984 resultados para Relaxation oscillators
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PURPOSE: The effects of β(2)-agonists on human skeletal muscle contractile properties, particularly on slow fibers, are unclear. Moreover, it remains to be ascertained whether central motor drive (CMD) during voluntary contractions could counter for eventual contractile alterations induced by β(2)-agonists. This study investigated central and peripheral neuromuscular adjustments induced by β(2)-agonist terbutaline on a predominantly slow human muscle, the soleus. METHODS: Ten recreationally active men ingested either a single dose of 8 mg of terbutaline or placebo in a randomized double-blind order (two experimental sessions). Isometric plantarflexion torque was measured during single and tetanic (10 and 100 Hz) stimulations as well as during submaximal and maximal voluntary contractions (MVC). Twitch peak torque and half-relaxation time were calculated. CMD was estimated via soleus electromyographic recordings obtained during voluntary contractions performed at approximately 50% MVC. RESULTS: MVC and twitch peak torque were not modified by terbutaline. Twitch half-relaxation time was 28% shorter after terbutaline administration compared with placebo (P < 0.001). Tetanic torques at 10 and 100 Hz were significantly lower after terbutaline intake compared with placebo (-40% and -24% respectively, P < 0.001). Despite comparable torque of submaximal voluntary contractions in the two conditions, CMD was 7% higher after terbutaline ingestion compared with placebo (P < 0.01). CONCLUSION: These results provide evidence that terbutaline modulates the contractility of the slow soleus muscle and suggest that the increased CMD during submaximal contractions may be viewed as a compensatory adjustment of the central nervous system to counter the weakening action induced by terbutaline on the contractile function of slow muscle fibers.
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We address the problem of scheduling a multiclass $M/M/m$ queue with Bernoulli feedback on $m$ parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity;and (ii) the number of servers. It follows that its relativesuboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical $c \mu$ rule. Our analysis is based on comparing the expected cost of Klimov's ruleto the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set ofwork decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the $c \mu$ rule for parallel scheduling.
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We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid(whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then theproblem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.
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This paper shows that liquidity constraints restrict jobcreation even when labor markets are flexible. In a dynamicmodel of labor demand, I show that in an environment of imperfect capital and imperfect labor markets, firms usetemporary contracts to relax financial constraints. Evidence for the predictions of the model is presented using Spanish data from the CBBE (Central de Balances del Banco de España - Balance Sheet data from the Bank of Spain). It is shown that firms substitute temporary laborfor permanent one and use less debt as their financial position improves. In particular, it is rejected that Spanish firms operate in an environment of free capital markets and of no labor adjustment costs. The labor reform of 1984, which created temporary contracts, implied to some extent a relaxation of liquidity constraints.Accordingly, firms used these contracts more extensivelyand used less debt; however, as capital markets continueto be imperfect, permanent job creation continues to beslow. Consequently, relaxation of liquidity constraints should also be part of a job creation strategy.
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We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.
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We develop a mathematical programming approach for the classicalPSPACE - hard restless bandit problem in stochastic optimization.We introduce a hierarchy of n (where n is the number of bandits)increasingly stronger linear programming relaxations, the lastof which is exact and corresponds to the (exponential size)formulation of the problem as a Markov decision chain, while theother relaxations provide bounds and are efficiently computed. Wealso propose a priority-index heuristic scheduling policy fromthe solution to the first-order relaxation, where the indices aredefined in terms of optimal dual variables. In this way wepropose a policy and a suboptimality guarantee. We report resultsof computational experiments that suggest that the proposedheuristic policy is nearly optimal. Moreover, the second-orderrelaxation is found to provide strong bounds on the optimalvalue.
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The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.
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We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.
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We performed numerical simulations of DNA chains to understand how local geometry of juxtaposed segments in knotted DNA molecules can guide type II DNA topoisomerases to perform very efficient relaxation of DNA knots. We investigated how the various parameters defining the geometry of inter-segmental juxtapositions at sites of inter-segmental passage reactions mediated by type II DNA topoisomerases can affect the topological consequences of these reactions. We confirmed the hypothesis that by recognizing specific geometry of juxtaposed DNA segments in knotted DNA molecules, type II DNA topoisomerases can maintain the steady-state knotting level below the topological equilibrium. In addition, we revealed that a preference for a particular geometry of juxtaposed segments as sites of strand-passage reaction enables type II DNA topoisomerases to select the most efficient pathway of relaxation of complex DNA knots. The analysis of the best selection criteria for efficient relaxation of complex knots revealed that local structures in random configurations of a given knot type statistically behave as analogous local structures in ideal geometric configurations of the corresponding knot type.
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Lithium is widely used in psychotherapy. The (6)Li isotope has a long intrinsic longitudinal relaxation time T(1) on the order of minutes, making it an ideal candidate for hyperpolarization experiments. In the present study we demonstrated that lithium-6 can be readily hyperpolarized within 30 min, while retaining a long polarization decay time on the order of a minute. We used the intrinsically long relaxation time for the detection of 500 nM contrast agent in vitro. Hyperpolarized lithium-6 was administered to the rat and its signal retained a decay time on the order of 70 sec in vivo. Localization experiments imply that the lithium signal originated from within the brain and that it was detectable up to 5 min after administration. We conclude that the detection of submicromolar contrast agents using hyperpolarized NMR nuclei such as (6)Li may provide a novel avenue for molecular imaging.
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The influence of the basis set size and the correlation energy in the static electrical properties of the CO molecule is assessed. In particular, we have studied both the nuclear relaxation and the vibrational contributions to the static molecular electrical properties, the vibrational Stark effect (VSE) and the vibrational intensity effect (VIE). From a mathematical point of view, when a static and uniform electric field is applied to a molecule, the energy of this system can be expressed in terms of a double power series with respect to the bond length and to the field strength. From the power series expansion of the potential energy, field-dependent expressions for the equilibrium geometry, for the potential energy and for the force constant are obtained. The nuclear relaxation and vibrational contributions to the molecular electrical properties are analyzed in terms of the derivatives of the electronic molecular properties. In general, the results presented show that accurate inclusion of the correlation energy and large basis sets are needed to calculate the molecular electrical properties and their derivatives with respect to either nuclear displacements or/and field strength. With respect to experimental data, the calculated power series coefficients are overestimated by the SCF, CISD, and QCISD methods. On the contrary, perturbation methods (MP2 and MP4) tend to underestimate them. In average and using the 6-311 + G(3df) basis set and for the CO molecule, the nuclear relaxation and the vibrational contributions to the molecular electrical properties amount to 11.7%, 3.3%, and 69.7% of the purely electronic μ, α, and β values, respectively
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The principal objective of the knot theory is to provide a simple way of classifying and ordering all the knot types. Here, we propose a natural classification of knots based on their intrinsic position in the knot space that is defined by the set of knots to which a given knot can be converted by individual intersegmental passages. In addition, we characterize various knots using a set of simple quantum numbers that can be determined upon inspection of minimal crossing diagram of a knot. These numbers include: crossing number; average three-dimensional writhe; number of topological domains; and the average relaxation value
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Stimulated echoes are widely used for imaging functional tissue parameters such as diffusion coefficient, perfusion, and flow rates. They are potentially interesting for the assessment of various cardiac functions. However, severe limitations of the stimulated echo acquisition mode occur, which are related to the special dynamic properties of the beating heart and flowing blood. To the well-known signal decay due to longitudinal relaxation and through-plane motion between the preparation and the read-out period of the stimulated echoes, additional signal loss is often observed. As the prepared magnetization is fixed with respect to the tissue, this signal loss is caused by the tissue deformation during the cardiac cycle, which leads to a modification of the modulation frequency of the magnetization. These effects are theoretically derived and corroborated by phantom and in vivo experiments.
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OBJECTIVE: Based on the law of Laplace, transventricular tension members were designed to diminish wall stress by changing the left ventricle (LV) globular shape to a bilobular one, thus reducing the ventricular wall radius of curvature. This concept was tested in a model of congestive heart failure. METHODS: Seven calves were used for the study (74.3+/-4.2 kg). Treatment efficacy was assessed with sonomicrometric wall motion analysis coupled with intraventricular pressure measurement. Preload increase was applied stepwise with tension members in released and tightened position. RESULTS: Tightening of the tension members improved systolic function for CVP>10 mmHg (dP/dt: 828+/-122 vs. 895+/-112 mmHg/s, P=0.019, for baseline and 20% stress level reduction respectively; wall thickening: 11.6+/-1.5 vs. 13.3+/-1.7%, P<0.001) and diastolic function (LV end-diastolic pressure: 15.9+/-4.8 vs. 13.6+/-2.7 mmHg, P<0.001, for CVP>10 mmHg; peak rate of wall thinning: -12.2+/-2.2 vs. -14+/-2.3 cm(2)/s, P<0.001 and logistic time constant of isovolumic relaxation: 48.4 +/-10.9 vs. 39.8+/-9.6ms, P<0.001, for CVP>5 mmHg). CONCLUSIONS: This less aggressive LV reduction method significantly improves contractility and relaxation parameters in this model of congestive heart failure.
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Quantification of short-echo time proton magnetic resonance spectroscopy results in >18 metabolite concentrations (neurochemical profile). Their quantification accuracy depends on the assessment of the contribution of macromolecule (MM) resonances, previously experimentally achieved by exploiting the several fold difference in T(1). To minimize effects of heterogeneities in metabolites T(1), the aim of the study was to assess MM signal contributions by combining inversion recovery (IR) and diffusion-weighted proton spectroscopy at high-magnetic field (14.1 T) and short echo time (= 8 msec) in the rat brain. IR combined with diffusion weighting experiments (with δ/Δ = 1.5/200 msec and b-value = 11.8 msec/μm(2)) showed that the metabolite nulled spectrum (inversion time = 740 msec) was affected by residuals attributed to creatine, inositol, taurine, choline, N-acetylaspartate as well as glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost not affected (< 8%). The combination of metabolite-nulled IR spectra with diffusion weighting allows a specific characterization of MM resonances with minimal metabolite signal contributions and is expected to lead to a more precise quantification of the neurochemical profile.