28 resultados para best-response dynamics

em Aston University Research Archive


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This study used magnetoencephalography (MEG) to examine the dynamic patterns of neural activity underlying the auditory steady-state response. We examined the continuous time-series of responses to a 32-Hz amplitude modulation. Fluctuations in the amplitude of the evoked response were found to be mediated by non-linear interactions with oscillatory processes both at the same source, in the alpha and beta frequency bands, and in the opposite hemisphere. © 2005 Elsevier Ireland Ltd. All rights reserved.

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PURPOSE. To compare the objective accommodative amplitude and dynamics of eyes implanted with the one-compartment-unit (1CU; HumanOptics AG, Erlangen, Germany) accommodative intraocular lenses (IOLs) with that measured subjectively. METHODS. Twenty eyes with a 1CU accommodative IOL implanted were refracted and distance and near acuity measured with a logMAR (logarithm of the minimum angle of resolution) chart. The objective accommodative stimulus-response curve for static targets between 0.17 and 4.00 D accommodative demand was measured with the SRW-5000 (Shin-Nippon Commerce Inc., Tokyo, Japan) and PowerRefractor (PlusOptiX, Nürnberg, Germany) autorefractors. Continuous objective recording of dynamic accommodation was measured with the SRW-5000, with the subject viewing a target moving from 0 to 2.50 D at 0.3 Hz through a Badal lens system. Wavefront aberrometry measures (Zywave; Bausch & Lomb, Rochester, NY) were made through undilated pupils. Subjective amplitude of accommodation was measured with the RAF (Royal Air Force accommodation and vergence measurement) rule. RESULTS. Four months after implantation best-corrected acuity was -0.01 ± 0.16 logMAR at distance and 0.60 ± 0.09 logMAR at near. Objectively, the static amplitude of accommodation was 0.72 ± 0.38 D. The average dynamic amplitude of accommodation was 0.71 ± 0.47 D, with a lag behind the target of 0.50 ± 0.48 seconds. Aberrometry showed a decrease in power of the lens-eye combination from the center to the periphery in all subjects (on average, -0.38 ± 0.28 D/mm). Subjective amplitude of accommodation was 2.24 ± 0.42 D. Two years after 1CU implantation, refractive error and distance visual acuity remained relatively stable, but near visual acuity, and the subjective and objective amplitudes of accommodation decreased. CONCLUSIONS. The objective accommodating effects of the 1CU lens appear to be limited, although patients are able to track a moving target. Subjective and objective accommodation was reduced at the 2-year follow-up. The greater subjective amplitude of accommodation is likely to result from the eye's depth of focus of and the aspheric nature of the IOL. Copyright © Association for Research in Vision and Ophthalmology.

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This research takes a dynamic view on the knowledge coordination process, aiming to explain how the process is affected by changes in the operating environment, from normal situations to emergencies in traditional and fast-response organizations, and why these changes occur. We first conceptualize the knowledge coordination process by distinguishing between four dimensions - what, when, how and who - that together capture the full scope of the knowledge coordination process. We use these dimensions to analyze knowledge coordination practices and the activities constituting these practices, in the IT functions of traditional and fast-response (military) organizations where we distinguish between "normal" and "emergency" operating conditions. Our findings indicate that (i) inter-relationships between knowledge coordination practices change under different operating conditions, and (ii) the patterns of change are different in traditional and fast-response organizations.

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A formalism for describing the dynamics of Genetic Algorithms (GAs) using method s from statistical mechanics is applied to the problem of generalization in a perceptron with binary weights. The dynamics are solved for the case where a new batch of training patterns is presented to each population member each generation, which considerably simplifies the calculation. The theory is shown to agree closely to simulations of a real GA averaged over many runs, accurately predicting the mean best solution found. For weak selection and large problem size the difference equations describing the dynamics can be expressed analytically and we find that the effects of noise due to the finite size of each training batch can be removed by increasing the population size appropriately. If this population resizing is used, one can deduce the most computationally efficient size of training batch each generation. For independent patterns this choice also gives the minimum total number of training patterns used. Although using independent patterns is a very inefficient use of training patterns in general, this work may also prove useful for determining the optimum batch size in the case where patterns are recycled.

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A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.

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Dynamical systems that involve impacts frequently arise in engineering. This Letter reports a study of such a system at microscale that consists of a nonlinear resonator operating with an unilateral impact. The microresonators were fabricated on silicon-on-insulator wafers by using a one-mask process and then characterised by using the capacitively driving and sensing method. Numerical results concerning the dynamics of this vibro-impact system were verified by the experiments. Bifurcation analysis was used to provide a qualitative scenario of the system steady-state solutions as a function of both the amplitude and the frequency of the external driving sinusoidal voltage. The results show that the amplitude of resonant peak is levelled off owing to the impact effect and that the bandwidth of impacting is dependent upon the nonlinearity and the operating conditions.

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Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.

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Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

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We explore the dynamics of a periodically driven Duffing resonator coupled elastically to a van der Pol oscillator in the case of 1?:?1 internal resonance in the cases of weak and strong coupling. Whilst strong coupling leads to dominating synchronization, the weak coupling case leads to a multitude of complex behaviours. A two-time scales method is used to obtain the frequency-amplitude modulation. The internal resonance leads to an antiresonance response of the Duffing resonator and a stagnant response (a small shoulder in the curve) of the van der Pol oscillator. The stability of the dynamic motions is also analyzed. The coupled system shows a hysteretic response pattern and symmetry-breaking facets. Chaotic behaviour of the coupled system is also observed and the dependence of the system dynamics on the parameters are also studied using bifurcation analysis.

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This thesis examines the dynamics of firm-level financing and investment decisions for six Southeast Asian countries. The study provides empirical evidence on the impacts of changes in the firm-level financing decisions during the period of financial liberalization by considering the debt and equity financing decisions of a set of non-financial firms. The empirical results show that firms in Indonesia, Pakistan, and South Korea have relatively faster speed of adjustment than other Southeast Asian countries to attain optimal debt and equity ratios in response to banking sector and stock market liberalization. In addition, contrary to widely held belief that firms adjust their financial ratios to industry levels, the results indicate that industry factors do not significantly impact on the speed of capital structure adjustments. This study also shows that non-linear estimation methods are more appropriate than linear estimation methods for capturing changes in capital structure. The empirical results also show that international stock market integration of these countries has significantly reduced the equity risk premium as well as the firm-level cost of equity capital. Thus stock market liberalization is associated with a decrease in the cost of equity capital of the firms. Developments in the securities markets infrastructure have also reduced the cost of equity capital. However, with increased integration there is the possibility of capital outflows from the emerging markets, which might reverse the pattern of decrease in cost of capital in these markets.

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The analysis and prediction of the dynamic behaviour of s7ructural components plays an important role in modern engineering design. :n this work, the so-called "mixed" finite element models based on Reissnen's variational principle are applied to the solution of free and forced vibration problems, for beam and :late structures. The mixed beam models are obtained by using elements of various shape functions ranging from simple linear to complex cubic and quadratic functions. The elements were in general capable of predicting the natural frequencies and dynamic responses with good accuracy. An isoparametric quadrilateral element with 8-nodes was developed for application to thin plate problems. The element has 32 degrees of freedom (one deflection, two bending and one twisting moment per node) which is suitable for discretization of plates with arbitrary geometry. A linear isoparametric element and two non-conforming displacement elements (4-node and 8-node quadrilateral) were extended to the solution of dynamic problems. An auto-mesh generation program was used to facilitate the preparation of input data required by the 8-node quadrilateral elements of mixed and displacement type. Numerical examples were solved using both the mixed beam and plate elements for predicting a structure's natural frequencies and dynamic response to a variety of forcing functions. The solutions were compared with the available analytical and displacement model solutions. The mixed elements developed have been found to have significant advantages over the conventional displacement elements in the solution of plate type problems. A dramatic saving in computational time is possible without any loss in solution accuracy. With beam type problems, there appears to be no significant advantages in using mixed models.

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This thesis was focused on theoretical models of synchronization to cortical dynamics as measured by magnetoencephalography (MEG). Dynamical systems theory was used in both identifying relevant variables for brain coordination and also in devising methods for their quantification. We presented a method for studying interactions of linear and chaotic neuronal sources using MEG beamforming techniques. We showed that such sources can be accurately reconstructed in terms of their location, temporal dynamics and possible interactions. Synchronization in low-dimensional nonlinear systems was studied to explore specific correlates of functional integration and segregation. In the case of interacting dissimilar systems, relevant coordination phenomena involved generalized and phase synchronization, which were often intermittent. Spatially-extended systems were then studied. For locally-coupled dissimilar systems, as in the case of cortical columns, clustering behaviour occurred. Synchronized clusters emerged at different frequencies and their boundaries were marked through oscillation death. The macroscopic mean field revealed sharp spectral peaks at the frequencies of the clusters and broader spectral drops at their boundaries. These results question existing models of Event Related Synchronization and Desynchronization. We re-examined the concept of the steady-state evoked response following an AM stimulus. We showed that very little variability in the AM following response could be accounted by system noise. We presented a methodology for detecting local and global nonlinear interactions from MEG data in order to account for residual variability. We found crosshemispheric nonlinear interactions of ongoing cortical rhythms concurrent with the stimulus and interactions of these rhythms with the following AM responses. Finally, we hypothesized that holistic spatial stimuli would be accompanied by the emergence of clusters in primary visual cortex resulting in frequency-specific MEG oscillations. Indeed, we found different frequency distributions in induced gamma oscillations for different spatial stimuli, which was suggestive of temporal coding of these spatial stimuli. Further, we addressed the bursting character of these oscillations, which was suggestive of intermittent nonlinear dynamics. However, we did not observe the characteristic-3/2 power-law scaling in the distribution of interburst intervals. Further, this distribution was only seldom significantly different to the one obtained in surrogate data, where nonlinear structure was destroyed. In conclusion, the work presented in this thesis suggests that advances in dynamical systems theory in conjunction with developments in magnetoencephalography may facilitate a mapping between levels of description int he brain. this may potentially represent a major advancement in neuroscience.

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We perform numerical simulations on a model describing a Brillouin-based temperature and strain sensor, testing its response when it is probed with relatively short pulses. Experimental results were recently published [e.g., Opt. Lett. 24, 510 (1999)] that showed a broadening of the Brillouin loss curve when the probe pulse duration is reduced, followed by a sudden and rather surprising reduction of the linewidth when the pulse duration gets shorter than the acoustic relaxation time. Our study reveals the processes responsible for this behavior. We give a clear physical insight into the problem, allowing us to define the best experimental conditions required for one to take the advantage of this effect.

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This thesis investigates changes in the oscillatory dynamics in key areas of the pain matrix during different modalities of pain. Gamma oscillations were seen in the primary somatosensory cortex in response to somatic electrical stimulation at painful and non-painful intensities. The strength of the gamma oscillations was found to relate to the intensity of the stimulus. Gamma oscillations were not seen during distal oesophageal electrical stimulation or the cold pressor test. Gamma oscillations were not seen in all participants during somatic electrical stimulation, however clear evoked responses from SI were seen in everyone. During a train of electrical pulses to the median nerve and the digit, a decrease in the frequency of the gamma oscillations was seen across the duration of the train. During a train of electrical stimuli to the median nerve and the digit, gamma oscillations were seen at ~20-100ms following stimulus onset and at frequencies between 30-100Hz. This gamma response was found to have a strong evoked component. Following a single electrical pulse to the digit, gamma oscillations were seen at 100-250ms and between 60-95Hz and were not temporally coincident with the main components of the evoked response. These results suggest that gamma oscillations may have an important role in encoding different aspects of sensory stimuli within their characteristics such as strength and frequency. These findings help to elucidate how somatic stimuli are processed within the cortex which in turn may be used to understand abnormal cases of somatosensory processing.