Prediction of Crude Oil Properties and Chemical Composition by Means of Steady-State and Time-Resolved Fluorescence

Steady-state and time-resolved fluorescence measurements are reported for several crude oils and their saturates, aromatics, resins, and asphaltenes (SARA) fractions (saturates, aromatics and resins), isolated from maltene after pentane precipitation of the asphaltenes. There is a clear relationship between the American Petroleum Institute (API) grade of the crude oils and their fluorescence emission intensity and maxima. Dilution of the crude oil samples with cyclohexane results in a significant increase of emission intensity and a blue shift, which is a clear indication of the presence of energy-transfer processes between the emissive chromophores present in the crude oil. Both the fluorescence spectra and the mean fluorescence lifetimes of the three SARA fractions and their mixtures indicate that the aromatics and resins are the major contributors to the emission of crude oils. Total synchronous fluorescence scan (TSFS) spectral maps are preferable to steady-state fluorescence spectra for discriminating between the fractions, making TSFS maps a particularly interesting choice for the development of fluorescence-based methods for the characterization and classification of crude oils. More detailed studies, using a much wider range of excitation and emission wavelengths, are necessary to determine the utility of time-resolved fluorescence (TRF) data for this purpose. Preliminary models constructed using TSFS spectra from 21 crude oil samples show a very good correlation (R(2) > 0.88) between the calculated and measured values of API and the SARA fraction concentrations. The use of models based on a fast fluorescence measurement may thus be an alternative to tedious and time-consuming chemical analysis in refineries.

Numerical prediction of three-dimensional time-dependent viscoelastic extrudate swell using differential and algebraic models

This study investigates the numerical simulation of three-dimensional time-dependent viscoelastic free surface flows using the Upper-Convected Maxwell (UCM) constitutive equation and an algebraic explicit model. This investigation was carried out to develop a simplified approach that can be applied to the extrudate swell problem. The relevant physics of this flow phenomenon is discussed in the paper and an algebraic model to predict the extrudate swell problem is presented. It is based on an explicit algebraic representation of the non-Newtonian extra-stress through a kinematic tensor formed with the scaled dyadic product of the velocity field. The elasticity of the fluid is governed by a single transport equation for a scalar quantity which has dimension of strain rate. Mass and momentum conservations, and the constitutive equation (UCM and algebraic model) were solved by a three-dimensional time-dependent finite difference method. The free surface of the fluid was modeled using a marker-and-cell approach. The algebraic model was validated by comparing the numerical predictions with analytic solutions for pipe flow. In comparison with the classical UCM model, one advantage of this approach is that computational workload is substantially reduced: the UCM model employs six differential equations while the algebraic model uses only one. The results showed stable flows with very large extrudate growths beyond those usually obtained with standard differential viscoelastic models. (C) 2010 Elsevier Ltd. All rights reserved.

System Identification and Prediction of Dengue Fever Incidence in Rio de Janeiro

Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.

Robust state prediction for descriptor systems

This paper deals with the problem of state prediction for descriptor systems subject to bounded uncertainties. The problem is stated in terms of the optimization of an appropriate quadratic functional. This functional is well suited to derive not only the robust predictor for descriptor systems but also that for usual state-space systems. Numerical examples are included in order to demonstrate the performance of this new filter. (C) 2008 Elsevier Ltd. All rights reserved.

Real-time and Doppler US after pediatric segmental liver transplantation

Background Accurate diagnosis of portal vein (PV) stenosis by real-time and color Doppler US (CD-US) after segmental liver transplantation in children can decrease morbidity by avoiding unnecessary biopsy, PV hypertension, thrombosis and loss of the graft. Objective To evaluate CD-US parameters for the prediction of PV stenosis after segmental liver transplantation in children. Materials and methods We retrospectively reviewed 61 CD-US examinations measuring the diameter at the PV anastomosis, velocities at the anastomosis (PV1) and in the segment proximal to the anastomosis (PV2), and the PV1/PV2 velocity ratio. The study group comprised patients with stenosis confirmed by angiography and the control group comprised patients with a good clinical outcome. Results PV stenosis was seen in 12 CD-US examinations. The mean PV diameter was smaller in the study group (2.6 mm versus 5.7 mm) and a PV diameter of < 3.5 mm was highly predictive of stenosis (sensitivity 100%, specificity 91.8%). Conclusion A PV diameter of < 3.5 mm is a highly predictive CD-US parameter for the detection of hemodynamically significant stenosis on angiography.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Prediction of dynamical, nonlinear, and unstable process behavior

Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.

Measuring time series predictability using support vector regression

Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive for many practical applications. The implementation of nonlinear models in time series analysis involves the estimation of a large set of parameters, frequently leading to overfitting problems. In this article, a predictability coefficient is estimated using a combination of nonlinear autoregressive models and the use of support vector regression in this model is explored. We illustrate the usefulness and interpretability of results by using electroencephalographic records of an epileptic patient.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.

Effect of cement type and water storage time on the push-out bond strength of a glass fiber post

This study investigated the effects of the cement type and the water storage time on the push-out bond strength of a glass fiber post. Glass fiber posts (Fibrekor, Jeneric Pentron) were luted to post spaces using a self-cured resin cement (C&B Cement [CB]), a glass ionomer cement (Ketac Cem [KC]) or a resin-modified glass ionomer cement (GC FujiCEM [FC]) according to the manufacturers’ instructions. For each luting agent, the specimens were exposed to one of the following water storage times (n=5): 1 day (T1), 7 days (T7), 90 days (T90) and 180 days (T180). Push-out tests were performed after the storage times. Control specimens were not exposed to water storage, but subjected to the push-out test 10 min after post cementation. Data (in MPa) were analyzed by Kruskal-Wallis and Dunn`s test (α=0.05). Cement type and water storage time had a significant effect (p<0.05) on the push-out bond strength. CB showed significantly higher values of retention (p<0.05) than KC and FC, irrespective of the water storage time. Water storage increased significantly the push-out bond strength in T7 and T90, regardless of the cement type (p<0.05). The results showed that fiber posts luted to post spaces with the self-cured resin cement exhibited the best bonding performance throughout the 180-day water storage period. All cements exhibited a tendency to increase the bond strength after 7 and 90 days of water storage, decreasing thereafter.

Effects of light-curing time on the cytotoxicity of a restorative composite resin on odontoblast-like cells

This in vitro study evaluated the cytotoxicity of an experimental restorative composite resin subjected to different light-curing regimens. METHODS: Forty round-shaped specimens were prepared and randomly assigned to four experimental groups (n=10), as follows: in Group 1, no light-curing; in Groups 2, 3 and 4, the composite resin specimens were light-cured for 20, 40 or 60 s, respectively. In Group 5, filter paper discs soaked in 5 µL PBS were used as negative controls. The resin specimens and paper discs were placed in wells of 24-well plates in which the odontoblast-like cells MDPC-23 (30,000 cells/cm²) were plated and incubated in a humidified incubator with 5% CO2 and 95% air at 37ºC for 72 h. The cytotoxicity was evaluated by the cell metabolism (MTT assay) and cell morphology (SEM). The data were analyzed statistically by Kruskal-Wallis and Mann-Whitney tests (p<0.05). RESULTS: In G1, cell metabolism decreased by 86.2%, indicating a severe cytotoxicity of the non-light-cured composite resin. On the other hand, cell metabolism decreased by only 13.3% and 13.5% in G2 and G3, respectively. No cytotoxic effects were observed in G4 and G5. In G1, only a few round-shaped cells with short processes on their cytoplasmic membrane were observed. In the other experimental groups as well as in control group, a number of spindle-shaped cells with long cytoplasmic processes were found. CONCLUSION: Regardless of the photoactivation time used in the present investigation, the experimental composite resin presented mild to no toxic effects to the odontoblast-like MDPC-23 cells. However, intense cytotoxic effects occurred when no light-curing was performed.

Surface and subsurface erosion of primary enamel by acid beverages over time

This study evaluated the influence of a cola-type soft drink and a soy-based orange juice on the surface and subsurface erosion of primary enamel, as a function of the exposure time. Seventy-five primary incisors were divided for microhardness test (n=45) or scanning electron microscopy (SEM) analysis (n=30). The specimens were randomly assigned to 3 groups: 1 - artificial saliva (control); 2 - cola-type soft drink; and 3 - soy-based orange juice. Immersion cycles in the beverages were undertaken under agitation for 5 min, 3 times a day, during 60 days. Surface microhardness was measured at 7, 15, 30, 45 and 60 days. After 60 days, specimens were bisected and subsurface microhardness was measured at 30, 60, 90, 120, 150 and 200 µm from the surface exposed. Data were analyzed by ANOVA and Tukey’s test (a=0.05). Groups 2 and 3 presented similar decrease of surface microhardness. Regarding subsurface microhardness, group 2 presented the lowest values. SEM images revealed that after 60 days the surfaces clearly exhibited structural loss, unlike those immersed in artificial saliva. It may be concluded that erosion of the surfaces exposed to the cola-type soft drink was more accentuated and directly proportional to the exposure time.

Influence of surface sealant on the translucency of composite resin: effect of immersion time and immersion media

This study evaluated the effect of surface sealant on the translucency of composite resin immersed in different solutions. The study involved the following materials: Charisma, Fortify and coffee, Coca-Cola®, tea and artificial saliva as solutions. Sixty-four specimens (n = 8) were manufactured and immersed in artificial saliva at 37 ± 1 °C. Samples were immersed in the solutions for three times a day and re-immersed in artificial saliva until the translucency readings. The measurements were carried out at nine times: T1 - 24 hours after specimen preparation, T2 - 24 hours after immersion in the solutions, T3 - 48 hours and T4 to T9 - 7, 14, 21, 30, 60 and 90 days, respectively, after immersion. The translucency values were measured using a JOUAN device. The results were subjected to ANOVA and Tukey's test at 5%. The surface sealant was not able to protect the composite resin against staining, the coffee showed the strongest staining action, followed by tea and regarding immersion time, a significant alteration was noted in the translucency of composite resin after 21 days.

In vitro analysis of thermocompaction time and gutta-percha type on quality of main canal and lateral canals filling

The aim of this study was to evaluate the quality of filling in main and lateral root canals performed with the McSpadden technique, regarding the time spent on the procedure and the type of gutta-percha employed. Fifty simulated root canals, made with six lateral canals placed two apiece in the cervical, middle and apical thirds of the root, were divided into 5 groups. Group A: McSpadden technique with conventional gutta-percha, performed with sufficient time for canal filling; Group B: McSpadden technique with conventional gutta-percha, performed in twice the mean time used in Group A; Group C: McSpadden technique with TP gutta-percha, performed with sufficient time for canal filling; Group D: McSpadden technique with TP gutta-percha, performed in twice the mean time used in Group C; Group E: lateral condensation technique. Images of the filled root canals were taken using a stereomicroscope and analyzed using the Leica QWIN Pro software for filling material flow, gutta-percha filling extension and sealer flow. Data were analyzed by analysis of variance (ANOVA) and Tukey test (p < 0.05). The best values of penetration in lateral canals in the middle third occurred in the groups where TP gutta-percha was used. However, in the apical third, group B showed the best values. Although a longer time of compactor use allows greater penetration of the filling material into the lateral canals, the presence of voids resulted in bad quality radiographic images, suggesting porosity. The best quality of filling material was observed in Group A (McSpadden technique with conventional Gutta-Percha, performed with sufficient time for root canal filling).

Um modelo estocástico combinado de previsão sazonal para a precipitação no Brasil

Este artigo discute um modelo de previsão combinada para a realização de prognósticos climáticos na escala sazonal. Nele, previsões pontuais de modelos estocásticos são agregadas para obter as melhores projeções no tempo. Utilizam-se modelos estocásticos autoregressivos integrados a médias móveis, de suavização exponencial e previsões por análise de correlações canônicas. O controle de qualidade das previsões é feito através da análise dos resíduos e da avaliação do percentual de redução da variância não-explicada da modelagem combinada em relação às previsões dos modelos individuais. Exemplos da aplicação desses conceitos em modelos desenvolvidos no Instituto Nacional de Meteorologia (INMET) mostram bons resultados e ilustram que as previsões do modelo combinado, superam na maior parte dos casos a de cada modelo componente, quando comparadas aos dados observados.