Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.

A peculiar Maxwell's Demon observed in a time-dependent stadium-like billiard

The dynamics of a driven stadium-like billiard is considered using the formalism of discrete mappings. The model presents a resonant velocity that depends on the rotation number around fixed points and external boundary perturbation which plays an important separation rule in the model. We show that particles exhibiting Fermi acceleration (initial velocity is above the resonant one) are scaling invariant with respect to the initial velocity and external perturbation. However, initial velocities below the resonant one lead the particles to decelerate therefore unlimited energy growth is not observed. This phenomenon may be interpreted as a specific Maxwell's Demon which may separate fast and slow billiard particles. (C) 2012 Elsevier B.V. All rights reserved.

Neural coding tools, based on Information Theory, applied to discrete time series: from electrophysiology to neuroethology

This work is supported by Brazilian agencies Fapesp, CAPES and CNPq

Effluent volume and dialysis dose in CRRT: time for reappraisal

The results of several studies assessing dialysis dose have dampened the enthusiasm of clinicians for considering dialysis dose as a modifiable factor influencing outcomes in patients with acute kidney injury. Powerful evidence from two large, multicenter trials indicates that increasing the dialysis dose, measured as hourly effluent volume, has no benefit in continuous renal replacement therapy (CRRT). However, some important operational characteristics that affect delivered dose were not evaluated. Effluent volume does not correspond to the actual delivered dose, as a decline in filter efficacy reduces solute removal during therapy. We believe that providing accurate parameters of delivered dose could improve the delivery of a prescribed dose and refine the assessment of the effect of dose on outcomes in critically ill patients treated with CRRT.

Anderson-like Transition for a Class of Random Sparse Models in d >= 2 Dimensions

We show that the Kronecker sum of d >= 2 copies of a random one-dimensional sparse model displays a spectral transition of the type predicted by Anderson, from absolutely continuous around the center of the band to pure point around the boundaries. Possible applications to physics and open problems are discussed briefly.

Lipid profile of the yolk under the influence of supplementaries sources rich in Ω-3 PUFAs in the diet of laying hens in the time

Two hundred eighty-eight 32-wk-old Hisex White laying hens were used in this research during a 10 weeks period, arranged in a 2 x 5 completely randomized factorial design, with three replicates of eight birds per treatment. Two groups: fish oil (OP) and Marine Algae (AM) with five DHA levels (120, 180, 240, 300 and 360 mg/100 g diet) were assigned including two control groups birds fed corn and soybean basal diet (CON) and a diet supplemented with AM (AM420) to study the effect of time 0, 2, 4, 6 and 8 weeks (wk) on the efficiency of egg yolk fatty acid enrichment. The means varied (p<0.01) of 17.63% (OP360) to 22.08% (AM420) is the total Polyunsaturated Fatty Acids (PUFAs) and 45.8 mg/g (OP360), 40.37 mg/g (OP360, 4 wk) to 65.82 mg/g (AM420) and 68.79 mg/g/yolk (AM120, 8 wk) for n-6 PUFAs. On the influence of sources and levels in the times, the means of n-3 PUFAs increased by 5.58 mg/g (AM120, 2 wk) to 14.16 mg/g (OP360, 6 wk) when compared to average of 3.34 mg PUFAs Ω/g/yolk (CON). Usually, the means DHA also increased from 22.34 (CON) to 176.53 mg (μ, OP360), 187.91 mg (OP360, 8 wk) and 192.96 mg (OP360, 6 wk) and 134.18 mg (μ, OP360), 135.79 mg (AM420, 6 wk), 149.75 mg DHA (AM420, 8 wk) per yolk. The opposite was observed for the means AA, so the effect of the sources, levels and times, decreased (P <0.01) of 99.83 mg (CON) to 31.99 mg (OP360, 4 wk), 40.43 mg (μ, OP360) to 61.21 mg (AM420) and 71.51 mg AA / yolk (μ, AM420). Variations of the average weight of 15.75g (OP360) to 17.08g (AM420) yolks of eggs de 32.55% (AM420) to 34.08% (OP360) of total lipids and 5.28 g (AM240) to 5.84 g (AM120) of fat in the yolk were not affected (p>0.05) by treatments, sources, levels and times studied. Starting of 2 week, the hens increased the level of n-3 PUFAs in the egg yolks, being expressively increased (p<0.01) until 4 weeks, which after the increased levels of n-3 PUFAs tended to if stabilize around of time of 8 experimental weeks, when it was more effective saturation of the tissues and yolk.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

Residence Time Distribution Models Derived from Non-Ideal Laminar Velocity Profiles in Tubes

The theoretical E-curve for the laminar flow of non-Newtonian fluids in circular tubes may not be accurate for real tubular systems with diffusion, mechanical vibration, wall roughness, pipe fittings, curves, coils, or corrugated walls. Deviations from the idealized laminar flow reactor (LFR) cannot be well represented using the axial dispersion or the tanks-in-series models of residence time distribution (RTD). In this work, four RTD models derived from non-ideal velocity profiles in segregated tube flow are proposed. They were used to represent the RTD of three tubular systems working with Newtonian and pseudoplastic fluids. Other RTD models were considered for comparison. The proposed models provided good adjustments, and it was possible to determine the active volumes. It is expected that these models can be useful for the analysis of LFR or for the evaluation of continuous thermal processing of viscous foods.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012