An oracle approach for interaction neighborhood estimation in random fields

We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.

2-Cyclohexyl-4-methyltetrahydropyran-4-ol

In the title compound, C(12)H(22)O(2), the 4-methyltetrahydropyran-4-ol ring adopts a conformation close to that of a chair and with the two O atoms syn; the cyclohexyl group occupies an equatorial position and adopts a chair conformation. In the crystal packing, supramolecular chains along the b axis are sustained by O-H center dot center dot center dot O hydrogen bonds. These are connected into undulating layers in the ab plane by C-H center dot center dot center dot O interactions.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

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.

Multiple random crack propagation using a boundary element formulation

This paper proposes a boundary element method (BEM) model that is used for the analysis of multiple random crack growth by considering linear elastic fracture mechanics problems and structures subjected to fatigue. The formulation presented in this paper is based on the dual boundary element method, in which singular and hyper-singular integral equations are used. This technique avoids singularities of the resulting algebraic system of equations, despite the fact that the collocation points coincide for the two opposite crack faces. In fracture mechanics analyses, the displacement correlation technique is applied to evaluate stress intensity factors. The maximum circumferential stress theory is used to evaluate the propagation angle and the effective stress intensity factor. The fatigue model uses Paris` law to predict structural life. Examples of simple and multi-fractured structures loaded until rupture are considered. These analyses demonstrate the robustness of the proposed model. In addition, the results indicate that this formulation is accurate and can model localisation and coalescence phenomena. (C) 2010 Elsevier Ltd. All rights reserved.

The random barrier-crossing problem

This paper addresses the time-variant reliability analysis of structures with random resistance or random system parameters. It deals with the problem of a random load process crossing a random barrier level. The implications of approximating the arrival rate of the first overload by an ensemble-crossing rate are studied. The error involved in this so-called ""ensemble-crossing rate"" approximation is described in terms of load process and barrier distribution parameters, and in terms of the number of load cycles. Existing results are reviewed, and significant improvements involving load process bandwidth, mean-crossing frequency and time are presented. The paper shows that the ensemble-crossing rate approximation can be accurate enough for problems where load process variance is large in comparison to barrier variance, but especially when the number of load cycles is small. This includes important practical applications like random vibration due to impact loadings and earthquake loading. Two application examples are presented, one involving earthquake loading and one involving a frame structure subject to wind and snow loadings. (C) 2007 Elsevier Ltd. All rights reserved.

Performance evaluation of packing materials in the removal of hydrogen sulphide in gas-phase biofilters: Polyurethane foam, sugarcane bagasse, and coconut fibre

The main objective of this work was to investigate three packing materials (polyurethane foam, sugar-cane bagasse, and coconut fibre) for biofiltration of a gaseous mixture containing hydrogen sulphide (H(2)S). Mixed cultures were obtained from two sources, aerated submerged biofilters and activated sludge, and were utilised as inoculums. Biofilters reached 100% removal efficiency after two clays of operation. The empty bed residence time was 495 for each of the biofilters. The reactors were operated simultaneously, and the inlet concentrations of H(2)S varied between 184 and 644 ppmv during the long-term continuous operation of the biofilters (100 clays). Average removal efficiencies remained above 99.3%, taking into consideration the entire period of operation. Average elimination capacities reached by the biofilters packed with polyurethane foam, coconut fibre, and sugarcane bagasse were in the range of 17.8-66.6; 18.9-68.8, and 18.7-72.9g m(-3) h(-1), respectively. Finally, we concluded that the packing materials tested in this work are appropriate for the long-term biofiltration of hydrogen sulphide. (C) 2010 Elsevier B.V. All rights reserved.

CONCENTRATION FIELDS NEAR AIR-WATER INTERFACES DURING INTERFACIAL MASS TRANSPORT: OXYGEN TRANSPORT AND RANDOM SQUARE WAVE ANALYSIS

Mass transfer across a gas-liquid interface was studied theoretically and experimentally, using transfer of oxygen into water as the gas-liquid system. The experimental results support the conclusions of a theoretical description of the concentration field that uses random square waves approximations. The effect of diffusion over the concentration records was quantified. It is shown that the peak of the normalized rills concentration fluctuation profiles must be lower than 0.5, and that the position of the peak of the rms value is an adequate measure of the thickness of the diffusive layer. The position of the peak is the boundary between the regions more subject to molecular diffusion or to turbulent transport of dissolved mass.

Simulation of the Barkhausen Noise using random field Ising model with long-range interaction

We present a method to simulate the Magnetic Barkhausen Noise using the Random Field Ising Model with magnetic long-range interaction. The method allows calculating the magnetic flux density behavior in particular sections of the lattice reticule. The results show an internal demagnetizing effect that proceeds from the magnetic long-range interactions. This demagnetizing effect induces the appearing of a magnetic pattern in the region of magnetic avalanches. When compared with the traditional method, the proposed numerical procedure neatly reduces computational costs of simulation. (c) 2008 Published by Elsevier B.V.

Replacement of Trays by Packing To Increase the Absorption Capacity of Acetone during Cellulose Acetate Spinning

All textile uses of cellulose acetate involve acetone recovery, which, because of safety issues, results in large installations, in order to work with dilute streams. This compromises the efficiency of all of the involved unit operations, in this case, acetone absorption in cold water, acetone distillation, and water chilling, making them more expensive. The present article proposes the improvement of the absorption of acetone in water, traditionally performed with sieve trays, by using structured packing instead. The advantageous implementation was enabled through the utilization of a calculation methodology based on concepts of thermodynamic equilibrium of the binary acetone/water system and empirical relations that allow the evaluation of the hydrodynamics of the proposed modification.

Exploring the random genesis of co-occurrence networks

Using the network random generation models from Gustedt (2009)[23], we simulate and analyze several characteristics (such as the number of components, the degree distribution and the clustering coefficient) of the generated networks. This is done for a variety of distributions (fixed value, Bernoulli, Poisson, binomial) that are used to control the parameters of the generation process. These parameters are in particular the size of newly appearing sets of objects, the number of contexts in which new elements appear initially, the number of objects that are shared with `parent` contexts, and, the time period inside which a context may serve as a parent context (aging). The results show that these models allow to fine-tune the generation process such that the graphs adopt properties as can be found in real world graphs. (C) 2011 Elsevier B.V. All rights reserved.

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Can Eucalyptus invade native forest fragments close to commercial stands?

Some Eucalyptus species are widely used as a plantation crop in tropical and subtropical regions. One reason for this is the diversity of end uses, but the main reason is the high level of wood production obtained from commercial plantings. With the advancement of biotechnology it will be possible to expand the geographical area in which eucalypts can be used as commercial plantation crops, especially in regions with current climatic restrictions. Despite the popularity of eucalypts and their increasing range, questions still exist, in both traditional planting areas and in the new regions: Can eucalypts invade areas of native vegetation, causing damage to natural ecosystems biodiversity? The objective of this study it was to assess whether eucalypts can invade native vegetation fragments in proximity to commercial stands, and what factors promote this invasive growth. Thus, three experiments were established in forest fragments located in three different regions of Brazil. Each experiment was composed of 40 plots (1 m(2) each one), 20 plots located at the border between the forest fragment and eucalypts plantation, and 20 plots in the interior of the forest fragments. In each experimental site, the plots were paired by two soil exposure conditions, 10 plots in natural conditions and 10 plots with soil exposure (no plant and no litter). During the rainy season, 2 g of eucalypts seeds were sown in each plot, including Eucalyptus grandis or a hybrid of E. urophylla x E. grandis, the most common commercial eucalypt species planted in the three region. At 15, 30, 45, 90, 180, 270 and 360 days after sowing, we assessed the number of seedlings of eucalypts and the number of seedlings of native species resulting from natural regeneration. Fifteen days after sowing, the greatest number of eucalypts seedlings (37 m(-2)) was observed in the plots with lower luminosity and exposed soil. Also, for native species, it was observed that exposed soil improved natural germination reaching the highest number of 163 seedlings per square meter. Site and soil exposure were the factors that have the greatest influence on seed germination of both eucalypt and native species. However, 270 days after sowing, eucalypt seedlings were not observed at any of the three experimental sites. The result shows the inability of eucalypts to adapt to condition outside of their natural range. However, native species demonstrated their strong capacity for natural regeneration in forest fragments under the same conditions where eucalypts were seeded. (C) 2011 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.