Establishing the risk of neonatal mortality using a fuzzy predictive model

O objetivo do artigo foi avaliar o uso da lógica fuzzy para estimar possibilidade de óbito neonatal. Desenvolveu-se um modelo computacional com base na teoria dos conjuntos fuzzy, tendo como variáveis peso ao nascer, idade gestacional, escore de Apgar e relato de natimorto. Empregou-se o método de inferência de Mamdani, e a variável de saída foi o risco de morte neonatal. Criaram-se 24 regras de acordo com as variáveis de entrada, e a validação do modelo utilizou um banco de dados real de uma cidade brasileira. A acurácia foi estimada pela curva ROC; os riscos foram comparados pelo teste t de Student. O programa MATLAB 6.5 foi usado para construir o modelo. Os riscos médios foram menores para os que sobreviveram (p < 0,001). A acurácia do modelo foi 0,90. A maior acurácia foi com possibilidade de risco igual ou menor que 25% (sensibilidade = 0,70, especificidade = 0,98, valor preditivo negativo = 0,99 e valor preditivo positivo = 0,22). O modelo mostrou acurácia e valor preditivo negativo bons, podendo ser utilizado em hospitais gerais.

Fluorescent lamp model based on equivalent resistances, considering the effects of dimming operation

This paper presents a new methodology for the determination of fluorescent lamp models based on equivalent resistances. One important feature of the proposed methodology is concerned with the inclusion of the filaments into the model, considering the effects of dimming operation on the equivalent resistances. The classical Series-Resonant Parallel-Loaded Half-Bridge inverter is used as the power stage of the ballast. Moreover, the variation of the inverter's switching frequency is the dimming technique assumed for the analyses. Results obtained with a F32T8 lamp indicate that the accuracy of the model is very satisfactory. Thus, the lamp models obtained with the proposed methodology have the potential to serve as an important tool for ballast designers, considering the necessity for evaluating the lamp/ballast compatibility, according to issues concerned to the operating conditions of the electrodes' filaments.

Accuracy assessment of a photogrammetric close-range reconstruction system

Geometric accuracy of a close-range photogrammetric system is assessed in this paper considering surface reconstruction with structured light as its main purpose. The system is based on an off-the-shelf digital camera and a pattern projector. The mathematical model for reconstruction is based on the parametric equation of the projected straight line combined with collinearity equations. A sequential approach for system calibration was developed and is presented. Results obtained from real data are also presented and discussed. Experiments with real data using a prototype have indicated 0.5mm of accuracy in height determination and 0.2mm in the XY plane considering an application where the object was 1630mm distant from the camera.

Bayesian approximations in randomized response model

Practical Bayesian inference depends upon detailed examination of posterior distribution. When the prior and likelihood are conjugate, this is easily carried out; however, in general, one must resort to numerical approximation. In this paper, our aim is to solve, using MAPLE, the Bayesian paradigm, for a very special data collecting procedure, known as the randomized-response technique. This allows researchers to obtain sensitive information while guaranteeing privacy to respondents. This approach intends to reduce false responses on sensitive questions. Exact methods and approximations will be compared from the accuracy point of view as well as for the computational effort.

Temperature and concentration dependence of density of model liquid foods

Density of binary solutions and combinations of sucrose, glucose, fructose, citric acid, malic acid, pectin, and inorganic salts were measured with an oscillating tube density meter in the temperature range from 10degrees to 60degreesC, at varying concentrations. Density can be predicted with accuracy better than 5 x 10(-5) g cm(-3) using predictive equations obtained by fitting the experimental data. Available literature values agreed well with experimental data. Relations for the excess molar volume of these solutions were derived in terms of mole fraction and temperature. A thermodynamic model for the volumetric analysis of multicomponent aqueous solutions containing electrolyte and non-electrolyte compounds was also proposed. These models can be used for prediction of density of liquid food systems, specially fruit juices and beverages, based on composition and temperature, with high accuracy and without elaborate experimental work.

An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe

Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.

One-dimensional analytical model for oxide thin film growth on Ti metal layers during laser heating in air

This paper presents the theoretical and experimental results for oxide thin film growth on titanium films previously deposited over glass substrate. Ti films of thickness 0.1 μm were heated by Nd:YAG laser pulses in air. The oxide tracks were created by moving the samples with a constant speed of 2 mm/s, under the laser action. The micro-topographic analysis of the tracks was performed by a microprofiler. The results taken along a straight line perpendicular to the track axis revealed a Gaussian profile that closely matches the laser's spatial mode profile, indicating the effectiveness of the surface temperature gradient on the film's growth process. The sample's micro-Raman spectra showed two strong bands at 447 and 612 cm -1 associated with the TiO 2 structure. This is a strong indication that thermo-oxidation reactions took place at the Ti film surface that reached an estimated temperature of 1160 K just due to the action of the first pulse. The results obtained from the numerical integration of the analytical equation which describes the oxidation rate (Wagner equation) are in agreement with the experimental data for film thickness in the high laser intensity region. This shows the partial accuracy of the one-dimensional model adopted for describing the film growth rate. © 2001 Elsevier Science B.V.

Modifying the stochastic model to mitigate GPS systematic errors in relative positioning

The GPS observables are subject to several errors. Among them, the systematic ones have great impact, because they degrade the accuracy of the accomplished positioning. These errors are those related, mainly, to GPS satellites orbits, multipath and atmospheric effects. Lately, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique (PLS). In this method, the errors are modeled as functions varying smoothly in time. It is like to change the stochastic model, in which the errors functions are incorporated, the results obtained are similar to those in which the functional model is changed. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method (CLS). In general, the solution requires a shorter data interval, minimizing costs. The method performance was analyzed in two experiments, using data from single frequency receivers. The first one was accomplished with a short baseline, where the main error was the multipath. In the second experiment, a baseline of 102 km was used. In this case, the predominant errors were due to the ionosphere and troposphere refraction. In the first experiment, using 5 minutes of data collection, the largest coordinates discrepancies in relation to the ground truth reached 1.6 cm and 3.3 cm in h coordinate for PLS and the CLS, respectively, in the second one, also using 5 minutes of data, the discrepancies were 27 cm in h for the PLS and 175 cm in h for the CLS. In these tests, it was also possible to verify a considerable improvement in the ambiguities resolution using the PLS in relation to the CLS, with a reduced data collection time interval. © Springer-Verlag Berlin Heidelberg 2007.

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems

This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

A new proposed rodent model of chemically induced prostate carcinogenesis: Distinct time-course prostate cancer progression in the dorsolateral and ventral lobes

Background. Characterization of novel rodent models for prostate cancer studies requires evaluation of either spontaneous and carcinogen-induced tumors as well as tumor incidence in different prostatic lobes. We propose a new short-term rodent model of chemically induced prostate carcinogenesis in which prostate cancer progression occurs differentially in the dorsolateral and ventral lobes. Methods. Adult gerbils were treated with MNU alone or associated with testosterone for 3 or 6 months of treatment. Tumor incidence, latency, localization, and immunohistochemistry (AR, PCNA, smooth muscle α-actin, p63, MGMT, and E-cadherin) were studied in both lobes. Results. Comparisons between both lobes revealed that lesions developed first in the DL while the VL presented longer tumor latency. However, after 6 months, there was a dramatic increase in tumor multiplicity in the VL, mainly in MNU-treated groups. Lesions clearly progressed from a premalignant to a malignant phenotype over time and tumor latency was decreased by MNU + testosterone administration. Three-dimensional reconstruction of the prostatic complex showed that the DL developed tumors exclusively in the periurethral area and showed intense AR, PCNA, and MGMT immunostaining. Moreover, VL lesions emerged throughout the entire lobe. MNU-induced lesions presented markers indicative of an aggressive phenotype: lack of basal cells, rupture of the smooth muscle cell layer, loss of E-cadherin, and high MGMT staining. Conclusions. There are distinct pathways involved in tumor progression in gerbil prostate lobes. This animal provides a good model for prostate cancer since it allows the investigation of advanced steps of carcinogenesis with shorter latency periods in both lobes. Copyright © 2013 Wiley Periodicals, Inc.

Accuracy of genomic predictions in Bos indicus (Nellore) cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

3D stability orbits close to 433 Eros using an effective polyhedral model method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Numerical solution of the FENE-CR model in complex flows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystems

There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.