972 resultados para Non-optimal Codon
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Positive-sense RNA viruses are important animal, plant, insect and bacteria pathogens and constitute the largest group of RNA viruses. Due to the relatively small size of their genomes, these viruses have evolved a variety of non-canonical translation mechanisms to optimize coding capacity expanding their proteome diversity. One such strategy is codon redefinition or recoding. First described in viruses, recoding is a programmed translation event in which codon alterations are context dependent. Recoding takes place in a subset of messenger RNA (mRNAs) with some products reflecting new, and some reflecting standard, meanings. The ratio between the two is both critical and highly regulated. While a variety of recoding mechanisms have been documented, (ribosome shunting, stop-carry on, termination-reinitiation, and translational bypassing), the two most extensively employed by RNA viruses are Programmed Ribosomal Frameshifting (PRF) and Programmed Ribosomal Readthrough (PRT). While both PRT and PRF subvert normal decoding for expression of C-terminal extension products, the former involves an alteration of reading frame, and the latter requires decoding of a non-sense codon. Both processes occur at a low but defined frequency, and both require Recoding Stimulatory Elements (RSE) for regulation and optimum functionality. These stimulatory signals can be embedded in the RNA in the form of sequence or secondary structure, or trans-acting factors outside the mRNA such as proteins or micro RNAs (miRNA). Despite 40+ years of study, the precise mechanisms by which viral RSE mediate ribosome recoding for the synthesis of their proteins, or how the ratio of these products is maintained, is poorly defined. This study reveals that in addition to a long distance RNA:RNA interaction, three alternate conformations and a phylogenetically conserved pseudoknot regulate PRT in the carmovirus Turnip crinkle virus (TCV).
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International audience
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An infinite-horizon discrete time model with multiple size-class structures using a transition matrix is built to assess optimal harvesting schedules in the context of Non-Industrial Private Forest (NIPF) owners. Three model specifications accounting for forest income, financial return on an asset and amenity valuations are considered. Numerical simulations suggest uneven-aged forest management where a rational forest owner adapts her or his forest policy by influencing the regeneration of trees or adjusting consumption dynamics depending on subjective time preference and market return rate dynamics on the financial asset. Moreover she or he does not value significantly non-market benefits captured by amenity valuations relatively to forest income.
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In the context of fading channels it is well established that, with a constrained transmit power, the bit rates achievable by signals that are not peaky vanish as the bandwidth grows without bound. Stepping back from the limit, we characterize the highest bit rate achievable by such non-peaky signals and the approximate bandwidth where that apex occurs. As it turns out, the gap between the highest rate achievable without peakedness and the infinite-bandwidth capacity (with unconstrained peakedness) is small for virtually all settings of interest to wireless communications. Thus, although strictly achieving capacity in wideband fading channels does require signal peakedness, bit rates not far from capacity can be achieved with conventional signaling formats that do not exhibit the serious practical drawbacks associated with peakedness. In addition, we show that the asymptotic decay of bit rate in the absence of peakedness usually takes hold at bandwidths so large that wideband fading models are called into question. Rather, ultrawideband models ought to be used.
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A technique is derived for solving a non-linear optimal control problem by iterating on a sequence of simplified problems in linear quadratic form. The technique is designed to achieve the correct solution of the original non-linear optimal control problem in spite of these simplifications. A mixed approach with a discrete performance index and continuous state variable system description is used as the basis of the design, and it is shown how the global problem can be decomposed into local sub-system problems and a co-ordinator within a hierarchical framework. An analysis of the optimality and convergence properties of the algorithm is presented and the effectiveness of the technique is demonstrated using a simulation example with a non-separable performance index.
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We study optimal labor income taxation in non-competitive labor markets. Firms offer screening contracts to workers who have private information about their productivity. A planner endowed with a Paretian social welfare function tries to induce allocations that maximize its objective. We provide necessary and sufficient conditions for implementation of constrained efficient allocations using tax schedules. All allocations that are implementable by a tax schedule display negative marginal tax rates for almost all workers. Not all allocations that are implementable in a competitive setting are implementable in this noncompetitive environment.
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We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.
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In this work, we use a nonlinear control based on Optimal Linear Control. We used as mathematical model a Duffing equation to model a supporting structure for an unbalanced rotating machine with limited power (non-ideal motor). Numerical simulations are performed for a set control parameter (depending on the voltage of the motor, that is, in the static and dynamic characteristic of the motor) The interaction of the non-ideal excitation with the structure may lead to the occurrence of interesting phenomena during the forward passage through the several resonance states of the system. Chaotic behavior is obtained for values of the parameters. Then, the proposed control strategy is applied in order to regulate the chaotic behavior, in order to obtain a periodic orbit and to decrease its amplitude. Both methodologies were used in complete agreement between them. The purpose of the paper is to give suggestions and recommendations to designers and engineers on how to drive this kind of system through resonance.
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In this paper, a load transportation system in platforms or suspended by cables is considered. It is a monorail device and is modelled as an inverted pendulum built on a car driven by a DC motor. The governing equations of motion were derived via Lagrange's equations. In the mathematical model we consider the interaction between the DC motor and the dynamical system, that is, we have a so-called non-ideal periodic problem. The problem is analysed and we also developed an optimal linear control design to stabilize the problem.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this work the problem of a spacecraft bi-impulsive transfer between two given non coplanar elliptical orbits, with minimum fuel consumption, is solved considering a non-Keplerian force field (the perturbing forces include Earth gravity harmonics and atmospheric drag). The problem is transformed in the Two Point Boundary Value Problem. It is developed and implemented a new algorithm, that uses the analytical expressions developed here. A dynamics that considered a Keplerian force field was used to produce an initial guess to solve the Two Point Boundary Value Problem. Several simulations were performed to observe the spacecraft orbital behaviour by different kind of perturbations and constraints, on a fuel consumption optimization point of view. (C) 2002 COSPAR. Published by Elsevier B.V. Ltd. All rights reserved.
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Recent optimizations of NMR spectroscopy have focused their attention on innovations in new hardware, such as novel probes and higher field strengths. Only recently has the potential to enhance the sensitivity of NMR through data acquisition strategies been investigated. This thesis has focused on the practice of enhancing the signal-to-noise ratio (SNR) of NMR using non-uniform sampling (NUS). After first establishing the concept and exact theory of compounding sensitivity enhancements in multiple non-uniformly sampled indirect dimensions, a new result was derived that NUS enhances both SNR and resolution at any given signal evolution time. In contrast, uniform sampling alternately optimizes SNR (t < 1.26T2) or resolution (t~3T2), each at the expense of the other. Experiments were designed and conducted on a plant natural product to explore this behavior of NUS in which the SNR and resolution continue to improve as acquisition time increases. Possible absolute sensitivity improvements of 1.5 and 1.9 are possible in each indirect dimension for matched and 2x biased exponentially decaying sampling densities, respectively, at an acquisition time of ¿T2. Recommendations for breaking into the linear regime of maximum entropy (MaxEnt) are proposed. Furthermore, examination into a novel sinusoidal sampling density resulted in improved line shapes in MaxEnt reconstructions of NUS data and comparable enhancement to a matched exponential sampling density. The Absolute Sample Sensitivity derived and demonstrated here for NUS holds great promise in expanding the adoption of non-uniform sampling.