Twofold adaptive partition of unity implicits

Partition of Unity Implicits (PUI) has been recently introduced for surface reconstruction from point clouds. In this work, we propose a PUI method that employs a set of well-observed solutions in order to produce geometrically pleasant results without requiring time consuming or mathematically overloaded computations. One feature of our technique is the use of multivariate orthogonal polynomials in the least-squares approximation, which allows the recursive refinement of the local fittings in terms of the degree of the polynomial. However, since the use of high-order approximations based only on the number of available points is not reliable, we introduce the concept of coverage domain. In addition, the method relies on the use of an algebraically defined triangulation to handle two important tasks in PUI: the spatial decomposition and an adaptive polygonization. As the spatial subdivision is based on tetrahedra, the generated mesh may present poorly-shaped triangles that are improved in this work by means a specific vertex displacement technique. Furthermore, we also address sharp features and raw data treatment. A further contribution is based on the PUI locality property that leads to an intuitive scheme for improving or repairing the surface by means of editing local functions.

Treadmill exercise testing of asymptomatic men and women without evidence of heart disease

The aim of this study was to test the hypothesis of differences in performance including differences in ST-T wave changes between healthy men and women submitted to an exercise stress test. Two hundred (45.4%) men and 241 (54.6%) women (mean age: 38.7 ± 11.0 years) were submitted to an exercise stress test. Physiologic and electrocardiographic variables were compared by the Student t-test and the chi-square test. To test the hypothesis of differences in ST-segment changes, data were ranked with functional models based on weighted least squares. To evaluate the influence of gender and age on the diagnosis of ST-segment abnormality, a logistic model was adjusted; P < 0.05 was considered to be significant. Rate-pressure product, duration of exercise and estimated functional capacity were higher in men (P < 0.05). Sixteen (6.7%) women and 9 (4.5%) men demonstrated ST-segment upslope ≥0.15 mV or downslope ≥0.10 mV; the difference was not statistically significant. Age increase of one year added 4% to the chance of upsloping of segment ST ≥0.15 mV or downsloping of segment ST ≥0.1 mV (P = 0.03; risk ratio = 1.040, 95% confidence interval (CI) = 1.002-1.080). Heart rate recovery was higher in women (P < 0.05). The chance of women showing an increase of systolic blood pressure ≤30 mmHg was 85% higher (P = 0.01; risk ratio = 1.85, 95%CI = 1.1-3.05). No significant difference in the frequency of ST-T wave changes was observed between men and women. Other differences may be related to different physical conditioning.

Chemometric Studies on Natural Products as Potential Inhibitors of the NADH Oxidase from Trypanosoma cruzi Using the VolSurf Approach

Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

COOP/WONCA Charts as a Screen for Mental Disorders in Primary Care

PURPOSE most people with mental disorders receive treatment in primary care. The charts developed by the Dartmouth Primary Care Cooperative Research Network (COOP) and the World Organization of National Colleges, Academies, and Academic Associations of General Practitioners/Family Physicians (WONCA) have not yet been evaluated as a screen for these disorders, using a structured psychiatric interview by an expert or considering diagnoses other than depression. We evaluated the validity and feasibility of the COOP/WONCA Charts as a mental disorders screen by comparing them both with other questionnaires previously validated and with the assessment of a mental health specialist using a structured diagnostic interview. METHODS We trained community health workers and nurse assistants working in a collaborative mental health care model to administer the COOP/WONCA Charts, the 20-item Self-Reporting Questionnaire (SRQ-20), and the World Health Organization Five Well-Being Index (WHO-5) to 120 primary care patients. A psychiatrist blinded to the patients' results on these questionnaires administered the SCID, or Structured Clinical Interview for the DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition). RESULTS The area under the receiver operating characteristic curve was at least 0.80 for single items, a 3-item combination, and the total score of the COOP/WONCA Charts, as well as for the SRQ-20 and the WHO-5, for screening both for all mental disorders and for depressive disorders. The accuracy, sensitivity, specificity, and positive and negative predictive values of these measures ranged between 0.77 and 0.92. Community health workers and nurse assistants rated the understandability, ease of use, and clinical relevance of all 3 questionnaires as satisfactory. CONCLUSIONS One-time assessment of patients with the COOP/WONCA Charts is a valid and feasible option for screening for mental disorders by primary care teams.

The B0.5 IVe CoRoT target HD 49330 II. Spectroscopic ground-based observations

Context. We present spectroscopic ground-based observations of the early Be star HD 49330 obtained simultaneously with the CoRoT-LRA1 run just before the burst observed in the CoRoT data. Aims. Ground-based spectroscopic observations of the early Be star HD 49330 obtained during the precursor phase and just before the start of an outburst allow us to disantangle stellar and circumstellar contributions and identify modes of stellar pulsations in this rapidly rotating star. Methods. Time series analysis (TSA) is performed on photospheric line profiles of He I and Si III by means of the least squares method. Results. We find two main frequencies f1 = 11.86 c d(-1) and f2 = 16.89 c d(-1) which can be associated with high order p-mode pulsations. We also detect a frequency f3 = 1.51 c d(-1) which can be associated with a low order g-mode. Moreover we show that the stellar line profile variability changed over the spectroscopic run. These results are in agreement with the results of the CoRoT data analysis, as shown in Huat et al. (2009). Conclusions. Our study of mid-and short-term spectroscopic variability allows the identification of p-and g-modes in HD 49330. It also allows us to display changes in the line profile variability before the start of an outburst. This brings new constraints for the seimic modelling of this star.

Avaliação de modelos geoidais gravimétricos determinados com funções covariâncias planas e esféricas (Estudo de Caso: Estado de São Paulo e adjacências)

The least squares collocation is a mathematical technique which is used in Geodesy for representation of the Earth's anomalous gravity field from heterogeneous data in type and precision. The use of this technique in the representation of the gravity field requires the statistical characteristics of data through covariance function. The covariances reflect the behavior of the gravity field, in magnitude and roughness. From the statistical point of view, the covariance function represents the statistical dependence among quantities of the gravity field at distinct points or, in other words, shows the tendency to have the same magnitude and the same sign. The determination of the covariance functions is necessary either to describe the behavior of the gravity field or to evaluate its functionals. This paper aims at presenting the results of a study on the plane and spherical covariance functions in determining gravimetric geoid models.

2-Benzoylpyridine semicarbazone

The title compound, C13H12N4O, crystallizes with two independent molecules in the asymmetric unit. The compound crystallizes as the ZE isomer, where Z and E refer to the configuration around the C=N and N-C bonds, respectively, with an N-H center dot center dot center dot N-py (py is pyridine) intramolecular hydrogen bond. The dihedral angles between the least-squares planes through the semicarbazone group and the pyridyl ring are 22.70 (9) and 27.26 (9)degrees for the two molecules. There are intermolecular N-H center dot center dot center dot O hydrogen bonds.

Design of 1D and 2D molecule-based magnets with the ligand 4,5-dimethyl-1,2-phenylenebis(oxamato)

Three new bimetallic oxamato-based magnets with the proligand 4,5-dimethyl-1,2-phenylenebis-(oxamato) (dmopba) were synthesized using water or dimethylsulfoxide (DMSO) as solvents. Single crystal X-ray diffraction provided structures for two of them: [MnCu(dmopba)(H(2)O)(3)]n center dot 4nH(2)O (1) and [MnCu(dmopba)(DMSO)(3)](n center dot)nDMSO (2). The crystalline structures for both 1 and 2 consist of linearly ordered oxamato-bridged Mn(II)Cu(II) bimetallic chains. The magnetic characterization revealed a typical behaviour of ferrimagnetic chains for 1 and 2. Least-squares fits of the experimental magnetic data performed in the 300-20 K temperature range led to J(MnCu) = -27.9 cm(-1), g(Cu) = 2.09 and g(Mn) = 1.98 for 1 and J(MnCu) = -30.5 cm(-1), g(Cu) = 2.09 and g(Mn) = 2.02 for 2 (H = -J(MnCu)Sigma S(Mn, i)(S(Cu, i) + S(Cu, i-1))). The two-dimensional ferrimagnetic system [Me(4)N](2n){Co(2)[Cu(dmopba)](3)}center dot 4nDMSO center dot nH(2)O (3) was prepared by reaction of Co(II) ions and an excess of [Cu(dmopba)](2-) in DMSO. The study of the temperature dependence of the magnetic susceptibility as well as the temperature and field dependences of the magnetization revealed a cluster glass-like behaviour for 3.

Definindo a arena política local: sistemas partidários municipais na federação brasileira

This article analyzes the Brazilian political system from the local perspective. Following Cox (1997), we review the problems with electoral coordination that emerge from a given institutional framework. Due to the characteristics of the Brazilian Federal system and its electoral rules, linkage between the three levels of government is not guaranteed a priori, but demands a coordinating effort by the parties' leadership. According to our hypothesis, the parties are capable of coordinating their election strategies at different levels in the party system. Regression models based on two-stage least squares (2SLS) and TOBIT, analyzing a panel of Brazilian municipalities with data from the 1994 and 2000 elections, show that the proportion of votes received by a party in a given election correlates closely with its previous votes in majoritarian elections. Despite institutional incentives, the Brazilian party system shows evidence that it is organized nationally to the extent that it links the competition for votes at the three levels of government (National, State, and Municipal).

Near infrared spectroscopy for soil bulk density assessment

P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 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.

An EFG method for the nonlinear analysis of plates undergoing arbitrarily large deformations

The applicability of a meshfree approximation method, namely the EFG method, on fully geometrically exact analysis of plates is investigated. Based on a unified nonlinear theory of plates, which allows for arbitrarily large rotations and displacements, a Galerkin approximation via MLS functions is settled. A hybrid method of analysis is proposed, where the solution is obtained by the independent approximation of the generalized internal displacement fields and the generalized boundary tractions. A consistent linearization procedure is performed, resulting in a semi-definite generalized tangent stiffness matrix which, for hyperelastic materials and conservative loadings, is always symmetric (even for configurations far from the generalized equilibrium trajectory). Besides the total Lagrangian formulation, an updated version is also presented, which enables the treatment of rotations beyond the parameterization limit. An extension of the arc-length method that includes the generalized domain displacement fields, the generalized boundary tractions and the load parameter in the constraint equation of the hyper-ellipsis is proposed to solve the resulting nonlinear problem. Extending the hybrid-displacement formulation, a multi-region decomposition is proposed to handle complex geometries. A criterium for the classification of the equilibrium`s stability, based on the Bordered-Hessian matrix analysis, is suggested. Several numerical examples are presented, illustrating the effectiveness of the method. Differently from the standard finite element methods (FEM), the resulting solutions are (arbitrary) smooth generalized displacement and stress fields. (c) 2007 Elsevier Ltd. All rights reserved.

In-Line Monitoring of Particle Size during Emulsion Polymerization under Different Operational Conditions using NIR Spectroscopy

In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.