40 resultados para Complexity of Distribution


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To explore the neural mechanisms related to representation of the manipulation dynamics of objects, we performed whole-brain fMRI while subjects balanced an object in stable and highly unstable states and while they balanced a rigid object and a flexible object in the same unstable state, in all cases without vision. In this way, we varied the extent to which an internal model of the manipulation dynamics was required in the moment-to-moment control of the object's orientation. We hypothesized that activity in primary motor cortex would reflect the amount of muscle activation under each condition. In contrast, we hypothesized that cerebellar activity would be more strongly related to the stability and complexity of the manipulation dynamics because the cerebellum has been implicated in internal model-based control. As hypothesized, the dynamics-related activation of the cerebellum was quite different from that of the primary motor cortex. Changes in cerebellar activity were much greater than would have been predicted from differences in muscle activation when the stability and complexity of the manipulation dynamics were contrasted. On the other hand, the activity of the primary motor cortex more closely resembled the mean motor output necessary to execute the task. We also discovered a small region near the anterior edge of the ipsilateral (right) inferior parietal lobule where activity was modulated with the complexity of the manipulation dynamics. We suggest that this is related to imagining the location and motion of an object with complex manipulation dynamics.

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The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved.

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The generation of new medicinal products is both a contributor to global economic growth and a source of valuable benefits to human health. Given their direct responsibility for public health, regulatory authorities monitor closely both the development and exploitation of the underlying technologies and the products derived from them. The manner in which such regulation is implemented can result in regulators constraining or facilitating the generation of new products. This paper will study as an example the impact of EU Risk Management Plans (EU-RMPs), which have been mandatory for the approval of new medicines since 2005, on both the industry and regulatory authorities. In interviews, the responses of those who had experience of the implementation of EU-RMPs were mixed. Although the benefits of a more structured and predictable approach to the evaluation of risk were appreciated, some respondents perceived the regulation as an excessive burden on their organisations. The exploration of factors that influence how EU-RMP regulation affects individual firms provides new insights for both regulators and managers, and demonstrates one aspect of the complexity of the process by which new medicinal products are brought to market.

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The generation of new medicinal products is both a contributor to global economic growth and a source of valuable benefits to human health. Given their direct responsibility for public health, regulatory authorities monitor closely both the development and exploitation of the underlying technologies and the products derived from them. The manner in which such regulation is implemented can result in regulators constraining or facilitating the generation of new products. This paper will study as an example the impact of EU Risk Management Plans (EU-RMPs), which have been mandatory for the approval of new medicines since 2005, on both the industry and regulatory authorities. In interviews, the responses of those who had experience of the implementation of EU-RMPs were mixed. Although the benefits of a more structured and predictable approach to the evaluation of risk were appreciated, some respondents perceived the regulation as an excessive burden on their organisations. The exploration of factors that influence how EU-RMP regulation affects individual firms provides new insights for both regulators and managers, and demonstrates one aspect of the complexity of the process by which new medicinal products are brought to market. © 2010 IEEE.

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The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities-whether it is snowboarding or ballroom dancing-but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved. © 2011 Macmillan Publishers Limited. All rights reserved.

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Triacylglycerols (TAGs) from microalgae have the potential to be used for biodiesel, but several technical and economic hurdles have to be overcome. A major challenge is efficient extraction of intracellular TAGs from algae. Here we investigate the use of enzymes to deconstruct algal cell walls/membranes. We describe a rapid and simple assay that can assess the efficacy of different enzyme treatments on TAG-containing algae. By this means crude papain and bromelain were found to be effective in releasing TAGs from the diatom Phaeodactylum tricornutum, most likely because of their cysteine protease activity. Pre-treating algal biomass with crude papain enabled complete extraction of TAGs using heptane/isopropyl alcohol. Heptane as a single solvent was also effective, although complete recovery of TAG was not obtained. Economic implications of these findings are discussed, with the aim to reduce the complexity of, and energy needed in, TAG extraction.

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While static equilibria of flexible strings subject to various load types (gravity, hydrostatic pressure, Newtonian wind) is well understood textbook material, the combinations of the very same loads can give rise to complex spatial behaviour at the core of which is the unilateral material constraint prohibiting compressive loads. While the effects of such constraints have been explored in optimisation problems involving straight cables, the geometric complexity of physical configurations has not yet been addressed. Here we show that flexible strings subject to combined smooth loads may not have smooth solutions in certain ranges of the load ratios. This non-smooth phenomenon is closely related to the collapse geometry of inflated tents. After proving the nonexistence of smooth solutions for a broad family of loadings we identify two alternative, critical geometries immediately preceding the collapse. We verify these analytical results by dynamical simulation of flexible chains as well as with simple table-top experiments with an inflated membrane.

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Triacylglycerols (TAGs) from microalgae have the potential to be used for biodiesel, but several technical and economic hurdles have to be overcome. A major challenge is efficient extraction of intracellular TAGs from algae. Here we investigate the use of enzymes to deconstruct algal cell walls/membranes. We describe a rapid and simple assay that can assess the efficacy of different enzyme treatments on TAG-containing algae. By this means crude papain and bromelain were found to be effective in releasing TAGs from the diatom Phaeodactylum tricornutum, most likely because of their cysteine protease activity. Pre-treating algal biomass with crude papain enabled complete extraction of TAGs using heptane/isopropyl alcohol. Heptane as a single solvent was also effective, although complete recovery of TAG was not obtained. Economic implications of these findings are discussed, with the aim to reduce the complexity of, and energy needed in, TAG extraction. © 2012 Elsevier B.V.

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Model predictive control allows systematic handling of physical and operational constraints through the use of constrained optimisation. It has also been shown to successfully exploit plant redundancy to maintain a level of control in scenarios when faults are present. Unfortunately, the computational complexity of each individual iteration of the algorithm to solve the optimisation problem scales cubically with the number of plant inputs, so the computational demands are high for large MIMO plants. Multiplexed MPC only calculates changes in a subset of the plant inputs at each sampling instant, thus reducing the complexity of the optimisation. This paper demonstrates the application of multiplexed model predictive control to a large transport airliner in a nominal and a contingency scenario. The performance is compared to that obtained with a conventional synchronous model predictive controller, designed using an equivalent cost function. © 2012 AACC American Automatic Control Council).

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Abstract-Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art Banged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air Bow to be reduced and provide a means of identifying and assessing the various parameters that control the air Bow. The mathematical model is formulated in terms of the Stokes steam function, ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained Bow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions. | Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art flanged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air flow to be reduced and provide a means of identifying and assessing the various parameters that control the air flow. The mathematical model is formulated in terms of the Stokes steam function, Ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained flow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions.

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Hybrid large-eddy type simulations for cold jet flows from a serrated nozzle are performed at an acoustic Mach number Ma ac = 0.9 and Re = 1.03×10 6. Since the solver being used tends towards having dissipative qualities, the subgrid scale (SGS) model is omitted, giving a numerical type LES (NLES) or implicit LES (ILES) reminiscent procedure. To overcome near wall streak resolution problems a near wall RANS (Reynolds averaged Navier-Stokes) model is smoothly blended to the LES making a hybrid RANS-ILES. The geometric complexity of the serrated nozzle is fully considered without simplification or emulation. An improved but still modest hexahedral multi-block grid with circa 20 million grid points (with respect to 12.5 million in Xia et al.; Int J Heat Fluid Flow 30:1067-1079, 2009) is used. Despite the modest grid size, encouraging and improved results are obtained. Directly resolved mean and second-order fluctuating quantities along the jet centerline and in the jet shear layer compare favorably with measurements. The radiated far-field sound predicted using the Ffowcs Williams and Hawkings (FW-H) surface integral method shows good agreement with the measurements in directivity and sound spectra. © 2011 Springer Science+Business Media B.V.

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The role of the collagen-platelet interaction is of crucial importance to the haemostatic response during both injury and pathogenesis of the blood vessel wall. Of particular interest is the high affinity interaction of the platelet transmembrane receptor, alpha 2 beta 1, responsible for firm attachment of platelets to collagen at and around injury sites. We employ single molecule force spectroscopy (SMFS) using the atomic force microscope (AFM) to study the interaction of the I-domain from integrin alpha 2 beta 1 with a synthetic collagen related triple-helical peptide containing the high-affinity integrin-binding GFOGER motif, and a control peptide lacking this sequence, referred to as GPP. By utilising synthetic peptides in this manner we are able to study at the molecular level subtleties that would otherwise be lost when considering cell-to-collagen matrix interactions using ensemble techniques. We demonstrate for the first time the complexity of this interaction as illustrated by the complex multi-peaked force spectra and confirm specificity using control blocking experiments. In addition we observe specific interaction of the GPP peptide sequence with the I-domain. We propose a model to explain these observations.

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Two adaptive numerical modelling techniques have been applied to prediction of fatigue thresholds in Ni-base superalloys. A Bayesian neural network and a neurofuzzy network have been compared, both of which have the ability to automatically adjust the network's complexity to the current dataset. In both cases, despite inevitable data restrictions, threshold values have been modelled with some degree of success. However, it is argued in this paper that the neurofuzzy modelling approach offers real benefits over the use of a classical neural network as the mathematical complexity of the relationships can be restricted to allow for the paucity of data, and the linguistic fuzzy rules produced allow assessment of the model without extensive interrogation and examination using a hypothetical dataset. The additive neurofuzzy network structure means that redundant inputs can be excluded from the model and simple sub-networks produced which represent global output trends. Both of these aspects are important for final verification and validation of the information extracted from the numerical data. In some situations neurofuzzy networks may require less data to produce a stable solution, and may be easier to verify in the light of existing physical understanding because of the production of transparent linguistic rules. © 1999 Elsevier Science S.A.

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Submarine landslides pose considerable hazards to coastal communities and offshore structures. The difficulty and cost of obtaining undisturbed samples of offshore soils for determining material properties required for slope stability analyses contribute to the complexity of the problem. There are significant advantages in using a simplified model for the seismic response of submarine slopes, compatible with the limited amount of information that can be realistically gathered, but still able to capture the key elements of clay behavior. This paper illustrates the process of parameter determination and calibration of the SIMPLE DSS model, developed for the study of seismic triggering of submarine slope instabilities. The selection of parameters and predictions of monotonic and cyclic simple shear response are carried out for Boston Blue Clay, a marine clay extensively studied and with a large experimental database available in the literature. The results show that the simplified model is able to reproduce the important trends in the response of the soil, especially in accounting for the effect of the slope.

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The effects of growth temperature and V/III ratio on the morphology and crystallographic phases of InP nanowires that are grown by metal organic chemical vapour deposition have been studied. We show that higher growth temperatures or higher V/III ratios promote the formation of wurtzite nanowires while zinc-blende nanowires are favourableat lower growth temperatures and lower V/III ratios. A schematic map of distribution of zinc-blende and wurtzite structures has been developed in the range of growth temperatures (400-510 °C) and V/III ratios (44 to 700) investigated in this study. © 2010 IOP Publishing Ltd.