946 resultados para Reverse self-control problem
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Possible evidence is presented for Maillard glycation of enzymes during oligosaccharide synthesis by reverse hydrolysis. In 70% (w/v) mannose solutions, 1,2-alpha-mannosidase from Penicillium citrinum lost 40% and alpha-mannosidase from almonds lost 60% activity at 55 degreesC over 2 weeks. Oligosaccharide yields were 15 and 45% respectively. Higher molecular weight glycation adducts were formed in a time-dependent manner as seen by MALDI-TOF. Inhibitors of the Maillard. reaction were able to partially alleviate these effects resulting in reduced loss of enzyme activity and oligosaccharide yield increases of 27-53% relative to the control. (C) 2004 Elsevier B.V. All rights reserved.
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During locomotion, retinal flow, gaze angle, and vestibular information can contribute to one's perception of self-motion. Their respective roles were investigated during active steering: Retinal flow and gaze angle were biased by altering the visual information during computer-simulated locomotion, and vestibular information was controlled through use of a motorized chair that rotated the participant around his or her vertical axis. Chair rotation was made appropriate for the steering response of the participant or made inappropriate by rotating a proportion of the veridical amount. Large steering errors resulted from selective manipulation of retinal flow and gaze angle, and the pattern of errors provided strong evidence for an additive model of combination. Vestibular information had little or no effect on steering performance, suggesting that vestibular signals are not integrated with visual information for the control of steering at these speeds.
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Eye-movements have long been considered a problem when trying to understand the visual control of locomotion. They transform the retinal image from a simple expanding pattern of moving texture elements (pure optic flow), into a complex combination of translation and rotation components (retinal flow). In this article we investigate whether there are measurable advantages to having an active free gaze, over a static gaze or tracking gaze, when steering along a winding path. We also examine patterns of free gaze behavior to determine preferred gaze strategies during active locomotion. Participants were asked to steer along a computer-simulated textured roadway with free gaze, fixed gaze, or gaze tracking the center of the roadway. Deviation of position from the center of the road was recorded along with their point of gaze. It was found that visually tracking the middle of the road produced smaller steering errors than for fixed gaze. Participants performed best at the steering task when allowed to sample naturally from the road ahead with free gaze. There was some variation in the gaze strategies used, but sampling was predominantly of areas proximal to the center of the road. These results diverge from traditional models of flow analysis.
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Background A significant proportion of women who are vulnerable to postnatal depression refuse to engage in treatment programmes. Little is known about them, other than some general demographic characteristics. In particular, their access to health care and their own and their infants' health outcomes are uncharted. Methods We conducted a nested cohort case-control study, using data from computerized health systems, and general practitioner (GP) and maternity records, to identify the characteristics, health service contacts, and maternal and infant health outcomes for primiparous antenatal clinic attenders at high risk for postnatal depression who either refused (self-exclusion group) or else agreed (take-up group) to receive additional Health Visiting support in pregnancy and the first 2 months postpartum. Results Women excluding themselves from Health Visitor support were younger and less highly educated than women willing to take up the support. They were less likely to attend midwifery, GP and routine Health Visitor appointments, but were more likely to book in late and to attend accident and emergency department (A&E). Their infants had poorer outcome in terms of gestation, birthweight and breastfeeding. Differences between the groups still obtained when age and education were taken into account for midwifery contacts, A&E attendance and gestation;the difference in the initiation of breast feeding was attenuated, but not wholly explained, by age and education. Conclusion A subgroup of psychologically vulnerable childbearing women are at particular risk for poor access to health care and adverse infant outcome. Barriers to take-up of services need to be understood in order better to deliver care.
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Visual control of locomotion is essential for most mammals and requires coordination between perceptual processes and action systems. Previous research on the neural systems engaged by self-motion has focused on heading perception, which is only one perceptual subcomponent. For effective steering, it is necessary to perceive an appropriate future path and then bring about the required change to heading. Using function magnetic resonance imaging in humans, we reveal a role for the parietal eye fields (PEFs) in directing spatially selective processes relating to future path information. A parietal area close to PEFs appears to be specialized for processing the future path information itself. Furthermore, a separate parietal area responds to visual position error signals, which occur when steering adjustments are imprecise. A network of three areas, the cerebellum, the supplementary eye fields, and dorsal premotor cortex, was found to be involved in generating appropriate motor responses for steering adjustments. This may reflect the demands of integrating visual inputs with the output response for the control device.
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This paper considers the motion planning problem for oriented vehicles travelling at unit speed in a 3-D space. A Lie group formulation arises naturally and the vehicles are modeled as kinematic control systems with drift defined on the orthonormal frame bundles of particular Riemannian manifolds, specifically, the 3-D space forms Euclidean space E-3, the sphere S-3, and the hyperboloid H'. The corresponding frame bundles are equal to the Euclidean group of motions SE(3), the rotation group SO(4), and the Lorentz group SO (1, 3). The maximum principle of optimal control shifts the emphasis for these systems to the associated Hamiltonian formalism. For an integrable case, the extremal curves are explicitly expressed in terms of elliptic functions. In this paper, a study at the singularities of the extremal curves are given, which correspond to critical points of these elliptic functions. The extremal curves are characterized as the intersections of invariant surfaces and are illustrated graphically at the singular points. It. is then shown that the projections, of the extremals onto the base space, called elastica, at these singular points, are curves of constant curvature and torsion, which in turn implies that the oriented vehicles trace helices.
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In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.
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The work reported in this paper proposes Swarm-Array computing, a novel technique inspired by swarm robotics, and built on the foundations of autonomic and parallel computing. The approach aims to apply autonomic computing constructs to parallel computing systems and in effect achieve the self-ware objectives that describe self-managing systems. The constitution of swarm-array computing comprising four constituents, namely the computing system, the problem/task, the swarm and the landscape is considered. Approaches that bind these constituents together are proposed. Space applications employing FPGAs are identified as a potential area for applying swarm-array computing for building reliable systems. The feasibility of a proposed approach is validated on the SeSAm multi-agent simulator and landscapes are generated using the MATLAB toolkit.
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The self-assembly and hydrogelation properties of two Fmoc-tripeptides [Fmoc = N-(fluorenyl-9-methoxycarbonyl)] are investigated, in borate buffer and other basic solutions. A remarkable difference in self-assembly properties is observed comparing Fmoc-VLK(Boc) with Fmoc-K(Boc)LV, both containing K protected by N(epsilon)-tert-butyloxycarbonate (Boc). In borate buffer, the former peptide forms highly anisotropic fibrils which show local alignment, and the hydrogels show flow-aligning properties. In contrast, Fmoc-K(Boc)LV forms highly branched fibrils that produce isotropic hydrogels with a much higher modulus (G' > 10(4) Pa), and lower concentration for hydrogel formation. The distinct self-assembled structures are ascribed to conformational differences, as revealed by secondary structure probes (CD, FTIR, Raman spectroscopy) and X-ray diffraction. Fmoc-VLK(Boc) forms well-defined beta-sheets with a cross-beta X-ray diffraction pattern, whereas Fmoc-KLV(Boc) forms unoriented assemblies with multiple stacked sheets. Interchange of the K and V residues when inverting the tripeptide sequence thus leads to substantial differences in self-assembled structures, suggesting a promising approach to control hydrogel properties.
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The conformation of a model peptide AAKLVFF based on a fragment of the amyloid beta peptide A beta 16-20, KLVFF, is investigated in methanol and water via solution NMR experiments and Molecular dynamics computer simulations. In previous work, we have shown that AAKLVFF forms peptide nanotubes in methanol and twisted fibrils in water. Chemical shift measurements were used to investigate the solubility of the peptide as a function of concentration in methanol and water. This enabled the determination of critical aggregation concentrations, The Solubility was lower in water. In dilute solution, diffusion coefficients revealed the presence of intermediate aggregates in concentrated solution, coexisting with NMR-silent larger aggregates, presumed to be beta-sheets. In water, diffusion coefficients did not change appreciably with concentration, indicating the presence mainly of monomers, coexisting with larger aggregates in more concentrated solution. Concentration-dependent chemical shift measurements indicated a folded conformation for the monomers/intermediate aggregates in dilute methanol, with unfolding at higher concentration. In water, an antiparallel arrangement of strands was indicated by certain ROESY peak correlations. The temperature-dependent solubility of AAKLVFF in methanol was well described by a van't Hoff analysis, providing a solubilization enthalpy and entropy. This pointed to the importance of solvophobic interactions in the self-assembly process. Molecular dynamics Simulations constrained by NOE values from NMR suggested disordered reverse turn structures for the monomer, with an antiparallel twisted conformation for dimers. To model the beta-sheet structures formed at higher concentration, possible model arrangements of strands into beta-sheets with parallel and antiparallel configurations and different stacking sequences were used as the basis for MD simulations; two particular arrangements of antiparallel beta-sheets were found to be stable, one being linear and twisted and the other twisted in two directions. These structures Were used to simulate Circular dichroism spectra. The roles of aromatic stacking interactions and charge transfer effects were also examined. Simulated spectra were found to be similar to those observed experimentally.(in water or methanol) which show a maximum at 215 or 218 nm due to pi-pi* interactions, when allowance is made for a 15-18 nm red-shift that may be due to light scattering effects.
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Objective. To examine the association between worry and problem-solving skills and beliefs (confidence and perceived control) in primary school children. Method. Children (8–11 years) were screened using the Penn State Worry Questionnaire for Children. High (N ¼ 27) and low (N ¼ 30) scorers completed measures of anxiety, problem-solving skills (generating alternative solutions to problems, planfulness, and effectiveness of solutions) and problem-solving beliefs(confidence and perceived control). Results. High and low worry groups differed significantly on measures of anxiety and problem-solving beliefs (confidence and control) but not on problem-solving skills. Conclusions. Consistent with findings with adults, worry in children was associated with cognitive distortions, not skills deficits. Interventions for worried children may benefit froma focus on increasing positive problem-solving beliefs.
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In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.
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A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.
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In the last few years a state-space formulation has been introduced into self-tuning control. This has not only allowed for a wider choice of possible control actions, but has also provided an insight into the theory underlying—and hidden by—that used in the polynomial description. This paper considers many of the self-tuning algorithms, both state-space and polynomial, presently in use, and by starting from first principles develops the observers which are, effectively, used in each case. At any specific time instant the state estimator can be regarded as taking one of two forms. In the first case the most recently available output measurement is excluded, and here an optimal and conditionally stable observer is obtained. In the second case the present output signal is included, and here it is shown that although the observer is once again conditionally stable, it is no longer optimal. This result is of significance, as many of the popular self-tuning controllers lie in the second, rather than first, category.