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.

Gaseous and fluvial carbon export from an Amazon forest watershed

The transfer of carbon (C) from Amazon forests to aquatic ecosystems as CO(2) supersaturated in groundwater that outgases to the atmosphere after it reaches small streams has been postulated to be an important component of terrestrial ecosystem C budgets. We measured C losses as soil respiration and methane (CH(4)) flux, direct CO(2) and CH(4) fluxes from the stream surface and fluvial export of dissolved inorganic C (DIC), dissolved organic C (DOC), and particulate C over an annual hydrologic cycle from a 1,319-ha forested Amazon perennial first-order headwater watershed at Tanguro Ranch in the southern Amazon state of Mato Grosso. Stream pCO(2) concentrations ranged from 6,491 to 14,976 mu atm and directly-measured stream CO(2) outgassing flux was 5,994 +/- A 677 g C m(-2) y(-1) of stream surface. Stream pCH(4) concentrations ranged from 291 to 438 mu atm and measured stream CH(4) outgassing flux was 987 +/- A 221 g C m(-2) y(-1). Despite high flux rates from the stream surface, the small area of stream itself (970 m(2), or 0.007% of watershed area) led to small directly-measured annual fluxes of CO(2) (0.44 +/- A 0.05 g C m(2) y(-1)) and CH(4) (0.07 +/- A 0.02 g C m(2) y(-1)) per unit watershed land area. Measured fluvial export of DIC (0.78 +/- A 0.04 g C m(-2) y(-1)), DOC (0.16 +/- A 0.03 g C m(-2) y(-1)) and coarse plus fine particulate C (0.001 +/- A 0.001 g C m(-2) y(-1)) per unit watershed land area were also small. However, stream discharge accounted for only 12% of the modeled annual watershed water output because deep groundwater flows dominated total runoff from the watershed. When C in this bypassing groundwater was included, total watershed export was 10.83 g C m(-2) y(-1) as CO(2) outgassing, 11.29 g C m(-2) y(-1) as fluvial DIC and 0.64 g C m(-2) y(-1) as fluvial DOC. Outgassing fluxes were somewhat lower than the 40-50 g C m(-2) y(-1) reported from other Amazon watersheds and may result in part from lower annual rainfall at Tanguro. Total stream-associated gaseous C losses were two orders of magnitude less than soil respiration (696 +/- A 147 g C m(-2) y(-1)), but total losses of C transported by water comprised up to about 20% of the +/- A 150 g C m(-2) (+/- 1.5 Mg C ha(-1)) that is exchanged annually across Amazon tropical forest canopies.

Dissolved carbon in an urban area of a river in the Brazilian Amazon

The main objective of this study was to evaluate dissolved organic and inorganic carbon dynamics along upstream and downstream reaches of the Acre River draining the city of Rio Branco, in the state of Acre, Brazil. Dissolved organic carbon (DOC) concentrations in the Acre River were significantly higher during the wet season, ranging from 385 +/- A 160 to 430 +/- A 131 mu M among the stations, with no difference in upstream and downstream concentrations. Dissolved inorganic carbon (DIC) showed an inverse pattern, with higher concentrations in the dry season, ranging from 816 +/- A 215 to 998 +/- A 754 mu M among the stations, as well as no difference in upstream and downstream DIC concentrations. Bicarbonate was the dominant DIC fraction and was mainly observed during the dry season. Due to lower pH values during the wet season, CO(2) partial pressure (pCO(2)) in the Acre River was higher in the wet season, with values ranging from 4,567 +/- A 1,813 to 4,893 +/- A 837 ppm among the stations. Our results indicate that, although the Acre River drains a large city with significant sewage disposal into the river, seasonal hydrological processes are the main driver of dissolved carbon dynamics, even in the downstream study reach directly influenced by urbanization.

Spatio-temporal patterns of throughfall and solute deposition in an open tropical rain forest

The brief interaction of precipitation with a forest canopy can create a high spatial variability of both throughfall and solute deposition. We hypothesized that (i) the variability in natural forest systems is high but depends on system-inherent stability, (ii) the spatial variability of solute deposition shows seasonal dynamics depending on the increase in rainfall frequency, and (iii) spatial patterns persist only in the short-term. The study area in the north-western Brazilian state of Rondonia is subject to a climate with a distinct wet and dry season. We collected rain and throughfall on an event basis during the early wet season (n = 14) and peak of the wet season (n = 14) and analyzed the samples for pH and concentrations of NH4+, Na+, K+, Ca2+ Mg2+,, Cl-, NO3-, SO42- and DOC. The coefficient 3 4 cient of variation for throughfall based on both sampling intervals was 29%, which is at the lower end of values reported from other tropical forest sites, but which is higher than in most temperate forests. Coefficients of variation of solute deposition ranged from 29% to 52%. This heterogeneity of solute deposition is neither particularly high nor particularly tow compared with a range of tropical and temperate forest ecosystems. We observed an increase in solute deposition variability with the progressing wet season, which was explained by a negative correlation between heterogeneity of solute deposition and antecedent dry period. The temporal stability of throughfall. patterns was Low during the early wet season, but gained in stability as the wet season progressed. We suggest that rapid plant growth at the beginning of the rainy season is responsible for the lower stability, whereas less vegetative activity during the later rainy season might favor the higher persistence of ""hot"" and ""cold"" spots of throughfall. quantities. The relatively high stability of throughfall patterns during later stages of the wet season may influence processes at the forest floor and in the soil. Solute deposition patterns showed less clear trends but all patterns displayed a short-term stability only. The weak stability of those patterns is apt to impede the formation of solute deposition -induced biochemical microhabitats in the soil. (C) 2008 Elsevier B.V. All rights reserved.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

H(infinity) filtering for rectangular discrete-time descriptor systems

This paper deals with the H(infinity) recursive estimation problem for general rectangular time-variant descriptor systems in discrete time. Riccati-equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory. In this approach, the nature determines a state sequence seeking to maximize the estimation cost, whereas the estimator tries to find an estimate that brings the estimation cost to a minimum. A solution exists for a specified gamma-level if the resulting cost is positive. In order to present some computational alternatives to the H(infinity) filters developed, they are rewritten in information form along with the respective array algorithms. (C) 2009 Elsevier Ltd. All rights reserved.

Biodegradability and toxicity assessment of bleach plant effluents treated anaerobically

As part of an experimental project on the treatment of bleach plant effluents the results of biodegradability and toxicity assessment of effluents from a bench-scale horizontal anaerobic immobilized bioreactor (HAIB) are discussed in this paper. The biodegradability of the bleach plant effluents from a Kraft pulp mill treated in the HAIB was evaluated using the modified Zahn-Wellens test. The inoculum came from a pulp mill wastewater treatment plant and the dissolved organic carbon (DOC) was used as the indicator of organic matter removal. The acute and chronic toxicity removal during the anaerobic treatment was estimated using Daphnia similis and Ceriodaphnia silvestrii respectively. Moreover, the evaluation of chromosome aberrations (CA), micronucleus frequencies (MN) and mitotic index (IM) in Allium cepa cells were used as genotoxicity indicators. The results indicate that the effluents from the anaerobic reactor are amenable to aerobic polishing. Acute and chronic toxicity were reduced by 90 and 81%, respectively. The largest CA and MN incidence in the meristematic cells of A. cepa were observed after exposure to the raw bleach plant effluent. The HAIB was able to reduce the acute and chronic toxicity as well as chromosome aberrations and the occurrence of micronucleus.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

A safety assessment methodology applied to CNS/ATM-based air traffic control system

In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm, based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining ""absolute"" and ""relative"" safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 [14], using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the ""Automatic Dependent Surveillance-Broadcasting"" (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric. (C) 2011 Elsevier Ltd. All rights reserved.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

USE OF SOLAR ENERGY IN THE TREATMENT OF WATER CONTAMINATED WITH PHENOL BY PHOTOCHEMICAL PROCESSES

The solar driven photo-Fenton process for treating water containing phenol as a contaminant has been evaluated by means of pilot-scale experiments with a parabolic trough solar reactor (PTR). The effects of Fe(II) (0.04-1.0 mmol L(-1)), H(2)O(2) (7-270 mmol L(-1)), initial phenol concentration (100 and 500 mg C L(-1)), solar radiation, and operation mode (batch and fed-batch) on the process efficiency were investigated. More than 90% of the dissolved organic carbon (DOC) was removed within 3 hours of irradiation or less, a performance equivalent to that of artificially-irradiated reactors, indicating that solar light can be used either as an effective complementary or as an alternative source of photons for the photo-Fenton degradation process. A non-linear multivariable model based on a neural network was fit to the experimental results of batch-mode experiments in order to evaluate the relative importance of the process variables considered on the DOC removal over the reaction time. This included solar radiation, which is not a controlled variable. The observed behavior of the system in batch-mode was compared with fed-batch experiments carried out under similar conditions. The main contribution of the study consists of the results from experiments under different conditions and the discussion of the system behavior. Both constitute important information for the design and scale-up of solar radiation-based photodegradation processes.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Carbon and nitrogen cycling in a tropical Brazilian soil cropped with sugarcane and irrigated with wastewater

Carbon (C) and nitrogen (N) dynamics in agro-systems can be altered as a consequence of treated sewage effluent (TSE) irrigation. The present study evaluated the effects of TSE irrigation over 16 months on N concentrations in sugarcane (leaves, stalks and juice), total soil carbon (TC), total soil nitrogen (TN), NO(3)(-)-N in soil and nitrate (NO(3)(-)) and dissolved organic carbon (DOC) in soil solution. The soil was classified as an Oxisol and samplings were carried out during the first productive crop cycle, from February 2005 (before planting) to September 2006 (after sugarcane harvest and 16 months of TSE irrigation). The experiment was arranged in a complete block design with five treatments and four replicates. Irrigated plots received 50% of the recommended mineral N fertilization and 100% (T100), 125% (T125), 150% (T150) and 200% (T200) of crop water demand. No mineral N and irrigation were applied to the control plots. TSE irrigation enhanced sugarcane yield but resulted in total-N inputs(804-1622 kg N ha(-1)) greater than exported N (463-597 kg N ha(-1)). Hence, throughout the irrigation period, high NO(3)(-) concentrations (up to 388 mg L(-1) at T200) and DOC (up to 142 mg L(-1) at T100) were measured in soil solution below the root zone, indicating the potential of groundwater contamination. TSE irrigation did not change soil TC and TN. (C) 2009 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved