Characterizing suspended sediments from the Piracicaba River Basin by means of k(0)-INAA

The inorganic chemical characterization of suspended sediments is of utmost relevance for the knowledge of the dynamics and movement of chemical elements in the aquatic and wet ecosystems. Despite the complexity of the effective design for studying this ecological compartment, this work has tested a procedure for analyzing suspended sediments by instrumental neutron activation analysis, k(0) method (k(0)-INAA). The chemical elements As, Ba, Br, Ca, Ce, Co, Cr, Cs, Eu, Fe, Hf, Fig, K, La, Mo, Na, Ni, Rb, Sb, Sc, Se, Sm, Sr, Ta, Tb, Th, Yb and Zn were quantified in the suspended sediment compartment by means of k(0)-INAA. When compared with World Average for rivers, high mass fractions of Fe (222,900 mg/kg), Ba (4990 mg/kg), Zn (1350 mg/kg), Cr (646 mg/kg), Co (74.5 mg/kg), Br (113 mg/kg) and Mo (31.9 mg/kg) were quantified in suspended sediments from the Piracicaba River, the Piracicamirim Stream and the Marins Stream. Results of the principal component analysis for standardized chemical element mass fractions indicated an intricate correlation among chemical elements evaluated, as a response of the contribution of natural and anthropogenic sources of chemical elements for ecosystems. (C) 2010 Elsevier B.V. All rights reserved.

Unraveling the Na,K-ATPase alpha(4) Subunit Assembling Induced by Large Amounts of C(12)E(8) by Means of Small-Angle X-ray Scattering

In the current work, we studied the effect of the nonionic detergent dodecyloctaethyleneglycol, C(12)E(8), on the structure and oligomeric form of the Na,K-ATPase membrane enzyme (sodium-potassium pump) in aqueous suspension, by means of small-angle X-ray scattering (SAXS). Samples composed of 2 mg/mL of Na,K-ATPase, extracted from rabbit kidney medulla, in the presence of a small amount of C(12)E(8) (0.005 mg/mL) and in larger concentrations ranging from 2.7 to 27 mg/mL did not present catalytic activity. Under this condition, an oligomerization of the alpha subunits is expected. SAXS data were analyzed by means of a global fitting procedure supposing that the scattering is due to two independent contributions: one coming from the enzyme and the other one from C(12)E(8) micelles. In the small detergent content (0.005 mg/mL), the SAXS results evidenced that Na,K-ATPase is associated into aggregates larger than (alpha beta)(2) form. When 2.7 mg/mL of C(12)E(8) is added, the data analysis revealed the presence of alpha(4) aggregates in the solution and some free micelles. Increasing the detergent amount up to 27 mg/mL does not disturb the alpha(4) aggregate: just more micelles of the same size and shape are proportionally formed in solution. We believe that our results shed light on a better understanding of how nonionic detergents induce subunit dissociation and reassembling to minimize the exposure of hydrophobic residues to the aqueous solvent.

Standard errors of fitted component means of normal mixtures

In this paper use consider the problem of providing standard errors of the component means in normal mixture models fitted to univariate or multivariate data by maximum likelihood via the EM algorithm. Two methods of estimation of the standard errors are considered: the standard information-based method and the computationally-intensive bootstrap method. They are compared empirically by their application to three real data sets and by a small-scale Monte Carlo experiment.

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

Constraint algorithm for k-presymplectic Hamiltonian systems. Application to singular field theories

The k-symplectic formulation of field theories is especially simple, since only tangent and cotangent bundles are needed in its description. Its defining elements show a close relationship with those in the symplectic formulation of mechanics. It will be shown that this relationship also stands in the presymplectic case. In a natural way,one can mimick the presymplectic constraint algorithm to obtain a constraint algorithmthat can be applied to k-presymplectic field theory, and more particularly to the Lagrangian and Hamiltonian formulations offield theories defined by a singular Lagrangian, as well as to the unified Lagrangian-Hamiltonian formalism (Skinner--Rusk formalism) for k-presymplectic field theory. Two examples of application of the algorithm are also analyzed.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

An algorithm for identifying agent-k-linked allocations in economies with indivisibilities

We consider envy-free (and budget-balanced) rules that are least manipulable with respect to agents counting or with respect to utility gains. Recently it has been shown that for any profile of quasi-linear preferences, the outcome of any such least manipulable envy-free rule can be obtained via agent-k-linked allocations. This note provides an algorithm for identifying agent-k-linked allocations.

Determinação de caminhos k-críticos em redes PERT

Neste trabalho, apresenta-se um estudo sobre os principais métodos para identificar os caminhos de maior duração em redes PERT, denominados na literatura de caminhos k-críticos (quando k = 1, tem-se o caminho mais longo, conhecido tradicionalmente por caminho crítico; quando k = 2, tem-se o segundo caminho mais longo, e assim sucessivamente). São discutidos três algoritmos apresentados na literatura e propõe-se um novo procedimento, denominado algoritmo da folga mínima, que apresenta algumas vantagens sobre os anteriores. O comportamento do algoritmo da folga mínima, quando aplicado a redes PERT, é verificado por meio de simulação.

Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm

The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

Comparison of nitrogen adsorption at 77 K on non-porous silica and pore wall of MCM-41 materials by means of density functional theory

Nitrogen adsorption on a surface of a non-porous reference material is widely used in the characterization. Traditionally, the enhancement of solid-fluid potential in a porous solid is accounted for by incorporating the surface curvature into the solid-fluid Potential of the flat reference surface. However, this calculation procedure has not been justified experimentally. In this paper, we derive the solid-fluid potential of mesoporous MCM-41 solid by using solely the adsorption isotherm of that solid. This solid-fluid potential is then compared with that of the non-porous reference surface. In derivation of the solid-fluid potential for both reference surface and mesoporous MCM-41 silica (diameter ranging front 3 to 6.5 nm) we employ the nonlocal density functional theory developed for amorphous solids. It is found that, to out, surprise, the solid-fluid potential of a porous solid is practically the same as that for the reference surface, indicating that there is no enhancement due to Surface curvature. This requires further investigations to explain this unusual departure from our conventional wisdom of curvature-induced enhancement. Accepting the curvature-independent solid-fluid potential derived from the non-porous reference surface, we analyze the hysteresis features of a series of MCM-41 samples. (c) 2005 Elsevier Inc. All rights reserved.

Distributed Genetic Algorithm Implementation by Means of Remote Methods Invocation Technique – Java RMI

The aim of this work is distributed genetic algorithm implementation (so called island algorithm) to accelerate the optimum searching process in space of solutions. Distributed genetic algorithm has also smaller chances to fall in local optimum. This conception depends on mutual cooperation of the clients which realize separate working of genetic algorithms on local machines. As a tool for implementation of distributed genetic algorithm, created to produce net's applications Java technology was chosen. In Java technology, there is a technique of remote methods invocation - Java RMI. By means of invoking remote methods it can send objects between clients and server RMI.

Vascular relaxation of canine visceral arteries after ischemia by means of supraceliac aortic cross-clamping followed by reperfusion

Background: The supraceliac aortic cross-clamping can be an option to save patients with hipovolemic shock due to abdominal trauma. However, this maneuver is associated with ischemia/reperfusion (I/R) injury strongly related to oxidative stress and reduction of nitric oxide bioavailability. Moreover, several studies demonstrated impairment in relaxation after I/R, but the time course of I/R necessary to induce vascular dysfunction is still controversial. We investigated whether 60 minutes of ischemia followed by 30 minutes of reperfusion do not change the relaxation of visceral arteries nor the plasma and renal levels of malondialdehyde (MDA) and nitrite plus nitrate (NOx). Methods: Male mongrel dogs (n = 27) were randomly allocated in one of the three groups: sham (no clamping, n = 9), ischemia (supraceliac aortic cross-clamping for 60 minutes, n = 9), and I/R (60 minutes of ischemia followed by reperfusion for 30 minutes, n = 9). Relaxation of visceral arteries (celiac trunk, renal and superior mesenteric arteries) was studied in organ chambers. MDA and NOx concentrations were determined using a commercially available kit and an ozone-based chemiluminescence assay, respectively. Results: Both acetylcholine and calcium ionophore caused relaxation in endothelium-intact rings and no statistical differences were observed among the three groups. Sodium nitroprusside promoted relaxation in endothelium-denuded rings, and there were no inter-group statistical differences. Both plasma and renal concentrations of MDA and NOx showed no significant difference among the groups. Conclusion: Supraceliac aortic cross-clamping for 60 minutes alone and followed by 30 minutes of reperfusion did not impair relaxation of canine visceral arteries nor evoke biochemical alterations in plasma or renal tissue.