A critical analysis of Doppler velocimetry in the differential diagnosis of malignant and benign ovarian masses

Objectives: To evaluate the intratumoral reliability of color Doppler parameters and the contribution of Doppler sonography to the gray-scale differential diagnosis of ovarian masses. Methods: An observational study was performed including 67 patients, 15 (22.4%) with malignant ovarian neoplasm and 52 (77.6%) with benign ovarian diseases. We performed the Doppler evaluation in two distinct vessels selected after decreasing the Doppler gain to sample only vessels with higher velocity flow. Doppler measurements were obtained from each identified vessel, and resistive index (RI), pulsatility index (PI), peak systolic velocity (PSV), and end-diastolic velocity (EDV) were measured. Intraclass coefficient of correlation (ICC), sensitivity, specificity, and potential improvement in gray-scale ultrasound performance were calculated. Results: The general ICC were 0.60 (95% CI 0.42- 0.73) for RI, 0.65 (95% CI 0.49- 0.77) for PI, 0.07 (95% CI- 0.17-0.30) for PSV, and 0.19 (95% CI -0.05-0.41) for EDV. The sensitivity and specificity were respectively 84.6% and 86.7% for RI, 69.2% and 93.3% for PI, 80.0% and 65.4% for gray-scale sonography, and 93.3% and 65.4% for gray-scale plus RI (p = 0.013). Conclusions: Gynecologists must be careful in interpreting results from Doppler evaluation of ovarian masses because PSV and EDV present poor intratumoral reliability. The lower RI value, evaluated in at least two distinct sites of the tumor, was able to improve the performance of gray-scale ultrasound in differential diagnosis of ovarian masses.

Comparison of a PCR assay in whole blood and serum specimens for canine brucellosis diagnosis

The performance of a serum PCR assay was compared with that of a blood PCR assay for the diagnosis of canine brucellosis caused by Brucella canis in 72 dogs. The dogs were classified into three groups (infected, non-infected and suspected brucellosis) according to the results of blood culture and serological tests. The sensitivities of blood PCR and serum PCR were, respectively, 97.14 per cent and 25.71 per cent. The specificities of both were 100 per cent. In the group of dogs with suspected brucellosis, three were positive by blood PCR and none was positive by serum PCR. Serum PCR showed little value for the direct diagnosis of canine brucellosis as the assay had low diagnostic sensitivity and fewer positive dogs were detected by this test than by blood culture, blood PCR, rapid slide agglutination test (RSAT) and RSAT with 2-mercaptoethanol.

Social interaction as a heuristic for combinatorial optimization problems

We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Economic viability of doses and split-applications of nitrogen fertilization in corn crop in a eutrophic Red Latosol

Nitrogen is the nutrient that is most absorbed by the corn crop, with the most complex management, and has the highest share on the cost of corn production. The objective of this work was to evaluate the economic viability of different rates and split-applications of nitrogen fertilization, as such as urea, in the corn crop in a eutrophic Red Latosol (Oxisol). The study was carried out in the Experimental Station of the Regional Pole of the Sao Paulo Northwest Agribusiness Development (APTA), in Votuporanga, State of Sao Paulo, Brazil. The experimental design was randomized complete blocks with nine treatments and four replications, consisting of five N rates: 0, 55, 95, 135 and 175 kg ha(-1), 15 kg ha-l applied in the seeding and the remainder in top dressing: 40 and 80 kg ha(-1) N at forty days after seeding (DAS), or 1/2 + 1/2 at 20 and 40 DAS; 120 kg ha-1 N split in 1/2 + 1/2 or 1/3 + 1/3 + 1/3 at 20, 40 or 60 DAS; 160 kg ha(-1) N split in 1/4 + 3/8 + 3/8 or 114 + 1/4 + 1/4 + 1/4 at 20, 40, 60 and 80 DAS. The application of 135 kg ha-l of N split in three times provided the best benefit/cost ratio. The non-application of N provided the lowest economic return, proving to be unviable.

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.

Extremal problems on sum-free sets and coverings in tridimensional spaces

Given a prime power q, define c (q) as the minimum cardinality of a subset H of F 3 q which satisfies the following property: every vector in this space di ff ers in at most 1 coordinate from a multiple of a vector in H. In this work, we introduce two extremal problems in combinatorial number theory aiming to discuss a known connection between the corresponding coverings and sum-free sets. Also, we provide several bounds on these maps which yield new classes of coverings, improving the previous upper bound on c (q)

Continuous opinions and discrete actions in opinion dynamics problems

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

Clinical relationships and ethical problems in primary care, Sao Paulo, SP, Brazil

Objectives: Main Objective: to identify ethical problems in primary care according to nurses` and doctors` perceptions. Secondary Objective: to know ethical issues of patient-professional relationships in primary care. Design: Synthesis to integrate and reinterpret primary results of qualitative studies. Setting: Primary healthcare centers, Sao Paulo, SP, Brazil. Participants and/or context: Incidental sample of 34 nurses and 36 medical doctors working in primary healthcare centers selected by convenience. Methods: Individual, semi-structured interviews to identity situations considered as sources of ethical problems. The sample is socially representative of primary care health centers and professionals. Data collection assured discourse saturation. Hermeneutic-dialectical discourse analysis was used to study the results. Results: Patient-professional relationships and team work were the main sources of ethical problems. The most important problems were patient information, privacy, confidentiality, interpersonal relationship, linkage and patient autonomy. These issues reflect the recent changes in clinical relation ships and show the peculiarities of primary care with its continuous care which lasts a long time. Healthcare involves multiprofessional team work in the midst of the patient claims for autonomy. Good care of patients needs requires a relationship based on communication and cooperation, and includes feelings and values, with communication skills. Conclusions: Ethical problems in primary care are common situations. For quality and humane primary care the relationship should consist of dialogue, trust and cooperation. (C) 2009 Elsevier Espana, S.L. All rights reserved.

Impact of Childhood Cancer on Parents` Relationships: An Integrative Review

Purpose: The diagnosis of cancer and the treatment decisions associated with it may cause uncertainty, stress, and anxiety among parents. Emotional tensions can affect parents` relationships during the trajectory of the child`s cancer illness. We conducted an integrative review to examine the evidence related to the effects of childhood cancer on parents` relationships. Methods: An integrative literature search of studies published between 1997 and 2009 was conducted in the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Psychology Information (PsycINFO), PubMed, Scopus, CUIDEN, and Latin American and Caribbean Health Science Literature (LILACS). The key words used were neoplasms, child, marriage, spouses, family relations, and nursing. Articles were reviewed if the (a) topic addressed parents` relationships during childhood cancer; (b) participants were mothers, fathers, or both; (c) design was either qualitative or quantitative; (d) language was English, Portuguese, or Spanish; (e) date of publication was between January 1997 and October 2009; and (f) abstract was available. Results: Fourteen articles met the search criteria and were reviewed using Cooper`s framework for integrative reviews. Four themes emerged: (a) changes in the parents` relationship during the trajectory of the child`s illness; (b) difficulty in communication between couples; (c) gender differences in parental stress and coping; and (d) role changes. Conclusions and Implications: Findings revealed positive and negative changes in parents` relationships, communication, stress, and roles. Nurses need to assess the impact of cancer diagnosis and treatments on parent relationships, offer support and encouragement, and allow expression of feelings. Future research is needed to develop and test interventions that increase parents` potentials and strengthen relationships during the challenging trajectory of their children`s cancer and treatment. Clinical Relevance: The multiple sources of stress and uncertainty associated with a child`s cancer diagnosis and treatment affect parents` relationships. Difficulties in communication appear frequently in parents` relationship. Our findings may guide healthcare professionals in identifying parents at risk for developing conflicts, communication problems, and lack of alignment between parents that could interfere with providing optimal care for their child with cancer. Healthcare professionals may promote dialogue and encourage parents to express their feelings, seek mutual support, and establish a partnership in dealing with the child`s illness.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Chaos-Galerkin solution of stochastic Timoshenko bending problems

This paper presents an accurate and efficient solution for the random transverse and angular displacement fields of uncertain Timoshenko beams. Approximate, numerical solutions are obtained using the Galerkin method and chaos polynomials. The Chaos-Galerkin scheme is constructed by respecting the theoretical conditions for existence and uniqueness of the solution. Numerical results show fast convergence to the exact solution, at excellent accuracies. The developed Chaos-Galerkin scheme accurately approximates the complete cumulative distribution function of the displacement responses. The Chaos-Galerkin scheme developed herein is a theoretically sound and efficient method for the solution of stochastic problems in engineering. (C) 2011 Elsevier Ltd. All rights reserved.

An alternative multi-region BEM technique for three-dimensional elastic problems

The main objective of this work is to present an alternative boundary element method (BEM) formulation for the static analysis of three-dimensional non-homogeneous isotropic solids. These problems can be solved using the classical boundary element formulation, analyzing each subregion separately and then joining them together by introducing equilibrium and displacements compatibility. Establishing relations between the displacement fundamental solutions of the different domains, the alternative technique proposed in this paper allows analyzing all the domains as one unique solid, not requiring equilibrium or compatibility equations. This formulation also leads to a smaller system of equations when compared to the usual subregion technique, and the results obtained are even more accurate. (C) 2008 Elsevier Ltd. All rights reserved.

Extended Fault-Location Formulation for Power Distribution Systems

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D`s distribution operation center.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.