Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

Programming peculiarities in two cochlear implant users with superficial siderosis of the central nervous system

To report the audiological outcomes of cochlear implantation in two patients with severe to profound sensorineural hearing loss secondary to superficial siderosis of the CNS and discuss some programming peculiarities that were found in these cases. Retrospective review. Data concerning clinical presentation, diagnosis and audiological assessment pre- and post-implantation were collected of two patients with superficial siderosis of the CNS. Both patients showed good hearing thresholds but variable speech perception outcomes. One patient did not achieve open-set speech recognition, but the other achieved 70% speech recognition in quiet. Electrical compound action potentials could not be elicited in either patient. Map parameters showed the need for increased charge. Electrode impedances showed high longitudinal variability. The implants were fairly beneficial in restoring hearing and improving communication abilities although many reprogramming sessions have been required. The hurdle in programming was the need of frequent adjustments due to the physiologic variations in electrical discharges and neural conduction, besides the changes in the impedances. Patients diagnosed with superficial siderosis may achieve limited results in speech perception scores due to both cochlear and retrocochlear reasons. Careful counseling about the results must be given to the patients and their families before the cochlear implantation indication.

Integrated pulp and paper mill planning and scheduling

This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations. (C) 2012 Elsevier Ltd. All rights reserved.

The effect of a Lucia jig for 30 minutes on neuromuscular re-programming, in normal subjects

The Lucia jig is a technique that promotes neuromuscular reprogramming of the masticatory system and allows the stabilization of the mandible without the interference of dental contacts, maintaining the mandible position in harmonic condition with the musculature in normal subjects or in patients with temporomandibular dysfunction (TMD). This study aimed to electromyographically analyze the activity (RMS) of the masseter and temporal muscles in normal subjects (control group) during the use of an anterior programming device, the Lucia jig, in place for 0, 5, 10, 20 and 30 minutes to demonstrate its effect on the stomatognathic system. Forty-two healthy dentate individuals (aged 21 to 40 years) with normal occlusion and without parafunctional habits or ternporomandibular dysfunction (RDC/TMD) were evaluated on the basis of the electromyographic activity of the masseter and temporal muscles before placement of a neuromuscular re-programming device, the Lucia jig, on the upper central incisors. There were no statistically significant differences (p < 0.05) in the electromyographic activity of the masticatory muscles in the different time periods. The Lucia jig changed the electromyographic activity by promoting a neuromuscular reprogramming. In most of the time periods, it decreased the activation of the masticatory muscles, showing that this device has wide applicability in dentistry. The use of a Lucia jig over 0, 5, 10, 15, 20 and 30 minutes did not promote any statistically significant increase in muscle activity despite differences in the data, thus showing that this intra-oral device can be used in dentistry.

Implications of maternal nutrient restriction in transgenerational programming of hypertension and endothelial dysfunction across F1-F3 offspring

Aims: An extensive variety of prenatal insults are associated with an increased incidence of metabolic and cardiovascular disorders in adult life. We previously demonstrated that maternal global nutrient restriction during pregnancy leads to increased blood pressure and endothelial dysfunction in the adult offspring. This study aimed to assess whether prenatal exposure to nutritional insult has transgenerational effects in F-2 and F-3 offspring. Main methods: For this, female Wistar rats were randomly divided into two groups on day 1 of pregnancy: a control group fed standard chow ad libitum and a restricted group fed 50% of the ad libitum intake throughout gestation. At delivery, all animals were fed a standard laboratory chow diet. At 11 weeks of age, one female and one male from each restricted litter were randomly selected and mated with rats from another restricted litters in order to generate the F-2 offspring. The same procedure produced F-3 generation. Similarly, the rats in the control group were bred for each generation. Key Findings: Our findings show that the deleterious effects of maternal nutrient restriction to which the F-0 mothers were exposed may not be limited to the male first generation. In fact, we found that elevated blood pressure, an impaired vasodilatory response to acetylcholine and alterations in NO production were all transferred to the subsequent males from F-2 and F-3 generations. Significance: Our data show that global nutrient restriction during pregnancy results in a specific phenotype that can be passed transgenerationally to a second and third generation. (c) 2012 Elsevier Inc. All rights reserved.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Cochlear Implantation Via the Middle Fossa Approach: Surgical and Programming Considerations

Objectives: To report the results of cochlear implantation via the middle fossa approach in 4 patients, discuss the complications, and present a detailed description of the programming specifications in these cases. Study Design: Retrospective case review. Setting: Tertiary-care referral center with a well-established cochlear implant program. Patients: Four patients with bilateral canal wall down mastoid cavities who underwent the middle fossa approach for cochlear implantation. Interventions: Cochlear implantation and subsequent rehabilitation. A middle fossa approach with cochleostomy was successfully performed on the most superficial part of the apical turn in 4 patients. A Nucleus 24 cochlear implant system was used in 3 patients and a MED-EL Sonata Medium device in 1 patient. The single electrode array was inserted through a cochleostomy from the cochlear apex and occupied the apical, middle, and basal turns. Telemetry and intraoperative impedance recordings were performed at the end of surgery. A CT scan of the temporal bones was performed to document electrode insertion for all of the patients. Main Outcome Measures: Complications, hearing thresholds, and speech perception outcomes were evaluated. Results: Neural response telemetry showed present responses in all but 1 patient, who demonstrated facial nerve stimulation during the test. Open-set speech perception varied from 30% to 100%, despite the frequency allocation order of the MAP. Conclusion: Cochlear implantation via the middle cranial fossa is a safe approach, although it is a challenging procedure, even for experienced surgeons.

Stochastic gravito-inertial modes discovered by CoRoT in the hot Be star HD51452

Context. Be stars are rapidly rotating stars with a circumstellar decretion disk. They usually undergo pressure and/or gravity pulsation modes excited by the kappa-mechanism, i.e. an effect of the opacity of iron-peak elements in the envelope of the star. In the Milky Way, p-modes are observed in stars that are hotter than or equal to the B3 spectral type, while g-modes are observed at the B2 spectral type and cooler. Aims. We observed a B0IVe star, HD51452, with the high-precision, high-cadence photometric CoRoT satellite and high-resolution, ground-based HARPS and SOPHIE spectrographs to study its pulsations in great detail. We also used the lower resolution spectra available in the BeSS database. Methods. We analyzed the CoRoT and spectroscopic data with several methods: CLEAN-NG, FREQFIND, and a sliding window method. We also analyzed spectral quantities, such as the violet over red (V/R) emission variations, to obtain information about the variation in the circumstellar environment. We calculated a stellar structure model with the ESTER code to test the various interpretation of the results. Results. We detect 189 frequencies of variations in the CoRoT light curve in the range between 0 and 4.5 c d(-1). The main frequencies are also recovered in the spectroscopic data. In particular we find that HD51452 undergoes gravito-inertial modes that are not in the domain of those excited by the kappa-mechanism. We propose that these are stochastic modes excited in the convective zones and that at least some of them are a multiplet of r-modes (i.e. subinertial modes mainly driven by the Coriolis acceleration). Stochastically excited gravito-inertial modes had never been observed in any star, and theory predicted that their very low amplitudes would be undetectable even with CoRoT. We suggest that the amplitudes are enhanced in HD51452 because of the very rapid stellar rotation. In addition, we find that the amplitude variations of these modes are related to the occurrence of minor outbursts. Conclusions. Thanks to CoRoT data, we have detected a new kind of pulsations in HD51452, which are stochastically excited gravito-inertial modes, probably due to its very rapid rotation. These modes are probably also present in other rapidly rotating hot Be stars.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

An integer linear programming approach for bilinear integer programming

We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear P. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. (C) 2011 Elsevier B.V. All rights reserved.

Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.