model, it is found that at low surface temperatures, Ts, the CNF growth is indeed controlled by surface diffusion, thus quantifying the semiempirical conclusions of earlier experiments. On the other hand, both the surface and bulk diffusion channels provide a comparable supply of carbon atoms to the stacked graphene sheets at elevated synthesis temperatures. It is also shown that at low Ts, insufficient for effective catalytic precursor decomposition, the plasma ions play a key role in the production of carbon atoms on the catalyst surface. The model is used to compute the growth rates for the two extreme cases of thermal and plasma-enhanced chemical vapor deposition of CNFs. More importantly, these results quantify and explain a number of observations and semiempirical conclusions of earlier experiments.

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Structural defects inevitably appear during the nucleation event that determines the structure and properties of single-walled carbon nanotubes. By combining ion bombardment experiments with atomistic simulations we reveal that ion bombardment in a suitable energy range allows these defects to be healed resulting in an enhanced nucleation of the carbon nanotube cap. The enhanced growth of the nanotube cap is explained by a nonthermal ion-induced graphene network restructuring mechanism.

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Handover performance is critical to support real-time traffic applications in wireless network communications. The longer the handover delay is, the longer an Mobile Node (MN) is prevented from sending and receiving any data packet. In real-time network communication applications, such as VoIP and video-conference, a long handover delay is often unacceptable. In order to achieve better handover performance, Fast Proxy Mobile IPv6 (FPMIPv6) has been standardised as an improvement to the original Proxy Mobile IPv6 (PMIPv6) in the Internet Engineering Task Force (IETF). The FPMIPv6 adopts a link layer triggering mechanism to perform two modes of operation: predictive and reactive modes. Using the link layer triggering, the handover performance of the FPMIPv6 can be improved in the predictive mode. However, an unsuccessful predictive handover operation will lead to activation of a reactive handover. In the reactive mode, MNs still experience long handover delays and a large amount of packet loss, which significantly degrade the handover performance of the FPMIPv6. Addressing this problem, this thesis presents an Enhanced Triggering Mechanism (ETM) in the FPMIPv6 to form an enhanced FPMIPv6 (eFPMIPv6). The ETM reduces the most time consuming processes in the reactive handover: the failed Handover Initiate (HO-Initiate) delay and bidirectional tunnel establishment delay. Consequently, the overall handover performance of the FPMIPv6 is enhanced in the eFPMIPv6. To show the advantages of the proposed eFPMIPv6, a theoretical analysis is carried out to mathematically model the performance of PMIPv6, FPMIPv6 and eFPMIPv6. Extensive case studies are conducted to validate the effectiveness of the presented eFPMIPv6 mechanism. They are carried out under various scenarios with changes in network link delay, traffic load, number of hops and MN moving velocity. The case studies show that the proposed mechanism ETM reduces the reactive handover delay, and the presented eFPMIPv6 outperforms the PMIPv6 and FPMIPv6 in terms of the overall handover performance.

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This project was a preliminary step towards the development of novel methods for early stage cancer diagnosis and treatment. Diagnostic imaging agents with high Raman signal enhancement were developed based on tailored assemblies of gold nanoparticles, which demonstrated potential for non-invasive detection from deep under the skin surface. Specifically designed polymers were employed to assemble gold nanoparticles into controlled morphologies including dimers, nanochains, nanoplates, globular and core-satellite nanostructures. Our findings suggest that the Raman enhancement is strongly dependent on assembly morphology and can be tuned to adapt to the requirements of the diagnostic agent.

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The surface enhanced Raman scattering effect has shown immense potential for detecting trace amounts of explosive vapor molecules. To date, efforts to produce a commercially available, reliable SERS sensor have been impeded by an inability to separate the electromagnetic enhancement produced by the metallic nanostructure from other signal enhancing effects. Here, we show a new Raman sensor that uses surface acoustic waves (SAWs) to produce controllable surface structures on gold films deposited on LiNbO3 substrates that modulate the Raman signal of a target compound (thiophenol) adsorbed on the films. We demonstrate that this sensor can dynamically control the Raman signal simply by changing the SAW’s amplitude, allowing the Raman signal enhancement factor to be directly measured with no variation in the concentration of the target compound. The physically adsorbed molecules can be removed from the sensor without physical cleaning or damage, making it possible to reuse it for real-time Raman detection.

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Reputation systems are employed to provide users with advice on the quality of items on the Web, based on the aggregated value of user-based ratings. Recommender systems are used online to suggest items to users according to the users, expressed preferences. Yet, recommender systems will endorse an item regardless of its reputation value. In this paper, we report the incorporation of reputation models into recommender systems to enhance the accuracy of recommendations. The proposed method separates the implementation of recommender and reputation systems for generality. Our experiment showed that the proposed method could enhance the accuracy of existing recommender systems.