Survival time of random walk in random environment among soft obstacles

We consider a Random Walk in Random Environment (RWRE) moving in an i.i.d. random field of obstacles. When the particle hits an obstacle, it disappears with a positive probability. We obtain quenched and annealed bounds on the tails of the survival time in the general d-dimensional case. We then consider a simplified one-dimensional model (where transition probabilities and obstacles are independent and the RWRE only moves to neighbour sites), and obtain finer results for the tail of the survival time. In addition, we study also the ""mixed"" probability measures (quenched with respect to the obstacles and annealed with respect to the transition probabilities and vice-versa) and give results for tails of the survival time with respect to these probability measures. Further, we apply the same methods to obtain bounds for the tails of hitting times of Branching Random Walks in Random Environment (BRWRE).

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Constant-random practice and the adaptive process in motor learning with varying amounts of constant practice

The adaptive process in motor learning was examined in terms of effects of varying amounts of constant practice performed before random practice. Participants pressed five response keys sequentially, the last one coincident with the lighting of a final visual stimulus provided by a complex coincident timing apparatus. Different visual stimulus speeds were used during the random practice. 33 children (M age=11.6 yr.) were randomly assigned to one of three experimental groups: constant-random, constant-random 33%, and constant-random 66%. The constant-random group practiced constantly until they reached a criterion of performance stabilization three consecutive trials within 50 msec. of error. The other two groups had additional constant practice of 33 and 66%, respectively, of the number of trials needed to achieve the stabilization criterion. All three groups performed 36 trials under random practice; in the adaptation phase, they practiced at a different visual stimulus speed adopted in the stabilization phase. Global performance measures were absolute, constant, and variable errors, and movement pattern was analyzed by relative timing and overall movement time. There was no group difference in relation to global performance measures and overall movement time. However, differences between the groups were observed on movement pattern, since constant-random 66% group changed its relative timing performance in the adaptation phase.

Neighborhood and Efficiency in Manufacturing in Brazilian Regions: A Spatial Markov Chain Analysis

This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.

Occlusal outcomes and efficiency of 1-and 2-phase protocols in the treatment of Class II Division 1 malocclusion

Introduction: The purpose of this study was to compare the occlusal outcomes and the efficiency of 1-phase and 2-phase treatment protocols in Class II Division 1 malocclusions. Treatment efficiency was defined as a change in the occlusal characteristics in a shorter treatment time. Methods: Class II Division 1 subjects ( n = 139) were divided into 2 groups according to the treatment protocol for Class II correction. Group 1 comprised 78 patients treated with a 1-phase treatment protocol at initial and final mean ages of 12.51 and 14.68 years. Group 2 comprised 61 patients treated with a 2-phase treatment protocol at initial and final mean ages of 11.21 and 14.70 years. Lateral cephalometric radiographs were taken at the pretreatment stage to evaluate morphological differences in the groups. The initial and final study models of the patients were evaluated by using the peer assessment rating index. Chi-square tests were used to test for differences between the 2 groups for categorical variables. Variables regarding occlusal results were compared by using independent t tests. A linear regression analysis was completed, with total treatment time as the dependent variable, to identify clinical factors that predict treatment length for patients with Class II malocclusions. Results: Similar occlusal outcomes were obtained between the 1-phase and the 2-phase treatment protocols, but the duration of treatment was significantly shorter in the 1-phase treatment protocol group. Conclusions: Treatment of Class II Division 1 malocclusions is more efficient with the 1-phase than the 2-phase treatment protocol.

NONHOMOGENEOUS RANDOM WALKS SYSTEMS ON Z

We consider a random walks system on Z in which each active particle performs a nearest-neighbor random walk and activates all inactive particles it encounters. The movement of an active particle stops when it reaches a certain number of jumps without activating any particle. We prove that if the process relies on efficient particles (i.e. those particles with a small probability of jumping to the left) being placed strategically on Z, then it might survive, having active particles at any time with positive probability. On the other hand, we may construct a process that dies out eventually almost surely, even if it relies on efficient particles. That is, we discuss what happens if particles are initially placed very far away from each other or if their probability of jumping to the right tends to I but not fast enough.

Stretching and folding mechanism in foams

We have described the stretching and folding of foams in a vertical Hele-Shaw cell containing air and a surfactant solution, from a sequence of upside-down flips. Besides the firactal dimension of the foam, we have observed the logistic growth for the soap film length. The stretching and folding mechanism is present during the foam formation, and this mechanism is observed even after the foam has reached its respective maximum fractal dimension. Observing the motion of bubbles inside the foam, large bubbles present power spectrum associated with random walk motion in both directions, while the small bubbles are scattered like balls in a Galton board. (C) 2008 Published by Elsevier B.V.

Open-circuit voltages: Theoretical and experimental optimizations of rear passivated silicon solar cells using Fz and Cz wafers

The theoretical and experimental open-circuit voltage optimizations of a simple fabrication process of silicon solar cells n(+)p with rear passivation are presented. The theoretical results were obtained by using an in-house developed program, including the light trapping effect and metal-grid optimization. On the other hand, the experimental steps were monitored by the photoconductive decay technique. The starting materials presented thickness of about 300 pm and resistivities: FZ (0.5 Omega cm), Cz-type 1 (2.5 Omega cm) and Cz-type 2 (3.3 Omega cm). The Gaussian profile emitters were optimized with sheet resistance between 55 Omega/sq and 100 Omega/sq, and approximately 2.0 mu m thickness in accordance to the theoretical results. Excellent implied open-circuit voltages of 670.8 mV, 652.5 mV and 662.6 mV, for FZ, Cz-type 1 and Cz-type 2 silicon wafers, respectively, could be associated to the measured lifetimes that represents solar cell efficiency up to 20% if a low cost anti-reflection coating system, composed by random pyramids and SiO(2) layer, is considered even for typical Cz silicon. (C) 2009 Elsevier Ltd. All rights reserved.

Modularity and robustness of bone networks

Cortical bones, essential for mechanical support and structure in many animals, involve a large number of canals organized in intricate fashion. By using state-of-the art image analysis and computer graphics, the 3D reconstruction of a whole bone (phalange) of a young chicken was obtained and represented in terms of a complex network where each canal was associated to an edge and every confluence of three or more canals yielded a respective node. The representation of the bone canal structure as a complex network has allowed several methods to be applied in order to characterize and analyze the canal system organization and the robustness. First, the distribution of the node degrees (i.e. the number of canals connected to each node) confirmed previous indications that bone canal networks follow a power law, and therefore present some highly connected nodes (hubs). The bone network was also found to be partitioned into communities or modules, i.e. groups of nodes which are more intensely connected to one another than with the rest of the network. We verified that each community exhibited distinct topological properties that are possibly linked with their specific function. In order to better understand the organization of the bone network, its resilience to two types of failures (random attack and cascaded failures) was also quantified comparatively to randomized and regular counterparts. The results indicate that the modular structure improves the robustness of the bone network when compared to a regular network with the same average degree and number of nodes. The effects of disease processes (e. g., osteoporosis) and mutations in genes (e.g., BMP4) that occur at the molecular level can now be investigated at the mesoscopic level by using network based approaches.

Random walks systems with killing on Z

We study random walks systems on Z whose general description follows. At time zero, there is a number N >= 1 of particles at each vertex of N, all being inactive, except for those placed at the vertex one. Each active particle performs a simple random walk on Z and, up to the time it dies, it activates all inactive particles that it meets along its way. An active particle dies at the instant it reaches a certain fixed total of jumps (L >= 1) without activating any particle, so that its lifetime depends strongly on the past of the process. We investigate how the probability of survival of the process depends on L and on the jumping probabilities of the active particles.

Spontaneous symmetry breaking in amnestically induced persistence

We investigate a recently proposed non-Markovian random walk model characterized by loss of memories of the recent past and amnestically induced persistence. We report numerical and analytical results showing the complete phase diagram, consisting of four phases, for this system: (i) classical nonpersistence, (ii) classical persistence, (iii) log-periodic nonpersistence, and (iv) log-periodic persistence driven by negative feedback. The first two phases possess continuous scale invariance symmetry, however, log-periodicity breaks this symmetry. Instead, log-periodic motion satisfies discrete scale invariance symmetry, with complex rather than real fractal dimensions. We find for log-periodic persistence evidence not only of statistical but also of geometric self-similarity.

Exceptional times for the dynamical discrete web

The dynamical discrete web (DyDW), introduced in the recent work of Howitt and Warren, is a system of coalescing simple symmetric one-dimensional random walks which evolve in an extra continuous dynamical time parameter tau. The evolution is by independent updating of the underlying Bernoulli variables indexed by discrete space-time that define the discrete web at any fixed tau. In this paper, we study the existence of exceptional (random) values of tau where the paths of the web do not behave like usual random walks and the Hausdorff dimension of the set of such exceptional tau. Our results are motivated by those about exceptional times for dynamical percolation in high dimension by Haggstrom, Peres and Steif, and in dimension two by Schramm and Steif. The exceptional behavior of the walks in the DyDW is rather different from the situation for the dynamical random walks of Benjamini, Haggstrom, Peres and Steif. For example, we prove that the walk from the origin S(0)(tau) violates the law of the iterated logarithm (LIL) on a set of tau of Hausdorff dimension one. We also discuss how these and other results should extend to the dynamical Brownian web, the natural scaling limit of the DyDW. (C) 2009 Elsevier B.V. All rights reserved.

AnSBBR Applied to a Personal Care Industry Wastewater Treatment: Effects of Fill Time, Volume Treated Per Cycle, and Organic Load

A study was performed regarding the effect of the relation between fill time, volume treated per cycle, and influent concentration at different applied organic loadings on the stability and efficiency of an anaerobic sequencing batch reactor containing immobilized biomass on polyurethane foam with recirculation of the liquid phase (AnSBBR) applied to the treatment of wastewater from a personal care industry. Total cycle length of the reactor was 8 h (480 min). Fill times were 10 min in the batch operation, 4 h in the fed-batch operation, and a 10-min batch followed by a 4-h fed batch in the mixed operation. Settling time was not necessary since the biomass was immobilized and decant time was 10 min. Volume of liquid medium in the reactor was 2.5 L, whereas volume treated per cycle ranged from 0.88 to 2.5 L in accordance with fill time. Influent concentration varied from 300 to 1,425 mg COD/L, resulting in an applied volumetric organic load of 0.9 and 1.5 g COD/L.d. Recirculation flow rate was 20 L/h, and the reactor was maintained at 30 A degrees C. Values of organic matter removal efficiency of filtered effluent samples were below 71% in the batch operations and above 74% in the operations of fed batch followed by batch. Feeding wastewater during part of the operational cycle was beneficial to the system, as it resulted in indirect control over the conversion of substrate into intermediates that would negatively interfere with the biochemical reactions regarding the degradation of organic matter. As a result, the average substrate consumption increased, leading to higher organic removal efficiencies in the fed-batch operations.

AnSBBR Applied to the Treatment of Metalworking Fluid Wastewater: Effect of Organic and Shock Load

An investigation was performed regarding the application of a mechanically stirred anaerobic sequencing batch biofilm reactor containing immobilized biomass on inert polyurethane foam (AnSBBR) to the treatment of soluble metalworking fluids to remove organic matter and produce methane. The effect of increasing organic matter and reactor fill time, as well as shock load, on reactor stability and efficiency have been analyzed. The 5-L AnSBBR was operated at 30 A degrees C in 8-h cycles, agitation of 400 rpm, and treated 2.0 L effluent per cycle. Organic matter was increased by increasing the influent concentration (500, 1,000, 2,000, and 3,000 mg chemical oxygen demand (COD)/L). Fill times investigated were in the batch mode (fill time 10 min) and fed-batch followed by batch (fill time 4 h). In the batch mode, organic matter removal efficiencies were 87%, 86%, and 80% for influent concentrations of 500, 1,000, and 2,000 mgCOD/L (1.50, 3.12, and 6.08 gCOD/L.d), respectively. At 3,000 mgCOD/L (9.38 gCOD/L.d), operational stability could not be achieved. The reactor managed to maintain stability when a shock load twice as high the feed concentration was applied, evidencing the robustness of the reactor to potential concentration variations in the wastewater being treated. Increasing the fill time to 4 h did not improve removal efficiency, which was 72% for 2,000 mgCOD/L. Thus, gradual feeding did not improve organic matter removal. The concentration of methane formed at 6.08 gCOD/L was 5.20 mmolCH(4), which corresponded to 78% of the biogas composition. The behavior of the reactor during batch and fed-batch feeding could be explained by a kinetic model that considers organic matter consumption, production, and consumption of total volatile acids and methane production.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.