30 resultados para Dynamic analysis

em Deakin Research Online - Australia


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Quantification of programmed and accidental cell death provides useful end-points for the anticancer drug efficacy assessment. Cell death is, however, a stochastic process. Therefore, the opportunity to dynamically quantify individual cellular states is advantageous over the commonly employed static, end-point assays. In this work, we describe the development and application of a microfabricated, dielectrophoretic (DEP) cell immobilization platform for the realtime analysis of cancer drug-induced cytotoxicity. Microelectrode arrays were designed to generate weak electro-thermal vortices that support efficient drug mixing and rapid cell immobilization at the delta-shape regions of strong electric field formed between the opposite microelectrodes. We applied this technology to the dynamic analysis of hematopoietic tumor cells that represent a particular challenge for real-time imaging due to their dislodgement during image acquisition. The present study was designed to provide a comprehensive mechanistic rationale for accelerated cell-based assays on DEP chips using real-time labeling with cell permeability markers. In this context, we provide data on the complex behavior of viable vs dying cells in the DEP fields and probe the effects of DEP fields upon cell responses to anticancer drugs and overall bioassay performance. Results indicate that simple DEP cell immobilization technology can be readily applied for the dynamic analysis of investigational drugs in hematopoietic cancer cells. This ability is of particular importance in studying the outcome of patient derived cancer cells, when exposed to therapeutic drugs, as these cells are often rare and difficult to collect, purify and immobilize.

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Electroactive polymers have attracted considerable attention in recent years due to their sensing and actuating properties which make them a material of choice for a wide range of applications including sensors, biomimetic robots, and biomedical micro devices. This paper presents an effective modeling strategy for nonlinear large deformation (small strains and moderate rotations) dynamic analysis of polymer actuators. Considering that the complicated electro-chemo-mechanical dynamics of these actuators is a drawback for their application in functional devices, establishing a mathematical model which can effectively predict the actuator's dynamic behavior can be of paramount importance. To effectively predict the actuator's dynamic behavior, a comprehensive mathematical model is proposed correlating the input voltage and the output bending displacement of polymer actuators. The proposed model, which is based on the rigid finite element (RFE) method, consists of two parts, namely electrical and mechanical models. The former is comprised of a ladder network of discrete resistive-capacitive components similar to the network used to model transmission lines, while the latter describes the actuator as a system of rigid links connected by spring-damping elements (sdes). Both electrical and mechanical components are validated through experimental results.

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Bone is known to adapt to the prevalent strain environment while the variation in strains, e.g., due to mechanical loading, modulates bone remodeling, and modeling. Dynamic strains rather than static strains provide the primary stimulus of bone functional adaptation. The finite element method can be generally used for estimating bone strains, but it may be limited to the static analysis of bone strains since the dynamic analysis requires expensive computation. Direct in vivo strain measurement, in turn, is an invasive procedure, limited to certain superficial bone sites, and requires surgical implementation of strain gauges and thus involves risks (e.g., infection). Therefore, to overcome difficulties associated with the finite element method and the in vivo strain measurements, the flexible multibody simulation approach has been recently introduced as a feasible method to estimate dynamic bone strains during physical activity. The purpose of the present study is to further strengthen the idea of using the flexible multibody approach for the analysis of dynamic bone strains. Besides discussing the background theory, magnetic resonance imaging is integrated into the flexible multibody approach framework so that the actual bone geometry could be better accounted for and the accuracy of prediction improved.

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Flood inundation is a common natural disaster and a growing development challenge for many cities and thousands of small towns around the world. Soil features have frequently altered with the rapid development of urbanised regions, which has led to more frequent and longer duration of flooding in urban flood-prone regions. Thus, this paper presents a geographic information system (GIS)-based methodology for measuring and visualising the effects on urban flash floods generated by land-use changes over time. The measurement is formulated with a time series in order to perform a dynamic analysis. A catchment mesh is introduced into a hydrological model for reflecting the spatial layouts of infrastructure and structures over different construction periods. The Geelong Waurn Ponds campus of Deakin University is then selected as a case study. Based on GIS simulation and mapping technologies, this research illustrates the evolutionary process of flash floods. The paper then describes flood inundation for different built environments and presents a comparison by quantifying the flooding extents for infrastructure and structures. The results reveal that the GIS-based estimation model can examine urban flash floods in different development phases and identify the change of flooding extents in terms of land-use planning. This study will bring benefits to urban planners in raising awareness of flood impact and the approach proposed here could be used for flood mitigation through future urban planning.

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Purpose – The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

Design/methodology/approach – The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short-term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

Findings –
The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre-shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

Practical implications –
The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

Originality/value – For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

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The present paper uses a dynamic open-economy model with wage indexation to examine the impact of tourism on employment and welfare. Both short-run and long-run situations are analysed. It is well known that tourism converts non-traded goods into tradable goods. An increase in the demand for a non-traded good raises its relative price, which results in an expansion of the non-traded sector at the expense of the traded goods sector. This output shift raises labour employment in the short run. However, in the long run, the higher relative price leads to higher wages, resulting in a negative impact on labour employment. If the output effect is dominant, the expansion in tourism raises employment and welfare. However, under realistic conditions tourism may lower both labour employment and welfare due to rising costs. These results are demonstrated by simulating a dynamic model for the case of Hong Kong.

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Ionic polymer conductive network composite (IPCNC) actuators are a class of electroactive polymer composites that exhibit some interesting electromechanical characteristics such as low voltage actuation, large displacements, and benefit from low density and elastic modulus. Thus, these emerging materials have potential applications in biomimetic and biomedical devices. Whereas significant efforts have been directed toward the development of IPMC actuators, the establishment of a proper mathematical model that could effectively predict the actuators' dynamic behavior is still a key challenge. This paper presents development of an effective modeling strategy for dynamic analysis of IPCNC actuators undergoing large bending deformations. The proposed model is composed of two parts, namely electrical and mechanical dynamic models. The electrical model describes the actuator as a resistive-capacitive (RC) transmission line, whereas the mechanical model describes the actuator as a system of rigid links connected by spring-damping elements. The proposed modeling approach is validated by experimental data, and the results are discussed. © 2014 Elsevier B.V. All rights reserved.

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Ionic polymers have attracted considerable attention due to their interesting sensing and actuating behavior which make them a proper choice for use in a wide range of applications including biomimetic robots and biomedical devices. The complicated electro-chemo-mechanical dynamics of ionic polymer actuators is a drawback for their applications in functional devices. Therefore, establishing a mathematical model which could effectively predict the actuators' dynamic behavior is of great interest. In this paper, a mathematical model, named equivalent dynamic thermoviscoelastic (EDT) model, based on thermal analogy and beam theory is proposed for dynamic analysis of bending-type ionic polymer actuators. Then, the developed model is extended for analyzing the performance of the actuator in finite element software. The finite element analysis of the actuator enables consideration of material and geometric nonlinearities and facilitates modeling of functional devices based on the ionic polymer actuators. The proposed modeling approach is validated using experimental data.

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Some aspects of numerical simulation of Lamb wave propagation in composite laminates using the finite element models with explicit dynamic analysis are addressed in this study. To correctly and efficiently describe the guided-wave excited/received by piezoelectric actuators/sensors, effective models of surface-bounded flat PZT disks based on effective force, moment and displacement are developed. Different finite element models for Lamb wave excitation, collection and propagation in isotropic plate and quasi-isotropic laminated composite are evaluated using continuum elements (3-D solid element) and structural elements (3-D shell element), to elaborate the validity and versatility of the proposed actuator/sensor models.

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Laser shock peening (LSP) is an innovative surface treatment technique for metal alloys, with the great improvement of their fatigue, corrosion and wear resistance performance. Finite element method has been widely applied to simulate the LSP to provide the theoretically predictive assessment and optimally parametric design. In the current work, 3-D numerical modelling approaches, combining the explicit dynamic analysis, static equilibrium analysis algorithms and different plasticity models for the high strain rate exceeding 106s-1, are further developed. To verify the proposed methods, 3-D static and dynamic FEA of AA7075-T7351 rods subject to two-sided laser shock peening are performed using the FEA package–ABAQUS. The dynamic and residual stress fields, shock wave propagation and surface deformation of the treated metal from different material modelling approaches have a good agreement.

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The scheduling of metal to different casters in a casthouse is a complicated problem, attempting to find the balance between pot-line, crucible carrier, furnace and casting machine capacity. in this paper, a description will be given of a casthouse modelling system designed to test different scenarios for casthouse design and operation. Using discrete-event simulation, the casthouse model incorporates variable arrival times of metal carriers, crucible movements, caster operation and furnace conditions. Each part of the system is individually modelled and synchronised using a series of signals or semaphores. in addition, an easy to operate user interface allows for the modification of key parameters, and analysis of model output. Results from the model will be presented for a case study, which highlights the effect different parameters have on overall casthouse performance. The case study uses past production data from a casthouse to validate the model outputs, with the aim to perform a sensitivity analysis on the overall system. Along with metal preparation times and caster strip-down/setup, the temperature evolution within the furnaces is one key parameter in determining casthouse performance.

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In statistical classification work, one method of speeding up the process is to use only a small percentage of the total parameter set available. In this paper, we apply this technique both to the classification of malware and the identification of malware from a set combined with cleanware. In order to demonstrate the usefulness of our method, we use the same sets of malware and cleanware as in an earlier paper. Using the statistical technique Information Gain (IG), we reduce the set of features used in the experiment from 7,605 to just over 1,000. The best accuracy obtained in the former paper using 7,605 features is 97.3% for malware versus cleanware detection and 97.4% for malware family classification; on the reduced feature set, we obtain a (best) accuracy of 94.6% on the malware versus cleanware test and 94.5% on the malware classification test. An interesting feature of the new tests presented here is the reduction in false negative rates by a factor of about 1/3 when compared with the results of the earlier paper. In addition, the speed with which our tests run is reduced by a factor of approximately 3/5 from the times posted for the original paper. The small loss in accuracy and improved false negative rate along with significant improvement in speed indicate that feature reduction should be further pursued as a tool to prevent algorithms from becoming intractable due to too much data.