Quantification of permanent and variable charges in reference soils of the State of Pernambuco, Brazil

The electrical charges in soil particles are divided into structural or permanent charges and variable charges. Permanent charges develop on the soil particle surface by isomorphic substitution. Variable charges arise from dissociation and association of protons (H+), protonation or deprotonation, and specific adsorption of cations and anions. The aim of this study was to quantify the permanent charges and variable charges of Reference Soils of the State of Pernambuco, Brazil. To do so, 24 subsurface profiles from different regions (nine in the Zona da Mata, eight in the Agreste, and seven in the Sertão) were sampled, representing approximately 80 % of the total area of the state. Measurements were performed using cesium chloride solution. Determination was made of the permanent charges and the charges in regard to the hydroxyl functional groups through selective ion exchange of Cs+ by Li+ and Cs+ by NH4+, respectively. All the soils analyzed exhibited variable cation exchange capacity, with proportions from 0.16 to 0.60 and an average of 0.40 when related to total cation exchange capacity.

Motion of a classical charged particle

The Lorentz-Dirac equation is not an unavoidable consequence of solely linear and angular momenta conservation for a point charge. It also requires an additional assumption concerning the elementary character of the charge. We here use a less restrictive elementarity assumption for a spinless charge and derive a system of conservation equations that are not properly the equation of motion because, as it contains an extra scalar variable, the future evolution of the charge is not determined. We show that a supplementary constitutive relation can be added so that the motion is determined and free from the troubles that are customary in the Lorentz-Dirac equation, i.e., preacceleration and runaways.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Telegrapher's equation with variable propagation speeds

All derivations of the one-dimensional telegraphers equation, based on the persistent random walk model, assume a constant speed of signal propagation. We generalize here the model to allow for a variable propagation speed and study several limiting cases in detail. We also show the connections of this model with anomalous diffusion behavior and with inertial dichotomous processes.

The Foundational Significance of Leggett's Non-local Hidden-Variable Theories

Laudisa (Found. Phys. 38:1110-1132, 2008) claims that experimental research on the class of non-local hidden-variable theories introduced by Leggett is misguided, because these theories are irrelevant for the foundations of quantum mechanics. I show that Laudisa's arguments fail to establish the pessimistic conclusion he draws from them. In particular, it is not the case that Leggett-inspired research is based on a mistaken understanding of Bell's theorem, nor that previous no-hidden-variable theorems already exclude Leggett's models. Finally, I argue that the framework of Bohmian mechanics brings out the importance of Leggett tests, rather than proving their irrelevance, as Laudisa supposes.

Surface Complexation Modeling in Variable Charge Soils: Charge Characterization by Potentiometric Titration

ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation), considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.

Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

Exact temporal evolution for some non-linear diffusion process

Exact solutions to FokkerPlanck equations with nonlinear drift are considered. Applications of these exact solutions for concrete models are studied. We arrive at the conclusion that for certain drifts we obtain divergent moments (and infinite relaxation time) if the diffusion process can be extended without any obstacle to the whole space. But if we introduce a potential barrier that limits the diffusion process, moments converge with a finite relaxation time.

Variational localized-site cluster expansions. X. Dimerization in linear Heisenberg chains

Ground-state instability to bond alternation in long linear chains is considered from the point of view of valence-bond (VB) theory. This instability is viewed as the consequence of a long-range order (LRO) which is expected if the ground state is reasonably described in terms of the Kekulé states (with nearest-neighbor singlet pairing). It is argued that the bond alternation and associated LRO predicted by this simple, VB picture is retained for certain linear Heisenberg models; many-body VB calculations on spin s=1 / 2 and s=1 chains are carried out in a test of this argument.

Water-Stable Aggregates and Associated Carbon in a Subtropical Rice Soil Under Variable Tillage

ABSTRACT Tillage systems can influence C sequestration by changing aggregate formation and C distribution within the aggregate. This study was undertaken to explore the impact of no-tillage without straw (NT-S) and with straw (NT+S), and moldboard plow without straw (MP-S) and with straw (MP+S), on soil aggregation and aggregate-associated C after six years of double rice planting in a Hydragric Anthrosol in Guangxi, southwest of China. Soil samples of 0.00-0.05, 0.05-0.20 and 0.20-0.30 m layers were wet-sieved and divided into four aggregate-size classes, >2 mm, 2.00-0.25 mm, 0.25-0.053 and <0.053 mm, respectively, for measuring aggregate associated C and humic and fulvic acids. Results showed that the soil organic carbon (SOC) stock in bulk soil was 40.2-51.1 % higher in the 0.00-0.05 m layer and 11.3-17.0 % lower in the 0.05-0.20 m layer in NT system (NT+S and NT-S) compared to the MP system (MP+S and MP-S), respectively. However, no statistical difference was found across the whole 0.00-0.30 m layer. The NT system increased the proportion of >2 mm aggregate fraction and reduced the proportion of <0.053 mm aggregates in both 0.00-0.05 and 0.05-0.20 m layers. The SOC concentration, SOC stock and humic and fulvic acids within the >0.25 mm macroaggregate fraction also significantly increased in the 0.00-0.5 m layer in NT system. However, those within the 2.00-0.25 mm aggregate fraction were significantly reduced in the 0.05-0.200 m layer under NT system. Straw incorporation increased not only the SOC stock in bulk soil, but also the proportion of macroaggregate, aggregate associated with SOC and humic and fulvic acids concentration within the aggregate. The effect of straw on C sequestration might be dependent on the location of straw incorporation. In conclusion, the NT system increased the total SOC accumulation and humic and fulvic acids within macroaggregates, thus contributing to C sequestration in the 0.00-0.05 m layer.

Genetic basis and variable phenotypic expression of Kallmann syndrome: towards a unifying theory.

Idiopathic hypogonadotropic hypogonadism (IHH) is defined by absent or incomplete puberty and characterised biochemically by low levels of sex steroids, with low or inappropriately normal gonadotropin hormones. IHH is frequently accompanied by non-reproductive abnormalities, most commonly anosmia, which is present in 50-60% of cases and defines Kallmann syndrome. The understanding of IHH has undergone rapid evolution, both in respect of genetics and breadth of phenotype. Once considered in monogenic Mendelian terms, it is now more coherently understood as a complex genetic condition. Oligogenic and complex genetic-environmental interactions have now been identified, with physiological and environmental factors interacting in genetically susceptible individuals to alter the clinical course and phenotype. These potentially link IHH to ancient evolutionary pressures on the ancestral human genome.

To select or to weigh: a comparative study of linear combination schemes for superparent-one-dependence estimators

We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.

Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.

Linear least squares estimation of the first order moving average parameter

We propose an iterative procedure to minimize the sum of squares function which avoids the nonlinear nature of estimating the first order moving average parameter and provides a closed form of the estimator. The asymptotic properties of the method are discussed and the consistency of the linear least squares estimator is proved for the invertible case. We perform various Monte Carlo experiments in order to compare the sample properties of the linear least squares estimator with its nonlinear counterpart for the conditional and unconditional cases. Some examples are also discussed